From 28d071193a6b43beeadb80f6af62e814eed019fd Mon Sep 17 00:00:00 2001
From: astamm <aymeric.stamm@cnrs.fr>
Date: Mon, 10 Jul 2023 22:25:56 +0000
Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20astamm/f?=
 =?UTF-8?q?dacluster@5415c9d204ae89b6131165f25a212b660d180679=20?=
 =?UTF-8?q?=F0=9F=9A=80?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 apple-touch-icon-120x120.png | Bin 18277 -> 18277 bytes
 apple-touch-icon-152x152.png | Bin 26792 -> 26792 bytes
 apple-touch-icon-180x180.png | Bin 35487 -> 35487 bytes
 apple-touch-icon-60x60.png   | Bin 6134 -> 6134 bytes
 apple-touch-icon-76x76.png   | Bin 8772 -> 8772 bytes
 apple-touch-icon.png         | Bin 35487 -> 35487 bytes
 favicon-16x16.png            | Bin 1310 -> 1310 bytes
 favicon-32x32.png            | Bin 2563 -> 2563 bytes
 pkgdown.yml                  |   2 +-
 reference/fdakmeans-1.png    | Bin 228914 -> 231512 bytes
 reference/fdakmeans-2.png    | Bin 186089 -> 194777 bytes
 reference/fdakmeans.html     |   2 +-
 search.json                  |   2 +-
 13 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/apple-touch-icon-120x120.png b/apple-touch-icon-120x120.png
index 992e07e8786921acdff2901c95283e68c9e606fb..ecb1ec7424bc11f36a50ee1889f4ba5613b26259 100644
GIT binary patch
delta 59
zcmaFb$N035aY7B7gvhKUJ&uh{CT{#jCRRoU+6D$z1_oJgp3Itj)J+LlOnPIC+T?F;
F`2bW}6OsS`

delta 59
zcmaFb$N035aY7B75ck{G)8!kROx*YlEvyU;wG9lc3=9sQ%5$20)J+LlY{T?x|0aKP
G%Lf3IFBU%l

diff --git a/apple-touch-icon-152x152.png b/apple-touch-icon-152x152.png
index a1098cdef5f9cb8dc010f6fc77ad3e36538919eb..49e72fb08642dbb75556bfd698b97925b59f138f 100644
GIT binary patch
delta 59
zcmZ2+k#WUE#tAiS5@IDe{wf=r%G3FcOstHIv<(cb3=IAjf89KpBSQ&UtVhq6f3jsp
FJ^*9G68``I

delta 59
zcmZ2+k#WUE#tAiSLOjI}<F0IMDo^J(w6HQX(l#)#GBEg{RC0eZM}`uzSY!Q}<jIy9
F`2dT=6pR1>

diff --git a/apple-touch-icon-180x180.png b/apple-touch-icon-180x180.png
index 5cf51a0d8c9fc37558f8d55f0e20a5a9ac154465..19442cfbba43a9a9f795974a6cdbdf4dd8660e8c 100644
GIT binary patch
delta 59
zcmbO~m1+J|rU^A{65`C+^_w;}<#qBKnOGSaYa19?85l&f{9~W|zf%cWOe@lD_hf^v
Fd;mjj63PGo

delta 59
zcmbO~m1+J|rU^A{LVR=I+yB_ul-J2`Xkle&qHSPcWneJ*ljGCL|2vhC#U8Ey89CXY
GD<1%(E*6Ub

diff --git a/apple-touch-icon-60x60.png b/apple-touch-icon-60x60.png
index dbb338c795f35c374788ac9ec32faedc14a61bbf..427d90d5fc302af87c5355ceea3aaa875af43869 100644
GIT binary patch
delta 57
zcmeyS|4n~F4V#2eF=Myw#-^iU{6;2Lh8Efe237_J*L&8=O%4-RLKa(gQFPJdcJX`w
DCXf<o

delta 57
zcmeyS|4n~F4Vw^0Nzbga8=H=b@f%uL8CYl=7+4t?%=n?rKRHZX30dsr(#e}Aw~OZk
E08^zC$^ZZW

diff --git a/apple-touch-icon-76x76.png b/apple-touch-icon-76x76.png
index 102f4e9ad26f0ba90985c40cbaaeff75b0ddd2d7..7a19bcf666c078a0821fbc27cf893f3025d892f4 100644
GIT binary patch
delta 57
zcmX@&a>Qjq4V#283)}A18=Hg``Hf7h3@x<{46F<c3V$zKHF=4m60#V>GC8ryR~7RC
D6g3g4

delta 57
zcmX@&a>Qjq4Vw_xtft=&H#P|?@*7%M85(FC7+4t?r0-4rHhGDn60(@sgS%dnuPWvP
E09gtY8~^|S

diff --git a/apple-touch-icon.png b/apple-touch-icon.png
index 3137c63cfe9a6062997553f01d626e7c30b17651..ab6cadcf174d30b571c2aa2975b65c568583cfa8 100644
GIT binary patch
delta 59
zcmbO~m1+J|rU^A{5)zZIBq?uf%IoAeGO;o;(Kax!GBB98_(136|D8(6V(<S|m`*n6
G$_D^@b`@3t

delta 59
zcmbO~m1+J|rU^A{Lj12@@aJu8%IoAew6HQX)iyA&GB7Z0^$MK)zf%cW%;m<Xx04OJ
F@&RjZ6x;v+

diff --git a/favicon-16x16.png b/favicon-16x16.png
index a458b073a40901548d37e9fa8c0879ed4065196c..4305fdc3aa6156f5d67b61f4fb649006f5f321a8 100644
GIT binary patch
delta 59
zcmbQoHIHk9IWwDtT-EmDVw-K5jTrfjOstFzv<(cb3=EdJJz<$#$D)KRc3nDV$K>@a
F`2gw85Z?d*

delta 59
zcmbQoHIHk9IWwD(NJ8(irp>m@MvVN17FI?E+6D$z1_m#Ul0+xhu_z&n&B(vCa`JkX
Fd;sbr5j+3@

diff --git a/favicon-32x32.png b/favicon-32x32.png
index 25fabb73e4a78b3126c8d2221892a236215bd87f..c937c95d99eae8ac64d0066f4bd7b00d7ea61550 100644
GIT binary patch
delta 57
zcmZn`X%?AK!zLlmyWxAo#->Xg{6;2L#)jGk237_J42JJFOit!hLKZ8`3FnzSg)<)j
D1Wyq8

delta 57
zcmZn`X%?AK!zLuw*Svh)#->Xg{Du}*Mn>8O237_Jb!&@lCMR<$A&c>UINdOL3THk5
D6e$um

diff --git a/pkgdown.yml b/pkgdown.yml
index 6e0b5c0..fa99dd2 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -6,5 +6,5 @@ articles:
   input-formats: input-formats.html
   berkeley-growth: berkeley-growth.html
   kmeans-initialisation: kmeans-initialisation.html
-last_built: 2023-07-10T22:18Z
+last_built: 2023-07-10T22:24Z
 
