Merge pull request #148 from Nathaniel-Fernandes/master

Minor updates
irinagain · Apr 13, 2024 · db465af · db465af
2 parents cca3e8e + 752fe6b
commit db465af
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diff --git a/NEWS.md b/NEWS.md
@@ -1,3 +1,7 @@
+# iglu 4.0.2
+* Fixed broken whiplash plot in MAGE documentation
+* Added MAGEmax plotting functionality
+
 # iglu 4.0.0
 * CRAN release to match upcoming paper summarizing updated MAGE algorithm, episode calculation functionality, meal metrics, clustering and new example data inclusion
 

diff --git a/R/mage_ma_single.R b/R/mage_ma_single.R
@@ -57,7 +57,7 @@ mage_ma_single <- function(data,
 
   ## 0. Calculates MAGE on 1 segment of CGM trace
   mage_atomic <- function(.data) {
-    nmeasurements = list_cross = types = count = crosses = num_extrema = minmax = indexes = s1 = s2 = standardD = heights = nadir2peak = idx = peak_or_nadir = plus_or_minus = first_excursion = NULL
+    nmeasurements = list_cross = types = count = crosses = num_extrema = minmax = indexes = s1 = s2 = standardD = heights = nadir2peak = idx = peak_or_nadir = plus_or_minus = first_excursion = max_direction = NULL
     rm(list=c('nmeasurements', 'list_cross', 'types', 'count', 'crosses', 'num_extrema', 'minmax', 'indexes', 's1', 's2', 'standardD', 'heights', 'nadir2peak', 'idx', 'peak_or_nadir', 'plus_or_minus', 'first_excursion'))
 
     if (all(is.na(.data$gl))) {
@@ -224,29 +224,30 @@ mage_ma_single <- function(data,
       return(data.frame(start=utils::head(.data$time, 1), end=utils::tail(.data$time, 1), mage=NA, plus_or_minus=NA, first_excursion=NA))
     }
 
-    plus_first = ifelse((length(mage_plus_heights) > 0) && (length(mage_minus_heights) == 0 || mage_plus_tp_pairs[[1]][2] <= mage_minus_tp_pairs[[1]][1]), TRUE, FALSE)
-    mage_plus = data.frame(start=utils::head(.data$time, 1), end=utils::tail(.data$time, 1),  mage=ifelse(length(mage_plus_heights), mean(mage_plus_heights, na.rm = TRUE), NA), plus_or_minus="PLUS", first_excursion=plus_first)
-    mage_minus = data.frame(start=utils::head(.data$time, 1), end=utils::tail(.data$time, 1), mage=ifelse(length(mage_minus_heights), abs(mean(mage_minus_heights, na.rm = TRUE)), NA), plus_or_minus="MINUS", first_excursion=!plus_first)
+    is_plus_first = ifelse((length(mage_plus_heights) > 0) && (length(mage_minus_heights) == 0 || mage_plus_tp_pairs[[1]][2] <= mage_minus_tp_pairs[[1]][1]), TRUE, FALSE)
+    mage_plus = data.frame(start=utils::head(.data$time, 1), end=utils::tail(.data$time, 1),  mage=ifelse(length(mage_plus_heights), mean(mage_plus_heights, na.rm = TRUE), NA), plus_or_minus="PLUS", first_excursion=is_plus_first)
+    mage_minus = data.frame(start=utils::head(.data$time, 1), end=utils::tail(.data$time, 1), mage=ifelse(length(mage_minus_heights), abs(mean(mage_minus_heights, na.rm = TRUE)), NA), plus_or_minus="MINUS", first_excursion=!is_plus_first)
+    is_plus_max = ifelse(mage_plus$mage >= mage_minus$mage, TRUE, FALSE)
 
     # save data for plotting
     pframe = parent.frame()
     pframe$all_data = base::rbind(pframe$all_data, .data)
 
     for (e in mage_plus_tp_pairs) {
-      pframe$all_tp_indexes = base::rbind(pframe$all_tp_indexes, data.frame(idx=indexes[e[1]], peak_or_nadir="NADIR", plus_or_minus="PLUS", first_excursion=plus_first))
-      pframe$all_tp_indexes = base::rbind(pframe$all_tp_indexes, data.frame(idx=indexes[e[2]], peak_or_nadir="PEAK", plus_or_minus="PLUS", first_excursion=plus_first))
+      pframe$all_tp_indexes = base::rbind(pframe$all_tp_indexes, data.frame(idx=indexes[e[1]], peak_or_nadir="NADIR", plus_or_minus="PLUS", first_excursion=is_plus_first, max_direction=is_plus_max))
+      pframe$all_tp_indexes = base::rbind(pframe$all_tp_indexes, data.frame(idx=indexes[e[2]], peak_or_nadir="PEAK", plus_or_minus="PLUS", first_excursion=is_plus_first, max_direction=is_plus_max))
     }
 