diff --git a/reference/fdakmeans-1.png b/reference/fdakmeans-1.png
index 546884a1353b947cb8fd3d2ea09c7deafc057f42..699f87b2d94347bddabfa677296a5a0313ebb03e 100644
GIT binary patch
literal 231512
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diff --git a/reference/fdakmeans.html b/reference/fdakmeans.html
index 205bfe7..9616c9e 100644
--- a/reference/fdakmeans.html
+++ b/reference/fdakmeans.html
@@ -272,7 +272,7 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Information about cluster initialization:</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  - Number of clusters: 2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  - Initial seeds for cluster centers:         14         4</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  - Initial seeds for cluster centers:         14         2</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Information about the methods used within the algorithm:</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  - Warping method: affine</span>
diff --git a/search.json b/search.json
index b8f06b2..4fd65e0 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
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This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"/articles/berkeley-growth.html","id":"the-berkeley-growth-data","dir":"Articles","previous_headings":"","what":"The Berkeley growth data","title":"Analysis of Berkeley growth data","text":"total 93 children (39 boys 54 girls) followed height cm measured time common grid age:  single observation actually time series \\(\\mathbf{x}_i = (x_i(t_1), \\dots, x_i(t_M))^\\top\\). can hypothesize know happened two consecutive points \\(t_j\\) \\(t_{j+1}\\) even though observe data \\((t_j, t_{j+1})\\). usually achieved via splines Fourier wavelet basis decomposition confer observation degree regularity account possible periodicity specificity data point. step data representation effectively transforms original observation \\(\\mathbf{x}_i\\) time series functional data point \\(x_i : \\mathcal{D} \\\\mathcal{M}\\).","code":"growth <- fda::growth mb <- as.factor(c(rep(\"male\", dim(growth$hgtm)[2]), rep(\"female\", dim(growth$hgtf)[2]))) N <- length(mb) x <- growth$age M <- length(x) y0 <- cbind(growth$hgtm, growth$hgtf) tibble::tibble(   Age = replicate(N, x, simplify = FALSE),   Height = purrr::array_tree(y0, margin = 2),   Gender = mb,   CurveID = 1:N ) |>    tidyr::unnest(cols = c(Age, Height)) |>    ggplot(aes(Age, Height, color = Gender, group = CurveID)) +    geom_point() +    geom_line() +   theme_bw() +    labs(     title = \"Heights of 39 boys and 54 girls from age 1 to 18\",      x = \"Age (years)\",      y = \"Height (cm)\"   )"},{"path":"/articles/berkeley-growth.html","id":"functional-data-representation","dir":"Articles","previous_headings":"","what":"Functional data representation","title":"Analysis of Berkeley growth data","text":"Given orthonormal basis \\(\\{e_b\\}_{b\\ge 1}\\) functional space observations assumed belong , can model observation \\(x_i\\) : \\[ x_i = f_i + \\varepsilon_i, \\] : \\[ f_i(t) = \\sum_{b=1}^B f_{ib} e_b(t), \\] truncation \\(B\\). coefficients \\(f_{ib}\\) adjusted minimizing cost function usually includes data attachment term rougness penalty term way enforce regularity functional representation. common use instance norm second derivative roughness penalty, case cost function becomes: \\[ \\sum_{m=1}^M \\left( x_i(t_m) - f_i(t_m) \\right)^2 + \\lambda \\sum_{m=1}^M \\left[ f_i^{(2)}(t_m) \\right]^2 \\] practice, functional representation can achieved R using fda package. following code adjusts B-spline representation growth curves weight \\(\\lambda\\) roughness penalty determined minimizing generalized cross-validation criterion: can now take look data representation:  can also compute display growth rate:  graph interesting tells us first peak growth velocity common boys girls early age, just birth; second peak growth velocity corresponding puberty happens earlier girls; variability second peak due gender also inter-subject variability. particular, one wanted perform clustering curves label boys girls (assuming information), figures show best chance accomplish clustering performing joint alignment clustering growth velocity curves can simultaneously () minimize within-group phase variability (ii) cluster curves based phase variability.","code":"basisobj <- fda::create.bspline.basis(rangeval = range(x), nbasis = 15) fd_vals <- purrr::map(1:N, \\(n) {   yobs <- y0[, n]   result <- fda::smooth.basis(x, yobs, basisobj)   yfd <- result$fd   cost <- function(lam) {     yfdPar <- fda::fdPar(yfd, 2, lam)     out <- fda::smooth.basis(x, yobs, yfdPar)     out$gcv   }   lambda_opt <- stats::optimise(cost, c(1e-8, 1))$minimum   if (lambda_opt <= 1e-8)     cli::cli_alert_warning(\"The optimal penalty has reached the lower bound (1e-8) for curve #{n}.\")   if (lambda_opt >= 1)     cli::cli_alert_warning(\"The optimal penalty has reached the upper bound (1) for curve #{n}.\")   yfdPar <- fda::fdPar(yfd, 2, lambda_opt)   fda::smooth.fd(yfd, yfdPar) }) fd <- fda::fd(   coef = fd_vals |>     purrr::map(\"coefs\") |>     purrr::reduce(cbind),   basisobj = basisobj ) y0 <- fda::eval.fd(x, fd, 0) tibble::tibble(   Age = replicate(N, x, simplify = FALSE),   Height = purrr::array_tree(y0, margin = 2),   Gender = mb,   CurveID = 1:N ) |>    tidyr::unnest(cols = c(Age, Height)) |>    ggplot(aes(Age, Height, color = Gender, group = CurveID)) +    geom_point() +    geom_line() +   theme_bw() +    labs(     title = \"Heights of 39 boys and 54 girls from age 1 to 18\",      x = \"Age (years)\",      y = \"Height (cm)\"   ) y1 <- fda::eval.fd(x, fd, 1) tibble::tibble(   Age = replicate(N, x, simplify = FALSE),   Height = purrr::array_tree(y1, margin = 2),   Gender = mb,   CurveID = 1:N ) |>   tidyr::unnest(cols = c(Age, Height)) |>   ggplot(aes(Age, Height, color = Gender, group = CurveID)) +   geom_point() +   geom_line() +   theme_bw() +   labs(     title = \"Growth velocity of 39 boys and 54 girls from age 1 to 18\",     x = \"Age (years)\",     y = \"Growth velocity (cm/year)\"   )"},{"path":"/articles/berkeley-growth.html","id":"clustering","dir":"Articles","previous_headings":"","what":"Clustering","title":"Analysis of Berkeley growth data","text":"Initial visualization data representation steps revealed , one aims clustering individuals based gender, (s)focus : searching 2 clusters; using growth velocity curves instead growth curves ; cluster based phase variability; perform intra-cluster alignment separate amplitude phase variability. However, still several possible clustering methods can explore perform task. Namely, fdacluster implements \\(k\\)-means algorithm well hierarchical clustering DBSCAN. can compare different clustering strategies: generates object class mcaps specialized S3 methods graphics::plot() ggplot2::autoplot(). called object class mcaps, methods gain optional arguments: validation_criterion choose validation criterion display distance--center (validation_criterion = \"wss\") silhouette values (validation_criterion = \"silhouette\"); choose whether mean criterion displayed (= \"mean\") entire distribution across observation form boxplot (= \"distribution\").  terms within-cluster distances center (WSS), hierarchical agglomerative clustering average complete linkage \\(k\\)-means stand .  terms individual silhouette values, DBSCAN appear comparison auto-detects number clusters found 1 cluster. methods, hierarchical agglomerative clustering average complete linkage stand . can therefore proceed hierarchical agglomerative clustering complete linkage example: generates object class caps specialized S3 methods graphics::plot() ggplot2::autoplot(). called object class caps, methods gain optional argument type can one amplitude phase. default type = \"amplitude\" case curves alignment shown colored cluster membership:  type = \"phase\", warping functions instead displayed gives sense phase variability data phase alignment. , colored cluster membership:  also possible show visual inspection internal cluster validation via diagnostic_plot() function, shows individual distance--center silhouette values, observations ordered decreasing value intra-cluster silhouette:  Finally, can explore correspondence non-supervised groups found actual gender distribution: second group almost entirely composed girls first group mainly composed men although 23.68% girls present group. interesting dig characteristics girls might explain clustering sees boys well understanding 1 boy seen girl.","code":"growth_mcaps <- compare_caps(   x = x,   y = t(y1),   n_clusters = 2,   metric = \"l2\",    clustering_method = c(     \"kmeans\",      \"hclust-complete\",      \"hclust-average\",      \"hclust-single\",     \"dbscan\"   ),    warping_class = \"affine\",    centroid_type = \"mean\",   cluster_on_phase = TRUE ) plot(growth_mcaps, validation_criterion = \"wss\", what = \"distribution\") plot(growth_mcaps, validation_criterion = \"silhouette\", what = \"distribution\") growth_caps <- fdahclust(   x = x,   y = t(y1),   n_clusters = 2,   metric = \"l2\",   warping_class = \"affine\",    centroid_type = \"mean\",   cluster_on_phase = TRUE ) plot(growth_caps, type = \"amplitude\") plot(growth_caps, type = \"phase\") diagnostic_plot(growth_caps) table(growth_caps$memberships, mb) |>    `rownames<-`(c(\"Group 1\", \"Group 2\")) |>    knitr::kable()"},{"path":"/articles/hierarchial-clustering.html","id":"theory","dir":"Articles","previous_headings":"","what":"Theory","title":"Hierarchical clustering","text":"Traditional hierarchical agglomerative clustering (HAC) usually carried two mandatory steps third optional one: Compute distance matrix \\(D\\) entry \\(d_{ij}\\) stores distance observation \\(\\) observation \\(j\\); Compute hierarchy clustering structures form dendrogram first assuming observation belongs cluster progressively merge observations groups observations together using -called linkage criterion; [optional] Cut tree given distance order form \\(k\\) clusters. steps incurs slight modifications comes clustering functional data. Step 1. Functional HAC needs account intrinsic amplitude phase variability inherent functional data. therefore natural computing distance two curves minimize distance possible warping functions chosen class, .e. integrate alignment computing distance matrix. idea assess far two curves optimal phase alignment. step achieved fdadist(). Step 2. process building hierarchy possible clustering structures change distance matrix \\(D\\) known. fact, practical point view R, still achieved via call stats::hclust(). , user can choose linkage criterion use assessing distances sets curves. sake simplicity, subset choices stats::hclust() function actually available fdacluster, namely complete, average, single ward.D2. Step 3. dendrogram built, big difference multivariate HAC functional HAC stems fact latter requires choice number clusters, hence making Step 3 mandatory well. , grouping structure chosen, curves need undergo last alignment centroid cluster assigned . , , within-cluster sum squared distances centroid silhouette values can assessed. step achieved call fdakmeans() \\(k = 1\\) initial centroid corresponding cluster medoid.","code":""},{"path":"/articles/hierarchial-clustering.html","id":"using-fdacluster","dir":"Articles","previous_headings":"","what":"Using fdacluster","title":"Hierarchical clustering","text":"steps enpapsulated single function fdacluster ease usage: first group arguments call arguments user likely interact . number clusters can specified argument n_clusters, choice class warping functions type centroid metric achieved arguments warping_class, centroid_type metric respectively. linkage criterion can selected via linkage_criterion. default, function performs affine registration using pointwise sample mean computing cluster centroid L2 distance original curves complete linkage. default, function uses amplitude data alignment assigning cluster membership observed curves. user can switch use phase data instead using cluster_on_phase = TRUE. second group arguments set sensible default values used internal call fdakmeans() \\(k = 1\\), performs within-cluster alignment centroid groups determined cutting dendrogram appropriate height. arguments meant changed unless results clustering via fdahclust() seem odd.","code":"fdahclust(   x,   y,   n_clusters = 1L,   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   centroid_type = c(\"mean\", \"median\", \"medoid\", \"lowess\", \"poly\"),   metric = c(\"l2\", \"pearson\"),   linkage_criterion = c(\"complete\", \"average\", \"single\", \"ward.D2\"),   cluster_on_phase = FALSE,   use_verbose = TRUE,      warping_options = c(0.15, 0.15),   maximum_number_of_iterations = 100L,   number_of_threads = 1L,   parallel_method = 0L,   distance_relative_tolerance = 0.001,   use_fence = FALSE,   check_total_dissimilarity = TRUE,   compute_overall_center = FALSE )"},{"path":[]},{"path":"/articles/hierarchial-clustering.html","id":"simulated-data-set","dir":"Articles","previous_headings":"Example","what":"Simulated data set","title":"Hierarchical clustering","text":"Let us consider following sample \\(30\\) simulated unidimensional curves: Looking data set, seems shall expect \\(3\\) groups aim clustering based phase variability probably \\(2\\) groups search clustering structure based amplitude variability.","code":""},{"path":"/articles/hierarchial-clustering.html","id":"hac-based-on-amplitude-variability","dir":"Articles","previous_headings":"Example","what":"HAC based on amplitude variability","title":"Hierarchical clustering","text":"can perform HAC based amplitude variability follows: fdahclust() function returns object class caps (Clustering Amplitude Phase Separation) S3 specialized methods ggplot2::autoplot() graphics::plot() implemented. instance, can visualize original aligned functional data set :  can visualize estimated warping functions :  can visualize distribution distances--center silhouette values across observations :","code":"out1 <- fdahclust(   simulated30_sub$x,   simulated30_sub$y,   n_clusters = 2,   centroid_type = \"mean\",   warping_class = \"affine\",   metric = \"l2\",    cluster_on_phase = FALSE ) #> ℹ Computing the distance matrix... #> ℹ Calculating the tree... #> ℹ Aligning all curves with respect to their centroid... #> ℹ Consolidating output... plot(out1, type = \"amplitude\") plot(out1, type = \"phase\") diagnostic_plot(out1)"},{"path":"/articles/hierarchial-clustering.html","id":"hac-based-on-phase-variability","dir":"Articles","previous_headings":"Example","what":"HAC based on phase variability","title":"Hierarchical clustering","text":"can perform HAC based phase variability switching cluster_on_phase argument TRUE: can inspect result :","code":"out2 <- fdahclust(   simulated30_sub$x,   simulated30_sub$y,   n_clusters = 3,   centroid_type = \"mean\",   warping_class = \"affine\",   metric = \"l2\",    cluster_on_phase = TRUE ) #> ℹ Computing the distance matrix... #> ℹ Calculating the tree... #> ℹ Aligning all curves with respect to their centroid... #> ℹ Consolidating output... plot(out2, type = \"amplitude\") plot(out2, type = \"phase\") diagnostic_plot(out2)"},{"path":"/articles/hierarchial-clustering.html","id":"choosing-the-number-of-clusters","dir":"Articles","previous_headings":"Example","what":"Choosing the number of clusters","title":"Hierarchical clustering","text":"helper function compare_caps() can used get intuition number clusters one looking . example, can generate data help choosing number clusters clustering amplitude data: example. asked specification optional argument warping_class use multiple warping classes store clustering results separately output later comparison. Multiple choices can also used arguments clustering_method centroid_type although example chose focus HAC complete linkage using mean centroid type. metric argument must however unique need use metric among methods later comparison. code generates object class mcaps dedicated S3 specializations ggplot2::autoplot() graphics::plot() well. methods gain two extra optional arguments: validation_criterion: string specifying validation criterion used comparison. Choices \"wss\" \"silhouette\". Defaults \"wss\". : string specifying kind information display validation criterion. Choices \"mean\" (plots mean values) \"distribution\" (plots boxplots). Defaults \"mean\". example, one can can visualize mean WSS specified methods :  case, plot clearly shows among set warping classes considered, one use affine warping search \\(2\\) groups goal cluster based amplitude variability. Let us now perform analysis goal clustering based phase variability instead:  case, expected looking original data set, plot suggests search \\(3\\) groups. even interesting case improvement terms WSS going shift warping class affine warping class. also expected looking original data set nice also reflected output diagnostic.","code":"ncores <- max(parallel::detectCores() - 1L, 1L) plan(multisession, workers = ncores) amplitude_data <- compare_caps(   x = simulated30_sub$x,    y = simulated30_sub$y,    n_clusters = 1:5,    metric = \"l2\",    warping_class = c(\"none\", \"shift\", \"dilation\", \"affine\"),   clustering_method = \"hclust-complete\",    centroid_type = \"mean\",    cluster_on_phase = FALSE ) plan(sequential) plot(amplitude_data, validation_criterion = \"wss\", what = \"mean\") ncores <- max(parallel::detectCores() - 1L, 1L) plan(multisession, workers = ncores) phase_data <- compare_caps(   x = simulated30_sub$x,    y = simulated30_sub$y,    n_clusters = 1:5,    metric = \"l2\",    warping_class = c(\"shift\", \"dilation\", \"affine\"),   clustering_method = \"hclust-complete\",    centroid_type = \"mean\",    cluster_on_phase = TRUE ) plan(sequential) plot(phase_data, validation_criterion = \"wss\", what = \"mean\")"},{"path":"/articles/input-formats.html","id":"native-format","dir":"Articles","previous_headings":"","what":"Native format","title":"Supported input formats","text":"native format fdacluster consists pair vector/matrix x matrix/array y respectively storing evaluation grids values curves grids.","code":""},{"path":"/articles/input-formats.html","id":"passing-evaluation-grids-through-the-x-argument","dir":"Articles","previous_headings":"Native format","what":"Passing evaluation grids through the x argument","title":"Supported input formats","text":"curves evaluated exact grid, x can either numeric vector size \\(M\\) numeric matrix size \\(N \\times M\\), case rows identical. however possible , despite common grid size, curves actually evaluated different grids. case, x matrix size \\(N \\times M\\).","code":""},{"path":"/articles/input-formats.html","id":"passing-curve-values-through-the-y-argument","dir":"Articles","previous_headings":"Native format","what":"Passing curve values through the y argument","title":"Supported input formats","text":"curves evaluate univariate codomain, y can either numeric matrix size \\(N \\times M\\) numeric array size \\(N \\times 1 \\times M\\). cases, stores individual curves rows value corresponding grid point either second dimension y matrix third dimension y array. however possible curves evaluate multivariate codomain dimension \\(L\\) case, y array size \\(N \\times L \\times M\\).","code":""},{"path":"/articles/input-formats.html","id":"parsers-for-standard-functional-r-objects","dir":"Articles","previous_headings":"","what":"Parsers for standard functional R objects","title":"Supported input formats","text":"reason choice native format computation efficiency. However, R landscape functional data analysis rich. led us make fdacluster compatible standard ways storing functional data R. Specifically, added support fd class fda package funData multiFunData classes funData package.","code":""},{"path":"/articles/input-formats.html","id":"support-for-fundata","dir":"Articles","previous_headings":"Parsers for standard functional R objects","what":"Support for funData","title":"Supported input formats","text":"funData package package designed sole purpose implement classes storing kinds functional data. Functional data domain codomain, can univariate multivariate. addition, function data sample might observed different grid. led authors funData package propose three different classes, namely (Happ-Kurz 2020): Class funData dense functional data arbitrary dimension (cases dimension domain \\(d \\\\{1, 2, 3\\}\\)) common set observation points \\(t_1, \\dots, t_S\\) curves. curves may missing values coded NA. Class irregFunData irregularly sampled functional data individual sampling points \\(t_{ij}\\), \\(j = 1, \\dots, S_i\\), \\(= 1, \\dots ,N\\) curves. number \\(S_i\\) location observation points can vary across individual observations. moment, data one-dimensional domains implemented. Class multiFunData multivariate functional data, combines \\(p\\) elements functional data may defined different dimensional domains (e.g., functions images). fdacluster package focuses functional data defined uni-dimensional domains possibly multivariate codomains possibly different evaluation grids per curve. , support three classes needed. achieved utility function format_inputs() can read classes funData package provided x argument y argument. Specifically, following code shows classes funData package transformed (x, y) matrix / array format:","code":"if (inherits(x, \"funData\")) {   if (length(x@argvals) > 1)     cli::cli_abort(c(       \"The {.pkg fdacluster} package does not support functional data defined \",       \"on multivariate domains.\"     ))   L <- 1   y <- x@X   dims <- dim(y)   N <- dims[1]   M <- dims[2]   y <- array(y, dim = c(N, L, M))   x <- x@argvals[[1]] } else if (inherits(x, \"irregFunData\")) {   L <- 1   N <- length(x@argvals)   M <- x@argvals |>      purrr::map_int(length) |>      mean() |>      round()   y <- array(dim = c(N, L, M))   y[, 1, ] <- x@X |>      purrr::imap(\\(values, id) approx(x@argvals[[id]], values, n = M)$y) |>      do.call(rbind, args = _)   x <- x@argvals |>      purrr::map(\\(grid) seq(min(grid), max(grid), length.out = M)) |>      do.call(rbind, args = _) } else if (inherits(x, \"multiFunData\")) {   L <- length(x)   dims <- dim(x[[1]]@X)   grid <- x[[1]]@argvals[[1]]   purrr::walk(x, \\(fData) {     if (length(fData@argvals) != 1)       cli::cli_abort(c(         \"The {.pkg fdacluster} package does not support functional data \",          \"defined on multivariate domains.\"       ))     if (any(fData@argvals[[1]] != grids))       cli::cli_abort(c(         \"All components of the {.cls multiFunData} object must share the same \",         \"evaluation grids.\"       ))     if (any(dim(fData@X) != dims))       cli::cli_abort(c(         \"All components of the {.cls multiFunData} object must have values \",          \"stored in matrices with the same dimensions.\"       ))   })   N <- dims[1]   M <- dims[2]   y <- array(dim = c(N, L, M))   for (l in 1:L) y[, l, ] <- x[[l]]@X   x <- grid } else   cli::cli_abort(c(     \"Functional data provided in a single argument {.arg x} must be either of \",     \"class {.cls funData} or of class {.cls irregFunData} or of class \",      \"{.cls multiFunData}.\"   ))"},{"path":"/articles/input-formats.html","id":"example-for-fundata-support-growth-data","dir":"Articles","previous_headings":"Parsers for standard functional R objects > Support for funData","what":"Example for funData support: Growth Data","title":"Supported input formats","text":"following lines code demonstrates clustering functions fdacluster handle objects class funData using Berkeley growth data study developed Silverman Ramsay (2002).","code":"growth <- fda::growth growthData <- funData::funData(   argvals = growth$age,    X = t(cbind(growth$hgtm, growth$hgtf)) ) out_growth <- fdakmeans(   x = growthData,   n_clusters = 2,   seeding_strategy = \"exhaustive-kmeans++\",   cluster_on_phase = TRUE,   use_verbose = FALSE ) plot(out_growth)"},{"path":"/articles/input-formats.html","id":"example-for-irregfundata-support-simulated-data","dir":"Articles","previous_headings":"Parsers for standard functional R objects > Support for funData","what":"Example for irregFunData support: Simulated Data","title":"Supported input formats","text":"following lines code demonstrates clustering functions fdacluster handle objects class irregFunData using -house simulated data fly.","code":"# Generates full grid argvals <- seq(0, 2 * pi, by = 0.01) # Simulate 30 irregular grids with various sampling points (number and values) indices <- replicate(30, sort(sample(1:length(argvals), sample(30:50, 1)))) argvalsIrreg <- lapply(indices, \\(i) argvals[i]) # Simulate functional data with obvious grouping structure withr::with_seed(1234, {   simData <- funData::irregFunData(     argvals = argvalsIrreg,      X = mapply(       function(x, a, b) a * sin(x + b),        x = argvalsIrreg,        a = c(rgamma(10, 25, 50), rgamma(10, 50, 50), rgamma(10, 100, 50)),       b = c(rnorm(10, -1, 0.1), rnorm(10, 0, 0.1), rnorm(10, 1, 0.1))     )   )   }) out_sim <- fdakmeans(   x = simData,   n_clusters = 3,   seeding_strategy = \"exhaustive-kmeans++\",   use_verbose = FALSE ) plot(out_sim)"},{"path":"/articles/input-formats.html","id":"example-for-multifundata-support-gait-data","dir":"Articles","previous_headings":"Parsers for standard functional R objects > Support for funData","what":"Example for multiFunData support: Gait Data","title":"Supported input formats","text":"following lines code demonstrates clustering functions fdacluster handle objects class multiFunData using gait data study developed Silverman Ramsay (2002).","code":"cycle_perc <- (0:19) / 19 * 100 hipData <- t(fda::gait[, , 1]) hipData <- hipData kneeData <- t(fda::gait[, , 2]) kneeData <- kneeData gaitData <- funData::multiFunData(   funData::funData(argvals = cycle_perc, X = hipData),    funData::funData(argvals = cycle_perc, X = kneeData) ) out_gait <- fdakmeans(   x = gaitData,   n_clusters = 1,   seeding_strategy = \"exhaustive\",   warping_class = \"srsf\",   use_verbose = FALSE ) p <- autoplot(out_gait) p$data$component_id <- factor(p$data$component_id, labels = c(\"Hip\", \"Knee\")) p + labs(y = \"Angle (degree)\", title = \"Gait Kinematics\")"},{"path":"/articles/input-formats.html","id":"support-for-fda","dir":"Articles","previous_headings":"Parsers for standard functional R objects","what":"Support for fda","title":"Supported input formats","text":"fda package features class fd hosting R structure functional data. representation, functional data decomposed number basis functions (Ramsay Silverman 2006). class list following 3 components: coefs: Stores coefficients functional datum sample corresponding expansion along basis functions; basis: Stores basis functions; fdnames: Stores IDs coefficient, observation dimension co-domain. Basis functions supported fda package exclusively defined univariate domains. , class fd handles functional data unidimensional domains. However, accommodates functional data evaluating multidimensional co-domain. achieved using three-dimensional array coefficients instead vector matrix. Indeed, quoting help page fd class: coef: vector, matrix, three-dimensional array coefficients. first dimension (elements vector) corresponds basis functions. second dimension corresponds number functional observations, curves replicates. coef vector, represents single functional observation. coef array, third dimension corresponds variables multivariate functional data objects. functional data object univariate coef vector matrix multivariate three-dimensional array. Consequently, fdacluster package handles objects class fd considering x, native format, stores unidimensional grids y object class fd. parses data following way:","code":"dims <- purrr::map_int(y$fdnames, length) M <- dims[1] N <- dims[2] L <- dims[3] if (is.vector(x)) {   if (length(x) != M)     cli::cli_abort(c(       \"The number of function evaluations ({M}) does not match the grid \",       \"size ({length(x)}).\"     ))   y <- fda::eval.fd(x, y) } else {   if (nrow(x) != N)     cli::cli_abort(c(       \"When provided multiple evaluation grids as a matrix, the number of \",       \"rows should match the number of curves.\"     ))   if (ncol(x) != M)     cli::cli_abort(c(       \"When provided multiple evaluation grids as a matrix, the number of \",       \"columns should match the common grid size.\"     ))   y <- fda::eval.fd(t(x), y) } if (is.null(dim(y))) {   # y is a single 1-dimensional curve   y <- array(y, dim = c(length(y), 1, 1)) } else if (length(dim(y)) == 2) {   # y is N 1-dimensional curves   y <- array(y, dim = c(dim(y), 1)) } y <- aperm(y, c(2, 3, 1))"},{"path":"/articles/input-formats.html","id":"example-for-fd-support-gait-data","dir":"Articles","previous_headings":"Parsers for standard functional R objects > Support for fda","what":"Example for fd support: Gait Data","title":"Supported input formats","text":"following lines code demonstrates clustering functions fdacluster handle objects class fd using gait data study developed Silverman Ramsay (2002).","code":"bspl <- fda::create.fourier.basis(rangeval = c(0, 100), nbasis = 5) gaitDataFD <- fda::smooth.basis(   argvals = cycle_perc,    y = fda::gait,    fdParobj = bspl )$fd out_gait_fd <- fdakmeans(   x = cycle_perc,   y = gaitDataFD,   n_clusters = 1,    seeding_strategy = \"exhaustive\",   warping_class = \"srsf\",   use_verbose = FALSE ) p <- autoplot(out_gait_fd) p$data$component_id <- factor(p$data$component_id, labels = c(\"Hip\", \"Knee\")) p + labs(y = \"Angle (degree)\", title = \"Gait Kinematics\")"},{"path":[]},{"path":"/articles/kmeans-initialisation.html","id":"manual-specification-of-the-initial-seeds","dir":"Articles","previous_headings":"","what":"Manual specification of the initial seeds","title":"Computing initial centroids in k-means","text":"can use optional argument seeds takes integer vector one can manually specify indices observations used initial centroids. vector hence needs size n_clusters. however leads outcome sensitive initial choice seeds:","code":"out_manual <- fdakmeans(   x = simulated30$x,   y = simulated30$y,   n_clusters = 2,   seeds = c(1, 21),   warping_class = \"affine\",   centroid_type = \"mean\",   metric = \"l2\",   cluster_on_phase = FALSE,   use_verbose = FALSE ) knitr::kable(table(out_manual$memberships, true_groups)) withr::with_seed(1234, {   initial_seeds <- replicate(10, sample.int(30, 2, replace = FALSE), simplify = FALSE)   outs_manual <- purrr::map(initial_seeds, \\(.seeds) {     fdakmeans(       x = simulated30$x,       y = simulated30$y,       n_clusters = 2,       seeds = .seeds,       warping_class = \"affine\",       centroid_type = \"mean\",       metric = \"l2\",       cluster_on_phase = FALSE,       use_verbose = FALSE     )   }) }) tibble::tibble(   Initialization = initial_seeds |>      purrr::map_chr(\\(.seeds) paste(.seeds, collapse = \",\")),    `Misclassification Rate (%)` = purrr::map_dbl(outs_manual, \\(.clus) {     tbl <- table(.clus$memberships, true_groups)     round(min(tbl[1, 1] + tbl[2, 2], tbl[1, 2] + tbl[2, 1]) / 30 * 100, 2)   }) ) |>    knitr::kable()"},{"path":"/articles/kmeans-initialisation.html","id":"k-means","dir":"Articles","previous_headings":"","what":"\\(k\\)-means++","title":"Computing initial centroids in k-means","text":"\\(k\\)-means++ strategy originally proposed Arthur Vassilvitskii (2007). algorithm nicely described corresponding Wikipedia page follows: Choose one center uniformly random among data points. data point \\(x\\) chosen yet, compute \\(D(x)\\), distance \\(x\\) nearest center already chosen. Choose one new data point random new center, using weighted probability distribution point \\(x\\) chosen probability proportional \\(D(x)^2\\). Repeat Steps \\(2\\) \\(3\\) \\(k\\) centers chosen. Now initial centers chosen, proceed using standard \\(k\\)-means clustering. Despite probabilistic nature outcome follows strategy, provides robust \\(k\\)-means procedure:","code":"withr::with_seed(1234, {   outs_kpp <- replicate(10, {     fdakmeans(       x = simulated30$x,       y = simulated30$y,       n_clusters = 2,       seeding_strategy = \"kmeans++\",       warping_class = \"affine\",       centroid_type = \"mean\",       metric = \"l2\",       cluster_on_phase = FALSE,       use_verbose = FALSE     )   }, simplify = FALSE) }) tibble::tibble(   Run = 1:10,    `Misclassification Rate (%)` = purrr::map_dbl(outs_kpp, \\(.clus) {     tbl <- table(.clus$memberships, true_groups)     round(min(tbl[1, 1] + tbl[2, 2], tbl[1, 2] + tbl[2, 1]) / 30 * 100, 2)   }) ) |>    knitr::kable()"},{"path":"/articles/kmeans-initialisation.html","id":"exhaustive-k-means","dir":"Articles","previous_headings":"","what":"Exhaustive \\(k\\)-means++","title":"Computing initial centroids in k-means","text":"\\(k\\)-means++ initialization procedure introduces two additional sources randomness: One randomly picking first centroid; , One picking remaining centroids based weighted probability distribution. easy, computational cost linear \\(N\\), get rid first source randomness exhaustively run \\(k\\)-means algorithm \\(k\\)-means++ initialization strategy using observation possible centroid first cluster. call exhaustive \\(k\\)-means++ strategy:","code":"withr::with_seed(1234, {   outs_ekpp <- replicate(10, {     fdakmeans(       x = simulated30$x,       y = simulated30$y,       n_clusters = 2,       seeding_strategy = \"exhaustive-kmeans++\",       warping_class = \"affine\",       centroid_type = \"mean\",       metric = \"l2\",       cluster_on_phase = FALSE,       use_verbose = FALSE     )   }, simplify = FALSE) }) tibble::tibble(   Run = 1:10,    `Misclassification Rate (%)` = purrr::map_dbl(outs_ekpp, \\(.clus) {     tbl <- table(.clus$memberships, true_groups)     round(min(tbl[1, 1] + tbl[2, 2], tbl[1, 2] + tbl[2, 1]) / 30 * 100, 2)   }) ) |>    knitr::kable()"},{"path":"/articles/kmeans-initialisation.html","id":"exhaustive-search","dir":"Articles","previous_headings":"","what":"Exhaustive search","title":"Computing initial centroids in k-means","text":"completeness, also possible perform exhaustive search although rarely practical. simulated data \\(N = 30\\) curves looking \\(2\\), achieved setting seeding_strategy = \"exhaustive\" require run algorithm 435 times instead \\(30\\) times exhaustive \\(k\\)-means++ strategy already achieves excellent robustness performances.","code":""},{"path":"/articles/kmeans-initialisation.html","id":"hierarchial-clustering","dir":"Articles","previous_headings":"","what":"Hierarchial clustering","title":"Computing initial centroids in k-means","text":"alternative use hierarchical clustering \\(k\\)-means get good initial candidates centroids: strategy completely deterministic. case, seems work well. However, perform badly \\(k\\)-means clustering hierarchial clustering meant provide clusters first place. Note also implement DBSCAN initialization strategy similar fashion, added benefit autotuning number clusters look . currently implemented user can well carry hand. First, run fdadbscan() data, tell many clusters search . use cluster medoids seeds argument fdakmeans().","code":"out <- fdakmeans(   x = simulated30$x,   y = simulated30$y,   n_clusters = 2,   seeding_strategy = \"hclust\",   warping_class = \"affine\",   centroid_type = \"mean\",   metric = \"l2\",   cluster_on_phase = FALSE,   use_verbose = FALSE ) knitr::kable(table(out_hclust$memberships, true_groups))"},{"path":"/articles/kmeans-initialisation.html","id":"final-recommandations","dir":"Articles","previous_headings":"","what":"Final recommandations","title":"Computing initial centroids in k-means","text":"functional data sets reasonable sample size, recommend use exhaustive \\(k\\)-means++ strategy. moderate large sample sizes, recommend switch \\(k\\)-means++ strategy. latter current running default fdakmeans().","code":""},{"path":[]},{"path":"/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Aymeric Stamm. Author, maintainer. Laura Sangalli. Contributor. Piercesare Secchi. Contributor. Simone Vantini. Contributor. Valeria Vitelli. Contributor. Alessandro Zito. Contributor.","code":""},{"path":"/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Stamm (2023). fdacluster: Joint Clustering Alignment Functional Data. https://astamm.github.io/fdacluster/index.html, https://github.com/astamm/fdacluster.","code":"@Manual{,   title = {fdacluster: Joint Clustering and Alignment of Functional Data},   author = {Aymeric Stamm},   year = {2023},   note = {https://astamm.github.io/fdacluster/index.html, https://github.com/astamm/fdacluster}, }"},{"path":"/index.html","id":"fdacluster-","dir":"","previous_headings":"","what":"Joint Clustering and Alignment of Functional Data","title":"Joint Clustering and Alignment of Functional Data","text":"fdacluster package provides implementations k-means, hierarchical agglomerative DBSCAN clustering methods functional data. Variability functional data intrinsically divided three components: amplitude, phase ancillary variability. first two sources variability can captured dedicated statistical analysis integrates curve alignment step. k-means HAC algorithms implemented fdacluster provide clustering structures based either ampltitude variation (default behavior) phase variation. achieved jointly performing clustering alignment functional data set. three main related functions fdakmeans() k-means, fdahclust() HAC fdadbscan() DBSCAN. methods handle multivariate codomains.","code":""},{"path":"/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Joint Clustering and Alignment of Functional Data","text":"can install official version CRAN via: can opt install development version GitHub :","code":"install.packages(\"fdacluster\") # install.packages(\"remotes\") remotes::install_github(\"astamm/fdacluster\")"},{"path":[]},{"path":"/index.html","id":"data-set","dir":"","previous_headings":"Example","what":"Data set","title":"Joint Clustering and Alignment of Functional Data","text":"Let us consider following simulated example 30 1-dimensional curves: Looking data set, seems shall expect 3 groups aim clustering based phase variability probably 2 groups search clustering structure based amplitude variability.","code":""},{"path":"/index.html","id":"k-means-based-on-amplitude-variability","dir":"","previous_headings":"Example","what":"k-means based on amplitude variability","title":"Joint Clustering and Alignment of Functional Data","text":"can perform k-means clustering based amplitude variability follows: fdakmeans(), fdahclust() fdadbscan() functions returns object class caps (Clustering Amplitude Phase Separation) S3 specialized methods ggplot2::autoplot() graphics::plot() implemented. Therefore, can visualize results simply :","code":"out1 <- fdakmeans(   simulated30$x,   simulated30$y,   seeds = c(1, 21),   n_clusters = 2,   centroid_type = \"mean\",   warping_class = \"affine\",   metric = \"pearson\",    cluster_on_phase = FALSE ) #> Information about the data set: #>  - Number of observations: 30 #>  - Number of dimensions: 1 #>  - Number of points: 200 #>  #> Information about cluster initialization: #>  - Number of clusters: 2 #>  - Initial seeds for cluster centers:          1        21 #>  #> Information about the methods used within the algorithm: #>  - Warping method: affine #>  - Center method: mean #>  - Dissimilarity method: pearson #>  - Optimization method: bobyqa #>  #> Information about warping parameter bounds: #>  - Warping options:    0.1500   0.1500 #>  #> Information about convergence criteria: #>  - Maximum number of iterations: 100 #>  - Distance relative tolerance: 0.001 #>  #> Information about parallelization setup: #>  - Number of threads: 1 #>  - Parallel method: 0 #>  #> Other information: #>  - Use fence to robustify: 0 #>  - Check total dissimilarity: 1 #>  - Compute overall center: 0 #>  #> Running k-centroid algorithm: #>  - Iteration #1 #>    * Size of cluster #0: 20 #>    * Size of cluster #1: 10 #>  - Iteration #2 #>    * Size of cluster #0: 20 #>    * Size of cluster #1: 10 #>  #> Active stopping criteria: #>  - Memberships did not change. plot(out1, type = \"amplitude\") plot(out1, type = \"phase\")"},{"path":"/index.html","id":"k-means-based-on-phase-variability","dir":"","previous_headings":"Example","what":"k-means based on phase variability","title":"Joint Clustering and Alignment of Functional Data","text":"can perform k-means clustering based phase variability switch cluster_on_phase argument TRUE: can inspect result:   can perform similar analyses using HAC DBSCAN instead k-means. fdacluster package also provides visualization tools help choosing optimal number cluster based WSS silhouette values. can achieved using combination functions compare_caps() plot.mcaps().","code":"out2 <- fdakmeans(   simulated30$x,   simulated30$y,   seeds = c(1, 11, 21),   n_clusters = 3,   centroid_type = \"mean\",   warping_class = \"affine\",   metric = \"pearson\",    cluster_on_phase = TRUE ) #> Information about the data set: #>  - Number of observations: 30 #>  - Number of dimensions: 1 #>  - Number of points: 200 #>  #> Information about cluster initialization: #>  - Number of clusters: 3 #>  - Initial seeds for cluster centers:          1        11        21 #>  #> Information about the methods used within the algorithm: #>  - Warping method: affine #>  - Center method: mean #>  - Dissimilarity method: pearson #>  - Optimization method: bobyqa #>  #> Information about warping parameter bounds: #>  - Warping options:    0.1500   0.1500 #>  #> Information about convergence criteria: #>  - Maximum number of iterations: 100 #>  - Distance relative tolerance: 0.001 #>  #> Information about parallelization setup: #>  - Number of threads: 1 #>  - Parallel method: 0 #>  #> Other information: #>  - Use fence to robustify: 0 #>  - Check total dissimilarity: 1 #>  - Compute overall center: 0 #>  #> Running k-centroid algorithm: #>  - Iteration #1 #>    * Size of cluster #0: 10 #>    * Size of cluster #1: 10 #>    * Size of cluster #2: 10 #>  - Iteration #2 #>    * Size of cluster #0: 10 #>    * Size of cluster #1: 10 #>    * Size of cluster #2: 10 #>  #> Active stopping criteria: #>  - Memberships did not change. plot(out2, type = \"amplitude\") plot(out2, type = \"phase\")"},{"path":"/reference/autoplot.caps.html","id":null,"dir":"Reference","previous_headings":"","what":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","title":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","text":"function creates visualization result k-mean alignment algorithm invisibly returns corresponding ggplot2::ggplot object enable customization plot. user can choose visualize either amplitude information data case original aligned curves shown phase information data case estimated warping functions shown.","code":""},{"path":"/reference/autoplot.caps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","text":"","code":"# S3 method for caps autoplot(object, type = c(\"amplitude\", \"phase\"), ...)"},{"path":"/reference/autoplot.caps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","text":"object object class caps. type string specifying type information display. Choices \"amplitude\" plotting original aligned curves represent amplitude information data \"phase\" plotting corresponding warping functions represent phase information data. Defaults \"amplitude\". ... used.","code":""},{"path":"/reference/autoplot.caps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","text":"ggplot2::ggplot object invisibly.","code":""},{"path":"/reference/autoplot.caps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","text":"","code":"ggplot2::autoplot(sim30_caps, type = \"amplitude\")  ggplot2::autoplot(sim30_caps, type = \"phase\")"},{"path":"/reference/autoplot.mcaps.html","id":null,"dir":"Reference","previous_headings":"","what":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","title":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","text":"S3 method implementation ggplot2::autoplot() generic objects class mcaps visualize performances multiple caps objects applied data sets either terms WSS terms silhouette values.","code":""},{"path":"/reference/autoplot.mcaps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","text":"","code":"# S3 method for mcaps autoplot(   object,   validation_criterion = c(\"wss\", \"silhouette\"),   what = c(\"mean\", \"distribution\"),   ... )"},{"path":"/reference/autoplot.mcaps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","text":"object object class mcaps. validation_criterion string specifying validation criterion used comparison. Choices \"wss\" \"silhouette\". Defaults \"wss\". string specifying kind information display validation criterion. Choices \"mean\" (plots mean values) \"distribution\" (plots boxplots). Defaults \"mean\". ... arguments passed specific methods.","code":""},{"path":"/reference/autoplot.mcaps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","text":"object class ggplot2::ggplot.","code":""},{"path":"/reference/autoplot.mcaps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","text":"","code":"p <- ggplot2::autoplot(sim30_mcaps)"},{"path":"/reference/caps.html","id":null,"dir":"Reference","previous_headings":"","what":"Class for clustering with amplitude and phase separation — caps","title":"Class for clustering with amplitude and phase separation — caps","text":"k-means algorithm joint amplitude phase separation produces number outputs. class meant encapsulate single object providing dedicated S3 methods e.g. plotting, summarizing, etc. name class stems Clustering Amplitude Phase Separation.","code":""},{"path":"/reference/caps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Class for clustering with amplitude and phase separation — caps","text":"","code":"as_caps(x)  is_caps(x)"},{"path":"/reference/caps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Class for clustering with amplitude and phase separation — caps","text":"x list coercible object class caps.","code":""},{"path":"/reference/caps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Class for clustering with amplitude and phase separation — caps","text":"function as_caps() returns object class caps. function is_caps() returns boolean evaluates TRUE input object class caps.","code":""},{"path":"/reference/caps.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Class for clustering with amplitude and phase separation — caps","text":"object class caps list following components: original_curves: numeric matrix shape \\(N \\times L \\times M\\) storing sample \\(N\\) \\(L\\)-dimensional original curves observed grids size \\(M\\). original_grids: numeric matrix size \\(N \\times M\\) storing grids size \\(M\\) original curves evaluated; aligned_grids: numeric matrix size \\(N \\times M\\) storing grids size \\(M\\) original curves must evaluated aligned; center_curves: numeric matrix shape \\(K \\times L \\times M\\) storing \\(K\\) centers \\(L\\)-dimensional curves observed grid size \\(M\\); center_grids: numeric matrix size \\(K \\times M\\) storing grids size \\(M\\) center curves evaluated; warpings: numeric matrix shape \\(N \\times M\\) storing estimated warping functions \\(N\\) curves evaluated within-cluster common grids size \\(M\\); n_clusters: integer value storing number clusters; memberships: integer vector length \\(N\\) storing cluster ID curve belongs ; distances_to_center: numeric vector length \\(N\\) storing distance curve center cluster; silhouettes: numeric vector length \\(N\\) storing silhouette values observation; amplitude_variation: numeric value storing fraction total variation explained amplitude variability. total_variation: numeric value storing amount total variation. n_iterations: integer value storing number iterations performed convergence; call_name: string storing name function used produce k-means alignment results; call_args: list containing exact arguments passed function call_name produced output.","code":""},{"path":"/reference/caps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Class for clustering with amplitude and phase separation — caps","text":"","code":"as_caps(sim30_caps) #> $original_curves #> , , 1 #>  #>               [,1] #>  [1,]  0.027585567 #>  [2,] -0.019122794 #>  [3,]  0.037127207 #>  [4,] -0.016504298 #>  [5,] -0.053862340 #>  [6,]  0.002390483 #>  [7,]  0.060582573 #>  [8,]  0.031296346 #>  [9,]  0.017802725 #> [10,] -0.016128447 #> [11,] -0.353705417 #> [12,] -0.306154690 #> [13,] -0.268853383 #> [14,] -0.336659606 #> [15,] -0.336139594 #> [16,] -0.282849484 #> [17,] -0.331959677 #> [18,] -0.381681429 #> [19,] -0.261148065 #> [20,] -0.294778598 #> [21,]  0.127915304 #> [22,] -0.115174088 #> [23,]  0.086588678 #> [24,] -0.058058695 #> [25,]  0.092733378 #> [26,]  0.144257098 #> [27,]  0.042433557 #> [28,]  0.018158416 #> [29,] -0.059882343 #> [30,] -0.071571086 #>  #> , , 2 #>  #>               [,1] #>  [1,]  0.056055003 #>  [2,]  0.012604059 #>  [3,]  0.071250063 #>  [4,]  0.014656955 #>  [5,] -0.022282594 #>  [6,]  0.038722846 #>  [7,]  0.096053308 #>  [8,]  0.064451572 #>  [9,]  0.046771344 #> [10,]  0.014178033 #> [11,] -0.332803768 #> [12,] -0.286771832 #> [13,] -0.247743379 #> [14,] -0.319789735 #> [15,] -0.315841203 #> [16,] -0.261729406 #> [17,] -0.311774826 #> [18,] -0.363619635 #> [19,] -0.238761424 #> [20,] -0.275920966 #> [21,]  0.182112461 #> [22,] -0.051964708 #> [23,]  0.143005410 #> [24,]  0.000138365 #> [25,]  0.157593431 #> [26,]  0.211320313 #> [27,]  0.108642486 #> [28,]  0.084472567 #> [29,]  0.002870550 #> [30,] -0.004164329 #>  #> , , 3 #>  #>               [,1] #>  [1,]  0.084745168 #>  [2,]  0.044626092 #>  [3,]  0.105624048 #>  [4,]  0.046139272 #>  [5,]  0.009640254 #>  [6,]  0.075381167 #>  [7,]  0.131781404 #>  [8,]  0.097841962 #>  [9,]  0.075974784 #> [10,]  0.044770905 #> [11,] -0.311445643 #> [12,] -0.267087941 #> [13,] -0.226289222 #> [14,] -0.302611375 #> [15,] -0.295144901 #> [16,] -0.240218256 #> [17,] -0.291163406 #> [18,] -0.345172668 #> [19,] -0.216054147 #> [20,] -0.256724223 #> [21,]  0.235907973 #> [22,]  0.010952036 #> [23,]  0.199042757 #> [24,]  0.058069824 #> [25,]  0.221925897 #> [26,]  0.277834500 #> [27,]  0.174415016 #> [28,]  0.150374942 #> [29,]  0.065316585 #> [30,]  0.062904089 #>  #> , , 4 #>  #>              [,1] #>  [1,]  0.11362927 #>  [2,]  0.07690931 #>  [3,]  0.14021664 #>  [4,]  0.07791130 #>  [5,]  0.04187577 #>  [6,]  0.11232416 #>  [7,]  0.16772645 #>  [8,]  0.13143551 #>  [9,]  0.10538807 #> [10,]  0.07562353 #> [11,] -0.28964722 #> [12,] -0.24711402 #> [13,] -0.20450512 #> [14,] -0.28513364 #> [15,] -0.27406491 #> [16,] -0.21833199 #> [17,] -0.27014045 #> [18,] -0.32635226 #> [19,] -0.19304030 #> [20,] -0.23720041 #> [21,]  0.28925807 #> [22,]  0.07351139 #> [23,]  0.25465227 #> [24,]  0.11568729 #> [25,]  0.28565906 #> [26,]  0.34372811 #> [27,]  0.23968122 #> [28,]  0.21579503 #> [29,]  0.12739697 #> [30,]  0.12955931 #>  #> , , 5 #>  #>              [,1] #>  [1,]  0.14268058 #>  [2,]  0.10941976 #>  [3,]  0.17499543 #>  [4,]  0.10994173 #>  [5,]  0.07439351 #>  [6,]  0.14951063 #>  [7,]  0.20384822 #>  [8,]  0.16520030 #>  [9,]  0.13498629 #> [10,]  0.10670932 #> [11,] -0.26742482 #> [12,] -0.22686117 #> [13,] -0.18240535 #> [14,] -0.26736570 #> [15,] -0.25261557 #> [16,] -0.19608667 #> [17,] -0.24872115 #> [18,] -0.30717026 #> [19,] -0.16973404 #> [20,] -0.21736167 #> [21,]  0.34211915 #> [22,]  0.13564860 #> [23,]  0.30978565 #> [24,]  0.17294242 #> [25,]  0.34872148 #> [26,]  0.40892990 #> [27,]  0.30437139 #> [28,]  0.28066248 #> [29,]  0.18905298 #> [30,]  0.19572654 #>  #> , , 6 #>  #>             [,1] #>  [1,]  0.1718725 #>  [2,]  0.1421236 #>  [3,]  0.2099281 #>  [4,]  0.1421993 #>  [5,]  0.1071631 #>  [6,]  0.1868995 #>  [7,]  0.2401067 #>  [8,]  0.1991045 #>  [9,]  0.1647446 #> [10,]  0.1380017 #> [11,] -0.2447949 #> [12,] -0.2063405 #> [13,] -0.1600043 #> [14,] -0.2493168 #> [15,] -0.2308114 #> [16,] -0.1734985 #> [17,] -0.2269208 #> [18,] -0.2876386 #> [19,] -0.1461496 #> [20,] -0.1972202 #> [21,]  0.3944478 #> [22,]  0.1972990 #> [23,]  0.3643948 #> [24,]  0.2297869 #> [25,]  0.4110421 #> [26,]  0.4733690 #> [27,]  0.3684161 #> [28,]  0.3449072 #> [29,]  0.2502260 #> [30,]  0.2613312 #>  #> , , 7 #>  #>             [,1] #>  [1,]  0.2011785 #>  [2,]  0.1749871 #>  [3,]  0.2449826 #>  [4,]  0.1746530 #>  [5,]  0.1401542 #>  [6,]  0.2244500 #>  [7,]  0.2764621 #>  [8,]  0.2331166 #>  [9,]  0.1946383 #> [10,]  0.1694743 #> [11,] -0.2217742 #> [12,] -0.1855634 #> [13,] -0.1373165 #> [14,] -0.2309963 #> [15,] -0.2086668 #> [16,] -0.1505837 #> [17,] -0.2047548 #> [18,] -0.2677695 #> [19,] -0.1223012 #> [20,] -0.1767884 #> [21,]  0.4462008 #> [22,]  0.2583981 #> [23,]  0.4184318 #> [24,]  0.2861727 #> [25,]  0.4725502 #> [26,]  0.5369752 #> [27,]  0.4317461 #> [28,]  0.4084594 #> [29,]  0.3108576 #> [30,]  0.3262988 #>  #> , , 8 #>  #>              [,1] #>  [1,]  0.23057223 #>  [2,]  0.20797659 #>  [3,]  0.28012680 #>  [4,]  0.20727163 #>  [5,]  0.17333658 #>  [6,]  0.26212140 #>  [7,]  0.31287490 #>  [8,]  0.26720494 #>  [9,]  0.22464267 #> [10,]  0.20110058 #> [11,] -0.19837931 #> [12,] -0.16454089 #> [13,] -0.11435628 #> [14,] -0.21241356 #> [15,] -0.18619667 #> [16,] -0.12735876 #> [17,] -0.18223873 #> [18,] -0.24757491 #> [19,] -0.09820322 #> [20,] -0.15607847 #> [21,]  0.49733519 #> [22,]  0.31888157 #> [23,]  0.47184906 #> [24,]  0.34205171 #> [25,]  0.53317568 #> [26,]  0.59967849 #> [27,]  0.49429288 #> [28,]  0.47124980 #> [29,]  0.37088947 #> [30,]  0.39055551 #>  #> , , 9 #>  #>              [,1] #>  [1,]  0.26002753 #>  [2,]  0.24105876 #>  [3,]  0.31532908 #>  [4,]  0.24002453 #>  [5,]  0.20668012 #>  [6,]  0.29987337 #>  [7,]  0.34930609 #>  [8,]  0.30133837 #>  [9,]  0.25473330 #> [10,]  0.23285444 #> [11,] -0.17462715 #> [12,] -0.14328448 #> [13,] -0.09113836 #> [14,] -0.19357800 #> [15,] -0.16341561 #> [16,] -0.10384000 #> [17,] -0.15938816 #> [18,] -0.22706726 #> [19,] -0.07387002 #> [20,] -0.13510295 #> [21,]  0.54780840 #> [22,]  0.37868539 #> [23,]  0.52459932 #> [24,]  0.39737621 #> [25,]  0.59284902 #> [26,]  0.66140980 #> [27,]  0.55598817 #> [28,]  0.53320941 #> [29,]  0.43026377 #> [30,]  0.45402753 #>  #> , , 10 #>  #>              [,1] #>  [1,]  0.28951840 #>  [2,]  0.27420042 #>  [3,]  0.35055792 #>  [4,]  0.27288101 #>  [5,]  0.24015486 #>  [6,]  0.33766585 #>  [7,]  0.38571686 #>  [8,]  0.33548586 #>  [9,]  0.28488584 #> [10,]  0.26470974 #> [11,] -0.15053463 #> [12,] -0.12180550 #> [13,] -0.06767730 #> [14,] -0.17449912 #> [15,] -0.14033848 #> [16,] -0.08004397 #> [17,] -0.13621881 #> [18,] -0.20625886 #> [19,] -0.04931601 #> [20,] -0.11387429 #> [21,]  0.59757811 #> [22,]  0.43774589 #> [23,]  0.57663564 #> [24,]  0.45209866 #> [25,]  0.65150136 #> [26,]  0.72210064 #> [27,]  0.61676437 #> [28,]  0.59426992 #> [29,]  0.48892288 #> [30,]  0.51664181 #>  #> , , 11 #>  #>              [,1] #>  [1,]  0.31901905 #>  [2,]  0.30736863 #>  [3,]  0.38578205 #>  [4,]  0.30581066 #>  [5,]  0.27373100 #>  [6,]  0.37545915 #>  [7,]  0.42206890 #>  [8,]  0.36961661 #>  [9,]  0.31507612 #> [10,]  0.29664054 #> [11,] -0.12611880 #> [12,] -0.10011538 #> [13,] -0.04398777 #> [14,] -0.15518645 #> [15,] -0.11698017 #> [16,] -0.05598721 #> [17,] -0.11274645 #> [18,] -0.18516212 #> [19,] -0.02455561 #> [20,] -0.09240502 #> [21,]  0.64660239 #> [22,]  0.49599983 #> [23,]  0.62791149 #> [24,]  0.50617180 #> [25,]  0.70906460 #> [26,]  0.78168332 #> [27,]  0.67655452 #> [28,]  0.65436363 #> [29,]  0.54680957 #> [30,]  0.57832581 #>  #> , , 12 #>  #>                [,1] #>  [1,]  0.3485039432 #>  [2,]  0.3405307499 #>  [3,]  0.4209705321 #>  [4,]  0.3387832960 #>  [5,]  0.3073789478 #>  [6,]  0.4132139583 #>  [7,]  0.4583243409 #>  [8,]  0.4037001695 #>  [9,]  0.3452801851 #> [10,]  0.3286210951 #> [11,] -0.1013967547 #> [12,] -0.0782255654 #> [13,] -0.0200844166 #> [14,] -0.1356495668 #> [15,] -0.0933556320 #> [16,] -0.0316863013 #> [17,] -0.0889869137 #> [18,] -0.1637895560 #> [19,]  0.0003967326 #> [20,] -0.0707077048 #> [21,]  0.6948397338 #> [22,]  0.5533844457 #> [23,]  0.6783808038 #> [24,]  0.5595487380 #> [25,]  0.7654714779 #> [26,]  0.8400910210 #> [27,]  0.7352923684 #> [28,]  0.7134235445 #> [29,]  0.6038671173 #> [30,]  0.6390076855 #>  #> , , 13 #>  #>               [,1] #>  [1,]  0.377947777 #>  [2,]  0.373654449 #>  [3,]  0.456092724 #>  [4,]  0.371769029 #>  [5,]  0.341069319 #>  [6,]  0.450891401 #>  [7,]  0.494445788 #>  [8,]  0.437706352 #>  [9,]  0.375474272 #> [10,]  0.360625845 #> [11,] -0.076385641 #> [12,] -0.056147528 #> [13,]  0.004018056 #> [14,] -0.115898082 #> [15,] -0.069479859 #> [16,] -0.007157864 #> [17,] -0.064956082 #> [18,] -0.142153718 #> [19,]  0.025526553 #> [20,] -0.048794935 #> [21,]  0.742249055 #> [22,]  0.609837535 #> [23,]  0.727997982 #> [24,]  0.612182913 #> [25,]  0.820655679 #> [26,]  0.897257859 #> [27,]  0.792912482 #> [28,]  0.771383449 #> [29,]  0.660039266 #> [30,]  0.698616335 #>  #> , , 14 #>  #>              [,1] #>  [1,]  0.40732554 #>  [2,]  0.40670774 #>  [3,]  0.49111833 #>  [4,]  0.40473825 #>  [5,]  0.37477299 #>  [6,]  0.48845307 #>  [7,]  0.53039639 #>  [8,]  0.47160533 #>  [9,]  0.40563485 #> [10,]  0.39262947 #> [11,] -0.05110267 #> [12,] -0.03389277 #> [13,]  0.02830496 #> [14,] -0.09594164 #> [15,] -0.04536788 #> [16,]  0.01758148 #> [17,] -0.04066988 #> [18,] -0.12026722 #> [19,]  0.05081940 #> [20,] -0.02667933 #> [21,]  0.78878976 #> [22,]  0.66529752 #> [23,]  0.77671797 #> [24,]  0.66402819 #> [25,]  0.87455188 #> [26,]  0.95311897 #> [27,]  0.84935029 #> [28,]  0.82817799 #> [29,]  0.71527035 #> [30,]  0.75708151 #>  #> , , 15 #>  #>               [,1] #>  [1,]  0.436612490 #>  [2,]  0.439659010 #>  [3,]  0.526017416 #>  [4,]  0.437661680 #>  [5,]  0.408461098 #>  [6,]  0.525861045 #>  [7,]  0.566139839 #>  [8,]  0.505367627 #>  [9,]  0.435738646 #> [10,]  0.424606875 #> [11,] -0.025565073 #> [12,] -0.011472808 #> [13,]  0.052761585 #> [14,] -0.075789896 #> [15,] -0.021034751 #> [16,]  0.042515094 #> [17,] -0.016144244 #> [18,] -0.098142717 #> [19,]  0.076260824 #> [20,] -0.004373524 #> [21,]  0.834421786 #> [22,]  0.719703533 #> [23,]  0.824496279 #> [24,]  0.715038899 #> [25,]  0.927095827 #> [26,]  1.007610590 #> [27,]  0.904542188 #> [28,]  0.883742755 #> [29,]  0.769505310 #> [30,]  0.814333902 #>  #> , , 16 #>  #>                [,1] #>  [1,]  0.4657842249 #>  [2,]  0.4724770346 #>  [3,]  0.5607604364 #>  [4,]  0.4705103720 #>  [5,]  0.4421050813 #>  [6,]  0.5630779631 #>  [7,]  0.6016404300 #>  [8,]  0.5389641564 #>  [9,]  0.4657626216 #> [10,]  0.4565332383 #> [11,]  0.0002098787 #> [12,]  0.0111008380 #> [13,]  0.0773732599 #> [14,] -0.0554525534 #> [15,]  0.0035044520 #> [16,]  0.0676263621 #> [17,]  0.0086048502 #> [18,] -0.0757929077 #> [19,]  0.1018363964 #> [20,]  0.0181098420 #> [21,]  0.8791055942 #> [22,]  0.7729954532 #> [23,]  0.8712890378 #> [24,]  0.7651698447 #> [25,]  0.9782244593 #> [26,]  1.0606701114 #> [27,]  0.9584255709 #> [28,]  0.9380143382 #> [29,]  0.8226897838 #> [30,]  0.8703052019 #>  #> , , 17 #>  #>              [,1] #>  [1,]  0.49481665 #>  [2,]  0.50513102 #>  [3,]  0.59531825 #>  [4,]  0.50325575 #>  [5,]  0.47567669 #>  [6,]  0.60006701 #>  [7,]  0.63686306 #>  [8,]  0.57236623 #>  [9,]  0.49568403 #> [10,]  0.48838400 #> [11,]  0.02620491 #> [12,]  0.03381664 #> [13,]  0.10212531 #> [14,] -0.03493931 #> [15,]  0.02823465 #> [16,]  0.09289868 #> [17,]  0.03356143 #> [18,] -0.05323052 #> [19,]  0.12753171 #> [20,]  0.04075812 #> [21,]  0.92280225 #> [22,]  0.82511400 #> [23,]  0.91705303 #> [24,]  0.81437638 #> [25,]  1.02787594 #> [26,]  1.11223618 #> [27,]  1.01093895 #> [28,]  0.99093043 #> [29,]  0.87477013 #> [30,]  0.92492821 #>  #> , , 18 #>  #>              [,1] #>  [1,]  0.52368603 #>  [2,]  0.53759062 #>  [3,]  0.62966215 #>  [4,]  0.53586963 #>  [5,]  0.50914800 #>  [6,]  0.63679199 #>  [7,]  0.67177329 #>  [8,]  0.60554560 #>  [9,]  0.52548041 #> [10,]  0.52013491 #> [11,]  0.05240276 #> [12,]  0.05666308 #> [13,]  0.12700311 #> [14,] -0.01425990 #> [15,]  0.05314075 #> [16,]  0.11831547 #> [17,]  0.05870954 #> [18,] -0.03046830 #> [19,]  0.15333239 #> [20,]  0.06355868 #> [21,]  0.96547345 #> [22,]  0.87600081 #> [23,]  0.96174574 #> [24,]  0.86261443 #> [25,]  1.07598976 #> [26,]  1.16224876 #> [27,]  1.06202199 #> [28,]  1.04242986 #> [29,]  0.92569352 #> [30,]  0.97813691 #>  #> , , 19 #>  #>               [,1] #>  [1,]  0.552368979 #>  [2,]  0.569825971 #>  [3,]  0.663763878 #>  [4,]  0.568324232 #>  [5,]  0.542491448 #>  [6,]  0.673217318 #>  [7,]  0.706337337 #>  [8,]  0.638474431 #>  [9,]  0.555129615 #> [10,]  0.551761998 #> [11,]  0.078786155 #> [12,]  0.079628639 #> [13,]  0.151992046 #> [14,]  0.006575965 #> [15,]  0.078207703 #> [16,]  0.143860202 #> [17,]  0.084033204 #> [18,] -0.007519029 #> [19,]  0.179224111 #> [20,]  0.086498896 #> [21,]  1.007081518 #> [22,]  0.925598462 #> [23,]  1.005325383 #> [24,]  0.909840544 #> [25,]  1.122506817 #> [26,]  1.210649210 #> [27,]  1.111615629 #> [28,]  1.092452735 #> [29,]  0.975407941 #> [30,]  1.029866542 #>  #> , , 20 #>  #>             [,1] #>  [1,] 0.58084249 #>  [2,] 0.60180769 #>  [3,] 0.69759563 #>  [4,] 0.60059219 #>  [5,] 0.57567986 #>  [6,] 0.70930807 #>  [7,] 0.74052212 #>  [8,] 0.67112539 #>  [9,] 0.58460980 #> [10,] 0.58324164 #> [11,] 0.10533786 #> [12,] 0.10270182 #> [13,] 0.17707756 #> [14,] 0.02755855 #> [15,] 0.10342044 #> [16,] 0.16951639 #> [17,] 0.10951651 #> [18,] 0.01560453 #> [19,] 0.20519258 #> [20,] 0.10956616 #> [21,] 1.04758951 #> [22,] 0.97385060 #> [23,] 1.04775097 #> [24,] 0.95601192 #> [25,] 1.16736947 #> [26,] 1.25738035 #> [27,] 1.15966208 #> [28,] 1.14094043 #> [29,] 1.02386231 #> [30,] 1.08005371 #>  #> , , 21 #>  #>             [,1] #>  [1,] 0.60908396 #>  [2,] 0.63350691 #>  [3,] 0.73113011 #>  [4,] 0.63264661 #>  [5,] 0.60868643 #>  [6,] 0.74503000 #>  [7,] 0.77429527 #>  [8,] 0.70347161 #>  [9,] 0.61389945 #> [10,] 0.61455054 #> [11,] 0.13204066 #> [12,] 0.12587114 #> [13,] 0.20224516 #> [14,] 0.04867812 #> [15,] 0.12876395 #> [16,] 0.19526763 #> [17,] 0.13514355 #> [18,] 0.03888958 #> [19,] 0.23122357 #> [20,] 0.13274788 #> [21,] 1.08696118 #> [22,] 1.02070195 #> [23,] 1.08898231 #> [24,] 1.00108647 #> [25,] 1.21052164 #> [26,] 1.30238653 #> [27,] 1.20610498 #> [28,] 1.18783573 #> [29,] 1.07100649 #> [30,] 1.12863645 #>  #> , , 22 #>  #>             [,1] #>  [1,] 0.63707118 #>  [2,] 0.66489534 #>  [3,] 0.76434051 #>  [4,] 0.66446103 #>  [5,] 0.64148479 #>  [6,] 0.78034958 #>  [7,] 0.80762519 #>  [8,] 0.73548674 #>  [9,] 0.64297741 #> [10,] 0.64566576 #> [11,] 0.15887741 #> [12,] 0.14912514 #> [13,] 0.22748038 #> [14,] 0.06992496 #> [15,] 0.15422323 #> [16,] 0.22109755 #> [17,] 0.16089847 #> [18,] 0.06232337 #> [19,] 0.25730292 #> [20,] 0.15603153 #> [21,] 1.12516105 #> [22,] 1.06609843 #> [23,] 1.12898010 #> [24,] 1.04502282 #> [25,] 1.25190888 #> [26,] 1.34561373 #> [27,] 1.25088939 #> [28,] 1.23308285 #> [29,] 1.11679137 #> [30,] 1.17555429 #>  #> , , 23 #>  #>             [,1] #>  [1,] 0.66478236 #>  [2,] 0.69594519 #>  [3,] 0.79720054 #>  [4,] 0.69600949 #>  [5,] 0.67404898 #>  [6,] 0.81523401 #>  [7,] 0.84048100 #>  [8,] 0.76714491 #>  [9,] 0.67182288 #> [10,] 0.67656472 #> [11,] 0.18583099 #> [12,] 0.17245241 #> [13,] 0.25276887 #> [14,] 0.09128936 #> [15,] 0.17978336 #> [16,] 0.24698989 #> [17,] 0.18676547 #> [18,] 0.08589311 #> [19,] 0.28341654 #> [20,] 0.17940460 #> [21,] 1.16215446 #> [22,] 1.10998719 #> [23,] 1.16770591 #> [24,] 1.08778041 #> [25,] 1.29147845 #> [26,] 1.38700958 #> [27,] 1.29396192 #> [28,] 1.27662754 #> [29,] 1.16116888 #> [30,] 1.22074837 #>  #> , , 24 #>  #>            [,1] #>  [1,] 0.6921961 #>  [2,] 0.7266293 #>  [3,] 0.8296844 #>  [4,] 0.7272665 #>  [5,] 0.7063535 #>  [6,] 0.8496512 #>  [7,] 0.8728326 #>  [8,] 0.7984208 #>  [9,] 0.7004154 #> [10,] 0.7072252 #> [11,] 0.2128844 #> [12,] 0.1958416 #> [13,] 0.2780963 #> [14,] 0.1127616 #> [15,] 0.2054295 #> [16,] 0.2729285 #> [17,] 0.2127288 #> [18,] 0.1095861 #> [19,] 0.3095504 #> [20,] 0.2028546 #> [21,] 1.1979076 #> [22,] 1.1523167 #> [23,] 1.2051223 #> [24,] 1.1293195 #> [25,] 1.3291794 #> [26,] 1.4265235 #> [27,] 1.3352708 #> [28,] 1.3184172 #> [29,] 1.2040921 #> [30,] 1.2641615 #>  #> , , 25 #>  #>            [,1] #>  [1,] 0.7192916 #>  [2,] 0.7569211 #>  [3,] 0.8617670 #>  [4,] 0.7582071 #>  [5,] 0.7383733 #>  [6,] 0.8835700 #>  [7,] 0.9046508 #>  [8,] 0.8292897 #>  [9,] 0.7287349 #> [10,] 0.7376254 #> [11,] 0.2400206 #> [12,] 0.2192812 #> [13,] 0.3034485 #> [14,] 0.1343320 #> [15,] 0.2311467 #> [16,] 0.2988972 #> [17,] 0.2387728 #> [18,] 0.1333895 #> [19,] 0.3356906 #> [20,] 0.2263692 #> [21,] 1.2323873 #> [22,] 1.1930367 #> [23,] 1.2411927 #> [24,] 1.1696011 #> [25,] 1.3649625 #> [26,] 1.4641067 #> [27,] 1.3747658 #> [28,] 1.3584007 #> [29,] 1.2455152 #> [30,] 1.3057382 #>  #> , , 26 #>  #>            [,1] #>  [1,] 0.7460483 #>  [2,] 0.7867946 #>  [3,] 0.8934237 #>  [4,] 0.7888069 #>  [5,] 0.7700838 #>  [6,] 0.9169598 #>  [7,] 0.9359070 #>  [8,] 0.8597274 #>  [9,] 0.7567618 #> [10,] 0.7677440 #> [11,] 0.2672228 #> [12,] 0.2427602 #> [13,] 0.3288113 #> [14,] 0.1559910 #> [15,] 0.2569203 #> [16,] 0.3248802 #> [17,] 0.2648819 #> [18,] 0.1572908 #> [19,] 0.3618233 #> [20,] 0.2499360 #> [21,] 1.2655618 #> [22,] 1.2320985 #> [23,] 1.2758817 #> [24,] 1.2085873 #> [25,] 1.3987807 #> [26,] 1.4997122 #> [27,] 1.4123986 #> [28,] 1.3965289 #> [29,] 1.2853938 #> [30,] 1.3454249 #>  #> , , 27 #>  #>            [,1] #>  [1,] 0.7724463 #>  [2,] 0.8162244 #>  [3,] 0.9246302 #>  [4,] 0.8190419 #>  [5,] 0.8014608 #>  [6,] 0.9497909 #>  [7,] 0.9665737 #>  [8,] 0.8897102 #>  [9,] 0.7844767 #> [10,] 0.7975598 #> [11,] 0.2944741 #> [12,] 0.2662671 #> [13,] 0.3541708 #> [14,] 0.1777288 #> [15,] 0.2827356 #> [16,] 0.3508615 #> [17,] 0.2910406 #> [18,] 0.1812772 #> [19,] 0.3879347 #> [20,] 0.2735427 #> [21,] 1.2973996 #> [22,] 1.2694549 #> [23,] 1.3091548 #> [24,] 1.2462410 #> [25,] 1.4305886 #> [26,] 1.5332951 #> [27,] 1.4481225 #> [28,] 1.4327543 #> [29,] 1.3236845 #> [30,] 1.3831698 #>  #> , , 28 #>  #>            [,1] #>  [1,] 0.7984659 #>  [2,] 0.8451858 #>  [3,] 0.9553633 #>  [4,] 0.8488887 #>  [5,] 0.8324809 #>  [6,] 0.9820344 #>  [7,] 0.9966239 #>  [8,] 0.9192151 #>  [9,] 0.8118607 #> [10,] 0.8270524 #> [11,] 0.3217580 #> [12,] 0.2897908 #> [13,] 0.3795129 #> [14,] 0.1995360 #> [15,] 0.3085781 #> [16,] 0.3768255 #> [17,] 0.3172335 #> [18,] 0.2053362 #> [19,] 0.4140112 #> [20,] 0.2971771 #> [21,] 1.3278707 #> [22,] 1.3050601 #> [23,] 1.3409788 #> [24,] 1.2825260 #> [25,] 1.4603432 #> [26,] 1.5648124 #> [27,] 1.4818927 #> [28,] 1.4670313 #> [29,] 1.3603454 #> [30,] 1.4189232 #>  #> , , 29 #>  #>            [,1] #>  [1,] 0.8240882 #>  [2,] 0.8736548 #>  [3,] 0.9855999 #>  [4,] 0.8783246 #>  [5,] 0.8631210 #>  [6,] 1.0136625 #>  [7,] 1.0260317 #>  [8,] 0.9482196 #>  [9,] 0.8388954 #> [10,] 0.8562015 #> [11,] 0.3490578 #> [12,] 0.3133202 #> [13,] 0.4048239 #> [14,] 0.2214029 #> [15,] 0.3344332 #> [16,] 0.4027565 #> [17,] 0.3434453 #> [18,] 0.2294552 #> [19,] 0.4400393 #> [20,] 0.3208270 #> [21,] 1.3569459 #> [22,] 1.3388701 #> [23,] 1.3713214 #> [24,] 1.3174074 #> [25,] 1.4880034 #> [26,] 1.5942232 #> [27,] 1.5136665 #> [28,] 1.4993162 #> [29,] 1.3953360 #> [30,] 1.4526375 #>  #> , , 30 #>  #>            [,1] #>  [1,] 0.8492945 #>  [2,] 0.9016080 #>  [3,] 1.0153178 #>  [4,] 0.9073273 #>  [5,] 0.8933584 #>  [6,] 1.0446477 #>  [7,] 1.0547719 #>  [8,] 0.9767020 #>  [9,] 0.8655627 #> [10,] 0.8849876 #> [11,] 0.3763572 #> [12,] 0.3368443 #> [13,] 0.4300901 #> [14,] 0.2433200 #> [15,] 0.3602865 #> [16,] 0.4286392 #> [17,] 0.3696608 #> [18,] 0.2536217 #> [19,] 0.4660056 #> [20,] 0.3444805 #> [21,] 1.3845970 #> [22,] 1.3708425 #> [23,] 1.4001515 #> [24,] 1.3508510 #> [25,] 1.5135303 #> [26,] 1.6214888 #> [27,] 1.5434030 #> [28,] 1.5295673 #> [29,] 1.4286172 #> [30,] 1.4842669 #>  #> , , 31 #>  #>            [,1] #>  [1,] 0.8740669 #>  [2,] 0.9290225 #>  [3,] 1.0444954 #>  [4,] 0.9358750 #>  [5,] 0.9231712 #>  [6,] 1.0749639 #>  [7,] 1.0828204 #>  [8,] 1.0046409 #>  [9,] 0.8918451 #> [10,] 0.9133911 #> [11,] 0.4036398 #> [12,] 0.3603520 #> [13,] 0.4552980 #> [14,] 0.2652778 #> [15,] 0.3861238 #> [16,] 0.4544581 #> [17,] 0.3958650 #> [18,] 0.2778233 #> [19,] 0.4918968 #> [20,] 0.3681256 #> [21,] 1.4107967 #> [22,] 1.4009366 #> [23,] 1.4274395 #> [24,] 1.3828240 #> [25,] 1.5368874 #> [26,] 1.6465726 #> [27,] 1.5710633 #> [28,] 1.5577449 #> [29,] 1.4601512 #> [30,] 1.5137682 #>  #> , , 32 #>  #>            [,1] #>  [1,] 0.8983877 #>  [2,] 0.9558765 #>  [3,] 1.0731114 #>  [4,] 0.9639468 #>  [5,] 0.9525378 #>  [6,] 1.1045855 #>  [7,] 1.1101535 #>  [8,] 1.0320157 #>  [9,] 0.9177252 #> [10,] 0.9413935 #> [11,] 0.4308894 #> [12,] 0.3838325 #> [13,] 0.4804341 #> [14,] 0.2872670 #> [15,] 0.4119309 #> [16,] 0.4801984 #> [17,] 0.4220429 #> [18,] 0.3020476 #> [19,] 0.5176998 #> [20,] 0.3917503 #> [21,] 1.4355192 #> [22,] 1.4291136 #> [23,] 1.4531565 #> [24,] 1.4132944 #> [25,] 1.5580404 #> [26,] 1.6694404 #> [27,] 1.5966106 #> [28,] 1.5838116 #> [29,] 1.4899019 #> [30,] 1.5411001 #>  #> , , 33 #>  #>            [,1] #>  [1,] 0.9222398 #>  [2,] 0.9821485 #>  [3,] 1.1011455 #>  [4,] 0.9915220 #>  [5,] 0.9814372 #>  [6,] 1.1334880 #>  [7,] 1.1367488 #>  [8,] 1.0588065 #>  [9,] 0.9431864 #> [10,] 0.9689762 #> [11,] 0.4580902 #> [12,] 0.4072748 #> [13,] 0.5054851 #> [14,] 0.3092781 #> [15,] 0.4376938 #> [16,] 0.5058449 #> [17,] 0.4481798 #> [18,] 0.3262823 #> [19,] 0.5434015 #> [20,] 0.4153429 #> [21,] 1.4587395 #> [22,] 1.4553364 #> [23,] 1.4772754 #> [24,] 1.4422317 #> [25,] 1.5769572 #> [26,] 1.6900600 #> [27,] 1.6200105 #> [28,] 1.6077320 #> [29,] 1.5178349 #> [30,] 1.5662239 #>  #> , , 34 #>  #>            [,1] #>  [1,] 0.9456067 #>  [2,] 1.0078177 #>  [3,] 1.1285779 #>  [4,] 1.0185807 #>  [5,] 1.0098492 #>  [6,] 1.1616474 #>  [7,] 1.1625846 #>  [8,] 1.0849938 #>  [9,] 0.9682124 #> [10,] 0.9961214 #> [11,] 0.4852261 #> [12,] 0.4306684 #> [13,] 0.5304380 #> [14,] 0.3313018 #> [15,] 0.4633986 #> [16,] 0.5313828 #> [17,] 0.4742610 #> [18,] 0.3505153 #> [19,] 0.5689892 #> [20,] 0.4388919 #> [21,] 1.4804337 #> [22,] 1.4795700 #> [23,] 1.4997700 #> [24,] 1.4696062 #> [25,] 1.5936085 #> [26,] 1.7084018 #> [27,] 1.6412306 #> [28,] 1.6294729 #> [29,] 1.5439172 #> [30,] 1.5891031 #>  #> , , 35 #>  #>            [,1] #>  [1,] 0.9684723 #>  [2,] 1.0328643 #>  [3,] 1.1553893 #>  [4,] 1.0451035 #>  [5,] 1.0377539 #>  [6,] 1.1890411 #>  [7,] 1.1876398 #>  [8,] 1.1105590 #>  [9,] 0.9927871 #> [10,] 1.0228116 #> [11,] 0.5122817 #> [12,] 0.4540025 #> [13,] 0.5552797 #> [14,] 0.3533288 #> [15,] 0.4890315 #> [16,] 0.5567977 #> [17,] 0.5002720 #> [18,] 0.3747344 #> [19,] 0.5944500 #> [20,] 0.4623855 #> [21,] 1.5005793 #> [22,] 1.5017813 #> [23,] 1.5206158 #> [24,] 1.4953897 #> [25,] 1.6079672 #> [26,] 1.7244387 #> [27,] 1.6602407 #> [28,] 1.6490034 #> [29,] 1.5681174 #> [30,] 1.6097038 #>  #> , , 36 #>  #>            [,1] #>  [1,] 0.9908211 #>  [2,] 1.0572690 #>  [3,] 1.1815612 #>  [4,] 1.0710717 #>  [5,] 1.0651319 #>  [6,] 1.2156468 #>  [7,] 1.2118946 #>  [8,] 1.1354839 #>  [9,] 1.0168952 #> [10,] 1.0490299 #> [11,] 0.5392413 #> [12,] 0.4772667 #> [13,] 0.5799974 #> [14,] 0.3753500 #> [15,] 0.5145789 #> [16,] 0.5820751 #> [17,] 0.5261985 #> [18,] 0.3989276 #> [19,] 0.6197714 #> [20,] 0.4858123 #> [21,] 1.5191549 #> [22,] 1.5219391 #> [23,] 1.5397894 #> [24,] 1.5195553 #> [25,] 1.6200089 #> [26,] 1.7381457 #> [27,] 1.6770132 #> [28,] 1.6662951 #> [29,] 1.5904061 #> [30,] 1.6279944 #>  #> , , 37 #>  #>            [,1] #>  [1,] 1.0126379 #>  [2,] 1.0810130 #>  [3,] 1.2070756 #>  [4,] 1.0964670 #>  [5,] 1.0919645 #>  [6,] 1.2414436 #>  [7,] 1.2353296 #>  [8,] 1.1597510 #>  [9,] 1.0405217 #> [10,] 1.0747597 #> [11,] 0.5660896 #> [12,] 0.5004503 #> [13,] 0.6045784 #> [14,] 0.3973562 #> [15,] 0.5400272 #> [16,] 0.6072008 #> [17,] 0.5520264 #> [18,] 0.4230830 #> [19,] 0.6449410 #> [20,] 0.5091611 #> [21,] 1.5361401 #> [22,] 1.5400143 #> [23,] 1.5572688 #> [24,] 1.5420771 #> [25,] 1.6297118 #> [26,] 1.7495007 #> [27,] 1.6915224 #> [28,] 1.6813217 #> [29,] 1.6107553 #> [30,] 1.6439461 #>  #> , , 38 #>  #>            [,1] #>  [1,] 1.0339082 #>  [2,] 1.1040786 #>  [3,] 1.2319152 #>  [4,] 1.1212719 #>  [5,] 1.1182336 #>  [6,] 1.2664111 #>  [7,] 1.2579266 #>  [8,] 1.1833436 #>  [9,] 1.0636520 #> [10,] 1.0999849 #> [11,] 0.5928116 #> [12,] 0.5235432 #> [13,] 0.6290103 #> [14,] 0.4193384 #> [15,] 0.5653633 #> [16,] 0.6321608 #> [17,] 0.5777415 #> [18,] 0.4471887 #> [19,] 0.6699467 #> [20,] 0.5324207 #> [21,] 1.5515163 #> [22,] 1.5559802 #> [23,] 1.5730335 #> [24,] 1.5629309 #> [25,] 1.6370565 #> [26,] 1.7584839 #> [27,] 1.7037456 #> [28,] 1.6940595 #> [29,] 1.6291391 #> [30,] 1.6575325 #>  #> , , 39 #>  #>            [,1] #>  [1,] 1.0546180 #>  [2,] 1.1264485 #>  [3,] 1.2560633 #>  [4,] 1.1454693 #>  [5,] 1.1439215 #>  [6,] 1.2905298 #>  [7,] 1.2796680 #>  [8,] 1.2062454 #>  [9,] 1.0862720 #> [10,] 1.1246901 #> [11,] 0.6193924 #> [12,] 0.5465351 #> [13,] 0.6532807 #> [14,] 0.4412875 #> [15,] 0.5905739 #> [16,] 0.6569414 #> [17,] 0.6033303 #> [18,] 0.4712331 #> [19,] 0.6947762 #> [20,] 0.5555799 #> [21,] 1.5652655 #> [22,] 1.5698118 #> [23,] 1.5870646 #> [24,] 1.5820935 #> [25,] 1.6420265 #> [26,] 1.7650781 #> [27,] 1.7136620 #> [28,] 1.7044873 #> [29,] 1.6455332 #> [30,] 1.6687302 #>  #> , , 40 #>  #>            [,1] #>  [1,] 1.0747537 #>  [2,] 1.1481062 #>  [3,] 1.2795038 #>  [4,] 1.1690427 #>  [5,] 1.1690113 #>  [6,] 1.3137811 #>  [7,] 1.3005370 #>  [8,] 1.2284408 #>  [9,] 1.1083680 #> [10,] 1.1488601 #> [11,] 0.6458171 #> [12,] 0.5694158 #> [13,] 0.6773774 #> [14,] 0.4631946 #> [15,] 0.6156460 #> [16,] 0.6815288 #> [17,] 0.6287789 #> [18,] 0.4952045 #> [19,] 0.7194177 #> [20,] 0.5786278 #> [21,] 1.5773715 #> [22,] 1.5814867 #> [23,] 1.5993445 #> [24,] 1.5995432 #> [25,] 1.6446081 #> [26,] 1.7692690 #> [27,] 1.7212538 #> [28,] 1.7125864 #> [29,] 1.6599153 #> [30,] 1.6775181 #>  #> , , 41 #>  #>            [,1] #>  [1,] 1.0943023 #>  [2,] 1.1690358 #>  [3,] 1.3022213 #>  [4,] 1.1919764 #>  [5,] 1.1934864 #>  [6,] 1.3361474 #>  [7,] 1.3205177 #>  [8,] 1.2499149 #>  [9,] 1.1299268 #> [10,] 1.1724802 #> [11,] 0.6720712 #> [12,] 0.5921753 #> [13,] 0.7012886 #> [14,] 0.4850510 #> [15,] 0.6405669 #> [16,] 0.7059098 #> [17,] 0.6540740 #> [18,] 0.5190915 #> [19,] 0.7438594 #> [20,] 0.6015537 #> [21,] 1.5878193 #> [22,] 1.5909846 #> [23,] 1.6098570 #> [24,] 1.6152599 #> [25,] 1.6447902 #> [26,] 1.7710447 #> [27,] 1.7265053 #> [28,] 1.7183406 #> [29,] 1.6722649 #> [30,] 1.6838782 #>  #> , , 42 #>  #>            [,1] #>  [1,] 1.1132512 #>  [2,] 1.1892223 #>  [3,] 1.3242010 #>  [4,] 1.2142549 #>  [5,] 1.2173309 #>  [6,] 1.3576116 #>  [7,] 1.3395949 #>  [8,] 1.2706534 #>  [9,] 1.1509356 #> [10,] 1.1955364 #> [11,] 0.6981406 #> [12,] 0.6148038 #> [13,] 0.7250024 #> [14,] 0.5068478 #> [15,] 0.6653238 #> [16,] 0.7300713 #> [17,] 0.6792023 #> [18,] 0.5428828 #> [19,] 0.7680899 #> [20,] 0.6243469 #> [21,] 1.5965952 #> [22,] 1.5982876 #> [23,] 1.6185878 #> [24,] 1.6292246 #> [25,] 1.6425646 #> [26,] 1.7703962 #> [27,] 1.7294037 #> [28,] 1.7217363 #> [29,] 1.6825636 #> [30,] 1.6877953 #>  #> , , 43 #>  #>            [,1] #>  [1,] 1.1315884 #>  [2,] 1.2086511 #>  [3,] 1.3454285 #>  [4,] 1.2358635 #>  [5,] 1.2405295 #>  [6,] 1.3781576 #>  [7,] 1.3577541 #>  [8,] 1.2906425 #>  [9,] 1.1713821 #> [10,] 1.2180148 #> [11,] 0.7240111 #> [12,] 0.6372915 #> [13,] 0.7485072 #> [14,] 0.5285763 #> [15,] 0.6899044 #> [16,] 0.7540003 #> [17,] 0.7041508 #> [18,] 0.5665670 #> [19,] 0.7920978 #> [20,] 0.6469968 #> [21,] 1.6036868 #> [22,] 1.6033800 #> [23,] 1.6255240 #> [24,] 1.6414202 #> [25,] 1.6379261 #> [26,] 1.7673170 #> [27,] 1.7299387 #> [28,] 1.7227626 #> [29,] 1.6907948 #> [30,] 1.6892569 #>  #> , , 44 #>  #>            [,1] #>  [1,] 1.1493022 #>  [2,] 1.2273084 #>  [3,] 1.3658903 #>  [4,] 1.2567881 #>  [5,] 1.2630674 #>  [6,] 1.3977701 #>  [7,] 1.3749817 #>  [8,] 1.3098692 #>  [9,] 1.1912543 #> [10,] 1.2399022 #> [11,] 0.7496689 #> [12,] 0.6596288 #> [13,] 0.7717917 #> [14,] 0.5502280 #> [15,] 0.7142964 #> [16,] 0.7776843 #> [17,] 0.7289066 #> [18,] 0.5901332 #> [19,] 0.8158719 #> [20,] 0.6694931 #> [21,] 1.6090832 #> [22,] 1.6062485 #> [23,] 1.6306540 #> [24,] 1.6518306 #> [25,] 1.6308721 #> [26,] 1.7618037 #> [27,] 1.7281026 #> [28,] 1.7214114 #> [29,] 1.6969440 #> [30,] 1.6882536 #>  #> , , 45 #>  #>            [,1] #>  [1,] 1.1663815 #>  [2,] 1.2451810 #>  [3,] 1.3855733 #>  [4,] 1.2770150 #>  [5,] 1.2849303 #>  [6,] 1.4164345 #>  [7,] 1.3912648 #>  [8,] 1.3283209 #>  [9,] 1.2105408 #> [10,] 1.2611859 #> [11,] 0.7751003 #> [12,] 0.6818060 #> [13,] 0.7948447 #> [14,] 0.5717945 #> [15,] 0.7384876 #> [16,] 0.8011106 #> [17,] 0.7534572 #> [18,] 0.6135703 #> [19,] 0.8394012 #> [20,] 0.6918257 #> [21,] 1.6127749 #> [22,] 1.6068825 #> [23,] 1.6339684 #> [24,] 1.6604415 #> [25,] 1.6214031 #> [26,] 1.7538555 #> [27,] 1.7238906 #> [28,] 1.7176771 #> [29,] 1.7009988 #> [30,] 1.6847788 #>  #> , , 46 #>  #>            [,1] #>  [1,] 1.1828158 #>  [2,] 1.2622564 #>  [3,] 1.4044650 #>  [4,] 1.2965310 #>  [5,] 1.3061044 #>  [6,] 1.4341371 #>  [7,] 1.4065909 #>  [8,] 1.3459858 #>  [9,] 1.2292303 #> [10,] 1.2818535 #> [11,] 0.8002921 #> [12,] 0.7038140 #> [13,] 0.8176551 #> [14,] 0.5932672 #> [15,] 0.7624663 #> [16,] 0.8242673 #> [17,] 0.7777900 #> [18,] 0.6368675 #> [19,] 0.8626750 #> [20,] 0.7139843 #> [21,] 1.6147540 #> [22,] 1.6052735 #> [23,] 1.6354588 #> [24,] 1.6672403 #> [25,] 1.6095226 #> [26,] 1.7434746 #> [27,] 1.7173004 #> [28,] 1.7115569 #> [29,] 1.7029487 #> [30,] 1.6788290 #>  #> , , 47 #>  #>            [,1] #>  [1,] 1.1985947 #>  [2,] 1.2785227 #>  [3,] 1.4225536 #>  [4,] 1.3153235 #>  [5,] 1.3265765 #>  [6,] 1.4508647 #>  [7,] 1.4209487 #>  [8,] 1.3628525 #>  [9,] 1.2473124 #> [10,] 1.3018931 #> [11,] 0.8252310 #> [12,] 0.7256433 #> [13,] 0.8402122 #> [14,] 0.6146379 #> [15,] 0.7862207 #> [16,] 0.8471422 #> [17,] 0.8018930 #> [18,] 0.6600143 #> [19,] 0.8856826 #> [20,] 0.7359592 #> [21,] 1.6150136 #> [22,] 1.6014157 #> [23,] 1.6351190 #> [24,] 1.6722156 #> [25,] 1.5952371 #> [26,] 1.7306660 #> [27,] 1.7083326 #> [28,] 1.7030510 #> [29,] 1.7027855 #> [30,] 1.6704037 #>  #> , , 48 #>  #>            [,1] #>  [1,] 1.2137087 #>  [2,] 1.2939686 #>  [3,] 1.4398276 #>  [4,] 1.3333805 #>  [5,] 1.3463340 #>  [6,] 1.4666051 #>  [7,] 1.4343270 #>  [8,] 1.3789102 #>  [9,] 1.2647767 #> [10,] 1.3212932 #> [11,] 0.8499041 #> [12,] 0.7472850 #> [13,] 0.8625054 #> [14,] 0.6358984 #> [15,] 0.8097394 #> [16,] 0.8697239 #> [17,] 0.8257541 #> [18,] 0.6829999 #> [19,] 0.9084137 #> [20,] 0.7577405 #> [21,] 1.6135487 #> [22,] 1.5953058 #> [23,] 1.6329441 #> [24,] 1.6753579 #> [25,] 1.5785560 #> [26,] 1.7154375 #> [27,] 1.6969905 #> [28,] 1.6921621 #> [29,] 1.7005030 #> [30,] 1.6595055 #>  #> , , 49 #>  #>            [,1] #>  [1,] 1.2281482 #>  [2,] 1.3085835 #>  [3,] 1.4562763 #>  [4,] 1.3506903 #>  [5,] 1.3653648 #>  [6,] 1.4813466 #>  [7,] 1.4467156 #>  [8,] 1.3941489 #>  [9,] 1.2816134 #> [10,] 1.3400428 #> [11,] 0.8742990 #> [12,] 0.7687300 #> [13,] 0.8845243 #> [14,] 0.6570406 #> [15,] 0.8330111 #> [16,] 0.8920007 #> [17,] 0.8493615 #> [18,] 0.7058142 #> [19,] 0.9308582 #> [20,] 0.7793188 #> [21,] 1.6103557 #> [22,] 1.5869430 #> [23,] 1.6289311 #> [24,] 1.6766591 #> [25,] 1.5594917 #> [26,] 1.6978000 #> [27,] 1.6832802 #> [28,] 1.6788959 #> [29,] 1.6960971 #> [30,] 1.6461400 #>  #> , , 50 #>  #>            [,1] #>  [1,] 1.2419046 #>  [2,] 1.3223572 #>  [3,] 1.4718894 #>  [4,] 1.3672418 #>  [5,] 1.3836570 #>  [6,] 1.4950782 #>  [7,] 1.4581047 #>  [8,] 1.4085587 #>  [9,] 1.2978130 #> [10,] 1.3581313 #> [11,] 0.8984030 #> [12,] 0.7899695 #> [13,] 0.9062587 #> [14,] 0.6780565 #> [15,] 0.8560247 #> [16,] 0.9139615 #> [17,] 0.8727039 #> [18,] 0.7284468 #> [19,] 0.9530060 #> [20,] 0.8006845 #> [21,] 1.6054324 #> [22,] 1.5763292 #> [23,] 1.6230786 #> [24,] 1.6761129 #> [25,] 1.5380599 #> [26,] 1.6777671 #> [27,] 1.6672108 #> [28,] 1.6632609 #> [29,] 1.6895661 #> [30,] 1.6303159 #>  #> , , 51 #>  #>            [,1] #>  [1,] 1.2549693 #>  [2,] 1.3352803 #>  [3,] 1.4866572 #>  [4,] 1.3830244 #>  [5,] 1.4011997 #>  [6,] 1.5077896 #>  [7,] 1.4684853 #>  [8,] 1.4221307 #>  [9,] 1.3133665 #> [10,] 1.3755485 #> [11,] 0.9222042 #> [12,] 0.8109949 #> [13,] 0.9276988 #> [14,] 0.6989382 #> [15,] 0.8787694 #> [16,] 0.9355954 #> [17,] 0.8957697 #> [18,] 0.7508877 #> [19,] 0.9748474 #> [20,] 0.8218285 #> [21,] 1.5987782 #> [22,] 1.5634689 #> [23,] 1.6153871 #> [24,] 1.6737145 #> [25,] 1.5142791 #> [26,] 1.6553556 #> [27,] 1.6487940 #> [28,] 1.6452686 #> [29,] 1.6809104 #> [30,] 1.6120452 #>  #> , , 52 #>  #>            [,1] #>  [1,] 1.2673343 #>  [2,] 1.3473437 #>  [3,] 1.5005705 #>  [4,] 1.3980278 #>  [5,] 1.4179819 #>  [6,] 1.5194712 #>  [7,] 1.4778486 #>  [8,] 1.4348562 #>  [9,] 1.3282651 #> [10,] 1.3922846 #> [11,] 0.9456907 #> [12,] 0.8317977 #> [13,] 0.9488347 #> [14,] 0.7196779 #> [15,] 0.9012346 #> [16,] 0.9568917 #> [17,] 0.9185481 #> [18,] 0.7731271 #> [19,] 0.9963728 #> [20,] 0.8427417 #> [21,] 1.5903940 #> [22,] 1.5483692 #> [23,] 1.6058586 #> [24,] 1.6694609 #> [25,] 1.4881710 #> [26,] 1.6305851 #> [27,] 1.6280444 #> [28,] 1.6249332 #> [29,] 1.6701325 #> [30,] 1.5913429 #>  #> , , 53 #>  #>            [,1] #>  [1,] 1.2789919 #>  [2,] 1.3585391 #>  [3,] 1.5136203 #>  [4,] 1.4122422 #>  [5,] 1.4339936 #>  [6,] 1.5301137 #>  [7,] 1.4861866 #>  [8,] 1.4467272 #>  [9,] 1.3425005 #> [10,] 1.4083301 #> [11,] 0.9688508 #> [12,] 0.8523694 #> [13,] 0.9696571 #> [14,] 0.7402678 #> [15,] 0.9234098 #> [16,] 0.9778400 #> [17,] 0.9410281 #> [18,] 0.7951551 #> [19,] 1.0175730 #> [20,] 0.8634152 #> [21,] 1.5802822 #> [22,] 1.5310397 #> [23,] 1.5944971 #> [24,] 1.6633509 #> [25,] 1.4597605 #> [26,] 1.6034782 #> [27,] 1.6049797 #> [28,] 1.6022719 #> [29,] 1.6572372 #> [30,] 1.5682272 #>  #> , , 54 #>  #>            [,1] #>  [1,] 1.2899347 #>  [2,] 1.3688585 #>  [3,] 1.5257985 #>  [4,] 1.4256583 #>  [5,] 1.4492250 #>  [6,] 1.5397088 #>  [7,] 1.4934916 #>  [8,] 1.4577359 #>  [9,] 1.3560648 #> [10,] 1.4236760 #> [11,] 0.9916732 #> [12,] 0.8727018 #> [13,] 0.9901565 #> [14,] 0.7607006 #> [15,] 0.9452849 #> [16,] 0.9984301 #> [17,] 0.9631992 #> [18,] 0.8169622 #> [19,] 1.0384387 #> [20,] 0.8838402 #> [21,] 1.5684469 #> [22,] 1.5114931 #> [23,] 1.5813082 #> [24,] 1.6553846 #> [25,] 1.4290755 #> [26,] 1.5740604 #> [27,] 1.5796202 #> [28,] 1.5773048 #> [29,] 1.6422318 #> [30,] 1.5427196 #>  #> , , 55 #>  #>            [,1] #>  [1,] 1.3001560 #>  [2,] 1.3782944 #>  [3,] 1.5370973 #>  [4,] 1.4382671 #>  [5,] 1.4636666 #>  [6,] 1.5482484 #>  [7,] 1.4997565 #>  [8,] 1.4678754 #>  [9,] 1.3689502 #> [10,] 1.4383137 #> [11,] 1.0141468 #> [12,] 0.8927869 #> [13,] 1.0103239 #> [14,] 0.7809686 #> [15,] 0.9668499 #> [16,] 1.0186522 #> [17,] 0.9850511 #> [18,] 0.8385391 #> [19,] 1.0589611 #> [20,] 0.9040082 #> [21,] 1.5548937 #> [22,] 1.4897444 #> [23,] 1.5662993 #> [24,] 1.6455643 #> [25,] 1.3961470 #> [26,] 1.5423603 #> [27,] 1.5519892 #> [28,] 1.5500550 #> [29,] 1.6251255 #> [30,] 1.5148445 #>  #> , , 56 #>  #>            [,1] #>  [1,] 1.3096490 #>  [2,] 1.3868399 #>  [3,] 1.5475091 #>  [4,] 1.4500599 #>  [5,] 1.4773095 #>  [6,] 1.5557251 #>  [7,] 1.5049745 #>  [8,] 1.4771389 #>  [9,] 1.3811495 #> [10,] 1.4522349 #> [11,] 1.0362608 #> [12,] 0.9126168 #> [13,] 1.0301504 #> [14,] 0.8010646 #> [15,] 0.9880950 #> [16,] 1.0384966 #> [17,] 1.0065735 #> [18,] 0.8598765 #> [19,] 1.0791315 #> [20,] 0.9239108 #> [21,] 1.5396297 #> [22,] 1.4658114 #> [23,] 1.5494797 #> [24,] 1.6338938 #> [25,] 1.3610090 #> [26,] 1.5084094 #> [27,] 1.5221131 #> [28,] 1.5205483 #> [29,] 1.6059301 #> [30,] 1.4846299 #>  #> , , 57 #>  #>            [,1] #>  [1,] 1.3184076 #>  [2,] 1.3944886 #>  [3,] 1.5570271 #>  [4,] 1.4610286 #>  [5,] 1.4901453 #>  [6,] 1.5621318 #>  [7,] 1.5091392 #>  [8,] 1.4855202 #>  [9,] 1.3926557 #> [10,] 1.4654316 #> [11,] 1.0580047 #> [12,] 0.9321837 #> [13,] 1.0496275 #> [14,] 0.8209814 #> [15,] 1.0090108 #> [16,] 1.0579539 #> [17,] 1.0277566 #> [18,] 0.8809654 #> [19,] 1.0989415 #> [20,] 0.9435398 #> [21,] 1.5226638 #> [22,] 1.4397148 #> [23,] 1.5308605 #> [24,] 1.6203786 #> [25,] 1.3236989 #> [26,] 1.4722422 #> [27,] 1.4900208 #> [28,] 1.4888138 #> [29,] 1.5846595 #> [30,] 1.4521067 #>  #> , , 58 #>  #>            [,1] #>  [1,] 1.3264258 #>  [2,] 1.4012343 #>  [3,] 1.5656446 #>  [4,] 1.4711651 #>  [5,] 1.5021657 #>  [6,] 1.5674620 #>  [7,] 1.5122448 #>  [8,] 1.4930134 #>  [9,] 1.4034622 #> [10,] 1.4778961 #> [11,] 1.0793681 #> [12,] 0.9514800 #> [13,] 1.0687466 #> [14,] 0.8407117 #> [15,] 1.0295879 #> [16,] 1.0770151 #> [17,] 1.0485908 #> [18,] 0.9017968 #> [19,] 1.1183826 #> [20,] 0.9628872 #> [21,] 1.5040063 #> [22,] 1.4114779 #> [23,] 1.5104545 #> [24,] 1.6050261 #> [25,] 1.2842569 #> [26,] 1.4338962 #> [27,] 1.4557443 #> [28,] 1.4548832 #> [29,] 1.5613300 #> [30,] 1.4173091 #>  #> , , 59 #>  #>            [,1] #>  [1,] 1.3336979 #>  [2,] 1.4070714 #>  [3,] 1.5733555 #>  [4,] 1.4804619 #>  [5,] 1.5133631 #>  [6,] 1.5717097 #>  [7,] 1.5142854 #>  [8,] 1.4996132 #>  [9,] 1.4135624 #> [10,] 1.4896212 #> [11,] 1.1003411 #> [12,] 0.9704983 #> [13,] 1.0874997 #> [14,] 0.8602487 #> [15,] 1.0498173 #> [16,] 1.0956712 #> [17,] 1.0690666 #> [18,] 0.9223621 #> [19,] 1.1374470 #> [20,] 0.9819451 #> [21,] 1.4836692 #> [22,] 1.3811268 #> [23,] 1.4882763 #> [24,] 1.5878454 #> [25,] 1.2427264 #> [26,] 1.3934117 #> [27,] 1.4193187 #> [28,] 1.4187912 #> [29,] 1.5359603 #> [30,] 1.3802745 #>  #> , , 60 #>  #>            [,1] #>  [1,] 1.3402187 #>  [2,] 1.4119946 #>  [3,] 1.5801537 #>  [4,] 1.4889118 #>  [5,] 1.5237299 #>  [6,] 1.5748690 #>  [7,] 1.5152558 #>  [8,] 1.5053145 #>  [9,] 1.4229504 #> [10,] 1.5005998 #> [11,] 1.1209139 #> [12,] 0.9892312 #> [13,] 1.1058788 #> [14,] 0.8795855 #> [15,] 1.0696901 #> [16,] 1.1139137 #> [17,] 1.0891750 #> [18,] 0.9426529 #> [19,] 1.1561268 #> [20,] 1.0007060 #> [21,] 1.4616660 #> [22,] 1.3486902 #> [23,] 1.4643426 #> [24,] 1.5688474 #> [25,] 1.1991540 #> [26,] 1.3508321 #> [27,] 1.3807816 #> [28,] 1.3805755 #> [29,] 1.5085712 #> [30,] 1.3410436 #>  #> , , 61 #>  #>            [,1] #>  [1,] 1.3459830 #>  [2,] 1.4159990 #>  [3,] 1.5860340 #>  [4,] 1.4965075 #>  [5,] 1.5332591 #>  [6,] 1.5769346 #>  [7,] 1.5151508 #>  [8,] 1.5101127 #>  [9,] 1.4316202 #> [10,] 1.5108252 #> [11,] 1.1410769 #> [12,] 1.0076718 #> [13,] 1.1238760 #> [14,] 0.8987153 #> [15,] 1.0891977 #> [16,] 1.1317342 #> [17,] 1.1089069 #> [18,] 0.9626606 #> [19,] 1.1744144 #> [20,] 1.0191622 #> [21,] 1.4380121 #> [22,] 1.3141997 #> [23,] 1.4386715 #> [24,] 1.5480448 #> [25,] 1.1535891 #> [26,] 1.3062036 #> [27,] 1.3401737 #> [28,] 1.3402767 #> [29,] 1.4791860 #> [30,] 1.2996602 #>  #> , , 62 #>  #>            [,1] #>  [1,] 1.3509860 #>  [2,] 1.4190799 #>  [3,] 1.5909909 #>  [4,] 1.5032424 #>  [5,] 1.5419439 #>  [6,] 1.5779016 #>  [7,] 1.5139657 #>  [8,] 1.5140033 #>  [9,] 1.4395663 #> [10,] 1.5202910 #> [11,] 1.1608211 #> [12,] 1.0258131 #> [13,] 1.1414839 #> [14,] 0.9176315 #> [15,] 1.1083317 #> [16,] 1.1491246 #> [17,] 1.1282537 #> [18,] 0.9823772 #> [19,] 1.1923025 #> [20,] 1.0373065 #> [21,] 1.4127243 #> [22,] 1.2776897 #> [23,] 1.4112833 #> [24,] 1.5254521 #> [25,] 1.1060843 #> [26,] 1.2595755 #> [27,] 1.2975385 #> [28,] 1.2979383 #> [29,] 1.4478304 #> [30,] 1.2561710 #>  #> , , 63 #>  #>            [,1] #>  [1,] 1.3552232 #>  [2,] 1.4212333 #>  [3,] 1.5950197 #>  [4,] 1.5091098 #>  [5,] 1.5497779 #>  [6,] 1.5777651 #>  [7,] 1.5116957 #>  [8,] 1.5169824 #>  [9,] 1.4467834 #> [10,] 1.5289909 #> [11,] 1.1801374 #> [12,] 1.0436482 #> [13,] 1.1586951 #> [14,] 0.9363275 #> [15,] 1.1270840 #> [16,] 1.1660772 #> [17,] 1.1472070 #> [18,] 1.0017948 #> [19,] 1.2097837 #> [20,] 1.0551318 #> [21,] 1.3858210 #> [22,] 1.2391970 #> [23,] 1.3821998 #> [24,] 1.5010855 #> [25,] 1.0566951 #> [26,] 1.2109996 #> [27,] 1.2529224 #> [28,] 1.2536065 #> [29,] 1.4145323 #> [30,] 1.2106264 #>  #> , , 64 #>  #>            [,1] #>  [1,] 1.3586900 #>  [2,] 1.4224550 #>  [3,] 1.5981158 #>  [4,] 1.5141035 #>  [5,] 1.5567548 #>  [6,] 1.5765208 #>  [7,] 1.5083365 #>  [8,] 1.5190464 #>  [9,] 1.4532662 #> [10,] 1.5369191 #> [11,] 1.1990171 #> [12,] 1.0611705 #> [13,] 1.1755027 #> [14,] 0.9547971 #> [15,] 1.1454466 #> [16,] 1.1825843 #> [17,] 1.1657585 #> [18,] 1.0209055 #> [19,] 1.2268512 #> [20,] 1.0726311 #> [21,] 1.3573222 #> [22,] 1.1987616 #> [23,] 1.3514450 #> [24,] 1.4749633 #> [25,] 1.0054801 #> [26,] 1.1605309 #> [27,] 1.2063746 #> [28,] 1.2073306 #> [29,] 1.3793219 #> [30,] 1.1630793 #>  #> , , 65 #>  #>            [,1] #>  [1,] 1.3613824 #>  [2,] 1.4227414 #>  [3,] 1.6002747 #>  [4,] 1.5182173 #>  [5,] 1.5628688 #>  [6,] 1.5741645 #>  [7,] 1.5038839 #>  [8,] 1.5201916 #>  [9,] 1.4590100 #> [10,] 1.5440697 #> [11,] 1.2174518 #> [12,] 1.0783737 #> [13,] 1.1918996 #> [14,] 0.9730340 #> [15,] 1.1634118 #> [16,] 1.1986387 #> [17,] 1.1839002 #> [18,] 1.0397017 #> [19,] 1.2434983 #> [20,] 1.0897977 #> [21,] 1.3272498 #> [22,] 1.1564258 #> [23,] 1.3190444 #> [24,] 1.4471052 #> [25,] 0.9525007 #> [26,] 1.1082271 #> [27,] 1.1579469 #> [28,] 1.1591625 #> [29,] 1.3422317 #> [30,] 1.1135862 #>  #> , , 66 #>  #>            [,1] #>  [1,] 1.3632964 #>  [2,] 1.4220891 #>  [3,] 1.6014923 #>  [4,] 1.5214451 #>  [5,] 1.5681141 #>  [6,] 1.5706921 #>  [7,] 1.4983336 #>  [8,] 1.5204151 #>  [9,] 1.4640100 #> [10,] 1.5504373 #> [11,] 1.2354333 #> [12,] 1.0952513 #> [13,] 1.2078792 #> [14,] 0.9910320 #> [15,] 1.1809721 #> [16,] 1.2142331 #> [17,] 1.2016244 #> [18,] 1.0581760 #> [19,] 1.2597184 #> [20,] 1.1066249 #> [21,] 1.2956269 #> [22,] 1.1122348 #> [23,] 1.2850254 #> [24,] 1.4175330 #> [25,] 0.8978213 #> [26,] 1.0541486 #> [27,] 1.1076941 #> [28,] 1.1091571 #> [29,] 1.3032968 #> [30,] 1.0622064 #>  #> , , 67 #>  #>            [,1] #>  [1,] 1.3644282 #>  [2,] 1.4204948 #>  [3,] 1.6017648 #>  [4,] 1.5237812 #>  [5,] 1.5724853 #>  [6,] 1.5661000 #>  [7,] 1.4916817 #>  [8,] 1.5197140 #>  [9,] 1.4682616 #> [10,] 1.5560166 #> [11,] 1.2529537 #> [12,] 1.1117973 #> [13,] 1.2234352 #> [14,] 1.0087850 #> [15,] 1.1981203 #> [16,] 1.2293608 #> [17,] 1.2189236 #> [18,] 1.0763211 #> [19,] 1.2755052 #> [20,] 1.1231064 #> [21,] 1.2624787 #> [22,] 1.0662366 #> [23,] 1.2494172 #> [24,] 1.3862702 #> [25,] 0.8415092 #> [26,] 0.9983587 #> [27,] 1.0556737 #> [28,] 1.0573719 #> [29,] 1.2625542 #> [30,] 1.0090022 #>  #> , , 68 #>  #>            [,1] #>  [1,] 1.3647740 #>  [2,] 1.4179557 #>  [3,] 1.6010885 #>  [4,] 1.5252197 #>  [5,] 1.5759770 #>  [6,] 1.5603846 #>  [7,] 1.4839243 #>  [8,] 1.5180854 #>  [9,] 1.4717606 #> [10,] 1.5608024 #> [11,] 1.2700053 #> [12,] 1.1280057 #> [13,] 1.2385611 #> [14,] 1.0262874 #> [15,] 1.2148493 #> [16,] 1.2440151 #> [17,] 1.2357904 #> [18,] 1.0941301 #> [19,] 1.2908526 #> [20,] 1.1392358 #> [21,] 1.2278315 #> [22,] 1.0184816 #> [23,] 1.2122510 #> [24,] 1.3533421 #> [25,] 0.7836342 #> [26,] 0.9409231 #> [27,] 1.0019458 #> [28,] 1.0038672 #> [29,] 1.2200435 #> [30,] 0.9540390 #>  #> , , 69 #>  #>            [,1] #>  [1,] 1.3643305 #>  [2,] 1.4144687 #>  [3,] 1.5994598 #>  [4,] 1.5257552 #>  [5,] 1.5785843 #>  [6,] 1.5535424 #>  [7,] 1.4750577 #>  [8,] 1.5155270 #>  [9,] 1.4745026 #> [10,] 1.5647898 #> [11,] 1.2865807 #> [12,] 1.1438708 #> [13,] 1.2532511 #> [14,] 1.0435332 #> [15,] 1.2311523 #> [16,] 1.2581898 #> [17,] 1.2522179 #> [18,] 1.1115959 #> [19,] 1.3057546 #> [20,] 1.1550072 #> [21,] 1.1917137 #> [22,] 0.9690230 #> [23,] 1.1735595 #> [24,] 1.3187759 #> [25,] 0.7242692 #> [26,] 0.8819105 #> [27,] 0.9465731 #> [28,] 0.9487061 #> [29,] 1.1758064 #> [30,] 0.8973851 #>  #> , , 70 #>  #>            [,1] #>  [1,] 1.3630941 #>  [2,] 1.4100314 #>  [3,] 1.5968754 #>  [4,] 1.5253820 #>  [5,] 1.5803022 #>  [6,] 1.5455702 #>  [7,] 1.4650781 #>  [8,] 1.5120365 #>  [9,] 1.4764836 #> [10,] 1.5679740 #> [11,] 1.3026727 #> [12,] 1.1593868 #> [13,] 1.2674992 #> [14,] 1.0605168 #> [15,] 1.2470226 #> [16,] 1.2718786 #> [17,] 1.2681990 #> [18,] 1.1287121 #> [19,] 1.3202057 #> [20,] 1.1704147 #> [21,] 1.1541548 #> [22,] 0.9179165 #> [23,] 1.1333774 #> [24,] 1.2826004 #> [25,] 0.6634896 #> [26,] 0.8213919 #> [27,] 0.8896212 #> [28,] 0.8919540 #> [29,] 1.1298870 #> [30,] 0.8391115 #>  #> , , 71 #>  #>            [,1] #>  [1,] 1.3610616 #>  [2,] 1.4046413 #>  [3,] 1.5933321 #>  [4,] 1.5240947 #>  [5,] 1.5811259 #>  [6,] 1.5364647 #>  [7,] 1.4539819 #>  [8,] 1.5076117 #>  [9,] 1.4776998 #> [10,] 1.5703502 #> [11,] 1.3182744 #> [12,] 1.1745483 #> [13,] 1.2812999 #> [14,] 1.0772328 #> [15,] 1.2624540 #> [16,] 1.2850756 #> [17,] 1.2837273 #> [18,] 1.1454719 #> [19,] 1.3342003 #> [20,] 1.1854524 #> [21,] 1.1151864 #> [22,] 0.8652205 #> [23,] 1.0917409 #> [24,] 1.2448464 #> [25,] 0.6013735 #> [26,] 0.7594410 #> [27,] 0.8311580 #> [28,] 0.8336793 #> [29,] 1.0823315 #> [30,] 0.7792924 #>  #> , , 72 #>  #>            [,1] #>  [1,] 1.3582297 #>  [2,] 1.3982959 #>  [3,] 1.5888268 #>  [4,] 1.5218880 #>  [5,] 1.5810508 #>  [6,] 1.5262230 #>  [7,] 1.4417654 #>  [8,] 1.5022509 #>  [9,] 1.4781472 #> [10,] 1.5719139 #> [11,] 1.3333790 #> [12,] 1.1893501 #> [13,] 1.2946477 #> [14,] 1.0936758 #> [15,] 1.2774401 #> [16,] 1.2977750 #> [17,] 1.2987962 #> [18,] 1.1618692 #> [19,] 1.3477331 #> [20,] 1.2001150 #> [21,] 1.0748412 #> [22,] 0.8109959 #> [23,] 1.0486882 #> [24,] 1.2055463 #> [25,] 0.5380016 #> [26,] 0.6961339 #> [27,] 0.7712540 #> [28,] 0.7739528 #> [29,] 1.0331883 #> [30,] 0.7180044 #>  #> , , 73 #>  #>            [,1] #>  [1,] 1.3545955 #>  [2,] 1.3909931 #>  [3,] 1.5833565 #>  [4,] 1.5187565 #>  [5,] 1.5800724 #>  [6,] 1.5148420 #>  [7,] 1.4284252 #>  [8,] 1.4959521 #>  [9,] 1.4778221 #> [10,] 1.5726607 #> [11,] 1.3479802 #> [12,] 1.2037868 #> [13,] 1.3075373 #> [14,] 1.1098404 #> [15,] 1.2919750 #> [16,] 1.3099716 #> [17,] 1.3133996 #> [18,] 1.1778977 #> [19,] 1.3607991 #> [20,] 1.2143969 #> [21,] 1.0331538 #> [22,] 0.7553061 #> [23,] 1.0042591 #> [24,] 1.1647343 #> [25,] 0.4734569 #> [26,] 0.6315491 #> [27,] 0.7099819 #> [28,] 0.7128475 #> [29,] 0.9825081 #> [30,] 0.6553269 #>  #> , , 74 #>  #>            [,1] #>  [1,] 1.3501559 #>  [2,] 1.3827308 #>  [3,] 1.5769185 #>  [4,] 1.5146948 #>  [5,] 1.5781863 #>  [6,] 1.5023188 #>  [7,] 1.4139578 #>  [8,] 1.4887136 #>  [9,] 1.4767210 #> [10,] 1.5725862 #> [11,] 1.3620716 #> [12,] 1.2178537 #> [13,] 1.3199638 #> [14,] 1.1257216 #> [15,] 1.3060530 #> [16,] 1.3216598 #> [17,] 1.3275314 #> [18,] 1.1935515 #> [19,] 1.3733932 #> [20,] 1.2282930 #> [21,] 0.9901602 #> [22,] 0.6982169 #> [23,] 0.9584952 #> [24,] 1.1224464 #> [25,] 0.4078249 #> [26,] 0.5657675 #> [27,] 0.6474173 #> [28,] 0.6504392 #> [29,] 0.9303437 #> [30,] 0.5913419 #>  #> , , 75 #>  #>            [,1] #>  [1,] 1.3449078 #>  [2,] 1.3735069 #>  [3,] 1.5695100 #>  [4,] 1.5096978 #>  [5,] 1.5753880 #>  [6,] 1.4886506 #>  [7,] 1.3983596 #>  [8,] 1.4805341 #>  [9,] 1.4748402 #> [10,] 1.5716862 #> [11,] 1.3756472 #> [12,] 1.2315457 #> [13,] 1.3319222 #> [14,] 1.1413144 #> [15,] 1.3196685 #> [16,] 1.3328348 #> [17,] 1.3411858 #> [18,] 1.2088248 #> [19,] 1.3855109 #> [20,] 1.2417981 #> [21,] 0.9458980 #> [22,] 0.6397965 #> [23,] 0.9114397 #> [24,] 1.0787204 #> [25,] 0.3411936 #> [26,] 0.4988721 #> [27,] 0.5836377 #> [28,] 0.5868059 #> [29,] 0.8767501 #> [30,] 0.5261342 #>  #> , , 76 #>  #>            [,1] #>  [1,] 1.3388484 #>  [2,] 1.3633196 #>  [3,] 1.5611283 #>  [4,] 1.5037600 #>  [5,] 1.5716735 #>  [6,] 1.4738347 #>  [7,] 1.3816275 #>  [8,] 1.4714120 #>  [9,] 1.4721762 #> [10,] 1.5699564 #> [11,] 1.3887013 #> [12,] 1.2448584 #> [13,] 1.3434080 #> [14,] 1.1566138 #> [15,] 1.3328160 #> [16,] 1.3434915 #> [17,] 1.3543572 #> [18,] 1.2237120 #> [19,] 1.3971476 #> [20,] 1.2549075 #> [21,] 0.9004063 #> [22,] 0.5801156 #> [23,] 0.8631375 #> [24,] 1.0335958 #> [25,] 0.2736529 #> [26,] 0.4309483 #> [27,] 0.5187230 #> [28,] 0.5220279 #> [29,] 0.8217842 #> [30,] 0.4597907 #>  #> , , 77 #>  #>            [,1] #>  [1,] 1.3319748 #>  [2,] 1.3521668 #>  [3,] 1.5517709 #>  [4,] 1.4968762 #>  [5,] 1.5670384 #>  [6,] 1.4578684 #>  [7,] 1.3637579 #>  [8,] 1.4613460 #>  [9,] 1.4687257 #> [10,] 1.5673927 #> [11,] 1.4012281 #> [12,] 1.2577870 #> [13,] 1.3544165 #> [14,] 1.1716151 #> [15,] 1.3454905 #> [16,] 1.3536253 #> [17,] 1.3670401 #> [18,] 1.2382077 #> [19,] 1.4082990 #> [20,] 1.2676164 #> [21,] 0.8537256 #> [22,] 0.5192469 #> [23,] 0.8136350 #> [24,] 0.9871135 #> [25,] 0.2052951 #> [26,] 0.3620834 #> [27,] 0.4527552 #> [28,] 0.4561877 #> [29,] 0.7655052 #> [30,] 0.3924009 #>  #> , , 78 #>  #>            [,1] #>  [1,] 1.3242842 #>  [2,] 1.3400470 #>  [3,] 1.5414350 #>  [4,] 1.4890411 #>  [5,] 1.5614786 #>  [6,] 1.4407491 #>  [7,] 1.3447478 #>  [8,] 1.4503348 #>  [9,] 1.4644852 #> [10,] 1.5639909 #> [11,] 1.4132225 #> [12,] 1.2703274 #> [13,] 1.3649435 #> [14,] 1.1863137 #> [15,] 1.3576869 #> [16,] 1.3632318 #> [17,] 1.3792294 #> [18,] 1.2523065 #> [19,] 1.4189610 #> [20,] 1.2799200 #> [21,] 0.8058980 #> [22,] 0.4572657 #> [23,] 0.7629806 #> [24,] 0.9393165 #> [25,] 0.1362145 #> [26,] 0.2923667 #> [27,] 0.3858185 #> [28,] 0.3893698 #> [29,] 0.7079742 #> [30,] 0.3240565 #>  #> , , 79 #>  #>             [,1] #>  [1,] 1.31577371 #>  [2,] 1.32695827 #>  [3,] 1.53011837 #>  [4,] 1.48024933 #>  [5,] 1.55498991 #>  [6,] 1.42247419 #>  [7,] 1.32459405 #>  [8,] 1.43837736 #>  [9,] 1.45945138 #> [10,] 1.55974710 #> [11,] 1.42467907 #> [12,] 1.28247520 #> [13,] 1.37498484 #> [14,] 1.20070495 #> [15,] 1.36940043 #> [16,] 1.37230647 #> [17,] 1.39091985 #> [18,] 1.26600342 #> [19,] 1.42912942 #> [20,] 1.29181416 #> [21,] 0.75696697 #> [22,] 0.39424929 #> [23,] 0.71122375 #> [24,] 0.89024924 #> [25,] 0.06650722 #> [26,] 0.22188960 #> [27,] 0.31799902 #> [28,] 0.32166092 #> [29,] 0.64925405 #> [30,] 0.25485140 #>  #> , , 80 #>  #>              [,1] #>  [1,]  1.30644060 #>  [2,]  1.31289908 #>  [3,]  1.51781846 #>  [4,]  1.47049558 #>  [5,]  1.54756833 #>  [6,]  1.40304129 #>  [7,]  1.30329359 #>  [8,]  1.42547251 #>  [9,]  1.45362092 #> [10,]  1.55465712 #> [11,]  1.43559292 #> [12,]  1.29422644 #> [13,]  1.38453651 #> [14,]  1.21478453 #> [15,]  1.38062646 #> [16,]  1.38084534 #> [17,]  1.40210666 #> [18,]  1.27929350 #> [19,]  1.43880063 #> [20,]  1.30329440 #> [21,]  0.70697751 #> [22,]  0.33027699 #> [23,]  0.65841584 #> [24,]  0.83995783 #> [25,] -0.00372876 #> [26,]  0.15074512 #> [27,]  0.24938493 #> [28,]  0.25314969 #> [29,]  0.58940990 #> [30,]  0.18488158 #>  #> , , 81 #>  #>              [,1] #>  [1,]  1.29628210 #>  [2,]  1.29786780 #>  [3,]  1.50453289 #>  [4,]  1.45977448 #>  [5,]  1.53920973 #>  [6,]  1.38244807 #>  [7,]  1.28084362 #>  [8,]  1.41161926 #>  [9,]  1.44699052 #> [10,]  1.54871697 #> [11,]  1.44595920 #> [12,]  1.30557718 #> [13,]  1.39359467 #> [14,]  1.22854814 #> [15,]  1.39136055 #> [16,]  1.38884436 #> [17,]  1.41278508 #> [18,]  1.29217197 #> [19,]  1.44797095 #> [20,]  1.31435660 #> [21,]  0.65597592 #> [22,]  0.26543027 #> [23,]  0.60460961 #> [24,]  0.78848999 #> [25,] -0.07439373 #> [26,]  0.07902807 #> [27,]  0.18006611 #> [28,]  0.18392652 #> [29,]  0.52850855 #> [30,]  0.11424500 #>  #> , , 82 #>  #>              [,1] #>  [1,]  1.28529548 #>  [2,]  1.28186295 #>  [3,]  1.49025933 #>  [4,]  1.44808064 #>  [5,]  1.52991004 #>  [6,]  1.36069232 #>  [7,]  1.25724150 #>  [8,]  1.39681666 #>  [9,]  1.43955689 #> [10,]  1.54192264 #> [11,]  1.45577329 #> [12,]  1.31652367 #> [13,]  1.40215567 #> [14,]  1.24199159 #> [15,]  1.40159843 #> [16,]  1.39629971 #> [17,]  1.42295052 #> [18,]  1.30463424 #> [19,]  1.45663691 #> [20,]  1.32499677 #> [21,]  0.60400992 #> [22,]  0.19979248 #> [23,]  0.54985929 #> [24,]  0.73589500 #> [25,] -0.14538641 #> [26,]  0.00683480 #> [27,]  0.11013419 #> [28,]  0.11408364 #> [29,]  0.46661864 #> [30,]  0.04304148 #>  #> , , 83 #>  #>              [,1] #>  [1,]  1.27347802 #>  [2,]  1.26488308 #>  [3,]  1.47499549 #>  [4,]  1.43540869 #>  [5,]  1.51966520 #>  [6,]  1.33777198 #>  [7,]  1.23248483 #>  [8,]  1.38106386 #>  [9,]  1.43131677 #> [10,]  1.53427010 #> [11,]  1.46503072 #> [12,]  1.32706228 #> [13,]  1.41021598 #> [14,]  1.25511081 #> [15,]  1.41133597 #> [16,]  1.40320773 #> [17,]  1.43259858 #> [18,]  1.31667586 #> [19,]  1.46479521 #> [20,]  1.33521103 #> [21,]  0.55112857 #> [22,]  0.13344887 #> [23,]  0.49422056 #> [24,]  0.68222372 #> [25,] -0.21660409 #> [26,] -0.06573682 #> [27,]  0.03968247 #> [28,]  0.04371490 #> [29,]  0.40381060 #> [30,] -0.02862745 #>  #> , , 84 #>  #>              [,1] #>  [1,]  1.26082703 #>  [2,]  1.24692686 #>  [3,]  1.45873910 #>  [4,]  1.42175320 #>  [5,]  1.50847116 #>  [6,]  1.31368518 #>  [7,]  1.20657145 #>  [8,]  1.36436007 #>  [9,]  1.42226688 #> [10,]  1.52575535 #> [11,]  1.47372720 #> [12,]  1.33718955 #> [13,]  1.41777222 #> [14,]  1.26790186 #> [15,]  1.42056925 #> [16,]  1.40956489 #> [17,]  1.44172497 #> [18,]  1.32829253 #> [19,]  1.47244267 #> [20,]  1.34499563 #> [21,]  0.49738221 #> [22,]  0.06648646 #> [23,]  0.43775046 #> [24,]  0.62752848 #> [25,] -0.28794274 #> [26,] -0.13858759 #> [27,] -0.03119427 #> [28,] -0.02708432 #> [29,]  0.34015652 #> [30,] -0.10065864 #>  #> , , 85 #>  #>               [,1] #>  [1,]  1.247339859 #>  [2,]  1.227993054 #>  [3,]  1.441487999 #>  [4,]  1.407108797 #>  [5,]  1.496323855 #>  [6,]  1.288430269 #>  [7,]  1.179499560 #>  [8,]  1.346704567 #>  [9,]  1.412403969 #> [10,]  1.516374372 #> [11,]  1.481858581 #> [12,]  1.346902126 #> [13,]  1.424821151 #> [14,]  1.280360909 #> [15,]  1.429294465 #> [16,]  1.415367793 #> [17,]  1.450325587 #> [18,]  1.339480139 #> [19,]  1.479576315 #> [20,]  1.354346956 #> [21,]  0.442822498 #> [22,] -0.001006074 #> [23,]  0.380507420 #> [24,]  0.571863134 #> [25,] -0.359297142 #> [26,] -0.211617071 #> [27,] -0.102399843 #> [28,] -0.098217199 #> [29,]  0.275730141 #> [30,] -0.172947465 #>  #> , , 86 #>  #>              [,1] #>  [1,]  1.23301388 #>  [2,]  1.20808055 #>  [3,]  1.42324005 #>  [4,]  1.39147008 #>  [5,]  1.48321926 #>  [6,]  1.26200583 #>  [7,]  1.15126772 #>  [8,]  1.32809675 #>  [9,]  1.40172479 #> [10,]  1.50612314 #> [11,]  1.48942088 #> [12,]  1.35619682 #> [13,]  1.43135967 #> [14,]  1.29248422 #> [15,]  1.43750798 #> [16,]  1.42061319 #> [17,]  1.45839642 #> [18,]  1.35023469 #> [19,]  1.48619327 #> [20,]  1.36326152 #> [21,]  0.38750231 #> [22,] -0.06893844 #> [23,]  0.32255114 #> [24,]  0.51528294 #> [25,] -0.43056108 #> [26,] -0.28472371 #> [27,] -0.17383675 #> [28,] -0.16958561 #> [29,]  0.21060678 #> [30,] -0.24538797 #>  #> , , 87 #>  #>             [,1] #>  [1,]  1.2178465 #>  [2,]  1.1871884 #>  [3,]  1.4039932 #>  [4,]  1.3748317 #>  [5,]  1.4691533 #>  [6,]  1.2344108 #>  [7,]  1.1218749 #>  [8,]  1.3085361 #>  [9,]  1.3902261 #> [10,]  1.4949976 #> [11,]  1.4964103 #> [12,]  1.3650706 #> [13,]  1.4373848 #> [14,]  1.3042682 #> [15,]  1.4452063 #> [16,]  1.4252980 #> [17,]  1.4659336 #> [18,]  1.3605524 #> [19,]  1.4922908 #> [20,]  1.3717360 #> [21,]  0.3314757 #> [22,] -0.1372189 #> [23,]  0.2639426 #> [24,]  0.4578446 #> [25,] -0.5016275 #> [26,] -0.3578050 #> [27,] -0.2454064 #> [28,] -0.2410903 #> [29,]  0.1448632 #> [30,] -0.3178730 #>  #> , , 88 #>  #>              [,1] #>  [1,]  1.20183526 #>  [2,]  1.16531569 #>  [3,]  1.38374556 #>  [4,]  1.35718836 #>  [5,]  1.45412206 #>  [6,]  1.20564429 #>  [7,]  1.09132072 #>  [8,]  1.28802218 #>  [9,]  1.37790464 #> [10,]  1.48299381 #> [11,]  1.50282300 #> [12,]  1.37352040 #> [13,]  1.44289370 #> [14,]  1.31570923 #> [15,]  1.45238606 #> [16,]  1.42941906 #> [17,]  1.47293343 #> [18,]  1.37042944 #> [19,]  1.49786637 #> [20,]  1.37976699 #> [21,]  0.27479798 #> [22,] -0.20575428 #> [23,]  0.20474389 #> [24,]  0.39960605 #> [25,] -0.57238845 #> [26,] -0.43075762 #> [27,] -0.31700899 #> [28,] -0.31263083 #> [29,]  0.07857768 #> [30,] -0.39029445 #>  #> , , 89 #>  #>              [,1] #>  [1,]  1.18497764 #>  [2,]  1.14246191 #>  [3,]  1.36249522 #>  [4,]  1.33853482 #>  [5,]  1.43812146 #>  [6,]  1.17570608 #>  [7,]  1.05960516 #>  [8,]  1.26655474 #>  [9,]  1.36475722 #> [10,]  1.47010766 #> [11,]  1.50865551 #> [12,]  1.38154355 #> [13,]  1.44788362 #> [14,]  1.32680400 #> [15,]  1.45904406 #> [16,]  1.43297360 #> [17,]  1.47939223 #> [18,]  1.37986240 #> [19,]  1.50291749 #> [20,]  1.38735150 #> [21,]  0.21752545 #> [22,] -0.27445022 #> [23,]  0.14501838 #> [24,]  0.34062673 #> [25,] -0.64273571 #> [26,] -0.50347753 #> [27,] -0.38854405 #> [28,] -0.38410604 #> [29,]  0.01182972 #> [30,] -0.46254319 #>  #> , , 90 #>  #>              [,1] #>  [1,]  1.16727131 #>  [2,]  1.11862662 #>  [3,]  1.34024050 #>  [4,]  1.31886595 #>  [5,]  1.42114758 #>  [6,]  1.14459623 #>  [7,]  1.02672902 #>  [8,]  1.24413365 #>  [9,]  1.35078062 #> [10,]  1.45633514 #> [11,]  1.51390435 #> [12,]  1.38913732 #> [13,]  1.45235193 #> [14,]  1.33754918 #> [15,]  1.46517720 #> [16,]  1.43595876 #> [17,]  1.48530651 #> [18,]  1.38884780 #> [19,]  1.50744184 #> [20,]  1.39448645 #> [21,]  0.15971556 #> [22,] -0.34321118 #> [23,]  0.08483045 #> [24,]  0.28096720 #> [25,] -0.71256051 #> [26,] -0.57586019 #> [27,] -0.45991022 #> [28,] -0.45541386 #> [29,] -0.05529985 #> [30,] -0.53450947 #>  #> , , 91 #>  #>              [,1] #>  [1,]  1.14871399 #>  [2,]  1.09380967 #>  [3,]  1.31697982 #>  [4,]  1.29817675 #>  [5,]  1.40319653 #>  [6,]  1.11231538 #>  [7,]  0.99269379 #>  [8,]  1.22075894 #>  [9,]  1.33597167 #> [10,]  1.44167226 #> [11,]  1.51856616 #> [12,]  1.39629916 #> [13,]  1.45629612 #> [14,]  1.34794153 #> [15,]  1.47078250 #> [16,]  1.43837184 #> [17,]  1.49067283 #> [18,]  1.39738236 #> [19,]  1.51143722 #> [20,]  1.40116889 #> [21,]  0.10142677 #> [22,] -0.41194059 #> [23,]  0.02424552 #> [24,]  0.22068931 #> [25,] -0.78175390 #> [26,] -0.64780068 #> [27,] -0.53100552 #> [28,] -0.52645166 #> [29,] -0.12272906 #> [30,] -0.60608297 #>  #> , , 92 #>  #>              [,1] #>  [1,]  1.12930357 #>  [2,]  1.06801122 #>  [3,]  1.29271182 #>  [4,]  1.27646236 #>  [5,]  1.38426449 #>  [6,]  1.07886477 #>  [7,]  0.95750180 #>  [8,]  1.19643084 #>  [9,]  1.32032723 #> [10,]  1.42611502 #> [11,]  1.52263769 #> [12,]  1.40302662 #> [13,]  1.45971377 #> [14,]  1.35797795 #> [15,]  1.47585711 #> [16,]  1.44021020 #> [17,]  1.49548788 #> [18,]  1.40546294 #> [19,]  1.51490154 #> [20,]  1.40739599 #> [21,]  0.04271852 #> [22,] -0.48054103 #> [23,] -0.03667002 #> [24,]  0.15985603 #> [25,] -0.85020694 #> [26,] -0.71919387 #> [27,] -0.60172754 #> [28,] -0.59711630 #> [29,] -0.19037483 #> [30,] -0.67715302 #>  #> , , 93 #>  #>              [,1] #>  [1,]  1.10903805 #>  [2,]  1.04123175 #>  [3,]  1.26743532 #>  [4,]  1.25371813 #>  [5,]  1.36434770 #>  [6,]  1.04424631 #>  [7,]  0.92115631 #>  [8,]  1.17114979 #>  [9,]  1.30384421 #> [10,]  1.40965947 #> [11,]  1.52611581 #> [12,]  1.40931738 #> [13,]  1.46260255 #> [14,]  1.36765541 #> [15,]  1.48039829 #> [16,]  1.44147131 #> [17,]  1.49974843 #> [18,]  1.41308648 #> [19,]  1.51783281 #> [20,]  1.41316501 #> [21,] -0.01634882 #> [22,] -0.54891428 #> [23,] -0.09784888 #> [24,]  0.09853147 #> [25,] -0.91781083 #> [26,] -0.78993456 #> [27,] -0.67197352 #> [28,] -0.66730434 #> [29,] -0.25815311 #> [30,] -0.74760873 #>  #> , , 94 #>  #>              [,1] #>  [1,]  1.08791561 #>  [2,]  1.01347215 #>  [3,]  1.24114938 #>  [4,]  1.22993965 #>  [5,]  1.34344255 #>  [6,]  1.00846270 #>  [7,]  0.88366161 #>  [8,]  1.14491652 #>  [9,]  1.28651958 #> [10,]  1.39230170 #> [11,]  1.52899745 #> [12,]  1.41516923 #> [13,]  1.46496023 #> [14,]  1.37697098 #> [15,]  1.48440341 #> [16,]  1.44215269 #> [17,]  1.50345131 #> [18,]  1.42025009 #> [19,]  1.52022917 #> [20,]  1.41847329 #> [21,] -0.07571400 #> [22,] -0.61696152 #> [23,] -0.15922292 #> [24,]  0.03678078 #> [25,] -0.98445715 #> [26,] -0.85991769 #> [27,] -0.74164058 #> [28,] -0.73691218 #> [29,] -0.32597896 #> [30,] -0.81733923 #>  #> , , 95 #>  #>              [,1] #>  [1,]  1.06593466 #>  [2,]  0.98473373 #>  [3,]  1.21385336 #>  [4,]  1.20512277 #>  [5,]  1.32154555 #>  [6,]  0.97151747 #>  [7,]  0.84502315 #>  [8,]  1.11773198 #>  [9,]  1.26835039 #> [10,]  1.37403786 #> [11,]  1.53127965 #> [12,]  1.42058005 #> [13,]  1.46678464 #> [14,]  1.38592181 #> [15,]  1.48786991 #> [16,]  1.44225194 #> [17,]  1.50659344 #> [18,]  1.42695095 #> [19,]  1.52208884 #> [20,]  1.42331827 #> [21,] -0.13531497 #> [22,] -0.68458346 #> [23,] -0.22072325 #> [24,] -0.02532989 #> [25,] -1.05003803 #> [26,] -0.92903850 #> [27,] -0.81062580 #> [28,] -0.80583622 #> [29,] -0.39376664 #> [30,] -0.88623380 #>  #> , , 96 #>  #>              [,1] #>  [1,]  1.04309381 #>  [2,]  0.95501828 #>  [3,]  1.18554690 #>  [4,]  1.17926369 #>  [5,]  1.29865338 #>  [6,]  0.93341510 #>  [7,]  0.80524761 #>  [8,]  1.08959751 #>  [9,]  1.24933378 #> [10,]  1.35486420 #> [11,]  1.53295951 #> [12,]  1.42554786 #> [13,]  1.46807372 #> [14,]  1.39450516 #> [15,]  1.49079536 #> [16,]  1.44176671 #> [17,]  1.50917182 #> [18,]  1.43318639 #> [19,]  1.52341014 #> [20,]  1.42769745 #> [21,] -0.19508892 #> [22,] -0.75168046 #> [23,] -0.28228027 #> [24,] -0.08773345 #> [25,] -1.11444638 #> [26,] -0.99719268 #> [27,] -0.87882647 #> [28,] -0.87397304 #> [29,] -0.46142973 #> [30,] -0.95418216 #>  #> , , 97 #>  #>             [,1] #>  [1,]  1.0193920 #>  [2,]  0.9243282 #>  [3,]  1.1562300 #>  [4,]  1.1523590 #>  [5,]  1.2747629 #>  [6,]  0.8941611 #>  [7,]  0.7643430 #>  [8,]  1.0605148 #>  [9,]  1.2294670 #> [10,]  1.3347770 #> [11,]  1.5340342 #> [12,]  1.4300708 #> [13,]  1.4688255 #> [14,]  1.4027183 #> [15,]  1.4931774 #> [16,]  1.4406947 #> [17,]  1.5111835 #> [18,]  1.4389538 #> [19,]  1.5241915 #> [20,]  1.4316084 #> [21,] -0.2549723 #> [22,] -0.8181527 #> [23,] -0.3438238 #> [24,] -0.1503620 #> [25,] -1.1775760 #> [26,] -1.0642766 #> [27,] -0.9461402 #> [28,] -0.9412196 #> [29,] -0.5288812 #> [30,] -1.0210746 #>  #> , , 98 #>  #>             [,1] #>  [1,]  0.9948284 #>  [2,]  0.8926663 #>  [3,]  1.1259032 #>  [4,]  1.1244056 #>  [5,]  1.2498712 #>  [6,]  0.8537622 #>  [7,]  0.7223190 #>  [8,]  1.0304858 #>  [9,]  1.2087475 #> [10,]  1.3137729 #> [11,]  1.5345010 #> [12,]  1.4341469 #> [13,]  1.4690379 #> [14,]  1.4105588 #> [15,]  1.4950137 #> [16,]  1.4390337 #> [17,]  1.5126255 #> [18,]  1.4442508 #> [19,]  1.5244313 #> [20,]  1.4350488 #> [21,] -0.3149010 #> [22,] -0.8839005 #> [23,] -0.4052830 #> [24,] -0.2131467 #> [25,] -1.2393221 #> [26,] -1.1301875 #> [27,] -1.0124652 #> [28,] -1.0074733 #> [29,] -0.5960337 #> [30,] -1.0868021 #>  #> , , 99 #>  #>             [,1] #>  [1,]  0.9694025 #>  [2,]  0.8600365 #>  [3,]  1.0945673 #>  [4,]  1.0954012 #>  [5,]  1.2239758 #>  [6,]  0.8122263 #>  [7,]  0.6791867 #>  [8,]  0.9995132 #>  [9,]  1.1871727 #> [10,]  1.2918483 #> [11,]  1.5343571 #> [12,]  1.4377747 #> [13,]  1.4687092 #> [14,]  1.4180240 #> [15,]  1.4963021 #> [16,]  1.4367815 #> [17,]  1.5134951 #> [18,]  1.4490748 #> [19,]  1.5241283 #> [20,]  1.4380164 #> [21,] -0.3748102 #> [22,] -0.9488240 #> [23,] -0.4665867 #> [24,] -0.2760181 #> [25,] -1.2995810 #> [26,] -1.1948235 #> [27,] -1.0777001 #> [28,] -1.0726324 #> [29,] -0.6627993 #> [30,] -1.1512568 #>  #> , , 100 #>  #>             [,1] #>  [1,]  0.9431144 #>  [2,]  0.8264429 #>  [3,]  1.0622236 #>  [4,]  1.0653436 #>  [5,]  1.1970742 #>  [6,]  0.7695627 #>  [7,]  0.6349589 #>  [8,]  0.9676000 #>  [9,]  1.1647405 #> [10,]  1.2690000 #> [11,]  1.5335999 #> [12,]  1.4409525 #> [13,]  1.4678375 #> [14,]  1.4251114 #> [15,]  1.4970405 #> [16,]  1.4339360 #> [17,]  1.5137894 #> [18,]  1.4534237 #> [19,]  1.5232810 #> [20,]  1.4405089 #> [21,] -0.4346348 #> [22,] -1.0128239 #> [23,] -0.5276633 #> [24,] -0.3389060 #> [25,] -1.3582507 #> [26,] -1.2580843 #> [27,] -1.1417449 #> [28,] -1.1365959 #> [29,] -0.7290899 #> [30,] -1.2143321 #>  #> , , 101 #>  #>             [,1] #>  [1,]  0.9159644 #>  [2,]  0.7918910 #>  [3,]  1.0288743 #>  [4,]  1.0342317 #>  [5,]  1.1691645 #>  [6,]  0.7257823 #>  [7,]  0.5896506 #>  [8,]  0.9347498 #>  [9,]  1.1414488 #> [10,]  1.2452252 #> [11,]  1.5322268 #> [12,]  1.4436787 #> [13,]  1.4664211 #> [14,]  1.4318188 #> [15,]  1.4972268 #> [16,]  1.4304949 #> [17,]  1.5135057 #> [18,]  1.4572953 #> [19,]  1.5218882 #> [20,]  1.4425242 #> [21,] -0.4943090 #> [22,] -1.0758014 #> [23,] -0.5884409 #> [24,] -0.4017398 #> [25,] -1.4152313 #> [26,] -1.3198706 #> [27,] -1.2045003 #> [28,] -1.1992640 #> [29,] -0.7948175 #> [30,] -1.2759226 #>  #> , , 102 #>  #>             [,1] #>  [1,]  0.8879534 #>  [2,]  0.7563868 #>  [3,]  0.9945217 #>  [4,]  1.0020648 #>  [5,]  1.1402452 #>  [6,]  0.6808974 #>  [7,]  0.5432786 #>  [8,]  0.9009667 #>  [9,]  1.1172958 #> [10,]  1.2205209 #> [11,]  1.5302352 #> [12,]  1.4459519 #> [13,]  1.4644582 #> [14,]  1.4381438 #> [15,]  1.4968590 #> [16,]  1.4264562 #> [17,]  1.5126412 #> [18,]  1.4606874 #> [19,]  1.5199487 #> [20,]  1.4440601 #> [21,] -0.5537667 #> [22,] -1.1376582 #> [23,] -0.6488474 #> [24,] -0.4644482 #> [25,] -1.4704246 #> [26,] -1.3800850 #> [27,] -1.2658683 #> [28,] -1.2605381 #> [29,] -0.8598939 #> [30,] -1.3359248 #>  #> , , 103 #>  #>             [,1] #>  [1,]  0.8590828 #>  [2,]  0.7199374 #>  [3,]  0.9591693 #>  [4,]  0.9688430 #>  [5,]  1.1103153 #>  [6,]  0.6349222 #>  [7,]  0.4958618 #>  [8,]  0.8662557 #>  [9,]  1.0922800 #> [10,]  1.1948848 #> [11,]  1.5276225 #> [12,]  1.4477707 #> [13,]  1.4619472 #> [14,]  1.4440843 #> [15,]  1.4959350 #> [16,]  1.4218179 #> [17,]  1.5111931 #> [18,]  1.4635980 #> [19,]  1.5174612 #> [20,]  1.4451146 #> [21,] -0.6129418 #> [22,] -1.1982970 #> [23,] -0.7088106 #> [24,] -0.5269595 #> [25,] -1.5237351 #> [26,] -1.4386319 #> [27,] -1.3257525 #> [28,] -1.3203213 #> [29,] -0.9242311 #> [30,] -1.3942369 #>  #> , , 104 #>  #>             [,1] #>  [1,]  0.8293546 #>  [2,]  0.6825510 #>  [3,]  0.9228210 #>  [4,]  0.9345675 #>  [5,]  1.0793741 #>  [6,]  0.5878729 #>  [7,]  0.4474217 #>  [8,]  0.8306224 #>  [9,]  1.0664002 #> [10,]  1.1683147 #> [11,]  1.5243862 #> [12,]  1.4491340 #> [13,]  1.4588863 #> [14,]  1.4496380 #> [15,]  1.4944531 #> [16,]  1.4165778 #> [17,]  1.5091589 #> [18,]  1.4660251 #> [19,]  1.5144247 #> [20,]  1.4456857 #> [21,] -0.6717675 #> [22,] -1.2576215 #> [23,] -0.7682582 #> [24,] -0.5892017 #> [25,] -1.5750694 #> [26,] -1.4954177 #> [27,] -1.3840581 #> [28,] -1.3785181 #> [29,] -0.9877413 #> [30,] -1.4507596 #>  #> , , 105 #>  #>             [,1] #>  [1,]  0.7987716 #>  [2,]  0.6442370 #>  [3,]  0.8854818 #>  [4,]  0.8992400 #>  [5,]  1.0474216 #>  [6,]  0.5397674 #>  [7,]  0.3979818 #>  [8,]  0.7940733 #>  [9,]  1.0396557 #> [10,]  1.1408086 #> [11,]  1.5205239 #> [12,]  1.4500403 #> [13,]  1.4552741 #> [14,]  1.4548028 #> [15,]  1.4924113 #> [16,]  1.4107339 #> [17,]  1.5065358 #> [18,]  1.4679668 #> [19,]  1.5108382 #> [20,]  1.4457714 #> [21,] -0.7301773 #> [22,] -1.3155365 #> [23,] -0.8271180 #> [24,] -0.6511025 #> [25,] -1.6243372 #> [26,] -1.5503511 #> [27,] -1.4406921 #> [28,] -1.4350351 #> [29,] -1.0503374 #> [30,] -1.5053954 #>  #> , , 106 #>  #>             [,1] #>  [1,]  0.7673370 #>  [2,]  0.6050060 #>  [3,]  0.8471573 #>  [4,]  0.8628636 #>  [5,]  1.0144586 #>  [6,]  0.4906260 #>  [7,]  0.3475687 #>  [8,]  0.7566155 #>  [9,]  1.0120459 #> [10,]  1.1123653 #> [11,]  1.5160330 #> [12,]  1.4504887 #> [13,]  1.4511088 #> [14,]  1.4595767 #> [15,]  1.4898079 #> [16,]  1.4042842 #> [17,]  1.5033211 #> [18,]  1.4694214 #> [19,]  1.5067007 #> [20,]  1.4453698 #> [21,] -0.7881043 #> [22,] -1.3719483 #> [23,] -0.8853181 #> [24,] -0.7125895 #> [25,] -1.6714512 #> [26,] -1.6033433 #> [27,] -1.4955637 #> [28,] -1.4897809 #> [29,] -1.1119325 #> [30,] -1.5580499 #>  #> , , 107 #>  #>             [,1] #>  [1,]  0.7350550 #>  [2,]  0.5648701 #>  [3,]  0.8078543 #>  [4,]  0.8254423 #>  [5,]  0.9804862 #>  [6,]  0.4404712 #>  [7,]  0.2962115 #>  [8,]  0.7182574 #>  [9,]  0.9835709 #> [10,]  1.0829838 #> [11,]  1.5109110 #> [12,]  1.4504781 #> [13,]  1.4463891 #> [14,]  1.4639577 #> [15,]  1.4866409 #> [16,]  1.3972267 #> [17,]  1.4995122 #> [18,]  1.4703870 #> [19,]  1.5020111 #> [20,]  1.4444788 #> [21,] -0.8454819 #> [22,] -1.4267648 #> [23,] -0.9427867 #> [24,] -0.7735902 #> [25,] -1.7163272 #> [26,] -1.6543080 #> [27,] -1.5485843 #> [28,] -1.5426664 #> [29,] -1.1724407 #> [30,] -1.6086314 #>  #> , , 108 #>  #>             [,1] #>  [1,]  0.7019307 #>  [2,]  0.5238426 #>  [3,]  0.7675807 #>  [4,]  0.7869815 #>  [5,]  0.9455068 #>  [6,]  0.3893279 #>  [7,]  0.2439421 #>  [8,]  0.6790082 #>  [9,]  0.9542312 #> [10,]  1.0526635 #> [11,]  1.5051555 #> [12,]  1.4500074 #> [13,]  1.4411132 #> [14,]  1.4679439 #> [15,]  1.4829087 #> [16,]  1.3895593 #> [17,]  1.4951065 #> [18,]  1.4708620 #> [19,]  1.4967687 #> [20,]  1.4430967 #> [21,] -0.9022433 #> [22,] -1.4798957 #> [23,] -0.9994524 #> [24,] -0.8340319 #> [25,] -1.7588845 #> [26,] -1.7031619 #> [27,] -1.5996677 #> [28,] -1.5936050 #> [29,] -1.2317768 #> [30,] -1.6570511 #>  #> , , 109 #>  #>             [,1] #>  [1,]  0.6679699 #>  [2,]  0.4819385 #>  [3,]  0.7263453 #>  [4,]  0.7474878 #>  [5,]  0.9095231 #>  [6,]  0.3372236 #>  [7,]  0.1907956 #>  [8,]  0.6388784 #>  [9,]  0.9240278 #> [10,]  1.0214047 #> [11,]  1.4987641 #> [12,]  1.4490756 #> [13,]  1.4352797 #> [14,]  1.4715334 #> [15,]  1.4786095 #> [16,]  1.3812801 #> [17,]  1.4901012 #> [18,]  1.4708447 #> [19,]  1.4909724 #> [20,]  1.4412216 #> [21,] -0.9583223 #> [22,] -1.5312527 #> [23,] -1.0552443 #> [24,] -0.8938423 #> [25,] -1.7990462 #> [26,] -1.7498249 #> [27,] -1.6487304 #> [28,] -1.6425130 #> [29,] -1.2898564 #> [30,] -1.7032237 #>  #> , , 110 #>  #>             [,1] #>  [1,]  0.6331795 #>  [2,]  0.4391744 #>  [3,]  0.6841584 #>  [4,]  0.7069690 #>  [5,]  0.8725392 #>  [6,]  0.2841887 #>  [7,]  0.1368104 #>  [8,]  0.5978794 #>  [9,]  0.8929625 #> [10,]  0.9892078 #> [11,]  1.4917342 #> [12,]  1.4476820 #> [13,]  1.4288872 #> [14,]  1.4747243 #> [15,]  1.4737416 #> [16,]  1.3723870 #> [17,]  1.4844937 #> [18,]  1.4703334 #> [19,]  1.4846215 #> [20,]  1.4388516 #> [21,] -1.0136525 #> [22,] -1.5807497 #> [23,] -1.1100921 #> [24,] -0.9529492 #> [25,] -1.8367394 #> [26,] -1.7942201 #> [27,] -1.6956920 #> [28,] -1.6893095 #> [29,] -1.3465967 #> [30,] -1.7470675 #>  #> , , 111 #>  #>              [,1] #>  [1,]  0.59756759 #>  [2,]  0.39556877 #>  [3,]  0.64103132 #>  [4,]  0.66543470 #>  [5,]  0.83455975 #>  [6,]  0.23025601 #>  [7,]  0.08202796 #>  [8,]  0.55602406 #>  [9,]  0.86103741 #> [10,]  0.95607440 #> [11,]  1.48406336 #> [12,]  1.44582559 #> [13,]  1.42193410 #> [14,]  1.47751477 #> [15,]  1.46830329 #> [16,]  1.36287799 #> [17,]  1.47828141 #> [18,]  1.46932676 #> [19,]  1.47771514 #> [20,]  1.43598484 #> [21,] -1.06816836 #> [22,] -1.62830310 #> [23,] -1.16392624 #> [24,] -1.01128060 #> [25,] -1.87189520 #> [26,] -1.83627425 #> [27,] -1.74047495 #> [28,] -1.73391662 #> [29,] -1.40191592 #> [30,] -1.78850446 #>  #> , , 112 #>  #>              [,1] #>  [1,]  0.56114310 #>  [2,]  0.35114187 #>  [3,]  0.59697705 #>  [4,]  0.62289599 #>  [5,]  0.79559081 #>  [6,]  0.17546178 #>  [7,]  0.02649337 #>  [8,]  0.51332655 #>  [9,]  0.82825559 #> [10,]  0.92200642 #> [11,]  1.47574921 #> [12,]  1.44350563 #> [13,]  1.41441897 #> [14,]  1.47990314 #> [15,]  1.46229291 #> [16,]  1.35275117 #> [17,]  1.47146157 #> [18,]  1.46782311 #> [19,]  1.47025257 #> [20,]  1.43261958 #> [21,] -1.12180444 #> [22,] -1.67383172 #> [23,] -1.21667778 #> [24,] -1.06876499 #> [25,] -1.90444940 #> [26,] -1.87591764 #> [27,] -1.78300519 #> [28,] -1.77626015 #> [29,] -1.45573366 #> [30,] -1.82746067 #>  #> , , 113 #>  #>              [,1] #>  [1,]  0.52391636 #>  [2,]  0.30591591 #>  [3,]  0.55200991 #>  [4,]  0.57936566 #>  [5,]  0.75563946 #>  [6,]  0.11984519 #>  [7,] -0.02974471 #>  [8,]  0.46980244 #>  [9,]  0.79462075 #> [10,]  0.88700674 #> [11,]  1.46678925 #> [12,]  1.44072137 #> [13,]  1.40634035 #> [14,]  1.48188766 #> [15,]  1.45570879 #> [16,]  1.34200453 #> [17,]  1.46403153 #> [18,]  1.46582101 #> [19,]  1.46223301 #> [20,]  1.42875400 #> [21,] -1.17449603 #> [22,] -1.71725738 #> [23,] -1.26827883 #> [24,] -1.12533135 #> [25,] -1.93434230 #> [26,] -1.91308469 #> [27,] -1.82321209 #> [28,] -1.81626924 #> [29,] -1.50797130 #> [30,] -1.86386650 #>  #> , , 114 #>  #>              [,1] #>  [1,]  0.48589893 #>  [2,]  0.25991522 #>  [3,]  0.50614589 #>  [4,]  0.53485831 #>  [5,]  0.71471403 #>  [6,]  0.06344874 #>  [7,] -0.08663389 #>  [8,]  0.42546883 #>  [9,]  0.76013745 #> [10,]  0.85107904 #> [11,]  1.45718104 #> [12,]  1.43747211 #> [13,]  1.39769680 #> [14,]  1.48346663 #> [15,]  1.44854927 #> [16,]  1.33063609 #> [17,]  1.45598862 #> [18,]  1.46331901 #> [19,]  1.45365575 #> [20,]  1.42438628 #> [21,] -1.22617902 #> [22,] -1.75850490 #> [23,] -1.31866251 #> [24,] -1.18090926 #> [25,] -1.96151913 #> [26,] -1.94771392 #> [27,] -1.86102879 #> [28,] -1.85387691 #> [29,] -1.55855192 #> [30,] -1.89765682 #>  #> , , 115 #>  #>               [,1] #>  [1,]  0.447103723 #>  [2,]  0.213166296 #>  [3,]  0.459402591 #>  [4,]  0.489390490 #>  [5,]  0.672824190 #>  [6,]  0.006318311 #>  [7,] -0.144117941 #>  [8,]  0.380344434 #>  [9,]  0.724811121 #> [10,]  0.814227917 #> [11,]  1.446922105 #> [12,]  1.433757176 #> [13,]  1.388486892 #> [14,]  1.484638384 #> [15,]  1.440812711 #> [16,]  1.318643904 #> [17,]  1.447330138 #> [18,]  1.460315719 #> [19,]  1.444520065 #> [20,]  1.419514650 #> [21,] -1.276790077 #> [22,] -1.797502313 #> [23,] -1.367763044 #> [24,] -1.235429019 #> [25,] -1.985930240 #> [26,] -1.979748237 #> [27,] -1.896392364 #> [28,] -1.889020156 #> [29,] -1.607400553 #> [30,] -1.928771274 #>  #> , , 116 #>  #>              [,1] #>  [1,]  0.40754511 #>  [2,]  0.16569793 #>  [3,]  0.41179944 #>  [4,]  0.44298077 #>  [5,]  0.62998104 #>  [6,] -0.05149666 #>  [7,] -0.20213665 #>  [8,]  0.33444965 #>  [9,]  0.68864812 #> [10,]  0.77645895 #> [11,]  1.43601001 #> [12,]  1.42957595 #> [13,]  1.37870920 #> [14,]  1.48540131 #> [15,]  1.43249749 #> [16,]  1.30602603 #> [17,]  1.43805339 #> [18,]  1.45680973 #> [19,]  1.43482529 #> [20,]  1.41413732 #> [21,] -1.32626671 #> [22,] -1.83418115 #> [23,] -1.41551595 #> [24,] -1.28882175 #> [25,] -2.00753131 #> [26,] -2.00913510 #> [27,] -1.92924401 #> [28,] -1.92164018 #> [29,] -1.65444432 #> [30,] -1.95715447 #>  #> , , 117 #>  #>             [,1] #>  [1,]  0.3672390 #>  [2,]  0.1175413 #>  [3,]  0.3633577 #>  [4,]  0.3956499 #>  [5,]  0.5861972 #>  [6,] -0.1099431 #>  [7,] -0.2606258 #>  [8,]  0.2878067 #>  [9,]  0.6516558 #> [10,]  0.7377788 #> [11,]  1.4244423 #> [12,]  1.4249278 #> [13,]  1.3683623 #> [14,]  1.4857538 #> [15,]  1.4236020 #> [16,]  1.2927805 #> [17,]  1.4281557 #> [18,]  1.4527997 #> [19,]  1.4245708 #> [20,]  1.4082525 #> [21,] -1.3745474 #> [22,] -1.8684766 #> [23,] -1.4618581 #> [24,] -1.3410195 #> [25,] -2.0262836 #> [26,] -2.0358268 #> [27,] -1.9595293 #> [28,] -1.9516826 #> [29,] -1.6996126 #> [30,] -1.9827562 #>  #> , , 118 #>  #>              [,1] #>  [1,]  0.32620278 #>  [2,]  0.06873015 #>  [3,]  0.31410066 #>  [4,]  0.34742079 #>  [5,]  0.54148680 #>  [6,] -0.16896409 #>  [7,] -0.31951685 #>  [8,]  0.24043957 #>  [9,]  0.61384269 #> [10,]  0.69819511 #> [11,]  1.41221652 #> [12,]  1.41981226 #> [13,]  1.35744483 #> [14,]  1.48569424 #> [15,]  1.41412454 #> [16,]  1.27890557 #> [17,]  1.41763429 #> [18,]  1.44828428 #> [19,]  1.41375582 #> [20,]  1.40185843 #> [21,] -1.42157158 #> [22,] -1.90032766 #> [23,] -1.50672781 #> [24,] -1.39195541 #> [25,] -2.04215395 #> [26,] -2.05978038 #> [27,] -1.98719828 #> [28,] -1.97909761 #> [29,] -1.74283717 #> [30,] -2.00553175 #>  #> , , 119 #>  #>              [,1] #>  [1,]  0.28445573 #>  [2,]  0.01930072 #>  [3,]  0.26405358 #>  [4,]  0.29831885 #>  [5,]  0.49586584 #>  [6,] -0.22849894 #>  [7,] -0.37873725 #>  [8,]  0.19237436 #>  [9,]  0.57521829 #> [10,]  0.65771694 #> [11,]  1.39933027 #> [12,]  1.41422872 #> [13,]  1.34595537 #> [14,]  1.48522111 #> [15,]  1.40406360 #> [16,]  1.26439925 #> [17,]  1.40648652 #> [18,]  1.44326216 #> [19,]  1.40237988 #> [20,]  1.39495331 #> [21,] -1.46728001 #> [22,] -1.92967752 #> [23,] -1.55006512 #> [24,] -1.44156372 #> [25,] -2.05511540 #> [26,] -2.08095832 #> [27,] -2.01220581 #> [28,] -2.00384022 #> [29,] -1.78405244 #> [30,] -2.02544193 #>  #> , , 120 #>  #>              [,1] #>  [1,]  0.24201874 #>  [2,] -0.03070798 #>  [3,]  0.21324395 #>  [4,]  0.24837186 #>  [5,]  0.44935198 #>  [6,] -0.28848293 #>  [7,] -0.43821000 #>  [8,]  0.14363913 #>  [9,]  0.53579342 #> [10,]  0.61635447 #> [11,]  1.38578113 #> [12,]  1.40817670 #> [13,]  1.33389256 #> [14,]  1.48433287 #> [15,]  1.39341754 #> [16,]  1.24925975 #> [17,]  1.39470968 #> [18,]  1.43773202 #> [19,]  1.39044233 #> [20,]  1.38753538 #> [21,] -1.51161458 #> [22,] -1.95647356 #> [23,] -1.59181171 #> [24,] -1.48978001 #> [25,] -2.06514695 #> [26,] -2.09932821 #> [27,] -2.03451159 #> [28,] -2.02587044 #> [29,] -1.82319553 #> [30,] -2.04245347 #>  #> , , 121 #>  #>              [,1] #>  [1,]  0.19891461 #>  [2,] -0.08125416 #>  [3,]  0.16170148 #>  [4,]  0.19761022 #>  [5,]  0.40196483 #>  [6,] -0.34884725 #>  [7,] -0.49785374 #>  [8,]  0.09426409 #>  [9,]  0.49558015 #> [10,]  0.57411927 #> [11,]  1.37156671 #> [12,]  1.40165574 #> [13,]  1.32125506 #> [14,]  1.48302797 #> [15,]  1.38218479 #> [16,]  1.23348533 #> [17,]  1.38230107 #> [18,]  1.43169259 #> [19,]  1.37794260 #> [20,]  1.37960285 #> [21,] -1.55451858 #> [22,] -1.98066767 #> [23,] -1.63191115 #> [24,] -1.53654122 #> [25,] -2.07223394 #> [26,] -2.11486320 #> [27,] -2.05408047 #> [28,] -2.04515341 #> [29,] -1.86020650 #> [30,] -2.05653909 #>  #> , , 122 #>  #>              [,1] #>  [1,]  0.15516805 #>  [2,] -0.13229315 #>  [3,]  0.10945824 #>  [4,]  0.14606702 #>  [5,]  0.35372596 #>  [6,] -0.40951897 #>  [7,] -0.55758275 #>  [8,]  0.04428169 #>  [9,]  0.45459190 #> [10,]  0.53102434 #> [11,]  1.35668466 #> [12,]  1.39466537 #> [13,]  1.30804154 #> [14,]  1.48130491 #> [15,]  1.37036378 #> [16,]  1.21707427 #> [17,]  1.36925801 #> [18,]  1.42514259 #> [19,]  1.36488016 #> [20,]  1.37115395 #> [21,] -1.59593679 #> [22,] -2.00221641 #> [23,] -1.67030896 #> [24,] -1.58178581 #> [25,] -2.07636817 #> [26,] -2.12754210 #> [27,] -2.07088253 #> [28,] -2.06165965 #> [29,] -1.89502846 #> [30,] -2.06767770 #>  #> , , 123 #>  #>               [,1] #>  [1,]  0.110805759 #>  [2,] -0.183777316 #>  [3,]  0.056548729 #>  [4,]  0.093778121 #>  [5,]  0.304659037 #>  [6,] -0.470420926 #>  [7,] -0.617306858 #>  [8,] -0.006273309 #>  [9,]  0.412843528 #> [10,]  0.487084176 #> [11,]  1.341132638 #> [12,]  1.387205168 #> [13,]  1.294250707 #> [14,]  1.479162194 #> [15,]  1.357952940 #> [16,]  1.200024921 #> [17,]  1.355577835 #> [18,]  1.418080754 #> [19,]  1.351254479 #> [20,]  1.362186893 #> [21,] -1.635815531 #> [22,] -2.021081196 #> [23,] -1.706952772 #> [24,] -1.625453870 #> [25,] -2.077548058 #> [26,] -2.137349487 #> [27,] -2.084893301 #> [28,] -2.075365149 #> [29,] -1.927607779 #> [30,] -2.075854641 #>  #> , , 124 #>  #>               [,1] #>  [1,]  0.065856548 #>  [2,] -0.235655974 #>  [3,]  0.003009972 #>  [4,]  0.040782285 #>  [5,]  0.254789899 #>  [6,] -0.531471710 #>  [7,] -0.676931466 #>  [8,] -0.057363762 #>  [9,]  0.370351359 #> [10,]  0.442314867 #> [11,]  1.324908388 #> [12,]  1.379274738 #> [13,]  1.279881284 #> [14,]  1.476598329 #> [15,]  1.344950742 #> [16,]  1.182335732 #> [17,]  1.341257918 #> [18,]  1.410505831 #> [19,]  1.337065075 #> [20,]  1.352699914 #> [21,] -1.674102836 #> [22,] -2.037228494 #> [23,] -1.741792436 #> [24,] -1.667487255 #> [25,] -2.075778784 #> [26,] -2.144275922 #> [27,] -2.096093893 #> [28,] -2.086251597 #> [29,] -1.957894198 #> [30,] -2.081061756 #>  #> , , 125 #>  #>              [,1] #>  [1,]  0.02035137 #>  [2,] -0.28787532 #>  [3,] -0.05111839 #>  [4,] -0.01287875 #>  [5,]  0.20414666 #>  [6,] -0.59258560 #>  [7,] -0.73635756 #>  [8,] -0.10895005 #>  [9,]  0.32713330 #> [10,]  0.39673416 #> [11,]  1.30800968 #> [12,]  1.37087369 #> [13,]  1.26493204 #> [14,]  1.47361183 #> [15,]  1.33135567 #> [16,]  1.16400523 #> [17,]  1.32629566 #> [18,]  1.40241658 #> [19,]  1.32231149 #> [20,]  1.34269124 #> [21,] -1.71074851 #> [22,] -2.05063000 #> [23,] -1.77478013 #> [24,] -1.70782968 #> [25,] -2.07107239 #> [26,] -2.14831803 #> [27,] -2.10447116 #> [28,] -2.09430648 #> [29,] -1.98584103 #> [30,] 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[14,]  1.46636506 #> [15,]  1.30238100 #> [16,]  1.12541494 #> [17,]  1.29443392 #> [18,]  1.38469016 #> [19,]  1.29111018 #> [20,]  1.32110176 #> [21,] -1.77892382 #> [22,] -2.06910952 #> [23,] -1.83502068 #> [24,] -1.78322657 #> [25,] -2.05293145 #> [26,] -2.14776683 #> [27,] -2.11273262 #> [28,] -2.10190136 #> [29,] -2.03454782 #> [30,] -2.07888384 #>  #> , , 128 #>  #>              [,1] #>  [1,] -0.11915655 #>  [2,] -0.44599145 #>  [3,] -0.21660394 #>  [4,] -0.17738906 #>  [5,]  0.04788947 #>  [6,] -0.77538377 #>  [7,] -0.91238932 #>  [8,] -0.26624919 #>  [9,]  0.19332779 #> [10,]  0.25532781 #> [11,]  1.25324572 #> [12,]  1.34284330 #> [13,]  1.21659379 #> [14,]  1.46210184 #> [15,]  1.28699854 #> [16,]  1.10515278 #> [17,]  1.27752950 #> [18,]  1.37505055 #> [19,]  1.27466174 #> [20,]  1.30951744 #> [21,] -1.81036299 #> [22,] -2.07415854 #> [23,] -1.86219064 #> [24,] -1.81817890 #> [25,] -2.03955625 #> [26,] -2.14319815 #> [27,] -2.11262037 #> [28,] -2.10144658 #> [29,] 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1.21332701 #> [12,]  1.32179711 #> [13,]  1.18144891 #> [14,]  1.45228840 #> [15,]  1.25443653 #> [16,]  1.06268967 #> [17,]  1.24176171 #> [18,]  1.35421252 #> [19,]  1.24006792 #> [20,]  1.28476101 #> [21,] -1.86773461 #> [22,] -2.07584627 #> [23,] -1.91044350 #> [24,] -1.88235340 #> [25,] -2.00439857 #> [26,] -2.12558463 #> [27,] -2.10396523 #> [28,] -2.09209260 #> [29,] -2.08911484 #> [30,] -2.05034037 #>  #> , , 131 #>  #>              [,1] #>  [1,] -0.26233215 #>  [2,] -0.60492591 #>  [3,] -0.38570217 #>  [4,] -0.34607935 #>  [5,] -0.11408551 #>  [6,] -0.95524973 #>  [7,] -1.08265793 #>  [8,] -0.42633286 #>  [9,]  0.05379901 #> [10,]  0.10743424 #> [11,]  1.19233956 #> [12,]  1.31056538 #> [13,]  1.16299784 #> [14,]  1.44673526 #> [15,]  1.23725442 #> [16,]  1.04048731 #> [17,]  1.22289388 #> [18,]  1.34301172 #> [19,]  1.22192217 #> [20,]  1.27158550 #> [21,] -1.89359020 #> [22,] -2.07249147 #> [23,] -1.93146065 #> [24,] -1.91148788 #> [25,] -1.98271865 #> [26,] -2.11260335 #> [27,] -2.09546340 #> [28,] -2.08323657 #> [29,] -2.10226148 #> [30,] -2.03510730 #>  #> , , 132 #>  #>               [,1] #>  [1,] -0.310666825 #>  [2,] -0.657750595 #>  [3,] -0.442612708 #>  [4,] -0.402960035 #>  [5,] -0.169150646 #>  [6,] -1.014043706 #>  [7,] -1.137564340 #>  [8,] -0.480058878 #>  [9,]  0.006147403 #> [10,]  0.056827104 #> [11,]  1.170664722 #> [12,]  1.298860880 #> [13,]  1.143959982 #> [14,]  1.440749210 #> [15,]  1.219469979 #> [16,]  1.017637133 #> [17,]  1.203367295 #> [18,]  1.331288175 #> [19,]  1.203210383 #> [20,]  1.257876222 #> [21,] -1.917511873 #> [22,] -2.066352196 #> [23,] -1.950366264 #> [24,] -1.938599793 #> [25,] -1.958385077 #> [26,] -2.096892437 #> [27,] -2.084216764 #> [28,] -2.071634075 #> [29,] -2.112853638 #> [30,] -2.017089131 #>  #> , , 133 #>  #>               [,1] #>  [1,] -0.359224251 #>  [2,] -0.710367598 #>  [3,] -0.499693015 #>  [4,] -0.460055076 #>  [5,] -0.224672643 #>  [6,] -1.072061428 #>  [7,] -1.191330300 #>  [8,] -0.533867022 #>  [9,] -0.042022069 #> [10,]  0.005619872 #> [11,]  1.148301179 #> [12,]  1.286683394 #> [13,]  1.124334671 #> [14,]  1.434328794 #> [15,]  1.201082098 #> [16,]  0.994138964 #> [17,]  1.183180024 #> [18,]  1.319040726 #> [19,]  1.183932566 #> [20,]  1.243631556 #> [21,] -1.939467558 #> [22,] -2.057447266 #> [23,] -1.967135340 #> [24,] -1.963652091 #> [25,] -1.931467142 #> [26,] -2.078500146 #> [27,] -2.070261925 #> [28,] -2.057322949 #> [29,] -2.120878249 #> [30,] -1.996341270 #>  #> , , 134 #>  #>              [,1] #>  [1,] -0.40795128 #>  [2,] -0.76269336 #>  [3,] -0.55687691 #>  [4,] -0.51729261 #>  [5,] -0.28059912 #>  [6,] -1.12917981 #>  [7,] -1.24382152 #>  [8,] -0.58769275 #>  [9,] -0.09067430 #> [10,] -0.04615126 #> [11,]  1.12524783 #> [12,]  1.27403272 #> [13,]  1.10412137 #> [14,]  1.42747254 #> [15,]  1.18208977 #> [16,]  0.96999288 #> [17,]  1.16233027 #> [18,]  1.30626825 #> [19,]  1.16408880 #> [20,]  1.22884991 #> [21,] -1.95942791 #> [22,] -2.04580191 #> [23,] -1.98174623 #> [24,] -1.98661065 #> [25,] -1.90204125 #> [26,] -2.05748134 #> [27,] -2.05364196 #> [28,] -2.04034756 #> [29,] -2.12632704 #> [30,] -1.97292634 #>  #> , , 135 #>  #>              [,1] #>  [1,] -0.45679209 #>  [2,] -0.81464106 #>  [3,] -0.61409506 #>  [4,] -0.57459722 #>  [5,] -0.33687467 #>  [6,] -1.18527215 #>  [7,] -1.29490077 #>  [8,] -0.64146857 #>  [9,] -0.13977197 #> [10,] -0.09844768 #> [11,]  1.10150377 #> [12,]  1.26090868 #> [13,]  1.08331969 #> [14,]  1.42017898 #> [15,]  1.16249210 #> [16,]  0.94519921 #> [17,]  1.14081642 #> [18,]  1.29296963 #> [19,]  1.14367927 #> [20,]  1.21352975 #> [21,] -1.97736639 #> [22,] -2.03144780 #> [23,] -1.99418071 #> [24,] -2.00744437 #> [25,] -1.87019085 #> [26,] -2.03389741 #> [27,] -2.03440641 #> [28,] -2.02075884 #> [29,] -2.12919662 #> [30,] -1.94691415 #>  #> , , 136 #>  #>             [,1] #>  [1,] -0.5056881 #>  [2,] -0.8661206 #>  [3,] -0.6712750 #>  [4,] -0.6318899 #>  [5,] -0.3934408 #>  [6,] -1.2402084 #>  [7,] -1.3444282 #>  [8,] -0.6951240 #>  [9,] -0.1892755 #> [10,] -0.1512283 #> [11,]  1.0770684 #> [12,]  1.2473111 #> [13,]  1.0619293 #> [14,]  1.4124466 #> [15,]  1.1422883 #> [16,]  0.9197586 #> [17,]  1.1186370 #> [18,]  1.2791438 #> [19,]  1.1227043 #> [20,]  1.1976696 #> [21,] -1.9932594 #> [22,] -2.0144231 #> [23,] -2.0044241 #> [24,] -2.0261253 #> [25,] -1.8360063 #> [26,] -2.0078163 #> [27,] -2.0126113 #> [28,] -1.9986142 #> [29,] -2.1294886 #> [30,] -1.9183816 #>  #> , , 137 #>  #>             [,1] #>  [1,] -0.5545782 #>  [2,] -0.9170389 #>  [3,] -0.7283409 #>  [4,] -0.6890882 #>  [5,] -0.4502358 #>  [6,] -1.2938553 #>  [7,] -1.3922616 #>  [8,] -0.7485858 #>  [9,] -0.2391429 #> [10,] -0.2044496 #> [11,]  1.0519412 #> [12,]  1.2332399 #> [13,]  1.0399503 #> [14,]  1.4042741 #> [15,]  1.1214777 #> [16,]  0.8936720 #> [17,]  1.0957908 #> [18,]  1.2647897 #> [19,]  1.1011642 #> [20,]  1.1812680 #> [21,] -2.0070863 #> [22,] -1.9947726 #> [23,] -2.0124653 #> [24,] -2.0426288 #> [25,] -1.7995847 #> [26,] -1.9793122 #> [27,] -1.9883191 #> [28,] -1.9739776 #> [29,] -2.1272096 #> [30,] -1.8874127 #>  #> , , 138 #>  #>             [,1] #>  [1,] -0.6033983 #>  [2,] -0.9672995 #>  [3,] -0.7852141 #>  [4,] -0.7461060 #>  [5,] -0.5071950 #>  [6,] -1.3460766 #>  [7,] -1.4382570 #>  [8,] -0.8017775 #>  [9,] -0.2893299 #> [10,] -0.2580654 #> [11,]  1.0261221 #> [12,]  1.2186950 #> [13,]  1.0173825 #> [14,]  1.3956598 #> [15,]  1.1000597 #> [16,]  0.8669407 #> [17,]  1.0722768 #> [18,]  1.2499063 #> [19,]  1.0790596 #> [20,]  1.1643236 #> [21,] -2.0188296 #> [22,] -1.9725475 #> [23,] -2.0182970 #> [24,] -2.0569333 #> [25,] -1.7610298 #> [26,] -1.9484659 #> [27,] -1.9615986 #> [28,] -1.9469194 #> [29,] -2.1223714 #> [30,] -1.8540982 #>  #> , , 139 #>  #>             [,1] #>  [1,] -0.6520819 #>  [2,] -1.0168034 #>  [3,] -0.8418125 #>  [4,] -0.8028538 #>  [5,] -0.5642503 #>  [6,] -1.3967338 #>  [7,] -1.4822687 #>  [8,] -0.8546200 #>  [9,] -0.3397898 #> [10,] -0.3120270 #> [11,]  0.9996113 #> [12,]  1.2036764 #> [13,]  0.9942263 #> [14,]  1.3866023 #> [15,]  1.0780341 #> [16,]  0.8395665 #> [17,]  1.0480942 #> [18,]  1.2344927 #> [19,]  1.0563912 #> [20,]  1.1468351 #> [21,] -2.0284750 #> [22,] -1.9478056 #> [23,] -2.0219155 #> [24,] -2.0690211 #> [25,] -1.7204517 #> [26,] -1.9153641 #> [27,] -1.9325250 #> [28,] -1.9175161 #> [29,] -2.1149911 #> [30,] -1.8185356 #>  #> , , 140 #>  #>             [,1] #>  [1,] -0.7005596 #>  [2,] -1.0654486 #>  [3,] -0.8980511 #>  [4,] -0.8592386 #>  [5,] -0.6213305 #>  [6,] -1.4456857 #>  [7,] -1.5241499 #>  [8,] -0.9070313 #>  [9,] -0.3904735 #> [10,] -0.3662828 #> [11,]  0.9724092 #> [12,]  1.1881839 #> [13,]  0.9704823 #> [14,]  1.3771002 #> [15,]  1.0554007 #> [16,]  0.8115513 #> [17,]  1.0232425 #> [18,]  1.2185480 #> [19,]  1.0331598 #> [20,]  1.1288014 #> [21,] -2.0360114 #> [22,] -1.9206113 #> [23,] -2.0233211 #> [24,] -2.0788777 #> [25,] -1.6779667 #> [26,] -1.8800997 #> [27,] -1.9011793 #> [28,] -1.8858507 #> [29,] -2.1050909 #> [30,] -1.7808290 #>  #> , , 141 #>  #>             [,1] #>  [1,] -0.7487594 #>  [2,] -1.1131304 #>  [3,] -0.9538417 #>  [4,] -0.9151641 #>  [5,] -0.6783614 #>  [6,] -1.4927893 #>  [7,] -1.5637534 #>  [8,] -0.9589264 #>  [9,] -0.4413294 #> [10,] -0.4207788 #> [11,]  0.9445169 #> [12,]  1.1722177 #> [13,]  0.9461509 #> [14,]  1.3671519 #> [15,]  1.0321593 #> [16,]  0.7828976 #> [17,]  0.9977215 #> [18,]  1.2020712 #> [19,]  1.0093664 #> [20,]  1.1102213 #> [21,] -2.0414310 #> [22,] -1.8910353 #> [23,] -2.0225180 #> [24,] -2.0864923 #> [25,] -1.6336970 #> [26,] -1.8427713 #> [27,] -1.8676491 #> [28,] -1.8520122 #> [29,] -2.0926985 #> [30,] -1.7410889 #>  #> , , 142 #>  #>             [,1] #>  [1,] -0.7966069 #>  [2,] -1.1597417 #>  [3,] -1.0090933 #>  [4,] -0.9705307 #>  [5,] -0.7352654 #>  [6,] -1.5379002 #>  [7,] -1.6009317 #>  [8,] -1.0102180 #>  [9,] -0.4923034 #> [10,] -0.4754581 #> [11,]  0.9159355 #> [12,]  1.1557779 #> [13,]  0.9212333 #> [14,]  1.3567561 #> [15,]  1.0083103 #> [16,]  0.7536085 #> [17,]  0.9715313 #> [18,]  1.1850615 #> [19,]  0.9850122 #> [20,]  1.0910939 #> [21,] -2.0447296 #> [22,] -1.8591548 #> [23,] -2.0195143 #> [24,] -2.0918579 #> [25,] -1.5877705 #> [26,] -1.8034834 #> [27,] -1.8320274 #> [28,] -1.8160954 #> [29,] -2.0778468 #> [30,] -1.6994317 #>  #> , , 143 #>  #>             [,1] #>  [1,] -0.8440248 #>  [2,] -1.2051731 #>  [3,] -1.0637119 #>  [4,] -1.0252356 #>  [5,] -0.7919617 #>  [6,] -1.5808728 #>  [7,] -1.6355376 #>  [8,] -1.0608158 #>  [9,] -0.5433389 #> [10,] -0.5302612 #> [11,]  0.8866667 #> [12,]  1.1388646 #> [13,]  0.8957306 #> [14,]  1.3459112 #> [15,]  0.9838540 #> [16,]  0.7236875 #> [17,]  0.9446723 #> [18,]  1.1675183 #> [19,]  0.9600986 #> [20,]  1.0714184 #> [21,] -2.0459061 #> [22,] -1.8250533 #> [23,] -2.0143221 #> [24,] -2.0949711 #> [25,] -1.5403202 #> [26,] -1.7623458 #> [27,] -1.7944133 #> [28,] -1.7782008 #> [29,] -2.0605740 #> [30,] -1.6559798 #>  #> , , 144 #>  #>             [,1] #>  [1,] -0.8909335 #>  [2,] -1.2493131 #>  [3,] -1.1176006 #>  [4,] -1.0791731 #>  [5,] -0.8483666 #>  [6,] -1.6215607 #>  [7,] -1.6674250 #>  [8,] -1.1106271 #>  [9,] -0.5943768 #> [10,] -0.5851257 #> [11,]  0.8567126 #> [12,]  1.1214780 #> [13,]  0.8696444 #> [14,]  1.3346159 #> [15,]  0.9587913 #> [16,]  0.6931384 #> [17,]  0.9171453 #> [18,]  1.1494409 #> [19,]  0.9346271 #> [20,]  1.0511940 #> [21,] -2.0449634 #> [22,] -1.7888205 #> [23,] -2.0069577 #> [24,] -2.0958325 #> [25,] -1.4914842 #> [26,] -1.7194733 #> [27,] -1.7549110 #> [28,] -1.7384347 #> [29,] -2.0409239 #> [30,] -1.6108609 #>  #> , , 145 #>  #>             [,1] #>  [1,] -0.9372512 #>  [2,] -1.2920483 #>  [3,] -1.1706601 #>  [4,] -1.1322345 #>  [5,] -0.9043930 #>  [6,] -1.6598173 #>  [7,] -1.6964493 #>  [8,] -1.1595568 #>  [9,] -0.6453556 #> [10,] -0.6399866 #> [11,]  0.8260759 #> [12,]  1.1036183 #> [13,]  0.8429764 #> [14,]  1.3228687 #> [15,]  0.9331229 #> [16,]  0.6619658 #> [17,]  0.8889516 #> [18,]  1.1308286 #> [19,]  0.9085997 #> [20,]  1.0304201 #> [21,] -2.0419076 #> [22,] -1.7505521 #> [23,] -1.9974414 #> [24,] -2.0944466 #> [25,] -1.4414052 #> [26,] -1.6749859 #> [27,] -1.7136305 #> [28,] -1.6969084 #> [29,] -2.0189454 #> [30,] -1.5642081 #>  #> , , 146 #>  #>             [,1] #>  [1,] -0.9828935 #>  [2,] -1.3332640 #>  [3,] -1.2227881 #>  [4,] -1.1843083 #>  [5,] -0.9599511 #>  [6,] -1.6954964 #>  [7,] -1.7224681 #>  [8,] -1.2075076 #>  [9,] -0.6962112 #> [10,] -0.6947761 #> [11,]  0.7947597 #> [12,]  1.0852859 #> [13,]  0.8157287 #> [14,]  1.3106682 #> [15,]  0.9068501 #> [16,]  0.6301748 #> [17,]  0.8600927 #> [18,]  1.1116811 #> [19,]  0.8820183 #> [20,]  1.0090964 #> [21,] -2.0367487 #> [22,] -1.7103496 #> [23,] -1.9857975 #> [24,] -2.0908219 #> [25,] -1.3902299 #> [26,] -1.6290080 #> [27,] -1.6706863 #> [28,] -1.6537383 #> [29,] -1.9946929 #> [30,] -1.5161591 #>  #> , , 147 #>  #>             [,1] #>  [1,] -1.0277738 #>  [2,] -1.3728439 #>  [3,] -1.2738804 #>  [4,] -1.2352805 #>  [5,] -1.0149481 #>  [6,] -1.7284527 #>  [7,] -1.7453416 #>  [8,] -1.2543799 #>  [9,] -0.7468770 #> [10,] -0.7494235 #> [11,]  0.7627676 #> [12,]  1.0664813 #> [13,]  0.7879038 #> [14,]  1.2980130 #> [15,]  0.8799744 #> [16,]  0.5977712 #> [17,]  0.8305707 #> [18,]  1.0919979 #> [19,]  0.8548854 #> [20,]  0.9872226 #> [21,] -2.0295002 #> [22,] -1.6683205 #> [23,] -1.9720548 #> [24,] -2.0849706 #> [25,] -1.3381088 #> [26,] -1.5816684 #> [27,] -1.6261981 #> [28,] -1.6090457 #> [29,] -1.9682261 #> [30,] -1.4668560 #>  #> , , 148 #>  #>             [,1] #>  [1,] -1.0718036 #>  [2,] -1.4106708 #>  [3,] -1.3238302 #>  [4,] -1.2850350 #>  [5,] -1.0692882 #>  [6,] -1.7585420 #>  [7,] -1.7649337 #>  [8,] -1.3000723 #>  [9,] -0.7972840 #> [10,] -0.8038556 #> [11,]  0.7301038 #> [12,]  1.0472049 #> [13,]  0.7595046 #> [14,]  1.2849018 #> [15,]  0.8524978 #> [16,]  0.5647614 #> [17,]  0.8003883 #> [18,]  1.0717788 #> [19,]  0.8272035 #> [20,]  0.9647987 #> [21,] -2.0201794 #> [22,] -1.6245773 #> [23,] -1.9562459 #> [24,] -2.0769095 #> [25,] -1.2851955 #> [26,] -1.5330995 #> [27,] -1.5802897 #> [28,] -1.5629559 #> [29,] -1.9396099 #> [30,] -1.4164451 #>  #> , , 149 #>  #>             [,1] #>  [1,] -1.1148924 #>  [2,] -1.4466270 #>  [3,] -1.3725287 #>  [4,] -1.3334532 #>  [5,] -1.1228730 #>  [6,] -1.7856224 #>  [7,] -1.7811124 #>  [8,] -1.3444815 #>  [9,] -0.8473608 #> [10,] -0.8579965 #> [11,]  0.6967733 #> [12,]  1.0274573 #> [13,]  0.7305342 #> [14,]  1.2713331 #> [15,]  0.8244224 #> [16,]  0.5311525 #> [17,]  0.7695484 #> [18,]  1.0510237 #> [19,]  0.7989756 #> [20,]  0.9418249 #> [21,] -2.0088074 #> [22,] -1.5792382 #> [23,] -1.9384077 #> [24,] -2.0666591 #> [25,] -1.2316465 #> [26,] -1.4834377 #> [27,] -1.5330892 #> [28,] -1.5155988 #> [29,] -1.9089141 #> [30,] -1.3650761 #>  #> , , 150 #>  #>             [,1] #>  [1,] -1.1569478 #>  [2,] -1.4805941 #>  [3,] -1.4198654 #>  [4,] -1.3804150 #>  [5,] -1.1756014 #>  [6,] -1.8095543 #>  [7,] -1.7937505 #>  [8,] -1.3875028 #>  [9,] -0.8970337 #> [10,] -0.9117676 #> [11,]  0.6627815 #> [12,]  1.0072392 #> [13,]  0.7009965 #> [14,]  1.2573058 #> [15,]  0.7957507 #> [16,]  0.4969523 #> [17,]  0.7380548 #> [18,]  1.0297326 #> [19,]  0.7702048 #> [20,]  0.9183015 #> [21,] -1.9954090 #> [22,] -1.5324262 #> [23,] -1.9185812 #> [24,] -2.0542442 #> [25,] -1.1776202 #> [26,] -1.4328219 #> [27,] -1.4847284 #> [28,] -1.4671075 #> [29,] -1.8762140 #> [30,] -1.3129014 #>  #> , , 151 #>  #>             [,1] #>  [1,] -1.1978760 #>  [2,] -1.5124542 #>  [3,] -1.4657279 #>  [4,] -1.4257983 #>  [5,] -1.2273699 #>  [6,] -1.8302017 #>  [7,] -1.8027264 #>  [8,] -1.4290300 #>  [9,] -0.9462266 #> [10,] -0.9650878 #> [11,]  0.6281347 #> [12,]  0.9865514 #> [13,]  0.6708954 #> [14,]  1.2428184 #> [15,]  0.7664859 #> [16,]  0.4621693 #> [17,]  0.7059115 #> [18,]  1.0079056 #> [19,]  0.7408949 #> [20,]  0.8942292 #> [21,] -1.9800128 #> [22,] -1.4842687 #> [23,] -1.8968115 #> [24,] -2.0396938 #> [25,] -1.1232768 #> [26,] -1.3813941 #> [27,] -1.4353424 #> [28,] -1.4176188 #> [29,] -1.8415896 #> [30,] -1.2600763 #>  #> , , 152 #>  #>             [,1] #>  [1,] -1.2375816 #>  [2,] -1.5420896 #>  [3,] -1.5100027 #>  [4,] -1.4694801 #>  [5,] -1.2780727 #>  [6,] -1.8474323 #>  [7,] -1.8079251 #>  [8,] -1.4689558 #>  [9,] -0.9948612 #> [10,] -1.0178734 #> [11,]  0.5928397 #> [12,]  0.9653949 #> [13,]  0.6402355 #> [14,]  1.2278698 #> [15,]  0.7366313 #> [16,]  0.4268129 #> [17,]  0.6731234 #> [18,]  0.9855431 #> [19,]  0.7110496 #> [20,]  0.8696089 #> [21,] -1.9626512 #> [22,] -1.4348978 #> [23,] -1.8731478 #> [24,] -2.0230407 #> [25,] -1.0687777 #> [26,] -1.3292983 #> [27,] -1.3850693 #> [28,] -1.3672721 #> [29,] -1.8051258 #> [30,] -1.2067580 #>  #> , , 153 #>  #>             [,1] #>  [1,] -1.2759679 #>  [2,] -1.5693835 #>  [3,] -1.5525748 #>  [4,] -1.5113362 #>  [5,] -1.3276019 #>  [6,] -1.8611184 #>  [7,] -1.8092383 #>  [8,] -1.5071721 #>  [9,] -1.0428570 #> [10,] -1.0700383 #> [11,]  0.5569043 #> [12,]  0.9437707 #> [13,]  0.6090219 #> [14,]  1.2124588 #> [15,]  0.7061907 #> [16,]  0.3908934 #> [17,]  0.6396961 #> [18,]  0.9626456 #> [19,]  0.6806734 #> [20,]  0.8444418 #> [21,] -1.9433603 #> [22,] -1.3844495 #> [23,] -1.8476434 #> [24,] -2.0043224 #> [25,] -1.0142842 #> [26,] -1.2766803 #> [27,] -1.3340497 #> [28,] -1.3162092 #> [29,] -1.7669121 #> [30,] -1.1531048 #>  #> , , 154 #>  #>             [,1] #>  [1,] -1.3129373 #>  [2,] -1.5942204 #>  [3,] -1.5933287 #>  [4,] -1.5512417 #>  [5,] -1.3758474 #>  [6,] -1.8711377 #>  [7,] -1.8065661 #>  [8,] -1.5435703 #>  [9,] -1.0901317 #> [10,] -1.1214941 #> [11,]  0.5203369 #> [12,]  0.9216800 #> [13,]  0.5772603 #> [14,]  1.1965843 #> [15,]  0.6751685 #> [16,]  0.3544217 #> [17,]  0.6056355 #> [18,]  0.9392137 #> [19,]  0.6497709 #> [20,]  0.8187293 #> [21,] -1.9221801 #> [22,] -1.3330634 #> [23,] -1.8203554 #> [24,] -1.9835802 #> [25,] -0.9599578 #> [26,] -1.2236869 #> [27,] -1.2824264 #> [28,] -1.2645742 #> [29,] -1.7270425 #> [30,] -1.0992759 #>  #> , , 155 #>  #>             [,1] #>  [1,] -1.3483915 #>  [2,] -1.6164867 #>  [3,] -1.6321482 #>  [4,] -1.5890715 #>  [5,] -1.4226978 #>  [6,] -1.8773739 #>  [7,] -1.7998168 #>  [8,] -1.5780413 #>  [9,] -1.1366006 #> [10,] -1.1721502 #> [11,]  0.4831468 #> [12,]  0.8991242 #> [13,]  0.5449566 #> [14,]  1.1802451 #> [15,]  0.6435696 #> [16,]  0.3174100 #> [17,]  0.5709485 #> [18,]  0.9152485 #> [19,]  0.6183473 #> [20,]  0.7924732 #> [21,] -1.8991545 #> [22,] -1.2808821 #> [23,] -1.7913449 #> [24,] -1.9608595 #> [25,] -0.9059590 #> [26,] -1.1704658 #> [27,] -1.2303434 #> [28,] -1.2125122 #> [29,] -1.6856155 #> [30,] -1.0454307 #>  #> , , 156 #>  #>             [,1] #>  [1,] -1.3822315 #>  [2,] -1.6360708 #>  [3,] -1.6689167 #>  [4,] -1.6247007 #>  [5,] -1.4680399 #>  [6,] -1.8797176 #>  [7,] -1.7889086 #>  [8,] -1.6104762 #>  [9,] -1.1821776 #> [10,] -1.2219139 #> [11,]  0.4453443 #> [12,]  0.8761047 #> [13,]  0.5121177 #> [14,]  1.1634403 #> [15,]  0.6113992 #> [16,]  0.2798712 #> [17,]  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[7,] -1.66987209 #>  [8,] -1.73834234 #>  [9,] -1.39355171 #> [10,] -1.45397145 #> [11,]  0.24756750 #> [12,]  0.75411740 #> [13,]  0.34017292 #> [14,]  1.07240192 #> [15,]  0.44220533 #> [16,]  0.08479243 #> [17,]  0.35015560 #> [18,]  0.76033682 #> [19,]  0.41920939 #> [20,]  0.62366572 #> [21,] -1.72515483 #> [22,] -0.95938715 #> [23,] -1.58499907 #> [24,] -1.78604485 #> [25,] -0.59753915 #> [26,] -0.85455873 #> [27,] -0.91633600 #> [28,] -0.89936072 #> [29,] -1.41034896 #> [30,] -0.73078781 #>  #> , , 162 #>  #>              [,1] #>  [1,] -1.54583174 #>  [2,] -1.69141471 #>  [3,] -1.83999159 #>  [4,] -1.78537266 #>  [5,] -1.70196118 #>  [6,] -1.80694604 #>  [7,] -1.63291485 #>  [8,] -1.75631860 #>  [9,] -1.43187992 #> [10,] -1.49633421 #> [11,]  0.20635811 #> [12,]  0.72835784 #> [13,]  0.30429913 #> [14,]  1.05278664 #> [15,]  0.40675272 #> [16,]  0.04441943 #> [17,]  0.31134327 #> [18,]  0.73268411 #> [19,]  0.38432242 #> [20,]  0.59368508 #> [21,] -1.69074069 #> [22,] 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#>  [5,] -1.7626239 #>  [6,] -1.7480259 #>  [7,] -1.5458097 #>  [8,] -1.7838717 #>  [9,] -1.5038365 #> [10,] -1.5761941 #> [11,]  0.1224178 #> [12,]  0.6754988 #> [13,]  0.2311544 #> [14,]  1.0121451 #> [15,]  0.3343085 #> [16,] -0.0375266 #> [17,]  0.2321086 #> [18,]  0.6758322 #> [19,]  0.3131727 #> [20,]  0.5321827 #> [21,] -1.6178879 #> [22,] -0.8000323 #> [23,] -1.4646212 #> [24,] -1.6768301 #> [25,] -0.4598282 #> [26,] -0.7051546 #> [27,] -0.7647998 #> [28,] -0.7487361 #> [29,] -1.2607738 #> [30,] -0.5855732 #>  #> , , 165 #>  #>              [,1] #>  [1,] -1.59791900 #>  [2,] -1.67499828 #>  [3,] -1.88865976 #>  [4,] -1.82628487 #>  [5,] -1.78919235 #>  [6,] -1.71189999 #>  [7,] -1.49571908 #>  [8,] -1.79326132 #>  [9,] -1.53727421 #> [10,] -1.61348382 #> [11,]  0.07972531 #> [12,]  0.64840605 #> [13,]  0.19390892 #> [14,]  0.99111852 #> [15,]  0.29733902 #> [16,] -0.07905492 #> [17,]  0.19171700 #> [18,]  0.64664055 #> [19,]  0.27693055 #> [20,]  0.50067269 #> [21,] -1.57960192 #> [22,] -0.74812352 #> [23,] -1.42252804 #> [24,] -1.63769650 #> [25,] -0.41722323 #> [26,] -0.65749736 #> [27,] -0.71600963 #> [28,] -0.70032000 #> [29,] -1.20996680 #> [30,] -0.53986755 #>  #> , , 166 #>  #>              [,1] #>  [1,] -1.61026251 #>  [2,] -1.66249049 #>  [3,] -1.89871997 #>  [4,] -1.83335714 #>  [5,] -1.81310316 #>  [6,] -1.67132470 #>  [7,] -1.44133500 #>  [8,] -1.79960774 #>  [9,] -1.56889108 #> [10,] -1.64887472 #> [11,]  0.03657884 #> [12,]  0.62087604 #> [13,]  0.15623309 #> [14,]  0.96962149 #> [15,]  0.25988734 #> [16,] -0.12092152 #> [17,]  0.15083164 #> [18,]  0.61694400 #> [19,]  0.24025853 #> [20,]  0.46866539 #> [21,] -1.54018294 #> [22,] -0.69706277 #> [23,] -1.37960875 #> [24,] -1.59733940 #> [25,] -0.37644638 #> [26,] -0.61110858 #> [27,] -0.66829107 #> [28,] -0.65300919 #> [29,] -1.15889832 #> [30,] -0.49570843 #>  #> , , 167 #>  #>              [,1] #>  [1,] -1.61995357 #>  [2,] -1.64637201 #>  [3,] -1.90553984 #>  [4,] -1.83698612 #>  [5,] -1.83424730 #>  [6,] -1.62631423 #>  [7,] -1.38272736 #>  [8,] -1.80282765 #>  [9,] -1.59859204 #> [10,] -1.68226296 #> [11,] -0.00699924 #> [12,]  0.59291286 #> [13,]  0.11814179 #> [14,]  0.94765424 #> [15,]  0.22196659 #> [16,] -0.16310084 #> [17,]  0.10947064 #> [18,]  0.58674736 #> [19,]  0.20316866 #> [20,]  0.43616807 #> [21,] -1.49971429 #> [22,] -0.64699131 #> [23,] -1.33596095 #> [24,] -1.55584786 #> [25,] -0.33759086 #> [26,] -0.56609627 #> [27,] -0.62176252 #> [28,] -0.60692088 #> [29,] -1.10769729 #> [30,] -0.45320168 #>  #> , , 168 #>  #>              [,1] #>  [1,] -1.62691148 #>  [2,] -1.62660003 #>  [3,] -1.90903086 #>  [4,] -1.83708406 #>  [5,] -1.85251845 #>  [6,] -1.57689812 #>  [7,] -1.31998340 #>  [8,] -1.80284266 #>  [9,] -1.62628266 #> [10,] -1.71354515 #> [11,] -0.05098530 #> [12,]  0.56452092 #> [13,]  0.07965081 #> [14,]  0.92521719 #> [15,]  0.18359075 #> [16,] -0.20556600 #> [17,]  0.06765335 #> [18,]  0.55605583 #> [19,]  0.16567373 #> [20,]  0.40318855 #> [21,] -1.45828185 #> [22,] -0.59804639 #> [23,] -1.29168406 #> [24,] -1.51331368 #> [25,] -0.30073959 #> [26,] -0.52256097 #> [27,] -0.57653617 #> [28,] -0.56216582 #> [29,] -1.05649281 #> [30,] -0.41244395 #>  #> , , 169 #>  #>              [,1] #>  [1,] -1.63105951 #>  [2,] -1.60314110 #>  [3,] -1.90910991 #>  [4,] -1.83356976 #>  [5,] -1.86781341 #>  [6,] -1.52312183 #>  [7,] -1.25320806 #>  [8,] -1.79957982 #>  [9,] -1.65186936 #> [10,] -1.74261867 #> [11,] -0.09535434 #> [12,]  0.53570495 #> [13,]  0.04077688 #> [14,]  0.90231094 #> [15,]  0.14477474 #> [16,] -0.24828876 #> [17,]  0.02540029 #> [18,]  0.52487509 #> [19,]  0.12778729 #> [20,]  0.36973529 #> [21,] -1.41597382 #> [22,] -0.55036048 #> [23,] -1.24687902 #> [24,] -1.46983117 #> [25,] -0.26596450 #> [26,] -0.48059512 #> [27,] -0.53271735 #> [28,] -0.51884763 #> [29,] -1.00541368 #> [30,] -0.37352201 #>  #> , , 170 #>  #>               [,1] #>  [1,] -1.632325321 #>  [2,] -1.575971725 #>  [3,] -1.905699699 #>  [4,] -1.826369194 #>  [5,] -1.880032569 #>  [6,] -1.465047233 #>  [7,] -1.182524254 #>  [8,] -1.792972115 #>  [9,] -1.675259751 #> [10,] -1.769381995 #> [11,] -0.140080006 #> [12,]  0.506470015 #> [13,]  0.001537676 #> [14,]  0.878936273 #> [15,]  0.105534379 #> [16,] -0.291239523 #> [17,] -0.017266772 #> [18,]  0.493211317 #> [19,]  0.089523686 #> [20,]  0.335817402 #> [21,] -1.372880567 #> [22,] -0.504060727 #> [23,] -1.201648006 #> [24,] -1.425496993 #> [25,] -0.233325908 #> [26,] -0.440282461 #> [27,] -0.490403945 #> [28,] -0.477062183 #> [29,] -0.954588003 #> [30,] -0.336512030 #>  #> , , 171 #>  #>              [,1] #>  [1,] -1.63064142 #>  [2,] -1.54507883 #>  [3,] -1.89872930 #>  [4,] -1.81541602 #>  [5,] -1.88908043 #>  [6,] -1.40275304 #>  [7,] -1.10807311 #>  [8,] -1.78295894 #>  [9,] -1.69636292 #> [10,] -1.79373502 #> [11,] -0.18513452 #> [12,]  0.47682157 #> [13,] -0.03804814 #> [14,]  0.85509421 #> [15,]  0.06588648 #> [16,] -0.33438729 #> [17,] -0.06032482 #> [18,]  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#> [28,] -0.083444529 #> [29,] -0.335511989 #> [30,] -0.032000612 #>  #> , , 185 #>  #>                [,1] #>  [1,] -1.274667e+00 #>  [2,] -7.429481e-01 #>  [3,] -1.407050e+00 #>  [4,] -1.253937e+00 #>  [5,] -1.643222e+00 #>  [6,] -1.736635e-01 #>  [7,]  2.082192e-01 #>  [8,] -1.270542e+00 #>  [9,] -1.707188e+00 #> [10,] -1.832077e+00 #> [11,] -8.313682e-01 #> [12,]  2.238692e-02 #> [13,] -6.156733e-01 #> [14,]  4.733974e-01 #> [15,] -5.200656e-01 #> [16,] -9.383947e-01 #> [17,] -6.881100e-01 #> [18,] -3.375257e-02 #> [19,] -5.173090e-01 #> [20,] -2.202542e-01 #> [21,] -6.976305e-01 #> [22,] -3.837306e-02 #> [23,] -5.418085e-01 #> [24,] -7.281999e-01 #> [25,] -3.033678e-05 #> [26,] -5.831512e-02 #> [27,] -7.352629e-02 #> [28,] -6.923181e-02 #> [29,] -3.018774e-01 #> [30,] -2.406884e-02 #>  #> , , 186 #>  #>               [,1] #>  [1,] -1.225205825 #>  [2,] -0.663017811 #>  [3,] -1.344005736 #>  [4,] -1.185615278 #>  [5,] -1.597524924 #>  [6,] -0.069489818 #>  [7,]  0.310342029 #>  [8,] -1.207944715 #>  [9,] -1.685136890 #> [10,] -1.810371538 #> [11,] -0.877014122 #> [12,] -0.012511246 #> [13,] -0.657489337 #> [14,]  0.442846732 #> [15,] -0.563083058 #> [16,] -0.979810296 #> [17,] -0.733348804 #> [18,] -0.071819209 #> [19,] -0.558940840 #> [20,] -0.259747918 #> [21,] -0.655108376 #> [22,] -0.024691367 #> [23,] -0.503465333 #> [24,] -0.684273587 #> [25,]  0.001401089 #> [26,] -0.046853701 #> [27,] -0.060426731 #> [28,] -0.056619176 #> [29,] -0.270047292 #> [30,] -0.017459375 #>  #> , , 187 #>  #>               [,1] #>  [1,] -1.172708013 #>  [2,] -0.580884117 #>  [3,] -1.277524735 #>  [4,] -1.113948862 #>  [5,] -1.548084244 #>  [6,]  0.035286887 #>  [7,]  0.411709327 #>  [8,] -1.142208665 #>  [9,] -1.659830798 #> [10,] -1.785157247 #> [11,] -0.922341361 #> [12,] -0.047672538 #> [13,] -0.699204669 #> [14,]  0.411883986 #> [15,] -0.606089956 #> [16,] -1.020734534 #> [17,] -0.778423268 #> [18,] -0.110167530 #> [19,] -0.600567516 #> [20,] -0.299430185 #> [21,] 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#>  [3,] -1.1346912159 #>  [4,] -0.9611443359 #>  [5,] -1.4381753225 #>  [6,]  0.2452232853 #>  [7,]  0.6106380771 #>  [8,] -1.0017800681 #>  [9,] -1.5994168643 #> [10,] -1.7241432170 #> [11,] -1.0118259627 #> [12,] -0.1187271076 #> [13,] -0.7821811739 #> [14,]  0.3487493621 #> [15,] -0.6919259197 #> [16,] -1.1008905323 #> [17,] -0.8678905777 #> [18,] -0.1876334840 #> [19,] -0.6836786000 #> [20,] -0.3792612785 #> [21,] -0.5329376643 #> [22,]  0.0038578354 #> [23,] -0.3958474930 #> [24,] -0.5581503542 #> [25,]  0.0003470434 #> [26,] -0.0198196267 #> [27,] -0.0299143414 #> [28,] -0.0272878364 #> [29,] -0.1857439367 #> [30,] -0.0039231588 #>  #> , , 190 #>  #>               [,1] #>  [1,] -0.997798784 #>  [2,] -0.323435074 #>  [3,] -1.058591305 #>  [4,] -0.880323823 #>  [5,] -1.377839164 #>  [6,]  0.349647145 #>  [7,]  0.707422316 #>  [8,] -0.927348900 #>  [9,] -1.564310501 #> [10,] -1.688335866 #> [11,] -1.055872952 #> [12,] -0.154590043 #> [13,] -0.823363411 #> [14,]  0.316592203 #> [15,] -0.734678858 #> [16,] -1.140010272 #> [17,] -0.912185746 #> [18,] -0.226711025 #> [19,] -0.725096950 #> [20,] -0.419358087 #> [21,] -0.494283903 #> [22,]  0.009479061 #> [23,] -0.362653212 #> [24,] -0.518278482 #> [25,] -0.001107385 #> [26,] -0.012771687 #> [27,] -0.022263044 #> [28,] -0.019918983 #> [29,] -0.161443908 #> [30,] -0.000899878 #>  #> , , 191 #>  #>               [,1] #>  [1,] -0.934013696 #>  [2,] -0.234722063 #>  [3,] -0.979559704 #>  [4,] -0.796793262 #>  [5,] -1.314024159 #>  [6,]  0.453205384 #>  [7,]  0.801900483 #>  [8,] -0.850301453 #>  [9,] -1.525952917 #> [10,] -1.649004974 #> [11,] -1.099380646 #> [12,] -0.190655392 #> [13,] -0.864287140 #> [14,]  0.284052443 #> [15,] -0.777269003 #> [16,] -1.178414779 #> [17,] -0.956121254 #> [18,] -0.265990037 #> [19,] -0.766378075 #> [20,] -0.459539355 #> [21,] -0.456791524 #> [22,]  0.013322531 #> [23,] -0.330887609 #> [24,] -0.479622786 #> [25,] -0.002747601 #> [26,] -0.006434192 #> [27,] -0.015636797 #> [28,] 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#> [21,] -0.3519563177 #> [22,]  0.0154775611 #> [23,] -0.2445730767 #> [24,] -0.3716456780 #> [25,] -0.0064200689 #> [26,]  0.0101423051 #> [27,] -0.0002777313 #> [28,]  0.0016307816 #> [29,] -0.0832143970 #> [30,]  0.0092546984 #>  #> , , 195 #>  #>               [,1] #>  [1,] -0.654717124 #>  [2,]  0.127658222 #>  [3,] -0.637495545 #>  [4,] -0.439656403 #>  [5,] -1.026123521 #>  [6,]  0.851070068 #>  [7,]  1.149084580 #>  [8,] -0.519361854 #>  [9,] -1.340593576 #> [10,] -1.456981292 #> [11,] -1.266834006 #> [12,] -0.336592748 #> [13,] -1.024536080 #> [14,]  0.150247593 #> [15,] -0.945162858 #> [16,] -1.323698613 #> [17,] -1.127206109 #> [18,] -0.424660108 #> [19,] -0.929403034 #> [20,] -0.620522123 #> [21,] -0.319758884 #> [22,]  0.013566486 #> [23,] -0.218897974 #> [24,] -0.338520278 #> [25,] -0.006409640 #> [26,]  0.015507054 #> [27,]  0.003928731 #> [28,]  0.005925706 #> [29,] -0.068273093 #> [30,]  0.012437277 #>  #> , , 196 #>  #>               [,1] #>  [1,] -0.579588113 #>  [2,]  0.218723803 #>  [3,] -0.546451488 #>  [4,] -0.345755931 #>  [5,] -0.946638871 #>  [6,]  0.944507768 #>  [7,]  1.226342814 #>  [8,] -0.431896082 #>  [9,] -1.286499353 #> [10,] -1.400522808 #> [11,] -1.306747345 #> [12,] -0.373402769 #> [13,] -1.063512522 #> [14,]  0.115934745 #> [15,] -0.986299903 #> [16,] -1.357633962 #> [17,] -1.168537522 #> [18,] -0.464592677 #> [19,] -0.969443835 #> [20,] -0.660676496 #> [21,] -0.289022228 #> [22,]  0.010619663 #> [23,] -0.194804070 #> [24,] -0.306915328 #> [25,] -0.005362121 #> [26,]  0.021134833 #> [27,]  0.007997375 #> [28,]  0.010170296 #> [29,] -0.055089110 #> [30,]  0.016350367 #>  #> , , 197 #>  #>               [,1] #>  [1,] -0.502668432 #>  [2,]  0.309386112 #>  [3,] -0.453621853 #>  [4,] -0.250507675 #>  [5,] -0.864456170 #>  [6,]  1.034767317 #>  [7,]  1.299081024 #>  [8,] -0.342960082 #>  [9,] -1.229428481 #> [10,] -1.340809061 #> [11,] -1.345755026 #> [12,] -0.410303182 #> [13,] -1.101961487 #> [14,]  0.081299160 #> [15,] 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#>  [9,] -1.041206571 #> [10,] -1.143009567 #> [11,] -1.456697852 #> [12,] -0.521330611 #> [13,] -1.213657399 #> [14,] -0.024421038 #> [15,] -1.146102498 #> [16,] -1.481979518 #> [17,] -1.326371359 #> [18,] -0.624570303 #> [19,] -1.125530250 #> [20,] -0.819917602 #> [21,] -0.181462697 #> [22,] -0.007672129 #> [23,] -0.114288475 #> [24,] -0.196447550 #> [25,]  0.014285658 #> [26,]  0.050616236 #> [27,]  0.027032430 #> [28,]  0.030850113 #> [29,] -0.018480015 #> [30,]  0.044187739 #>  #>  #> $original_grids #>       [,1]      [,2]       [,3]       [,4]      [,5]     [,6]      [,7] #>  [1,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [2,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [3,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [4,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [5,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [6,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [7,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [8,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [9,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [10,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [11,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [12,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [13,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [14,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [15,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [16,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [17,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [18,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [19,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [20,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [21,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [22,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [23,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [24,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [25,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [26,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [27,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [28,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [29,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [30,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>            [,8]      [,9]     [,10]    [,11]     [,12]     [,13]     [,14] #>  [1,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [2,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [3,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [4,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [5,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [6,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [7,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [8,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [9,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [10,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [11,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [12,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [13,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [14,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [15,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [16,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [17,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [18,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [19,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [20,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [21,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [22,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [23,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [24,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [25,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [26,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [27,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [28,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [29,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [30,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>           [,15]     [,16]     [,17]     [,18]     [,19]     [,20]     [,21] #>  [1,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [2,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [3,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [4,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [5,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [6,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [7,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [8,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [9,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [10,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [11,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [12,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [13,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [14,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [15,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [16,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [17,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [18,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [19,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [20,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [21,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [22,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [23,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [24,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [25,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [26,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [27,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [28,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [29,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [30,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>           [,22]     [,23]     [,24]     [,25]     [,26]     [,27]     [,28] #>  [1,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [2,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [3,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [4,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [5,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [6,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [7,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [8,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [9,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [10,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [11,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [12,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [13,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [14,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [15,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [16,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [17,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [18,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [19,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [20,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [21,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [22,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [23,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [24,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [25,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [26,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [27,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [28,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [29,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [30,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>           [,29]     [,30]     [,31]     [,32]    [,33]    [,34]    [,35] #>  [1,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [2,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [3,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [4,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [5,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [6,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [7,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [8,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [9,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [10,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [11,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [12,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [13,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [14,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [15,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [16,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [17,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [18,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [19,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [20,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [21,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [22,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [23,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [24,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [25,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [26,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [27,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [28,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [29,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [30,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>          [,36]    [,37]   [,38]    [,39]    [,40]    [,41]    [,42]    [,43] #>  [1,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [2,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [3,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [4,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [5,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [6,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [7,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [8,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [9,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [10,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [11,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [12,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [13,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [14,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [15,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [16,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [17,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [18,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [19,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [20,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [21,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [22,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [23,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [24,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [25,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [26,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [27,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [28,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [29,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [30,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>          [,44]    [,45]    [,46]    [,47]    [,48]    [,49]    [,50]   [,51] #>  [1,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [2,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [3,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [4,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [5,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [6,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [7,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [8,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [9,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [10,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [11,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [12,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [13,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [14,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [15,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [16,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [17,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [18,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [19,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [20,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [21,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [22,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [23,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [24,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [25,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [26,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [27,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [28,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [29,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [30,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>          [,52]    [,53]    [,54]    [,55]    [,56]    [,57]    [,58]   [,59] #>  [1,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [2,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [3,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [4,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [5,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [6,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [7,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [8,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [9,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [10,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [11,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [12,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [13,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [14,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [15,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [16,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [17,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [18,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [19,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [20,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [21,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [22,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [23,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [24,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [25,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [26,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [27,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [28,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [29,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [30,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>          [,60]    [,61]    [,62]    [,63]    [,64]    [,65]    [,66]    [,67] #>  [1,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [2,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [3,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [4,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [5,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [6,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [7,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [8,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [9,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [10,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [11,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [12,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [13,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [14,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [15,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [16,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [17,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [18,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [19,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [20,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [21,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [22,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [23,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [24,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [25,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [26,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [27,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [28,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [29,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [30,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>          [,68]    [,69]    [,70]    [,71]    [,72]    [,73]    [,74]    [,75] #>  [1,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [2,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [3,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [4,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [5,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [6,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [7,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [8,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [9,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [10,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [11,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [12,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [13,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [14,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [15,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [16,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [17,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [18,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [19,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [20,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [21,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [22,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [23,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [24,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [25,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [26,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [27,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [28,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [29,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [30,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>          [,76]    [,77]    [,78]    [,79]   [,80]    [,81]    [,82]    [,83] #>  [1,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [2,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [3,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [4,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [5,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [6,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [7,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [8,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [9,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [10,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [11,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [12,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [13,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [14,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [15,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [16,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [17,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [18,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [19,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [20,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [21,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [22,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [23,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [24,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [25,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [26,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [27,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [28,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [29,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [30,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>          [,84]    [,85]    [,86]    [,87]   [,88]    [,89]    [,90]    [,91] #>  [1,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [2,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [3,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [4,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [5,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [6,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [7,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [8,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [9,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [10,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [11,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [12,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [13,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [14,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [15,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [16,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [17,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [18,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [19,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [20,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [21,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [22,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [23,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [24,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [25,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [26,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [27,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [28,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [29,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [30,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>          [,92]    [,93]    [,94]    [,95]    [,96]    [,97]    [,98]    [,99] #>  [1,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [2,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [3,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [4,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [5,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [6,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [7,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [8,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [9,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [10,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [11,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [12,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [13,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [14,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [15,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [16,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [17,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [18,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [19,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [20,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [21,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [22,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [23,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [24,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [25,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [26,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [27,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [28,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [29,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [30,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>         [,100]  [,101]   [,102]   [,103]   [,104]   [,105]   [,106]   [,107] #>  [1,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [2,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [3,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [4,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [5,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [6,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [7,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [8,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [9,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [10,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [11,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [12,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [13,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [14,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [15,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [16,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [17,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [18,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [19,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [20,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [21,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [22,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [23,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [24,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [25,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [26,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [27,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [28,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [29,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [30,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>         [,108]  [,109]   [,110]   [,111]   [,112]   [,113]   [,114]   [,115] #>  [1,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [2,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [3,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [4,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [5,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [6,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [7,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [8,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [9,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [10,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [11,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [12,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [13,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [14,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [15,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [16,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [17,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [18,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [19,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [20,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [21,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [22,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [23,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [24,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [25,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [26,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [27,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [28,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [29,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [30,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>         [,116]  [,117]   [,118]   [,119]   [,120]   [,121]   [,122]   [,123] #>  [1,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [2,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [3,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [4,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [5,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [6,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [7,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [8,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [9,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [10,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [11,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [12,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [13,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [14,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [15,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [16,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [17,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [18,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [19,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [20,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [21,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [22,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [23,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [24,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [25,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [26,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [27,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [28,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [29,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [30,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>         [,124]   [,125]   [,126]   [,127]   [,128]   [,129]  [,130]   [,131] #>  [1,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [2,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [3,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [4,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [5,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [6,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [7,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [8,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [9,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [10,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [11,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [12,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [13,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [14,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [15,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [16,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [17,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [18,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [19,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [20,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [21,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [22,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [23,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [24,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [25,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [26,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [27,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [28,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [29,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [30,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>         [,132]   [,133]   [,134]   [,135]   [,136]   [,137]  [,138]   [,139] #>  [1,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [2,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [3,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [4,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [5,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [6,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [7,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [8,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [9,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [10,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [11,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [12,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [13,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [14,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [15,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [16,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [17,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [18,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [19,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [20,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [21,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [22,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [23,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [24,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [25,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [26,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [27,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [28,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [29,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [30,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>         [,140]   [,141]   [,142]   [,143]   [,144]   [,145] [,146]   [,147] #>  [1,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [2,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [3,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [4,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [5,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [6,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [7,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [8,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [9,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [10,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [11,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [12,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [13,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [14,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [15,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [16,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [17,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [18,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [19,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [20,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [21,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [22,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [23,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [24,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [25,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [26,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [27,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [28,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [29,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [30,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>         [,148]   [,149]   [,150]   [,151]   [,152]   [,153]   [,154]   [,155] #>  [1,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [2,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [3,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [4,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [5,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [6,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [7,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [8,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [9,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [10,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [11,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [12,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [13,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [14,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [15,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [16,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [17,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [18,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [19,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [20,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [21,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [22,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [23,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [24,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [25,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [26,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [27,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [28,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [29,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [30,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>         [,156]   [,157]   [,158]  [,159]   [,160]   [,161]   [,162]   [,163] #>  [1,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [2,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [3,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [4,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [5,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [6,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [7,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [8,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [9,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [10,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [11,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [12,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [13,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [14,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [15,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [16,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [17,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [18,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [19,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [20,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [21,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [22,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [23,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [24,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [25,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [26,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [27,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [28,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [29,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [30,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>         [,164]   [,165]   [,166]  [,167]   [,168]   [,169]   [,170]   [,171] #>  [1,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [2,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [3,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [4,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [5,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [6,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [7,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [8,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [9,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [10,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [11,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [12,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [13,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [14,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [15,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [16,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [17,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [18,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [19,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [20,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [21,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [22,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [23,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [24,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [25,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [26,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [27,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [28,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [29,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [30,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>         [,172]   [,173]   [,174]  [,175]   [,176]   [,177]   [,178]   [,179] #>  [1,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [2,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [3,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [4,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [5,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [6,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [7,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [8,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [9,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [10,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [11,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [12,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [13,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [14,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [15,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [16,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [17,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [18,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [19,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [20,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [21,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [22,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [23,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [24,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [25,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [26,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [27,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [28,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [29,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [30,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>         [,180]   [,181]   [,182]   [,183]   [,184]   [,185]   [,186]   [,187] #>  [1,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [2,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [3,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [4,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [5,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [6,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [7,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [8,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [9,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [10,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [11,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [12,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [13,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [14,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [15,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [16,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [17,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [18,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [19,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [20,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [21,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [22,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [23,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [24,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [25,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [26,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [27,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [28,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [29,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [30,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>       [,188]   [,189]   [,190]   [,191]   [,192]   [,193]   [,194]   [,195] #>  [1,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [2,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [3,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [4,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [5,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [6,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [7,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [8,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [9,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [10,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [11,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [12,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [13,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [14,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [15,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [16,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [17,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [18,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [19,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [20,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [21,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [22,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [23,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [24,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [25,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [26,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [27,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [28,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [29,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [30,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>        [,196]   [,197]   [,198]   [,199]   [,200] #>  [1,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [2,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [3,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [4,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [5,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [6,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [7,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [8,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [9,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [10,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [11,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [12,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [13,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [14,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [15,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [16,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [17,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [18,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [19,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [20,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [21,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [22,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [23,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [24,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [25,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [26,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [27,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [28,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [29,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [30,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  #> $aligned_curves #> , , 1 #>  #>               [,1] #>  [1,]  0.044037928 #>  [2,] -0.003589190 #>  [3,]  0.042949160 #>  [4,] -0.004056012 #>  [5,] -0.016555706 #>  [6,]  0.040463764 #>  [7,]  0.082490080 #>  [8,]  0.067859664 #>  [9,]  0.019317344 #> [10,] -0.010674987 #> [11,] -0.349207475 #> [12,] -0.283425857 #> [13,] -0.262359012 #> [14,] -0.309079280 #> [15,] -0.325655713 #> [16,] -0.279267180 #> [17,] -0.303933532 #> [18,] -0.353684631 #> [19,] -0.259111966 #> [20,] -0.272116467 #> [21,]  0.143951289 #> [22,]  0.020859321 #> [23,]  0.086742558 #> [24,]  0.025595473 #> [25,]  0.146633932 #> [26,]  0.160713308 #> [27,]  0.092579844 #> [28,]  0.028069376 #> [29,]  0.025800806 #> [30,]  0.026730680 #>  #> , , 2 #>  #>              [,1] #>  [1,]  0.07242614 #>  [2,]  0.02820462 #>  [3,]  0.07701022 #>  [4,]  0.02704986 #>  [5,]  0.01514741 #>  [6,]  0.07668968 #>  [7,]  0.11713223 #>  [8,]  0.10109675 #>  [9,]  0.04823389 #> [10,]  0.01952885 #> [11,] -0.32817804 #> [12,] -0.26372971 #> [13,] -0.24113453 #> [14,] -0.29180895 #> [15,] -0.30522497 #> [16,] -0.25802492 #> [17,] -0.28323475 #> [18,] -0.33514118 #> [19,] -0.23666152 #> [20,] -0.25294596 #> [21,]  0.19784714 #> [22,]  0.08115150 #> [23,]  0.14311545 #> [24,]  0.08288095 #> [25,]  0.20669338 #> [26,]  0.22514442 #> [27,]  0.15632235 #> [28,]  0.09226318 #> [29,]  0.08751084 #> [30,]  0.08974213 #>  #> , , 3 #>  #>              [,1] #>  [1,]  0.10100063 #>  [2,]  0.06026461 #>  [3,]  0.11129446 #>  [4,]  0.05844114 #>  [5,]  0.04712487 #>  [6,]  0.11318125 #>  [7,]  0.15198863 #>  [8,]  0.13451425 #>  [9,]  0.07735204 #> [10,]  0.04997669 #> [11,] -0.30680827 #> [12,] -0.24386524 #> [13,] -0.21965563 #> [14,] -0.27441120 #> [15,] -0.28447700 #> [16,] -0.23649566 #> [17,] -0.26221547 #> [18,] -0.31634916 #> [19,] -0.21400140 #> [20,] -0.23356434 #> [21,]  0.25133378 #> [22,]  0.14104578 #> [23,]  0.19910681 #> [24,]  0.13983797 #> [25,]  0.26624596 #> [26,]  0.28905404 #> [27,]  0.21960806 #> [28,]  0.15606480 #> [29,]  0.14884008 #> [30,]  0.15236256 #>  #> , , 4 #>  #>              [,1] #>  [1,]  0.12975066 #>  [2,]  0.09255983 #>  [3,]  0.14577527 #>  [4,]  0.09009160 #>  [5,]  0.07935324 #>  [6,]  0.14990079 #>  [7,]  0.18702409 #>  [8,]  0.16808577 #>  [9,]  0.10665456 #> [10,]  0.08065022 #> [11,] -0.28509073 #> [12,] -0.22371275 #> [13,] -0.19792270 #> [14,] -0.25666813 #> [15,] -0.26341293 #> [16,] -0.21466810 #> [17,] -0.24088036 #> [18,] -0.29721476 #> [19,] -0.19110410 #> [20,] -0.21390637 #> [21,]  0.30437048 #> [22,]  0.20048437 #> [23,]  0.25466980 #> [24,]  0.19642153 #> [25,]  0.32523446 #> [26,]  0.35237859 #> [27,]  0.28237394 #> [28,]  0.21941034 #> [29,]  0.20973178 #> [30,]  0.21453022 #>  #> , , 5 #>  #>             [,1] #>  [1,]  0.1586507 #>  [2,]  0.1250594 #>  [3,]  0.1804261 #>  [4,]  0.1219792 #>  [5,]  0.1118091 #>  [6,]  0.1868108 #>  [7,]  0.2222036 #>  [8,]  0.2017850 #>  [9,]  0.1361253 #> [10,]  0.1115366 #> [11,] -0.2628093 #> [12,] 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0.73801703 #>  [7,] 0.74343825 #>  [8,] 0.70304120 #>  [9,] 0.58402429 #> [10,] 0.58493335 #> [11,] 0.10925367 #> [12,] 0.12697418 #> [13,] 0.18327025 #> [14,] 0.05734821 #> [15,] 0.11333214 #> [16,] 0.17298889 #> [17,] 0.14145463 #> [18,] 0.04699090 #> [19,] 0.20613529 #> [20,] 0.13316921 #> [21,] 1.05704684 #> [22,] 1.04274488 #> [23,] 1.04734919 #> [24,] 1.01315792 #> [25,] 1.14679669 #> [26,] 1.23548490 #> [27,] 1.16607611 #> [28,] 1.11940654 #> [29,] 1.07928905 #> [30,] 1.09746927 #>  #> , , 21 #>  #>             [,1] #>  [1,] 0.62085141 #>  [2,] 0.64699802 #>  [3,] 0.73411167 #>  [4,] 0.64106891 #>  [5,] 0.64079842 #>  [6,] 0.77297562 #>  [7,] 0.77626351 #>  [8,] 0.73491226 #>  [9,] 0.61324127 #> [10,] 0.61604802 #> [11,] 0.13585016 #> [12,] 0.15007405 #> [13,] 0.20836859 #> [14,] 0.07843478 #> [15,] 0.13854974 #> [16,] 0.19867991 #> [17,] 0.16707710 #> [18,] 0.07026082 #> [19,] 0.23207396 #> [20,] 0.15624091 #> [21,] 1.09602962 #> [22,] 1.08585513 #> [23,] 1.08853860 #> [24,] 1.05644276 #> [25,] 1.18777905 #> [26,] 1.27959261 #> [27,] 1.21081732 #> [28,] 1.16554402 #> [29,] 1.12438860 #> [30,] 1.14273352 #>  #> , , 22 #>  #>             [,1] #>  [1,] 0.64851029 #>  [2,] 0.67814278 #>  [3,] 0.76712139 #>  [4,] 0.67259475 #>  [5,] 0.67303748 #>  [6,] 0.80752622 #>  [7,] 0.80866262 #>  [8,] 0.76633347 #>  [9,] 0.64217166 #> [10,] 0.64691023 #> [11,] 0.16262992 #> [12,] 0.17324101 #> [13,] 0.23351792 #> [14,] 0.09957158 #> [15,] 0.16385624 #> [16,] 0.22448109 #> [17,] 0.19277701 #> [18,] 0.09362500 #> [19,] 0.25808518 #> [20,] 0.17939089 #> [21,] 1.13385639 #> [22,] 1.12754306 #> [23,] 1.12850749 #> [24,] 1.09853950 #> [25,] 1.22725714 #> [26,] 1.32207813 #> [27,] 1.25400264 #> [28,] 1.21016107 #> [29,] 1.16810247 #> [30,] 1.18651176 #>  #> , , 23 #>  #>            [,1] #>  [1,] 0.6758888 #>  [2,] 0.7089486 #>  [3,] 0.7997974 #>  [4,] 0.7038308 #>  [5,] 0.7050416 #>  [6,] 0.8416392 #>  [7,] 0.8405535 #>  [8,] 0.7973904 #>  [9,] 0.6708881 #> [10,] 0.6775729 #> [11,] 0.1894920 #> [12,] 0.1964845 #> [13,] 0.2587410 #> [14,] 0.1208492 #> [15,] 0.1892929 #> [16,] 0.2503303 #> [17,] 0.2185523 #> [18,] 0.1170962 #> [19,] 0.2841186 #> [20,] 0.2025936 #> [21,] 1.1703653 #> [22,] 1.1677631 #> [23,] 1.1672187 #> [24,] 1.1394065 #> [25,] 1.2651881 #> [26,] 1.3628942 #> [27,] 1.2955839 #> [28,] 1.2532078 #> [29,] 1.2103854 #> [30,] 1.2287557 #>  #> , , 24 #>  #>            [,1] #>  [1,] 0.7029608 #>  [2,] 0.7393853 #>  [3,] 0.8321187 #>  [4,] 0.7347838 #>  [5,] 0.7367899 #>  [6,] 0.8752365 #>  [7,] 0.8719712 #>  [8,] 0.8280637 #>  [9,] 0.6993775 #> [10,] 0.7080216 #> [11,] 0.2164331 #> [12,] 0.2197588 #> [13,] 0.2839874 #> [14,] 0.1422049 #> [15,] 0.2147917 #> [16,] 0.2762147 #> [17,] 0.2444384 #> [18,] 0.1407022 #> [19,] 0.3101693 #> [20,] 0.2258971 #> [21,] 1.2056537 #> [22,] 1.2064709 #> [23,] 1.2046361 #> [24,] 1.1790476 #> [25,] 1.3015302 #> [26,] 1.4019949 #> [27,] 1.3355144 #> [28,] 1.2946359 #> [29,] 1.2511934 #> [30,] 1.2694182 #>  #> , , 25 #>  #>            [,1] #>  [1,] 0.7297313 #>  [2,] 0.7694145 #>  [3,] 0.8640647 #>  [4,] 0.7654331 #>  [5,] 0.7682030 #>  [6,] 0.9083263 #>  [7,] 0.9028905 #>  [8,] 0.8583332 #>  [9,] 0.7276259 #> [10,] 0.7382387 #> [11,] 0.2434910 #> [12,] 0.2430895 #> [13,] 0.3092530 #> [14,] 0.1636373 #> [15,] 0.2403446 #> [16,] 0.3021347 #> [17,] 0.2703687 #> [18,] 0.1643699 #> [19,] 0.3362305 #> [20,] 0.2492332 #> [21,] 1.2396911 #> [22,] 1.2436234 #> [23,] 1.2407242 #> [24,] 1.2173486 #> [25,] 1.3362432 #> [26,] 1.4393360 #> [27,] 1.3737489 #> [28,] 1.3343981 #> [29,] 1.2904833 #> [30,] 1.3084538 #>  #> , , 26 #>  #>            [,1] #>  [1,] 0.7561126 #>  [2,] 0.7990087 #>  [3,] 0.8956087 #>  [4,] 0.7957583 #>  [5,] 0.7992446 #>  [6,] 0.9408817 #>  [7,] 0.9332864 #>  [8,] 0.8881795 #>  [9,] 0.7556081 #> [10,] 0.7681920 #> [11,] 0.2705985 #> [12,] 0.2664386 #> [13,] 0.3345311 #> [14,] 0.1851626 #> [15,] 0.2659686 #> [16,] 0.3280659 #> [17,] 0.2963364 #> [18,] 0.1881373 #> [19,] 0.3622814 #> [20,] 0.2726023 #> [21,] 1.2724479 #> [22,] 1.2791787 #> [23,] 1.2754486 #> [24,] 1.2542926 #> [25,] 1.3692881 #> [26,] 1.4748747 #> [27,] 1.4102435 #> [28,] 1.3724490 #> [29,] 1.3282136 #> [30,] 1.3458180 #>  #> , , 27 #>  #>            [,1] #>  [1,] 0.7821432 #>  [2,] 0.8281642 #>  [3,] 0.9266607 #>  [4,] 0.8257272 #>  [5,] 0.8299527 #>  [6,] 0.9728508 #>  [7,] 0.9631349 #>  [8,] 0.9175823 #>  [9,] 0.7831727 #> [10,] 0.7977496 #> [11,] 0.2977433 #> [12,] 0.2898040 #> [13,] 0.3597988 #> [14,] 0.2067193 #> [15,] 0.2916179 #> [16,] 0.3539919 #> [17,] 0.3223494 #> [18,] 0.2119727 #> [19,] 0.3883223 #> [20,] 0.2960142 #> [21,] 1.3038952 #> [22,] 1.3130964 #> [23,] 1.3087761 #> [24,] 1.2899000 #> [25,] 1.4006275 #> [26,] 1.5085699 #> [27,] 1.4449560 #> [28,] 1.4087444 #> [29,] 1.3643438 #> [30,] 1.3813734 #>  #> , , 28 #>  #>            [,1] #>  [1,] 0.8078177 #>  [2,] 0.8568588 #>  [3,] 0.9571768 #>  [4,] 0.8552938 #>  [5,] 0.8603137 #>  [6,] 1.0042239 #>  [7,] 0.9924125 #>  [8,] 0.9464658 #>  [9,] 0.8104338 #> [10,] 0.8270128 #> [11,] 0.3249280 #> [12,] 0.3131769 #> [13,] 0.3850551 #> [14,] 0.2283669 #> [15,] 0.3172876 #> [16,] 0.3799078 #> [17,] 0.3483719 #> [18,] 0.2358445 #> [19,] 0.4143061 #> [20,] 0.3194334 #> [21,] 1.3340052 #> [22,] 1.3453375 #> [23,] 1.3406741 #> [24,] 1.3241385 #> [25,] 1.4302253 #> [26,] 1.5403822 #> [27,] 1.4778458 #> [28,] 1.4432419 #> [29,] 1.3988347 #> [30,] 1.4151476 #>  #> , , 29 #>  #>            [,1] #>  [1,] 0.8331020 #>  [2,] 0.8850080 #>  [3,] 0.9872214 #>  [4,] 0.8844189 #>  [5,] 0.8903102 #>  [6,] 1.0349868 #>  [7,] 1.0210964 #>  [8,] 0.9747430 #>  [9,] 0.8373816 #> [10,] 0.8559693 #> [11,] 0.3521243 #> [12,] 0.3365446 #> [13,] 0.4102637 #> [14,] 0.2500376 #> [15,] 0.3429698 #> [16,] 0.4057719 #> [17,] 0.3743957 #> [18,] 0.2597806 #> [19,] 0.4402533 #> [20,] 0.3428600 #> [21,] 1.3627507 #> [22,] 1.3758643 #> [23,] 1.3711096 #> [24,] 1.3569768 #> [25,] 1.4580470 #> [26,] 1.5702739 #> [27,] 1.5088480 #> [28,] 1.4759008 #> [29,] 1.4316486 #> [30,] 1.4471214 #>  #> , , 30 #>  #>            [,1] #>  [1,] 0.8579686 #>  [2,] 0.9126372 #>  [3,] 1.0167776 #>  [4,] 0.9130919 #>  [5,] 0.9199245 #>  [6,] 1.0651151 #>  [7,] 1.0491646 #>  [8,] 1.0025030 #>  [9,] 0.8640040 #> [10,] 0.8846043 #> [11,] 0.3793171 #> [12,] 0.3598962 #> [13,] 0.4354289 #> [14,] 0.2717590 #> [15,] 0.3686412 #> [16,] 0.4315940 #> [17,] 0.4004053 #> [18,] 0.2837390 #> [19,] 0.4661568 #> [20,] 0.3662741 #> [21,] 1.3900851 #> [22,] 1.4046407 #> [23,] 1.3999307 #> [24,] 1.3883844 #> [25,] 1.4840596 #> [26,] 1.5982089 #> [27,] 1.5379236 #> [28,] 1.5066819 #> [29,] 1.4627492 #> [30,] 1.4772572 #>  #> , , 31 #>  #>            [,1] #>  [1,] 0.8824134 #>  [2,] 0.9397353 #>  [3,] 1.0458275 #>  [4,] 0.9413308 #>  [5,] 0.9490475 #>  [6,] 1.0945851 #>  [7,] 1.0765955 #>  [8,] 1.0297341 #>  [9,] 0.8902710 #> [10,] 0.9128828 #> [11,] 0.4064985 #> [12,] 0.3832180 #> [13,] 0.4605529 #> [14,] 0.2935033 #> [15,] 0.3943006 #> [16,] 0.4573665 #> [17,] 0.4263831 #> [18,] 0.3077142 #> [19,] 0.4919472 #> [20,] 0.3896752 #> [21,] 1.4159352 #> [22,] 1.4316322 #> [23,] 1.4271196 #> [24,] 1.4183318 #> [25,] 1.5082317 #> [26,] 1.6241533 #> [27,] 1.5650592 #> [28,] 1.5355479 #> [29,] 1.4921008 #> [30,] 1.5055187 #>  #> , , 32 #>  #>            [,1] #>  [1,] 0.9063475 #>  [2,] 0.9662825 #>  [3,] 1.0743513 #>  [4,] 0.9691181 #>  [5,] 0.9776602 #>  [6,] 1.1233742 #>  [7,] 1.1033686 #>  [8,] 1.0564197 #>  [9,] 0.9160072 #> [10,] 0.9406332 #> [11,] 0.4336311 #> [12,] 0.4065223 #> [13,] 0.4855710 #> [14,] 0.3152639 #> [15,] 0.4199145 #> [16,] 0.4830352 #> [17,] 0.4523267 #> [18,] 0.3317017 #> [19,] 0.5176738 #> [20,] 0.4130429 #> [21,] 1.4402932 #> [22,] 1.4568059 #> [23,] 1.4527498 #> [24,] 1.4467906 #> [25,] 1.5305337 #> [26,] 1.6480748 #> [27,] 1.5902250 #> [28,] 1.5624632 #> [29,] 1.5196630 #> [30,] 1.5318717 #>  #> , , 33 #>  #>            [,1] #>  [1,] 0.9298255 #>  [2,] 0.9922596 #>  [3,] 1.1023230 #>  [4,] 0.9964368 #>  [5,] 1.0058168 #>  [6,] 1.1514603 #>  [7,] 1.1294157 #>  [8,] 1.0825436 #>  [9,] 0.9413578 #> [10,] 0.9680036 #> [11,] 0.4607221 #> [12,] 0.4297435 #> [13,] 0.5105130 #> [14,] 0.3370373 #> [15,] 0.4454822 #> [16,] 0.5086080 #> [17,] 0.4782097 #> [18,] 0.3556816 #> [19,] 0.5433150 #> [20,] 0.4363637 #> [21,] 1.4630814 #> [22,] 1.4801304 #> [23,] 1.4767975 #> [24,] 1.4737335 #> [25,] 1.5508836 #> [26,] 1.6699430 #> [27,] 1.6133894 #> [28,] 1.5873941 #> [29,] 1.5453812 #> [30,] 1.5562837 #>  #> , , 34 #>  #>            [,1] #>  [1,] 0.9528504 #>  [2,] 1.0176211 #>  [3,] 1.1295385 #>  [4,] 1.0232575 #>  [5,] 1.0335112 #>  [6,] 1.1788219 #>  [7,] 1.1547268 #>  [8,] 1.1080895 #>  [9,] 0.9663171 #> [10,] 0.9949842 #> [11,] 0.4877663 #> [12,] 0.4529267 #> [13,] 0.5353852 #> [14,] 0.3588114 #> [15,] 0.4710069 #> [16,] 0.5340917 #> [17,] 0.5040091 #> [18,] 0.3796503 #> [19,] 0.5687992 #> [20,] 0.4596509 #> [21,] 1.4843014 #> [22,] 1.5015551 #> [23,] 1.4992377 #> [24,] 1.4991209 #> [25,] 1.5692482 #> [26,] 1.6897297 #> [27,] 1.6345227 #> [28,] 1.6103089 #> [29,] 1.5692545 #> [30,] 1.5787238 #>  #> , , 35 #>  #>            [,1] #>  [1,] 0.9753961 #>  [2,] 1.0423333 #>  [3,] 1.1561550 #>  [4,] 1.0495318 #>  [5,] 1.0607284 #>  [6,] 1.2053677 #>  [7,] 1.1793171 #>  [8,] 1.1329078 #>  [9,] 0.9908763 #> [10,] 1.0215631 #> [11,] 0.5146923 #> [12,] 0.4760473 #> [13,] 0.5600950 #> [14,] 0.3805754 #> [15,] 0.4964292 #> [16,] 0.5594548 #> [17,] 0.5297399 #> [18,] 0.4035827 #> [19,] 0.5941922 #> [20,] 0.4828465 #> [21,] 1.5040054 #> [22,] 1.5210200 #> [23,] 1.5200466 #> [24,] 1.5228801 #> [25,] 1.5856445 #> [26,] 1.7074086 #> [27,] 1.6535971 #> [28,] 1.6311776 #> [29,] 1.5912033 #> [30,] 1.5991631 #>  #> , , 36 #>  #>            [,1] #>  [1,] 0.9974331 #>  [2,] 1.0664170 #>  [3,] 1.1821699 #>  [4,] 1.0751878 #>  [5,] 1.0874538 #>  [6,] 1.2311301 #>  [7,] 1.2031647 #>  [8,] 1.1570272 #>  [9,] 1.0149993 #> [10,] 1.0477031 #> [11,] 0.5415329 #> [12,] 0.4990682 #> [13,] 0.5846971 #> [14,] 0.4023240 #> [15,] 0.5217708 #> [16,] 0.5846395 #> [17,] 0.5553783 #> [18,] 0.4274872 #> [19,] 0.6194502 #> [20,] 0.5059788 #> [21,] 1.5221739 #> [22,] 1.5385501 #> [23,] 1.5392016 #> [24,] 1.5449927 #> [25,] 1.6000662 #> [26,] 1.7229553 #> [27,] 1.6705869 #> [28,] 1.6499726 #> [29,] 1.6112401 #> [30,] 1.6175746 #>  #> , , 37 #>  #>            [,1] #>  [1,] 1.0189376 #>  [2,] 1.0898562 #>  [3,] 1.2075686 #>  [4,] 1.1002657 #>  [5,] 1.1135508 #>  [6,] 1.2561043 #>  [7,] 1.2262236 #>  [8,] 1.1805035 #>  [9,] 1.0384955 #> [10,] 1.0732003 #> [11,] 0.5682864 #> [12,] 0.5220362 #> [13,] 0.6092018 #> [14,] 0.4240484 #> [15,] 0.5470399 #> [16,] 0.6097021 #> [17,] 0.5808693 #> [18,] 0.4513309 #> [19,] 0.6445186 #> [20,] 0.5290543 #> [21,] 1.5387884 #> [22,] 1.5541215 #> [23,] 1.5566818 #> [24,] 1.5653383 #> [25,] 1.6124930 #> [26,] 1.7363478 #> [27,] 1.6854685 #> [28,] 1.6666678 #> [29,] 1.6293497 #> [30,] 1.6339334 #>  #> , , 38 #>  #>            [,1] #>  [1,] 1.0398313 #>  [2,] 1.1125555 #>  [3,] 1.2323368 #>  [4,] 1.1247843 #>  [5,] 1.1390249 #>  [6,] 1.2802719 #>  [7,] 1.2484904 #>  [8,] 1.2033334 #>  [9,] 1.0615327 #> [10,] 1.0982398 #> [11,] 0.5948915 #> [12,] 0.5448591 #> [13,] 0.6334897 #> [14,] 0.4457314 #> [15,] 0.5721509 #> [16,] 0.6346381 #> [17,] 0.6062603 #> [18,] 0.4751102 #> [19,] 0.6694692 #> [20,] 0.5519744 #> [21,] 1.5538315 #> [22,] 1.5677118 #> [23,] 1.5724672 #> [24,] 1.5840208 #> [25,] 1.6229063 #> [26,] 1.7475659 #> [27,] 1.6982203 #> [28,] 1.6812250 #> [29,] 1.6455091 #> [30,] 1.6482163 #>  #> , , 39 #>  #>            [,1] #>  [1,] 1.0601790 #>  [2,] 1.1345566 #>  [3,] 1.2564548 #>  [4,] 1.1487296 #>  [5,] 1.1639359 #>  [6,] 1.3035968 #>  [7,] 1.2699677 #>  [8,] 1.2255040 #>  [9,] 1.0841101 #> [10,] 1.1228159 #> [11,] 0.6213402 #> [12,] 0.5675973 #> [13,] 0.6576392 #> [14,] 0.4673932 #> [15,] 0.5971481 #> [16,] 0.6593074 #> [17,] 0.6315400 #> [18,] 0.4988449 #> [19,] 0.6942276 #> [20,] 0.5748239 #> [21,] 1.5672869 #> [22,] 1.5793007 #> [23,] 1.5865394 #> [24,] 1.6010399 #> [25,] 1.6312894 #> [26,] 1.7565918 #> [27,] 1.7088229 #> [28,] 1.6935796 #> [29,] 1.6596966 #> [30,] 1.6604024 #>  #> , , 40 #>  #>            [,1] #>  [1,] 1.0799933 #>  [2,] 1.1558618 #>  [3,] 1.2797836 #>  [4,] 1.1720878 #>  [5,] 1.1882874 #>  [6,] 1.3260488 #>  [7,] 1.2906406 #>  [8,] 1.2470028 #>  [9,] 1.1062221 #> [10,] 1.1469189 #> [11,] 0.6476633 #> [12,] 0.5902450 #> [13,] 0.6816650 #> [14,] 0.4889741 #> [15,] 0.6220445 #> [16,] 0.6838164 #> [17,] 0.6565960 #> [18,] 0.5224515 #> [19,] 0.7187740 #> [20,] 0.5975746 #> [21,] 1.5791395 #> [22,] 1.5888700 #> [23,] 1.5988812 #> [24,] 1.6163773 #> [25,] 1.6376277 #> [26,] 1.7634100 #> [27,] 1.7172589 #> [28,] 1.7037687 #> [29,] 1.6718927 #> [30,] 1.6704727 #>  #> , , 41 #>  #>            [,1] #>  [1,] 1.0992599 #>  [2,] 1.1764569 #>  [3,] 1.3023122 #>  [4,] 1.1948348 #>  [5,] 1.2120670 #>  [6,] 1.3476242 #>  [7,] 1.3104947 #>  [8,] 1.2677874 #>  [9,] 1.1278265 #> [10,] 1.1705051 #> [11,] 0.6738335 #> [12,] 0.6127003 #> [13,] 0.7054220 #> [14,] 0.5105246 #> [15,] 0.6467288 #> [16,] 0.7081616 #> [17,] 0.6815261 #> [18,] 0.5459802 #> [19,] 0.7431781 #> [20,] 0.6201394 #> [21,] 1.5893499 #> [22,] 1.5964030 #> [23,] 1.6094771 #> [24,] 1.6300155 #> [25,] 1.6419084 #> [26,] 1.7680069 #> [27,] 1.7235133 #> [28,] 1.7117752 #> [29,] 1.6820795 #> [30,] 1.6784103 #>  #> , , 42 #>  #>            [,1] #>  [1,] 1.1179462 #>  [2,] 1.1963285 #>  [3,] 1.3241432 #>  [4,] 1.2169241 #>  [5,] 1.2352579 #>  [6,] 1.3683259 #>  [7,] 1.3295166 #>  [8,] 1.2877098 #>  [9,] 1.1487251 #> [10,] 1.1933660 #> [11,] 0.6997504 #> [12,] 0.6350713 #> [13,] 0.7290111 #> [14,] 0.5319774 #> [15,] 0.6712674 #> [16,] 0.7322426 #> [17,] 0.7063284 #> [18,] 0.5694357 #> [19,] 0.7673251 #> [20,] 0.6426107 #> [21,] 1.5978263 #> [22,] 1.6018855 #> [23,] 1.6183129 #> [24,] 1.6419387 #> [25,] 1.6441210 #> [26,] 1.7703716 #> [27,] 1.7275732 #> [28,] 1.7175845 #> [29,] 1.6902412 #> [30,] 1.6842005 #>  #> , , 43 #>  #>            [,1] #>  [1,] 1.1360016 #>  [2,] 1.2154390 #>  [3,] 1.3452692 #>  [4,] 1.2382371 #>  [5,] 1.2576980 #>  [6,] 1.3881394 #>  [7,] 1.3476824 #>  [8,] 1.3068637 #>  [9,] 1.1691004 #> [10,] 1.2156956 #> [11,] 0.7255140 #> [12,] 0.6572624 #> [13,] 0.7524513 #> [14,] 0.5533659 #> [15,] 0.6956783 #> [16,] 0.7560720 #> [17,] 0.7308359 #> [18,] 0.5927133 #> [19,] 0.7912475 #> [20,] 0.6649261 #> [21,] 1.6046128 #> [22,] 1.6053051 #> [23,] 1.6253742 #> [24,] 1.6521324 #> [25,] 1.6442568 #> [26,] 1.7704951 #> [27,] 1.7294281 #> [28,] 1.7211840 #> [29,] 1.6963638 #> [30,] 1.6878307 #>  #> , , 44 #>  #>            [,1] #>  [1,] 1.1533667 #>  [2,] 1.2337568 #>  [3,] 1.3656790 #>  [4,] 1.2588806 #>  [5,] 1.2794484 #>  [6,] 1.4070511 #>  [7,] 1.3648980 #>  [8,] 1.3252778 #>  [9,] 1.1889566 #> [10,] 1.2374954 #> [11,] 0.7511207 #> [12,] 0.6793034 #> [13,] 0.7755733 #> [14,] 0.5746820 #> [15,] 0.7198250 #> [16,] 0.7797028 #> [17,] 0.7551874 #> [18,] 0.6159031 #> [19,] 0.8150059 #> [20,] 0.6870557 #> [21,] 1.6095702 #> [22,] 1.6066515 #> [23,] 1.6305710 #> [24,] 1.6605831 #> [25,] 1.6423093 #> [26,] 1.7683710 #> [27,] 1.7290698 #> [28,] 1.7225636 #> [29,] 1.7004353 #> [30,] 1.6892076 #>  #> , , 45 #>  #>            [,1] #>  [1,] 1.1701120 #>  [2,] 1.2512945 #>  [3,] 1.3853615 #>  [4,] 1.2788660 #>  [5,] 1.3005418 #>  [6,] 1.4250479 #>  [7,] 1.3812411 #>  [8,] 1.3429563 #>  [9,] 1.2082919 #> [10,] 1.2587611 #> [11,] 0.7763861 #> [12,] 0.7012402 #> [13,] 0.7984988 #> [14,] 0.5958807 #> [15,] 0.7437956 #> [16,] 0.8031049 #> [17,] 0.7793819 #> [18,] 0.6389563 #> [19,] 0.8384350 #> [20,] 0.7090694 #> [21,] 1.6128637 #> [22,] 1.6059166 #> [23,] 1.6337824 #> [24,] 1.6672790 #> [25,] 1.6382740 #> [26,] 1.7639952 #> [27,] 1.7264922 #> [28,] 1.7217156 #> [29,] 1.7024455 #> [30,] 1.6883456 #>  #> , , 46 #>  #>            [,1] #>  [1,] 1.1862597 #>  [2,] 1.2680575 #>  [3,] 1.4042940 #>  [4,] 1.2981821 #>  [5,] 1.3209900 #>  [6,] 1.4420366 #>  [7,] 1.3967006 #>  [8,] 1.3598895 #>  [9,] 1.2270578 #> [10,] 1.2794420 #> [11,] 0.8014547 #> [12,] 0.7228855 #> [13,] 0.8212519 #> [14,] 0.6170364 #> [15,] 0.7676132 #> [16,] 0.8261310 #> [17,] 0.8032496 #> [18,] 0.6618299 #> [19,] 0.8616354 #> [20,] 0.7308500 #> [21,] 1.6144862 #> [22,] 1.6030942 #> [23,] 1.6351869 #> [24,] 1.6722095 #> [25,] 1.6321486 #> [26,] 1.7573638 #> [27,] 1.7216918 #> [28,] 1.7186344 #> [29,] 1.7023864 #> [30,] 1.6852992 #>  #> , , 47 #>  #>            [,1] #>  [1,] 1.2018017 #>  [2,] 1.2839475 #>  [3,] 1.4221971 #>  [4,] 1.3168187 #>  [5,] 1.3407893 #>  [6,] 1.4580608 #>  [7,] 1.4112662 #>  [8,] 1.3760686 #>  [9,] 1.2450547 #> [10,] 1.2993335 #> [11,] 0.8263283 #> [12,] 0.7444220 #> [13,] 0.8436399 #> [14,] 0.6379999 #> [15,] 0.7911164 #> [16,] 0.8489397 #> [17,] 0.8269078 #> [18,] 0.6845974 #> [19,] 0.8846541 #> [20,] 0.7524601 #> [21,] 1.6144320 #> [22,] 1.5981806 #> [23,] 1.6347814 #> [24,] 1.6753586 #> [25,] 1.6239330 #> [26,] 1.7484440 #> [27,] 1.7146674 #> [28,] 1.7133171 #> [29,] 1.7002521 #> [30,] 1.6800652 #>  #> , , 48 #>  #>            [,1] #>  [1,] 1.2167088 #>  [2,] 1.2990135 #>  [3,] 1.4393339 #>  [4,] 1.3347573 #>  [5,] 1.3598993 #>  [6,] 1.4731323 #>  [7,] 1.4249279 #>  [8,] 1.3913900 #>  [9,] 1.2624731 #> [10,] 1.3186287 #> [11,] 0.8508812 #> [12,] 0.7657614 #> [13,] 0.8658043 #> [14,] 0.6589040 #> [15,] 0.8144147 #> [16,] 0.8715230 #> [17,] 0.8503770 #> [18,] 0.7071431 #> [19,] 0.9072645 #> [20,] 0.7739358 #> [21,] 1.6126966 #> [22,] 1.5911740 #> [23,] 1.6325613 #> [24,] 1.6766092 #> [25,] 1.6136292 #> [26,] 1.7372462 #> [27,] 1.7054202 #> [28,] 1.7057630 #> [29,] 1.6960385 #> [30,] 1.6726431 #>  #> , , 49 #>  #>            [,1] #>  [1,] 1.2309277 #>  [2,] 1.3132713 #>  [3,] 1.4556970 #>  [4,] 1.3519580 #>  [5,] 1.3781944 #>  [6,] 1.4872407 #>  [7,] 1.4376762 #>  [8,] 1.4058064 #>  [9,] 1.2793223 #> [10,] 1.3373367 #> [11,] 0.8751376 #> [12,] 0.7868629 #> [13,] 0.8877738 #> [14,] 0.6796541 #> [15,] 0.8375361 #> [16,] 0.8936698 #> [17,] 0.8735154 #> [18,] 0.7295249 #> [19,] 0.9296497 #> [20,] 0.7950894 #> [21,] 1.6092768 #> [22,] 1.5820749 #> [23,] 1.6285240 #> [24,] 1.6758677 #> [25,] 1.6012414 #> [26,] 1.7238051 #> [27,] 1.6939539 #> [28,] 1.6959741 #> [29,] 1.6897438 #> [30,] 1.6630343 #>  #> , , 50 #>  #>            [,1] #>  [1,] 1.2443779 #>  [2,] 1.3267120 #>  [3,] 1.4712782 #>  [4,] 1.3682448 #>  [5,] 1.3957412 #>  [6,] 1.5003764 #>  [7,] 1.4495024 #>  [8,] 1.4193909 #>  [9,] 1.2956046 #> [10,] 1.3554594 #> [11,] 0.8991633 #> [12,] 0.8078374 #> [13,] 0.9093343 #> [14,] 0.7002797 #> [15,] 0.8602953 #> [16,] 0.9155365 #> [17,] 0.8963761 #> [18,] 0.7517922 #> [19,] 0.9518401 #> [20,] 0.8160979 #> [21,] 1.6041707 #> [22,] 1.5708862 #> [23,] 1.6226682 #> [24,] 1.6733311 #> [25,] 1.5867432 #> [26,] 1.7081290 #> [27,] 1.6802746 #> [28,] 1.6839545 #> [29,] 1.6813681 #> [30,] 1.6512430 #>  #> , , 51 #>  #>            [,1] #>  [1,] 1.2571493 #>  [2,] 1.3393271 #>  [3,] 1.4860693 #>  [4,] 1.3838015 #>  [5,] 1.4125547 #>  [6,] 1.5125302 #>  [7,] 1.4603855 #>  [8,] 1.4321675 #>  [9,] 1.3112645 #> [10,] 1.3729390 #> [11,] 0.9229073 #> [12,] 0.8284763 #> [13,] 0.9306456 #> [14,] 0.7208025 #> [15,] 0.8828225 #> [16,] 0.9371431 #> [17,] 0.9190171 #> [18,] 0.7737301 #> [19,] 0.9735365 #> [20,] 0.8369135 #> [21,] 1.5973762 #> [22,] 1.5576127 #> [23,] 1.6149944 #> [24,] 1.6689977 #> [25,] 1.5701086 #> [26,] 1.6902287 #> [27,] 1.6643908 #> [28,] 1.6697113 #> [29,] 1.6709139 #> [30,] 1.6372756 #>  #> , , 52 #>  #>            [,1] #>  [1,] 1.2692737 #>  [2,] 1.3510911 #>  [3,] 1.5000588 #>  [4,] 1.3986246 #>  [5,] 1.4286508 #>  [6,] 1.5236675 #>  [7,] 1.4702897 #>  [8,] 1.4441451 #>  [9,] 1.3261071 #> [10,] 1.3895818 #> [11,] 0.9462296 #> [12,] 0.8489606 #> [13,] 0.9517408 #> [14,] 0.7411188 #> [15,] 0.9051502 #> [16,] 0.9583807 #> [17,] 0.9413344 #> [18,] 0.7955252 #> [19,] 0.9950181 #> [20,] 0.8573998 #> [21,] 1.5888684 #> [22,] 1.5422618 #> [23,] 1.6055045 #> [24,] 1.6628665 #> [25,] 1.5513810 #> [26,] 1.6701174 #> [27,] 1.6463136 #> [28,] 1.6532536 #> [29,] 1.6583855 #> [30,] 1.6211409 #>  #> , , 53 #>  #>            [,1] #>  [1,] 1.2807451 #>  [2,] 1.3619736 #>  [3,] 1.5130678 #>  [4,] 1.4127061 #>  [5,] 1.4440375 #>  [6,] 1.5337641 #>  [7,] 1.4792307 #>  [8,] 1.4553173 #>  [9,] 1.3403247 #> [10,] 1.4055718 #> [11,] 0.9693028 #> [12,] 0.8692436 #> [13,] 0.9723859 #> [14,] 0.7613636 #> [15,] 0.9270703 #> [16,] 0.9792074 #> [17,] 0.9632953 #> [18,] 0.8171530 #> [19,] 1.0162713 #> [20,] 0.8777268 #> [21,] 1.5785463 #> [22,] 1.5248432 #> [23,] 1.5942024 #> [24,] 1.6549381 #> [25,] 1.5306109 #> [26,] 1.6478111 #> [27,] 1.6260564 #> [28,] 1.6345933 #> [29,] 1.6437897 #> [30,] 1.6028500 #>  #> , , 54 #>  #>            [,1] #>  [1,] 1.2915422 #>  [2,] 1.3719697 #>  [3,] 1.5251311 #>  [4,] 1.4260381 #>  [5,] 1.4586465 #>  [6,] 1.5428390 #>  [7,] 1.4871459 #>  [8,] 1.4656781 #>  [9,] 1.3539312 #> [10,] 1.4209256 #> [11,] 0.9921279 #> [12,] 0.8891812 #> [13,] 0.9927570 #> [14,] 0.7813412 #> [15,] 0.9487331 #> [16,] 0.9997486 #> [17,] 0.9850125 #> [18,] 0.8384505 #> [19,] 1.0369905 #> [20,] 0.8977988 #> [21,] 1.5664202 #> [22,] 1.5053686 #> [23,] 1.5810934 #> [24,] 1.6452144 #> [25,] 1.5078144 #> [26,] 1.6233281 #> [27,] 1.6036354 #> [28,] 1.6137449 #> [29,] 1.6271353 #> [30,] 1.5824167 #>  #> , , 55 #>  #>            [,1] #>  [1,] 1.3016258 #>  [2,] 1.3811093 #>  [3,] 1.5363615 #>  [4,] 1.4386080 #>  [5,] 1.4724007 #>  [6,] 1.5508992 #>  [7,] 1.4940570 #>  [8,] 1.4750553 #>  [9,] 1.3669333 #> [10,] 1.4356520 #> [11,] 1.0144159 #> [12,] 0.9089651 #> [13,] 1.0128921 #> [14,] 0.8012150 #> [15,] 0.9701753 #> [16,] 1.0199979 #> [17,] 1.0064221 #> [18,] 0.8595914 #> [19,] 1.0574815 #> [20,] 0.9175493 #> [21,] 1.5525487 #> [22,] 1.4838522 #> [23,] 1.5661845 #> [24,] 1.6336991 #> [25,] 1.4830094 #> [26,] 1.5966894 #> [27,] 1.5790691 #> [28,] 1.5907251 #> [29,] 1.6084331 #> [30,] 1.5598570 #>  #> , , 56 #>  #>            [,1] #>  [1,] 1.3108661 #>  [2,] 1.3892963 #>  [3,] 1.5467617 #>  [4,] 1.4503690 #>  [5,] 1.4853666 #>  [6,] 1.5579379 #>  [7,] 1.4999994 #>  [8,] 1.4835242 #>  [9,] 1.3792686 #> [10,] 1.4496857 #> [11,] 1.0364211 #> [12,] 0.9284170 #> [13,] 1.0325409 #> [14,] 0.8209014 #> [15,] 0.9911670 #> [16,] 1.0396768 #> [17,] 1.0273865 #> [18,] 0.8804730 #> [19,] 1.0776965 #> [20,] 0.9371159 #> [21,] 1.5370121 #> [22,] 1.4603107 #> [23,] 1.5494844 #> [24,] 1.6203972 #> [25,] 1.4562166 #> [26,] 1.5679183 #> [27,] 1.5523785 #> [28,] 1.5655536 #> [29,] 1.5876964 #> [30,] 1.5351895 #>  #> , , 57 #>  #>            [,1] #>  [1,] 1.3193817 #>  [2,] 1.3965795 #>  [3,] 1.5563259 #>  [4,] 1.4611326 #>  [5,] 1.4975394 #>  [6,] 1.5638662 #>  [7,] 1.5049674 #>  [8,] 1.4911194 #>  [9,] 1.3907509 #> [10,] 1.4628498 #> [11,] 1.0581425 #> [12,] 0.9476348 #> [13,] 1.0518896 #> [14,] 0.8403938 #> [15,] 1.0118773 #> [16,] 1.0590618 #> [17,] 1.0480915 #> [18,] 0.9010660 #> [19,] 1.0973772 #> [20,] 0.9563526 #> [21,] 1.5198191 #> [22,] 1.4347629 #> [23,] 1.5310035 #> [24,] 1.6053154 #> [25,] 1.4274587 #> [26,] 1.5370408 #> [27,] 1.5235874 #> [28,] 1.5382523 #> [29,] 1.5649406 #> [30,] 1.5084351 #>  #> , , 58 #>  #>            [,1] #>  [1,] 1.3272135 #>  [2,] 1.4029869 #>  [3,] 1.5650487 #>  [4,] 1.4711116 #>  [5,] 1.5089349 #>  [6,] 1.5687279 #>  [7,] 1.5089554 #>  [8,] 1.4978639 #>  [9,] 1.4015694 #> [10,] 1.4753124 #> [11,] 1.0793949 #> [12,] 0.9666539 #> [13,] 1.0709831 #> [14,] 0.8597704 #> [15,] 1.0323472 #> [16,] 1.0781377 #> [17,] 1.0685126 #> [18,] 0.9214860 #> [19,] 1.1168044 #> [20,] 0.9753068 #> [21,] 1.5009797 #> [22,] 1.4072299 #> [23,] 1.5107334 #> [24,] 1.5884620 #> [25,] 1.3967608 #> [26,] 1.5040854 #> [27,] 1.4927217 #> [28,] 1.5088459 #> [29,] 1.5401833 #> [30,] 1.4796174 #>  #> , , 59 #>  #>            [,1] #>  [1,] 1.3343573 #>  [2,] 1.4085136 #>  [3,] 1.5728810 #>  [4,] 1.4803009 #>  [5,] 1.5195748 #>  [6,] 1.5725491 #>  [7,] 1.5119583 #>  [8,] 1.5037681 #>  [9,] 1.4117425 #> [10,] 1.4870972 #> [11,] 1.1002426 #> [12,] 0.9852365 #> [13,] 1.0895626 #> [14,] 0.8788300 #> [15,] 1.0523282 #> [16,] 1.0966830 #> [17,] 1.0883894 #> [18,] 0.9415338 #> [19,] 1.1358978 #> [20,] 0.9940549 #> [21,] 1.4805054 #> [22,] 1.3777355 #> [23,] 1.4884701 #> [24,] 1.5698467 #> [25,] 1.3641501 #> [26,] 1.4690832 #> [27,] 1.4598102 #> [28,] 1.4773616 #> [29,] 1.5134442 #> [30,] 1.4487623 #>  #> , , 60 #>  #>            [,1] #>  [1,] 1.3408006 #>  [2,] 1.4131548 #>  [3,] 1.5795913 #>  [4,] 1.4886946 #>  [5,] 1.5293594 #>  [6,] 1.5753247 #>  [7,] 1.5139710 #>  [8,] 1.5088279 #>  [9,] 1.4212810 #> [10,] 1.4982204 #> [11,] 1.1207739 #> [12,] 1.0036503 #> [13,] 1.1078149 #> [14,] 0.8977935 #> [15,] 1.0720011 #> [16,] 1.1148229 #> [17,] 1.1079944 #> [18,] 0.9613464 #> [19,] 1.1544710 #> [20,] 1.0123740 #> [21,] 1.4584089 #> [22,] 1.3463055 #> [23,] 1.4644672 #> [24,] 1.5493967 #> [25,] 1.3296563 #> [26,] 1.4320677 #> [27,] 1.4248840 #> [28,] 1.4438289 #> [29,] 1.4847455 #> [30,] 1.4158981 #>  #> , , 61 #>  #>            [,1] #>  [1,] 1.3465190 #>  [2,] 1.4168984 #>  [3,] 1.5854248 #>  [4,] 1.4962868 #>  [5,] 1.5382688 #>  [6,] 1.5770499 #>  [7,] 1.5149889 #>  [8,] 1.5129845 #>  [9,] 1.4301156 #> [10,] 1.5086092 #> [11,] 1.1409132 #> [12,] 1.0217393 #> [13,] 1.1257932 #> [14,] 0.9164571 #> [15,] 1.0914143 #> [16,] 1.1326243 #> [17,] 1.1273323 #> [18,] 0.9809768 #> [19,] 1.1727674 #> [20,] 1.0304669 #> [21,] 1.4347045 #> [22,] 1.3129683 #> [23,] 1.4387480 #> [24,] 1.5270205 #> [25,] 1.2933114 #> [26,] 1.3930751 #> [27,] 1.3879768 #> [28,] 1.4082804 #> [29,] 1.4541114 #> [30,] 1.3810119 #>  #> , , 62 #>  #>            [,1] #>  [1,] 1.3513304 #>  [2,] 1.4197134 #>  [3,] 1.5903905 #>  [4,] 1.5030693 #>  [5,] 1.5463640 #>  [6,] 1.5777202 #>  [7,] 1.5150075 #>  [8,] 1.5161597 #>  [9,] 1.4380720 #> [10,] 1.5181072 #> [11,] 1.1605023 #> [12,] 1.0394955 #> [13,] 1.1432337 #> [14,] 0.9349612 #> [15,] 1.1103132 #> [16,] 1.1500012 #> [17,] 1.1460558 #> [18,] 1.0001167 #> [19,] 1.1906654 #> [20,] 1.0482905 #> [21,] 1.4094001 #> [22,] 1.2777510 #> [23,] 1.4113326 #> [24,] 1.5028923 #> [25,] 1.2551493 #> [26,] 1.3521439 #> [27,] 1.3491249 #> [28,] 1.3707507 #> [29,] 1.4215683 #> [30,] 1.3441005 #>  #> , , 63 #>  #>            [,1] #>  [1,] 1.3553817 #>  [2,] 1.4215725 #>  [3,] 1.5944878 #>  [4,] 1.5089831 #>  [5,] 1.5536211 #>  [6,] 1.5773313 #>  [7,] 1.5140225 #>  [8,] 1.5183968 #>  [9,] 1.4453326 #> [10,] 1.5268620 #> [11,] 1.1797639 #> [12,] 1.0570623 #> [13,] 1.1603207 #> [14,] 0.9532579 #> [15,] 1.1288743 #> [16,] 1.1668135 #> [17,] 1.1644841 #> [18,] 1.0190693 #> [19,] 1.2080644 #> [20,] 1.0656753 #> [21,] 1.3824786 #> [22,] 1.2406248 #> [23,] 1.3822426 #> [24,] 1.4770597 #> [25,] 1.2152067 #> [26,] 1.3093151 #> [27,] 1.3083668 #> [28,] 1.3312773 #> [29,] 1.3871450 #> [30,] 1.3052853 #>  #> , , 64 #>  #>            [,1] #>  [1,] 1.3587222 #>  [2,] 1.4225294 #>  [3,] 1.5977128 #>  [4,] 1.5138484 #>  [5,] 1.5600502 #>  [6,] 1.5758781 #>  [7,] 1.5120109 #>  [8,] 1.5197338 #>  [9,] 1.4519194 #> [10,] 1.5349034 #> [11,] 1.1987063 #> [12,] 1.0741285 #> [13,] 1.1771162 #> [14,] 0.9712769 #> [15,] 1.1471564 #> [16,] 1.1832801 #> [17,] 1.1826141 #> [18,] 1.0377580 #> [19,] 1.2251672 #> [20,] 1.0828420 #> [21,] 1.3538765 #> [22,] 1.2016932 #> [23,] 1.3515010 #> [24,] 1.4495462 #> [25,] 1.1735221 #> [26,] 1.2646324 #> [27,] 1.2657438 #> [28,] 1.2899001 #> [29,] 1.3508723 #> [30,] 1.2646052 #>  #> , , 65 #>  #>            [,1] #>  [1,] 1.3613486 #>  [2,] 1.4224928 #>  [3,] 1.6000602 #>  [4,] 1.5178818 #>  [5,] 1.5656884 #>  [6,] 1.5733362 #>  [7,] 1.5088866 #>  [8,] 1.5201970 #>  [9,] 1.4578473 #> [10,] 1.5422554 #> [11,] 1.2169530 #> [12,] 1.0910020 #> [13,] 1.1933536 #> [14,] 0.9891794 #> [15,] 1.1649024 #> [16,] 1.1994030 #> [17,] 1.2001663 #> [18,] 1.0560056 #> [19,] 1.2418021 #> [20,] 1.0996652 #> [21,] 1.3235930 #> [22,] 1.1609943 #> [23,] 1.3191327 #> [24,] 1.4203720 #> [25,] 1.1301365 #> [26,] 1.2181418 #> [27,] 1.2212897 #> [28,] 1.2466615 #> [29,] 1.3127835 #> [30,] 1.2221012 #>  #> , , 66 #>  #>           [,1] #>  [1,] 1.363258 #>  [2,] 1.421506 #>  [3,] 1.601321 #>  [4,] 1.521083 #>  [5,] 1.570403 #>  [6,] 1.569659 #>  [7,] 1.504724 #>  [8,] 1.519795 #>  [9,] 1.463040 #> [10,] 1.548838 #> [11,] 1.234855 #> [12,] 1.107568 #> [13,] 1.209212 #> [14,] 1.006661 #> [15,] 1.182282 #> [16,] 1.214826 #> [17,] 1.217348 #> [18,] 1.074039 #> [19,] 1.257965 #> [20,] 1.116075 #> [21,] 1.291805 #> [22,] 1.118568 #> [23,] 1.285164 #> [24,] 1.389559 #> [25,] 1.085093 #> [26,] 1.169892 #> [27,] 1.175032 #> [28,] 1.201606 #> [29,] 1.272914 #> [30,] 1.177817 #>  #> , , 67 #>  #>           [,1] #>  [1,] 1.364439 #>  [2,] 1.419607 #>  [3,] 1.601576 #>  [4,] 1.523446 #>  [5,] 1.574236 #>  [6,] 1.564908 #>  [7,] 1.499500 #>  [8,] 1.518526 #>  [9,] 1.467338 #> [10,] 1.554517 #> [11,] 1.252405 #> [12,] 1.123689 #> [13,] 1.224763 #> [14,] 1.024030 #> [15,] 1.199364 #> [16,] 1.229876 #> [17,] 1.234203 #> [18,] 1.091702 #> [19,] 1.273817 #> [20,] 1.132254 #> [21,] 1.258535 #> [22,] 1.074458 #> [23,] 1.249624 #> [24,] 1.357131 #> [25,] 1.038426 #> [26,] 1.119933 #> [27,] 1.127038 #> [28,] 1.154782 #> [29,] 1.231301 #> [30,] 1.131798 #>  #> , , 68 #>  #>            [,1] #>  [1,] 1.3646621 #>  [2,] 1.4167922 #>  [3,] 1.6009291 #>  [4,] 1.5249676 #>  [5,] 1.5772383 #>  [6,] 1.5589992 #>  [7,] 1.4932408 #>  [8,] 1.5162612 #>  [9,] 1.4709127 #> [10,] 1.5594168 #> [11,] 1.2693643 #> [12,] 1.1396006 #> [13,] 1.2397390 #> [14,] 1.0410823 #> [15,] 1.2158924 #> [16,] 1.2445551 #> [17,] 1.2505222 #> [18,] 1.1090026 #> [19,] 1.2891276 #> [20,] 1.1480160 #> [21,] 1.2238100 #> [22,] 1.0287080 #> [23,] 1.2125411 #> [24,] 1.3231116 #> [25,] 0.9901509 #> [26,] 1.0683186 #> [27,] 1.0773716 #> [28,] 1.1062386 #> [29,] 1.1879486 #> [30,] 1.0840929 #>  #> , , 69 #>  #>            [,1] #>  [1,] 1.3640946 #>  [2,] 1.4130604 #>  [3,] 1.5993906 #>  [4,] 1.5256420 #>  [5,] 1.5793689 #>  [6,] 1.5519690 #>  [7,] 1.4859544 #>  [8,] 1.5130615 #>  [9,] 1.4737901 #> [10,] 1.5635724 #> [11,] 1.2858429 #> [12,] 1.1550483 #> [13,] 1.2543117 #> [14,] 1.0579122 #> [15,] 1.2320260 #> [16,] 1.2586610 #> [17,] 1.2663874 #> [18,] 1.1260743 #> [19,] 1.3039986 #> [20,] 1.1634044 #> [21,] 1.1876552 #> [22,] 0.9813656 #> [23,] 1.1739480 #> [24,] 1.2875289 #> [25,] 0.9403200 #> [26,] 1.0151044 #> [27,] 1.0260861 #> [28,] 1.0560280 #> [29,] 1.1429193 #> [30,] 1.0347522 #>  #> , , 70 #>  #>            [,1] #>  [1,] 1.3627956 #>  [2,] 1.4084087 #>  [3,] 1.5969580 #>  [4,] 1.5253979 #>  [5,] 1.5806271 #>  [6,] 1.5438541 #>  [7,] 1.4776374 #>  [8,] 1.5088985 #>  [9,] 1.4759888 #> [10,] 1.5670155 #> [11,] 1.3019395 #> [12,] 1.1702143 #> [13,] 1.2685620 #> [14,] 1.0745311 #> [15,] 1.2478456 #> [16,] 1.2722415 #> [17,] 1.2819058 #> [18,] 1.1426432 #> [19,] 1.3185483 #> [20,] 1.1785366 #> [21,] 1.1500989 #> [22,] 0.9324801 #> [23,] 1.1338777 #> [24,] 1.2504105 #> [25,] 0.8890333 #> [26,] 0.9603482 #> [27,] 0.9732372 #> [28,] 1.0041948 #> [29,] 1.0962753 #> [30,] 0.9838287 #>  #> , , 71 #>  #>            [,1] #>  [1,] 1.3607627 #>  [2,] 1.4028069 #>  [3,] 1.5936287 #>  [4,] 1.5240672 #>  [5,] 1.5810665 #>  [6,] 1.5346517 #>  [7,] 1.4682863 #>  [8,] 1.5038169 #>  [9,] 1.4774256 #> [10,] 1.5696580 #> [11,] 1.3175550 #> [12,] 1.1850890 #> [13,] 1.2822236 #> [14,] 1.0907699 #> [15,] 1.2630971 #> [16,] 1.2854289 #> [17,] 1.2969368 #> [18,] 1.1589350 #> [19,] 1.3324787 #> [20,] 1.1931732 #> [21,] 1.1111705 #> [22,] 0.8821031 #> [23,] 1.0923650 #> [24,] 1.2117861 #> [25,] 0.8363453 #> [26,] 0.9041101 #> [27,] 0.9188832 #> [28,] 0.9507671 #> [29,] 1.0480629 #> [30,] 0.9313776 #>  #> , , 72 #>  #>            [,1] #>  [1,] 1.3579935 #>  [2,] 1.3962123 #>  [3,] 1.5893210 #>  [4,] 1.5218638 #>  [5,] 1.5805193 #>  [6,] 1.5243589 #>  [7,] 1.4578982 #>  [8,] 1.4978529 #>  [9,] 1.4779560 #> [10,] 1.5713921 #> [11,] 1.3325300 #> [12,] 1.1994420 #> [13,] 1.2954584 #> [14,] 1.1068783 #> [15,] 1.2779265 #> [16,] 1.2981754 #> [17,] 1.3114213 #> [18,] 1.1749583 #> [19,] 1.3460061 #> [20,] 1.2074992 #> [21,] 1.0709005 #> [22,] 0.8302883 #> [23,] 1.0494462 #> [24,] 1.1715739 #> [25,] 0.7823124 #> [26,] 0.8464524 #> [27,] 0.8630842 #> [28,] 0.8958474 #> [29,] 0.9983306 #> [30,] 0.8774562 #>  #> , , 73 #>  #>            [,1] #>  [1,] 1.3544789 #>  [2,] 1.3886845 #>  [3,] 1.5838804 #>  [4,] 1.5187916 #>  [5,] 1.5790937 #>  [6,] 1.5129731 #>  [7,] 1.4464697 #>  [8,] 1.4910096 #>  [9,] 1.4777401 #> [10,] 1.5723141 #> [11,] 1.3471174 #> [12,] 1.2135806 #> [13,] 1.3083575 #> [14,] 1.1225381 #> [15,] 1.2924266 #> [16,] 1.3102152 #> [17,] 1.3255492 #> [18,] 1.1904146 #> [19,] 1.3592074 #> [20,] 1.2214997 #> [21,] 1.0293127 #> [22,] 0.7770918 #> [23,] 1.0049949 #> [24,] 1.1298922 #> [25,] 0.7269930 #> [26,] 0.7874397 #> [27,] 0.8059028 #> [28,] 0.8394977 #> [29,] 0.9471289 #> [30,] 0.8221242 #>  #> , , 74 #>  #>            [,1] #>  [1,] 1.3500223 #>  [2,] 1.3801440 #>  [3,] 1.5775005 #>  [4,] 1.5148463 #>  [5,] 1.5768270 #>  [6,] 1.5004916 #>  [7,] 1.4339978 #>  [8,] 1.4832791 #>  [9,] 1.4768060 #> [10,] 1.5724639 #> [11,] 1.3613226 #> [12,] 1.2272829 #> [13,] 1.3206570 #> [14,] 1.1380442 #> [15,] 1.3063477 #> [16,] 1.3218657 #> [17,] 1.3392405 #> [18,] 1.2056365 #> [19,] 1.3717083 #> [20,] 1.2349864 #> [21,] 0.9863961 #> [22,] 0.7225716 #> [23,] 0.9591931 #> [24,] 1.0867357 #> [25,] 0.6704474 #> [26,] 0.7271387 #> [27,] 0.7474037 #> [28,] 0.7817820 #> [29,] 0.8945102 #> [30,] 0.7654432 #>  #> , , 75 #>  #>            [,1] #>  [1,] 1.3447197 #>  [2,] 1.3706245 #>  [3,] 1.5702036 #>  [4,] 1.5100233 #>  [5,] 1.5736628 #>  [6,] 1.4869118 #>  [7,] 1.4203947 #>  [8,] 1.4744822 #>  [9,] 1.4751765 #> [10,] 1.5718814 #> [11,] 1.3747326 #> [12,] 1.2405996 #> [13,] 1.3325074 #> [14,] 1.1532263 #> [15,] 1.3198200 #> [16,] 1.3331220 #> [17,] 1.3522848 #> [18,] 1.2205029 #> [19,] 1.3838457 #> [20,] 1.2482038 #> [21,] 0.9420905 #> [22,] 0.6667878 #> [23,] 0.9121164 #> [24,] 1.0421935 #> [25,] 0.6127382 #> [26,] 0.6656180 #> [27,] 0.6876538 #> [28,] 0.7227664 #> [29,] 0.8405290 #> [30,] 0.7074770 #>  #> , , 76 #>  #>            [,1] #>  [1,] 1.3386641 #>  [2,] 1.3601724 #>  [3,] 1.5619960 #>  [4,] 1.5043182 #>  [5,] 1.5695841 #>  [6,] 1.4722312 #>  [7,] 1.4057022 #>  [8,] 1.4647944 #>  [9,] 1.4727607 #> [10,] 1.5704701 #> [11,] 1.3877477 #> [12,] 1.2536574 #> [13,] 1.3440098 #> [14,] 1.1681079 #> [15,] 1.3329492 #> [16,] 1.3436449 #> [17,] 1.3649645 #> [18,] 1.2348588 #> [19,] 1.3956517 #> [20,] 1.2610108 #> [21,] 0.8965506 #> [22,] 0.6098026 #> [23,] 0.8638106 #> [24,] 0.9963283 #> [25,] 0.5539294 #> [26,] 0.6029485 #> [27,] 0.6267218 #> [28,] 0.6625193 #> [29,] 0.7852420 #> [30,] 0.6482917 #>  #> , , 77 #>  #>            [,1] #>  [1,] 1.3318580 #>  [2,] 1.3487858 #>  [3,] 1.5528757 #>  [4,] 1.4976316 #>  [5,] 1.5646629 #>  [6,] 1.4564432 #>  [7,] 1.3899564 #>  [8,] 1.4541383 #>  [9,] 1.4694311 #> [10,] 1.5681491 #> [11,] 1.4003589 #> [12,] 1.2661238 #> [13,] 1.3549048 #> [14,] 1.1827817 #> [15,] 1.3454915 #> [16,] 1.3537039 #> [17,] 1.3772446 #> [18,] 1.2489525 #> [19,] 1.4066850 #> [20,] 1.2733407 #> [21,] 0.8498605 #> [22,] 0.5516801 #> [23,] 0.8143207 #> [24,] 0.9491842 #> [25,] 0.4940871 #> [26,] 0.5392029 #> [27,] 0.5646786 #> [28,] 0.6011110 #> [29,] 0.7287074 #> [30,] 0.5879550 #>  #> , , 78 #>  #>            [,1] #>  [1,] 1.3242993 #>  [2,] 1.3364633 #>  [3,] 1.5428403 #>  [4,] 1.4898603 #>  [5,] 1.5586947 #>  [6,] 1.4395212 #>  [7,] 1.3731544 #>  [8,] 1.4425499 #>  [9,] 1.4653339 #> [10,] 1.5649857 #> [11,] 1.4122880 #> [12,] 1.2783652 #> [13,] 1.3653289 #> [14,] 1.1969927 #> [15,] 1.3575591 #> [16,] 1.3633435 #> [17,] 1.3888151 #> [18,] 1.2625813 #> [19,] 1.4173907 #> [20,] 1.2854027 #> [21,] 0.8020599 #> [22,] 0.4924866 #> [23,] 0.7636935 #> [24,] 0.9008024 #> [25,] 0.4332791 #> [26,] 0.4744558 #> [27,] 0.5015971 #> [28,] 0.5386141 #> [29,] 0.6709856 #> [30,] 0.5265299 #>  #> , , 79 #>  #>            [,1] #>  [1,] 1.3159813 #>  [2,] 1.3232032 #>  [3,] 1.5316557 #>  [4,] 1.4811658 #>  [5,] 1.5518561 #>  [6,] 1.4213588 #>  [7,] 1.3552933 #>  [8,] 1.4300746 #>  [9,] 1.4604993 #> [10,] 1.5610236 #> [11,] 1.4236870 #> [12,] 1.2902017 #> [13,] 1.3753943 #> [14,] 1.2110615 #> [15,] 1.3692712 #> [16,] 1.3724066 #> [17,] 1.4000103 #> [18,] 1.2758084 #> [19,] 1.4277211 #> [20,] 1.2969726 #> [21,] 0.7531895 #> [22,] 0.4322898 #> [23,] 0.7119771 #> [24,] 0.8512257 #> [25,] 0.3715752 #> [26,] 0.4087836 #> [27,] 0.4375519 #> [28,] 0.4751026 #> [29,] 0.6121389 #> [30,] 0.4640418 #>  #> , , 80 #>  #>            [,1] #>  [1,] 1.3067412 #>  [2,] 1.3089834 #>  [3,] 1.5194468 #>  [4,] 1.4715627 #>  [5,] 1.5441633 #>  [6,] 1.4020376 #>  [7,] 1.3363705 #>  [8,] 1.4167114 #>  [9,] 1.4549542 #> [10,] 1.5563109 #> [11,] 1.4346565 #> [12,] 1.3015510 #> [13,] 1.3848467 #> [14,] 1.2246810 #> [15,] 1.3803914 #> [16,] 1.3808325 #> [17,] 1.4108284 #> [18,] 1.2887599 #> [19,] 1.4372927 #> [20,] 1.3081153 #> [21,] 0.7032915 #> [22,] 0.3711599 #> [23,] 0.6592211 #> [24,] 0.8004979 #> [25,] 0.3090464 #> [26,] 0.3422646 #> [27,] 0.3726194 #> [28,] 0.4106530 #> [29,] 0.5522308 #> [30,] 0.4006283 #>  #> , , 81 #>  #>            [,1] #>  [1,] 1.2965994 #>  [2,] 1.2937685 #>  [3,] 1.5062941 #>  [4,] 1.4610518 #>  [5,] 1.5355554 #>  [6,] 1.3816033 #>  [7,] 1.3163536 #>  [8,] 1.4023828 #>  [9,] 1.4485999 #> [10,] 1.5507427 #> [11,] 1.4450761 #> [12,] 1.3126507 #> [13,] 1.3938076 #> [14,] 1.2380895 #> [15,] 1.3910117 #> [16,] 1.3888336 #> [17,] 1.4208911 #> [18,] 1.3011020 #> [19,] 1.4465294 #> [20,] 1.3189776 #> [21,] 0.6524090 #> [22,] 0.3091682 #> [23,] 0.6054764 #> [24,] 0.7486647 #> [25,] 0.2457656 #> [26,] 0.2749787 #> [27,] 0.3068779 #> [28,] 0.3453432 #> [29,] 0.4913160 #> [30,] 0.3363650 #>  #> , , 82 #>  #>            [,1] #>  [1,] 1.2856851 #>  [2,] 1.2775820 #>  [3,] 1.4922169 #>  [4,] 1.4496284 #>  [5,] 1.5259986 #>  [6,] 1.3600537 #>  [7,] 1.2952239 #>  [8,] 1.3870493 #>  [9,] 1.4413259 #> [10,] 1.5442634 #> [11,] 1.4547977 #> [12,] 1.3231775 #> [13,] 1.4024001 #> [14,] 1.2511813 #> [15,] 1.4012656 #> [16,] 1.3964053 #> [17,] 1.4305587 #> [18,] 1.3131517 #> [19,] 1.4553486 #> [20,] 1.3292711 #> [21,] 0.6005866 #> [22,] 0.2463883 #> [23,] 0.5507955 #> [24,] 0.6957728 #> [25,] 0.1818073 #> [26,] 0.2070074 #> [27,] 0.2404073 #> [28,] 0.2792529 #> [29,] 0.4294677 #> [30,] 0.2713295 #>  #> , , 83 #>  #>            [,1] #>  [1,] 1.2740051 #>  [2,] 1.2603728 #>  [3,] 1.4772132 #>  [4,] 1.4372881 #>  [5,] 1.5155577 #>  [6,] 1.3373872 #>  [7,] 1.2730220 #>  [8,] 1.3708049 #>  [9,] 1.4332642 #> [10,] 1.5369152 #> [11,] 1.4640875 #> [12,] 1.3334063 #> [13,] 1.4103763 #> [14,] 1.2638793 #> [15,] 1.4109249 #> [16,] 1.4031414 #> [17,] 1.4398309 #> [18,] 1.3248473 #> [19,] 1.4634289 #> [20,] 1.3392003 #> [21,] 0.5478700 #> [22,] 0.1828950 #> [23,] 0.4952320 #> [24,] 0.6418646 #> [25,] 0.1172473 #> [26,] 0.1384315 #> [27,] 0.1732890 #> [28,] 0.2124636 #> [29,] 0.3667635 #> [30,] 0.2056007 #>  #> , , 84 #>  #>             [,1] #>  [1,] 1.26155728 #>  [2,] 1.24216389 #>  [3,] 1.46128122 #>  [4,] 1.42390124 #>  [5,] 1.50403555 #>  [6,] 1.31360190 #>  [7,] 1.24974793 #>  [8,] 1.35359915 #>  [9,] 1.42444643 #> [10,] 1.52874271 #> [11,] 1.47294021 #> [12,] 1.34326005 #> [13,] 1.41784112 #> [14,] 1.27638286 #> [15,] 1.42006007 #> [16,] 1.40946117 #> [17,] 1.44839582 #> [18,] 1.33594577 #> [19,] 1.47115958 #> [20,] 1.34879274 #> [21,] 0.49430153 #> [22,] 0.11876494 #> [23,] 0.43884097 #> [24,] 0.58690910 #> [25,] 0.05216211 #> [26,] 0.06932803 #> [27,] 0.10560602 #> [28,] 0.14505807 #> [29,] 0.30327400 #> [30,] 0.13925909 #>  #> , , 85 #>  #>                [,1] #>  [1,]  1.2483379427 #>  [2,]  1.2230088828 #>  [3,]  1.4443033260 #>  [4,]  1.4094339458 #>  [5,]  1.4916403005 #>  [6,]  1.2886963885 #>  [7,]  1.2253730337 #>  [8,]  1.3354545370 #>  [9,]  1.4149035327 #> [10,]  1.5198003313 #> [11,]  1.4809464985 #> [12,]  1.3525576942 #> [13,]  1.4249290951 #> [14,]  1.2883637999 #> [15,]  1.4288190829 #> [16,]  1.4153512537 #> [17,]  1.4564925318 #> [18,]  1.3467719926 #> [19,]  1.4784241064 #> [20,]  1.3578015666 #> [21,]  0.4398676374 #> [22,]  0.0540762322 #> [23,]  0.3816787039 #> [24,]  0.5310553860 #> [25,] -0.0133746322 #> [26,] -0.0002024938 #> [27,]  0.0374426288 #> [28,]  0.0771208727 #> [29,]  0.2390715572 #> [30,]  0.0723868022 #>  #> , , 86 #>  #>               [,1] #>  [1,]  1.234218446 #>  [2,]  1.202906842 #>  [3,]  1.426209358 #>  [4,]  1.393992892 #>  [5,]  1.478368843 #>  [6,]  1.262669357 #>  [7,]  1.199821683 #>  [8,]  1.316417701 #>  [9,]  1.404528767 #> [10,]  1.509975851 #> [11,]  1.488516653 #> [12,]  1.361610317 #> [13,]  1.431399318 #> [14,]  1.300193987 #> [15,]  1.436983100 #> [16,]  1.420518944 #> [17,]  1.464174327 #> [18,]  1.357152316 #> [19,]  1.484995586 #> [20,]  1.366494315 #> [21,]  0.384612485 #> [22,] -0.011091648 #> [23,]  0.323802331 #> [24,]  0.474356008 #> [25,] -0.079287026 #> [26,] -0.070072560 #> [27,] -0.031115472 #> [28,]  0.008737797 #> [29,]  0.174229834 #> [30,]  0.005067146 #>  #> , , 87 #>  #>              [,1] #>  [1,]  1.21914100 #>  [2,]  1.18185693 #>  [3,]  1.40713221 #>  [4,]  1.37760191 #>  [5,]  1.46417212 #>  [6,]  1.23551977 #>  [7,]  1.17319252 #>  [8,]  1.29648825 #>  [9,]  1.39322962 #> [10,]  1.49922539 #> [11,]  1.49564726 #> [12,]  1.37013646 #> [13,]  1.43733917 #> [14,]  1.31158099 #> [15,]  1.44459938 #> [16,]  1.42513321 #> [17,]  1.47122001 #> [18,]  1.36700520 #> [19,]  1.49120018 #> [20,]  1.37472999 #> [21,]  0.32867947 #> [22,] -0.07665784 #> [23,]  0.26521953 #> [24,]  0.41682619 #> [25,] -0.14547261 #> [26,] -0.14019384 #> [27,] -0.09998138 #> [28,] -0.06000405 #> [29,]  0.10882392 #> [30,] -0.06261525 #>  #> , , 88 #>  #>              [,1] #>  [1,]  1.20327257 #>  [2,]  1.15985845 #>  [3,]  1.38710309 #>  [4,]  1.36026794 #>  [5,]  1.44900927 #>  [6,]  1.20724689 #>  [7,]  1.14548445 #>  [8,]  1.27551809 #>  [9,]  1.38112263 #> [10,]  1.48759888 #> [11,]  1.50202612 #> [12,]  1.37825966 #> [13,]  1.44289470 #> [14,]  1.32268355 #> [15,]  1.45183108 #> [16,]  1.42929650 #> [17,]  1.47770561 #> [18,]  1.37656127 #> [19,]  1.49687765 #> [20,]  1.38245034 #> [21,]  0.27212083 #> [22,] -0.14254023 #> [23,]  0.20602061 #> [24,]  0.35854759 #> [25,] -0.21184907 #> [26,] -0.21047695 #> [27,] -0.16906709 #> [28,] -0.12901636 #> [29,]  0.04293019 #> [30,] -0.13057458 #>  #> , , 89 #>  #>              [,1] #>  [1,]  1.18662423 #>  [2,]  1.13689821 #>  [3,]  1.36613578 #>  [4,]  1.34198659 #>  [5,]  1.43288591 #>  [6,]  1.17785031 #>  [7,]  1.11669674 #>  [8,]  1.25360978 #>  [9,]  1.36824107 #> [10,]  1.47512731 #> [11,]  1.50784734 #> [12,]  1.38605208 #> [13,]  1.44783276 #> [14,]  1.33347581 #> [15,]  1.45846929 #> [16,]  1.43290533 #> [17,]  1.48376767 #> [18,]  1.38556693 #> [19,]  1.50191861 #> [20,]  1.38987259 #> [21,]  0.21498933 #> [22,] -0.20865552 #> [23,]  0.14630553 #> [24,]  0.29959522 #> [25,] -0.27833316 #> [26,] -0.28083160 #> [27,] -0.23828357 #> [28,] -0.19820975 #> [29,] -0.02337371 #> [30,] -0.19872395 #>  #> , , 90 #>  #>              [,1] #>  [1,]  1.16919413 #>  [2,]  1.11294810 #>  [3,]  1.34422885 #>  [4,]  1.32275353 #>  [5,]  1.41568813 #>  [6,]  1.14726108 #>  [7,]  1.08682910 #>  [8,]  1.23077701 #>  [9,]  1.35461995 #> [10,]  1.46185660 #> [11,]  1.51320516 #> [12,]  1.39322814 #> [13,]  1.45222208 #> [14,]  1.34381002 #> [15,]  1.46453685 #> [16,]  1.43577242 #> [17,]  1.48926434 #> [18,]  1.39415924 #> [19,]  1.50657991 #> [20,]  1.39674826 #> [21,]  0.15733865 #> [22,] -0.27491934 #> [23,]  0.08613815 #> [24,]  0.24002764 #> [25,] -0.34484076 #> [26,] -0.35116665 #> [27,] -0.30754086 #> [28,] -0.26749383 #> [29,] -0.09000901 #> [30,] -0.26697550 #>  #> , , 91 #>  #>              [,1] #>  [1,]  1.15098046 #>  [2,]  1.08799585 #>  [3,]  1.32135343 #>  [4,]  1.30240757 #>  [5,]  1.39759573 #>  [6,]  1.11543919 #>  [7,]  1.05588171 #>  [8,]  1.20698990 #>  [9,]  1.34014431 #> [10,]  1.44767678 #> [11,]  1.51796045 #> [12,]  1.40015310 #> [13,]  1.45622056 #> [14,]  1.35397954 #> [15,]  1.47021253 #> [16,]  1.43819648 #> [17,]  1.49410151 #> [18,]  1.40242087 #> [19,]  1.51064702 #> [20,]  1.40316321 #> [21,]  0.09922337 #> [22,] -0.34124543 #> [23,]  0.02558185 #> [24,]  0.17990318 #> [25,] -0.41128699 #> [26,] -0.42139026 #> [27,] -0.37674824 #> [28,] -0.33677737 #> [29,] -0.15689587 #> [30,] -0.33524049 #>  #> , , 92 #>  #>              [,1] #>  [1,]  1.13187486 #>  [2,]  1.06202073 #>  [3,]  1.29733710 #>  [4,]  1.28098928 #>  [5,]  1.37860579 #>  [6,]  1.08246416 #>  [7,]  1.02385529 #>  [8,]  1.18226473 #>  [9,]  1.32474027 #> [10,]  1.43255641 #> [11,]  1.52198426 #> [12,]  1.40659071 #> [13,]  1.45960329 #> [14,]  1.36357141 #> [15,]  1.47529787 #> [16,]  1.44018697 #> [17,]  1.49850783 #> [18,]  1.41002344 #> [19,]  1.51413516 #> [20,]  1.40928197 #> [21,]  0.04069891 #> [22,] -0.40754200 #> [23,] -0.03529909 #> [24,]  0.11928119 #> [25,] -0.47758631 #> [26,] -0.49141001 #> [27,] -0.44581428 #> [28,] -0.40596835 #> [29,] -0.22395344 #> [30,] -0.40342940 #>  #> , , 93 #>  #>              [,1] #>  [1,]  1.11178837 #>  [2,]  1.03503569 #>  [3,]  1.27226560 #>  [4,]  1.25854973 #>  [5,]  1.35868053 #>  [6,]  1.04836405 #>  [7,]  0.99075115 #>  [8,]  1.15664739 #>  [9,]  1.30850888 #> [10,]  1.41655330 #> [11,]  1.52554368 #> [12,]  1.41253788 #> [13,]  1.46241951 #> [14,]  1.37299238 #> [15,]  1.47979022 #> [16,]  1.44129928 #> [17,]  1.50239237 #> [18,]  1.41732319 #> [19,]  1.51723588 #> [20,]  1.41477065 #> [21,] -0.01817850 #> [22,] -0.47372151 #> [23,] -0.09643957 #> [24,]  0.05822193 #> [25,] -0.54365264 #> [26,] -0.56113301 #> [27,] -0.51464701 #> [28,] -0.47497415 #> [29,] -0.29109998 #> [30,] -0.47145207 #>  #> , , 94 #>  #>               [,1] #>  [1,]  1.090886738 #>  [2,]  1.007102963 #>  [3,]  1.246220155 #>  [4,]  1.235120205 #>  [5,]  1.337776402 #>  [6,]  1.013146523 #>  [7,]  0.956571274 #>  [8,]  1.130112907 #>  [9,]  1.291484548 #> [10,]  1.399684946 #> [11,]  1.528621181 #> [12,]  1.418211044 #> [13,]  1.464839217 #> [14,]  1.381988679 #> [15,]  1.483884453 #> [16,]  1.441948366 #> [17,]  1.505568721 #> [18,]  1.424187100 #> [19,]  1.519672807 #> [20,]  1.419864956 #> [21,] -0.077351844 #> [22,] -0.539696206 #> [23,] -0.157773678 #> [24,] -0.003213404 #> [25,] -0.609399428 #> [26,] -0.630466013 #> [27,] -0.583153987 #> [28,] -0.543701616 #> [29,] -0.358252974 #> [30,] -0.539217798 #>  #> , , 95 #>  #>              [,1] #>  [1,]  1.06918841 #>  [2,]  0.97822391 #>  [3,]  1.21922941 #>  [4,]  1.21071637 #>  [5,]  1.31583312 #>  [6,]  0.97681482 #>  [7,]  0.92131716 #>  [8,]  1.10252162 #>  [9,]  1.27370689 #> [10,]  1.38198774 #> [11,]  1.53082685 #> [12,]  1.42322797 #> [13,]  1.46664608 #> [14,]  1.39061555 #> [15,]  1.48739288 #> [16,]  1.44214024 #> [17,]  1.50831326 #> [18,]  1.43045796 #> [19,]  1.52158866 #> [20,]  1.42463812 #> [21,] -0.13676367 #> [22,] -0.60537781 #> [23,] -0.21923481 #> [24,] -0.06497157 #> [25,] -0.67473983 #> [26,] -0.69931558 #> [27,] -0.65124249 #> [28,] -0.61205722 #> [29,] -0.42532916 #> [30,] -0.60663546 #>  #> , , 96 #>  #>             [,1] #>  [1,]  1.0466979 #>  [2,]  0.9484003 #>  [3,]  1.1912930 #>  [4,]  1.1853349 #>  [5,]  1.2928264 #>  [6,]  0.9393730 #>  [7,]  0.8848584 #>  [8,]  1.0740416 #>  [9,]  1.2550527 #> [10,]  1.3633547 #> [11,]  1.5325655 #> [12,]  1.4279548 #> [13,]  1.4678691 #> [14,]  1.3989480 #> [15,]  1.4902864 #> [16,]  1.4416416 #> [17,]  1.5105586 #> [18,]  1.4364302 #> [19,]  1.5231145 #> [20,]  1.4287264 #> [21,] -0.1963741 #> [22,] -0.6706776 #> [23,] -0.2807557 #> [24,] -0.1269871 #> [25,] -0.7395868 #> [26,] -0.7675882 #> [27,] -0.7188196 #> [28,] -0.6799472 #> [29,] -0.4922447 #> [30,] -0.6735828 #>  #> , , 97 #>  #>             [,1] #>  [1,]  1.0234144 #>  [2,]  0.9176345 #>  [3,]  1.1624109 #>  [4,]  1.1589729 #>  [5,]  1.2689064 #>  [6,]  0.9008260 #>  [7,]  0.8472726 #>  [8,]  1.0446352 #>  [9,]  1.2354679 #> [10,]  1.3437677 #> [11,]  1.5338387 #> [12,]  1.4322345 #> [13,]  1.4686907 #> [14,]  1.4067741 #> [15,]  1.4927766 #> [16,]  1.4405020 #> [17,]  1.5120527 #> [18,]  1.4418706 #> [19,]  1.5239044 #> [20,]  1.4324873 #> [21,] -0.2560843 #> [22,] -0.7355066 #> [23,] -0.3422685 #> [24,] -0.1891755 #> [25,] -0.8038530 #> [26,] -0.8351904 #> [27,] -0.7857924 #> [28,] -0.7472776 #> [29,] -0.5589152 #> [30,] -0.7399823 #>  #> , , 98 #>  #>             [,1] #>  [1,]  0.9992354 #>  [2,]  0.8859250 #>  [3,]  1.1324315 #>  [4,]  1.1314386 #>  [5,]  1.2440709 #>  [6,]  0.8611797 #>  [7,]  0.8086275 #>  [8,]  1.0142873 #>  [9,]  1.2150379 #> [10,]  1.3232927 #> [11,]  1.5343060 #> [12,]  1.4359609 #> [13,]  1.4689033 #> [14,]  1.4144345 #> [15,]  1.4946866 #> [16,]  1.4388939 #> [17,]  1.5131040 #> [18,]  1.4468001 #> [19,]  1.5242310 #> [20,]  1.4358063 #> [21,] -0.3158286 #> [22,] -0.7997757 #> [23,] -0.4037048 #> [24,] -0.2514722 #> [25,] -0.8674516 #> [26,] -0.9020290 #> [27,] -0.8520680 #> [28,] -0.8139547 #> [29,] -0.6252559 #> [30,] -0.8057462 #>  #> , , 99 #>  #>             [,1] #>  [1,]  0.9740949 #>  [2,]  0.8532536 #>  [3,]  1.1013759 #>  [4,]  1.1028524 #>  [5,]  1.2182932 #>  [6,]  0.8204410 #>  [7,]  0.7689329 #>  [8,]  0.9830164 #>  [9,]  1.1937982 #> [10,]  1.3019342 #> [11,]  1.5342014 #> [12,]  1.4394249 #> [13,]  1.4685152 #> [14,]  1.4215358 #> [15,]  1.4959603 #> [16,]  1.4367669 #> [17,]  1.5136851 #> [18,]  1.4514111 #> [19,]  1.5241701 #> [20,]  1.4385511 #> [21,] -0.3755467 #> [22,] -0.8633955 #> [23,] -0.4649959 #> [24,] -0.3138119 #> [25,] -0.9302953 #> [26,] -0.9680110 #> [27,] -0.9175538 #> [28,] -0.8798846 #> [29,] -0.6911819 #> [30,] -0.8707833 #>  #> , , 100 #>  #>             [,1] #>  [1,]  0.9481121 #>  [2,]  0.8195770 #>  [3,]  1.0693166 #>  [4,]  1.0732107 #>  [5,]  1.1915325 #>  [6,]  0.7786181 #>  [7,]  0.7281971 #>  [8,]  0.9508660 #>  [9,]  1.1717934 #> [10,]  1.2797181 #> [11,]  1.5336078 #> [12,]  1.4422932 #> [13,]  1.4677213 #> [14,]  1.4283969 #> [15,]  1.4968261 #> [16,]  1.4337964 #> [17,]  1.5134770 #> [18,]  1.4553968 #> [19,]  1.5232989 #> [20,]  1.4409679 #> [21,] -0.4351775 #> [22,] -0.9262771 #> [23,] -0.5260723 #> [24,] -0.3761233 #> [25,] -0.9922977 #> [26,] -1.0330441 #> [27,] -0.9821576 #> [28,] -0.9449741 #> [29,] -0.7566078 #> [30,] -0.9350022 #>  #> , , 101 #>  #>             [,1] #>  [1,]  0.9213181 #>  [2,]  0.7849087 #>  [3,]  1.0362928 #>  [4,]  1.0425508 #>  [5,]  1.1636571 #>  [6,]  0.7356616 #>  [7,]  0.6864299 #>  [8,]  0.9177451 #>  [9,]  1.1488928 #> [10,]  1.2565415 #> [11,]  1.5323690 #> [12,]  1.4447672 #> [13,]  1.4663231 #> [14,]  1.4348404 #> [15,]  1.4971184 #> [16,]  1.4303684 #> [17,]  1.5128044 #> [18,]  1.4589783 #> [19,]  1.5220214 #> [20,]  1.4428106 #> [21,] -0.4946599 #> [22,] -0.9883315 #> [23,] -0.5868460 #> [24,] -0.4383368 #> [25,] -1.0533671 #> [26,] -1.0970306 #> [27,] -1.0457873 #> [28,] -1.0091302 #> [29,] -0.8214375 #> [30,] -0.9983123 #>  #> , , 102 #>  #>             [,1] #>  [1,]  0.8937305 #>  [2,]  0.7492561 #>  [3,]  1.0023296 #>  [4,]  1.0109005 #>  [5,]  1.1347389 #>  [6,]  0.6915846 #>  [7,]  0.6436423 #>  [8,]  0.8836592 #>  [9,]  1.1250634 #> [10,]  1.2324010 #> [11,]  1.5303791 #> [12,]  1.4468468 #> [13,]  1.4643074 #> [14,]  1.4408634 #> [15,]  1.4967530 #> [16,]  1.4264834 #> [17,]  1.5116682 #> [18,]  1.4621557 #> [19,]  1.5203376 #> [20,]  1.4441682 #> [21,] -0.5539322 #> [22,] -1.0494702 #> [23,] -0.6472151 #> [24,] -0.5003851 #> [25,] -1.1134142 #> [26,] -1.1598783 #> [27,] -1.1083347 #> [28,] -1.0722537 #> [29,] -0.8855817 #> [30,] -1.0606234 #>  #> , , 103 #>  #>             [,1] #>  [1,]  0.8653504 #>  [2,]  0.7126918 #>  [3,]  0.9674295 #>  [4,]  0.9782596 #>  [5,]  1.1048970 #>  [6,]  0.6464592 #>  [7,]  0.5998471 #>  [8,]  0.8487072 #>  [9,]  1.1003750 #> [10,]  1.2073710 #> [11,]  1.5278987 #> [12,]  1.4483192 #> [13,]  1.4618821 #> [14,]  1.4466446 #> [15,]  1.4959760 #> [16,]  1.4217598 #> [17,]  1.5097685 #> [18,]  1.4646912 #> [19,]  1.5178196 #> [20,]  1.4452149 #> [21,] -0.6129326 #> [22,] -1.1096052 #> [23,] -0.7071382 #> [24,] -0.5622015 #> [25,] -1.1722846 #> [26,] -1.2215025 #> [27,] -1.1697070 #> [28,] -1.1342259 #> [29,] -0.9489647 #> [30,] -1.1218461 #>  #> , , 104 #>  #>             [,1] #>  [1,]  0.8360841 #>  [2,]  0.6752237 #>  [3,]  0.9315344 #>  [4,]  0.9446145 #>  [5,]  1.0741310 #>  [6,]  0.6002422 #>  [7,]  0.5550583 #>  [8,]  0.8128505 #>  [9,]  1.0748642 #> [10,]  1.1814438 #> [11,]  1.5248968 #> [12,]  1.4495270 #> [13,]  1.4588578 #> [14,]  1.4518492 #> [15,]  1.4946328 #> [16,]  1.4164971 #> [17,]  1.5073419 #> [18,]  1.4669053 #> [19,]  1.5149249 #> [20,]  1.4455852 #> [21,] -0.6715990 #> [22,] -1.1686491 #> [23,] -0.7665461 #> [24,] -0.6237186 #> [25,] -1.2299578 #> [26,] -1.2818145 #> [27,] -1.2298300 #> [28,] -1.1949842 #> [29,] -1.0115018 #> [30,] -1.1818919 #>  #> , , 105 #>  #>             [,1] #>  [1,]  0.8058915 #>  [2,]  0.6368606 #>  [3,]  0.8945613 #>  [4,]  0.9097917 #>  [5,]  1.0424257 #>  [6,]  0.5529864 #>  [7,]  0.5092919 #>  [8,]  0.7760842 #>  [9,]  1.0485814 #> [10,]  1.1546339 #> [11,]  1.5210113 #> [12,]  1.4501795 #> [13,]  1.4551993 #> [14,]  1.4568804 #> [15,]  1.4926108 #> [16,]  1.4107527 #> [17,]  1.5044383 #> [18,]  1.4686060 #> [19,]  1.5115816 #> [20,]  1.4455417 #> [21,] -0.7298686 #> [22,] -1.2265155 #> [23,] -0.8253690 #> [24,] -0.6848690 #> [25,] -1.2863520 #> [26,] -1.3407266 #> [27,] -1.2886159 #> [28,] -1.2544393 #> [29,] -1.0731090 #> [30,] -1.2406732 #>  #> , , 106 #>  #>             [,1] #>  [1,]  0.7748443 #>  [2,]  0.5976124 #>  [3,]  0.8565563 #>  [4,]  0.8739511 #>  [5,]  1.0097491 #>  [6,]  0.5047314 #>  [7,]  0.4625366 #>  [8,]  0.7384375 #>  [9,]  1.0213894 #> [10,]  1.1268447 #> [11,]  1.5166332 #> [12,]  1.4503637 #> [13,]  1.4511280 #> [14,]  1.4613771 #> [15,]  1.4901742 #> [16,]  1.4043590 #> [17,]  1.5008478 #> [18,]  1.4697391 #> [19,]  1.5074353 #> [20,]  1.4451896 #> [21,] -0.7876541 #> [22,] -1.2831187 #> [23,] -0.8835372 #> [24,] -0.7455854 #> [25,] -1.3413855 #> [26,] -1.3981530 #> [27,] -1.3459780 #> [28,] -1.3125033 #> [29,] -1.1337024 #> [30,] -1.2981037 #>  #> , , 107 #>  #>             [,1] #>  [1,]  0.7429882 #>  [2,]  0.5574902 #>  [3,]  0.8175973 #>  [4,]  0.8370529 #>  [5,]  0.9758963 #>  [6,]  0.4554996 #>  [7,]  0.4147633 #>  [8,]  0.6999507 #>  [9,]  0.9932781 #> [10,]  1.0980886 #> [11,]  1.5117679 #> [12,]  1.4502440 #> [13,]  1.4464633 #> [14,]  1.4655587 #> [15,]  1.4871792 #> [16,]  1.3972342 #> [17,]  1.4966395 #> [18,]  1.4705583 #> [19,]  1.5029118 #> [20,]  1.4440768 #> [21,] -0.8448154 #> [22,] -1.3383744 #> [23,] -0.9409815 #> [24,] -0.8057613 #> [25,] -1.3949779 #> [26,] -1.4540090 #> [27,] -1.4018315 #> [28,] -1.3690895 #> [29,] -1.1931993 #> [30,] -1.3540985 #>  #> , , 108 #>  #>             [,1] #>  [1,]  0.7103549 #>  [2,]  0.5164909 #>  [3,]  0.7777260 #>  [4,]  0.7991401 #>  [5,]  0.9410399 #>  [6,]  0.4053130 #>  [7,]  0.3660780 #>  [8,]  0.6604785 #>  [9,]  0.9643021 #> [10,]  1.0684488 #> [11,]  1.5060495 #> [12,]  1.4494408 #> [13,]  1.4411479 #> [14,]  1.4693448 #> [15,]  1.4834840 #> [16,]  1.3896324 #> [17,]  1.4919491 #> [18,]  1.4707652 #> [19,]  1.4978995 #> [20,]  1.4426268 #> [21,] -0.9013654 #> [22,] -1.3921992 #> [23,] -0.9976328 #> [24,] -0.8653341 #> [25,] -1.4470504 #> [26,] -1.5082122 #> [27,] -1.4560931 #> [28,] -1.4241130 #> [29,] -1.2515176 #> [30,] -1.4085741 #>  #> , , 109 #>  #>             [,1] #>  [1,]  0.6769487 #>  [2,]  0.4745784 #>  [3,]  0.7369520 #>  [4,]  0.7602554 #>  [5,]  0.9052668 #>  [6,]  0.3541963 #>  [7,]  0.3165056 #>  [8,]  0.6201642 #>  [9,]  0.9344992 #> [10,]  1.0379067 #> [11,]  1.4997511 #> [12,]  1.4483534 #> [13,]  1.4354167 #> [14,]  1.4726645 #> [15,]  1.4793719 #> [16,]  1.3815510 #> [17,]  1.4866142 #> [18,]  1.4704943 #> [19,]  1.4921189 #> [20,]  1.4407625 #> [21,] -0.9572430 #> [22,] -1.4445116 #> [23,] -1.0534225 #> [24,] -0.9242549 #> [25,] -1.4975258 #> [26,] -1.5606818 #> [27,] -1.5086813 #> [28,] -1.4774908 #> [29,] -1.3085762 #> [30,] -1.4614487 #>  #> , , 110 #>  #>             [,1] #>  [1,]  0.6426889 #>  [2,]  0.4317715 #>  [3,]  0.6952832 #>  [4,]  0.7204052 #>  [5,]  0.8685803 #>  [6,]  0.3021760 #>  [7,]  0.2660660 #>  [8,]  0.5790419 #>  [9,]  0.9039257 #> [10,]  1.0064652 #> [11,]  1.4929411 #> [12,]  1.4467577 #> [13,]  1.4290980 #> [14,]  1.4757965 #> [15,]  1.4747095 #> [16,]  1.3725251 #> [17,]  1.4806106 #> [18,]  1.4698920 #> [19,]  1.4859561 #> [20,]  1.4382377 #> [21,] -1.0123867 #> [22,] -1.4952314 #> [23,] -1.1082826 #> [24,] -0.9824567 #> [25,] -1.5463286 #> [26,] -1.6113394 #> [27,] -1.5595168 #> [28,] -1.5291418 #> [29,] -1.3642954 #> [30,] -1.5126425 #>  #> , , 111 #>  #>             [,1] #>  [1,]  0.6075641 #>  [2,]  0.3880935 #>  [3,]  0.6525566 #>  [4,]  0.6795562 #>  [5,]  0.8309768 #>  [6,]  0.2492813 #>  [7,]  0.2147672 #>  [8,]  0.5370799 #>  [9,]  0.8724411 #> [10,]  0.9740363 #> [11,]  1.4854466 #> [12,]  1.4446339 #> [13,]  1.4221119 #> [14,]  1.4782811 #> [15,]  1.4693257 #> [16,]  1.3630318 #> [17,]  1.4741317 #> [18,]  1.4685900 #> [19,]  1.4792667 #> [20,]  1.4353745 #> [21,] -1.0667352 #> [22,] -1.5442803 #> [23,] -1.1621458 #> [24,] -1.0398725 #> [25,] -1.5933856 #> [26,] -1.6601088 #> [27,] -1.6085224 #> [28,] -1.5789870 #> [29,] -1.4185965 #> [30,] -1.5620775 #>  #> , , 112 #>  #>             [,1] #>  [1,]  0.5716005 #>  [2,]  0.3436276 #>  [3,]  0.6088877 #>  [4,]  0.6376059 #>  [5,]  0.7924402 #>  [6,]  0.1955045 #>  [7,]  0.1626518 #>  [8,]  0.4942800 #>  [9,]  0.8400592 #> [10,]  0.9406500 #> [11,]  1.4771873 #> [12,]  1.4422395 #> [13,]  1.4147075 #> [14,]  1.4805765 #> [15,]  1.4635216 #> [16,]  1.3530617 #> [17,]  1.4670297 #> [18,]  1.4669147 #> [19,]  1.4718467 #> [20,]  1.4319679 #> [21,] -1.1202276 #> [22,] -1.5915819 #> [23,] -1.2149454 #> [24,] -1.0964297 #> [25,] -1.6386253 #> [26,] -1.7069162 #> [27,] -1.6556234 #> [28,] -1.6269498 #> [29,] -1.4714024 #> [30,] -1.6096780 #>  #> , , 113 #>  #>             [,1] #>  [1,]  0.5348599 #>  [2,]  0.2983948 #>  [3,]  0.5642991 #>  [4,]  0.5947076 #>  [5,]  0.7526987 #>  [6,]  0.1408767 #>  [7,]  0.1097778 #>  [8,]  0.4506898 #>  [9,]  0.8068204 #> [10,]  0.9063981 #> [11,]  1.4684127 #> [12,]  1.4391924 #> [13,]  1.4067218 #> [14,]  1.4823450 #> [15,]  1.4571724 #> [16,]  1.3422983 #> [17,]  1.4592126 #> [18,]  1.4647730 #> [19,]  1.4640316 #> [20,]  1.4280196 #> [21,] -1.1728036 #> [22,] -1.6370618 #> [23,] -1.2666155 #> [24,] -1.1520303 #> [25,] -1.6819787 #> [26,] -1.7516906 #> [27,] -1.7007475 #> [28,] -1.6729562 #> [29,] -1.5226375 #> [30,] -1.6552889 #>  #> , , 114 #>  #>              [,1] #>  [1,]  0.49738792 #>  [2,]  0.25241779 #>  [3,]  0.51883977 #>  [4,]  0.55081050 #>  [5,]  0.71202228 #>  [6,]  0.08548755 #>  [7,]  0.05618297 #>  [8,]  0.40630967 #>  [9,]  0.77276386 #> [10,]  0.87125275 #> [11,]  1.45907797 #> [12,]  1.43577893 #> [13,]  1.39805185 #> [14,]  1.48375065 #> [15,]  1.45008739 #> [16,]  1.33091413 #> [17,]  1.45091579 #> [18,]  1.46201327 #> [19,]  1.45564449 #> [20,]  1.42373742 #> [21,] -1.22440315 #> [22,] -1.68064816 #> [23,] -1.31709122 #> [24,] -1.20660615 #> [25,] -1.72337922 #> [26,] -1.79436397 #> [27,] -1.74382520 #> [28,] -1.71693490 #> [29,] -1.57222803 #> [30,] -1.69886489 #>  #> , , 115 #>  #>               [,1] #>  [1,]  0.459194282 #>  [2,]  0.205721054 #>  [3,]  0.472552959 #>  [4,]  0.505962357 #>  [5,]  0.670466878 #>  [6,]  0.029378223 #>  [7,]  0.001908055 #>  [8,]  0.361076882 #>  [9,]  0.737951977 #> [10,]  0.835205995 #> [11,]  1.448852629 #> [12,]  1.431919077 #> [13,]  1.388961195 #> [14,]  1.484823529 #> [15,]  1.442578246 #> [16,]  1.319030936 #> [17,]  1.442023754 #> [18,]  1.458921396 #> [19,]  1.446586793 #> [20,]  1.418770999 #> [21,] -1.274967222 #> [22,] -1.722271325 #> [23,] -1.366277723 #> [24,] -1.260124380 #> [25,] -1.762762923 #> [26,] -1.834871006 #> [27,] -1.784790035 #> [28,] -1.758817351 #> [29,] -1.620102036 #> [30,] -1.740385169 #>  #> , , 116 #>  #>              [,1] #>  [1,]  0.42021653 #>  [2,]  0.15833102 #>  [3,]  0.42545400 #>  [4,]  0.46022369 #>  [5,]  0.62804128 #>  [6,] -0.02741463 #>  [7,] -0.05300332 #>  [8,]  0.31513390 #>  [9,]  0.70224497 #> [10,]  0.79818189 #> [11,]  1.43811049 #> [12,]  1.42747713 #> [13,]  1.37929567 #> [14,]  1.48536371 #> [15,]  1.43452167 #> [16,]  1.30654267 #> [17,]  1.43237517 #> [18,]  1.45524007 #> [19,]  1.43712173 #> [20,]  1.41336616 #> [21,] -1.32443619 #> [22,] -1.76186440 #> [23,] -1.41397297 #> [24,] -1.31252123 #> [25,] -1.80006856 #> [26,] -1.87314978 #> [27,] -1.82357851 #> [28,] -1.79853818 #> [29,] -1.66618965 #> [30,] -1.77978522 #>  #> , , 117 #>  #>              [,1] #>  [1,]  0.38044632 #>  [2,]  0.11026823 #>  [3,]  0.37748073 #>  [4,]  0.41361102 #>  [5,]  0.58475397 #>  [6,] -0.08485854 #>  [7,] -0.10855361 #>  [8,]  0.26850000 #>  [9,]  0.66568122 #> [10,]  0.76022892 #> [11,]  1.42685997 #> [12,]  1.42276475 #> [13,]  1.36892898 #> [14,]  1.48572156 #> [15,]  1.42572438 #> [16,]  1.29322714 #> [17,]  1.42223058 #> [18,]  1.45102776 #> [19,]  1.42702442 #> [20,]  1.40764583 #> [21,] -1.37259104 #> [22,] -1.79936326 #> [23,] -1.46025584 #> [24,] -1.36373384 #> [25,] -1.83523785 #> [26,] -1.90914169 #> [27,] -1.86013042 #> [28,] -1.83603523 #> [29,] -1.71042318 #> [30,] -1.81700362 #>  #> , , 118 #>  #>             [,1] #>  [1,]  0.3399385 #>  [2,]  0.0615377 #>  [3,]  0.3286426 #>  [4,]  0.3660836 #>  [5,]  0.5406108 #>  [6,] -0.1428912 #>  [7,] -0.1646440 #>  [8,]  0.2211600 #>  [9,]  0.6282890 #> [10,]  0.7214463 #> [11,]  1.4147097 #> [12,]  1.4174395 #> [13,]  1.3581395 #> [14,]  1.4854338 #> [15,]  1.4164998 #> [16,]  1.2794208 #> [17,]  1.4115255 #> [18,]  1.4464942 #> [19,]  1.4163241 #> [20,]  1.4011174 #> [21,] -1.4194255 #> [22,] -1.8347067 #> [23,] -1.5050773 #> [24,] -1.4137003 #> [25,] -1.8682156 #> [26,] -1.9427917 #> [27,] -1.8943890 #> [28,] -1.8712498 #> [29,] -1.7527373 #> [30,] -1.8519822 #>  #> , , 119 #>  #>             [,1] #>  [1,]  0.2987325 #>  [2,]  0.0121542 #>  [3,]  0.2789877 #>  [4,]  0.3176160 #>  [5,]  0.4952932 #>  [6,] -0.2014403 #>  [7,] -0.2212056 #>  [8,]  0.1731223 #>  [9,]  0.5901087 #> [10,]  0.6818006 #> [11,]  1.4019737 #> [12,]  1.4116807 #> [13,]  1.3467817 #> [14,]  1.4849011 #> [15,]  1.4067215 #> [16,]  1.2651396 #> [17,]  1.4000275 #> [18,]  1.4412698 #> [19,]  1.4052100 #> [20,]  1.3942350 #> [21,] -1.4649664 #> [22,] -1.8677878 #> [23,] -1.5483806 #> [24,] -1.4622260 #> [25,] -1.8989498 #> [26,] -1.9740483 #> [27,] -1.9263011 #> [28,] -1.9041266 #> [29,] -1.7930692 #> [30,] -1.8846661 #>  #> , , 120 #>  #>              [,1] #>  [1,]  0.25687096 #>  [2,] -0.03782558 #>  [3,]  0.22857737 #>  [4,]  0.26834624 #>  [5,]  0.44915240 #>  [6,] -0.26044795 #>  [7,] -0.27818063 #>  [8,]  0.12445608 #>  [9,]  0.55120853 #> [10,]  0.64127404 #> [11,]  1.38870315 #> [12,]  1.40557759 #> [13,]  1.33470564 #> [14,]  1.48387207 #> [15,]  1.39619787 #> [16,]  1.24990707 #> [17,]  1.38800498 #> [18,]  1.43560796 #> [19,]  1.39339644 #> [20,]  1.38696958 #> [21,] -1.50916498 #> [22,] -1.89856007 #> [23,] -1.59010940 #> [24,] -1.50936363 #> [25,] -1.92727883 #> [26,] -2.00281076 #> [27,] -1.95581742 #> [28,] -1.93461440 #> [29,] -1.83135858 #> [30,] -1.91500441 #>  #> , , 121 #>  #>              [,1] #>  [1,]  0.21438530 #>  [2,] -0.08831279 #>  [3,]  0.17746558 #>  [4,]  0.21823542 #>  [5,]  0.40221674 #>  [6,] -0.31985316 #>  [7,] -0.33550788 #>  [8,]  0.07512554 #>  [9,]  0.51145568 #> [10,]  0.59980731 #> [11,]  1.37470893 #> [12,]  1.39881326 #> [13,]  1.32220507 #> [14,]  1.48243122 #> [15,]  1.38524357 #> [16,]  1.23416191 #> [17,]  1.37545152 #> [18,]  1.42958489 #> [19,]  1.38104577 #> [20,]  1.37895234 #> [21,] -1.55196856 #> [22,] -1.92700944 #> [23,] -1.63020933 #> [24,] -1.55506331 #> [25,] -1.95322611 #> [26,] -2.02906825 #> [27,] -1.98289244 #> [28,] -1.96266568 #> [29,] -1.86754821 #> [30,] -1.94294958 #>  #> , , 122 #>  #>              [,1] #>  [1,]  0.17123761 #>  [2,] -0.13926584 #>  [3,]  0.12568680 #>  [4,]  0.16733457 #>  [5,]  0.35450308 #>  [6,] -0.37959127 #>  [7,] -0.39312282 #>  [8,]  0.02519439 #>  [9,]  0.47091233 #> [10,]  0.55746730 #> [11,]  1.35993823 #> [12,]  1.39176054 #> [13,]  1.30914291 #> [14,]  1.48071581 #> [15,]  1.37372947 #> [16,]  1.21791305 #> [17,]  1.36208222 #> [18,]  1.42282914 #> [19,]  1.36827983 #> [20,]  1.37059381 #> [21,] -1.59332566 #> [22,] -1.95308877 #> [23,] -1.66862775 #> [24,] -1.59926847 #> [25,] -1.97678651 #> [26,] -2.05279859 #> [27,] -2.00748486 #> [28,] -1.98823710 #> [29,] -1.90158364 #> [30,] -1.96845821 #>  #> , , 123 #>  #>              [,1] #>  [1,]  0.12742734 #>  [2,] -0.19064065 #>  [3,]  0.07326382 #>  [4,]  0.11571861 #>  [5,]  0.30602947 #>  [6,] -0.43960179 #>  [7,] -0.45095744 #>  [8,] -0.02525649 #>  [9,]  0.42959745 #> [10,]  0.51435843 #> [11,]  1.34462749 #> [12,]  1.38414468 #> [13,]  1.29534533 #> [14,]  1.47840011 #> [15,]  1.36146563 #> [16,]  1.20091948 #> [17,]  1.34815332 #> [18,]  1.41572041 #> [19,]  1.35474461 #> [20,]  1.36172597 #> [21,] -1.63318619 #> [22,] -1.97675482 #> [23,] -1.70531398 #> [24,] -1.64192406 #> [25,] -1.99792695 #> [26,] -2.07396885 #> [27,] -2.02955761 #> [28,] -2.01128957 #> [29,] -1.93341358 #> [30,] -1.99149093 #>  #> , , 124 #>  #>              [,1] #>  [1,]  0.08303796 #>  [2,] -0.24239061 #>  [3,]  0.02010767 #>  [4,]  0.06342015 #>  [5,]  0.25679882 #>  [6,] -0.49980406 #>  [7,] -0.50894020 #>  [8,] -0.07619536 #>  [9,]  0.38755287 #> [10,]  0.47044621 #> [11,]  1.32871697 #> [12,]  1.37603657 #> [13,]  1.28112190 #> [14,]  1.47589098 #> [15,]  1.34876754 #> [16,]  1.18321892 #> [17,]  1.33369390 #> [18,]  1.40809474 #> [19,]  1.34073649 #> [20,]  1.35223657 #> [21,] -1.67150151 #> [22,] -1.99796834 #> [23,] -1.74021943 #> [24,] -1.68297660 #> [25,] -2.01661493 #> [26,] -2.09254903 #> [27,] -2.04907805 #> [28,] -2.03178842 #> [29,] -1.96299000 #> [30,] -2.01201259 #>  #> , , 125 #>  #>              [,1] #>  [1,]  0.03809124 #>  [2,] -0.29446652 #>  [3,] -0.03362766 #>  [4,]  0.01041291 #>  [5,]  0.20658443 #>  [6,] -0.56010342 #>  [7,] -0.56699509 #>  [8,] -0.12761010 #>  [9,]  0.34485162 #> [10,]  0.42570640 #> [11,]  1.31191183 #> [12,]  1.36765531 #> [13,]  1.26634389 #> [14,]  1.47274207 #> [15,]  1.33550384 #> [16,]  1.16500986 #> [17,]  1.31845557 #> [18,]  1.39987439 #> [19,]  1.32631649 #> [20,]  1.34239655 #> [21,] -1.70822454 #> [22,] -2.01669422 #> [23,] -1.77329768 #> [24,] -1.72235871 #> [25,] -2.03282213 #> [26,] -2.10851376 #> [27,] -2.06601807 #> [28,] -2.04970355 #> [29,] -1.99026829 #> [30,] -2.02999243 #>  #> , , 126 #>  #>               [,1] #>  [1,] -0.007370704 #>  [2,] -0.346817704 #>  [3,] -0.087925892 #>  [4,] -0.043257036 #>  [5,]  0.155684466 #>  [6,] -0.620419106 #>  [7,] -0.625039061 #>  [8,] -0.179479537 #>  [9,]  0.301376212 #> [10,]  0.380100940 #> [11,]  1.294566861 #> [12,]  1.358566699 #> [13,]  1.250813423 #> [14,]  1.469298460 #> [15,]  1.321486458 #> [16,]  1.146243344 #> [17,]  1.302601730 #> [18,]  1.391314601 #> [19,]  1.311055059 #> [20,]  1.331909081 #> [21,] -1.743309827 #> [22,] -2.032901677 #> [23,] -1.804504597 #> [24,] -1.759978586 #> [25,] -2.046524562 #> [26,] -2.121842470 #> [27,] -2.080354285 #> [28,] -2.065009568 #> [29,] -2.015207373 #> [30,] -2.045404201 #>  #> , , 127 #>  #>              [,1] #>  [1,] -0.05329729 #>  [2,] -0.39939321 #>  [3,] -0.14272732 #>  [4,] -0.09748145 #>  [5,]  0.10413495 #>  [6,] -0.68066666 #>  [7,] -0.68297585 #>  [8,] -0.23172050 #>  [9,]  0.25720446 #> [10,]  0.33371359 #> [11,]  1.27669248 #> [12,]  1.34915161 #> [13,]  1.23485622 #> [14,]  1.46542848 #> [15,]  1.30703105 #> [16,]  1.12655070 #> [17,]  1.28623206 #> [18,]  1.38208747 #> [19,]  1.29538311 #> [20,]  1.32092390 #> [21,] -1.77664912 #> [22,] -2.04656439 #> [23,] -1.83379842 #> [24,] -1.79577363 #> [25,] -2.05770265 #> [26,] -2.13251948 #> [27,] -2.09206812 #> [28,] -2.07768594 #> [29,] -2.03776989 #> [30,] -2.05822632 #>  #> , , 128 #>  #>              [,1] #>  [1,] -0.09969533 #>  [2,] -0.45213747 #>  [3,] -0.19796897 #>  [4,] -0.15224958 #>  [5,]  0.05196657 #>  [6,] -0.74075793 #>  [7,] -0.74069424 #>  [8,] -0.28434899 #>  [9,]  0.21236184 #> [10,]  0.28665020 #> [11,]  1.25787359 #> [12,]  1.33925014 #> [13,]  1.21835184 #> [14,]  1.46108174 #> [15,]  1.29200456 #> [16,]  1.10635998 #> [17,]  1.26910315 #> [18,]  1.37236990 #> [19,]  1.27926090 #> [20,]  1.30959742 #> [21,] -1.80801101 #> [22,] -2.05766061 #> [23,] -1.86113989 #> [24,] -1.82976306 #> [25,] -2.06634138 #> [26,] -2.14053415 #> [27,] -2.10114597 #> [28,] -2.08771711 #> [29,] -2.05792232 #> [30,] -2.06844197 #>  #> , , 129 #>  #>                [,1] #>  [1,] -0.1465465842 #>  [2,] -0.5049631790 #>  [3,] -0.2536103218 #>  [4,] -0.2075074744 #>  [5,] -0.0007917271 #>  [6,] -0.8005929384 #>  [7,] -0.7981110203 #>  [8,] -0.3372457096 #>  [9,]  0.1668883910 #> [10,]  0.2388813169 #> [11,]  1.2384669381 #> [12,]  1.3287951291 #> [13,]  1.2010782862 #> [14,]  1.4565088611 #> [15,]  1.2762210208 #> [16,]  1.0856773792 #> [17,]  1.2513084510 #> [18,]  1.3623297753 #> [19,]  1.2623165639 #> [20,]  1.2974732793 #> [21,] -1.8375409034 #> [22,] -2.0661733475 #> [23,] -1.8864804921 #> [24,] -1.8619032623 #> [25,] -2.0724304278 #> [26,] -2.1458809654 #> [27,] -2.1075793070 #> [28,] -2.0950926455 #> [29,] -2.0756285029 #> [30,] -2.0760392713 #>  #> , , 130 #>  #>              [,1] #>  [1,] -0.19375628 #>  [2,] -0.55779194 #>  [3,] -0.30964917 #>  [4,] -0.26318100 #>  [5,] -0.05414077 #>  [6,] -0.86006434 #>  [7,] -0.85513118 #>  [8,] -0.39036314 #>  [9,]  0.12085300 #> [10,]  0.19038182 #> [11,]  1.21850420 #> [12,]  1.31806741 #> [13,]  1.18337773 #> [14,]  1.45125031 #> [15,]  1.25999558 #> [16,]  1.06410171 #> [17,]  1.23300118 #> [18,]  1.35151766 #> [19,]  1.24497546 #> [20,]  1.28496608 #> [21,] -1.86524636 #> [22,] -2.07209046 #> [23,] -1.90955155 #> [24,] -1.89210590 #> [25,] -2.07596424 #> [26,] -2.14855967 #> [27,] -2.11136479 #> [28,] -2.09980732 #> [29,] -2.09082997 #> [30,] -2.08094432 #>  #> , , 131 #>  #>              [,1] #>  [1,] -0.24130205 #>  [2,] -0.61055581 #>  [3,] -0.36600350 #>  [4,] -0.31921324 #>  [5,] -0.10816042 #>  [6,] -0.91906973 #>  [7,] -0.91165633 #>  [8,] -0.44365488 #>  [9,]  0.07416851 #> [10,]  0.14113996 #> [11,]  1.19778169 #> [12,]  1.30667377 #> [13,]  1.16513792 #> [14,]  1.44578732 #> [15,]  1.24319410 #> [16,]  1.04193984 #> [17,]  1.21396191 #> [18,]  1.34031147 #> [19,]  1.22714178 #> [20,]  1.27209349 #> [21,] -1.89110072 #> [22,] -2.07540478 #> [23,] -1.93050880 #> [24,] -1.92022120 #> [25,] -2.07694215 #> [26,] -2.14857532 #> [27,] -2.11250435 #> [28,] -2.10186124 #> [29,] -2.10353833 #> [30,] -2.08311747 #>  #> , , 132 #>  #>              [,1] #>  [1,] -0.28913755 #>  [2,] -0.66318403 #>  [3,] -0.42260688 #>  [4,] -0.37558118 #>  [5,] -0.16265606 #>  [6,] -0.97751333 #>  [7,] -0.96758479 #>  [8,] -0.49707192 #>  [9,]  0.02692347 #> [10,]  0.09125223 #> [11,]  1.17627782 #> [12,]  1.29488628 #> [13,]  1.14611291 #> [14,]  1.43972418 #> [15,]  1.22563299 #> [16,]  1.01925900 #> [17,]  1.19421282 #> [18,]  1.32869848 #> [19,]  1.20852157 #> [20,]  1.25837074 #> [21,] -1.91507175 #> [22,] -2.07611424 #> [23,] -1.94937198 #> [24,] -1.94636241 #> [25,] -2.07536847 #> [26,] -2.14593839 #> [27,] -2.11100530 #> [28,] -2.10125992 #> [29,] -2.11374299 #> [30,] -2.08266869 #>  #> , , 133 #>  #>              [,1] #>  [1,] -0.33720192 #>  [2,] -0.71560312 #>  [3,] -0.47939597 #>  [4,] -0.43219426 #>  [5,] -0.21757378 #>  [6,] -1.03528834 #>  [7,] -1.02281165 #>  [8,] -0.55056003 #>  [9,] -0.02084724 #> [10,]  0.04081319 #> [11,]  1.15421255 #> [12,]  1.28271766 #> [13,]  1.12666140 #> [14,]  1.43331269 #> [15,]  1.20762617 #> [16,]  0.99589193 #> [17,]  1.17394286 #> [18,]  1.31635979 #> [19,]  1.18950743 #> [20,]  1.24431083 #> [21,] -1.93712944 #> [22,] -2.07422199 #> [23,] -1.96612178 #> [24,] -1.97049628 #> [25,] -2.07125254 #> [26,] -2.14066484 #> [27,] -2.10688042 #> [28,] -2.09801441 #> [29,] -2.12143178 #> [30,] -2.07960798 #>  #> , , 134 #>  #>              [,1] #>  [1,] -0.38546532 #>  [2,] -0.76773683 #>  [3,] -0.53630569 #>  [4,] -0.48896983 #>  [5,] -0.27286719 #>  [6,] -1.09225106 #>  [7,] -1.07722893 #>  [8,] -0.60404746 #>  [9,] -0.06910386 #> [10,] -0.01018369 #> [11,]  1.13151199 #> [12,]  1.26991744 #> [13,]  1.10667928 #> [14,]  1.42653416 #> [15,]  1.18903906 #> [16,]  0.97173679 #> [17,]  1.15297615 #> [18,]  1.30366886 #> [19,]  1.16996127 #> [20,]  1.22977765 #> [21,] -1.95724620 #> [22,] -2.06973644 #> [23,] -1.98073755 #> [24,] -1.99259218 #> [25,] -2.06460885 #> [26,] -2.13277615 #> [27,] -2.10014799 #> [28,] -2.09212603 #> [29,] -2.12657009 #> [30,] -2.07395077 #>  #> , , 135 #>  #>              [,1] #>  [1,] -0.43387636 #>  [2,] -0.81950538 #>  [3,] -0.59327540 #>  [4,] -0.54584537 #>  [5,] -0.32849424 #>  [6,] -1.14823516 #>  [7,] -1.13072569 #>  [8,] -0.65745140 #>  [9,] -0.11778336 #> [10,] -0.06174371 #> [11,]  1.10792395 #> [12,]  1.25682814 #> [13,]  1.08589703 #> [14,]  1.41921153 #> [15,]  1.16969082 #> [16,]  0.94707061 #> [17,]  1.13126258 #> [18,]  1.29041230 #> [19,]  1.14966761 #> [20,]  1.21453708 #> [21,] -1.97539686 #> [22,] -2.06267138 #> [23,] -1.99320188 #> [24,] -2.01262218 #> [25,] -2.05545709 #> [26,] -2.12229939 #> [27,] -2.09083185 #> [28,] -2.08356194 #> [29,] -2.12912805 #> [30,] -2.06571793 #>  #> , , 136 #>  #>             [,1] #>  [1,] -0.4823588 #>  [2,] -0.8708191 #>  [3,] -0.6502438 #>  [4,] -0.6027491 #>  [5,] -0.3844331 #>  [6,] -1.2031807 #>  [7,] -1.1831882 #>  [8,] -0.7107120 #>  [9,] -0.1669302 #> [10,] -0.1138739 #> [11,]  1.0837802 #> [12,]  1.2431239 #> [13,]  1.0646898 #> [14,]  1.4116934 #> [15,]  1.1498933 #> [16,]  0.9218905 #> [17,]  1.1090083 #> [18,]  1.2765842 #> [19,]  1.1289786 #> [20,]  1.1989356 #> [21,] -1.9915588 #> [22,] -2.0530461 #> [23,] -2.0035007 #> [24,] -2.0305611 #> [25,] -2.0438222 #> [26,] -2.1092673 #> [27,] -2.0789615 #> [28,] -2.0724228 #> [29,] -2.1291620 #> [30,] -2.0549358 #>  #> , , 137 #>  #>             [,1] #>  [1,] -0.5308597 #>  [2,] -0.9215122 #>  [3,] -0.7071176 #>  [4,] -0.6596049 #>  [5,] -0.4406417 #>  [6,] -1.2569672 #>  [7,] -1.2345000 #>  [8,] -0.7637673 #>  [9,] -0.2164523 #> [10,] -0.1664612 #> [11,]  1.0590854 #> [12,]  1.2289671 #> [13,]  1.0429615 #> [14,]  1.4034154 #> [15,]  1.1295122 #> [16,]  0.8957428 #> [17,]  1.0861010 #> [18,]  1.2624132 #> [19,]  1.1077213 #> [20,]  1.1827268 #> [21,] -2.0057119 #> [22,] -2.0408853 #> [23,] -2.0116231 #> [24,] -2.0463868 #> [25,] -2.0296582 #> [26,] -2.0937180 #> [27,] -2.0645720 #> [28,] -2.0587429 #> [29,] -2.1266790 #> [30,] -2.0416365 #>  #> , , 138 #>  #>             [,1] #>  [1,] -0.5793238 #>  [2,] -0.9714864 #>  [3,] -0.7638277 #>  [4,] -0.7163408 #>  [5,] -0.4970072 #>  [6,] -1.3094717 #>  [7,] -1.2844010 #>  [8,] -0.8165469 #>  [9,] -0.2663044 #> [10,] -0.2194247 #> [11,]  1.0334300 #> [12,]  1.2145269 #> [13,]  1.0204199 #> [14,]  1.3949171 #> [15,]  1.1083699 #> [16,]  0.8690954 #> [17,]  1.0623939 #> [18,]  1.2475025 #> [19,]  1.0857592 #> [20,]  1.1659470 #> [21,] -2.0176357 #> [22,] -2.0262193 #> [23,] -2.0175620 #> [24,] -2.0600600 #> [25,] -2.0130116 #> [26,] -2.0756957 #> [27,] -2.0476874 #> [28,] -2.0425622 #> [29,] -2.1216912 #> [30,] -2.0258572 #>  #> , , 139 #>  #>             [,1] #>  [1,] -0.6276949 #>  [2,] -1.0207039 #>  [3,] -0.8202811 #>  [4,] -0.7728367 #>  [5,] -0.5534673 #>  [6,] -1.3605687 #>  [7,] -1.3328543 #>  [8,] -0.8689678 #>  [9,] -0.3164444 #> [10,] -0.2727467 #> [11,]  1.0071903 #> [12,]  1.1993529 #> [13,]  0.9974559 #> [14,]  1.3858945 #> [15,]  1.0867753 #> [16,]  0.8419454 #> [17,]  1.0381365 #> [18,]  1.2321411 #> [19,]  1.0633961 #> [20,]  1.1488018 #> [21,] -2.0273199 #> [22,] -2.0090840 #> [23,] -2.0213136 #> [24,] -2.0715174 #> [25,] -1.9939797 #> [26,] -2.0552497 #> [27,] -2.0283298 #> [28,] -2.0239264 #> [29,] -2.1142157 #> [30,] -2.0076413 #>  #> , , 140 #>  #>             [,1] #>  [1,] -0.6759033 #>  [2,] -1.0690710 #>  [3,] -0.8764094 #>  [4,] -0.8290138 #>  [5,] -0.6099629 #>  [6,] -1.4101308 #>  [7,] -1.3797189 #>  [8,] -0.9209374 #>  [9,] -0.3668157 #> [10,] -0.3264091 #> [11,]  0.9803831 #> [12,]  1.1838826 #> [13,]  0.9739819 #> [14,]  1.3764582 #> [15,]  1.0645951 #> [16,]  0.8139846 #> [17,]  1.0133065 #> [18,]  1.2164593 #> [19,]  1.0404322 #> [20,]  1.1309043 #> [21,] -2.0349157 #> [22,] -1.9895210 #> [23,] -2.0228777 #> [24,] -2.0807267 #> [25,] -1.9726255 #> [26,] -2.0324353 #> [27,] -2.0065840 #> [28,] -2.0028868 #> [29,] -2.1042746 #> [30,] -1.9870372 #>  #> , , 141 #>  #>             [,1] #>  [1,] -0.7238474 #>  [2,] -1.1164919 #>  [3,] -0.9321512 #>  [4,] -0.8848024 #>  [5,] -0.6664376 #>  [6,] -1.4580286 #>  [7,] -1.4248394 #>  [8,] -0.9723236 #>  [9,] -0.4174071 #> [10,] -0.3803909 #> [11,]  0.9527970 #> [12,]  1.1678904 #> [13,]  0.9496833 #> [14,]  1.3667037 #> [15,]  1.0416556 #> [16,]  0.7853805 #> [17,]  0.9875856 #> [18,]  1.1999224 #> [19,]  1.0168099 #> [20,]  1.1125653 #> [21,] -2.0404448 #> [22,] -1.9675773 #> [23,] -2.0222578 #> [24,] -2.0877632 #> [25,] -1.9490016 #> [26,] -2.0073130 #> [27,] -1.9825199 #> [28,] -1.9795007 #> [29,] -2.0918950 #> [30,] -1.9640992 #>  #> , , 142 #>  #>             [,1] #>  [1,] -0.7714949 #>  [2,] -1.1628690 #>  [3,] -0.9874332 #>  [4,] -0.9400943 #>  [5,] -0.7228094 #>  [6,] -1.5040940 #>  [7,] -1.4681220 #>  [8,] -1.0230705 #>  [9,] -0.4681338 #> [10,] -0.4345825 #> [11,]  0.9244461 #> [12,]  1.1513784 #> [13,]  0.9249646 #> [14,]  1.3563155 #> [15,]  1.0182615 #> [16,]  0.7562668 #> [17,]  0.9613240 #> [18,]  1.1830371 #> [19,]  0.9927751 #> [20,]  1.0938552 #> [21,] -2.0439073 #> [22,] -1.9433057 #> [23,] -2.0194611 #> [24,] -2.0925018 #> [25,] -1.9231660 #> [26,] -1.9799490 #> [27,] -1.9562012 #> [28,] -1.9538306 #> [29,] -2.0771092 #> [30,] -1.9388869 #>  #> , , 143 #>  #>             [,1] #>  [1,] -0.8187582 #>  [2,] -1.2081025 #>  [3,] -1.0420654 #>  [4,] -0.9947846 #>  [5,] -0.7789685 #>  [6,] -1.5481235 #>  [7,] -1.5094591 #>  [8,] -1.0731351 #>  [9,] -0.5189394 #> [10,] -0.4889184 #> [11,]  0.8955275 #> [12,]  1.1345948 #> [13,]  0.8997441 #> [14,]  1.3457192 #> [15,]  0.9942815 #> [16,]  0.7265480 #> [17,]  0.9345254 #> [18,]  1.1657018 #> [19,]  0.9681003 #> [20,]  1.0742796 #> [21,] -2.0453025 #> [22,] -1.9167646 #> [23,] -2.0144980 #> [24,] -2.0949533 #> [25,] -1.8951817 #> [26,] -1.9504149 #> [27,] -1.9276970 #> [28,] -1.9259449 #> [29,] -2.0599546 #> [30,] -1.9114654 #>  #> , , 144 #>  #>             [,1] #>  [1,] -0.8655628 #>  [2,] -1.2520909 #>  [3,] -1.0960100 #>  [4,] -1.0487865 #>  [5,] -0.8348450 #>  [6,] -1.5900486 #>  [7,] -1.5487221 #>  [8,] -1.1224399 #>  [9,] -0.5697770 #> [10,] -0.5433572 #> [11,]  0.8659571 #> [12,]  1.1170966 #> [13,]  0.8737019 #> [14,]  1.3344139 #> [15,]  0.9695464 #> [16,]  0.6959922 #> [17,]  0.9068508 #> [18,]  1.1476554 #> [19,]  0.9428341 #> [20,]  1.0543637 #> [21,] -2.0446324 #> [22,] -1.8880178 #> [23,] -2.0071823 #> [24,] -2.0952255 #> [25,] 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-1.3594828 #>  [6,] -1.8618732 #>  [7,] -1.7967129 #>  [8,] -1.5498046 #>  [9,] -1.0655027 #> [10,] -1.0788373 #> [11,]  0.5329726 #> [12,]  0.9176679 #> [13,]  0.5833138 #> [14,]  1.1982024 #> [15,]  0.6906332 #> [16,]  0.3585817 #> [17,]  0.5954544 #> [18,]  0.9394710 #> [19,]  0.6607685 #> [20,]  0.8252341 #> [21,] -1.9248995 #> [22,] -1.4967634 #> [23,] -1.8211698 #> [24,] -1.9804954 #> [25,] -1.4685101 #> [26,] -1.5077407 #> [27,] -1.4947516 #> [28,] -1.4976719 #> [29,] -1.7306566 #> [30,] -1.4873057 #>  #> , , 155 #>  #>             [,1] #>  [1,] -1.3260542 #>  [2,] -1.6171267 #>  [3,] -1.6149140 #>  [4,] -1.5647401 #>  [5,] -1.4063066 #>  [6,] -1.8716503 #>  [7,] -1.8043044 #>  [8,] -1.5834953 #>  [9,] -1.1122729 #> [10,] -1.1299002 #> [11,]  0.4960479 #> [12,]  0.8951390 #> [13,]  0.5513251 #> [14,]  1.1822705 #> [15,]  0.6595846 #> [16,]  0.3216975 #> [17,]  0.5608929 #> [18,]  0.9156666 #> [19,]  0.6295094 #> [20,]  0.7993929 #> [21,] -1.9022555 #> [22,] -1.4494557 #> [23,] -1.7923213 #> [24,] -1.9576178 #> [25,] -1.4213765 #> [26,] -1.4595020 #> [27,] -1.4472092 #> [28,] -1.4503579 #> [29,] -1.6898132 #> [30,] -1.4402786 #>  #> , , 156 #>  #>             [,1] #>  [1,] -1.3606898 #>  [2,] -1.6362801 #>  [3,] -1.6523244 #>  [4,] -1.6015944 #>  [5,] -1.4516392 #>  [6,] -1.8774691 #>  [7,] -1.8081881 #>  [8,] -1.6152441 #>  [9,] -1.1580925 #> [10,] -1.1799709 #> [11,]  0.4586237 #> [12,]  0.8723466 #> [13,]  0.5185778 #> [14,]  1.1655340 #> [15,]  0.6278346 #> [16,]  0.2844051 #> [17,]  0.5257135 #> [18,]  0.8915121 #> [19,]  0.5978826 #> [20,]  0.7730943 #> [21,] -1.8778497 #> [22,] -1.4011115 #> [23,] -1.7618253 #> [24,] -1.9328843 #> [25,] -1.3733366 #> [26,] -1.4104319 #> [27,] -1.3988060 #> [28,] -1.4021516 #> [29,] -1.6475334 #> [30,] -1.3923425 #>  #> , , 157 #>  #>             [,1] #>  [1,] -1.3936610 #>  [2,] -1.6527085 #>  [3,] -1.6877135 #>  [4,] -1.6362337 #>  [5,] -1.4954402 #>  [6,] -1.8792175 #>  [7,] -1.8084337 #>  [8,] -1.6449614 #>  [9,] -1.2030033 #> [10,] -1.2291519 #> [11,]  0.4206693 #> [12,]  0.8488096 #> [13,]  0.4854505 #> [14,]  1.1485903 #> [15,]  0.5956458 #> [16,]  0.2464100 #> [17,]  0.4897971 #> [18,]  0.8667210 #> [19,]  0.5657797 #> [20,]  0.7460428 #> [21,] -1.8517288 #> [22,] -1.3518547 #> [23,] -1.7297471 #> [24,] -1.9063457 #> [25,] -1.3245276 #> [26,] -1.3606576 #> [27,] -1.3496682 #> [28,] -1.3531801 #> [29,] -1.6039196 #> [30,] -1.3436220 #>  #> , , 158 #>  #>             [,1] #>  [1,] -1.4249426 #>  [2,] -1.6663204 #>  [3,] -1.7209043 #>  [4,] -1.6684913 #>  [5,] -1.5376949 #>  [6,] -1.8771170 #>  [7,] -1.8049553 #>  [8,] -1.6725581 #>  [9,] -1.2469179 #> [10,] -1.2774327 #> [11,]  0.3819394 #> [12,]  0.8249729 #> [13,]  0.4518813 #> [14,]  1.1310793 #> [15,]  0.5629124 #> [16,]  0.2079622 #> [17,]  0.4534116 #> [18,]  0.8414171 #> [19,]  0.5330097 #> [20,]  0.7186461 #> [21,] -1.8239427 #> [22,] -1.3018119 #> [23,] -1.6960729 #> [24,] -1.8780566 #> [25,] -1.2750732 #> [26,] -1.3103198 #> [27,] -1.2999243 #> [28,] -1.3035724 #> [29,] -1.5590779 #> [30,] -1.2942443 #>  #> , , 159 #>  #>             [,1] #>  [1,] -1.4541811 #>  [2,] -1.6770238 #>  [3,] -1.7517499 #>  [4,] -1.6983346 #>  [5,] -1.5783140 #>  [6,] -1.8710837 #>  [7,] -1.7972631 #>  [8,] -1.6978934 #>  [9,] -1.2897570 #> [10,] -1.3247209 #> [11,]  0.3427192 #> [12,]  0.8007048 #> [13,]  0.4175862 #> [14,]  1.1131601 #> [15,]  0.5295037 #> [16,]  0.1691230 #> [17,]  0.4165243 #> [18,]  0.8157743 #> [19,]  0.4998891 #> [20,]  0.6907155 #> [21,] -1.7943818 #> [22,] -1.2511125 #> [23,] -1.6608449 #> [24,] -1.8480747 #> [25,] -1.2250991 #> [26,] -1.2595508 #> [27,] -1.2497040 #> [28,] -1.2534593 #> [29,] -1.5131174 #> [30,] -1.2443379 #>  #> , , 160 #>  #>             [,1] #>  [1,] -1.4816127 #>  [2,] -1.6847305 #>  [3,] -1.7801894 #>  [4,] -1.7252993 #>  [5,] -1.6167352 #>  [6,] -1.8610421 #>  [7,] -1.7856332 #>  [8,] -1.7207332 #>  [9,] -1.3314795 #> [10,] -1.3709061 #> [11,]  0.3030191 #> [12,]  0.7758932 #> [13,]  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[12,]  0.53350955 #> [13,]  0.05017047 #> [14,]  0.90872962 #> [15,]  0.16804807 #> [16,] -0.24209003 #> [17,]  0.01754195 #> [18,]  0.52996885 #> [19,]  0.14290530 #> [20,]  0.38309479 #> [21,] -1.42398833 #> [22,] -0.73743217 #> [23,] -1.24886705 #> [24,] -1.46953003 #> [25,] -0.72494327 #> [26,] -0.75675229 #> [27,] -0.75003134 #> [28,] -0.75362208 #> [29,] -1.01779322 #> [30,] -0.74522571 #>  #> , , 170 #>  #>              [,1] #>  [1,] -1.63131954 #>  [2,] -1.57528508 #>  [3,] -1.90707695 #>  [4,] -1.83128461 #>  [5,] -1.87374763 #>  [6,] -1.52811635 #>  [7,] -1.44647639 #>  [8,] -1.79123797 #>  [9,] -1.66167380 #> [10,] -1.74440497 #> [11,] -0.12195131 #> [12,]  0.50429265 #> [13,]  0.01122205 #> [14,]  0.88566026 #> [15,]  0.12936360 #> [16,] -0.28489341 #> [17,] -0.02491991 #> [18,]  0.49884992 #> [19,]  0.10488014 #> [20,]  0.34971851 #> [21,] -1.38116176 #> [22,] -0.68835162 #> [23,] -1.20370047 #> [24,] -1.42558701 #> [25,] -0.67767214 #> [26,] -0.70972386 #> [27,] 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[11,] -0.21181043 #> [12,]  0.44497203 #> [13,] -0.06790694 #> [14,]  0.83843082 #> [15,]  0.05065783 #> [16,] -0.37115998 #> [17,] -0.11085030 #> [18,]  0.43481800 #> [19,]  0.02781654 #> [20,]  0.28155959 #> [21,] -1.29345644 #> [22,] -0.59312744 #> [23,] -1.11245719 #> [24,] -1.33561350 #> [25,] -0.58625181 #> [26,] -0.61894077 #> [27,] -0.61246675 #> [28,] -0.61579889 #> [29,] -0.86775069 #> [30,] -0.60720679 #>  #> , , 173 #>  #>             [,1] #>  [1,] -1.6235957 #>  [2,] -1.4727482 #>  [3,] -1.8808925 #>  [4,] -1.7959200 #>  [5,] -1.8956862 #>  [6,] -1.3450023 #>  [7,] -1.2647299 #>  [8,] -1.7509884 #>  [9,] -1.7214465 #> [10,] -1.8157766 #> [11,] -0.2571290 #> [12,]  0.4146525 #> [13,] -0.1078546 #> [14,]  0.8140155 #> [15,]  0.0107898 #> [16,] -0.4144692 #> [17,] -0.1543882 #> [18,]  0.4022653 #> [19,] -0.0112403 #> [20,]  0.2468200 #> [21,] -1.2487904 #> [22,] -0.5472240 #> [23,] -1.0665881 #> [24,] -1.2897718 #> [25,] -0.5423518 #> [26,] -0.5753855 #> [27,] -0.5689472 #> [28,] -0.5721852 #> [29,] -0.8187444 #> [30,] -0.5634952 #>  #> , , 174 #>  #>              [,1] #>  [1,] -1.61536883 #>  [2,] -1.43052248 #>  [3,] -1.86509114 #>  [4,] -1.77615352 #>  [5,] -1.89651992 #>  [6,] -1.27611660 #>  [7,] -1.19671300 #>  [8,] -1.73014578 #>  [9,] -1.73670246 #> [10,] -1.83499641 #> [11,] -0.30271850 #> [12,]  0.38409918 #> [13,] -0.14821207 #> [14,]  0.78933748 #> [15,] -0.02953410 #> [16,] -0.45792597 #> [17,] -0.19816165 #> [18,]  0.36907142 #> [19,] -0.05055041 #> [20,]  0.21163836 #> [21,] -1.20371562 #> [22,] -0.50261250 #> [23,] -1.02071508 #> [24,] -1.24348809 #> [25,] -0.49976715 #> [26,] -0.53317730 #> [27,] -0.52676014 #> [28,] -0.52989857 #> [29,] -0.77043923 #> [30,] -0.52109824 #>  #> , , 175 #>  #>              [,1] #>  [1,] -1.60412676 #>  [2,] -1.38475597 #>  [3,] -1.84524450 #>  [4,] -1.75271463 #>  [5,] -1.89395891 #>  [6,] -1.20349001 #>  [7,] -1.12517086 #>  [8,] -1.70557994 #>  [9,] -1.74948765 #> [10,] -1.85181755 #> [11,] -0.34854292 #> [12,]  0.35294410 #> [13,] -0.18876072 #> [14,]  0.76393427 #> [15,] -0.07012135 #> [16,] -0.50142296 #> [17,] -0.24222025 #> [18,]  0.33559469 #> [19,] -0.09027121 #> [20,]  0.17616542 #> [21,] -1.15832329 #> [22,] -0.45940609 #> [23,] -0.97494033 #> [24,] -1.19685973 #> [25,] -0.45859244 #> [26,] -0.49239987 #> [27,] -0.48601257 #> [28,] -0.48902750 #> [29,] -0.72294963 #> [30,] -0.48010722 #>  #> , , 176 #>  #>             [,1] #>  [1,] -1.5895654 #>  [2,] -1.3355005 #>  [3,] -1.8215934 #>  [4,] -1.7255820 #>  [5,] -1.8880493 #>  [6,] -1.1272551 #>  [7,] -1.0502392 #>  [8,] -1.6776411 #>  [9,] -1.7591957 #> [10,] -1.8649116 #> [11,] -0.3945146 #> [12,]  0.3215222 #> [13,] -0.2295181 #> [14,]  0.7383280 #> [15,] -0.1110064 #> [16,] -0.5449472 #> [17,] -0.2865898 #> [18,]  0.3016605 #> [19,] -0.1302098 #> [20,]  0.1401656 #> [21,] -1.1127052 #> [22,] -0.4177589 #> [23,] -0.9293639 #> [24,] -1.1499848 #> [25,] -0.4189162 #> [26,] -0.4531297 #> [27,] -0.4467852 #> [28,] -0.4496531 #> [29,] -0.6763865 #> [30,] -0.4406067 #>  #> , , 177 #>  #>             [,1] #>  [1,] -1.5714022 #>  [2,] -1.2828120 #>  [3,] -1.7943737 #>  [4,] -1.6947416 #>  [5,] -1.8785054 #>  [6,] -1.0475600 #>  [7,] -0.9720686 #>  [8,] -1.6463249 #>  [9,] -1.7663428 #> [10,] -1.8753149 #> [11,] -0.4406371 #> [12,]  0.2897960 #> [13,] -0.2705847 #> [14,]  0.7121397 #> [15,] -0.1522756 #> [16,] -0.5884649 #> [17,] -0.3311212 #> [18,]  0.2672407 #> [19,] -0.1703731 #> [20,]  0.1038437 #> [21,] -1.0669536 #> [22,] -0.3777174 #> [23,] -0.8840846 #> [24,] -1.1029604 #> [25,] -0.3808202 #> [26,] -0.4154355 #> [27,] -0.4091322 #> [28,] -0.4118489 #> [29,] -0.6308571 #> [30,] -0.4026741 #>  #> , , 178 #>  #>             [,1] #>  [1,] -1.5502548 #>  [2,] -1.2267574 #>  [3,] -1.7633411 #>  [4,] -1.6600797 #>  [5,] -1.8651079 #>  [6,] -0.9645303 #>  [7,] -0.8908240 #>  [8,] -1.6116301 #>  [9,] -1.7708414 #> [10,] -1.8830760 #> [11,] -0.4868906 #> [12,]  0.2575726 #> [13,] -0.3117875 #> [14,]  0.6855609 #> 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[29,] -0.42228044 #> [30,] -0.23875180 #>  #> , , 183 #>  #>              [,1] #>  [1,] -1.39754539 #>  [2,] -0.89850601 #>  [3,] -1.55104243 #>  [4,] -1.42682339 #>  [5,] -1.74444708 #>  [6,] -0.50556339 #>  [7,] -0.44453992 #>  [8,] -1.38439698 #>  [9,] -1.74900755 #> [10,] -1.87557812 #> [11,] -0.71831793 #> [12,]  0.09177883 #> [13,] -0.51974583 #> [14,]  0.54610097 #> [15,] -0.40441908 #> [16,] -0.84694111 #> [17,] -0.60105971 #> [18,]  0.05291220 #> [19,] -0.41585605 #> [20,] -0.12119721 #> [21,] -0.79516052 #> [22,] -0.17559838 #> [23,] -0.62399191 #> [24,] -0.82387705 #> [25,] -0.18906373 #> [26,] -0.22511839 #> [27,] -0.21923767 #> [28,] -0.22102263 #> [29,] -0.38496828 #> [30,] -0.21150955 #>  #> , , 184 #>  #>              [,1] #>  [1,] -1.35715738 #>  [2,] -0.82371856 #>  [3,] -1.49749374 #>  [4,] -1.36919799 #>  [5,] -1.70883523 #>  [6,] -0.40700842 #>  [7,] -0.34910295 #>  [8,] -1.32871598 #>  [9,] -1.73561491 #> [10,] -1.86464730 #> [11,] -0.76435199 #> [12,]  0.05770563 #> [13,] -0.56150456 #> [14,]  0.51691401 #> [15,] -0.44699251 #> [16,] -0.88910434 #> [17,] -0.64616757 #> [18,]  0.01598521 #> [19,] -0.45725815 #> [20,] -0.15974692 #> [21,] -0.75124746 #> [22,] -0.14882469 #> [23,] -0.58341696 #> [24,] -0.77879553 #> [25,] -0.16366966 #> [26,] -0.19963340 #> [27,] -0.19388809 #> [28,] -0.19552252 #> [29,] -0.34929427 #> [30,] -0.18613506 #>  #> , , 185 #>  #>              [,1] #>  [1,] -1.31383402 #>  [2,] -0.74643806 #>  [3,] -1.44030837 #>  [4,] -1.30805853 #>  [5,] -1.66974179 #>  [6,] -0.30685007 #>  [7,] -0.25219866 #>  [8,] -1.26991831 #>  [9,] -1.71910714 #> [10,] -1.85068726 #> [11,] -0.81016174 #> [12,]  0.02331990 #> [13,] -0.60326152 #> [14,]  0.48729100 #> [15,] -0.48964497 #> [16,] -0.93090164 #> [17,] -0.69116768 #> [18,] -0.02135287 #> [19,] -0.49870467 #> [20,] -0.19854478 #> [21,] -0.70796615 #> [22,] -0.12412949 #> [23,] -0.54385815 #> [24,] -0.73437288 #> [25,] -0.14021872 #> [26,] -0.17594289 #> [27,] -0.17036195 #> [28,] 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[12,] -0.04619759 #> [13,] -0.68653713 #> [14,]  0.42682438 #> [15,] -0.57507947 #> [16,] -1.01332995 #> [17,] -0.78081487 #> [18,] -0.09674908 #> [19,] -0.58170056 #> [20,] -0.27672069 #> [21,] -0.62363477 #> [22,] -0.08102730 #> [23,] -0.46825872 #> [24,] -0.64785870 #> [25,] -0.09914774 #> [26,] -0.13385741 #> [27,] -0.12870744 #> [28,] -0.12991144 #> [29,] -0.25265109 #> [30,] -0.12117603 #>  #> , , 188 #>  #>                [,1] #>  [1,] -1.1662203750 #>  [2,] -0.5014544901 #>  [3,] -1.2476064293 #>  [4,] -1.1027455992 #>  [5,] -1.5307307254 #>  [6,]  0.0003200125 #>  [7,]  0.0441850859 #>  [8,] -1.0743284481 #>  [9,] -1.6492979474 #> [10,] -1.7854552571 #> [11,] -0.9460185744 #> [12,] -0.0814390563 #> [13,] -0.7280485682 #> [14,]  0.3961233298 #> [15,] -0.6177920998 #> [16,] -1.0536219851 #> [17,] -0.8253146286 #> [18,] -0.1348938881 #> [19,] -0.6231825251 #> [20,] -0.3160892883 #> [21,] -0.5827469528 #> [22,] -0.0626191759 #> [23,] -0.4323905426 #> [24,] -0.6059377589 #> [25,] 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-0.92899218 #>  [9,] -1.58723991 #> [10,] -1.72616676 #> [11,] -1.03476156 #> [12,] -0.15240868 #> [13,] -0.81042520 #> [14,]  0.33328546 #> [15,] -0.70297200 #> [16,] -1.13273757 #> [17,] -0.91353953 #> [18,] -0.21185764 #> [19,] -0.70593496 #> [20,] -0.39525219 #> [21,] -0.50397494 #> [22,] -0.03200065 #> [23,] -0.36464344 #> [24,] -0.52537752 #> [25,] -0.05201461 #> [26,] -0.08334364 #> [27,] -0.07915163 #> [28,] -0.07996177 #> [29,] -0.17237694 #> [30,] -0.07241068 #>  #> , , 191 #>  #>              [,1] #>  [1,] -0.99120323 #>  [2,] -0.24087952 #>  [3,] -1.02572354 #>  [4,] -0.86971704 #>  [5,] -1.35843966 #>  [6,]  0.31077156 #>  [7,]  0.34230918 #>  [8,] -0.85258708 #>  [9,] -1.55075624 #> [10,] -1.69034230 #> [11,] -1.07829801 #> [12,] -0.18825555 #> [13,] -0.85135020 #> [14,]  0.30131384 #> [15,] -0.74542798 #> [16,] -1.17103690 #> [17,] -0.95714411 #> [18,] -0.25064867 #> [19,] -0.74717252 #> [20,] -0.43498430 #> [21,] -0.46631805 #> [22,] -0.01971994 #> [23,] -0.33286386 #> [24,] -0.48688864 #> [25,] -0.04002001 #> [26,] -0.06962388 #> [27,] -0.06584842 #> [28,] -0.06653517 #> [29,] -0.14934986 #> [30,] -0.05952587 #>  #> , , 192 #>  #>               [,1] #>  [1,] -0.927846253 #>  [2,] -0.151430660 #>  [3,] -0.945922332 #>  [4,] -0.786712215 #>  [5,] -1.294473886 #>  [6,]  0.413315517 #>  [7,]  0.440440947 #>  [8,] -0.773864803 #>  [9,] -1.511330715 #> [10,] -1.651172850 #> [11,] -1.121294832 #> [12,] -0.224216394 #> [13,] -0.891862872 #> [14,]  0.268926182 #> [15,] -0.787636779 #> [16,] -1.208703169 #> [17,] -1.000271008 #> [18,] -0.289608110 #> [19,] -0.788233838 #> [20,] -0.474801775 #> [21,] -0.429849782 #> [22,] -0.009391611 #> [23,] -0.302539100 #> [24,] -0.449669099 #> [25,] -0.029751103 #> [26,] -0.057330083 #> [27,] -0.054023160 #> [28,] -0.054589869 #> [29,] -0.128189601 #> [30,] -0.048206745 #>  #> , , 193 #>  #>                [,1] #>  [1,] -0.8621029910 #>  [2,] -0.0612346559 #>  [3,] -0.8634782947 #>  [4,] -0.7011804352 #>  [5,] -1.2272746039 #>  [6,]  0.5148034988 #>  [7,]  0.5373862114 #>  [8,] -0.6929602898 #>  [9,] -1.4689360318 #> [10,] -1.6088401542 #> [11,] -1.1637718204 #> [12,] -0.2604100580 #> [13,] -0.9321084008 #> [14,]  0.2363166388 #> [15,] -0.8296705655 #> [16,] -1.2457227956 #> [17,] -1.0430389712 #> [18,] -0.3287869079 #> [19,] -0.8290790586 #> [20,] -0.5146648039 #> [21,] -0.3947176468 #> [22,] -0.0009506878 #> [23,] -0.2737055535 #> [24,] -0.4137600509 #> [25,] -0.0211318892 #> [26,] -0.0463864896 #> [27,] -0.0435810995 #> [28,] -0.0440305606 #> [29,] -0.1088818850 #> [30,] -0.0383646605 #>  #> , , 194 #>  #>               [,1] #>  [1,] -0.793969297 #>  [2,]  0.029409586 #>  [3,] -0.778436232 #>  [4,] -0.612978846 #>  [5,] -1.156783858 #>  [6,]  0.614789471 #>  [7,]  0.632805927 #>  [8,] -0.609698769 #>  [9,] -1.423489975 #> [10,] -1.563415799 #> [11,] -1.205479064 #> [12,] -0.296718211 #> [13,] -0.972076178 #> [14,]  0.203162446 #> [15,] -0.871521814 #> [16,] -1.281666341 #> [17,] -1.085323033 #> [18,] -0.368052426 #> [19,] -0.869764151 #> [20,] -0.554533848 #> [21,] -0.360927022 #> [22,]  0.005679786 #> [23,] -0.246393127 #> [24,] -0.379213313 #> [25,] -0.014075323 #> [26,] -0.036663391 #> [27,] -0.034416491 #> [28,] -0.034750773 #> [29,] -0.091402096 #> [30,] -0.029899868 #>  #> , , 195 #>  #>               [,1] #>  [1,] -0.723033985 #>  [2,]  0.120232407 #>  [3,] -0.690937937 #>  [4,] -0.522831778 #>  [5,] -1.082827863 #>  [6,]  0.712919209 #>  [7,]  0.726360094 #>  [8,] -0.524373642 #>  [9,] -1.374907167 #> [10,] -1.514921147 #> [11,] -1.246385959 #> [12,] -0.333130120 #> [13,] -1.011444675 #> [14,]  0.169852026 #> [15,] -0.912936953 #> [16,] -1.316619840 #> [17,] -1.126856321 #> [18,] -0.407450136 #> [19,] -0.910123436 #> [20,] -0.594394656 #> [21,] -0.328501182 #> [22,]  0.010588706 #> [23,] -0.220624993 #> [24,] -0.346081079 #> [25,] -0.008483452 #> [26,] -0.028030462 #> [27,] -0.026412853 #> [28,] -0.026633161 #> [29,] -0.075715152 #> [30,] -0.022701724 #>  #> , , 196 #>  #>               [,1] #>  [1,] -0.650185151 #>  [2,]  0.210965645 #>  [3,] -0.601464681 #>  [4,] -0.431000154 #>  [5,] -1.006079725 #>  [6,]  0.808876599 #>  [7,]  0.817709199 #>  [8,] -0.437473487 #>  [9,] -1.322666912 #> [10,] -1.462046044 #> [11,] -1.286626433 #> [12,] -0.369714638 #> [13,] -1.050438623 #> [14,]  0.136076678 #> [15,] -0.954081406 #> [16,] -1.350761662 #> [17,] -1.167911970 #> [18,] -0.446946438 #> [19,] -0.950168936 #> [20,] -0.634194932 #> [21,] -0.297487149 #> [22,]  0.013876794 #> [23,] -0.196417360 #> [24,] -0.314410123 #> [25,] -0.004247608 #> [26,] -0.020357565 #> [27,] -0.019443316 #> [28,] -0.019549847 #> [29,] -0.061775408 #> [30,] -0.016648980 #>  #> , , 197 #>  #>               [,1] #>  [1,] -0.575556006 #>  [2,]  0.301335857 #>  [3,] -0.510181120 #>  [4,] -0.337692869 #>  [5,] -0.926768895 #>  [6,]  0.902308278 #>  [7,]  0.906515719 #>  [8,] -0.349204238 #>  [9,] -1.267716729 #> [10,] -1.405994499 #> [11,] -1.325993755 #> [12,] -0.406349954 #> [13,] -1.089050306 #> [14,]  0.102036688 #> [15,] -0.994949646 #> [16,] -1.383907153 #> [17,] -1.208422332 #> [18,] -0.486487819 #> [19,] -0.989965720 #> [20,] -0.673946655 #> [21,] -0.267926926 #> [22,]  0.015656420 #> [23,] -0.173779270 #> [24,] -0.284241546 #> [25,] -0.001248661 #> [26,] -0.013504909 #> [27,] -0.013371022 #> [28,] -0.013362835 #> [29,] -0.049526606 #> [30,] -0.011610129 #>  #> , , 198 #>  #>                [,1] #>  [1,] -0.4992844973 #>  [2,]  0.3910651625 #>  [3,] -0.4172109171 #>  [4,] -0.2431268687 #>  [5,] -0.8450142561 #>  [6,]  0.9928641217 #>  [7,]  0.9924456596 #>  [8,] -0.2597557343 #>  [9,] -1.2100624012 #> [10,] -1.3469856946 #> [11,] -1.3642721753 #> [12,] -0.4430702374 #> [13,] -1.1268635293 #> [14,]  0.0676871160 #> [15,] -1.0351706383 #> [16,] -1.4155595078 #> [17,] -1.2478365998 #> [18,] -0.5260827053 #> [19,] -1.0292632788 #> [20,] -0.7135514435 #> [21,] -0.2398572798 #> [22,]  0.0160513632 #> [23,] -0.1527124075 #> [24,] -0.2556105251 #> [25,]  0.0006426683 #> [26,] -0.0073235578 #> [27,] -0.0080496092 #> [28,] -0.0079275363 #> [29,] -0.0389018667 #> [30,] -0.0074438167 #>  #> , , 199 #>  #>               [,1] #>  [1,] -0.421510053 #>  [2,]  0.479872129 #>  [3,] -0.322725528 #>  [4,] -0.147522287 #>  [5,] -0.760881674 #>  [6,]  1.080198918 #>  [7,]  1.075144276 #>  [8,] -0.169324367 #>  [9,] -1.149663371 #> [10,] -1.285143955 #> [11,] -1.401682659 #> [12,] -0.479833582 #> [13,] -1.164186428 #> [14,]  0.032975565 #> [15,] -1.075020746 #> [16,] -1.446249705 #> [17,] -1.286657771 #> [18,] -0.565674696 #> [19,] -1.068161911 #> [20,] -0.753012020 #> [21,] -0.213309519 #> [22,]  0.015196505 #> [23,] -0.133210934 #> [24,] -0.228546073 #> [25,]  0.001565434 #> [26,] -0.001656003 #> [27,] -0.003323753 #> [28,] -0.003094051 #> [29,] -0.029823744 #> [30,] -0.004014870 #>  #> , , 200 #>  #>                [,1] #>  [1,] -0.3423687995 #>  [2,]  0.5674727056 #>  [3,] -0.2270817231 #>  [4,] -0.0510936687 #>  [5,] -0.6743401179 #>  [6,]  1.1639740745 #>  [7,]  1.1540960933 #>  [8,] -0.0781127999 #>  [9,] -1.0864557084 #> [10,] -1.2205292742 #> [11,] -1.4381773667 #> [12,] -0.5166220923 #> [13,] -1.2010177137 #> [14,] -0.0018695731 #> [15,] -1.1144993261 #> [16,] -1.4760011597 #> [17,] -1.3248925041 #> [18,] -0.6052645843 #> [19,] -1.1067078697 #> [20,] -0.7923624353 #> [21,] -0.1883092902 #> [22,]  0.0132374553 #> [23,] -0.1152613448 #> [24,] -0.2030708185 #> [25,]  0.0016680301 #> [26,]  0.0036631880 #> [27,]  0.0009702148 #> [28,]  0.0013246578 #> [29,] -0.0222043173 #> [30,] -0.0011514266 #>  #>  #> $aligned_grids #>             [,1]       [,2]       [,3]       [,4]      [,5]      [,6]      [,7] #>  [1,] 0.56832832 0.59466626 0.62100420 0.64734214 0.6736801 0.7000180 0.7263560 #>  [2,] 0.53675452 0.56483775 0.59292097 0.62100420 0.6490874 0.6771706 0.7052539 #>  [3,] 0.56832832 0.59498358 0.62163885 0.64829411 0.6749494 0.7016046 0.7282599 #>  [4,] 0.50518073 0.53215332 0.55912591 0.58609850 0.6130711 0.6400437 0.6670163 #>  [5,] 0.50518073 0.53136001 0.55753928 0.58371856 0.6098978 0.6360771 0.6622564 #>  [6,] 0.56832832 0.59704619 0.62576407 0.65448194 0.6831998 0.7119177 0.7406356 #>  [7,] 0.59990211 0.62846133 0.65702054 0.68557975 0.7141390 0.7426982 0.7712574 #>  [8,] 0.59990211 0.62671604 0.65352997 0.68034390 0.7071578 0.7339717 0.7607857 #>  [9,] 0.53675452 0.56198183 0.58720913 0.61243644 0.6376637 0.6628910 0.6881183 #> [10,] 0.50518073 0.53040803 0.55563534 0.58086264 0.6060899 0.6313172 0.6565446 #> [11,] 0.18944277 0.21149683 0.23355089 0.25560495 0.2776590 0.2997131 0.3217671 #> [12,] 0.28416416 0.30352096 0.32287776 0.34223456 0.3615914 0.3809482 0.4003050 #> [13,] 0.28416416 0.30526624 0.32636833 0.34747041 0.3685725 0.3896746 0.4107767 #> [14,] 0.22101657 0.23926273 0.25750890 0.27575506 0.2940012 0.3122474 0.3304935 #> [15,] 0.22101657 0.24211865 0.26322074 0.28432282 0.3054249 0.3265270 0.3476291 #> [16,] 0.25259036 0.27480308 0.29701581 0.31922853 0.3414412 0.3636540 0.3858667 #> [17,] 0.22101657 0.24259464 0.26417271 0.28575078 0.3073289 0.3289069 0.3504850 #> [18,] 0.18944277 0.20943422 0.22942567 0.24941712 0.2694086 0.2894000 0.3093915 #> [19,] 0.31573796 0.33636405 0.35699015 0.37761625 0.3982423 0.4188684 0.4394945 #> [20,] 0.25259036 0.27274047 0.29289059 0.31304070 0.3331908 0.3533409 0.3734910 #> [21,] 0.06314759 0.09170680 0.12026602 0.14882523 0.1773844 0.2059437 0.2345029 #> [22,] 0.00000000 0.03157380 0.06314759 0.09472139 0.1262952 0.1578690 0.1894428 #> [23,] 0.03157380 0.06092632 0.09027884 0.11963137 0.1489839 0.1783364 0.2076889 #> [24,] 0.00000000 0.02887654 0.05775307 0.08662961 0.1155061 0.1443827 0.1732592 #> [25,] 0.06314759 0.09440406 0.12566053 0.15691700 0.1881735 0.2194299 0.2506864 #> [26,] 0.06314759 0.09440406 0.12566053 0.15691700 0.1881735 0.2194299 0.2506864 #> [27,] 0.03157380 0.06298893 0.09440406 0.12581920 0.1572343 0.1886495 0.2200646 #> [28,] 0.00000000 0.03157380 0.06314759 0.09472139 0.1262952 0.1578690 0.1894428 #> [29,] 0.00000000 0.03062182 0.06124364 0.09186547 0.1224873 0.1531091 0.1837309 #> [30,] 0.00000000 0.03157380 0.06314759 0.09472139 0.1262952 0.1578690 0.1894428 #>            [,8]      [,9]     [,10]     [,11]     [,12]     [,13]     [,14] #>  [1,] 0.7526939 0.7790318 0.8053698 0.8317077 0.8580457 0.8843836 0.9107215 #>  [2,] 0.7333371 0.7614203 0.7895036 0.8175868 0.8456700 0.8737532 0.9018365 #>  [3,] 0.7549152 0.7815704 0.8082257 0.8348810 0.8615362 0.8881915 0.9148468 #>  [4,] 0.6939889 0.7209614 0.7479340 0.7749066 0.8018792 0.8288518 0.8558244 #>  [5,] 0.6884357 0.7146149 0.7407942 0.7669735 0.7931528 0.8193321 0.8455113 #>  [6,] 0.7693534 0.7980713 0.8267892 0.8555071 0.8842249 0.9129428 0.9416607 #>  [7,] 0.7998166 0.8283758 0.8569350 0.8854942 0.9140534 0.9426127 0.9711719 #>  [8,] 0.7875996 0.8144135 0.8412275 0.8680414 0.8948553 0.9216692 0.9484832 #>  [9,] 0.7133457 0.7385730 0.7638003 0.7890276 0.8142549 0.8394822 0.8647095 #> [10,] 0.6817719 0.7069992 0.7322265 0.7574538 0.7826811 0.8079084 0.8331357 #> [11,] 0.3438212 0.3658752 0.3879293 0.4099834 0.4320374 0.4540915 0.4761455 #> [12,] 0.4196618 0.4390186 0.4583754 0.4777322 0.4970890 0.5164458 0.5358025 #> [13,] 0.4318788 0.4529808 0.4740829 0.4951850 0.5162871 0.5373892 0.5584913 #> [14,] 0.3487397 0.3669859 0.3852320 0.4034782 0.4217244 0.4399705 0.4582167 #> [15,] 0.3687312 0.3898332 0.4109353 0.4320374 0.4531395 0.4742416 0.4953437 #> [16,] 0.4080794 0.4302921 0.4525048 0.4747176 0.4969303 0.5191430 0.5413557 #> [17,] 0.3720631 0.3936411 0.4152192 0.4367973 0.4583754 0.4799534 0.5015315 #> [18,] 0.3293829 0.3493744 0.3693658 0.3893573 0.4093487 0.4293402 0.4493316 #> [19,] 0.4601206 0.4807467 0.5013728 0.5219989 0.5426250 0.5632511 0.5838772 #> [20,] 0.3936411 0.4137912 0.4339414 0.4540915 0.4742416 0.4943917 0.5145418 #> [21,] 0.2630621 0.2916213 0.3201805 0.3487397 0.3772989 0.4058581 0.4344173 #> [22,] 0.2210166 0.2525904 0.2841642 0.3157380 0.3473118 0.3788855 0.4104593 #> [23,] 0.2370415 0.2663940 0.2957465 0.3250990 0.3544516 0.3838041 0.4131566 #> [24,] 0.2021358 0.2310123 0.2598888 0.2887654 0.3176419 0.3465184 0.3753950 #> [25,] 0.2819429 0.3131994 0.3444558 0.3757123 0.4069688 0.4382252 0.4694817 #> [26,] 0.2819429 0.3131994 0.3444558 0.3757123 0.4069688 0.4382252 0.4694817 #> [27,] 0.2514797 0.2828949 0.3143100 0.3457251 0.3771403 0.4085554 0.4399705 #> [28,] 0.2210166 0.2525904 0.2841642 0.3157380 0.3473118 0.3788855 0.4104593 #> [29,] 0.2143528 0.2449746 0.2755964 0.3062182 0.3368400 0.3674619 0.3980837 #> [30,] 0.2210166 0.2525904 0.2841642 0.3157380 0.3473118 0.3788855 0.4104593 #>           [,15]     [,16]     [,17]     [,18]     [,19]     [,20]     [,21] #>  [1,] 0.9370595 0.9633974 0.9897354 1.0160733 1.0424112 1.0687492 1.0950871 #>  [2,] 0.9299197 0.9580029 0.9860861 1.0141694 1.0422526 1.0703358 1.0984190 #>  [3,] 0.9415020 0.9681573 0.9948126 1.0214678 1.0481231 1.0747783 1.1014336 #>  [4,] 0.8827970 0.9097696 0.9367422 0.9637147 0.9906873 1.0176599 1.0446325 #>  [5,] 0.8716906 0.8978699 0.9240492 0.9502284 0.9764077 1.0025870 1.0287663 #>  [6,] 0.9703786 0.9990964 1.0278143 1.0565322 1.0852501 1.1139679 1.1426858 #>  [7,] 0.9997311 1.0282903 1.0568495 1.0854087 1.1139679 1.1425271 1.1710864 #>  [8,] 0.9752971 1.0021110 1.0289249 1.0557389 1.0825528 1.1093667 1.1361807 #>  [9,] 0.8899368 0.9151641 0.9403914 0.9656187 0.9908460 1.0160733 1.0413006 #> [10,] 0.8583630 0.8835903 0.9088176 0.9340449 0.9592722 0.9844995 1.0097268 #> [11,] 0.4981996 0.5202536 0.5423077 0.5643618 0.5864158 0.6084699 0.6305239 #> [12,] 0.5551593 0.5745161 0.5938729 0.6132297 0.6325865 0.6519433 0.6713001 #> [13,] 0.5795933 0.6006954 0.6217975 0.6428996 0.6640017 0.6851038 0.7062058 #> [14,] 0.4764629 0.4947090 0.5129552 0.5312013 0.5494475 0.5676937 0.5859398 #> [15,] 0.5164458 0.5375478 0.5586499 0.5797520 0.6008541 0.6219562 0.6430583 #> [16,] 0.5635685 0.5857812 0.6079939 0.6302066 0.6524193 0.6746321 0.6968448 #> [17,] 0.5231096 0.5446876 0.5662657 0.5878438 0.6094219 0.6309999 0.6525780 #> [18,] 0.4693231 0.4893145 0.5093059 0.5292974 0.5492888 0.5692803 0.5892717 #> [19,] 0.6045033 0.6251294 0.6457555 0.6663816 0.6870077 0.7076338 0.7282599 #> [20,] 0.5346919 0.5548420 0.5749921 0.5951422 0.6152924 0.6354425 0.6555926 #> [21,] 0.4629766 0.4915358 0.5200950 0.5486542 0.5772134 0.6057726 0.6343318 #> [22,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [23,] 0.4425091 0.4718616 0.5012142 0.5305667 0.5599192 0.5892717 0.6186243 #> [24,] 0.4042715 0.4331480 0.4620246 0.4909011 0.5197777 0.5486542 0.5775307 #> [25,] 0.5007382 0.5319947 0.5632511 0.5945076 0.6257641 0.6570205 0.6882770 #> [26,] 0.5007382 0.5319947 0.5632511 0.5945076 0.6257641 0.6570205 0.6882770 #> [27,] 0.4713857 0.5028008 0.5342159 0.5656311 0.5970462 0.6284613 0.6598765 #> [28,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [29,] 0.4287055 0.4593273 0.4899491 0.5205710 0.5511928 0.5818146 0.6124364 #> [30,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>           [,22]     [,23]     [,24]     [,25]     [,26]     [,27]     [,28] #>  [1,] 1.1214251 1.1477630 1.1741009 1.2004389 1.2267768 1.2531148 1.2794527 #>  [2,] 1.1265023 1.1545855 1.1826687 1.2107519 1.2388352 1.2669184 1.2950016 #>  [3,] 1.1280889 1.1547441 1.1813994 1.2080547 1.2347099 1.2613652 1.2880205 #>  [4,] 1.0716051 1.0985777 1.1255503 1.1525229 1.1794955 1.2064680 1.2334406 #>  [5,] 1.0549456 1.0811248 1.1073041 1.1334834 1.1596627 1.1858419 1.2120212 #>  [6,] 1.1714037 1.2001216 1.2288394 1.2575573 1.2862752 1.3149931 1.3437109 #>  [7,] 1.1996456 1.2282048 1.2567640 1.2853232 1.3138824 1.3424416 1.3710008 #>  [8,] 1.1629946 1.1898085 1.2166224 1.2434364 1.2702503 1.2970642 1.3238781 #>  [9,] 1.0665279 1.0917552 1.1169825 1.1422098 1.1674371 1.1926644 1.2178917 #> [10,] 1.0349541 1.0601814 1.0854087 1.1106360 1.1358633 1.1610906 1.1863179 #> [11,] 0.6525780 0.6746321 0.6966861 0.7187402 0.7407942 0.7628483 0.7849023 #> [12,] 0.6906569 0.7100137 0.7293705 0.7487273 0.7680841 0.7874409 0.8067977 #> [13,] 0.7273079 0.7484100 0.7695121 0.7906142 0.8117163 0.8328184 0.8539204 #> [14,] 0.6041860 0.6224322 0.6406783 0.6589245 0.6771706 0.6954168 0.7136630 #> [15,] 0.6641603 0.6852624 0.7063645 0.7274666 0.7485687 0.7696708 0.7907728 #> [16,] 0.7190575 0.7412702 0.7634829 0.7856957 0.8079084 0.8301211 0.8523338 #> [17,] 0.6741561 0.6957341 0.7173122 0.7388903 0.7604684 0.7820464 0.8036245 #> [18,] 0.6092632 0.6292546 0.6492461 0.6692375 0.6892290 0.7092204 0.7292119 #> [19,] 0.7488860 0.7695121 0.7901382 0.8107643 0.8313904 0.8520165 0.8726426 #> [20,] 0.6757427 0.6958928 0.7160429 0.7361930 0.7563431 0.7764932 0.7966434 #> [21,] 0.6628910 0.6914503 0.7200095 0.7485687 0.7771279 0.8056871 0.8342463 #> [22,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [23,] 0.6479768 0.6773293 0.7066818 0.7360344 0.7653869 0.7947394 0.8240919 #> [24,] 0.6064073 0.6352838 0.6641603 0.6930369 0.7219134 0.7507900 0.7796665 #> [25,] 0.7195335 0.7507900 0.7820464 0.8133029 0.8445594 0.8758158 0.9070723 #> [26,] 0.7195335 0.7507900 0.7820464 0.8133029 0.8445594 0.8758158 0.9070723 #> [27,] 0.6912916 0.7227067 0.7541219 0.7855370 0.8169521 0.8483673 0.8797824 #> [28,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [29,] 0.6430583 0.6736801 0.7043019 0.7349237 0.7655455 0.7961674 0.8267892 #> [30,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>           [,29]     [,30]     [,31]     [,32]     [,33]     [,34]     [,35] #>  [1,] 1.3057906 1.3321286 1.3584665 1.3848045 1.4111424 1.4374803 1.4638183 #>  [2,] 1.3230848 1.3511681 1.3792513 1.4073345 1.4354177 1.4635010 1.4915842 #>  [3,] 1.3146757 1.3413310 1.3679863 1.3946415 1.4212968 1.4479520 1.4746073 #>  [4,] 1.2604132 1.2873858 1.3143584 1.3413310 1.3683036 1.3952762 1.4222488 #>  [5,] 1.2382005 1.2643798 1.2905591 1.3167383 1.3429176 1.3690969 1.3952762 #>  [6,] 1.3724288 1.4011467 1.4298645 1.4585824 1.4873003 1.5160182 1.5447360 #>  [7,] 1.3995601 1.4281193 1.4566785 1.4852377 1.5137969 1.5423561 1.5709153 #>  [8,] 1.3506921 1.3775060 1.4043199 1.4311338 1.4579478 1.4847617 1.5115756 #>  [9,] 1.2431190 1.2683463 1.2935736 1.3188009 1.3440283 1.3692556 1.3944829 #> [10,] 1.2115452 1.2367725 1.2619998 1.2872272 1.3124545 1.3376818 1.3629091 #> [11,] 0.8069564 0.8290105 0.8510645 0.8731186 0.8951726 0.9172267 0.9392808 #> [12,] 0.8261545 0.8455113 0.8648681 0.8842249 0.9035817 0.9229385 0.9422953 #> [13,] 0.8750225 0.8961246 0.9172267 0.9383288 0.9594309 0.9805329 1.0016350 #> [14,] 0.7319091 0.7501553 0.7684015 0.7866476 0.8048938 0.8231400 0.8413861 #> [15,] 0.8118749 0.8329770 0.8540791 0.8751812 0.8962833 0.9173854 0.9384874 #> [16,] 0.8745465 0.8967593 0.9189720 0.9411847 0.9633974 0.9856101 1.0078229 #> [17,] 0.8252026 0.8467806 0.8683587 0.8899368 0.9115149 0.9330929 0.9546710 #> [18,] 0.7492033 0.7691948 0.7891862 0.8091777 0.8291691 0.8491606 0.8691520 #> [19,] 0.8932687 0.9138948 0.9345209 0.9551470 0.9757731 0.9963992 1.0170253 #> [20,] 0.8167935 0.8369436 0.8570937 0.8772438 0.8973939 0.9175440 0.9376941 #> [21,] 0.8628055 0.8913647 0.9199240 0.9484832 0.9770424 1.0056016 1.0341608 #> [22,] 0.8840663 0.9156401 0.9472139 0.9787877 1.0103615 1.0419353 1.0735090 #> [23,] 0.8534445 0.8827970 0.9121495 0.9415020 0.9708545 1.0002071 1.0295596 #> [24,] 0.8085430 0.8374196 0.8662961 0.8951726 0.9240492 0.9529257 0.9818022 #> [25,] 0.9383288 0.9695852 1.0008417 1.0320982 1.0633547 1.0946111 1.1258676 #> [26,] 0.9383288 0.9695852 1.0008417 1.0320982 1.0633547 1.0946111 1.1258676 #> [27,] 0.9111975 0.9426127 0.9740278 1.0054429 1.0368581 1.0682732 1.0996883 #> [28,] 0.8840663 0.9156401 0.9472139 0.9787877 1.0103615 1.0419353 1.0735090 #> [29,] 0.8574110 0.8880328 0.9186547 0.9492765 0.9798983 1.0105201 1.0411419 #> [30,] 0.8840663 0.9156401 0.9472139 0.9787877 1.0103615 1.0419353 1.0735090 #>           [,36]     [,37]     [,38]     [,39]     [,40]     [,41]     [,42] #>  [1,] 1.4901562 1.5164942 1.5428321 1.5691700 1.5955080 1.6218459 1.6481839 #>  [2,] 1.5196674 1.5477506 1.5758339 1.6039171 1.6320003 1.6600835 1.6881668 #>  [3,] 1.5012626 1.5279178 1.5545731 1.5812284 1.6078836 1.6345389 1.6611942 #>  [4,] 1.4492213 1.4761939 1.5031665 1.5301391 1.5571117 1.5840843 1.6110569 #>  [5,] 1.4214554 1.4476347 1.4738140 1.4999933 1.5261726 1.5523518 1.5785311 #>  [6,] 1.5734539 1.6021718 1.6308897 1.6596075 1.6883254 1.7170433 1.7457612 #>  [7,] 1.5994745 1.6280337 1.6565930 1.6851522 1.7137114 1.7422706 1.7708298 #>  [8,] 1.5383896 1.5652035 1.5920174 1.6188313 1.6456453 1.6724592 1.6992731 #>  [9,] 1.4197102 1.4449375 1.4701648 1.4953921 1.5206194 1.5458467 1.5710740 #> [10,] 1.3881364 1.4133637 1.4385910 1.4638183 1.4890456 1.5142729 1.5395002 #> [11,] 0.9613348 0.9833889 1.0054429 1.0274970 1.0495510 1.0716051 1.0936592 #> [12,] 0.9616521 0.9810089 1.0003657 1.0197225 1.0390793 1.0584361 1.0777929 #> [13,] 1.0227371 1.0438392 1.0649413 1.0860434 1.1071455 1.1282475 1.1493496 #> [14,] 0.8596323 0.8778784 0.8961246 0.9143708 0.9326169 0.9508631 0.9691093 #> [15,] 0.9595895 0.9806916 1.0017937 1.0228958 1.0439979 1.0650999 1.0862020 #> [16,] 1.0300356 1.0522483 1.0744610 1.0966737 1.1188865 1.1410992 1.1633119 #> [17,] 0.9762491 0.9978271 1.0194052 1.0409833 1.0625613 1.0841394 1.1057175 #> [18,] 0.8891435 0.9091349 0.9291264 0.9491178 0.9691093 0.9891007 1.0090922 #> [19,] 1.0376514 1.0582775 1.0789036 1.0995297 1.1201558 1.1407819 1.1614080 #> [20,] 0.9578442 0.9779943 0.9981445 1.0182946 1.0384447 1.0585948 1.0787449 #> [21,] 1.0627200 1.0912792 1.1198384 1.1483976 1.1769569 1.2055161 1.2340753 #> [22,] 1.1050828 1.1366566 1.1682304 1.1998042 1.2313780 1.2629518 1.2945256 #> [23,] 1.0589121 1.0882646 1.1176172 1.1469697 1.1763222 1.2056747 1.2350273 #> [24,] 1.0106788 1.0395553 1.0684319 1.0973084 1.1261849 1.1550615 1.1839380 #> [25,] 1.1571241 1.1883805 1.2196370 1.2508935 1.2821500 1.3134064 1.3446629 #> [26,] 1.1571241 1.1883805 1.2196370 1.2508935 1.2821500 1.3134064 1.3446629 #> [27,] 1.1311035 1.1625186 1.1939337 1.2253489 1.2567640 1.2881791 1.3195943 #> [28,] 1.1050828 1.1366566 1.1682304 1.1998042 1.2313780 1.2629518 1.2945256 #> [29,] 1.0717638 1.1023856 1.1330074 1.1636292 1.1942510 1.2248729 1.2554947 #> [30,] 1.1050828 1.1366566 1.1682304 1.1998042 1.2313780 1.2629518 1.2945256 #>           [,43]    [,44]    [,45]    [,46]    [,47]    [,48]    [,49]    [,50] #>  [1,] 1.6745218 1.700860 1.727198 1.753536 1.779874 1.806211 1.832549 1.858887 #>  [2,] 1.7162500 1.744333 1.772416 1.800500 1.828583 1.856666 1.884749 1.912833 #>  [3,] 1.6878494 1.714505 1.741160 1.767815 1.794470 1.821126 1.847781 1.874436 #>  [4,] 1.6380295 1.665002 1.691975 1.718947 1.745920 1.772892 1.799865 1.826838 #>  [5,] 1.6047104 1.630890 1.657069 1.683248 1.709428 1.735607 1.761786 1.787965 #>  [6,] 1.7744790 1.803197 1.831915 1.860633 1.889351 1.918068 1.946786 1.975504 #>  [7,] 1.7993890 1.827948 1.856507 1.885067 1.913626 1.942185 1.970744 1.999304 #>  [8,] 1.7260870 1.752901 1.779715 1.806529 1.833343 1.860157 1.886971 1.913785 #>  [9,] 1.5963013 1.621529 1.646756 1.671983 1.697211 1.722438 1.747665 1.772892 #> [10,] 1.5647275 1.589955 1.615182 1.640409 1.665637 1.690864 1.716091 1.741319 #> [11,] 1.1157132 1.137767 1.159821 1.181875 1.203929 1.225984 1.248038 1.270092 #> [12,] 1.0971497 1.116507 1.135863 1.155220 1.174577 1.193934 1.213291 1.232647 #> [13,] 1.1704517 1.191554 1.212656 1.233758 1.254860 1.275962 1.297064 1.318166 #> [14,] 0.9873554 1.005602 1.023848 1.042094 1.060340 1.078586 1.096832 1.115079 #> [15,] 1.1073041 1.128406 1.149508 1.170610 1.191712 1.212815 1.233917 1.255019 #> [16,] 1.1855246 1.207737 1.229950 1.252163 1.274376 1.296588 1.318801 1.341014 #> [17,] 1.1272956 1.148874 1.170452 1.192030 1.213608 1.235186 1.256764 1.278342 #> [18,] 1.0290836 1.049075 1.069067 1.089058 1.109049 1.129041 1.149032 1.169024 #> [19,] 1.1820341 1.202660 1.223286 1.243912 1.264538 1.285165 1.305791 1.326417 #> [20,] 1.0988950 1.119045 1.139195 1.159345 1.179495 1.199646 1.219796 1.239946 #> [21,] 1.2626345 1.291194 1.319753 1.348312 1.376871 1.405431 1.433990 1.462549 #> [22,] 1.3260994 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 #> [23,] 1.2643798 1.293732 1.323085 1.352437 1.381790 1.411142 1.440495 1.469847 #> [24,] 1.2128145 1.241691 1.270568 1.299444 1.328321 1.357197 1.386074 1.414950 #> [25,] 1.3759194 1.407176 1.438432 1.469689 1.500945 1.532202 1.563458 1.594715 #> [26,] 1.3759194 1.407176 1.438432 1.469689 1.500945 1.532202 1.563458 1.594715 #> [27,] 1.3510094 1.382425 1.413840 1.445255 1.476670 1.508085 1.539500 1.570915 #> [28,] 1.3260994 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 #> [29,] 1.2861165 1.316738 1.347360 1.377982 1.408604 1.439226 1.469847 1.500469 #> [30,] 1.3260994 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 #>          [,51]    [,52]    [,53]    [,54]    [,55]    [,56]    [,57]    [,58] #>  [1,] 1.885225 1.911563 1.937901 1.964239 1.990577 2.016915 2.043253 2.069591 #>  [2,] 1.940916 1.968999 1.997082 2.025165 2.053249 2.081332 2.109415 2.137498 #>  [3,] 1.901092 1.927747 1.954402 1.981057 2.007713 2.034368 2.061023 2.087678 #>  [4,] 1.853810 1.880783 1.907755 1.934728 1.961701 1.988673 2.015646 2.042618 #>  [5,] 1.814145 1.840324 1.866503 1.892682 1.918862 1.945041 1.971220 1.997400 #>  [6,] 2.004222 2.032940 2.061658 2.090376 2.119094 2.147811 2.176529 2.205247 #>  [7,] 2.027863 2.056422 2.084981 2.113540 2.142100 2.170659 2.199218 2.227777 #>  [8,] 1.940598 1.967412 1.994226 2.021040 2.047854 2.074668 2.101482 2.128296 #>  [9,] 1.798120 1.823347 1.848574 1.873802 1.899029 1.924256 1.949484 1.974711 #> [10,] 1.766546 1.791773 1.817001 1.842228 1.867455 1.892682 1.917910 1.943137 #> [11,] 1.292146 1.314200 1.336254 1.358308 1.380362 1.402416 1.424470 1.446524 #> [12,] 1.252004 1.271361 1.290718 1.310075 1.329431 1.348788 1.368145 1.387502 #> [13,] 1.339268 1.360370 1.381473 1.402575 1.423677 1.444779 1.465881 1.486983 #> [14,] 1.133325 1.151571 1.169817 1.188063 1.206309 1.224556 1.242802 1.261048 #> [15,] 1.276121 1.297223 1.318325 1.339427 1.360529 1.381631 1.402733 1.423835 #> [16,] 1.363226 1.385439 1.407652 1.429865 1.452077 1.474290 1.496503 1.518715 #> [17,] 1.299920 1.321498 1.343076 1.364654 1.386232 1.407810 1.429389 1.450967 #> [18,] 1.189015 1.209007 1.228998 1.248990 1.268981 1.288972 1.308964 1.328955 #> [19,] 1.347043 1.367669 1.388295 1.408921 1.429547 1.450173 1.470799 1.491426 #> [20,] 1.260096 1.280246 1.300396 1.320546 1.340696 1.360846 1.380997 1.401147 #> [21,] 1.491108 1.519667 1.548227 1.576786 1.605345 1.633904 1.662463 1.691023 #> [22,] 1.578690 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 #> [23,] 1.499200 1.528552 1.557905 1.587258 1.616610 1.645963 1.675315 1.704668 #> [24,] 1.443827 1.472703 1.501580 1.530456 1.559333 1.588210 1.617086 1.645963 #> [25,] 1.625971 1.657228 1.688484 1.719741 1.750997 1.782253 1.813510 1.844766 #> [26,] 1.625971 1.657228 1.688484 1.719741 1.750997 1.782253 1.813510 1.844766 #> [27,] 1.602330 1.633746 1.665161 1.696576 1.727991 1.759406 1.790821 1.822236 #> [28,] 1.578690 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 #> [29,] 1.531091 1.561713 1.592335 1.622957 1.653578 1.684200 1.714822 1.745444 #> [30,] 1.578690 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 #>          [,59]    [,60]    [,61]    [,62]    [,63]    [,64]    [,65]    [,66] #>  [1,] 2.095929 2.122267 2.148605 2.174943 2.201281 2.227619 2.253956 2.280294 #>  [2,] 2.165582 2.193665 2.221748 2.249831 2.277914 2.305998 2.334081 2.362164 #>  [3,] 2.114334 2.140989 2.167644 2.194299 2.220955 2.247610 2.274265 2.300921 #>  [4,] 2.069591 2.096563 2.123536 2.150509 2.177481 2.204454 2.231426 2.258399 #>  [5,] 2.023579 2.049758 2.075937 2.102117 2.128296 2.154475 2.180655 2.206834 #>  [6,] 2.233965 2.262683 2.291401 2.320119 2.348837 2.377554 2.406272 2.434990 #>  [7,] 2.256336 2.284896 2.313455 2.342014 2.370573 2.399132 2.427692 2.456251 #>  [8,] 2.155110 2.181924 2.208738 2.235552 2.262366 2.289180 2.315993 2.342807 #>  [9,] 1.999938 2.025165 2.050393 2.075620 2.100847 2.126075 2.151302 2.176529 #> [10,] 1.968364 1.993592 2.018819 2.044046 2.069274 2.094501 2.119728 2.144955 #> [11,] 1.468578 1.490632 1.512686 1.534740 1.556794 1.578848 1.600902 1.622957 #> [12,] 1.406859 1.426215 1.445572 1.464929 1.484286 1.503643 1.522999 1.542356 #> [13,] 1.508085 1.529187 1.550289 1.571391 1.592493 1.613595 1.634698 1.655800 #> [14,] 1.279294 1.297540 1.315786 1.334033 1.352279 1.370525 1.388771 1.407017 #> [15,] 1.444937 1.466040 1.487142 1.508244 1.529346 1.550448 1.571550 1.592652 #> [16,] 1.540928 1.563141 1.585354 1.607566 1.629779 1.651992 1.674204 1.696417 #> [17,] 1.472545 1.494123 1.515701 1.537279 1.558857 1.580435 1.602013 1.623591 #> [18,] 1.348947 1.368938 1.388930 1.408921 1.428913 1.448904 1.468895 1.488887 #> [19,] 1.512052 1.532678 1.553304 1.573930 1.594556 1.615182 1.635808 1.656434 #> [20,] 1.421297 1.441447 1.461597 1.481747 1.501897 1.522047 1.542197 1.562348 #> [21,] 1.719582 1.748141 1.776700 1.805260 1.833819 1.862378 1.890937 1.919496 #> [22,] 1.831280 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 #> [23,] 1.734020 1.763373 1.792725 1.822078 1.851430 1.880783 1.910135 1.939488 #> [24,] 1.674839 1.703716 1.732592 1.761469 1.790345 1.819222 1.848098 1.876975 #> [25,] 1.876023 1.907279 1.938536 1.969792 2.001049 2.032305 2.063562 2.094818 #> [26,] 1.876023 1.907279 1.938536 1.969792 2.001049 2.032305 2.063562 2.094818 #> [27,] 1.853652 1.885067 1.916482 1.947897 1.979312 2.010727 2.042142 2.073557 #> [28,] 1.831280 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 #> [29,] 1.776066 1.806687 1.837309 1.867931 1.898553 1.929175 1.959797 1.990418 #> [30,] 1.831280 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 #>          [,67]    [,68]    [,69]    [,70]    [,71]    [,72]    [,73]    [,74] #>  [1,] 2.306632 2.332970 2.359308 2.385646 2.411984 2.438322 2.464660 2.490998 #>  [2,] 2.390247 2.418331 2.446414 2.474497 2.502580 2.530664 2.558747 2.586830 #>  [3,] 2.327576 2.354231 2.380886 2.407542 2.434197 2.460852 2.487507 2.514163 #>  [4,] 2.285372 2.312344 2.339317 2.366289 2.393262 2.420235 2.447207 2.474180 #>  [5,] 2.233013 2.259192 2.285372 2.311551 2.337730 2.363909 2.390089 2.416268 #>  [6,] 2.463708 2.492426 2.521144 2.549862 2.578580 2.607297 2.636015 2.664733 #>  [7,] 2.484810 2.513369 2.541929 2.570488 2.599047 2.627606 2.656165 2.684725 #>  [8,] 2.369621 2.396435 2.423249 2.450063 2.476877 2.503691 2.530505 2.557319 #>  [9,] 2.201757 2.226984 2.252211 2.277438 2.302666 2.327893 2.353120 2.378348 #> [10,] 2.170183 2.195410 2.220637 2.245865 2.271092 2.296319 2.321547 2.346774 #> [11,] 1.645011 1.667065 1.689119 1.711173 1.733227 1.755281 1.777335 1.799389 #> [12,] 1.561713 1.581070 1.600427 1.619783 1.639140 1.658497 1.677854 1.697211 #> [13,] 1.676902 1.698004 1.719106 1.740208 1.761310 1.782412 1.803514 1.824616 #> [14,] 1.425263 1.443510 1.461756 1.480002 1.498248 1.516494 1.534740 1.552986 #> [15,] 1.613754 1.634856 1.655958 1.677060 1.698162 1.719265 1.740367 1.761469 #> [16,] 1.718630 1.740843 1.763055 1.785268 1.807481 1.829694 1.851906 1.874119 #> [17,] 1.645169 1.666747 1.688325 1.709903 1.731482 1.753060 1.774638 1.796216 #> [18,] 1.508878 1.528870 1.548861 1.568853 1.588844 1.608836 1.628827 1.648819 #> [19,] 1.677060 1.697686 1.718313 1.738939 1.759565 1.780191 1.800817 1.821443 #> [20,] 1.582498 1.602648 1.622798 1.642948 1.663098 1.683248 1.703398 1.723548 #> [21,] 1.948056 1.976615 2.005174 2.033733 2.062292 2.090852 2.119411 2.147970 #> [22,] 2.083871 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 #> [23,] 1.968840 1.998193 2.027545 2.056898 2.086250 2.115603 2.144955 2.174308 #> [24,] 1.905851 1.934728 1.963604 1.992481 2.021358 2.050234 2.079111 2.107987 #> [25,] 2.126075 2.157331 2.188588 2.219844 2.251101 2.282357 2.313613 2.344870 #> [26,] 2.126075 2.157331 2.188588 2.219844 2.251101 2.282357 2.313613 2.344870 #> [27,] 2.104973 2.136388 2.167803 2.199218 2.230633 2.262048 2.293463 2.324879 #> [28,] 2.083871 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 #> [29,] 2.021040 2.051662 2.082284 2.112906 2.143528 2.174149 2.204771 2.235393 #> [30,] 2.083871 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 #>          [,75]    [,76]    [,77]    [,78]    [,79]    [,80]    [,81]    [,82] #>  [1,] 2.517336 2.543674 2.570012 2.596350 2.622688 2.649026 2.675364 2.701701 #>  [2,] 2.614913 2.642996 2.671080 2.699163 2.727246 2.755329 2.783413 2.811496 #>  [3,] 2.540818 2.567473 2.594128 2.620784 2.647439 2.674094 2.700749 2.727405 #>  [4,] 2.501152 2.528125 2.555098 2.582070 2.609043 2.636015 2.662988 2.689960 #>  [5,] 2.442447 2.468627 2.494806 2.520985 2.547164 2.573344 2.599523 2.625702 #>  [6,] 2.693451 2.722169 2.750887 2.779605 2.808323 2.837040 2.865758 2.894476 #>  [7,] 2.713284 2.741843 2.770402 2.798961 2.827521 2.856080 2.884639 2.913198 #>  [8,] 2.584133 2.610947 2.637761 2.664574 2.691388 2.718202 2.745016 2.771830 #>  [9,] 2.403575 2.428802 2.454030 2.479257 2.504484 2.529712 2.554939 2.580166 #> [10,] 2.372001 2.397229 2.422456 2.447683 2.472910 2.498138 2.523365 2.548592 #> [11,] 1.821443 1.843497 1.865551 1.887605 1.909659 1.931713 1.953767 1.975821 #> [12,] 1.716567 1.735924 1.755281 1.774638 1.793995 1.813351 1.832708 1.852065 #> [13,] 1.845718 1.866820 1.887923 1.909025 1.930127 1.951229 1.972331 1.993433 #> [14,] 1.571233 1.589479 1.607725 1.625971 1.644217 1.662463 1.680710 1.698956 #> [15,] 1.782571 1.803673 1.824775 1.845877 1.866979 1.888081 1.909183 1.930285 #> [16,] 1.896332 1.918544 1.940757 1.962970 1.985183 2.007395 2.029608 2.051821 #> [17,] 1.817794 1.839372 1.860950 1.882528 1.904106 1.925684 1.947262 1.968840 #> [18,] 1.668810 1.688801 1.708793 1.728784 1.748776 1.768767 1.788759 1.808750 #> [19,] 1.842069 1.862695 1.883321 1.903947 1.924574 1.945200 1.965826 1.986452 #> [20,] 1.743699 1.763849 1.783999 1.804149 1.824299 1.844449 1.864599 1.884749 #> [21,] 2.176529 2.205088 2.233648 2.262207 2.290766 2.319325 2.347885 2.376444 #> [22,] 2.336461 2.368035 2.399608 2.431182 2.462756 2.494330 2.525904 2.557477 #> [23,] 2.203661 2.233013 2.262366 2.291718 2.321071 2.350423 2.379776 2.409128 #> [24,] 2.136864 2.165740 2.194617 2.223493 2.252370 2.281246 2.310123 2.338999 #> [25,] 2.376126 2.407383 2.438639 2.469896 2.501152 2.532409 2.563665 2.594922 #> [26,] 2.376126 2.407383 2.438639 2.469896 2.501152 2.532409 2.563665 2.594922 #> [27,] 2.356294 2.387709 2.419124 2.450539 2.481954 2.513369 2.544784 2.576200 #> [28,] 2.336461 2.368035 2.399608 2.431182 2.462756 2.494330 2.525904 2.557477 #> [29,] 2.266015 2.296637 2.327258 2.357880 2.388502 2.419124 2.449746 2.480368 #> [30,] 2.336461 2.368035 2.399608 2.431182 2.462756 2.494330 2.525904 2.557477 #>          [,83]    [,84]    [,85]    [,86]    [,87]    [,88]    [,89]    [,90] #>  [1,] 2.728039 2.754377 2.780715 2.807053 2.833391 2.859729 2.886067 2.912405 #>  [2,] 2.839579 2.867662 2.895745 2.923829 2.951912 2.979995 3.008078 3.036162 #>  [3,] 2.754060 2.780715 2.807371 2.834026 2.860681 2.887336 2.913992 2.940647 #>  [4,] 2.716933 2.743906 2.770878 2.797851 2.824823 2.851796 2.878769 2.905741 #>  [5,] 2.651881 2.678061 2.704240 2.730419 2.756599 2.782778 2.808957 2.835136 #>  [6,] 2.923194 2.951912 2.980630 3.009348 3.038066 3.066783 3.095501 3.124219 #>  [7,] 2.941758 2.970317 2.998876 3.027435 3.055994 3.084554 3.113113 3.141672 #>  [8,] 2.798644 2.825458 2.852272 2.879086 2.905900 2.932714 2.959528 2.986342 #>  [9,] 2.605393 2.630621 2.655848 2.681075 2.706303 2.731530 2.756757 2.781985 #> [10,] 2.573820 2.599047 2.624274 2.649502 2.674729 2.699956 2.725183 2.750411 #> [11,] 1.997876 2.019930 2.041984 2.064038 2.086092 2.108146 2.130200 2.152254 #> [12,] 1.871422 1.890778 1.910135 1.929492 1.948849 1.968206 1.987562 2.006919 #> [13,] 2.014535 2.035637 2.056739 2.077841 2.098943 2.120046 2.141148 2.162250 #> [14,] 1.717202 1.735448 1.753694 1.771940 1.790187 1.808433 1.826679 1.844925 #> [15,] 1.951387 1.972490 1.993592 2.014694 2.035796 2.056898 2.078000 2.099102 #> [16,] 2.074033 2.096246 2.118459 2.140672 2.162884 2.185097 2.207310 2.229522 #> [17,] 1.990418 2.011996 2.033575 2.055153 2.076731 2.098309 2.119887 2.141465 #> [18,] 1.828742 1.848733 1.868724 1.888716 1.908707 1.928699 1.948690 1.968682 #> [19,] 2.007078 2.027704 2.048330 2.068956 2.089582 2.110208 2.130835 2.151461 #> [20,] 1.904899 1.925050 1.945200 1.965350 1.985500 2.005650 2.025800 2.045950 #> [21,] 2.405003 2.433562 2.462121 2.490681 2.519240 2.547799 2.576358 2.604917 #> [22,] 2.589051 2.620625 2.652199 2.683773 2.715346 2.746920 2.778494 2.810068 #> [23,] 2.438481 2.467833 2.497186 2.526538 2.555891 2.585243 2.614596 2.643948 #> [24,] 2.367876 2.396753 2.425629 2.454506 2.483382 2.512259 2.541135 2.570012 #> [25,] 2.626178 2.657435 2.688691 2.719948 2.751204 2.782461 2.813717 2.844974 #> [26,] 2.626178 2.657435 2.688691 2.719948 2.751204 2.782461 2.813717 2.844974 #> [27,] 2.607615 2.639030 2.670445 2.701860 2.733275 2.764690 2.796106 2.827521 #> [28,] 2.589051 2.620625 2.652199 2.683773 2.715346 2.746920 2.778494 2.810068 #> [29,] 2.510989 2.541611 2.572233 2.602855 2.633477 2.664098 2.694720 2.725342 #> [30,] 2.589051 2.620625 2.652199 2.683773 2.715346 2.746920 2.778494 2.810068 #>          [,91]    [,92]    [,93]    [,94]    [,95]    [,96]    [,97]    [,98] #>  [1,] 2.938743 2.965081 2.991419 3.017757 3.044095 3.070433 3.096771 3.123108 #>  [2,] 3.064245 3.092328 3.120411 3.148494 3.176578 3.204661 3.232744 3.260827 #>  [3,] 2.967302 2.993957 3.020613 3.047268 3.073923 3.100578 3.127234 3.153889 #>  [4,] 2.932714 2.959686 2.986659 3.013632 3.040604 3.067577 3.094549 3.121522 #>  [5,] 2.861316 2.887495 2.913674 2.939854 2.966033 2.992212 3.018391 3.044571 #>  [6,] 3.152937 3.181655 3.210373 3.239091 3.267809 3.296526 3.325244 3.353962 #>  [7,] 3.170231 3.198790 3.227350 3.255909 3.284468 3.313027 3.341586 3.370146 #>  [8,] 3.013156 3.039969 3.066783 3.093597 3.120411 3.147225 3.174039 3.200853 #>  [9,] 2.807212 2.832439 2.857666 2.882894 2.908121 2.933348 2.958576 2.983803 #> [10,] 2.775638 2.800865 2.826093 2.851320 2.876547 2.901775 2.927002 2.952229 #> [11,] 2.174308 2.196362 2.218416 2.240470 2.262524 2.284578 2.306632 2.328686 #> [12,] 2.026276 2.045633 2.064990 2.084346 2.103703 2.123060 2.142417 2.161774 #> [13,] 2.183352 2.204454 2.225556 2.246658 2.267760 2.288862 2.309964 2.331066 #> [14,] 1.863171 1.881417 1.899664 1.917910 1.936156 1.954402 1.972648 1.990894 #> [15,] 2.120204 2.141306 2.162408 2.183510 2.204613 2.225715 2.246817 2.267919 #> [16,] 2.251735 2.273948 2.296161 2.318373 2.340586 2.362799 2.385012 2.407224 #> [17,] 2.163043 2.184621 2.206199 2.227777 2.249355 2.270933 2.292511 2.314089 #> [18,] 1.988673 2.008665 2.028656 2.048647 2.068639 2.088630 2.108622 2.128613 #> [19,] 2.172087 2.192713 2.213339 2.233965 2.254591 2.275217 2.295843 2.316469 #> [20,] 2.066100 2.086250 2.106401 2.126551 2.146701 2.166851 2.187001 2.207151 #> [21,] 2.633477 2.662036 2.690595 2.719154 2.747714 2.776273 2.804832 2.833391 #> [22,] 2.841642 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 #> [23,] 2.673301 2.702653 2.732006 2.761358 2.790711 2.820064 2.849416 2.878769 #> [24,] 2.598888 2.627765 2.656641 2.685518 2.714394 2.743271 2.772148 2.801024 #> [25,] 2.876230 2.907486 2.938743 2.969999 3.001256 3.032512 3.063769 3.095025 #> [26,] 2.876230 2.907486 2.938743 2.969999 3.001256 3.032512 3.063769 3.095025 #> [27,] 2.858936 2.890351 2.921766 2.953181 2.984596 3.016011 3.047427 3.078842 #> [28,] 2.841642 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 #> [29,] 2.755964 2.786586 2.817208 2.847829 2.878451 2.909073 2.939695 2.970317 #> [30,] 2.841642 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 #>          [,99]   [,100]   [,101]   [,102]   [,103]   [,104]   [,105]   [,106] #>  [1,] 3.149446 3.175784 3.202122 3.228460 3.254798 3.281136 3.307474 3.333812 #>  [2,] 3.288911 3.316994 3.345077 3.373160 3.401243 3.429327 3.457410 3.485493 #>  [3,] 3.180544 3.207200 3.233855 3.260510 3.287165 3.313821 3.340476 3.367131 #>  [4,] 3.148494 3.175467 3.202440 3.229412 3.256385 3.283357 3.310330 3.337303 #>  [5,] 3.070750 3.096929 3.123108 3.149288 3.175467 3.201646 3.227826 3.254005 #>  [6,] 3.382680 3.411398 3.440116 3.468834 3.497551 3.526269 3.554987 3.583705 #>  [7,] 3.398705 3.427264 3.455823 3.484383 3.512942 3.541501 3.570060 3.598619 #>  [8,] 3.227667 3.254481 3.281295 3.308109 3.334923 3.361737 3.388551 3.415364 #>  [9,] 3.009030 3.034258 3.059485 3.084712 3.109940 3.135167 3.160394 3.185621 #> [10,] 2.977457 3.002684 3.027911 3.053138 3.078366 3.103593 3.128820 3.154048 #> [11,] 2.350740 2.372795 2.394849 2.416903 2.438957 2.461011 2.483065 2.505119 #> [12,] 2.181130 2.200487 2.219844 2.239201 2.258558 2.277914 2.297271 2.316628 #> [13,] 2.352168 2.373271 2.394373 2.415475 2.436577 2.457679 2.478781 2.499883 #> [14,] 2.009141 2.027387 2.045633 2.063879 2.082125 2.100371 2.118618 2.136864 #> [15,] 2.289021 2.310123 2.331225 2.352327 2.373429 2.394531 2.415633 2.436735 #> [16,] 2.429437 2.451650 2.473862 2.496075 2.518288 2.540501 2.562713 2.584926 #> [17,] 2.335668 2.357246 2.378824 2.400402 2.421980 2.443558 2.465136 2.486714 #> [18,] 2.148605 2.168596 2.188588 2.208579 2.228571 2.248562 2.268553 2.288545 #> [19,] 2.337096 2.357722 2.378348 2.398974 2.419600 2.440226 2.460852 2.481478 #> [20,] 2.227301 2.247451 2.267601 2.287752 2.307902 2.328052 2.348202 2.368352 #> [21,] 2.861950 2.890510 2.919069 2.947628 2.976187 3.004746 3.033306 3.061865 #> [22,] 3.094232 3.125806 3.157380 3.188953 3.220527 3.252101 3.283675 3.315249 #> [23,] 2.908121 2.937474 2.966826 2.996179 3.025531 3.054884 3.084236 3.113589 #> [24,] 2.829901 2.858777 2.887654 2.916530 2.945407 2.974283 3.003160 3.032036 #> [25,] 3.126282 3.157538 3.188795 3.220051 3.251308 3.282564 3.313821 3.345077 #> [26,] 3.126282 3.157538 3.188795 3.220051 3.251308 3.282564 3.313821 3.345077 #> [27,] 3.110257 3.141672 3.173087 3.204502 3.235917 3.267333 3.298748 3.330163 #> [28,] 3.094232 3.125806 3.157380 3.188953 3.220527 3.252101 3.283675 3.315249 #> [29,] 3.000939 3.031560 3.062182 3.092804 3.123426 3.154048 3.184669 3.215291 #> [30,] 3.094232 3.125806 3.157380 3.188953 3.220527 3.252101 3.283675 3.315249 #>         [,107]   [,108]   [,109]   [,110]   [,111]   [,112]   [,113]   [,114] #>  [1,] 3.360150 3.386488 3.412826 3.439164 3.465502 3.491840 3.518178 3.544516 #>  [2,] 3.513576 3.541660 3.569743 3.597826 3.625909 3.653993 3.682076 3.710159 #>  [3,] 3.393786 3.420442 3.447097 3.473752 3.500407 3.527063 3.553718 3.580373 #>  [4,] 3.364275 3.391248 3.418220 3.445193 3.472166 3.499138 3.526111 3.553083 #>  [5,] 3.280184 3.306363 3.332543 3.358722 3.384901 3.411081 3.437260 3.463439 #>  [6,] 3.612423 3.641141 3.669859 3.698577 3.727294 3.756012 3.784730 3.813448 #>  [7,] 3.627179 3.655738 3.684297 3.712856 3.741415 3.769975 3.798534 3.827093 #>  [8,] 3.442178 3.468992 3.495806 3.522620 3.549434 3.576248 3.603062 3.629876 #>  [9,] 3.210849 3.236076 3.261303 3.286531 3.311758 3.336985 3.362213 3.387440 #> [10,] 3.179275 3.204502 3.229730 3.254957 3.280184 3.305411 3.330639 3.355866 #> [11,] 2.527173 2.549227 2.571281 2.593335 2.615389 2.637443 2.659497 2.681551 #> [12,] 2.335985 2.355342 2.374698 2.394055 2.413412 2.432769 2.452126 2.471482 #> [13,] 2.520985 2.542087 2.563189 2.584291 2.605393 2.626496 2.647598 2.668700 #> [14,] 2.155110 2.173356 2.191602 2.209848 2.228095 2.246341 2.264587 2.282833 #> [15,] 2.457838 2.478940 2.500042 2.521144 2.542246 2.563348 2.584450 2.605552 #> [16,] 2.607139 2.629351 2.651564 2.673777 2.695990 2.718202 2.740415 2.762628 #> [17,] 2.508292 2.529870 2.551448 2.573026 2.594604 2.616182 2.637761 2.659339 #> [18,] 2.308536 2.328528 2.348519 2.368511 2.388502 2.408494 2.428485 2.448476 #> [19,] 2.502104 2.522730 2.543356 2.563983 2.584609 2.605235 2.625861 2.646487 #> [20,] 2.388502 2.408652 2.428802 2.448952 2.469103 2.489253 2.509403 2.529553 #> [21,] 3.090424 3.118983 3.147542 3.176102 3.204661 3.233220 3.261779 3.290339 #> [22,] 3.346822 3.378396 3.409970 3.441544 3.473118 3.504691 3.536265 3.567839 #> [23,] 3.142941 3.172294 3.201646 3.230999 3.260351 3.289704 3.319056 3.348409 #> [24,] 3.060913 3.089789 3.118666 3.147542 3.176419 3.205296 3.234172 3.263049 #> [25,] 3.376334 3.407590 3.438846 3.470103 3.501359 3.532616 3.563872 3.595129 #> [26,] 3.376334 3.407590 3.438846 3.470103 3.501359 3.532616 3.563872 3.595129 #> [27,] 3.361578 3.392993 3.424408 3.455823 3.487238 3.518654 3.550069 3.581484 #> [28,] 3.346822 3.378396 3.409970 3.441544 3.473118 3.504691 3.536265 3.567839 #> [29,] 3.245913 3.276535 3.307157 3.337779 3.368400 3.399022 3.429644 3.460266 #> [30,] 3.346822 3.378396 3.409970 3.441544 3.473118 3.504691 3.536265 3.567839 #>         [,115]   [,116]   [,117]   [,118]   [,119]   [,120]   [,121]   [,122] #>  [1,] 3.570853 3.597191 3.623529 3.649867 3.676205 3.702543 3.728881 3.755219 #>  [2,] 3.738242 3.766325 3.794409 3.822492 3.850575 3.878658 3.906742 3.934825 #>  [3,] 3.607028 3.633684 3.660339 3.686994 3.713650 3.740305 3.766960 3.793615 #>  [4,] 3.580056 3.607028 3.634001 3.660974 3.687946 3.714919 3.741891 3.768864 #>  [5,] 3.489618 3.515798 3.541977 3.568156 3.594335 3.620515 3.646694 3.672873 #>  [6,] 3.842166 3.870884 3.899602 3.928320 3.957037 3.985755 4.014473 4.043191 #>  [7,] 3.855652 3.884211 3.912771 3.941330 3.969889 3.998448 4.027008 4.055567 #>  [8,] 3.656690 3.683504 3.710318 3.737132 3.763945 3.790759 3.817573 3.844387 #>  [9,] 3.412667 3.437894 3.463122 3.488349 3.513576 3.538804 3.564031 3.589258 #> [10,] 3.381093 3.406321 3.431548 3.456775 3.482003 3.507230 3.532457 3.557685 #> [11,] 2.703605 2.725659 2.747714 2.769768 2.791822 2.813876 2.835930 2.857984 #> [12,] 2.490839 2.510196 2.529553 2.548910 2.568266 2.587623 2.606980 2.626337 #> [13,] 2.689802 2.710904 2.732006 2.753108 2.774210 2.795312 2.816414 2.837516 #> [14,] 2.301079 2.319325 2.337572 2.355818 2.374064 2.392310 2.410556 2.428802 #> [15,] 2.626654 2.647756 2.668858 2.689960 2.711063 2.732165 2.753267 2.774369 #> [16,] 2.784840 2.807053 2.829266 2.851479 2.873691 2.895904 2.918117 2.940330 #> [17,] 2.680917 2.702495 2.724073 2.745651 2.767229 2.788807 2.810385 2.831963 #> [18,] 2.468468 2.488459 2.508451 2.528442 2.548434 2.568425 2.588417 2.608408 #> [19,] 2.667113 2.687739 2.708365 2.728991 2.749617 2.770244 2.790870 2.811496 #> [20,] 2.549703 2.569853 2.590003 2.610153 2.630303 2.650454 2.670604 2.690754 #> [21,] 3.318898 3.347457 3.376016 3.404575 3.433135 3.461694 3.490253 3.518812 #> [22,] 3.599413 3.630986 3.662560 3.694134 3.725708 3.757282 3.788855 3.820429 #> [23,] 3.377761 3.407114 3.436467 3.465819 3.495172 3.524524 3.553877 3.583229 #> [24,] 3.291925 3.320802 3.349678 3.378555 3.407431 3.436308 3.465184 3.494061 #> [25,] 3.626385 3.657642 3.688898 3.720155 3.751411 3.782668 3.813924 3.845181 #> [26,] 3.626385 3.657642 3.688898 3.720155 3.751411 3.782668 3.813924 3.845181 #> [27,] 3.612899 3.644314 3.675729 3.707144 3.738560 3.769975 3.801390 3.832805 #> [28,] 3.599413 3.630986 3.662560 3.694134 3.725708 3.757282 3.788855 3.820429 #> [29,] 3.490888 3.521510 3.552131 3.582753 3.613375 3.643997 3.674619 3.705240 #> [30,] 3.599413 3.630986 3.662560 3.694134 3.725708 3.757282 3.788855 3.820429 #>         [,123]   [,124]   [,125]   [,126]   [,127]   [,128]   [,129]   [,130] #>  [1,] 3.781557 3.807895 3.834233 3.860571 3.886909 3.913247 3.939585 3.965923 #>  [2,] 3.962908 3.990991 4.019074 4.047158 4.075241 4.103324 4.131407 4.159491 #>  [3,] 3.820271 3.846926 3.873581 3.900236 3.926892 3.953547 3.980202 4.006857 #>  [4,] 3.795837 3.822809 3.849782 3.876754 3.903727 3.930700 3.957672 3.984645 #>  [5,] 3.699053 3.725232 3.751411 3.777590 3.803770 3.829949 3.856128 3.882308 #>  [6,] 4.071909 4.100627 4.129345 4.158063 4.186780 4.215498 4.244216 4.272934 #>  [7,] 4.084126 4.112685 4.141244 4.169804 4.198363 4.226922 4.255481 4.284040 #>  [8,] 3.871201 3.898015 3.924829 3.951643 3.978457 4.005271 4.032085 4.058899 #>  [9,] 3.614486 3.639713 3.664940 3.690168 3.715395 3.740622 3.765849 3.791077 #> [10,] 3.582912 3.608139 3.633366 3.658594 3.683821 3.709048 3.734276 3.759503 #> [11,] 2.880038 2.902092 2.924146 2.946200 2.968254 2.990308 3.012362 3.034416 #> [12,] 2.645694 2.665050 2.684407 2.703764 2.723121 2.742478 2.761834 2.781191 #> [13,] 2.858618 2.879721 2.900823 2.921925 2.943027 2.964129 2.985231 3.006333 #> [14,] 2.447048 2.465295 2.483541 2.501787 2.520033 2.538279 2.556525 2.574772 #> [15,] 2.795471 2.816573 2.837675 2.858777 2.879879 2.900981 2.922083 2.943185 #> [16,] 2.962542 2.984755 3.006968 3.029180 3.051393 3.073606 3.095819 3.118031 #> [17,] 2.853541 2.875119 2.896697 2.918275 2.939854 2.961432 2.983010 3.004588 #> [18,] 2.628399 2.648391 2.668382 2.688374 2.708365 2.728357 2.748348 2.768340 #> [19,] 2.832122 2.852748 2.873374 2.894000 2.914626 2.935252 2.955878 2.976505 #> [20,] 2.710904 2.731054 2.751204 2.771354 2.791504 2.811654 2.831805 2.851955 #> [21,] 3.547371 3.575931 3.604490 3.633049 3.661608 3.690168 3.718727 3.747286 #> [22,] 3.852003 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.073020 #> [23,] 3.612582 3.641934 3.671287 3.700639 3.729992 3.759344 3.788697 3.818049 #> [24,] 3.522937 3.551814 3.580691 3.609567 3.638444 3.667320 3.696197 3.725073 #> [25,] 3.876437 3.907694 3.938950 3.970206 4.001463 4.032719 4.063976 4.095232 #> [26,] 3.876437 3.907694 3.938950 3.970206 4.001463 4.032719 4.063976 4.095232 #> [27,] 3.864220 3.895635 3.927050 3.958465 3.989881 4.021296 4.052711 4.084126 #> [28,] 3.852003 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.073020 #> [29,] 3.735862 3.766484 3.797106 3.827728 3.858350 3.888971 3.919593 3.950215 #> [30,] 3.852003 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.073020 #>         [,131]   [,132]   [,133]   [,134]   [,135]   [,136]   [,137]   [,138] #>  [1,] 3.992261 4.018598 4.044936 4.071274 4.097612 4.123950 4.150288 4.176626 #>  [2,] 4.187574 4.215657 4.243740 4.271823 4.299907 4.327990 4.356073 4.384156 #>  [3,] 4.033513 4.060168 4.086823 4.113479 4.140134 4.166789 4.193444 4.220100 #>  [4,] 4.011617 4.038590 4.065562 4.092535 4.119508 4.146480 4.173453 4.200425 #>  [5,] 3.908487 3.934666 3.960845 3.987025 4.013204 4.039383 4.065562 4.091742 #>  [6,] 4.301652 4.330370 4.359088 4.387806 4.416523 4.445241 4.473959 4.502677 #>  [7,] 4.312600 4.341159 4.369718 4.398277 4.426837 4.455396 4.483955 4.512514 #>  [8,] 4.085713 4.112527 4.139340 4.166154 4.192968 4.219782 4.246596 4.273410 #>  [9,] 3.816304 3.841531 3.866759 3.891986 3.917213 3.942441 3.967668 3.992895 #> [10,] 3.784730 3.809958 3.835185 3.860412 3.885639 3.910867 3.936094 3.961321 #> [11,] 3.056470 3.078524 3.100578 3.122633 3.144687 3.166741 3.188795 3.210849 #> [12,] 2.800548 2.819905 2.839262 2.858618 2.877975 2.897332 2.916689 2.936046 #> [13,] 3.027435 3.048537 3.069639 3.090741 3.111843 3.132946 3.154048 3.175150 #> [14,] 2.593018 2.611264 2.629510 2.647756 2.666002 2.684249 2.702495 2.720741 #> [15,] 2.964288 2.985390 3.006492 3.027594 3.048696 3.069798 3.090900 3.112002 #> [16,] 3.140244 3.162457 3.184669 3.206882 3.229095 3.251308 3.273520 3.295733 #> [17,] 3.026166 3.047744 3.069322 3.090900 3.112478 3.134056 3.155634 3.177212 #> [18,] 2.788331 2.808323 2.828314 2.848305 2.868297 2.888288 2.908280 2.928271 #> [19,] 2.997131 3.017757 3.038383 3.059009 3.079635 3.100261 3.120887 3.141513 #> [20,] 2.872105 2.892255 2.912405 2.932555 2.952705 2.972855 2.993005 3.013156 #> [21,] 3.775845 3.804404 3.832964 3.861523 3.890082 3.918641 3.947200 3.975760 #> [22,] 4.104593 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.325610 #> [23,] 3.847402 3.876754 3.906107 3.935459 3.964812 3.994164 4.023517 4.052870 #> [24,] 3.753950 3.782826 3.811703 3.840579 3.869456 3.898332 3.927209 3.956086 #> [25,] 4.126489 4.157745 4.189002 4.220258 4.251515 4.282771 4.314028 4.345284 #> [26,] 4.126489 4.157745 4.189002 4.220258 4.251515 4.282771 4.314028 4.345284 #> [27,] 4.115541 4.146956 4.178371 4.209787 4.241202 4.272617 4.304032 4.335447 #> [28,] 4.104593 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.325610 #> [29,] 3.980837 4.011459 4.042080 4.072702 4.103324 4.133946 4.164568 4.195190 #> [30,] 4.104593 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.325610 #>         [,139]   [,140]   [,141]   [,142]   [,143]   [,144]   [,145]   [,146] #>  [1,] 4.202964 4.229302 4.255640 4.281978 4.308316 4.334654 4.360992 4.387330 #>  [2,] 4.412240 4.440323 4.468406 4.496489 4.524572 4.552656 4.580739 4.608822 #>  [3,] 4.246755 4.273410 4.300065 4.326721 4.353376 4.380031 4.406686 4.433342 #>  [4,] 4.227398 4.254371 4.281343 4.308316 4.335288 4.362261 4.389234 4.416206 #>  [5,] 4.117921 4.144100 4.170280 4.196459 4.222638 4.248817 4.274997 4.301176 #>  [6,] 4.531395 4.560113 4.588831 4.617549 4.646266 4.674984 4.703702 4.732420 #>  [7,] 4.541073 4.569633 4.598192 4.626751 4.655310 4.683869 4.712429 4.740988 #>  [8,] 4.300224 4.327038 4.353852 4.380666 4.407480 4.434294 4.461108 4.487922 #>  [9,] 4.018122 4.043350 4.068577 4.093804 4.119032 4.144259 4.169486 4.194714 #> [10,] 3.986549 4.011776 4.037003 4.062231 4.087458 4.112685 4.137912 4.163140 #> [11,] 3.232903 3.254957 3.277011 3.299065 3.321119 3.343173 3.365227 3.387281 #> [12,] 2.955402 2.974759 2.994116 3.013473 3.032830 3.052186 3.071543 3.090900 #> [13,] 3.196252 3.217354 3.238456 3.259558 3.280660 3.301762 3.322864 3.343966 #> [14,] 2.738987 2.757233 2.775479 2.793726 2.811972 2.830218 2.848464 2.866710 #> [15,] 3.133104 3.154206 3.175308 3.196410 3.217513 3.238615 3.259717 3.280819 #> [16,] 3.317946 3.340159 3.362371 3.384584 3.406797 3.429009 3.451222 3.473435 #> [17,] 3.198790 3.220368 3.241947 3.263525 3.285103 3.306681 3.328259 3.349837 #> [18,] 2.948263 2.968254 2.988246 3.008237 3.028228 3.048220 3.068211 3.088203 #> [19,] 3.162139 3.182766 3.203392 3.224018 3.244644 3.265270 3.285896 3.306522 #> [20,] 3.033306 3.053456 3.073606 3.093756 3.113906 3.134056 3.154206 3.174356 #> [21,] 4.004319 4.032878 4.061437 4.089996 4.118556 4.147115 4.175674 4.204233 #> [22,] 4.357184 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.578200 #> [23,] 4.082222 4.111575 4.140927 4.170280 4.199632 4.228985 4.258337 4.287690 #> [24,] 3.984962 4.013839 4.042715 4.071592 4.100468 4.129345 4.158221 4.187098 #> [25,] 4.376541 4.407797 4.439054 4.470310 4.501566 4.532823 4.564079 4.595336 #> [26,] 4.376541 4.407797 4.439054 4.470310 4.501566 4.532823 4.564079 4.595336 #> [27,] 4.366862 4.398277 4.429692 4.461108 4.492523 4.523938 4.555353 4.586768 #> [28,] 4.357184 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.578200 #> [29,] 4.225811 4.256433 4.287055 4.317677 4.348299 4.378921 4.409542 4.440164 #> [30,] 4.357184 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.578200 #>         [,147]   [,148]   [,149]   [,150]   [,151]   [,152]   [,153]   [,154] #>  [1,] 4.413668 4.440005 4.466343 4.492681 4.519019 4.545357 4.571695 4.598033 #>  [2,] 4.636905 4.664989 4.693072 4.721155 4.749238 4.777322 4.805405 4.833488 #>  [3,] 4.459997 4.486652 4.513307 4.539963 4.566618 4.593273 4.619929 4.646584 #>  [4,] 4.443179 4.470151 4.497124 4.524097 4.551069 4.578042 4.605014 4.631987 #>  [5,] 4.327355 4.353535 4.379714 4.405893 4.432072 4.458252 4.484431 4.510610 #>  [6,] 4.761138 4.789856 4.818574 4.847292 4.876009 4.904727 4.933445 4.962163 #>  [7,] 4.769547 4.798106 4.826665 4.855225 4.883784 4.912343 4.940902 4.969462 #>  [8,] 4.514735 4.541549 4.568363 4.595177 4.621991 4.648805 4.675619 4.702433 #>  [9,] 4.219941 4.245168 4.270396 4.295623 4.320850 4.346077 4.371305 4.396532 #> [10,] 4.188367 4.213594 4.238822 4.264049 4.289276 4.314504 4.339731 4.364958 #> [11,] 3.409335 3.431389 3.453443 3.475497 3.497551 3.519606 3.541660 3.563714 #> [12,] 3.110257 3.129614 3.148970 3.168327 3.187684 3.207041 3.226398 3.245754 #> [13,] 3.365068 3.386171 3.407273 3.428375 3.449477 3.470579 3.491681 3.512783 #> [14,] 2.884956 2.903203 2.921449 2.939695 2.957941 2.976187 2.994433 3.012680 #> [15,] 3.301921 3.323023 3.344125 3.365227 3.386329 3.407431 3.428533 3.449635 #> [16,] 3.495648 3.517860 3.540073 3.562286 3.584498 3.606711 3.628924 3.651137 #> [17,] 3.371415 3.392993 3.414571 3.436149 3.457727 3.479305 3.500883 3.522461 #> [18,] 3.108194 3.128186 3.148177 3.168169 3.188160 3.208151 3.228143 3.248134 #> [19,] 3.327148 3.347774 3.368400 3.389026 3.409653 3.430279 3.450905 3.471531 #> [20,] 3.194507 3.214657 3.234807 3.254957 3.275107 3.295257 3.315407 3.335557 #> [21,] 4.232793 4.261352 4.289911 4.318470 4.347029 4.375589 4.404148 4.432707 #> [22,] 4.609774 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 #> [23,] 4.317042 4.346395 4.375747 4.405100 4.434452 4.463805 4.493157 4.522510 #> [24,] 4.215974 4.244851 4.273727 4.302604 4.331480 4.360357 4.389234 4.418110 #> [25,] 4.626592 4.657849 4.689105 4.720362 4.751618 4.782875 4.814131 4.845388 #> [26,] 4.626592 4.657849 4.689105 4.720362 4.751618 4.782875 4.814131 4.845388 #> [27,] 4.618183 4.649598 4.681014 4.712429 4.743844 4.775259 4.806674 4.838089 #> [28,] 4.609774 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 #> [29,] 4.470786 4.501408 4.532030 4.562651 4.593273 4.623895 4.654517 4.685139 #> [30,] 4.609774 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 #>         [,155]   [,156]   [,157]   [,158]   [,159]   [,160]   [,161]   [,162] #>  [1,] 4.624371 4.650709 4.677047 4.703385 4.729723 4.756061 4.782399 4.808737 #>  [2,] 4.861571 4.889654 4.917738 4.945821 4.973904 5.001987 5.030071 5.058154 #>  [3,] 4.673239 4.699894 4.726550 4.753205 4.779860 4.806515 4.833171 4.859826 #>  [4,] 4.658959 4.685932 4.712905 4.739877 4.766850 4.793822 4.820795 4.847768 #>  [5,] 4.536789 4.562969 4.589148 4.615327 4.641507 4.667686 4.693865 4.720044 #>  [6,] 4.990881 5.019599 5.048317 5.077035 5.105752 5.134470 5.163188 5.191906 #>  [7,] 4.998021 5.026580 5.055139 5.083698 5.112258 5.140817 5.169376 5.197935 #>  [8,] 4.729247 4.756061 4.782875 4.809689 4.836503 4.863316 4.890130 4.916944 #>  [9,] 4.421759 4.446987 4.472214 4.497441 4.522669 4.547896 4.573123 4.598350 #> [10,] 4.390186 4.415413 4.440640 4.465867 4.491095 4.516322 4.541549 4.566777 #> [11,] 3.585768 3.607822 3.629876 3.651930 3.673984 3.696038 3.718092 3.740146 #> [12,] 3.265111 3.284468 3.303825 3.323182 3.342538 3.361895 3.381252 3.400609 #> [13,] 3.533885 3.554987 3.576089 3.597191 3.618294 3.639396 3.660498 3.681600 #> [14,] 3.030926 3.049172 3.067418 3.085664 3.103910 3.122157 3.140403 3.158649 #> [15,] 3.470738 3.491840 3.512942 3.534044 3.555146 3.576248 3.597350 3.618452 #> [16,] 3.673349 3.695562 3.717775 3.739987 3.762200 3.784413 3.806626 3.828838 #> [17,] 3.544040 3.565618 3.587196 3.608774 3.630352 3.651930 3.673508 3.695086 #> [18,] 3.268126 3.288117 3.308109 3.328100 3.348092 3.368083 3.388075 3.408066 #> [19,] 3.492157 3.512783 3.533409 3.554035 3.574661 3.595287 3.615914 3.636540 #> [20,] 3.355707 3.375858 3.396008 3.416158 3.436308 3.456458 3.476608 3.496758 #> [21,] 4.461266 4.489825 4.518385 4.546944 4.575503 4.604062 4.632622 4.661181 #> [22,] 4.862365 4.893938 4.925512 4.957086 4.988660 5.020233 5.051807 5.083381 #> [23,] 4.551862 4.581215 4.610567 4.639920 4.669273 4.698625 4.727978 4.757330 #> [24,] 4.446987 4.475863 4.504740 4.533616 4.562493 4.591369 4.620246 4.649122 #> [25,] 4.876644 4.907901 4.939157 4.970414 5.001670 5.032926 5.064183 5.095439 #> [26,] 4.876644 4.907901 4.939157 4.970414 5.001670 5.032926 5.064183 5.095439 #> [27,] 4.869504 4.900919 4.932335 4.963750 4.995165 5.026580 5.057995 5.089410 #> [28,] 4.862365 4.893938 4.925512 4.957086 4.988660 5.020233 5.051807 5.083381 #> [29,] 4.715761 4.746382 4.777004 4.807626 4.838248 4.868870 4.899491 4.930113 #> [30,] 4.862365 4.893938 4.925512 4.957086 4.988660 5.020233 5.051807 5.083381 #>         [,163]   [,164]   [,165]   [,166]   [,167]   [,168]   [,169]   [,170] #>  [1,] 4.835075 4.861413 4.887750 4.914088 4.940426 4.966764 4.993102 5.019440 #>  [2,] 5.086237 5.114320 5.142403 5.170487 5.198570 5.226653 5.254736 5.282820 #>  [3,] 4.886481 4.913136 4.939792 4.966447 4.993102 5.019757 5.046413 5.073068 #>  [4,] 4.874740 4.901713 4.928685 4.955658 4.982631 5.009603 5.036576 5.063548 #>  [5,] 4.746224 4.772403 4.798582 4.824762 4.850941 4.877120 4.903299 4.929479 #>  [6,] 5.220624 5.249342 5.278060 5.306778 5.335495 5.364213 5.392931 5.421649 #>  [7,] 5.226494 5.255054 5.283613 5.312172 5.340731 5.369291 5.397850 5.426409 #>  [8,] 4.943758 4.970572 4.997386 5.024200 5.051014 5.077828 5.104642 5.131456 #>  [9,] 4.623578 4.648805 4.674032 4.699260 4.724487 4.749714 4.774942 4.800169 #> [10,] 4.592004 4.617231 4.642459 4.667686 4.692913 4.718140 4.743368 4.768595 #> [11,] 3.762200 3.784254 3.806308 3.828362 3.850416 3.872470 3.894525 3.916579 #> [12,] 3.419966 3.439322 3.458679 3.478036 3.497393 3.516750 3.536106 3.555463 #> [13,] 3.702702 3.723804 3.744906 3.766008 3.787110 3.808212 3.829314 3.850416 #> [14,] 3.176895 3.195141 3.213387 3.231634 3.249880 3.268126 3.286372 3.304618 #> [15,] 3.639554 3.660656 3.681758 3.702861 3.723963 3.745065 3.766167 3.787269 #> [16,] 3.851051 3.873264 3.895477 3.917689 3.939902 3.962115 3.984327 4.006540 #> [17,] 3.716664 3.738242 3.759820 3.781398 3.802976 3.824554 3.846133 3.867711 #> [18,] 3.428057 3.448049 3.468040 3.488032 3.508023 3.528015 3.548006 3.567998 #> [19,] 3.657166 3.677792 3.698418 3.719044 3.739670 3.760296 3.780922 3.801548 #> [20,] 3.516908 3.537058 3.557209 3.577359 3.597509 3.617659 3.637809 3.657959 #> [21,] 4.689740 4.718299 4.746858 4.775418 4.803977 4.832536 4.861095 4.889654 #> [22,] 5.114955 5.146529 5.178102 5.209676 5.241250 5.272824 5.304398 5.335971 #> [23,] 4.786683 4.816035 4.845388 4.874740 4.904093 4.933445 4.962798 4.992150 #> [24,] 4.677999 4.706875 4.735752 4.764629 4.793505 4.822382 4.851258 4.880135 #> [25,] 5.126696 5.157952 5.189209 5.220465 5.251722 5.282978 5.314235 5.345491 #> [26,] 5.126696 5.157952 5.189209 5.220465 5.251722 5.282978 5.314235 5.345491 #> [27,] 5.120825 5.152241 5.183656 5.215071 5.246486 5.277901 5.309316 5.340731 #> [28,] 5.114955 5.146529 5.178102 5.209676 5.241250 5.272824 5.304398 5.335971 #> [29,] 4.960735 4.991357 5.021979 5.052601 5.083222 5.113844 5.144466 5.175088 #> [30,] 5.114955 5.146529 5.178102 5.209676 5.241250 5.272824 5.304398 5.335971 #>         [,171]   [,172]   [,173]   [,174]   [,175]   [,176]   [,177]   [,178] #>  [1,] 5.045778 5.072116 5.098454 5.124792 5.151130 5.177468 5.203806 5.230144 #>  [2,] 5.310903 5.338986 5.367069 5.395152 5.423236 5.451319 5.479402 5.507485 #>  [3,] 5.099723 5.126379 5.153034 5.179689 5.206344 5.233000 5.259655 5.286310 #>  [4,] 5.090521 5.117493 5.144466 5.171439 5.198411 5.225384 5.252356 5.279329 #>  [5,] 4.955658 4.981837 5.008016 5.034196 5.060375 5.086554 5.112734 5.138913 #>  [6,] 5.450367 5.479085 5.507803 5.536521 5.565238 5.593956 5.622674 5.651392 #>  [7,] 5.454968 5.483527 5.512087 5.540646 5.569205 5.597764 5.626323 5.654883 #>  [8,] 5.158270 5.185084 5.211898 5.238711 5.265525 5.292339 5.319153 5.345967 #>  [9,] 4.825396 4.850623 4.875851 4.901078 4.926305 4.951533 4.976760 5.001987 #> [10,] 4.793822 4.819050 4.844277 4.869504 4.894732 4.919959 4.945186 4.970414 #> [11,] 3.938633 3.960687 3.982741 4.004795 4.026849 4.048903 4.070957 4.093011 #> [12,] 3.574820 3.594177 3.613534 3.632890 3.652247 3.671604 3.690961 3.710318 #> [13,] 3.871519 3.892621 3.913723 3.934825 3.955927 3.977029 3.998131 4.019233 #> [14,] 3.322864 3.341110 3.359357 3.377603 3.395849 3.414095 3.432341 3.450587 #> [15,] 3.808371 3.829473 3.850575 3.871677 3.892779 3.913881 3.934983 3.956086 #> [16,] 4.028753 4.050966 4.073178 4.095391 4.117604 4.139816 4.162029 4.184242 #> [17,] 3.889289 3.910867 3.932445 3.954023 3.975601 3.997179 4.018757 4.040335 #> [18,] 3.587989 3.607980 3.627972 3.647963 3.667955 3.687946 3.707938 3.727929 #> [19,] 3.822175 3.842801 3.863427 3.884053 3.904679 3.925305 3.945931 3.966557 #> [20,] 3.678109 3.698259 3.718409 3.738560 3.758710 3.778860 3.799010 3.819160 #> [21,] 4.918214 4.946773 4.975332 5.003891 5.032450 5.061010 5.089569 5.118128 #> [22,] 5.367545 5.399119 5.430693 5.462267 5.493840 5.525414 5.556988 5.588562 #> [23,] 5.021503 5.050855 5.080208 5.109560 5.138913 5.168265 5.197618 5.226970 #> [24,] 4.909011 4.937888 4.966764 4.995641 5.024517 5.053394 5.082270 5.111147 #> [25,] 5.376748 5.408004 5.439261 5.470517 5.501774 5.533030 5.564286 5.595543 #> [26,] 5.376748 5.408004 5.439261 5.470517 5.501774 5.533030 5.564286 5.595543 #> [27,] 5.372146 5.403562 5.434977 5.466392 5.497807 5.529222 5.560637 5.592052 #> [28,] 5.367545 5.399119 5.430693 5.462267 5.493840 5.525414 5.556988 5.588562 #> [29,] 5.205710 5.236332 5.266953 5.297575 5.328197 5.358819 5.389441 5.420062 #> [30,] 5.367545 5.399119 5.430693 5.462267 5.493840 5.525414 5.556988 5.588562 #>         [,179]   [,180]   [,181]   [,182]   [,183]   [,184]   [,185]   [,186] #>  [1,] 5.256482 5.282820 5.309158 5.335495 5.361833 5.388171 5.414509 5.440847 #>  [2,] 5.535569 5.563652 5.591735 5.619818 5.647902 5.675985 5.704068 5.732151 #>  [3,] 5.312965 5.339621 5.366276 5.392931 5.419586 5.446242 5.472897 5.499552 #>  [4,] 5.306302 5.333274 5.360247 5.387219 5.414192 5.441165 5.468137 5.495110 #>  [5,] 5.165092 5.191271 5.217451 5.243630 5.269809 5.295989 5.322168 5.348347 #>  [6,] 5.680110 5.708828 5.737546 5.766264 5.794981 5.823699 5.852417 5.881135 #>  [7,] 5.683442 5.712001 5.740560 5.769119 5.797679 5.826238 5.854797 5.883356 #>  [8,] 5.372781 5.399595 5.426409 5.453223 5.480037 5.506851 5.533665 5.560479 #>  [9,] 5.027215 5.052442 5.077669 5.102897 5.128124 5.153351 5.178578 5.203806 #> [10,] 4.995641 5.020868 5.046095 5.071323 5.096550 5.121777 5.147005 5.172232 #> [11,] 4.115065 4.137119 4.159173 4.181227 4.203281 4.225335 4.247389 4.269444 #> [12,] 3.729674 3.749031 3.768388 3.787745 3.807102 3.826458 3.845815 3.865172 #> [13,] 4.040335 4.061437 4.082539 4.103641 4.124744 4.145846 4.166948 4.188050 #> [14,] 3.468834 3.487080 3.505326 3.523572 3.541818 3.560064 3.578311 3.596557 #> [15,] 3.977188 3.998290 4.019392 4.040494 4.061596 4.082698 4.103800 4.124902 #> [16,] 4.206455 4.228667 4.250880 4.273093 4.295305 4.317518 4.339731 4.361944 #> [17,] 4.061913 4.083491 4.105069 4.126647 4.148226 4.169804 4.191382 4.212960 #> [18,] 3.747921 3.767912 3.787903 3.807895 3.827886 3.847878 3.867869 3.887861 #> [19,] 3.987183 4.007809 4.028436 4.049062 4.069688 4.090314 4.110940 4.131566 #> [20,] 3.839310 3.859460 3.879610 3.899760 3.919911 3.940061 3.960211 3.980361 #> [21,] 5.146687 5.175247 5.203806 5.232365 5.260924 5.289483 5.318043 5.346602 #> [22,] 5.620136 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 #> [23,] 5.256323 5.285675 5.315028 5.344381 5.373733 5.403086 5.432438 5.461791 #> [24,] 5.140024 5.168900 5.197777 5.226653 5.255530 5.284406 5.313283 5.342159 #> [25,] 5.626799 5.658056 5.689312 5.720569 5.751825 5.783082 5.814338 5.845595 #> [26,] 5.626799 5.658056 5.689312 5.720569 5.751825 5.783082 5.814338 5.845595 #> [27,] 5.623468 5.654883 5.686298 5.717713 5.749128 5.780543 5.811958 5.843373 #> [28,] 5.620136 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 #> [29,] 5.450684 5.481306 5.511928 5.542550 5.573172 5.603793 5.634415 5.665037 #> [30,] 5.620136 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 #>         [,187]   [,188]   [,189]   [,190]   [,191]   [,192]   [,193]   [,194] #>  [1,] 5.467185 5.493523 5.519861 5.546199 5.572537 5.598875 5.625213 5.651551 #>  [2,] 5.760234 5.788318 5.816401 5.844484 5.872567 5.900651 5.928734 5.956817 #>  [3,] 5.526208 5.552863 5.579518 5.606173 5.632829 5.659484 5.686139 5.712794 #>  [4,] 5.522082 5.549055 5.576027 5.603000 5.629973 5.656945 5.683918 5.710890 #>  [5,] 5.374526 5.400706 5.426885 5.453064 5.479243 5.505423 5.531602 5.557781 #>  [6,] 5.909853 5.938571 5.967289 5.996007 6.024724 6.053442 6.082160 6.110878 #>  [7,] 5.911916 5.940475 5.969034 5.997593 6.026152 6.054712 6.083271 6.111830 #>  [8,] 5.587293 5.614106 5.640920 5.667734 5.694548 5.721362 5.748176 5.774990 #>  [9,] 5.229033 5.254260 5.279488 5.304715 5.329942 5.355170 5.380397 5.405624 #> [10,] 5.197459 5.222687 5.247914 5.273141 5.298368 5.323596 5.348823 5.374050 #> [11,] 4.291498 4.313552 4.335606 4.357660 4.379714 4.401768 4.423822 4.445876 #> [12,] 3.884529 3.903886 3.923242 3.942599 3.961956 3.981313 4.000670 4.020026 #> [13,] 4.209152 4.230254 4.251356 4.272458 4.293560 4.314662 4.335764 4.356866 #> [14,] 3.614803 3.633049 3.651295 3.669541 3.687788 3.706034 3.724280 3.742526 #> [15,] 4.146004 4.167106 4.188208 4.209311 4.230413 4.251515 4.272617 4.293719 #> [16,] 4.384156 4.406369 4.428582 4.450795 4.473007 4.495220 4.517433 4.539645 #> [17,] 4.234538 4.256116 4.277694 4.299272 4.320850 4.342428 4.364006 4.385584 #> [18,] 3.907852 3.927844 3.947835 3.967827 3.987818 4.007809 4.027801 4.047792 #> [19,] 4.152192 4.172818 4.193444 4.214070 4.234696 4.255323 4.275949 4.296575 #> [20,] 4.000511 4.020661 4.040811 4.060961 4.081111 4.101262 4.121412 4.141562 #> [21,] 5.375161 5.403720 5.432279 5.460839 5.489398 5.517957 5.546516 5.575076 #> [22,] 5.872726 5.904300 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 #> [23,] 5.491143 5.520496 5.549848 5.579201 5.608553 5.637906 5.667258 5.696611 #> [24,] 5.371036 5.399912 5.428789 5.457665 5.486542 5.515418 5.544295 5.573172 #> [25,] 5.876851 5.908108 5.939364 5.970621 6.001877 6.033134 6.064390 6.095646 #> [26,] 5.876851 5.908108 5.939364 5.970621 6.001877 6.033134 6.064390 6.095646 #> [27,] 5.874789 5.906204 5.937619 5.969034 6.000449 6.031864 6.063279 6.094695 #> [28,] 5.872726 5.904300 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 #> [29,] 5.695659 5.726281 5.756902 5.787524 5.818146 5.848768 5.879390 5.910012 #> [30,] 5.872726 5.904300 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 #>         [,195]   [,196]   [,197]   [,198]   [,199]   [,200] #>  [1,] 5.677889 5.704227 5.730565 5.756902 5.783240 5.809578 #>  [2,] 5.984900 6.012983 6.041067 6.069150 6.097233 6.125316 #>  [3,] 5.739450 5.766105 5.792760 5.819415 5.846071 5.872726 #>  [4,] 5.737863 5.764836 5.791808 5.818781 5.845753 5.872726 #>  [5,] 5.583961 5.610140 5.636319 5.662498 5.688678 5.714857 #>  [6,] 6.139596 6.168314 6.197032 6.225750 6.254467 6.283185 #>  [7,] 6.140389 6.168948 6.197508 6.226067 6.254626 6.283185 #>  [8,] 5.801804 5.828618 5.855432 5.882246 5.909060 5.935874 #>  [9,] 5.430851 5.456079 5.481306 5.506533 5.531761 5.556988 #> [10,] 5.399278 5.424505 5.449732 5.474960 5.500187 5.525414 #> [11,] 4.467930 4.489984 4.512038 4.534092 4.556146 4.578200 #> [12,] 4.039383 4.058740 4.078097 4.097454 4.116810 4.136167 #> [13,] 4.377969 4.399071 4.420173 4.441275 4.462377 4.483479 #> [14,] 3.760772 3.779018 3.797265 3.815511 3.833757 3.852003 #> [15,] 4.314821 4.335923 4.357025 4.378127 4.399229 4.420331 #> [16,] 4.561858 4.584071 4.606284 4.628496 4.650709 4.672922 #> [17,] 4.407162 4.428740 4.450319 4.471897 4.493475 4.515053 #> [18,] 4.067784 4.087775 4.107767 4.127758 4.147750 4.167741 #> [19,] 4.317201 4.337827 4.358453 4.379079 4.399705 4.420331 #> [20,] 4.161712 4.181862 4.202012 4.222162 4.242312 4.262462 #> [21,] 5.603635 5.632194 5.660753 5.689312 5.717872 5.746431 #> [22,] 6.125316 6.156890 6.188464 6.220038 6.251612 6.283185 #> [23,] 5.725963 5.755316 5.784668 5.814021 5.843373 5.872726 #> [24,] 5.602048 5.630925 5.659801 5.688678 5.717554 5.746431 #> [25,] 6.126903 6.158159 6.189416 6.220672 6.251929 6.283185 #> [26,] 6.126903 6.158159 6.189416 6.220672 6.251929 6.283185 #> [27,] 6.126110 6.157525 6.188940 6.220355 6.251770 6.283185 #> [28,] 6.125316 6.156890 6.188464 6.220038 6.251612 6.283185 #> [29,] 5.940633 5.971255 6.001877 6.032499 6.063121 6.093743 #> [30,] 6.125316 6.156890 6.188464 6.220038 6.251612 6.283185 #>  #> $center_curves #> , , 1 #>  #>            [,1] #> [1,] 0.06497012 #> [2,] 0.13511093 #>  #> , , 2 #>  #>            [,1] #> [1,] 0.08452816 #> [2,] 0.19134922 #>  #> , , 3 #>  #>           [,1] #> [1,] 0.1041682 #> [2,] 0.2471764 #>  #> , , 4 #>  #>           [,1] #> [1,] 0.1238844 #> [2,] 0.3025496 #>  #> , , 5 #>  #>           [,1] #> [1,] 0.1436761 #> [2,] 0.3574285 #>  #> , , 6 #>  #>           [,1] #> [1,] 0.1635299 #> [2,] 0.4117503 #>  #> , , 7 #>  #>           [,1] #> [1,] 0.1834412 #> [2,] 0.4654860 #>  #> , , 8 #>  #>           [,1] #> [1,] 0.2034034 #> [2,] 0.5185908 #>  #> , , 9 #>  #>           [,1] #> [1,] 0.2234078 #> [2,] 0.5709993 #>  #> , , 10 #>  #>           [,1] #> [1,] 0.2434509 #> [2,] 0.6226754 #>  #> , , 11 #>  #>           [,1] #> [1,] 0.2635227 #> [2,] 0.6735849 #>  #> , , 12 #>  #>           [,1] #> [1,] 0.2836163 #> [2,] 0.7236903 #>  #> , , 13 #>  #>           [,1] #> [1,] 0.3037275 #> [2,] 0.7729353 #>  #> , , 14 #>  #>           [,1] #> [1,] 0.3238472 #> [2,] 0.8212877 #>  #> , , 15 #>  #>           [,1] #> [1,] 0.3439693 #> [2,] 0.8687042 #>  #> , , 16 #>  #>           [,1] #> [1,] 0.3640873 #> [2,] 0.9151381 #>  #> , , 17 #>  #>           [,1] #> [1,] 0.3841945 #> [2,] 0.9605241 #>  #> , , 18 #>  #>           [,1] #> [1,] 0.4042832 #> [2,] 1.0048502 #>  #> , , 19 #>  #>           [,1] #> [1,] 0.4243475 #> [2,] 1.0480663 #>  #> , , 20 #>  #>           [,1] #> [1,] 0.4443828 #> [2,] 1.0901378 #>  #> , , 21 #>  #>           [,1] #> [1,] 0.4643802 #> [2,] 1.1310452 #>  #> , , 22 #>  #>           [,1] #> [1,] 0.4843323 #> [2,] 1.1707513 #>  #> , , 23 #>  #>           [,1] #> [1,] 0.5042363 #> [2,] 1.2091870 #>  #> , , 24 #>  #>           [,1] #> [1,] 0.5240825 #> [2,] 1.2463368 #>  #> , , 25 #>  #>           [,1] #> [1,] 0.5438682 #> [2,] 1.2821544 #>  #> , , 26 #>  #>           [,1] #> [1,] 0.5635812 #> [2,] 1.3166148 #>  #> , , 27 #>  #>           [,1] #> [1,] 0.5832195 #> [2,] 1.3496740 #>  #> , , 28 #>  #>           [,1] #> [1,] 0.6027814 #> [2,] 1.3813227 #>  #> , , 29 #>  #>           [,1] #> [1,] 0.6222499 #> [2,] 1.4115406 #>  #> , , 30 #>  #>           [,1] #> [1,] 0.6416345 #> [2,] 1.4402755 #>  #> , , 31 #>  #>           [,1] #> [1,] 0.6609064 #> [2,] 1.4674947 #>  #> , , 32 #>  #>           [,1] #> [1,] 0.6800816 #> [2,] 1.4931778 #>  #> , , 33 #>  #>           [,1] #> [1,] 0.6991477 #> [2,] 1.5172787 #>  #> , , 34 #>  #>           [,1] #> [1,] 0.7180897 #> [2,] 1.5397811 #>  #> , , 35 #>  #>          [,1] #> [1,] 0.736920 #> [2,] 1.560688 #>  #> , , 36 #>  #>           [,1] #> [1,] 0.7556113 #> [2,] 1.5799632 #>  #> , , 37 #>  #>           [,1] #> [1,] 0.7741729 #> [2,] 1.5975766 #>  #> , , 38 #>  #>           [,1] #> [1,] 0.7925999 #> [2,] 1.6135375 #>  #> , , 39 #>  #>           [,1] #> [1,] 0.8108833 #> [2,] 1.6278311 #>  #> , , 40 #>  #>          [,1] #> [1,] 0.829014 #> [2,] 1.640384 #>  #> , , 41 #>  #>           [,1] #> [1,] 0.8469876 #> [2,] 1.6512040 #>  #> , , 42 #>  #>           [,1] #> [1,] 0.8648055 #> [2,] 1.6602843 #>  #> , , 43 #>  #>           [,1] #> [1,] 0.8824561 #> [2,] 1.6676363 #>  #> , , 44 #>  #>           [,1] #> [1,] 0.8999453 #> [2,] 1.6731948 #>  #> , , 45 #>  #>           [,1] #> [1,] 0.9172451 #> [2,] 1.6769856 #>  #> , , 46 #>  #>           [,1] #> [1,] 0.9343774 #> [2,] 1.6790216 #>  #> , , 47 #>  #>           [,1] #> [1,] 0.9513252 #> [2,] 1.6792680 #>  #> , , 48 #>  #>           [,1] #> [1,] 0.9680756 #> [2,] 1.6777185 #>  #> , , 49 #>  #>           [,1] #> [1,] 0.9846444 #> [2,] 1.6743657 #>  #> , , 50 #>  #>          [,1] #> [1,] 1.001008 #> [2,] 1.669210 #>  #> , , 51 #>  #>          [,1] #> [1,] 1.017173 #> [2,] 1.662248 #>  #> , , 52 #>  #>          [,1] #> [1,] 1.033127 #> [2,] 1.653509 #>  #> , , 53 #>  #>          [,1] #> [1,] 1.048868 #> [2,] 1.642980 #>  #> , , 54 #>  #>          [,1] #> [1,] 1.064398 #> [2,] 1.630653 #>  #> , , 55 #>  #>          [,1] #> [1,] 1.079722 #> [2,] 1.616568 #>  #> , , 56 #>  #>          [,1] #> [1,] 1.094805 #> [2,] 1.600722 #>  #> , , 57 #>  #>          [,1] #> [1,] 1.109666 #> [2,] 1.583079 #>  #> , , 58 #>  #>          [,1] #> [1,] 1.124296 #> [2,] 1.563654 #>  #> , , 59 #>  #>          [,1] #> [1,] 1.138694 #> [2,] 1.542498 #>  #> , , 60 #>  #>          [,1] #> [1,] 1.152860 #> [2,] 1.519636 #>  #> , , 61 #>  #>          [,1] #> [1,] 1.166769 #> [2,] 1.495037 #>  #> , , 62 #>  #>          [,1] #> [1,] 1.180447 #> [2,] 1.468763 #>  #> , , 63 #>  #>          [,1] #> [1,] 1.193864 #> [2,] 1.440839 #>  #> , , 64 #>  #>          [,1] #> [1,] 1.207038 #> [2,] 1.411264 #>  #> , , 65 #>  #>          [,1] #> [1,] 1.219959 #> [2,] 1.380032 #>  #> , , 66 #>  #>          [,1] #> [1,] 1.232613 #> [2,] 1.347199 #>  #> , , 67 #>  #>          [,1] #> [1,] 1.245021 #> [2,] 1.312787 #>  #> , , 68 #>  #>          [,1] #> [1,] 1.257141 #> [2,] 1.276825 #>  #> , , 69 #>  #>          [,1] #> [1,] 1.269012 #> [2,] 1.239357 #>  #> , , 70 #>  #>          [,1] #> [1,] 1.280612 #> [2,] 1.200405 #>  #> , , 71 #>  #>          [,1] #> [1,] 1.291930 #> [2,] 1.159998 #>  #> , , 72 #>  #>          [,1] #> [1,] 1.302973 #> [2,] 1.118161 #>  #> , , 73 #>  #>          [,1] #> [1,] 1.313743 #> [2,] 1.074941 #>  #> , , 74 #>  #>          [,1] #> [1,] 1.324231 #> [2,] 1.030361 #>  #> , , 75 #>  #>           [,1] #> [1,] 1.3344394 #> [2,] 0.9844585 #>  #> , , 76 #>  #>           [,1] #> [1,] 1.3443652 #> [2,] 0.9373073 #>  #> , , 77 #>  #>           [,1] #> [1,] 1.3539729 #> [2,] 0.8889499 #>  #> , , 78 #>  #>           [,1] #> [1,] 1.3633333 #> [2,] 0.8393976 #>  #> , , 79 #>  #>           [,1] #> [1,] 1.3723702 #> [2,] 0.7887181 #>  #> , , 80 #>  #>           [,1] #> [1,] 1.3811158 #> [2,] 0.7369613 #>  #> , , 81 #>  #>           [,1] #> [1,] 1.3895872 #> [2,] 0.6841574 #>  #> , , 82 #>  #>           [,1] #> [1,] 1.3977255 #> [2,] 0.6303596 #>  #> , , 83 #>  #>           [,1] #> [1,] 1.4056039 #> [2,] 0.5756207 #>  #> , , 84 #>  #>           [,1] #> [1,] 1.4131425 #> [2,] 0.5200089 #>  #> , , 85 #>  #>           [,1] #> [1,] 1.4203824 #> [2,] 0.4635605 #>  #> , , 86 #>  #>           [,1] #> [1,] 1.4273308 #> [2,] 0.4063395 #>  #> , , 87 #>  #>           [,1] #> [1,] 1.4339644 #> [2,] 0.3484031 #>  #> , , 88 #>  #>           [,1] #> [1,] 1.4402976 #> [2,] 0.2898029 #>  #> , , 89 #>  #>           [,1] #> [1,] 1.4462995 #> [2,] 0.2305995 #>  #> , , 90 #>  #>           [,1] #> [1,] 1.4520016 #> [2,] 0.1708606 #>  #> , , 91 #>  #>           [,1] #> [1,] 1.4573751 #> [2,] 0.1106363 #>  #> , , 92 #>  #>            [,1] #> [1,] 1.46245162 #> [2,] 0.04998966 #>  #> , , 93 #>  #>             [,1] #> [1,]  1.46720310 #> [2,] -0.01100713 #>  #> , , 94 #>  #>             [,1] #> [1,]  1.47163346 #> [2,] -0.07229319 #>  #> , , 95 #>  #>            [,1] #> [1,]  1.4757436 #> [2,] -0.1338116 #>  #> , , 96 #>  #>            [,1] #> [1,]  1.4795285 #> [2,] -0.1954921 #>  #> , , 97 #>  #>            [,1] #> [1,]  1.4830055 #> [2,] -0.2572697 #>  #> , , 98 #>  #>            [,1] #> [1,]  1.4861416 #> [2,] -0.3190785 #>  #> , , 99 #>  #>            [,1] #> [1,]  1.4889695 #> [2,] -0.3808491 #>  #> , , 100 #>  #>            [,1] #> [1,]  1.4914450 #> [2,] -0.4425126 #>  #> , , 101 #>  #>            [,1] #> [1,]  1.4936164 #> [2,] -0.5040048 #>  #> , , 102 #>  #>            [,1] #> [1,]  1.4954520 #> [2,] -0.5652545 #>  #> , , 103 #>  #>            [,1] #> [1,]  1.4969476 #> [2,] -0.6261964 #>  #> , , 104 #>  #>            [,1] #> [1,]  1.4981354 #> [2,] -0.6867597 #>  #> , , 105 #>  #>            [,1] #> [1,]  1.4989764 #> [2,] -0.7468755 #>  #> , , 106 #>  #>            [,1] #> [1,]  1.4994862 #> [2,] -0.8064741 #>  #> , , 107 #>  #>            [,1] #> [1,]  1.4996647 #> [2,] -0.8654928 #>  #> , , 108 #>  #>            [,1] #> [1,]  1.4995005 #> [2,] -0.9238479 #>  #> , , 109 #>  #>            [,1] #> [1,]  1.4990063 #> [2,] -0.9814771 #>  #> , , 110 #>  #>           [,1] #> [1,]  1.498189 #> [2,] -1.038326 #>  #> , , 111 #>  #>           [,1] #> [1,]  1.497004 #> [2,] -1.094331 #>  #> , , 112 #>  #>           [,1] #> [1,]  1.495502 #> [2,] -1.149396 #>  #> , , 113 #>  #>           [,1] #> [1,]  1.493671 #> [2,] -1.203453 #>  #> , , 114 #>  #>           [,1] #> [1,]  1.491470 #> [2,] -1.256467 #>  #> , , 115 #>  #>           [,1] #> [1,]  1.488972 #> [2,] -1.308368 #>  #> , , 116 #>  #>           [,1] #> [1,]  1.486082 #> [2,] -1.359048 #>  #> , , 117 #>  #>           [,1] #> [1,]  1.482876 #> [2,] -1.408487 #>  #> , , 118 #>  #>           [,1] #> [1,]  1.479328 #> [2,] -1.456633 #>  #> , , 119 #>  #>           [,1] #> [1,]  1.475425 #> [2,] -1.503413 #>  #> , , 120 #>  #>           [,1] #> [1,]  1.471199 #> [2,] -1.548749 #>  #> , , 121 #>  #>           [,1] #> [1,]  1.466608 #> [2,] -1.592590 #>  #> , , 122 #>  #>           [,1] #> [1,]  1.461671 #> [2,] -1.634894 #>  #> , , 123 #>  #>           [,1] #> [1,]  1.456388 #> [2,] -1.675604 #>  #> , , 124 #>  #>           [,1] #> [1,]  1.450778 #> [2,] -1.714660 #>  #> , , 125 #>  #>           [,1] #> [1,]  1.444793 #> [2,] -1.752009 #>  #> , , 126 #>  #>           [,1] #> [1,]  1.438469 #> [2,] -1.787594 #>  #> , , 127 #>  #>           [,1] #> [1,]  1.431793 #> [2,] -1.821392 #>  #> , , 128 #>  #>           [,1] #> [1,]  1.424767 #> [2,] -1.853363 #>  #> , , 129 #>  #>           [,1] #> [1,]  1.417404 #> [2,] -1.883406 #>  #> , , 130 #>  #>           [,1] #> [1,]  1.409660 #> [2,] -1.911534 #>  #> , , 131 #>  #>           [,1] #> [1,]  1.401583 #> [2,] -1.937729 #>  #> , , 132 #>  #>           [,1] #> [1,]  1.393138 #> [2,] -1.961943 #>  #> , , 133 #>  #>           [,1] #> [1,]  1.384366 #> [2,] -1.984085 #>  #> , , 134 #>  #>           [,1] #> [1,]  1.375228 #> [2,] -2.004183 #>  #> , , 135 #>  #>           [,1] #> [1,]  1.365705 #> [2,] -2.022229 #>  #> , , 136 #>  #>           [,1] #> [1,]  1.355866 #> [2,] -2.038159 #>  #> , , 137 #>  #>           [,1] #> [1,]  1.345631 #> [2,] -2.051943 #>  #> , , 138 #>  #>           [,1] #> [1,]  1.335078 #> [2,] -2.063601 #>  #> , , 139 #>  #>           [,1] #> [1,]  1.324142 #> [2,] -2.073130 #>  #> , , 140 #>  #>           [,1] #> [1,]  1.312840 #> [2,] -2.080469 #>  #> , , 141 #>  #>           [,1] #> [1,]  1.301214 #> [2,] -2.085624 #>  #> , , 142 #>  #>           [,1] #> [1,]  1.289193 #> [2,] -2.088614 #>  #> , , 143 #>  #>           [,1] #> [1,]  1.276819 #> [2,] -2.089427 #>  #> , , 144 #>  #>           [,1] #> [1,]  1.264094 #> [2,] -2.088085 #>  #> , , 145 #>  #>           [,1] #> [1,]  1.250982 #> [2,] -2.084591 #>  #> , , 146 #>  #>           [,1] #> [1,]  1.237540 #> [2,] -2.078949 #>  #> , , 147 #>  #>           [,1] #> [1,]  1.223721 #> [2,] -2.071166 #>  #> , , 148 #>  #>           [,1] #> [1,]  1.209518 #> [2,] -2.061302 #>  #> , , 149 #>  #>          [,1] #> [1,]  1.19498 #> [2,] -2.04935 #>  #> , , 150 #>  #>           [,1] #> [1,]  1.180067 #> [2,] -2.035299 #>  #> , , 151 #>  #>           [,1] #> [1,]  1.164781 #> [2,] -2.019243 #>  #> , , 152 #>  #>          [,1] #> [1,]  1.14914 #> [2,] -2.00121 #>  #> , , 153 #>  #>           [,1] #> [1,]  1.133126 #> [2,] -1.981209 #>  #> , , 154 #>  #>           [,1] #> [1,]  1.116759 #> [2,] -1.959271 #>  #> , , 155 #>  #>           [,1] #> [1,]  1.100005 #> [2,] -1.935485 #>  #> , , 156 #>  #>           [,1] #> [1,]  1.082898 #> [2,] -1.909903 #>  #> , , 157 #>  #>           [,1] #> [1,]  1.065420 #> [2,] -1.882534 #>  #> , , 158 #>  #>           [,1] #> [1,]  1.047582 #> [2,] -1.853471 #>  #> , , 159 #>  #>           [,1] #> [1,]  1.029380 #> [2,] -1.822774 #>  #> , , 160 #>  #>           [,1] #> [1,]  1.010790 #> [2,] -1.790504 #>  #> , , 161 #>  #>            [,1] #> [1,]  0.9918585 #> [2,] -1.7567114 #>  #> , , 162 #>  #>            [,1] #> [1,]  0.9725529 #> [2,] -1.7215002 #>  #> , , 163 #>  #>           [,1] #> [1,]  0.952877 #> [2,] -1.684921 #>  #> , , 164 #>  #>            [,1] #> [1,]  0.9328483 #> [2,] -1.6470586 #>  #> , , 165 #>  #>            [,1] #> [1,]  0.9124405 #> [2,] -1.6080013 #>  #> , , 166 #>  #>            [,1] #> [1,]  0.8916736 #> [2,] -1.5678274 #>  #> , , 167 #>  #>            [,1] #> [1,]  0.8705646 #> [2,] -1.5266050 #>  #> , , 168 #>  #>            [,1] #> [1,]  0.8490532 #> [2,] -1.4844341 #>  #> , , 169 #>  #>            [,1] #> [1,]  0.8272091 #> [2,] -1.4414137 #>  #> , , 170 #>  #>            [,1] #> [1,]  0.8050175 #> [2,] -1.3976363 #>  #> , , 171 #>  #>            [,1] #> [1,]  0.7824332 #> [2,] -1.3531879 #>  #> , , 172 #>  #>            [,1] #> [1,]  0.7595275 #> [2,] -1.3081750 #>  #> , , 173 #>  #>           [,1] #> [1,]  0.736247 #> [2,] -1.262692 #>  #> , , 174 #>  #>            [,1] #> [1,]  0.7126106 #> [2,] -1.2168302 #>  #> , , 175 #>  #>            [,1] #> [1,]  0.6886412 #> [2,] -1.1706920 #>  #> , , 176 #>  #>            [,1] #> [1,]  0.6642918 #> [2,] -1.1243772 #>  #> , , 177 #>  #>            [,1] #> [1,]  0.6396302 #> [2,] -1.0779855 #>  #> , , 178 #>  #>            [,1] #> [1,]  0.6146129 #> [2,] -1.0316187 #>  #> , , 179 #>  #>            [,1] #> [1,]  0.5892528 #> [2,] -0.9853738 #>  #> , , 180 #>  #>            [,1] #> [1,]  0.5635611 #> [2,] -0.9393516 #>  #> , , 181 #>  #>            [,1] #> [1,]  0.5375240 #> [2,] -0.8936506 #>  #> , , 182 #>  #>            [,1] #> [1,]  0.5111707 #> [2,] -0.8483713 #>  #> , , 183 #>  #>            [,1] #> [1,]  0.4844698 #> [2,] -0.8035977 #>  #> , , 184 #>  #>            [,1] #> [1,]  0.4574575 #> [2,] -0.7594433 #>  #> , , 185 #>  #>            [,1] #> [1,]  0.4301303 #> [2,] -0.7159905 #>  #> , , 186 #>  #>            [,1] #> [1,]  0.4024745 #> [2,] -0.6733142 #>  #> , , 187 #>  #>            [,1] #> [1,]  0.3745374 #> [2,] -0.6314963 #>  #> , , 188 #>  #>            [,1] #> [1,]  0.3462629 #> [2,] -0.5906449 #>  #> , , 189 #>  #>            [,1] #> [1,]  0.3176950 #> [2,] -0.5508186 #>  #> , , 190 #>  #>            [,1] #> [1,]  0.2888553 #> [2,] -0.5120953 #>  #> , , 191 #>  #>            [,1] #> [1,]  0.2596925 #> [2,] -0.4745579 #>  #> , , 192 #>  #>            [,1] #> [1,]  0.2302770 #> [2,] -0.4382669 #>  #> , , 193 #>  #>            [,1] #> [1,]  0.2005802 #> [2,] -0.4032874 #>  #> , , 194 #>  #>            [,1] #> [1,]  0.1705978 #> [2,] -0.3696600 #>  #> , , 195 #>  #>            [,1] #> [1,]  0.1403705 #> [2,] -0.3374500 #>  #> , , 196 #>  #>            [,1] #> [1,]  0.1098806 #> [2,] -0.3066814 #>  #> , , 197 #>  #>             [,1] #> [1,]  0.07915083 #> [2,] -0.27740306 #>  #> , , 198 #>  #>             [,1] #> [1,]  0.04818582 #> [2,] -0.24966979 #>  #> , , 199 #>  #>             [,1] #> [1,]  0.01697984 #> [2,] -0.22347604 #>  #> , , 200 #>  #>             [,1] #> [1,] -0.01444034 #> [2,] -0.19883855 #>  #>  #> $center_grids #>            [,1]       [,2]      [,3]      [,4]      [,5]      [,6]      [,7] #> [1,] 0.58175701 0.59824927 0.6147415 0.6312338 0.6477261 0.6642183 0.6807106 #> [2,] 0.05517908 0.08381685 0.1124546 0.1410924 0.1697302 0.1983679 0.2270057 #>           [,8]      [,9]     [,10]     [,11]     [,12]     [,13]     [,14] #> [1,] 0.6972028 0.7136951 0.7301874 0.7466796 0.7631719 0.7796642 0.7961564 #> [2,] 0.2556435 0.2842813 0.3129190 0.3415568 0.3701946 0.3988323 0.4274701 #>          [,15]     [,16]     [,17]     [,18]     [,19]     [,20]     [,21] #> [1,] 0.8126487 0.8291410 0.8456332 0.8621255 0.8786177 0.8951100 0.9116023 #> [2,] 0.4561079 0.4847457 0.5133834 0.5420212 0.5706590 0.5992968 0.6279345 #>          [,22]     [,23]     [,24]     [,25]     [,26]     [,27]     [,28] #> [1,] 0.9280945 0.9445868 0.9610791 0.9775713 0.9940636 1.0105558 1.0270481 #> [2,] 0.6565723 0.6852101 0.7138479 0.7424856 0.7711234 0.7997612 0.8283989 #>          [,29]     [,30]     [,31]    [,32]     [,33]    [,34]    [,35] #> [1,] 1.0435404 1.0600326 1.0765249 1.093017 1.1095094 1.126002 1.142494 #> [2,] 0.8570367 0.8856745 0.9143123 0.942950 0.9715878 1.000226 1.028863 #>         [,36]    [,37]    [,38]    [,39]    [,40]    [,41]    [,42]    [,43] #> [1,] 1.158986 1.175478 1.191971 1.208463 1.224955 1.241448 1.257940 1.274432 #> [2,] 1.057501 1.086139 1.114777 1.143414 1.172052 1.200690 1.229328 1.257966 #>         [,44]    [,45]    [,46]    [,47]    [,48]    [,49]    [,50]    [,51] #> [1,] 1.290924 1.307417 1.323909 1.340401 1.356893 1.373386 1.389878 1.406370 #> [2,] 1.286603 1.315241 1.343879 1.372517 1.401154 1.429792 1.458430 1.487068 #>         [,52]    [,53]    [,54]    [,55]    [,56]    [,57]    [,58]    [,59] #> [1,] 1.422862 1.439355 1.455847 1.472339 1.488831 1.505324 1.521816 1.538308 #> [2,] 1.515705 1.544343 1.572981 1.601619 1.630257 1.658894 1.687532 1.716170 #>         [,60]    [,61]    [,62]    [,63]    [,64]    [,65]    [,66]    [,67] #> [1,] 1.554801 1.571293 1.587785 1.604277 1.620770 1.637262 1.653754 1.670246 #> [2,] 1.744808 1.773445 1.802083 1.830721 1.859359 1.887997 1.916634 1.945272 #>         [,68]    [,69]    [,70]    [,71]    [,72]    [,73]    [,74]    [,75] #> [1,] 1.686739 1.703231 1.719723 1.736215 1.752708 1.769200 1.785692 1.802184 #> [2,] 1.973910 2.002548 2.031185 2.059823 2.088461 2.117099 2.145736 2.174374 #>         [,76]    [,77]    [,78]    [,79]    [,80]    [,81]    [,82]    [,83] #> [1,] 1.818677 1.835169 1.851661 1.868154 1.884646 1.901138 1.917630 1.934123 #> [2,] 2.203012 2.231650 2.260288 2.288925 2.317563 2.346201 2.374839 2.403476 #>         [,84]    [,85]    [,86]    [,87]    [,88]    [,89]    [,90]    [,91] #> [1,] 1.950615 1.967107 1.983599 2.000092 2.016584 2.033076 2.049568 2.066061 #> [2,] 2.432114 2.460752 2.489390 2.518028 2.546665 2.575303 2.603941 2.632579 #>         [,92]    [,93]    [,94]   [,95]    [,96]    [,97]    [,98]    [,99] #> [1,] 2.082553 2.099045 2.115537 2.13203 2.148522 2.165014 2.181507 2.197999 #> [2,] 2.661216 2.689854 2.718492 2.74713 2.775767 2.804405 2.833043 2.861681 #>        [,100]   [,101]   [,102]   [,103]  [,104]   [,105]   [,106]   [,107] #> [1,] 2.214491 2.230983 2.247476 2.263968 2.28046 2.296952 2.313445 2.329937 #> [2,] 2.890319 2.918956 2.947594 2.976232 3.00487 3.033507 3.062145 3.090783 #>        [,108]   [,109]   [,110]   [,111]   [,112]  [,113]   [,114]   [,115] #> [1,] 2.346429 2.362921 2.379414 2.395906 2.412398 2.42889 2.445383 2.461875 #> [2,] 3.119421 3.148059 3.176696 3.205334 3.233972 3.26261 3.291247 3.319885 #>        [,116]   [,117]   [,118]   [,119]   [,120]   [,121]   [,122]   [,123] #> [1,] 2.478367 2.494859 2.511352 2.527844 2.544336 2.560829 2.577321 2.593813 #> [2,] 3.348523 3.377161 3.405799 3.434436 3.463074 3.491712 3.520350 3.548987 #>        [,124]   [,125]   [,126]   [,127]   [,128]   [,129]   [,130]   [,131] #> [1,] 2.610305 2.626798 2.643290 2.659782 2.676274 2.692767 2.709259 2.725751 #> [2,] 3.577625 3.606263 3.634901 3.663538 3.692176 3.720814 3.749452 3.778090 #>        [,132]   [,133]   [,134]   [,135]   [,136]   [,137]   [,138]   [,139] #> [1,] 2.742243 2.758736 2.775228 2.791720 2.808212 2.824705 2.841197 2.857689 #> [2,] 3.806727 3.835365 3.864003 3.892641 3.921278 3.949916 3.978554 4.007192 #>        [,140]   [,141]   [,142]   [,143]   [,144]   [,145]   [,146]   [,147] #> [1,] 2.874182 2.890674 2.907166 2.923658 2.940151 2.956643 2.973135 2.989627 #> [2,] 4.035830 4.064467 4.093105 4.121743 4.150381 4.179018 4.207656 4.236294 #>        [,148]   [,149]   [,150]   [,151]   [,152]   [,153]   [,154]   [,155] #> [1,] 3.006120 3.022612 3.039104 3.055596 3.072089 3.088581 3.105073 3.121565 #> [2,] 4.264932 4.293569 4.322207 4.350845 4.379483 4.408121 4.436758 4.465396 #>        [,156]   [,157]   [,158]   [,159]   [,160]   [,161]   [,162]   [,163] #> [1,] 3.138058 3.154550 3.171042 3.187535 3.204027 3.220519 3.237011 3.253504 #> [2,] 4.494034 4.522672 4.551309 4.579947 4.608585 4.637223 4.665861 4.694498 #>        [,164]   [,165]   [,166]   [,167]   [,168]   [,169]   [,170]   [,171] #> [1,] 3.269996 3.286488 3.302980 3.319473 3.335965 3.352457 3.368949 3.385442 #> [2,] 4.723136 4.751774 4.780412 4.809049 4.837687 4.866325 4.894963 4.923600 #>        [,172]   [,173]   [,174]   [,175]   [,176]   [,177]   [,178]   [,179] #> [1,] 3.401934 3.418426 3.434918 3.451411 3.467903 3.484395 3.500888 3.517380 #> [2,] 4.952238 4.980876 5.009514 5.038152 5.066789 5.095427 5.124065 5.152703 #>        [,180]   [,181]   [,182]   [,183]   [,184]   [,185]   [,186]   [,187] #> [1,] 3.533872 3.550364 3.566857 3.583349 3.599841 3.616333 3.632826 3.649318 #> [2,] 5.181340 5.209978 5.238616 5.267254 5.295892 5.324529 5.353167 5.381805 #>        [,188]   [,189]   [,190]   [,191]   [,192]   [,193]   [,194]   [,195] #> [1,] 3.665810 3.682302 3.698795 3.715287 3.731779 3.748271 3.764764 3.781256 #> [2,] 5.410443 5.439080 5.467718 5.496356 5.524994 5.553631 5.582269 5.610907 #>        [,196]   [,197]   [,198]   [,199]   [,200] #> [1,] 3.797748 3.814241 3.830733 3.847225 3.863717 #> [2,] 5.639545 5.668183 5.696820 5.725458 5.754096 #>  #> $warpings #>               [,1]        [,2]         [,3]       [,4]       [,5]       [,6] #>  [1,]  1.030805198  1.05294860  1.075092011 1.09723542 1.11937882 1.14152223 #>  [2,]  1.001787925  1.02684018  1.051892439 1.07694470 1.10199695 1.12704921 #>  [3,]  1.045478224  1.06807127  1.090664311 1.11325735 1.13585040 1.15844344 #>  [4,]  0.928816380  0.95201431  0.975212243 0.99841017 1.02160811 1.04480604 #>  [5,]  0.897059469  0.91898331  0.940907159 0.96283100 0.98475485 1.00667869 #>  [6,]  1.061447992  1.08790519  1.114362386 1.14081958 1.16727678 1.19373398 #>  [7,]  1.139957673  1.16653163  1.193105580 1.21967953 1.24625349 1.27282744 #>  [8,]  1.082712462  1.10562153  1.128530590 1.15143965 1.17434872 1.19725778 #>  [9,]  0.965902671  0.98613473  1.006366794 1.02659886 1.04683092 1.06706298 #> [10,]  0.906922598  0.92721265  0.947502698 0.96779275 0.98808280 1.00837285 #> [11,]  0.317491592  0.33295298  0.348414378 0.36387577 0.37933716 0.39479856 #> [12,]  0.436722570  0.44866741  0.460612250 0.47255709 0.48450193 0.49644677 #> [13,]  0.468195084  0.48234493  0.496494786 0.51064464 0.52479449 0.53894434 #> [14,]  0.320243339  0.33090863  0.341573924 0.35223922 0.36290451 0.37356980 #> [15,]  0.358748478  0.37294634  0.387144194 0.40134205 0.41553991 0.42973777 #> [16,]  0.426851992  0.44250846  0.458164919 0.47382138 0.48947785 0.50513431 #> [17,]  0.343146905  0.35799965  0.372852389 0.38770513 0.40255787 0.41741062 #> [18,]  0.279548534  0.29233634  0.305124147 0.31791195 0.33069976 0.34348757 #> [19,]  0.520722532  0.53423640  0.547750258 0.56126412 0.57477798 0.58829185 #> [20,]  0.390965538  0.40394880  0.416932072 0.42991534 0.44289861 0.45588187 #> [21,]  0.111956906  0.13786423  0.163771557 0.18967888 0.21558621 0.24149353 #> [22,] -0.070649556 -0.03791667 -0.005183782 0.02754910 0.06028199 0.09301488 #> [23,]  0.060854717  0.08815012  0.115445532 0.14274094 0.17003635 0.19733175 #> [24,] -0.041924595 -0.01528699  0.011350611 0.03798821 0.06462582 0.09126342 #> [25,]  0.102342650  0.13553519  0.168727739 0.20192028 0.23511283 0.26830537 #> [26,]  0.120126505  0.15227385  0.184421197 0.21656854 0.24871589 0.28086324 #> [27,]  0.039451017  0.07175713  0.104063250 0.13636937 0.16867548 0.20098160 #> [28,] -0.004871023  0.02772095  0.060312932 0.09290491 0.12549689 0.15808886 #> [29,] -0.042271170 -0.01228534  0.017700492 0.04768632 0.07767215 0.10765798 #> [30,] -0.048958273 -0.01544011  0.018078049 0.05159621 0.08511437 0.11863253 #>            [,7]      [,8]      [,9]     [,10]     [,11]     [,12]     [,13] #>  [1,] 1.1636656 1.1858090 1.2079524 1.2300959 1.2522393 1.2743827 1.2965261 #>  [2,] 1.1521015 1.1771537 1.2022060 1.2272582 1.2523105 1.2773628 1.3024150 #>  [3,] 1.1810365 1.2036295 1.2262226 1.2488156 1.2714087 1.2940017 1.3165947 #>  [4,] 1.0680040 1.0912019 1.1143998 1.1375978 1.1607957 1.1839936 1.2071916 #>  [5,] 1.0286025 1.0505264 1.0724502 1.0943741 1.1162979 1.1382218 1.1601456 #>  [6,] 1.2201912 1.2466484 1.2731056 1.2995628 1.3260200 1.3524772 1.3789344 #>  [7,] 1.2994014 1.3259753 1.3525493 1.3791233 1.4056972 1.4322712 1.4588451 #>  [8,] 1.2201668 1.2430759 1.2659850 1.2888940 1.3118031 1.3347122 1.3576212 #>  [9,] 1.0872950 1.1075271 1.1277592 1.1479912 1.1682233 1.1884553 1.2086874 #> [10,] 1.0286629 1.0489529 1.0692430 1.0895330 1.1098231 1.1301131 1.1504032 #> [11,] 0.4102599 0.4257213 0.4411827 0.4566441 0.4721055 0.4875669 0.5030283 #> [12,] 0.5083916 0.5203365 0.5322813 0.5442261 0.5561710 0.5681158 0.5800607 #> [13,] 0.5530942 0.5672440 0.5813939 0.5955437 0.6096936 0.6238434 0.6379933 #> [14,] 0.3842351 0.3949004 0.4055657 0.4162310 0.4268963 0.4375616 0.4482269 #> [15,] 0.4439356 0.4581335 0.4723313 0.4865292 0.5007271 0.5149249 0.5291228 #> [16,] 0.5207908 0.5364472 0.5521037 0.5677602 0.5834166 0.5990731 0.6147296 #> [17,] 0.4322634 0.4471161 0.4619688 0.4768216 0.4916743 0.5065271 0.5213798 #> [18,] 0.3562754 0.3690632 0.3818510 0.3946388 0.4074266 0.4202144 0.4330022 #> [19,] 0.6018057 0.6153196 0.6288334 0.6423473 0.6558612 0.6693750 0.6828889 #> [20,] 0.4688651 0.4818484 0.4948317 0.5078149 0.5207982 0.5337815 0.5467647 #> [21,] 0.2674009 0.2933082 0.3192155 0.3451228 0.3710302 0.3969375 0.4228448 #> [22,] 0.1257478 0.1584807 0.1912135 0.2239464 0.2566793 0.2894122 0.3221451 #> [23,] 0.2246272 0.2519226 0.2792180 0.3065134 0.3338088 0.3611042 0.3883996 #> [24,] 0.1179010 0.1445386 0.1711762 0.1978138 0.2244514 0.2510890 0.2777266 #> [25,] 0.3014979 0.3346905 0.3678830 0.4010756 0.4342681 0.4674606 0.5006532 #> [26,] 0.3130106 0.3451579 0.3773053 0.4094526 0.4416000 0.4737473 0.5058947 #> [27,] 0.2332877 0.2655938 0.2978999 0.3302061 0.3625122 0.3948183 0.4271244 #> [28,] 0.1906808 0.2232728 0.2558648 0.2884568 0.3210488 0.3536407 0.3862327 #> [29,] 0.1376438 0.1676296 0.1976155 0.2276013 0.2575871 0.2875730 0.3175588 #> [30,] 0.1521507 0.1856689 0.2191870 0.2527052 0.2862233 0.3197415 0.3532597 #>           [,14]     [,15]     [,16]     [,17]     [,18]     [,19]     [,20] #>  [1,] 1.3186695 1.3408129 1.3629563 1.3850997 1.4072431 1.4293865 1.4515299 #>  [2,] 1.3274673 1.3525195 1.3775718 1.4026240 1.4276763 1.4527285 1.4777808 #>  [3,] 1.3391878 1.3617808 1.3843739 1.4069669 1.4295600 1.4521530 1.4747461 #>  [4,] 1.2303895 1.2535874 1.2767854 1.2999833 1.3231812 1.3463791 1.3695771 #>  [5,] 1.1820695 1.2039933 1.2259171 1.2478410 1.2697648 1.2916887 1.3136125 #>  [6,] 1.4053916 1.4318487 1.4583059 1.4847631 1.5112203 1.5376775 1.5641347 #>  [7,] 1.4854191 1.5119930 1.5385670 1.5651409 1.5917149 1.6182888 1.6448628 #>  [8,] 1.3805303 1.4034394 1.4263484 1.4492575 1.4721665 1.4950756 1.5179847 #>  [9,] 1.2289195 1.2491515 1.2693836 1.2896157 1.3098477 1.3300798 1.3503118 #> [10,] 1.1706932 1.1909833 1.2112733 1.2315634 1.2518535 1.2721435 1.2924336 #> [11,] 0.5184897 0.5339511 0.5494125 0.5648739 0.5803353 0.5957967 0.6112581 #> [12,] 0.5920055 0.6039503 0.6158952 0.6278400 0.6397849 0.6517297 0.6636745 #> [13,] 0.6521432 0.6662930 0.6804429 0.6945927 0.7087426 0.7228924 0.7370423 #> [14,] 0.4588921 0.4695574 0.4802227 0.4908880 0.5015533 0.5122186 0.5228839 #> [15,] 0.5433206 0.5575185 0.5717163 0.5859142 0.6001121 0.6143099 0.6285078 #> [16,] 0.6303860 0.6460425 0.6616989 0.6773554 0.6930119 0.7086683 0.7243248 #> [17,] 0.5362326 0.5510853 0.5659380 0.5807908 0.5956435 0.6104963 0.6253490 #> [18,] 0.4457900 0.4585778 0.4713656 0.4841534 0.4969412 0.5097291 0.5225169 #> [19,] 0.6964028 0.7099166 0.7234305 0.7369443 0.7504582 0.7639721 0.7774859 #> [20,] 0.5597480 0.5727313 0.5857145 0.5986978 0.6116811 0.6246643 0.6376476 #> [21,] 0.4487521 0.4746595 0.5005668 0.5264741 0.5523814 0.5782888 0.6041961 #> [22,] 0.3548780 0.3876109 0.4203437 0.4530766 0.4858095 0.5185424 0.5512753 #> [23,] 0.4156950 0.4429904 0.4702858 0.4975812 0.5248766 0.5521720 0.5794675 #> [24,] 0.3043642 0.3310019 0.3576395 0.3842771 0.4109147 0.4375523 0.4641899 #> [25,] 0.5338457 0.5670383 0.6002308 0.6334234 0.6666159 0.6998085 0.7330010 #> [26,] 0.5380420 0.5701893 0.6023367 0.6344840 0.6666314 0.6987787 0.7309261 #> [27,] 0.4594305 0.4917366 0.5240428 0.5563489 0.5886550 0.6209611 0.6532672 #> [28,] 0.4188247 0.4514167 0.4840086 0.5166006 0.5491926 0.5817846 0.6143765 #> [29,] 0.3475446 0.3775305 0.4075163 0.4375021 0.4674880 0.4974738 0.5274596 #> [30,] 0.3867778 0.4202960 0.4538141 0.4873323 0.5208505 0.5543686 0.5878868 #>           [,21]     [,22]     [,23]     [,24]     [,25]     [,26]     [,27] #>  [1,] 1.4736733 1.4958167 1.5179601 1.5401035 1.5622469 1.5843904 1.6065338 #>  [2,] 1.5028331 1.5278853 1.5529376 1.5779898 1.6030421 1.6280943 1.6531466 #>  [3,] 1.4973391 1.5199321 1.5425252 1.5651182 1.5877113 1.6103043 1.6328974 #>  [4,] 1.3927750 1.4159729 1.4391709 1.4623688 1.4855667 1.5087647 1.5319626 #>  [5,] 1.3355364 1.3574602 1.3793841 1.4013079 1.4232317 1.4451556 1.4670794 #>  [6,] 1.5905919 1.6170491 1.6435063 1.6699635 1.6964207 1.7228779 1.7493351 #>  [7,] 1.6714367 1.6980107 1.7245847 1.7511586 1.7777326 1.8043065 1.8308805 #>  [8,] 1.5408937 1.5638028 1.5867119 1.6096209 1.6325300 1.6554391 1.6783481 #>  [9,] 1.3705439 1.3907760 1.4110080 1.4312401 1.4514721 1.4717042 1.4919363 #> [10,] 1.3127236 1.3330137 1.3533037 1.3735938 1.3938838 1.4141739 1.4344639 #> [11,] 0.6267195 0.6421808 0.6576422 0.6731036 0.6885650 0.7040264 0.7194878 #> [12,] 0.6756194 0.6875642 0.6995091 0.7114539 0.7233987 0.7353436 0.7472884 #> [13,] 0.7511921 0.7653420 0.7794918 0.7936417 0.8077915 0.8219414 0.8360912 #> [14,] 0.5335492 0.5442145 0.5548798 0.5655451 0.5762104 0.5868757 0.5975410 #> [15,] 0.6427056 0.6569035 0.6711014 0.6852992 0.6994971 0.7136949 0.7278928 #> [16,] 0.7399813 0.7556377 0.7712942 0.7869507 0.8026071 0.8182636 0.8339200 #> [17,] 0.6402017 0.6550545 0.6699072 0.6847600 0.6996127 0.7144655 0.7293182 #> [18,] 0.5353047 0.5480925 0.5608803 0.5736681 0.5864559 0.5992437 0.6120315 #> [19,] 0.7909998 0.8045137 0.8180275 0.8315414 0.8450552 0.8585691 0.8720830 #> [20,] 0.6506309 0.6636141 0.6765974 0.6895807 0.7025639 0.7155472 0.7285305 #> [21,] 0.6301034 0.6560107 0.6819181 0.7078254 0.7337327 0.7596400 0.7855474 #> [22,] 0.5840082 0.6167411 0.6494740 0.6822068 0.7149397 0.7476726 0.7804055 #> [23,] 0.6067629 0.6340583 0.6613537 0.6886491 0.7159445 0.7432399 0.7705353 #> [24,] 0.4908275 0.5174651 0.5441027 0.5707403 0.5973779 0.6240155 0.6506531 #> [25,] 0.7661935 0.7993861 0.8325786 0.8657712 0.8989637 0.9321563 0.9653488 #> [26,] 0.7630734 0.7952208 0.8273681 0.8595155 0.8916628 0.9238102 0.9559575 #> [27,] 0.6855733 0.7178795 0.7501856 0.7824917 0.8147978 0.8471039 0.8794100 #> [28,] 0.6469685 0.6795605 0.7121525 0.7447445 0.7773364 0.8099284 0.8425204 #> [29,] 0.5574455 0.5874313 0.6174171 0.6474029 0.6773888 0.7073746 0.7373604 #> [30,] 0.6214049 0.6549231 0.6884413 0.7219594 0.7554776 0.7889958 0.8225139 #>           [,28]     [,29]     [,30]     [,31]     [,32]     [,33]     [,34] #>  [1,] 1.6286772 1.6508206 1.6729640 1.6951074 1.7172508 1.7393942 1.7615376 #>  [2,] 1.6781989 1.7032511 1.7283034 1.7533556 1.7784079 1.8034601 1.8285124 #>  [3,] 1.6554904 1.6780834 1.7006765 1.7232695 1.7458626 1.7684556 1.7910487 #>  [4,] 1.5551605 1.5783585 1.6015564 1.6247543 1.6479523 1.6711502 1.6943481 #>  [5,] 1.4890033 1.5109271 1.5328510 1.5547748 1.5766987 1.5986225 1.6205464 #>  [6,] 1.7757923 1.8022495 1.8287067 1.8551639 1.8816211 1.9080783 1.9345355 #>  [7,] 1.8574544 1.8840284 1.9106023 1.9371763 1.9637502 1.9903242 2.0168982 #>  [8,] 1.7012572 1.7241663 1.7470753 1.7699844 1.7928934 1.8158025 1.8387116 #>  [9,] 1.5121683 1.5324004 1.5526325 1.5728645 1.5930966 1.6133286 1.6335607 #> [10,] 1.4547540 1.4750440 1.4953341 1.5156241 1.5359142 1.5562042 1.5764943 #> [11,] 0.7349492 0.7504106 0.7658720 0.7813334 0.7967948 0.8122562 0.8277176 #> [12,] 0.7592333 0.7711781 0.7831229 0.7950678 0.8070126 0.8189575 0.8309023 #> [13,] 0.8502411 0.8643909 0.8785408 0.8926906 0.9068405 0.9209903 0.9351402 #> [14,] 0.6082062 0.6188715 0.6295368 0.6402021 0.6508674 0.6615327 0.6721980 #> [15,] 0.7420906 0.7562885 0.7704864 0.7846842 0.7988821 0.8130799 0.8272778 #> [16,] 0.8495765 0.8652330 0.8808894 0.8965459 0.9122024 0.9278588 0.9435153 #> [17,] 0.7441709 0.7590237 0.7738764 0.7887292 0.8035819 0.8184347 0.8332874 #> [18,] 0.6248193 0.6376071 0.6503949 0.6631827 0.6759705 0.6887583 0.7015461 #> [19,] 0.8855968 0.8991107 0.9126246 0.9261384 0.9396523 0.9531661 0.9666800 #> [20,] 0.7415137 0.7544970 0.7674803 0.7804635 0.7934468 0.8064301 0.8194133 #> [21,] 0.8114547 0.8373620 0.8632693 0.8891767 0.9150840 0.9409913 0.9668986 #> [22,] 0.8131384 0.8458713 0.8786042 0.9113370 0.9440699 0.9768028 1.0095357 #> [23,] 0.7978307 0.8251261 0.8524215 0.8797169 0.9070123 0.9343078 0.9616032 #> [24,] 0.6772907 0.7039283 0.7305659 0.7572035 0.7838411 0.8104787 0.8371163 #> [25,] 0.9985414 1.0317339 1.0649265 1.0981190 1.1313115 1.1645041 1.1976966 #> [26,] 0.9881048 1.0202522 1.0523995 1.0845469 1.1166942 1.1488416 1.1809889 #> [27,] 0.9117162 0.9440223 0.9763284 1.0086345 1.0409406 1.0732467 1.1055529 #> [28,] 0.8751124 0.9077043 0.9402963 0.9728883 1.0054803 1.0380723 1.0706642 #> [29,] 0.7673463 0.7973321 0.8273179 0.8573038 0.8872896 0.9172754 0.9472613 #> [30,] 0.8560321 0.8895502 0.9230684 0.9565866 0.9901047 1.0236229 1.0571410 #>           [,35]     [,36]     [,37]     [,38]     [,39]     [,40]     [,41] #>  [1,] 1.7836810 1.8058244 1.8279678 1.8501112 1.8722546 1.8943980 1.9165414 #>  [2,] 1.8535647 1.8786169 1.9036692 1.9287214 1.9537737 1.9788259 2.0038782 #>  [3,] 1.8136417 1.8362348 1.8588278 1.8814208 1.9040139 1.9266069 1.9492000 #>  [4,] 1.7175461 1.7407440 1.7639419 1.7871398 1.8103378 1.8335357 1.8567336 #>  [5,] 1.6424702 1.6643940 1.6863179 1.7082417 1.7301656 1.7520894 1.7740133 #>  [6,] 1.9609927 1.9874499 2.0139071 2.0403643 2.0668215 2.0932787 2.1197359 #>  [7,] 2.0434721 2.0700461 2.0966200 2.1231940 2.1497679 2.1763419 2.2029158 #>  [8,] 1.8616206 1.8845297 1.9074388 1.9303478 1.9532569 1.9761660 1.9990750 #>  [9,] 1.6537928 1.6740248 1.6942569 1.7144889 1.7347210 1.7549531 1.7751851 #> [10,] 1.5967843 1.6170744 1.6373644 1.6576545 1.6779445 1.6982346 1.7185246 #> [11,] 0.8431790 0.8586403 0.8741017 0.8895631 0.9050245 0.9204859 0.9359473 #> [12,] 0.8428471 0.8547920 0.8667368 0.8786817 0.8906265 0.9025713 0.9145162 #> [13,] 0.9492900 0.9634399 0.9775897 0.9917396 1.0058894 1.0200393 1.0341891 #> [14,] 0.6828633 0.6935286 0.7041939 0.7148592 0.7255245 0.7361898 0.7468551 #> [15,] 0.8414757 0.8556735 0.8698714 0.8840692 0.8982671 0.9124649 0.9266628 #> [16,] 0.9591718 0.9748282 0.9904847 1.0061411 1.0217976 1.0374541 1.0531105 #> [17,] 0.8481401 0.8629929 0.8778456 0.8926984 0.9075511 0.9224039 0.9372566 #> [18,] 0.7143340 0.7271218 0.7399096 0.7526974 0.7654852 0.7782730 0.7910608 #> [19,] 0.9801939 0.9937077 1.0072216 1.0207355 1.0342493 1.0477632 1.0612770 #> [20,] 0.8323966 0.8453799 0.8583631 0.8713464 0.8843297 0.8973129 0.9102962 #> [21,] 0.9928060 1.0187133 1.0446206 1.0705279 1.0964353 1.1223426 1.1482499 #> [22,] 1.0422686 1.0750015 1.1077344 1.1404673 1.1732001 1.2059330 1.2386659 #> [23,] 0.9888986 1.0161940 1.0434894 1.0707848 1.0980802 1.1253756 1.1526710 #> [24,] 0.8637539 0.8903915 0.9170291 0.9436667 0.9703043 0.9969419 1.0235795 #> [25,] 1.2308892 1.2640817 1.2972743 1.3304668 1.3636594 1.3968519 1.4300444 #> [26,] 1.2131363 1.2452836 1.2774310 1.3095783 1.3417257 1.3738730 1.4060203 #> [27,] 1.1378590 1.1701651 1.2024712 1.2347773 1.2670834 1.2993896 1.3316957 #> [28,] 1.1032562 1.1358482 1.1684402 1.2010321 1.2336241 1.2662161 1.2988081 #> [29,] 0.9772471 1.0072329 1.0372187 1.0672046 1.0971904 1.1271762 1.1571621 #> [30,] 1.0906592 1.1241774 1.1576955 1.1912137 1.2247318 1.2582500 1.2917682 #>           [,42]     [,43]     [,44]     [,45]     [,46]     [,47]     [,48] #>  [1,] 1.9386848 1.9608283 1.9829717 2.0051151 2.0272585 2.0494019 2.0715453 #>  [2,] 2.0289305 2.0539827 2.0790350 2.1040872 2.1291395 2.1541917 2.1792440 #>  [3,] 1.9717930 1.9943861 2.0169791 2.0395721 2.0621652 2.0847582 2.1073513 #>  [4,] 1.8799316 1.9031295 1.9263274 1.9495254 1.9727233 1.9959212 2.0191192 #>  [5,] 1.7959371 1.8178610 1.8397848 1.8617086 1.8836325 1.9055563 1.9274802 #>  [6,] 2.1461931 2.1726503 2.1991075 2.2255647 2.2520219 2.2784790 2.3049362 #>  [7,] 2.2294898 2.2560637 2.2826377 2.3092116 2.3357856 2.3623596 2.3889335 #>  [8,] 2.0219841 2.0448931 2.0678022 2.0907113 2.1136203 2.1365294 2.1594385 #>  [9,] 1.7954172 1.8156492 1.8358813 1.8561134 1.8763454 1.8965775 1.9168096 #> [10,] 1.7388147 1.7591047 1.7793948 1.7996848 1.8199749 1.8402649 1.8605550 #> [11,] 0.9514087 0.9668701 0.9823315 0.9977929 1.0132543 1.0287157 1.0441771 #> [12,] 0.9264610 0.9384059 0.9503507 0.9622955 0.9742404 0.9861852 0.9981301 #> [13,] 1.0483390 1.0624888 1.0766387 1.0907885 1.1049384 1.1190882 1.1332381 #> [14,] 0.7575203 0.7681856 0.7788509 0.7895162 0.8001815 0.8108468 0.8215121 #> [15,] 0.9408607 0.9550585 0.9692564 0.9834542 0.9976521 1.0118499 1.0260478 #> [16,] 1.0687670 1.0844235 1.1000799 1.1157364 1.1313928 1.1470493 1.1627058 #> [17,] 0.9521093 0.9669621 0.9818148 0.9966676 1.0115203 1.0263730 1.0412258 #> [18,] 0.8038486 0.8166364 0.8294242 0.8422120 0.8549998 0.8677876 0.8805754 #> [19,] 1.0747909 1.0883048 1.1018186 1.1153325 1.1288464 1.1423602 1.1558741 #> [20,] 0.9232795 0.9362627 0.9492460 0.9622293 0.9752125 0.9881958 1.0011791 #> [21,] 1.1741572 1.2000646 1.2259719 1.2518792 1.2777865 1.3036939 1.3296012 #> [22,] 1.2713988 1.3041317 1.3368646 1.3695975 1.4023303 1.4350632 1.4677961 #> [23,] 1.1799664 1.2072618 1.2345572 1.2618526 1.2891480 1.3164435 1.3437389 #> [24,] 1.0502171 1.0768547 1.1034923 1.1301299 1.1567676 1.1834052 1.2100428 #> [25,] 1.4632370 1.4964295 1.5296221 1.5628146 1.5960072 1.6291997 1.6623923 #> [26,] 1.4381677 1.4703150 1.5024624 1.5346097 1.5667571 1.5989044 1.6310518 #> [27,] 1.3640018 1.3963079 1.4286140 1.4609201 1.4932263 1.5255324 1.5578385 #> [28,] 1.3314001 1.3639920 1.3965840 1.4291760 1.4617680 1.4943599 1.5269519 #> [29,] 1.1871479 1.2171337 1.2471196 1.2771054 1.3070912 1.3370771 1.3670629 #> [30,] 1.3252863 1.3588045 1.3923226 1.4258408 1.4593590 1.4928771 1.5263953 #>           [,49]     [,50]     [,51]     [,52]     [,53]     [,54]     [,55] #>  [1,] 2.0936887 2.1158321 2.1379755 2.1601189 2.1822623 2.2044057 2.2265491 #>  [2,] 2.2042963 2.2293485 2.2544008 2.2794530 2.3045053 2.3295575 2.3546098 #>  [3,] 2.1299443 2.1525374 2.1751304 2.1977235 2.2203165 2.2429095 2.2655026 #>  [4,] 2.0423171 2.0655150 2.0887130 2.1119109 2.1351088 2.1583068 2.1815047 #>  [5,] 1.9494040 1.9713279 1.9932517 2.0151756 2.0370994 2.0590232 2.0809471 #>  [6,] 2.3313934 2.3578506 2.3843078 2.4107650 2.4372222 2.4636794 2.4901366 #>  [7,] 2.4155075 2.4420814 2.4686554 2.4952293 2.5218033 2.5483772 2.5749512 #>  [8,] 2.1823475 2.2052566 2.2281657 2.2510747 2.2739838 2.2968929 2.3198019 #>  [9,] 1.9370416 1.9572737 1.9775057 1.9977378 2.0179699 2.0382019 2.0584340 #> [10,] 1.8808450 1.9011351 1.9214251 1.9417152 1.9620052 1.9822953 2.0025853 #> [11,] 1.0596385 1.0750998 1.0905612 1.1060226 1.1214840 1.1369454 1.1524068 #> [12,] 1.0100749 1.0220197 1.0339646 1.0459094 1.0578543 1.0697991 1.0817439 #> [13,] 1.1473879 1.1615378 1.1756877 1.1898375 1.2039874 1.2181372 1.2322871 #> [14,] 0.8321774 0.8428427 0.8535080 0.8641733 0.8748386 0.8855039 0.8961692 #> [15,] 1.0402457 1.0544435 1.0686414 1.0828392 1.0970371 1.1112350 1.1254328 #> [16,] 1.1783622 1.1940187 1.2096752 1.2253316 1.2409881 1.2566446 1.2723010 #> [17,] 1.0560785 1.0709313 1.0857840 1.1006368 1.1154895 1.1303422 1.1451950 #> [18,] 0.8933632 0.9061511 0.9189389 0.9317267 0.9445145 0.9573023 0.9700901 #> [19,] 1.1693880 1.1829018 1.1964157 1.2099295 1.2234434 1.2369573 1.2504711 #> [20,] 1.0141623 1.0271456 1.0401289 1.0531121 1.0660954 1.0790787 1.0920619 #> [21,] 1.3555085 1.3814158 1.4073232 1.4332305 1.4591378 1.4850452 1.5109525 #> [22,] 1.5005290 1.5332619 1.5659948 1.5987277 1.6314606 1.6641934 1.6969263 #> [23,] 1.3710343 1.3983297 1.4256251 1.4529205 1.4802159 1.5075113 1.5348067 #> [24,] 1.2366804 1.2633180 1.2899556 1.3165932 1.3432308 1.3698684 1.3965060 #> [25,] 1.6955848 1.7287774 1.7619699 1.7951624 1.8283550 1.8615475 1.8947401 #> [26,] 1.6631991 1.6953465 1.7274938 1.7596411 1.7917885 1.8239358 1.8560832 #> [27,] 1.5901446 1.6224507 1.6547568 1.6870630 1.7193691 1.7516752 1.7839813 #> [28,] 1.5595439 1.5921359 1.6247279 1.6573198 1.6899118 1.7225038 1.7550958 #> [29,] 1.3970487 1.4270346 1.4570204 1.4870062 1.5169920 1.5469779 1.5769637 #> [30,] 1.5599135 1.5934316 1.6269498 1.6604679 1.6939861 1.7275043 1.7610224 #>           [,56]     [,57]    [,58]     [,59]     [,60]     [,61]     [,62] #>  [1,] 2.2486925 2.2708359 2.292979 2.3151228 2.3372662 2.3594096 2.3815530 #>  [2,] 2.3796621 2.4047143 2.429767 2.4548188 2.4798711 2.5049233 2.5299756 #>  [3,] 2.2880956 2.3106887 2.333282 2.3558748 2.3784678 2.4010608 2.4236539 #>  [4,] 2.2047026 2.2279005 2.251098 2.2742964 2.2974943 2.3206923 2.3438902 #>  [5,] 2.1028709 2.1247948 2.146719 2.1686425 2.1905663 2.2124902 2.2344140 #>  [6,] 2.5165938 2.5430510 2.569508 2.5959654 2.6224226 2.6488798 2.6753370 #>  [7,] 2.6015251 2.6280991 2.654673 2.6812470 2.7078210 2.7343949 2.7609689 #>  [8,] 2.3427110 2.3656200 2.388529 2.4114382 2.4343472 2.4572563 2.4801654 #>  [9,] 2.0786660 2.0988981 2.119130 2.1393622 2.1595943 2.1798264 2.2000584 #> [10,] 2.0228754 2.0431654 2.063455 2.0837455 2.1040356 2.1243256 2.1446157 #> [11,] 1.1678682 1.1833296 1.198791 1.2142524 1.2297138 1.2451752 1.2606366 #> [12,] 1.0936888 1.1056336 1.117578 1.1295233 1.1414681 1.1534130 1.1653578 #> [13,] 1.2464369 1.2605868 1.274737 1.2888865 1.3030363 1.3171862 1.3313360 #> [14,] 0.9068344 0.9174997 0.928165 0.9388303 0.9494956 0.9601609 0.9708262 #> [15,] 1.1396307 1.1538285 1.168026 1.1822242 1.1964221 1.2106200 1.2248178 #> [16,] 1.2879575 1.3036139 1.319270 1.3349269 1.3505833 1.3662398 1.3818963 #> [17,] 1.1600477 1.1749005 1.189753 1.2046060 1.2194587 1.2343114 1.2491642 #> [18,] 0.9828779 0.9956657 1.008454 1.0212413 1.0340291 1.0468169 1.0596047 #> [19,] 1.2639850 1.2774989 1.291013 1.3045266 1.3180404 1.3315543 1.3450682 #> [20,] 1.1050452 1.1180285 1.131012 1.1439950 1.1569783 1.1699616 1.1829448 #> [21,] 1.5368598 1.5627671 1.588674 1.6145818 1.6404891 1.6663964 1.6923038 #> [22,] 1.7296592 1.7623921 1.795125 1.8278579 1.8605908 1.8933237 1.9260565 #> [23,] 1.5621021 1.5893975 1.616693 1.6439883 1.6712838 1.6985792 1.7258746 #> [24,] 1.4231436 1.4497812 1.476419 1.5030564 1.5296940 1.5563316 1.5829692 #> [25,] 1.9279326 1.9611252 1.994318 2.0275103 2.0607028 2.0938953 2.1270879 #> [26,] 1.8882305 1.9203779 1.952525 1.9846726 2.0168199 2.0489673 2.0811146 #> [27,] 1.8162874 1.8485935 1.880900 1.9132058 1.9455119 1.9778180 2.0101241 #> [28,] 1.7876877 1.8202797 1.852872 1.8854637 1.9180556 1.9506476 1.9832396 #> [29,] 1.6069495 1.6369354 1.666921 1.6969070 1.7268929 1.7568787 1.7868645 #> [30,] 1.7945406 1.8280587 1.861577 1.8950951 1.9286132 1.9621314 1.9956495 #>           [,63]     [,64]    [,65]    [,66]    [,67]    [,68]    [,69]    [,70] #>  [1,] 2.4036964 2.4258398 2.447983 2.470127 2.492270 2.514413 2.536557 2.558700 #>  [2,] 2.5550279 2.5800801 2.605132 2.630185 2.655237 2.680289 2.705341 2.730394 #>  [3,] 2.4462469 2.4688400 2.491433 2.514026 2.536619 2.559212 2.581805 2.604398 #>  [4,] 2.3670881 2.3902861 2.413484 2.436682 2.459880 2.483078 2.506276 2.529474 #>  [5,] 2.2563379 2.2782617 2.300186 2.322109 2.344033 2.365957 2.387881 2.409805 #>  [6,] 2.7017942 2.7282514 2.754709 2.781166 2.807623 2.834080 2.860537 2.886995 #>  [7,] 2.7875428 2.8141168 2.840691 2.867265 2.893839 2.920413 2.946987 2.973560 #>  [8,] 2.5030744 2.5259835 2.548893 2.571802 2.594711 2.617620 2.640529 2.663438 #>  [9,] 2.2202905 2.2405225 2.260755 2.280987 2.301219 2.321451 2.341683 2.361915 #> [10,] 2.1649057 2.1851958 2.205486 2.225776 2.246066 2.266356 2.286646 2.306936 #> [11,] 1.2760980 1.2915593 1.307021 1.322482 1.337944 1.353405 1.368866 1.384328 #> [12,] 1.1773027 1.1892475 1.201192 1.213137 1.225082 1.237027 1.248972 1.260917 #> [13,] 1.3454859 1.3596357 1.373786 1.387935 1.402085 1.416235 1.430385 1.444535 #> [14,] 0.9814915 0.9921568 1.002822 1.013487 1.024153 1.034818 1.045483 1.056149 #> [15,] 1.2390157 1.2532135 1.267411 1.281609 1.295807 1.310005 1.324203 1.338401 #> [16,] 1.3975527 1.4132092 1.428866 1.444522 1.460179 1.475835 1.491492 1.507148 #> [17,] 1.2640169 1.2788697 1.293722 1.308575 1.323428 1.338281 1.353133 1.367986 #> [18,] 1.0723925 1.0851803 1.097968 1.110756 1.123544 1.136332 1.149119 1.161907 #> [19,] 1.3585820 1.3720959 1.385610 1.399124 1.412637 1.426151 1.439665 1.453179 #> [20,] 1.1959281 1.2089114 1.221895 1.234878 1.247861 1.260844 1.273828 1.286811 #> [21,] 1.7182111 1.7441184 1.770026 1.795933 1.821840 1.847748 1.873655 1.899562 #> [22,] 1.9587894 1.9915223 2.024255 2.056988 2.089721 2.122454 2.155187 2.187920 #> [23,] 1.7531700 1.7804654 1.807761 1.835056 1.862352 1.889647 1.916942 1.944238 #> [24,] 1.6096068 1.6362444 1.662882 1.689520 1.716157 1.742795 1.769432 1.796070 #> [25,] 2.1602804 2.1934730 2.226666 2.259858 2.293051 2.326243 2.359436 2.392628 #> [26,] 2.1132620 2.1454093 2.177557 2.209704 2.241851 2.273999 2.306146 2.338293 #> [27,] 2.0424302 2.0747364 2.107042 2.139349 2.171655 2.203961 2.236267 2.268573 #> [28,] 2.0158316 2.0484236 2.081016 2.113608 2.146199 2.178791 2.211383 2.243975 #> [29,] 1.8168504 1.8468362 1.876822 1.906808 1.936794 1.966780 1.996765 2.026751 #> [30,] 2.0291677 2.0626859 2.096204 2.129722 2.163240 2.196759 2.230277 2.263795 #>          [,71]    [,72]    [,73]    [,74]    [,75]    [,76]    [,77]    [,78] #>  [1,] 2.580844 2.602987 2.625130 2.647274 2.669417 2.691561 2.713704 2.735847 #>  [2,] 2.755446 2.780498 2.805550 2.830603 2.855655 2.880707 2.905759 2.930812 #>  [3,] 2.626991 2.649584 2.672177 2.694770 2.717363 2.739957 2.762550 2.785143 #>  [4,] 2.552672 2.575870 2.599067 2.622265 2.645463 2.668661 2.691859 2.715057 #>  [5,] 2.431729 2.453652 2.475576 2.497500 2.519424 2.541348 2.563272 2.585196 #>  [6,] 2.913452 2.939909 2.966366 2.992823 3.019281 3.045738 3.072195 3.098652 #>  [7,] 3.000134 3.026708 3.053282 3.079856 3.106430 3.133004 3.159578 3.186152 #>  [8,] 2.686347 2.709256 2.732165 2.755074 2.777983 2.800892 2.823801 2.846710 #>  [9,] 2.382147 2.402379 2.422611 2.442843 2.463075 2.483307 2.503539 2.523771 #> [10,] 2.327226 2.347516 2.367806 2.388096 2.408386 2.428676 2.448966 2.469256 #> [11,] 1.399789 1.415250 1.430712 1.446173 1.461635 1.477096 1.492557 1.508019 #> [12,] 1.272861 1.284806 1.296751 1.308696 1.320641 1.332586 1.344530 1.356475 #> [13,] 1.458685 1.472835 1.486984 1.501134 1.515284 1.529434 1.543584 1.557734 #> [14,] 1.066814 1.077479 1.088144 1.098810 1.109475 1.120140 1.130806 1.141471 #> [15,] 1.352599 1.366796 1.380994 1.395192 1.409390 1.423588 1.437786 1.451984 #> [16,] 1.522804 1.538461 1.554117 1.569774 1.585430 1.601087 1.616743 1.632400 #> [17,] 1.382839 1.397692 1.412544 1.427397 1.442250 1.457103 1.471955 1.486808 #> [18,] 1.174695 1.187483 1.200271 1.213058 1.225846 1.238634 1.251422 1.264210 #> [19,] 1.466693 1.480207 1.493721 1.507235 1.520748 1.534262 1.547776 1.561290 #> [20,] 1.299794 1.312777 1.325761 1.338744 1.351727 1.364711 1.377694 1.390677 #> [21,] 1.925470 1.951377 1.977284 2.003192 2.029099 2.055006 2.080914 2.106821 #> [22,] 2.220653 2.253385 2.286118 2.318851 2.351584 2.384317 2.417050 2.449783 #> [23,] 1.971533 1.998829 2.026124 2.053419 2.080715 2.108010 2.135306 2.162601 #> [24,] 1.822708 1.849345 1.875983 1.902620 1.929258 1.955896 1.982533 2.009171 #> [25,] 2.425821 2.459013 2.492206 2.525398 2.558591 2.591784 2.624976 2.658169 #> [26,] 2.370441 2.402588 2.434735 2.466883 2.499030 2.531177 2.563325 2.595472 #> [27,] 2.300879 2.333185 2.365491 2.397798 2.430104 2.462410 2.494716 2.527022 #> [28,] 2.276567 2.309159 2.341751 2.374343 2.406935 2.439527 2.472119 2.504711 #> [29,] 2.056737 2.086723 2.116709 2.146694 2.176680 2.206666 2.236652 2.266638 #> [30,] 2.297313 2.330831 2.364349 2.397867 2.431386 2.464904 2.498422 2.531940 #>          [,79]    [,80]    [,81]    [,82]    [,83]    [,84]    [,85]    [,86] #>  [1,] 2.757991 2.780134 2.802278 2.824421 2.846564 2.868708 2.890851 2.912995 #>  [2,] 2.955864 2.980916 3.005968 3.031021 3.056073 3.081125 3.106178 3.131230 #>  [3,] 2.807736 2.830329 2.852922 2.875515 2.898108 2.920701 2.943294 2.965887 #>  [4,] 2.738255 2.761453 2.784651 2.807849 2.831047 2.854245 2.877443 2.900641 #>  [5,] 2.607119 2.629043 2.650967 2.672891 2.694815 2.716739 2.738662 2.760586 #>  [6,] 3.125109 3.151567 3.178024 3.204481 3.230938 3.257395 3.283853 3.310310 #>  [7,] 3.212726 3.239300 3.265874 3.292448 3.319022 3.345596 3.372170 3.398744 #>  [8,] 2.869619 2.892529 2.915438 2.938347 2.961256 2.984165 3.007074 3.029983 #>  [9,] 2.544003 2.564236 2.584468 2.604700 2.624932 2.645164 2.665396 2.685628 #> [10,] 2.489547 2.509837 2.530127 2.550417 2.570707 2.590997 2.611287 2.631577 #> [11,] 1.523480 1.538942 1.554403 1.569864 1.585326 1.600787 1.616249 1.631710 #> [12,] 1.368420 1.380365 1.392310 1.404255 1.416199 1.428144 1.440089 1.452034 #> [13,] 1.571883 1.586033 1.600183 1.614333 1.628483 1.642633 1.656783 1.670932 #> [14,] 1.152136 1.162801 1.173467 1.184132 1.194797 1.205463 1.216128 1.226793 #> [15,] 1.466181 1.480379 1.494577 1.508775 1.522973 1.537171 1.551369 1.565566 #> [16,] 1.648056 1.663713 1.679369 1.695026 1.710682 1.726338 1.741995 1.757651 #> [17,] 1.501661 1.516514 1.531366 1.546219 1.561072 1.575925 1.590777 1.605630 #> [18,] 1.276997 1.289785 1.302573 1.315361 1.328149 1.340936 1.353724 1.366512 #> [19,] 1.574804 1.588318 1.601832 1.615345 1.628859 1.642373 1.655887 1.669401 #> [20,] 1.403660 1.416644 1.429627 1.442610 1.455593 1.468577 1.481560 1.494543 #> [21,] 2.132728 2.158636 2.184543 2.210450 2.236358 2.262265 2.288172 2.314080 #> [22,] 2.482516 2.515248 2.547981 2.580714 2.613447 2.646180 2.678913 2.711646 #> [23,] 2.189896 2.217192 2.244487 2.271783 2.299078 2.326374 2.353669 2.380964 #> [24,] 2.035808 2.062446 2.089084 2.115721 2.142359 2.168996 2.195634 2.222272 #> [25,] 2.691361 2.724554 2.757746 2.790939 2.824131 2.857324 2.890516 2.923709 #> [26,] 2.627619 2.659767 2.691914 2.724062 2.756209 2.788356 2.820504 2.852651 #> [27,] 2.559328 2.591634 2.623940 2.656246 2.688553 2.720859 2.753165 2.785471 #> [28,] 2.537303 2.569895 2.602487 2.635079 2.667671 2.700263 2.732855 2.765447 #> [29,] 2.296624 2.326609 2.356595 2.386581 2.416567 2.446553 2.476539 2.506524 #> [30,] 2.565458 2.598976 2.632495 2.666013 2.699531 2.733049 2.766567 2.800085 #>          [,87]    [,88]    [,89]    [,90]    [,91]    [,92]    [,93]    [,94] #>  [1,] 2.935138 2.957282 2.979425 3.001568 3.023712 3.045855 3.067999 3.090142 #>  [2,] 3.156282 3.181334 3.206387 3.231439 3.256491 3.281543 3.306596 3.331648 #>  [3,] 2.988480 3.011073 3.033666 3.056259 3.078852 3.101445 3.124038 3.146631 #>  [4,] 2.923838 2.947036 2.970234 2.993432 3.016630 3.039828 3.063026 3.086224 #>  [5,] 2.782510 2.804434 2.826358 2.848282 2.870206 2.892129 2.914053 2.935977 #>  [6,] 3.336767 3.363224 3.389681 3.416139 3.442596 3.469053 3.495510 3.521967 #>  [7,] 3.425318 3.451892 3.478466 3.505040 3.531614 3.558187 3.584761 3.611335 #>  [8,] 3.052892 3.075801 3.098710 3.121619 3.144528 3.167437 3.190346 3.213255 #>  [9,] 2.705860 2.726092 2.746324 2.766556 2.786788 2.807020 2.827252 2.847484 #> [10,] 2.651867 2.672157 2.692447 2.712737 2.733027 2.753317 2.773607 2.793897 #> [11,] 1.647171 1.662633 1.678094 1.693556 1.709017 1.724478 1.739940 1.755401 #> [12,] 1.463979 1.475924 1.487868 1.499813 1.511758 1.523703 1.535648 1.547593 #> [13,] 1.685082 1.699232 1.713382 1.727532 1.741682 1.755832 1.769981 1.784131 #> [14,] 1.237459 1.248124 1.258789 1.269454 1.280120 1.290785 1.301450 1.312116 #> [15,] 1.579764 1.593962 1.608160 1.622358 1.636556 1.650754 1.664951 1.679149 #> [16,] 1.773308 1.788964 1.804621 1.820277 1.835934 1.851590 1.867247 1.882903 #> [17,] 1.620483 1.635335 1.650188 1.665041 1.679894 1.694746 1.709599 1.724452 #> [18,] 1.379300 1.392088 1.404876 1.417663 1.430451 1.443239 1.456027 1.468815 #> [19,] 1.682915 1.696429 1.709942 1.723456 1.736970 1.750484 1.763998 1.777512 #> [20,] 1.507526 1.520510 1.533493 1.546476 1.559460 1.572443 1.585426 1.598409 #> [21,] 2.339987 2.365894 2.391802 2.417709 2.443616 2.469524 2.495431 2.521338 #> [22,] 2.744379 2.777112 2.809844 2.842577 2.875310 2.908043 2.940776 2.973509 #> [23,] 2.408260 2.435555 2.462851 2.490146 2.517441 2.544737 2.572032 2.599328 #> [24,] 2.248909 2.275547 2.302184 2.328822 2.355460 2.382097 2.408735 2.435373 #> [25,] 2.956902 2.990094 3.023287 3.056479 3.089672 3.122864 3.156057 3.189249 #> [26,] 2.884798 2.916946 2.949093 2.981240 3.013388 3.045535 3.077682 3.109830 #> [27,] 2.817777 2.850083 2.882389 2.914695 2.947002 2.979308 3.011614 3.043920 #> [28,] 2.798039 2.830631 2.863223 2.895815 2.928407 2.960999 2.993591 3.026183 #> [29,] 2.536510 2.566496 2.596482 2.626468 2.656454 2.686439 2.716425 2.746411 #> [30,] 2.833604 2.867122 2.900640 2.934158 2.967676 3.001194 3.034713 3.068231 #>          [,95]    [,96]    [,97]    [,98]    [,99]   [,100]   [,101]   [,102] #>  [1,] 3.112285 3.134429 3.156572 3.178716 3.200859 3.223002 3.245146 3.267289 #>  [2,] 3.356700 3.381752 3.406805 3.431857 3.456909 3.481961 3.507014 3.532066 #>  [3,] 3.169224 3.191817 3.214410 3.237003 3.259597 3.282190 3.304783 3.327376 #>  [4,] 3.109422 3.132620 3.155818 3.179016 3.202214 3.225412 3.248610 3.271807 #>  [5,] 2.957901 2.979825 3.001749 3.023672 3.045596 3.067520 3.089444 3.111368 #>  [6,] 3.548424 3.574882 3.601339 3.627796 3.654253 3.680710 3.707168 3.733625 #>  [7,] 3.637909 3.664483 3.691057 3.717631 3.744205 3.770779 3.797353 3.823927 #>  [8,] 3.236164 3.259074 3.281983 3.304892 3.327801 3.350710 3.373619 3.396528 #>  [9,] 2.867716 2.887948 2.908181 2.928413 2.948645 2.968877 2.989109 3.009341 #> [10,] 2.814187 2.834477 2.854767 2.875057 2.895348 2.915638 2.935928 2.956218 #> [11,] 1.770863 1.786324 1.801785 1.817247 1.832708 1.848169 1.863631 1.879092 #> [12,] 1.559538 1.571482 1.583427 1.595372 1.607317 1.619262 1.631207 1.643151 #> [13,] 1.798281 1.812431 1.826581 1.840731 1.854881 1.869030 1.883180 1.897330 #> [14,] 1.322781 1.333446 1.344111 1.354777 1.365442 1.376107 1.386773 1.397438 #> [15,] 1.693347 1.707545 1.721743 1.735941 1.750139 1.764336 1.778534 1.792732 #> [16,] 1.898560 1.914216 1.929872 1.945529 1.961185 1.976842 1.992498 2.008155 #> [17,] 1.739305 1.754157 1.769010 1.783863 1.798716 1.813568 1.828421 1.843274 #> [18,] 1.481602 1.494390 1.507178 1.519966 1.532754 1.545541 1.558329 1.571117 #> [19,] 1.791026 1.804540 1.818053 1.831567 1.845081 1.858595 1.872109 1.885623 #> [20,] 1.611393 1.624376 1.637359 1.650342 1.663326 1.676309 1.689292 1.702275 #> [21,] 2.547245 2.573153 2.599060 2.624967 2.650875 2.676782 2.702689 2.728597 #> [22,] 3.006242 3.038975 3.071708 3.104440 3.137173 3.169906 3.202639 3.235372 #> [23,] 2.626623 2.653918 2.681214 2.708509 2.735805 2.763100 2.790395 2.817691 #> [24,] 2.462010 2.488648 2.515285 2.541923 2.568561 2.595198 2.621836 2.648473 #> [25,] 3.222442 3.255634 3.288827 3.322020 3.355212 3.388405 3.421597 3.454790 #> [26,] 3.141977 3.174124 3.206272 3.238419 3.270566 3.302714 3.334861 3.367008 #> [27,] 3.076226 3.108532 3.140838 3.173144 3.205450 3.237757 3.270063 3.302369 #> [28,] 3.058775 3.091367 3.123959 3.156551 3.189143 3.221735 3.254327 3.286919 #> [29,] 2.776397 2.806383 2.836369 2.866354 2.896340 2.926326 2.956312 2.986298 #> [30,] 3.101749 3.135267 3.168785 3.202303 3.235822 3.269340 3.302858 3.336376 #>         [,103]   [,104]   [,105]   [,106]   [,107]   [,108]   [,109]   [,110] #>  [1,] 3.289433 3.311576 3.333719 3.355863 3.378006 3.400150 3.422293 3.444436 #>  [2,] 3.557118 3.582170 3.607223 3.632275 3.657327 3.682379 3.707432 3.732484 #>  [3,] 3.349969 3.372562 3.395155 3.417748 3.440341 3.462934 3.485527 3.508120 #>  [4,] 3.295005 3.318203 3.341401 3.364599 3.387797 3.410995 3.434193 3.457391 #>  [5,] 3.133292 3.155215 3.177139 3.199063 3.220987 3.242911 3.264835 3.286759 #>  [6,] 3.760082 3.786539 3.812996 3.839454 3.865911 3.892368 3.918825 3.945282 #>  [7,] 3.850501 3.877075 3.903649 3.930223 3.956797 3.983371 4.009945 4.036519 #>  [8,] 3.419437 3.442346 3.465255 3.488164 3.511073 3.533982 3.556891 3.579800 #>  [9,] 3.029573 3.049805 3.070037 3.090269 3.110501 3.130733 3.150965 3.171197 #> [10,] 2.976508 2.996798 3.017088 3.037378 3.057668 3.077958 3.098248 3.118538 #> [11,] 1.894554 1.910015 1.925476 1.940938 1.956399 1.971861 1.987322 2.002783 #> [12,] 1.655096 1.667041 1.678986 1.690931 1.702876 1.714820 1.726765 1.738710 #> [13,] 1.911480 1.925630 1.939780 1.953929 1.968079 1.982229 1.996379 2.010529 #> [14,] 1.408103 1.418768 1.429434 1.440099 1.450764 1.461430 1.472095 1.482760 #> [15,] 1.806930 1.821128 1.835326 1.849524 1.863721 1.877919 1.892117 