     for (e in mage_minus_tp_pairs) {
-      pframe$all_tp_indexes = base::rbind(pframe$all_tp_indexes, data.frame(idx=indexes[e[1]], peak_or_nadir="PEAK", plus_or_minus="MINUS", first_excursion=!plus_first))
-      pframe$all_tp_indexes = base::rbind(pframe$all_tp_indexes, data.frame(idx=indexes[e[2]], peak_or_nadir="NADIR", plus_or_minus="MINUS", first_excursion=!plus_first))
+      pframe$all_tp_indexes = base::rbind(pframe$all_tp_indexes, data.frame(idx=indexes[e[1]], peak_or_nadir="PEAK", plus_or_minus="MINUS", first_excursion=!is_plus_first, max_direction=!is_plus_max))
+      pframe$all_tp_indexes = base::rbind(pframe$all_tp_indexes, data.frame(idx=indexes[e[2]], peak_or_nadir="NADIR", plus_or_minus="MINUS", first_excursion=!is_plus_first, max_direction=!is_plus_max))
     }
 
     return(base::rbind(mage_plus, mage_minus))
   }
 
   ## 1. Preprocessing
-  MA_Short = MA_Long = DELTA_SHORT_LONG = TP = id = .xmin = .xmax = gap = x = y = xend = yend = hours = weight = idx = peak_or_nadir = plus_or_minus = first_excursion = NULL
+  MA_Short = MA_Long = DELTA_SHORT_LONG = TP = id = .xmin = .xmax = gap = x = y = xend = yend = hours = weight = idx = peak_or_nadir = plus_or_minus = first_excursion = max_direction = NULL
   rm(list = c("MA_Short", "MA_Long", "DELTA_SHORT_LONG", "TP", ".xmin", ".xmax", "id", "gap", "x", "y", "xend", "yend", "hours", "weight", "idx", "peak_or_nadir", "plus_or_minus", "first_excursion"))
 
   data = check_data_columns(data)
@@ -372,14 +373,12 @@ mage_ma_single <- function(data,
     direction = match.arg(direction, c('avg', 'service', 'max', 'plus', 'minus'))
     plot_type = match.arg(plot_type, c('ggplot', 'plotly'))
 
-    if (direction == "max") {
-      stop("Plotting functionality for MAGEmax is not possible right now. Please request this feature on GitHub if you'd like it. Thank you for your patience.")
-    }
-
-    if (direction == "avg") {
+    if (direction == 'avg') {
       tp_indexes <- dplyr::select(all_tp_indexes, idx, peak_or_nadir, plus_or_minus)
     } else if (direction == 'service') {
       tp_indexes <- dplyr::filter(all_tp_indexes, first_excursion==TRUE) %>% dplyr::select(idx, peak_or_nadir, plus_or_minus)
+    } else if (direction == 'max') {
+      tp_indexes <- dplyr::filter(all_tp_indexes, max_direction==TRUE) %>% dplyr::select(idx, peak_or_nadir, plus_or_minus)
     } else {
       tp_indexes <- dplyr::filter(all_tp_indexes, plus_or_minus==ifelse(direction == 'plus', "PLUS", "MINUS")) %>% dplyr::select(idx, peak_or_nadir, plus_or_minus)
     }

diff --git a/vignettes/MAGE.Rmd b/vignettes/MAGE.Rmd
@@ -132,7 +132,7 @@ Service et al. [3] by two of the authors, who were unaware of the
 outcome of the proposed algorithm's outputs.
 
 |                                Dataset                                 | Diabetes Type |     Age group      | Subject ID  | Number of days used (CGM traces) |
-|:------------------------:|:----------:|:----------:|:----------:|:----------:|
+|:------------------:|:-----------:|:-----------:|:-----------:|:-----------:|
 |   [Hall et al. (2018)](https://doi.org/10.1371/journal.pbio.2005143)   |     None      |   Adults (\> 18)   | 1636-69-001 |                5                 |
 |                                                                        |               |                    | 1636-69-026 |                6                 |
 | [Tsalikian et al. (2005)](https://doi.org/10.1016/j.jpeds.2005.04.065) |    Type 1     | Children (10 - 18) |      2      |                1                 |
@@ -551,7 +551,7 @@ correction for whiplash. Notice the true peak is properly identified for
 $tp_{12}$.
 
 ```{r, echo=FALSE, fig.width=10, fig.height=7, out.width="700px", out.height ="400px"}
-knitr::include_graphics("mage_figures/boxplot-of-errors.png")
+knitr::include_graphics("mage_figures/whiplash2.png")
 ```
 
 **Figure 6.** Plot of Subject 1636-69-026 via MAGE iglu v3.5.0 without

diff --git a/vignettes/iglu.Rmd b/vignettes/iglu.Rmd
@@ -24,7 +24,7 @@ Multiple CGM-derived metrics have been developed to assess the quality of glycem
 
 The iglu package is designed to work with Continuous Glucose Monitor (CGM) data in the form of a data frame with the following three columns present:
 
-* Blood glucose level measurement [in mg/dL] (`"gl"`)
+* Glucose level measurement [in mg/dL] (`"gl"`)
 
 * Timestamp for glucose measurement (`"time"`)