1.906315 #> [16,] 2.023811 2.039468 2.055124 2.070781 2.086437 2.102094 2.117750 2.133407 #> [17,] 1.858127 1.872979 1.887832 1.902685 1.917538 1.932390 1.947243 1.962096 #> [18,] 1.583905 1.596693 1.609480 1.622268 1.635056 1.647844 1.660632 1.673419 #> [19,] 1.899137 1.912650 1.926164 1.939678 1.953192 1.966706 1.980220 1.993734 #> [20,] 1.715259 1.728242 1.741225 1.754209 1.767192 1.780175 1.793158 1.806142 #> [21,] 2.754504 2.780411 2.806319 2.832226 2.858133 2.884041 2.909948 2.935855 #> [22,] 3.268105 3.300838 3.333571 3.366304 3.399036 3.431769 3.464502 3.497235 #> [23,] 2.844986 2.872282 2.899577 2.926872 2.954168 2.981463 3.008759 3.036054 #> [24,] 2.675111 2.701749 2.728386 2.755024 2.781661 2.808299 2.834937 2.861574 #> [25,] 3.487982 3.521175 3.554367 3.587560 3.620752 3.653945 3.687138 3.720330 #> [26,] 3.399156 3.431303 3.463450 3.495598 3.527745 3.559893 3.592040 3.624187 #> [27,] 3.334675 3.366981 3.399287 3.431593 3.463899 3.496205 3.528512 3.560818 #> [28,] 3.319511 3.352103 3.384695 3.417287 3.449879 3.482471 3.515063 3.547655 #> [29,] 3.016284 3.046269 3.076255 3.106241 3.136227 3.166213 3.196199 3.226184 #> [30,] 3.369894 3.403412 3.436930 3.470449 3.503967 3.537485 3.571003 3.604521 #>         [,111]   [,112]   [,113]   [,114]   [,115]   [,116]   [,117]   [,118] #>  [1,] 3.466580 3.488723 3.510867 3.533010 3.555153 3.577297 3.599440 3.621584 #>  [2,] 3.757536 3.782588 3.807641 3.832693 3.857745 3.882797 3.907850 3.932902 #>  [3,] 3.530713 3.553306 3.575899 3.598492 3.621085 3.643678 3.666271 3.688864 #>  [4,] 3.480589 3.503787 3.526985 3.550183 3.573381 3.596579 3.619776 3.642974 #>  [5,] 3.308682 3.330606 3.352530 3.374454 3.396378 3.418302 3.440225 3.462149 #>  [6,] 3.971740 3.998197 4.024654 4.051111 4.077568 4.104026 4.130483 4.156940 #>  [7,] 4.063093 4.089667 4.116241 4.142814 4.169388 4.195962 4.222536 4.249110 #>  [8,] 3.602709 3.625619 3.648528 3.671437 3.694346 3.717255 3.740164 3.763073 #>  [9,] 3.191429 3.211661 3.231894 3.252126 3.272358 3.292590 3.312822 3.333054 #> [10,] 3.138828 3.159118 3.179408 3.199698 3.219988 3.240278 3.260568 3.280858 #> [11,] 2.018245 2.033706 2.049168 2.064629 2.080090 2.095552 2.111013 2.126475 #> [12,] 1.750655 1.762600 1.774545 1.786490 1.798434 1.810379 1.822324 1.834269 #> [13,] 2.024679 2.038829 2.052978 2.067128 2.081278 2.095428 2.109578 2.123728 #> [14,] 1.493426 1.504091 1.514756 1.525421 1.536087 1.546752 1.557417 1.568083 #> [15,] 1.920513 1.934711 1.948909 1.963106 1.977304 1.991502 2.005700 2.019898 #> [16,] 2.149063 2.164719 2.180376 2.196032 2.211689 2.227345 2.243002 2.258658 #> [17,] 1.976949 1.991801 2.006654 2.021507 2.036360 2.051212 2.066065 2.080918 #> [18,] 1.686207 1.698995 1.711783 1.724571 1.737358 1.750146 1.762934 1.775722 #> [19,] 2.007247 2.020761 2.034275 2.047789 2.061303 2.074817 2.088331 2.101844 #> [20,] 1.819125 1.832108 1.845091 1.858075 1.871058 1.884041 1.897024 1.910008 #> [21,] 2.961763 2.987670 3.013577 3.039485 3.065392 3.091299 3.117207 3.143114 #> [22,] 3.529968 3.562701 3.595434 3.628167 3.660900 3.693632 3.726365 3.759098 #> [23,] 3.063350 3.090645 3.117940 3.145236 3.172531 3.199827 3.227122 3.254417 #> [24,] 2.888212 2.914849 2.941487 2.968125 2.994762 3.021400 3.048037 3.074675 #> [25,] 3.753523 3.786715 3.819908 3.853100 3.886293 3.919485 3.952678 3.985870 #> [26,] 3.656335 3.688482 3.720629 3.752777 3.784924 3.817071 3.849219 3.881366 #> [27,] 3.593124 3.625430 3.657736 3.690042 3.722348 3.754654 3.786961 3.819267 #> [28,] 3.580246 3.612838 3.645430 3.678022 3.710614 3.743206 3.775798 3.808390 #> [29,] 3.256170 3.286156 3.316142 3.346128 3.376114 3.406099 3.436085 3.466071 #> [30,] 3.638039 3.671558 3.705076 3.738594 3.772112 3.805630 3.839148 3.872667 #>         [,119]   [,120]   [,121]   [,122]   [,123]   [,124]   [,125]   [,126] #>  [1,] 3.643727 3.665871 3.688014 3.710157 3.732301 3.754444 3.776588 3.798731 #>  [2,] 3.957954 3.983006 4.008059 4.033111 4.058163 4.083216 4.108268 4.133320 #>  [3,] 3.711457 3.734050 3.756643 3.779237 3.801830 3.824423 3.847016 3.869609 #>  [4,] 3.666172 3.689370 3.712568 3.735766 3.758964 3.782162 3.805360 3.828558 #>  [5,] 3.484073 3.505997 3.527921 3.549845 3.571769 3.593692 3.615616 3.637540 #>  [6,] 4.183397 4.209854 4.236312 4.262769 4.289226 4.315683 4.342140 4.368598 #>  [7,] 4.275684 4.302258 4.328832 4.355406 4.381980 4.408554 4.435128 4.461702 #>  [8,] 3.785982 3.808891 3.831800 3.854709 3.877618 3.900527 3.923436 3.946345 #>  [9,] 3.353286 3.373518 3.393750 3.413982 3.434214 3.454446 3.474678 3.494910 #> [10,] 3.301149 3.321439 3.341729 3.362019 3.382309 3.402599 3.422889 3.443179 #> [11,] 2.141936 2.157397 2.172859 2.188320 2.203782 2.219243 2.234704 2.250166 #> [12,] 1.846214 1.858159 1.870103 1.882048 1.893993 1.905938 1.917883 1.929828 #> [13,] 2.137878 2.152027 2.166177 2.180327 2.194477 2.208627 2.222777 2.236927 #> [14,] 1.578748 1.589413 1.600078 1.610744 1.621409 1.632074 1.642740 1.653405 #> [15,] 2.034096 2.048294 2.062491 2.076689 2.090887 2.105085 2.119283 2.133481 #> [16,] 2.274315 2.289971 2.305628 2.321284 2.336941 2.352597 2.368253 2.383910 #> [17,] 2.095770 2.110623 2.125476 2.140329 2.155181 2.170034 2.184887 2.199740 #> [18,] 1.788510 1.801298 1.814085 1.826873 1.839661 1.852449 1.865237 1.878024 #> [19,] 2.115358 2.128872 2.142386 2.155900 2.169414 2.182928 2.196442 2.209955 #> [20,] 1.922991 1.935974 1.948958 1.961941 1.974924 1.987907 2.000891 2.013874 #> [21,] 3.169021 3.194929 3.220836 3.246743 3.272651 3.298558 3.324465 3.350373 #> [22,] 3.791831 3.824564 3.857297 3.890030 3.922763 3.955496 3.988228 4.020961 #> [23,] 3.281713 3.309008 3.336304 3.363599 3.390894 3.418190 3.445485 3.472781 #> [24,] 3.101313 3.127950 3.154588 3.181225 3.207863 3.234501 3.261138 3.287776 #> [25,] 4.019063 4.052255 4.085448 4.118641 4.151833 4.185026 4.218218 4.251411 #> [26,] 3.913513 3.945661 3.977808 4.009955 4.042103 4.074250 4.106397 4.138545 #> [27,] 3.851573 3.883879 3.916185 3.948491 3.980797 4.013103 4.045409 4.077716 #> [28,] 3.840982 3.873574 3.906166 3.938758 3.971350 4.003942 4.036534 4.069126 #> [29,] 3.496057 3.526043 3.556029 3.586014 3.616000 3.645986 3.675972 3.705958 #> [30,] 3.906185 3.939703 3.973221 4.006739 4.040257 4.073776 4.107294 4.140812 #>         [,127]   [,128]   [,129]   [,130]   [,131]   [,132]   [,133]   [,134] #>  [1,] 3.820874 3.843018 3.865161 3.887305 3.909448 3.931591 3.953735 3.975878 #>  [2,] 4.158372 4.183425 4.208477 4.233529 4.258581 4.283634 4.308686 4.333738 #>  [3,] 3.892202 3.914795 3.937388 3.959981 3.982574 4.005167 4.027760 4.050353 #>  [4,] 3.851756 3.874954 3.898152 3.921350 3.944547 3.967745 3.990943 4.014141 #>  [5,] 3.659464 3.681388 3.703312 3.725235 3.747159 3.769083 3.791007 3.812931 #>  [6,] 4.395055 4.421512 4.447969 4.474426 4.500884 4.527341 4.553798 4.580255 #>  [7,] 4.488276 4.514850 4.541424 4.567998 4.594572 4.621146 4.647720 4.674294 #>  [8,] 3.969255 3.992164 4.015073 4.037982 4.060891 4.083800 4.106709 4.129618 #>  [9,] 3.515142 3.535374 3.555607 3.575839 3.596071 3.616303 3.636535 3.656767 #> [10,] 3.463469 3.483759 3.504049 3.524339 3.544629 3.564919 3.585209 3.605499 #> [11,] 2.265627 2.281088 2.296550 2.312011 2.327473 2.342934 2.358395 2.373857 #> [12,] 1.941772 1.953717 1.965662 1.977607 1.989552 2.001497 2.013441 2.025386 #> [13,] 2.251076 2.265226 2.279376 2.293526 2.307676 2.321826 2.335975 2.350125 #> [14,] 1.664070 1.674736 1.685401 1.696066 1.706731 1.717397 1.728062 1.738727 #> [15,] 2.147679 2.161876 2.176074 2.190272 2.204470 2.218668 2.232866 2.247064 #> [16,] 2.399566 2.415223 2.430879 2.446536 2.462192 2.477849 2.493505 2.509162 #> [17,] 2.214592 2.229445 2.244298 2.259151 2.274003 2.288856 2.303709 2.318562 #> [18,] 1.890812 1.903600 1.916388 1.929176 1.941963 1.954751 1.967539 1.980327 #> [19,] 2.223469 2.236983 2.250497 2.264011 2.277525 2.291039 2.304552 2.318066 #> [20,] 2.026857 2.039840 2.052824 2.065807 2.078790 2.091773 2.104757 2.117740 #> [21,] 3.376280 3.402187 3.428095 3.454002 3.479909 3.505817 3.531724 3.557631 #> [22,] 4.053694 4.086427 4.119160 4.151893 4.184626 4.217359 4.250091 4.282824 #> [23,] 3.500076 3.527371 3.554667 3.581962 3.609258 3.636553 3.663848 3.691144 #> [24,] 3.314413 3.341051 3.367689 3.394326 3.420964 3.447601 3.474239 3.500877 #> [25,] 4.284603 4.317796 4.350988 4.384181 4.417373 4.450566 4.483759 4.516951 #> [26,] 4.170692 4.202839 4.234987 4.267134 4.299281 4.331429 4.363576 4.395724 #> [27,] 4.110022 4.142328 4.174634 4.206940 4.239246 4.271552 4.303858 4.336165 #> [28,] 4.101718 4.134310 4.166902 4.199494 4.232086 4.264678 4.297270 4.329862 #> [29,] 3.735944 3.765929 3.795915 3.825901 3.855887 3.885873 3.915859 3.945844 #> [30,] 4.174330 4.207848 4.241366 4.274884 4.308403 4.341921 4.375439 4.408957 #>         [,135]   [,136]   [,137]   [,138]   [,139]   [,140]   [,141]   [,142] #>  [1,] 3.998022 4.020165 4.042308 4.064452 4.086595 4.108739 4.130882 4.153025 #>  [2,] 4.358790 4.383843 4.408895 4.433947 4.458999 4.484052 4.509104 4.534156 #>  [3,] 4.072946 4.095539 4.118132 4.140725 4.163318 4.185911 4.208504 4.231097 #>  [4,] 4.037339 4.060537 4.083735 4.106933 4.130131 4.153329 4.176527 4.199725 #>  [5,] 3.834855 3.856779 3.878702 3.900626 3.922550 3.944474 3.966398 3.988322 #>  [6,] 4.606712 4.633170 4.659627 4.686084 4.712541 4.738998 4.765456 4.791913 #>  [7,] 4.700867 4.727441 4.754015 4.780589 4.807163 4.833737 4.860311 4.886885 #>  [8,] 4.152527 4.175436 4.198345 4.221254 4.244163 4.267072 4.289981 4.312890 #>  [9,] 3.676999 3.697231 3.717463 3.737695 3.757927 3.778159 3.798391 3.818623 #> [10,] 3.625789 3.646079 3.666369 3.686659 3.706950 3.727240 3.747530 3.767820 #> [11,] 2.389318 2.404780 2.420241 2.435702 2.451164 2.466625 2.482087 2.497548 #> [12,] 2.037331 2.049276 2.061221 2.073166 2.085111 2.097055 2.109000 2.120945 #> [13,] 2.364275 2.378425 2.392575 2.406725 2.420875 2.435024 2.449174 2.463324 #> [14,] 1.749393 1.760058 1.770723 1.781388 1.792054 1.802719 1.813384 1.824050 #> [15,] 2.261261 2.275459 2.289657 2.303855 2.318053 2.332251 2.346449 2.360646 #> [16,] 2.524818 2.540475 2.556131 2.571787 2.587444 2.603100 2.618757 2.634413 #> [17,] 2.333414 2.348267 2.363120 2.377973 2.392825 2.407678 2.422531 2.437384 #> [18,] 1.993115 2.005902 2.018690 2.031478 2.044266 2.057054 2.069841 2.082629 #> [19,] 2.331580 2.345094 2.358608 2.372122 2.385636 2.399149 2.412663 2.426177 #> [20,] 2.130723 2.143707 2.156690 2.169673 2.182656 2.195640 2.208623 2.221606 #> [21,] 3.583539 3.609446 3.635353 3.661260 3.687168 3.713075 3.738982 3.764890 #> [22,] 4.315557 4.348290 4.381023 4.413756 4.446489 4.479222 4.511955 4.544687 #> [23,] 3.718439 3.745735 3.773030 3.800326 3.827621 3.854916 3.882212 3.909507 #> [24,] 3.527514 3.554152 3.580789 3.607427 3.634065 3.660702 3.687340 3.713977 #> [25,] 4.550144 4.583336 4.616529 4.649721 4.682914 4.716106 4.749299 4.782491 #> [26,] 4.427871 4.460018 4.492166 4.524313 4.556460 4.588608 4.620755 4.652902 #> [27,] 4.368471 4.400777 4.433083 4.465389 4.497695 4.530001 4.562307 4.594613 #> [28,] 4.362454 4.395046 4.427638 4.460230 4.492822 4.525414 4.558006 4.590598 #> [29,] 3.975830 4.005816 4.035802 4.065788 4.095774 4.125759 4.155745 4.185731 #> [30,] 4.442475 4.475993 4.509512 4.543030 4.576548 4.610066 4.643584 4.677102 #>         [,143]   [,144]   [,145]   [,146]   [,147]   [,148]   [,149]   [,150] #>  [1,] 4.175169 4.197312 4.219456 4.241599 4.263742 4.285886 4.308029 4.330173 #>  [2,] 4.559208 4.584261 4.609313 4.634365 4.659417 4.684470 4.709522 4.734574 #>  [3,] 4.253690 4.276283 4.298877 4.321470 4.344063 4.366656 4.389249 4.411842 #>  [4,] 4.222923 4.246121 4.269319 4.292516 4.315714 4.338912 4.362110 4.385308 #>  [5,] 4.010245 4.032169 4.054093 4.076017 4.097941 4.119865 4.141789 4.163712 #>  [6,] 4.818370 4.844827 4.871284 4.897742 4.924199 4.950656 4.977113 5.003570 #>  [7,] 4.913459 4.940033 4.966607 4.993181 5.019755 5.046329 5.072903 5.099477 #>  [8,] 4.335800 4.358709 4.381618 4.404527 4.427436 4.450345 4.473254 4.496163 #>  [9,] 3.838855 3.859087 3.879320 3.899552 3.919784 3.940016 3.960248 3.980480 #> [10,] 3.788110 3.808400 3.828690 3.848980 3.869270 3.889560 3.909850 3.930140 #> [11,] 2.513009 2.528471 2.543932 2.559394 2.574855 2.590316 2.605778 2.621239 #> [12,] 2.132890 2.144835 2.156780 2.168724 2.180669 2.192614 2.204559 2.216504 #> [13,] 2.477474 2.491624 2.505774 2.519924 2.534073 2.548223 2.562373 2.576523 #> [14,] 1.834715 1.845380 1.856046 1.866711 1.877376 1.888041 1.898707 1.909372 #> [15,] 2.374844 2.389042 2.403240 2.417438 2.431636 2.445834 2.460031 2.474229 #> [16,] 2.650070 2.665726 2.681383 2.697039 2.712696 2.728352 2.744009 2.759665 #> [17,] 2.452236 2.467089 2.481942 2.496795 2.511647 2.526500 2.541353 2.556205 #> [18,] 2.095417 2.108205 2.120993 2.133780 2.146568 2.159356 2.172144 2.184932 #> [19,] 2.439691 2.453205 2.466719 2.480233 2.493747 2.507260 2.520774 2.534288 #> [20,] 2.234589 2.247573 2.260556 2.273539 2.286523 2.299506 2.312489 2.325472 #> [21,] 3.790797 3.816704 3.842612 3.868519 3.894426 3.920334 3.946241 3.972148 #> [22,] 4.577420 4.610153 4.642886 4.675619 4.708352 4.741085 4.773818 4.806551 #> [23,] 3.936803 3.964098 3.991393 4.018689 4.045984 4.073280 4.100575 4.127870 #> [24,] 3.740615 3.767253 3.793890 3.820528 3.847165 3.873803 3.900441 3.927078 #> [25,] 4.815684 4.848877 4.882069 4.915262 4.948454 4.981647 5.014839 5.048032 #> [26,] 4.685050 4.717197 4.749344 4.781492 4.813639 4.845786 4.877934 4.910081 #> [27,] 4.626920 4.659226 4.691532 4.723838 4.756144 4.788450 4.820756 4.853062 #> [28,] 4.623190 4.655782 4.688374 4.720966 4.753558 4.786150 4.818742 4.851334 #> [29,] 4.215717 4.245703 4.275688 4.305674 4.335660 4.365646 4.395632 4.425618 #> [30,] 4.710621 4.744139 4.777657 4.811175 4.844693 4.878211 4.911730 4.945248 #>         [,151]   [,152]   [,153]   [,154]   [,155]   [,156]   [,157]   [,158] #>  [1,] 4.352316 4.374460 4.396603 4.418746 4.440890 4.463033 4.485177 4.507320 #>  [2,] 4.759626 4.784679 4.809731 4.834783 4.859835 4.884888 4.909940 4.934992 #>  [3,] 4.434435 4.457028 4.479621 4.502214 4.524807 4.547400 4.569993 4.592586 #>  [4,] 4.408506 4.431704 4.454902 4.478100 4.501298 4.524496 4.547694 4.570892 #>  [5,] 4.185636 4.207560 4.229484 4.251408 4.273332 4.295255 4.317179 4.339103 #>  [6,] 5.030028 5.056485 5.082942 5.109399 5.135856 5.162314 5.188771 5.215228 #>  [7,] 5.126051 5.152625 5.179199 5.205773 5.232347 5.258921 5.285494 5.312068 #>  [8,] 4.519072 4.541981 4.564890 4.587799 4.610708 4.633617 4.656526 4.679436 #>  [9,] 4.000712 4.020944 4.041176 4.061408 4.081640 4.101872 4.122104 4.142336 #> [10,] 3.950430 3.970720 3.991010 4.011300 4.031590 4.051880 4.072170 4.092460 #> [11,] 2.636701 2.652162 2.667623 2.683085 2.698546 2.714007 2.729469 2.744930 #> [12,] 2.228449 2.240393 2.252338 2.264283 2.276228 2.288173 2.300118 2.312062 #> [13,] 2.590673 2.604823 2.618972 2.633122 2.647272 2.661422 2.675572 2.689722 #> [14,] 1.920037 1.930703 1.941368 1.952033 1.962698 1.973364 1.984029 1.994694 #> [15,] 2.488427 2.502625 2.516823 2.531021 2.545219 2.559416 2.573614 2.587812 #> [16,] 2.775322 2.790978 2.806634 2.822291 2.837947 2.853604 2.869260 2.884917 #> [17,] 2.571058 2.585911 2.600764 2.615616 2.630469 2.645322 2.660175 2.675027 #> [18,] 2.197720 2.210507 2.223295 2.236083 2.248871 2.261659 2.274446 2.287234 #> [19,] 2.547802 2.561316 2.574830 2.588344 2.601857 2.615371 2.628885 2.642399 #> [20,] 2.338456 2.351439 2.364422 2.377405 2.390389 2.403372 2.416355 2.429338 #> [21,] 3.998056 4.023963 4.049870 4.075778 4.101685 4.127592 4.153500 4.179407 #> [22,] 4.839283 4.872016 4.904749 4.937482 4.970215 5.002948 5.035681 5.068414 #> [23,] 4.155166 4.182461 4.209757 4.237052 4.264347 4.291643 4.318938 4.346234 #> [24,] 3.953716 3.980353 4.006991 4.033629 4.060266 4.086904 4.113542 4.140179 #> [25,] 5.081224 5.114417 5.147609 5.180802 5.213995 5.247187 5.280380 5.313572 #> [26,] 4.942228 4.974376 5.006523 5.038670 5.070818 5.102965 5.135112 5.167260 #> [27,] 4.885368 4.917675 4.949981 4.982287 5.014593 5.046899 5.079205 5.111511 #> [28,] 4.883926 4.916518 4.949110 4.981702 5.014294 5.046885 5.079477 5.112069 #> [29,] 4.455603 4.485589 4.515575 4.545561 4.575547 4.605533 4.635518 4.665504 #> [30,] 4.978766 5.012284 5.045802 5.079320 5.112839 5.146357 5.179875 5.213393 #>         [,159]   [,160]   [,161]   [,162]   [,163]   [,164]   [,165]   [,166] #>  [1,] 4.529463 4.551607 4.573750 4.595894 4.618037 4.640180 4.662324 4.684467 #>  [2,] 4.960045 4.985097 5.010149 5.035201 5.060254 5.085306 5.110358 5.135410 #>  [3,] 4.615179 4.637772 4.660365 4.682958 4.705551 4.728144 4.750737 4.773330 #>  [4,] 4.594090 4.617287 4.640485 4.663683 4.686881 4.710079 4.733277 4.756475 #>  [5,] 4.361027 4.382951 4.404875 4.426798 4.448722 4.470646 4.492570 4.514494 #>  [6,] 5.241685 5.268142 5.294599 5.321057 5.347514 5.373971 5.400428 5.426885 #>  [7,] 5.338642 5.365216 5.391790 5.418364 5.444938 5.471512 5.498086 5.524660 #>  [8,] 4.702345 4.725254 4.748163 4.771072 4.793981 4.816890 4.839799 4.862708 #>  [9,] 4.162568 4.182800 4.203032 4.223265 4.243497 4.263729 4.283961 4.304193 #> [10,] 4.112751 4.133041 4.153331 4.173621 4.193911 4.214201 4.234491 4.254781 #> [11,] 2.760392 2.775853 2.791314 2.806776 2.822237 2.837699 2.853160 2.868621 #> [12,] 2.324007 2.335952 2.347897 2.359842 2.371787 2.383732 2.395676 2.407621 #> [13,] 2.703872 2.718021 2.732171 2.746321 2.760471 2.774621 2.788771 2.802921 #> [14,] 2.005360 2.016025 2.026690 2.037355 2.048021 2.058686 2.069351 2.080017 #> [15,] 2.602010 2.616208 2.630406 2.644604 2.658801 2.672999 2.687197 2.701395 #> [16,] 2.900573 2.916230 2.931886 2.947543 2.963199 2.978856 2.994512 3.010168 #> [17,] 2.689880 2.704733 2.719586 2.734438 2.749291 2.764144 2.778997 2.793849 #> [18,] 2.300022 2.312810 2.325598 2.338385 2.351173 2.363961 2.376749 2.389537 #> [19,] 2.655913 2.669427 2.682941 2.696454 2.709968 2.723482 2.736996 2.750510 #> [20,] 2.442322 2.455305 2.468288 2.481272 2.494255 2.507238 2.520221 2.533205 #> [21,] 4.205314 4.231222 4.257129 4.283036 4.308944 4.334851 4.360758 4.386666 #> [22,] 5.101147 5.133879 5.166612 5.199345 5.232078 5.264811 5.297544 5.330277 #> [23,] 4.373529 4.400824 4.428120 4.455415 4.482711 4.510006 4.537302 4.564597 #> [24,] 4.166817 4.193454 4.220092 4.246730 4.273367 4.300005 4.326642 4.353280 #> [25,] 5.346765 5.379957 5.413150 5.446342 5.479535 5.512727 5.545920 5.579113 #> [26,] 5.199407 5.231555 5.263702 5.295849 5.327997 5.360144 5.392291 5.424439 #> [27,] 5.143817 5.176124 5.208430 5.240736 5.273042 5.305348 5.337654 5.369960 #> [28,] 5.144661 5.177253 5.209845 5.242437 5.275029 5.307621 5.340213 5.372805 #> [29,] 4.695490 4.725476 4.755462 4.785448 4.815433 4.845419 4.875405 4.905391 #> [30,] 5.246911 5.280429 5.313947 5.347466 5.380984 5.414502 5.448020 5.481538 #>         [,167]   [,168]   [,169]   [,170]   [,171]   [,172]   [,173]   [,174] #>  [1,] 4.706611 4.728754 4.750897 4.773041 4.795184 4.817328 4.839471 4.861614 #>  [2,] 5.160463 5.185515 5.210567 5.235619 5.260672 5.285724 5.310776 5.335828 #>  [3,] 4.795923 4.818517 4.841110 4.863703 4.886296 4.908889 4.931482 4.954075 #>  [4,] 4.779673 4.802871 4.826069 4.849267 4.872465 4.895663 4.918861 4.942059 #>  [5,] 4.536418 4.558342 4.580265 4.602189 4.624113 4.646037 4.667961 4.689885 #>  [6,] 5.453343 5.479800 5.506257 5.532714 5.559171 5.585629 5.612086 5.638543 #>  [7,] 5.551234 5.577808 5.604382 5.630956 5.657530 5.684104 5.710678 5.737252 #>  [8,] 4.885617 4.908526 4.931435 4.954344 4.977253 5.000162 5.023071 5.045981 #>  [9,] 4.324425 4.344657 4.364889 4.385121 4.405353 4.425585 4.445817 4.466049 #> [10,] 4.275071 4.295361 4.315651 4.335941 4.356231 4.376521 4.396811 4.417101 #> [11,] 2.884083 2.899544 2.915006 2.930467 2.945928 2.961390 2.976851 2.992313 #> [12,] 2.419566 2.431511 2.443456 2.455401 2.467345 2.479290 2.491235 2.503180 #> [13,] 2.817070 2.831220 2.845370 2.859520 2.873670 2.887820 2.901970 2.916119 #> [14,] 2.090682 2.101347 2.112013 2.122678 2.133343 2.144008 2.154674 2.165339 #> [15,] 2.715593 2.729791 2.743989 2.758186 2.772384 2.786582 2.800780 2.814978 #> [16,] 3.025825 3.041481 3.057138 3.072794 3.088451 3.104107 3.119764 3.135420 #> [17,] 2.808702 2.823555 2.838408 2.853260 2.868113 2.882966 2.897819 2.912671 #> [18,] 2.402324 2.415112 2.427900 2.440688 2.453476 2.466263 2.479051 2.491839 #> [19,] 2.764024 2.777538 2.791051 2.804565 2.818079 2.831593 2.845107 2.858621 #> [20,] 2.546188 2.559171 2.572154 2.585138 2.598121 2.611104 2.624087 2.637071 #> [21,] 4.412573 4.438480 4.464388 4.490295 4.516202 4.542110 4.568017 4.593924 #> [22,] 5.363010 5.395743 5.428475 5.461208 5.493941 5.526674 5.559407 5.592140 #> [23,] 4.591892 4.619188 4.646483 4.673779 4.701074 4.728369 4.755665 4.782960 #> [24,] 4.379918 4.406555 4.433193 4.459830 4.486468 4.513106 4.539743 4.566381 #> [25,] 5.612305 5.645498 5.678690 5.711883 5.745075 5.778268 5.811460 5.844653 #> [26,] 5.456586 5.488733 5.520881 5.553028 5.585175 5.617323 5.649470 5.681617 #> [27,] 5.402266 5.434572 5.466879 5.499185 5.531491 5.563797 5.596103 5.628409 #> [28,] 5.405397 5.437989 5.470581 5.503173 5.535765 5.568357 5.600949 5.633541 #> [29,] 4.935377 4.965363 4.995348 5.025334 5.055320 5.085306 5.115292 5.145278 #> [30,] 5.515056 5.548575 5.582093 5.615611 5.649129 5.682647 5.716165 5.749684 #>         [,175]   [,176]   [,177]   [,178]   [,179]   [,180]   [,181]   [,182] #>  [1,] 4.883758 4.905901 4.928045 4.950188 4.972331 4.994475 5.016618 5.038762 #>  [2,] 5.360881 5.385933 5.410985 5.436037 5.461090 5.486142 5.511194 5.536246 #>  [3,] 4.976668 4.999261 5.021854 5.044447 5.067040 5.089633 5.112226 5.134819 #>  [4,] 4.965256 4.988454 5.011652 5.034850 5.058048 5.081246 5.104444 5.127642 #>  [5,] 4.711808 4.733732 4.755656 4.777580 4.799504 4.821428 4.843352 4.865275 #>  [6,] 5.665000 5.691457 5.717915 5.744372 5.770829 5.797286 5.823743 5.850201 #>  [7,] 5.763826 5.790400 5.816974 5.843548 5.870121 5.896695 5.923269 5.949843 #>  [8,] 5.068890 5.091799 5.114708 5.137617 5.160526 5.183435 5.206344 5.229253 #>  [9,] 4.486281 4.506513 4.526745 4.546978 4.567210 4.587442 4.607674 4.627906 #> [10,] 4.437391 4.457681 4.477971 4.498261 4.518552 4.538842 4.559132 4.579422 #> [11,] 3.007774 3.023235 3.038697 3.054158 3.069620 3.085081 3.100542 3.116004 #> [12,] 2.515125 2.527070 2.539014 2.550959 2.562904 2.574849 2.586794 2.598739 #> [13,] 2.930269 2.944419 2.958569 2.972719 2.986869 3.001018 3.015168 3.029318 #> [14,] 2.176004 2.186670 2.197335 2.208000 2.218665 2.229331 2.239996 2.250661 #> [15,] 2.829176 2.843374 2.857572 2.871769 2.885967 2.900165 2.914363 2.928561 #> [16,] 3.151077 3.166733 3.182390 3.198046 3.213702 3.229359 3.245015 3.260672 #> [17,] 2.927524 2.942377 2.957230 2.972082 2.986935 3.001788 3.016641 3.031493 #> [18,] 2.504627 2.517415 2.530202 2.542990 2.555778 2.568566 2.581354 2.594142 #> [19,] 2.872135 2.885649 2.899162 2.912676 2.926190 2.939704 2.953218 2.966732 #> [20,] 2.650054 2.663037 2.676021 2.689004 2.701987 2.714970 2.727954 2.740937 #> [21,] 4.619832 4.645739 4.671646 4.697553 4.723461 4.749368 4.775275 4.801183 #> [22,] 5.624873 5.657606 5.690339 5.723071 5.755804 5.788537 5.821270 5.854003 #> [23,] 4.810256 4.837551 4.864846 4.892142 4.919437 4.946733 4.974028 5.001323 #> [24,] 4.593018 4.619656 4.646294 4.672931 4.699569 4.726206 4.752844 4.779482 #> [25,] 5.877845 5.911038 5.944231 5.977423 6.010616 6.043808 6.077001 6.110193 #> [26,] 5.713765 5.745912 5.778059 5.810207 5.842354 5.874501 5.906649 5.938796 #> [27,] 5.660715 5.693021 5.725328 5.757634 5.789940 5.822246 5.854552 5.886858 #> [28,] 5.666133 5.698725 5.731317 5.763909 5.796501 5.829093 5.861685 5.894277 #> [29,] 5.175263 5.205249 5.235235 5.265221 5.295207 5.325193 5.355178 5.385164 #> [30,] 5.783202 5.816720 5.850238 5.883756 5.917274 5.950793 5.984311 6.017829 #>         [,183]   [,184]   [,185]   [,186]   [,187]   [,188]   [,189]   [,190] #>  [1,] 5.060905 5.083049 5.105192 5.127335 5.149479 5.171622 5.193766 5.215909 #>  [2,] 5.561299 5.586351 5.611403 5.636455 5.661508 5.686560 5.711612 5.736664 #>  [3,] 5.157412 5.180005 5.202598 5.225191 5.247784 5.270377 5.292970 5.315563 #>  [4,] 5.150840 5.174038 5.197236 5.220434 5.243632 5.266830 5.290028 5.313225 #>  [5,] 4.887199 4.909123 4.931047 4.952971 4.974895 4.996818 5.018742 5.040666 #>  [6,] 5.876658 5.903115 5.929572 5.956029 5.982487 6.008944 6.035401 6.061858 #>  [7,] 5.976417 6.002991 6.029565 6.056139 6.082713 6.109287 6.135861 6.162435 #>  [8,] 5.252162 5.275071 5.297980 5.320889 5.343798 5.366707 5.389616 5.412526 #>  [9,] 4.648138 4.668370 4.688602 4.708834 4.729066 4.749298 4.769530 4.789762 #> [10,] 4.599712 4.620002 4.640292 4.660582 4.680872 4.701162 4.721452 4.741742 #> [11,] 3.131465 3.146926 3.162388 3.177849 3.193311 3.208772 3.224233 3.239695 #> [12,] 2.610683 2.622628 2.634573 2.646518 2.658463 2.670408 2.682353 2.694297 #> [13,] 3.043468 3.057618 3.071768 3.085918 3.100067 3.114217 3.128367 3.142517 #> [14,] 2.261327 2.271992 2.282657 2.293323 2.303988 2.314653 2.325318 2.335984 #> [15,] 2.942759 2.956957 2.971154 2.985352 2.999550 3.013748 3.027946 3.042144 #> [16,] 3.276328 3.291985 3.307641 3.323298 3.338954 3.354611 3.370267 3.385924 #> [17,] 3.046346 3.061199 3.076051 3.090904 3.105757 3.120610 3.135462 3.150315 #> [18,] 2.606929 2.619717 2.632505 2.645293 2.658081 2.670868 2.683656 2.696444 #> [19,] 2.980246 2.993759 3.007273 3.020787 3.034301 3.047815 3.061329 3.074843 #> [20,] 2.753920 2.766903 2.779887 2.792870 2.805853 2.818836 2.831820 2.844803 #> [21,] 4.827090 4.852997 4.878905 4.904812 4.930719 4.956627 4.982534 5.008441 #> [22,] 5.886736 5.919469 5.952202 5.984934 6.017667 6.050400 6.083133 6.115866 #> [23,] 5.028619 5.055914 5.083210 5.110505 5.137800 5.165096 5.192391 5.219687 #> [24,] 4.806119 4.832757 4.859394 4.886032 4.912670 4.939307 4.965945 4.992582 #> [25,] 6.143386 6.176578 6.209771 6.242963 6.276156 6.309349 6.342541 6.375734 #> [26,] 5.970943 6.003091 6.035238 6.067386 6.099533 6.131680 6.163828 6.195975 #> [27,] 5.919164 5.951470 5.983776 6.016083 6.048389 6.080695 6.113001 6.145307 #> [28,] 5.926869 5.959461 5.992053 6.024645 6.057237 6.089829 6.122421 6.155013 #> [29,] 5.415150 5.445136 5.475122 5.505108 5.535093 5.565079 5.595065 5.625051 #> [30,] 6.051347 6.084865 6.118383 6.151902 6.185420 6.218938 6.252456 6.285974 #>         [,191]   [,192]   [,193]   [,194]   [,195]   [,196]   [,197]   [,198] #>  [1,] 5.238052 5.260196 5.282339 5.304483 5.326626 5.348769 5.370913 5.393056 #>  [2,] 5.761717 5.786769 5.811821 5.836874 5.861926 5.886978 5.912030 5.937083 #>  [3,] 5.338157 5.360750 5.383343 5.405936 5.428529 5.451122 5.473715 5.496308 #>  [4,] 5.336423 5.359621 5.382819 5.406017 5.429215 5.452413 5.475611 5.498809 #>  [5,] 5.062590 5.084514 5.106438 5.128362 5.150285 5.172209 5.194133 5.216057 #>  [6,] 6.088315 6.114773 6.141230 6.167687 6.194144 6.220601 6.247059 6.273516 #>  [7,] 6.189009 6.215583 6.242157 6.268731 6.295305 6.321879 6.348453 6.375027 #>  [8,] 5.435435 5.458344 5.481253 5.504162 5.527071 5.549980 5.572889 5.595798 #>  [9,] 4.809994 4.830226 4.850458 4.870691 4.890923 4.911155 4.931387 4.951619 #> [10,] 4.762032 4.782322 4.802612 4.822902 4.843192 4.863482 4.883772 4.904062 #> [11,] 3.255156 3.270618 3.286079 3.301540 3.317002 3.332463 3.347925 3.363386 #> [12,] 2.706242 2.718187 2.730132 2.742077 2.754022 2.765966 2.777911 2.789856 #> [13,] 3.156667 3.170817 3.184967 3.199116 3.213266 3.227416 3.241566 3.255716 #> [14,] 2.346649 2.357314 2.367980 2.378645 2.389310 2.399975 2.410641 2.421306 #> [15,] 3.056342 3.070539 3.084737 3.098935 3.113133 3.127331 3.141529 3.155727 #> [16,] 3.401580 3.417237 3.432893 3.448549 3.464206 3.479862 3.495519 3.511175 #> [17,] 3.165168 3.180021 3.194873 3.209726 3.224579 3.239432 3.254284 3.269137 #> [18,] 2.709232 2.722020 2.734807 2.747595 2.760383 2.773171 2.785959 2.798746 #> [19,] 3.088356 3.101870 3.115384 3.128898 3.142412 3.155926 3.169440 3.182954 #> [20,] 2.857786 2.870770 2.883753 2.896736 2.909719 2.922703 2.935686 2.948669 #> [21,] 5.034349 5.060256 5.086163 5.112071 5.137978 5.163885 5.189793 5.215700 #> [22,] 6.148599 6.181332 6.214065 6.246798 6.279530 6.312263 6.344996 6.377729 #> [23,] 5.246982 5.274278 5.301573 5.328868 5.356164 5.383459 5.410755 5.438050 #> [24,] 5.019220 5.045858 5.072495 5.099133 5.125770 5.152408 5.179046 5.205683 #> [25,] 6.408926 6.442119 6.475311 6.508504 6.541696 6.574889 6.608081 6.641274 #> [26,] 6.228122 6.260270 6.292417 6.324564 6.356712 6.388859 6.421006 6.453154 #> [27,] 6.177613 6.209919 6.242225 6.274532 6.306838 6.339144 6.371450 6.403756 #> [28,] 6.187605 6.220197 6.252789 6.285381 6.317973 6.350565 6.383157 6.415749 #> [29,] 5.655037 5.685023 5.715008 5.744994 5.774980 5.804966 5.834952 5.864938 #> [30,] 6.319492 6.353010 6.386529 6.420047 6.453565 6.487083 6.520601 6.554119 #>         [,199]   [,200] #>  [1,] 5.415200 5.437343 #>  [2,] 5.962135 5.987187 #>  [3,] 5.518901 5.541494 #>  [4,] 5.522007 5.545205 #>  [5,] 5.237981 5.259905 #>  [6,] 6.299973 6.326430 #>  [7,] 6.401601 6.428174 #>  [8,] 5.618707 5.641616 #>  [9,] 4.971851 4.992083 #> [10,] 4.924353 4.944643 #> [11,] 3.378847 3.394309 #> [12,] 2.801801 2.813746 #> [13,] 3.269866 3.284016 #> [14,] 2.431971 2.442637 #> [15,] 3.169924 3.184122 #> [16,] 3.526832 3.542488 #> [17,] 3.283990 3.298843 #> [18,] 2.811534 2.824322 #> [19,] 3.196467 3.209981 #> [20,] 2.961652 2.974636 #> [21,] 5.241607 5.267515 #> [22,] 6.410462 6.443195 #> [23,] 5.465345 5.492641 #> [24,] 5.232321 5.258958 #> [25,] 6.674467 6.707659 #> [26,] 6.485301 6.517448 #> [27,] 6.436062 6.468368 #> [28,] 6.448341 6.480932 #> [29,] 5.894923 5.924909 #> [30,] 6.587638 6.621156 #>  #> $n_clusters #> [1] 2 #>  #> $memberships #>  [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 #>  #> $distances_to_center #>  [1] 1.435690e-07 8.772803e-06 3.146653e-06 1.102877e-05 2.000723e-06 #>  [6] 4.401335e-06 1.163654e-06 1.566382e-05 1.581490e-06 5.370269e-06 #> [11] 3.493894e-06 1.493107e-05 3.060315e-07 2.249079e-06 9.439335e-08 #> [16] 6.040630e-07 1.015906e-05 3.737756e-07 1.025968e-05 3.212466e-06 #> [21] 2.138381e-05 9.563699e-05 2.243895e-06 1.402764e-06 1.470732e-05 #> [26] 4.079484e-05 2.272736e-05 2.521653e-05 1.602216e-06 5.209759e-06 #>  #> $silhouettes #>  [1] 0.9998670 0.9996938 0.9998243 0.9993937 0.9998277 0.9997924 0.9998357 #>  [8] 0.9995409 0.9999025 0.9998513 0.9999301 0.9999018 0.9999629 0.9999643 #> [15] 0.9999654 0.9999516 0.9998826 0.9999729 0.9999020 0.9999541 0.9998198 #> [22] 0.9994794 0.9998915 0.9998993 0.9998286 0.9997110 0.9997933 0.9997820 #> [29] 0.9998919 0.9998688 #>  #> $amplitude_variation #> [1] 1.364288e-08 #>  #> $total_variation #> [1] 0.6714711 #>  #> $n_iterations #> [1] 2 #>  #> $call_name #> [1] \"fdakmeans\" #>  #> $call_args #> $call_args$x #> simulated30$x #>  #> $call_args$y #> simulated30$y #>  #> $call_args$n_clusters #> [1] 2 #>  #> $call_args$seeds #> [1]  1 21 #>  #> $call_args$seeding_strategy #> [1] \"kmeans++\" #>  #> $call_args$warping_class #> [1] \"affine\" #>  #> $call_args$centroid_type #> [1] \"mean\" #>  #> $call_args$metric #> [1] \"pearson\" #>  #> $call_args$cluster_on_phase #> [1] FALSE #>  #> $call_args$use_verbose #> [1] TRUE #>  #> $call_args$warping_options #> c(0.15, 0.15) #>  #> $call_args$maximum_number_of_iterations #> [1] 100 #>  #> $call_args$number_of_threads #> [1] 1 #>  #> $call_args$parallel_method #> [1] 0 #>  #> $call_args$distance_relative_tolerance #> [1] 0.001 #>  #> $call_args$use_fence #> [1] FALSE #>  #> $call_args$check_total_dissimilarity #> [1] TRUE #>  #> $call_args$compute_overall_center #> [1] FALSE #>  #> $call_args$add_silhouettes #> [1] TRUE #>  #>  #> attr(,\"class\") #> [1] \"caps\" \"list\" is_caps(sim30_caps) #> [1] TRUE"},{"path":"/reference/compare_caps.html","id":null,"dir":"Reference","previous_headings":"","what":"Generates results of multiple clustering strategies — compare_caps","title":"Generates results of multiple clustering strategies — compare_caps","text":"function searches clusters input data set using different strategies generates object class mcaps stores multiple objects class caps. helper function facilitate comparison clustering methods choice optimal one.","code":""},{"path":"/reference/compare_caps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generates results of multiple clustering strategies — compare_caps","text":"","code":"compare_caps(   x,   y,   n_clusters = 1:5,   metric = c(\"l2\", \"pearson\"),   clustering_method = c(\"kmeans\", \"hclust-complete\", \"hclust-average\", \"hclust-single\",     \"dbscan\"),   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   centroid_type = c(\"mean\", \"medoid\", \"median\", \"lowess\", \"poly\"),   cluster_on_phase = FALSE )"},{"path":"/reference/compare_caps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generates results of multiple clustering strategies — compare_caps","text":"x numeric vector length \\(M\\) numeric matrix shape \\(N \\times M\\) object class funData::funData. numeric vector matrix, specifies grid(s) size \\(M\\) \\(N\\) curves observed. object class funData::funData, contains whole functional data set y argument used. y Either numeric matrix shape \\(N \\times M\\) numeric array shape \\(N \\times L \\times M\\) object class fda::fd. numeric matrix array, specifies \\(N\\)-sample \\(L\\)-dimensional curves observed grids size \\(M\\). object class fda::fd, contains necessary information functional data set able evaluate user-defined grids. n_clusters integer vector specifying set clustering partitions create. Defaults 1:5. metric string specifying metric used compare curves. Choices \"l2\" \"pearson\". Defaults \"l2\". Used warping_class != \"srsf\". boundary-preserving warping class, L2 distance SRSFs original curves used. clustering_method character vector specifying one clustering methods fit. Choices \"kmeans\", \"hclust-complete\", \"hclust-average\", \"hclust-single\" \"dbscan\". Defaults . warping_class character vector specifying one classes warping functions use curve alignment. Choices \"affine\", \"dilation\", \"none\", \"shift\" \"srsf\". Defaults . centroid_type character vector specifying one ways compute centroids. Choices \"mean\", \"medoid\", \"median\", \"lowess\" \"poly\". Defaults . cluster_on_phase boolean specifying whether clustering based phase variation amplitude variation. Defaults FALSE implies amplitude variation.","code":""},{"path":"/reference/compare_caps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generates results of multiple clustering strategies — compare_caps","text":"object class mcaps tibble::tibble storing objects class caps correspondence combination possible choices input arguments.","code":""},{"path":"/reference/compare_caps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generates results of multiple clustering strategies — compare_caps","text":"","code":"#---------------------------------- # Compare k-means results with k = 1, 2, 3, 4, 5 using mean centroid and # various warping classes. if (FALSE) { sim30_mcaps <- compare_caps(   x = simulated30_sub$x,   y = simulated30_sub$y,   warping_class = c(\"none\", \"shift\", \"dilation\", \"affine\"),   clustering_method = \"kmeans\",   centroid_type = \"mean\" ) }  #---------------------------------- # Then visualize the results # Either with ggplot2 via ggplot2::autoplot(sim30_mcaps) # or using graphics::plot() # You can visualize the WSS values: plot(sim30_mcaps, validation_criterion = \"wss\", what = \"mean\")  plot(sim30_mcaps, validation_criterion = \"wss\", what = \"distribution\")  # Or the average silhouette values: plot(sim30_mcaps, validation_criterion = \"silhouette\", what = \"mean\")  plot(sim30_mcaps, validation_criterion = \"silhouette\", what = \"distribution\")"},{"path":"/reference/diagnostic_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","title":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","text":"function plots values distance center silhouette observation. Observations ordered within cluster decreasing value silhouette.","code":""},{"path":"/reference/diagnostic_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","text":"","code":"diagnostic_plot(x)"},{"path":"/reference/diagnostic_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","text":"x object class caps.","code":""},{"path":"/reference/diagnostic_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","text":"object class ggplot2::ggplot.","code":""},{"path":"/reference/diagnostic_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","text":"","code":"diagnostic_plot(sim30_caps)"},{"path":"/reference/fdacluster-package.html","id":null,"dir":"Reference","previous_headings":"","what":"fdacluster: Joint Clustering and Alignment of Functional Data — fdacluster-package","title":"fdacluster: Joint Clustering and Alignment of Functional Data — fdacluster-package","text":"Implementations k-means, hierarchical agglomerative DBSCAN clustering methods functional data allows jointly aligning clustering curves. supports functional data defined one-dimensional domains possibly evaluating multivariate codomains. supports functional data defined arrays also via 'fd' 'funData' classes functional data defined 'fda' 'funData' packages respectively. currently supports shift, dilation affine warping functions functional data defined real line uses SRSF framework handle boundary-preserving warping functional data defined specific interval. Main reference k-means algorithm: Sangalli L.M., Secchi P., Vantini S., Vitelli V. (2010) \"k-mean alignment curve clustering\" doi:10.1016/j.csda.2009.12.008 . Main reference SRSF framework: Tucker, J. D., Wu, W., & Srivastava, . (2013) \"Generative models functional data using phase amplitude separation\" doi:10.1016/j.csda.2012.12.001 .","code":""},{"path":"/reference/fdacluster-package.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"fdacluster: Joint Clustering and Alignment of Functional Data — fdacluster-package","text":"Arthur, D., S. Vassilvitskii. 2007. “K-Means++ Advantages Careful Seeding.” Proceedings Eighteenth Annual ACM-SIAM Symposium Discrete Algorithms, 1027–35. Marron, J. S., J. O. Ramsay, L. M. Sangalli, . Srivastava. 2014. “Statistics Time Warpings Phase Variations.” Marron, J. S., J. O. Ramsay, L. M. Sangalli, . Srivastava. 2015. “Functional Data Analysis Amplitude Phase Variation.” Statistical Science, 468–84. Ramsay, J., B. W. Silverman. 2005. Functional Data Analysis. Springer Series Statistics. Springer. Sangalli, L. M., P. Secchi, S. Vantini, V. Vitelli. 2010. “K-Mean Alignment Curve Clustering.” Computational Statistics & Data Analysis 54 (5): 1219–33. Tucker, J. D., W. Wu, . Srivastava. 2013. “Generative Models Functional Data Using Phase Amplitude Separation.” Computational Statistics & Data Analysis 61: 50–66. Vantini, S. 2012. “Definition Phase Amplitude Variability Functional Data Analysis.” Test 21 (4): 676–96. https://doi.org/10.1007/s11749-011-0268-9.","code":""},{"path":[]},{"path":"/reference/fdacluster-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"fdacluster: Joint Clustering and Alignment of Functional Data — fdacluster-package","text":"Maintainer: Aymeric Stamm aymeric.stamm@cnrs.fr (ORCID) contributors: Laura Sangalli laura.sangalli@polimi.[contributor] Piercesare Secchi piercesare.secchi@polimi.[contributor] Simone Vantini simone.vantini@polimi.[contributor] Valeria Vitelli valeria.vitelli@medisin.uio.[contributor] Alessandro Zito zito.ales@gmail.com [contributor]","code":""},{"path":"/reference/fdadbscan.html","id":null,"dir":"Reference","previous_headings":"","what":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","title":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","text":"function extends DBSCAN functional data. includes possibility separate amplitude phase information.","code":""},{"path":"/reference/fdadbscan.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","text":"","code":"fdadbscan(   x,   y,   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   centroid_type = \"mean\",   metric = c(\"l2\", \"pearson\"),   cluster_on_phase = FALSE,   use_verbose = TRUE,   warping_options = c(0.15, 0.15),   maximum_number_of_iterations = 100L,   number_of_threads = 1L,   parallel_method = 0L,   distance_relative_tolerance = 0.001,   use_fence = FALSE,   check_total_dissimilarity = TRUE,   compute_overall_center = FALSE )"},{"path":"/reference/fdadbscan.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","text":"x numeric vector length \\(M\\) numeric matrix shape \\(N \\times M\\) object class funData::funData. numeric vector matrix, specifies grid(s) size \\(M\\) \\(N\\) curves observed. object class funData::funData, contains whole functional data set y argument used. y Either numeric matrix shape \\(N \\times M\\) numeric array shape \\(N \\times L \\times M\\) object class fda::fd. numeric matrix array, specifies \\(N\\)-sample \\(L\\)-dimensional curves observed grids size \\(M\\). object class fda::fd, contains necessary information functional data set able evaluate user-defined grids. warping_class string specifying warping class Choices \"affine\", \"dilation\", \"none\", \"shift\" \"srsf\". Defaults \"affine\". SRSF class class boundary-preserving. centroid_type string specifying type centroid compute. Choices \"mean\", \"median\" \"medoid\", \"lowess\" \"poly\". Defaults \"mean\". LOWESS appproximation chosen, user can append integer 0 100 \"lowess20\". number used smoother span. gives proportion points plot influence smooth value. Larger values give smoothness. default value 10%. polynomial approximation chosen, user can append positive integer \"poly3\". number used degree polynomial model. default value 4L. metric string specifying metric used compare curves. Choices \"l2\" \"pearson\". Defaults \"l2\". Used warping_class != \"srsf\". boundary-preserving warping class, L2 distance SRSFs original curves used. cluster_on_phase boolean specifying whether clustering based phase variation amplitude variation. Defaults FALSE implies amplitude variation. use_verbose boolean specifying whether algorithm output details steps console. Defaults TRUE. warping_options numeric vector supplied helper chosen warping_class decide warping parameter bounds. used warping_class != \"srsf\". maximum_number_of_iterations integer specifying maximum number iterations algorithm stops convergence criterion met. Defaults 100L. number_of_threads integer value specifying number threads used parallelization. Defaults 1L. used warping_class != \"srsf\". parallel_method integer value specifying type desired parallelization template computation, 0L, templates computed parallel. 1L, parallelization occurs within single template computation (medoid method now). Defaults 0L. used warping_class != \"srsf\". distance_relative_tolerance numeric value specifying relative tolerance distance update two iterations. observations sufficiently improved sense, algorithm stops. Defaults 1e-3. used warping_class != \"srsf\". use_fence boolean specifying whether fence algorithm used robustify algorithm outliers. Defaults FALSE. used warping_class != \"srsf\". check_total_dissimilarity boolean specifying whether additional stopping criterion based improvement total dissimilarity used. Defaults TRUE. used warping_class != \"srsf\". compute_overall_center boolean specifying whether overall center also computed. Defaults FALSE. used warping_class != \"srsf\".","code":""},{"path":"/reference/fdadbscan.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","text":"object class caps.","code":""},{"path":"/reference/fdadbscan.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","text":"","code":"#---------------------------------- # Extracts 15 out of the 30 simulated curves in `simulated30_sub` data set idx <- c(1:5, 11:15) x <- simulated30_sub$x[idx, ] y <- simulated30_sub$y[idx, , ]  #---------------------------------- # Runs an HAC with affine alignment, searching for 2 clusters out <- fdadbscan(   x = x,   y = y,   warping_class = \"affine\" ) #> ℹ Computing the distance matrix... #> ℹ Aligning all curves with respect to their centroid... #> ℹ Consolidating output...  #---------------------------------- # Then visualize the results # Either with ggplot2 via ggplot2::autoplot(out) # or using graphics::plot() # You can visualize the original and aligned curves with: plot(out, type = \"amplitude\")  # Or the estimated warping functions with: plot(out, type = \"phase\")"},{"path":"/reference/fdadist.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","title":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","text":"function computes matrix pairwise distances curves functional data sample. can achieved without phase amplitude separation, can done using variety warping classes.","code":""},{"path":"/reference/fdadist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","text":"","code":"fdadist(   x,   y = NULL,   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   metric = c(\"l2\", \"pearson\"),   cluster_on_phase = FALSE,   labels = NULL )"},{"path":"/reference/fdadist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","text":"x numeric vector length \\(M\\) numeric matrix shape \\(N \\times M\\) object class funData::funData. numeric vector matrix, specifies grid(s) size \\(M\\) \\(N\\) curves observed. object class funData::funData, contains whole functional data set y argument used. y Either numeric matrix shape \\(N \\times M\\) numeric array shape \\(N \\times L \\times M\\) object class fda::fd. numeric matrix array, specifies \\(N\\)-sample \\(L\\)-dimensional curves observed grids size \\(M\\). object class fda::fd, contains necessary information functional data set able evaluate user-defined grids. warping_class string specifying warping class Choices \"affine\", \"dilation\", \"none\", \"shift\" \"srsf\". Defaults \"affine\". SRSF class class boundary-preserving. metric string specifying metric used compare curves. Choices \"l2\" \"pearson\". Defaults \"l2\". Used warping_class != \"srsf\". boundary-preserving warping class, L2 distance SRSFs original curves used. cluster_on_phase boolean specifying whether clustering based phase variation amplitude variation. Defaults FALSE implies amplitude variation. labels character vector specifying curve labels. Defaults NULL uses sequential numbers labels.","code":""},{"path":"/reference/fdadist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","text":"stats::dist object storing distance matrix input curves using metric specified argument metric warping class specified argument warping_class.","code":""},{"path":"/reference/fdadist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","text":"","code":"idx <- c(1:5, 11:15, 21:25) D <- fdadist(simulated30_sub$x[idx, ], simulated30_sub$y[idx, , ])"},{"path":"/reference/fdahclust.html","id":null,"dir":"Reference","previous_headings":"","what":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"function extends hierarchical agglomerative clustering functional data. includes possibility separate amplitude phase information.","code":""},{"path":"/reference/fdahclust.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"","code":"fdahclust(   x,   y = NULL,   n_clusters = 1L,   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   centroid_type = \"mean\",   metric = c(\"l2\", \"pearson\"),   linkage_criterion = c(\"complete\", \"average\", \"single\", \"ward.D2\"),   cluster_on_phase = FALSE,   use_verbose = TRUE,   warping_options = c(0.15, 0.15),   maximum_number_of_iterations = 100L,   number_of_threads = 1L,   parallel_method = 0L,   distance_relative_tolerance = 0.001,   use_fence = FALSE,   check_total_dissimilarity = TRUE,   compute_overall_center = FALSE )"},{"path":"/reference/fdahclust.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"x numeric vector length \\(M\\) numeric matrix shape \\(N \\times M\\) object class funData::funData. numeric vector matrix, specifies grid(s) size \\(M\\) \\(N\\) curves observed. object class funData::funData, contains whole functional data set y argument used. y Either numeric matrix shape \\(N \\times M\\) numeric array shape \\(N \\times L \\times M\\) object class fda::fd. numeric matrix array, specifies \\(N\\)-sample \\(L\\)-dimensional curves observed grids size \\(M\\). object class fda::fd, contains necessary information functional data set able evaluate user-defined grids. n_clusters integer value specifying number clusters. Defaults 1L. warping_class string specifying warping class Choices \"affine\", \"dilation\", \"none\", \"shift\" \"srsf\". Defaults \"affine\". SRSF class class boundary-preserving. centroid_type string specifying type centroid compute. Choices \"mean\", \"median\" \"medoid\", \"lowess\" \"poly\". Defaults \"mean\". LOWESS appproximation chosen, user can append integer 0 100 \"lowess20\". number used smoother span. gives proportion points plot influence smooth value. Larger values give smoothness. default value 10%. polynomial approximation chosen, user can append positive integer \"poly3\". number used degree polynomial model. default value 4L. metric string specifying metric used compare curves. Choices \"l2\" \"pearson\". Defaults \"l2\". Used warping_class != \"srsf\". boundary-preserving warping class, L2 distance SRSFs original curves used. linkage_criterion string specifying linkage criterion used compute distances sets curves. Choices \"complete\" complete linkage, \"average\" average linkage \"single\" single linkage. See stats::hclust() details. Defaults \"complete\". cluster_on_phase boolean specifying whether clustering based phase variation amplitude variation. Defaults FALSE implies amplitude variation. use_verbose boolean specifying whether algorithm output details steps console. Defaults TRUE. warping_options numeric vector supplied helper chosen warping_class decide warping parameter bounds. used warping_class != \"srsf\". maximum_number_of_iterations integer specifying maximum number iterations algorithm stops convergence criterion met. Defaults 100L. number_of_threads integer value specifying number threads used parallelization. Defaults 1L. used warping_class != \"srsf\". parallel_method integer value specifying type desired parallelization template computation, 0L, templates computed parallel. 1L, parallelization occurs within single template computation (medoid method now). Defaults 0L. used warping_class != \"srsf\". distance_relative_tolerance numeric value specifying relative tolerance distance update two iterations. observations sufficiently improved sense, algorithm stops. Defaults 1e-3. used warping_class != \"srsf\". use_fence boolean specifying whether fence algorithm used robustify algorithm outliers. Defaults FALSE. used warping_class != \"srsf\". check_total_dissimilarity boolean specifying whether additional stopping criterion based improvement total dissimilarity used. Defaults TRUE. used warping_class != \"srsf\". compute_overall_center boolean specifying whether overall center also computed. Defaults FALSE. used warping_class != \"srsf\".","code":""},{"path":"/reference/fdahclust.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"object class caps.","code":""},{"path":"/reference/fdahclust.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"number clusters required input , functional data, hierarchical clustering performed, curves within clusters need aligned corresponding centroid.","code":""},{"path":"/reference/fdahclust.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"","code":"#---------------------------------- # Extracts 15 out of the 30 simulated curves in `simulated30_sub` data set idx <- c(1:5, 11:15, 21:25) x <- simulated30_sub$x[idx, ] y <- simulated30_sub$y[idx, , ]  #---------------------------------- # Runs an HAC with affine alignment, searching for 2 clusters out <- fdahclust(   x = x,   y = y,   n_clusters = 2,   warping_class = \"affine\" ) #> ℹ Computing the distance matrix... #> ℹ Calculating the tree... #> ℹ Aligning all curves with respect to their centroid... #> ℹ Consolidating output...  #---------------------------------- # Then visualize the results # Either with ggplot2 via ggplot2::autoplot(out) # or using graphics::plot() # You can visualize the original and aligned curves with: plot(out, type = \"amplitude\")  # Or the estimated warping functions with: plot(out, type = \"phase\")"},{"path":"/reference/fdakmeans.html","id":null,"dir":"Reference","previous_headings":"","what":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","title":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","text":"function provides implementations k-means clustering algorithm functional data, possible joint amplitude phase separation. number warping class implemented achieve separation.","code":""},{"path":"/reference/fdakmeans.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","text":"","code":"fdakmeans(   x,   y = NULL,   n_clusters = 1L,   seeds = NULL,   seeding_strategy = c(\"kmeans++\", \"exhaustive-kmeans++\", \"exhaustive\", \"hclust\"),   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   centroid_type = \"mean\",   metric = c(\"l2\", \"pearson\"),   cluster_on_phase = FALSE,   use_verbose = TRUE,   warping_options = c(0.15, 0.15),   maximum_number_of_iterations = 100L,   number_of_threads = 1L,   parallel_method = 0L,   distance_relative_tolerance = 0.001,   use_fence = FALSE,   check_total_dissimilarity = TRUE,   compute_overall_center = FALSE,   add_silhouettes = TRUE )"},{"path":"/reference/fdakmeans.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","text":"x numeric vector length \\(M\\) numeric matrix shape \\(N \\times M\\) object class funData::funData. numeric vector matrix, specifies grid(s) size \\(M\\) \\(N\\) curves observed. object class funData::funData, contains whole functional data set y argument used. y Either numeric matrix shape \\(N \\times M\\) numeric array shape \\(N \\times L \\times M\\) object class fda::fd. numeric matrix array, specifies \\(N\\)-sample \\(L\\)-dimensional curves observed grids size \\(M\\). object class fda::fd, contains necessary information functional data set able evaluate user-defined grids. n_clusters integer value specifying number clusters. Defaults 1L. seeds integer value vector specifying indices initial centroids. integer vector, interpreted indices intial centroids therefore length n_clusters. integer value, interpreted index first initial centroid subsequent centroids chosen according k-means++ strategy. can NULL case argument seeding_strategy used automatically provide suitable indices. Defaults NULL. seeding_strategy character string specifying strategy choosing initial centroids case argument seeds set NULL. Choices \"kmeans++\", \"exhaustive-kmeans++\" performs exhaustive search choice first centroid, \"exhaustive\" tries combinations initial centroids \"hclust\" first performs hierarchical clustering using Ward's linkage criterion identify initial centroids. Defaults \"kmeans++\", fastest strategy. warping_class string specifying warping class Choices \"affine\", \"dilation\", \"none\", \"shift\" \"srsf\". Defaults \"affine\". SRSF class class boundary-preserving. centroid_type string specifying type centroid compute. Choices \"mean\", \"median\" \"medoid\", \"lowess\" \"poly\". Defaults \"mean\". LOWESS appproximation chosen, user can append integer 0 100 \"lowess20\". number used smoother span. gives proportion points plot influence smooth value. Larger values give smoothness. default value 10%. polynomial approximation chosen, user can append positive integer \"poly3\". number used degree polynomial model. default value 4L. metric string specifying metric used compare curves. Choices \"l2\" \"pearson\". Defaults \"l2\". Used warping_class != \"srsf\". boundary-preserving warping class, L2 distance SRSFs original curves used. cluster_on_phase boolean specifying whether clustering based phase variation amplitude variation. Defaults FALSE implies amplitude variation. use_verbose boolean specifying whether algorithm output details steps console. Defaults TRUE. warping_options numeric vector supplied helper chosen warping_class decide warping parameter bounds. used warping_class != \"srsf\". maximum_number_of_iterations integer specifying maximum number iterations algorithm stops convergence criterion met. Defaults 100L. number_of_threads integer value specifying number threads used parallelization. Defaults 1L. used warping_class != \"srsf\". parallel_method integer value specifying type desired parallelization template computation, 0L, templates computed parallel. 1L, parallelization occurs within single template computation (medoid method now). Defaults 0L. used warping_class != \"srsf\". distance_relative_tolerance numeric value specifying relative tolerance distance update two iterations. observations sufficiently improved sense, algorithm stops. Defaults 1e-3. used warping_class != \"srsf\". use_fence boolean specifying whether fence algorithm used robustify algorithm outliers. Defaults FALSE. used warping_class != \"srsf\". check_total_dissimilarity boolean specifying whether additional stopping criterion based improvement total dissimilarity used. Defaults TRUE. used warping_class != \"srsf\". compute_overall_center boolean specifying whether overall center also computed. Defaults FALSE. used warping_class != \"srsf\". add_silhouettes boolean specifying whether silhouette values computed observation internal validation clustering structure. Defaults TRUE.","code":""},{"path":"/reference/fdakmeans.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","text":"object class caps.","code":""},{"path":"/reference/fdakmeans.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","text":"","code":"#---------------------------------- # Extracts 15 out of the 30 simulated curves in `simulated30_sub` data set idx <- c(1:5, 11:15, 21:25) x <- simulated30_sub$x[idx, ] y <- simulated30_sub$y[idx, , ]  #---------------------------------- # Runs a k-means clustering with affine alignment, searching for 2 clusters out <- fdakmeans(   x = x,   y = y,   n_clusters = 2,   warping_class = \"affine\" ) #> ℹ Computing initial centroids using kmeans++ strategy... #> Information about the data set: #>  - Number of observations: 15 #>  - Number of dimensions: 1 #>  - Number of points: 30 #>  #> Information about cluster initialization: #>  - Number of clusters: 2 #>  - Initial seeds for cluster centers:         14         4 #>  #> Information about the methods used within the algorithm: #>  - Warping method: affine #>  - Center method: mean #>  - Dissimilarity method: l2 #>  - Optimization method: bobyqa #>  #> Information about warping parameter bounds: #>  - Warping options:    0.1500   0.1500 #>  #> Information about convergence criteria: #>  - Maximum number of iterations: 100 #>  - Distance relative tolerance: 0.001 #>  #> Information about parallelization setup: #>  - Number of threads: 1 #>  - Parallel method: 0 #>  #> Other information: #>  - Use fence to robustify: 0 #>  - Check total dissimilarity: 1 #>  - Compute overall center: 0 #>  #> Running k-centroid algorithm: #>  - Iteration #1 #>    * Size of cluster #0: 5 #>    * Size of cluster #1: 10 #>  - Iteration #2 #>    * Size of cluster #0: 5 #>    * Size of cluster #1: 10 #>  #> Active stopping criteria: #>  - Memberships did not change.  #---------------------------------- # Then visualize the results # Either with ggplot2 via ggplot2::autoplot(out) # or using graphics::plot() # You can visualize the original and aligned curves with: plot(out, type = \"amplitude\")  # Or the estimated warping functions with: plot(out, type = \"phase\")"},{"path":"/reference/lp.html","id":null,"dir":"Reference","previous_headings":"","what":"Linear and integer programming — lp","title":"Linear and integer programming — lp","text":"Interface lp_solve linear/integer programming system.","code":""},{"path":"/reference/lp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Linear and integer programming — lp","text":"","code":"lp(   direction = \"min\",   objective.in,   const.mat,   const.dir,   const.rhs,   transpose.constraints = TRUE,   int.vec,   presolve = 0,   compute.sens = 0,   binary.vec,   all.int = FALSE,   all.bin = FALSE,   scale = 196,   dense.const,   num.bin.solns = 1,   use.rw = FALSE,   timeout = 0L )"},{"path":"/reference/lp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Linear and integer programming — lp","text":"direction Character string giving direction optimization: \"min\" (default) \"max.\" objective.Numeric vector coefficients objective function const.mat Matrix numeric constraint coefficients, one row  per constraint, one column per variable (unless transpose.constraints =  FALSE; see ). const.dir Vector character strings giving direction  constraint: value one \"<,\" \"<=,\" \"=,\" \"==,\" \">,\" \">=\". (pair two values identical.) const.rhs Vector numeric values right-hand sides  constraints. transpose.constraints default constraint occupies row  const.mat, matrix needs transposed passed  optimizing code.  large constraint matrices may wiser  construct constraints matrix column--column. case set  transpose.constraints FALSE. int.vec Numeric vector giving indices variables  required integer. length vector therefore  number integer variables. presolve Numeric: presolve? Default 0 (); non-zero value means \"yes.\" Currently ignored. compute.sens Numeric: compute sensitivity? Default 0 (); non-zero value means \"yes.\" binary.vec Numeric vector like int.vec giving indices variables  required binary. .int Logical: variables integer? Default: FALSE. .bin Logical: variables binary? Default: FALSE. scale Integer: value lpSolve scaling. Details can found lpSolve documentation. Set 0 scaling. Default: 196 dense.const Three column dense constraint array. ignored const.mat supplied. Otherwise columns constraint number, column number, value; one row non-zero entry constraint matrix. num.bin.solns Integer: .bin=TRUE, user can request num.bin.solns optimal solutions returned. use.rw Logical: TRUE num.bin.solns > 1, write lp file read back solution first. just defeat bug somewhere. Although default FALSE, recommend set TRUE need num.bin.solns > 1, bug found. timeout Integer: timeout variable seconds, defaults 0L means limit set.","code":""},{"path":"/reference/lp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Linear and integer programming — lp","text":"lpSolve::lp.object object.","code":""},{"path":"/reference/lp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Linear and integer programming — lp","text":"function calls lp_solve 5.5 solver. system many options supported . current version maintained https://lpsolve.sourceforge.net/5.5/. Note every variable assumed >= 0!","code":""},{"path":"/reference/plot.caps.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots the result of a clustering strategy stored in a caps object — plot.caps","title":"Plots the result of a clustering strategy stored in a caps object — plot.caps","text":"function creates visualization result k-mean alignment algorithm without returning plot data object. user can choose visualize either amplitude information data case original aligned curves shown phase information data case estimated warping functions shown.","code":""},{"path":"/reference/plot.caps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots the result of a clustering strategy stored in a caps object — plot.caps","text":"","code":"# S3 method for caps plot(x, type = c(\"amplitude\", \"phase\"), ...)"},{"path":"/reference/plot.caps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots the result of a clustering strategy stored in a caps object — plot.caps","text":"x object class caps. type string specifying type information display. Choices \"amplitude\" plotting original aligned curves represent amplitude information data \"phase\" plotting corresponding warping functions represent phase information data. Defaults \"amplitude\". ... used.","code":""},{"path":"/reference/plot.caps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots the result of a clustering strategy stored in a caps object — plot.caps","text":"","code":"plot(sim30_caps, type = \"amplitude\")  plot(sim30_caps, type = \"phase\")"},{"path":"/reference/plot.mcaps.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots results of multiple clustering strategies — plot.mcaps","title":"Plots results of multiple clustering strategies — plot.mcaps","text":"S3 method implementation graphics::plot() generic objects class mcaps visualize performances multiple caps objects applied data sets either terms WSS terms silhouette values.","code":""},{"path":"/reference/plot.mcaps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots results of multiple clustering strategies — plot.mcaps","text":"","code":"# S3 method for mcaps plot(   x,   validation_criterion = c(\"wss\", \"silhouette\"),   what = c(\"mean\", \"distribution\"),   ... )"},{"path":"/reference/plot.mcaps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots results of multiple clustering strategies — plot.mcaps","text":"x object class mcaps. validation_criterion string specifying validation criterion used comparison. Choices \"wss\" \"silhouette\". Defaults \"wss\". string specifying kind information display validation criterion. Choices \"mean\" (plots mean values) \"distribution\" (plots boxplots). Defaults \"mean\". ... arguments passed specific methods.","code":""},{"path":"/reference/plot.mcaps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots results of multiple clustering strategies — plot.mcaps","text":"","code":"plot(sim30_mcaps)"},{"path":"/reference/sim30_caps.html","id":null,"dir":"Reference","previous_headings":"","what":"A caps object from simulated data for examples — sim30_caps","title":"A caps object from simulated data for examples — sim30_caps","text":"object class caps storing result fdakmeans() function applied data set simulated30 using affine warping class Pearson metric searching 2 clusters.","code":""},{"path":"/reference/sim30_caps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A caps object from simulated data for examples — sim30_caps","text":"","code":"sim30_caps"},{"path":"/reference/sim30_caps.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"A caps object from simulated data for examples — sim30_caps","text":"object class caps.","code":""},{"path":"/reference/sim30_mcaps.html","id":null,"dir":"Reference","previous_headings":"","what":"An mcaps object from simulated data for examples — sim30_mcaps","title":"An mcaps object from simulated data for examples — sim30_mcaps","text":"object class mcaps storing result compare_caps() function applied data set simulated30_sub comparing clustering structures found fdakmeans() function mean centroid type used various classes warping functions varying number clusters.","code":""},{"path":"/reference/sim30_mcaps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"An mcaps object from simulated data for examples — sim30_mcaps","text":"","code":"sim30_mcaps"},{"path":"/reference/sim30_mcaps.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"An mcaps object from simulated data for examples — sim30_mcaps","text":"object class mcaps effectively tibble::tibble 5 columns many rows clustering strategies compare. 5 column-variables : n_clusters: number clusters; clustering_method: clustering method; warping_class: class warping functions used curve alignment; centroid_type: type centroid used compute cluster representative; caps_obj: result corresponding clustering strategy objects class caps.","code":""},{"path":"/reference/simulated30.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulated data for examples — simulated30","title":"Simulated data for examples — simulated30","text":"data set containing 30 simulated uni-dimensional curves.","code":""},{"path":"/reference/simulated30.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulated data for examples — simulated30","text":"","code":"simulated30"},{"path":"/reference/simulated30.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Simulated data for examples — simulated30","text":"list abscissas x values y: x Matrix 30x200; y Array 30x1x200.","code":""},{"path":"/reference/simulated30_sub.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulated data for examples — simulated30_sub","title":"Simulated data for examples — simulated30_sub","text":"data set containing 30 simulated uni-dimensional curves.","code":""},{"path":"/reference/simulated30_sub.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulated data for examples — simulated30_sub","text":"","code":"simulated30_sub"},{"path":"/reference/simulated30_sub.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Simulated data for examples — simulated30_sub","text":"list abscissas x values y: x Matrix 30x30; y Array 30x1x30.","code":""},{"path":"/reference/simulated90.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulated data from the CSDA paper — simulated90","title":"Simulated data from the CSDA paper — simulated90","text":"data set containing 90 simulated uni-dimensional curves.","code":""},{"path":"/reference/simulated90.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulated data from the CSDA paper — simulated90","text":"","code":"simulated90"},{"path":"/reference/simulated90.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Simulated data from the CSDA paper — simulated90","text":"list abscissas x values y: x Vector size 100; y Matrix size 90x100.","code":""},{"path":[]},{"path":"/news/index.html","id":"fdacluster-030","dir":"Changelog","previous_headings":"","what":"fdacluster 0.3.0","title":"fdacluster 0.3.0","text":"CRAN release: 2023-07-04 Added median centroid type; Median mean centroid types now defined union individual grids; Simplified caps class avoid storing objects multiple times different names; Added vignette initialization strategies k-means; Added article use case Berkeley growth study; Added article supported input formats.","code":""},{"path":"/news/index.html","id":"fdacluster-022","dir":"Changelog","previous_headings":"","what":"fdacluster 0.2.2","title":"fdacluster 0.2.2","text":"CRAN release: 2023-05-25 Make sure one can use fdacluster namespace notation. Make sure use fda funData checking available.","code":""},{"path":"/news/index.html","id":"fdacluster-021","dir":"Changelog","previous_headings":"","what":"fdacluster 0.2.1","title":"fdacluster 0.2.1","text":"CRAN release: 2023-05-19 Add DBSCAN clustering; Fix C++ compiler issues errored accessing empty vectors.","code":""},{"path":"/news/index.html","id":"fdacluster-020","dir":"Changelog","previous_headings":"","what":"fdacluster 0.2.0","title":"fdacluster 0.2.0","text":"CRAN release: 2023-05-18 Add hierarchical clustering; Enforce n_clusters output via linear programming (LP) using lpSolve package; New caps class storing results functional Clustering Amplitude Phase Separation consistent way; Add tools comparing clustering results (mcaps objects, autoplot plot specialized method implementations); Add seeding strategies kmeans (via hierarchical clustering k-means++ k-means++ exhaustive search first center exhaustive search centers); Add within-cluster domain auto-extension via mean imputation; Add possibility cluster according phase variability instead amplitude variability. Renaming functions: perform k-means alignment, now use fdakmeans(), perform HAC alignment, now use fdahclust().","code":""},{"path":"/news/index.html","id":"fdacluster-011","dir":"Changelog","previous_headings":"","what":"fdacluster 0.1.1","title":"fdacluster 0.1.1","text":"CRAN release: 2022-05-09 Fixed undefined behavior sanitizer issues spotted UBSAN. Added reference published work related package DESCRIPTION.","code":""},{"path":"/news/index.html","id":"fdacluster-010","dir":"Changelog","previous_headings":"","what":"fdacluster 0.1.0","title":"fdacluster 0.1.0","text":"CRAN release: 2022-02-01 Initial release. Added NEWS.md file track changes package.","code":""}]
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This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"/articles/berkeley-growth.html","id":"the-berkeley-growth-data","dir":"Articles","previous_headings":"","what":"The Berkeley growth data","title":"Analysis of Berkeley growth data","text":"total 93 children (39 boys 54 girls) followed height cm measured time common grid age:  single observation actually time series \\(\\mathbf{x}_i = (x_i(t_1), \\dots, x_i(t_M))^\\top\\). can hypothesize know happened two consecutive points \\(t_j\\) \\(t_{j+1}\\) even though observe data \\((t_j, t_{j+1})\\). usually achieved via splines Fourier wavelet basis decomposition confer observation degree regularity account possible periodicity specificity data point. step data representation effectively transforms original observation \\(\\mathbf{x}_i\\) time series functional data point \\(x_i : \\mathcal{D} \\\\mathcal{M}\\).","code":"growth <- fda::growth mb <- as.factor(c(rep(\"male\", dim(growth$hgtm)[2]), rep(\"female\", dim(growth$hgtf)[2]))) N <- length(mb) x <- growth$age M <- length(x) y0 <- cbind(growth$hgtm, growth$hgtf) tibble::tibble(   Age = replicate(N, x, simplify = FALSE),   Height = purrr::array_tree(y0, margin = 2),   Gender = mb,   CurveID = 1:N ) |>    tidyr::unnest(cols = c(Age, Height)) |>    ggplot(aes(Age, Height, color = Gender, group = CurveID)) +    geom_point() +    geom_line() +   theme_bw() +    labs(     title = \"Heights of 39 boys and 54 girls from age 1 to 18\",      x = \"Age (years)\",      y = \"Height (cm)\"   )"},{"path":"/articles/berkeley-growth.html","id":"functional-data-representation","dir":"Articles","previous_headings":"","what":"Functional data representation","title":"Analysis of Berkeley growth data","text":"Given orthonormal basis \\(\\{e_b\\}_{b\\ge 1}\\) functional space observations assumed belong , can model observation \\(x_i\\) : \\[ x_i = f_i + \\varepsilon_i, \\] : \\[ f_i(t) = \\sum_{b=1}^B f_{ib} e_b(t), \\] truncation \\(B\\). coefficients \\(f_{ib}\\) adjusted minimizing cost function usually includes data attachment term rougness penalty term way enforce regularity functional representation. common use instance norm second derivative roughness penalty, case cost function becomes: \\[ \\sum_{m=1}^M \\left( x_i(t_m) - f_i(t_m) \\right)^2 + \\lambda \\sum_{m=1}^M \\left[ f_i^{(2)}(t_m) \\right]^2 \\] practice, functional representation can achieved R using fda package. following code adjusts B-spline representation growth curves weight \\(\\lambda\\) roughness penalty determined minimizing generalized cross-validation criterion: can now take look data representation:  can also compute display growth rate:  graph interesting tells us first peak growth velocity common boys girls early age, just birth; second peak growth velocity corresponding puberty happens earlier girls; variability second peak due gender also inter-subject variability. particular, one wanted perform clustering curves label boys girls (assuming information), figures show best chance accomplish clustering performing joint alignment clustering growth velocity curves can simultaneously () minimize within-group phase variability (ii) cluster curves based phase variability.","code":"basisobj <- fda::create.bspline.basis(rangeval = range(x), nbasis = 15) fd_vals <- purrr::map(1:N, \\(n) {   yobs <- y0[, n]   result <- fda::smooth.basis(x, yobs, basisobj)   yfd <- result$fd   cost <- function(lam) {     yfdPar <- fda::fdPar(yfd, 2, lam)     out <- fda::smooth.basis(x, yobs, yfdPar)     out$gcv   }   lambda_opt <- stats::optimise(cost, c(1e-8, 1))$minimum   if (lambda_opt <= 1e-8)     cli::cli_alert_warning(\"The optimal penalty has reached the lower bound (1e-8) for curve #{n}.\")   if (lambda_opt >= 1)     cli::cli_alert_warning(\"The optimal penalty has reached the upper bound (1) for curve #{n}.\")   yfdPar <- fda::fdPar(yfd, 2, lambda_opt)   fda::smooth.fd(yfd, yfdPar) }) fd <- fda::fd(   coef = fd_vals |>     purrr::map(\"coefs\") |>     purrr::reduce(cbind),   basisobj = basisobj ) y0 <- fda::eval.fd(x, fd, 0) tibble::tibble(   Age = replicate(N, x, simplify = FALSE),   Height = purrr::array_tree(y0, margin = 2),   Gender = mb,   CurveID = 1:N ) |>    tidyr::unnest(cols = c(Age, Height)) |>    ggplot(aes(Age, Height, color = Gender, group = CurveID)) +    geom_point() +    geom_line() +   theme_bw() +    labs(     title = \"Heights of 39 boys and 54 girls from age 1 to 18\",      x = \"Age (years)\",      y = \"Height (cm)\"   ) y1 <- fda::eval.fd(x, fd, 1) tibble::tibble(   Age = replicate(N, x, simplify = FALSE),   Height = purrr::array_tree(y1, margin = 2),   Gender = mb,   CurveID = 1:N ) |>   tidyr::unnest(cols = c(Age, Height)) |>   ggplot(aes(Age, Height, color = Gender, group = CurveID)) +   geom_point() +   geom_line() +   theme_bw() +   labs(     title = \"Growth velocity of 39 boys and 54 girls from age 1 to 18\",     x = \"Age (years)\",     y = \"Growth velocity (cm/year)\"   )"},{"path":"/articles/berkeley-growth.html","id":"clustering","dir":"Articles","previous_headings":"","what":"Clustering","title":"Analysis of Berkeley growth data","text":"Initial visualization data representation steps revealed , one aims clustering individuals based gender, (s)focus : searching 2 clusters; using growth velocity curves instead growth curves ; cluster based phase variability; perform intra-cluster alignment separate amplitude phase variability. However, still several possible clustering methods can explore perform task. Namely, fdacluster implements \\(k\\)-means algorithm well hierarchical clustering DBSCAN. can compare different clustering strategies: generates object class mcaps specialized S3 methods graphics::plot() ggplot2::autoplot(). called object class mcaps, methods gain optional arguments: validation_criterion choose validation criterion display distance--center (validation_criterion = \"wss\") silhouette values (validation_criterion = \"silhouette\"); choose whether mean criterion displayed (= \"mean\") entire distribution across observation form boxplot (= \"distribution\").  terms within-cluster distances center (WSS), hierarchical agglomerative clustering average complete linkage \\(k\\)-means stand .  terms individual silhouette values, DBSCAN appear comparison auto-detects number clusters found 1 cluster. methods, hierarchical agglomerative clustering average complete linkage stand . can therefore proceed hierarchical agglomerative clustering complete linkage example: generates object class caps specialized S3 methods graphics::plot() ggplot2::autoplot(). called object class caps, methods gain optional argument type can one amplitude phase. default type = \"amplitude\" case curves alignment shown colored cluster membership:  type = \"phase\", warping functions instead displayed gives sense phase variability data phase alignment. , colored cluster membership:  also possible show visual inspection internal cluster validation via diagnostic_plot() function, shows individual distance--center silhouette values, observations ordered decreasing value intra-cluster silhouette:  Finally, can explore correspondence non-supervised groups found actual gender distribution: second group almost entirely composed girls first group mainly composed men although 23.68% girls present group. interesting dig characteristics girls might explain clustering sees boys well understanding 1 boy seen girl.","code":"growth_mcaps <- compare_caps(   x = x,   y = t(y1),   n_clusters = 2,   metric = \"l2\",    clustering_method = c(     \"kmeans\",      \"hclust-complete\",      \"hclust-average\",      \"hclust-single\",     \"dbscan\"   ),    warping_class = \"affine\",    centroid_type = \"mean\",   cluster_on_phase = TRUE ) plot(growth_mcaps, validation_criterion = \"wss\", what = \"distribution\") plot(growth_mcaps, validation_criterion = \"silhouette\", what = \"distribution\") growth_caps <- fdahclust(   x = x,   y = t(y1),   n_clusters = 2,   metric = \"l2\",   warping_class = \"affine\",    centroid_type = \"mean\",   cluster_on_phase = TRUE ) plot(growth_caps, type = \"amplitude\") plot(growth_caps, type = \"phase\") diagnostic_plot(growth_caps) table(growth_caps$memberships, mb) |>    `rownames<-`(c(\"Group 1\", \"Group 2\")) |>    knitr::kable()"},{"path":"/articles/hierarchial-clustering.html","id":"theory","dir":"Articles","previous_headings":"","what":"Theory","title":"Hierarchical clustering","text":"Traditional hierarchical agglomerative clustering (HAC) usually carried two mandatory steps third optional one: Compute distance matrix \\(D\\) entry \\(d_{ij}\\) stores distance observation \\(\\) observation \\(j\\); Compute hierarchy clustering structures form dendrogram first assuming observation belongs cluster progressively merge observations groups observations together using -called linkage criterion; [optional] Cut tree given distance order form \\(k\\) clusters. steps incurs slight modifications comes clustering functional data. Step 1. Functional HAC needs account intrinsic amplitude phase variability inherent functional data. therefore natural computing distance two curves minimize distance possible warping functions chosen class, .e. integrate alignment computing distance matrix. idea assess far two curves optimal phase alignment. step achieved fdadist(). Step 2. process building hierarchy possible clustering structures change distance matrix \\(D\\) known. fact, practical point view R, still achieved via call stats::hclust(). , user can choose linkage criterion use assessing distances sets curves. sake simplicity, subset choices stats::hclust() function actually available fdacluster, namely complete, average, single ward.D2. Step 3. dendrogram built, big difference multivariate HAC functional HAC stems fact latter requires choice number clusters, hence making Step 3 mandatory well. , grouping structure chosen, curves need undergo last alignment centroid cluster assigned . , , within-cluster sum squared distances centroid silhouette values can assessed. step achieved call fdakmeans() \\(k = 1\\) initial centroid corresponding cluster medoid.","code":""},{"path":"/articles/hierarchial-clustering.html","id":"using-fdacluster","dir":"Articles","previous_headings":"","what":"Using fdacluster","title":"Hierarchical clustering","text":"steps enpapsulated single function fdacluster ease usage: first group arguments call arguments user likely interact . number clusters can specified argument n_clusters, choice class warping functions type centroid metric achieved arguments warping_class, centroid_type metric respectively. linkage criterion can selected via linkage_criterion. default, function performs affine registration using pointwise sample mean computing cluster centroid L2 distance original curves complete linkage. default, function uses amplitude data alignment assigning cluster membership observed curves. user can switch use phase data instead using cluster_on_phase = TRUE. second group arguments set sensible default values used internal call fdakmeans() \\(k = 1\\), performs within-cluster alignment centroid groups determined cutting dendrogram appropriate height. arguments meant changed unless results clustering via fdahclust() seem odd.","code":"fdahclust(   x,   y,   n_clusters = 1L,   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   centroid_type = c(\"mean\", \"median\", \"medoid\", \"lowess\", \"poly\"),   metric = c(\"l2\", \"pearson\"),   linkage_criterion = c(\"complete\", \"average\", \"single\", \"ward.D2\"),   cluster_on_phase = FALSE,   use_verbose = TRUE,      warping_options = c(0.15, 0.15),   maximum_number_of_iterations = 100L,   number_of_threads = 1L,   parallel_method = 0L,   distance_relative_tolerance = 0.001,   use_fence = FALSE,   check_total_dissimilarity = TRUE,   compute_overall_center = FALSE )"},{"path":[]},{"path":"/articles/hierarchial-clustering.html","id":"simulated-data-set","dir":"Articles","previous_headings":"Example","what":"Simulated data set","title":"Hierarchical clustering","text":"Let us consider following sample \\(30\\) simulated unidimensional curves: Looking data set, seems shall expect \\(3\\) groups aim clustering based phase variability probably \\(2\\) groups search clustering structure based amplitude variability.","code":""},{"path":"/articles/hierarchial-clustering.html","id":"hac-based-on-amplitude-variability","dir":"Articles","previous_headings":"Example","what":"HAC based on amplitude variability","title":"Hierarchical clustering","text":"can perform HAC based amplitude variability follows: fdahclust() function returns object class caps (Clustering Amplitude Phase Separation) S3 specialized methods ggplot2::autoplot() graphics::plot() implemented. instance, can visualize original aligned functional data set :  can visualize estimated warping functions :  can visualize distribution distances--center silhouette values across observations :","code":"out1 <- fdahclust(   simulated30_sub$x,   simulated30_sub$y,   n_clusters = 2,   centroid_type = \"mean\",   warping_class = \"affine\",   metric = \"l2\",    cluster_on_phase = FALSE ) #> ℹ Computing the distance matrix... #> ℹ Calculating the tree... #> ℹ Aligning all curves with respect to their centroid... #> ℹ Consolidating output... plot(out1, type = \"amplitude\") plot(out1, type = \"phase\") diagnostic_plot(out1)"},{"path":"/articles/hierarchial-clustering.html","id":"hac-based-on-phase-variability","dir":"Articles","previous_headings":"Example","what":"HAC based on phase variability","title":"Hierarchical clustering","text":"can perform HAC based phase variability switching cluster_on_phase argument TRUE: can inspect result :","code":"out2 <- fdahclust(   simulated30_sub$x,   simulated30_sub$y,   n_clusters = 3,   centroid_type = \"mean\",   warping_class = \"affine\",   metric = \"l2\",    cluster_on_phase = TRUE ) #> ℹ Computing the distance matrix... #> ℹ Calculating the tree... #> ℹ Aligning all curves with respect to their centroid... #> ℹ Consolidating output... plot(out2, type = \"amplitude\") plot(out2, type = \"phase\") diagnostic_plot(out2)"},{"path":"/articles/hierarchial-clustering.html","id":"choosing-the-number-of-clusters","dir":"Articles","previous_headings":"Example","what":"Choosing the number of clusters","title":"Hierarchical clustering","text":"helper function compare_caps() can used get intuition number clusters one looking . example, can generate data help choosing number clusters clustering amplitude data: example. asked specification optional argument warping_class use multiple warping classes store clustering results separately output later comparison. Multiple choices can also used arguments clustering_method centroid_type although example chose focus HAC complete linkage using mean centroid type. metric argument must however unique need use metric among methods later comparison. code generates object class mcaps dedicated S3 specializations ggplot2::autoplot() graphics::plot() well. methods gain two extra optional arguments: validation_criterion: string specifying validation criterion used comparison. Choices \"wss\" \"silhouette\". Defaults \"wss\". : string specifying kind information display validation criterion. Choices \"mean\" (plots mean values) \"distribution\" (plots boxplots). Defaults \"mean\". example, one can can visualize mean WSS specified methods :  case, plot clearly shows among set warping classes considered, one use affine warping search \\(2\\) groups goal cluster based amplitude variability. Let us now perform analysis goal clustering based phase variability instead:  case, expected looking original data set, plot suggests search \\(3\\) groups. even interesting case improvement terms WSS going shift warping class affine warping class. also expected looking original data set nice also reflected output diagnostic.","code":"ncores <- max(parallel::detectCores() - 1L, 1L) plan(multisession, workers = ncores) amplitude_data <- compare_caps(   x = simulated30_sub$x,    y = simulated30_sub$y,    n_clusters = 1:5,    metric = \"l2\",    warping_class = c(\"none\", \"shift\", \"dilation\", \"affine\"),   clustering_method = \"hclust-complete\",    centroid_type = \"mean\",    cluster_on_phase = FALSE ) plan(sequential) plot(amplitude_data, validation_criterion = \"wss\", what = \"mean\") ncores <- max(parallel::detectCores() - 1L, 1L) plan(multisession, workers = ncores) phase_data <- compare_caps(   x = simulated30_sub$x,    y = simulated30_sub$y,    n_clusters = 1:5,    metric = \"l2\",    warping_class = c(\"shift\", \"dilation\", \"affine\"),   clustering_method = \"hclust-complete\",    centroid_type = \"mean\",    cluster_on_phase = TRUE ) plan(sequential) plot(phase_data, validation_criterion = \"wss\", what = \"mean\")"},{"path":"/articles/input-formats.html","id":"native-format","dir":"Articles","previous_headings":"","what":"Native format","title":"Supported input formats","text":"native format fdacluster consists pair vector/matrix x matrix/array y respectively storing evaluation grids values curves grids.","code":""},{"path":"/articles/input-formats.html","id":"passing-evaluation-grids-through-the-x-argument","dir":"Articles","previous_headings":"Native format","what":"Passing evaluation grids through the x argument","title":"Supported input formats","text":"curves evaluated exact grid, x can either numeric vector size \\(M\\) numeric matrix size \\(N \\times M\\), case rows identical. however possible , despite common grid size, curves actually evaluated different grids. case, x matrix size \\(N \\times M\\).","code":""},{"path":"/articles/input-formats.html","id":"passing-curve-values-through-the-y-argument","dir":"Articles","previous_headings":"Native format","what":"Passing curve values through the y argument","title":"Supported input formats","text":"curves evaluate univariate codomain, y can either numeric matrix size \\(N \\times M\\) numeric array size \\(N \\times 1 \\times M\\). cases, stores individual curves rows value corresponding grid point either second dimension y matrix third dimension y array. however possible curves evaluate multivariate codomain dimension \\(L\\) case, y array size \\(N \\times L \\times M\\).","code":""},{"path":"/articles/input-formats.html","id":"parsers-for-standard-functional-r-objects","dir":"Articles","previous_headings":"","what":"Parsers for standard functional R objects","title":"Supported input formats","text":"reason choice native format computation efficiency. However, R landscape functional data analysis rich. led us make fdacluster compatible standard ways storing functional data R. Specifically, added support fd class fda package funData multiFunData classes funData package.","code":""},{"path":"/articles/input-formats.html","id":"support-for-fundata","dir":"Articles","previous_headings":"Parsers for standard functional R objects","what":"Support for funData","title":"Supported input formats","text":"funData package package designed sole purpose implement classes storing kinds functional data. Functional data domain codomain, can univariate multivariate. addition, function data sample might observed different grid. led authors funData package propose three different classes, namely (Happ-Kurz 2020): Class funData dense functional data arbitrary dimension (cases dimension domain \\(d \\\\{1, 2, 3\\}\\)) common set observation points \\(t_1, \\dots, t_S\\) curves. curves may missing values coded NA. Class irregFunData irregularly sampled functional data individual sampling points \\(t_{ij}\\), \\(j = 1, \\dots, S_i\\), \\(= 1, \\dots ,N\\) curves. number \\(S_i\\) location observation points can vary across individual observations. moment, data one-dimensional domains implemented. Class multiFunData multivariate functional data, combines \\(p\\) elements functional data may defined different dimensional domains (e.g., functions images). fdacluster package focuses functional data defined uni-dimensional domains possibly multivariate codomains possibly different evaluation grids per curve. , support three classes needed. achieved utility function format_inputs() can read classes funData package provided x argument y argument. Specifically, following code shows classes funData package transformed (x, y) matrix / array format:","code":"if (inherits(x, \"funData\")) {   if (length(x@argvals) > 1)     cli::cli_abort(c(       \"The {.pkg fdacluster} package does not support functional data defined \",       \"on multivariate domains.\"     ))   L <- 1   y <- x@X   dims <- dim(y)   N <- dims[1]   M <- dims[2]   y <- array(y, dim = c(N, L, M))   x <- x@argvals[[1]] } else if (inherits(x, \"irregFunData\")) {   L <- 1   N <- length(x@argvals)   M <- x@argvals |>      purrr::map_int(length) |>      mean() |>      round()   y <- array(dim = c(N, L, M))   y[, 1, ] <- x@X |>      purrr::imap(\\(values, id) approx(x@argvals[[id]], values, n = M)$y) |>      do.call(rbind, args = _)   x <- x@argvals |>      purrr::map(\\(grid) seq(min(grid), max(grid), length.out = M)) |>      do.call(rbind, args = _) } else if (inherits(x, \"multiFunData\")) {   L <- length(x)   dims <- dim(x[[1]]@X)   grid <- x[[1]]@argvals[[1]]   purrr::walk(x, \\(fData) {     if (length(fData@argvals) != 1)       cli::cli_abort(c(         \"The {.pkg fdacluster} package does not support functional data \",          \"defined on multivariate domains.\"       ))     if (any(fData@argvals[[1]] != grids))       cli::cli_abort(c(         \"All components of the {.cls multiFunData} object must share the same \",         \"evaluation grids.\"       ))     if (any(dim(fData@X) != dims))       cli::cli_abort(c(         \"All components of the {.cls multiFunData} object must have values \",          \"stored in matrices with the same dimensions.\"       ))   })   N <- dims[1]   M <- dims[2]   y <- array(dim = c(N, L, M))   for (l in 1:L) y[, l, ] <- x[[l]]@X   x <- grid } else   cli::cli_abort(c(     \"Functional data provided in a single argument {.arg x} must be either of \",     \"class {.cls funData} or of class {.cls irregFunData} or of class \",      \"{.cls multiFunData}.\"   ))"},{"path":"/articles/input-formats.html","id":"example-for-fundata-support-growth-data","dir":"Articles","previous_headings":"Parsers for standard functional R objects > Support for funData","what":"Example for funData support: Growth Data","title":"Supported input formats","text":"following lines code demonstrates clustering functions fdacluster handle objects class funData using Berkeley growth data study developed Silverman Ramsay (2002).","code":"growth <- fda::growth growthData <- funData::funData(   argvals = growth$age,    X = t(cbind(growth$hgtm, growth$hgtf)) ) out_growth <- fdakmeans(   x = growthData,   n_clusters = 2,   seeding_strategy = \"exhaustive-kmeans++\",   cluster_on_phase = TRUE,   use_verbose = FALSE ) plot(out_growth)"},{"path":"/articles/input-formats.html","id":"example-for-irregfundata-support-simulated-data","dir":"Articles","previous_headings":"Parsers for standard functional R objects > Support for funData","what":"Example for irregFunData support: Simulated Data","title":"Supported input formats","text":"following lines code demonstrates clustering functions fdacluster handle objects class irregFunData using -house simulated data fly.","code":"# Generates full grid argvals <- seq(0, 2 * pi, by = 0.01) # Simulate 30 irregular grids with various sampling points (number and values) indices <- replicate(30, sort(sample(1:length(argvals), sample(30:50, 1)))) argvalsIrreg <- lapply(indices, \\(i) argvals[i]) # Simulate functional data with obvious grouping structure withr::with_seed(1234, {   simData <- funData::irregFunData(     argvals = argvalsIrreg,      X = mapply(       function(x, a, b) a * sin(x + b),        x = argvalsIrreg,        a = c(rgamma(10, 25, 50), rgamma(10, 50, 50), rgamma(10, 100, 50)),       b = c(rnorm(10, -1, 0.1), rnorm(10, 0, 0.1), rnorm(10, 1, 0.1))     )   )   }) out_sim <- fdakmeans(   x = simData,   n_clusters = 3,   seeding_strategy = \"exhaustive-kmeans++\",   use_verbose = FALSE ) plot(out_sim)"},{"path":"/articles/input-formats.html","id":"example-for-multifundata-support-gait-data","dir":"Articles","previous_headings":"Parsers for standard functional R objects > Support for funData","what":"Example for multiFunData support: Gait Data","title":"Supported input formats","text":"following lines code demonstrates clustering functions fdacluster handle objects class multiFunData using gait data study developed Silverman Ramsay (2002).","code":"cycle_perc <- (0:19) / 19 * 100 hipData <- t(fda::gait[, , 1]) hipData <- hipData kneeData <- t(fda::gait[, , 2]) kneeData <- kneeData gaitData <- funData::multiFunData(   funData::funData(argvals = cycle_perc, X = hipData),    funData::funData(argvals = cycle_perc, X = kneeData) ) out_gait <- fdakmeans(   x = gaitData,   n_clusters = 1,   seeding_strategy = \"exhaustive\",   warping_class = \"srsf\",   use_verbose = FALSE ) p <- autoplot(out_gait) p$data$component_id <- factor(p$data$component_id, labels = c(\"Hip\", \"Knee\")) p + labs(y = \"Angle (degree)\", title = \"Gait Kinematics\")"},{"path":"/articles/input-formats.html","id":"support-for-fda","dir":"Articles","previous_headings":"Parsers for standard functional R objects","what":"Support for fda","title":"Supported input formats","text":"fda package features class fd hosting R structure functional data. representation, functional data decomposed number basis functions (Ramsay Silverman 2006). class list following 3 components: coefs: Stores coefficients functional datum sample corresponding expansion along basis functions; basis: Stores basis functions; fdnames: Stores IDs coefficient, observation dimension co-domain. Basis functions supported fda package exclusively defined univariate domains. , class fd handles functional data unidimensional domains. However, accommodates functional data evaluating multidimensional co-domain. achieved using three-dimensional array coefficients instead vector matrix. Indeed, quoting help page fd class: coef: vector, matrix, three-dimensional array coefficients. first dimension (elements vector) corresponds basis functions. second dimension corresponds number functional observations, curves replicates. coef vector, represents single functional observation. coef array, third dimension corresponds variables multivariate functional data objects. functional data object univariate coef vector matrix multivariate three-dimensional array. Consequently, fdacluster package handles objects class fd considering x, native format, stores unidimensional grids y object class fd. parses data following way:","code":"dims <- purrr::map_int(y$fdnames, length) M <- dims[1] N <- dims[2] L <- dims[3] if (is.vector(x)) {   if (length(x) != M)     cli::cli_abort(c(       \"The number of function evaluations ({M}) does not match the grid \",       \"size ({length(x)}).\"     ))   y <- fda::eval.fd(x, y) } else {   if (nrow(x) != N)     cli::cli_abort(c(       \"When provided multiple evaluation grids as a matrix, the number of \",       \"rows should match the number of curves.\"     ))   if (ncol(x) != M)     cli::cli_abort(c(       \"When provided multiple evaluation grids as a matrix, the number of \",       \"columns should match the common grid size.\"     ))   y <- fda::eval.fd(t(x), y) } if (is.null(dim(y))) {   # y is a single 1-dimensional curve   y <- array(y, dim = c(length(y), 1, 1)) } else if (length(dim(y)) == 2) {   # y is N 1-dimensional curves   y <- array(y, dim = c(dim(y), 1)) } y <- aperm(y, c(2, 3, 1))"},{"path":"/articles/input-formats.html","id":"example-for-fd-support-gait-data","dir":"Articles","previous_headings":"Parsers for standard functional R objects > Support for fda","what":"Example for fd support: Gait Data","title":"Supported input formats","text":"following lines code demonstrates clustering functions fdacluster handle objects class fd using gait data study developed Silverman Ramsay (2002).","code":"bspl <- fda::create.fourier.basis(rangeval = c(0, 100), nbasis = 5) gaitDataFD <- fda::smooth.basis(   argvals = cycle_perc,    y = fda::gait,    fdParobj = bspl )$fd out_gait_fd <- fdakmeans(   x = cycle_perc,   y = gaitDataFD,   n_clusters = 1,    seeding_strategy = \"exhaustive\",   warping_class = \"srsf\",   use_verbose = FALSE ) p <- autoplot(out_gait_fd) p$data$component_id <- factor(p$data$component_id, labels = c(\"Hip\", \"Knee\")) p + labs(y = \"Angle (degree)\", title = \"Gait Kinematics\")"},{"path":[]},{"path":"/articles/kmeans-initialisation.html","id":"manual-specification-of-the-initial-seeds","dir":"Articles","previous_headings":"","what":"Manual specification of the initial seeds","title":"Computing initial centroids in k-means","text":"can use optional argument seeds takes integer vector one can manually specify indices observations used initial centroids. vector hence needs size n_clusters. however leads outcome sensitive initial choice seeds:","code":"out_manual <- fdakmeans(   x = simulated30$x,   y = simulated30$y,   n_clusters = 2,   seeds = c(1, 21),   warping_class = \"affine\",   centroid_type = \"mean\",   metric = \"l2\",   cluster_on_phase = FALSE,   use_verbose = FALSE ) knitr::kable(table(out_manual$memberships, true_groups)) withr::with_seed(1234, {   initial_seeds <- replicate(10, sample.int(30, 2, replace = FALSE), simplify = FALSE)   outs_manual <- purrr::map(initial_seeds, \\(.seeds) {     fdakmeans(       x = simulated30$x,       y = simulated30$y,       n_clusters = 2,       seeds = .seeds,       warping_class = \"affine\",       centroid_type = \"mean\",       metric = \"l2\",       cluster_on_phase = FALSE,       use_verbose = FALSE     )   }) }) tibble::tibble(   Initialization = initial_seeds |>      purrr::map_chr(\\(.seeds) paste(.seeds, collapse = \",\")),    `Misclassification Rate (%)` = purrr::map_dbl(outs_manual, \\(.clus) {     tbl <- table(.clus$memberships, true_groups)     round(min(tbl[1, 1] + tbl[2, 2], tbl[1, 2] + tbl[2, 1]) / 30 * 100, 2)   }) ) |>    knitr::kable()"},{"path":"/articles/kmeans-initialisation.html","id":"k-means","dir":"Articles","previous_headings":"","what":"\\(k\\)-means++","title":"Computing initial centroids in k-means","text":"\\(k\\)-means++ strategy originally proposed Arthur Vassilvitskii (2007). algorithm nicely described corresponding Wikipedia page follows: Choose one center uniformly random among data points. data point \\(x\\) chosen yet, compute \\(D(x)\\), distance \\(x\\) nearest center already chosen. Choose one new data point random new center, using weighted probability distribution point \\(x\\) chosen probability proportional \\(D(x)^2\\). Repeat Steps \\(2\\) \\(3\\) \\(k\\) centers chosen. Now initial centers chosen, proceed using standard \\(k\\)-means clustering. Despite probabilistic nature outcome follows strategy, provides robust \\(k\\)-means procedure:","code":"withr::with_seed(1234, {   outs_kpp <- replicate(10, {     fdakmeans(       x = simulated30$x,       y = simulated30$y,       n_clusters = 2,       seeding_strategy = \"kmeans++\",       warping_class = \"affine\",       centroid_type = \"mean\",       metric = \"l2\",       cluster_on_phase = FALSE,       use_verbose = FALSE     )   }, simplify = FALSE) }) tibble::tibble(   Run = 1:10,    `Misclassification Rate (%)` = purrr::map_dbl(outs_kpp, \\(.clus) {     tbl <- table(.clus$memberships, true_groups)     round(min(tbl[1, 1] + tbl[2, 2], tbl[1, 2] + tbl[2, 1]) / 30 * 100, 2)   }) ) |>    knitr::kable()"},{"path":"/articles/kmeans-initialisation.html","id":"exhaustive-k-means","dir":"Articles","previous_headings":"","what":"Exhaustive \\(k\\)-means++","title":"Computing initial centroids in k-means","text":"\\(k\\)-means++ initialization procedure introduces two additional sources randomness: One randomly picking first centroid; , One picking remaining centroids based weighted probability distribution. easy, computational cost linear \\(N\\), get rid first source randomness exhaustively run \\(k\\)-means algorithm \\(k\\)-means++ initialization strategy using observation possible centroid first cluster. call exhaustive \\(k\\)-means++ strategy:","code":"withr::with_seed(1234, {   outs_ekpp <- replicate(10, {     fdakmeans(       x = simulated30$x,       y = simulated30$y,       n_clusters = 2,       seeding_strategy = \"exhaustive-kmeans++\",       warping_class = \"affine\",       centroid_type = \"mean\",       metric = \"l2\",       cluster_on_phase = FALSE,       use_verbose = FALSE     )   }, simplify = FALSE) }) tibble::tibble(   Run = 1:10,    `Misclassification Rate (%)` = purrr::map_dbl(outs_ekpp, \\(.clus) {     tbl <- table(.clus$memberships, true_groups)     round(min(tbl[1, 1] + tbl[2, 2], tbl[1, 2] + tbl[2, 1]) / 30 * 100, 2)   }) ) |>    knitr::kable()"},{"path":"/articles/kmeans-initialisation.html","id":"exhaustive-search","dir":"Articles","previous_headings":"","what":"Exhaustive search","title":"Computing initial centroids in k-means","text":"completeness, also possible perform exhaustive search although rarely practical. simulated data \\(N = 30\\) curves looking \\(2\\), achieved setting seeding_strategy = \"exhaustive\" require run algorithm 435 times instead \\(30\\) times exhaustive \\(k\\)-means++ strategy already achieves excellent robustness performances.","code":""},{"path":"/articles/kmeans-initialisation.html","id":"hierarchial-clustering","dir":"Articles","previous_headings":"","what":"Hierarchial clustering","title":"Computing initial centroids in k-means","text":"alternative use hierarchical clustering \\(k\\)-means get good initial candidates centroids: strategy completely deterministic. case, seems work well. However, perform badly \\(k\\)-means clustering hierarchial clustering meant provide clusters first place. Note also implement DBSCAN initialization strategy similar fashion, added benefit autotuning number clusters look . currently implemented user can well carry hand. First, run fdadbscan() data, tell many clusters search . use cluster medoids seeds argument fdakmeans().","code":"out <- fdakmeans(   x = simulated30$x,   y = simulated30$y,   n_clusters = 2,   seeding_strategy = \"hclust\",   warping_class = \"affine\",   centroid_type = \"mean\",   metric = \"l2\",   cluster_on_phase = FALSE,   use_verbose = FALSE ) knitr::kable(table(out_hclust$memberships, true_groups))"},{"path":"/articles/kmeans-initialisation.html","id":"final-recommandations","dir":"Articles","previous_headings":"","what":"Final recommandations","title":"Computing initial centroids in k-means","text":"functional data sets reasonable sample size, recommend use exhaustive \\(k\\)-means++ strategy. moderate large sample sizes, recommend switch \\(k\\)-means++ strategy. latter current running default fdakmeans().","code":""},{"path":[]},{"path":"/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Aymeric Stamm. Author, maintainer. Laura Sangalli. Contributor. Piercesare Secchi. Contributor. Simone Vantini. Contributor. Valeria Vitelli. Contributor. Alessandro Zito. Contributor.","code":""},{"path":"/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Stamm (2023). fdacluster: Joint Clustering Alignment Functional Data. https://astamm.github.io/fdacluster/index.html, https://github.com/astamm/fdacluster.","code":"@Manual{,   title = {fdacluster: Joint Clustering and Alignment of Functional Data},   author = {Aymeric Stamm},   year = {2023},   note = {https://astamm.github.io/fdacluster/index.html, https://github.com/astamm/fdacluster}, }"},{"path":"/index.html","id":"fdacluster-","dir":"","previous_headings":"","what":"Joint Clustering and Alignment of Functional Data","title":"Joint Clustering and Alignment of Functional Data","text":"fdacluster package provides implementations k-means, hierarchical agglomerative DBSCAN clustering methods functional data. Variability functional data intrinsically divided three components: amplitude, phase ancillary variability. first two sources variability can captured dedicated statistical analysis integrates curve alignment step. k-means HAC algorithms implemented fdacluster provide clustering structures based either ampltitude variation (default behavior) phase variation. achieved jointly performing clustering alignment functional data set. three main related functions fdakmeans() k-means, fdahclust() HAC fdadbscan() DBSCAN. methods handle multivariate codomains.","code":""},{"path":"/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Joint Clustering and Alignment of Functional Data","text":"can install official version CRAN via: can opt install development version GitHub :","code":"install.packages(\"fdacluster\") # install.packages(\"remotes\") remotes::install_github(\"astamm/fdacluster\")"},{"path":[]},{"path":"/index.html","id":"data-set","dir":"","previous_headings":"Example","what":"Data set","title":"Joint Clustering and Alignment of Functional Data","text":"Let us consider following simulated example 30 1-dimensional curves: Looking data set, seems shall expect 3 groups aim clustering based phase variability probably 2 groups search clustering structure based amplitude variability.","code":""},{"path":"/index.html","id":"k-means-based-on-amplitude-variability","dir":"","previous_headings":"Example","what":"k-means based on amplitude variability","title":"Joint Clustering and Alignment of Functional Data","text":"can perform k-means clustering based amplitude variability follows: fdakmeans(), fdahclust() fdadbscan() functions returns object class caps (Clustering Amplitude Phase Separation) S3 specialized methods ggplot2::autoplot() graphics::plot() implemented. Therefore, can visualize results simply :","code":"out1 <- fdakmeans(   simulated30$x,   simulated30$y,   seeds = c(1, 21),   n_clusters = 2,   centroid_type = \"mean\",   warping_class = \"affine\",   metric = \"pearson\",    cluster_on_phase = FALSE ) #> Information about the data set: #>  - Number of observations: 30 #>  - Number of dimensions: 1 #>  - Number of points: 200 #>  #> Information about cluster initialization: #>  - Number of clusters: 2 #>  - Initial seeds for cluster centers:          1        21 #>  #> Information about the methods used within the algorithm: #>  - Warping method: affine #>  - Center method: mean #>  - Dissimilarity method: pearson #>  - Optimization method: bobyqa #>  #> Information about warping parameter bounds: #>  - Warping options:    0.1500   0.1500 #>  #> Information about convergence criteria: #>  - Maximum number of iterations: 100 #>  - Distance relative tolerance: 0.001 #>  #> Information about parallelization setup: #>  - Number of threads: 1 #>  - Parallel method: 0 #>  #> Other information: #>  - Use fence to robustify: 0 #>  - Check total dissimilarity: 1 #>  - Compute overall center: 0 #>  #> Running k-centroid algorithm: #>  - Iteration #1 #>    * Size of cluster #0: 20 #>    * Size of cluster #1: 10 #>  - Iteration #2 #>    * Size of cluster #0: 20 #>    * Size of cluster #1: 10 #>  #> Active stopping criteria: #>  - Memberships did not change. plot(out1, type = \"amplitude\") plot(out1, type = \"phase\")"},{"path":"/index.html","id":"k-means-based-on-phase-variability","dir":"","previous_headings":"Example","what":"k-means based on phase variability","title":"Joint Clustering and Alignment of Functional Data","text":"can perform k-means clustering based phase variability switch cluster_on_phase argument TRUE: can inspect result:   can perform similar analyses using HAC DBSCAN instead k-means. fdacluster package also provides visualization tools help choosing optimal number cluster based WSS silhouette values. can achieved using combination functions compare_caps() plot.mcaps().","code":"out2 <- fdakmeans(   simulated30$x,   simulated30$y,   seeds = c(1, 11, 21),   n_clusters = 3,   centroid_type = \"mean\",   warping_class = \"affine\",   metric = \"pearson\",    cluster_on_phase = TRUE ) #> Information about the data set: #>  - Number of observations: 30 #>  - Number of dimensions: 1 #>  - Number of points: 200 #>  #> Information about cluster initialization: #>  - Number of clusters: 3 #>  - Initial seeds for cluster centers:          1        11        21 #>  #> Information about the methods used within the algorithm: #>  - Warping method: affine #>  - Center method: mean #>  - Dissimilarity method: pearson #>  - Optimization method: bobyqa #>  #> Information about warping parameter bounds: #>  - Warping options:    0.1500   0.1500 #>  #> Information about convergence criteria: #>  - Maximum number of iterations: 100 #>  - Distance relative tolerance: 0.001 #>  #> Information about parallelization setup: #>  - Number of threads: 1 #>  - Parallel method: 0 #>  #> Other information: #>  - Use fence to robustify: 0 #>  - Check total dissimilarity: 1 #>  - Compute overall center: 0 #>  #> Running k-centroid algorithm: #>  - Iteration #1 #>    * Size of cluster #0: 10 #>    * Size of cluster #1: 10 #>    * Size of cluster #2: 10 #>  - Iteration #2 #>    * Size of cluster #0: 10 #>    * Size of cluster #1: 10 #>    * Size of cluster #2: 10 #>  #> Active stopping criteria: #>  - Memberships did not change. plot(out2, type = \"amplitude\") plot(out2, type = \"phase\")"},{"path":"/reference/autoplot.caps.html","id":null,"dir":"Reference","previous_headings":"","what":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","title":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","text":"function creates visualization result k-mean alignment algorithm invisibly returns corresponding ggplot2::ggplot object enable customization plot. user can choose visualize either amplitude information data case original aligned curves shown phase information data case estimated warping functions shown.","code":""},{"path":"/reference/autoplot.caps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","text":"","code":"# S3 method for caps autoplot(object, type = c(\"amplitude\", \"phase\"), ...)"},{"path":"/reference/autoplot.caps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","text":"object object class caps. type string specifying type information display. Choices \"amplitude\" plotting original aligned curves represent amplitude information data \"phase\" plotting corresponding warping functions represent phase information data. Defaults \"amplitude\". ... used.","code":""},{"path":"/reference/autoplot.caps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","text":"ggplot2::ggplot object invisibly.","code":""},{"path":"/reference/autoplot.caps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Visualizes the result of a clustering strategy stored in a caps object with\nggplot2 — autoplot.caps","text":"","code":"ggplot2::autoplot(sim30_caps, type = \"amplitude\")  ggplot2::autoplot(sim30_caps, type = \"phase\")"},{"path":"/reference/autoplot.mcaps.html","id":null,"dir":"Reference","previous_headings":"","what":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","title":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","text":"S3 method implementation ggplot2::autoplot() generic objects class mcaps visualize performances multiple caps objects applied data sets either terms WSS terms silhouette values.","code":""},{"path":"/reference/autoplot.mcaps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","text":"","code":"# S3 method for mcaps autoplot(   object,   validation_criterion = c(\"wss\", \"silhouette\"),   what = c(\"mean\", \"distribution\"),   ... )"},{"path":"/reference/autoplot.mcaps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","text":"object object class mcaps. validation_criterion string specifying validation criterion used comparison. Choices \"wss\" \"silhouette\". Defaults \"wss\". string specifying kind information display validation criterion. Choices \"mean\" (plots mean values) \"distribution\" (plots boxplots). Defaults \"mean\". ... arguments passed specific methods.","code":""},{"path":"/reference/autoplot.mcaps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","text":"object class ggplot2::ggplot.","code":""},{"path":"/reference/autoplot.mcaps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Visualizes results of multiple clustering strategies using ggplot2 — autoplot.mcaps","text":"","code":"p <- ggplot2::autoplot(sim30_mcaps)"},{"path":"/reference/caps.html","id":null,"dir":"Reference","previous_headings":"","what":"Class for clustering with amplitude and phase separation — caps","title":"Class for clustering with amplitude and phase separation — caps","text":"k-means algorithm joint amplitude phase separation produces number outputs. class meant encapsulate single object providing dedicated S3 methods e.g. plotting, summarizing, etc. name class stems Clustering Amplitude Phase Separation.","code":""},{"path":"/reference/caps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Class for clustering with amplitude and phase separation — caps","text":"","code":"as_caps(x)  is_caps(x)"},{"path":"/reference/caps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Class for clustering with amplitude and phase separation — caps","text":"x list coercible object class caps.","code":""},{"path":"/reference/caps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Class for clustering with amplitude and phase separation — caps","text":"function as_caps() returns object class caps. function is_caps() returns boolean evaluates TRUE input object class caps.","code":""},{"path":"/reference/caps.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Class for clustering with amplitude and phase separation — caps","text":"object class caps list following components: original_curves: numeric matrix shape \\(N \\times L \\times M\\) storing sample \\(N\\) \\(L\\)-dimensional original curves observed grids size \\(M\\). original_grids: numeric matrix size \\(N \\times M\\) storing grids size \\(M\\) original curves evaluated; aligned_grids: numeric matrix size \\(N \\times M\\) storing grids size \\(M\\) original curves must evaluated aligned; center_curves: numeric matrix shape \\(K \\times L \\times M\\) storing \\(K\\) centers \\(L\\)-dimensional curves observed grid size \\(M\\); center_grids: numeric matrix size \\(K \\times M\\) storing grids size \\(M\\) center curves evaluated; warpings: numeric matrix shape \\(N \\times M\\) storing estimated warping functions \\(N\\) curves evaluated within-cluster common grids size \\(M\\); n_clusters: integer value storing number clusters; memberships: integer vector length \\(N\\) storing cluster ID curve belongs ; distances_to_center: numeric vector length \\(N\\) storing distance curve center cluster; silhouettes: numeric vector length \\(N\\) storing silhouette values observation; amplitude_variation: numeric value storing fraction total variation explained amplitude variability. total_variation: numeric value storing amount total variation. n_iterations: integer value storing number iterations performed convergence; call_name: string storing name function used produce k-means alignment results; call_args: list containing exact arguments passed function call_name produced output.","code":""},{"path":"/reference/caps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Class for clustering with amplitude and phase separation — caps","text":"","code":"as_caps(sim30_caps) #> $original_curves #> , , 1 #>  #>               [,1] #>  [1,]  0.027585567 #>  [2,] -0.019122794 #>  [3,]  0.037127207 #>  [4,] -0.016504298 #>  [5,] -0.053862340 #>  [6,]  0.002390483 #>  [7,]  0.060582573 #>  [8,]  0.031296346 #>  [9,]  0.017802725 #> [10,] -0.016128447 #> [11,] -0.353705417 #> [12,] -0.306154690 #> [13,] -0.268853383 #> [14,] -0.336659606 #> [15,] -0.336139594 #> [16,] -0.282849484 #> [17,] -0.331959677 #> [18,] -0.381681429 #> [19,] -0.261148065 #> [20,] -0.294778598 #> [21,]  0.127915304 #> [22,] -0.115174088 #> [23,]  0.086588678 #> [24,] -0.058058695 #> [25,]  0.092733378 #> [26,]  0.144257098 #> [27,]  0.042433557 #> [28,]  0.018158416 #> [29,] -0.059882343 #> [30,] -0.071571086 #>  #> , , 2 #>  #>               [,1] #>  [1,]  0.056055003 #>  [2,]  0.012604059 #>  [3,]  0.071250063 #>  [4,]  0.014656955 #>  [5,] -0.022282594 #>  [6,]  0.038722846 #>  [7,]  0.096053308 #>  [8,]  0.064451572 #>  [9,]  0.046771344 #> [10,]  0.014178033 #> [11,] -0.332803768 #> [12,] -0.286771832 #> [13,] -0.247743379 #> [14,] -0.319789735 #> [15,] -0.315841203 #> [16,] -0.261729406 #> [17,] -0.311774826 #> [18,] -0.363619635 #> [19,] -0.238761424 #> [20,] -0.275920966 #> [21,]  0.182112461 #> [22,] -0.051964708 #> [23,]  0.143005410 #> [24,]  0.000138365 #> [25,]  0.157593431 #> [26,]  0.211320313 #> [27,]  0.108642486 #> [28,]  0.084472567 #> [29,]  0.002870550 #> [30,] -0.004164329 #>  #> , , 3 #>  #>               [,1] #>  [1,]  0.084745168 #>  [2,]  0.044626092 #>  [3,]  0.105624048 #>  [4,]  0.046139272 #>  [5,]  0.009640254 #>  [6,]  0.075381167 #>  [7,]  0.131781404 #>  [8,]  0.097841962 #>  [9,]  0.075974784 #> [10,]  0.044770905 #> [11,] -0.311445643 #> [12,] -0.267087941 #> [13,] -0.226289222 #> [14,] -0.302611375 #> [15,] -0.295144901 #> [16,] -0.240218256 #> [17,] -0.291163406 #> [18,] -0.345172668 #> [19,] -0.216054147 #> [20,] -0.256724223 #> [21,]  0.235907973 #> [22,]  0.010952036 #> [23,]  0.199042757 #> [24,]  0.058069824 #> [25,]  0.221925897 #> [26,]  0.277834500 #> [27,]  0.174415016 #> [28,]  0.150374942 #> [29,]  0.065316585 #> [30,]  0.062904089 #>  #> , , 4 #>  #>              [,1] #>  [1,]  0.11362927 #>  [2,]  0.07690931 #>  [3,]  0.14021664 #>  [4,]  0.07791130 #>  [5,]  0.04187577 #>  [6,]  0.11232416 #>  [7,]  0.16772645 #>  [8,]  0.13143551 #>  [9,]  0.10538807 #> [10,]  0.07562353 #> [11,] -0.28964722 #> [12,] -0.24711402 #> [13,] -0.20450512 #> [14,] -0.28513364 #> [15,] -0.27406491 #> [16,] -0.21833199 #> [17,] -0.27014045 #> [18,] -0.32635226 #> [19,] -0.19304030 #> [20,] -0.23720041 #> [21,]  0.28925807 #> [22,]  0.07351139 #> [23,]  0.25465227 #> [24,]  0.11568729 #> [25,]  0.28565906 #> [26,]  0.34372811 #> [27,]  0.23968122 #> [28,]  0.21579503 #> [29,]  0.12739697 #> [30,]  0.12955931 #>  #> , , 5 #>  #>              [,1] #>  [1,]  0.14268058 #>  [2,]  0.10941976 #>  [3,]  0.17499543 #>  [4,]  0.10994173 #>  [5,]  0.07439351 #>  [6,]  0.14951063 #>  [7,]  0.20384822 #>  [8,]  0.16520030 #>  [9,]  0.13498629 #> [10,]  0.10670932 #> [11,] -0.26742482 #> [12,] -0.22686117 #> [13,] -0.18240535 #> [14,] -0.26736570 #> [15,] -0.25261557 #> [16,] -0.19608667 #> [17,] -0.24872115 #> [18,] -0.30717026 #> [19,] -0.16973404 #> [20,] -0.21736167 #> [21,]  0.34211915 #> [22,]  0.13564860 #> [23,]  0.30978565 #> [24,]  0.17294242 #> [25,]  0.34872148 #> [26,]  0.40892990 #> [27,]  0.30437139 #> [28,]  0.28066248 #> [29,]  0.18905298 #> [30,]  0.19572654 #>  #> , , 6 #>  #>             [,1] #>  [1,]  0.1718725 #>  [2,]  0.1421236 #>  [3,]  0.2099281 #>  [4,]  0.1421993 #>  [5,]  0.1071631 #>  [6,]  0.1868995 #>  [7,]  0.2401067 #>  [8,]  0.1991045 #>  [9,]  0.1647446 #> [10,]  0.1380017 #> [11,] -0.2447949 #> [12,] -0.2063405 #> [13,] -0.1600043 #> [14,] -0.2493168 #> [15,] -0.2308114 #> [16,] -0.1734985 #> [17,] -0.2269208 #> [18,] -0.2876386 #> [19,] -0.1461496 #> [20,] -0.1972202 #> [21,]  0.3944478 #> [22,]  0.1972990 #> [23,]  0.3643948 #> [24,]  0.2297869 #> [25,]  0.4110421 #> [26,]  0.4733690 #> [27,]  0.3684161 #> [28,]  0.3449072 #> [29,]  0.2502260 #> [30,]  0.2613312 #>  #> , , 7 #>  #>             [,1] #>  [1,]  0.2011785 #>  [2,]  0.1749871 #>  [3,]  0.2449826 #>  [4,]  0.1746530 #>  [5,]  0.1401542 #>  [6,]  0.2244500 #>  [7,]  0.2764621 #>  [8,]  0.2331166 #>  [9,]  0.1946383 #> [10,]  0.1694743 #> [11,] -0.2217742 #> [12,] -0.1855634 #> [13,] -0.1373165 #> [14,] -0.2309963 #> [15,] -0.2086668 #> [16,] -0.1505837 #> [17,] -0.2047548 #> [18,] -0.2677695 #> [19,] -0.1223012 #> [20,] -0.1767884 #> [21,]  0.4462008 #> [22,]  0.2583981 #> [23,]  0.4184318 #> [24,]  0.2861727 #> [25,]  0.4725502 #> [26,]  0.5369752 #> [27,]  0.4317461 #> [28,]  0.4084594 #> [29,]  0.3108576 #> [30,]  0.3262988 #>  #> , , 8 #>  #>              [,1] #>  [1,]  0.23057223 #>  [2,]  0.20797659 #>  [3,]  0.28012680 #>  [4,]  0.20727163 #>  [5,]  0.17333658 #>  [6,]  0.26212140 #>  [7,]  0.31287490 #>  [8,]  0.26720494 #>  [9,]  0.22464267 #> [10,]  0.20110058 #> [11,] -0.19837931 #> [12,] -0.16454089 #> [13,] -0.11435628 #> [14,] -0.21241356 #> [15,] -0.18619667 #> [16,] -0.12735876 #> [17,] -0.18223873 #> [18,] -0.24757491 #> [19,] -0.09820322 #> [20,] -0.15607847 #> [21,]  0.49733519 #> [22,]  0.31888157 #> [23,]  0.47184906 #> [24,]  0.34205171 #> [25,]  0.53317568 #> [26,]  0.59967849 #> [27,]  0.49429288 #> [28,]  0.47124980 #> [29,]  0.37088947 #> [30,]  0.39055551 #>  #> , , 9 #>  #>              [,1] #>  [1,]  0.26002753 #>  [2,]  0.24105876 #>  [3,]  0.31532908 #>  [4,]  0.24002453 #>  [5,]  0.20668012 #>  [6,]  0.29987337 #>  [7,]  0.34930609 #>  [8,]  0.30133837 #>  [9,]  0.25473330 #> [10,]  0.23285444 #> [11,] -0.17462715 #> [12,] -0.14328448 #> [13,] -0.09113836 #> [14,] -0.19357800 #> [15,] -0.16341561 #> [16,] -0.10384000 #> [17,] -0.15938816 #> [18,] -0.22706726 #> [19,] -0.07387002 #> [20,] -0.13510295 #> [21,]  0.54780840 #> [22,]  0.37868539 #> [23,]  0.52459932 #> [24,]  0.39737621 #> [25,]  0.59284902 #> [26,]  0.66140980 #> [27,]  0.55598817 #> [28,]  0.53320941 #> [29,]  0.43026377 #> [30,]  0.45402753 #>  #> , , 10 #>  #>              [,1] #>  [1,]  0.28951840 #>  [2,]  0.27420042 #>  [3,]  0.35055792 #>  [4,]  0.27288101 #>  [5,]  0.24015486 #>  [6,]  0.33766585 #>  [7,]  0.38571686 #>  [8,]  0.33548586 #>  [9,]  0.28488584 #> [10,]  0.26470974 #> [11,] -0.15053463 #> [12,] -0.12180550 #> [13,] -0.06767730 #> [14,] -0.17449912 #> [15,] -0.14033848 #> [16,] -0.08004397 #> [17,] -0.13621881 #> [18,] -0.20625886 #> [19,] -0.04931601 #> [20,] -0.11387429 #> [21,]  0.59757811 #> [22,]  0.43774589 #> [23,]  0.57663564 #> [24,]  0.45209866 #> [25,]  0.65150136 #> [26,]  0.72210064 #> [27,]  0.61676437 #> [28,]  0.59426992 #> [29,]  0.48892288 #> [30,]  0.51664181 #>  #> , , 11 #>  #>              [,1] #>  [1,]  0.31901905 #>  [2,]  0.30736863 #>  [3,]  0.38578205 #>  [4,]  0.30581066 #>  [5,]  0.27373100 #>  [6,]  0.37545915 #>  [7,]  0.42206890 #>  [8,]  0.36961661 #>  [9,]  0.31507612 #> [10,]  0.29664054 #> [11,] -0.12611880 #> [12,] -0.10011538 #> [13,] -0.04398777 #> [14,] -0.15518645 #> [15,] -0.11698017 #> [16,] -0.05598721 #> [17,] -0.11274645 #> [18,] -0.18516212 #> [19,] -0.02455561 #> 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[12,] 0.17245241 #> [13,] 0.25276887 #> [14,] 0.09128936 #> [15,] 0.17978336 #> [16,] 0.24698989 #> [17,] 0.18676547 #> [18,] 0.08589311 #> [19,] 0.28341654 #> [20,] 0.17940460 #> [21,] 1.16215446 #> [22,] 1.10998719 #> [23,] 1.16770591 #> [24,] 1.08778041 #> [25,] 1.29147845 #> [26,] 1.38700958 #> [27,] 1.29396192 #> [28,] 1.27662754 #> [29,] 1.16116888 #> [30,] 1.22074837 #>  #> , , 24 #>  #>            [,1] #>  [1,] 0.6921961 #>  [2,] 0.7266293 #>  [3,] 0.8296844 #>  [4,] 0.7272665 #>  [5,] 0.7063535 #>  [6,] 0.8496512 #>  [7,] 0.8728326 #>  [8,] 0.7984208 #>  [9,] 0.7004154 #> [10,] 0.7072252 #> [11,] 0.2128844 #> [12,] 0.1958416 #> [13,] 0.2780963 #> [14,] 0.1127616 #> [15,] 0.2054295 #> [16,] 0.2729285 #> [17,] 0.2127288 #> [18,] 0.1095861 #> [19,] 0.3095504 #> [20,] 0.2028546 #> [21,] 1.1979076 #> [22,] 1.1523167 #> [23,] 1.2051223 #> [24,] 1.1293195 #> [25,] 1.3291794 #> [26,] 1.4265235 #> [27,] 1.3352708 #> [28,] 1.3184172 #> [29,] 1.2040921 #> [30,] 1.2641615 #>  #> , , 25 #>  #>            [,1] #>  [1,] 0.7192916 #>  [2,] 0.7569211 #>  [3,] 0.8617670 #>  [4,] 0.7582071 #>  [5,] 0.7383733 #>  [6,] 0.8835700 #>  [7,] 0.9046508 #>  [8,] 0.8292897 #>  [9,] 0.7287349 #> [10,] 0.7376254 #> [11,] 0.2400206 #> [12,] 0.2192812 #> [13,] 0.3034485 #> [14,] 0.1343320 #> [15,] 0.2311467 #> [16,] 0.2988972 #> [17,] 0.2387728 #> [18,] 0.1333895 #> [19,] 0.3356906 #> [20,] 0.2263692 #> [21,] 1.2323873 #> [22,] 1.1930367 #> [23,] 1.2411927 #> [24,] 1.1696011 #> [25,] 1.3649625 #> [26,] 1.4641067 #> [27,] 1.3747658 #> [28,] 1.3584007 #> [29,] 1.2455152 #> [30,] 1.3057382 #>  #> , , 26 #>  #>            [,1] #>  [1,] 0.7460483 #>  [2,] 0.7867946 #>  [3,] 0.8934237 #>  [4,] 0.7888069 #>  [5,] 0.7700838 #>  [6,] 0.9169598 #>  [7,] 0.9359070 #>  [8,] 0.8597274 #>  [9,] 0.7567618 #> [10,] 0.7677440 #> [11,] 0.2672228 #> [12,] 0.2427602 #> [13,] 0.3288113 #> [14,] 0.1559910 #> [15,] 0.2569203 #> [16,] 0.3248802 #> [17,] 0.2648819 #> [18,] 0.1572908 #> [19,] 0.3618233 #> [20,] 0.2499360 #> [21,] 1.2655618 #> [22,] 1.2320985 #> [23,] 1.2758817 #> [24,] 1.2085873 #> [25,] 1.3987807 #> [26,] 1.4997122 #> [27,] 1.4123986 #> [28,] 1.3965289 #> [29,] 1.2853938 #> [30,] 1.3454249 #>  #> , , 27 #>  #>            [,1] #>  [1,] 0.7724463 #>  [2,] 0.8162244 #>  [3,] 0.9246302 #>  [4,] 0.8190419 #>  [5,] 0.8014608 #>  [6,] 0.9497909 #>  [7,] 0.9665737 #>  [8,] 0.8897102 #>  [9,] 0.7844767 #> [10,] 0.7975598 #> [11,] 0.2944741 #> [12,] 0.2662671 #> [13,] 0.3541708 #> [14,] 0.1777288 #> [15,] 0.2827356 #> [16,] 0.3508615 #> [17,] 0.2910406 #> [18,] 0.1812772 #> [19,] 0.3879347 #> [20,] 0.2735427 #> [21,] 1.2973996 #> [22,] 1.2694549 #> [23,] 1.3091548 #> [24,] 1.2462410 #> [25,] 1.4305886 #> [26,] 1.5332951 #> [27,] 1.4481225 #> [28,] 1.4327543 #> [29,] 1.3236845 #> [30,] 1.3831698 #>  #> , , 28 #>  #>            [,1] #>  [1,] 0.7984659 #>  [2,] 0.8451858 #>  [3,] 0.9553633 #>  [4,] 0.8488887 #>  [5,] 0.8324809 #>  [6,] 0.9820344 #>  [7,] 0.9966239 #>  [8,] 0.9192151 #>  [9,] 0.8118607 #> [10,] 0.8270524 #> [11,] 0.3217580 #> [12,] 0.2897908 #> [13,] 0.3795129 #> [14,] 0.1995360 #> [15,] 0.3085781 #> [16,] 0.3768255 #> [17,] 0.3172335 #> [18,] 0.2053362 #> [19,] 0.4140112 #> [20,] 0.2971771 #> [21,] 1.3278707 #> [22,] 1.3050601 #> [23,] 1.3409788 #> [24,] 1.2825260 #> [25,] 1.4603432 #> [26,] 1.5648124 #> [27,] 1.4818927 #> [28,] 1.4670313 #> [29,] 1.3603454 #> [30,] 1.4189232 #>  #> , , 29 #>  #>            [,1] #>  [1,] 0.8240882 #>  [2,] 0.8736548 #>  [3,] 0.9855999 #>  [4,] 0.8783246 #>  [5,] 0.8631210 #>  [6,] 1.0136625 #>  [7,] 1.0260317 #>  [8,] 0.9482196 #>  [9,] 0.8388954 #> [10,] 0.8562015 #> [11,] 0.3490578 #> [12,] 0.3133202 #> [13,] 0.4048239 #> [14,] 0.2214029 #> [15,] 0.3344332 #> [16,] 0.4027565 #> [17,] 0.3434453 #> [18,] 0.2294552 #> [19,] 0.4400393 #> [20,] 0.3208270 #> [21,] 1.3569459 #> [22,] 1.3388701 #> [23,] 1.3713214 #> [24,] 1.3174074 #> [25,] 1.4880034 #> [26,] 1.5942232 #> [27,] 1.5136665 #> [28,] 1.4993162 #> [29,] 1.3953360 #> [30,] 1.4526375 #>  #> , , 30 #>  #>            [,1] #>  [1,] 0.8492945 #>  [2,] 0.9016080 #>  [3,] 1.0153178 #>  [4,] 0.9073273 #>  [5,] 0.8933584 #>  [6,] 1.0446477 #>  [7,] 1.0547719 #>  [8,] 0.9767020 #>  [9,] 0.8655627 #> [10,] 0.8849876 #> [11,] 0.3763572 #> [12,] 0.3368443 #> [13,] 0.4300901 #> [14,] 0.2433200 #> [15,] 0.3602865 #> [16,] 0.4286392 #> [17,] 0.3696608 #> [18,] 0.2536217 #> [19,] 0.4660056 #> [20,] 0.3444805 #> [21,] 1.3845970 #> [22,] 1.3708425 #> [23,] 1.4001515 #> [24,] 1.3508510 #> [25,] 1.5135303 #> [26,] 1.6214888 #> [27,] 1.5434030 #> [28,] 1.5295673 #> [29,] 1.4286172 #> [30,] 1.4842669 #>  #> , , 31 #>  #>            [,1] #>  [1,] 0.8740669 #>  [2,] 0.9290225 #>  [3,] 1.0444954 #>  [4,] 0.9358750 #>  [5,] 0.9231712 #>  [6,] 1.0749639 #>  [7,] 1.0828204 #>  [8,] 1.0046409 #>  [9,] 0.8918451 #> [10,] 0.9133911 #> [11,] 0.4036398 #> [12,] 0.3603520 #> [13,] 0.4552980 #> [14,] 0.2652778 #> [15,] 0.3861238 #> [16,] 0.4544581 #> [17,] 0.3958650 #> [18,] 0.2778233 #> [19,] 0.4918968 #> [20,] 0.3681256 #> [21,] 1.4107967 #> [22,] 1.4009366 #> [23,] 1.4274395 #> [24,] 1.3828240 #> [25,] 1.5368874 #> [26,] 1.6465726 #> [27,] 1.5710633 #> [28,] 1.5577449 #> [29,] 1.4601512 #> [30,] 1.5137682 #>  #> , , 32 #>  #>            [,1] #>  [1,] 0.8983877 #>  [2,] 0.9558765 #>  [3,] 1.0731114 #>  [4,] 0.9639468 #>  [5,] 0.9525378 #>  [6,] 1.1045855 #>  [7,] 1.1101535 #>  [8,] 1.0320157 #>  [9,] 0.9177252 #> [10,] 0.9413935 #> [11,] 0.4308894 #> [12,] 0.3838325 #> [13,] 0.4804341 #> [14,] 0.2872670 #> [15,] 0.4119309 #> [16,] 0.4801984 #> [17,] 0.4220429 #> [18,] 0.3020476 #> [19,] 0.5176998 #> [20,] 0.3917503 #> [21,] 1.4355192 #> [22,] 1.4291136 #> [23,] 1.4531565 #> [24,] 1.4132944 #> [25,] 1.5580404 #> [26,] 1.6694404 #> [27,] 1.5966106 #> [28,] 1.5838116 #> [29,] 1.4899019 #> [30,] 1.5411001 #>  #> , , 33 #>  #>            [,1] #>  [1,] 0.9222398 #>  [2,] 0.9821485 #>  [3,] 1.1011455 #>  [4,] 0.9915220 #>  [5,] 0.9814372 #>  [6,] 1.1334880 #>  [7,] 1.1367488 #>  [8,] 1.0588065 #>  [9,] 0.9431864 #> [10,] 0.9689762 #> [11,] 0.4580902 #> [12,] 0.4072748 #> [13,] 0.5054851 #> [14,] 0.3092781 #> [15,] 0.4376938 #> [16,] 0.5058449 #> [17,] 0.4481798 #> [18,] 0.3262823 #> [19,] 0.5434015 #> [20,] 0.4153429 #> [21,] 1.4587395 #> [22,] 1.4553364 #> [23,] 1.4772754 #> [24,] 1.4422317 #> [25,] 1.5769572 #> [26,] 1.6900600 #> [27,] 1.6200105 #> [28,] 1.6077320 #> [29,] 1.5178349 #> [30,] 1.5662239 #>  #> , , 34 #>  #>            [,1] #>  [1,] 0.9456067 #>  [2,] 1.0078177 #>  [3,] 1.1285779 #>  [4,] 1.0185807 #>  [5,] 1.0098492 #>  [6,] 1.1616474 #>  [7,] 1.1625846 #>  [8,] 1.0849938 #>  [9,] 0.9682124 #> [10,] 0.9961214 #> [11,] 0.4852261 #> [12,] 0.4306684 #> [13,] 0.5304380 #> [14,] 0.3313018 #> [15,] 0.4633986 #> [16,] 0.5313828 #> [17,] 0.4742610 #> [18,] 0.3505153 #> [19,] 0.5689892 #> [20,] 0.4388919 #> [21,] 1.4804337 #> [22,] 1.4795700 #> [23,] 1.4997700 #> [24,] 1.4696062 #> [25,] 1.5936085 #> [26,] 1.7084018 #> [27,] 1.6412306 #> [28,] 1.6294729 #> [29,] 1.5439172 #> [30,] 1.5891031 #>  #> , , 35 #>  #>            [,1] #>  [1,] 0.9684723 #>  [2,] 1.0328643 #>  [3,] 1.1553893 #>  [4,] 1.0451035 #>  [5,] 1.0377539 #>  [6,] 1.1890411 #>  [7,] 1.1876398 #>  [8,] 1.1105590 #>  [9,] 0.9927871 #> [10,] 1.0228116 #> [11,] 0.5122817 #> [12,] 0.4540025 #> [13,] 0.5552797 #> [14,] 0.3533288 #> [15,] 0.4890315 #> [16,] 0.5567977 #> [17,] 0.5002720 #> [18,] 0.3747344 #> [19,] 0.5944500 #> [20,] 0.4623855 #> [21,] 1.5005793 #> [22,] 1.5017813 #> [23,] 1.5206158 #> [24,] 1.4953897 #> [25,] 1.6079672 #> [26,] 1.7244387 #> [27,] 1.6602407 #> [28,] 1.6490034 #> [29,] 1.5681174 #> [30,] 1.6097038 #>  #> , , 36 #>  #>            [,1] #>  [1,] 0.9908211 #>  [2,] 1.0572690 #>  [3,] 1.1815612 #>  [4,] 1.0710717 #>  [5,] 1.0651319 #>  [6,] 1.2156468 #>  [7,] 1.2118946 #>  [8,] 1.1354839 #>  [9,] 1.0168952 #> [10,] 1.0490299 #> [11,] 0.5392413 #> [12,] 0.4772667 #> [13,] 0.5799974 #> [14,] 0.3753500 #> [15,] 0.5145789 #> [16,] 0.5820751 #> [17,] 0.5261985 #> [18,] 0.3989276 #> [19,] 0.6197714 #> [20,] 0.4858123 #> [21,] 1.5191549 #> [22,] 1.5219391 #> [23,] 1.5397894 #> [24,] 1.5195553 #> [25,] 1.6200089 #> [26,] 1.7381457 #> [27,] 1.6770132 #> [28,] 1.6662951 #> [29,] 1.5904061 #> [30,] 1.6279944 #>  #> , , 37 #>  #>            [,1] #>  [1,] 1.0126379 #>  [2,] 1.0810130 #>  [3,] 1.2070756 #>  [4,] 1.0964670 #>  [5,] 1.0919645 #>  [6,] 1.2414436 #>  [7,] 1.2353296 #>  [8,] 1.1597510 #>  [9,] 1.0405217 #> [10,] 1.0747597 #> [11,] 0.5660896 #> [12,] 0.5004503 #> [13,] 0.6045784 #> [14,] 0.3973562 #> [15,] 0.5400272 #> [16,] 0.6072008 #> [17,] 0.5520264 #> [18,] 0.4230830 #> [19,] 0.6449410 #> [20,] 0.5091611 #> [21,] 1.5361401 #> [22,] 1.5400143 #> [23,] 1.5572688 #> [24,] 1.5420771 #> [25,] 1.6297118 #> [26,] 1.7495007 #> [27,] 1.6915224 #> [28,] 1.6813217 #> [29,] 1.6107553 #> [30,] 1.6439461 #>  #> , , 38 #>  #>            [,1] #>  [1,] 1.0339082 #>  [2,] 1.1040786 #>  [3,] 1.2319152 #>  [4,] 1.1212719 #>  [5,] 1.1182336 #>  [6,] 1.2664111 #>  [7,] 1.2579266 #>  [8,] 1.1833436 #>  [9,] 1.0636520 #> [10,] 1.0999849 #> [11,] 0.5928116 #> [12,] 0.5235432 #> [13,] 0.6290103 #> [14,] 0.4193384 #> [15,] 0.5653633 #> [16,] 0.6321608 #> [17,] 0.5777415 #> [18,] 0.4471887 #> [19,] 0.6699467 #> [20,] 0.5324207 #> [21,] 1.5515163 #> [22,] 1.5559802 #> [23,] 1.5730335 #> [24,] 1.5629309 #> [25,] 1.6370565 #> [26,] 1.7584839 #> [27,] 1.7037456 #> [28,] 1.6940595 #> [29,] 1.6291391 #> [30,] 1.6575325 #>  #> , , 39 #>  #>            [,1] #>  [1,] 1.0546180 #>  [2,] 1.1264485 #>  [3,] 1.2560633 #>  [4,] 1.1454693 #>  [5,] 1.1439215 #>  [6,] 1.2905298 #>  [7,] 1.2796680 #>  [8,] 1.2062454 #>  [9,] 1.0862720 #> [10,] 1.1246901 #> [11,] 0.6193924 #> [12,] 0.5465351 #> [13,] 0.6532807 #> [14,] 0.4412875 #> [15,] 0.5905739 #> [16,] 0.6569414 #> [17,] 0.6033303 #> [18,] 0.4712331 #> [19,] 0.6947762 #> [20,] 0.5555799 #> [21,] 1.5652655 #> [22,] 1.5698118 #> [23,] 1.5870646 #> [24,] 1.5820935 #> [25,] 1.6420265 #> [26,] 1.7650781 #> [27,] 1.7136620 #> [28,] 1.7044873 #> [29,] 1.6455332 #> [30,] 1.6687302 #>  #> , , 40 #>  #>            [,1] #>  [1,] 1.0747537 #>  [2,] 1.1481062 #>  [3,] 1.2795038 #>  [4,] 1.1690427 #>  [5,] 1.1690113 #>  [6,] 1.3137811 #>  [7,] 1.3005370 #>  [8,] 1.2284408 #>  [9,] 1.1083680 #> [10,] 1.1488601 #> [11,] 0.6458171 #> [12,] 0.5694158 #> [13,] 0.6773774 #> [14,] 0.4631946 #> [15,] 0.6156460 #> [16,] 0.6815288 #> [17,] 0.6287789 #> [18,] 0.4952045 #> [19,] 0.7194177 #> [20,] 0.5786278 #> [21,] 1.5773715 #> [22,] 1.5814867 #> [23,] 1.5993445 #> [24,] 1.5995432 #> [25,] 1.6446081 #> [26,] 1.7692690 #> [27,] 1.7212538 #> [28,] 1.7125864 #> [29,] 1.6599153 #> [30,] 1.6775181 #>  #> , , 41 #>  #>            [,1] #>  [1,] 1.0943023 #>  [2,] 1.1690358 #>  [3,] 1.3022213 #>  [4,] 1.1919764 #>  [5,] 1.1934864 #>  [6,] 1.3361474 #>  [7,] 1.3205177 #>  [8,] 1.2499149 #>  [9,] 1.1299268 #> [10,] 1.1724802 #> [11,] 0.6720712 #> [12,] 0.5921753 #> [13,] 0.7012886 #> [14,] 0.4850510 #> [15,] 0.6405669 #> [16,] 0.7059098 #> [17,] 0.6540740 #> [18,] 0.5190915 #> [19,] 0.7438594 #> [20,] 0.6015537 #> [21,] 1.5878193 #> [22,] 1.5909846 #> [23,] 1.6098570 #> [24,] 1.6152599 #> [25,] 1.6447902 #> [26,] 1.7710447 #> [27,] 1.7265053 #> [28,] 1.7183406 #> [29,] 1.6722649 #> [30,] 1.6838782 #>  #> , , 42 #>  #>            [,1] #>  [1,] 1.1132512 #>  [2,] 1.1892223 #>  [3,] 1.3242010 #>  [4,] 1.2142549 #>  [5,] 1.2173309 #>  [6,] 1.3576116 #>  [7,] 1.3395949 #>  [8,] 1.2706534 #>  [9,] 1.1509356 #> [10,] 1.1955364 #> [11,] 0.6981406 #> [12,] 0.6148038 #> [13,] 0.7250024 #> [14,] 0.5068478 #> [15,] 0.6653238 #> [16,] 0.7300713 #> [17,] 0.6792023 #> [18,] 0.5428828 #> [19,] 0.7680899 #> [20,] 0.6243469 #> [21,] 1.5965952 #> [22,] 1.5982876 #> [23,] 1.6185878 #> [24,] 1.6292246 #> [25,] 1.6425646 #> [26,] 1.7703962 #> [27,] 1.7294037 #> [28,] 1.7217363 #> [29,] 1.6825636 #> [30,] 1.6877953 #>  #> , , 43 #>  #>            [,1] #>  [1,] 1.1315884 #>  [2,] 1.2086511 #>  [3,] 1.3454285 #>  [4,] 1.2358635 #>  [5,] 1.2405295 #>  [6,] 1.3781576 #>  [7,] 1.3577541 #>  [8,] 1.2906425 #>  [9,] 1.1713821 #> [10,] 1.2180148 #> [11,] 0.7240111 #> [12,] 0.6372915 #> [13,] 0.7485072 #> [14,] 0.5285763 #> [15,] 0.6899044 #> [16,] 0.7540003 #> [17,] 0.7041508 #> [18,] 0.5665670 #> [19,] 0.7920978 #> [20,] 0.6469968 #> [21,] 1.6036868 #> [22,] 1.6033800 #> [23,] 1.6255240 #> [24,] 1.6414202 #> [25,] 1.6379261 #> [26,] 1.7673170 #> [27,] 1.7299387 #> [28,] 1.7227626 #> [29,] 1.6907948 #> [30,] 1.6892569 #>  #> , , 44 #>  #>            [,1] #>  [1,] 1.1493022 #>  [2,] 1.2273084 #>  [3,] 1.3658903 #>  [4,] 1.2567881 #>  [5,] 1.2630674 #>  [6,] 1.3977701 #>  [7,] 1.3749817 #>  [8,] 1.3098692 #>  [9,] 1.1912543 #> [10,] 1.2399022 #> [11,] 0.7496689 #> [12,] 0.6596288 #> [13,] 0.7717917 #> [14,] 0.5502280 #> [15,] 0.7142964 #> [16,] 0.7776843 #> [17,] 0.7289066 #> [18,] 0.5901332 #> [19,] 0.8158719 #> [20,] 0.6694931 #> [21,] 1.6090832 #> [22,] 1.6062485 #> [23,] 1.6306540 #> [24,] 1.6518306 #> [25,] 1.6308721 #> [26,] 1.7618037 #> [27,] 1.7281026 #> [28,] 1.7214114 #> [29,] 1.6969440 #> [30,] 1.6882536 #>  #> , , 45 #>  #>            [,1] #>  [1,] 1.1663815 #>  [2,] 1.2451810 #>  [3,] 1.3855733 #>  [4,] 1.2770150 #>  [5,] 1.2849303 #>  [6,] 1.4164345 #>  [7,] 1.3912648 #>  [8,] 1.3283209 #>  [9,] 1.2105408 #> [10,] 1.2611859 #> [11,] 0.7751003 #> [12,] 0.6818060 #> [13,] 0.7948447 #> [14,] 0.5717945 #> [15,] 0.7384876 #> [16,] 0.8011106 #> [17,] 0.7534572 #> [18,] 0.6135703 #> [19,] 0.8394012 #> [20,] 0.6918257 #> [21,] 1.6127749 #> [22,] 1.6068825 #> [23,] 1.6339684 #> [24,] 1.6604415 #> [25,] 1.6214031 #> [26,] 1.7538555 #> [27,] 1.7238906 #> [28,] 1.7176771 #> [29,] 1.7009988 #> [30,] 1.6847788 #>  #> , , 46 #>  #>            [,1] #>  [1,] 1.1828158 #>  [2,] 1.2622564 #>  [3,] 1.4044650 #>  [4,] 1.2965310 #>  [5,] 1.3061044 #>  [6,] 1.4341371 #>  [7,] 1.4065909 #>  [8,] 1.3459858 #>  [9,] 1.2292303 #> [10,] 1.2818535 #> [11,] 0.8002921 #> [12,] 0.7038140 #> [13,] 0.8176551 #> [14,] 0.5932672 #> [15,] 0.7624663 #> [16,] 0.8242673 #> [17,] 0.7777900 #> [18,] 0.6368675 #> [19,] 0.8626750 #> [20,] 0.7139843 #> [21,] 1.6147540 #> [22,] 1.6052735 #> [23,] 1.6354588 #> [24,] 1.6672403 #> [25,] 1.6095226 #> [26,] 1.7434746 #> [27,] 1.7173004 #> [28,] 1.7115569 #> [29,] 1.7029487 #> [30,] 1.6788290 #>  #> , , 47 #>  #>            [,1] #>  [1,] 1.1985947 #>  [2,] 1.2785227 #>  [3,] 1.4225536 #>  [4,] 1.3153235 #>  [5,] 1.3265765 #>  [6,] 1.4508647 #>  [7,] 1.4209487 #>  [8,] 1.3628525 #>  [9,] 1.2473124 #> [10,] 1.3018931 #> [11,] 0.8252310 #> [12,] 0.7256433 #> [13,] 0.8402122 #> [14,] 0.6146379 #> [15,] 0.7862207 #> [16,] 0.8471422 #> [17,] 0.8018930 #> [18,] 0.6600143 #> [19,] 0.8856826 #> [20,] 0.7359592 #> [21,] 1.6150136 #> [22,] 1.6014157 #> [23,] 1.6351190 #> [24,] 1.6722156 #> [25,] 1.5952371 #> [26,] 1.7306660 #> [27,] 1.7083326 #> [28,] 1.7030510 #> [29,] 1.7027855 #> [30,] 1.6704037 #>  #> , , 48 #>  #>            [,1] #>  [1,] 1.2137087 #>  [2,] 1.2939686 #>  [3,] 1.4398276 #>  [4,] 1.3333805 #>  [5,] 1.3463340 #>  [6,] 1.4666051 #>  [7,] 1.4343270 #>  [8,] 1.3789102 #>  [9,] 1.2647767 #> [10,] 1.3212932 #> [11,] 0.8499041 #> [12,] 0.7472850 #> [13,] 0.8625054 #> [14,] 0.6358984 #> [15,] 0.8097394 #> [16,] 0.8697239 #> [17,] 0.8257541 #> [18,] 0.6829999 #> [19,] 0.9084137 #> [20,] 0.7577405 #> [21,] 1.6135487 #> [22,] 1.5953058 #> [23,] 1.6329441 #> [24,] 1.6753579 #> [25,] 1.5785560 #> [26,] 1.7154375 #> [27,] 1.6969905 #> [28,] 1.6921621 #> [29,] 1.7005030 #> [30,] 1.6595055 #>  #> , , 49 #>  #>            [,1] #>  [1,] 1.2281482 #>  [2,] 1.3085835 #>  [3,] 1.4562763 #>  [4,] 1.3506903 #>  [5,] 1.3653648 #>  [6,] 1.4813466 #>  [7,] 1.4467156 #>  [8,] 1.3941489 #>  [9,] 1.2816134 #> [10,] 1.3400428 #> [11,] 0.8742990 #> [12,] 0.7687300 #> [13,] 0.8845243 #> [14,] 0.6570406 #> [15,] 0.8330111 #> [16,] 0.8920007 #> [17,] 0.8493615 #> [18,] 0.7058142 #> [19,] 0.9308582 #> [20,] 0.7793188 #> [21,] 1.6103557 #> [22,] 1.5869430 #> [23,] 1.6289311 #> [24,] 1.6766591 #> [25,] 1.5594917 #> [26,] 1.6978000 #> [27,] 1.6832802 #> [28,] 1.6788959 #> [29,] 1.6960971 #> [30,] 1.6461400 #>  #> , , 50 #>  #>            [,1] #>  [1,] 1.2419046 #>  [2,] 1.3223572 #>  [3,] 1.4718894 #>  [4,] 1.3672418 #>  [5,] 1.3836570 #>  [6,] 1.4950782 #>  [7,] 1.4581047 #>  [8,] 1.4085587 #>  [9,] 1.2978130 #> [10,] 1.3581313 #> [11,] 0.8984030 #> [12,] 0.7899695 #> [13,] 0.9062587 #> [14,] 0.6780565 #> [15,] 0.8560247 #> [16,] 0.9139615 #> [17,] 0.8727039 #> [18,] 0.7284468 #> [19,] 0.9530060 #> [20,] 0.8006845 #> [21,] 1.6054324 #> [22,] 1.5763292 #> [23,] 1.6230786 #> [24,] 1.6761129 #> [25,] 1.5380599 #> [26,] 1.6777671 #> [27,] 1.6672108 #> [28,] 1.6632609 #> [29,] 1.6895661 #> [30,] 1.6303159 #>  #> , , 51 #>  #>            [,1] #>  [1,] 1.2549693 #>  [2,] 1.3352803 #>  [3,] 1.4866572 #>  [4,] 1.3830244 #>  [5,] 1.4011997 #>  [6,] 1.5077896 #>  [7,] 1.4684853 #>  [8,] 1.4221307 #>  [9,] 1.3133665 #> [10,] 1.3755485 #> [11,] 0.9222042 #> [12,] 0.8109949 #> [13,] 0.9276988 #> [14,] 0.6989382 #> [15,] 0.8787694 #> [16,] 0.9355954 #> [17,] 0.8957697 #> [18,] 0.7508877 #> [19,] 0.9748474 #> [20,] 0.8218285 #> [21,] 1.5987782 #> [22,] 1.5634689 #> [23,] 1.6153871 #> [24,] 1.6737145 #> [25,] 1.5142791 #> [26,] 1.6553556 #> [27,] 1.6487940 #> [28,] 1.6452686 #> [29,] 1.6809104 #> [30,] 1.6120452 #>  #> , , 52 #>  #>            [,1] #>  [1,] 1.2673343 #>  [2,] 1.3473437 #>  [3,] 1.5005705 #>  [4,] 1.3980278 #>  [5,] 1.4179819 #>  [6,] 1.5194712 #>  [7,] 1.4778486 #>  [8,] 1.4348562 #>  [9,] 1.3282651 #> [10,] 1.3922846 #> [11,] 0.9456907 #> [12,] 0.8317977 #> [13,] 0.9488347 #> [14,] 0.7196779 #> [15,] 0.9012346 #> [16,] 0.9568917 #> [17,] 0.9185481 #> [18,] 0.7731271 #> [19,] 0.9963728 #> [20,] 0.8427417 #> [21,] 1.5903940 #> [22,] 1.5483692 #> [23,] 1.6058586 #> [24,] 1.6694609 #> [25,] 1.4881710 #> [26,] 1.6305851 #> [27,] 1.6280444 #> [28,] 1.6249332 #> [29,] 1.6701325 #> [30,] 1.5913429 #>  #> , , 53 #>  #>            [,1] #>  [1,] 1.2789919 #>  [2,] 1.3585391 #>  [3,] 1.5136203 #>  [4,] 1.4122422 #>  [5,] 1.4339936 #>  [6,] 1.5301137 #>  [7,] 1.4861866 #>  [8,] 1.4467272 #>  [9,] 1.3425005 #> [10,] 1.4083301 #> [11,] 0.9688508 #> [12,] 0.8523694 #> [13,] 0.9696571 #> [14,] 0.7402678 #> [15,] 0.9234098 #> [16,] 0.9778400 #> [17,] 0.9410281 #> [18,] 0.7951551 #> [19,] 1.0175730 #> [20,] 0.8634152 #> [21,] 1.5802822 #> [22,] 1.5310397 #> [23,] 1.5944971 #> [24,] 1.6633509 #> [25,] 1.4597605 #> [26,] 1.6034782 #> [27,] 1.6049797 #> [28,] 1.6022719 #> [29,] 1.6572372 #> [30,] 1.5682272 #>  #> , , 54 #>  #>            [,1] #>  [1,] 1.2899347 #>  [2,] 1.3688585 #>  [3,] 1.5257985 #>  [4,] 1.4256583 #>  [5,] 1.4492250 #>  [6,] 1.5397088 #>  [7,] 1.4934916 #>  [8,] 1.4577359 #>  [9,] 1.3560648 #> [10,] 1.4236760 #> [11,] 0.9916732 #> [12,] 0.8727018 #> [13,] 0.9901565 #> [14,] 0.7607006 #> [15,] 0.9452849 #> [16,] 0.9984301 #> [17,] 0.9631992 #> [18,] 0.8169622 #> [19,] 1.0384387 #> [20,] 0.8838402 #> [21,] 1.5684469 #> [22,] 1.5114931 #> [23,] 1.5813082 #> [24,] 1.6553846 #> [25,] 1.4290755 #> [26,] 1.5740604 #> [27,] 1.5796202 #> [28,] 1.5773048 #> [29,] 1.6422318 #> [30,] 1.5427196 #>  #> , , 55 #>  #>            [,1] #>  [1,] 1.3001560 #>  [2,] 1.3782944 #>  [3,] 1.5370973 #>  [4,] 1.4382671 #>  [5,] 1.4636666 #>  [6,] 1.5482484 #>  [7,] 1.4997565 #>  [8,] 1.4678754 #>  [9,] 1.3689502 #> [10,] 1.4383137 #> [11,] 1.0141468 #> [12,] 0.8927869 #> [13,] 1.0103239 #> [14,] 0.7809686 #> [15,] 0.9668499 #> [16,] 1.0186522 #> [17,] 0.9850511 #> [18,] 0.8385391 #> [19,] 1.0589611 #> [20,] 0.9040082 #> [21,] 1.5548937 #> [22,] 1.4897444 #> [23,] 1.5662993 #> [24,] 1.6455643 #> [25,] 1.3961470 #> [26,] 1.5423603 #> [27,] 1.5519892 #> [28,] 1.5500550 #> [29,] 1.6251255 #> [30,] 1.5148445 #>  #> , , 56 #>  #>            [,1] #>  [1,] 1.3096490 #>  [2,] 1.3868399 #>  [3,] 1.5475091 #>  [4,] 1.4500599 #>  [5,] 1.4773095 #>  [6,] 1.5557251 #>  [7,] 1.5049745 #>  [8,] 1.4771389 #>  [9,] 1.3811495 #> [10,] 1.4522349 #> [11,] 1.0362608 #> [12,] 0.9126168 #> [13,] 1.0301504 #> [14,] 0.8010646 #> [15,] 0.9880950 #> [16,] 1.0384966 #> [17,] 1.0065735 #> [18,] 0.8598765 #> [19,] 1.0791315 #> [20,] 0.9239108 #> [21,] 1.5396297 #> [22,] 1.4658114 #> [23,] 1.5494797 #> [24,] 1.6338938 #> [25,] 1.3610090 #> [26,] 1.5084094 #> [27,] 1.5221131 #> [28,] 1.5205483 #> [29,] 1.6059301 #> [30,] 1.4846299 #>  #> , , 57 #>  #>            [,1] #>  [1,] 1.3184076 #>  [2,] 1.3944886 #>  [3,] 1.5570271 #>  [4,] 1.4610286 #>  [5,] 1.4901453 #>  [6,] 1.5621318 #>  [7,] 1.5091392 #>  [8,] 1.4855202 #>  [9,] 1.3926557 #> [10,] 1.4654316 #> [11,] 1.0580047 #> [12,] 0.9321837 #> [13,] 1.0496275 #> [14,] 0.8209814 #> [15,] 1.0090108 #> [16,] 1.0579539 #> [17,] 1.0277566 #> [18,] 0.8809654 #> [19,] 1.0989415 #> [20,] 0.9435398 #> [21,] 1.5226638 #> [22,] 1.4397148 #> [23,] 1.5308605 #> [24,] 1.6203786 #> [25,] 1.3236989 #> [26,] 1.4722422 #> [27,] 1.4900208 #> [28,] 1.4888138 #> [29,] 1.5846595 #> [30,] 1.4521067 #>  #> , , 58 #>  #>            [,1] #>  [1,] 1.3264258 #>  [2,] 1.4012343 #>  [3,] 1.5656446 #>  [4,] 1.4711651 #>  [5,] 1.5021657 #>  [6,] 1.5674620 #>  [7,] 1.5122448 #>  [8,] 1.4930134 #>  [9,] 1.4034622 #> [10,] 1.4778961 #> [11,] 1.0793681 #> [12,] 0.9514800 #> [13,] 1.0687466 #> [14,] 0.8407117 #> [15,] 1.0295879 #> [16,] 1.0770151 #> [17,] 1.0485908 #> [18,] 0.9017968 #> [19,] 1.1183826 #> [20,] 0.9628872 #> [21,] 1.5040063 #> [22,] 1.4114779 #> [23,] 1.5104545 #> [24,] 1.6050261 #> [25,] 1.2842569 #> [26,] 1.4338962 #> [27,] 1.4557443 #> [28,] 1.4548832 #> [29,] 1.5613300 #> [30,] 1.4173091 #>  #> , , 59 #>  #>            [,1] #>  [1,] 1.3336979 #>  [2,] 1.4070714 #>  [3,] 1.5733555 #>  [4,] 1.4804619 #>  [5,] 1.5133631 #>  [6,] 1.5717097 #>  [7,] 1.5142854 #>  [8,] 1.4996132 #>  [9,] 1.4135624 #> [10,] 1.4896212 #> [11,] 1.1003411 #> [12,] 0.9704983 #> [13,] 1.0874997 #> [14,] 0.8602487 #> [15,] 1.0498173 #> [16,] 1.0956712 #> [17,] 1.0690666 #> [18,] 0.9223621 #> [19,] 1.1374470 #> [20,] 0.9819451 #> [21,] 1.4836692 #> [22,] 1.3811268 #> [23,] 1.4882763 #> [24,] 1.5878454 #> [25,] 1.2427264 #> [26,] 1.3934117 #> [27,] 1.4193187 #> [28,] 1.4187912 #> [29,] 1.5359603 #> [30,] 1.3802745 #>  #> , , 60 #>  #>            [,1] #>  [1,] 1.3402187 #>  [2,] 1.4119946 #>  [3,] 1.5801537 #>  [4,] 1.4889118 #>  [5,] 1.5237299 #>  [6,] 1.5748690 #>  [7,] 1.5152558 #>  [8,] 1.5053145 #>  [9,] 1.4229504 #> [10,] 1.5005998 #> [11,] 1.1209139 #> [12,] 0.9892312 #> [13,] 1.1058788 #> [14,] 0.8795855 #> [15,] 1.0696901 #> [16,] 1.1139137 #> [17,] 1.0891750 #> [18,] 0.9426529 #> [19,] 1.1561268 #> [20,] 1.0007060 #> [21,] 1.4616660 #> [22,] 1.3486902 #> [23,] 1.4643426 #> [24,] 1.5688474 #> [25,] 1.1991540 #> [26,] 1.3508321 #> [27,] 1.3807816 #> [28,] 1.3805755 #> [29,] 1.5085712 #> [30,] 1.3410436 #>  #> , , 61 #>  #>            [,1] #>  [1,] 1.3459830 #>  [2,] 1.4159990 #>  [3,] 1.5860340 #>  [4,] 1.4965075 #>  [5,] 1.5332591 #>  [6,] 1.5769346 #>  [7,] 1.5151508 #>  [8,] 1.5101127 #>  [9,] 1.4316202 #> [10,] 1.5108252 #> [11,] 1.1410769 #> [12,] 1.0076718 #> [13,] 1.1238760 #> [14,] 0.8987153 #> [15,] 1.0891977 #> [16,] 1.1317342 #> [17,] 1.1089069 #> [18,] 0.9626606 #> [19,] 1.1744144 #> [20,] 1.0191622 #> [21,] 1.4380121 #> [22,] 1.3141997 #> [23,] 1.4386715 #> [24,] 1.5480448 #> [25,] 1.1535891 #> [26,] 1.3062036 #> [27,] 1.3401737 #> [28,] 1.3402767 #> [29,] 1.4791860 #> [30,] 1.2996602 #>  #> , , 62 #>  #>            [,1] #>  [1,] 1.3509860 #>  [2,] 1.4190799 #>  [3,] 1.5909909 #>  [4,] 1.5032424 #>  [5,] 1.5419439 #>  [6,] 1.5779016 #>  [7,] 1.5139657 #>  [8,] 1.5140033 #>  [9,] 1.4395663 #> [10,] 1.5202910 #> [11,] 1.1608211 #> [12,] 1.0258131 #> [13,] 1.1414839 #> [14,] 0.9176315 #> [15,] 1.1083317 #> [16,] 1.1491246 #> [17,] 1.1282537 #> [18,] 0.9823772 #> [19,] 1.1923025 #> [20,] 1.0373065 #> [21,] 1.4127243 #> [22,] 1.2776897 #> [23,] 1.4112833 #> [24,] 1.5254521 #> [25,] 1.1060843 #> [26,] 1.2595755 #> [27,] 1.2975385 #> [28,] 1.2979383 #> [29,] 1.4478304 #> [30,] 1.2561710 #>  #> , , 63 #>  #>            [,1] #>  [1,] 1.3552232 #>  [2,] 1.4212333 #>  [3,] 1.5950197 #>  [4,] 1.5091098 #>  [5,] 1.5497779 #>  [6,] 1.5777651 #>  [7,] 1.5116957 #>  [8,] 1.5169824 #>  [9,] 1.4467834 #> [10,] 1.5289909 #> [11,] 1.1801374 #> [12,] 1.0436482 #> [13,] 1.1586951 #> [14,] 0.9363275 #> [15,] 1.1270840 #> [16,] 1.1660772 #> [17,] 1.1472070 #> [18,] 1.0017948 #> [19,] 1.2097837 #> [20,] 1.0551318 #> [21,] 1.3858210 #> [22,] 1.2391970 #> [23,] 1.3821998 #> [24,] 1.5010855 #> [25,] 1.0566951 #> [26,] 1.2109996 #> [27,] 1.2529224 #> [28,] 1.2536065 #> [29,] 1.4145323 #> [30,] 1.2106264 #>  #> , , 64 #>  #>            [,1] #>  [1,] 1.3586900 #>  [2,] 1.4224550 #>  [3,] 1.5981158 #>  [4,] 1.5141035 #>  [5,] 1.5567548 #>  [6,] 1.5765208 #>  [7,] 1.5083365 #>  [8,] 1.5190464 #>  [9,] 1.4532662 #> [10,] 1.5369191 #> [11,] 1.1990171 #> [12,] 1.0611705 #> [13,] 1.1755027 #> [14,] 0.9547971 #> [15,] 1.1454466 #> [16,] 1.1825843 #> [17,] 1.1657585 #> [18,] 1.0209055 #> [19,] 1.2268512 #> [20,] 1.0726311 #> [21,] 1.3573222 #> [22,] 1.1987616 #> [23,] 1.3514450 #> [24,] 1.4749633 #> [25,] 1.0054801 #> [26,] 1.1605309 #> [27,] 1.2063746 #> [28,] 1.2073306 #> [29,] 1.3793219 #> [30,] 1.1630793 #>  #> , , 65 #>  #>            [,1] #>  [1,] 1.3613824 #>  [2,] 1.4227414 #>  [3,] 1.6002747 #>  [4,] 1.5182173 #>  [5,] 1.5628688 #>  [6,] 1.5741645 #>  [7,] 1.5038839 #>  [8,] 1.5201916 #>  [9,] 1.4590100 #> [10,] 1.5440697 #> [11,] 1.2174518 #> [12,] 1.0783737 #> [13,] 1.1918996 #> [14,] 0.9730340 #> [15,] 1.1634118 #> [16,] 1.1986387 #> [17,] 1.1839002 #> [18,] 1.0397017 #> [19,] 1.2434983 #> [20,] 1.0897977 #> [21,] 1.3272498 #> [22,] 1.1564258 #> [23,] 1.3190444 #> [24,] 1.4471052 #> [25,] 0.9525007 #> [26,] 1.1082271 #> [27,] 1.1579469 #> [28,] 1.1591625 #> [29,] 1.3422317 #> [30,] 1.1135862 #>  #> , , 66 #>  #>            [,1] #>  [1,] 1.3632964 #>  [2,] 1.4220891 #>  [3,] 1.6014923 #>  [4,] 1.5214451 #>  [5,] 1.5681141 #>  [6,] 1.5706921 #>  [7,] 1.4983336 #>  [8,] 1.5204151 #>  [9,] 1.4640100 #> [10,] 1.5504373 #> [11,] 1.2354333 #> [12,] 1.0952513 #> [13,] 1.2078792 #> [14,] 0.9910320 #> [15,] 1.1809721 #> [16,] 1.2142331 #> [17,] 1.2016244 #> [18,] 1.0581760 #> [19,] 1.2597184 #> [20,] 1.1066249 #> [21,] 1.2956269 #> [22,] 1.1122348 #> [23,] 1.2850254 #> [24,] 1.4175330 #> [25,] 0.8978213 #> [26,] 1.0541486 #> [27,] 1.1076941 #> [28,] 1.1091571 #> [29,] 1.3032968 #> [30,] 1.0622064 #>  #> , , 67 #>  #>            [,1] #>  [1,] 1.3644282 #>  [2,] 1.4204948 #>  [3,] 1.6017648 #>  [4,] 1.5237812 #>  [5,] 1.5724853 #>  [6,] 1.5661000 #>  [7,] 1.4916817 #>  [8,] 1.5197140 #>  [9,] 1.4682616 #> [10,] 1.5560166 #> [11,] 1.2529537 #> [12,] 1.1117973 #> [13,] 1.2234352 #> [14,] 1.0087850 #> [15,] 1.1981203 #> [16,] 1.2293608 #> [17,] 1.2189236 #> [18,] 1.0763211 #> [19,] 1.2755052 #> [20,] 1.1231064 #> [21,] 1.2624787 #> [22,] 1.0662366 #> [23,] 1.2494172 #> [24,] 1.3862702 #> [25,] 0.8415092 #> [26,] 0.9983587 #> [27,] 1.0556737 #> [28,] 1.0573719 #> [29,] 1.2625542 #> [30,] 1.0090022 #>  #> , , 68 #>  #>            [,1] #>  [1,] 1.3647740 #>  [2,] 1.4179557 #>  [3,] 1.6010885 #>  [4,] 1.5252197 #>  [5,] 1.5759770 #>  [6,] 1.5603846 #>  [7,] 1.4839243 #>  [8,] 1.5180854 #>  [9,] 1.4717606 #> [10,] 1.5608024 #> [11,] 1.2700053 #> [12,] 1.1280057 #> [13,] 1.2385611 #> [14,] 1.0262874 #> [15,] 1.2148493 #> [16,] 1.2440151 #> [17,] 1.2357904 #> [18,] 1.0941301 #> [19,] 1.2908526 #> [20,] 1.1392358 #> [21,] 1.2278315 #> [22,] 1.0184816 #> [23,] 1.2122510 #> [24,] 1.3533421 #> [25,] 0.7836342 #> [26,] 0.9409231 #> [27,] 1.0019458 #> [28,] 1.0038672 #> [29,] 1.2200435 #> [30,] 0.9540390 #>  #> , , 69 #>  #>            [,1] #>  [1,] 1.3643305 #>  [2,] 1.4144687 #>  [3,] 1.5994598 #>  [4,] 1.5257552 #>  [5,] 1.5785843 #>  [6,] 1.5535424 #>  [7,] 1.4750577 #>  [8,] 1.5155270 #>  [9,] 1.4745026 #> [10,] 1.5647898 #> [11,] 1.2865807 #> [12,] 1.1438708 #> [13,] 1.2532511 #> [14,] 1.0435332 #> [15,] 1.2311523 #> [16,] 1.2581898 #> [17,] 1.2522179 #> [18,] 1.1115959 #> [19,] 1.3057546 #> [20,] 1.1550072 #> [21,] 1.1917137 #> [22,] 0.9690230 #> [23,] 1.1735595 #> [24,] 1.3187759 #> [25,] 0.7242692 #> [26,] 0.8819105 #> [27,] 0.9465731 #> [28,] 0.9487061 #> [29,] 1.1758064 #> [30,] 0.8973851 #>  #> , , 70 #>  #>            [,1] #>  [1,] 1.3630941 #>  [2,] 1.4100314 #>  [3,] 1.5968754 #>  [4,] 1.5253820 #>  [5,] 1.5803022 #>  [6,] 1.5455702 #>  [7,] 1.4650781 #>  [8,] 1.5120365 #>  [9,] 1.4764836 #> [10,] 1.5679740 #> [11,] 1.3026727 #> [12,] 1.1593868 #> [13,] 1.2674992 #> [14,] 1.0605168 #> [15,] 1.2470226 #> [16,] 1.2718786 #> [17,] 1.2681990 #> [18,] 1.1287121 #> [19,] 1.3202057 #> [20,] 1.1704147 #> [21,] 1.1541548 #> [22,] 0.9179165 #> [23,] 1.1333774 #> [24,] 1.2826004 #> [25,] 0.6634896 #> [26,] 0.8213919 #> [27,] 0.8896212 #> [28,] 0.8919540 #> [29,] 1.1298870 #> [30,] 0.8391115 #>  #> , , 71 #>  #>            [,1] #>  [1,] 1.3610616 #>  [2,] 1.4046413 #>  [3,] 1.5933321 #>  [4,] 1.5240947 #>  [5,] 1.5811259 #>  [6,] 1.5364647 #>  [7,] 1.4539819 #>  [8,] 1.5076117 #>  [9,] 1.4776998 #> [10,] 1.5703502 #> [11,] 1.3182744 #> [12,] 1.1745483 #> [13,] 1.2812999 #> [14,] 1.0772328 #> [15,] 1.2624540 #> [16,] 1.2850756 #> [17,] 1.2837273 #> [18,] 1.1454719 #> [19,] 1.3342003 #> [20,] 1.1854524 #> [21,] 1.1151864 #> [22,] 0.8652205 #> [23,] 1.0917409 #> [24,] 1.2448464 #> [25,] 0.6013735 #> [26,] 0.7594410 #> [27,] 0.8311580 #> [28,] 0.8336793 #> [29,] 1.0823315 #> [30,] 0.7792924 #>  #> , , 72 #>  #>            [,1] #>  [1,] 1.3582297 #>  [2,] 1.3982959 #>  [3,] 1.5888268 #>  [4,] 1.5218880 #>  [5,] 1.5810508 #>  [6,] 1.5262230 #>  [7,] 1.4417654 #>  [8,] 1.5022509 #>  [9,] 1.4781472 #> [10,] 1.5719139 #> [11,] 1.3333790 #> [12,] 1.1893501 #> [13,] 1.2946477 #> [14,] 1.0936758 #> [15,] 1.2774401 #> [16,] 1.2977750 #> [17,] 1.2987962 #> [18,] 1.1618692 #> [19,] 1.3477331 #> [20,] 1.2001150 #> [21,] 1.0748412 #> [22,] 0.8109959 #> [23,] 1.0486882 #> [24,] 1.2055463 #> [25,] 0.5380016 #> [26,] 0.6961339 #> [27,] 0.7712540 #> [28,] 0.7739528 #> [29,] 1.0331883 #> [30,] 0.7180044 #>  #> , , 73 #>  #>            [,1] #>  [1,] 1.3545955 #>  [2,] 1.3909931 #>  [3,] 1.5833565 #>  [4,] 1.5187565 #>  [5,] 1.5800724 #>  [6,] 1.5148420 #>  [7,] 1.4284252 #>  [8,] 1.4959521 #>  [9,] 1.4778221 #> [10,] 1.5726607 #> [11,] 1.3479802 #> [12,] 1.2037868 #> [13,] 1.3075373 #> [14,] 1.1098404 #> [15,] 1.2919750 #> [16,] 1.3099716 #> [17,] 1.3133996 #> [18,] 1.1778977 #> [19,] 1.3607991 #> [20,] 1.2143969 #> [21,] 1.0331538 #> [22,] 0.7553061 #> [23,] 1.0042591 #> [24,] 1.1647343 #> [25,] 0.4734569 #> [26,] 0.6315491 #> [27,] 0.7099819 #> [28,] 0.7128475 #> [29,] 0.9825081 #> [30,] 0.6553269 #>  #> , , 74 #>  #>            [,1] #>  [1,] 1.3501559 #>  [2,] 1.3827308 #>  [3,] 1.5769185 #>  [4,] 1.5146948 #>  [5,] 1.5781863 #>  [6,] 1.5023188 #>  [7,] 1.4139578 #>  [8,] 1.4887136 #>  [9,] 1.4767210 #> [10,] 1.5725862 #> [11,] 1.3620716 #> [12,] 1.2178537 #> [13,] 1.3199638 #> [14,] 1.1257216 #> [15,] 1.3060530 #> [16,] 1.3216598 #> [17,] 1.3275314 #> [18,] 1.1935515 #> [19,] 1.3733932 #> [20,] 1.2282930 #> [21,] 0.9901602 #> [22,] 0.6982169 #> [23,] 0.9584952 #> [24,] 1.1224464 #> [25,] 0.4078249 #> [26,] 0.5657675 #> [27,] 0.6474173 #> [28,] 0.6504392 #> [29,] 0.9303437 #> [30,] 0.5913419 #>  #> , , 75 #>  #>            [,1] #>  [1,] 1.3449078 #>  [2,] 1.3735069 #>  [3,] 1.5695100 #>  [4,] 1.5096978 #>  [5,] 1.5753880 #>  [6,] 1.4886506 #>  [7,] 1.3983596 #>  [8,] 1.4805341 #>  [9,] 1.4748402 #> [10,] 1.5716862 #> [11,] 1.3756472 #> [12,] 1.2315457 #> [13,] 1.3319222 #> [14,] 1.1413144 #> [15,] 1.3196685 #> [16,] 1.3328348 #> [17,] 1.3411858 #> [18,] 1.2088248 #> [19,] 1.3855109 #> [20,] 1.2417981 #> [21,] 0.9458980 #> [22,] 0.6397965 #> [23,] 0.9114397 #> [24,] 1.0787204 #> [25,] 0.3411936 #> [26,] 0.4988721 #> [27,] 0.5836377 #> [28,] 0.5868059 #> [29,] 0.8767501 #> [30,] 0.5261342 #>  #> , , 76 #>  #>            [,1] #>  [1,] 1.3388484 #>  [2,] 1.3633196 #>  [3,] 1.5611283 #>  [4,] 1.5037600 #>  [5,] 1.5716735 #>  [6,] 1.4738347 #>  [7,] 1.3816275 #>  [8,] 1.4714120 #>  [9,] 1.4721762 #> [10,] 1.5699564 #> [11,] 1.3887013 #> [12,] 1.2448584 #> [13,] 1.3434080 #> [14,] 1.1566138 #> [15,] 1.3328160 #> [16,] 1.3434915 #> [17,] 1.3543572 #> [18,] 1.2237120 #> [19,] 1.3971476 #> [20,] 1.2549075 #> [21,] 0.9004063 #> [22,] 0.5801156 #> [23,] 0.8631375 #> [24,] 1.0335958 #> [25,] 0.2736529 #> [26,] 0.4309483 #> [27,] 0.5187230 #> [28,] 0.5220279 #> [29,] 0.8217842 #> [30,] 0.4597907 #>  #> , , 77 #>  #>            [,1] #>  [1,] 1.3319748 #>  [2,] 1.3521668 #>  [3,] 1.5517709 #>  [4,] 1.4968762 #>  [5,] 1.5670384 #>  [6,] 1.4578684 #>  [7,] 1.3637579 #>  [8,] 1.4613460 #>  [9,] 1.4687257 #> [10,] 1.5673927 #> [11,] 1.4012281 #> [12,] 1.2577870 #> [13,] 1.3544165 #> [14,] 1.1716151 #> [15,] 1.3454905 #> [16,] 1.3536253 #> [17,] 1.3670401 #> [18,] 1.2382077 #> [19,] 1.4082990 #> [20,] 1.2676164 #> [21,] 0.8537256 #> [22,] 0.5192469 #> [23,] 0.8136350 #> [24,] 0.9871135 #> [25,] 0.2052951 #> [26,] 0.3620834 #> [27,] 0.4527552 #> [28,] 0.4561877 #> [29,] 0.7655052 #> [30,] 0.3924009 #>  #> , , 78 #>  #>            [,1] #>  [1,] 1.3242842 #>  [2,] 1.3400470 #>  [3,] 1.5414350 #>  [4,] 1.4890411 #>  [5,] 1.5614786 #>  [6,] 1.4407491 #>  [7,] 1.3447478 #>  [8,] 1.4503348 #>  [9,] 1.4644852 #> [10,] 1.5639909 #> [11,] 1.4132225 #> [12,] 1.2703274 #> [13,] 1.3649435 #> [14,] 1.1863137 #> [15,] 1.3576869 #> [16,] 1.3632318 #> [17,] 1.3792294 #> [18,] 1.2523065 #> [19,] 1.4189610 #> [20,] 1.2799200 #> [21,] 0.8058980 #> [22,] 0.4572657 #> [23,] 0.7629806 #> [24,] 0.9393165 #> [25,] 0.1362145 #> [26,] 0.2923667 #> [27,] 0.3858185 #> [28,] 0.3893698 #> [29,] 0.7079742 #> [30,] 0.3240565 #>  #> , , 79 #>  #>             [,1] #>  [1,] 1.31577371 #>  [2,] 1.32695827 #>  [3,] 1.53011837 #>  [4,] 1.48024933 #>  [5,] 1.55498991 #>  [6,] 1.42247419 #>  [7,] 1.32459405 #>  [8,] 1.43837736 #>  [9,] 1.45945138 #> [10,] 1.55974710 #> [11,] 1.42467907 #> [12,] 1.28247520 #> [13,] 1.37498484 #> [14,] 1.20070495 #> [15,] 1.36940043 #> [16,] 1.37230647 #> [17,] 1.39091985 #> [18,] 1.26600342 #> [19,] 1.42912942 #> [20,] 1.29181416 #> [21,] 0.75696697 #> [22,] 0.39424929 #> [23,] 0.71122375 #> [24,] 0.89024924 #> [25,] 0.06650722 #> [26,] 0.22188960 #> [27,] 0.31799902 #> [28,] 0.32166092 #> [29,] 0.64925405 #> [30,] 0.25485140 #>  #> , , 80 #>  #>              [,1] #>  [1,]  1.30644060 #>  [2,]  1.31289908 #>  [3,]  1.51781846 #>  [4,]  1.47049558 #>  [5,]  1.54756833 #>  [6,]  1.40304129 #>  [7,]  1.30329359 #>  [8,]  1.42547251 #>  [9,]  1.45362092 #> [10,]  1.55465712 #> [11,]  1.43559292 #> [12,]  1.29422644 #> [13,]  1.38453651 #> [14,]  1.21478453 #> [15,]  1.38062646 #> [16,]  1.38084534 #> [17,]  1.40210666 #> [18,]  1.27929350 #> [19,]  1.43880063 #> [20,]  1.30329440 #> [21,]  0.70697751 #> [22,]  0.33027699 #> [23,]  0.65841584 #> [24,]  0.83995783 #> [25,] -0.00372876 #> [26,]  0.15074512 #> [27,]  0.24938493 #> [28,]  0.25314969 #> [29,]  0.58940990 #> [30,]  0.18488158 #>  #> , , 81 #>  #>              [,1] #>  [1,]  1.29628210 #>  [2,]  1.29786780 #>  [3,]  1.50453289 #>  [4,]  1.45977448 #>  [5,]  1.53920973 #>  [6,]  1.38244807 #>  [7,]  1.28084362 #>  [8,]  1.41161926 #>  [9,]  1.44699052 #> [10,]  1.54871697 #> [11,]  1.44595920 #> [12,]  1.30557718 #> [13,]  1.39359467 #> [14,]  1.22854814 #> [15,]  1.39136055 #> [16,]  1.38884436 #> [17,]  1.41278508 #> [18,]  1.29217197 #> [19,]  1.44797095 #> [20,]  1.31435660 #> [21,]  0.65597592 #> [22,]  0.26543027 #> [23,]  0.60460961 #> [24,]  0.78848999 #> [25,] -0.07439373 #> [26,]  0.07902807 #> [27,]  0.18006611 #> [28,]  0.18392652 #> [29,]  0.52850855 #> [30,]  0.11424500 #>  #> , , 82 #>  #>              [,1] #>  [1,]  1.28529548 #>  [2,]  1.28186295 #>  [3,]  1.49025933 #>  [4,]  1.44808064 #>  [5,]  1.52991004 #>  [6,]  1.36069232 #>  [7,]  1.25724150 #>  [8,]  1.39681666 #>  [9,]  1.43955689 #> [10,]  1.54192264 #> [11,]  1.45577329 #> [12,]  1.31652367 #> [13,]  1.40215567 #> [14,]  1.24199159 #> [15,]  1.40159843 #> [16,]  1.39629971 #> [17,]  1.42295052 #> [18,]  1.30463424 #> [19,]  1.45663691 #> [20,]  1.32499677 #> [21,]  0.60400992 #> [22,]  0.19979248 #> [23,]  0.54985929 #> [24,]  0.73589500 #> [25,] -0.14538641 #> [26,]  0.00683480 #> [27,]  0.11013419 #> [28,]  0.11408364 #> [29,]  0.46661864 #> [30,]  0.04304148 #>  #> , , 83 #>  #>              [,1] #>  [1,]  1.27347802 #>  [2,]  1.26488308 #>  [3,]  1.47499549 #>  [4,]  1.43540869 #>  [5,]  1.51966520 #>  [6,]  1.33777198 #>  [7,]  1.23248483 #>  [8,]  1.38106386 #>  [9,]  1.43131677 #> [10,]  1.53427010 #> [11,]  1.46503072 #> [12,]  1.32706228 #> [13,]  1.41021598 #> [14,]  1.25511081 #> [15,]  1.41133597 #> [16,]  1.40320773 #> [17,]  1.43259858 #> [18,]  1.31667586 #> [19,]  1.46479521 #> [20,]  1.33521103 #> [21,]  0.55112857 #> [22,]  0.13344887 #> [23,]  0.49422056 #> [24,]  0.68222372 #> [25,] -0.21660409 #> [26,] -0.06573682 #> [27,]  0.03968247 #> [28,]  0.04371490 #> [29,]  0.40381060 #> [30,] -0.02862745 #>  #> , , 84 #>  #>              [,1] #>  [1,]  1.26082703 #>  [2,]  1.24692686 #>  [3,]  1.45873910 #>  [4,]  1.42175320 #>  [5,]  1.50847116 #>  [6,]  1.31368518 #>  [7,]  1.20657145 #>  [8,]  1.36436007 #>  [9,]  1.42226688 #> [10,]  1.52575535 #> [11,]  1.47372720 #> [12,]  1.33718955 #> [13,]  1.41777222 #> [14,]  1.26790186 #> [15,]  1.42056925 #> [16,]  1.40956489 #> [17,]  1.44172497 #> [18,]  1.32829253 #> [19,]  1.47244267 #> [20,]  1.34499563 #> [21,]  0.49738221 #> [22,]  0.06648646 #> [23,]  0.43775046 #> [24,]  0.62752848 #> [25,] -0.28794274 #> [26,] -0.13858759 #> [27,] -0.03119427 #> [28,] -0.02708432 #> [29,]  0.34015652 #> [30,] -0.10065864 #>  #> , , 85 #>  #>               [,1] #>  [1,]  1.247339859 #>  [2,]  1.227993054 #>  [3,]  1.441487999 #>  [4,]  1.407108797 #>  [5,]  1.496323855 #>  [6,]  1.288430269 #>  [7,]  1.179499560 #>  [8,]  1.346704567 #>  [9,]  1.412403969 #> [10,]  1.516374372 #> [11,]  1.481858581 #> [12,]  1.346902126 #> [13,]  1.424821151 #> [14,]  1.280360909 #> [15,]  1.429294465 #> [16,]  1.415367793 #> [17,]  1.450325587 #> [18,]  1.339480139 #> [19,]  1.479576315 #> [20,]  1.354346956 #> [21,]  0.442822498 #> [22,] -0.001006074 #> [23,]  0.380507420 #> [24,]  0.571863134 #> [25,] -0.359297142 #> [26,] -0.211617071 #> [27,] -0.102399843 #> [28,] -0.098217199 #> [29,]  0.275730141 #> [30,] -0.172947465 #>  #> , , 86 #>  #>              [,1] #>  [1,]  1.23301388 #>  [2,]  1.20808055 #>  [3,]  1.42324005 #>  [4,]  1.39147008 #>  [5,]  1.48321926 #>  [6,]  1.26200583 #>  [7,]  1.15126772 #>  [8,]  1.32809675 #>  [9,]  1.40172479 #> [10,]  1.50612314 #> [11,]  1.48942088 #> [12,]  1.35619682 #> [13,]  1.43135967 #> [14,]  1.29248422 #> [15,]  1.43750798 #> [16,]  1.42061319 #> [17,]  1.45839642 #> [18,]  1.35023469 #> [19,]  1.48619327 #> [20,]  1.36326152 #> [21,]  0.38750231 #> [22,] -0.06893844 #> [23,]  0.32255114 #> [24,]  0.51528294 #> [25,] -0.43056108 #> [26,] -0.28472371 #> [27,] -0.17383675 #> [28,] -0.16958561 #> [29,]  0.21060678 #> [30,] -0.24538797 #>  #> , , 87 #>  #>             [,1] #>  [1,]  1.2178465 #>  [2,]  1.1871884 #>  [3,]  1.4039932 #>  [4,]  1.3748317 #>  [5,]  1.4691533 #>  [6,]  1.2344108 #>  [7,]  1.1218749 #>  [8,]  1.3085361 #>  [9,]  1.3902261 #> [10,]  1.4949976 #> [11,]  1.4964103 #> [12,]  1.3650706 #> [13,]  1.4373848 #> [14,]  1.3042682 #> [15,]  1.4452063 #> [16,]  1.4252980 #> [17,]  1.4659336 #> [18,]  1.3605524 #> [19,]  1.4922908 #> [20,]  1.3717360 #> [21,]  0.3314757 #> [22,] -0.1372189 #> [23,]  0.2639426 #> [24,]  0.4578446 #> [25,] -0.5016275 #> [26,] -0.3578050 #> [27,] -0.2454064 #> [28,] -0.2410903 #> [29,]  0.1448632 #> [30,] -0.3178730 #>  #> , , 88 #>  #>              [,1] #>  [1,]  1.20183526 #>  [2,]  1.16531569 #>  [3,]  1.38374556 #>  [4,]  1.35718836 #>  [5,]  1.45412206 #>  [6,]  1.20564429 #>  [7,]  1.09132072 #>  [8,]  1.28802218 #>  [9,]  1.37790464 #> [10,]  1.48299381 #> [11,]  1.50282300 #> [12,]  1.37352040 #> [13,]  1.44289370 #> [14,]  1.31570923 #> [15,]  1.45238606 #> [16,]  1.42941906 #> [17,]  1.47293343 #> [18,]  1.37042944 #> [19,]  1.49786637 #> [20,]  1.37976699 #> [21,]  0.27479798 #> [22,] -0.20575428 #> [23,]  0.20474389 #> [24,]  0.39960605 #> [25,] -0.57238845 #> [26,] -0.43075762 #> [27,] -0.31700899 #> [28,] -0.31263083 #> [29,]  0.07857768 #> [30,] -0.39029445 #>  #> , , 89 #>  #>              [,1] #>  [1,]  1.18497764 #>  [2,]  1.14246191 #>  [3,]  1.36249522 #>  [4,]  1.33853482 #>  [5,]  1.43812146 #>  [6,]  1.17570608 #>  [7,]  1.05960516 #>  [8,]  1.26655474 #>  [9,]  1.36475722 #> [10,]  1.47010766 #> [11,]  1.50865551 #> [12,]  1.38154355 #> [13,]  1.44788362 #> [14,]  1.32680400 #> [15,]  1.45904406 #> [16,]  1.43297360 #> [17,]  1.47939223 #> [18,]  1.37986240 #> [19,]  1.50291749 #> [20,]  1.38735150 #> [21,]  0.21752545 #> [22,] -0.27445022 #> [23,]  0.14501838 #> [24,]  0.34062673 #> [25,] -0.64273571 #> [26,] -0.50347753 #> [27,] -0.38854405 #> [28,] -0.38410604 #> [29,]  0.01182972 #> [30,] -0.46254319 #>  #> , , 90 #>  #>              [,1] #>  [1,]  1.16727131 #>  [2,]  1.11862662 #>  [3,]  1.34024050 #>  [4,]  1.31886595 #>  [5,]  1.42114758 #>  [6,]  1.14459623 #>  [7,]  1.02672902 #>  [8,]  1.24413365 #>  [9,]  1.35078062 #> [10,]  1.45633514 #> [11,]  1.51390435 #> [12,]  1.38913732 #> [13,]  1.45235193 #> [14,]  1.33754918 #> [15,]  1.46517720 #> [16,]  1.43595876 #> [17,]  1.48530651 #> [18,]  1.38884780 #> [19,]  1.50744184 #> [20,]  1.39448645 #> [21,]  0.15971556 #> [22,] -0.34321118 #> [23,]  0.08483045 #> [24,]  0.28096720 #> [25,] -0.71256051 #> [26,] -0.57586019 #> [27,] -0.45991022 #> [28,] -0.45541386 #> [29,] -0.05529985 #> [30,] -0.53450947 #>  #> , , 91 #>  #>              [,1] #>  [1,]  1.14871399 #>  [2,]  1.09380967 #>  [3,]  1.31697982 #>  [4,]  1.29817675 #>  [5,]  1.40319653 #>  [6,]  1.11231538 #>  [7,]  0.99269379 #>  [8,]  1.22075894 #>  [9,]  1.33597167 #> [10,]  1.44167226 #> [11,]  1.51856616 #> [12,]  1.39629916 #> [13,]  1.45629612 #> [14,]  1.34794153 #> [15,]  1.47078250 #> [16,]  1.43837184 #> [17,]  1.49067283 #> [18,]  1.39738236 #> [19,]  1.51143722 #> [20,]  1.40116889 #> [21,]  0.10142677 #> [22,] -0.41194059 #> [23,]  0.02424552 #> [24,]  0.22068931 #> [25,] -0.78175390 #> [26,] -0.64780068 #> [27,] -0.53100552 #> [28,] -0.52645166 #> [29,] -0.12272906 #> [30,] -0.60608297 #>  #> , , 92 #>  #>              [,1] #>  [1,]  1.12930357 #>  [2,]  1.06801122 #>  [3,]  1.29271182 #>  [4,]  1.27646236 #>  [5,]  1.38426449 #>  [6,]  1.07886477 #>  [7,]  0.95750180 #>  [8,]  1.19643084 #>  [9,]  1.32032723 #> [10,]  1.42611502 #> [11,]  1.52263769 #> [12,]  1.40302662 #> [13,]  1.45971377 #> [14,]  1.35797795 #> [15,]  1.47585711 #> [16,]  1.44021020 #> [17,]  1.49548788 #> [18,]  1.40546294 #> [19,]  1.51490154 #> [20,]  1.40739599 #> [21,]  0.04271852 #> [22,] -0.48054103 #> [23,] -0.03667002 #> [24,]  0.15985603 #> [25,] -0.85020694 #> [26,] -0.71919387 #> [27,] -0.60172754 #> [28,] -0.59711630 #> [29,] -0.19037483 #> [30,] -0.67715302 #>  #> , , 93 #>  #>              [,1] #>  [1,]  1.10903805 #>  [2,]  1.04123175 #>  [3,]  1.26743532 #>  [4,]  1.25371813 #>  [5,]  1.36434770 #>  [6,]  1.04424631 #>  [7,]  0.92115631 #>  [8,]  1.17114979 #>  [9,]  1.30384421 #> [10,]  1.40965947 #> [11,]  1.52611581 #> [12,]  1.40931738 #> [13,]  1.46260255 #> [14,]  1.36765541 #> [15,]  1.48039829 #> [16,]  1.44147131 #> [17,]  1.49974843 #> [18,]  1.41308648 #> [19,]  1.51783281 #> [20,]  1.41316501 #> [21,] -0.01634882 #> [22,] -0.54891428 #> [23,] -0.09784888 #> [24,]  0.09853147 #> [25,] -0.91781083 #> [26,] -0.78993456 #> [27,] -0.67197352 #> [28,] -0.66730434 #> [29,] -0.25815311 #> [30,] -0.74760873 #>  #> , , 94 #>  #>              [,1] #>  [1,]  1.08791561 #>  [2,]  1.01347215 #>  [3,]  1.24114938 #>  [4,]  1.22993965 #>  [5,]  1.34344255 #>  [6,]  1.00846270 #>  [7,]  0.88366161 #>  [8,]  1.14491652 #>  [9,]  1.28651958 #> [10,]  1.39230170 #> [11,]  1.52899745 #> [12,]  1.41516923 #> [13,]  1.46496023 #> [14,]  1.37697098 #> [15,]  1.48440341 #> [16,]  1.44215269 #> [17,]  1.50345131 #> [18,]  1.42025009 #> [19,]  1.52022917 #> [20,]  1.41847329 #> [21,] -0.07571400 #> [22,] -0.61696152 #> [23,] -0.15922292 #> [24,]  0.03678078 #> [25,] -0.98445715 #> [26,] -0.85991769 #> [27,] -0.74164058 #> [28,] -0.73691218 #> [29,] -0.32597896 #> [30,] -0.81733923 #>  #> , , 95 #>  #>              [,1] #>  [1,]  1.06593466 #>  [2,]  0.98473373 #>  [3,]  1.21385336 #>  [4,]  1.20512277 #>  [5,]  1.32154555 #>  [6,]  0.97151747 #>  [7,]  0.84502315 #>  [8,]  1.11773198 #>  [9,]  1.26835039 #> [10,]  1.37403786 #> [11,]  1.53127965 #> [12,]  1.42058005 #> [13,]  1.46678464 #> [14,]  1.38592181 #> [15,]  1.48786991 #> [16,]  1.44225194 #> [17,]  1.50659344 #> [18,]  1.42695095 #> [19,]  1.52208884 #> [20,]  1.42331827 #> [21,] -0.13531497 #> [22,] -0.68458346 #> [23,] -0.22072325 #> [24,] -0.02532989 #> [25,] -1.05003803 #> [26,] -0.92903850 #> [27,] -0.81062580 #> [28,] -0.80583622 #> [29,] -0.39376664 #> [30,] -0.88623380 #>  #> , , 96 #>  #>              [,1] #>  [1,]  1.04309381 #>  [2,]  0.95501828 #>  [3,]  1.18554690 #>  [4,]  1.17926369 #>  [5,]  1.29865338 #>  [6,]  0.93341510 #>  [7,]  0.80524761 #>  [8,]  1.08959751 #>  [9,]  1.24933378 #> [10,]  1.35486420 #> [11,]  1.53295951 #> [12,]  1.42554786 #> [13,]  1.46807372 #> [14,]  1.39450516 #> [15,]  1.49079536 #> [16,]  1.44176671 #> [17,]  1.50917182 #> [18,]  1.43318639 #> [19,]  1.52341014 #> [20,]  1.42769745 #> [21,] -0.19508892 #> [22,] -0.75168046 #> [23,] -0.28228027 #> [24,] -0.08773345 #> [25,] -1.11444638 #> [26,] -0.99719268 #> [27,] -0.87882647 #> [28,] -0.87397304 #> [29,] -0.46142973 #> [30,] -0.95418216 #>  #> , , 97 #>  #>             [,1] #>  [1,]  1.0193920 #>  [2,]  0.9243282 #>  [3,]  1.1562300 #>  [4,]  1.1523590 #>  [5,]  1.2747629 #>  [6,]  0.8941611 #>  [7,]  0.7643430 #>  [8,]  1.0605148 #>  [9,]  1.2294670 #> [10,]  1.3347770 #> [11,]  1.5340342 #> [12,]  1.4300708 #> [13,]  1.4688255 #> [14,]  1.4027183 #> [15,]  1.4931774 #> [16,]  1.4406947 #> [17,]  1.5111835 #> [18,]  1.4389538 #> [19,]  1.5241915 #> [20,]  1.4316084 #> [21,] -0.2549723 #> [22,] -0.8181527 #> [23,] -0.3438238 #> [24,] -0.1503620 #> [25,] -1.1775760 #> [26,] -1.0642766 #> [27,] -0.9461402 #> [28,] -0.9412196 #> [29,] -0.5288812 #> [30,] -1.0210746 #>  #> , , 98 #>  #>             [,1] #>  [1,]  0.9948284 #>  [2,]  0.8926663 #>  [3,]  1.1259032 #>  [4,]  1.1244056 #>  [5,]  1.2498712 #>  [6,]  0.8537622 #>  [7,]  0.7223190 #>  [8,]  1.0304858 #>  [9,]  1.2087475 #> [10,]  1.3137729 #> [11,]  1.5345010 #> [12,]  1.4341469 #> [13,]  1.4690379 #> [14,]  1.4105588 #> [15,]  1.4950137 #> [16,]  1.4390337 #> [17,]  1.5126255 #> [18,]  1.4442508 #> [19,]  1.5244313 #> [20,]  1.4350488 #> [21,] -0.3149010 #> [22,] -0.8839005 #> [23,] -0.4052830 #> [24,] -0.2131467 #> [25,] -1.2393221 #> [26,] -1.1301875 #> [27,] -1.0124652 #> [28,] -1.0074733 #> [29,] -0.5960337 #> [30,] -1.0868021 #>  #> , , 99 #>  #>             [,1] #>  [1,]  0.9694025 #>  [2,]  0.8600365 #>  [3,]  1.0945673 #>  [4,]  1.0954012 #>  [5,]  1.2239758 #>  [6,]  0.8122263 #>  [7,]  0.6791867 #>  [8,]  0.9995132 #>  [9,]  1.1871727 #> [10,]  1.2918483 #> [11,]  1.5343571 #> [12,]  1.4377747 #> [13,]  1.4687092 #> [14,]  1.4180240 #> [15,]  1.4963021 #> [16,]  1.4367815 #> [17,]  1.5134951 #> [18,]  1.4490748 #> [19,]  1.5241283 #> [20,]  1.4380164 #> [21,] -0.3748102 #> [22,] -0.9488240 #> [23,] -0.4665867 #> [24,] -0.2760181 #> [25,] -1.2995810 #> [26,] -1.1948235 #> [27,] -1.0777001 #> [28,] -1.0726324 #> [29,] -0.6627993 #> [30,] -1.1512568 #>  #> , , 100 #>  #>             [,1] #>  [1,]  0.9431144 #>  [2,]  0.8264429 #>  [3,]  1.0622236 #>  [4,]  1.0653436 #>  [5,]  1.1970742 #>  [6,]  0.7695627 #>  [7,]  0.6349589 #>  [8,]  0.9676000 #>  [9,]  1.1647405 #> [10,]  1.2690000 #> [11,]  1.5335999 #> [12,]  1.4409525 #> [13,]  1.4678375 #> [14,]  1.4251114 #> [15,]  1.4970405 #> [16,]  1.4339360 #> [17,]  1.5137894 #> [18,]  1.4534237 #> [19,]  1.5232810 #> [20,]  1.4405089 #> [21,] -0.4346348 #> [22,] -1.0128239 #> [23,] -0.5276633 #> [24,] -0.3389060 #> [25,] -1.3582507 #> [26,] -1.2580843 #> [27,] -1.1417449 #> [28,] -1.1365959 #> [29,] -0.7290899 #> [30,] -1.2143321 #>  #> , , 101 #>  #>             [,1] #>  [1,]  0.9159644 #>  [2,]  0.7918910 #>  [3,]  1.0288743 #>  [4,]  1.0342317 #>  [5,]  1.1691645 #>  [6,]  0.7257823 #>  [7,]  0.5896506 #>  [8,]  0.9347498 #>  [9,]  1.1414488 #> [10,]  1.2452252 #> [11,]  1.5322268 #> [12,]  1.4436787 #> [13,]  1.4664211 #> [14,]  1.4318188 #> [15,]  1.4972268 #> [16,]  1.4304949 #> [17,]  1.5135057 #> [18,]  1.4572953 #> [19,]  1.5218882 #> [20,]  1.4425242 #> [21,] -0.4943090 #> [22,] -1.0758014 #> [23,] -0.5884409 #> [24,] -0.4017398 #> [25,] -1.4152313 #> [26,] -1.3198706 #> [27,] -1.2045003 #> [28,] -1.1992640 #> [29,] -0.7948175 #> [30,] -1.2759226 #>  #> , , 102 #>  #>             [,1] #>  [1,]  0.8879534 #>  [2,]  0.7563868 #>  [3,]  0.9945217 #>  [4,]  1.0020648 #>  [5,]  1.1402452 #>  [6,]  0.6808974 #>  [7,]  0.5432786 #>  [8,]  0.9009667 #>  [9,]  1.1172958 #> [10,]  1.2205209 #> [11,]  1.5302352 #> [12,]  1.4459519 #> [13,]  1.4644582 #> [14,]  1.4381438 #> [15,]  1.4968590 #> [16,]  1.4264562 #> [17,]  1.5126412 #> [18,]  1.4606874 #> [19,]  1.5199487 #> [20,]  1.4440601 #> [21,] -0.5537667 #> [22,] -1.1376582 #> [23,] -0.6488474 #> [24,] -0.4644482 #> [25,] -1.4704246 #> [26,] -1.3800850 #> [27,] -1.2658683 #> [28,] -1.2605381 #> [29,] -0.8598939 #> [30,] -1.3359248 #>  #> , , 103 #>  #>             [,1] #>  [1,]  0.8590828 #>  [2,]  0.7199374 #>  [3,]  0.9591693 #>  [4,]  0.9688430 #>  [5,]  1.1103153 #>  [6,]  0.6349222 #>  [7,]  0.4958618 #>  [8,]  0.8662557 #>  [9,]  1.0922800 #> [10,]  1.1948848 #> [11,]  1.5276225 #> [12,]  1.4477707 #> [13,]  1.4619472 #> [14,]  1.4440843 #> [15,]  1.4959350 #> [16,]  1.4218179 #> [17,]  1.5111931 #> [18,]  1.4635980 #> [19,]  1.5174612 #> [20,]  1.4451146 #> [21,] -0.6129418 #> [22,] -1.1982970 #> [23,] -0.7088106 #> [24,] -0.5269595 #> [25,] -1.5237351 #> [26,] -1.4386319 #> [27,] -1.3257525 #> [28,] -1.3203213 #> [29,] -0.9242311 #> [30,] -1.3942369 #>  #> , , 104 #>  #>             [,1] #>  [1,]  0.8293546 #>  [2,]  0.6825510 #>  [3,]  0.9228210 #>  [4,]  0.9345675 #>  [5,]  1.0793741 #>  [6,]  0.5878729 #>  [7,]  0.4474217 #>  [8,]  0.8306224 #>  [9,]  1.0664002 #> [10,]  1.1683147 #> [11,]  1.5243862 #> [12,]  1.4491340 #> [13,]  1.4588863 #> [14,]  1.4496380 #> [15,]  1.4944531 #> [16,]  1.4165778 #> [17,]  1.5091589 #> [18,]  1.4660251 #> [19,]  1.5144247 #> [20,]  1.4456857 #> [21,] -0.6717675 #> [22,] -1.2576215 #> [23,] -0.7682582 #> [24,] -0.5892017 #> [25,] -1.5750694 #> [26,] -1.4954177 #> [27,] -1.3840581 #> [28,] -1.3785181 #> [29,] -0.9877413 #> [30,] -1.4507596 #>  #> , , 105 #>  #>             [,1] #>  [1,]  0.7987716 #>  [2,]  0.6442370 #>  [3,]  0.8854818 #>  [4,]  0.8992400 #>  [5,]  1.0474216 #>  [6,]  0.5397674 #>  [7,]  0.3979818 #>  [8,]  0.7940733 #>  [9,]  1.0396557 #> [10,]  1.1408086 #> [11,]  1.5205239 #> [12,]  1.4500403 #> [13,]  1.4552741 #> [14,]  1.4548028 #> [15,]  1.4924113 #> [16,]  1.4107339 #> [17,]  1.5065358 #> [18,]  1.4679668 #> [19,]  1.5108382 #> [20,]  1.4457714 #> [21,] -0.7301773 #> [22,] -1.3155365 #> [23,] -0.8271180 #> [24,] -0.6511025 #> [25,] -1.6243372 #> [26,] -1.5503511 #> [27,] -1.4406921 #> [28,] -1.4350351 #> [29,] -1.0503374 #> [30,] -1.5053954 #>  #> , , 106 #>  #>             [,1] #>  [1,]  0.7673370 #>  [2,]  0.6050060 #>  [3,]  0.8471573 #>  [4,]  0.8628636 #>  [5,]  1.0144586 #>  [6,]  0.4906260 #>  [7,]  0.3475687 #>  [8,]  0.7566155 #>  [9,]  1.0120459 #> [10,]  1.1123653 #> [11,]  1.5160330 #> [12,]  1.4504887 #> [13,]  1.4511088 #> [14,]  1.4595767 #> [15,]  1.4898079 #> [16,]  1.4042842 #> [17,]  1.5033211 #> [18,]  1.4694214 #> [19,]  1.5067007 #> [20,]  1.4453698 #> [21,] -0.7881043 #> [22,] -1.3719483 #> [23,] -0.8853181 #> [24,] -0.7125895 #> [25,] -1.6714512 #> [26,] -1.6033433 #> [27,] -1.4955637 #> [28,] -1.4897809 #> [29,] -1.1119325 #> [30,] -1.5580499 #>  #> , , 107 #>  #>             [,1] #>  [1,]  0.7350550 #>  [2,]  0.5648701 #>  [3,]  0.8078543 #>  [4,]  0.8254423 #>  [5,]  0.9804862 #>  [6,]  0.4404712 #>  [7,]  0.2962115 #>  [8,]  0.7182574 #>  [9,]  0.9835709 #> [10,]  1.0829838 #> [11,]  1.5109110 #> [12,]  1.4504781 #> [13,]  1.4463891 #> [14,]  1.4639577 #> [15,]  1.4866409 #> [16,]  1.3972267 #> [17,]  1.4995122 #> [18,]  1.4703870 #> [19,]  1.5020111 #> [20,]  1.4444788 #> [21,] -0.8454819 #> [22,] -1.4267648 #> [23,] -0.9427867 #> [24,] -0.7735902 #> [25,] -1.7163272 #> [26,] -1.6543080 #> [27,] -1.5485843 #> [28,] -1.5426664 #> [29,] -1.1724407 #> [30,] -1.6086314 #>  #> , , 108 #>  #>             [,1] #>  [1,]  0.7019307 #>  [2,]  0.5238426 #>  [3,]  0.7675807 #>  [4,]  0.7869815 #>  [5,]  0.9455068 #>  [6,]  0.3893279 #>  [7,]  0.2439421 #>  [8,]  0.6790082 #>  [9,]  0.9542312 #> [10,]  1.0526635 #> [11,]  1.5051555 #> [12,]  1.4500074 #> [13,]  1.4411132 #> [14,]  1.4679439 #> [15,]  1.4829087 #> [16,]  1.3895593 #> [17,]  1.4951065 #> [18,]  1.4708620 #> [19,]  1.4967687 #> [20,]  1.4430967 #> [21,] -0.9022433 #> [22,] -1.4798957 #> [23,] -0.9994524 #> [24,] -0.8340319 #> [25,] -1.7588845 #> [26,] -1.7031619 #> [27,] -1.5996677 #> [28,] -1.5936050 #> [29,] -1.2317768 #> [30,] -1.6570511 #>  #> , , 109 #>  #>             [,1] #>  [1,]  0.6679699 #>  [2,]  0.4819385 #>  [3,]  0.7263453 #>  [4,]  0.7474878 #>  [5,]  0.9095231 #>  [6,]  0.3372236 #>  [7,]  0.1907956 #>  [8,]  0.6388784 #>  [9,]  0.9240278 #> [10,]  1.0214047 #> [11,]  1.4987641 #> [12,]  1.4490756 #> [13,]  1.4352797 #> [14,]  1.4715334 #> [15,]  1.4786095 #> [16,]  1.3812801 #> [17,]  1.4901012 #> [18,]  1.4708447 #> [19,]  1.4909724 #> [20,]  1.4412216 #> [21,] -0.9583223 #> [22,] -1.5312527 #> [23,] -1.0552443 #> [24,] -0.8938423 #> [25,] -1.7990462 #> [26,] -1.7498249 #> [27,] -1.6487304 #> [28,] -1.6425130 #> [29,] -1.2898564 #> [30,] -1.7032237 #>  #> , , 110 #>  #>             [,1] #>  [1,]  0.6331795 #>  [2,]  0.4391744 #>  [3,]  0.6841584 #>  [4,]  0.7069690 #>  [5,]  0.8725392 #>  [6,]  0.2841887 #>  [7,]  0.1368104 #>  [8,]  0.5978794 #>  [9,]  0.8929625 #> [10,]  0.9892078 #> [11,]  1.4917342 #> [12,]  1.4476820 #> [13,]  1.4288872 #> [14,]  1.4747243 #> [15,]  1.4737416 #> [16,]  1.3723870 #> [17,]  1.4844937 #> [18,]  1.4703334 #> [19,]  1.4846215 #> [20,]  1.4388516 #> [21,] -1.0136525 #> [22,] -1.5807497 #> [23,] -1.1100921 #> [24,] -0.9529492 #> [25,] -1.8367394 #> [26,] -1.7942201 #> [27,] -1.6956920 #> [28,] -1.6893095 #> [29,] -1.3465967 #> [30,] -1.7470675 #>  #> , , 111 #>  #>              [,1] #>  [1,]  0.59756759 #>  [2,]  0.39556877 #>  [3,]  0.64103132 #>  [4,]  0.66543470 #>  [5,]  0.83455975 #>  [6,]  0.23025601 #>  [7,]  0.08202796 #>  [8,]  0.55602406 #>  [9,]  0.86103741 #> [10,]  0.95607440 #> [11,]  1.48406336 #> [12,]  1.44582559 #> [13,]  1.42193410 #> [14,]  1.47751477 #> [15,]  1.46830329 #> [16,]  1.36287799 #> [17,]  1.47828141 #> [18,]  1.46932676 #> [19,]  1.47771514 #> [20,]  1.43598484 #> [21,] -1.06816836 #> [22,] -1.62830310 #> [23,] -1.16392624 #> [24,] -1.01128060 #> [25,] -1.87189520 #> [26,] -1.83627425 #> [27,] -1.74047495 #> [28,] -1.73391662 #> [29,] -1.40191592 #> [30,] -1.78850446 #>  #> , , 112 #>  #>              [,1] #>  [1,]  0.56114310 #>  [2,]  0.35114187 #>  [3,]  0.59697705 #>  [4,]  0.62289599 #>  [5,]  0.79559081 #>  [6,]  0.17546178 #>  [7,]  0.02649337 #>  [8,]  0.51332655 #>  [9,]  0.82825559 #> [10,]  0.92200642 #> [11,]  1.47574921 #> [12,]  1.44350563 #> [13,]  1.41441897 #> [14,]  1.47990314 #> [15,]  1.46229291 #> [16,]  1.35275117 #> [17,]  1.47146157 #> [18,]  1.46782311 #> [19,]  1.47025257 #> [20,]  1.43261958 #> [21,] -1.12180444 #> [22,] -1.67383172 #> [23,] -1.21667778 #> [24,] -1.06876499 #> [25,] -1.90444940 #> [26,] -1.87591764 #> [27,] -1.78300519 #> [28,] -1.77626015 #> [29,] -1.45573366 #> [30,] -1.82746067 #>  #> , , 113 #>  #>              [,1] #>  [1,]  0.52391636 #>  [2,]  0.30591591 #>  [3,]  0.55200991 #>  [4,]  0.57936566 #>  [5,]  0.75563946 #>  [6,]  0.11984519 #>  [7,] -0.02974471 #>  [8,]  0.46980244 #>  [9,]  0.79462075 #> [10,]  0.88700674 #> [11,]  1.46678925 #> [12,]  1.44072137 #> [13,]  1.40634035 #> [14,]  1.48188766 #> [15,]  1.45570879 #> [16,]  1.34200453 #> [17,]  1.46403153 #> [18,]  1.46582101 #> [19,]  1.46223301 #> [20,]  1.42875400 #> [21,] -1.17449603 #> [22,] -1.71725738 #> [23,] -1.26827883 #> [24,] -1.12533135 #> [25,] -1.93434230 #> [26,] -1.91308469 #> [27,] -1.82321209 #> [28,] -1.81626924 #> [29,] -1.50797130 #> [30,] -1.86386650 #>  #> , , 114 #>  #>              [,1] #>  [1,]  0.48589893 #>  [2,]  0.25991522 #>  [3,]  0.50614589 #>  [4,]  0.53485831 #>  [5,]  0.71471403 #>  [6,]  0.06344874 #>  [7,] -0.08663389 #>  [8,]  0.42546883 #>  [9,]  0.76013745 #> [10,]  0.85107904 #> [11,]  1.45718104 #> [12,]  1.43747211 #> [13,]  1.39769680 #> [14,]  1.48346663 #> [15,]  1.44854927 #> [16,]  1.33063609 #> [17,]  1.45598862 #> [18,]  1.46331901 #> [19,]  1.45365575 #> [20,]  1.42438628 #> [21,] -1.22617902 #> [22,] -1.75850490 #> [23,] -1.31866251 #> [24,] -1.18090926 #> [25,] -1.96151913 #> [26,] -1.94771392 #> [27,] -1.86102879 #> [28,] -1.85387691 #> [29,] -1.55855192 #> [30,] -1.89765682 #>  #> , , 115 #>  #>               [,1] #>  [1,]  0.447103723 #>  [2,]  0.213166296 #>  [3,]  0.459402591 #>  [4,]  0.489390490 #>  [5,]  0.672824190 #>  [6,]  0.006318311 #>  [7,] -0.144117941 #>  [8,]  0.380344434 #>  [9,]  0.724811121 #> [10,]  0.814227917 #> [11,]  1.446922105 #> [12,]  1.433757176 #> [13,]  1.388486892 #> [14,]  1.484638384 #> [15,]  1.440812711 #> [16,]  1.318643904 #> [17,]  1.447330138 #> [18,]  1.460315719 #> [19,]  1.444520065 #> [20,]  1.419514650 #> [21,] -1.276790077 #> [22,] -1.797502313 #> [23,] -1.367763044 #> [24,] -1.235429019 #> [25,] -1.985930240 #> [26,] -1.979748237 #> [27,] -1.896392364 #> [28,] -1.889020156 #> [29,] -1.607400553 #> [30,] -1.928771274 #>  #> , , 116 #>  #>              [,1] #>  [1,]  0.40754511 #>  [2,]  0.16569793 #>  [3,]  0.41179944 #>  [4,]  0.44298077 #>  [5,]  0.62998104 #>  [6,] -0.05149666 #>  [7,] -0.20213665 #>  [8,]  0.33444965 #>  [9,]  0.68864812 #> [10,]  0.77645895 #> [11,]  1.43601001 #> [12,]  1.42957595 #> [13,]  1.37870920 #> [14,]  1.48540131 #> [15,]  1.43249749 #> [16,]  1.30602603 #> [17,]  1.43805339 #> [18,]  1.45680973 #> [19,]  1.43482529 #> [20,]  1.41413732 #> [21,] -1.32626671 #> [22,] -1.83418115 #> [23,] -1.41551595 #> [24,] -1.28882175 #> [25,] -2.00753131 #> [26,] -2.00913510 #> [27,] -1.92924401 #> [28,] -1.92164018 #> [29,] -1.65444432 #> [30,] -1.95715447 #>  #> , , 117 #>  #>             [,1] #>  [1,]  0.3672390 #>  [2,]  0.1175413 #>  [3,]  0.3633577 #>  [4,]  0.3956499 #>  [5,]  0.5861972 #>  [6,] -0.1099431 #>  [7,] -0.2606258 #>  [8,]  0.2878067 #>  [9,]  0.6516558 #> [10,]  0.7377788 #> [11,]  1.4244423 #> [12,]  1.4249278 #> [13,]  1.3683623 #> [14,]  1.4857538 #> [15,]  1.4236020 #> [16,]  1.2927805 #> [17,]  1.4281557 #> [18,]  1.4527997 #> [19,]  1.4245708 #> [20,]  1.4082525 #> [21,] -1.3745474 #> [22,] -1.8684766 #> [23,] -1.4618581 #> [24,] -1.3410195 #> [25,] -2.0262836 #> [26,] -2.0358268 #> [27,] -1.9595293 #> [28,] -1.9516826 #> [29,] -1.6996126 #> [30,] -1.9827562 #>  #> , , 118 #>  #>              [,1] #>  [1,]  0.32620278 #>  [2,]  0.06873015 #>  [3,]  0.31410066 #>  [4,]  0.34742079 #>  [5,]  0.54148680 #>  [6,] -0.16896409 #>  [7,] -0.31951685 #>  [8,]  0.24043957 #>  [9,]  0.61384269 #> [10,]  0.69819511 #> [11,]  1.41221652 #> [12,]  1.41981226 #> [13,]  1.35744483 #> [14,]  1.48569424 #> [15,]  1.41412454 #> [16,]  1.27890557 #> [17,]  1.41763429 #> [18,]  1.44828428 #> [19,]  1.41375582 #> [20,]  1.40185843 #> [21,] -1.42157158 #> [22,] -1.90032766 #> [23,] -1.50672781 #> [24,] -1.39195541 #> [25,] -2.04215395 #> [26,] -2.05978038 #> [27,] -1.98719828 #> [28,] -1.97909761 #> [29,] -1.74283717 #> [30,] -2.00553175 #>  #> , , 119 #>  #>              [,1] #>  [1,]  0.28445573 #>  [2,]  0.01930072 #>  [3,]  0.26405358 #>  [4,]  0.29831885 #>  [5,]  0.49586584 #>  [6,] -0.22849894 #>  [7,] -0.37873725 #>  [8,]  0.19237436 #>  [9,]  0.57521829 #> [10,]  0.65771694 #> [11,]  1.39933027 #> [12,]  1.41422872 #> [13,]  1.34595537 #> [14,]  1.48522111 #> [15,]  1.40406360 #> [16,]  1.26439925 #> [17,]  1.40648652 #> [18,]  1.44326216 #> [19,]  1.40237988 #> [20,]  1.39495331 #> [21,] -1.46728001 #> [22,] -1.92967752 #> [23,] -1.55006512 #> [24,] -1.44156372 #> [25,] -2.05511540 #> [26,] -2.08095832 #> [27,] -2.01220581 #> [28,] -2.00384022 #> [29,] -1.78405244 #> [30,] -2.02544193 #>  #> , , 120 #>  #>              [,1] #>  [1,]  0.24201874 #>  [2,] -0.03070798 #>  [3,]  0.21324395 #>  [4,]  0.24837186 #>  [5,]  0.44935198 #>  [6,] -0.28848293 #>  [7,] -0.43821000 #>  [8,]  0.14363913 #>  [9,]  0.53579342 #> [10,]  0.61635447 #> [11,]  1.38578113 #> [12,]  1.40817670 #> [13,]  1.33389256 #> [14,]  1.48433287 #> [15,]  1.39341754 #> [16,]  1.24925975 #> [17,]  1.39470968 #> [18,]  1.43773202 #> [19,]  1.39044233 #> [20,]  1.38753538 #> [21,] -1.51161458 #> [22,] -1.95647356 #> [23,] -1.59181171 #> [24,] -1.48978001 #> [25,] -2.06514695 #> [26,] -2.09932821 #> [27,] -2.03451159 #> [28,] -2.02587044 #> [29,] -1.82319553 #> [30,] -2.04245347 #>  #> , , 121 #>  #>              [,1] #>  [1,]  0.19891461 #>  [2,] -0.08125416 #>  [3,]  0.16170148 #>  [4,]  0.19761022 #>  [5,]  0.40196483 #>  [6,] -0.34884725 #>  [7,] -0.49785374 #>  [8,]  0.09426409 #>  [9,]  0.49558015 #> [10,]  0.57411927 #> [11,]  1.37156671 #> [12,]  1.40165574 #> [13,]  1.32125506 #> [14,]  1.48302797 #> [15,]  1.38218479 #> [16,]  1.23348533 #> [17,]  1.38230107 #> [18,]  1.43169259 #> [19,]  1.37794260 #> [20,]  1.37960285 #> [21,] -1.55451858 #> [22,] -1.98066767 #> [23,] -1.63191115 #> [24,] -1.53654122 #> [25,] -2.07223394 #> [26,] -2.11486320 #> [27,] -2.05408047 #> [28,] -2.04515341 #> [29,] -1.86020650 #> [30,] -2.05653909 #>  #> , , 122 #>  #>              [,1] #>  [1,]  0.15516805 #>  [2,] -0.13229315 #>  [3,]  0.10945824 #>  [4,]  0.14606702 #>  [5,]  0.35372596 #>  [6,] -0.40951897 #>  [7,] -0.55758275 #>  [8,]  0.04428169 #>  [9,]  0.45459190 #> [10,]  0.53102434 #> [11,]  1.35668466 #> [12,]  1.39466537 #> [13,]  1.30804154 #> [14,]  1.48130491 #> [15,]  1.37036378 #> [16,]  1.21707427 #> [17,]  1.36925801 #> [18,]  1.42514259 #> [19,]  1.36488016 #> [20,]  1.37115395 #> [21,] -1.59593679 #> [22,] -2.00221641 #> [23,] -1.67030896 #> [24,] -1.58178581 #> [25,] -2.07636817 #> [26,] -2.12754210 #> [27,] -2.07088253 #> [28,] -2.06165965 #> [29,] -1.89502846 #> [30,] -2.06767770 #>  #> , , 123 #>  #>               [,1] #>  [1,]  0.110805759 #>  [2,] -0.183777316 #>  [3,]  0.056548729 #>  [4,]  0.093778121 #>  [5,]  0.304659037 #>  [6,] -0.470420926 #>  [7,] -0.617306858 #>  [8,] -0.006273309 #>  [9,]  0.412843528 #> [10,]  0.487084176 #> [11,]  1.341132638 #> [12,]  1.387205168 #> [13,]  1.294250707 #> [14,]  1.479162194 #> [15,]  1.357952940 #> [16,]  1.200024921 #> [17,]  1.355577835 #> [18,]  1.418080754 #> [19,]  1.351254479 #> [20,]  1.362186893 #> [21,] -1.635815531 #> [22,] -2.021081196 #> [23,] -1.706952772 #> [24,] -1.625453870 #> [25,] -2.077548058 #> [26,] -2.137349487 #> [27,] -2.084893301 #> [28,] -2.075365149 #> [29,] -1.927607779 #> [30,] -2.075854641 #>  #> , , 124 #>  #>               [,1] #>  [1,]  0.065856548 #>  [2,] -0.235655974 #>  [3,]  0.003009972 #>  [4,]  0.040782285 #>  [5,]  0.254789899 #>  [6,] -0.531471710 #>  [7,] -0.676931466 #>  [8,] -0.057363762 #>  [9,]  0.370351359 #> [10,]  0.442314867 #> [11,]  1.324908388 #> [12,]  1.379274738 #> [13,]  1.279881284 #> [14,]  1.476598329 #> [15,]  1.344950742 #> [16,]  1.182335732 #> [17,]  1.341257918 #> [18,]  1.410505831 #> [19,]  1.337065075 #> [20,]  1.352699914 #> [21,] -1.674102836 #> [22,] -2.037228494 #> [23,] -1.741792436 #> [24,] -1.667487255 #> [25,] -2.075778784 #> [26,] -2.144275922 #> [27,] -2.096093893 #> [28,] -2.086251597 #> [29,] -1.957894198 #> [30,] -2.081061756 #>  #> , , 125 #>  #>              [,1] #>  [1,]  0.02035137 #>  [2,] -0.28787532 #>  [3,] -0.05111839 #>  [4,] -0.01287875 #>  [5,]  0.20414666 #>  [6,] -0.59258560 #>  [7,] -0.73635756 #>  [8,] -0.10895005 #>  [9,]  0.32713330 #> [10,]  0.39673416 #> [11,]  1.30800968 #> [12,]  1.37087369 #> [13,]  1.26493204 #> [14,]  1.47361183 #> [15,]  1.33135567 #> [16,]  1.16400523 #> [17,]  1.32629566 #> [18,]  1.40241658 #> [19,]  1.32231149 #> [20,]  1.34269124 #> [21,] -1.71074851 #> [22,] -2.05063000 #> [23,] -1.77478013 #> [24,] -1.70782968 #> [25,] -2.07107239 #> [26,] -2.14831803 #> [27,] -2.10447116 #> [28,] -2.09430648 #> [29,] -1.98584103 #> [30,] -2.08329759 #>  #> , , 126 #>  #>              [,1] #>  [1,] -0.02567659 #>  [2,] -0.34037838 #>  [3,] -0.10579404 #>  [4,] -0.06716017 #>  [5,]  0.15275980 #>  [6,] -0.65367254 #>  [7,] -0.79548176 #>  [8,] -0.16099001 #>  [9,]  0.28320889 #> [10,]  0.35036156 #> [11,]  1.29043437 #> [12,]  1.36200166 #> [13,]  1.24940180 #> [14,]  1.47020123 #> [15,]  1.31716624 #> [16,]  1.14503205 #> [17,]  1.31068849 #> [18,]  1.39381176 #> [19,]  1.30699332 #> [20,]  1.33215911 #> [21,] -1.74570427 #> [22,] -2.06126279 #> [23,] -1.80587047 #> [24,] -1.74642684 #> [25,] -2.06344792 #> [26,] -2.14947862 #> [27,] -2.11001783 #> [28,] -2.09952323 #> [29,] -2.01140528 #> [30,] -2.08256752 #>  #> , , 127 #>  #>              [,1] #>  [1,] -0.07219185 #>  [2,] -0.39310492 #>  [3,] -0.16097187 #>  [4,] -0.12201401 #>  [5,]  0.10066224 #>  [6,] -0.71463816 #>  [7,] -0.85419633 #>  [8,] -0.21343888 #>  [9,]  0.23859937 #> [10,]  0.30321836 #> [11,]  1.27218038 #> [12,]  1.35265831 #> [13,]  1.23328941 #> [14,]  1.46636506 #> [15,]  1.30238100 #> [16,]  1.12541494 #> [17,]  1.29443392 #> [18,]  1.38469016 #> [19,]  1.29111018 #> [20,]  1.32110176 #> [21,] -1.77892382 #> [22,] -2.06910952 #> [23,] -1.83502068 #> [24,] -1.78322657 #> [25,] -2.05293145 #> [26,] -2.14776683 #> [27,] -2.11273262 #> [28,] -2.10190136 #> [29,] -2.03454782 #> [30,] -2.07888384 #>  #> , , 128 #>  #>              [,1] #>  [1,] -0.11915655 #>  [2,] -0.44599145 #>  [3,] -0.21660394 #>  [4,] -0.17738906 #>  [5,]  0.04788947 #>  [6,] -0.77538377 #>  [7,] -0.91238932 #>  [8,] -0.26624919 #>  [9,]  0.19332779 #> [10,]  0.25532781 #> [11,]  1.25324572 #> [12,]  1.34284330 #> [13,]  1.21659379 #> [14,]  1.46210184 #> [15,]  1.28699854 #> [16,]  1.10515278 #> [17,]  1.27752950 #> [18,]  1.37505055 #> [19,]  1.27466174 #> [20,]  1.30951744 #> [21,] -1.81036299 #> [22,] -2.07415854 #> [23,] -1.86219064 #> [24,] -1.81817890 #> [25,] -2.03955625 #> [26,] -2.14319815 #> [27,] -2.11262037 #> [28,] -2.10144658 #> [29,] -2.05523353 #> [30,] -2.07226592 #>  #> , , 129 #>  #>               [,1] #>  [1,] -0.166530433 #>  [2,] -0.498971129 #>  [3,] -0.272639395 #>  [4,] -0.233230800 #>  [5,] -0.005520421 #>  [6,] -0.835806393 #>  [7,] -0.969944628 #>  [8,] -0.319370754 #>  [9,]  0.147419006 #> [10,]  0.206715075 #> [11,]  1.233628517 #> [12,]  1.332556328 #> [13,]  1.199313942 #> [14,]  1.457410104 #> [15,]  1.271017489 #> [16,]  1.084244630 #> [17,]  1.259972853 #> [18,]  1.364891740 #> [19,]  1.257647727 #> [20,]  1.297404432 #> [21,] -1.839979796 #> [22,] -2.076404059 #> [23,] -1.887343045 #> [24,] -1.851236223 #> [25,] -2.023362736 #> [26,] -2.135794584 #> [27,] -2.109692124 #> [28,] -2.098170867 #> [29,] -2.073431435 #> [30,] -2.062740203 #>  #> , , 130 #>  #>              [,1] #>  [1,] -0.21427073 #>  [2,] -0.55197380 #>  [3,] -0.32902442 #>  [4,] -0.28948134 #>  [5,] -0.05952661 #>  [6,] -0.89579883 #>  [7,] -1.02674215 #>  [8,] -0.37275059 #>  [9,]  0.10089982 #> [10,]  0.15740743 #> [11,]  1.21332701 #> [12,]  1.32179711 #> [13,]  1.18144891 #> [14,]  1.45228840 #> [15,]  1.25443653 #> [16,]  1.06268967 #> [17,]  1.24176171 #> [18,]  1.35421252 #> [19,]  1.24006792 #> [20,]  1.28476101 #> [21,] -1.86773461 #> [22,] -2.07584627 #> [23,] -1.91044350 #> [24,] -1.88235340 #> [25,] -2.00439857 #> [26,] -2.12558463 #> [27,] -2.10396523 #> [28,] -2.09209260 #> [29,] -2.08911484 #> [30,] -2.05034037 #>  #> , , 131 #>  #>              [,1] #>  [1,] -0.26233215 #>  [2,] -0.60492591 #>  [3,] -0.38570217 #>  [4,] -0.34607935 #>  [5,] -0.11408551 #>  [6,] -0.95524973 #>  [7,] -1.08265793 #>  [8,] -0.42633286 #>  [9,]  0.05379901 #> [10,]  0.10743424 #> [11,]  1.19233956 #> [12,]  1.31056538 #> [13,]  1.16299784 #> [14,]  1.44673526 #> [15,]  1.23725442 #> [16,]  1.04048731 #> [17,]  1.22289388 #> [18,]  1.34301172 #> [19,]  1.22192217 #> [20,]  1.27158550 #> [21,] -1.89359020 #> [22,] -2.07249147 #> [23,] -1.93146065 #> [24,] -1.91148788 #> [25,] -1.98271865 #> [26,] -2.11260335 #> 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#>  [9,] -0.042022069 #> [10,]  0.005619872 #> [11,]  1.148301179 #> [12,]  1.286683394 #> [13,]  1.124334671 #> [14,]  1.434328794 #> [15,]  1.201082098 #> [16,]  0.994138964 #> [17,]  1.183180024 #> [18,]  1.319040726 #> [19,]  1.183932566 #> [20,]  1.243631556 #> [21,] -1.939467558 #> [22,] -2.057447266 #> [23,] -1.967135340 #> [24,] -1.963652091 #> [25,] -1.931467142 #> [26,] -2.078500146 #> [27,] -2.070261925 #> [28,] -2.057322949 #> [29,] -2.120878249 #> [30,] -1.996341270 #>  #> , , 134 #>  #>              [,1] #>  [1,] -0.40795128 #>  [2,] -0.76269336 #>  [3,] -0.55687691 #>  [4,] -0.51729261 #>  [5,] -0.28059912 #>  [6,] -1.12917981 #>  [7,] -1.24382152 #>  [8,] -0.58769275 #>  [9,] -0.09067430 #> [10,] -0.04615126 #> [11,]  1.12524783 #> [12,]  1.27403272 #> [13,]  1.10412137 #> [14,]  1.42747254 #> [15,]  1.18208977 #> [16,]  0.96999288 #> [17,]  1.16233027 #> [18,]  1.30626825 #> [19,]  1.16408880 #> [20,]  1.22884991 #> [21,] -1.95942791 #> [22,] -2.04580191 #> [23,] 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-0.8909335 #>  [2,] -1.2493131 #>  [3,] -1.1176006 #>  [4,] -1.0791731 #>  [5,] -0.8483666 #>  [6,] -1.6215607 #>  [7,] -1.6674250 #>  [8,] -1.1106271 #>  [9,] -0.5943768 #> [10,] -0.5851257 #> [11,]  0.8567126 #> [12,]  1.1214780 #> [13,]  0.8696444 #> [14,]  1.3346159 #> [15,]  0.9587913 #> [16,]  0.6931384 #> [17,]  0.9171453 #> [18,]  1.1494409 #> [19,]  0.9346271 #> [20,]  1.0511940 #> [21,] -2.0449634 #> [22,] -1.7888205 #> [23,] -2.0069577 #> [24,] -2.0958325 #> [25,] -1.4914842 #> [26,] -1.7194733 #> [27,] -1.7549110 #> [28,] -1.7384347 #> [29,] -2.0409239 #> [30,] -1.6108609 #>  #> , , 145 #>  #>             [,1] #>  [1,] -0.9372512 #>  [2,] -1.2920483 #>  [3,] -1.1706601 #>  [4,] -1.1322345 #>  [5,] -0.9043930 #>  [6,] -1.6598173 #>  [7,] -1.6964493 #>  [8,] -1.1595568 #>  [9,] -0.6453556 #> [10,] -0.6399866 #> [11,]  0.8260759 #> [12,]  1.1036183 #> [13,]  0.8429764 #> [14,]  1.3228687 #> [15,]  0.9331229 #> [16,]  0.6619658 #> [17,]  0.8889516 #> [18,]  1.1308286 #> [19,]  0.9085997 #> [20,]  1.0304201 #> [21,] -2.0419076 #> [22,] -1.7505521 #> [23,] -1.9974414 #> [24,] -2.0944466 #> [25,] -1.4414052 #> [26,] -1.6749859 #> [27,] -1.7136305 #> [28,] -1.6969084 #> [29,] -2.0189454 #> [30,] -1.5642081 #>  #> , , 146 #>  #>             [,1] #>  [1,] -0.9828935 #>  [2,] -1.3332640 #>  [3,] -1.2227881 #>  [4,] -1.1843083 #>  [5,] -0.9599511 #>  [6,] -1.6954964 #>  [7,] -1.7224681 #>  [8,] -1.2075076 #>  [9,] -0.6962112 #> [10,] -0.6947761 #> [11,]  0.7947597 #> [12,]  1.0852859 #> [13,]  0.8157287 #> [14,]  1.3106682 #> [15,]  0.9068501 #> [16,]  0.6301748 #> [17,]  0.8600927 #> [18,]  1.1116811 #> [19,]  0.8820183 #> [20,]  1.0090964 #> [21,] -2.0367487 #> [22,] -1.7103496 #> [23,] -1.9857975 #> [24,] -2.0908219 #> [25,] -1.3902299 #> [26,] -1.6290080 #> [27,] -1.6706863 #> [28,] -1.6537383 #> [29,] -1.9946929 #> [30,] -1.5161591 #>  #> , , 147 #>  #>             [,1] #>  [1,] -1.0277738 #>  [2,] -1.3728439 #>  [3,] -1.2738804 #>  [4,] -1.2352805 #>  [5,] -1.0149481 #>  [6,] -1.7284527 #>  [7,] -1.7453416 #>  [8,] -1.2543799 #>  [9,] -0.7468770 #> [10,] -0.7494235 #> [11,]  0.7627676 #> [12,]  1.0664813 #> [13,]  0.7879038 #> [14,]  1.2980130 #> [15,]  0.8799744 #> [16,]  0.5977712 #> [17,]  0.8305707 #> [18,]  1.0919979 #> [19,]  0.8548854 #> [20,]  0.9872226 #> [21,] -2.0295002 #> [22,] -1.6683205 #> [23,] -1.9720548 #> [24,] -2.0849706 #> [25,] -1.3381088 #> [26,] -1.5816684 #> [27,] -1.6261981 #> [28,] -1.6090457 #> [29,] -1.9682261 #> [30,] -1.4668560 #>  #> , , 148 #>  #>             [,1] #>  [1,] -1.0718036 #>  [2,] -1.4106708 #>  [3,] -1.3238302 #>  [4,] -1.2850350 #>  [5,] -1.0692882 #>  [6,] -1.7585420 #>  [7,] -1.7649337 #>  [8,] -1.3000723 #>  [9,] -0.7972840 #> [10,] -0.8038556 #> [11,]  0.7301038 #> [12,]  1.0472049 #> [13,]  0.7595046 #> [14,]  1.2849018 #> [15,]  0.8524978 #> [16,]  0.5647614 #> [17,]  0.8003883 #> [18,]  1.0717788 #> [19,]  0.8272035 #> [20,]  0.9647987 #> [21,] -2.0201794 #> [22,] -1.6245773 #> [23,] 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-1.4353424 #> [28,] -1.4176188 #> [29,] -1.8415896 #> [30,] -1.2600763 #>  #> , , 152 #>  #>             [,1] #>  [1,] -1.2375816 #>  [2,] -1.5420896 #>  [3,] -1.5100027 #>  [4,] -1.4694801 #>  [5,] -1.2780727 #>  [6,] -1.8474323 #>  [7,] -1.8079251 #>  [8,] -1.4689558 #>  [9,] -0.9948612 #> [10,] -1.0178734 #> [11,]  0.5928397 #> [12,]  0.9653949 #> [13,]  0.6402355 #> [14,]  1.2278698 #> [15,]  0.7366313 #> [16,]  0.4268129 #> [17,]  0.6731234 #> [18,]  0.9855431 #> [19,]  0.7110496 #> [20,]  0.8696089 #> [21,] -1.9626512 #> [22,] -1.4348978 #> [23,] -1.8731478 #> [24,] -2.0230407 #> [25,] -1.0687777 #> [26,] -1.3292983 #> [27,] -1.3850693 #> [28,] -1.3672721 #> [29,] -1.8051258 #> [30,] -1.2067580 #>  #> , , 153 #>  #>             [,1] #>  [1,] -1.2759679 #>  [2,] -1.5693835 #>  [3,] -1.5525748 #>  [4,] -1.5113362 #>  [5,] -1.3276019 #>  [6,] -1.8611184 #>  [7,] -1.8092383 #>  [8,] -1.5071721 #>  [9,] -1.0428570 #> [10,] -1.0700383 #> [11,]  0.5569043 #> [12,]  0.9437707 #> [13,]  0.6090219 #> [14,]  1.2124588 #> [15,]  0.7061907 #> [16,]  0.3908934 #> [17,]  0.6396961 #> [18,]  0.9626456 #> [19,]  0.6806734 #> [20,]  0.8444418 #> [21,] -1.9433603 #> [22,] -1.3844495 #> [23,] -1.8476434 #> [24,] -2.0043224 #> [25,] -1.0142842 #> [26,] -1.2766803 #> [27,] -1.3340497 #> [28,] -1.3162092 #> [29,] -1.7669121 #> [30,] -1.1531048 #>  #> , , 154 #>  #>             [,1] #>  [1,] -1.3129373 #>  [2,] -1.5942204 #>  [3,] -1.5933287 #>  [4,] -1.5512417 #>  [5,] -1.3758474 #>  [6,] -1.8711377 #>  [7,] -1.8065661 #>  [8,] -1.5435703 #>  [9,] -1.0901317 #> [10,] -1.1214941 #> [11,]  0.5203369 #> [12,]  0.9216800 #> [13,]  0.5772603 #> [14,]  1.1965843 #> [15,]  0.6751685 #> [16,]  0.3544217 #> [17,]  0.6056355 #> [18,]  0.9392137 #> [19,]  0.6497709 #> [20,]  0.8187293 #> [21,] -1.9221801 #> [22,] -1.3330634 #> [23,] -1.8203554 #> [24,] -1.9835802 #> [25,] -0.9599578 #> [26,] -1.2236869 #> [27,] -1.2824264 #> [28,] -1.2645742 #> [29,] -1.7270425 #> [30,] -1.0992759 #>  #> , , 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-1.7358357 #>  [4,] -1.6888594 #>  [5,] -1.5537406 #>  [6,] -1.8723273 #>  [7,] -1.7543390 #>  [8,] -1.6688044 #>  [9,] -1.2703021 #> [10,] -1.3183835 #> [11,]  0.3679472 #> [12,]  0.8286816 #> [13,]  0.4448640 #> [14,]  1.1284302 #> [15,]  0.5453687 #> [16,]  0.2032686 #> [17,]  0.4632094 #> [18,]  0.8401649 #> [19,]  0.5210080 #> [20,]  0.7104663 #> [21,] -1.8194967 #> [22,] -1.1210352 #> [23,] -1.6946462 #> [24,] -1.8813428 #> [25,] -0.7475039 #> [26,] -1.0109096 #> [27,] -1.0727920 #> [28,] -1.0552288 #> [29,] -1.5530348 #> [30,] -0.8853788 #>  #> , , 159 #>  #>             [,1] #>  [1,] -1.4730738 #>  [2,] -1.6776589 #>  [3,] -1.7657550 #>  [4,] -1.7171430 #>  [5,] -1.5938679 #>  [6,] -1.8624151 #>  [7,] -1.7305680 #>  [8,] -1.6944829 #>  [9,] -1.3126691 #> [10,] -1.3648946 #> [11,]  0.3283777 #> [12,]  0.8042818 #> [13,]  0.4104657 #> [14,]  1.1102232 #> [15,]  0.5115221 #> [16,]  0.1642358 #> [17,]  0.4261010 #> [18,]  0.8140799 #> [19,]  0.4875607 #> [20,]  0.6820607 #> [21,] -1.7895998 #> [22,] -1.0671505 #> [23,] -1.6594316 #> [24,] -1.8512444 #> [25,] -0.6963772 #> [26,] -0.9582464 #> [27,] -1.0203260 #> [28,] -1.0029227 #> [29,] -1.5064413 #> [30,] -0.8330411 #>  #> , , 160 #>  #>             [,1] #>  [1,] -1.4994659 #>  [2,] -1.6854616 #>  [3,] -1.7931621 #>  [4,] -1.7427348 #>  [5,] -1.6320247 #>  [6,] -1.8482551 #>  [7,] -1.7024201 #>  [8,] -1.7176967 #>  [9,] -1.3537834 #> [10,] -1.4101242 #> [11,]  0.2882461 #> [12,]  0.7794263 #> [13,]  0.3755654 #> [14,]  1.0915473 #> [15,]  0.4771315 #> [16,]  0.1247376 #> [17,]  0.3884125 #> [18,]  0.7874697 #> [19,]  0.4536251 #> [20,]  0.6531258 #> [21,] -1.7581307 #> [22,] -1.0132171 #> [23,] -1.6228551 #> [24,] -1.8194554 #> [25,] -0.6463423 #> [26,] -0.9060831 #> [27,] -0.9681266 #> [28,] -0.9509193 #> [29,] -1.4588395 #> [30,] -0.7814622 #>  #> , , 161 #>  #>              [,1] #>  [1,] -1.52375060 #>  [2,] -1.69007595 #>  [3,] -1.81794434 #>  [4,] -1.76551653 #>  [5,] -1.66809449 #>  [6,] -1.82978310 #>  [7,] -1.66987209 #>  [8,] -1.73834234 #>  [9,] -1.39355171 #> [10,] -1.45397145 #> [11,]  0.24756750 #> [12,]  0.75411740 #> [13,]  0.34017292 #> [14,]  1.07240192 #> [15,]  0.44220533 #> [16,]  0.08479243 #> [17,]  0.35015560 #> [18,]  0.76033682 #> [19,]  0.41920939 #> [20,]  0.62366572 #> [21,] -1.72515483 #> [22,] -0.95938715 #> [23,] -1.58499907 #> [24,] -1.78604485 #> [25,] -0.59753915 #> [26,] -0.85455873 #> [27,] -0.91633600 #> [28,] -0.89936072 #> [29,] -1.41034896 #> [30,] -0.73078781 #>  #> , , 162 #>  #>              [,1] #>  [1,] -1.54583174 #>  [2,] -1.69141471 #>  [3,] -1.83999159 #>  [4,] -1.78537266 #>  [5,] -1.70196118 #>  [6,] -1.80694604 #>  [7,] -1.63291485 #>  [8,] -1.75631860 #>  [9,] -1.43187992 #> [10,] -1.49633421 #> [11,]  0.20635811 #> [12,]  0.72835784 #> [13,]  0.30429913 #> [14,]  1.05278664 #> [15,]  0.40675272 #> [16,]  0.04441943 #> [17,]  0.31134327 #> [18,]  0.73268411 #> [19,]  0.38432242 #> [20,]  0.59368508 #> [21,] -1.69074069 #> [22,] -0.90581261 #> [23,] -1.54594882 #> [24,] -1.75108569 #> [25,] -0.55010203 #> [26,] -0.80380908 #> [27,] -0.86509403 #> [28,] -0.84838693 #> [29,] -1.36109148 #> [30,] -0.68115896 #>  #> , , 163 #>  #>               [,1] #>  [1,] -1.565614822 #>  [2,] -1.689396642 #>  [3,] -1.859195957 #>  [4,] -1.802190985 #>  [5,] -1.733509164 #>  [6,] -1.779703029 #>  [7,] -1.591553806 #>  [8,] -1.771526880 #>  [9,] -1.468673251 #> [10,] -1.537109602 #> [11,]  0.164635363 #> [12,]  0.702150578 #> [13,]  0.267955510 #> [14,]  1.032701100 #> [15,]  0.370783567 #> [16,]  0.003639173 #> [17,]  0.271989300 #> [18,]  0.704514739 #> [19,]  0.348973506 #> [20,]  0.563188902 #> [21,] -1.654960062 #> [22,] -0.852644488 #> [23,] -1.505792561 #> [24,] -1.714654200 #> [25,] -0.504158381 #> [26,] -0.753965528 #> [27,] -0.814537556 #> [28,] -0.798134484 #> [29,] -1.311191159 #> [30,] -0.632711044 #>  #> , , 164 #>  #>             [,1] #>  [1,] -1.5830073 #>  [2,] -1.6839470 #>  [3,] -1.8754525 #>  [4,] -1.8158631 #>  [5,] -1.7626239 #>  [6,] -1.7480259 #>  [7,] -1.5458097 #>  [8,] -1.7838717 #>  [9,] -1.5038365 #> [10,] -1.5761941 #> [11,]  0.1224178 #> [12,]  0.6754988 #> [13,]  0.2311544 #> [14,]  1.0121451 #> [15,]  0.3343085 #> [16,] -0.0375266 #> [17,]  0.2321086 #> [18,]  0.6758322 #> [19,]  0.3131727 #> [20,]  0.5321827 #> [21,] -1.6178879 #> [22,] -0.8000323 #> [23,] -1.4646212 #> [24,] -1.6768301 #> [25,] -0.4598282 #> [26,] -0.7051546 #> [27,] -0.7647998 #> [28,] -0.7487361 #> [29,] -1.2607738 #> [30,] -0.5855732 #>  #> , , 165 #>  #>              [,1] #>  [1,] -1.59791900 #>  [2,] -1.67499828 #>  [3,] -1.88865976 #>  [4,] -1.82628487 #>  [5,] -1.78919235 #>  [6,] -1.71189999 #>  [7,] -1.49571908 #>  [8,] -1.79326132 #>  [9,] -1.53727421 #> [10,] -1.61348382 #> [11,]  0.07972531 #> [12,]  0.64840605 #> [13,]  0.19390892 #> [14,]  0.99111852 #> [15,]  0.29733902 #> [16,] -0.07905492 #> [17,]  0.19171700 #> [18,]  0.64664055 #> [19,]  0.27693055 #> [20,]  0.50067269 #> [21,] -1.57960192 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[21,] -1.45828185 #> [22,] -0.59804639 #> [23,] -1.29168406 #> [24,] -1.51331368 #> [25,] -0.30073959 #> [26,] -0.52256097 #> [27,] -0.57653617 #> [28,] -0.56216582 #> [29,] -1.05649281 #> [30,] -0.41244395 #>  #> , , 169 #>  #>              [,1] #>  [1,] -1.63105951 #>  [2,] -1.60314110 #>  [3,] -1.90910991 #>  [4,] -1.83356976 #>  [5,] -1.86781341 #>  [6,] -1.52312183 #>  [7,] -1.25320806 #>  [8,] -1.79957982 #>  [9,] -1.65186936 #> [10,] -1.74261867 #> [11,] -0.09535434 #> [12,]  0.53570495 #> [13,]  0.04077688 #> [14,]  0.90231094 #> [15,]  0.14477474 #> [16,] -0.24828876 #> [17,]  0.02540029 #> [18,]  0.52487509 #> [19,]  0.12778729 #> [20,]  0.36973529 #> [21,] -1.41597382 #> [22,] -0.55036048 #> [23,] -1.24687902 #> [24,] -1.46983117 #> [25,] -0.26596450 #> [26,] -0.48059512 #> [27,] -0.53271735 #> [28,] -0.51884763 #> [29,] -1.00541368 #> [30,] -0.37352201 #>  #> , , 170 #>  #>               [,1] #>  [1,] -1.632325321 #>  [2,] -1.575971725 #>  [3,] -1.905699699 #>  [4,] 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[2,] -1.47212552 #>  [3,] -1.87385918 #>  [4,] -1.78202851 #>  [5,] -1.89730355 #>  [6,] -1.26590731 #>  [7,] -0.94852487 #>  [8,] -1.75250874 #>  [9,] -1.73135332 #> [10,] -1.83481895 #> [11,] -0.27611189 #> [12,]  0.41630786 #> [13,] -0.11817987 #> [14,]  0.80601300 #> [15,] -0.01455977 #> [16,] -0.42114280 #> [17,] -0.14751536 #> [18,]  0.39539135 #> [19,] -0.02737467 #> [20,]  0.23137724 #> [21,] -1.23982093 #> [22,] -0.37465484 #> [23,] -1.06443384 #> [24,] -1.28838132 #> [25,] -0.14864585 #> [26,] -0.32995835 #> [27,] -0.37334986 #> [28,] -0.36173215 #> [29,] -0.80489213 #> [30,] -0.23754434 #>  #> , , 174 #>  #>              [,1] #>  [1,] -1.60729772 #>  [2,] -1.43009567 #>  [3,] -1.85585406 #>  [4,] -1.75950519 #>  [5,] -1.89631259 #>  [6,] -1.19160061 #>  [7,] -0.86380168 #>  [8,] -1.73198693 #>  [9,] -1.74506911 #> [10,] -1.85135994 #> [11,] -0.32197197 #> [12,]  0.38545547 #> [13,] -0.15868333 #> [14,]  0.78077702 #> [15,] -0.05531947 #> [16,] -0.46468148 #> [17,] 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[1,] -1.57600525 #>  [2,] -1.33509776 #>  [3,] -1.80850240 #>  [4,] -1.70265070 #>  [5,] -1.88375480 #>  [6,] -1.03196614 #>  [7,] -0.68552807 #>  [8,] -1.68019960 #>  [9,] -1.76453396 #> [10,] -1.87598618 #> [11,] -0.41426687 #> [12,]  0.32259499 #> [13,] -0.24045135 #> [14,]  0.72892414 #> [15,] -0.13780743 #> [16,] -0.55189728 #> [17,] -0.28058298 #> [18,]  0.29349804 #> [19,] -0.14707202 #> [20,]  0.12315060 #> [21,] -1.10310882 #> [22,] -0.26164496 #> [23,] -0.92712333 #> [24,] -1.14725484 #> [25,] -0.08413434 #> [26,] -0.23657407 #> [27,] -0.27252449 #> [28,] -0.26277960 #> [29,] -0.66192015 #> [30,] -0.15738713 #>  #> , , 177 #>  #>              [,1] #>  [1,] -1.55552968 #>  [2,] -1.28223528 #>  [3,] -1.77910233 #>  [4,] -1.66829175 #>  [5,] -1.87205961 #>  [6,] -0.94699113 #>  [7,] -0.59245941 #>  [8,] -1.64890058 #>  [9,] -1.77012962 #> [10,] -1.88389993 #> [11,] -0.46062994 #> [12,]  0.29060241 #> [13,] -0.28166697 #> [14,]  0.70231201 #> [15,] -0.17949059 #> [16,] -0.59549669 #> [17,] -0.32542997 #> [18,]  0.25867174 #> [19,] -0.18750433 #> [20,]  0.08629483 #> [21,] -1.05718429 #> [22,] -0.22801697 #> [23,] -0.88181476 #> [24,] -1.09981114 #> [25,] -0.06705083 #> [26,] -0.20933106 #> [27,] -0.24273710 #> [28,] -0.23363340 #> [29,] -0.61629472 #> [30,] -0.13488323 #>  #> , , 178 #>  #>              [,1] #>  [1,] -1.53180295 #>  [2,] -1.22588960 #>  [3,] -1.74586648 #>  [4,] -1.62997862 #>  [5,] -1.85668026 #>  [6,] -0.85884277 #>  [7,] -0.49711936 #>  [8,] -1.61399145 #>  [9,] -1.77287146 #> [10,] -1.88877293 #> [11,] -0.50708638 #> [12,]  0.25824608 #> [13,] -0.32306920 #> [14,]  0.67524641 #> [15,] -0.22143460 #> [16,] -0.63903624 #> [17,] -0.37046955 #> [18,]  0.22343212 #> [19,] -0.22816844 #> [20,]  0.04907352 #> [21,] -1.01124820 #> [22,] -0.19651980 #> [23,] -0.83690653 #> [24,] -1.05234342 #> [25,] -0.05210659 #> [26,] -0.18403344 #> [27,] -0.21489964 #> [28,] -0.20643900 #> [29,] -0.57186373 #> [30,] -0.11445269 #>  #> , , 179 #>  #>    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#> [21,] -0.3519563177 #> [22,]  0.0154775611 #> [23,] -0.2445730767 #> [24,] -0.3716456780 #> [25,] -0.0064200689 #> [26,]  0.0101423051 #> [27,] -0.0002777313 #> [28,]  0.0016307816 #> [29,] -0.0832143970 #> [30,]  0.0092546984 #>  #> , , 195 #>  #>               [,1] #>  [1,] -0.654717124 #>  [2,]  0.127658222 #>  [3,] -0.637495545 #>  [4,] -0.439656403 #>  [5,] -1.026123521 #>  [6,]  0.851070068 #>  [7,]  1.149084580 #>  [8,] -0.519361854 #>  [9,] -1.340593576 #> [10,] -1.456981292 #> [11,] -1.266834006 #> [12,] -0.336592748 #> [13,] -1.024536080 #> [14,]  0.150247593 #> [15,] -0.945162858 #> [16,] -1.323698613 #> [17,] -1.127206109 #> [18,] -0.424660108 #> [19,] -0.929403034 #> [20,] -0.620522123 #> [21,] -0.319758884 #> [22,]  0.013566486 #> [23,] -0.218897974 #> [24,] -0.338520278 #> [25,] -0.006409640 #> [26,]  0.015507054 #> [27,]  0.003928731 #> [28,]  0.005925706 #> [29,] -0.068273093 #> [30,]  0.012437277 #>  #> , , 196 #>  #>               [,1] #>  [1,] -0.579588113 #>  [2,]  0.218723803 #>  [3,] -0.546451488 #>  [4,] -0.345755931 #>  [5,] -0.946638871 #>  [6,]  0.944507768 #>  [7,]  1.226342814 #>  [8,] -0.431896082 #>  [9,] -1.286499353 #> [10,] -1.400522808 #> [11,] -1.306747345 #> [12,] -0.373402769 #> [13,] -1.063512522 #> [14,]  0.115934745 #> [15,] -0.986299903 #> [16,] -1.357633962 #> [17,] -1.168537522 #> [18,] -0.464592677 #> [19,] -0.969443835 #> [20,] -0.660676496 #> [21,] -0.289022228 #> [22,]  0.010619663 #> [23,] -0.194804070 #> [24,] -0.306915328 #> [25,] -0.005362121 #> [26,]  0.021134833 #> [27,]  0.007997375 #> [28,]  0.010170296 #> [29,] -0.055089110 #> [30,]  0.016350367 #>  #> , , 197 #>  #>               [,1] #>  [1,] -0.502668432 #>  [2,]  0.309386112 #>  [3,] -0.453621853 #>  [4,] -0.250507675 #>  [5,] -0.864456170 #>  [6,]  1.034767317 #>  [7,]  1.299081024 #>  [8,] -0.342960082 #>  [9,] -1.229428481 #> [10,] -1.340809061 #> [11,] -1.345755026 #> [12,] -0.410303182 #> [13,] -1.101961487 #> [14,]  0.081299160 #> [15,] -1.027010614 #> [16,] -1.390492115 #> [17,] -1.209178968 #> [18,] -0.504578528 #> [19,] -1.009118845 #> [20,] -0.700728452 #> [21,] -0.259789972 #> [22,]  0.006821956 #> [23,] -0.172299749 #> [24,] -0.276873409 #> [25,] -0.003022507 #> [26,]  0.027240082 #> [27,]  0.012130854 #> [28,]  0.014570853 #> [29,] -0.043598440 #> [30,]  0.021237324 #>  #> , , 198 #>  #>                [,1] #>  [1,] -0.4241418388 #>  [2,]  0.3993390525 #>  [3,] -0.3592399023 #>  [4,] -0.1541812292 #>  [5,] -0.7797507914 #>  [6,]  1.1214751190 #>  [7,]  1.3669719811 #>  [8,] -0.2527834549 #>  [9,] -1.1694609433 #> [10,] -1.2779218562 #> [11,] -1.3837927577 #> [12,] -0.4472727485 #> [13,] -1.1398347803 #> [14,]  0.0463528277 #> [15,] -1.0672472594 #> [16,] -1.4222108091 #> [17,] -1.2490716686 #> [18,] -0.5445896009 #> [19,] -1.0483866182 #> [20,] -0.7406432686 #> [21,] -0.2320996347 #> [22,]  0.0023689326 #> [23,] -0.1513854889 #> [24,] -0.2484302751 #> [25,]  0.0008640167 #> [26,]  0.0340411750 #> [27,]  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#>  [9,] -1.041206571 #> [10,] -1.143009567 #> [11,] -1.456697852 #> [12,] -0.521330611 #> [13,] -1.213657399 #> [14,] -0.024421038 #> [15,] -1.146102498 #> [16,] -1.481979518 #> [17,] -1.326371359 #> [18,] -0.624570303 #> [19,] -1.125530250 #> [20,] -0.819917602 #> [21,] -0.181462697 #> [22,] -0.007672129 #> [23,] -0.114288475 #> [24,] -0.196447550 #> [25,]  0.014285658 #> [26,]  0.050616236 #> [27,]  0.027032430 #> [28,]  0.030850113 #> [29,] -0.018480015 #> [30,]  0.044187739 #>  #>  #> $original_grids #>       [,1]      [,2]       [,3]       [,4]      [,5]     [,6]      [,7] #>  [1,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [2,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [3,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [4,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [5,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [6,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [7,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [8,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>  [9,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [10,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [11,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [12,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [13,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [14,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [15,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [16,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [17,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [18,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [19,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [20,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [21,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [22,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [23,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [24,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [25,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [26,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [27,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [28,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [29,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #> [30,]    0 0.0315738 0.06314759 0.09472139 0.1262952 0.157869 0.1894428 #>            [,8]      [,9]     [,10]    [,11]     [,12]     [,13]     [,14] #>  [1,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [2,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [3,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [4,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [5,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [6,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [7,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [8,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>  [9,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [10,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [11,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [12,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [13,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [14,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [15,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [16,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [17,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [18,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [19,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [20,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [21,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [22,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [23,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [24,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [25,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [26,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [27,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [28,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [29,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #> [30,] 0.2210166 0.2525904 0.2841642 0.315738 0.3473118 0.3788855 0.4104593 #>           [,15]     [,16]     [,17]     [,18]     [,19]     [,20]     [,21] #>  [1,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [2,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [3,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [4,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [5,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [6,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [7,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [8,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>  [9,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [10,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [11,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [12,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [13,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [14,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [15,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [16,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [17,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [18,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [19,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [20,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [21,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [22,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [23,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [24,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [25,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [26,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [27,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [28,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [29,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [30,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>           [,22]     [,23]     [,24]     [,25]     [,26]     [,27]     [,28] #>  [1,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [2,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [3,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [4,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [5,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [6,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [7,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [8,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>  [9,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [10,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [11,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [12,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [13,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [14,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [15,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [16,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [17,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [18,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [19,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [20,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [21,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [22,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [23,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [24,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [25,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [26,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [27,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [28,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [29,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [30,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>           [,29]     [,30]     [,31]     [,32]    [,33]    [,34]    [,35] #>  [1,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [2,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [3,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [4,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [5,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [6,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [7,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [8,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>  [9,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [10,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [11,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [12,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [13,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [14,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [15,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [16,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [17,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [18,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [19,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [20,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [21,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [22,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [23,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [24,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [25,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [26,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [27,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [28,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [29,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #> [30,] 0.8840663 0.9156401 0.9472139 0.9787877 1.010361 1.041935 1.073509 #>          [,36]    [,37]   [,38]    [,39]    [,40]    [,41]    [,42]    [,43] #>  [1,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [2,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [3,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [4,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [5,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [6,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [7,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [8,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>  [9,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [10,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [11,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [12,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [13,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [14,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [15,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [16,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [17,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [18,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [19,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [20,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [21,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [22,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [23,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [24,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [25,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [26,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [27,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [28,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [29,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #> [30,] 1.105083 1.136657 1.16823 1.199804 1.231378 1.262952 1.294526 1.326099 #>          [,44]    [,45]    [,46]    [,47]    [,48]    [,49]    [,50]   [,51] #>  [1,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [2,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [3,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [4,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [5,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [6,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [7,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [8,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>  [9,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [10,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [11,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [12,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [13,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [14,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [15,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [16,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [17,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [18,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [19,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [20,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [21,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [22,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [23,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [24,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [25,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [26,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [27,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [28,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [29,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #> [30,] 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 1.57869 #>          [,52]    [,53]    [,54]    [,55]    [,56]    [,57]    [,58]   [,59] #>  [1,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [2,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [3,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [4,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [5,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [6,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [7,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [8,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>  [9,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [10,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [11,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [12,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [13,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [14,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [15,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [16,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [17,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [18,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [19,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [20,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [21,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [22,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [23,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [24,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [25,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [26,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [27,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [28,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [29,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #> [30,] 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 1.83128 #>          [,60]    [,61]    [,62]    [,63]    [,64]    [,65]    [,66]    [,67] #>  [1,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [2,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [3,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [4,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [5,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [6,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [7,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [8,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>  [9,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [10,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [11,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [12,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [13,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [14,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [15,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [16,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [17,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [18,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [19,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [20,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [21,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [22,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [23,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [24,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [25,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [26,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [27,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [28,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [29,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #> [30,] 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 2.083871 #>          [,68]    [,69]    [,70]    [,71]    [,72]    [,73]    [,74]    [,75] #>  [1,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [2,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [3,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [4,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [5,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [6,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [7,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [8,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>  [9,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [10,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [11,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [12,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [13,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [14,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [15,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [16,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [17,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [18,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [19,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [20,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [21,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [22,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [23,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [24,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [25,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [26,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [27,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [28,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [29,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #> [30,] 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 2.336461 #>          [,76]    [,77]    [,78]    [,79]   [,80]    [,81]    [,82]    [,83] #>  [1,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [2,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [3,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [4,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [5,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [6,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [7,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [8,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>  [9,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [10,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [11,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [12,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [13,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [14,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [15,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [16,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [17,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [18,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [19,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [20,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [21,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [22,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [23,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [24,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [25,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [26,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [27,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [28,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [29,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #> [30,] 2.368035 2.399608 2.431182 2.462756 2.49433 2.525904 2.557477 2.589051 #>          [,84]    [,85]    [,86]    [,87]   [,88]    [,89]    [,90]    [,91] #>  [1,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [2,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [3,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [4,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [5,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [6,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [7,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [8,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>  [9,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [10,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [11,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [12,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [13,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [14,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [15,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [16,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [17,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [18,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [19,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [20,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [21,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [22,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [23,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [24,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [25,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [26,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [27,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [28,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [29,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #> [30,] 2.620625 2.652199 2.683773 2.715346 2.74692 2.778494 2.810068 2.841642 #>          [,92]    [,93]    [,94]    [,95]    [,96]    [,97]    [,98]    [,99] #>  [1,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [2,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [3,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [4,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [5,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [6,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [7,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [8,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>  [9,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [10,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [11,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [12,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [13,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [14,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [15,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [16,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [17,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [18,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [19,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [20,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [21,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [22,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [23,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [24,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [25,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [26,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [27,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [28,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [29,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #> [30,] 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 3.094232 #>         [,100]  [,101]   [,102]   [,103]   [,104]   [,105]   [,106]   [,107] #>  [1,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [2,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [3,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [4,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [5,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [6,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [7,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [8,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>  [9,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [10,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [11,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [12,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [13,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [14,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [15,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [16,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [17,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [18,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [19,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [20,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [21,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [22,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [23,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [24,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [25,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [26,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [27,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [28,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [29,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #> [30,] 3.125806 3.15738 3.188953 3.220527 3.252101 3.283675 3.315249 3.346822 #>         [,108]  [,109]   [,110]   [,111]   [,112]   [,113]   [,114]   [,115] #>  [1,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [2,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [3,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [4,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [5,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [6,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [7,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [8,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>  [9,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [10,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [11,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [12,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [13,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [14,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [15,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [16,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [17,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [18,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [19,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [20,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [21,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [22,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [23,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [24,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [25,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [26,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [27,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [28,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [29,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #> [30,] 3.378396 3.40997 3.441544 3.473118 3.504691 3.536265 3.567839 3.599413 #>         [,116]  [,117]   [,118]   [,119]   [,120]   [,121]   [,122]   [,123] #>  [1,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [2,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [3,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [4,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [5,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [6,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [7,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [8,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>  [9,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [10,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [11,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [12,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [13,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [14,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [15,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [16,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [17,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [18,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [19,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [20,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [21,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [22,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [23,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [24,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [25,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [26,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [27,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [28,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [29,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #> [30,] 3.630986 3.66256 3.694134 3.725708 3.757282 3.788855 3.820429 3.852003 #>         [,124]   [,125]   [,126]   [,127]   [,128]   [,129]  [,130]   [,131] #>  [1,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [2,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [3,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [4,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [5,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [6,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [7,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [8,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>  [9,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [10,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [11,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [12,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [13,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [14,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [15,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [16,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [17,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [18,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [19,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [20,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [21,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [22,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [23,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [24,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [25,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [26,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [27,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [28,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [29,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #> [30,] 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.07302 4.104593 #>         [,132]   [,133]   [,134]   [,135]   [,136]   [,137]  [,138]   [,139] #>  [1,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [2,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [3,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [4,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [5,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [6,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [7,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [8,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>  [9,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [10,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [11,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [12,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [13,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [14,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [15,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [16,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [17,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [18,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [19,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [20,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [21,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [22,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [23,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [24,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [25,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [26,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [27,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [28,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [29,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #> [30,] 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.32561 4.357184 #>         [,140]   [,141]   [,142]   [,143]   [,144]   [,145] [,146]   [,147] #>  [1,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [2,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [3,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [4,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [5,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [6,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [7,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [8,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>  [9,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [10,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [11,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [12,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [13,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [14,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [15,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [16,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [17,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [18,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [19,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [20,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [21,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [22,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [23,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [24,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [25,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [26,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [27,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [28,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [29,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #> [30,] 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.5782 4.609774 #>         [,148]   [,149]   [,150]   [,151]   [,152]   [,153]   [,154]   [,155] #>  [1,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [2,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [3,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [4,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [5,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [6,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [7,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [8,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>  [9,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [10,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [11,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [12,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [13,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [14,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [15,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [16,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [17,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [18,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [19,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [20,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [21,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [22,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [23,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [24,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [25,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [26,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [27,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [28,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [29,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #> [30,] 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 4.862365 #>         [,156]   [,157]   [,158]  [,159]   [,160]   [,161]   [,162]   [,163] #>  [1,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [2,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [3,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [4,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [5,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [6,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [7,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [8,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>  [9,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [10,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [11,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [12,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [13,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [14,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [15,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [16,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [17,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [18,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [19,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [20,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [21,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [22,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [23,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [24,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [25,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [26,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [27,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [28,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [29,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #> [30,] 4.893938 4.925512 4.957086 4.98866 5.020233 5.051807 5.083381 5.114955 #>         [,164]   [,165]   [,166]  [,167]   [,168]   [,169]   [,170]   [,171] #>  [1,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [2,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [3,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [4,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [5,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [6,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [7,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [8,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>  [9,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [10,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [11,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [12,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [13,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [14,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [15,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [16,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [17,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [18,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [19,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [20,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [21,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [22,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [23,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [24,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [25,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [26,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [27,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [28,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [29,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #> [30,] 5.146529 5.178102 5.209676 5.24125 5.272824 5.304398 5.335971 5.367545 #>         [,172]   [,173]   [,174]  [,175]   [,176]   [,177]   [,178]   [,179] #>  [1,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [2,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [3,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [4,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [5,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [6,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [7,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [8,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>  [9,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [10,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [11,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [12,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [13,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [14,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [15,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [16,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [17,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [18,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [19,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [20,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [21,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [22,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [23,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [24,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [25,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [26,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [27,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [28,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [29,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #> [30,] 5.399119 5.430693 5.462267 5.49384 5.525414 5.556988 5.588562 5.620136 #>         [,180]   [,181]   [,182]   [,183]   [,184]   [,185]   [,186]   [,187] #>  [1,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [2,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [3,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [4,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [5,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [6,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [7,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [8,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>  [9,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [10,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [11,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [12,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [13,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [14,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [15,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [16,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [17,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [18,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [19,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [20,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [21,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [22,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [23,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [24,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [25,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [26,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [27,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [28,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [29,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #> [30,] 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 5.872726 #>       [,188]   [,189]   [,190]   [,191]   [,192]   [,193]   [,194]   [,195] #>  [1,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [2,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [3,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [4,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [5,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [6,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [7,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [8,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>  [9,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [10,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [11,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [12,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [13,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [14,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [15,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [16,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [17,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [18,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [19,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [20,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [21,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [22,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [23,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [24,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [25,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [26,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [27,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [28,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [29,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #> [30,] 5.9043 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 6.125316 #>        [,196]   [,197]   [,198]   [,199]   [,200] #>  [1,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [2,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [3,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [4,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [5,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [6,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [7,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [8,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  [9,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [10,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [11,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [12,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [13,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [14,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [15,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [16,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [17,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [18,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [19,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [20,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [21,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [22,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [23,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [24,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [25,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [26,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [27,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [28,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [29,] 6.15689 6.188464 6.220038 6.251612 6.283185 #> [30,] 6.15689 6.188464 6.220038 6.251612 6.283185 #>  #> $aligned_curves #> , , 1 #>  #>               [,1] #>  [1,]  0.044037928 #>  [2,] -0.003589190 #>  [3,]  0.042949160 #>  [4,] -0.004056012 #>  [5,] -0.016555706 #>  [6,]  0.040463764 #>  [7,]  0.082490080 #>  [8,]  0.067859664 #>  [9,]  0.019317344 #> [10,] -0.010674987 #> [11,] -0.349207475 #> [12,] -0.283425857 #> [13,] -0.262359012 #> [14,] -0.309079280 #> [15,] -0.325655713 #> [16,] -0.279267180 #> [17,] -0.303933532 #> [18,] -0.353684631 #> [19,] -0.259111966 #> [20,] -0.272116467 #> [21,]  0.143951289 #> [22,]  0.020859321 #> [23,]  0.086742558 #> [24,]  0.025595473 #> [25,]  0.146633932 #> [26,]  0.160713308 #> [27,]  0.092579844 #> [28,]  0.028069376 #> [29,]  0.025800806 #> [30,]  0.026730680 #>  #> , , 2 #>  #>              [,1] #>  [1,]  0.07242614 #>  [2,]  0.02820462 #>  [3,]  0.07701022 #>  [4,]  0.02704986 #>  [5,]  0.01514741 #>  [6,]  0.07668968 #>  [7,]  0.11713223 #>  [8,]  0.10109675 #>  [9,]  0.04823389 #> [10,]  0.01952885 #> [11,] -0.32817804 #> [12,] -0.26372971 #> [13,] -0.24113453 #> [14,] -0.29180895 #> [15,] -0.30522497 #> [16,] -0.25802492 #> [17,] -0.28323475 #> [18,] -0.33514118 #> [19,] -0.23666152 #> [20,] -0.25294596 #> [21,]  0.19784714 #> [22,]  0.08115150 #> [23,]  0.14311545 #> [24,]  0.08288095 #> [25,]  0.20669338 #> [26,]  0.22514442 #> [27,]  0.15632235 #> [28,]  0.09226318 #> [29,]  0.08751084 #> [30,]  0.08974213 #>  #> , , 3 #>  #>              [,1] #>  [1,]  0.10100063 #>  [2,]  0.06026461 #>  [3,]  0.11129446 #>  [4,]  0.05844114 #>  [5,]  0.04712487 #>  [6,]  0.11318125 #>  [7,]  0.15198863 #>  [8,]  0.13451425 #>  [9,]  0.07735204 #> [10,]  0.04997669 #> [11,] -0.30680827 #> [12,] -0.24386524 #> [13,] -0.21965563 #> [14,] -0.27441120 #> [15,] -0.28447700 #> [16,] -0.23649566 #> [17,] -0.26221547 #> [18,] -0.31634916 #> [19,] -0.21400140 #> [20,] -0.23356434 #> [21,]  0.25133378 #> [22,]  0.14104578 #> [23,]  0.19910681 #> [24,]  0.13983797 #> [25,]  0.26624596 #> [26,]  0.28905404 #> [27,]  0.21960806 #> [28,]  0.15606480 #> [29,]  0.14884008 #> [30,]  0.15236256 #>  #> , , 4 #>  #>              [,1] #>  [1,]  0.12975066 #>  [2,]  0.09255983 #>  [3,]  0.14577527 #>  [4,]  0.09009160 #>  [5,]  0.07935324 #>  [6,]  0.14990079 #>  [7,]  0.18702409 #>  [8,]  0.16808577 #>  [9,]  0.10665456 #> [10,]  0.08065022 #> [11,] -0.28509073 #> [12,] -0.22371275 #> [13,] -0.19792270 #> [14,] -0.25666813 #> [15,] -0.26341293 #> [16,] -0.21466810 #> [17,] -0.24088036 #> [18,] -0.29721476 #> [19,] -0.19110410 #> [20,] -0.21390637 #> [21,]  0.30437048 #> [22,]  0.20048437 #> [23,]  0.25466980 #> [24,]  0.19642153 #> [25,]  0.32523446 #> [26,]  0.35237859 #> [27,]  0.28237394 #> [28,]  0.21941034 #> [29,]  0.20973178 #> [30,]  0.21453022 #>  #> , , 5 #>  #>             [,1] #>  [1,]  0.1586507 #>  [2,]  0.1250594 #>  [3,]  0.1804261 #>  [4,]  0.1219792 #>  [5,]  0.1118091 #>  [6,]  0.1868108 #>  [7,]  0.2222036 #>  [8,]  0.2017850 #>  [9,]  0.1361253 #> [10,]  0.1115366 #> [11,] -0.2628093 #> [12,] -0.2032642 #> [13,] -0.1757381 #> [14,] -0.2386641 #> [15,] -0.2418750 #> [16,] -0.1923619 #> [17,] -0.2190509 #> [18,] -0.2776526 #> [19,] -0.1677727 #> [20,] -0.1938587 #> [21,]  0.3569166 #> [22,]  0.2594096 #> [23,]  0.3097577 #> [24,]  0.2525868 #> [25,]  0.3836019 #> [26,]  0.4150548 #> [27,]  0.3445572 #> [28,]  0.2822361 #> [29,]  0.2701293 #> [30,]  0.2761836 #>  #> , , 6 #>  #>             [,1] #>  [1,]  0.1876709 #>  [2,]  0.1577379 #>  [3,]  0.2152218 #>  [4,]  0.1540821 #>  [5,]  0.1444725 #>  [6,]  0.2238738 #>  [7,]  0.2574922 #>  [8,]  0.2355858 #>  [9,]  0.1657503 #> [10,]  0.1426302 #> [11,] -0.2401635 #> [12,] -0.1826650 #> [13,] -0.1533303 #> [14,] -0.2204369 #> [15,] -0.2200537 #> [16,] -0.1697367 #> [17,] -0.1969117 #> [18,] -0.2578779 #> [19,] -0.1442523 #> [20,] -0.1736168 #> [21,]  0.4089318 #> [22,]  0.3177513 #> [23,]  0.3643241 #> [24,]  0.3082889 #> [25,]  0.4412917 #> [26,]  0.4770197 #> [27,]  0.4060952 #> [28,]  0.3444738 #> [29,]  0.3299761 #> [30,]  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#> [16,] -0.12364978 #> [17,] -0.15167465 #> [18,] -0.21726032 #> [19,] -0.09640753 #> [20,] -0.13223091 #> [21,]  0.51120560 #> [22,]  0.43245950 #> [23,]  0.47170722 #> [24,]  0.41811829 #> [25,]  0.55441328 #> [26,]  0.59856582 #> [27,]  0.52698737 #> [28,]  0.46690300 #> [29,]  0.44779326 #> [30,]  0.45744527 #>  #> , , 9 #>  #>              [,1] #>  [1,]  0.27522958 #>  [2,]  0.25650638 #>  [3,]  0.32022063 #>  [4,]  0.25139290 #>  [5,]  0.24353908 #>  [6,]  0.33561065 #>  [7,]  0.36366335 #>  [8,]  0.33732842 #>  [9,]  0.25542635 #> [10,]  0.23693129 #> [11,] -0.17005905 #> [12,] -0.11921496 #> [13,] -0.08447911 #> [14,] -0.16413942 #> [15,] -0.15267235 #> [16,] -0.10008563 #> [17,] -0.12855779 #> [18,] -0.19659470 #> [19,] -0.07215232 #> [20,] -0.11123387 #> [21,]  0.56136350 #> [22,]  0.48872283 #> [23,]  0.52443225 #> [24,]  0.47213451 #> [25,]  0.60973384 #> [26,]  0.65802351 #> [27,]  0.58621839 #> [28,]  0.52698448 #> [29,]  0.50565202 #> [30,]  0.51642733 #>  #> , , 10 #>  #>              [,1] #>  [1,]  0.30449132 #>  [2,]  0.28956140 #>  [3,]  0.35530235 #>  [4,]  0.28405299 #>  [5,]  0.27678216 #>  [6,]  0.37291662 #>  [7,]  0.39903567 #>  [8,]  0.37124330 #>  [9,]  0.28545619 #> [10,]  0.26857214 #> [11,] -0.14601793 #> [12,] -0.09760847 #> [13,] -0.06108681 #> [14,] -0.14496248 #> [15,] -0.12966907 #> [16,] -0.07630690 #> [17,] -0.10520994 #> [18,] -0.17555186 #> [19,] -0.04767663 #> [20,] -0.08990123 #> [21,]  0.61078437 #> [22,]  0.54418401 #> [23,]  0.57645230 #> [24,]  0.52548371 #> [25,]  0.66415418 #> [26,]  0.71651877 #> [27,]  0.64455816 #> [28,]  0.58622778 #> [29,]  0.56273719 #> [30,]  0.57453628 #>  #> , , 11 #>  #>              [,1] #>  [1,]  0.33374985 #>  [2,]  0.32262889 #>  [3,]  0.39037464 #>  [4,]  0.31677080 #>  [5,]  0.31009006 #>  [6,]  0.41019240 #>  [7,]  0.43434239 #>  [8,]  0.40511001 #>  [9,]  0.31552738 #> [10,]  0.30029074 #> [11,] -0.12170016 #> [12,] -0.07588233 #> [13,] -0.03736830 #> [14,] -0.12553714 #> [15,] -0.10630237 #> [16,] -0.05231792 #> [17,] -0.08151786 #> [18,] -0.15428059 #> [19,] -0.02294861 #> [20,] -0.06838179 #> [21,]  0.65946895 #> [22,]  0.59878742 #> [23,]  0.62772235 #> [24,]  0.57814257 #> [25,]  0.71761998 #> [26,]  0.77396952 #> [27,]  0.70194650 #> [28,]  0.64457148 #> [29,]  0.61899403 #> [30,]  0.63175960 #>  #> , , 12 #>  #>               [,1] #>  [1,]  0.362982581 #>  [2,]  0.355672718 #>  [3,]  0.425412162 #>  [4,]  0.349520969 #>  [5,]  0.343439858 #>  [6,]  0.447402305 #>  [7,]  0.469541981 #>  [8,]  0.438903614 #>  [9,]  0.345616215 #> [10,]  0.332067194 #> [11,] -0.096951960 #> [12,] -0.053904899 #> [13,] -0.013491613 #> [14,] -0.105890139 #> [15,] -0.082724566 #> [16,] -0.027979502 #> [17,] -0.057566107 #> [18,] -0.132801657 #> [19,]  0.001915422 #> [20,] -0.046726456 #> [21,]  0.707327598 #> [22,]  0.652477922 #> [23,]  0.678197807 #> [24,]  0.630067856 #> [25,]  0.770077546 #> [26,]  0.830336305 #> [27,]  0.758323904 #> [28,]  0.701954805 #> [29,]  0.674368301 #> [30,]  0.688038584 #>  #> , , 13 #>  #>               [,1] #>  [1,]  0.392169189 #>  [2,]  0.388663562 #>  [3,]  0.460387321 #>  [4,]  0.382276510 #>  [5,]  0.376806938 #>  [6,]  0.484495966 #>  [7,]  0.504596172 #>  [8,]  0.472599402 #>  [9,]  0.375689299 #> [10,]  0.363856403 #> [11,] -0.071991509 #> [12,] -0.031776289 #> [13,]  0.010535582 #> [14,] -0.086105778 #> [15,] -0.058947268 #> [16,] -0.003463095 #> [17,] -0.033417816 #> [18,] -0.110992952 #> [19,]  0.026977737 #> [20,] -0.024746914 #> [21,]  0.754319457 #> [22,]  0.705201010 #> [23,]  0.727834526 #> [24,]  0.681191722 #> [25,]  0.821473873 #> [26,]  0.885562678 #> [27,]  0.813631576 #> [28,]  0.758317635 #> [29,]  0.728806311 #> [30,]  0.743315150 #>  #> , , 14 #>  #>               [,1] #>  [1,]  0.421267230 #>  [2,]  0.421572457 #>  [3,]  0.495259943 #>  [4,]  0.415009105 #>  [5,]  0.410150959 #>  [6,]  0.521432918 #>  [7,]  0.539478640 #>  [8,]  0.506171740 #>  [9,]  0.405730362 #> [10,]  0.395640962 #> [11,] -0.046817553 #> [12,] -0.009539090 #> [13,]  0.034825522 #> [14,] -0.066045846 #> [15,] -0.034863702 #> [16,]  0.021220919 #> [17,] -0.008997499 #> [18,] -0.089027373 #> [19,]  0.052218620 #> [20,] -0.002644967 #> [21,]  0.800450358 #> [22,]  0.756902804 #> [23,]  0.776588847 #> [24,]  0.731430486 #> [25,]  0.871756688 #> [26,]  0.939590844 #> [27,]  0.867811521 #> [28,]  0.813600607 #> [29,]  0.782254989 #> [30,]  0.797531935 #>  #> , , 15 #>  #>              [,1] #>  [1,]  0.45026624 #>  [2,]  0.45436613 #>  [3,]  0.52998124 #>  [4,]  0.44768862 #>  [5,]  0.44344751 #>  [6,]  0.55818380 #>  [7,]  0.57415789 #>  [8,]  0.53954560 #>  [9,]  0.43572302 #> [10,]  0.42740225 #> [11,] -0.02129434 #> [12,]  0.01294064 #> [13,]  0.05924019 #> [14,] -0.04590614 #> [15,] -0.01060606 #> [16,]  0.04614390 #> [17,]  0.01565638 #> [18,] -0.06682271 #> [19,]  0.07756558 #> [20,]  0.01959806 #> [21,]  0.84568313 #> [22,]  0.80753013 #> [23,]  0.82441674 #> [24,]  0.78079889 #> [25,]  0.92087452 #> [26,]  0.99236392 #> [27,]  0.92080659 #> [28,]  0.86774516 #> [29,]  0.83466192 #> [30,]  0.85063234 #>  #> , , 16 #>  #>               [,1] #>  [1,]  0.479144849 #>  [2,]  0.487011245 #>  [3,]  0.564547332 #>  [4,]  0.480275529 #>  [5,]  0.476674835 #>  [6,]  0.594716681 #>  [7,]  0.608602900 #>  [8,]  0.572717392 #>  [9,]  0.465648404 #> [10,]  0.459118263 #> [11,]  0.004431358 #> [12,]  0.035501005 #> [13,]  0.083771573 #> [14,] -0.025525794 #> [15,]  0.013813274 #> [16,]  0.071246820 #> [17,]  0.040467615 #> [18,] -0.044384582 #> [19,]  0.103078917 #> [20,]  0.042073896 #> [21,]  0.889981104 #> [22,]  0.857030571 #> [23,]  0.871156728 #> [24,]  0.829255607 #> [25,]  0.968721657 #> [26,]  1.043826033 #> [27,]  0.972560557 #> [28,]  0.920693602 #> [29,]  0.885975421 #> [30,]  0.902560605 #>  #> , , 17 #>  #>               [,1] #>  [1,]  0.507875172 #>  [2,]  0.519479539 #>  [3,]  0.598934536 #>  [4,]  0.512753578 #>  [5,]  0.509811424 #>  [6,]  0.630998762 #>  [7,]  0.642783160 #>  [8,]  0.605675382 #>  [9,]  0.495434559 #> [10,]  0.490733908 #> [11,]  0.030329333 #> [12,]  0.058206272 #> [13,]  0.108502234 #> [14,] -0.005025678 #> [15,]  0.038480718 #> [16,]  0.096475960 #> [17,]  0.065467738 #> [18,] -0.021821819 #> [19,]  0.128708148 #> [20,]  0.064647767 #> [21,]  0.933308119 #> [22,]  0.905352528 #> [23,]  0.916841548 #> [24,]  0.876759820 #> [25,]  1.015271251 #> [26,]  1.093922326 #> [27,]  1.023018156 #> [28,]  0.972389182 #> [29,]  0.936144549 #> [30,]  0.953261849 #>  #> , , 18 #>  #>               [,1] #>  [1,] 0.5364349236 #>  [2,] 0.5517478250 #>  [3,] 0.6331193839 #>  [4,] 0.5450993301 #>  [5,] 0.5428343856 #>  [6,] 0.6669974438 #>  [7,] 0.6766686787 #>  [8,] 0.6383970445 #>  [9,] 0.5251025968 #> [10,] 0.5222528924 #> [11,] 0.0564605774 #> [12,] 0.0810329205 #> [13,] 0.1333238507 #> [14,] 0.0156357648 #> [15,] 0.0632849004 #> [16,] 0.1218397366 #> [17,] 0.0906774706 #> [18,] 0.0009754445 #> [19,] 0.1544128764 #> [20,] 0.0873663049 #> [21,] 0.9756285724 #> [22,] 0.9524452711 #> [23,] 0.9614614933 #> [24,] 0.9232712801 #> [25,] 1.0604969149 #> [26,] 1.1425990724 #> [27,] 1.0721251698 #> [28,] 1.0227761432 #> [29,] 0.9851192006 #> [30,] 1.0026821448 #>  #> , , 19 #>  #>             [,1] #>  [1,] 0.56481589 #>  [2,] 0.58378904 #>  [3,] 0.66707593 #>  [4,] 0.57728939 #>  [5,] 0.57569324 #>  [6,] 0.70268069 #>  [7,] 0.71023001 #>  [8,] 0.67085975 #>  [9,] 0.55463757 #> [10,] 0.55365897 #> [11,] 0.08279225 #> [12,] 0.10392415 #> [13,] 0.15822896 #> [14,] 0.03645703 #> [15,] 0.08821387 #> [16,] 0.14737422 #> [17,] 0.11600529 #> [18,] 0.02393088 #> [19,] 0.18024211 #> [20,] 0.11022928 #> [21,] 1.01689592 #> [22,] 0.99825900 #> [23,] 1.00497723 #> [24,] 0.96875033 #> [25,] 1.10435421 #> [26,] 1.18980371 #> [27,] 1.11982847 #> [28,] 1.07179979 #> [29,] 1.03285014 #> [30,] 1.05076857 #>  #> , , 20 #>  #>             [,1] #>  [1,] 0.59294904 #>  [2,] 0.61553938 #>  [3,] 0.70077310 #>  [4,] 0.60929194 #>  [5,] 0.60834410 #>  [6,] 0.73801703 #>  [7,] 0.74343825 #>  [8,] 0.70304120 #>  [9,] 0.58402429 #> [10,] 0.58493335 #> [11,] 0.10925367 #> [12,] 0.12697418 #> [13,] 0.18327025 #> [14,] 0.05734821 #> [15,] 0.11333214 #> [16,] 0.17298889 #> [17,] 0.14145463 #> [18,] 0.04699090 #> [19,] 0.20613529 #> [20,] 0.13316921 #> [21,] 1.05704684 #> [22,] 1.04274488 #> [23,] 1.04734919 #> [24,] 1.01315792 #> [25,] 1.14679669 #> [26,] 1.23548490 #> [27,] 1.16607611 #> [28,] 1.11940654 #> [29,] 1.07928905 #> [30,] 1.09746927 #>  #> , , 21 #>  #>             [,1] #>  [1,] 0.62085141 #>  [2,] 0.64699802 #>  [3,] 0.73411167 #>  [4,] 0.64106891 #>  [5,] 0.64079842 #>  [6,] 0.77297562 #>  [7,] 0.77626351 #>  [8,] 0.73491226 #>  [9,] 0.61324127 #> [10,] 0.61604802 #> [11,] 0.13585016 #> [12,] 0.15007405 #> [13,] 0.20836859 #> [14,] 0.07843478 #> [15,] 0.13854974 #> [16,] 0.19867991 #> [17,] 0.16707710 #> [18,] 0.07026082 #> [19,] 0.23207396 #> [20,] 0.15624091 #> [21,] 1.09602962 #> [22,] 1.08585513 #> [23,] 1.08853860 #> [24,] 1.05644276 #> [25,] 1.18777905 #> [26,] 1.27959261 #> [27,] 1.21081732 #> [28,] 1.16554402 #> [29,] 1.12438860 #> [30,] 1.14273352 #>  #> , , 22 #>  #>             [,1] #>  [1,] 0.64851029 #>  [2,] 0.67814278 #>  [3,] 0.76712139 #>  [4,] 0.67259475 #>  [5,] 0.67303748 #>  [6,] 0.80752622 #>  [7,] 0.80866262 #>  [8,] 0.76633347 #>  [9,] 0.64217166 #> [10,] 0.64691023 #> [11,] 0.16262992 #> [12,] 0.17324101 #> [13,] 0.23351792 #> [14,] 0.09957158 #> [15,] 0.16385624 #> [16,] 0.22448109 #> [17,] 0.19277701 #> [18,] 0.09362500 #> [19,] 0.25808518 #> [20,] 0.17939089 #> [21,] 1.13385639 #> [22,] 1.12754306 #> [23,] 1.12850749 #> [24,] 1.09853950 #> [25,] 1.22725714 #> [26,] 1.32207813 #> [27,] 1.25400264 #> [28,] 1.21016107 #> [29,] 1.16810247 #> [30,] 1.18651176 #>  #> , , 23 #>  #>            [,1] #>  [1,] 0.6758888 #>  [2,] 0.7089486 #>  [3,] 0.7997974 #>  [4,] 0.7038308 #>  [5,] 0.7050416 #>  [6,] 0.8416392 #>  [7,] 0.8405535 #>  [8,] 0.7973904 #>  [9,] 0.6708881 #> [10,] 0.6775729 #> [11,] 0.1894920 #> [12,] 0.1964845 #> [13,] 0.2587410 #> [14,] 0.1208492 #> [15,] 0.1892929 #> [16,] 0.2503303 #> [17,] 0.2185523 #> [18,] 0.1170962 #> [19,] 0.2841186 #> [20,] 0.2025936 #> [21,] 1.1703653 #> [22,] 1.1677631 #> [23,] 1.1672187 #> [24,] 1.1394065 #> [25,] 1.2651881 #> [26,] 1.3628942 #> [27,] 1.2955839 #> [28,] 1.2532078 #> [29,] 1.2103854 #> [30,] 1.2287557 #>  #> , , 24 #>  #>            [,1] #>  [1,] 0.7029608 #>  [2,] 0.7393853 #>  [3,] 0.8321187 #>  [4,] 0.7347838 #>  [5,] 0.7367899 #>  [6,] 0.8752365 #>  [7,] 0.8719712 #>  [8,] 0.8280637 #>  [9,] 0.6993775 #> [10,] 0.7080216 #> [11,] 0.2164331 #> [12,] 0.2197588 #> [13,] 0.2839874 #> [14,] 0.1422049 #> [15,] 0.2147917 #> [16,] 0.2762147 #> [17,] 0.2444384 #> [18,] 0.1407022 #> [19,] 0.3101693 #> [20,] 0.2258971 #> [21,] 1.2056537 #> [22,] 1.2064709 #> [23,] 1.2046361 #> [24,] 1.1790476 #> [25,] 1.3015302 #> [26,] 1.4019949 #> [27,] 1.3355144 #> [28,] 1.2946359 #> [29,] 1.2511934 #> [30,] 1.2694182 #>  #> , , 25 #>  #>            [,1] #>  [1,] 0.7297313 #>  [2,] 0.7694145 #>  [3,] 0.8640647 #>  [4,] 0.7654331 #>  [5,] 0.7682030 #>  [6,] 0.9083263 #>  [7,] 0.9028905 #>  [8,] 0.8583332 #>  [9,] 0.7276259 #> [10,] 0.7382387 #> [11,] 0.2434910 #> [12,] 0.2430895 #> [13,] 0.3092530 #> [14,] 0.1636373 #> [15,] 0.2403446 #> [16,] 0.3021347 #> [17,] 0.2703687 #> [18,] 0.1643699 #> [19,] 0.3362305 #> [20,] 0.2492332 #> [21,] 1.2396911 #> [22,] 1.2436234 #> [23,] 1.2407242 #> [24,] 1.2173486 #> [25,] 1.3362432 #> [26,] 1.4393360 #> [27,] 1.3737489 #> [28,] 1.3343981 #> [29,] 1.2904833 #> [30,] 1.3084538 #>  #> , , 26 #>  #>            [,1] #>  [1,] 0.7561126 #>  [2,] 0.7990087 #>  [3,] 0.8956087 #>  [4,] 0.7957583 #>  [5,] 0.7992446 #>  [6,] 0.9408817 #>  [7,] 0.9332864 #>  [8,] 0.8881795 #>  [9,] 0.7556081 #> [10,] 0.7681920 #> [11,] 0.2705985 #> [12,] 0.2664386 #> [13,] 0.3345311 #> [14,] 0.1851626 #> [15,] 0.2659686 #> [16,] 0.3280659 #> [17,] 0.2963364 #> [18,] 0.1881373 #> [19,] 0.3622814 #> [20,] 0.2726023 #> [21,] 1.2724479 #> [22,] 1.2791787 #> [23,] 1.2754486 #> [24,] 1.2542926 #> [25,] 1.3692881 #> [26,] 1.4748747 #> [27,] 1.4102435 #> [28,] 1.3724490 #> [29,] 1.3282136 #> [30,] 1.3458180 #>  #> , , 27 #>  #>            [,1] #>  [1,] 0.7821432 #>  [2,] 0.8281642 #>  [3,] 0.9266607 #>  [4,] 0.8257272 #>  [5,] 0.8299527 #>  [6,] 0.9728508 #>  [7,] 0.9631349 #>  [8,] 0.9175823 #>  [9,] 0.7831727 #> [10,] 0.7977496 #> [11,] 0.2977433 #> [12,] 0.2898040 #> [13,] 0.3597988 #> [14,] 0.2067193 #> [15,] 0.2916179 #> [16,] 0.3539919 #> [17,] 0.3223494 #> [18,] 0.2119727 #> [19,] 0.3883223 #> [20,] 0.2960142 #> [21,] 1.3038952 #> [22,] 1.3130964 #> [23,] 1.3087761 #> [24,] 1.2899000 #> [25,] 1.4006275 #> [26,] 1.5085699 #> [27,] 1.4449560 #> [28,] 1.4087444 #> [29,] 1.3643438 #> [30,] 1.3813734 #>  #> , , 28 #>  #>            [,1] #>  [1,] 0.8078177 #>  [2,] 0.8568588 #>  [3,] 0.9571768 #>  [4,] 0.8552938 #>  [5,] 0.8603137 #>  [6,] 1.0042239 #>  [7,] 0.9924125 #>  [8,] 0.9464658 #>  [9,] 0.8104338 #> [10,] 0.8270128 #> [11,] 0.3249280 #> [12,] 0.3131769 #> [13,] 0.3850551 #> [14,] 0.2283669 #> [15,] 0.3172876 #> [16,] 0.3799078 #> [17,] 0.3483719 #> [18,] 0.2358445 #> [19,] 0.4143061 #> [20,] 0.3194334 #> [21,] 1.3340052 #> [22,] 1.3453375 #> [23,] 1.3406741 #> [24,] 1.3241385 #> [25,] 1.4302253 #> [26,] 1.5403822 #> [27,] 1.4778458 #> [28,] 1.4432419 #> [29,] 1.3988347 #> [30,] 1.4151476 #>  #> , , 29 #>  #>            [,1] #>  [1,] 0.8331020 #>  [2,] 0.8850080 #>  [3,] 0.9872214 #>  [4,] 0.8844189 #>  [5,] 0.8903102 #>  [6,] 1.0349868 #>  [7,] 1.0210964 #>  [8,] 0.9747430 #>  [9,] 0.8373816 #> [10,] 0.8559693 #> [11,] 0.3521243 #> [12,] 0.3365446 #> [13,] 0.4102637 #> [14,] 0.2500376 #> [15,] 0.3429698 #> [16,] 0.4057719 #> [17,] 0.3743957 #> [18,] 0.2597806 #> [19,] 0.4402533 #> [20,] 0.3428600 #> [21,] 1.3627507 #> [22,] 1.3758643 #> [23,] 1.3711096 #> [24,] 1.3569768 #> [25,] 1.4580470 #> [26,] 1.5702739 #> [27,] 1.5088480 #> [28,] 1.4759008 #> [29,] 1.4316486 #> [30,] 1.4471214 #>  #> , , 30 #>  #>            [,1] #>  [1,] 0.8579686 #>  [2,] 0.9126372 #>  [3,] 1.0167776 #>  [4,] 0.9130919 #>  [5,] 0.9199245 #>  [6,] 1.0651151 #>  [7,] 1.0491646 #>  [8,] 1.0025030 #>  [9,] 0.8640040 #> [10,] 0.8846043 #> [11,] 0.3793171 #> [12,] 0.3598962 #> [13,] 0.4354289 #> [14,] 0.2717590 #> [15,] 0.3686412 #> [16,] 0.4315940 #> [17,] 0.4004053 #> [18,] 0.2837390 #> [19,] 0.4661568 #> [20,] 0.3662741 #> [21,] 1.3900851 #> [22,] 1.4046407 #> [23,] 1.3999307 #> [24,] 1.3883844 #> [25,] 1.4840596 #> [26,] 1.5982089 #> [27,] 1.5379236 #> [28,] 1.5066819 #> [29,] 1.4627492 #> [30,] 1.4772572 #>  #> , , 31 #>  #>            [,1] #>  [1,] 0.8824134 #>  [2,] 0.9397353 #>  [3,] 1.0458275 #>  [4,] 0.9413308 #>  [5,] 0.9490475 #>  [6,] 1.0945851 #>  [7,] 1.0765955 #>  [8,] 1.0297341 #>  [9,] 0.8902710 #> [10,] 0.9128828 #> [11,] 0.4064985 #> [12,] 0.3832180 #> [13,] 0.4605529 #> [14,] 0.2935033 #> [15,] 0.3943006 #> [16,] 0.4573665 #> [17,] 0.4263831 #> [18,] 0.3077142 #> [19,] 0.4919472 #> [20,] 0.3896752 #> [21,] 1.4159352 #> [22,] 1.4316322 #> [23,] 1.4271196 #> [24,] 1.4183318 #> [25,] 1.5082317 #> [26,] 1.6241533 #> [27,] 1.5650592 #> [28,] 1.5355479 #> [29,] 1.4921008 #> [30,] 1.5055187 #>  #> , , 32 #>  #>            [,1] #>  [1,] 0.9063475 #>  [2,] 0.9662825 #>  [3,] 1.0743513 #>  [4,] 0.9691181 #>  [5,] 0.9776602 #>  [6,] 1.1233742 #>  [7,] 1.1033686 #>  [8,] 1.0564197 #>  [9,] 0.9160072 #> [10,] 0.9406332 #> [11,] 0.4336311 #> [12,] 0.4065223 #> [13,] 0.4855710 #> [14,] 0.3152639 #> [15,] 0.4199145 #> [16,] 0.4830352 #> [17,] 0.4523267 #> [18,] 0.3317017 #> [19,] 0.5176738 #> [20,] 0.4130429 #> [21,] 1.4402932 #> [22,] 1.4568059 #> [23,] 1.4527498 #> [24,] 1.4467906 #> [25,] 1.5305337 #> [26,] 1.6480748 #> [27,] 1.5902250 #> [28,] 1.5624632 #> [29,] 1.5196630 #> [30,] 1.5318717 #>  #> , , 33 #>  #>            [,1] #>  [1,] 0.9298255 #>  [2,] 0.9922596 #>  [3,] 1.1023230 #>  [4,] 0.9964368 #>  [5,] 1.0058168 #>  [6,] 1.1514603 #>  [7,] 1.1294157 #>  [8,] 1.0825436 #>  [9,] 0.9413578 #> [10,] 0.9680036 #> [11,] 0.4607221 #> [12,] 0.4297435 #> [13,] 0.5105130 #> [14,] 0.3370373 #> [15,] 0.4454822 #> [16,] 0.5086080 #> [17,] 0.4782097 #> [18,] 0.3556816 #> [19,] 0.5433150 #> [20,] 0.4363637 #> [21,] 1.4630814 #> [22,] 1.4801304 #> [23,] 1.4767975 #> [24,] 1.4737335 #> [25,] 1.5508836 #> [26,] 1.6699430 #> [27,] 1.6133894 #> [28,] 1.5873941 #> [29,] 1.5453812 #> [30,] 1.5562837 #>  #> , , 34 #>  #>            [,1] #>  [1,] 0.9528504 #>  [2,] 1.0176211 #>  [3,] 1.1295385 #>  [4,] 1.0232575 #>  [5,] 1.0335112 #>  [6,] 1.1788219 #>  [7,] 1.1547268 #>  [8,] 1.1080895 #>  [9,] 0.9663171 #> [10,] 0.9949842 #> [11,] 0.4877663 #> [12,] 0.4529267 #> [13,] 0.5353852 #> [14,] 0.3588114 #> [15,] 0.4710069 #> [16,] 0.5340917 #> [17,] 0.5040091 #> [18,] 0.3796503 #> [19,] 0.5687992 #> [20,] 0.4596509 #> [21,] 1.4843014 #> [22,] 1.5015551 #> [23,] 1.4992377 #> [24,] 1.4991209 #> [25,] 1.5692482 #> [26,] 1.6897297 #> [27,] 1.6345227 #> [28,] 1.6103089 #> [29,] 1.5692545 #> [30,] 1.5787238 #>  #> , , 35 #>  #>            [,1] #>  [1,] 0.9753961 #>  [2,] 1.0423333 #>  [3,] 1.1561550 #>  [4,] 1.0495318 #>  [5,] 1.0607284 #>  [6,] 1.2053677 #>  [7,] 1.1793171 #>  [8,] 1.1329078 #>  [9,] 0.9908763 #> [10,] 1.0215631 #> [11,] 0.5146923 #> [12,] 0.4760473 #> [13,] 0.5600950 #> [14,] 0.3805754 #> [15,] 0.4964292 #> [16,] 0.5594548 #> [17,] 0.5297399 #> [18,] 0.4035827 #> [19,] 0.5941922 #> [20,] 0.4828465 #> [21,] 1.5040054 #> [22,] 1.5210200 #> [23,] 1.5200466 #> [24,] 1.5228801 #> [25,] 1.5856445 #> [26,] 1.7074086 #> [27,] 1.6535971 #> [28,] 1.6311776 #> [29,] 1.5912033 #> [30,] 1.5991631 #>  #> , , 36 #>  #>            [,1] #>  [1,] 0.9974331 #>  [2,] 1.0664170 #>  [3,] 1.1821699 #>  [4,] 1.0751878 #>  [5,] 1.0874538 #>  [6,] 1.2311301 #>  [7,] 1.2031647 #>  [8,] 1.1570272 #>  [9,] 1.0149993 #> [10,] 1.0477031 #> [11,] 0.5415329 #> [12,] 0.4990682 #> [13,] 0.5846971 #> [14,] 0.4023240 #> [15,] 0.5217708 #> [16,] 0.5846395 #> [17,] 0.5553783 #> [18,] 0.4274872 #> [19,] 0.6194502 #> [20,] 0.5059788 #> [21,] 1.5221739 #> [22,] 1.5385501 #> [23,] 1.5392016 #> [24,] 1.5449927 #> [25,] 1.6000662 #> [26,] 1.7229553 #> [27,] 1.6705869 #> [28,] 1.6499726 #> [29,] 1.6112401 #> [30,] 1.6175746 #>  #> , , 37 #>  #>            [,1] #>  [1,] 1.0189376 #>  [2,] 1.0898562 #>  [3,] 1.2075686 #>  [4,] 1.1002657 #>  [5,] 1.1135508 #>  [6,] 1.2561043 #>  [7,] 1.2262236 #>  [8,] 1.1805035 #>  [9,] 1.0384955 #> [10,] 1.0732003 #> [11,] 0.5682864 #> [12,] 0.5220362 #> [13,] 0.6092018 #> [14,] 0.4240484 #> [15,] 0.5470399 #> [16,] 0.6097021 #> [17,] 0.5808693 #> [18,] 0.4513309 #> [19,] 0.6445186 #> [20,] 0.5290543 #> [21,] 1.5387884 #> [22,] 1.5541215 #> [23,] 1.5566818 #> [24,] 1.5653383 #> [25,] 1.6124930 #> [26,] 1.7363478 #> [27,] 1.6854685 #> [28,] 1.6666678 #> [29,] 1.6293497 #> [30,] 1.6339334 #>  #> , , 38 #>  #>            [,1] #>  [1,] 1.0398313 #>  [2,] 1.1125555 #>  [3,] 1.2323368 #>  [4,] 1.1247843 #>  [5,] 1.1390249 #>  [6,] 1.2802719 #>  [7,] 1.2484904 #>  [8,] 1.2033334 #>  [9,] 1.0615327 #> [10,] 1.0982398 #> [11,] 0.5948915 #> [12,] 0.5448591 #> [13,] 0.6334897 #> [14,] 0.4457314 #> [15,] 0.5721509 #> [16,] 0.6346381 #> [17,] 0.6062603 #> [18,] 0.4751102 #> [19,] 0.6694692 #> [20,] 0.5519744 #> [21,] 1.5538315 #> [22,] 1.5677118 #> [23,] 1.5724672 #> [24,] 1.5840208 #> [25,] 1.6229063 #> [26,] 1.7475659 #> [27,] 1.6982203 #> [28,] 1.6812250 #> [29,] 1.6455091 #> [30,] 1.6482163 #>  #> , , 39 #>  #>            [,1] #>  [1,] 1.0601790 #>  [2,] 1.1345566 #>  [3,] 1.2564548 #>  [4,] 1.1487296 #>  [5,] 1.1639359 #>  [6,] 1.3035968 #>  [7,] 1.2699677 #>  [8,] 1.2255040 #>  [9,] 1.0841101 #> [10,] 1.1228159 #> [11,] 0.6213402 #> [12,] 0.5675973 #> [13,] 0.6576392 #> [14,] 0.4673932 #> [15,] 0.5971481 #> [16,] 0.6593074 #> [17,] 0.6315400 #> [18,] 0.4988449 #> [19,] 0.6942276 #> [20,] 0.5748239 #> [21,] 1.5672869 #> [22,] 1.5793007 #> [23,] 1.5865394 #> [24,] 1.6010399 #> [25,] 1.6312894 #> [26,] 1.7565918 #> [27,] 1.7088229 #> [28,] 1.6935796 #> [29,] 1.6596966 #> [30,] 1.6604024 #>  #> , , 40 #>  #>            [,1] #>  [1,] 1.0799933 #>  [2,] 1.1558618 #>  [3,] 1.2797836 #>  [4,] 1.1720878 #>  [5,] 1.1882874 #>  [6,] 1.3260488 #>  [7,] 1.2906406 #>  [8,] 1.2470028 #>  [9,] 1.1062221 #> [10,] 1.1469189 #> [11,] 0.6476633 #> [12,] 0.5902450 #> [13,] 0.6816650 #> [14,] 0.4889741 #> [15,] 0.6220445 #> [16,] 0.6838164 #> [17,] 0.6565960 #> [18,] 0.5224515 #> [19,] 0.7187740 #> [20,] 0.5975746 #> [21,] 1.5791395 #> [22,] 1.5888700 #> [23,] 1.5988812 #> [24,] 1.6163773 #> [25,] 1.6376277 #> [26,] 1.7634100 #> [27,] 1.7172589 #> [28,] 1.7037687 #> [29,] 1.6718927 #> [30,] 1.6704727 #>  #> , , 41 #>  #>            [,1] #>  [1,] 1.0992599 #>  [2,] 1.1764569 #>  [3,] 1.3023122 #>  [4,] 1.1948348 #>  [5,] 1.2120670 #>  [6,] 1.3476242 #>  [7,] 1.3104947 #>  [8,] 1.2677874 #>  [9,] 1.1278265 #> [10,] 1.1705051 #> [11,] 0.6738335 #> [12,] 0.6127003 #> [13,] 0.7054220 #> [14,] 0.5105246 #> [15,] 0.6467288 #> [16,] 0.7081616 #> [17,] 0.6815261 #> [18,] 0.5459802 #> [19,] 0.7431781 #> [20,] 0.6201394 #> [21,] 1.5893499 #> [22,] 1.5964030 #> [23,] 1.6094771 #> [24,] 1.6300155 #> [25,] 1.6419084 #> [26,] 1.7680069 #> [27,] 1.7235133 #> [28,] 1.7117752 #> [29,] 1.6820795 #> [30,] 1.6784103 #>  #> , , 42 #>  #>            [,1] #>  [1,] 1.1179462 #>  [2,] 1.1963285 #>  [3,] 1.3241432 #>  [4,] 1.2169241 #>  [5,] 1.2352579 #>  [6,] 1.3683259 #>  [7,] 1.3295166 #>  [8,] 1.2877098 #>  [9,] 1.1487251 #> [10,] 1.1933660 #> [11,] 0.6997504 #> [12,] 0.6350713 #> [13,] 0.7290111 #> [14,] 0.5319774 #> [15,] 0.6712674 #> [16,] 0.7322426 #> [17,] 0.7063284 #> [18,] 0.5694357 #> [19,] 0.7673251 #> [20,] 0.6426107 #> [21,] 1.5978263 #> [22,] 1.6018855 #> [23,] 1.6183129 #> [24,] 1.6419387 #> [25,] 1.6441210 #> [26,] 1.7703716 #> [27,] 1.7275732 #> [28,] 1.7175845 #> [29,] 1.6902412 #> [30,] 1.6842005 #>  #> , , 43 #>  #>            [,1] #>  [1,] 1.1360016 #>  [2,] 1.2154390 #>  [3,] 1.3452692 #>  [4,] 1.2382371 #>  [5,] 1.2576980 #>  [6,] 1.3881394 #>  [7,] 1.3476824 #>  [8,] 1.3068637 #>  [9,] 1.1691004 #> [10,] 1.2156956 #> [11,] 0.7255140 #> [12,] 0.6572624 #> [13,] 0.7524513 #> [14,] 0.5533659 #> [15,] 0.6956783 #> [16,] 0.7560720 #> [17,] 0.7308359 #> [18,] 0.5927133 #> [19,] 0.7912475 #> [20,] 0.6649261 #> [21,] 1.6046128 #> [22,] 1.6053051 #> [23,] 1.6253742 #> [24,] 1.6521324 #> [25,] 1.6442568 #> [26,] 1.7704951 #> [27,] 1.7294281 #> [28,] 1.7211840 #> [29,] 1.6963638 #> [30,] 1.6878307 #>  #> , , 44 #>  #>            [,1] #>  [1,] 1.1533667 #>  [2,] 1.2337568 #>  [3,] 1.3656790 #>  [4,] 1.2588806 #>  [5,] 1.2794484 #>  [6,] 1.4070511 #>  [7,] 1.3648980 #>  [8,] 1.3252778 #>  [9,] 1.1889566 #> [10,] 1.2374954 #> [11,] 0.7511207 #> [12,] 0.6793034 #> [13,] 0.7755733 #> [14,] 0.5746820 #> [15,] 0.7198250 #> [16,] 0.7797028 #> [17,] 0.7551874 #> [18,] 0.6159031 #> [19,] 0.8150059 #> [20,] 0.6870557 #> [21,] 1.6095702 #> [22,] 1.6066515 #> [23,] 1.6305710 #> [24,] 1.6605831 #> [25,] 1.6423093 #> [26,] 1.7683710 #> [27,] 1.7290698 #> [28,] 1.7225636 #> [29,] 1.7004353 #> [30,] 1.6892076 #>  #> , , 45 #>  #>            [,1] #>  [1,] 1.1701120 #>  [2,] 1.2512945 #>  [3,] 1.3853615 #>  [4,] 1.2788660 #>  [5,] 1.3005418 #>  [6,] 1.4250479 #>  [7,] 1.3812411 #>  [8,] 1.3429563 #>  [9,] 1.2082919 #> [10,] 1.2587611 #> [11,] 0.7763861 #> [12,] 0.7012402 #> [13,] 0.7984988 #> [14,] 0.5958807 #> [15,] 0.7437956 #> [16,] 0.8031049 #> [17,] 0.7793819 #> [18,] 0.6389563 #> [19,] 0.8384350 #> [20,] 0.7090694 #> [21,] 1.6128637 #> [22,] 1.6059166 #> [23,] 1.6337824 #> [24,] 1.6672790 #> [25,] 1.6382740 #> [26,] 1.7639952 #> [27,] 1.7264922 #> [28,] 1.7217156 #> [29,] 1.7024455 #> [30,] 1.6883456 #>  #> , , 46 #>  #>            [,1] #>  [1,] 1.1862597 #>  [2,] 1.2680575 #>  [3,] 1.4042940 #>  [4,] 1.2981821 #>  [5,] 1.3209900 #>  [6,] 1.4420366 #>  [7,] 1.3967006 #>  [8,] 1.3598895 #>  [9,] 1.2270578 #> [10,] 1.2794420 #> [11,] 0.8014547 #> [12,] 0.7228855 #> [13,] 0.8212519 #> [14,] 0.6170364 #> [15,] 0.7676132 #> [16,] 0.8261310 #> [17,] 0.8032496 #> [18,] 0.6618299 #> [19,] 0.8616354 #> [20,] 0.7308500 #> [21,] 1.6144862 #> [22,] 1.6030942 #> [23,] 1.6351869 #> [24,] 1.6722095 #> [25,] 1.6321486 #> [26,] 1.7573638 #> [27,] 1.7216918 #> [28,] 1.7186344 #> [29,] 1.7023864 #> [30,] 1.6852992 #>  #> , , 47 #>  #>            [,1] #>  [1,] 1.2018017 #>  [2,] 1.2839475 #>  [3,] 1.4221971 #>  [4,] 1.3168187 #>  [5,] 1.3407893 #>  [6,] 1.4580608 #>  [7,] 1.4112662 #>  [8,] 1.3760686 #>  [9,] 1.2450547 #> [10,] 1.2993335 #> [11,] 0.8263283 #> [12,] 0.7444220 #> [13,] 0.8436399 #> [14,] 0.6379999 #> [15,] 0.7911164 #> [16,] 0.8489397 #> [17,] 0.8269078 #> [18,] 0.6845974 #> [19,] 0.8846541 #> [20,] 0.7524601 #> [21,] 1.6144320 #> [22,] 1.5981806 #> [23,] 1.6347814 #> [24,] 1.6753586 #> [25,] 1.6239330 #> [26,] 1.7484440 #> [27,] 1.7146674 #> [28,] 1.7133171 #> [29,] 1.7002521 #> [30,] 1.6800652 #>  #> , , 48 #>  #>            [,1] #>  [1,] 1.2167088 #>  [2,] 1.2990135 #>  [3,] 1.4393339 #>  [4,] 1.3347573 #>  [5,] 1.3598993 #>  [6,] 1.4731323 #>  [7,] 1.4249279 #>  [8,] 1.3913900 #>  [9,] 1.2624731 #> [10,] 1.3186287 #> [11,] 0.8508812 #> [12,] 0.7657614 #> [13,] 0.8658043 #> [14,] 0.6589040 #> [15,] 0.8144147 #> [16,] 0.8715230 #> [17,] 0.8503770 #> [18,] 0.7071431 #> [19,] 0.9072645 #> [20,] 0.7739358 #> [21,] 1.6126966 #> [22,] 1.5911740 #> [23,] 1.6325613 #> [24,] 1.6766092 #> [25,] 1.6136292 #> [26,] 1.7372462 #> [27,] 1.7054202 #> [28,] 1.7057630 #> [29,] 1.6960385 #> [30,] 1.6726431 #>  #> , , 49 #>  #>            [,1] #>  [1,] 1.2309277 #>  [2,] 1.3132713 #>  [3,] 1.4556970 #>  [4,] 1.3519580 #>  [5,] 1.3781944 #>  [6,] 1.4872407 #>  [7,] 1.4376762 #>  [8,] 1.4058064 #>  [9,] 1.2793223 #> [10,] 1.3373367 #> [11,] 0.8751376 #> [12,] 0.7868629 #> [13,] 0.8877738 #> [14,] 0.6796541 #> [15,] 0.8375361 #> [16,] 0.8936698 #> [17,] 0.8735154 #> [18,] 0.7295249 #> [19,] 0.9296497 #> [20,] 0.7950894 #> [21,] 1.6092768 #> [22,] 1.5820749 #> [23,] 1.6285240 #> [24,] 1.6758677 #> [25,] 1.6012414 #> [26,] 1.7238051 #> [27,] 1.6939539 #> [28,] 1.6959741 #> [29,] 1.6897438 #> [30,] 1.6630343 #>  #> , , 50 #>  #>            [,1] #>  [1,] 1.2443779 #>  [2,] 1.3267120 #>  [3,] 1.4712782 #>  [4,] 1.3682448 #>  [5,] 1.3957412 #>  [6,] 1.5003764 #>  [7,] 1.4495024 #>  [8,] 1.4193909 #>  [9,] 1.2956046 #> [10,] 1.3554594 #> [11,] 0.8991633 #> [12,] 0.8078374 #> [13,] 0.9093343 #> [14,] 0.7002797 #> [15,] 0.8602953 #> [16,] 0.9155365 #> [17,] 0.8963761 #> [18,] 0.7517922 #> [19,] 0.9518401 #> [20,] 0.8160979 #> [21,] 1.6041707 #> [22,] 1.5708862 #> [23,] 1.6226682 #> [24,] 1.6733311 #> [25,] 1.5867432 #> [26,] 1.7081290 #> [27,] 1.6802746 #> [28,] 1.6839545 #> [29,] 1.6813681 #> [30,] 1.6512430 #>  #> , , 51 #>  #>            [,1] #>  [1,] 1.2571493 #>  [2,] 1.3393271 #>  [3,] 1.4860693 #>  [4,] 1.3838015 #>  [5,] 1.4125547 #>  [6,] 1.5125302 #>  [7,] 1.4603855 #>  [8,] 1.4321675 #>  [9,] 1.3112645 #> [10,] 1.3729390 #> [11,] 0.9229073 #> [12,] 0.8284763 #> [13,] 0.9306456 #> [14,] 0.7208025 #> [15,] 0.8828225 #> [16,] 0.9371431 #> [17,] 0.9190171 #> [18,] 0.7737301 #> [19,] 0.9735365 #> [20,] 0.8369135 #> [21,] 1.5973762 #> [22,] 1.5576127 #> [23,] 1.6149944 #> [24,] 1.6689977 #> [25,] 1.5701086 #> [26,] 1.6902287 #> [27,] 1.6643908 #> [28,] 1.6697113 #> [29,] 1.6709139 #> [30,] 1.6372756 #>  #> , , 52 #>  #>            [,1] #>  [1,] 1.2692737 #>  [2,] 1.3510911 #>  [3,] 1.5000588 #>  [4,] 1.3986246 #>  [5,] 1.4286508 #>  [6,] 1.5236675 #>  [7,] 1.4702897 #>  [8,] 1.4441451 #>  [9,] 1.3261071 #> [10,] 1.3895818 #> [11,] 0.9462296 #> [12,] 0.8489606 #> [13,] 0.9517408 #> [14,] 0.7411188 #> [15,] 0.9051502 #> [16,] 0.9583807 #> [17,] 0.9413344 #> [18,] 0.7955252 #> [19,] 0.9950181 #> [20,] 0.8573998 #> [21,] 1.5888684 #> [22,] 1.5422618 #> [23,] 1.6055045 #> [24,] 1.6628665 #> [25,] 1.5513810 #> [26,] 1.6701174 #> [27,] 1.6463136 #> [28,] 1.6532536 #> [29,] 1.6583855 #> [30,] 1.6211409 #>  #> , , 53 #>  #>            [,1] #>  [1,] 1.2807451 #>  [2,] 1.3619736 #>  [3,] 1.5130678 #>  [4,] 1.4127061 #>  [5,] 1.4440375 #>  [6,] 1.5337641 #>  [7,] 1.4792307 #>  [8,] 1.4553173 #>  [9,] 1.3403247 #> [10,] 1.4055718 #> [11,] 0.9693028 #> [12,] 0.8692436 #> [13,] 0.9723859 #> [14,] 0.7613636 #> [15,] 0.9270703 #> [16,] 0.9792074 #> [17,] 0.9632953 #> [18,] 0.8171530 #> [19,] 1.0162713 #> [20,] 0.8777268 #> [21,] 1.5785463 #> [22,] 1.5248432 #> [23,] 1.5942024 #> [24,] 1.6549381 #> [25,] 1.5306109 #> [26,] 1.6478111 #> [27,] 1.6260564 #> [28,] 1.6345933 #> [29,] 1.6437897 #> [30,] 1.6028500 #>  #> , , 54 #>  #>            [,1] #>  [1,] 1.2915422 #>  [2,] 1.3719697 #>  [3,] 1.5251311 #>  [4,] 1.4260381 #>  [5,] 1.4586465 #>  [6,] 1.5428390 #>  [7,] 1.4871459 #>  [8,] 1.4656781 #>  [9,] 1.3539312 #> [10,] 1.4209256 #> [11,] 0.9921279 #> [12,] 0.8891812 #> [13,] 0.9927570 #> [14,] 0.7813412 #> [15,] 0.9487331 #> [16,] 0.9997486 #> [17,] 0.9850125 #> [18,] 0.8384505 #> [19,] 1.0369905 #> [20,] 0.8977988 #> [21,] 1.5664202 #> [22,] 1.5053686 #> [23,] 1.5810934 #> [24,] 1.6452144 #> [25,] 1.5078144 #> [26,] 1.6233281 #> [27,] 1.6036354 #> [28,] 1.6137449 #> [29,] 1.6271353 #> [30,] 1.5824167 #>  #> , , 55 #>  #>            [,1] #>  [1,] 1.3016258 #>  [2,] 1.3811093 #>  [3,] 1.5363615 #>  [4,] 1.4386080 #>  [5,] 1.4724007 #>  [6,] 1.5508992 #>  [7,] 1.4940570 #>  [8,] 1.4750553 #>  [9,] 1.3669333 #> [10,] 1.4356520 #> [11,] 1.0144159 #> [12,] 0.9089651 #> [13,] 1.0128921 #> [14,] 0.8012150 #> [15,] 0.9701753 #> [16,] 1.0199979 #> [17,] 1.0064221 #> [18,] 0.8595914 #> [19,] 1.0574815 #> [20,] 0.9175493 #> [21,] 1.5525487 #> [22,] 1.4838522 #> [23,] 1.5661845 #> [24,] 1.6336991 #> [25,] 1.4830094 #> [26,] 1.5966894 #> [27,] 1.5790691 #> [28,] 1.5907251 #> [29,] 1.6084331 #> [30,] 1.5598570 #>  #> , , 56 #>  #>            [,1] #>  [1,] 1.3108661 #>  [2,] 1.3892963 #>  [3,] 1.5467617 #>  [4,] 1.4503690 #>  [5,] 1.4853666 #>  [6,] 1.5579379 #>  [7,] 1.4999994 #>  [8,] 1.4835242 #>  [9,] 1.3792686 #> [10,] 1.4496857 #> [11,] 1.0364211 #> [12,] 0.9284170 #> [13,] 1.0325409 #> [14,] 0.8209014 #> [15,] 0.9911670 #> [16,] 1.0396768 #> [17,] 1.0273865 #> [18,] 0.8804730 #> [19,] 1.0776965 #> [20,] 0.9371159 #> [21,] 1.5370121 #> [22,] 1.4603107 #> [23,] 1.5494844 #> [24,] 1.6203972 #> [25,] 1.4562166 #> [26,] 1.5679183 #> [27,] 1.5523785 #> [28,] 1.5655536 #> [29,] 1.5876964 #> [30,] 1.5351895 #>  #> , , 57 #>  #>            [,1] #>  [1,] 1.3193817 #>  [2,] 1.3965795 #>  [3,] 1.5563259 #>  [4,] 1.4611326 #>  [5,] 1.4975394 #>  [6,] 1.5638662 #>  [7,] 1.5049674 #>  [8,] 1.4911194 #>  [9,] 1.3907509 #> [10,] 1.4628498 #> [11,] 1.0581425 #> [12,] 0.9476348 #> [13,] 1.0518896 #> [14,] 0.8403938 #> [15,] 1.0118773 #> [16,] 1.0590618 #> [17,] 1.0480915 #> [18,] 0.9010660 #> [19,] 1.0973772 #> [20,] 0.9563526 #> [21,] 1.5198191 #> [22,] 1.4347629 #> [23,] 1.5310035 #> [24,] 1.6053154 #> [25,] 1.4274587 #> [26,] 1.5370408 #> [27,] 1.5235874 #> [28,] 1.5382523 #> [29,] 1.5649406 #> [30,] 1.5084351 #>  #> , , 58 #>  #>            [,1] #>  [1,] 1.3272135 #>  [2,] 1.4029869 #>  [3,] 1.5650487 #>  [4,] 1.4711116 #>  [5,] 1.5089349 #>  [6,] 1.5687279 #>  [7,] 1.5089554 #>  [8,] 1.4978639 #>  [9,] 1.4015694 #> [10,] 1.4753124 #> [11,] 1.0793949 #> [12,] 0.9666539 #> [13,] 1.0709831 #> [14,] 0.8597704 #> [15,] 1.0323472 #> [16,] 1.0781377 #> [17,] 1.0685126 #> [18,] 0.9214860 #> [19,] 1.1168044 #> [20,] 0.9753068 #> [21,] 1.5009797 #> [22,] 1.4072299 #> [23,] 1.5107334 #> [24,] 1.5884620 #> [25,] 1.3967608 #> [26,] 1.5040854 #> [27,] 1.4927217 #> [28,] 1.5088459 #> [29,] 1.5401833 #> [30,] 1.4796174 #>  #> , , 59 #>  #>            [,1] #>  [1,] 1.3343573 #>  [2,] 1.4085136 #>  [3,] 1.5728810 #>  [4,] 1.4803009 #>  [5,] 1.5195748 #>  [6,] 1.5725491 #>  [7,] 1.5119583 #>  [8,] 1.5037681 #>  [9,] 1.4117425 #> [10,] 1.4870972 #> [11,] 1.1002426 #> [12,] 0.9852365 #> [13,] 1.0895626 #> [14,] 0.8788300 #> [15,] 1.0523282 #> [16,] 1.0966830 #> [17,] 1.0883894 #> [18,] 0.9415338 #> [19,] 1.1358978 #> [20,] 0.9940549 #> [21,] 1.4805054 #> [22,] 1.3777355 #> [23,] 1.4884701 #> [24,] 1.5698467 #> [25,] 1.3641501 #> [26,] 1.4690832 #> [27,] 1.4598102 #> [28,] 1.4773616 #> [29,] 1.5134442 #> [30,] 1.4487623 #>  #> , , 60 #>  #>            [,1] #>  [1,] 1.3408006 #>  [2,] 1.4131548 #>  [3,] 1.5795913 #>  [4,] 1.4886946 #>  [5,] 1.5293594 #>  [6,] 1.5753247 #>  [7,] 1.5139710 #>  [8,] 1.5088279 #>  [9,] 1.4212810 #> [10,] 1.4982204 #> [11,] 1.1207739 #> [12,] 1.0036503 #> [13,] 1.1078149 #> [14,] 0.8977935 #> [15,] 1.0720011 #> [16,] 1.1148229 #> [17,] 1.1079944 #> [18,] 0.9613464 #> [19,] 1.1544710 #> [20,] 1.0123740 #> [21,] 1.4584089 #> [22,] 1.3463055 #> [23,] 1.4644672 #> [24,] 1.5493967 #> [25,] 1.3296563 #> [26,] 1.4320677 #> [27,] 1.4248840 #> [28,] 1.4438289 #> [29,] 1.4847455 #> [30,] 1.4158981 #>  #> , , 61 #>  #>            [,1] #>  [1,] 1.3465190 #>  [2,] 1.4168984 #>  [3,] 1.5854248 #>  [4,] 1.4962868 #>  [5,] 1.5382688 #>  [6,] 1.5770499 #>  [7,] 1.5149889 #>  [8,] 1.5129845 #>  [9,] 1.4301156 #> [10,] 1.5086092 #> [11,] 1.1409132 #> [12,] 1.0217393 #> [13,] 1.1257932 #> [14,] 0.9164571 #> [15,] 1.0914143 #> [16,] 1.1326243 #> [17,] 1.1273323 #> [18,] 0.9809768 #> [19,] 1.1727674 #> [20,] 1.0304669 #> [21,] 1.4347045 #> [22,] 1.3129683 #> [23,] 1.4387480 #> [24,] 1.5270205 #> [25,] 1.2933114 #> [26,] 1.3930751 #> [27,] 1.3879768 #> [28,] 1.4082804 #> [29,] 1.4541114 #> [30,] 1.3810119 #>  #> , , 62 #>  #>            [,1] #>  [1,] 1.3513304 #>  [2,] 1.4197134 #>  [3,] 1.5903905 #>  [4,] 1.5030693 #>  [5,] 1.5463640 #>  [6,] 1.5777202 #>  [7,] 1.5150075 #>  [8,] 1.5161597 #>  [9,] 1.4380720 #> [10,] 1.5181072 #> [11,] 1.1605023 #> [12,] 1.0394955 #> [13,] 1.1432337 #> [14,] 0.9349612 #> [15,] 1.1103132 #> [16,] 1.1500012 #> [17,] 1.1460558 #> [18,] 1.0001167 #> [19,] 1.1906654 #> [20,] 1.0482905 #> [21,] 1.4094001 #> [22,] 1.2777510 #> [23,] 1.4113326 #> [24,] 1.5028923 #> [25,] 1.2551493 #> [26,] 1.3521439 #> [27,] 1.3491249 #> [28,] 1.3707507 #> [29,] 1.4215683 #> [30,] 1.3441005 #>  #> , , 63 #>  #>            [,1] #>  [1,] 1.3553817 #>  [2,] 1.4215725 #>  [3,] 1.5944878 #>  [4,] 1.5089831 #>  [5,] 1.5536211 #>  [6,] 1.5773313 #>  [7,] 1.5140225 #>  [8,] 1.5183968 #>  [9,] 1.4453326 #> [10,] 1.5268620 #> [11,] 1.1797639 #> [12,] 1.0570623 #> [13,] 1.1603207 #> [14,] 0.9532579 #> [15,] 1.1288743 #> [16,] 1.1668135 #> [17,] 1.1644841 #> [18,] 1.0190693 #> [19,] 1.2080644 #> [20,] 1.0656753 #> [21,] 1.3824786 #> [22,] 1.2406248 #> [23,] 1.3822426 #> [24,] 1.4770597 #> [25,] 1.2152067 #> [26,] 1.3093151 #> [27,] 1.3083668 #> [28,] 1.3312773 #> [29,] 1.3871450 #> [30,] 1.3052853 #>  #> , , 64 #>  #>            [,1] #>  [1,] 1.3587222 #>  [2,] 1.4225294 #>  [3,] 1.5977128 #>  [4,] 1.5138484 #>  [5,] 1.5600502 #>  [6,] 1.5758781 #>  [7,] 1.5120109 #>  [8,] 1.5197338 #>  [9,] 1.4519194 #> [10,] 1.5349034 #> [11,] 1.1987063 #> [12,] 1.0741285 #> [13,] 1.1771162 #> [14,] 0.9712769 #> [15,] 1.1471564 #> [16,] 1.1832801 #> [17,] 1.1826141 #> [18,] 1.0377580 #> [19,] 1.2251672 #> [20,] 1.0828420 #> [21,] 1.3538765 #> [22,] 1.2016932 #> [23,] 1.3515010 #> [24,] 1.4495462 #> [25,] 1.1735221 #> [26,] 1.2646324 #> [27,] 1.2657438 #> [28,] 1.2899001 #> [29,] 1.3508723 #> [30,] 1.2646052 #>  #> , , 65 #>  #>            [,1] #>  [1,] 1.3613486 #>  [2,] 1.4224928 #>  [3,] 1.6000602 #>  [4,] 1.5178818 #>  [5,] 1.5656884 #>  [6,] 1.5733362 #>  [7,] 1.5088866 #>  [8,] 1.5201970 #>  [9,] 1.4578473 #> [10,] 1.5422554 #> [11,] 1.2169530 #> [12,] 1.0910020 #> [13,] 1.1933536 #> [14,] 0.9891794 #> [15,] 1.1649024 #> [16,] 1.1994030 #> [17,] 1.2001663 #> [18,] 1.0560056 #> [19,] 1.2418021 #> [20,] 1.0996652 #> [21,] 1.3235930 #> [22,] 1.1609943 #> [23,] 1.3191327 #> [24,] 1.4203720 #> [25,] 1.1301365 #> [26,] 1.2181418 #> [27,] 1.2212897 #> [28,] 1.2466615 #> [29,] 1.3127835 #> [30,] 1.2221012 #>  #> , , 66 #>  #>           [,1] #>  [1,] 1.363258 #>  [2,] 1.421506 #>  [3,] 1.601321 #>  [4,] 1.521083 #>  [5,] 1.570403 #>  [6,] 1.569659 #>  [7,] 1.504724 #>  [8,] 1.519795 #>  [9,] 1.463040 #> [10,] 1.548838 #> [11,] 1.234855 #> [12,] 1.107568 #> [13,] 1.209212 #> [14,] 1.006661 #> [15,] 1.182282 #> [16,] 1.214826 #> [17,] 1.217348 #> [18,] 1.074039 #> [19,] 1.257965 #> [20,] 1.116075 #> [21,] 1.291805 #> [22,] 1.118568 #> [23,] 1.285164 #> [24,] 1.389559 #> [25,] 1.085093 #> [26,] 1.169892 #> [27,] 1.175032 #> [28,] 1.201606 #> [29,] 1.272914 #> [30,] 1.177817 #>  #> , , 67 #>  #>           [,1] #>  [1,] 1.364439 #>  [2,] 1.419607 #>  [3,] 1.601576 #>  [4,] 1.523446 #>  [5,] 1.574236 #>  [6,] 1.564908 #>  [7,] 1.499500 #>  [8,] 1.518526 #>  [9,] 1.467338 #> [10,] 1.554517 #> [11,] 1.252405 #> [12,] 1.123689 #> [13,] 1.224763 #> [14,] 1.024030 #> [15,] 1.199364 #> [16,] 1.229876 #> [17,] 1.234203 #> [18,] 1.091702 #> [19,] 1.273817 #> [20,] 1.132254 #> [21,] 1.258535 #> [22,] 1.074458 #> [23,] 1.249624 #> [24,] 1.357131 #> [25,] 1.038426 #> [26,] 1.119933 #> [27,] 1.127038 #> [28,] 1.154782 #> [29,] 1.231301 #> [30,] 1.131798 #>  #> , , 68 #>  #>            [,1] #>  [1,] 1.3646621 #>  [2,] 1.4167922 #>  [3,] 1.6009291 #>  [4,] 1.5249676 #>  [5,] 1.5772383 #>  [6,] 1.5589992 #>  [7,] 1.4932408 #>  [8,] 1.5162612 #>  [9,] 1.4709127 #> [10,] 1.5594168 #> [11,] 1.2693643 #> [12,] 1.1396006 #> [13,] 1.2397390 #> [14,] 1.0410823 #> [15,] 1.2158924 #> [16,] 1.2445551 #> [17,] 1.2505222 #> [18,] 1.1090026 #> [19,] 1.2891276 #> [20,] 1.1480160 #> [21,] 1.2238100 #> [22,] 1.0287080 #> [23,] 1.2125411 #> [24,] 1.3231116 #> [25,] 0.9901509 #> [26,] 1.0683186 #> [27,] 1.0773716 #> [28,] 1.1062386 #> [29,] 1.1879486 #> [30,] 1.0840929 #>  #> , , 69 #>  #>            [,1] #>  [1,] 1.3640946 #>  [2,] 1.4130604 #>  [3,] 1.5993906 #>  [4,] 1.5256420 #>  [5,] 1.5793689 #>  [6,] 1.5519690 #>  [7,] 1.4859544 #>  [8,] 1.5130615 #>  [9,] 1.4737901 #> [10,] 1.5635724 #> [11,] 1.2858429 #> [12,] 1.1550483 #> [13,] 1.2543117 #> [14,] 1.0579122 #> [15,] 1.2320260 #> [16,] 1.2586610 #> [17,] 1.2663874 #> [18,] 1.1260743 #> [19,] 1.3039986 #> [20,] 1.1634044 #> [21,] 1.1876552 #> [22,] 0.9813656 #> [23,] 1.1739480 #> [24,] 1.2875289 #> [25,] 0.9403200 #> [26,] 1.0151044 #> [27,] 1.0260861 #> [28,] 1.0560280 #> [29,] 1.1429193 #> [30,] 1.0347522 #>  #> , , 70 #>  #>            [,1] #>  [1,] 1.3627956 #>  [2,] 1.4084087 #>  [3,] 1.5969580 #>  [4,] 1.5253979 #>  [5,] 1.5806271 #>  [6,] 1.5438541 #>  [7,] 1.4776374 #>  [8,] 1.5088985 #>  [9,] 1.4759888 #> [10,] 1.5670155 #> [11,] 1.3019395 #> [12,] 1.1702143 #> [13,] 1.2685620 #> [14,] 1.0745311 #> [15,] 1.2478456 #> [16,] 1.2722415 #> [17,] 1.2819058 #> [18,] 1.1426432 #> [19,] 1.3185483 #> [20,] 1.1785366 #> [21,] 1.1500989 #> [22,] 0.9324801 #> [23,] 1.1338777 #> [24,] 1.2504105 #> [25,] 0.8890333 #> [26,] 0.9603482 #> [27,] 0.9732372 #> [28,] 1.0041948 #> [29,] 1.0962753 #> [30,] 0.9838287 #>  #> , , 71 #>  #>            [,1] #>  [1,] 1.3607627 #>  [2,] 1.4028069 #>  [3,] 1.5936287 #>  [4,] 1.5240672 #>  [5,] 1.5810665 #>  [6,] 1.5346517 #>  [7,] 1.4682863 #>  [8,] 1.5038169 #>  [9,] 1.4774256 #> [10,] 1.5696580 #> [11,] 1.3175550 #> [12,] 1.1850890 #> [13,] 1.2822236 #> [14,] 1.0907699 #> [15,] 1.2630971 #> [16,] 1.2854289 #> [17,] 1.2969368 #> [18,] 1.1589350 #> [19,] 1.3324787 #> [20,] 1.1931732 #> [21,] 1.1111705 #> [22,] 0.8821031 #> [23,] 1.0923650 #> [24,] 1.2117861 #> [25,] 0.8363453 #> [26,] 0.9041101 #> [27,] 0.9188832 #> [28,] 0.9507671 #> [29,] 1.0480629 #> [30,] 0.9313776 #>  #> , , 72 #>  #>            [,1] #>  [1,] 1.3579935 #>  [2,] 1.3962123 #>  [3,] 1.5893210 #>  [4,] 1.5218638 #>  [5,] 1.5805193 #>  [6,] 1.5243589 #>  [7,] 1.4578982 #>  [8,] 1.4978529 #>  [9,] 1.4779560 #> [10,] 1.5713921 #> [11,] 1.3325300 #> [12,] 1.1994420 #> [13,] 1.2954584 #> [14,] 1.1068783 #> [15,] 1.2779265 #> [16,] 1.2981754 #> [17,] 1.3114213 #> [18,] 1.1749583 #> [19,] 1.3460061 #> [20,] 1.2074992 #> [21,] 1.0709005 #> [22,] 0.8302883 #> [23,] 1.0494462 #> [24,] 1.1715739 #> [25,] 0.7823124 #> [26,] 0.8464524 #> [27,] 0.8630842 #> [28,] 0.8958474 #> [29,] 0.9983306 #> [30,] 0.8774562 #>  #> , , 73 #>  #>            [,1] #>  [1,] 1.3544789 #>  [2,] 1.3886845 #>  [3,] 1.5838804 #>  [4,] 1.5187916 #>  [5,] 1.5790937 #>  [6,] 1.5129731 #>  [7,] 1.4464697 #>  [8,] 1.4910096 #>  [9,] 1.4777401 #> [10,] 1.5723141 #> [11,] 1.3471174 #> [12,] 1.2135806 #> [13,] 1.3083575 #> [14,] 1.1225381 #> [15,] 1.2924266 #> [16,] 1.3102152 #> [17,] 1.3255492 #> [18,] 1.1904146 #> [19,] 1.3592074 #> [20,] 1.2214997 #> [21,] 1.0293127 #> [22,] 0.7770918 #> [23,] 1.0049949 #> [24,] 1.1298922 #> [25,] 0.7269930 #> [26,] 0.7874397 #> [27,] 0.8059028 #> [28,] 0.8394977 #> [29,] 0.9471289 #> [30,] 0.8221242 #>  #> , , 74 #>  #>            [,1] #>  [1,] 1.3500223 #>  [2,] 1.3801440 #>  [3,] 1.5775005 #>  [4,] 1.5148463 #>  [5,] 1.5768270 #>  [6,] 1.5004916 #>  [7,] 1.4339978 #>  [8,] 1.4832791 #>  [9,] 1.4768060 #> [10,] 1.5724639 #> [11,] 1.3613226 #> [12,] 1.2272829 #> [13,] 1.3206570 #> [14,] 1.1380442 #> [15,] 1.3063477 #> [16,] 1.3218657 #> [17,] 1.3392405 #> [18,] 1.2056365 #> [19,] 1.3717083 #> [20,] 1.2349864 #> [21,] 0.9863961 #> [22,] 0.7225716 #> [23,] 0.9591931 #> [24,] 1.0867357 #> [25,] 0.6704474 #> [26,] 0.7271387 #> [27,] 0.7474037 #> [28,] 0.7817820 #> [29,] 0.8945102 #> [30,] 0.7654432 #>  #> , , 75 #>  #>            [,1] #>  [1,] 1.3447197 #>  [2,] 1.3706245 #>  [3,] 1.5702036 #>  [4,] 1.5100233 #>  [5,] 1.5736628 #>  [6,] 1.4869118 #>  [7,] 1.4203947 #>  [8,] 1.4744822 #>  [9,] 1.4751765 #> [10,] 1.5718814 #> [11,] 1.3747326 #> [12,] 1.2405996 #> [13,] 1.3325074 #> [14,] 1.1532263 #> [15,] 1.3198200 #> [16,] 1.3331220 #> [17,] 1.3522848 #> [18,] 1.2205029 #> [19,] 1.3838457 #> [20,] 1.2482038 #> [21,] 0.9420905 #> [22,] 0.6667878 #> [23,] 0.9121164 #> [24,] 1.0421935 #> [25,] 0.6127382 #> [26,] 0.6656180 #> [27,] 0.6876538 #> [28,] 0.7227664 #> [29,] 0.8405290 #> [30,] 0.7074770 #>  #> , , 76 #>  #>            [,1] #>  [1,] 1.3386641 #>  [2,] 1.3601724 #>  [3,] 1.5619960 #>  [4,] 1.5043182 #>  [5,] 1.5695841 #>  [6,] 1.4722312 #>  [7,] 1.4057022 #>  [8,] 1.4647944 #>  [9,] 1.4727607 #> [10,] 1.5704701 #> [11,] 1.3877477 #> [12,] 1.2536574 #> [13,] 1.3440098 #> [14,] 1.1681079 #> [15,] 1.3329492 #> [16,] 1.3436449 #> [17,] 1.3649645 #> [18,] 1.2348588 #> [19,] 1.3956517 #> [20,] 1.2610108 #> [21,] 0.8965506 #> [22,] 0.6098026 #> [23,] 0.8638106 #> [24,] 0.9963283 #> [25,] 0.5539294 #> [26,] 0.6029485 #> [27,] 0.6267218 #> [28,] 0.6625193 #> [29,] 0.7852420 #> [30,] 0.6482917 #>  #> , , 77 #>  #>            [,1] #>  [1,] 1.3318580 #>  [2,] 1.3487858 #>  [3,] 1.5528757 #>  [4,] 1.4976316 #>  [5,] 1.5646629 #>  [6,] 1.4564432 #>  [7,] 1.3899564 #>  [8,] 1.4541383 #>  [9,] 1.4694311 #> [10,] 1.5681491 #> [11,] 1.4003589 #> [12,] 1.2661238 #> [13,] 1.3549048 #> [14,] 1.1827817 #> [15,] 1.3454915 #> [16,] 1.3537039 #> [17,] 1.3772446 #> [18,] 1.2489525 #> [19,] 1.4066850 #> [20,] 1.2733407 #> [21,] 0.8498605 #> [22,] 0.5516801 #> [23,] 0.8143207 #> [24,] 0.9491842 #> [25,] 0.4940871 #> [26,] 0.5392029 #> [27,] 0.5646786 #> [28,] 0.6011110 #> [29,] 0.7287074 #> [30,] 0.5879550 #>  #> , , 78 #>  #>            [,1] #>  [1,] 1.3242993 #>  [2,] 1.3364633 #>  [3,] 1.5428403 #>  [4,] 1.4898603 #>  [5,] 1.5586947 #>  [6,] 1.4395212 #>  [7,] 1.3731544 #>  [8,] 1.4425499 #>  [9,] 1.4653339 #> [10,] 1.5649857 #> [11,] 1.4122880 #> [12,] 1.2783652 #> [13,] 1.3653289 #> [14,] 1.1969927 #> [15,] 1.3575591 #> [16,] 1.3633435 #> [17,] 1.3888151 #> [18,] 1.2625813 #> [19,] 1.4173907 #> [20,] 1.2854027 #> [21,] 0.8020599 #> [22,] 0.4924866 #> [23,] 0.7636935 #> [24,] 0.9008024 #> [25,] 0.4332791 #> [26,] 0.4744558 #> [27,] 0.5015971 #> [28,] 0.5386141 #> [29,] 0.6709856 #> [30,] 0.5265299 #>  #> , , 79 #>  #>            [,1] #>  [1,] 1.3159813 #>  [2,] 1.3232032 #>  [3,] 1.5316557 #>  [4,] 1.4811658 #>  [5,] 1.5518561 #>  [6,] 1.4213588 #>  [7,] 1.3552933 #>  [8,] 1.4300746 #>  [9,] 1.4604993 #> [10,] 1.5610236 #> [11,] 1.4236870 #> [12,] 1.2902017 #> [13,] 1.3753943 #> [14,] 1.2110615 #> [15,] 1.3692712 #> [16,] 1.3724066 #> [17,] 1.4000103 #> [18,] 1.2758084 #> [19,] 1.4277211 #> [20,] 1.2969726 #> [21,] 0.7531895 #> [22,] 0.4322898 #> [23,] 0.7119771 #> [24,] 0.8512257 #> [25,] 0.3715752 #> [26,] 0.4087836 #> [27,] 0.4375519 #> [28,] 0.4751026 #> [29,] 0.6121389 #> [30,] 0.4640418 #>  #> , , 80 #>  #>            [,1] #>  [1,] 1.3067412 #>  [2,] 1.3089834 #>  [3,] 1.5194468 #>  [4,] 1.4715627 #>  [5,] 1.5441633 #>  [6,] 1.4020376 #>  [7,] 1.3363705 #>  [8,] 1.4167114 #>  [9,] 1.4549542 #> [10,] 1.5563109 #> [11,] 1.4346565 #> [12,] 1.3015510 #> [13,] 1.3848467 #> [14,] 1.2246810 #> [15,] 1.3803914 #> [16,] 1.3808325 #> [17,] 1.4108284 #> [18,] 1.2887599 #> [19,] 1.4372927 #> [20,] 1.3081153 #> [21,] 0.7032915 #> [22,] 0.3711599 #> [23,] 0.6592211 #> [24,] 0.8004979 #> [25,] 0.3090464 #> [26,] 0.3422646 #> [27,] 0.3726194 #> [28,] 0.4106530 #> [29,] 0.5522308 #> [30,] 0.4006283 #>  #> , , 81 #>  #>            [,1] #>  [1,] 1.2965994 #>  [2,] 1.2937685 #>  [3,] 1.5062941 #>  [4,] 1.4610518 #>  [5,] 1.5355554 #>  [6,] 1.3816033 #>  [7,] 1.3163536 #>  [8,] 1.4023828 #>  [9,] 1.4485999 #> [10,] 1.5507427 #> [11,] 1.4450761 #> [12,] 1.3126507 #> [13,] 1.3938076 #> [14,] 1.2380895 #> [15,] 1.3910117 #> [16,] 1.3888336 #> [17,] 1.4208911 #> [18,] 1.3011020 #> [19,] 1.4465294 #> [20,] 1.3189776 #> [21,] 0.6524090 #> [22,] 0.3091682 #> [23,] 0.6054764 #> [24,] 0.7486647 #> [25,] 0.2457656 #> [26,] 0.2749787 #> [27,] 0.3068779 #> [28,] 0.3453432 #> [29,] 0.4913160 #> [30,] 0.3363650 #>  #> , , 82 #>  #>            [,1] #>  [1,] 1.2856851 #>  [2,] 1.2775820 #>  [3,] 1.4922169 #>  [4,] 1.4496284 #>  [5,] 1.5259986 #>  [6,] 1.3600537 #>  [7,] 1.2952239 #>  [8,] 1.3870493 #>  [9,] 1.4413259 #> [10,] 1.5442634 #> [11,] 1.4547977 #> [12,] 1.3231775 #> [13,] 1.4024001 #> [14,] 1.2511813 #> [15,] 1.4012656 #> [16,] 1.3964053 #> [17,] 1.4305587 #> [18,] 1.3131517 #> [19,] 1.4553486 #> [20,] 1.3292711 #> [21,] 0.6005866 #> [22,] 0.2463883 #> [23,] 0.5507955 #> [24,] 0.6957728 #> [25,] 0.1818073 #> [26,] 0.2070074 #> [27,] 0.2404073 #> [28,] 0.2792529 #> [29,] 0.4294677 #> [30,] 0.2713295 #>  #> , , 83 #>  #>            [,1] #>  [1,] 1.2740051 #>  [2,] 1.2603728 #>  [3,] 1.4772132 #>  [4,] 1.4372881 #>  [5,] 1.5155577 #>  [6,] 1.3373872 #>  [7,] 1.2730220 #>  [8,] 1.3708049 #>  [9,] 1.4332642 #> [10,] 1.5369152 #> [11,] 1.4640875 #> [12,] 1.3334063 #> [13,] 1.4103763 #> [14,] 1.2638793 #> [15,] 1.4109249 #> [16,] 1.4031414 #> [17,] 1.4398309 #> [18,] 1.3248473 #> [19,] 1.4634289 #> [20,] 1.3392003 #> [21,] 0.5478700 #> [22,] 0.1828950 #> [23,] 0.4952320 #> [24,] 0.6418646 #> [25,] 0.1172473 #> [26,] 0.1384315 #> [27,] 0.1732890 #> [28,] 0.2124636 #> [29,] 0.3667635 #> [30,] 0.2056007 #>  #> , , 84 #>  #>             [,1] #>  [1,] 1.26155728 #>  [2,] 1.24216389 #>  [3,] 1.46128122 #>  [4,] 1.42390124 #>  [5,] 1.50403555 #>  [6,] 1.31360190 #>  [7,] 1.24974793 #>  [8,] 1.35359915 #>  [9,] 1.42444643 #> [10,] 1.52874271 #> [11,] 1.47294021 #> [12,] 1.34326005 #> [13,] 1.41784112 #> [14,] 1.27638286 #> [15,] 1.42006007 #> [16,] 1.40946117 #> [17,] 1.44839582 #> [18,] 1.33594577 #> [19,] 1.47115958 #> [20,] 1.34879274 #> [21,] 0.49430153 #> [22,] 0.11876494 #> [23,] 0.43884097 #> [24,] 0.58690910 #> [25,] 0.05216211 #> [26,] 0.06932803 #> [27,] 0.10560602 #> [28,] 0.14505807 #> [29,] 0.30327400 #> [30,] 0.13925909 #>  #> , , 85 #>  #>                [,1] #>  [1,]  1.2483379427 #>  [2,]  1.2230088828 #>  [3,]  1.4443033260 #>  [4,]  1.4094339458 #>  [5,]  1.4916403005 #>  [6,]  1.2886963885 #>  [7,]  1.2253730337 #>  [8,]  1.3354545370 #>  [9,]  1.4149035327 #> [10,]  1.5198003313 #> [11,]  1.4809464985 #> [12,]  1.3525576942 #> [13,]  1.4249290951 #> [14,]  1.2883637999 #> [15,]  1.4288190829 #> [16,]  1.4153512537 #> [17,]  1.4564925318 #> [18,]  1.3467719926 #> [19,]  1.4784241064 #> [20,]  1.3578015666 #> [21,]  0.4398676374 #> [22,]  0.0540762322 #> [23,]  0.3816787039 #> [24,]  0.5310553860 #> [25,] -0.0133746322 #> [26,] -0.0002024938 #> [27,]  0.0374426288 #> [28,]  0.0771208727 #> [29,]  0.2390715572 #> [30,]  0.0723868022 #>  #> , , 86 #>  #>               [,1] #>  [1,]  1.234218446 #>  [2,]  1.202906842 #>  [3,]  1.426209358 #>  [4,]  1.393992892 #>  [5,]  1.478368843 #>  [6,]  1.262669357 #>  [7,]  1.199821683 #>  [8,]  1.316417701 #>  [9,]  1.404528767 #> [10,]  1.509975851 #> [11,]  1.488516653 #> [12,]  1.361610317 #> [13,]  1.431399318 #> [14,]  1.300193987 #> [15,]  1.436983100 #> [16,]  1.420518944 #> [17,]  1.464174327 #> [18,]  1.357152316 #> [19,]  1.484995586 #> [20,]  1.366494315 #> [21,]  0.384612485 #> [22,] -0.011091648 #> [23,]  0.323802331 #> [24,]  0.474356008 #> [25,] -0.079287026 #> [26,] -0.070072560 #> [27,] -0.031115472 #> [28,]  0.008737797 #> [29,]  0.174229834 #> [30,]  0.005067146 #>  #> , , 87 #>  #>              [,1] #>  [1,]  1.21914100 #>  [2,]  1.18185693 #>  [3,]  1.40713221 #>  [4,]  1.37760191 #>  [5,]  1.46417212 #>  [6,]  1.23551977 #>  [7,]  1.17319252 #>  [8,]  1.29648825 #>  [9,]  1.39322962 #> [10,]  1.49922539 #> [11,]  1.49564726 #> [12,]  1.37013646 #> [13,]  1.43733917 #> [14,]  1.31158099 #> [15,]  1.44459938 #> [16,]  1.42513321 #> [17,]  1.47122001 #> [18,]  1.36700520 #> [19,]  1.49120018 #> [20,]  1.37472999 #> [21,]  0.32867947 #> [22,] -0.07665784 #> [23,]  0.26521953 #> [24,]  0.41682619 #> [25,] -0.14547261 #> [26,] -0.14019384 #> [27,] -0.09998138 #> [28,] -0.06000405 #> [29,]  0.10882392 #> [30,] -0.06261525 #>  #> , , 88 #>  #>              [,1] #>  [1,]  1.20327257 #>  [2,]  1.15985845 #>  [3,]  1.38710309 #>  [4,]  1.36026794 #>  [5,]  1.44900927 #>  [6,]  1.20724689 #>  [7,]  1.14548445 #>  [8,]  1.27551809 #>  [9,]  1.38112263 #> [10,]  1.48759888 #> [11,]  1.50202612 #> [12,]  1.37825966 #> [13,]  1.44289470 #> [14,]  1.32268355 #> [15,]  1.45183108 #> [16,]  1.42929650 #> [17,]  1.47770561 #> [18,]  1.37656127 #> [19,]  1.49687765 #> [20,]  1.38245034 #> [21,]  0.27212083 #> [22,] -0.14254023 #> [23,]  0.20602061 #> [24,]  0.35854759 #> [25,] -0.21184907 #> [26,] -0.21047695 #> [27,] -0.16906709 #> [28,] -0.12901636 #> [29,]  0.04293019 #> [30,] -0.13057458 #>  #> , , 89 #>  #>              [,1] #>  [1,]  1.18662423 #>  [2,]  1.13689821 #>  [3,]  1.36613578 #>  [4,]  1.34198659 #>  [5,]  1.43288591 #>  [6,]  1.17785031 #>  [7,]  1.11669674 #>  [8,]  1.25360978 #>  [9,]  1.36824107 #> [10,]  1.47512731 #> [11,]  1.50784734 #> [12,]  1.38605208 #> [13,]  1.44783276 #> [14,]  1.33347581 #> [15,]  1.45846929 #> [16,]  1.43290533 #> [17,]  1.48376767 #> [18,]  1.38556693 #> [19,]  1.50191861 #> [20,]  1.38987259 #> [21,]  0.21498933 #> [22,] -0.20865552 #> [23,]  0.14630553 #> [24,]  0.29959522 #> [25,] -0.27833316 #> [26,] -0.28083160 #> [27,] -0.23828357 #> [28,] -0.19820975 #> [29,] -0.02337371 #> [30,] -0.19872395 #>  #> , , 90 #>  #>              [,1] #>  [1,]  1.16919413 #>  [2,]  1.11294810 #>  [3,]  1.34422885 #>  [4,]  1.32275353 #>  [5,]  1.41568813 #>  [6,]  1.14726108 #>  [7,]  1.08682910 #>  [8,]  1.23077701 #>  [9,]  1.35461995 #> [10,]  1.46185660 #> [11,]  1.51320516 #> [12,]  1.39322814 #> [13,]  1.45222208 #> [14,]  1.34381002 #> [15,]  1.46453685 #> [16,]  1.43577242 #> [17,]  1.48926434 #> [18,]  1.39415924 #> [19,]  1.50657991 #> [20,]  1.39674826 #> [21,]  0.15733865 #> [22,] -0.27491934 #> [23,]  0.08613815 #> [24,]  0.24002764 #> [25,] -0.34484076 #> [26,] -0.35116665 #> [27,] -0.30754086 #> [28,] -0.26749383 #> [29,] -0.09000901 #> [30,] -0.26697550 #>  #> , , 91 #>  #>              [,1] #>  [1,]  1.15098046 #>  [2,]  1.08799585 #>  [3,]  1.32135343 #>  [4,]  1.30240757 #>  [5,]  1.39759573 #>  [6,]  1.11543919 #>  [7,]  1.05588171 #>  [8,]  1.20698990 #>  [9,]  1.34014431 #> [10,]  1.44767678 #> [11,]  1.51796045 #> [12,]  1.40015310 #> [13,]  1.45622056 #> [14,]  1.35397954 #> [15,]  1.47021253 #> [16,]  1.43819648 #> [17,]  1.49410151 #> [18,]  1.40242087 #> [19,]  1.51064702 #> [20,]  1.40316321 #> [21,]  0.09922337 #> [22,] -0.34124543 #> [23,]  0.02558185 #> [24,]  0.17990318 #> [25,] -0.41128699 #> [26,] -0.42139026 #> [27,] -0.37674824 #> [28,] -0.33677737 #> [29,] -0.15689587 #> [30,] -0.33524049 #>  #> , , 92 #>  #>              [,1] #>  [1,]  1.13187486 #>  [2,]  1.06202073 #>  [3,]  1.29733710 #>  [4,]  1.28098928 #>  [5,]  1.37860579 #>  [6,]  1.08246416 #>  [7,]  1.02385529 #>  [8,]  1.18226473 #>  [9,]  1.32474027 #> [10,]  1.43255641 #> [11,]  1.52198426 #> [12,]  1.40659071 #> [13,]  1.45960329 #> [14,]  1.36357141 #> [15,]  1.47529787 #> [16,]  1.44018697 #> [17,]  1.49850783 #> [18,]  1.41002344 #> [19,]  1.51413516 #> [20,]  1.40928197 #> [21,]  0.04069891 #> [22,] -0.40754200 #> [23,] -0.03529909 #> [24,]  0.11928119 #> [25,] -0.47758631 #> [26,] -0.49141001 #> [27,] -0.44581428 #> [28,] -0.40596835 #> [29,] -0.22395344 #> [30,] -0.40342940 #>  #> , , 93 #>  #>              [,1] #>  [1,]  1.11178837 #>  [2,]  1.03503569 #>  [3,]  1.27226560 #>  [4,]  1.25854973 #>  [5,]  1.35868053 #>  [6,]  1.04836405 #>  [7,]  0.99075115 #>  [8,]  1.15664739 #>  [9,]  1.30850888 #> [10,]  1.41655330 #> [11,]  1.52554368 #> [12,]  1.41253788 #> [13,]  1.46241951 #> [14,]  1.37299238 #> [15,]  1.47979022 #> [16,]  1.44129928 #> [17,]  1.50239237 #> [18,]  1.41732319 #> [19,]  1.51723588 #> [20,]  1.41477065 #> [21,] -0.01817850 #> [22,] -0.47372151 #> [23,] -0.09643957 #> [24,]  0.05822193 #> [25,] -0.54365264 #> [26,] -0.56113301 #> [27,] -0.51464701 #> [28,] -0.47497415 #> [29,] -0.29109998 #> [30,] -0.47145207 #>  #> , , 94 #>  #>               [,1] #>  [1,]  1.090886738 #>  [2,]  1.007102963 #>  [3,]  1.246220155 #>  [4,]  1.235120205 #>  [5,]  1.337776402 #>  [6,]  1.013146523 #>  [7,]  0.956571274 #>  [8,]  1.130112907 #>  [9,]  1.291484548 #> [10,]  1.399684946 #> [11,]  1.528621181 #> [12,]  1.418211044 #> [13,]  1.464839217 #> [14,]  1.381988679 #> [15,]  1.483884453 #> [16,]  1.441948366 #> [17,]  1.505568721 #> [18,]  1.424187100 #> [19,]  1.519672807 #> [20,]  1.419864956 #> [21,] -0.077351844 #> [22,] -0.539696206 #> [23,] -0.157773678 #> [24,] -0.003213404 #> [25,] -0.609399428 #> [26,] -0.630466013 #> [27,] -0.583153987 #> [28,] -0.543701616 #> [29,] -0.358252974 #> [30,] -0.539217798 #>  #> , , 95 #>  #>              [,1] #>  [1,]  1.06918841 #>  [2,]  0.97822391 #>  [3,]  1.21922941 #>  [4,]  1.21071637 #>  [5,]  1.31583312 #>  [6,]  0.97681482 #>  [7,]  0.92131716 #>  [8,]  1.10252162 #>  [9,]  1.27370689 #> [10,]  1.38198774 #> [11,]  1.53082685 #> [12,]  1.42322797 #> [13,]  1.46664608 #> [14,]  1.39061555 #> [15,]  1.48739288 #> [16,]  1.44214024 #> [17,]  1.50831326 #> [18,]  1.43045796 #> [19,]  1.52158866 #> [20,]  1.42463812 #> [21,] -0.13676367 #> [22,] -0.60537781 #> [23,] -0.21923481 #> [24,] -0.06497157 #> [25,] -0.67473983 #> [26,] -0.69931558 #> [27,] -0.65124249 #> [28,] -0.61205722 #> [29,] -0.42532916 #> [30,] -0.60663546 #>  #> , , 96 #>  #>             [,1] #>  [1,]  1.0466979 #>  [2,]  0.9484003 #>  [3,]  1.1912930 #>  [4,]  1.1853349 #>  [5,]  1.2928264 #>  [6,]  0.9393730 #>  [7,]  0.8848584 #>  [8,]  1.0740416 #>  [9,]  1.2550527 #> [10,]  1.3633547 #> [11,]  1.5325655 #> [12,]  1.4279548 #> [13,]  1.4678691 #> [14,]  1.3989480 #> [15,]  1.4902864 #> [16,]  1.4416416 #> [17,]  1.5105586 #> [18,]  1.4364302 #> [19,]  1.5231145 #> [20,]  1.4287264 #> [21,] -0.1963741 #> [22,] -0.6706776 #> [23,] -0.2807557 #> [24,] -0.1269871 #> [25,] -0.7395868 #> [26,] -0.7675882 #> [27,] -0.7188196 #> [28,] -0.6799472 #> [29,] -0.4922447 #> [30,] -0.6735828 #>  #> , , 97 #>  #>             [,1] #>  [1,]  1.0234144 #>  [2,]  0.9176345 #>  [3,]  1.1624109 #>  [4,]  1.1589729 #>  [5,]  1.2689064 #>  [6,]  0.9008260 #>  [7,]  0.8472726 #>  [8,]  1.0446352 #>  [9,]  1.2354679 #> [10,]  1.3437677 #> [11,]  1.5338387 #> [12,]  1.4322345 #> [13,]  1.4686907 #> [14,]  1.4067741 #> [15,]  1.4927766 #> [16,]  1.4405020 #> [17,]  1.5120527 #> [18,]  1.4418706 #> [19,]  1.5239044 #> [20,]  1.4324873 #> [21,] -0.2560843 #> [22,] -0.7355066 #> [23,] -0.3422685 #> [24,] -0.1891755 #> [25,] -0.8038530 #> [26,] -0.8351904 #> [27,] -0.7857924 #> [28,] -0.7472776 #> [29,] -0.5589152 #> [30,] -0.7399823 #>  #> , , 98 #>  #>             [,1] #>  [1,]  0.9992354 #>  [2,]  0.8859250 #>  [3,]  1.1324315 #>  [4,]  1.1314386 #>  [5,]  1.2440709 #>  [6,]  0.8611797 #>  [7,]  0.8086275 #>  [8,]  1.0142873 #>  [9,]  1.2150379 #> [10,]  1.3232927 #> [11,]  1.5343060 #> [12,]  1.4359609 #> [13,]  1.4689033 #> [14,]  1.4144345 #> [15,]  1.4946866 #> [16,]  1.4388939 #> [17,]  1.5131040 #> [18,]  1.4468001 #> [19,]  1.5242310 #> [20,]  1.4358063 #> [21,] -0.3158286 #> [22,] -0.7997757 #> [23,] -0.4037048 #> [24,] -0.2514722 #> [25,] -0.8674516 #> [26,] -0.9020290 #> [27,] -0.8520680 #> [28,] -0.8139547 #> [29,] -0.6252559 #> [30,] -0.8057462 #>  #> , , 99 #>  #>             [,1] #>  [1,]  0.9740949 #>  [2,]  0.8532536 #>  [3,]  1.1013759 #>  [4,]  1.1028524 #>  [5,]  1.2182932 #>  [6,]  0.8204410 #>  [7,]  0.7689329 #>  [8,]  0.9830164 #>  [9,]  1.1937982 #> [10,]  1.3019342 #> [11,]  1.5342014 #> [12,]  1.4394249 #> [13,]  1.4685152 #> [14,]  1.4215358 #> [15,]  1.4959603 #> [16,]  1.4367669 #> [17,]  1.5136851 #> [18,]  1.4514111 #> [19,]  1.5241701 #> [20,]  1.4385511 #> [21,] -0.3755467 #> [22,] -0.8633955 #> [23,] -0.4649959 #> [24,] -0.3138119 #> [25,] -0.9302953 #> [26,] -0.9680110 #> [27,] -0.9175538 #> [28,] -0.8798846 #> [29,] -0.6911819 #> [30,] -0.8707833 #>  #> , , 100 #>  #>             [,1] #>  [1,]  0.9481121 #>  [2,]  0.8195770 #>  [3,]  1.0693166 #>  [4,]  1.0732107 #>  [5,]  1.1915325 #>  [6,]  0.7786181 #>  [7,]  0.7281971 #>  [8,]  0.9508660 #>  [9,]  1.1717934 #> [10,]  1.2797181 #> [11,]  1.5336078 #> [12,]  1.4422932 #> [13,]  1.4677213 #> [14,]  1.4283969 #> [15,]  1.4968261 #> [16,]  1.4337964 #> [17,]  1.5134770 #> [18,]  1.4553968 #> [19,]  1.5232989 #> [20,]  1.4409679 #> [21,] -0.4351775 #> [22,] -0.9262771 #> [23,] -0.5260723 #> [24,] -0.3761233 #> [25,] -0.9922977 #> [26,] -1.0330441 #> [27,] -0.9821576 #> [28,] -0.9449741 #> [29,] -0.7566078 #> [30,] -0.9350022 #>  #> , , 101 #>  #>             [,1] #>  [1,]  0.9213181 #>  [2,]  0.7849087 #>  [3,]  1.0362928 #>  [4,]  1.0425508 #>  [5,]  1.1636571 #>  [6,]  0.7356616 #>  [7,]  0.6864299 #>  [8,]  0.9177451 #>  [9,]  1.1488928 #> [10,]  1.2565415 #> [11,]  1.5323690 #> [12,]  1.4447672 #> [13,]  1.4663231 #> [14,]  1.4348404 #> [15,]  1.4971184 #> [16,]  1.4303684 #> [17,]  1.5128044 #> [18,]  1.4589783 #> [19,]  1.5220214 #> [20,]  1.4428106 #> [21,] -0.4946599 #> [22,] -0.9883315 #> [23,] -0.5868460 #> [24,] -0.4383368 #> [25,] -1.0533671 #> [26,] -1.0970306 #> [27,] -1.0457873 #> [28,] -1.0091302 #> [29,] -0.8214375 #> [30,] -0.9983123 #>  #> , , 102 #>  #>             [,1] #>  [1,]  0.8937305 #>  [2,]  0.7492561 #>  [3,]  1.0023296 #>  [4,]  1.0109005 #>  [5,]  1.1347389 #>  [6,]  0.6915846 #>  [7,]  0.6436423 #>  [8,]  0.8836592 #>  [9,]  1.1250634 #> [10,]  1.2324010 #> [11,]  1.5303791 #> [12,]  1.4468468 #> [13,]  1.4643074 #> [14,]  1.4408634 #> [15,]  1.4967530 #> [16,]  1.4264834 #> [17,]  1.5116682 #> [18,]  1.4621557 #> [19,]  1.5203376 #> [20,]  1.4441682 #> [21,] -0.5539322 #> [22,] -1.0494702 #> [23,] -0.6472151 #> [24,] -0.5003851 #> [25,] -1.1134142 #> [26,] -1.1598783 #> [27,] -1.1083347 #> [28,] -1.0722537 #> [29,] -0.8855817 #> [30,] -1.0606234 #>  #> , , 103 #>  #>             [,1] #>  [1,]  0.8653504 #>  [2,]  0.7126918 #>  [3,]  0.9674295 #>  [4,]  0.9782596 #>  [5,]  1.1048970 #>  [6,]  0.6464592 #>  [7,]  0.5998471 #>  [8,]  0.8487072 #>  [9,]  1.1003750 #> [10,]  1.2073710 #> [11,]  1.5278987 #> [12,]  1.4483192 #> [13,]  1.4618821 #> [14,]  1.4466446 #> [15,]  1.4959760 #> [16,]  1.4217598 #> [17,]  1.5097685 #> [18,]  1.4646912 #> [19,]  1.5178196 #> [20,]  1.4452149 #> [21,] -0.6129326 #> [22,] -1.1096052 #> [23,] -0.7071382 #> [24,] -0.5622015 #> [25,] -1.1722846 #> [26,] -1.2215025 #> [27,] -1.1697070 #> [28,] -1.1342259 #> [29,] -0.9489647 #> [30,] -1.1218461 #>  #> , , 104 #>  #>             [,1] #>  [1,]  0.8360841 #>  [2,]  0.6752237 #>  [3,]  0.9315344 #>  [4,]  0.9446145 #>  [5,]  1.0741310 #>  [6,]  0.6002422 #>  [7,]  0.5550583 #>  [8,]  0.8128505 #>  [9,]  1.0748642 #> [10,]  1.1814438 #> [11,]  1.5248968 #> [12,]  1.4495270 #> [13,]  1.4588578 #> [14,]  1.4518492 #> [15,]  1.4946328 #> [16,]  1.4164971 #> [17,]  1.5073419 #> [18,]  1.4669053 #> [19,]  1.5149249 #> [20,]  1.4455852 #> [21,] -0.6715990 #> [22,] -1.1686491 #> [23,] -0.7665461 #> [24,] -0.6237186 #> [25,] -1.2299578 #> [26,] -1.2818145 #> [27,] -1.2298300 #> [28,] -1.1949842 #> [29,] -1.0115018 #> [30,] -1.1818919 #>  #> , , 105 #>  #>             [,1] #>  [1,]  0.8058915 #>  [2,]  0.6368606 #>  [3,]  0.8945613 #>  [4,]  0.9097917 #>  [5,]  1.0424257 #>  [6,]  0.5529864 #>  [7,]  0.5092919 #>  [8,]  0.7760842 #>  [9,]  1.0485814 #> [10,]  1.1546339 #> [11,]  1.5210113 #> [12,]  1.4501795 #> [13,]  1.4551993 #> [14,]  1.4568804 #> [15,]  1.4926108 #> [16,]  1.4107527 #> [17,]  1.5044383 #> [18,]  1.4686060 #> [19,]  1.5115816 #> [20,]  1.4455417 #> [21,] -0.7298686 #> [22,] -1.2265155 #> [23,] -0.8253690 #> [24,] -0.6848690 #> [25,] -1.2863520 #> [26,] -1.3407266 #> [27,] -1.2886159 #> [28,] -1.2544393 #> [29,] -1.0731090 #> [30,] -1.2406732 #>  #> , , 106 #>  #>             [,1] #>  [1,]  0.7748443 #>  [2,]  0.5976124 #>  [3,]  0.8565563 #>  [4,]  0.8739511 #>  [5,]  1.0097491 #>  [6,]  0.5047314 #>  [7,]  0.4625366 #>  [8,]  0.7384375 #>  [9,]  1.0213894 #> [10,]  1.1268447 #> [11,]  1.5166332 #> [12,]  1.4503637 #> [13,]  1.4511280 #> [14,]  1.4613771 #> [15,]  1.4901742 #> [16,]  1.4043590 #> [17,]  1.5008478 #> [18,]  1.4697391 #> [19,]  1.5074353 #> [20,]  1.4451896 #> [21,] -0.7876541 #> [22,] -1.2831187 #> [23,] -0.8835372 #> [24,] -0.7455854 #> [25,] -1.3413855 #> [26,] -1.3981530 #> [27,] -1.3459780 #> [28,] -1.3125033 #> [29,] -1.1337024 #> [30,] -1.2981037 #>  #> , , 107 #>  #>             [,1] #>  [1,]  0.7429882 #>  [2,]  0.5574902 #>  [3,]  0.8175973 #>  [4,]  0.8370529 #>  [5,]  0.9758963 #>  [6,]  0.4554996 #>  [7,]  0.4147633 #>  [8,]  0.6999507 #>  [9,]  0.9932781 #> [10,]  1.0980886 #> [11,]  1.5117679 #> [12,]  1.4502440 #> [13,]  1.4464633 #> [14,]  1.4655587 #> [15,]  1.4871792 #> [16,]  1.3972342 #> [17,]  1.4966395 #> [18,]  1.4705583 #> [19,]  1.5029118 #> [20,]  1.4440768 #> [21,] -0.8448154 #> [22,] -1.3383744 #> [23,] -0.9409815 #> [24,] -0.8057613 #> [25,] -1.3949779 #> [26,] -1.4540090 #> [27,] -1.4018315 #> [28,] -1.3690895 #> [29,] -1.1931993 #> [30,] -1.3540985 #>  #> , , 108 #>  #>             [,1] #>  [1,]  0.7103549 #>  [2,]  0.5164909 #>  [3,]  0.7777260 #>  [4,]  0.7991401 #>  [5,]  0.9410399 #>  [6,]  0.4053130 #>  [7,]  0.3660780 #>  [8,]  0.6604785 #>  [9,]  0.9643021 #> [10,]  1.0684488 #> [11,]  1.5060495 #> [12,]  1.4494408 #> [13,]  1.4411479 #> [14,]  1.4693448 #> [15,]  1.4834840 #> [16,]  1.3896324 #> [17,]  1.4919491 #> [18,]  1.4707652 #> [19,]  1.4978995 #> [20,]  1.4426268 #> [21,] -0.9013654 #> [22,] -1.3921992 #> [23,] -0.9976328 #> [24,] -0.8653341 #> [25,] -1.4470504 #> [26,] -1.5082122 #> [27,] -1.4560931 #> [28,] -1.4241130 #> [29,] -1.2515176 #> [30,] -1.4085741 #>  #> , , 109 #>  #>             [,1] #>  [1,]  0.6769487 #>  [2,]  0.4745784 #>  [3,]  0.7369520 #>  [4,]  0.7602554 #>  [5,]  0.9052668 #>  [6,]  0.3541963 #>  [7,]  0.3165056 #>  [8,]  0.6201642 #>  [9,]  0.9344992 #> [10,]  1.0379067 #> [11,]  1.4997511 #> [12,]  1.4483534 #> [13,]  1.4354167 #> [14,]  1.4726645 #> [15,]  1.4793719 #> [16,]  1.3815510 #> [17,]  1.4866142 #> [18,]  1.4704943 #> [19,]  1.4921189 #> [20,]  1.4407625 #> [21,] -0.9572430 #> [22,] -1.4445116 #> [23,] -1.0534225 #> [24,] -0.9242549 #> [25,] -1.4975258 #> [26,] -1.5606818 #> [27,] -1.5086813 #> [28,] -1.4774908 #> [29,] -1.3085762 #> [30,] -1.4614487 #>  #> , , 110 #>  #>             [,1] #>  [1,]  0.6426889 #>  [2,]  0.4317715 #>  [3,]  0.6952832 #>  [4,]  0.7204052 #>  [5,]  0.8685803 #>  [6,]  0.3021760 #>  [7,]  0.2660660 #>  [8,]  0.5790419 #>  [9,]  0.9039257 #> [10,]  1.0064652 #> [11,]  1.4929411 #> [12,]  1.4467577 #> [13,]  1.4290980 #> [14,]  1.4757965 #> [15,]  1.4747095 #> [16,]  1.3725251 #> [17,]  1.4806106 #> [18,]  1.4698920 #> [19,]  1.4859561 #> [20,]  1.4382377 #> [21,] -1.0123867 #> [22,] -1.4952314 #> [23,] -1.1082826 #> [24,] -0.9824567 #> [25,] -1.5463286 #> [26,] -1.6113394 #> [27,] -1.5595168 #> [28,] -1.5291418 #> [29,] -1.3642954 #> [30,] -1.5126425 #>  #> , , 111 #>  #>             [,1] #>  [1,]  0.6075641 #>  [2,]  0.3880935 #>  [3,]  0.6525566 #>  [4,]  0.6795562 #>  [5,]  0.8309768 #>  [6,]  0.2492813 #>  [7,]  0.2147672 #>  [8,]  0.5370799 #>  [9,]  0.8724411 #> [10,]  0.9740363 #> [11,]  1.4854466 #> [12,]  1.4446339 #> [13,]  1.4221119 #> [14,]  1.4782811 #> [15,]  1.4693257 #> [16,]  1.3630318 #> [17,]  1.4741317 #> [18,]  1.4685900 #> [19,]  1.4792667 #> [20,]  1.4353745 #> [21,] -1.0667352 #> [22,] -1.5442803 #> [23,] -1.1621458 #> [24,] -1.0398725 #> [25,] -1.5933856 #> [26,] -1.6601088 #> [27,] -1.6085224 #> [28,] -1.5789870 #> [29,] -1.4185965 #> [30,] -1.5620775 #>  #> , , 112 #>  #>             [,1] #>  [1,]  0.5716005 #>  [2,]  0.3436276 #>  [3,]  0.6088877 #>  [4,]  0.6376059 #>  [5,]  0.7924402 #>  [6,]  0.1955045 #>  [7,]  0.1626518 #>  [8,]  0.4942800 #>  [9,]  0.8400592 #> [10,]  0.9406500 #> [11,]  1.4771873 #> [12,]  1.4422395 #> [13,]  1.4147075 #> [14,]  1.4805765 #> [15,]  1.4635216 #> [16,]  1.3530617 #> [17,]  1.4670297 #> [18,]  1.4669147 #> [19,]  1.4718467 #> [20,]  1.4319679 #> [21,] -1.1202276 #> [22,] -1.5915819 #> [23,] -1.2149454 #> [24,] -1.0964297 #> [25,] -1.6386253 #> [26,] -1.7069162 #> [27,] -1.6556234 #> [28,] -1.6269498 #> [29,] -1.4714024 #> [30,] -1.6096780 #>  #> , , 113 #>  #>             [,1] #>  [1,]  0.5348599 #>  [2,]  0.2983948 #>  [3,]  0.5642991 #>  [4,]  0.5947076 #>  [5,]  0.7526987 #>  [6,]  0.1408767 #>  [7,]  0.1097778 #>  [8,]  0.4506898 #>  [9,]  0.8068204 #> [10,]  0.9063981 #> [11,]  1.4684127 #> [12,]  1.4391924 #> [13,]  1.4067218 #> [14,]  1.4823450 #> [15,]  1.4571724 #> [16,]  1.3422983 #> [17,]  1.4592126 #> [18,]  1.4647730 #> [19,]  1.4640316 #> [20,]  1.4280196 #> [21,] -1.1728036 #> [22,] -1.6370618 #> [23,] -1.2666155 #> [24,] -1.1520303 #> [25,] -1.6819787 #> [26,] -1.7516906 #> [27,] -1.7007475 #> [28,] -1.6729562 #> [29,] -1.5226375 #> [30,] -1.6552889 #>  #> , , 114 #>  #>              [,1] #>  [1,]  0.49738792 #>  [2,]  0.25241779 #>  [3,]  0.51883977 #>  [4,]  0.55081050 #>  [5,]  0.71202228 #>  [6,]  0.08548755 #>  [7,]  0.05618297 #>  [8,]  0.40630967 #>  [9,]  0.77276386 #> [10,]  0.87125275 #> [11,]  1.45907797 #> [12,]  1.43577893 #> [13,]  1.39805185 #> [14,]  1.48375065 #> [15,]  1.45008739 #> [16,]  1.33091413 #> [17,]  1.45091579 #> [18,]  1.46201327 #> [19,]  1.45564449 #> [20,]  1.42373742 #> [21,] -1.22440315 #> [22,] -1.68064816 #> [23,] -1.31709122 #> [24,] -1.20660615 #> [25,] -1.72337922 #> [26,] -1.79436397 #> [27,] -1.74382520 #> [28,] -1.71693490 #> [29,] -1.57222803 #> [30,] -1.69886489 #>  #> , , 115 #>  #>               [,1] #>  [1,]  0.459194282 #>  [2,]  0.205721054 #>  [3,]  0.472552959 #>  [4,]  0.505962357 #>  [5,]  0.670466878 #>  [6,]  0.029378223 #>  [7,]  0.001908055 #>  [8,]  0.361076882 #>  [9,]  0.737951977 #> [10,]  0.835205995 #> [11,]  1.448852629 #> [12,]  1.431919077 #> [13,]  1.388961195 #> [14,]  1.484823529 #> [15,]  1.442578246 #> [16,]  1.319030936 #> [17,]  1.442023754 #> [18,]  1.458921396 #> [19,]  1.446586793 #> [20,]  1.418770999 #> [21,] -1.274967222 #> [22,] -1.722271325 #> [23,] -1.366277723 #> [24,] -1.260124380 #> [25,] -1.762762923 #> [26,] -1.834871006 #> [27,] -1.784790035 #> [28,] -1.758817351 #> [29,] -1.620102036 #> [30,] -1.740385169 #>  #> , , 116 #>  #>              [,1] #>  [1,]  0.42021653 #>  [2,]  0.15833102 #>  [3,]  0.42545400 #>  [4,]  0.46022369 #>  [5,]  0.62804128 #>  [6,] -0.02741463 #>  [7,] -0.05300332 #>  [8,]  0.31513390 #>  [9,]  0.70224497 #> [10,]  0.79818189 #> [11,]  1.43811049 #> [12,]  1.42747713 #> [13,]  1.37929567 #> [14,]  1.48536371 #> [15,]  1.43452167 #> [16,]  1.30654267 #> [17,]  1.43237517 #> [18,]  1.45524007 #> [19,]  1.43712173 #> [20,]  1.41336616 #> [21,] -1.32443619 #> [22,] -1.76186440 #> [23,] -1.41397297 #> [24,] -1.31252123 #> [25,] -1.80006856 #> [26,] -1.87314978 #> [27,] -1.82357851 #> [28,] -1.79853818 #> [29,] -1.66618965 #> [30,] -1.77978522 #>  #> , , 117 #>  #>              [,1] #>  [1,]  0.38044632 #>  [2,]  0.11026823 #>  [3,]  0.37748073 #>  [4,]  0.41361102 #>  [5,]  0.58475397 #>  [6,] -0.08485854 #>  [7,] -0.10855361 #>  [8,]  0.26850000 #>  [9,]  0.66568122 #> [10,]  0.76022892 #> [11,]  1.42685997 #> [12,]  1.42276475 #> [13,]  1.36892898 #> [14,]  1.48572156 #> [15,]  1.42572438 #> [16,]  1.29322714 #> [17,]  1.42223058 #> [18,]  1.45102776 #> [19,]  1.42702442 #> [20,]  1.40764583 #> [21,] -1.37259104 #> [22,] -1.79936326 #> [23,] -1.46025584 #> [24,] -1.36373384 #> [25,] -1.83523785 #> [26,] -1.90914169 #> [27,] -1.86013042 #> [28,] -1.83603523 #> [29,] -1.71042318 #> [30,] -1.81700362 #>  #> , , 118 #>  #>             [,1] #>  [1,]  0.3399385 #>  [2,]  0.0615377 #>  [3,]  0.3286426 #>  [4,]  0.3660836 #>  [5,]  0.5406108 #>  [6,] -0.1428912 #>  [7,] -0.1646440 #>  [8,]  0.2211600 #>  [9,]  0.6282890 #> [10,]  0.7214463 #> [11,]  1.4147097 #> [12,]  1.4174395 #> [13,]  1.3581395 #> [14,]  1.4854338 #> [15,]  1.4164998 #> [16,]  1.2794208 #> [17,]  1.4115255 #> [18,]  1.4464942 #> [19,]  1.4163241 #> [20,]  1.4011174 #> [21,] -1.4194255 #> [22,] -1.8347067 #> [23,] -1.5050773 #> [24,] -1.4137003 #> [25,] -1.8682156 #> [26,] -1.9427917 #> [27,] -1.8943890 #> [28,] -1.8712498 #> [29,] -1.7527373 #> [30,] -1.8519822 #>  #> , , 119 #>  #>             [,1] #>  [1,]  0.2987325 #>  [2,]  0.0121542 #>  [3,]  0.2789877 #>  [4,]  0.3176160 #>  [5,]  0.4952932 #>  [6,] -0.2014403 #>  [7,] -0.2212056 #>  [8,]  0.1731223 #>  [9,]  0.5901087 #> [10,]  0.6818006 #> [11,]  1.4019737 #> [12,]  1.4116807 #> [13,]  1.3467817 #> [14,]  1.4849011 #> [15,]  1.4067215 #> [16,]  1.2651396 #> [17,]  1.4000275 #> [18,]  1.4412698 #> [19,]  1.4052100 #> [20,]  1.3942350 #> [21,] -1.4649664 #> [22,] -1.8677878 #> [23,] -1.5483806 #> [24,] -1.4622260 #> [25,] -1.8989498 #> [26,] -1.9740483 #> [27,] -1.9263011 #> [28,] -1.9041266 #> [29,] -1.7930692 #> [30,] -1.8846661 #>  #> , , 120 #>  #>              [,1] #>  [1,]  0.25687096 #>  [2,] -0.03782558 #>  [3,]  0.22857737 #>  [4,]  0.26834624 #>  [5,]  0.44915240 #>  [6,] -0.26044795 #>  [7,] -0.27818063 #>  [8,]  0.12445608 #>  [9,]  0.55120853 #> [10,]  0.64127404 #> [11,]  1.38870315 #> [12,]  1.40557759 #> [13,]  1.33470564 #> [14,]  1.48387207 #> [15,]  1.39619787 #> [16,]  1.24990707 #> [17,]  1.38800498 #> [18,]  1.43560796 #> [19,]  1.39339644 #> [20,]  1.38696958 #> [21,] -1.50916498 #> [22,] -1.89856007 #> [23,] -1.59010940 #> [24,] -1.50936363 #> [25,] -1.92727883 #> [26,] -2.00281076 #> [27,] -1.95581742 #> [28,] -1.93461440 #> [29,] -1.83135858 #> [30,] -1.91500441 #>  #> , , 121 #>  #>              [,1] #>  [1,]  0.21438530 #>  [2,] -0.08831279 #>  [3,]  0.17746558 #>  [4,]  0.21823542 #>  [5,]  0.40221674 #>  [6,] -0.31985316 #>  [7,] -0.33550788 #>  [8,]  0.07512554 #>  [9,]  0.51145568 #> [10,]  0.59980731 #> [11,]  1.37470893 #> [12,]  1.39881326 #> [13,]  1.32220507 #> [14,]  1.48243122 #> [15,]  1.38524357 #> [16,]  1.23416191 #> [17,]  1.37545152 #> [18,]  1.42958489 #> [19,]  1.38104577 #> [20,]  1.37895234 #> [21,] -1.55196856 #> [22,] -1.92700944 #> [23,] -1.63020933 #> [24,] -1.55506331 #> [25,] -1.95322611 #> [26,] -2.02906825 #> [27,] -1.98289244 #> [28,] -1.96266568 #> [29,] -1.86754821 #> [30,] -1.94294958 #>  #> , , 122 #>  #>              [,1] #>  [1,]  0.17123761 #>  [2,] -0.13926584 #>  [3,]  0.12568680 #>  [4,]  0.16733457 #>  [5,]  0.35450308 #>  [6,] -0.37959127 #>  [7,] -0.39312282 #>  [8,]  0.02519439 #>  [9,]  0.47091233 #> [10,]  0.55746730 #> [11,]  1.35993823 #> [12,]  1.39176054 #> [13,]  1.30914291 #> [14,]  1.48071581 #> [15,]  1.37372947 #> [16,]  1.21791305 #> [17,]  1.36208222 #> [18,]  1.42282914 #> [19,]  1.36827983 #> [20,]  1.37059381 #> [21,] -1.59332566 #> [22,] -1.95308877 #> [23,] -1.66862775 #> [24,] -1.59926847 #> [25,] -1.97678651 #> [26,] -2.05279859 #> [27,] -2.00748486 #> [28,] -1.98823710 #> [29,] -1.90158364 #> [30,] -1.96845821 #>  #> , , 123 #>  #>              [,1] #>  [1,]  0.12742734 #>  [2,] -0.19064065 #>  [3,]  0.07326382 #>  [4,]  0.11571861 #>  [5,]  0.30602947 #>  [6,] -0.43960179 #>  [7,] -0.45095744 #>  [8,] -0.02525649 #>  [9,]  0.42959745 #> [10,]  0.51435843 #> [11,]  1.34462749 #> [12,]  1.38414468 #> [13,]  1.29534533 #> [14,]  1.47840011 #> [15,]  1.36146563 #> [16,]  1.20091948 #> [17,]  1.34815332 #> [18,]  1.41572041 #> [19,]  1.35474461 #> [20,]  1.36172597 #> [21,] -1.63318619 #> [22,] -1.97675482 #> [23,] -1.70531398 #> [24,] -1.64192406 #> [25,] -1.99792695 #> [26,] -2.07396885 #> [27,] -2.02955761 #> [28,] -2.01128957 #> [29,] -1.93341358 #> [30,] -1.99149093 #>  #> , , 124 #>  #>              [,1] #>  [1,]  0.08303796 #>  [2,] -0.24239061 #>  [3,]  0.02010767 #>  [4,]  0.06342015 #>  [5,]  0.25679882 #>  [6,] -0.49980406 #>  [7,] -0.50894020 #>  [8,] -0.07619536 #>  [9,]  0.38755287 #> [10,]  0.47044621 #> [11,]  1.32871697 #> [12,]  1.37603657 #> [13,]  1.28112190 #> [14,]  1.47589098 #> [15,]  1.34876754 #> [16,]  1.18321892 #> [17,]  1.33369390 #> [18,]  1.40809474 #> [19,]  1.34073649 #> [20,]  1.35223657 #> [21,] -1.67150151 #> [22,] -1.99796834 #> [23,] -1.74021943 #> [24,] -1.68297660 #> [25,] -2.01661493 #> [26,] -2.09254903 #> [27,] -2.04907805 #> [28,] -2.03178842 #> [29,] -1.96299000 #> [30,] -2.01201259 #>  #> , , 125 #>  #>              [,1] #>  [1,]  0.03809124 #>  [2,] -0.29446652 #>  [3,] -0.03362766 #>  [4,]  0.01041291 #>  [5,]  0.20658443 #>  [6,] -0.56010342 #>  [7,] -0.56699509 #>  [8,] -0.12761010 #>  [9,]  0.34485162 #> [10,]  0.42570640 #> [11,]  1.31191183 #> [12,]  1.36765531 #> [13,]  1.26634389 #> [14,]  1.47274207 #> [15,]  1.33550384 #> [16,]  1.16500986 #> [17,]  1.31845557 #> [18,]  1.39987439 #> [19,]  1.32631649 #> [20,]  1.34239655 #> [21,] -1.70822454 #> [22,] -2.01669422 #> [23,] -1.77329768 #> [24,] -1.72235871 #> [25,] -2.03282213 #> [26,] -2.10851376 #> [27,] -2.06601807 #> [28,] -2.04970355 #> [29,] -1.99026829 #> [30,] -2.02999243 #>  #> , , 126 #>  #>               [,1] #>  [1,] -0.007370704 #>  [2,] -0.346817704 #>  [3,] -0.087925892 #>  [4,] -0.043257036 #>  [5,]  0.155684466 #>  [6,] -0.620419106 #>  [7,] -0.625039061 #>  [8,] -0.179479537 #>  [9,]  0.301376212 #> [10,]  0.380100940 #> [11,]  1.294566861 #> [12,]  1.358566699 #> [13,]  1.250813423 #> [14,]  1.469298460 #> [15,]  1.321486458 #> [16,]  1.146243344 #> [17,]  1.302601730 #> [18,]  1.391314601 #> [19,]  1.311055059 #> [20,]  1.331909081 #> [21,] -1.743309827 #> [22,] -2.032901677 #> [23,] -1.804504597 #> [24,] -1.759978586 #> [25,] -2.046524562 #> [26,] -2.121842470 #> [27,] -2.080354285 #> [28,] -2.065009568 #> [29,] -2.015207373 #> [30,] -2.045404201 #>  #> , , 127 #>  #>              [,1] #>  [1,] -0.05329729 #>  [2,] -0.39939321 #>  [3,] -0.14272732 #>  [4,] -0.09748145 #>  [5,]  0.10413495 #>  [6,] -0.68066666 #>  [7,] -0.68297585 #>  [8,] -0.23172050 #>  [9,]  0.25720446 #> [10,]  0.33371359 #> [11,]  1.27669248 #> [12,]  1.34915161 #> [13,]  1.23485622 #> [14,]  1.46542848 #> [15,]  1.30703105 #> [16,]  1.12655070 #> [17,]  1.28623206 #> [18,]  1.38208747 #> [19,]  1.29538311 #> [20,]  1.32092390 #> [21,] -1.77664912 #> [22,] -2.04656439 #> [23,] -1.83379842 #> [24,] -1.79577363 #> [25,] -2.05770265 #> [26,] -2.13251948 #> [27,] -2.09206812 #> [28,] -2.07768594 #> [29,] -2.03776989 #> [30,] -2.05822632 #>  #> , , 128 #>  #>              [,1] #>  [1,] -0.09969533 #>  [2,] -0.45213747 #>  [3,] -0.19796897 #>  [4,] -0.15224958 #>  [5,]  0.05196657 #>  [6,] -0.74075793 #>  [7,] -0.74069424 #>  [8,] -0.28434899 #>  [9,]  0.21236184 #> [10,]  0.28665020 #> [11,]  1.25787359 #> [12,]  1.33925014 #> [13,]  1.21835184 #> [14,]  1.46108174 #> [15,]  1.29200456 #> [16,]  1.10635998 #> [17,]  1.26910315 #> [18,]  1.37236990 #> [19,]  1.27926090 #> [20,]  1.30959742 #> [21,] -1.80801101 #> [22,] -2.05766061 #> [23,] -1.86113989 #> [24,] -1.82976306 #> [25,] -2.06634138 #> [26,] -2.14053415 #> [27,] -2.10114597 #> [28,] -2.08771711 #> [29,] -2.05792232 #> [30,] -2.06844197 #>  #> , , 129 #>  #>                [,1] #>  [1,] -0.1465465842 #>  [2,] -0.5049631790 #>  [3,] -0.2536103218 #>  [4,] -0.2075074744 #>  [5,] -0.0007917271 #>  [6,] -0.8005929384 #>  [7,] -0.7981110203 #>  [8,] -0.3372457096 #>  [9,]  0.1668883910 #> [10,]  0.2388813169 #> [11,]  1.2384669381 #> [12,]  1.3287951291 #> [13,]  1.2010782862 #> [14,]  1.4565088611 #> [15,]  1.2762210208 #> [16,]  1.0856773792 #> [17,]  1.2513084510 #> [18,]  1.3623297753 #> [19,]  1.2623165639 #> [20,]  1.2974732793 #> [21,] -1.8375409034 #> [22,] -2.0661733475 #> [23,] -1.8864804921 #> [24,] -1.8619032623 #> [25,] -2.0724304278 #> [26,] -2.1458809654 #> [27,] -2.1075793070 #> [28,] -2.0950926455 #> [29,] -2.0756285029 #> [30,] -2.0760392713 #>  #> , , 130 #>  #>              [,1] #>  [1,] -0.19375628 #>  [2,] -0.55779194 #>  [3,] -0.30964917 #>  [4,] -0.26318100 #>  [5,] -0.05414077 #>  [6,] -0.86006434 #>  [7,] -0.85513118 #>  [8,] -0.39036314 #>  [9,]  0.12085300 #> [10,]  0.19038182 #> [11,]  1.21850420 #> [12,]  1.31806741 #> [13,]  1.18337773 #> [14,]  1.45125031 #> [15,]  1.25999558 #> [16,]  1.06410171 #> [17,]  1.23300118 #> [18,]  1.35151766 #> [19,]  1.24497546 #> [20,]  1.28496608 #> [21,] -1.86524636 #> [22,] -2.07209046 #> [23,] -1.90955155 #> [24,] -1.89210590 #> [25,] -2.07596424 #> [26,] -2.14855967 #> [27,] -2.11136479 #> [28,] -2.09980732 #> [29,] -2.09082997 #> [30,] -2.08094432 #>  #> , , 131 #>  #>              [,1] #>  [1,] -0.24130205 #>  [2,] -0.61055581 #>  [3,] -0.36600350 #>  [4,] -0.31921324 #>  [5,] -0.10816042 #>  [6,] -0.91906973 #>  [7,] -0.91165633 #>  [8,] -0.44365488 #>  [9,]  0.07416851 #> [10,]  0.14113996 #> [11,]  1.19778169 #> [12,]  1.30667377 #> [13,]  1.16513792 #> [14,]  1.44578732 #> [15,]  1.24319410 #> [16,]  1.04193984 #> [17,]  1.21396191 #> [18,]  1.34031147 #> [19,]  1.22714178 #> [20,]  1.27209349 #> [21,] -1.89110072 #> [22,] -2.07540478 #> [23,] -1.93050880 #> [24,] -1.92022120 #> [25,] -2.07694215 #> [26,] -2.14857532 #> [27,] -2.11250435 #> [28,] -2.10186124 #> [29,] -2.10353833 #> [30,] -2.08311747 #>  #> , , 132 #>  #>              [,1] #>  [1,] -0.28913755 #>  [2,] -0.66318403 #>  [3,] -0.42260688 #>  [4,] -0.37558118 #>  [5,] -0.16265606 #>  [6,] -0.97751333 #>  [7,] -0.96758479 #>  [8,] -0.49707192 #>  [9,]  0.02692347 #> [10,]  0.09125223 #> [11,]  1.17627782 #> [12,]  1.29488628 #> [13,]  1.14611291 #> [14,]  1.43972418 #> [15,]  1.22563299 #> [16,]  1.01925900 #> [17,]  1.19421282 #> [18,]  1.32869848 #> [19,]  1.20852157 #> [20,]  1.25837074 #> [21,] -1.91507175 #> [22,] -2.07611424 #> [23,] -1.94937198 #> [24,] -1.94636241 #> [25,] -2.07536847 #> [26,] -2.14593839 #> [27,] -2.11100530 #> [28,] -2.10125992 #> [29,] -2.11374299 #> [30,] -2.08266869 #>  #> , , 133 #>  #>              [,1] #>  [1,] -0.33720192 #>  [2,] -0.71560312 #>  [3,] -0.47939597 #>  [4,] -0.43219426 #>  [5,] -0.21757378 #>  [6,] -1.03528834 #>  [7,] -1.02281165 #>  [8,] -0.55056003 #>  [9,] -0.02084724 #> [10,]  0.04081319 #> [11,]  1.15421255 #> [12,]  1.28271766 #> [13,]  1.12666140 #> [14,]  1.43331269 #> [15,]  1.20762617 #> [16,]  0.99589193 #> [17,]  1.17394286 #> [18,]  1.31635979 #> [19,]  1.18950743 #> [20,]  1.24431083 #> [21,] -1.93712944 #> [22,] -2.07422199 #> [23,] -1.96612178 #> [24,] -1.97049628 #> [25,] -2.07125254 #> [26,] -2.14066484 #> [27,] -2.10688042 #> [28,] -2.09801441 #> [29,] -2.12143178 #> [30,] -2.07960798 #>  #> , , 134 #>  #>              [,1] #>  [1,] -0.38546532 #>  [2,] -0.76773683 #>  [3,] -0.53630569 #>  [4,] -0.48896983 #>  [5,] -0.27286719 #>  [6,] -1.09225106 #>  [7,] -1.07722893 #>  [8,] -0.60404746 #>  [9,] -0.06910386 #> [10,] -0.01018369 #> [11,]  1.13151199 #> [12,]  1.26991744 #> [13,]  1.10667928 #> [14,]  1.42653416 #> [15,]  1.18903906 #> [16,]  0.97173679 #> [17,]  1.15297615 #> [18,]  1.30366886 #> [19,]  1.16996127 #> [20,]  1.22977765 #> [21,] -1.95724620 #> [22,] -2.06973644 #> [23,] -1.98073755 #> [24,] -1.99259218 #> [25,] -2.06460885 #> [26,] -2.13277615 #> [27,] -2.10014799 #> [28,] -2.09212603 #> [29,] -2.12657009 #> [30,] -2.07395077 #>  #> , , 135 #>  #>              [,1] #>  [1,] -0.43387636 #>  [2,] -0.81950538 #>  [3,] -0.59327540 #>  [4,] -0.54584537 #>  [5,] -0.32849424 #>  [6,] -1.14823516 #>  [7,] -1.13072569 #>  [8,] -0.65745140 #>  [9,] -0.11778336 #> [10,] -0.06174371 #> [11,]  1.10792395 #> [12,]  1.25682814 #> [13,]  1.08589703 #> [14,]  1.41921153 #> [15,]  1.16969082 #> [16,]  0.94707061 #> [17,]  1.13126258 #> [18,]  1.29041230 #> [19,]  1.14966761 #> [20,]  1.21453708 #> [21,] -1.97539686 #> [22,] -2.06267138 #> [23,] -1.99320188 #> [24,] -2.01262218 #> [25,] -2.05545709 #> [26,] -2.12229939 #> [27,] -2.09083185 #> [28,] -2.08356194 #> [29,] -2.12912805 #> [30,] -2.06571793 #>  #> , , 136 #>  #>             [,1] #>  [1,] -0.4823588 #>  [2,] -0.8708191 #>  [3,] -0.6502438 #>  [4,] -0.6027491 #>  [5,] -0.3844331 #>  [6,] -1.2031807 #>  [7,] -1.1831882 #>  [8,] -0.7107120 #>  [9,] -0.1669302 #> [10,] -0.1138739 #> [11,]  1.0837802 #> [12,]  1.2431239 #> [13,]  1.0646898 #> [14,]  1.4116934 #> [15,]  1.1498933 #> [16,]  0.9218905 #> [17,]  1.1090083 #> [18,]  1.2765842 #> [19,]  1.1289786 #> [20,]  1.1989356 #> [21,] -1.9915588 #> [22,] -2.0530461 #> [23,] -2.0035007 #> [24,] -2.0305611 #> [25,] -2.0438222 #> [26,] -2.1092673 #> [27,] -2.0789615 #> [28,] -2.0724228 #> [29,] -2.1291620 #> [30,] -2.0549358 #>  #> , , 137 #>  #>             [,1] #>  [1,] -0.5308597 #>  [2,] -0.9215122 #>  [3,] -0.7071176 #>  [4,] -0.6596049 #>  [5,] -0.4406417 #>  [6,] -1.2569672 #>  [7,] -1.2345000 #>  [8,] -0.7637673 #>  [9,] -0.2164523 #> [10,] -0.1664612 #> [11,]  1.0590854 #> [12,]  1.2289671 #> [13,]  1.0429615 #> [14,]  1.4034154 #> [15,]  1.1295122 #> [16,]  0.8957428 #> [17,]  1.0861010 #> [18,]  1.2624132 #> [19,]  1.1077213 #> [20,]  1.1827268 #> [21,] -2.0057119 #> [22,] -2.0408853 #> [23,] -2.0116231 #> [24,] -2.0463868 #> [25,] -2.0296582 #> [26,] -2.0937180 #> [27,] -2.0645720 #> [28,] -2.0587429 #> [29,] -2.1266790 #> [30,] -2.0416365 #>  #> , , 138 #>  #>             [,1] #>  [1,] -0.5793238 #>  [2,] -0.9714864 #>  [3,] -0.7638277 #>  [4,] -0.7163408 #>  [5,] -0.4970072 #>  [6,] -1.3094717 #>  [7,] -1.2844010 #>  [8,] -0.8165469 #>  [9,] -0.2663044 #> [10,] -0.2194247 #> [11,]  1.0334300 #> [12,]  1.2145269 #> [13,]  1.0204199 #> [14,]  1.3949171 #> [15,]  1.1083699 #> [16,]  0.8690954 #> [17,]  1.0623939 #> [18,]  1.2475025 #> [19,]  1.0857592 #> [20,]  1.1659470 #> [21,] -2.0176357 #> [22,] -2.0262193 #> [23,] -2.0175620 #> [24,] -2.0600600 #> [25,] -2.0130116 #> [26,] -2.0756957 #> [27,] -2.0476874 #> [28,] -2.0425622 #> [29,] -2.1216912 #> [30,] -2.0258572 #>  #> , , 139 #>  #>             [,1] #>  [1,] -0.6276949 #>  [2,] -1.0207039 #>  [3,] -0.8202811 #>  [4,] -0.7728367 #>  [5,] -0.5534673 #>  [6,] -1.3605687 #>  [7,] -1.3328543 #>  [8,] -0.8689678 #>  [9,] -0.3164444 #> [10,] -0.2727467 #> [11,]  1.0071903 #> [12,]  1.1993529 #> [13,]  0.9974559 #> [14,]  1.3858945 #> [15,]  1.0867753 #> [16,]  0.8419454 #> [17,]  1.0381365 #> [18,]  1.2321411 #> [19,]  1.0633961 #> [20,]  1.1488018 #> [21,] -2.0273199 #> [22,] -2.0090840 #> [23,] -2.0213136 #> [24,] -2.0715174 #> [25,] -1.9939797 #> [26,] -2.0552497 #> [27,] -2.0283298 #> [28,] -2.0239264 #> [29,] -2.1142157 #> [30,] -2.0076413 #>  #> , , 140 #>  #>             [,1] #>  [1,] -0.6759033 #>  [2,] -1.0690710 #>  [3,] -0.8764094 #>  [4,] -0.8290138 #>  [5,] -0.6099629 #>  [6,] -1.4101308 #>  [7,] -1.3797189 #>  [8,] -0.9209374 #>  [9,] -0.3668157 #> [10,] -0.3264091 #> [11,]  0.9803831 #> [12,]  1.1838826 #> [13,]  0.9739819 #> [14,]  1.3764582 #> [15,]  1.0645951 #> [16,]  0.8139846 #> [17,]  1.0133065 #> [18,]  1.2164593 #> [19,]  1.0404322 #> [20,]  1.1309043 #> [21,] -2.0349157 #> [22,] -1.9895210 #> [23,] -2.0228777 #> [24,] -2.0807267 #> [25,] -1.9726255 #> [26,] -2.0324353 #> [27,] -2.0065840 #> [28,] -2.0028868 #> [29,] -2.1042746 #> [30,] -1.9870372 #>  #> , , 141 #>  #>             [,1] #>  [1,] -0.7238474 #>  [2,] -1.1164919 #>  [3,] -0.9321512 #>  [4,] -0.8848024 #>  [5,] -0.6664376 #>  [6,] -1.4580286 #>  [7,] -1.4248394 #>  [8,] -0.9723236 #>  [9,] -0.4174071 #> [10,] -0.3803909 #> [11,]  0.9527970 #> [12,]  1.1678904 #> [13,]  0.9496833 #> [14,]  1.3667037 #> [15,]  1.0416556 #> [16,]  0.7853805 #> [17,]  0.9875856 #> [18,]  1.1999224 #> [19,]  1.0168099 #> [20,]  1.1125653 #> [21,] -2.0404448 #> [22,] -1.9675773 #> [23,] -2.0222578 #> [24,] -2.0877632 #> [25,] -1.9490016 #> [26,] -2.0073130 #> [27,] -1.9825199 #> [28,] -1.9795007 #> [29,] -2.0918950 #> [30,] -1.9640992 #>  #> , , 142 #>  #>             [,1] #>  [1,] -0.7714949 #>  [2,] -1.1628690 #>  [3,] -0.9874332 #>  [4,] -0.9400943 #>  [5,] -0.7228094 #>  [6,] -1.5040940 #>  [7,] -1.4681220 #>  [8,] -1.0230705 #>  [9,] -0.4681338 #> [10,] -0.4345825 #> [11,]  0.9244461 #> [12,]  1.1513784 #> [13,]  0.9249646 #> [14,]  1.3563155 #> [15,]  1.0182615 #> [16,]  0.7562668 #> [17,]  0.9613240 #> [18,]  1.1830371 #> [19,]  0.9927751 #> [20,]  1.0938552 #> [21,] -2.0439073 #> [22,] -1.9433057 #> [23,] -2.0194611 #> [24,] -2.0925018 #> [25,] -1.9231660 #> [26,] -1.9799490 #> [27,] -1.9562012 #> [28,] -1.9538306 #> [29,] -2.0771092 #> [30,] -1.9388869 #>  #> , , 143 #>  #>             [,1] #>  [1,] -0.8187582 #>  [2,] -1.2081025 #>  [3,] -1.0420654 #>  [4,] -0.9947846 #>  [5,] -0.7789685 #>  [6,] -1.5481235 #>  [7,] -1.5094591 #>  [8,] -1.0731351 #>  [9,] -0.5189394 #> [10,] -0.4889184 #> [11,]  0.8955275 #> [12,]  1.1345948 #> [13,]  0.8997441 #> [14,]  1.3457192 #> [15,]  0.9942815 #> [16,]  0.7265480 #> [17,]  0.9345254 #> [18,]  1.1657018 #> [19,]  0.9681003 #> [20,]  1.0742796 #> [21,] -2.0453025 #> [22,] -1.9167646 #> [23,] -2.0144980 #> [24,] -2.0949533 #> [25,] -1.8951817 #> [26,] -1.9504149 #> [27,] -1.9276970 #> [28,] -1.9259449 #> [29,] -2.0599546 #> [30,] -1.9114654 #>  #> , , 144 #>  #>             [,1] #>  [1,] -0.8655628 #>  [2,] -1.2520909 #>  [3,] -1.0960100 #>  [4,] -1.0487865 #>  [5,] -0.8348450 #>  [6,] -1.5900486 #>  [7,] -1.5487221 #>  [8,] -1.1224399 #>  [9,] -0.5697770 #> [10,] -0.5433572 #> [11,]  0.8659571 #> [12,]  1.1170966 #> [13,]  0.8737019 #> [14,]  1.3344139 #> [15,]  0.9695464 #> [16,]  0.6959922 #> [17,]  0.9068508 #> [18,]  1.1476554 #> [19,]  0.9428341 #> [20,]  1.0543637 #> [21,] -2.0446324 #> [22,] -1.8880178 #> [23,] -2.0071823 #> [24,] -2.0952255 #> [25,] -1.8651170 #> [26,] -1.9187874 #> [27,] -1.8970818 #> [28,] -1.8959173 #> [29,] -2.0404737 #> [30,] -1.8819052 #>  #> , , 145 #>  #>             [,1] #>  [1,] -0.9118493 #>  [2,] -1.2947188 #>  [3,] -1.1491579 #>  [4,] -1.1020332 #>  [5,] -0.8903781 #>  [6,] -1.6296854 #>  [7,] -1.5857823 #>  [8,] -1.1708848 #>  [9,] -0.6205959 #> [10,] -0.5978546 #> [11,]  0.8355373 #> [12,]  1.0992477 #> [13,]  0.8472428 #> [14,]  1.3228304 #> [15,]  0.9443556 #> [16,]  0.6649472 #> [17,]  0.8785966 #> [18,]  1.1292560 #> [19,]  0.9171493 #> [20,]  1.0339873 #> [21,] -2.0419026 #> [22,] -1.8571346 #> [23,] -1.9976233 #> [24,] -2.0933237 #> [25,] -1.8330453 #> [26,] -1.8851484 #> [27,] -1.8644352 #> [28,] -1.8638267 #> [29,] -2.0187140 #> [30,] -1.8502820 #>  #> , , 146 #>  #>             [,1] #>  [1,] -0.9575241 #>  [2,] -1.3357051 #>  [3,] -1.2014145 #>  [4,] -1.1542516 #>  [5,] -0.9455049 #>  [6,] -1.6667623 #>  [7,] -1.6205112 #>  [8,] -1.2183506 #>  [9,] -0.6713161 #> [10,] -0.6523312 #> [11,]  0.8045674 #> [12,]  1.0809853 #> [13,]  0.8202878 #> [14,]  1.3107811 #> [15,]  0.9185808 #> [16,]  0.6334359 #> [17,]  0.8498248 #> [18,]  1.1102470 #> [19,]  0.8907721 #> [20,]  1.0128308 #> [21,] -2.0371213 #> [22,] -1.8241899 #> [23,] -1.9859567 #> [24,] -2.0892572 #> [25,] -1.7990448 #> [26,] -1.8495850 #> [27,] -1.8298422 #> [28,] -1.8297575 #> [29,] -1.9947283 #> [30,] -1.8166767 #>  #> , , 147 #>  #>             [,1] #>  [1,] -1.0024173 #>  [2,] -1.3748921 #>  [3,] -1.2527110 #>  [4,] -1.2054619 #>  [5,] -1.0001548 #>  [6,] -1.7013227 #>  [7,] -1.6527805 #>  [8,] -1.2647033 #>  [9,] -0.7218752 #> [10,] -0.7067084 #> [11,]  0.7730322 #> [12,]  1.0621282 #> [13,]  0.7925188 #> [14,]  1.2982508 #> [15,]  0.8920581 #> [16,]  0.6010151 #> [17,]  0.8202153 #> [18,]  1.0906870 #> [19,]  0.8638774 #> [20,]  0.9913148 #> [21,] -2.0303002 #> [22,] -1.7892401 #> [23,] -1.9722170 #> [24,] -2.0830383 #> [25,] -1.7631987 #> [26,] -1.8121889 #> [27,] -1.7933925 #> [28,] -1.7937991 #> [29,] -1.9685742 #> [30,] -1.7811574 #>  #> , , 148 #>  #>             [,1] #>  [1,] -1.0465626 #>  [2,] -1.4123560 #>  [3,] -1.3029871 #>  [4,] -1.2555859 #>  [5,] -1.0541381 #>  [6,] -1.7332340 #>  [7,] -1.6823444 #>  [8,] -1.3096929 #>  [9,] -0.7722053 #> [10,] -0.7609383 #> [11,]  0.7405902 #> [12,]  1.0429857 #> [13,]  0.7643380 #> [14,]  1.2854538 #> [15,]  0.8650802 #> [16,]  0.5681019 #> [17,]  0.7899912 #> [18,]  1.0707833 #> [19,]  0.8365672 #> [20,]  0.9692374 #> [21,] -2.0213673 #> [22,] -1.7523504 #> [23,] -1.9564363 #> [24,] -2.0746832 #> [25,] -1.7255949 #> [26,] -1.7730566 #> [27,] -1.7551807 #> [28,] -1.7560457 #> [29,] -1.9403145 #> [30,] -1.7437403 #>  #> , , 149 #>  #>             [,1] #>  [1,] -1.0898578 #>  [2,] -1.4479905 #>  [3,] -1.3520557 #>  [4,] -1.3044848 #>  [5,] -1.1073639 #>  [6,] -1.7623650 #>  [7,] -1.7089695 #>  [8,] -1.3534398 #>  [9,] -0.8222516 #> [10,] -0.8149576 #> [11,]  0.7075828 #> [12,]  1.0231831 #> [13,]  0.7356697 #> [14,]  1.2719108 #> [15,]  0.8375227 #> [16,]  0.5347090 #> [17,]  0.7592594 #> [18,]  1.0500971 #> [19,]  0.8085090 #> [20,]  0.9465210 #> [21,] -2.0102610 #> [22,] -1.7136624 #> [23,] -1.9386505 #> [24,] -2.0642118 #> [25,] -1.6863256 #> [26,] -1.7322892 #> [27,] -1.7153059 #> [28,] -1.7165962 #> [29,] -1.9100168 #> [30,] -1.7046276 #>  #> , , 150 #>  #>             [,1] #>  [1,] -1.1321927 #>  [2,] -1.4816880 #>  [3,] -1.3997102 #>  [4,] -1.3520112 #>  [5,] -1.1597504 #>  [6,] -1.7885863 #>  [7,] -1.7327263 #>  [8,] -1.3958569 #>  [9,] -0.8719687 #> [10,] -0.8686958 #> [11,]  0.6740241 #> [12,]  1.0029735 #> [13,]  0.7061998 #> [14,]  1.2581568 #> [15,]  0.8092282 #> [16,]  0.5006323 #> [17,]  0.7277390 #> [18,]  1.0289983 #> [19,]  0.7800058 #> [20,]  0.9234279 #> [21,] -1.9970370 #> [22,] -1.6732721 #> [23,] -1.9188993 #> [24,] -2.0516474 #> [25,] -1.6454878 #> [26,] -1.6899917 #> [27,] -1.6738717 #> [28,] -1.6755541 #> [29,] -1.8777535 #> [30,] -1.6639201 #>  #> , , 151 #>  #>             [,1] #>  [1,] -1.1734780 #>  [2,] -1.5133409 #>  [3,] -1.4460165 #>  [4,] -1.3980498 #>  [5,] -1.2112457 #>  [6,] -1.8117707 #>  [7,] -1.7534945 #>  [8,] -1.4368559 #>  [9,] -0.9211953 #> [10,] -0.9219761 #> [11,]  0.6397057 #> [12,]  0.9824511 #> [13,]  0.6763256 #> [14,]  1.2437763 #> [15,]  0.7804812 #> [16,]  0.4659061 #> [17,]  0.6955805 #> [18,]  1.0075474 #> [19,]  0.7510841 #> [20,]  0.8996447 #> [21,] -1.9818424 #> [22,] -1.6312798 #> [23,] -1.8972263 #> [24,] -2.0370022 #> [25,] -1.6031823 #> [26,] -1.6462735 #> [27,] -1.6309859 #> [28,] -1.6330271 #> [29,] -1.8436019 #> [30,] -1.6217232 #>  #> , , 152 #>  #>             [,1] #>  [1,] -1.2136319 #>  [2,] -1.5428424 #>  [3,] -1.4907429 #>  [4,] -1.4425614 #>  [5,] -1.2617992 #>  [6,] -1.8317943 #>  [7,] -1.7711571 #>  [8,] -1.4763095 #>  [9,] -0.9699100 #> [10,] -0.9747879 #> [11,]  0.6046937 #> [12,]  0.9612298 #> [13,]  0.6459753 #> [14,]  1.2290528 #> [15,]  0.7511621 #> [16,]  0.4307222 #> [17,]  0.6629162 #> [18,]  0.9852384 #> [19,]  0.7213873 #> [20,]  0.8753661 #> [21,] -1.9647316 #> [22,] -1.5877908 #> [23,] -1.8736790 #> [24,] -2.0202547 #> [25,] -1.5595140 #> [26,] -1.6012475 #> [27,] -1.5867599 #> [28,] -1.5891269 #> [29,] -1.8076436 #> [30,] -1.5781459 #>  #> , , 153 #>  #>             [,1] #>  [1,] -1.2523986 #>  [2,] -1.5700859 #>  [3,] -1.5338172 #>  [4,] -1.4850994 #>  [5,] -1.3113283 #>  [6,] -1.8485361 #>  [7,] -1.7856006 #>  [8,] -1.5140514 #>  [9,] -1.0180344 #> [10,] -1.0271020 #> [11,]  0.5691466 #> [12,]  0.9397219 #> [13,]  0.6148415 #> [14,]  1.2139137 #> [15,]  0.7211213 #> [16,]  0.3950454 #> [17,]  0.6295230 #> [18,]  0.9625964 #> [19,]  0.6913034 #> [20,]  0.8507145 #> [21,] -1.9457383 #> [22,] -1.5429142 #> [23,] -1.8483086 #> [24,] -2.0014341 #> [25,] -1.5145918 #> [26,] -1.5550300 #> [27,] -1.5413090 #> [28,] -1.5439688 #> [29,] -1.7699650 #> [30,] -1.5333013 #>  #> , , 154 #>  #>             [,1] #>  [1,] -1.2899019 #>  [2,] -1.5949514 #>  [3,] -1.5752392 #>  [4,] -1.5258605 #>  [5,] -1.3594828 #>  [6,] -1.8618732 #>  [7,] -1.7967129 #>  [8,] -1.5498046 #>  [9,] -1.0655027 #> [10,] -1.0788373 #> [11,]  0.5329726 #> [12,]  0.9176679 #> [13,]  0.5833138 #> [14,]  1.1982024 #> [15,]  0.6906332 #> [16,]  0.3585817 #> [17,]  0.5954544 #> [18,]  0.9394710 #> [19,]  0.6607685 #> [20,]  0.8252341 #> [21,] -1.9248995 #> [22,] -1.4967634 #> [23,] -1.8211698 #> [24,] -1.9804954 #> [25,] -1.4685101 #> [26,] -1.5077407 #> [27,] -1.4947516 #> [28,] -1.4976719 #> [29,] -1.7306566 #> [30,] -1.4873057 #>  #> , , 155 #>  #>             [,1] #>  [1,] -1.3260542 #>  [2,] -1.6171267 #>  [3,] -1.6149140 #>  [4,] -1.5647401 #>  [5,] -1.4063066 #>  [6,] -1.8716503 #>  [7,] -1.8043044 #>  [8,] -1.5834953 #>  [9,] -1.1122729 #> [10,] -1.1299002 #> [11,]  0.4960479 #> [12,]  0.8951390 #> [13,]  0.5513251 #> [14,]  1.1822705 #> [15,]  0.6595846 #> [16,]  0.3216975 #> [17,]  0.5608929 #> [18,]  0.9156666 #> [19,]  0.6295094 #> [20,]  0.7993929 #> [21,] -1.9022555 #> [22,] -1.4494557 #> [23,] 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#> [30,] -1.14346082 #>  #> , , 162 #>  #>             [,1] #>  [1,] -1.5306431 #>  [2,] -1.6908209 #>  [3,] -1.8294741 #>  [4,] -1.7713867 #>  [5,] -1.6876117 #>  [6,] -1.8286736 #>  [7,] -1.7504756 #>  [8,] -1.7578515 #>  [9,] -1.4106544 #> [10,] -1.4586996 #> [11,]  0.2217619 #> [12,]  0.7250601 #> [13,]  0.3120939 #> [14,]  1.0567431 #> [15,]  0.4263097 #> [16,]  0.0496889 #> [17,]  0.3021915 #> [18,]  0.7353471 #> [19,]  0.3975071 #> [20,]  0.6036462 #> [21,] -1.6963643 #> [22,] -1.0963959 #> [23,] -1.5474296 #> [24,] -1.7486013 #> [25,] -1.0733339 #> [26,] -1.1059675 #> [27,] -1.0974960 #> [28,] -1.1014092 #> [29,] -1.3696593 #> [30,] -1.0927526 #>  #> , , 163 #>  #>               [,1] #>  [1,] -1.551889231 #>  [2,] -1.689039689 #>  [3,] -1.849811785 #>  [4,] -1.790294887 #>  [5,] -1.719735905 #>  [6,] -1.806240399 #>  [7,] -1.726857576 #>  [8,] -1.772473829 #>  [9,] -1.448142054 #> [10,] -1.500580683 #> [11,]  0.180423700 #> [12,]  0.698958717 #> [13,]  0.275994339 #> [14,]  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[13,]  0.16495157 #> [14,]  0.97482988 #> [15,]  0.28159081 #> [16,] -0.11507330 #> [17,]  0.14230187 #> [18,]  0.62086717 #> [19,]  0.25456781 #> [20,]  0.48050621 #> [21,] -1.54714854 #> [22,] -0.88903186 #> [23,] -1.38136368 #> [24,] -1.59608583 #> [25,] -0.87148843 #> [26,] -0.90307874 #> [27,] -0.89583702 #> [28,] -0.89962824 #> [29,] -1.16980327 #> [30,] -0.89124992 #>  #> , , 167 #>  #>              [,1] #>  [1,] -1.61258716 #>  [2,] -1.64541610 #>  [3,] -1.90194367 #>  [4,] -1.83395179 #>  [5,] -1.82414929 #>  [6,] -1.67401130 #>  [7,] -1.59155267 #>  [8,] -1.80274317 #>  [9,] -1.58147762 #> [10,] -1.65127306 #> [11,]  0.01018164 #> [12,]  0.59028432 #> [13,]  0.12716473 #> [14,]  0.95334307 #> [15,]  0.24423333 #> [16,] -0.15715037 #> [17,]  0.10113358 #> [18,]  0.59113019 #> [19,]  0.21770613 #> [20,]  0.44858144 #> [21,] -1.50704549 #> [22,] -0.83790224 #> [23,] -1.33779666 #> [24,] -1.55486864 #> [25,] -0.82197135 #> [26,] -0.85354432 #> [27,] -0.84651108 #> [28,] -0.85024386 #> [29,] -1.11912354 #> [30,] -0.84188076 #>  #> , , 168 #>  #>              [,1] #>  [1,] -1.62159272 #>  [2,] -1.62561073 #>  [3,] -1.90726834 #>  [4,] -1.83642476 #>  [5,] -1.84353444 #>  [6,] -1.62971493 #>  [7,] -1.54750756 #>  [8,] -1.80201742 #>  [9,] -1.61020719 #> [10,] -1.68423979 #> [11,] -0.03353761 #> [12,]  0.56201933 #> [13,]  0.08880683 #> [14,]  0.93114272 #> [15,]  0.20631699 #> [16,] -0.19951423 #> [17,]  0.05962162 #> [18,]  0.56077079 #> [19,]  0.18054198 #> [20,]  0.41599461 #> [21,] -1.46597793 #> [22,] -0.78732528 #> [23,] -1.29359865 #> [24,] -1.51265398 #> [25,] -0.77308249 #> [26,] -0.80472994 #> [27,] -0.79786949 #> [28,] -0.80153503 #> [29,] -1.06841052 #> [30,] -0.79316574 #>  #> , , 169 #>  #>              [,1] #>  [1,] -1.62789382 #>  [2,] -1.60224087 #>  [3,] -1.90879200 #>  [4,] -1.83555776 #>  [5,] -1.86004883 #>  [6,] -1.58101619 #>  [7,] -1.49921422 #>  [8,] -1.79819926 #>  [9,] -1.63695618 #> [10,] -1.71532030 #> [11,] -0.07758460 #> [12,]  0.53350955 #> [13,]  0.05017047 #> [14,]  0.90872962 #> [15,]  0.16804807 #> [16,] -0.24209003 #> [17,]  0.01754195 #> [18,]  0.52996885 #> [19,]  0.14290530 #> [20,]  0.38309479 #> [21,] -1.42398833 #> [22,] -0.73743217 #> [23,] -1.24886705 #> [24,] -1.46953003 #> [25,] -0.72494327 #> [26,] -0.75675229 #> [27,] -0.75003134 #> [28,] -0.75362208 #> [29,] -1.01779322 #> [30,] -0.74522571 #>  #> , , 170 #>  #>              [,1] #>  [1,] -1.63131954 #>  [2,] -1.57528508 #>  [3,] -1.90707695 #>  [4,] -1.83128461 #>  [5,] -1.87374763 #>  [6,] -1.52811635 #>  [7,] -1.44647639 #>  [8,] -1.79123797 #>  [9,] -1.66167380 #> [10,] -1.74440497 #> [11,] -0.12195131 #> [12,]  0.50429265 #> [13,]  0.01122205 #> [14,]  0.88566026 #> [15,]  0.12936360 #> [16,] -0.28489341 #> [17,] -0.02491991 #> [18,]  0.49884992 #> [19,]  0.10488014 #> [20,]  0.34971851 #> [21,] -1.38116176 #> [22,] -0.68835162 #> [23,] -1.20370047 #> [24,] -1.42558701 #> [25,] -0.67767214 #> [26,] -0.70972386 #> [27,] -0.70311183 #> [28,] -0.70662135 #> [29,] -0.96739570 #> [30,] -0.69817791 #>  #> , , 171 #>  #>              [,1] #>  [1,] -1.63150398 #>  [2,] -1.54473053 #>  [3,] -1.90194740 #>  [4,] -1.82340976 #>  [5,] -1.88440574 #>  [6,] -1.47109673 #>  [7,] -1.38971872 #>  [8,] -1.78108449 #>  [9,] -1.68382491 #> [10,] -1.77046573 #> [11,] -0.16673232 #> [12,]  0.47483794 #> [13,] -0.02822327 #> [14,]  0.86226971 #> [15,]  0.09016637 #> [16,] -0.32796198 #> [17,] -0.06767551 #> [18,]  0.46698035 #> [19,]  0.06657100 #> [20,]  0.31578709 #> [21,] -1.33761679 #> [22,] -0.64020932 #> [23,] -1.15819851 #> [24,] -1.38091695 #> [25,] -0.63139465 #> [26,] -0.66375249 #> [27,] -0.65722171 #> [28,] -0.66064468 #> [29,] -0.91734101 #> [30,] -0.65213545 #>  #> , , 172 #>  #>              [,1] #>  [1,] -1.62894500 #>  [2,] -1.51057321 #>  [3,] -1.89323079 #>  [4,] -1.81163514 #>  [5,] -1.89155986 #>  [6,] -1.41002966 #>  [7,] -1.32910067 #>  [8,] -1.76769442 #>  [9,] -1.70378080 #> [10,] -1.79424376 #> 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[28,] -0.5721852 #> [29,] -0.8187444 #> [30,] -0.5634952 #>  #> , , 174 #>  #>              [,1] #>  [1,] -1.61536883 #>  [2,] -1.43052248 #>  [3,] -1.86509114 #>  [4,] -1.77615352 #>  [5,] -1.89651992 #>  [6,] -1.27611660 #>  [7,] -1.19671300 #>  [8,] -1.73014578 #>  [9,] -1.73670246 #> [10,] -1.83499641 #> [11,] -0.30271850 #> [12,]  0.38409918 #> [13,] -0.14821207 #> [14,]  0.78933748 #> [15,] -0.02953410 #> [16,] -0.45792597 #> [17,] -0.19816165 #> [18,]  0.36907142 #> [19,] -0.05055041 #> [20,]  0.21163836 #> [21,] -1.20371562 #> [22,] -0.50261250 #> [23,] -1.02071508 #> [24,] -1.24348809 #> [25,] -0.49976715 #> [26,] -0.53317730 #> [27,] -0.52676014 #> [28,] -0.52989857 #> [29,] -0.77043923 #> [30,] -0.52109824 #>  #> , , 175 #>  #>              [,1] #>  [1,] -1.60412676 #>  [2,] -1.38475597 #>  [3,] -1.84524450 #>  [4,] -1.75271463 #>  [5,] -1.89395891 #>  [6,] -1.20349001 #>  [7,] -1.12517086 #>  [8,] -1.70557994 #>  [9,] -1.74948765 #> [10,] -1.85181755 #> [11,] -0.34854292 #> [12,]  0.35294410 #> [13,] -0.18876072 #> [14,]  0.76393427 #> [15,] -0.07012135 #> [16,] -0.50142296 #> [17,] -0.24222025 #> [18,]  0.33559469 #> [19,] -0.09027121 #> [20,]  0.17616542 #> [21,] -1.15832329 #> [22,] -0.45940609 #> [23,] -0.97494033 #> [24,] -1.19685973 #> [25,] -0.45859244 #> [26,] -0.49239987 #> [27,] -0.48601257 #> [28,] -0.48902750 #> [29,] -0.72294963 #> [30,] -0.48010722 #>  #> , , 176 #>  #>             [,1] #>  [1,] -1.5895654 #>  [2,] -1.3355005 #>  [3,] -1.8215934 #>  [4,] -1.7255820 #>  [5,] -1.8880493 #>  [6,] -1.1272551 #>  [7,] -1.0502392 #>  [8,] -1.6776411 #>  [9,] -1.7591957 #> [10,] -1.8649116 #> [11,] -0.3945146 #> [12,]  0.3215222 #> [13,] -0.2295181 #> [14,]  0.7383280 #> [15,] -0.1110064 #> [16,] -0.5449472 #> [17,] -0.2865898 #> [18,]  0.3016605 #> [19,] -0.1302098 #> [20,]  0.1401656 #> [21,] -1.1127052 #> [22,] -0.4177589 #> [23,] -0.9293639 #> [24,] -1.1499848 #> [25,] -0.4189162 #> [26,] -0.4531297 #> [27,] -0.4467852 #> [28,] -0.4496531 #> [29,] -0.6763865 #> [30,] -0.4406067 #>  #> , , 177 #>  #>             [,1] #>  [1,] -1.5714022 #>  [2,] -1.2828120 #>  [3,] -1.7943737 #>  [4,] -1.6947416 #>  [5,] -1.8785054 #>  [6,] -1.0475600 #>  [7,] -0.9720686 #>  [8,] -1.6463249 #>  [9,] -1.7663428 #> [10,] -1.8753149 #> [11,] -0.4406371 #> [12,]  0.2897960 #> [13,] -0.2705847 #> [14,]  0.7121397 #> [15,] -0.1522756 #> [16,] -0.5884649 #> [17,] -0.3311212 #> [18,]  0.2672407 #> [19,] -0.1703731 #> [20,]  0.1038437 #> [21,] -1.0669536 #> [22,] -0.3777174 #> [23,] -0.8840846 #> [24,] -1.1029604 #> [25,] -0.3808202 #> [26,] -0.4154355 #> [27,] -0.4091322 #> [28,] -0.4118489 #> [29,] -0.6308571 #> [30,] -0.4026741 #>  #> , , 178 #>  #>             [,1] #>  [1,] -1.5502548 #>  [2,] -1.2267574 #>  [3,] -1.7633411 #>  [4,] -1.6600797 #>  [5,] -1.8651079 #>  [6,] -0.9645303 #>  [7,] -0.8908240 #>  [8,] -1.6116301 #>  [9,] -1.7708414 #> [10,] -1.8830760 #> [11,] -0.4868906 #> [12,]  0.2575726 #> [13,] -0.3117875 #> [14,]  0.6855609 #> [15,] -0.1937530 #> [16,] -0.6319106 #> [17,] -0.3758207 #> [18,]  0.2325370 #> [19,] -0.2108660 #> [20,]  0.0672048 #> [21,] -1.0211611 #> [22,] -0.3393703 #> [23,] -0.8392003 #> [24,] -1.0559048 #> [25,] -0.3443793 #> [26,] -0.3793776 #> [27,] -0.3731177 #> [28,] -0.3756802 #> [29,] -0.5864772 #> [30,] -0.3663790 #>  #> , , 179 #>  #>              [,1] #>  [1,] -1.52610909 #>  [2,] -1.16741504 #>  [3,] -1.72845352 #>  [4,] -1.62136083 #>  [5,] -1.84832221 #>  [6,] -0.87810698 #>  [7,] -0.80668529 #>  [8,] -1.57355588 #>  [9,] -1.77256573 #> [10,] -1.88814018 #> [11,] -0.53319409 #> [12,]  0.22513570 #> [13,] -0.35313646 #> [14,]  0.65858497 #> [15,] -0.23546078 #> [16,] -0.67527951 #> [17,] -0.42073728 #> [18,]  0.19730383 #> [19,] -0.25151381 #> [20,]  0.03009154 #> [21,] -0.97542031 #> [22,] -0.30279857 #> [23,] -0.79480692 #> [24,] -1.00893525 #> [25,] -0.30966069 #> [26,] -0.34500793 #> [27,] -0.33879709 #> [28,] -0.34120360 #> [29,] -0.54334489 #> [30,] -0.33178286 #>  #> , , 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[29,] -0.42228044 #> [30,] -0.23875180 #>  #> , , 183 #>  #>              [,1] #>  [1,] -1.39754539 #>  [2,] -0.89850601 #>  [3,] -1.55104243 #>  [4,] -1.42682339 #>  [5,] -1.74444708 #>  [6,] -0.50556339 #>  [7,] -0.44453992 #>  [8,] -1.38439698 #>  [9,] -1.74900755 #> [10,] -1.87557812 #> [11,] -0.71831793 #> [12,]  0.09177883 #> [13,] -0.51974583 #> [14,]  0.54610097 #> [15,] -0.40441908 #> [16,] -0.84694111 #> [17,] -0.60105971 #> [18,]  0.05291220 #> [19,] -0.41585605 #> [20,] -0.12119721 #> [21,] -0.79516052 #> [22,] -0.17559838 #> [23,] -0.62399191 #> [24,] -0.82387705 #> [25,] -0.18906373 #> [26,] -0.22511839 #> [27,] -0.21923767 #> [28,] -0.22102263 #> [29,] -0.38496828 #> [30,] -0.21150955 #>  #> , , 184 #>  #>              [,1] #>  [1,] -1.35715738 #>  [2,] -0.82371856 #>  [3,] -1.49749374 #>  [4,] -1.36919799 #>  [5,] -1.70883523 #>  [6,] -0.40700842 #>  [7,] -0.34910295 #>  [8,] -1.32871598 #>  [9,] -1.73561491 #> [10,] -1.86464730 #> [11,] -0.76435199 #> [12,]  0.05770563 #> [13,] -0.56150456 #> [14,]  0.51691401 #> [15,] -0.44699251 #> [16,] -0.88910434 #> [17,] -0.64616757 #> [18,]  0.01598521 #> [19,] -0.45725815 #> [20,] -0.15974692 #> [21,] -0.75124746 #> [22,] -0.14882469 #> [23,] -0.58341696 #> [24,] -0.77879553 #> [25,] -0.16366966 #> [26,] -0.19963340 #> [27,] -0.19388809 #> [28,] -0.19552252 #> [29,] -0.34929427 #> [30,] -0.18613506 #>  #> , , 185 #>  #>              [,1] #>  [1,] -1.31383402 #>  [2,] -0.74643806 #>  [3,] -1.44030837 #>  [4,] -1.30805853 #>  [5,] -1.66974179 #>  [6,] -0.30685007 #>  [7,] -0.25219866 #>  [8,] -1.26991831 #>  [9,] -1.71910714 #> [10,] -1.85068726 #> [11,] -0.81016174 #> [12,]  0.02331990 #> [13,] -0.60326152 #> [14,]  0.48729100 #> [15,] -0.48964497 #> [16,] -0.93090164 #> [17,] -0.69116768 #> [18,] -0.02135287 #> [19,] -0.49870467 #> [20,] -0.19854478 #> [21,] -0.70796615 #> [22,] -0.12412949 #> [23,] -0.54385815 #> [24,] -0.73437288 #> [25,] -0.14021872 #> [26,] -0.17594289 #> [27,] -0.17036195 #> [28,] -0.17184911 #> [29,] -0.31531744 #> [30,] -0.16262956 #>  #> , , 186 #>  #>              [,1] #>  [1,] -1.26761079 #>  [2,] -0.66684504 #>  [3,] -1.37951674 #>  [4,] -1.24329436 #>  [5,] -1.62707683 #>  [6,] -0.20537509 #>  [7,] -0.15413096 #>  [8,] -1.20806307 #>  [9,] -1.69882859 #> [10,] -1.83218575 #> [11,] -0.85576939 #> [12,] -0.01135944 #> [13,] -0.64493881 #> [14,]  0.45734425 #> [15,] -0.53236274 #> [16,] -0.97235744 #> [17,] -0.73605179 #> [18,] -0.05888718 #> [19,] -0.54020223 #> [20,] -0.23749636 #> [21,] -0.66540113 #> [22,] -0.10152869 #> [23,] -0.50541188 #> [24,] -0.69069837 #> [25,] -0.11871390 #> [26,] -0.15402767 #> [27,] -0.14864391 #> [28,] -0.14998749 #> [29,] -0.28308882 #> [30,] -0.14098344 #>  #> , , 187 #>  #>              [,1] #>  [1,] -1.21847018 #>  [2,] -0.58512003 #>  [3,] -1.31545009 #>  [4,] -1.17465751 #>  [5,] -1.58074961 #>  [6,] -0.10288195 #>  [7,] -0.05523589 #>  [8,] -1.14300162 #>  [9,] -1.67557690 #> [10,] -1.81039624 #> [11,] -0.90110367 #> [12,] -0.04619759 #> [13,] -0.68653713 #> [14,]  0.42682438 #> [15,] -0.57507947 #> [16,] -1.01332995 #> [17,] -0.78081487 #> [18,] -0.09674908 #> [19,] -0.58170056 #> [20,] -0.27672069 #> [21,] -0.62363477 #> [22,] -0.08102730 #> [23,] -0.46825872 #> [24,] -0.64785870 #> [25,] -0.09914774 #> [26,] -0.13385741 #> [27,] -0.12870744 #> [28,] -0.12991144 #> [29,] -0.25265109 #> [30,] -0.12117603 #>  #> , , 188 #>  #>                [,1] #>  [1,] -1.1662203750 #>  [2,] -0.5014544901 #>  [3,] -1.2476064293 #>  [4,] -1.1027455992 #>  [5,] -1.5307307254 #>  [6,]  0.0003200125 #>  [7,]  0.0441850859 #>  [8,] -1.0743284481 #>  [9,] -1.6492979474 #> [10,] -1.7854552571 #> [11,] -0.9460185744 #> [12,] -0.0814390563 #> [13,] -0.7280485682 #> [14,]  0.3961233298 #> [15,] -0.6177920998 #> [16,] -1.0536219851 #> [17,] -0.8253146286 #> [18,] -0.1348938881 #> [19,] -0.6231825251 #> [20,] -0.3160892883 #> [21,] -0.5827469528 #> [22,] -0.0626191759 #> [23,] -0.4323905426 #> [24,] -0.6059377589 #> [25,] 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[24,] -0.48688864 #> [25,] -0.04002001 #> [26,] -0.06962388 #> [27,] -0.06584842 #> [28,] -0.06653517 #> [29,] -0.14934986 #> [30,] -0.05952587 #>  #> , , 192 #>  #>               [,1] #>  [1,] -0.927846253 #>  [2,] -0.151430660 #>  [3,] -0.945922332 #>  [4,] -0.786712215 #>  [5,] -1.294473886 #>  [6,]  0.413315517 #>  [7,]  0.440440947 #>  [8,] -0.773864803 #>  [9,] -1.511330715 #> [10,] -1.651172850 #> [11,] -1.121294832 #> [12,] -0.224216394 #> [13,] -0.891862872 #> [14,]  0.268926182 #> [15,] -0.787636779 #> [16,] -1.208703169 #> [17,] -1.000271008 #> [18,] -0.289608110 #> [19,] -0.788233838 #> [20,] -0.474801775 #> [21,] -0.429849782 #> [22,] -0.009391611 #> [23,] -0.302539100 #> [24,] -0.449669099 #> [25,] -0.029751103 #> [26,] -0.057330083 #> [27,] -0.054023160 #> [28,] -0.054589869 #> [29,] -0.128189601 #> [30,] -0.048206745 #>  #> , , 193 #>  #>                [,1] #>  [1,] -0.8621029910 #>  [2,] -0.0612346559 #>  [3,] -0.8634782947 #>  [4,] -0.7011804352 #>  [5,] 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-1.085323033 #> [18,] -0.368052426 #> [19,] -0.869764151 #> [20,] -0.554533848 #> [21,] -0.360927022 #> [22,]  0.005679786 #> [23,] -0.246393127 #> [24,] -0.379213313 #> [25,] -0.014075323 #> [26,] -0.036663391 #> [27,] -0.034416491 #> [28,] -0.034750773 #> [29,] -0.091402096 #> [30,] -0.029899868 #>  #> , , 195 #>  #>               [,1] #>  [1,] -0.723033985 #>  [2,]  0.120232407 #>  [3,] -0.690937937 #>  [4,] -0.522831778 #>  [5,] -1.082827863 #>  [6,]  0.712919209 #>  [7,]  0.726360094 #>  [8,] -0.524373642 #>  [9,] -1.374907167 #> [10,] -1.514921147 #> [11,] -1.246385959 #> [12,] -0.333130120 #> [13,] -1.011444675 #> [14,]  0.169852026 #> [15,] -0.912936953 #> [16,] -1.316619840 #> [17,] -1.126856321 #> [18,] -0.407450136 #> [19,] -0.910123436 #> [20,] -0.594394656 #> [21,] -0.328501182 #> [22,]  0.010588706 #> [23,] -0.220624993 #> [24,] -0.346081079 #> [25,] -0.008483452 #> [26,] -0.028030462 #> [27,] -0.026412853 #> [28,] -0.026633161 #> [29,] -0.075715152 #> [30,] -0.022701724 #>  #> , , 196 #>  #>               [,1] #>  [1,] -0.650185151 #>  [2,]  0.210965645 #>  [3,] -0.601464681 #>  [4,] -0.431000154 #>  [5,] -1.006079725 #>  [6,]  0.808876599 #>  [7,]  0.817709199 #>  [8,] -0.437473487 #>  [9,] -1.322666912 #> [10,] -1.462046044 #> [11,] -1.286626433 #> [12,] -0.369714638 #> [13,] -1.050438623 #> [14,]  0.136076678 #> [15,] -0.954081406 #> [16,] -1.350761662 #> [17,] -1.167911970 #> [18,] -0.446946438 #> [19,] -0.950168936 #> [20,] -0.634194932 #> [21,] -0.297487149 #> [22,]  0.013876794 #> [23,] -0.196417360 #> [24,] -0.314410123 #> [25,] -0.004247608 #> [26,] -0.020357565 #> [27,] -0.019443316 #> [28,] -0.019549847 #> [29,] -0.061775408 #> [30,] -0.016648980 #>  #> , , 197 #>  #>               [,1] #>  [1,] -0.575556006 #>  [2,]  0.301335857 #>  [3,] -0.510181120 #>  [4,] -0.337692869 #>  [5,] -0.926768895 #>  [6,]  0.902308278 #>  [7,]  0.906515719 #>  [8,] -0.349204238 #>  [9,] -1.267716729 #> [10,] -1.405994499 #> [11,] -1.325993755 #> [12,] -0.406349954 #> [13,] -1.089050306 #> [14,]  0.102036688 #> [15,] -0.994949646 #> [16,] -1.383907153 #> [17,] -1.208422332 #> [18,] -0.486487819 #> [19,] -0.989965720 #> [20,] -0.673946655 #> [21,] -0.267926926 #> [22,]  0.015656420 #> [23,] -0.173779270 #> [24,] -0.284241546 #> [25,] -0.001248661 #> [26,] -0.013504909 #> [27,] -0.013371022 #> [28,] -0.013362835 #> [29,] -0.049526606 #> [30,] -0.011610129 #>  #> , , 198 #>  #>                [,1] #>  [1,] -0.4992844973 #>  [2,]  0.3910651625 #>  [3,] -0.4172109171 #>  [4,] -0.2431268687 #>  [5,] -0.8450142561 #>  [6,]  0.9928641217 #>  [7,]  0.9924456596 #>  [8,] -0.2597557343 #>  [9,] -1.2100624012 #> [10,] -1.3469856946 #> [11,] -1.3642721753 #> [12,] -0.4430702374 #> [13,] -1.1268635293 #> [14,]  0.0676871160 #> [15,] -1.0351706383 #> [16,] -1.4155595078 #> [17,] -1.2478365998 #> [18,] -0.5260827053 #> [19,] -1.0292632788 #> [20,] -0.7135514435 #> [21,] -0.2398572798 #> [22,]  0.0160513632 #> [23,] -0.1527124075 #> [24,] -0.2556105251 #> [25,]  0.0006426683 #> [26,] -0.0073235578 #> [27,] -0.0080496092 #> [28,] -0.0079275363 #> [29,] -0.0389018667 #> [30,] -0.0074438167 #>  #> , , 199 #>  #>               [,1] #>  [1,] -0.421510053 #>  [2,]  0.479872129 #>  [3,] -0.322725528 #>  [4,] -0.147522287 #>  [5,] -0.760881674 #>  [6,]  1.080198918 #>  [7,]  1.075144276 #>  [8,] -0.169324367 #>  [9,] -1.149663371 #> [10,] -1.285143955 #> [11,] -1.401682659 #> [12,] -0.479833582 #> [13,] -1.164186428 #> [14,]  0.032975565 #> [15,] -1.075020746 #> [16,] -1.446249705 #> [17,] -1.286657771 #> [18,] -0.565674696 #> [19,] -1.068161911 #> [20,] -0.753012020 #> [21,] -0.213309519 #> [22,]  0.015196505 #> [23,] -0.133210934 #> [24,] -0.228546073 #> [25,]  0.001565434 #> [26,] -0.001656003 #> [27,] -0.003323753 #> [28,] -0.003094051 #> [29,] -0.029823744 #> [30,] -0.004014870 #>  #> , , 200 #>  #>                [,1] #>  [1,] -0.3423687995 #>  [2,]  0.5674727056 #>  [3,] -0.2270817231 #>  [4,] -0.0510936687 #>  [5,] -0.6743401179 #>  [6,]  1.1639740745 #>  [7,]  1.1540960933 #>  [8,] -0.0781127999 #>  [9,] -1.0864557084 #> [10,] -1.2205292742 #> [11,] -1.4381773667 #> [12,] -0.5166220923 #> [13,] -1.2010177137 #> [14,] -0.0018695731 #> [15,] -1.1144993261 #> [16,] -1.4760011597 #> [17,] -1.3248925041 #> [18,] -0.6052645843 #> [19,] -1.1067078697 #> [20,] -0.7923624353 #> [21,] -0.1883092902 #> [22,]  0.0132374553 #> [23,] -0.1152613448 #> [24,] -0.2030708185 #> [25,]  0.0016680301 #> [26,]  0.0036631880 #> [27,]  0.0009702148 #> [28,]  0.0013246578 #> [29,] -0.0222043173 #> [30,] -0.0011514266 #>  #>  #> $aligned_grids #>             [,1]       [,2]       [,3]       [,4]      [,5]      [,6]      [,7] #>  [1,] 0.56832832 0.59466626 0.62100420 0.64734214 0.6736801 0.7000180 0.7263560 #>  [2,] 0.53675452 0.56483775 0.59292097 0.62100420 0.6490874 0.6771706 0.7052539 #>  [3,] 0.56832832 0.59498358 0.62163885 0.64829411 0.6749494 0.7016046 0.7282599 #>  [4,] 0.50518073 0.53215332 0.55912591 0.58609850 0.6130711 0.6400437 0.6670163 #>  [5,] 0.50518073 0.53136001 0.55753928 0.58371856 0.6098978 0.6360771 0.6622564 #>  [6,] 0.56832832 0.59704619 0.62576407 0.65448194 0.6831998 0.7119177 0.7406356 #>  [7,] 0.59990211 0.62846133 0.65702054 0.68557975 0.7141390 0.7426982 0.7712574 #>  [8,] 0.59990211 0.62671604 0.65352997 0.68034390 0.7071578 0.7339717 0.7607857 #>  [9,] 0.53675452 0.56198183 0.58720913 0.61243644 0.6376637 0.6628910 0.6881183 #> [10,] 0.50518073 0.53040803 0.55563534 0.58086264 0.6060899 0.6313172 0.6565446 #> [11,] 0.18944277 0.21149683 0.23355089 0.25560495 0.2776590 0.2997131 0.3217671 #> [12,] 0.28416416 0.30352096 0.32287776 0.34223456 0.3615914 0.3809482 0.4003050 #> [13,] 0.28416416 0.30526624 0.32636833 0.34747041 0.3685725 0.3896746 0.4107767 #> [14,] 0.22101657 0.23926273 0.25750890 0.27575506 0.2940012 0.3122474 0.3304935 #> [15,] 0.22101657 0.24211865 0.26322074 0.28432282 0.3054249 0.3265270 0.3476291 #> [16,] 0.25259036 0.27480308 0.29701581 0.31922853 0.3414412 0.3636540 0.3858667 #> [17,] 0.22101657 0.24259464 0.26417271 0.28575078 0.3073289 0.3289069 0.3504850 #> [18,] 0.18944277 0.20943422 0.22942567 0.24941712 0.2694086 0.2894000 0.3093915 #> [19,] 0.31573796 0.33636405 0.35699015 0.37761625 0.3982423 0.4188684 0.4394945 #> [20,] 0.25259036 0.27274047 0.29289059 0.31304070 0.3331908 0.3533409 0.3734910 #> [21,] 0.06314759 0.09170680 0.12026602 0.14882523 0.1773844 0.2059437 0.2345029 #> [22,] 0.00000000 0.03157380 0.06314759 0.09472139 0.1262952 0.1578690 0.1894428 #> [23,] 0.03157380 0.06092632 0.09027884 0.11963137 0.1489839 0.1783364 0.2076889 #> [24,] 0.00000000 0.02887654 0.05775307 0.08662961 0.1155061 0.1443827 0.1732592 #> [25,] 0.06314759 0.09440406 0.12566053 0.15691700 0.1881735 0.2194299 0.2506864 #> [26,] 0.06314759 0.09440406 0.12566053 0.15691700 0.1881735 0.2194299 0.2506864 #> [27,] 0.03157380 0.06298893 0.09440406 0.12581920 0.1572343 0.1886495 0.2200646 #> [28,] 0.00000000 0.03157380 0.06314759 0.09472139 0.1262952 0.1578690 0.1894428 #> [29,] 0.00000000 0.03062182 0.06124364 0.09186547 0.1224873 0.1531091 0.1837309 #> [30,] 0.00000000 0.03157380 0.06314759 0.09472139 0.1262952 0.1578690 0.1894428 #>            [,8]      [,9]     [,10]     [,11]     [,12]     [,13]     [,14] #>  [1,] 0.7526939 0.7790318 0.8053698 0.8317077 0.8580457 0.8843836 0.9107215 #>  [2,] 0.7333371 0.7614203 0.7895036 0.8175868 0.8456700 0.8737532 0.9018365 #>  [3,] 0.7549152 0.7815704 0.8082257 0.8348810 0.8615362 0.8881915 0.9148468 #>  [4,] 0.6939889 0.7209614 0.7479340 0.7749066 0.8018792 0.8288518 0.8558244 #>  [5,] 0.6884357 0.7146149 0.7407942 0.7669735 0.7931528 0.8193321 0.8455113 #>  [6,] 0.7693534 0.7980713 0.8267892 0.8555071 0.8842249 0.9129428 0.9416607 #>  [7,] 0.7998166 0.8283758 0.8569350 0.8854942 0.9140534 0.9426127 0.9711719 #>  [8,] 0.7875996 0.8144135 0.8412275 0.8680414 0.8948553 0.9216692 0.9484832 #>  [9,] 0.7133457 0.7385730 0.7638003 0.7890276 0.8142549 0.8394822 0.8647095 #> [10,] 0.6817719 0.7069992 0.7322265 0.7574538 0.7826811 0.8079084 0.8331357 #> [11,] 0.3438212 0.3658752 0.3879293 0.4099834 0.4320374 0.4540915 0.4761455 #> [12,] 0.4196618 0.4390186 0.4583754 0.4777322 0.4970890 0.5164458 0.5358025 #> [13,] 0.4318788 0.4529808 0.4740829 0.4951850 0.5162871 0.5373892 0.5584913 #> [14,] 0.3487397 0.3669859 0.3852320 0.4034782 0.4217244 0.4399705 0.4582167 #> [15,] 0.3687312 0.3898332 0.4109353 0.4320374 0.4531395 0.4742416 0.4953437 #> [16,] 0.4080794 0.4302921 0.4525048 0.4747176 0.4969303 0.5191430 0.5413557 #> [17,] 0.3720631 0.3936411 0.4152192 0.4367973 0.4583754 0.4799534 0.5015315 #> [18,] 0.3293829 0.3493744 0.3693658 0.3893573 0.4093487 0.4293402 0.4493316 #> [19,] 0.4601206 0.4807467 0.5013728 0.5219989 0.5426250 0.5632511 0.5838772 #> [20,] 0.3936411 0.4137912 0.4339414 0.4540915 0.4742416 0.4943917 0.5145418 #> [21,] 0.2630621 0.2916213 0.3201805 0.3487397 0.3772989 0.4058581 0.4344173 #> [22,] 0.2210166 0.2525904 0.2841642 0.3157380 0.3473118 0.3788855 0.4104593 #> [23,] 0.2370415 0.2663940 0.2957465 0.3250990 0.3544516 0.3838041 0.4131566 #> [24,] 0.2021358 0.2310123 0.2598888 0.2887654 0.3176419 0.3465184 0.3753950 #> [25,] 0.2819429 0.3131994 0.3444558 0.3757123 0.4069688 0.4382252 0.4694817 #> [26,] 0.2819429 0.3131994 0.3444558 0.3757123 0.4069688 0.4382252 0.4694817 #> [27,] 0.2514797 0.2828949 0.3143100 0.3457251 0.3771403 0.4085554 0.4399705 #> [28,] 0.2210166 0.2525904 0.2841642 0.3157380 0.3473118 0.3788855 0.4104593 #> [29,] 0.2143528 0.2449746 0.2755964 0.3062182 0.3368400 0.3674619 0.3980837 #> [30,] 0.2210166 0.2525904 0.2841642 0.3157380 0.3473118 0.3788855 0.4104593 #>           [,15]     [,16]     [,17]     [,18]     [,19]     [,20]     [,21] #>  [1,] 0.9370595 0.9633974 0.9897354 1.0160733 1.0424112 1.0687492 1.0950871 #>  [2,] 0.9299197 0.9580029 0.9860861 1.0141694 1.0422526 1.0703358 1.0984190 #>  [3,] 0.9415020 0.9681573 0.9948126 1.0214678 1.0481231 1.0747783 1.1014336 #>  [4,] 0.8827970 0.9097696 0.9367422 0.9637147 0.9906873 1.0176599 1.0446325 #>  [5,] 0.8716906 0.8978699 0.9240492 0.9502284 0.9764077 1.0025870 1.0287663 #>  [6,] 0.9703786 0.9990964 1.0278143 1.0565322 1.0852501 1.1139679 1.1426858 #>  [7,] 0.9997311 1.0282903 1.0568495 1.0854087 1.1139679 1.1425271 1.1710864 #>  [8,] 0.9752971 1.0021110 1.0289249 1.0557389 1.0825528 1.1093667 1.1361807 #>  [9,] 0.8899368 0.9151641 0.9403914 0.9656187 0.9908460 1.0160733 1.0413006 #> [10,] 0.8583630 0.8835903 0.9088176 0.9340449 0.9592722 0.9844995 1.0097268 #> [11,] 0.4981996 0.5202536 0.5423077 0.5643618 0.5864158 0.6084699 0.6305239 #> [12,] 0.5551593 0.5745161 0.5938729 0.6132297 0.6325865 0.6519433 0.6713001 #> [13,] 0.5795933 0.6006954 0.6217975 0.6428996 0.6640017 0.6851038 0.7062058 #> [14,] 0.4764629 0.4947090 0.5129552 0.5312013 0.5494475 0.5676937 0.5859398 #> [15,] 0.5164458 0.5375478 0.5586499 0.5797520 0.6008541 0.6219562 0.6430583 #> [16,] 0.5635685 0.5857812 0.6079939 0.6302066 0.6524193 0.6746321 0.6968448 #> [17,] 0.5231096 0.5446876 0.5662657 0.5878438 0.6094219 0.6309999 0.6525780 #> [18,] 0.4693231 0.4893145 0.5093059 0.5292974 0.5492888 0.5692803 0.5892717 #> [19,] 0.6045033 0.6251294 0.6457555 0.6663816 0.6870077 0.7076338 0.7282599 #> [20,] 0.5346919 0.5548420 0.5749921 0.5951422 0.6152924 0.6354425 0.6555926 #> [21,] 0.4629766 0.4915358 0.5200950 0.5486542 0.5772134 0.6057726 0.6343318 #> [22,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [23,] 0.4425091 0.4718616 0.5012142 0.5305667 0.5599192 0.5892717 0.6186243 #> [24,] 0.4042715 0.4331480 0.4620246 0.4909011 0.5197777 0.5486542 0.5775307 #> [25,] 0.5007382 0.5319947 0.5632511 0.5945076 0.6257641 0.6570205 0.6882770 #> [26,] 0.5007382 0.5319947 0.5632511 0.5945076 0.6257641 0.6570205 0.6882770 #> [27,] 0.4713857 0.5028008 0.5342159 0.5656311 0.5970462 0.6284613 0.6598765 #> [28,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #> [29,] 0.4287055 0.4593273 0.4899491 0.5205710 0.5511928 0.5818146 0.6124364 #> [30,] 0.4420331 0.4736069 0.5051807 0.5367545 0.5683283 0.5999021 0.6314759 #>           [,22]     [,23]     [,24]     [,25]     [,26]     [,27]     [,28] #>  [1,] 1.1214251 1.1477630 1.1741009 1.2004389 1.2267768 1.2531148 1.2794527 #>  [2,] 1.1265023 1.1545855 1.1826687 1.2107519 1.2388352 1.2669184 1.2950016 #>  [3,] 1.1280889 1.1547441 1.1813994 1.2080547 1.2347099 1.2613652 1.2880205 #>  [4,] 1.0716051 1.0985777 1.1255503 1.1525229 1.1794955 1.2064680 1.2334406 #>  [5,] 1.0549456 1.0811248 1.1073041 1.1334834 1.1596627 1.1858419 1.2120212 #>  [6,] 1.1714037 1.2001216 1.2288394 1.2575573 1.2862752 1.3149931 1.3437109 #>  [7,] 1.1996456 1.2282048 1.2567640 1.2853232 1.3138824 1.3424416 1.3710008 #>  [8,] 1.1629946 1.1898085 1.2166224 1.2434364 1.2702503 1.2970642 1.3238781 #>  [9,] 1.0665279 1.0917552 1.1169825 1.1422098 1.1674371 1.1926644 1.2178917 #> [10,] 1.0349541 1.0601814 1.0854087 1.1106360 1.1358633 1.1610906 1.1863179 #> [11,] 0.6525780 0.6746321 0.6966861 0.7187402 0.7407942 0.7628483 0.7849023 #> [12,] 0.6906569 0.7100137 0.7293705 0.7487273 0.7680841 0.7874409 0.8067977 #> [13,] 0.7273079 0.7484100 0.7695121 0.7906142 0.8117163 0.8328184 0.8539204 #> [14,] 0.6041860 0.6224322 0.6406783 0.6589245 0.6771706 0.6954168 0.7136630 #> [15,] 0.6641603 0.6852624 0.7063645 0.7274666 0.7485687 0.7696708 0.7907728 #> [16,] 0.7190575 0.7412702 0.7634829 0.7856957 0.8079084 0.8301211 0.8523338 #> [17,] 0.6741561 0.6957341 0.7173122 0.7388903 0.7604684 0.7820464 0.8036245 #> [18,] 0.6092632 0.6292546 0.6492461 0.6692375 0.6892290 0.7092204 0.7292119 #> [19,] 0.7488860 0.7695121 0.7901382 0.8107643 0.8313904 0.8520165 0.8726426 #> [20,] 0.6757427 0.6958928 0.7160429 0.7361930 0.7563431 0.7764932 0.7966434 #> [21,] 0.6628910 0.6914503 0.7200095 0.7485687 0.7771279 0.8056871 0.8342463 #> [22,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [23,] 0.6479768 0.6773293 0.7066818 0.7360344 0.7653869 0.7947394 0.8240919 #> [24,] 0.6064073 0.6352838 0.6641603 0.6930369 0.7219134 0.7507900 0.7796665 #> [25,] 0.7195335 0.7507900 0.7820464 0.8133029 0.8445594 0.8758158 0.9070723 #> [26,] 0.7195335 0.7507900 0.7820464 0.8133029 0.8445594 0.8758158 0.9070723 #> [27,] 0.6912916 0.7227067 0.7541219 0.7855370 0.8169521 0.8483673 0.8797824 #> [28,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #> [29,] 0.6430583 0.6736801 0.7043019 0.7349237 0.7655455 0.7961674 0.8267892 #> [30,] 0.6630497 0.6946235 0.7261973 0.7577711 0.7893449 0.8209187 0.8524925 #>           [,29]     [,30]     [,31]     [,32]     [,33]     [,34]     [,35] #>  [1,] 1.3057906 1.3321286 1.3584665 1.3848045 1.4111424 1.4374803 1.4638183 #>  [2,] 1.3230848 1.3511681 1.3792513 1.4073345 1.4354177 1.4635010 1.4915842 #>  [3,] 1.3146757 1.3413310 1.3679863 1.3946415 1.4212968 1.4479520 1.4746073 #>  [4,] 1.2604132 1.2873858 1.3143584 1.3413310 1.3683036 1.3952762 1.4222488 #>  [5,] 1.2382005 1.2643798 1.2905591 1.3167383 1.3429176 1.3690969 1.3952762 #>  [6,] 1.3724288 1.4011467 1.4298645 1.4585824 1.4873003 1.5160182 1.5447360 #>  [7,] 1.3995601 1.4281193 1.4566785 1.4852377 1.5137969 1.5423561 1.5709153 #>  [8,] 1.3506921 1.3775060 1.4043199 1.4311338 1.4579478 1.4847617 1.5115756 #>  [9,] 1.2431190 1.2683463 1.2935736 1.3188009 1.3440283 1.3692556 1.3944829 #> [10,] 1.2115452 1.2367725 1.2619998 1.2872272 1.3124545 1.3376818 1.3629091 #> [11,] 0.8069564 0.8290105 0.8510645 0.8731186 0.8951726 0.9172267 0.9392808 #> [12,] 0.8261545 0.8455113 0.8648681 0.8842249 0.9035817 0.9229385 0.9422953 #> [13,] 0.8750225 0.8961246 0.9172267 0.9383288 0.9594309 0.9805329 1.0016350 #> [14,] 0.7319091 0.7501553 0.7684015 0.7866476 0.8048938 0.8231400 0.8413861 #> [15,] 0.8118749 0.8329770 0.8540791 0.8751812 0.8962833 0.9173854 0.9384874 #> [16,] 0.8745465 0.8967593 0.9189720 0.9411847 0.9633974 0.9856101 1.0078229 #> [17,] 0.8252026 0.8467806 0.8683587 0.8899368 0.9115149 0.9330929 0.9546710 #> [18,] 0.7492033 0.7691948 0.7891862 0.8091777 0.8291691 0.8491606 0.8691520 #> [19,] 0.8932687 0.9138948 0.9345209 0.9551470 0.9757731 0.9963992 1.0170253 #> [20,] 0.8167935 0.8369436 0.8570937 0.8772438 0.8973939 0.9175440 0.9376941 #> [21,] 0.8628055 0.8913647 0.9199240 0.9484832 0.9770424 1.0056016 1.0341608 #> [22,] 0.8840663 0.9156401 0.9472139 0.9787877 1.0103615 1.0419353 1.0735090 #> [23,] 0.8534445 0.8827970 0.9121495 0.9415020 0.9708545 1.0002071 1.0295596 #> [24,] 0.8085430 0.8374196 0.8662961 0.8951726 0.9240492 0.9529257 0.9818022 #> [25,] 0.9383288 0.9695852 1.0008417 1.0320982 1.0633547 1.0946111 1.1258676 #> [26,] 0.9383288 0.9695852 1.0008417 1.0320982 1.0633547 1.0946111 1.1258676 #> [27,] 0.9111975 0.9426127 0.9740278 1.0054429 1.0368581 1.0682732 1.0996883 #> [28,] 0.8840663 0.9156401 0.9472139 0.9787877 1.0103615 1.0419353 1.0735090 #> [29,] 0.8574110 0.8880328 0.9186547 0.9492765 0.9798983 1.0105201 1.0411419 #> [30,] 0.8840663 0.9156401 0.9472139 0.9787877 1.0103615 1.0419353 1.0735090 #>           [,36]     [,37]     [,38]     [,39]     [,40]     [,41]     [,42] #>  [1,] 1.4901562 1.5164942 1.5428321 1.5691700 1.5955080 1.6218459 1.6481839 #>  [2,] 1.5196674 1.5477506 1.5758339 1.6039171 1.6320003 1.6600835 1.6881668 #>  [3,] 1.5012626 1.5279178 1.5545731 1.5812284 1.6078836 1.6345389 1.6611942 #>  [4,] 1.4492213 1.4761939 1.5031665 1.5301391 1.5571117 1.5840843 1.6110569 #>  [5,] 1.4214554 1.4476347 1.4738140 1.4999933 1.5261726 1.5523518 1.5785311 #>  [6,] 1.5734539 1.6021718 1.6308897 1.6596075 1.6883254 1.7170433 1.7457612 #>  [7,] 1.5994745 1.6280337 1.6565930 1.6851522 1.7137114 1.7422706 1.7708298 #>  [8,] 1.5383896 1.5652035 1.5920174 1.6188313 1.6456453 1.6724592 1.6992731 #>  [9,] 1.4197102 1.4449375 1.4701648 1.4953921 1.5206194 1.5458467 1.5710740 #> [10,] 1.3881364 1.4133637 1.4385910 1.4638183 1.4890456 1.5142729 1.5395002 #> [11,] 0.9613348 0.9833889 1.0054429 1.0274970 1.0495510 1.0716051 1.0936592 #> [12,] 0.9616521 0.9810089 1.0003657 1.0197225 1.0390793 1.0584361 1.0777929 #> [13,] 1.0227371 1.0438392 1.0649413 1.0860434 1.1071455 1.1282475 1.1493496 #> [14,] 0.8596323 0.8778784 0.8961246 0.9143708 0.9326169 0.9508631 0.9691093 #> [15,] 0.9595895 0.9806916 1.0017937 1.0228958 1.0439979 1.0650999 1.0862020 #> [16,] 1.0300356 1.0522483 1.0744610 1.0966737 1.1188865 1.1410992 1.1633119 #> [17,] 0.9762491 0.9978271 1.0194052 1.0409833 1.0625613 1.0841394 1.1057175 #> [18,] 0.8891435 0.9091349 0.9291264 0.9491178 0.9691093 0.9891007 1.0090922 #> [19,] 1.0376514 1.0582775 1.0789036 1.0995297 1.1201558 1.1407819 1.1614080 #> [20,] 0.9578442 0.9779943 0.9981445 1.0182946 1.0384447 1.0585948 1.0787449 #> [21,] 1.0627200 1.0912792 1.1198384 1.1483976 1.1769569 1.2055161 1.2340753 #> [22,] 1.1050828 1.1366566 1.1682304 1.1998042 1.2313780 1.2629518 1.2945256 #> [23,] 1.0589121 1.0882646 1.1176172 1.1469697 1.1763222 1.2056747 1.2350273 #> [24,] 1.0106788 1.0395553 1.0684319 1.0973084 1.1261849 1.1550615 1.1839380 #> [25,] 1.1571241 1.1883805 1.2196370 1.2508935 1.2821500 1.3134064 1.3446629 #> [26,] 1.1571241 1.1883805 1.2196370 1.2508935 1.2821500 1.3134064 1.3446629 #> [27,] 1.1311035 1.1625186 1.1939337 1.2253489 1.2567640 1.2881791 1.3195943 #> [28,] 1.1050828 1.1366566 1.1682304 1.1998042 1.2313780 1.2629518 1.2945256 #> [29,] 1.0717638 1.1023856 1.1330074 1.1636292 1.1942510 1.2248729 1.2554947 #> [30,] 1.1050828 1.1366566 1.1682304 1.1998042 1.2313780 1.2629518 1.2945256 #>           [,43]    [,44]    [,45]    [,46]    [,47]    [,48]    [,49]    [,50] #>  [1,] 1.6745218 1.700860 1.727198 1.753536 1.779874 1.806211 1.832549 1.858887 #>  [2,] 1.7162500 1.744333 1.772416 1.800500 1.828583 1.856666 1.884749 1.912833 #>  [3,] 1.6878494 1.714505 1.741160 1.767815 1.794470 1.821126 1.847781 1.874436 #>  [4,] 1.6380295 1.665002 1.691975 1.718947 1.745920 1.772892 1.799865 1.826838 #>  [5,] 1.6047104 1.630890 1.657069 1.683248 1.709428 1.735607 1.761786 1.787965 #>  [6,] 1.7744790 1.803197 1.831915 1.860633 1.889351 1.918068 1.946786 1.975504 #>  [7,] 1.7993890 1.827948 1.856507 1.885067 1.913626 1.942185 1.970744 1.999304 #>  [8,] 1.7260870 1.752901 1.779715 1.806529 1.833343 1.860157 1.886971 1.913785 #>  [9,] 1.5963013 1.621529 1.646756 1.671983 1.697211 1.722438 1.747665 1.772892 #> [10,] 1.5647275 1.589955 1.615182 1.640409 1.665637 1.690864 1.716091 1.741319 #> [11,] 1.1157132 1.137767 1.159821 1.181875 1.203929 1.225984 1.248038 1.270092 #> [12,] 1.0971497 1.116507 1.135863 1.155220 1.174577 1.193934 1.213291 1.232647 #> [13,] 1.1704517 1.191554 1.212656 1.233758 1.254860 1.275962 1.297064 1.318166 #> [14,] 0.9873554 1.005602 1.023848 1.042094 1.060340 1.078586 1.096832 1.115079 #> [15,] 1.1073041 1.128406 1.149508 1.170610 1.191712 1.212815 1.233917 1.255019 #> [16,] 1.1855246 1.207737 1.229950 1.252163 1.274376 1.296588 1.318801 1.341014 #> [17,] 1.1272956 1.148874 1.170452 1.192030 1.213608 1.235186 1.256764 1.278342 #> [18,] 1.0290836 1.049075 1.069067 1.089058 1.109049 1.129041 1.149032 1.169024 #> [19,] 1.1820341 1.202660 1.223286 1.243912 1.264538 1.285165 1.305791 1.326417 #> [20,] 1.0988950 1.119045 1.139195 1.159345 1.179495 1.199646 1.219796 1.239946 #> [21,] 1.2626345 1.291194 1.319753 1.348312 1.376871 1.405431 1.433990 1.462549 #> [22,] 1.3260994 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 #> [23,] 1.2643798 1.293732 1.323085 1.352437 1.381790 1.411142 1.440495 1.469847 #> [24,] 1.2128145 1.241691 1.270568 1.299444 1.328321 1.357197 1.386074 1.414950 #> [25,] 1.3759194 1.407176 1.438432 1.469689 1.500945 1.532202 1.563458 1.594715 #> [26,] 1.3759194 1.407176 1.438432 1.469689 1.500945 1.532202 1.563458 1.594715 #> [27,] 1.3510094 1.382425 1.413840 1.445255 1.476670 1.508085 1.539500 1.570915 #> [28,] 1.3260994 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 #> [29,] 1.2861165 1.316738 1.347360 1.377982 1.408604 1.439226 1.469847 1.500469 #> [30,] 1.3260994 1.357673 1.389247 1.420821 1.452395 1.483968 1.515542 1.547116 #>          [,51]    [,52]    [,53]    [,54]    [,55]    [,56]    [,57]    [,58] #>  [1,] 1.885225 1.911563 1.937901 1.964239 1.990577 2.016915 2.043253 2.069591 #>  [2,] 1.940916 1.968999 1.997082 2.025165 2.053249 2.081332 2.109415 2.137498 #>  [3,] 1.901092 1.927747 1.954402 1.981057 2.007713 2.034368 2.061023 2.087678 #>  [4,] 1.853810 1.880783 1.907755 1.934728 1.961701 1.988673 2.015646 2.042618 #>  [5,] 1.814145 1.840324 1.866503 1.892682 1.918862 1.945041 1.971220 1.997400 #>  [6,] 2.004222 2.032940 2.061658 2.090376 2.119094 2.147811 2.176529 2.205247 #>  [7,] 2.027863 2.056422 2.084981 2.113540 2.142100 2.170659 2.199218 2.227777 #>  [8,] 1.940598 1.967412 1.994226 2.021040 2.047854 2.074668 2.101482 2.128296 #>  [9,] 1.798120 1.823347 1.848574 1.873802 1.899029 1.924256 1.949484 1.974711 #> [10,] 1.766546 1.791773 1.817001 1.842228 1.867455 1.892682 1.917910 1.943137 #> [11,] 1.292146 1.314200 1.336254 1.358308 1.380362 1.402416 1.424470 1.446524 #> [12,] 1.252004 1.271361 1.290718 1.310075 1.329431 1.348788 1.368145 1.387502 #> [13,] 1.339268 1.360370 1.381473 1.402575 1.423677 1.444779 1.465881 1.486983 #> [14,] 1.133325 1.151571 1.169817 1.188063 1.206309 1.224556 1.242802 1.261048 #> [15,] 1.276121 1.297223 1.318325 1.339427 1.360529 1.381631 1.402733 1.423835 #> [16,] 1.363226 1.385439 1.407652 1.429865 1.452077 1.474290 1.496503 1.518715 #> [17,] 1.299920 1.321498 1.343076 1.364654 1.386232 1.407810 1.429389 1.450967 #> [18,] 1.189015 1.209007 1.228998 1.248990 1.268981 1.288972 1.308964 1.328955 #> [19,] 1.347043 1.367669 1.388295 1.408921 1.429547 1.450173 1.470799 1.491426 #> [20,] 1.260096 1.280246 1.300396 1.320546 1.340696 1.360846 1.380997 1.401147 #> [21,] 1.491108 1.519667 1.548227 1.576786 1.605345 1.633904 1.662463 1.691023 #> [22,] 1.578690 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 #> [23,] 1.499200 1.528552 1.557905 1.587258 1.616610 1.645963 1.675315 1.704668 #> [24,] 1.443827 1.472703 1.501580 1.530456 1.559333 1.588210 1.617086 1.645963 #> [25,] 1.625971 1.657228 1.688484 1.719741 1.750997 1.782253 1.813510 1.844766 #> [26,] 1.625971 1.657228 1.688484 1.719741 1.750997 1.782253 1.813510 1.844766 #> [27,] 1.602330 1.633746 1.665161 1.696576 1.727991 1.759406 1.790821 1.822236 #> [28,] 1.578690 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 #> [29,] 1.531091 1.561713 1.592335 1.622957 1.653578 1.684200 1.714822 1.745444 #> [30,] 1.578690 1.610264 1.641837 1.673411 1.704985 1.736559 1.768133 1.799706 #>          [,59]    [,60]    [,61]    [,62]    [,63]    [,64]    [,65]    [,66] #>  [1,] 2.095929 2.122267 2.148605 2.174943 2.201281 2.227619 2.253956 2.280294 #>  [2,] 2.165582 2.193665 2.221748 2.249831 2.277914 2.305998 2.334081 2.362164 #>  [3,] 2.114334 2.140989 2.167644 2.194299 2.220955 2.247610 2.274265 2.300921 #>  [4,] 2.069591 2.096563 2.123536 2.150509 2.177481 2.204454 2.231426 2.258399 #>  [5,] 2.023579 2.049758 2.075937 2.102117 2.128296 2.154475 2.180655 2.206834 #>  [6,] 2.233965 2.262683 2.291401 2.320119 2.348837 2.377554 2.406272 2.434990 #>  [7,] 2.256336 2.284896 2.313455 2.342014 2.370573 2.399132 2.427692 2.456251 #>  [8,] 2.155110 2.181924 2.208738 2.235552 2.262366 2.289180 2.315993 2.342807 #>  [9,] 1.999938 2.025165 2.050393 2.075620 2.100847 2.126075 2.151302 2.176529 #> [10,] 1.968364 1.993592 2.018819 2.044046 2.069274 2.094501 2.119728 2.144955 #> [11,] 1.468578 1.490632 1.512686 1.534740 1.556794 1.578848 1.600902 1.622957 #> [12,] 1.406859 1.426215 1.445572 1.464929 1.484286 1.503643 1.522999 1.542356 #> [13,] 1.508085 1.529187 1.550289 1.571391 1.592493 1.613595 1.634698 1.655800 #> [14,] 1.279294 1.297540 1.315786 1.334033 1.352279 1.370525 1.388771 1.407017 #> [15,] 1.444937 1.466040 1.487142 1.508244 1.529346 1.550448 1.571550 1.592652 #> [16,] 1.540928 1.563141 1.585354 1.607566 1.629779 1.651992 1.674204 1.696417 #> [17,] 1.472545 1.494123 1.515701 1.537279 1.558857 1.580435 1.602013 1.623591 #> [18,] 1.348947 1.368938 1.388930 1.408921 1.428913 1.448904 1.468895 1.488887 #> [19,] 1.512052 1.532678 1.553304 1.573930 1.594556 1.615182 1.635808 1.656434 #> [20,] 1.421297 1.441447 1.461597 1.481747 1.501897 1.522047 1.542197 1.562348 #> [21,] 1.719582 1.748141 1.776700 1.805260 1.833819 1.862378 1.890937 1.919496 #> [22,] 1.831280 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 #> [23,] 1.734020 1.763373 1.792725 1.822078 1.851430 1.880783 1.910135 1.939488 #> [24,] 1.674839 1.703716 1.732592 1.761469 1.790345 1.819222 1.848098 1.876975 #> [25,] 1.876023 1.907279 1.938536 1.969792 2.001049 2.032305 2.063562 2.094818 #> [26,] 1.876023 1.907279 1.938536 1.969792 2.001049 2.032305 2.063562 2.094818 #> [27,] 1.853652 1.885067 1.916482 1.947897 1.979312 2.010727 2.042142 2.073557 #> [28,] 1.831280 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 #> [29,] 1.776066 1.806687 1.837309 1.867931 1.898553 1.929175 1.959797 1.990418 #> [30,] 1.831280 1.862854 1.894428 1.926002 1.957575 1.989149 2.020723 2.052297 #>          [,67]    [,68]    [,69]    [,70]    [,71]    [,72]    [,73]    [,74] #>  [1,] 2.306632 2.332970 2.359308 2.385646 2.411984 2.438322 2.464660 2.490998 #>  [2,] 2.390247 2.418331 2.446414 2.474497 2.502580 2.530664 2.558747 2.586830 #>  [3,] 2.327576 2.354231 2.380886 2.407542 2.434197 2.460852 2.487507 2.514163 #>  [4,] 2.285372 2.312344 2.339317 2.366289 2.393262 2.420235 2.447207 2.474180 #>  [5,] 2.233013 2.259192 2.285372 2.311551 2.337730 2.363909 2.390089 2.416268 #>  [6,] 2.463708 2.492426 2.521144 2.549862 2.578580 2.607297 2.636015 2.664733 #>  [7,] 2.484810 2.513369 2.541929 2.570488 2.599047 2.627606 2.656165 2.684725 #>  [8,] 2.369621 2.396435 2.423249 2.450063 2.476877 2.503691 2.530505 2.557319 #>  [9,] 2.201757 2.226984 2.252211 2.277438 2.302666 2.327893 2.353120 2.378348 #> [10,] 2.170183 2.195410 2.220637 2.245865 2.271092 2.296319 2.321547 2.346774 #> [11,] 1.645011 1.667065 1.689119 1.711173 1.733227 1.755281 1.777335 1.799389 #> [12,] 1.561713 1.581070 1.600427 1.619783 1.639140 1.658497 1.677854 1.697211 #> [13,] 1.676902 1.698004 1.719106 1.740208 1.761310 1.782412 1.803514 1.824616 #> [14,] 1.425263 1.443510 1.461756 1.480002 1.498248 1.516494 1.534740 1.552986 #> [15,] 1.613754 1.634856 1.655958 1.677060 1.698162 1.719265 1.740367 1.761469 #> [16,] 1.718630 1.740843 1.763055 1.785268 1.807481 1.829694 1.851906 1.874119 #> [17,] 1.645169 1.666747 1.688325 1.709903 1.731482 1.753060 1.774638 1.796216 #> [18,] 1.508878 1.528870 1.548861 1.568853 1.588844 1.608836 1.628827 1.648819 #> [19,] 1.677060 1.697686 1.718313 1.738939 1.759565 1.780191 1.800817 1.821443 #> [20,] 1.582498 1.602648 1.622798 1.642948 1.663098 1.683248 1.703398 1.723548 #> [21,] 1.948056 1.976615 2.005174 2.033733 2.062292 2.090852 2.119411 2.147970 #> [22,] 2.083871 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 #> [23,] 1.968840 1.998193 2.027545 2.056898 2.086250 2.115603 2.144955 2.174308 #> [24,] 1.905851 1.934728 1.963604 1.992481 2.021358 2.050234 2.079111 2.107987 #> [25,] 2.126075 2.157331 2.188588 2.219844 2.251101 2.282357 2.313613 2.344870 #> [26,] 2.126075 2.157331 2.188588 2.219844 2.251101 2.282357 2.313613 2.344870 #> [27,] 2.104973 2.136388 2.167803 2.199218 2.230633 2.262048 2.293463 2.324879 #> [28,] 2.083871 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 #> [29,] 2.021040 2.051662 2.082284 2.112906 2.143528 2.174149 2.204771 2.235393 #> [30,] 2.083871 2.115444 2.147018 2.178592 2.210166 2.241739 2.273313 2.304887 #>          [,75]    [,76]    [,77]    [,78]    [,79]    [,80]    [,81]    [,82] #>  [1,] 2.517336 2.543674 2.570012 2.596350 2.622688 2.649026 2.675364 2.701701 #>  [2,] 2.614913 2.642996 2.671080 2.699163 2.727246 2.755329 2.783413 2.811496 #>  [3,] 2.540818 2.567473 2.594128 2.620784 2.647439 2.674094 2.700749 2.727405 #>  [4,] 2.501152 2.528125 2.555098 2.582070 2.609043 2.636015 2.662988 2.689960 #>  [5,] 2.442447 2.468627 2.494806 2.520985 2.547164 2.573344 2.599523 2.625702 #>  [6,] 2.693451 2.722169 2.750887 2.779605 2.808323 2.837040 2.865758 2.894476 #>  [7,] 2.713284 2.741843 2.770402 2.798961 2.827521 2.856080 2.884639 2.913198 #>  [8,] 2.584133 2.610947 2.637761 2.664574 2.691388 2.718202 2.745016 2.771830 #>  [9,] 2.403575 2.428802 2.454030 2.479257 2.504484 2.529712 2.554939 2.580166 #> [10,] 2.372001 2.397229 2.422456 2.447683 2.472910 2.498138 2.523365 2.548592 #> [11,] 1.821443 1.843497 1.865551 1.887605 1.909659 1.931713 1.953767 1.975821 #> [12,] 1.716567 1.735924 1.755281 1.774638 1.793995 1.813351 1.832708 1.852065 #> [13,] 1.845718 1.866820 1.887923 1.909025 1.930127 1.951229 1.972331 1.993433 #> [14,] 1.571233 1.589479 1.607725 1.625971 1.644217 1.662463 1.680710 1.698956 #> [15,] 1.782571 1.803673 1.824775 1.845877 1.866979 1.888081 1.909183 1.930285 #> [16,] 1.896332 1.918544 1.940757 1.962970 1.985183 2.007395 2.029608 2.051821 #> [17,] 1.817794 1.839372 1.860950 1.882528 1.904106 1.925684 1.947262 1.968840 #> [18,] 1.668810 1.688801 1.708793 1.728784 1.748776 1.768767 1.788759 1.808750 #> [19,] 1.842069 1.862695 1.883321 1.903947 1.924574 1.945200 1.965826 1.986452 #> [20,] 1.743699 1.763849 1.783999 1.804149 1.824299 1.844449 1.864599 1.884749 #> [21,] 2.176529 2.205088 2.233648 2.262207 2.290766 2.319325 2.347885 2.376444 #> [22,] 2.336461 2.368035 2.399608 2.431182 2.462756 2.494330 2.525904 2.557477 #> [23,] 2.203661 2.233013 2.262366 2.291718 2.321071 2.350423 2.379776 2.409128 #> [24,] 2.136864 2.165740 2.194617 2.223493 2.252370 2.281246 2.310123 2.338999 #> [25,] 2.376126 2.407383 2.438639 2.469896 2.501152 2.532409 2.563665 2.594922 #> [26,] 2.376126 2.407383 2.438639 2.469896 2.501152 2.532409 2.563665 2.594922 #> [27,] 2.356294 2.387709 2.419124 2.450539 2.481954 2.513369 2.544784 2.576200 #> [28,] 2.336461 2.368035 2.399608 2.431182 2.462756 2.494330 2.525904 2.557477 #> [29,] 2.266015 2.296637 2.327258 2.357880 2.388502 2.419124 2.449746 2.480368 #> [30,] 2.336461 2.368035 2.399608 2.431182 2.462756 2.494330 2.525904 2.557477 #>          [,83]    [,84]    [,85]    [,86]    [,87]    [,88]    [,89]    [,90] #>  [1,] 2.728039 2.754377 2.780715 2.807053 2.833391 2.859729 2.886067 2.912405 #>  [2,] 2.839579 2.867662 2.895745 2.923829 2.951912 2.979995 3.008078 3.036162 #>  [3,] 2.754060 2.780715 2.807371 2.834026 2.860681 2.887336 2.913992 2.940647 #>  [4,] 2.716933 2.743906 2.770878 2.797851 2.824823 2.851796 2.878769 2.905741 #>  [5,] 2.651881 2.678061 2.704240 2.730419 2.756599 2.782778 2.808957 2.835136 #>  [6,] 2.923194 2.951912 2.980630 3.009348 3.038066 3.066783 3.095501 3.124219 #>  [7,] 2.941758 2.970317 2.998876 3.027435 3.055994 3.084554 3.113113 3.141672 #>  [8,] 2.798644 2.825458 2.852272 2.879086 2.905900 2.932714 2.959528 2.986342 #>  [9,] 2.605393 2.630621 2.655848 2.681075 2.706303 2.731530 2.756757 2.781985 #> [10,] 2.573820 2.599047 2.624274 2.649502 2.674729 2.699956 2.725183 2.750411 #> [11,] 1.997876 2.019930 2.041984 2.064038 2.086092 2.108146 2.130200 2.152254 #> [12,] 1.871422 1.890778 1.910135 1.929492 1.948849 1.968206 1.987562 2.006919 #> [13,] 2.014535 2.035637 2.056739 2.077841 2.098943 2.120046 2.141148 2.162250 #> [14,] 1.717202 1.735448 1.753694 1.771940 1.790187 1.808433 1.826679 1.844925 #> [15,] 1.951387 1.972490 1.993592 2.014694 2.035796 2.056898 2.078000 2.099102 #> [16,] 2.074033 2.096246 2.118459 2.140672 2.162884 2.185097 2.207310 2.229522 #> [17,] 1.990418 2.011996 2.033575 2.055153 2.076731 2.098309 2.119887 2.141465 #> [18,] 1.828742 1.848733 1.868724 1.888716 1.908707 1.928699 1.948690 1.968682 #> [19,] 2.007078 2.027704 2.048330 2.068956 2.089582 2.110208 2.130835 2.151461 #> [20,] 1.904899 1.925050 1.945200 1.965350 1.985500 2.005650 2.025800 2.045950 #> [21,] 2.405003 2.433562 2.462121 2.490681 2.519240 2.547799 2.576358 2.604917 #> [22,] 2.589051 2.620625 2.652199 2.683773 2.715346 2.746920 2.778494 2.810068 #> [23,] 2.438481 2.467833 2.497186 2.526538 2.555891 2.585243 2.614596 2.643948 #> [24,] 2.367876 2.396753 2.425629 2.454506 2.483382 2.512259 2.541135 2.570012 #> [25,] 2.626178 2.657435 2.688691 2.719948 2.751204 2.782461 2.813717 2.844974 #> [26,] 2.626178 2.657435 2.688691 2.719948 2.751204 2.782461 2.813717 2.844974 #> [27,] 2.607615 2.639030 2.670445 2.701860 2.733275 2.764690 2.796106 2.827521 #> [28,] 2.589051 2.620625 2.652199 2.683773 2.715346 2.746920 2.778494 2.810068 #> [29,] 2.510989 2.541611 2.572233 2.602855 2.633477 2.664098 2.694720 2.725342 #> [30,] 2.589051 2.620625 2.652199 2.683773 2.715346 2.746920 2.778494 2.810068 #>          [,91]    [,92]    [,93]    [,94]    [,95]    [,96]    [,97]    [,98] #>  [1,] 2.938743 2.965081 2.991419 3.017757 3.044095 3.070433 3.096771 3.123108 #>  [2,] 3.064245 3.092328 3.120411 3.148494 3.176578 3.204661 3.232744 3.260827 #>  [3,] 2.967302 2.993957 3.020613 3.047268 3.073923 3.100578 3.127234 3.153889 #>  [4,] 2.932714 2.959686 2.986659 3.013632 3.040604 3.067577 3.094549 3.121522 #>  [5,] 2.861316 2.887495 2.913674 2.939854 2.966033 2.992212 3.018391 3.044571 #>  [6,] 3.152937 3.181655 3.210373 3.239091 3.267809 3.296526 3.325244 3.353962 #>  [7,] 3.170231 3.198790 3.227350 3.255909 3.284468 3.313027 3.341586 3.370146 #>  [8,] 3.013156 3.039969 3.066783 3.093597 3.120411 3.147225 3.174039 3.200853 #>  [9,] 2.807212 2.832439 2.857666 2.882894 2.908121 2.933348 2.958576 2.983803 #> [10,] 2.775638 2.800865 2.826093 2.851320 2.876547 2.901775 2.927002 2.952229 #> [11,] 2.174308 2.196362 2.218416 2.240470 2.262524 2.284578 2.306632 2.328686 #> [12,] 2.026276 2.045633 2.064990 2.084346 2.103703 2.123060 2.142417 2.161774 #> [13,] 2.183352 2.204454 2.225556 2.246658 2.267760 2.288862 2.309964 2.331066 #> [14,] 1.863171 1.881417 1.899664 1.917910 1.936156 1.954402 1.972648 1.990894 #> [15,] 2.120204 2.141306 2.162408 2.183510 2.204613 2.225715 2.246817 2.267919 #> [16,] 2.251735 2.273948 2.296161 2.318373 2.340586 2.362799 2.385012 2.407224 #> [17,] 2.163043 2.184621 2.206199 2.227777 2.249355 2.270933 2.292511 2.314089 #> [18,] 1.988673 2.008665 2.028656 2.048647 2.068639 2.088630 2.108622 2.128613 #> [19,] 2.172087 2.192713 2.213339 2.233965 2.254591 2.275217 2.295843 2.316469 #> [20,] 2.066100 2.086250 2.106401 2.126551 2.146701 2.166851 2.187001 2.207151 #> [21,] 2.633477 2.662036 2.690595 2.719154 2.747714 2.776273 2.804832 2.833391 #> [22,] 2.841642 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 #> [23,] 2.673301 2.702653 2.732006 2.761358 2.790711 2.820064 2.849416 2.878769 #> [24,] 2.598888 2.627765 2.656641 2.685518 2.714394 2.743271 2.772148 2.801024 #> [25,] 2.876230 2.907486 2.938743 2.969999 3.001256 3.032512 3.063769 3.095025 #> [26,] 2.876230 2.907486 2.938743 2.969999 3.001256 3.032512 3.063769 3.095025 #> [27,] 2.858936 2.890351 2.921766 2.953181 2.984596 3.016011 3.047427 3.078842 #> [28,] 2.841642 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 #> [29,] 2.755964 2.786586 2.817208 2.847829 2.878451 2.909073 2.939695 2.970317 #> [30,] 2.841642 2.873215 2.904789 2.936363 2.967937 2.999511 3.031084 3.062658 #>          [,99]   [,100]   [,101]   [,102]   [,103]   [,104]   [,105]   [,106] #>  [1,] 3.149446 3.175784 3.202122 3.228460 3.254798 3.281136 3.307474 3.333812 #>  [2,] 3.288911 3.316994 3.345077 3.373160 3.401243 3.429327 3.457410 3.485493 #>  [3,] 3.180544 3.207200 3.233855 3.260510 3.287165 3.313821 3.340476 3.367131 #>  [4,] 3.148494 3.175467 3.202440 3.229412 3.256385 3.283357 3.310330 3.337303 #>  [5,] 3.070750 3.096929 3.123108 3.149288 3.175467 3.201646 3.227826 3.254005 #>  [6,] 3.382680 3.411398 3.440116 3.468834 3.497551 3.526269 3.554987 3.583705 #>  [7,] 3.398705 3.427264 3.455823 3.484383 3.512942 3.541501 3.570060 3.598619 #>  [8,] 3.227667 3.254481 3.281295 3.308109 3.334923 3.361737 3.388551 3.415364 #>  [9,] 3.009030 3.034258 3.059485 3.084712 3.109940 3.135167 3.160394 3.185621 #> [10,] 2.977457 3.002684 3.027911 3.053138 3.078366 3.103593 3.128820 3.154048 #> [11,] 2.350740 2.372795 2.394849 2.416903 2.438957 2.461011 2.483065 2.505119 #> [12,] 2.181130 2.200487 2.219844 2.239201 2.258558 2.277914 2.297271 2.316628 #> [13,] 2.352168 2.373271 2.394373 2.415475 2.436577 2.457679 2.478781 2.499883 #> [14,] 2.009141 2.027387 2.045633 2.063879 2.082125 2.100371 2.118618 2.136864 #> [15,] 2.289021 2.310123 2.331225 2.352327 2.373429 2.394531 2.415633 2.436735 #> [16,] 2.429437 2.451650 2.473862 2.496075 2.518288 2.540501 2.562713 2.584926 #> [17,] 2.335668 2.357246 2.378824 2.400402 2.421980 2.443558 2.465136 2.486714 #> [18,] 2.148605 2.168596 2.188588 2.208579 2.228571 2.248562 2.268553 2.288545 #> [19,] 2.337096 2.357722 2.378348 2.398974 2.419600 2.440226 2.460852 2.481478 #> [20,] 2.227301 2.247451 2.267601 2.287752 2.307902 2.328052 2.348202 2.368352 #> [21,] 2.861950 2.890510 2.919069 2.947628 2.976187 3.004746 3.033306 3.061865 #> [22,] 3.094232 3.125806 3.157380 3.188953 3.220527 3.252101 3.283675 3.315249 #> [23,] 2.908121 2.937474 2.966826 2.996179 3.025531 3.054884 3.084236 3.113589 #> [24,] 2.829901 2.858777 2.887654 2.916530 2.945407 2.974283 3.003160 3.032036 #> [25,] 3.126282 3.157538 3.188795 3.220051 3.251308 3.282564 3.313821 3.345077 #> [26,] 3.126282 3.157538 3.188795 3.220051 3.251308 3.282564 3.313821 3.345077 #> [27,] 3.110257 3.141672 3.173087 3.204502 3.235917 3.267333 3.298748 3.330163 #> [28,] 3.094232 3.125806 3.157380 3.188953 3.220527 3.252101 3.283675 3.315249 #> [29,] 3.000939 3.031560 3.062182 3.092804 3.123426 3.154048 3.184669 3.215291 #> [30,] 3.094232 3.125806 3.157380 3.188953 3.220527 3.252101 3.283675 3.315249 #>         [,107]   [,108]   [,109]   [,110]   [,111]   [,112]   [,113]   [,114] #>  [1,] 3.360150 3.386488 3.412826 3.439164 3.465502 3.491840 3.518178 3.544516 #>  [2,] 3.513576 3.541660 3.569743 3.597826 3.625909 3.653993 3.682076 3.710159 #>  [3,] 3.393786 3.420442 3.447097 3.473752 3.500407 3.527063 3.553718 3.580373 #>  [4,] 3.364275 3.391248 3.418220 3.445193 3.472166 3.499138 3.526111 3.553083 #>  [5,] 3.280184 3.306363 3.332543 3.358722 3.384901 3.411081 3.437260 3.463439 #>  [6,] 3.612423 3.641141 3.669859 3.698577 3.727294 3.756012 3.784730 3.813448 #>  [7,] 3.627179 3.655738 3.684297 3.712856 3.741415 3.769975 3.798534 3.827093 #>  [8,] 3.442178 3.468992 3.495806 3.522620 3.549434 3.576248 3.603062 3.629876 #>  [9,] 3.210849 3.236076 3.261303 3.286531 3.311758 3.336985 3.362213 3.387440 #> [10,] 3.179275 3.204502 3.229730 3.254957 3.280184 3.305411 3.330639 3.355866 #> [11,] 2.527173 2.549227 2.571281 2.593335 2.615389 2.637443 2.659497 2.681551 #> [12,] 2.335985 2.355342 2.374698 2.394055 2.413412 2.432769 2.452126 2.471482 #> [13,] 2.520985 2.542087 2.563189 2.584291 2.605393 2.626496 2.647598 2.668700 #> [14,] 2.155110 2.173356 2.191602 2.209848 2.228095 2.246341 2.264587 2.282833 #> [15,] 2.457838 2.478940 2.500042 2.521144 2.542246 2.563348 2.584450 2.605552 #> [16,] 2.607139 2.629351 2.651564 2.673777 2.695990 2.718202 2.740415 2.762628 #> [17,] 2.508292 2.529870 2.551448 2.573026 2.594604 2.616182 2.637761 2.659339 #> [18,] 2.308536 2.328528 2.348519 2.368511 2.388502 2.408494 2.428485 2.448476 #> [19,] 2.502104 2.522730 2.543356 2.563983 2.584609 2.605235 2.625861 2.646487 #> [20,] 2.388502 2.408652 2.428802 2.448952 2.469103 2.489253 2.509403 2.529553 #> [21,] 3.090424 3.118983 3.147542 3.176102 3.204661 3.233220 3.261779 3.290339 #> [22,] 3.346822 3.378396 3.409970 3.441544 3.473118 3.504691 3.536265 3.567839 #> [23,] 3.142941 3.172294 3.201646 3.230999 3.260351 3.289704 3.319056 3.348409 #> [24,] 3.060913 3.089789 3.118666 3.147542 3.176419 3.205296 3.234172 3.263049 #> [25,] 3.376334 3.407590 3.438846 3.470103 3.501359 3.532616 3.563872 3.595129 #> [26,] 3.376334 3.407590 3.438846 3.470103 3.501359 3.532616 3.563872 3.595129 #> [27,] 3.361578 3.392993 3.424408 3.455823 3.487238 3.518654 3.550069 3.581484 #> [28,] 3.346822 3.378396 3.409970 3.441544 3.473118 3.504691 3.536265 3.567839 #> [29,] 3.245913 3.276535 3.307157 3.337779 3.368400 3.399022 3.429644 3.460266 #> [30,] 3.346822 3.378396 3.409970 3.441544 3.473118 3.504691 3.536265 3.567839 #>         [,115]   [,116]   [,117]   [,118]   [,119]   [,120]   [,121]   [,122] #>  [1,] 3.570853 3.597191 3.623529 3.649867 3.676205 3.702543 3.728881 3.755219 #>  [2,] 3.738242 3.766325 3.794409 3.822492 3.850575 3.878658 3.906742 3.934825 #>  [3,] 3.607028 3.633684 3.660339 3.686994 3.713650 3.740305 3.766960 3.793615 #>  [4,] 3.580056 3.607028 3.634001 3.660974 3.687946 3.714919 3.741891 3.768864 #>  [5,] 3.489618 3.515798 3.541977 3.568156 3.594335 3.620515 3.646694 3.672873 #>  [6,] 3.842166 3.870884 3.899602 3.928320 3.957037 3.985755 4.014473 4.043191 #>  [7,] 3.855652 3.884211 3.912771 3.941330 3.969889 3.998448 4.027008 4.055567 #>  [8,] 3.656690 3.683504 3.710318 3.737132 3.763945 3.790759 3.817573 3.844387 #>  [9,] 3.412667 3.437894 3.463122 3.488349 3.513576 3.538804 3.564031 3.589258 #> [10,] 3.381093 3.406321 3.431548 3.456775 3.482003 3.507230 3.532457 3.557685 #> [11,] 2.703605 2.725659 2.747714 2.769768 2.791822 2.813876 2.835930 2.857984 #> [12,] 2.490839 2.510196 2.529553 2.548910 2.568266 2.587623 2.606980 2.626337 #> [13,] 2.689802 2.710904 2.732006 2.753108 2.774210 2.795312 2.816414 2.837516 #> [14,] 2.301079 2.319325 2.337572 2.355818 2.374064 2.392310 2.410556 2.428802 #> [15,] 2.626654 2.647756 2.668858 2.689960 2.711063 2.732165 2.753267 2.774369 #> [16,] 2.784840 2.807053 2.829266 2.851479 2.873691 2.895904 2.918117 2.940330 #> [17,] 2.680917 2.702495 2.724073 2.745651 2.767229 2.788807 2.810385 2.831963 #> [18,] 2.468468 2.488459 2.508451 2.528442 2.548434 2.568425 2.588417 2.608408 #> [19,] 2.667113 2.687739 2.708365 2.728991 2.749617 2.770244 2.790870 2.811496 #> [20,] 2.549703 2.569853 2.590003 2.610153 2.630303 2.650454 2.670604 2.690754 #> [21,] 3.318898 3.347457 3.376016 3.404575 3.433135 3.461694 3.490253 3.518812 #> [22,] 3.599413 3.630986 3.662560 3.694134 3.725708 3.757282 3.788855 3.820429 #> [23,] 3.377761 3.407114 3.436467 3.465819 3.495172 3.524524 3.553877 3.583229 #> [24,] 3.291925 3.320802 3.349678 3.378555 3.407431 3.436308 3.465184 3.494061 #> [25,] 3.626385 3.657642 3.688898 3.720155 3.751411 3.782668 3.813924 3.845181 #> [26,] 3.626385 3.657642 3.688898 3.720155 3.751411 3.782668 3.813924 3.845181 #> [27,] 3.612899 3.644314 3.675729 3.707144 3.738560 3.769975 3.801390 3.832805 #> [28,] 3.599413 3.630986 3.662560 3.694134 3.725708 3.757282 3.788855 3.820429 #> [29,] 3.490888 3.521510 3.552131 3.582753 3.613375 3.643997 3.674619 3.705240 #> [30,] 3.599413 3.630986 3.662560 3.694134 3.725708 3.757282 3.788855 3.820429 #>         [,123]   [,124]   [,125]   [,126]   [,127]   [,128]   [,129]   [,130] #>  [1,] 3.781557 3.807895 3.834233 3.860571 3.886909 3.913247 3.939585 3.965923 #>  [2,] 3.962908 3.990991 4.019074 4.047158 4.075241 4.103324 4.131407 4.159491 #>  [3,] 3.820271 3.846926 3.873581 3.900236 3.926892 3.953547 3.980202 4.006857 #>  [4,] 3.795837 3.822809 3.849782 3.876754 3.903727 3.930700 3.957672 3.984645 #>  [5,] 3.699053 3.725232 3.751411 3.777590 3.803770 3.829949 3.856128 3.882308 #>  [6,] 4.071909 4.100627 4.129345 4.158063 4.186780 4.215498 4.244216 4.272934 #>  [7,] 4.084126 4.112685 4.141244 4.169804 4.198363 4.226922 4.255481 4.284040 #>  [8,] 3.871201 3.898015 3.924829 3.951643 3.978457 4.005271 4.032085 4.058899 #>  [9,] 3.614486 3.639713 3.664940 3.690168 3.715395 3.740622 3.765849 3.791077 #> [10,] 3.582912 3.608139 3.633366 3.658594 3.683821 3.709048 3.734276 3.759503 #> [11,] 2.880038 2.902092 2.924146 2.946200 2.968254 2.990308 3.012362 3.034416 #> [12,] 2.645694 2.665050 2.684407 2.703764 2.723121 2.742478 2.761834 2.781191 #> [13,] 2.858618 2.879721 2.900823 2.921925 2.943027 2.964129 2.985231 3.006333 #> [14,] 2.447048 2.465295 2.483541 2.501787 2.520033 2.538279 2.556525 2.574772 #> [15,] 2.795471 2.816573 2.837675 2.858777 2.879879 2.900981 2.922083 2.943185 #> [16,] 2.962542 2.984755 3.006968 3.029180 3.051393 3.073606 3.095819 3.118031 #> [17,] 2.853541 2.875119 2.896697 2.918275 2.939854 2.961432 2.983010 3.004588 #> [18,] 2.628399 2.648391 2.668382 2.688374 2.708365 2.728357 2.748348 2.768340 #> [19,] 2.832122 2.852748 2.873374 2.894000 2.914626 2.935252 2.955878 2.976505 #> [20,] 2.710904 2.731054 2.751204 2.771354 2.791504 2.811654 2.831805 2.851955 #> [21,] 3.547371 3.575931 3.604490 3.633049 3.661608 3.690168 3.718727 3.747286 #> [22,] 3.852003 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.073020 #> [23,] 3.612582 3.641934 3.671287 3.700639 3.729992 3.759344 3.788697 3.818049 #> [24,] 3.522937 3.551814 3.580691 3.609567 3.638444 3.667320 3.696197 3.725073 #> [25,] 3.876437 3.907694 3.938950 3.970206 4.001463 4.032719 4.063976 4.095232 #> [26,] 3.876437 3.907694 3.938950 3.970206 4.001463 4.032719 4.063976 4.095232 #> [27,] 3.864220 3.895635 3.927050 3.958465 3.989881 4.021296 4.052711 4.084126 #> [28,] 3.852003 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.073020 #> [29,] 3.735862 3.766484 3.797106 3.827728 3.858350 3.888971 3.919593 3.950215 #> [30,] 3.852003 3.883577 3.915151 3.946724 3.978298 4.009872 4.041446 4.073020 #>         [,131]   [,132]   [,133]   [,134]   [,135]   [,136]   [,137]   [,138] #>  [1,] 3.992261 4.018598 4.044936 4.071274 4.097612 4.123950 4.150288 4.176626 #>  [2,] 4.187574 4.215657 4.243740 4.271823 4.299907 4.327990 4.356073 4.384156 #>  [3,] 4.033513 4.060168 4.086823 4.113479 4.140134 4.166789 4.193444 4.220100 #>  [4,] 4.011617 4.038590 4.065562 4.092535 4.119508 4.146480 4.173453 4.200425 #>  [5,] 3.908487 3.934666 3.960845 3.987025 4.013204 4.039383 4.065562 4.091742 #>  [6,] 4.301652 4.330370 4.359088 4.387806 4.416523 4.445241 4.473959 4.502677 #>  [7,] 4.312600 4.341159 4.369718 4.398277 4.426837 4.455396 4.483955 4.512514 #>  [8,] 4.085713 4.112527 4.139340 4.166154 4.192968 4.219782 4.246596 4.273410 #>  [9,] 3.816304 3.841531 3.866759 3.891986 3.917213 3.942441 3.967668 3.992895 #> [10,] 3.784730 3.809958 3.835185 3.860412 3.885639 3.910867 3.936094 3.961321 #> [11,] 3.056470 3.078524 3.100578 3.122633 3.144687 3.166741 3.188795 3.210849 #> [12,] 2.800548 2.819905 2.839262 2.858618 2.877975 2.897332 2.916689 2.936046 #> [13,] 3.027435 3.048537 3.069639 3.090741 3.111843 3.132946 3.154048 3.175150 #> [14,] 2.593018 2.611264 2.629510 2.647756 2.666002 2.684249 2.702495 2.720741 #> [15,] 2.964288 2.985390 3.006492 3.027594 3.048696 3.069798 3.090900 3.112002 #> [16,] 3.140244 3.162457 3.184669 3.206882 3.229095 3.251308 3.273520 3.295733 #> [17,] 3.026166 3.047744 3.069322 3.090900 3.112478 3.134056 3.155634 3.177212 #> [18,] 2.788331 2.808323 2.828314 2.848305 2.868297 2.888288 2.908280 2.928271 #> [19,] 2.997131 3.017757 3.038383 3.059009 3.079635 3.100261 3.120887 3.141513 #> [20,] 2.872105 2.892255 2.912405 2.932555 2.952705 2.972855 2.993005 3.013156 #> [21,] 3.775845 3.804404 3.832964 3.861523 3.890082 3.918641 3.947200 3.975760 #> [22,] 4.104593 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.325610 #> [23,] 3.847402 3.876754 3.906107 3.935459 3.964812 3.994164 4.023517 4.052870 #> [24,] 3.753950 3.782826 3.811703 3.840579 3.869456 3.898332 3.927209 3.956086 #> [25,] 4.126489 4.157745 4.189002 4.220258 4.251515 4.282771 4.314028 4.345284 #> [26,] 4.126489 4.157745 4.189002 4.220258 4.251515 4.282771 4.314028 4.345284 #> [27,] 4.115541 4.146956 4.178371 4.209787 4.241202 4.272617 4.304032 4.335447 #> [28,] 4.104593 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.325610 #> [29,] 3.980837 4.011459 4.042080 4.072702 4.103324 4.133946 4.164568 4.195190 #> [30,] 4.104593 4.136167 4.167741 4.199315 4.230889 4.262462 4.294036 4.325610 #>         [,139]   [,140]   [,141]   [,142]   [,143]   [,144]   [,145]   [,146] #>  [1,] 4.202964 4.229302 4.255640 4.281978 4.308316 4.334654 4.360992 4.387330 #>  [2,] 4.412240 4.440323 4.468406 4.496489 4.524572 4.552656 4.580739 4.608822 #>  [3,] 4.246755 4.273410 4.300065 4.326721 4.353376 4.380031 4.406686 4.433342 #>  [4,] 4.227398 4.254371 4.281343 4.308316 4.335288 4.362261 4.389234 4.416206 #>  [5,] 4.117921 4.144100 4.170280 4.196459 4.222638 4.248817 4.274997 4.301176 #>  [6,] 4.531395 4.560113 4.588831 4.617549 4.646266 4.674984 4.703702 4.732420 #>  [7,] 4.541073 4.569633 4.598192 4.626751 4.655310 4.683869 4.712429 4.740988 #>  [8,] 4.300224 4.327038 4.353852 4.380666 4.407480 4.434294 4.461108 4.487922 #>  [9,] 4.018122 4.043350 4.068577 4.093804 4.119032 4.144259 4.169486 4.194714 #> [10,] 3.986549 4.011776 4.037003 4.062231 4.087458 4.112685 4.137912 4.163140 #> [11,] 3.232903 3.254957 3.277011 3.299065 3.321119 3.343173 3.365227 3.387281 #> [12,] 2.955402 2.974759 2.994116 3.013473 3.032830 3.052186 3.071543 3.090900 #> [13,] 3.196252 3.217354 3.238456 3.259558 3.280660 3.301762 3.322864 3.343966 #> [14,] 2.738987 2.757233 2.775479 2.793726 2.811972 2.830218 2.848464 2.866710 #> [15,] 3.133104 3.154206 3.175308 3.196410 3.217513 3.238615 3.259717 3.280819 #> [16,] 3.317946 3.340159 3.362371 3.384584 3.406797 3.429009 3.451222 3.473435 #> [17,] 3.198790 3.220368 3.241947 3.263525 3.285103 3.306681 3.328259 3.349837 #> [18,] 2.948263 2.968254 2.988246 3.008237 3.028228 3.048220 3.068211 3.088203 #> [19,] 3.162139 3.182766 3.203392 3.224018 3.244644 3.265270 3.285896 3.306522 #> [20,] 3.033306 3.053456 3.073606 3.093756 3.113906 3.134056 3.154206 3.174356 #> [21,] 4.004319 4.032878 4.061437 4.089996 4.118556 4.147115 4.175674 4.204233 #> [22,] 4.357184 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.578200 #> [23,] 4.082222 4.111575 4.140927 4.170280 4.199632 4.228985 4.258337 4.287690 #> [24,] 3.984962 4.013839 4.042715 4.071592 4.100468 4.129345 4.158221 4.187098 #> [25,] 4.376541 4.407797 4.439054 4.470310 4.501566 4.532823 4.564079 4.595336 #> [26,] 4.376541 4.407797 4.439054 4.470310 4.501566 4.532823 4.564079 4.595336 #> [27,] 4.366862 4.398277 4.429692 4.461108 4.492523 4.523938 4.555353 4.586768 #> [28,] 4.357184 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.578200 #> [29,] 4.225811 4.256433 4.287055 4.317677 4.348299 4.378921 4.409542 4.440164 #> [30,] 4.357184 4.388758 4.420331 4.451905 4.483479 4.515053 4.546627 4.578200 #>         [,147]   [,148]   [,149]   [,150]   [,151]   [,152]   [,153]   [,154] #>  [1,] 4.413668 4.440005 4.466343 4.492681 4.519019 4.545357 4.571695 4.598033 #>  [2,] 4.636905 4.664989 4.693072 4.721155 4.749238 4.777322 4.805405 4.833488 #>  [3,] 4.459997 4.486652 4.513307 4.539963 4.566618 4.593273 4.619929 4.646584 #>  [4,] 4.443179 4.470151 4.497124 4.524097 4.551069 4.578042 4.605014 4.631987 #>  [5,] 4.327355 4.353535 4.379714 4.405893 4.432072 4.458252 4.484431 4.510610 #>  [6,] 4.761138 4.789856 4.818574 4.847292 4.876009 4.904727 4.933445 4.962163 #>  [7,] 4.769547 4.798106 4.826665 4.855225 4.883784 4.912343 4.940902 4.969462 #>  [8,] 4.514735 4.541549 4.568363 4.595177 4.621991 4.648805 4.675619 4.702433 #>  [9,] 4.219941 4.245168 4.270396 4.295623 4.320850 4.346077 4.371305 4.396532 #> [10,] 4.188367 4.213594 4.238822 4.264049 4.289276 4.314504 4.339731 4.364958 #> [11,] 3.409335 3.431389 3.453443 3.475497 3.497551 3.519606 3.541660 3.563714 #> [12,] 3.110257 3.129614 3.148970 3.168327 3.187684 3.207041 3.226398 3.245754 #> [13,] 3.365068 3.386171 3.407273 3.428375 3.449477 3.470579 3.491681 3.512783 #> [14,] 2.884956 2.903203 2.921449 2.939695 2.957941 2.976187 2.994433 3.012680 #> [15,] 3.301921 3.323023 3.344125 3.365227 3.386329 3.407431 3.428533 3.449635 #> [16,] 3.495648 3.517860 3.540073 3.562286 3.584498 3.606711 3.628924 3.651137 #> [17,] 3.371415 3.392993 3.414571 3.436149 3.457727 3.479305 3.500883 3.522461 #> [18,] 3.108194 3.128186 3.148177 3.168169 3.188160 3.208151 3.228143 3.248134 #> [19,] 3.327148 3.347774 3.368400 3.389026 3.409653 3.430279 3.450905 3.471531 #> [20,] 3.194507 3.214657 3.234807 3.254957 3.275107 3.295257 3.315407 3.335557 #> [21,] 4.232793 4.261352 4.289911 4.318470 4.347029 4.375589 4.404148 4.432707 #> [22,] 4.609774 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 #> [23,] 4.317042 4.346395 4.375747 4.405100 4.434452 4.463805 4.493157 4.522510 #> [24,] 4.215974 4.244851 4.273727 4.302604 4.331480 4.360357 4.389234 4.418110 #> [25,] 4.626592 4.657849 4.689105 4.720362 4.751618 4.782875 4.814131 4.845388 #> [26,] 4.626592 4.657849 4.689105 4.720362 4.751618 4.782875 4.814131 4.845388 #> [27,] 4.618183 4.649598 4.681014 4.712429 4.743844 4.775259 4.806674 4.838089 #> [28,] 4.609774 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 #> [29,] 4.470786 4.501408 4.532030 4.562651 4.593273 4.623895 4.654517 4.685139 #> [30,] 4.609774 4.641348 4.672922 4.704496 4.736069 4.767643 4.799217 4.830791 #>         [,155]   [,156]   [,157]   [,158]   [,159]   [,160]   [,161]   [,162] #>  [1,] 4.624371 4.650709 4.677047 4.703385 4.729723 4.756061 4.782399 4.808737 #>  [2,] 4.861571 4.889654 4.917738 4.945821 4.973904 5.001987 5.030071 5.058154 #>  [3,] 4.673239 4.699894 4.726550 4.753205 4.779860 4.806515 4.833171 4.859826 #>  [4,] 4.658959 4.685932 4.712905 4.739877 4.766850 4.793822 4.820795 4.847768 #>  [5,] 4.536789 4.562969 4.589148 4.615327 4.641507 4.667686 4.693865 4.720044 #>  [6,] 4.990881 5.019599 5.048317 5.077035 5.105752 5.134470 5.163188 5.191906 #>  [7,] 4.998021 5.026580 5.055139 5.083698 5.112258 5.140817 5.169376 5.197935 #>  [8,] 4.729247 4.756061 4.782875 4.809689 4.836503 4.863316 4.890130 4.916944 #>  [9,] 4.421759 4.446987 4.472214 4.497441 4.522669 4.547896 4.573123 4.598350 #> [10,] 4.390186 4.415413 4.440640 4.465867 4.491095 4.516322 4.541549 4.566777 #> [11,] 3.585768 3.607822 3.629876 3.651930 3.673984 3.696038 3.718092 3.740146 #> [12,] 3.265111 3.284468 3.303825 3.323182 3.342538 3.361895 3.381252 3.400609 #> [13,] 3.533885 3.554987 3.576089 3.597191 3.618294 3.639396 3.660498 3.681600 #> [14,] 3.030926 3.049172 3.067418 3.085664 3.103910 3.122157 3.140403 3.158649 #> [15,] 3.470738 3.491840 3.512942 3.534044 3.555146 3.576248 3.597350 3.618452 #> [16,] 3.673349 3.695562 3.717775 3.739987 3.762200 3.784413 3.806626 3.828838 #> [17,] 3.544040 3.565618 3.587196 3.608774 3.630352 3.651930 3.673508 3.695086 #> [18,] 3.268126 3.288117 3.308109 3.328100 3.348092 3.368083 3.388075 3.408066 #> [19,] 3.492157 3.512783 3.533409 3.554035 3.574661 3.595287 3.615914 3.636540 #> [20,] 3.355707 3.375858 3.396008 3.416158 3.436308 3.456458 3.476608 3.496758 #> [21,] 4.461266 4.489825 4.518385 4.546944 4.575503 4.604062 4.632622 4.661181 #> [22,] 4.862365 4.893938 4.925512 4.957086 4.988660 5.020233 5.051807 5.083381 #> [23,] 4.551862 4.581215 4.610567 4.639920 4.669273 4.698625 4.727978 4.757330 #> [24,] 4.446987 4.475863 4.504740 4.533616 4.562493 4.591369 4.620246 4.649122 #> [25,] 4.876644 4.907901 4.939157 4.970414 5.001670 5.032926 5.064183 5.095439 #> [26,] 4.876644 4.907901 4.939157 4.970414 5.001670 5.032926 5.064183 5.095439 #> [27,] 4.869504 4.900919 4.932335 4.963750 4.995165 5.026580 5.057995 5.089410 #> [28,] 4.862365 4.893938 4.925512 4.957086 4.988660 5.020233 5.051807 5.083381 #> [29,] 4.715761 4.746382 4.777004 4.807626 4.838248 4.868870 4.899491 4.930113 #> [30,] 4.862365 4.893938 4.925512 4.957086 4.988660 5.020233 5.051807 5.083381 #>         [,163]   [,164]   [,165]   [,166]   [,167]   [,168]   [,169]   [,170] #>  [1,] 4.835075 4.861413 4.887750 4.914088 4.940426 4.966764 4.993102 5.019440 #>  [2,] 5.086237 5.114320 5.142403 5.170487 5.198570 5.226653 5.254736 5.282820 #>  [3,] 4.886481 4.913136 4.939792 4.966447 4.993102 5.019757 5.046413 5.073068 #>  [4,] 4.874740 4.901713 4.928685 4.955658 4.982631 5.009603 5.036576 5.063548 #>  [5,] 4.746224 4.772403 4.798582 4.824762 4.850941 4.877120 4.903299 4.929479 #>  [6,] 5.220624 5.249342 5.278060 5.306778 5.335495 5.364213 5.392931 5.421649 #>  [7,] 5.226494 5.255054 5.283613 5.312172 5.340731 5.369291 5.397850 5.426409 #>  [8,] 4.943758 4.970572 4.997386 5.024200 5.051014 5.077828 5.104642 5.131456 #>  [9,] 4.623578 4.648805 4.674032 4.699260 4.724487 4.749714 4.774942 4.800169 #> [10,] 4.592004 4.617231 4.642459 4.667686 4.692913 4.718140 4.743368 4.768595 #> [11,] 3.762200 3.784254 3.806308 3.828362 3.850416 3.872470 3.894525 3.916579 #> [12,] 3.419966 3.439322 3.458679 3.478036 3.497393 3.516750 3.536106 3.555463 #> [13,] 3.702702 3.723804 3.744906 3.766008 3.787110 3.808212 3.829314 3.850416 #> [14,] 3.176895 3.195141 3.213387 3.231634 3.249880 3.268126 3.286372 3.304618 #> [15,] 3.639554 3.660656 3.681758 3.702861 3.723963 3.745065 3.766167 3.787269 #> [16,] 3.851051 3.873264 3.895477 3.917689 3.939902 3.962115 3.984327 4.006540 #> [17,] 3.716664 3.738242 3.759820 3.781398 3.802976 3.824554 3.846133 3.867711 #> [18,] 3.428057 3.448049 3.468040 3.488032 3.508023 3.528015 3.548006 3.567998 #> [19,] 3.657166 3.677792 3.698418 3.719044 3.739670 3.760296 3.780922 3.801548 #> [20,] 3.516908 3.537058 3.557209 3.577359 3.597509 3.617659 3.637809 3.657959 #> [21,] 4.689740 4.718299 4.746858 4.775418 4.803977 4.832536 4.861095 4.889654 #> [22,] 5.114955 5.146529 5.178102 5.209676 5.241250 5.272824 5.304398 5.335971 #> [23,] 4.786683 4.816035 4.845388 4.874740 4.904093 4.933445 4.962798 4.992150 #> [24,] 4.677999 4.706875 4.735752 4.764629 4.793505 4.822382 4.851258 4.880135 #> [25,] 5.126696 5.157952 5.189209 5.220465 5.251722 5.282978 5.314235 5.345491 #> [26,] 5.126696 5.157952 5.189209 5.220465 5.251722 5.282978 5.314235 5.345491 #> [27,] 5.120825 5.152241 5.183656 5.215071 5.246486 5.277901 5.309316 5.340731 #> [28,] 5.114955 5.146529 5.178102 5.209676 5.241250 5.272824 5.304398 5.335971 #> [29,] 4.960735 4.991357 5.021979 5.052601 5.083222 5.113844 5.144466 5.175088 #> [30,] 5.114955 5.146529 5.178102 5.209676 5.241250 5.272824 5.304398 5.335971 #>         [,171]   [,172]   [,173]   [,174]   [,175]   [,176]   [,177]   [,178] #>  [1,] 5.045778 5.072116 5.098454 5.124792 5.151130 5.177468 5.203806 5.230144 #>  [2,] 5.310903 5.338986 5.367069 5.395152 5.423236 5.451319 5.479402 5.507485 #>  [3,] 5.099723 5.126379 5.153034 5.179689 5.206344 5.233000 5.259655 5.286310 #>  [4,] 5.090521 5.117493 5.144466 5.171439 5.198411 5.225384 5.252356 5.279329 #>  [5,] 4.955658 4.981837 5.008016 5.034196 5.060375 5.086554 5.112734 5.138913 #>  [6,] 5.450367 5.479085 5.507803 5.536521 5.565238 5.593956 5.622674 5.651392 #>  [7,] 5.454968 5.483527 5.512087 5.540646 5.569205 5.597764 5.626323 5.654883 #>  [8,] 5.158270 5.185084 5.211898 5.238711 5.265525 5.292339 5.319153 5.345967 #>  [9,] 4.825396 4.850623 4.875851 4.901078 4.926305 4.951533 4.976760 5.001987 #> [10,] 4.793822 4.819050 4.844277 4.869504 4.894732 4.919959 4.945186 4.970414 #> [11,] 3.938633 3.960687 3.982741 4.004795 4.026849 4.048903 4.070957 4.093011 #> [12,] 3.574820 3.594177 3.613534 3.632890 3.652247 3.671604 3.690961 3.710318 #> [13,] 3.871519 3.892621 3.913723 3.934825 3.955927 3.977029 3.998131 4.019233 #> [14,] 3.322864 3.341110 3.359357 3.377603 3.395849 3.414095 3.432341 3.450587 #> [15,] 3.808371 3.829473 3.850575 3.871677 3.892779 3.913881 3.934983 3.956086 #> [16,] 4.028753 4.050966 4.073178 4.095391 4.117604 4.139816 4.162029 4.184242 #> [17,] 3.889289 3.910867 3.932445 3.954023 3.975601 3.997179 4.018757 4.040335 #> [18,] 3.587989 3.607980 3.627972 3.647963 3.667955 3.687946 3.707938 3.727929 #> [19,] 3.822175 3.842801 3.863427 3.884053 3.904679 3.925305 3.945931 3.966557 #> [20,] 3.678109 3.698259 3.718409 3.738560 3.758710 3.778860 3.799010 3.819160 #> [21,] 4.918214 4.946773 4.975332 5.003891 5.032450 5.061010 5.089569 5.118128 #> [22,] 5.367545 5.399119 5.430693 5.462267 5.493840 5.525414 5.556988 5.588562 #> [23,] 5.021503 5.050855 5.080208 5.109560 5.138913 5.168265 5.197618 5.226970 #> [24,] 4.909011 4.937888 4.966764 4.995641 5.024517 5.053394 5.082270 5.111147 #> [25,] 5.376748 5.408004 5.439261 5.470517 5.501774 5.533030 5.564286 5.595543 #> [26,] 5.376748 5.408004 5.439261 5.470517 5.501774 5.533030 5.564286 5.595543 #> [27,] 5.372146 5.403562 5.434977 5.466392 5.497807 5.529222 5.560637 5.592052 #> [28,] 5.367545 5.399119 5.430693 5.462267 5.493840 5.525414 5.556988 5.588562 #> [29,] 5.205710 5.236332 5.266953 5.297575 5.328197 5.358819 5.389441 5.420062 #> [30,] 5.367545 5.399119 5.430693 5.462267 5.493840 5.525414 5.556988 5.588562 #>         [,179]   [,180]   [,181]   [,182]   [,183]   [,184]   [,185]   [,186] #>  [1,] 5.256482 5.282820 5.309158 5.335495 5.361833 5.388171 5.414509 5.440847 #>  [2,] 5.535569 5.563652 5.591735 5.619818 5.647902 5.675985 5.704068 5.732151 #>  [3,] 5.312965 5.339621 5.366276 5.392931 5.419586 5.446242 5.472897 5.499552 #>  [4,] 5.306302 5.333274 5.360247 5.387219 5.414192 5.441165 5.468137 5.495110 #>  [5,] 5.165092 5.191271 5.217451 5.243630 5.269809 5.295989 5.322168 5.348347 #>  [6,] 5.680110 5.708828 5.737546 5.766264 5.794981 5.823699 5.852417 5.881135 #>  [7,] 5.683442 5.712001 5.740560 5.769119 5.797679 5.826238 5.854797 5.883356 #>  [8,] 5.372781 5.399595 5.426409 5.453223 5.480037 5.506851 5.533665 5.560479 #>  [9,] 5.027215 5.052442 5.077669 5.102897 5.128124 5.153351 5.178578 5.203806 #> [10,] 4.995641 5.020868 5.046095 5.071323 5.096550 5.121777 5.147005 5.172232 #> [11,] 4.115065 4.137119 4.159173 4.181227 4.203281 4.225335 4.247389 4.269444 #> [12,] 3.729674 3.749031 3.768388 3.787745 3.807102 3.826458 3.845815 3.865172 #> [13,] 4.040335 4.061437 4.082539 4.103641 4.124744 4.145846 4.166948 4.188050 #> [14,] 3.468834 3.487080 3.505326 3.523572 3.541818 3.560064 3.578311 3.596557 #> [15,] 3.977188 3.998290 4.019392 4.040494 4.061596 4.082698 4.103800 4.124902 #> [16,] 4.206455 4.228667 4.250880 4.273093 4.295305 4.317518 4.339731 4.361944 #> [17,] 4.061913 4.083491 4.105069 4.126647 4.148226 4.169804 4.191382 4.212960 #> [18,] 3.747921 3.767912 3.787903 3.807895 3.827886 3.847878 3.867869 3.887861 #> [19,] 3.987183 4.007809 4.028436 4.049062 4.069688 4.090314 4.110940 4.131566 #> [20,] 3.839310 3.859460 3.879610 3.899760 3.919911 3.940061 3.960211 3.980361 #> [21,] 5.146687 5.175247 5.203806 5.232365 5.260924 5.289483 5.318043 5.346602 #> [22,] 5.620136 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 #> [23,] 5.256323 5.285675 5.315028 5.344381 5.373733 5.403086 5.432438 5.461791 #> [24,] 5.140024 5.168900 5.197777 5.226653 5.255530 5.284406 5.313283 5.342159 #> [25,] 5.626799 5.658056 5.689312 5.720569 5.751825 5.783082 5.814338 5.845595 #> [26,] 5.626799 5.658056 5.689312 5.720569 5.751825 5.783082 5.814338 5.845595 #> [27,] 5.623468 5.654883 5.686298 5.717713 5.749128 5.780543 5.811958 5.843373 #> [28,] 5.620136 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 #> [29,] 5.450684 5.481306 5.511928 5.542550 5.573172 5.603793 5.634415 5.665037 #> [30,] 5.620136 5.651709 5.683283 5.714857 5.746431 5.778005 5.809578 5.841152 #>         [,187]   [,188]   [,189]   [,190]   [,191]   [,192]   [,193]   [,194] #>  [1,] 5.467185 5.493523 5.519861 5.546199 5.572537 5.598875 5.625213 5.651551 #>  [2,] 5.760234 5.788318 5.816401 5.844484 5.872567 5.900651 5.928734 5.956817 #>  [3,] 5.526208 5.552863 5.579518 5.606173 5.632829 5.659484 5.686139 5.712794 #>  [4,] 5.522082 5.549055 5.576027 5.603000 5.629973 5.656945 5.683918 5.710890 #>  [5,] 5.374526 5.400706 5.426885 5.453064 5.479243 5.505423 5.531602 5.557781 #>  [6,] 5.909853 5.938571 5.967289 5.996007 6.024724 6.053442 6.082160 6.110878 #>  [7,] 5.911916 5.940475 5.969034 5.997593 6.026152 6.054712 6.083271 6.111830 #>  [8,] 5.587293 5.614106 5.640920 5.667734 5.694548 5.721362 5.748176 5.774990 #>  [9,] 5.229033 5.254260 5.279488 5.304715 5.329942 5.355170 5.380397 5.405624 #> [10,] 5.197459 5.222687 5.247914 5.273141 5.298368 5.323596 5.348823 5.374050 #> [11,] 4.291498 4.313552 4.335606 4.357660 4.379714 4.401768 4.423822 4.445876 #> [12,] 3.884529 3.903886 3.923242 3.942599 3.961956 3.981313 4.000670 4.020026 #> [13,] 4.209152 4.230254 4.251356 4.272458 4.293560 4.314662 4.335764 4.356866 #> [14,] 3.614803 3.633049 3.651295 3.669541 3.687788 3.706034 3.724280 3.742526 #> [15,] 4.146004 4.167106 4.188208 4.209311 4.230413 4.251515 4.272617 4.293719 #> [16,] 4.384156 4.406369 4.428582 4.450795 4.473007 4.495220 4.517433 4.539645 #> [17,] 4.234538 4.256116 4.277694 4.299272 4.320850 4.342428 4.364006 4.385584 #> [18,] 3.907852 3.927844 3.947835 3.967827 3.987818 4.007809 4.027801 4.047792 #> [19,] 4.152192 4.172818 4.193444 4.214070 4.234696 4.255323 4.275949 4.296575 #> [20,] 4.000511 4.020661 4.040811 4.060961 4.081111 4.101262 4.121412 4.141562 #> [21,] 5.375161 5.403720 5.432279 5.460839 5.489398 5.517957 5.546516 5.575076 #> [22,] 5.872726 5.904300 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 #> [23,] 5.491143 5.520496 5.549848 5.579201 5.608553 5.637906 5.667258 5.696611 #> [24,] 5.371036 5.399912 5.428789 5.457665 5.486542 5.515418 5.544295 5.573172 #> [25,] 5.876851 5.908108 5.939364 5.970621 6.001877 6.033134 6.064390 6.095646 #> [26,] 5.876851 5.908108 5.939364 5.970621 6.001877 6.033134 6.064390 6.095646 #> [27,] 5.874789 5.906204 5.937619 5.969034 6.000449 6.031864 6.063279 6.094695 #> [28,] 5.872726 5.904300 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 #> [29,] 5.695659 5.726281 5.756902 5.787524 5.818146 5.848768 5.879390 5.910012 #> [30,] 5.872726 5.904300 5.935874 5.967447 5.999021 6.030595 6.062169 6.093743 #>         [,195]   [,196]   [,197]   [,198]   [,199]   [,200] #>  [1,] 5.677889 5.704227 5.730565 5.756902 5.783240 5.809578 #>  [2,] 5.984900 6.012983 6.041067 6.069150 6.097233 6.125316 #>  [3,] 5.739450 5.766105 5.792760 5.819415 5.846071 5.872726 #>  [4,] 5.737863 5.764836 5.791808 5.818781 5.845753 5.872726 #>  [5,] 5.583961 5.610140 5.636319 5.662498 5.688678 5.714857 #>  [6,] 6.139596 6.168314 6.197032 6.225750 6.254467 6.283185 #>  [7,] 6.140389 6.168948 6.197508 6.226067 6.254626 6.283185 #>  [8,] 5.801804 5.828618 5.855432 5.882246 5.909060 5.935874 #>  [9,] 5.430851 5.456079 5.481306 5.506533 5.531761 5.556988 #> [10,] 5.399278 5.424505 5.449732 5.474960 5.500187 5.525414 #> [11,] 4.467930 4.489984 4.512038 4.534092 4.556146 4.578200 #> [12,] 4.039383 4.058740 4.078097 4.097454 4.116810 4.136167 #> [13,] 4.377969 4.399071 4.420173 4.441275 4.462377 4.483479 #> [14,] 3.760772 3.779018 3.797265 3.815511 3.833757 3.852003 #> [15,] 4.314821 4.335923 4.357025 4.378127 4.399229 4.420331 #> [16,] 4.561858 4.584071 4.606284 4.628496 4.650709 4.672922 #> [17,] 4.407162 4.428740 4.450319 4.471897 4.493475 4.515053 #> [18,] 4.067784 4.087775 4.107767 4.127758 4.147750 4.167741 #> [19,] 4.317201 4.337827 4.358453 4.379079 4.399705 4.420331 #> [20,] 4.161712 4.181862 4.202012 4.222162 4.242312 4.262462 #> [21,] 5.603635 5.632194 5.660753 5.689312 5.717872 5.746431 #> [22,] 6.125316 6.156890 6.188464 6.220038 6.251612 6.283185 #> [23,] 5.725963 5.755316 5.784668 5.814021 5.843373 5.872726 #> [24,] 5.602048 5.630925 5.659801 5.688678 5.717554 5.746431 #> [25,] 6.126903 6.158159 6.189416 6.220672 6.251929 6.283185 #> [26,] 6.126903 6.158159 6.189416 6.220672 6.251929 6.283185 #> [27,] 6.126110 6.157525 6.188940 6.220355 6.251770 6.283185 #> [28,] 6.125316 6.156890 6.188464 6.220038 6.251612 6.283185 #> [29,] 5.940633 5.971255 6.001877 6.032499 6.063121 6.093743 #> [30,] 6.125316 6.156890 6.188464 6.220038 6.251612 6.283185 #>  #> $center_curves #> , , 1 #>  #>            [,1] #> [1,] 0.06497012 #> [2,] 0.13511093 #>  #> , , 2 #>  #>            [,1] #> [1,] 0.08452816 #> [2,] 0.19134922 #>  #> , , 3 #>  #>           [,1] #> [1,] 0.1041682 #> [2,] 0.2471764 #>  #> , , 4 #>  #>           [,1] #> [1,] 0.1238844 #> [2,] 0.3025496 #>  #> , , 5 #>  #>           [,1] #> [1,] 0.1436761 #> [2,] 0.3574285 #>  #> , , 6 #>  #>           [,1] #> [1,] 0.1635299 #> [2,] 0.4117503 #>  #> , , 7 #>  #>           [,1] #> [1,] 0.1834412 #> [2,] 0.4654860 #>  #> , , 8 #>  #>           [,1] #> [1,] 0.2034034 #> [2,] 0.5185908 #>  #> , , 9 #>  #>           [,1] #> [1,] 0.2234078 #> [2,] 0.5709993 #>  #> , , 10 #>  #>           [,1] #> [1,] 0.2434509 #> [2,] 0.6226754 #>  #> , , 11 #>  #>           [,1] #> [1,] 0.2635227 #> [2,] 0.6735849 #>  #> , , 12 #>  #>           [,1] #> [1,] 0.2836163 #> [2,] 0.7236903 #>  #> , , 13 #>  #>           [,1] #> [1,] 0.3037275 #> [2,] 0.7729353 #>  #> , , 14 #>  #>           [,1] #> [1,] 0.3238472 #> [2,] 0.8212877 #>  #> , , 15 #>  #>           [,1] #> [1,] 0.3439693 #> [2,] 0.8687042 #>  #> , , 16 #>  #>           [,1] #> [1,] 0.3640873 #> [2,] 0.9151381 #>  #> , , 17 #>  #>           [,1] #> [1,] 0.3841945 #> [2,] 0.9605241 #>  #> , , 18 #>  #>           [,1] #> [1,] 0.4042832 #> [2,] 1.0048502 #>  #> , , 19 #>  #>           [,1] #> [1,] 0.4243475 #> [2,] 1.0480663 #>  #> , , 20 #>  #>           [,1] #> [1,] 0.4443828 #> [2,] 1.0901378 #>  #> , , 21 #>  #>           [,1] #> [1,] 0.4643802 #> [2,] 1.1310452 #>  #> , , 22 #>  #>           [,1] #> [1,] 0.4843323 #> [2,] 1.1707513 #>  #> , , 23 #>  #>           [,1] #> [1,] 0.5042363 #> [2,] 1.2091870 #>  #> , , 24 #>  #>           [,1] #> [1,] 0.5240825 #> [2,] 1.2463368 #>  #> , , 25 #>  #>           [,1] #> [1,] 0.5438682 #> [2,] 1.2821544 #>  #> , , 26 #>  #>           [,1] #> [1,] 0.5635812 #> [2,] 1.3166148 #>  #> , , 27 #>  #>           [,1] #> [1,] 0.5832195 #> [2,] 1.3496740 #>  #> , , 28 #>  #>           [,1] #> [1,] 0.6027814 #> [2,] 1.3813227 #>  #> , , 29 #>  #>           [,1] #> [1,] 0.6222499 #> [2,] 1.4115406 #>  #> , , 30 #>  #>           [,1] #> [1,] 0.6416345 #> [2,] 1.4402755 #>  #> , , 31 #>  #>           [,1] #> [1,] 0.6609064 #> [2,] 1.4674947 #>  #> , , 32 #>  #>           [,1] #> [1,] 0.6800816 #> [2,] 1.4931778 #>  #> , , 33 #>  #>           [,1] #> [1,] 0.6991477 #> [2,] 1.5172787 #>  #> , , 34 #>  #>           [,1] #> [1,] 0.7180897 #> [2,] 1.5397811 #>  #> , , 35 #>  #>          [,1] #> [1,] 0.736920 #> [2,] 1.560688 #>  #> , , 36 #>  #>           [,1] #> [1,] 0.7556113 #> [2,] 1.5799632 #>  #> , , 37 #>  #>           [,1] #> [1,] 0.7741729 #> [2,] 1.5975766 #>  #> , , 38 #>  #>           [,1] #> [1,] 0.7925999 #> [2,] 1.6135375 #>  #> , , 39 #>  #>           [,1] #> [1,] 0.8108833 #> [2,] 1.6278311 #>  #> , , 40 #>  #>          [,1] #> [1,] 0.829014 #> [2,] 1.640384 #>  #> , , 41 #>  #>           [,1] #> [1,] 0.8469876 #> [2,] 1.6512040 #>  #> , , 42 #>  #>           [,1] #> [1,] 0.8648055 #> [2,] 1.6602843 #>  #> , , 43 #>  #>           [,1] #> [1,] 0.8824561 #> [2,] 1.6676363 #>  #> , , 44 #>  #>           [,1] #> [1,] 0.8999453 #> [2,] 1.6731948 #>  #> , , 45 #>  #>           [,1] #> [1,] 0.9172451 #> [2,] 1.6769856 #>  #> , , 46 #>  #>           [,1] #> [1,] 0.9343774 #> [2,] 1.6790216 #>  #> , , 47 #>  #>           [,1] #> [1,] 0.9513252 #> [2,] 1.6792680 #>  #> , , 48 #>  #>           [,1] #> [1,] 0.9680756 #> [2,] 1.6777185 #>  #> , , 49 #>  #>           [,1] #> [1,] 0.9846444 #> [2,] 1.6743657 #>  #> , , 50 #>  #>          [,1] #> [1,] 1.001008 #> [2,] 1.669210 #>  #> , , 51 #>  #>          [,1] #> [1,] 1.017173 #> [2,] 1.662248 #>  #> , , 52 #>  #>          [,1] #> [1,] 1.033127 #> [2,] 1.653509 #>  #> , , 53 #>  #>          [,1] #> [1,] 1.048868 #> [2,] 1.642980 #>  #> , , 54 #>  #>          [,1] #> [1,] 1.064398 #> [2,] 1.630653 #>  #> , , 55 #>  #>          [,1] #> [1,] 1.079722 #> [2,] 1.616568 #>  #> , , 56 #>  #>          [,1] #> [1,] 1.094805 #> [2,] 1.600722 #>  #> , , 57 #>  #>          [,1] #> [1,] 1.109666 #> [2,] 1.583079 #>  #> , , 58 #>  #>          [,1] #> [1,] 1.124296 #> [2,] 1.563654 #>  #> , , 59 #>  #>          [,1] #> [1,] 1.138694 #> [2,] 1.542498 #>  #> , , 60 #>  #>          [,1] #> [1,] 1.152860 #> [2,] 1.519636 #>  #> , , 61 #>  #>          [,1] #> [1,] 1.166769 #> [2,] 1.495037 #>  #> , , 62 #>  #>          [,1] #> [1,] 1.180447 #> [2,] 1.468763 #>  #> , , 63 #>  #>          [,1] #> [1,] 1.193864 #> [2,] 1.440839 #>  #> , , 64 #>  #>          [,1] #> [1,] 1.207038 #> [2,] 1.411264 #>  #> , , 65 #>  #>          [,1] #> [1,] 1.219959 #> [2,] 1.380032 #>  #> , , 66 #>  #>          [,1] #> [1,] 1.232613 #> [2,] 1.347199 #>  #> , , 67 #>  #>          [,1] #> [1,] 1.245021 #> [2,] 1.312787 #>  #> , , 68 #>  #>          [,1] #> [1,] 1.257141 #> [2,] 1.276825 #>  #> , , 69 #>  #>          [,1] #> [1,] 1.269012 #> [2,] 1.239357 #>  #> , , 70 #>  #>          [,1] #> [1,] 1.280612 #> [2,] 1.200405 #>  #> , , 71 #>  #>          [,1] #> [1,] 1.291930 #> [2,] 1.159998 #>  #> , , 72 #>  #>          [,1] #> [1,] 1.302973 #> [2,] 1.118161 #>  #> , , 73 #>  #>          [,1] #> [1,] 1.313743 #> [2,] 1.074941 #>  #> , , 74 #>  #>          [,1] #> [1,] 1.324231 #> [2,] 1.030361 #>  #> , , 75 #>  #>           [,1] #> [1,] 1.3344394 #> [2,] 0.9844585 #>  #> , , 76 #>  #>           [,1] #> [1,] 1.3443652 #> [2,] 0.9373073 #>  #> , , 77 #>  #>           [,1] #> [1,] 1.3539729 #> [2,] 0.8889499 #>  #> , , 78 #>  #>           [,1] #> [1,] 1.3633333 #> [2,] 0.8393976 #>  #> , , 79 #>  #>           [,1] #> [1,] 1.3723702 #> [2,] 0.7887181 #>  #> , , 80 #>  #>           [,1] #> [1,] 1.3811158 #> [2,] 0.7369613 #>  #> , , 81 #>  #>           [,1] #> [1,] 1.3895872 #> [2,] 0.6841574 #>  #> , , 82 #>  #>           [,1] #> [1,] 1.3977255 #> [2,] 0.6303596 #>  #> , , 83 #>  #>           [,1] #> [1,] 1.4056039 #> [2,] 0.5756207 #>  #> , , 84 #>  #>           [,1] #> [1,] 1.4131425 #> [2,] 0.5200089 #>  #> , , 85 #>  #>           [,1] #> [1,] 1.4203824 #> [2,] 0.4635605 #>  #> , , 86 #>  #>           [,1] #> [1,] 1.4273308 #> [2,] 0.4063395 #>  #> , , 87 #>  #>           [,1] #> [1,] 1.4339644 #> [2,] 0.3484031 #>  #> , , 88 #>  #>           [,1] #> [1,] 1.4402976 #> [2,] 0.2898029 #>  #> , , 89 #>  #>           [,1] #> [1,] 1.4462995 #> [2,] 0.2305995 #>  #> , , 90 #>  #>           [,1] #> [1,] 1.4520016 #> [2,] 0.1708606 #>  #> , , 91 #>  #>           [,1] #> [1,] 1.4573751 #> [2,] 0.1106363 #>  #> , , 92 #>  #>            [,1] #> [1,] 1.46245162 #> [2,] 0.04998966 #>  #> , , 93 #>  #>             [,1] #> [1,]  1.46720310 #> [2,] -0.01100713 #>  #> , , 94 #>  #>             [,1] #> [1,]  1.47163346 #> [2,] -0.07229319 #>  #> , , 95 #>  #>            [,1] #> [1,]  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[2,] -0.9238479 #>  #> , , 109 #>  #>            [,1] #> [1,]  1.4990063 #> [2,] -0.9814771 #>  #> , , 110 #>  #>           [,1] #> [1,]  1.498189 #> [2,] -1.038326 #>  #> , , 111 #>  #>           [,1] #> [1,]  1.497004 #> [2,] -1.094331 #>  #> , , 112 #>  #>           [,1] #> [1,]  1.495502 #> [2,] -1.149396 #>  #> , , 113 #>  #>           [,1] #> [1,]  1.493671 #> [2,] -1.203453 #>  #> , , 114 #>  #>           [,1] #> [1,]  1.491470 #> [2,] -1.256467 #>  #> , , 115 #>  #>           [,1] #> [1,]  1.488972 #> [2,] -1.308368 #>  #> , , 116 #>  #>           [,1] #> [1,]  1.486082 #> [2,] -1.359048 #>  #> , , 117 #>  #>           [,1] #> [1,]  1.482876 #> [2,] -1.408487 #>  #> , , 118 #>  #>           [,1] #> [1,]  1.479328 #> [2,] -1.456633 #>  #> , , 119 #>  #>           [,1] #> [1,]  1.475425 #> [2,] -1.503413 #>  #> , , 120 #>  #>           [,1] #> [1,]  1.471199 #> [2,] -1.548749 #>  #> , , 121 #>  #>           [,1] #> [1,]  1.466608 #> [2,] -1.592590 #>  #> , , 122 #>  #>           [,1] #> [1,]  1.461671 #> [2,] -1.634894 #>  #> , , 123 #>  #>           [,1] #> [1,]  1.456388 #> [2,] -1.675604 #>  #> , , 124 #>  #>           [,1] #> [1,]  1.450778 #> [2,] -1.714660 #>  #> , , 125 #>  #>           [,1] #> [1,]  1.444793 #> [2,] -1.752009 #>  #> , , 126 #>  #>           [,1] #> [1,]  1.438469 #> [2,] -1.787594 #>  #> , , 127 #>  #>           [,1] #> [1,]  1.431793 #> [2,] -1.821392 #>  #> , , 128 #>  #>           [,1] #> [1,]  1.424767 #> [2,] -1.853363 #>  #> , , 129 #>  #>           [,1] #> [1,]  1.417404 #> [2,] -1.883406 #>  #> , , 130 #>  #>           [,1] #> [1,]  1.409660 #> [2,] -1.911534 #>  #> , , 131 #>  #>           [,1] #> [1,]  1.401583 #> [2,] -1.937729 #>  #> , , 132 #>  #>           [,1] #> [1,]  1.393138 #> [2,] -1.961943 #>  #> , , 133 #>  #>           [,1] #> [1,]  1.384366 #> [2,] -1.984085 #>  #> , , 134 #>  #>           [,1] #> [1,]  1.375228 #> [2,] -2.004183 #>  #> , , 135 #>  #>           [,1] #> [1,]  1.365705 #> [2,] -2.022229 #>  #> , , 136 #>  #>           [,1] #> [1,]  1.355866 #> [2,] -2.038159 #>  #> , , 137 #>  #>           [,1] #> [1,]  1.345631 #> [2,] -2.051943 #>  #> , , 138 #>  #>           [,1] #> [1,]  1.335078 #> [2,] -2.063601 #>  #> , , 139 #>  #>           [,1] #> [1,]  1.324142 #> [2,] -2.073130 #>  #> , , 140 #>  #>           [,1] #> [1,]  1.312840 #> [2,] -2.080469 #>  #> , , 141 #>  #>           [,1] #> [1,]  1.301214 #> [2,] -2.085624 #>  #> , , 142 #>  #>           [,1] #> [1,]  1.289193 #> [2,] -2.088614 #>  #> , , 143 #>  #>           [,1] #> [1,]  1.276819 #> [2,] -2.089427 #>  #> , , 144 #>  #>           [,1] #> [1,]  1.264094 #> [2,] -2.088085 #>  #> , , 145 #>  #>           [,1] #> [1,]  1.250982 #> [2,] -2.084591 #>  #> , , 146 #>  #>           [,1] #> [1,]  1.237540 #> [2,] -2.078949 #>  #> , , 147 #>  #>           [,1] #> [1,]  1.223721 #> [2,] -2.071166 #>  #> , , 148 #>  #>           [,1] #> [1,]  1.209518 #> [2,] -2.061302 #>  #> , , 149 #>  #>          [,1] #> [1,]  1.19498 #> [2,] -2.04935 #>  #> , , 150 #>  #>           [,1] #> [1,]  1.180067 #> [2,] -2.035299 #>  #> , , 151 #>  #>           [,1] #> [1,]  1.164781 #> [2,] -2.019243 #>  #> , , 152 #>  #>          [,1] #> [1,]  1.14914 #> [2,] -2.00121 #>  #> , , 153 #>  #>           [,1] #> [1,]  1.133126 #> [2,] -1.981209 #>  #> , , 154 #>  #>           [,1] #> [1,]  1.116759 #> [2,] -1.959271 #>  #> , , 155 #>  #>           [,1] #> [1,]  1.100005 #> [2,] -1.935485 #>  #> , , 156 #>  #>           [,1] #> [1,]  1.082898 #> [2,] -1.909903 #>  #> , , 157 #>  #>           [,1] #> [1,]  1.065420 #> [2,] -1.882534 #>  #> , , 158 #>  #>           [,1] #> [1,]  1.047582 #> [2,] -1.853471 #>  #> , , 159 #>  #>           [,1] #> [1,]  1.029380 #> [2,] -1.822774 #>  #> , , 160 #>  #>           [,1] #> [1,]  1.010790 #> [2,] -1.790504 #>  #> , , 161 #>  #>            [,1] #> [1,]  0.9918585 #> [2,] -1.7567114 #>  #> , , 162 #>  #>            [,1] #> [1,]  0.9725529 #> [2,] -1.7215002 #>  #> , , 163 #>  #>           [,1] #> [1,]  0.952877 #> [2,] -1.684921 #>  #> , , 164 #>  #>            [,1] #> [1,]  0.9328483 #> [2,] -1.6470586 #>  #> , , 165 #>  #>            [,1] #> [1,]  0.9124405 #> [2,] -1.6080013 #>  #> , , 166 #>  #>            [,1] #> [1,]  0.8916736 #> [2,] -1.5678274 #>  #> , , 167 #>  #>            [,1] #> [1,]  0.8705646 #> [2,] -1.5266050 #>  #> , , 168 #>  #>            [,1] #> [1,]  0.8490532 #> [2,] -1.4844341 #>  #> , , 169 #>  #>            [,1] #> [1,]  0.8272091 #> [2,] -1.4414137 #>  #> , , 170 #>  #>            [,1] #> [1,]  0.8050175 #> [2,] -1.3976363 #>  #> , , 171 #>  #>            [,1] #> [1,]  0.7824332 #> [2,] -1.3531879 #>  #> , , 172 #>  #>            [,1] #> [1,]  0.7595275 #> [2,] -1.3081750 #>  #> , , 173 #>  #>           [,1] #> [1,]  0.736247 #> [2,] -1.262692 #>  #> , , 174 #>  #>            [,1] #> [1,]  0.7126106 #> [2,] -1.2168302 #>  #> , , 175 #>  #>            [,1] #> [1,]  0.6886412 #> [2,] -1.1706920 #>  #> , , 176 #>  #>            [,1] #> [1,]  0.6642918 #> [2,] -1.1243772 #>  #> , , 177 #>  #>            [,1] #> [1,]  0.6396302 #> [2,] -1.0779855 #>  #> , , 178 #>  #>            [,1] #> [1,]  0.6146129 #> [2,] -1.0316187 #>  #> , , 179 #>  #>            [,1] #> [1,]  0.5892528 #> [2,] -0.9853738 #>  #> , , 180 #>  #>            [,1] #> [1,]  0.5635611 #> [2,] -0.9393516 #>  #> , , 181 #>  #>            [,1] #> [1,]  0.5375240 #> [2,] -0.8936506 #>  #> , , 182 #>  #>            [,1] #> [1,]  0.5111707 #> [2,] -0.8483713 #>  #> , , 183 #>  #>            [,1] #> [1,]  0.4844698 #> [2,] -0.8035977 #>  #> , , 184 #>  #>            [,1] #> [1,]  0.4574575 #> [2,] -0.7594433 #>  #> , , 185 #>  #>            [,1] #> [1,]  0.4301303 #> [2,] -0.7159905 #>  #> , , 186 #>  #>            [,1] #> [1,]  0.4024745 #> [2,] -0.6733142 #>  #> , , 187 #>  #>            [,1] #> [1,]  0.3745374 #> [2,] -0.6314963 #>  #> , , 188 #>  #>            [,1] #> [1,]  0.3462629 #> [2,] -0.5906449 #>  #> , , 189 #>  #>            [,1] #> [1,]  0.3176950 #> [2,] -0.5508186 #>  #> , , 190 #>  #>            [,1] #> [1,]  0.2888553 #> [2,] -0.5120953 #>  #> , , 191 #>  #>            [,1] #> [1,]  0.2596925 #> [2,] -0.4745579 #>  #> , , 192 #>  #>            [,1] #> [1,]  0.2302770 #> [2,] -0.4382669 #>  #> , , 193 #>  #>            [,1] #> [1,]  0.2005802 #> [2,] -0.4032874 #>  #> , , 194 #>  #>            [,1] #> [1,]  0.1705978 #> [2,] -0.3696600 #>  #> , , 195 #>  #>            [,1] #> [1,]  0.1403705 #> [2,] -0.3374500 #>  #> , , 196 #>  #>            [,1] #> [1,]  0.1098806 #> [2,] -0.3066814 #>  #> , , 197 #>  #>             [,1] #> [1,]  0.07915083 #> [2,] -0.27740306 #>  #> , , 198 #>  #>             [,1] #> [1,]  0.04818582 #> [2,] -0.24966979 #>  #> , , 199 #>  #>             [,1] #> [1,]  0.01697984 #> [2,] -0.22347604 #>  #> , , 200 #>  #>             [,1] #> [1,] -0.01444034 #> [2,] -0.19883855 #>  #>  #> $center_grids #>            [,1]       [,2]      [,3]      [,4]      [,5]      [,6]      [,7] #> [1,] 0.58175701 0.59824927 0.6147415 0.6312338 0.6477261 0.6642183 0.6807106 #> [2,] 0.05517908 0.08381685 0.1124546 0.1410924 0.1697302 0.1983679 0.2270057 #>           [,8]      [,9]     [,10]     [,11]     [,12]     [,13]     [,14] #> [1,] 0.6972028 0.7136951 0.7301874 0.7466796 0.7631719 0.7796642 0.7961564 #> [2,] 0.2556435 0.2842813 0.3129190 0.3415568 0.3701946 0.3988323 0.4274701 #>          [,15]     [,16]     [,17]     [,18]     [,19]     [,20]     [,21] #> [1,] 0.8126487 0.8291410 0.8456332 0.8621255 0.8786177 0.8951100 0.9116023 #> [2,] 0.4561079 0.4847457 0.5133834 0.5420212 0.5706590 0.5992968 0.6279345 #>          [,22]     [,23]     [,24]     [,25]     [,26]     [,27]     [,28] #> [1,] 0.9280945 0.9445868 0.9610791 0.9775713 0.9940636 1.0105558 1.0270481 #> [2,] 0.6565723 0.6852101 0.7138479 0.7424856 0.7711234 0.7997612 0.8283989 #>          [,29]     [,30]     [,31]    [,32]     [,33]    [,34]    [,35] #> [1,] 1.0435404 1.0600326 1.0765249 1.093017 1.1095094 1.126002 1.142494 #> [2,] 0.8570367 0.8856745 0.9143123 0.942950 0.9715878 1.000226 1.028863 #>         [,36]    [,37]    [,38]    [,39]    [,40]    [,41]    [,42]    [,43] #> [1,] 1.158986 1.175478 1.191971 1.208463 1.224955 1.241448 1.257940 1.274432 #> [2,] 1.057501 1.086139 1.114777 1.143414 1.172052 1.200690 1.229328 1.257966 #>         [,44]    [,45]    [,46]    [,47]    [,48]    [,49]    [,50]    [,51] #> [1,] 1.290924 1.307417 1.323909 1.340401 1.356893 1.373386 1.389878 1.406370 #> [2,] 1.286603 1.315241 1.343879 1.372517 1.401154 1.429792 1.458430 1.487068 #>         [,52]    [,53]    [,54]    [,55]    [,56]    [,57]    [,58]    [,59] #> [1,] 1.422862 1.439355 1.455847 1.472339 1.488831 1.505324 1.521816 1.538308 #> [2,] 1.515705 1.544343 1.572981 1.601619 1.630257 1.658894 1.687532 1.716170 #>         [,60]    [,61]    [,62]    [,63]    [,64]    [,65]    [,66]    [,67] #> [1,] 1.554801 1.571293 1.587785 1.604277 1.620770 1.637262 1.653754 1.670246 #> [2,] 1.744808 1.773445 1.802083 1.830721 1.859359 1.887997 1.916634 1.945272 #>         [,68]    [,69]    [,70]    [,71]    [,72]    [,73]    [,74]    [,75] #> [1,] 1.686739 1.703231 1.719723 1.736215 1.752708 1.769200 1.785692 1.802184 #> [2,] 1.973910 2.002548 2.031185 2.059823 2.088461 2.117099 2.145736 2.174374 #>         [,76]    [,77]    [,78]    [,79]    [,80]    [,81]    [,82]    [,83] #> [1,] 1.818677 1.835169 1.851661 1.868154 1.884646 1.901138 1.917630 1.934123 #> [2,] 2.203012 2.231650 2.260288 2.288925 2.317563 2.346201 2.374839 2.403476 #>         [,84]    [,85]    [,86]    [,87]    [,88]    [,89]    [,90]    [,91] #> [1,] 1.950615 1.967107 1.983599 2.000092 2.016584 2.033076 2.049568 2.066061 #> [2,] 2.432114 2.460752 2.489390 2.518028 2.546665 2.575303 2.603941 2.632579 #>         [,92]    [,93]    [,94]   [,95]    [,96]    [,97]    [,98]    [,99] #> [1,] 2.082553 2.099045 2.115537 2.13203 2.148522 2.165014 2.181507 2.197999 #> [2,] 2.661216 2.689854 2.718492 2.74713 2.775767 2.804405 2.833043 2.861681 #>        [,100]   [,101]   [,102]   [,103]  [,104]   [,105]   [,106]   [,107] #> [1,] 2.214491 2.230983 2.247476 2.263968 2.28046 2.296952 2.313445 2.329937 #> [2,] 2.890319 2.918956 2.947594 2.976232 3.00487 3.033507 3.062145 3.090783 #>        [,108]   [,109]   [,110]   [,111]   [,112]  [,113]   [,114]   [,115] #> [1,] 2.346429 2.362921 2.379414 2.395906 2.412398 2.42889 2.445383 2.461875 #> [2,] 3.119421 3.148059 3.176696 3.205334 3.233972 3.26261 3.291247 3.319885 #>        [,116]   [,117]   [,118]   [,119]   [,120]   [,121]   [,122]   [,123] #> [1,] 2.478367 2.494859 2.511352 2.527844 2.544336 2.560829 2.577321 2.593813 #> [2,] 3.348523 3.377161 3.405799 3.434436 3.463074 3.491712 3.520350 3.548987 #>        [,124]   [,125]   [,126]   [,127]   [,128]   [,129]   [,130]   [,131] #> [1,] 2.610305 2.626798 2.643290 2.659782 2.676274 2.692767 2.709259 2.725751 #> [2,] 3.577625 3.606263 3.634901 3.663538 3.692176 3.720814 3.749452 3.778090 #>        [,132]   [,133]   [,134]   [,135]   [,136]   [,137]   [,138]   [,139] #> [1,] 2.742243 2.758736 2.775228 2.791720 2.808212 2.824705 2.841197 2.857689 #> [2,] 3.806727 3.835365 3.864003 3.892641 3.921278 3.949916 3.978554 4.007192 #>        [,140]   [,141]   [,142]   [,143]   [,144]   [,145]   [,146]   [,147] #> [1,] 2.874182 2.890674 2.907166 2.923658 2.940151 2.956643 2.973135 2.989627 #> [2,] 4.035830 4.064467 4.093105 4.121743 4.150381 4.179018 4.207656 4.236294 #>        [,148]   [,149]   [,150]   [,151]   [,152]   [,153]   [,154]   [,155] #> [1,] 3.006120 3.022612 3.039104 3.055596 3.072089 3.088581 3.105073 3.121565 #> [2,] 4.264932 4.293569 4.322207 4.350845 4.379483 4.408121 4.436758 4.465396 #>        [,156]   [,157]   [,158]   [,159]   [,160]   [,161]   [,162]   [,163] #> [1,] 3.138058 3.154550 3.171042 3.187535 3.204027 3.220519 3.237011 3.253504 #> [2,] 4.494034 4.522672 4.551309 4.579947 4.608585 4.637223 4.665861 4.694498 #>        [,164]   [,165]   [,166]   [,167]   [,168]   [,169]   [,170]   [,171] #> [1,] 3.269996 3.286488 3.302980 3.319473 3.335965 3.352457 3.368949 3.385442 #> [2,] 4.723136 4.751774 4.780412 4.809049 4.837687 4.866325 4.894963 4.923600 #>        [,172]   [,173]   [,174]   [,175]   [,176]   [,177]   [,178]   [,179] #> [1,] 3.401934 3.418426 3.434918 3.451411 3.467903 3.484395 3.500888 3.517380 #> [2,] 4.952238 4.980876 5.009514 5.038152 5.066789 5.095427 5.124065 5.152703 #>        [,180]   [,181]   [,182]   [,183]   [,184]   [,185]   [,186]   [,187] #> [1,] 3.533872 3.550364 3.566857 3.583349 3.599841 3.616333 3.632826 3.649318 #> [2,] 5.181340 5.209978 5.238616 5.267254 5.295892 5.324529 5.353167 5.381805 #>        [,188]   [,189]   [,190]   [,191]   [,192]   [,193]   [,194]   [,195] #> [1,] 3.665810 3.682302 3.698795 3.715287 3.731779 3.748271 3.764764 3.781256 #> [2,] 5.410443 5.439080 5.467718 5.496356 5.524994 5.553631 5.582269 5.610907 #>        [,196]   [,197]   [,198]   [,199]   [,200] #> [1,] 3.797748 3.814241 3.830733 3.847225 3.863717 #> [2,] 5.639545 5.668183 5.696820 5.725458 5.754096 #>  #> $warpings #>               [,1]        [,2]         [,3]       [,4]       [,5]       [,6] #>  [1,]  1.030805198  1.05294860  1.075092011 1.09723542 1.11937882 1.14152223 #>  [2,]  1.001787925  1.02684018  1.051892439 1.07694470 1.10199695 1.12704921 #>  [3,]  1.045478224  1.06807127  1.090664311 1.11325735 1.13585040 1.15844344 #>  [4,]  0.928816380  0.95201431  0.975212243 0.99841017 1.02160811 1.04480604 #>  [5,]  0.897059469  0.91898331  0.940907159 0.96283100 0.98475485 1.00667869 #>  [6,]  1.061447992  1.08790519  1.114362386 1.14081958 1.16727678 1.19373398 #>  [7,]  1.139957673  1.16653163  1.193105580 1.21967953 1.24625349 1.27282744 #>  [8,]  1.082712462  1.10562153  1.128530590 1.15143965 1.17434872 1.19725778 #>  [9,]  0.965902671  0.98613473  1.006366794 1.02659886 1.04683092 1.06706298 #> [10,]  0.906922598  0.92721265  0.947502698 0.96779275 0.98808280 1.00837285 #> [11,]  0.317491592  0.33295298  0.348414378 0.36387577 0.37933716 0.39479856 #> [12,]  0.436722570  0.44866741  0.460612250 0.47255709 0.48450193 0.49644677 #> [13,]  0.468195084  0.48234493  0.496494786 0.51064464 0.52479449 0.53894434 #> [14,]  0.320243339  0.33090863  0.341573924 0.35223922 0.36290451 0.37356980 #> [15,]  0.358748478  0.37294634  0.387144194 0.40134205 0.41553991 0.42973777 #> [16,]  0.426851992  0.44250846  0.458164919 0.47382138 0.48947785 0.50513431 #> [17,]  0.343146905  0.35799965  0.372852389 0.38770513 0.40255787 0.41741062 #> [18,]  0.279548534  0.29233634  0.305124147 0.31791195 0.33069976 0.34348757 #> [19,]  0.520722532  0.53423640  0.547750258 0.56126412 0.57477798 0.58829185 #> [20,]  0.390965538  0.40394880  0.416932072 0.42991534 0.44289861 0.45588187 #> [21,]  0.111956906  0.13786423  0.163771557 0.18967888 0.21558621 0.24149353 #> [22,] -0.070649556 -0.03791667 -0.005183782 0.02754910 0.06028199 0.09301488 #> [23,]  0.060854717  0.08815012  0.115445532 0.14274094 0.17003635 0.19733175 #> [24,] -0.041924595 -0.01528699  0.011350611 0.03798821 0.06462582 0.09126342 #> [25,]  0.102342650  0.13553519  0.168727739 0.20192028 0.23511283 0.26830537 #> [26,]  0.120126505  0.15227385  0.184421197 0.21656854 0.24871589 0.28086324 #> [27,]  0.039451017  0.07175713  0.104063250 0.13636937 0.16867548 0.20098160 #> [28,] -0.004871023  0.02772095  0.060312932 0.09290491 0.12549689 0.15808886 #> [29,] -0.042271170 -0.01228534  0.017700492 0.04768632 0.07767215 0.10765798 #> [30,] -0.048958273 -0.01544011  0.018078049 0.05159621 0.08511437 0.11863253 #>            [,7]      [,8]      [,9]     [,10]     [,11]     [,12]     [,13] #>  [1,] 1.1636656 1.1858090 1.2079524 1.2300959 1.2522393 1.2743827 1.2965261 #>  [2,] 1.1521015 1.1771537 1.2022060 1.2272582 1.2523105 1.2773628 1.3024150 #>  [3,] 1.1810365 1.2036295 1.2262226 1.2488156 1.2714087 1.2940017 1.3165947 #>  [4,] 1.0680040 1.0912019 1.1143998 1.1375978 1.1607957 1.1839936 1.2071916 #>  [5,] 1.0286025 1.0505264 1.0724502 1.0943741 1.1162979 1.1382218 1.1601456 #>  [6,] 1.2201912 1.2466484 1.2731056 1.2995628 1.3260200 1.3524772 1.3789344 #>  [7,] 1.2994014 1.3259753 1.3525493 1.3791233 1.4056972 1.4322712 1.4588451 #>  [8,] 1.2201668 1.2430759 1.2659850 1.2888940 1.3118031 1.3347122 1.3576212 #>  [9,] 1.0872950 1.1075271 1.1277592 1.1479912 1.1682233 1.1884553 1.2086874 #> [10,] 1.0286629 1.0489529 1.0692430 1.0895330 1.1098231 1.1301131 1.1504032 #> [11,] 0.4102599 0.4257213 0.4411827 0.4566441 0.4721055 0.4875669 0.5030283 #> [12,] 0.5083916 0.5203365 0.5322813 0.5442261 0.5561710 0.5681158 0.5800607 #> [13,] 0.5530942 0.5672440 0.5813939 0.5955437 0.6096936 0.6238434 0.6379933 #> [14,] 0.3842351 0.3949004 0.4055657 0.4162310 0.4268963 0.4375616 0.4482269 #> [15,] 0.4439356 0.4581335 0.4723313 0.4865292 0.5007271 0.5149249 0.5291228 #> [16,] 0.5207908 0.5364472 0.5521037 0.5677602 0.5834166 0.5990731 0.6147296 #> [17,] 0.4322634 0.4471161 0.4619688 0.4768216 0.4916743 0.5065271 0.5213798 #> [18,] 0.3562754 0.3690632 0.3818510 0.3946388 0.4074266 0.4202144 0.4330022 #> [19,] 0.6018057 0.6153196 0.6288334 0.6423473 0.6558612 0.6693750 0.6828889 #> [20,] 0.4688651 0.4818484 0.4948317 0.5078149 0.5207982 0.5337815 0.5467647 #> [21,] 0.2674009 0.2933082 0.3192155 0.3451228 0.3710302 0.3969375 0.4228448 #> [22,] 0.1257478 0.1584807 0.1912135 0.2239464 0.2566793 0.2894122 0.3221451 #> [23,] 0.2246272 0.2519226 0.2792180 0.3065134 0.3338088 0.3611042 0.3883996 #> [24,] 0.1179010 0.1445386 0.1711762 0.1978138 0.2244514 0.2510890 0.2777266 #> [25,] 0.3014979 0.3346905 0.3678830 0.4010756 0.4342681 0.4674606 0.5006532 #> [26,] 0.3130106 0.3451579 0.3773053 0.4094526 0.4416000 0.4737473 0.5058947 #> [27,] 0.2332877 0.2655938 0.2978999 0.3302061 0.3625122 0.3948183 0.4271244 #> [28,] 0.1906808 0.2232728 0.2558648 0.2884568 0.3210488 0.3536407 0.3862327 #> [29,] 0.1376438 0.1676296 0.1976155 0.2276013 0.2575871 0.2875730 0.3175588 #> [30,] 0.1521507 0.1856689 0.2191870 0.2527052 0.2862233 0.3197415 0.3532597 #>           [,14]     [,15]     [,16]     [,17]     [,18]     [,19]     [,20] #>  [1,] 1.3186695 1.3408129 1.3629563 1.3850997 1.4072431 1.4293865 1.4515299 #>  [2,] 1.3274673 1.3525195 1.3775718 1.4026240 1.4276763 1.4527285 1.4777808 #>  [3,] 1.3391878 1.3617808 1.3843739 1.4069669 1.4295600 1.4521530 1.4747461 #>  [4,] 1.2303895 1.2535874 1.2767854 1.2999833 1.3231812 1.3463791 1.3695771 #>  [5,] 1.1820695 1.2039933 1.2259171 1.2478410 1.2697648 1.2916887 1.3136125 #>  [6,] 1.4053916 1.4318487 1.4583059 1.4847631 1.5112203 1.5376775 1.5641347 #>  [7,] 1.4854191 1.5119930 1.5385670 1.5651409 1.5917149 1.6182888 1.6448628 #>  [8,] 1.3805303 1.4034394 1.4263484 1.4492575 1.4721665 1.4950756 1.5179847 #>  [9,] 1.2289195 1.2491515 1.2693836 1.2896157 1.3098477 1.3300798 1.3503118 #> [10,] 1.1706932 1.1909833 1.2112733 1.2315634 1.2518535 1.2721435 1.2924336 #> [11,] 0.5184897 0.5339511 0.5494125 0.5648739 0.5803353 0.5957967 0.6112581 #> [12,] 0.5920055 0.6039503 0.6158952 0.6278400 0.6397849 0.6517297 0.6636745 #> [13,] 0.6521432 0.6662930 0.6804429 0.6945927 0.7087426 0.7228924 0.7370423 #> [14,] 0.4588921 0.4695574 0.4802227 0.4908880 0.5015533 0.5122186 0.5228839 #> [15,] 0.5433206 0.5575185 0.5717163 0.5859142 0.6001121 0.6143099 0.6285078 #> [16,] 0.6303860 0.6460425 0.6616989 0.6773554 0.6930119 0.7086683 0.7243248 #> [17,] 0.5362326 0.5510853 0.5659380 0.5807908 0.5956435 0.6104963 0.6253490 #> [18,] 0.4457900 0.4585778 0.4713656 0.4841534 0.4969412 0.5097291 0.5225169 #> [19,] 0.6964028 0.7099166 0.7234305 0.7369443 0.7504582 0.7639721 0.7774859 #> [20,] 0.5597480 0.5727313 0.5857145 0.5986978 0.6116811 0.6246643 0.6376476 #> [21,] 0.4487521 0.4746595 0.5005668 0.5264741 0.5523814 0.5782888 0.6041961 #> [22,] 0.3548780 0.3876109 0.4203437 0.4530766 0.4858095 0.5185424 0.5512753 #> [23,] 0.4156950 0.4429904 0.4702858 0.4975812 0.5248766 0.5521720 0.5794675 #> [24,] 0.3043642 0.3310019 0.3576395 0.3842771 0.4109147 0.4375523 0.4641899 #> [25,] 0.5338457 0.5670383 0.6002308 0.6334234 0.6666159 0.6998085 0.7330010 #> [26,] 0.5380420 0.5701893 0.6023367 0.6344840 0.6666314 0.6987787 0.7309261 #> [27,] 0.4594305 0.4917366 0.5240428 0.5563489 0.5886550 0.6209611 0.6532672 #> [28,] 0.4188247 0.4514167 0.4840086 0.5166006 0.5491926 0.5817846 0.6143765 #> [29,] 0.3475446 0.3775305 0.4075163 0.4375021 0.4674880 0.4974738 0.5274596 #> [30,] 0.3867778 0.4202960 0.4538141 0.4873323 0.5208505 0.5543686 0.5878868 #>           [,21]     [,22]     [,23]     [,24]     [,25]     [,26]     [,27] #>  [1,] 1.4736733 1.4958167 1.5179601 1.5401035 1.5622469 1.5843904 1.6065338 #>  [2,] 1.5028331 1.5278853 1.5529376 1.5779898 1.6030421 1.6280943 1.6531466 #>  [3,] 1.4973391 1.5199321 1.5425252 1.5651182 1.5877113 1.6103043 1.6328974 #>  [4,] 1.3927750 1.4159729 1.4391709 1.4623688 1.4855667 1.5087647 1.5319626 #>  [5,] 1.3355364 1.3574602 1.3793841 1.4013079 1.4232317 1.4451556 1.4670794 #>  [6,] 1.5905919 1.6170491 1.6435063 1.6699635 1.6964207 1.7228779 1.7493351 #>  [7,] 1.6714367 1.6980107 1.7245847 1.7511586 1.7777326 1.8043065 1.8308805 #>  [8,] 1.5408937 1.5638028 1.5867119 1.6096209 1.6325300 1.6554391 1.6783481 #>  [9,] 1.3705439 1.3907760 1.4110080 1.4312401 1.4514721 1.4717042 1.4919363 #> [10,] 1.3127236 1.3330137 1.3533037 1.3735938 1.3938838 1.4141739 1.4344639 #> [11,] 0.6267195 0.6421808 0.6576422 0.6731036 0.6885650 0.7040264 0.7194878 #> [12,] 0.6756194 0.6875642 0.6995091 0.7114539 0.7233987 0.7353436 0.7472884 #> [13,] 0.7511921 0.7653420 0.7794918 0.7936417 0.8077915 0.8219414 0.8360912 #> [14,] 0.5335492 0.5442145 0.5548798 0.5655451 0.5762104 0.5868757 0.5975410 #> [15,] 0.6427056 0.6569035 0.6711014 0.6852992 0.6994971 0.7136949 0.7278928 #> [16,] 0.7399813 0.7556377 0.7712942 0.7869507 0.8026071 0.8182636 0.8339200 #> [17,] 0.6402017 0.6550545 0.6699072 0.6847600 0.6996127 0.7144655 0.7293182 #> [18,] 0.5353047 0.5480925 0.5608803 0.5736681 0.5864559 0.5992437 0.6120315 #> [19,] 0.7909998 0.8045137 0.8180275 0.8315414 0.8450552 0.8585691 0.8720830 #> [20,] 0.6506309 0.6636141 0.6765974 0.6895807 0.7025639 0.7155472 0.7285305 #> [21,] 0.6301034 0.6560107 0.6819181 0.7078254 0.7337327 0.7596400 0.7855474 #> [22,] 0.5840082 0.6167411 0.6494740 0.6822068 0.7149397 0.7476726 0.7804055 #> [23,] 0.6067629 0.6340583 0.6613537 0.6886491 0.7159445 0.7432399 0.7705353 #> [24,] 0.4908275 0.5174651 0.5441027 0.5707403 0.5973779 0.6240155 0.6506531 #> [25,] 0.7661935 0.7993861 0.8325786 0.8657712 0.8989637 0.9321563 0.9653488 #> [26,] 0.7630734 0.7952208 0.8273681 0.8595155 0.8916628 0.9238102 0.9559575 #> [27,] 0.6855733 0.7178795 0.7501856 0.7824917 0.8147978 0.8471039 0.8794100 #> [28,] 0.6469685 0.6795605 0.7121525 0.7447445 0.7773364 0.8099284 0.8425204 #> [29,] 0.5574455 0.5874313 0.6174171 0.6474029 0.6773888 0.7073746 0.7373604 #> [30,] 0.6214049 0.6549231 0.6884413 0.7219594 0.7554776 0.7889958 0.8225139 #>           [,28]     [,29]     [,30]     [,31]     [,32]     [,33]     [,34] #>  [1,] 1.6286772 1.6508206 1.6729640 1.6951074 1.7172508 1.7393942 1.7615376 #>  [2,] 1.6781989 1.7032511 1.7283034 1.7533556 1.7784079 1.8034601 1.8285124 #>  [3,] 1.6554904 1.6780834 1.7006765 1.7232695 1.7458626 1.7684556 1.7910487 #>  [4,] 1.5551605 1.5783585 1.6015564 1.6247543 1.6479523 1.6711502 1.6943481 #>  [5,] 1.4890033 1.5109271 1.5328510 1.5547748 1.5766987 1.5986225 1.6205464 #>  [6,] 1.7757923 1.8022495 1.8287067 1.8551639 1.8816211 1.9080783 1.9345355 #>  [7,] 1.8574544 1.8840284 1.9106023 1.9371763 1.9637502 1.9903242 2.0168982 #>  [8,] 1.7012572 1.7241663 1.7470753 1.7699844 1.7928934 1.8158025 1.8387116 #>  [9,] 1.5121683 1.5324004 1.5526325 1.5728645 1.5930966 1.6133286 1.6335607 #> [10,] 1.4547540 1.4750440 1.4953341 1.5156241 1.5359142 1.5562042 1.5764943 #> [11,] 0.7349492 0.7504106 0.7658720 0.7813334 0.7967948 0.8122562 0.8277176 #> [12,] 0.7592333 0.7711781 0.7831229 0.7950678 0.8070126 0.8189575 0.8309023 #> [13,] 0.8502411 0.8643909 0.8785408 0.8926906 0.9068405 0.9209903 0.9351402 #> [14,] 0.6082062 0.6188715 0.6295368 0.6402021 0.6508674 0.6615327 0.6721980 #> [15,] 0.7420906 0.7562885 0.7704864 0.7846842 0.7988821 0.8130799 0.8272778 #> [16,] 0.8495765 0.8652330 0.8808894 0.8965459 0.9122024 0.9278588 0.9435153 #> [17,] 0.7441709 0.7590237 0.7738764 0.7887292 0.8035819 0.8184347 0.8332874 #> [18,] 0.6248193 0.6376071 0.6503949 0.6631827 0.6759705 0.6887583 0.7015461 #> [19,] 0.8855968 0.8991107 0.9126246 0.9261384 0.9396523 0.9531661 0.9666800 #> [20,] 0.7415137 0.7544970 0.7674803 0.7804635 0.7934468 0.8064301 0.8194133 #> [21,] 0.8114547 0.8373620 0.8632693 0.8891767 0.9150840 0.9409913 0.9668986 #> [22,] 0.8131384 0.8458713 0.8786042 0.9113370 0.9440699 0.9768028 1.0095357 #> [23,] 0.7978307 0.8251261 0.8524215 0.8797169 0.9070123 0.9343078 0.9616032 #> [24,] 0.6772907 0.7039283 0.7305659 0.7572035 0.7838411 0.8104787 0.8371163 #> [25,] 0.9985414 1.0317339 1.0649265 1.0981190 1.1313115 1.1645041 1.1976966 #> [26,] 0.9881048 1.0202522 1.0523995 1.0845469 1.1166942 1.1488416 1.1809889 #> [27,] 0.9117162 0.9440223 0.9763284 1.0086345 1.0409406 1.0732467 1.1055529 #> [28,] 0.8751124 0.9077043 0.9402963 0.9728883 1.0054803 1.0380723 1.0706642 #> [29,] 0.7673463 0.7973321 0.8273179 0.8573038 0.8872896 0.9172754 0.9472613 #> [30,] 0.8560321 0.8895502 0.9230684 0.9565866 0.9901047 1.0236229 1.0571410 #>           [,35]     [,36]     [,37]     [,38]     [,39]     [,40]     [,41] #>  [1,] 1.7836810 1.8058244 1.8279678 1.8501112 1.8722546 1.8943980 1.9165414 #>  [2,] 1.8535647 1.8786169 1.9036692 1.9287214 1.9537737 1.9788259 2.0038782 #>  [3,] 1.8136417 1.8362348 1.8588278 1.8814208 1.9040139 1.9266069 1.9492000 #>  [4,] 1.7175461 1.7407440 1.7639419 1.7871398 1.8103378 1.8335357 1.8567336 #>  [5,] 1.6424702 1.6643940 1.6863179 1.7082417 1.7301656 1.7520894 1.7740133 #>  [6,] 1.9609927 1.9874499 2.0139071 2.0403643 2.0668215 2.0932787 2.1197359 #>  [7,] 2.0434721 2.0700461 2.0966200 2.1231940 2.1497679 2.1763419 2.2029158 #>  [8,] 1.8616206 1.8845297 1.9074388 1.9303478 1.9532569 1.9761660 1.9990750 #>  [9,] 1.6537928 1.6740248 1.6942569 1.7144889 1.7347210 1.7549531 1.7751851 #> [10,] 1.5967843 1.6170744 1.6373644 1.6576545 1.6779445 1.6982346 1.7185246 #> [11,] 0.8431790 0.8586403 0.8741017 0.8895631 0.9050245 0.9204859 0.9359473 #> [12,] 0.8428471 0.8547920 0.8667368 0.8786817 0.8906265 0.9025713 0.9145162 #> [13,] 0.9492900 0.9634399 0.9775897 0.9917396 1.0058894 1.0200393 1.0341891 #> [14,] 0.6828633 0.6935286 0.7041939 0.7148592 0.7255245 0.7361898 0.7468551 #> [15,] 0.8414757 0.8556735 0.8698714 0.8840692 0.8982671 0.9124649 0.9266628 #> [16,] 0.9591718 0.9748282 0.9904847 1.0061411 1.0217976 1.0374541 1.0531105 #> [17,] 0.8481401 0.8629929 0.8778456 0.8926984 0.9075511 0.9224039 0.9372566 #> [18,] 0.7143340 0.7271218 0.7399096 0.7526974 0.7654852 0.7782730 0.7910608 #> [19,] 0.9801939 0.9937077 1.0072216 1.0207355 1.0342493 1.0477632 1.0612770 #> [20,] 0.8323966 0.8453799 0.8583631 0.8713464 0.8843297 0.8973129 0.9102962 #> [21,] 0.9928060 1.0187133 1.0446206 1.0705279 1.0964353 1.1223426 1.1482499 #> [22,] 1.0422686 1.0750015 1.1077344 1.1404673 1.1732001 1.2059330 1.2386659 #> [23,] 0.9888986 1.0161940 1.0434894 1.0707848 1.0980802 1.1253756 1.1526710 #> [24,] 0.8637539 0.8903915 0.9170291 0.9436667 0.9703043 0.9969419 1.0235795 #> [25,] 1.2308892 1.2640817 1.2972743 1.3304668 1.3636594 1.3968519 1.4300444 #> [26,] 1.2131363 1.2452836 1.2774310 1.3095783 1.3417257 1.3738730 1.4060203 #> [27,] 1.1378590 1.1701651 1.2024712 1.2347773 1.2670834 1.2993896 1.3316957 #> [28,] 1.1032562 1.1358482 1.1684402 1.2010321 1.2336241 1.2662161 1.2988081 #> [29,] 0.9772471 1.0072329 1.0372187 1.0672046 1.0971904 1.1271762 1.1571621 #> [30,] 1.0906592 1.1241774 1.1576955 1.1912137 1.2247318 1.2582500 1.2917682 #>           [,42]     [,43]     [,44]     [,45]     [,46]     [,47]     [,48] #>  [1,] 1.9386848 1.9608283 1.9829717 2.0051151 2.0272585 2.0494019 2.0715453 #>  [2,] 2.0289305 2.0539827 2.0790350 2.1040872 2.1291395 2.1541917 2.1792440 #>  [3,] 1.9717930 1.9943861 2.0169791 2.0395721 2.0621652 2.0847582 2.1073513 #>  [4,] 1.8799316 1.9031295 1.9263274 1.9495254 1.9727233 1.9959212 2.0191192 #>  [5,] 1.7959371 1.8178610 1.8397848 1.8617086 1.8836325 1.9055563 1.9274802 #>  [6,] 2.1461931 2.1726503 2.1991075 2.2255647 2.2520219 2.2784790 2.3049362 #>  [7,] 2.2294898 2.2560637 2.2826377 2.3092116 2.3357856 2.3623596 2.3889335 #>  [8,] 2.0219841 2.0448931 2.0678022 2.0907113 2.1136203 2.1365294 2.1594385 #>  [9,] 1.7954172 1.8156492 1.8358813 1.8561134 1.8763454 1.8965775 1.9168096 #> [10,] 1.7388147 1.7591047 1.7793948 1.7996848 1.8199749 1.8402649 1.8605550 #> [11,] 0.9514087 0.9668701 0.9823315 0.9977929 1.0132543 1.0287157 1.0441771 #> [12,] 0.9264610 0.9384059 0.9503507 0.9622955 0.9742404 0.9861852 0.9981301 #> [13,] 1.0483390 1.0624888 1.0766387 1.0907885 1.1049384 1.1190882 1.1332381 #> [14,] 0.7575203 0.7681856 0.7788509 0.7895162 0.8001815 0.8108468 0.8215121 #> [15,] 0.9408607 0.9550585 0.9692564 0.9834542 0.9976521 1.0118499 1.0260478 #> [16,] 1.0687670 1.0844235 1.1000799 1.1157364 1.1313928 1.1470493 1.1627058 #> [17,] 0.9521093 0.9669621 0.9818148 0.9966676 1.0115203 1.0263730 1.0412258 #> [18,] 0.8038486 0.8166364 0.8294242 0.8422120 0.8549998 0.8677876 0.8805754 #> [19,] 1.0747909 1.0883048 1.1018186 1.1153325 1.1288464 1.1423602 1.1558741 #> [20,] 0.9232795 0.9362627 0.9492460 0.9622293 0.9752125 0.9881958 1.0011791 #> [21,] 1.1741572 1.2000646 1.2259719 1.2518792 1.2777865 1.3036939 1.3296012 #> [22,] 1.2713988 1.3041317 1.3368646 1.3695975 1.4023303 1.4350632 1.4677961 #> [23,] 1.1799664 1.2072618 1.2345572 1.2618526 1.2891480 1.3164435 1.3437389 #> [24,] 1.0502171 1.0768547 1.1034923 1.1301299 1.1567676 1.1834052 1.2100428 #> [25,] 1.4632370 1.4964295 1.5296221 1.5628146 1.5960072 1.6291997 1.6623923 #> [26,] 1.4381677 1.4703150 1.5024624 1.5346097 1.5667571 1.5989044 1.6310518 #> [27,] 1.3640018 1.3963079 1.4286140 1.4609201 1.4932263 1.5255324 1.5578385 #> [28,] 1.3314001 1.3639920 1.3965840 1.4291760 1.4617680 1.4943599 1.5269519 #> [29,] 1.1871479 1.2171337 1.2471196 1.2771054 1.3070912 1.3370771 1.3670629 #> [30,] 1.3252863 1.3588045 1.3923226 1.4258408 1.4593590 1.4928771 1.5263953 #>           [,49]     [,50]     [,51]     [,52]     [,53]     [,54]     [,55] #>  [1,] 2.0936887 2.1158321 2.1379755 2.1601189 2.1822623 2.2044057 2.2265491 #>  [2,] 2.2042963 2.2293485 2.2544008 2.2794530 2.3045053 2.3295575 2.3546098 #>  [3,] 2.1299443 2.1525374 2.1751304 2.1977235 2.2203165 2.2429095 2.2655026 #>  [4,] 2.0423171 2.0655150 2.0887130 2.1119109 2.1351088 2.1583068 2.1815047 #>  [5,] 1.9494040 1.9713279 1.9932517 2.0151756 2.0370994 2.0590232 2.0809471 #>  [6,] 2.3313934 2.3578506 2.3843078 2.4107650 2.4372222 2.4636794 2.4901366 #>  [7,] 2.4155075 2.4420814 2.4686554 2.4952293 2.5218033 2.5483772 2.5749512 #>  [8,] 2.1823475 2.2052566 2.2281657 2.2510747 2.2739838 2.2968929 2.3198019 #>  [9,] 1.9370416 1.9572737 1.9775057 1.9977378 2.0179699 2.0382019 2.0584340 #> [10,] 1.8808450 1.9011351 1.9214251 1.9417152 1.9620052 1.9822953 2.0025853 #> [11,] 1.0596385 1.0750998 1.0905612 1.1060226 1.1214840 1.1369454 1.1524068 #> [12,] 1.0100749 1.0220197 1.0339646 1.0459094 1.0578543 1.0697991 1.0817439 #> [13,] 1.1473879 1.1615378 1.1756877 1.1898375 1.2039874 1.2181372 1.2322871 #> [14,] 0.8321774 0.8428427 0.8535080 0.8641733 0.8748386 0.8855039 0.8961692 #> [15,] 1.0402457 1.0544435 1.0686414 1.0828392 1.0970371 1.1112350 1.1254328 #> [16,] 1.1783622 1.1940187 1.2096752 1.2253316 1.2409881 1.2566446 1.2723010 #> [17,] 1.0560785 1.0709313 1.0857840 1.1006368 1.1154895 1.1303422 1.1451950 #> [18,] 0.8933632 0.9061511 0.9189389 0.9317267 0.9445145 0.9573023 0.9700901 #> [19,] 1.1693880 1.1829018 1.1964157 1.2099295 1.2234434 1.2369573 1.2504711 #> [20,] 1.0141623 1.0271456 1.0401289 1.0531121 1.0660954 1.0790787 1.0920619 #> [21,] 1.3555085 1.3814158 1.4073232 1.4332305 1.4591378 1.4850452 1.5109525 #> [22,] 1.5005290 1.5332619 1.5659948 1.5987277 1.6314606 1.6641934 1.6969263 #> [23,] 1.3710343 1.3983297 1.4256251 1.4529205 1.4802159 1.5075113 1.5348067 #> [24,] 1.2366804 1.2633180 1.2899556 1.3165932 1.3432308 1.3698684 1.3965060 #> [25,] 1.6955848 1.7287774 1.7619699 1.7951624 1.8283550 1.8615475 1.8947401 #> [26,] 1.6631991 1.6953465 1.7274938 1.7596411 1.7917885 1.8239358 1.8560832 #> [27,] 1.5901446 1.6224507 1.6547568 1.6870630 1.7193691 1.7516752 1.7839813 #> [28,] 1.5595439 1.5921359 1.6247279 1.6573198 1.6899118 1.7225038 1.7550958 #> [29,] 1.3970487 1.4270346 1.4570204 1.4870062 1.5169920 1.5469779 1.5769637 #> [30,] 1.5599135 1.5934316 1.6269498 1.6604679 1.6939861 1.7275043 1.7610224 #>           [,56]     [,57]    [,58]     [,59]     [,60]     [,61]     [,62] #>  [1,] 2.2486925 2.2708359 2.292979 2.3151228 2.3372662 2.3594096 2.3815530 #>  [2,] 2.3796621 2.4047143 2.429767 2.4548188 2.4798711 2.5049233 2.5299756 #>  [3,] 2.2880956 2.3106887 2.333282 2.3558748 2.3784678 2.4010608 2.4236539 #>  [4,] 2.2047026 2.2279005 2.251098 2.2742964 2.2974943 2.3206923 2.3438902 #>  [5,] 2.1028709 2.1247948 2.146719 2.1686425 2.1905663 2.2124902 2.2344140 #>  [6,] 2.5165938 2.5430510 2.569508 2.5959654 2.6224226 2.6488798 2.6753370 #>  [7,] 2.6015251 2.6280991 2.654673 2.6812470 2.7078210 2.7343949 2.7609689 #>  [8,] 2.3427110 2.3656200 2.388529 2.4114382 2.4343472 2.4572563 2.4801654 #>  [9,] 2.0786660 2.0988981 2.119130 2.1393622 2.1595943 2.1798264 2.2000584 #> [10,] 2.0228754 2.0431654 2.063455 2.0837455 2.1040356 2.1243256 2.1446157 #> [11,] 1.1678682 1.1833296 1.198791 1.2142524 1.2297138 1.2451752 1.2606366 #> [12,] 1.0936888 1.1056336 1.117578 1.1295233 1.1414681 1.1534130 1.1653578 #> [13,] 1.2464369 1.2605868 1.274737 1.2888865 1.3030363 1.3171862 1.3313360 #> [14,] 0.9068344 0.9174997 0.928165 0.9388303 0.9494956 0.9601609 0.9708262 #> [15,] 1.1396307 1.1538285 1.168026 1.1822242 1.1964221 1.2106200 1.2248178 #> [16,] 1.2879575 1.3036139 1.319270 1.3349269 1.3505833 1.3662398 1.3818963 #> [17,] 1.1600477 1.1749005 1.189753 1.2046060 1.2194587 1.2343114 1.2491642 #> [18,] 0.9828779 0.9956657 1.008454 1.0212413 1.0340291 1.0468169 1.0596047 #> [19,] 1.2639850 1.2774989 1.291013 1.3045266 1.3180404 1.3315543 1.3450682 #> [20,] 1.1050452 1.1180285 1.131012 1.1439950 1.1569783 1.1699616 1.1829448 #> [21,] 1.5368598 1.5627671 1.588674 1.6145818 1.6404891 1.6663964 1.6923038 #> [22,] 1.7296592 1.7623921 1.795125 1.8278579 1.8605908 1.8933237 1.9260565 #> [23,] 1.5621021 1.5893975 1.616693 1.6439883 1.6712838 1.6985792 1.7258746 #> [24,] 1.4231436 1.4497812 1.476419 1.5030564 1.5296940 1.5563316 1.5829692 #> [25,] 1.9279326 1.9611252 1.994318 2.0275103 2.0607028 2.0938953 2.1270879 #> [26,] 1.8882305 1.9203779 1.952525 1.9846726 2.0168199 2.0489673 2.0811146 #> [27,] 1.8162874 1.8485935 1.880900 1.9132058 1.9455119 1.9778180 2.0101241 #> [28,] 1.7876877 1.8202797 1.852872 1.8854637 1.9180556 1.9506476 1.9832396 #> [29,] 1.6069495 1.6369354 1.666921 1.6969070 1.7268929 1.7568787 1.7868645 #> [30,] 1.7945406 1.8280587 1.861577 1.8950951 1.9286132 1.9621314 1.9956495 #>           [,63]     [,64]    [,65]    [,66]    [,67]    [,68]    [,69]    [,70] #>  [1,] 2.4036964 2.4258398 2.447983 2.470127 2.492270 2.514413 2.536557 2.558700 #>  [2,] 2.5550279 2.5800801 2.605132 2.630185 2.655237 2.680289 2.705341 2.730394 #>  [3,] 2.4462469 2.4688400 2.491433 2.514026 2.536619 2.559212 2.581805 2.604398 #>  [4,] 2.3670881 2.3902861 2.413484 2.436682 2.459880 2.483078 2.506276 2.529474 #>  [5,] 2.2563379 2.2782617 2.300186 2.322109 2.344033 2.365957 2.387881 2.409805 #>  [6,] 2.7017942 2.7282514 2.754709 2.781166 2.807623 2.834080 2.860537 2.886995 #>  [7,] 2.7875428 2.8141168 2.840691 2.867265 2.893839 2.920413 2.946987 2.973560 #>  [8,] 2.5030744 2.5259835 2.548893 2.571802 2.594711 2.617620 2.640529 2.663438 #>  [9,] 2.2202905 2.2405225 2.260755 2.280987 2.301219 2.321451 2.341683 2.361915 #> [10,] 2.1649057 2.1851958 2.205486 2.225776 2.246066 2.266356 2.286646 2.306936 #> [11,] 1.2760980 1.2915593 1.307021 1.322482 1.337944 1.353405 1.368866 1.384328 #> [12,] 1.1773027 1.1892475 1.201192 1.213137 1.225082 1.237027 1.248972 1.260917 #> [13,] 1.3454859 1.3596357 1.373786 1.387935 1.402085 1.416235 1.430385 1.444535 #> [14,] 0.9814915 0.9921568 1.002822 1.013487 1.024153 1.034818 1.045483 1.056149 #> [15,] 1.2390157 1.2532135 1.267411 1.281609 1.295807 1.310005 1.324203 1.338401 #> [16,] 1.3975527 1.4132092 1.428866 1.444522 1.460179 1.475835 1.491492 1.507148 #> [17,] 1.2640169 1.2788697 1.293722 1.308575 1.323428 1.338281 1.353133 1.367986 #> [18,] 1.0723925 1.0851803 1.097968 1.110756 1.123544 1.136332 1.149119 1.161907 #> [19,] 1.3585820 1.3720959 1.385610 1.399124 1.412637 1.426151 1.439665 1.453179 #> [20,] 1.1959281 1.2089114 1.221895 1.234878 1.247861 1.260844 1.273828 1.286811 #> [21,] 1.7182111 1.7441184 1.770026 1.795933 1.821840 1.847748 1.873655 1.899562 #> [22,] 1.9587894 1.9915223 2.024255 2.056988 2.089721 2.122454 2.155187 2.187920 #> [23,] 1.7531700 1.7804654 1.807761 1.835056 1.862352 1.889647 1.916942 1.944238 #> [24,] 1.6096068 1.6362444 1.662882 1.689520 1.716157 1.742795 1.769432 1.796070 #> [25,] 2.1602804 2.1934730 2.226666 2.259858 2.293051 2.326243 2.359436 2.392628 #> [26,] 2.1132620 2.1454093 2.177557 2.209704 2.241851 2.273999 2.306146 2.338293 #> [27,] 2.0424302 2.0747364 2.107042 2.139349 2.171655 2.203961 2.236267 2.268573 #> [28,] 2.0158316 2.0484236 2.081016 2.113608 2.146199 2.178791 2.211383 2.243975 #> [29,] 1.8168504 1.8468362 1.876822 1.906808 1.936794 1.966780 1.996765 2.026751 #> [30,] 2.0291677 2.0626859 2.096204 2.129722 2.163240 2.196759 2.230277 2.263795 #>          [,71]    [,72]    [,73]    [,74]    [,75]    [,76]    [,77]    [,78] #>  [1,] 2.580844 2.602987 2.625130 2.647274 2.669417 2.691561 2.713704 2.735847 #>  [2,] 2.755446 2.780498 2.805550 2.830603 2.855655 2.880707 2.905759 2.930812 #>  [3,] 2.626991 2.649584 2.672177 2.694770 2.717363 2.739957 2.762550 2.785143 #>  [4,] 2.552672 2.575870 2.599067 2.622265 2.645463 2.668661 2.691859 2.715057 #>  [5,] 2.431729 2.453652 2.475576 2.497500 2.519424 2.541348 2.563272 2.585196 #>  [6,] 2.913452 2.939909 2.966366 2.992823 3.019281 3.045738 3.072195 3.098652 #>  [7,] 3.000134 3.026708 3.053282 3.079856 3.106430 3.133004 3.159578 3.186152 #>  [8,] 2.686347 2.709256 2.732165 2.755074 2.777983 2.800892 2.823801 2.846710 #>  [9,] 2.382147 2.402379 2.422611 2.442843 2.463075 2.483307 2.503539 2.523771 #> [10,] 2.327226 2.347516 2.367806 2.388096 2.408386 2.428676 2.448966 2.469256 #> [11,] 1.399789 1.415250 1.430712 1.446173 1.461635 1.477096 1.492557 1.508019 #> [12,] 1.272861 1.284806 1.296751 1.308696 1.320641 1.332586 1.344530 1.356475 #> [13,] 1.458685 1.472835 1.486984 1.501134 1.515284 1.529434 1.543584 1.557734 #> [14,] 1.066814 1.077479 1.088144 1.098810 1.109475 1.120140 1.130806 1.141471 #> [15,] 1.352599 1.366796 1.380994 1.395192 1.409390 1.423588 1.437786 1.451984 #> [16,] 1.522804 1.538461 1.554117 1.569774 1.585430 1.601087 1.616743 1.632400 #> [17,] 1.382839 1.397692 1.412544 1.427397 1.442250 1.457103 1.471955 1.486808 #> [18,] 1.174695 1.187483 1.200271 1.213058 1.225846 1.238634 1.251422 1.264210 #> [19,] 1.466693 1.480207 1.493721 1.507235 1.520748 1.534262 1.547776 1.561290 #> [20,] 1.299794 1.312777 1.325761 1.338744 1.351727 1.364711 1.377694 1.390677 #> [21,] 1.925470 1.951377 1.977284 2.003192 2.029099 2.055006 2.080914 2.106821 #> [22,] 2.220653 2.253385 2.286118 2.318851 2.351584 2.384317 2.417050 2.449783 #> [23,] 1.971533 1.998829 2.026124 2.053419 2.080715 2.108010 2.135306 2.162601 #> [24,] 1.822708 1.849345 1.875983 1.902620 1.929258 1.955896 1.982533 2.009171 #> [25,] 2.425821 2.459013 2.492206 2.525398 2.558591 2.591784 2.624976 2.658169 #> [26,] 2.370441 2.402588 2.434735 2.466883 2.499030 2.531177 2.563325 2.595472 #> [27,] 2.300879 2.333185 2.365491 2.397798 2.430104 2.462410 2.494716 2.527022 #> [28,] 2.276567 2.309159 2.341751 2.374343 2.406935 2.439527 2.472119 2.504711 #> [29,] 2.056737 2.086723 2.116709 2.146694 2.176680 2.206666 2.236652 2.266638 #> [30,] 2.297313 2.330831 2.364349 2.397867 2.431386 2.464904 2.498422 2.531940 #>          [,79]    [,80]    [,81]    [,82]    [,83]    [,84]    [,85]    [,86] #>  [1,] 2.757991 2.780134 2.802278 2.824421 2.846564 2.868708 2.890851 2.912995 #>  [2,] 2.955864 2.980916 3.005968 3.031021 3.056073 3.081125 3.106178 3.131230 #>  [3,] 2.807736 2.830329 2.852922 2.875515 2.898108 2.920701 2.943294 2.965887 #>  [4,] 2.738255 2.761453 2.784651 2.807849 2.831047 2.854245 2.877443 2.900641 #>  [5,] 2.607119 2.629043 2.650967 2.672891 2.694815 2.716739 2.738662 2.760586 #>  [6,] 3.125109 3.151567 3.178024 3.204481 3.230938 3.257395 3.283853 3.310310 #>  [7,] 3.212726 3.239300 3.265874 3.292448 3.319022 3.345596 3.372170 3.398744 #>  [8,] 2.869619 2.892529 2.915438 2.938347 2.961256 2.984165 3.007074 3.029983 #>  [9,] 2.544003 2.564236 2.584468 2.604700 2.624932 2.645164 2.665396 2.685628 #> [10,] 2.489547 2.509837 2.530127 2.550417 2.570707 2.590997 2.611287 2.631577 #> [11,] 1.523480 1.538942 1.554403 1.569864 1.585326 1.600787 1.616249 1.631710 #> [12,] 1.368420 1.380365 1.392310 1.404255 1.416199 1.428144 1.440089 1.452034 #> [13,] 1.571883 1.586033 1.600183 1.614333 1.628483 1.642633 1.656783 1.670932 #> [14,] 1.152136 1.162801 1.173467 1.184132 1.194797 1.205463 1.216128 1.226793 #> [15,] 1.466181 1.480379 1.494577 1.508775 1.522973 1.537171 1.551369 1.565566 #> [16,] 1.648056 1.663713 1.679369 1.695026 1.710682 1.726338 1.741995 1.757651 #> [17,] 1.501661 1.516514 1.531366 1.546219 1.561072 1.575925 1.590777 1.605630 #> [18,] 1.276997 1.289785 1.302573 1.315361 1.328149 1.340936 1.353724 1.366512 #> [19,] 1.574804 1.588318 1.601832 1.615345 1.628859 1.642373 1.655887 1.669401 #> [20,] 1.403660 1.416644 1.429627 1.442610 1.455593 1.468577 1.481560 1.494543 #> [21,] 2.132728 2.158636 2.184543 2.210450 2.236358 2.262265 2.288172 2.314080 #> [22,] 2.482516 2.515248 2.547981 2.580714 2.613447 2.646180 2.678913 2.711646 #> [23,] 2.189896 2.217192 2.244487 2.271783 2.299078 2.326374 2.353669 2.380964 #> [24,] 2.035808 2.062446 2.089084 2.115721 2.142359 2.168996 2.195634 2.222272 #> [25,] 2.691361 2.724554 2.757746 2.790939 2.824131 2.857324 2.890516 2.923709 #> [26,] 2.627619 2.659767 2.691914 2.724062 2.756209 2.788356 2.820504 2.852651 #> [27,] 2.559328 2.591634 2.623940 2.656246 2.688553 2.720859 2.753165 2.785471 #> [28,] 2.537303 2.569895 2.602487 2.635079 2.667671 2.700263 2.732855 2.765447 #> [29,] 2.296624 2.326609 2.356595 2.386581 2.416567 2.446553 2.476539 2.506524 #> [30,] 2.565458 2.598976 2.632495 2.666013 2.699531 2.733049 2.766567 2.800085 #>          [,87]    [,88]    [,89]    [,90]    [,91]    [,92]    [,93]    [,94] #>  [1,] 2.935138 2.957282 2.979425 3.001568 3.023712 3.045855 3.067999 3.090142 #>  [2,] 3.156282 3.181334 3.206387 3.231439 3.256491 3.281543 3.306596 3.331648 #>  [3,] 2.988480 3.011073 3.033666 3.056259 3.078852 3.101445 3.124038 3.146631 #>  [4,] 2.923838 2.947036 2.970234 2.993432 3.016630 3.039828 3.063026 3.086224 #>  [5,] 2.782510 2.804434 2.826358 2.848282 2.870206 2.892129 2.914053 2.935977 #>  [6,] 3.336767 3.363224 3.389681 3.416139 3.442596 3.469053 3.495510 3.521967 #>  [7,] 3.425318 3.451892 3.478466 3.505040 3.531614 3.558187 3.584761 3.611335 #>  [8,] 3.052892 3.075801 3.098710 3.121619 3.144528 3.167437 3.190346 3.213255 #>  [9,] 2.705860 2.726092 2.746324 2.766556 2.786788 2.807020 2.827252 2.847484 #> [10,] 2.651867 2.672157 2.692447 2.712737 2.733027 2.753317 2.773607 2.793897 #> [11,] 1.647171 1.662633 1.678094 1.693556 1.709017 1.724478 1.739940 1.755401 #> [12,] 1.463979 1.475924 1.487868 1.499813 1.511758 1.523703 1.535648 1.547593 #> [13,] 1.685082 1.699232 1.713382 1.727532 1.741682 1.755832 1.769981 1.784131 #> [14,] 1.237459 1.248124 1.258789 1.269454 1.280120 1.290785 1.301450 1.312116 #> [15,] 1.579764 1.593962 1.608160 1.622358 1.636556 1.650754 1.664951 1.679149 #> [16,] 1.773308 1.788964 1.804621 1.820277 1.835934 1.851590 1.867247 1.882903 #> [17,] 1.620483 1.635335 1.650188 1.665041 1.679894 1.694746 1.709599 1.724452 #> [18,] 1.379300 1.392088 1.404876 1.417663 1.430451 1.443239 1.456027 1.468815 #> [19,] 1.682915 1.696429 1.709942 1.723456 1.736970 1.750484 1.763998 1.777512 #> [20,] 1.507526 1.520510 1.533493 1.546476 1.559460 1.572443 1.585426 1.598409 #> [21,] 2.339987 2.365894 2.391802 2.417709 2.443616 2.469524 2.495431 2.521338 #> [22,] 2.744379 2.777112 2.809844 2.842577 2.875310 2.908043 2.940776 2.973509 #> [23,] 2.408260 2.435555 2.462851 2.490146 2.517441 2.544737 2.572032 2.599328 #> [24,] 2.248909 2.275547 2.302184 2.328822 2.355460 2.382097 2.408735 2.435373 #> [25,] 2.956902 2.990094 3.023287 3.056479 3.089672 3.122864 3.156057 3.189249 #> [26,] 2.884798 2.916946 2.949093 2.981240 3.013388 3.045535 3.077682 3.109830 #> [27,] 2.817777 2.850083 2.882389 2.914695 2.947002 2.979308 3.011614 3.043920 #> [28,] 2.798039 2.830631 2.863223 2.895815 2.928407 2.960999 2.993591 3.026183 #> [29,] 2.536510 2.566496 2.596482 2.626468 2.656454 2.686439 2.716425 2.746411 #> [30,] 2.833604 2.867122 2.900640 2.934158 2.967676 3.001194 3.034713 3.068231 #>          [,95]    [,96]    [,97]    [,98]    [,99]   [,100]   [,101]   [,102] #>  [1,] 3.112285 3.134429 3.156572 3.178716 3.200859 3.223002 3.245146 3.267289 #>  [2,] 3.356700 3.381752 3.406805 3.431857 3.456909 3.481961 3.507014 3.532066 #>  [3,] 3.169224 3.191817 3.214410 3.237003 3.259597 3.282190 3.304783 3.327376 #>  [4,] 3.109422 3.132620 3.155818 3.179016 3.202214 3.225412 3.248610 3.271807 #>  [5,] 2.957901 2.979825 3.001749 3.023672 3.045596 3.067520 3.089444 3.111368 #>  [6,] 3.548424 3.574882 3.601339 3.627796 3.654253 3.680710 3.707168 3.733625 #>  [7,] 3.637909 3.664483 3.691057 3.717631 3.744205 3.770779 3.797353 3.823927 #>  [8,] 3.236164 3.259074 3.281983 3.304892 3.327801 3.350710 3.373619 3.396528 #>  [9,] 2.867716 2.887948 2.908181 2.928413 2.948645 2.968877 2.989109 3.009341 #> [10,] 2.814187 2.834477 2.854767 2.875057 2.895348 2.915638 2.935928 2.956218 #> [11,] 1.770863 1.786324 1.801785 1.817247 1.832708 1.848169 1.863631 1.879092 #> [12,] 1.559538 1.571482 1.583427 1.595372 1.607317 1.619262 1.631207 1.643151 #> [13,] 1.798281 1.812431 1.826581 1.840731 1.854881 1.869030 1.883180 1.897330 #> [14,] 1.322781 1.333446 1.344111 1.354777 1.365442 1.376107 1.386773 1.397438 #> [15,] 1.693347 1.707545 1.721743 1.735941 1.750139 1.764336 1.778534 1.792732 #> [16,] 1.898560 1.914216 1.929872 1.945529 1.961185 1.976842 1.992498 2.008155 #> [17,] 1.739305 1.754157 1.769010 1.783863 1.798716 1.813568 1.828421 1.843274 #> [18,] 1.481602 1.494390 1.507178 1.519966 1.532754 1.545541 1.558329 1.571117 #> [19,] 1.791026 1.804540 1.818053 1.831567 1.845081 1.858595 1.872109 1.885623 #> [20,] 1.611393 1.624376 1.637359 1.650342 1.663326 1.676309 1.689292 1.702275 #> [21,] 2.547245 2.573153 2.599060 2.624967 2.650875 2.676782 2.702689 2.728597 #> [22,] 3.006242 3.038975 3.071708 3.104440 3.137173 3.169906 3.202639 3.235372 #> [23,] 2.626623 2.653918 2.681214 2.708509 2.735805 2.763100 2.790395 2.817691 #> [24,] 2.462010 2.488648 2.515285 2.541923 2.568561 2.595198 2.621836 2.648473 #> [25,] 3.222442 3.255634 3.288827 3.322020 3.355212 3.388405 3.421597 3.454790 #> [26,] 3.141977 3.174124 3.206272 3.238419 3.270566 3.302714 3.334861 3.367008 #> [27,] 3.076226 3.108532 3.140838 3.173144 3.205450 3.237757 3.270063 3.302369 #> [28,] 3.058775 3.091367 3.123959 3.156551 3.189143 3.221735 3.254327 3.286919 #> [29,] 2.776397 2.806383 2.836369 2.866354 2.896340 2.926326 2.956312 2.986298 #> [30,] 3.101749 3.135267 3.168785 3.202303 3.235822 3.269340 3.302858 3.336376 #>         [,103]   [,104]   [,105]   [,106]   [,107]   [,108]   [,109]   [,110] #>  [1,] 3.289433 3.311576 3.333719 3.355863 3.378006 3.400150 3.422293 3.444436 #>  [2,] 3.557118 3.582170 3.607223 3.632275 3.657327 3.682379 3.707432 3.732484 #>  [3,] 3.349969 3.372562 3.395155 3.417748 3.440341 3.462934 3.485527 3.508120 #>  [4,] 3.295005 3.318203 3.341401 3.364599 3.387797 3.410995 3.434193 3.457391 #>  [5,] 3.133292 3.155215 3.177139 3.199063 3.220987 3.242911 3.264835 3.286759 #>  [6,] 3.760082 3.786539 3.812996 3.839454 3.865911 3.892368 3.918825 3.945282 #>  [7,] 3.850501 3.877075 3.903649 3.930223 3.956797 3.983371 4.009945 4.036519 #>  [8,] 3.419437 3.442346 3.465255 3.488164 3.511073 3.533982 3.556891 3.579800 #>  [9,] 3.029573 3.049805 3.070037 3.090269 3.110501 3.130733 3.150965 3.171197 #> [10,] 2.976508 2.996798 3.017088 3.037378 3.057668 3.077958 3.098248 3.118538 #> [11,] 1.894554 1.910015 1.925476 1.940938 1.956399 1.971861 1.987322 2.002783 #> [12,] 1.655096 1.667041 1.678986 1.690931 1.702876 1.714820 1.726765 1.738710 #> [13,] 1.911480 1.925630 1.939780 1.953929 1.968079 1.982229 1.996379 2.010529 #> [14,] 1.408103 1.418768 1.429434 1.440099 1.450764 1.461430 1.472095 1.482760 #> [15,] 1.806930 1.821128 1.835326 1.849524 1.863721 1.877919 1.892117 1.906315 #> [16,] 2.023811 2.039468 2.055124 2.070781 2.086437 2.102094 2.117750 2.133407 #> [17,] 1.858127 1.872979 1.887832 1.902685 1.917538 1.932390 1.947243 1.962096 #> [18,] 1.583905 1.596693 1.609480 1.622268 1.635056 1.647844 1.660632 1.673419 #> [19,] 1.899137 1.912650 1.926164 1.939678 1.953192 1.966706 1.980220 1.993734 #> [20,] 1.715259 1.728242 1.741225 1.754209 1.767192 1.780175 1.793158 1.806142 #> [21,] 2.754504 2.780411 2.806319 2.832226 2.858133 2.884041 2.909948 2.935855 #> [22,] 3.268105 3.300838 3.333571 3.366304 3.399036 3.431769 3.464502 3.497235 #> [23,] 2.844986 2.872282 2.899577 2.926872 2.954168 2.981463 3.008759 3.036054 #> [24,] 2.675111 2.701749 2.728386 2.755024 2.781661 2.808299 2.834937 2.861574 #> [25,] 3.487982 3.521175 3.554367 3.587560 3.620752 3.653945 3.687138 3.720330 #> [26,] 3.399156 3.431303 3.463450 3.495598 3.527745 3.559893 3.592040 3.624187 #> [27,] 3.334675 3.366981 3.399287 3.431593 3.463899 3.496205 3.528512 3.560818 #> [28,] 3.319511 3.352103 3.384695 3.417287 3.449879 3.482471 3.515063 3.547655 #> [29,] 3.016284 3.046269 3.076255 3.106241 3.136227 3.166213 3.196199 3.226184 #> [30,] 3.369894 3.403412 3.436930 3.470449 3.503967 3.537485 3.571003 3.604521 #>         [,111]   [,112]   [,113]   [,114]   [,115]   [,116]   [,117]   [,118] #>  [1,] 3.466580 3.488723 3.510867 3.533010 3.555153 3.577297 3.599440 3.621584 #>  [2,] 3.757536 3.782588 3.807641 3.832693 3.857745 3.882797 3.907850 3.932902 #>  [3,] 3.530713 3.553306 3.575899 3.598492 3.621085 3.643678 3.666271 3.688864 #>  [4,] 3.480589 3.503787 3.526985 3.550183 3.573381 3.596579 3.619776 3.642974 #>  [5,] 3.308682 3.330606 3.352530 3.374454 3.396378 3.418302 3.440225 3.462149 #>  [6,] 3.971740 3.998197 4.024654 4.051111 4.077568 4.104026 4.130483 4.156940 #>  [7,] 4.063093 4.089667 4.116241 4.142814 4.169388 4.195962 4.222536 4.249110 #>  [8,] 3.602709 3.625619 3.648528 3.671437 3.694346 3.717255 3.740164 3.763073 #>  [9,] 3.191429 3.211661 3.231894 3.252126 3.272358 3.292590 3.312822 3.333054 #> [10,] 3.138828 3.159118 3.179408 3.199698 3.219988 3.240278 3.260568 3.280858 #> [11,] 2.018245 2.033706 2.049168 2.064629 2.080090 2.095552 2.111013 2.126475 #> [12,] 1.750655 1.762600 1.774545 1.786490 1.798434 1.810379 1.822324 1.834269 #> [13,] 2.024679 2.038829 2.052978 2.067128 2.081278 2.095428 2.109578 2.123728 #> [14,] 1.493426 1.504091 1.514756 1.525421 1.536087 1.546752 1.557417 1.568083 #> [15,] 1.920513 1.934711 1.948909 1.963106 1.977304 1.991502 2.005700 2.019898 #> [16,] 2.149063 2.164719 2.180376 2.196032 2.211689 2.227345 2.243002 2.258658 #> [17,] 1.976949 1.991801 2.006654 2.021507 2.036360 2.051212 2.066065 2.080918 #> [18,] 1.686207 1.698995 1.711783 1.724571 1.737358 1.750146 1.762934 1.775722 #> [19,] 2.007247 2.020761 2.034275 2.047789 2.061303 2.074817 2.088331 2.101844 #> [20,] 1.819125 1.832108 1.845091 1.858075 1.871058 1.884041 1.897024 1.910008 #> [21,] 2.961763 2.987670 3.013577 3.039485 3.065392 3.091299 3.117207 3.143114 #> [22,] 3.529968 3.562701 3.595434 3.628167 3.660900 3.693632 3.726365 3.759098 #> [23,] 3.063350 3.090645 3.117940 3.145236 3.172531 3.199827 3.227122 3.254417 #> [24,] 2.888212 2.914849 2.941487 2.968125 2.994762 3.021400 3.048037 3.074675 #> [25,] 3.753523 3.786715 3.819908 3.853100 3.886293 3.919485 3.952678 3.985870 #> [26,] 3.656335 3.688482 3.720629 3.752777 3.784924 3.817071 3.849219 3.881366 #> [27,] 3.593124 3.625430 3.657736 3.690042 3.722348 3.754654 3.786961 3.819267 #> [28,] 3.580246 3.612838 3.645430 3.678022 3.710614 3.743206 3.775798 3.808390 #> [29,] 3.256170 3.286156 3.316142 3.346128 3.376114 3.406099 3.436085 3.466071 #> [30,] 3.638039 3.671558 3.705076 3.738594 3.772112 3.805630 3.839148 3.872667 #>         [,119]   [,120]   [,121]   [,122]   [,123]   [,124]   [,125]   [,126] #>  [1,] 3.643727 3.665871 3.688014 3.710157 3.732301 3.754444 3.776588 3.798731 #>  [2,] 3.957954 3.983006 4.008059 4.033111 4.058163 4.083216 4.108268 4.133320 #>  [3,] 3.711457 3.734050 3.756643 3.779237 3.801830 3.824423 3.847016 3.869609 #>  [4,] 3.666172 3.689370 3.712568 3.735766 3.758964 3.782162 3.805360 3.828558 #>  [5,] 3.484073 3.505997 3.527921 3.549845 3.571769 3.593692 3.615616 3.637540 #>  [6,] 4.183397 4.209854 4.236312 4.262769 4.289226 4.315683 4.342140 4.368598 #>  [7,] 4.275684 4.302258 4.328832 4.355406 4.381980 4.408554 4.435128 4.461702 #>  [8,] 3.785982 3.808891 3.831800 3.854709 3.877618 3.900527 3.923436 3.946345 #>  [9,] 3.353286 3.373518 3.393750 3.413982 3.434214 3.454446 3.474678 3.494910 #> [10,] 3.301149 3.321439 3.341729 3.362019 3.382309 3.402599 3.422889 3.443179 #> [11,] 2.141936 2.157397 2.172859 2.188320 2.203782 2.219243 2.234704 2.250166 #> [12,] 1.846214 1.858159 1.870103 1.882048 1.893993 1.905938 1.917883 1.929828 #> [13,] 2.137878 2.152027 2.166177 2.180327 2.194477 2.208627 2.222777 2.236927 #> [14,] 1.578748 1.589413 1.600078 1.610744 1.621409 1.632074 1.642740 1.653405 #> [15,] 2.034096 2.048294 2.062491 2.076689 2.090887 2.105085 2.119283 2.133481 #> [16,] 2.274315 2.289971 2.305628 2.321284 2.336941 2.352597 2.368253 2.383910 #> [17,] 2.095770 2.110623 2.125476 2.140329 2.155181 2.170034 2.184887 2.199740 #> [18,] 1.788510 1.801298 1.814085 1.826873 1.839661 1.852449 1.865237 1.878024 #> [19,] 2.115358 2.128872 2.142386 2.155900 2.169414 2.182928 2.196442 2.209955 #> [20,] 1.922991 1.935974 1.948958 1.961941 1.974924 1.987907 2.000891 2.013874 #> [21,] 3.169021 3.194929 3.220836 3.246743 3.272651 3.298558 3.324465 3.350373 #> [22,] 3.791831 3.824564 3.857297 3.890030 3.922763 3.955496 3.988228 4.020961 #> [23,] 3.281713 3.309008 3.336304 3.363599 3.390894 3.418190 3.445485 3.472781 #> [24,] 3.101313 3.127950 3.154588 3.181225 3.207863 3.234501 3.261138 3.287776 #> [25,] 4.019063 4.052255 4.085448 4.118641 4.151833 4.185026 4.218218 4.251411 #> [26,] 3.913513 3.945661 3.977808 4.009955 4.042103 4.074250 4.106397 4.138545 #> [27,] 3.851573 3.883879 3.916185 3.948491 3.980797 4.013103 4.045409 4.077716 #> [28,] 3.840982 3.873574 3.906166 3.938758 3.971350 4.003942 4.036534 4.069126 #> [29,] 3.496057 3.526043 3.556029 3.586014 3.616000 3.645986 3.675972 3.705958 #> [30,] 3.906185 3.939703 3.973221 4.006739 4.040257 4.073776 4.107294 4.140812 #>         [,127]   [,128]   [,129]   [,130]   [,131]   [,132]   [,133]   [,134] #>  [1,] 3.820874 3.843018 3.865161 3.887305 3.909448 3.931591 3.953735 3.975878 #>  [2,] 4.158372 4.183425 4.208477 4.233529 4.258581 4.283634 4.308686 4.333738 #>  [3,] 3.892202 3.914795 3.937388 3.959981 3.982574 4.005167 4.027760 4.050353 #>  [4,] 3.851756 3.874954 3.898152 3.921350 3.944547 3.967745 3.990943 4.014141 #>  [5,] 3.659464 3.681388 3.703312 3.725235 3.747159 3.769083 3.791007 3.812931 #>  [6,] 4.395055 4.421512 4.447969 4.474426 4.500884 4.527341 4.553798 4.580255 #>  [7,] 4.488276 4.514850 4.541424 4.567998 4.594572 4.621146 4.647720 4.674294 #>  [8,] 3.969255 3.992164 4.015073 4.037982 4.060891 4.083800 4.106709 4.129618 #>  [9,] 3.515142 3.535374 3.555607 3.575839 3.596071 3.616303 3.636535 3.656767 #> [10,] 3.463469 3.483759 3.504049 3.524339 3.544629 3.564919 3.585209 3.605499 #> [11,] 2.265627 2.281088 2.296550 2.312011 2.327473 2.342934 2.358395 2.373857 #> [12,] 1.941772 1.953717 1.965662 1.977607 1.989552 2.001497 2.013441 2.025386 #> [13,] 2.251076 2.265226 2.279376 2.293526 2.307676 2.321826 2.335975 2.350125 #> [14,] 1.664070 1.674736 1.685401 1.696066 1.706731 1.717397 1.728062 1.738727 #> [15,] 2.147679 2.161876 2.176074 2.190272 2.204470 2.218668 2.232866 2.247064 #> [16,] 2.399566 2.415223 2.430879 2.446536 2.462192 2.477849 2.493505 2.509162 #> [17,] 2.214592 2.229445 2.244298 2.259151 2.274003 2.288856 2.303709 2.318562 #> [18,] 1.890812 1.903600 1.916388 1.929176 1.941963 1.954751 1.967539 1.980327 #> [19,] 2.223469 2.236983 2.250497 2.264011 2.277525 2.291039 2.304552 2.318066 #> [20,] 2.026857 2.039840 2.052824 2.065807 2.078790 2.091773 2.104757 2.117740 #> [21,] 3.376280 3.402187 3.428095 3.454002 3.479909 3.505817 3.531724 3.557631 #> [22,] 4.053694 4.086427 4.119160 4.151893 4.184626 4.217359 4.250091 4.282824 #> [23,] 3.500076 3.527371 3.554667 3.581962 3.609258 3.636553 3.663848 3.691144 #> [24,] 3.314413 3.341051 3.367689 3.394326 3.420964 3.447601 3.474239 3.500877 #> [25,] 4.284603 4.317796 4.350988 4.384181 4.417373 4.450566 4.483759 4.516951 #> [26,] 4.170692 4.202839 4.234987 4.267134 4.299281 4.331429 4.363576 4.395724 #> [27,] 4.110022 4.142328 4.174634 4.206940 4.239246 4.271552 4.303858 4.336165 #> [28,] 4.101718 4.134310 4.166902 4.199494 4.232086 4.264678 4.297270 4.329862 #> [29,] 3.735944 3.765929 3.795915 3.825901 3.855887 3.885873 3.915859 3.945844 #> [30,] 4.174330 4.207848 4.241366 4.274884 4.308403 4.341921 4.375439 4.408957 #>         [,135]   [,136]   [,137]   [,138]   [,139]   [,140]   [,141]   [,142] #>  [1,] 3.998022 4.020165 4.042308 4.064452 4.086595 4.108739 4.130882 4.153025 #>  [2,] 4.358790 4.383843 4.408895 4.433947 4.458999 4.484052 4.509104 4.534156 #>  [3,] 4.072946 4.095539 4.118132 4.140725 4.163318 4.185911 4.208504 4.231097 #>  [4,] 4.037339 4.060537 4.083735 4.106933 4.130131 4.153329 4.176527 4.199725 #>  [5,] 3.834855 3.856779 3.878702 3.900626 3.922550 3.944474 3.966398 3.988322 #>  [6,] 4.606712 4.633170 4.659627 4.686084 4.712541 4.738998 4.765456 4.791913 #>  [7,] 4.700867 4.727441 4.754015 4.780589 4.807163 4.833737 4.860311 4.886885 #>  [8,] 4.152527 4.175436 4.198345 4.221254 4.244163 4.267072 4.289981 4.312890 #>  [9,] 3.676999 3.697231 3.717463 3.737695 3.757927 3.778159 3.798391 3.818623 #> [10,] 3.625789 3.646079 3.666369 3.686659 3.706950 3.727240 3.747530 3.767820 #> [11,] 2.389318 2.404780 2.420241 2.435702 2.451164 2.466625 2.482087 2.497548 #> [12,] 2.037331 2.049276 2.061221 2.073166 2.085111 2.097055 2.109000 2.120945 #> [13,] 2.364275 2.378425 2.392575 2.406725 2.420875 2.435024 2.449174 2.463324 #> [14,] 1.749393 1.760058 1.770723 1.781388 1.792054 1.802719 1.813384 1.824050 #> [15,] 2.261261 2.275459 2.289657 2.303855 2.318053 2.332251 2.346449 2.360646 #> [16,] 2.524818 2.540475 2.556131 2.571787 2.587444 2.603100 2.618757 2.634413 #> [17,] 2.333414 2.348267 2.363120 2.377973 2.392825 2.407678 2.422531 2.437384 #> [18,] 1.993115 2.005902 2.018690 2.031478 2.044266 2.057054 2.069841 2.082629 #> [19,] 2.331580 2.345094 2.358608 2.372122 2.385636 2.399149 2.412663 2.426177 #> [20,] 2.130723 2.143707 2.156690 2.169673 2.182656 2.195640 2.208623 2.221606 #> [21,] 3.583539 3.609446 3.635353 3.661260 3.687168 3.713075 3.738982 3.764890 #> [22,] 4.315557 4.348290 4.381023 4.413756 4.446489 4.479222 4.511955 4.544687 #> [23,] 3.718439 3.745735 3.773030 3.800326 3.827621 3.854916 3.882212 3.909507 #> [24,] 3.527514 3.554152 3.580789 3.607427 3.634065 3.660702 3.687340 3.713977 #> [25,] 4.550144 4.583336 4.616529 4.649721 4.682914 4.716106 4.749299 4.782491 #> [26,] 4.427871 4.460018 4.492166 4.524313 4.556460 4.588608 4.620755 4.652902 #> [27,] 4.368471 4.400777 4.433083 4.465389 4.497695 4.530001 4.562307 4.594613 #> [28,] 4.362454 4.395046 4.427638 4.460230 4.492822 4.525414 4.558006 4.590598 #> [29,] 3.975830 4.005816 4.035802 4.065788 4.095774 4.125759 4.155745 4.185731 #> [30,] 4.442475 4.475993 4.509512 4.543030 4.576548 4.610066 4.643584 4.677102 #>         [,143]   [,144]   [,145]   [,146]   [,147]   [,148]   [,149]   [,150] #>  [1,] 4.175169 4.197312 4.219456 4.241599 4.263742 4.285886 4.308029 4.330173 #>  [2,] 4.559208 4.584261 4.609313 4.634365 4.659417 4.684470 4.709522 4.734574 #>  [3,] 4.253690 4.276283 4.298877 4.321470 4.344063 4.366656 4.389249 4.411842 #>  [4,] 4.222923 4.246121 4.269319 4.292516 4.315714 4.338912 4.362110 4.385308 #>  [5,] 4.010245 4.032169 4.054093 4.076017 4.097941 4.119865 4.141789 4.163712 #>  [6,] 4.818370 4.844827 4.871284 4.897742 4.924199 4.950656 4.977113 5.003570 #>  [7,] 4.913459 4.940033 4.966607 4.993181 5.019755 5.046329 5.072903 5.099477 #>  [8,] 4.335800 4.358709 4.381618 4.404527 4.427436 4.450345 4.473254 4.496163 #>  [9,] 3.838855 3.859087 3.879320 3.899552 3.919784 3.940016 3.960248 3.980480 #> [10,] 3.788110 3.808400 3.828690 3.848980 3.869270 3.889560 3.909850 3.930140 #> [11,] 2.513009 2.528471 2.543932 2.559394 2.574855 2.590316 2.605778 2.621239 #> [12,] 2.132890 2.144835 2.156780 2.168724 2.180669 2.192614 2.204559 2.216504 #> [13,] 2.477474 2.491624 2.505774 2.519924 2.534073 2.548223 2.562373 2.576523 #> [14,] 1.834715 1.845380 1.856046 1.866711 1.877376 1.888041 1.898707 1.909372 #> [15,] 2.374844 2.389042 2.403240 2.417438 2.431636 2.445834 2.460031 2.474229 #> [16,] 2.650070 2.665726 2.681383 2.697039 2.712696 2.728352 2.744009 2.759665 #> [17,] 2.452236 2.467089 2.481942 2.496795 2.511647 2.526500 2.541353 2.556205 #> [18,] 2.095417 2.108205 2.120993 2.133780 2.146568 2.159356 2.172144 2.184932 #> [19,] 2.439691 2.453205 2.466719 2.480233 2.493747 2.507260 2.520774 2.534288 #> [20,] 2.234589 2.247573 2.260556 2.273539 2.286523 2.299506 2.312489 2.325472 #> [21,] 3.790797 3.816704 3.842612 3.868519 3.894426 3.920334 3.946241 3.972148 #> [22,] 4.577420 4.610153 4.642886 4.675619 4.708352 4.741085 4.773818 4.806551 #> [23,] 3.936803 3.964098 3.991393 4.018689 4.045984 4.073280 4.100575 4.127870 #> [24,] 3.740615 3.767253 3.793890 3.820528 3.847165 3.873803 3.900441 3.927078 #> [25,] 4.815684 4.848877 4.882069 4.915262 4.948454 4.981647 5.014839 5.048032 #> [26,] 4.685050 4.717197 4.749344 4.781492 4.813639 4.845786 4.877934 4.910081 #> [27,] 4.626920 4.659226 4.691532 4.723838 4.756144 4.788450 4.820756 4.853062 #> [28,] 4.623190 4.655782 4.688374 4.720966 4.753558 4.786150 4.818742 4.851334 #> [29,] 4.215717 4.245703 4.275688 4.305674 4.335660 4.365646 4.395632 4.425618 #> [30,] 4.710621 4.744139 4.777657 4.811175 4.844693 4.878211 4.911730 4.945248 #>         [,151]   [,152]   [,153]   [,154]   [,155]   [,156]   [,157]   [,158] #>  [1,] 4.352316 4.374460 4.396603 4.418746 4.440890 4.463033 4.485177 4.507320 #>  [2,] 4.759626 4.784679 4.809731 4.834783 4.859835 4.884888 4.909940 4.934992 #>  [3,] 4.434435 4.457028 4.479621 4.502214 4.524807 4.547400 4.569993 4.592586 #>  [4,] 4.408506 4.431704 4.454902 4.478100 4.501298 4.524496 4.547694 4.570892 #>  [5,] 4.185636 4.207560 4.229484 4.251408 4.273332 4.295255 4.317179 4.339103 #>  [6,] 5.030028 5.056485 5.082942 5.109399 5.135856 5.162314 5.188771 5.215228 #>  [7,] 5.126051 5.152625 5.179199 5.205773 5.232347 5.258921 5.285494 5.312068 #>  [8,] 4.519072 4.541981 4.564890 4.587799 4.610708 4.633617 4.656526 4.679436 #>  [9,] 4.000712 4.020944 4.041176 4.061408 4.081640 4.101872 4.122104 4.142336 #> [10,] 3.950430 3.970720 3.991010 4.011300 4.031590 4.051880 4.072170 4.092460 #> [11,] 2.636701 2.652162 2.667623 2.683085 2.698546 2.714007 2.729469 2.744930 #> [12,] 2.228449 2.240393 2.252338 2.264283 2.276228 2.288173 2.300118 2.312062 #> [13,] 2.590673 2.604823 2.618972 2.633122 2.647272 2.661422 2.675572 2.689722 #> [14,] 1.920037 1.930703 1.941368 1.952033 1.962698 1.973364 1.984029 1.994694 #> [15,] 2.488427 2.502625 2.516823 2.531021 2.545219 2.559416 2.573614 2.587812 #> [16,] 2.775322 2.790978 2.806634 2.822291 2.837947 2.853604 2.869260 2.884917 #> [17,] 2.571058 2.585911 2.600764 2.615616 2.630469 2.645322 2.660175 2.675027 #> [18,] 2.197720 2.210507 2.223295 2.236083 2.248871 2.261659 2.274446 2.287234 #> [19,] 2.547802 2.561316 2.574830 2.588344 2.601857 2.615371 2.628885 2.642399 #> [20,] 2.338456 2.351439 2.364422 2.377405 2.390389 2.403372 2.416355 2.429338 #> [21,] 3.998056 4.023963 4.049870 4.075778 4.101685 4.127592 4.153500 4.179407 #> [22,] 4.839283 4.872016 4.904749 4.937482 4.970215 5.002948 5.035681 5.068414 #> [23,] 4.155166 4.182461 4.209757 4.237052 4.264347 4.291643 4.318938 4.346234 #> [24,] 3.953716 3.980353 4.006991 4.033629 4.060266 4.086904 4.113542 4.140179 #> [25,] 5.081224 5.114417 5.147609 5.180802 5.213995 5.247187 5.280380 5.313572 #> [26,] 4.942228 4.974376 5.006523 5.038670 5.070818 5.102965 5.135112 5.167260 #> [27,] 4.885368 4.917675 4.949981 4.982287 5.014593 5.046899 5.079205 5.111511 #> [28,] 4.883926 4.916518 4.949110 4.981702 5.014294 5.046885 5.079477 5.112069 #> [29,] 4.455603 4.485589 4.515575 4.545561 4.575547 4.605533 4.635518 4.665504 #> [30,] 4.978766 5.012284 5.045802 5.079320 5.112839 5.146357 5.179875 5.213393 #>         [,159]   [,160]   [,161]   [,162]   [,163]   [,164]   [,165]   [,166] #>  [1,] 4.529463 4.551607 4.573750 4.595894 4.618037 4.640180 4.662324 4.684467 #>  [2,] 4.960045 4.985097 5.010149 5.035201 5.060254 5.085306 5.110358 5.135410 #>  [3,] 4.615179 4.637772 4.660365 4.682958 4.705551 4.728144 4.750737 4.773330 #>  [4,] 4.594090 4.617287 4.640485 4.663683 4.686881 4.710079 4.733277 4.756475 #>  [5,] 4.361027 4.382951 4.404875 4.426798 4.448722 4.470646 4.492570 4.514494 #>  [6,] 5.241685 5.268142 5.294599 5.321057 5.347514 5.373971 5.400428 5.426885 #>  [7,] 5.338642 5.365216 5.391790 5.418364 5.444938 5.471512 5.498086 5.524660 #>  [8,] 4.702345 4.725254 4.748163 4.771072 4.793981 4.816890 4.839799 4.862708 #>  [9,] 4.162568 4.182800 4.203032 4.223265 4.243497 4.263729 4.283961 4.304193 #> [10,] 4.112751 4.133041 4.153331 4.173621 4.193911 4.214201 4.234491 4.254781 #> [11,] 2.760392 2.775853 2.791314 2.806776 2.822237 2.837699 2.853160 2.868621 #> [12,] 2.324007 2.335952 2.347897 2.359842 2.371787 2.383732 2.395676 2.407621 #> [13,] 2.703872 2.718021 2.732171 2.746321 2.760471 2.774621 2.788771 2.802921 #> [14,] 2.005360 2.016025 2.026690 2.037355 2.048021 2.058686 2.069351 2.080017 #> [15,] 2.602010 2.616208 2.630406 2.644604 2.658801 2.672999 2.687197 2.701395 #> [16,] 2.900573 2.916230 2.931886 2.947543 2.963199 2.978856 2.994512 3.010168 #> [17,] 2.689880 2.704733 2.719586 2.734438 2.749291 2.764144 2.778997 2.793849 #> [18,] 2.300022 2.312810 2.325598 2.338385 2.351173 2.363961 2.376749 2.389537 #> [19,] 2.655913 2.669427 2.682941 2.696454 2.709968 2.723482 2.736996 2.750510 #> [20,] 2.442322 2.455305 2.468288 2.481272 2.494255 2.507238 2.520221 2.533205 #> [21,] 4.205314 4.231222 4.257129 4.283036 4.308944 4.334851 4.360758 4.386666 #> [22,] 5.101147 5.133879 5.166612 5.199345 5.232078 5.264811 5.297544 5.330277 #> [23,] 4.373529 4.400824 4.428120 4.455415 4.482711 4.510006 4.537302 4.564597 #> [24,] 4.166817 4.193454 4.220092 4.246730 4.273367 4.300005 4.326642 4.353280 #> [25,] 5.346765 5.379957 5.413150 5.446342 5.479535 5.512727 5.545920 5.579113 #> [26,] 5.199407 5.231555 5.263702 5.295849 5.327997 5.360144 5.392291 5.424439 #> [27,] 5.143817 5.176124 5.208430 5.240736 5.273042 5.305348 5.337654 5.369960 #> [28,] 5.144661 5.177253 5.209845 5.242437 5.275029 5.307621 5.340213 5.372805 #> [29,] 4.695490 4.725476 4.755462 4.785448 4.815433 4.845419 4.875405 4.905391 #> [30,] 5.246911 5.280429 5.313947 5.347466 5.380984 5.414502 5.448020 5.481538 #>         [,167]   [,168]   [,169]   [,170]   [,171]   [,172]   [,173]   [,174] #>  [1,] 4.706611 4.728754 4.750897 4.773041 4.795184 4.817328 4.839471 4.861614 #>  [2,] 5.160463 5.185515 5.210567 5.235619 5.260672 5.285724 5.310776 5.335828 #>  [3,] 4.795923 4.818517 4.841110 4.863703 4.886296 4.908889 4.931482 4.954075 #>  [4,] 4.779673 4.802871 4.826069 4.849267 4.872465 4.895663 4.918861 4.942059 #>  [5,] 4.536418 4.558342 4.580265 4.602189 4.624113 4.646037 4.667961 4.689885 #>  [6,] 5.453343 5.479800 5.506257 5.532714 5.559171 5.585629 5.612086 5.638543 #>  [7,] 5.551234 5.577808 5.604382 5.630956 5.657530 5.684104 5.710678 5.737252 #>  [8,] 4.885617 4.908526 4.931435 4.954344 4.977253 5.000162 5.023071 5.045981 #>  [9,] 4.324425 4.344657 4.364889 4.385121 4.405353 4.425585 4.445817 4.466049 #> [10,] 4.275071 4.295361 4.315651 4.335941 4.356231 4.376521 4.396811 4.417101 #> [11,] 2.884083 2.899544 2.915006 2.930467 2.945928 2.961390 2.976851 2.992313 #> [12,] 2.419566 2.431511 2.443456 2.455401 2.467345 2.479290 2.491235 2.503180 #> [13,] 2.817070 2.831220 2.845370 2.859520 2.873670 2.887820 2.901970 2.916119 #> [14,] 2.090682 2.101347 2.112013 2.122678 2.133343 2.144008 2.154674 2.165339 #> [15,] 2.715593 2.729791 2.743989 2.758186 2.772384 2.786582 2.800780 2.814978 #> [16,] 3.025825 3.041481 3.057138 3.072794 3.088451 3.104107 3.119764 3.135420 #> [17,] 2.808702 2.823555 2.838408 2.853260 2.868113 2.882966 2.897819 2.912671 #> [18,] 2.402324 2.415112 2.427900 2.440688 2.453476 2.466263 2.479051 2.491839 #> [19,] 2.764024 2.777538 2.791051 2.804565 2.818079 2.831593 2.845107 2.858621 #> [20,] 2.546188 2.559171 2.572154 2.585138 2.598121 2.611104 2.624087 2.637071 #> [21,] 4.412573 4.438480 4.464388 4.490295 4.516202 4.542110 4.568017 4.593924 #> [22,] 5.363010 5.395743 5.428475 5.461208 5.493941 5.526674 5.559407 5.592140 #> [23,] 4.591892 4.619188 4.646483 4.673779 4.701074 4.728369 4.755665 4.782960 #> [24,] 4.379918 4.406555 4.433193 4.459830 4.486468 4.513106 4.539743 4.566381 #> [25,] 5.612305 5.645498 5.678690 5.711883 5.745075 5.778268 5.811460 5.844653 #> [26,] 5.456586 5.488733 5.520881 5.553028 5.585175 5.617323 5.649470 5.681617 #> [27,] 5.402266 5.434572 5.466879 5.499185 5.531491 5.563797 5.596103 5.628409 #> [28,] 5.405397 5.437989 5.470581 5.503173 5.535765 5.568357 5.600949 5.633541 #> [29,] 4.935377 4.965363 4.995348 5.025334 5.055320 5.085306 5.115292 5.145278 #> [30,] 5.515056 5.548575 5.582093 5.615611 5.649129 5.682647 5.716165 5.749684 #>         [,175]   [,176]   [,177]   [,178]   [,179]   [,180]   [,181]   [,182] #>  [1,] 4.883758 4.905901 4.928045 4.950188 4.972331 4.994475 5.016618 5.038762 #>  [2,] 5.360881 5.385933 5.410985 5.436037 5.461090 5.486142 5.511194 5.536246 #>  [3,] 4.976668 4.999261 5.021854 5.044447 5.067040 5.089633 5.112226 5.134819 #>  [4,] 4.965256 4.988454 5.011652 5.034850 5.058048 5.081246 5.104444 5.127642 #>  [5,] 4.711808 4.733732 4.755656 4.777580 4.799504 4.821428 4.843352 4.865275 #>  [6,] 5.665000 5.691457 5.717915 5.744372 5.770829 5.797286 5.823743 5.850201 #>  [7,] 5.763826 5.790400 5.816974 5.843548 5.870121 5.896695 5.923269 5.949843 #>  [8,] 5.068890 5.091799 5.114708 5.137617 5.160526 5.183435 5.206344 5.229253 #>  [9,] 4.486281 4.506513 4.526745 4.546978 4.567210 4.587442 4.607674 4.627906 #> [10,] 4.437391 4.457681 4.477971 4.498261 4.518552 4.538842 4.559132 4.579422 #> [11,] 3.007774 3.023235 3.038697 3.054158 3.069620 3.085081 3.100542 3.116004 #> [12,] 2.515125 2.527070 2.539014 2.550959 2.562904 2.574849 2.586794 2.598739 #> [13,] 2.930269 2.944419 2.958569 2.972719 2.986869 3.001018 3.015168 3.029318 #> [14,] 2.176004 2.186670 2.197335 2.208000 2.218665 2.229331 2.239996 2.250661 #> [15,] 2.829176 2.843374 2.857572 2.871769 2.885967 2.900165 2.914363 2.928561 #> [16,] 3.151077 3.166733 3.182390 3.198046 3.213702 3.229359 3.245015 3.260672 #> [17,] 2.927524 2.942377 2.957230 2.972082 2.986935 3.001788 3.016641 3.031493 #> [18,] 2.504627 2.517415 2.530202 2.542990 2.555778 2.568566 2.581354 2.594142 #> [19,] 2.872135 2.885649 2.899162 2.912676 2.926190 2.939704 2.953218 2.966732 #> [20,] 2.650054 2.663037 2.676021 2.689004 2.701987 2.714970 2.727954 2.740937 #> [21,] 4.619832 4.645739 4.671646 4.697553 4.723461 4.749368 4.775275 4.801183 #> [22,] 5.624873 5.657606 5.690339 5.723071 5.755804 5.788537 5.821270 5.854003 #> [23,] 4.810256 4.837551 4.864846 4.892142 4.919437 4.946733 4.974028 5.001323 #> [24,] 4.593018 4.619656 4.646294 4.672931 4.699569 4.726206 4.752844 4.779482 #> [25,] 5.877845 5.911038 5.944231 5.977423 6.010616 6.043808 6.077001 6.110193 #> [26,] 5.713765 5.745912 5.778059 5.810207 5.842354 5.874501 5.906649 5.938796 #> [27,] 5.660715 5.693021 5.725328 5.757634 5.789940 5.822246 5.854552 5.886858 #> [28,] 5.666133 5.698725 5.731317 5.763909 5.796501 5.829093 5.861685 5.894277 #> [29,] 5.175263 5.205249 5.235235 5.265221 5.295207 5.325193 5.355178 5.385164 #> [30,] 5.783202 5.816720 5.850238 5.883756 5.917274 5.950793 5.984311 6.017829 #>         [,183]   [,184]   [,185]   [,186]   [,187]   [,188]   [,189]   [,190] #>  [1,] 5.060905 5.083049 5.105192 5.127335 5.149479 5.171622 5.193766 5.215909 #>  [2,] 5.561299 5.586351 5.611403 5.636455 5.661508 5.686560 5.711612 5.736664 #>  [3,] 5.157412 5.180005 5.202598 5.225191 5.247784 5.270377 5.292970 5.315563 #>  [4,] 5.150840 5.174038 5.197236 5.220434 5.243632 5.266830 5.290028 5.313225 #>  [5,] 4.887199 4.909123 4.931047 4.952971 4.974895 4.996818 5.018742 5.040666 #>  [6,] 5.876658 5.903115 5.929572 5.956029 5.982487 6.008944 6.035401 6.061858 #>  [7,] 5.976417 6.002991 6.029565 6.056139 6.082713 6.109287 6.135861 6.162435 #>  [8,] 5.252162 5.275071 5.297980 5.320889 5.343798 5.366707 5.389616 5.412526 #>  [9,] 4.648138 4.668370 4.688602 4.708834 4.729066 4.749298 4.769530 4.789762 #> [10,] 4.599712 4.620002 4.640292 4.660582 4.680872 4.701162 4.721452 4.741742 #> [11,] 3.131465 3.146926 3.162388 3.177849 3.193311 3.208772 3.224233 3.239695 #> [12,] 2.610683 2.622628 2.634573 2.646518 2.658463 2.670408 2.682353 2.694297 #> [13,] 3.043468 3.057618 3.071768 3.085918 3.100067 3.114217 3.128367 3.142517 #> [14,] 2.261327 2.271992 2.282657 2.293323 2.303988 2.314653 2.325318 2.335984 #> [15,] 2.942759 2.956957 2.971154 2.985352 2.999550 3.013748 3.027946 3.042144 #> [16,] 3.276328 3.291985 3.307641 3.323298 3.338954 3.354611 3.370267 3.385924 #> [17,] 3.046346 3.061199 3.076051 3.090904 3.105757 3.120610 3.135462 3.150315 #> [18,] 2.606929 2.619717 2.632505 2.645293 2.658081 2.670868 2.683656 2.696444 #> [19,] 2.980246 2.993759 3.007273 3.020787 3.034301 3.047815 3.061329 3.074843 #> [20,] 2.753920 2.766903 2.779887 2.792870 2.805853 2.818836 2.831820 2.844803 #> [21,] 4.827090 4.852997 4.878905 4.904812 4.930719 4.956627 4.982534 5.008441 #> [22,] 5.886736 5.919469 5.952202 5.984934 6.017667 6.050400 6.083133 6.115866 #> [23,] 5.028619 5.055914 5.083210 5.110505 5.137800 5.165096 5.192391 5.219687 #> [24,] 4.806119 4.832757 4.859394 4.886032 4.912670 4.939307 4.965945 4.992582 #> [25,] 6.143386 6.176578 6.209771 6.242963 6.276156 6.309349 6.342541 6.375734 #> [26,] 5.970943 6.003091 6.035238 6.067386 6.099533 6.131680 6.163828 6.195975 #> [27,] 5.919164 5.951470 5.983776 6.016083 6.048389 6.080695 6.113001 6.145307 #> [28,] 5.926869 5.959461 5.992053 6.024645 6.057237 6.089829 6.122421 6.155013 #> [29,] 5.415150 5.445136 5.475122 5.505108 5.535093 5.565079 5.595065 5.625051 #> [30,] 6.051347 6.084865 6.118383 6.151902 6.185420 6.218938 6.252456 6.285974 #>         [,191]   [,192]   [,193]   [,194]   [,195]   [,196]   [,197]   [,198] #>  [1,] 5.238052 5.260196 5.282339 5.304483 5.326626 5.348769 5.370913 5.393056 #>  [2,] 5.761717 5.786769 5.811821 5.836874 5.861926 5.886978 5.912030 5.937083 #>  [3,] 5.338157 5.360750 5.383343 5.405936 5.428529 5.451122 5.473715 5.496308 #>  [4,] 5.336423 5.359621 5.382819 5.406017 5.429215 5.452413 5.475611 5.498809 #>  [5,] 5.062590 5.084514 5.106438 5.128362 5.150285 5.172209 5.194133 5.216057 #>  [6,] 6.088315 6.114773 6.141230 6.167687 6.194144 6.220601 6.247059 6.273516 #>  [7,] 6.189009 6.215583 6.242157 6.268731 6.295305 6.321879 6.348453 6.375027 #>  [8,] 5.435435 5.458344 5.481253 5.504162 5.527071 5.549980 5.572889 5.595798 #>  [9,] 4.809994 4.830226 4.850458 4.870691 4.890923 4.911155 4.931387 4.951619 #> [10,] 4.762032 4.782322 4.802612 4.822902 4.843192 4.863482 4.883772 4.904062 #> [11,] 3.255156 3.270618 3.286079 3.301540 3.317002 3.332463 3.347925 3.363386 #> [12,] 2.706242 2.718187 2.730132 2.742077 2.754022 2.765966 2.777911 2.789856 #> [13,] 3.156667 3.170817 3.184967 3.199116 3.213266 3.227416 3.241566 3.255716 #> [14,] 2.346649 2.357314 2.367980 2.378645 2.389310 2.399975 2.410641 2.421306 #> [15,] 3.056342 3.070539 3.084737 3.098935 3.113133 3.127331 3.141529 3.155727 #> [16,] 3.401580 3.417237 3.432893 3.448549 3.464206 3.479862 3.495519 3.511175 #> [17,] 3.165168 3.180021 3.194873 3.209726 3.224579 3.239432 3.254284 3.269137 #> [18,] 2.709232 2.722020 2.734807 2.747595 2.760383 2.773171 2.785959 2.798746 #> [19,] 3.088356 3.101870 3.115384 3.128898 3.142412 3.155926 3.169440 3.182954 #> [20,] 2.857786 2.870770 2.883753 2.896736 2.909719 2.922703 2.935686 2.948669 #> [21,] 5.034349 5.060256 5.086163 5.112071 5.137978 5.163885 5.189793 5.215700 #> [22,] 6.148599 6.181332 6.214065 6.246798 6.279530 6.312263 6.344996 6.377729 #> [23,] 5.246982 5.274278 5.301573 5.328868 5.356164 5.383459 5.410755 5.438050 #> [24,] 5.019220 5.045858 5.072495 5.099133 5.125770 5.152408 5.179046 5.205683 #> [25,] 6.408926 6.442119 6.475311 6.508504 6.541696 6.574889 6.608081 6.641274 #> [26,] 6.228122 6.260270 6.292417 6.324564 6.356712 6.388859 6.421006 6.453154 #> [27,] 6.177613 6.209919 6.242225 6.274532 6.306838 6.339144 6.371450 6.403756 #> [28,] 6.187605 6.220197 6.252789 6.285381 6.317973 6.350565 6.383157 6.415749 #> [29,] 5.655037 5.685023 5.715008 5.744994 5.774980 5.804966 5.834952 5.864938 #> [30,] 6.319492 6.353010 6.386529 6.420047 6.453565 6.487083 6.520601 6.554119 #>         [,199]   [,200] #>  [1,] 5.415200 5.437343 #>  [2,] 5.962135 5.987187 #>  [3,] 5.518901 5.541494 #>  [4,] 5.522007 5.545205 #>  [5,] 5.237981 5.259905 #>  [6,] 6.299973 6.326430 #>  [7,] 6.401601 6.428174 #>  [8,] 5.618707 5.641616 #>  [9,] 4.971851 4.992083 #> [10,] 4.924353 4.944643 #> [11,] 3.378847 3.394309 #> [12,] 2.801801 2.813746 #> [13,] 3.269866 3.284016 #> [14,] 2.431971 2.442637 #> [15,] 3.169924 3.184122 #> [16,] 3.526832 3.542488 #> [17,] 3.283990 3.298843 #> [18,] 2.811534 2.824322 #> [19,] 3.196467 3.209981 #> [20,] 2.961652 2.974636 #> [21,] 5.241607 5.267515 #> [22,] 6.410462 6.443195 #> [23,] 5.465345 5.492641 #> [24,] 5.232321 5.258958 #> [25,] 6.674467 6.707659 #> [26,] 6.485301 6.517448 #> [27,] 6.436062 6.468368 #> [28,] 6.448341 6.480932 #> [29,] 5.894923 5.924909 #> [30,] 6.587638 6.621156 #>  #> $n_clusters #> [1] 2 #>  #> $memberships #>  [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 #>  #> $distances_to_center #>  [1] 1.435690e-07 8.772803e-06 3.146653e-06 1.102877e-05 2.000723e-06 #>  [6] 4.401335e-06 1.163654e-06 1.566382e-05 1.581490e-06 5.370269e-06 #> [11] 3.493894e-06 1.493107e-05 3.060315e-07 2.249079e-06 9.439335e-08 #> [16] 6.040630e-07 1.015906e-05 3.737756e-07 1.025968e-05 3.212466e-06 #> [21] 2.138381e-05 9.563699e-05 2.243895e-06 1.402764e-06 1.470732e-05 #> [26] 4.079484e-05 2.272736e-05 2.521653e-05 1.602216e-06 5.209759e-06 #>  #> $silhouettes #>  [1] 0.9998670 0.9996938 0.9998243 0.9993937 0.9998277 0.9997924 0.9998357 #>  [8] 0.9995409 0.9999025 0.9998513 0.9999301 0.9999018 0.9999629 0.9999643 #> [15] 0.9999654 0.9999516 0.9998826 0.9999729 0.9999020 0.9999541 0.9998198 #> [22] 0.9994794 0.9998915 0.9998993 0.9998286 0.9997110 0.9997933 0.9997820 #> [29] 0.9998919 0.9998688 #>  #> $amplitude_variation #> [1] 1.364288e-08 #>  #> $total_variation #> [1] 0.6714711 #>  #> $n_iterations #> [1] 2 #>  #> $call_name #> [1] \"fdakmeans\" #>  #> $call_args #> $call_args$x #> simulated30$x #>  #> $call_args$y #> simulated30$y #>  #> $call_args$n_clusters #> [1] 2 #>  #> $call_args$seeds #> [1]  1 21 #>  #> $call_args$seeding_strategy #> [1] \"kmeans++\" #>  #> $call_args$warping_class #> [1] \"affine\" #>  #> $call_args$centroid_type #> [1] \"mean\" #>  #> $call_args$metric #> [1] \"pearson\" #>  #> $call_args$cluster_on_phase #> [1] FALSE #>  #> $call_args$use_verbose #> [1] TRUE #>  #> $call_args$warping_options #> c(0.15, 0.15) #>  #> $call_args$maximum_number_of_iterations #> [1] 100 #>  #> $call_args$number_of_threads #> [1] 1 #>  #> $call_args$parallel_method #> [1] 0 #>  #> $call_args$distance_relative_tolerance #> [1] 0.001 #>  #> $call_args$use_fence #> [1] FALSE #>  #> $call_args$check_total_dissimilarity #> [1] TRUE #>  #> $call_args$compute_overall_center #> [1] FALSE #>  #> $call_args$add_silhouettes #> [1] TRUE #>  #>  #> attr(,\"class\") #> [1] \"caps\" \"list\" is_caps(sim30_caps) #> [1] TRUE"},{"path":"/reference/compare_caps.html","id":null,"dir":"Reference","previous_headings":"","what":"Generates results of multiple clustering strategies — compare_caps","title":"Generates results of multiple clustering strategies — compare_caps","text":"function searches clusters input data set using different strategies generates object class mcaps stores multiple objects class caps. helper function facilitate comparison clustering methods choice optimal one.","code":""},{"path":"/reference/compare_caps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generates results of multiple clustering strategies — compare_caps","text":"","code":"compare_caps(   x,   y,   n_clusters = 1:5,   metric = c(\"l2\", \"pearson\"),   clustering_method = c(\"kmeans\", \"hclust-complete\", \"hclust-average\", \"hclust-single\",     \"dbscan\"),   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   centroid_type = c(\"mean\", \"medoid\", \"median\", \"lowess\", \"poly\"),   cluster_on_phase = FALSE )"},{"path":"/reference/compare_caps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generates results of multiple clustering strategies — compare_caps","text":"x numeric vector length \\(M\\) numeric matrix shape \\(N \\times M\\) object class funData::funData. numeric vector matrix, specifies grid(s) size \\(M\\) \\(N\\) curves observed. object class funData::funData, contains whole functional data set y argument used. y Either numeric matrix shape \\(N \\times M\\) numeric array shape \\(N \\times L \\times M\\) object class fda::fd. numeric matrix array, specifies \\(N\\)-sample \\(L\\)-dimensional curves observed grids size \\(M\\). object class fda::fd, contains necessary information functional data set able evaluate user-defined grids. n_clusters integer vector specifying set clustering partitions create. Defaults 1:5. metric string specifying metric used compare curves. Choices \"l2\" \"pearson\". Defaults \"l2\". Used warping_class != \"srsf\". boundary-preserving warping class, L2 distance SRSFs original curves used. clustering_method character vector specifying one clustering methods fit. Choices \"kmeans\", \"hclust-complete\", \"hclust-average\", \"hclust-single\" \"dbscan\". Defaults . warping_class character vector specifying one classes warping functions use curve alignment. Choices \"affine\", \"dilation\", \"none\", \"shift\" \"srsf\". Defaults . centroid_type character vector specifying one ways compute centroids. Choices \"mean\", \"medoid\", \"median\", \"lowess\" \"poly\". Defaults . cluster_on_phase boolean specifying whether clustering based phase variation amplitude variation. Defaults FALSE implies amplitude variation.","code":""},{"path":"/reference/compare_caps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generates results of multiple clustering strategies — compare_caps","text":"object class mcaps tibble::tibble storing objects class caps correspondence combination possible choices input arguments.","code":""},{"path":"/reference/compare_caps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generates results of multiple clustering strategies — compare_caps","text":"","code":"#---------------------------------- # Compare k-means results with k = 1, 2, 3, 4, 5 using mean centroid and # various warping classes. if (FALSE) { sim30_mcaps <- compare_caps(   x = simulated30_sub$x,   y = simulated30_sub$y,   warping_class = c(\"none\", \"shift\", \"dilation\", \"affine\"),   clustering_method = \"kmeans\",   centroid_type = \"mean\" ) }  #---------------------------------- # Then visualize the results # Either with ggplot2 via ggplot2::autoplot(sim30_mcaps) # or using graphics::plot() # You can visualize the WSS values: plot(sim30_mcaps, validation_criterion = \"wss\", what = \"mean\")  plot(sim30_mcaps, validation_criterion = \"wss\", what = \"distribution\")  # Or the average silhouette values: plot(sim30_mcaps, validation_criterion = \"silhouette\", what = \"mean\")  plot(sim30_mcaps, validation_criterion = \"silhouette\", what = \"distribution\")"},{"path":"/reference/diagnostic_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","title":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","text":"function plots values distance center silhouette observation. Observations ordered within cluster decreasing value silhouette.","code":""},{"path":"/reference/diagnostic_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","text":"","code":"diagnostic_plot(x)"},{"path":"/reference/diagnostic_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","text":"x object class caps.","code":""},{"path":"/reference/diagnostic_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","text":"object class ggplot2::ggplot.","code":""},{"path":"/reference/diagnostic_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Diagnostic plot for the result of a clustering strategy stored in a caps\nobject — diagnostic_plot","text":"","code":"diagnostic_plot(sim30_caps)"},{"path":"/reference/fdacluster-package.html","id":null,"dir":"Reference","previous_headings":"","what":"fdacluster: Joint Clustering and Alignment of Functional Data — fdacluster-package","title":"fdacluster: Joint Clustering and Alignment of Functional Data — fdacluster-package","text":"Implementations k-means, hierarchical agglomerative DBSCAN clustering methods functional data allows jointly aligning clustering curves. supports functional data defined one-dimensional domains possibly evaluating multivariate codomains. supports functional data defined arrays also via 'fd' 'funData' classes functional data defined 'fda' 'funData' packages respectively. currently supports shift, dilation affine warping functions functional data defined real line uses SRSF framework handle boundary-preserving warping functional data defined specific interval. Main reference k-means algorithm: Sangalli L.M., Secchi P., Vantini S., Vitelli V. (2010) \"k-mean alignment curve clustering\" doi:10.1016/j.csda.2009.12.008 . Main reference SRSF framework: Tucker, J. D., Wu, W., & Srivastava, . (2013) \"Generative models functional data using phase amplitude separation\" doi:10.1016/j.csda.2012.12.001 .","code":""},{"path":"/reference/fdacluster-package.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"fdacluster: Joint Clustering and Alignment of Functional Data — fdacluster-package","text":"Arthur, D., S. Vassilvitskii. 2007. “K-Means++ Advantages Careful Seeding.” Proceedings Eighteenth Annual ACM-SIAM Symposium Discrete Algorithms, 1027–35. Marron, J. S., J. O. Ramsay, L. M. Sangalli, . Srivastava. 2014. “Statistics Time Warpings Phase Variations.” Marron, J. S., J. O. Ramsay, L. M. Sangalli, . Srivastava. 2015. “Functional Data Analysis Amplitude Phase Variation.” Statistical Science, 468–84. Ramsay, J., B. W. Silverman. 2005. Functional Data Analysis. Springer Series Statistics. Springer. Sangalli, L. M., P. Secchi, S. Vantini, V. Vitelli. 2010. “K-Mean Alignment Curve Clustering.” Computational Statistics & Data Analysis 54 (5): 1219–33. Tucker, J. D., W. Wu, . Srivastava. 2013. “Generative Models Functional Data Using Phase Amplitude Separation.” Computational Statistics & Data Analysis 61: 50–66. Vantini, S. 2012. “Definition Phase Amplitude Variability Functional Data Analysis.” Test 21 (4): 676–96. https://doi.org/10.1007/s11749-011-0268-9.","code":""},{"path":[]},{"path":"/reference/fdacluster-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"fdacluster: Joint Clustering and Alignment of Functional Data — fdacluster-package","text":"Maintainer: Aymeric Stamm aymeric.stamm@cnrs.fr (ORCID) contributors: Laura Sangalli laura.sangalli@polimi.[contributor] Piercesare Secchi piercesare.secchi@polimi.[contributor] Simone Vantini simone.vantini@polimi.[contributor] Valeria Vitelli valeria.vitelli@medisin.uio.[contributor] Alessandro Zito zito.ales@gmail.com [contributor]","code":""},{"path":"/reference/fdadbscan.html","id":null,"dir":"Reference","previous_headings":"","what":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","title":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","text":"function extends DBSCAN functional data. includes possibility separate amplitude phase information.","code":""},{"path":"/reference/fdadbscan.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","text":"","code":"fdadbscan(   x,   y,   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   centroid_type = \"mean\",   metric = c(\"l2\", \"pearson\"),   cluster_on_phase = FALSE,   use_verbose = TRUE,   warping_options = c(0.15, 0.15),   maximum_number_of_iterations = 100L,   number_of_threads = 1L,   parallel_method = 0L,   distance_relative_tolerance = 0.001,   use_fence = FALSE,   check_total_dissimilarity = TRUE,   compute_overall_center = FALSE )"},{"path":"/reference/fdadbscan.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","text":"x numeric vector length \\(M\\) numeric matrix shape \\(N \\times M\\) object class funData::funData. numeric vector matrix, specifies grid(s) size \\(M\\) \\(N\\) curves observed. object class funData::funData, contains whole functional data set y argument used. y Either numeric matrix shape \\(N \\times M\\) numeric array shape \\(N \\times L \\times M\\) object class fda::fd. numeric matrix array, specifies \\(N\\)-sample \\(L\\)-dimensional curves observed grids size \\(M\\). object class fda::fd, contains necessary information functional data set able evaluate user-defined grids. warping_class string specifying warping class Choices \"affine\", \"dilation\", \"none\", \"shift\" \"srsf\". Defaults \"affine\". SRSF class class boundary-preserving. centroid_type string specifying type centroid compute. Choices \"mean\", \"median\" \"medoid\", \"lowess\" \"poly\". Defaults \"mean\". LOWESS appproximation chosen, user can append integer 0 100 \"lowess20\". number used smoother span. gives proportion points plot influence smooth value. Larger values give smoothness. default value 10%. polynomial approximation chosen, user can append positive integer \"poly3\". number used degree polynomial model. default value 4L. metric string specifying metric used compare curves. Choices \"l2\" \"pearson\". Defaults \"l2\". Used warping_class != \"srsf\". boundary-preserving warping class, L2 distance SRSFs original curves used. cluster_on_phase boolean specifying whether clustering based phase variation amplitude variation. Defaults FALSE implies amplitude variation. use_verbose boolean specifying whether algorithm output details steps console. Defaults TRUE. warping_options numeric vector supplied helper chosen warping_class decide warping parameter bounds. used warping_class != \"srsf\". maximum_number_of_iterations integer specifying maximum number iterations algorithm stops convergence criterion met. Defaults 100L. number_of_threads integer value specifying number threads used parallelization. Defaults 1L. used warping_class != \"srsf\". parallel_method integer value specifying type desired parallelization template computation, 0L, templates computed parallel. 1L, parallelization occurs within single template computation (medoid method now). Defaults 0L. used warping_class != \"srsf\". distance_relative_tolerance numeric value specifying relative tolerance distance update two iterations. observations sufficiently improved sense, algorithm stops. Defaults 1e-3. used warping_class != \"srsf\". use_fence boolean specifying whether fence algorithm used robustify algorithm outliers. Defaults FALSE. used warping_class != \"srsf\". check_total_dissimilarity boolean specifying whether additional stopping criterion based improvement total dissimilarity used. Defaults TRUE. used warping_class != \"srsf\". compute_overall_center boolean specifying whether overall center also computed. Defaults FALSE. used warping_class != \"srsf\".","code":""},{"path":"/reference/fdadbscan.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","text":"object class caps.","code":""},{"path":"/reference/fdadbscan.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Performs density-based clustering for functional data with amplitude and\nphase separation — fdadbscan","text":"","code":"#---------------------------------- # Extracts 15 out of the 30 simulated curves in `simulated30_sub` data set idx <- c(1:5, 11:15) x <- simulated30_sub$x[idx, ] y <- simulated30_sub$y[idx, , ]  #---------------------------------- # Runs an HAC with affine alignment, searching for 2 clusters out <- fdadbscan(   x = x,   y = y,   warping_class = \"affine\" ) #> ℹ Computing the distance matrix... #> ℹ Aligning all curves with respect to their centroid... #> ℹ Consolidating output...  #---------------------------------- # Then visualize the results # Either with ggplot2 via ggplot2::autoplot(out) # or using graphics::plot() # You can visualize the original and aligned curves with: plot(out, type = \"amplitude\")  # Or the estimated warping functions with: plot(out, type = \"phase\")"},{"path":"/reference/fdadist.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","title":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","text":"function computes matrix pairwise distances curves functional data sample. can achieved without phase amplitude separation, can done using variety warping classes.","code":""},{"path":"/reference/fdadist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","text":"","code":"fdadist(   x,   y = NULL,   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   metric = c(\"l2\", \"pearson\"),   cluster_on_phase = FALSE,   labels = NULL )"},{"path":"/reference/fdadist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","text":"x numeric vector length \\(M\\) numeric matrix shape \\(N \\times M\\) object class funData::funData. numeric vector matrix, specifies grid(s) size \\(M\\) \\(N\\) curves observed. object class funData::funData, contains whole functional data set y argument used. y Either numeric matrix shape \\(N \\times M\\) numeric array shape \\(N \\times L \\times M\\) object class fda::fd. numeric matrix array, specifies \\(N\\)-sample \\(L\\)-dimensional curves observed grids size \\(M\\). object class fda::fd, contains necessary information functional data set able evaluate user-defined grids. warping_class string specifying warping class Choices \"affine\", \"dilation\", \"none\", \"shift\" \"srsf\". Defaults \"affine\". SRSF class class boundary-preserving. metric string specifying metric used compare curves. Choices \"l2\" \"pearson\". Defaults \"l2\". Used warping_class != \"srsf\". boundary-preserving warping class, L2 distance SRSFs original curves used. cluster_on_phase boolean specifying whether clustering based phase variation amplitude variation. Defaults FALSE implies amplitude variation. labels character vector specifying curve labels. Defaults NULL uses sequential numbers labels.","code":""},{"path":"/reference/fdadist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","text":"stats::dist object storing distance matrix input curves using metric specified argument metric warping class specified argument warping_class.","code":""},{"path":"/reference/fdadist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Computes the distance matrix for functional data with amplitude and phase\nseparation — fdadist","text":"","code":"idx <- c(1:5, 11:15, 21:25) D <- fdadist(simulated30_sub$x[idx, ], simulated30_sub$y[idx, , ])"},{"path":"/reference/fdahclust.html","id":null,"dir":"Reference","previous_headings":"","what":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"function extends hierarchical agglomerative clustering functional data. includes possibility separate amplitude phase information.","code":""},{"path":"/reference/fdahclust.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"","code":"fdahclust(   x,   y = NULL,   n_clusters = 1L,   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   centroid_type = \"mean\",   metric = c(\"l2\", \"pearson\"),   linkage_criterion = c(\"complete\", \"average\", \"single\", \"ward.D2\"),   cluster_on_phase = FALSE,   use_verbose = TRUE,   warping_options = c(0.15, 0.15),   maximum_number_of_iterations = 100L,   number_of_threads = 1L,   parallel_method = 0L,   distance_relative_tolerance = 0.001,   use_fence = FALSE,   check_total_dissimilarity = TRUE,   compute_overall_center = FALSE )"},{"path":"/reference/fdahclust.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"x numeric vector length \\(M\\) numeric matrix shape \\(N \\times M\\) object class funData::funData. numeric vector matrix, specifies grid(s) size \\(M\\) \\(N\\) curves observed. object class funData::funData, contains whole functional data set y argument used. y Either numeric matrix shape \\(N \\times M\\) numeric array shape \\(N \\times L \\times M\\) object class fda::fd. numeric matrix array, specifies \\(N\\)-sample \\(L\\)-dimensional curves observed grids size \\(M\\). object class fda::fd, contains necessary information functional data set able evaluate user-defined grids. n_clusters integer value specifying number clusters. Defaults 1L. warping_class string specifying warping class Choices \"affine\", \"dilation\", \"none\", \"shift\" \"srsf\". Defaults \"affine\". SRSF class class boundary-preserving. centroid_type string specifying type centroid compute. Choices \"mean\", \"median\" \"medoid\", \"lowess\" \"poly\". Defaults \"mean\". LOWESS appproximation chosen, user can append integer 0 100 \"lowess20\". number used smoother span. gives proportion points plot influence smooth value. Larger values give smoothness. default value 10%. polynomial approximation chosen, user can append positive integer \"poly3\". number used degree polynomial model. default value 4L. metric string specifying metric used compare curves. Choices \"l2\" \"pearson\". Defaults \"l2\". Used warping_class != \"srsf\". boundary-preserving warping class, L2 distance SRSFs original curves used. linkage_criterion string specifying linkage criterion used compute distances sets curves. Choices \"complete\" complete linkage, \"average\" average linkage \"single\" single linkage. See stats::hclust() details. Defaults \"complete\". cluster_on_phase boolean specifying whether clustering based phase variation amplitude variation. Defaults FALSE implies amplitude variation. use_verbose boolean specifying whether algorithm output details steps console. Defaults TRUE. warping_options numeric vector supplied helper chosen warping_class decide warping parameter bounds. used warping_class != \"srsf\". maximum_number_of_iterations integer specifying maximum number iterations algorithm stops convergence criterion met. Defaults 100L. number_of_threads integer value specifying number threads used parallelization. Defaults 1L. used warping_class != \"srsf\". parallel_method integer value specifying type desired parallelization template computation, 0L, templates computed parallel. 1L, parallelization occurs within single template computation (medoid method now). Defaults 0L. used warping_class != \"srsf\". distance_relative_tolerance numeric value specifying relative tolerance distance update two iterations. observations sufficiently improved sense, algorithm stops. Defaults 1e-3. used warping_class != \"srsf\". use_fence boolean specifying whether fence algorithm used robustify algorithm outliers. Defaults FALSE. used warping_class != \"srsf\". check_total_dissimilarity boolean specifying whether additional stopping criterion based improvement total dissimilarity used. Defaults TRUE. used warping_class != \"srsf\". compute_overall_center boolean specifying whether overall center also computed. Defaults FALSE. used warping_class != \"srsf\".","code":""},{"path":"/reference/fdahclust.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"object class caps.","code":""},{"path":"/reference/fdahclust.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"number clusters required input , functional data, hierarchical clustering performed, curves within clusters need aligned corresponding centroid.","code":""},{"path":"/reference/fdahclust.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Performs hierarchical clustering for functional data with amplitude and phase\nseparation — fdahclust","text":"","code":"#---------------------------------- # Extracts 15 out of the 30 simulated curves in `simulated30_sub` data set idx <- c(1:5, 11:15, 21:25) x <- simulated30_sub$x[idx, ] y <- simulated30_sub$y[idx, , ]  #---------------------------------- # Runs an HAC with affine alignment, searching for 2 clusters out <- fdahclust(   x = x,   y = y,   n_clusters = 2,   warping_class = \"affine\" ) #> ℹ Computing the distance matrix... #> ℹ Calculating the tree... #> ℹ Aligning all curves with respect to their centroid... #> ℹ Consolidating output...  #---------------------------------- # Then visualize the results # Either with ggplot2 via ggplot2::autoplot(out) # or using graphics::plot() # You can visualize the original and aligned curves with: plot(out, type = \"amplitude\")  # Or the estimated warping functions with: plot(out, type = \"phase\")"},{"path":"/reference/fdakmeans.html","id":null,"dir":"Reference","previous_headings":"","what":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","title":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","text":"function provides implementations k-means clustering algorithm functional data, possible joint amplitude phase separation. number warping class implemented achieve separation.","code":""},{"path":"/reference/fdakmeans.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","text":"","code":"fdakmeans(   x,   y = NULL,   n_clusters = 1L,   seeds = NULL,   seeding_strategy = c(\"kmeans++\", \"exhaustive-kmeans++\", \"exhaustive\", \"hclust\"),   warping_class = c(\"affine\", \"dilation\", \"none\", \"shift\", \"srsf\"),   centroid_type = \"mean\",   metric = c(\"l2\", \"pearson\"),   cluster_on_phase = FALSE,   use_verbose = TRUE,   warping_options = c(0.15, 0.15),   maximum_number_of_iterations = 100L,   number_of_threads = 1L,   parallel_method = 0L,   distance_relative_tolerance = 0.001,   use_fence = FALSE,   check_total_dissimilarity = TRUE,   compute_overall_center = FALSE,   add_silhouettes = TRUE )"},{"path":"/reference/fdakmeans.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","text":"x numeric vector length \\(M\\) numeric matrix shape \\(N \\times M\\) object class funData::funData. numeric vector matrix, specifies grid(s) size \\(M\\) \\(N\\) curves observed. object class funData::funData, contains whole functional data set y argument used. y Either numeric matrix shape \\(N \\times M\\) numeric array shape \\(N \\times L \\times M\\) object class fda::fd. numeric matrix array, specifies \\(N\\)-sample \\(L\\)-dimensional curves observed grids size \\(M\\). object class fda::fd, contains necessary information functional data set able evaluate user-defined grids. n_clusters integer value specifying number clusters. Defaults 1L. seeds integer value vector specifying indices initial centroids. integer vector, interpreted indices intial centroids therefore length n_clusters. integer value, interpreted index first initial centroid subsequent centroids chosen according k-means++ strategy. can NULL case argument seeding_strategy used automatically provide suitable indices. Defaults NULL. seeding_strategy character string specifying strategy choosing initial centroids case argument seeds set NULL. Choices \"kmeans++\", \"exhaustive-kmeans++\" performs exhaustive search choice first centroid, \"exhaustive\" tries combinations initial centroids \"hclust\" first performs hierarchical clustering using Ward's linkage criterion identify initial centroids. Defaults \"kmeans++\", fastest strategy. warping_class string specifying warping class Choices \"affine\", \"dilation\", \"none\", \"shift\" \"srsf\". Defaults \"affine\". SRSF class class boundary-preserving. centroid_type string specifying type centroid compute. Choices \"mean\", \"median\" \"medoid\", \"lowess\" \"poly\". Defaults \"mean\". LOWESS appproximation chosen, user can append integer 0 100 \"lowess20\". number used smoother span. gives proportion points plot influence smooth value. Larger values give smoothness. default value 10%. polynomial approximation chosen, user can append positive integer \"poly3\". number used degree polynomial model. default value 4L. metric string specifying metric used compare curves. Choices \"l2\" \"pearson\". Defaults \"l2\". Used warping_class != \"srsf\". boundary-preserving warping class, L2 distance SRSFs original curves used. cluster_on_phase boolean specifying whether clustering based phase variation amplitude variation. Defaults FALSE implies amplitude variation. use_verbose boolean specifying whether algorithm output details steps console. Defaults TRUE. warping_options numeric vector supplied helper chosen warping_class decide warping parameter bounds. used warping_class != \"srsf\". maximum_number_of_iterations integer specifying maximum number iterations algorithm stops convergence criterion met. Defaults 100L. number_of_threads integer value specifying number threads used parallelization. Defaults 1L. used warping_class != \"srsf\". parallel_method integer value specifying type desired parallelization template computation, 0L, templates computed parallel. 1L, parallelization occurs within single template computation (medoid method now). Defaults 0L. used warping_class != \"srsf\". distance_relative_tolerance numeric value specifying relative tolerance distance update two iterations. observations sufficiently improved sense, algorithm stops. Defaults 1e-3. used warping_class != \"srsf\". use_fence boolean specifying whether fence algorithm used robustify algorithm outliers. Defaults FALSE. used warping_class != \"srsf\". check_total_dissimilarity boolean specifying whether additional stopping criterion based improvement total dissimilarity used. Defaults TRUE. used warping_class != \"srsf\". compute_overall_center boolean specifying whether overall center also computed. Defaults FALSE. used warping_class != \"srsf\". add_silhouettes boolean specifying whether silhouette values computed observation internal validation clustering structure. Defaults TRUE.","code":""},{"path":"/reference/fdakmeans.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","text":"object class caps.","code":""},{"path":"/reference/fdakmeans.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Performs k-means clustering for functional data with amplitude and phase\nseparation — fdakmeans","text":"","code":"#---------------------------------- # Extracts 15 out of the 30 simulated curves in `simulated30_sub` data set idx <- c(1:5, 11:15, 21:25) x <- simulated30_sub$x[idx, ] y <- simulated30_sub$y[idx, , ]  #---------------------------------- # Runs a k-means clustering with affine alignment, searching for 2 clusters out <- fdakmeans(   x = x,   y = y,   n_clusters = 2,   warping_class = \"affine\" ) #> ℹ Computing initial centroids using kmeans++ strategy... #> Information about the data set: #>  - Number of observations: 15 #>  - Number of dimensions: 1 #>  - Number of points: 30 #>  #> Information about cluster initialization: #>  - Number of clusters: 2 #>  - Initial seeds for cluster centers:         14         2 #>  #> Information about the methods used within the algorithm: #>  - Warping method: affine #>  - Center method: mean #>  - Dissimilarity method: l2 #>  - Optimization method: bobyqa #>  #> Information about warping parameter bounds: #>  - Warping options:    0.1500   0.1500 #>  #> Information about convergence criteria: #>  - Maximum number of iterations: 100 #>  - Distance relative tolerance: 0.001 #>  #> Information about parallelization setup: #>  - Number of threads: 1 #>  - Parallel method: 0 #>  #> Other information: #>  - Use fence to robustify: 0 #>  - Check total dissimilarity: 1 #>  - Compute overall center: 0 #>  #> Running k-centroid algorithm: #>  - Iteration #1 #>    * Size of cluster #0: 5 #>    * Size of cluster #1: 10 #>  - Iteration #2 #>    * Size of cluster #0: 5 #>    * Size of cluster #1: 10 #>  #> Active stopping criteria: #>  - Memberships did not change.  #---------------------------------- # Then visualize the results # Either with ggplot2 via ggplot2::autoplot(out) # or using graphics::plot() # You can visualize the original and aligned curves with: plot(out, type = \"amplitude\")  # Or the estimated warping functions with: plot(out, type = \"phase\")"},{"path":"/reference/lp.html","id":null,"dir":"Reference","previous_headings":"","what":"Linear and integer programming — lp","title":"Linear and integer programming — lp","text":"Interface lp_solve linear/integer programming system.","code":""},{"path":"/reference/lp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Linear and integer programming — lp","text":"","code":"lp(   direction = \"min\",   objective.in,   const.mat,   const.dir,   const.rhs,   transpose.constraints = TRUE,   int.vec,   presolve = 0,   compute.sens = 0,   binary.vec,   all.int = FALSE,   all.bin = FALSE,   scale = 196,   dense.const,   num.bin.solns = 1,   use.rw = FALSE,   timeout = 0L )"},{"path":"/reference/lp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Linear and integer programming — lp","text":"direction Character string giving direction optimization: \"min\" (default) \"max.\" objective.Numeric vector coefficients objective function const.mat Matrix numeric constraint coefficients, one row  per constraint, one column per variable (unless transpose.constraints =  FALSE; see ). const.dir Vector character strings giving direction  constraint: value one \"<,\" \"<=,\" \"=,\" \"==,\" \">,\" \">=\". (pair two values identical.) const.rhs Vector numeric values right-hand sides  constraints. transpose.constraints default constraint occupies row  const.mat, matrix needs transposed passed  optimizing code.  large constraint matrices may wiser  construct constraints matrix column--column. case set  transpose.constraints FALSE. int.vec Numeric vector giving indices variables  required integer. length vector therefore  number integer variables. presolve Numeric: presolve? Default 0 (); non-zero value means \"yes.\" Currently ignored. compute.sens Numeric: compute sensitivity? Default 0 (); non-zero value means \"yes.\" binary.vec Numeric vector like int.vec giving indices variables  required binary. .int Logical: variables integer? Default: FALSE. .bin Logical: variables binary? Default: FALSE. scale Integer: value lpSolve scaling. Details can found lpSolve documentation. Set 0 scaling. Default: 196 dense.const Three column dense constraint array. ignored const.mat supplied. Otherwise columns constraint number, column number, value; one row non-zero entry constraint matrix. num.bin.solns Integer: .bin=TRUE, user can request num.bin.solns optimal solutions returned. use.rw Logical: TRUE num.bin.solns > 1, write lp file read back solution first. just defeat bug somewhere. Although default FALSE, recommend set TRUE need num.bin.solns > 1, bug found. timeout Integer: timeout variable seconds, defaults 0L means limit set.","code":""},{"path":"/reference/lp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Linear and integer programming — lp","text":"lpSolve::lp.object object.","code":""},{"path":"/reference/lp.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Linear and integer programming — lp","text":"function calls lp_solve 5.5 solver. system many options supported . current version maintained https://lpsolve.sourceforge.net/5.5/. Note every variable assumed >= 0!","code":""},{"path":"/reference/plot.caps.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots the result of a clustering strategy stored in a caps object — plot.caps","title":"Plots the result of a clustering strategy stored in a caps object — plot.caps","text":"function creates visualization result k-mean alignment algorithm without returning plot data object. user can choose visualize either amplitude information data case original aligned curves shown phase information data case estimated warping functions shown.","code":""},{"path":"/reference/plot.caps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots the result of a clustering strategy stored in a caps object — plot.caps","text":"","code":"# S3 method for caps plot(x, type = c(\"amplitude\", \"phase\"), ...)"},{"path":"/reference/plot.caps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots the result of a clustering strategy stored in a caps object — plot.caps","text":"x object class caps. type string specifying type information display. Choices \"amplitude\" plotting original aligned curves represent amplitude information data \"phase\" plotting corresponding warping functions represent phase information data. Defaults \"amplitude\". ... used.","code":""},{"path":"/reference/plot.caps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots the result of a clustering strategy stored in a caps object — plot.caps","text":"","code":"plot(sim30_caps, type = \"amplitude\")  plot(sim30_caps, type = \"phase\")"},{"path":"/reference/plot.mcaps.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots results of multiple clustering strategies — plot.mcaps","title":"Plots results of multiple clustering strategies — plot.mcaps","text":"S3 method implementation graphics::plot() generic objects class mcaps visualize performances multiple caps objects applied data sets either terms WSS terms silhouette values.","code":""},{"path":"/reference/plot.mcaps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots results of multiple clustering strategies — plot.mcaps","text":"","code":"# S3 method for mcaps plot(   x,   validation_criterion = c(\"wss\", \"silhouette\"),   what = c(\"mean\", \"distribution\"),   ... )"},{"path":"/reference/plot.mcaps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots results of multiple clustering strategies — plot.mcaps","text":"x object class mcaps. validation_criterion string specifying validation criterion used comparison. Choices \"wss\" \"silhouette\". Defaults \"wss\". string specifying kind information display validation criterion. Choices \"mean\" (plots mean values) \"distribution\" (plots boxplots). Defaults \"mean\". ... arguments passed specific methods.","code":""},{"path":"/reference/plot.mcaps.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots results of multiple clustering strategies — plot.mcaps","text":"","code":"plot(sim30_mcaps)"},{"path":"/reference/sim30_caps.html","id":null,"dir":"Reference","previous_headings":"","what":"A caps object from simulated data for examples — sim30_caps","title":"A caps object from simulated data for examples — sim30_caps","text":"object class caps storing result fdakmeans() function applied data set simulated30 using affine warping class Pearson metric searching 2 clusters.","code":""},{"path":"/reference/sim30_caps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A caps object from simulated data for examples — sim30_caps","text":"","code":"sim30_caps"},{"path":"/reference/sim30_caps.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"A caps object from simulated data for examples — sim30_caps","text":"object class caps.","code":""},{"path":"/reference/sim30_mcaps.html","id":null,"dir":"Reference","previous_headings":"","what":"An mcaps object from simulated data for examples — sim30_mcaps","title":"An mcaps object from simulated data for examples — sim30_mcaps","text":"object class mcaps storing result compare_caps() function applied data set simulated30_sub comparing clustering structures found fdakmeans() function mean centroid type used various classes warping functions varying number clusters.","code":""},{"path":"/reference/sim30_mcaps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"An mcaps object from simulated data for examples — sim30_mcaps","text":"","code":"sim30_mcaps"},{"path":"/reference/sim30_mcaps.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"An mcaps object from simulated data for examples — sim30_mcaps","text":"object class mcaps effectively tibble::tibble 5 columns many rows clustering strategies compare. 5 column-variables : n_clusters: number clusters; clustering_method: clustering method; warping_class: class warping functions used curve alignment; centroid_type: type centroid used compute cluster representative; caps_obj: result corresponding clustering strategy objects class caps.","code":""},{"path":"/reference/simulated30.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulated data for examples — simulated30","title":"Simulated data for examples — simulated30","text":"data set containing 30 simulated uni-dimensional curves.","code":""},{"path":"/reference/simulated30.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulated data for examples — simulated30","text":"","code":"simulated30"},{"path":"/reference/simulated30.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Simulated data for examples — simulated30","text":"list abscissas x values y: x Matrix 30x200; y Array 30x1x200.","code":""},{"path":"/reference/simulated30_sub.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulated data for examples — simulated30_sub","title":"Simulated data for examples — simulated30_sub","text":"data set containing 30 simulated uni-dimensional curves.","code":""},{"path":"/reference/simulated30_sub.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulated data for examples — simulated30_sub","text":"","code":"simulated30_sub"},{"path":"/reference/simulated30_sub.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Simulated data for examples — simulated30_sub","text":"list abscissas x values y: x Matrix 30x30; y Array 30x1x30.","code":""},{"path":"/reference/simulated90.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulated data from the CSDA paper — simulated90","title":"Simulated data from the CSDA paper — simulated90","text":"data set containing 90 simulated uni-dimensional curves.","code":""},{"path":"/reference/simulated90.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulated data from the CSDA paper — simulated90","text":"","code":"simulated90"},{"path":"/reference/simulated90.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Simulated data from the CSDA paper — simulated90","text":"list abscissas x values y: x Vector size 100; y Matrix size 90x100.","code":""},{"path":[]},{"path":"/news/index.html","id":"fdacluster-030","dir":"Changelog","previous_headings":"","what":"fdacluster 0.3.0","title":"fdacluster 0.3.0","text":"CRAN release: 2023-07-04 Added median centroid type; Median mean centroid types now defined union individual grids; Simplified caps class avoid storing objects multiple times different names; Added vignette initialization strategies k-means; Added article use case Berkeley growth study; Added article supported input formats.","code":""},{"path":"/news/index.html","id":"fdacluster-022","dir":"Changelog","previous_headings":"","what":"fdacluster 0.2.2","title":"fdacluster 0.2.2","text":"CRAN release: 2023-05-25 Make sure one can use fdacluster namespace notation. Make sure use fda funData checking available.","code":""},{"path":"/news/index.html","id":"fdacluster-021","dir":"Changelog","previous_headings":"","what":"fdacluster 0.2.1","title":"fdacluster 0.2.1","text":"CRAN release: 2023-05-19 Add DBSCAN clustering; Fix C++ compiler issues errored accessing empty vectors.","code":""},{"path":"/news/index.html","id":"fdacluster-020","dir":"Changelog","previous_headings":"","what":"fdacluster 0.2.0","title":"fdacluster 0.2.0","text":"CRAN release: 2023-05-18 Add hierarchical clustering; Enforce n_clusters output via linear programming (LP) using lpSolve package; New caps class storing results functional Clustering Amplitude Phase Separation consistent way; Add tools comparing clustering results (mcaps objects, autoplot plot specialized method implementations); Add seeding strategies kmeans (via hierarchical clustering k-means++ k-means++ exhaustive search first center exhaustive search centers); Add within-cluster domain auto-extension via mean imputation; Add possibility cluster according phase variability instead amplitude variability. Renaming functions: perform k-means alignment, now use fdakmeans(), perform HAC alignment, now use fdahclust().","code":""},{"path":"/news/index.html","id":"fdacluster-011","dir":"Changelog","previous_headings":"","what":"fdacluster 0.1.1","title":"fdacluster 0.1.1","text":"CRAN release: 2022-05-09 Fixed undefined behavior sanitizer issues spotted UBSAN. Added reference published work related package DESCRIPTION.","code":""},{"path":"/news/index.html","id":"fdacluster-010","dir":"Changelog","previous_headings":"","what":"fdacluster 0.1.0","title":"fdacluster 0.1.0","text":"CRAN release: 2022-02-01 Initial release. Added NEWS.md file track changes package.","code":""}]