Optimized functions

R/co_agg.R

@@ -94,47 +94,51 @@ co_agg.default <- function(imgs,channels,size,npixel,dstep=1,pwidth,zstep,freec=
         ch2_t[ch2_t > 0] <- 1} else stop("Kernel smooth has to be odd integers in all directions")
     }
 
+    # Sum channels
+    sumch <- ch1_t+ch2_t
+
     # Densities of channels
     d1 <- length(which(ch1_t == 1))/length(ch1_t)
     d2 <- length(which(ch2_t == 1))/length(ch2_t)
+    d12 <- length(which(sumch > 0))/length(sumch)
 
     # Addresses in array (pixels)
     side <- dim(ch1_t)[1]
     address_array <- array(1:(side*side*dim(ch1_t)[3]), 
                            c(side, side, dim(ch1_t)[3]))
 
     # Coordinates of pixels in channel1 (pixels)
-    ch1_add <- data.frame(which(ch1_t == 1, T))
+    ch1_add <- data.frame(which(ch1_t > 0, T))
     colnames(ch1_add) <- c("x", "y", "z")
 
     # Coordinates of pixels in channel2 (pixels)
-    ch2_add <- data.frame(which(ch2_t == 1, T))
+    ch2_add <- data.frame(which(ch2_t > 0, T))
     colnames(ch2_add) <- c("x", "y", "z")
 
-    # Coordinates of all pixels (pixels)
-    ch_add <- data.frame(which(ch1_t == 1 | ch1_t == 0, T))
-    colnames(ch_add) <- c("x", "y", "z")
+    # Coordinates of pixels in either channel (pixels)
+    ch_sum <- data.frame(which(sumch > 0, T))
+    colnames(ch_sum) <- c("x", "y", "z")
 
     # Randomly sample pixels (pixels)
-    these <- sample(1:dim(ch_add)[1], size = npixel)
+    these <- sample(1:dim(ch_sum)[1], size = npixel)
 
     # Get their addresses
-    ch_pix <- ch_add[these,]
+    ch_pix <- ch_sum[these,]
 
     # Matrix to collect results
     hits <- matrix(NA, length(ds), npixel)
     totals <- matrix(NA, length(ds), npixel)
-    
+
     # Loop through pixels
     for(j in 1:npixel){
 
       # Focal pixel position
       p <- ch_pix[j,]
-      
-      # Does the focal pixel have a colour?
+
+      # What colour is the focal pixel
       test1 <- ch1_add[ch1_add$x == p$x & ch1_add$y == p$y & ch1_add$z == p$z,]
       test2 <- ch2_add[ch2_add$x == p$x & ch2_add$y == p$y & ch2_add$z == p$z,]
-      
+
       # Coordinates of the box (pixels)
       xrange <- c(p$x-(size/pwidth), p$x+(size/pwidth))
       yrange <- c(p$y-(size/pwidth), p$y+(size/pwidth))
@@ -181,14 +185,10 @@ co_agg.default <- function(imgs,channels,size,npixel,dstep=1,pwidth,zstep,freec=
       }
 
       # Hits
-      if((nrow(test1)+nrow(test2))==0) {hits[,j] <- 0} else {
-
-        for(l in 1:(length(ds))){
-          if(nrow(test1)>0 & nrow(test2)==0) hits[l,j] <- length(which(id2[positions[[l]]]==1))
-          if(nrow(test2)>0 & nrow(test1)==0) hits[l,j] <- length(which(id1[positions[[l]]]==1))
-          if(nrow(test1)>0 & nrow(test2)>0) hits[l,j] <- length(which(id1[positions[[l]]]==1))+length(which(id2[positions[[l]]]==1))      
-        }
-
+      for(l in 1:(length(ds))){
+          if(nrow(test1)==1 && nrow(test2)==0) hits[l,j] <- length(which(id2[positions[[l]]]==1))
+          if(nrow(test2)==1 && nrow(test1)==0) hits[l,j] <- length(which(id1[positions[[l]]]==1))
+          if(nrow(test1)==1 && nrow(test2)==1) hits[l,j] <- length(which(id1[positions[[l]]]==1))+length(which(id2[positions[[l]]]==1))      
       }
 
     }
@@ -199,8 +199,8 @@ co_agg.default <- function(imgs,channels,size,npixel,dstep=1,pwidth,zstep,freec=
 
     # Calculate probability and co-aggregation
     Prop <- hits.sum/totals.sum
-    CA <- Prop/(2*d1*d2)
-    
+    CA <- Prop/(2*(d1*d2/d12))
+
     theseCC <- cbind(gsub(channels[1],"",sub(".*/", "", ch1_files[i])),ds, CA)
     theseCC <- as.data.frame(theseCC)
     colnames(theseCC) <- c("Img", "Distance", "CA")

R/cross_ratio.R

@@ -99,37 +99,25 @@ cross_ratio.default <- function(imgs,focal.channel,target.channels,size,npixel,d
         ch.f <- medianFilter(ch.f,kern.s)
         ch.f[ch.f > 0] <- 1} else stop("Kernel smooth has to be odd integers in all directions")
     }
-    
+
     # Densities of channels
     d1 <- length(which(ch.t1 == 1))/length(ch.t1)
     d2 <- length(which(ch.t2 == 1))/length(ch.t2)
-    
+
     # Addresses in array (pixels)
     side <- dim(ch.t1)[1]
     address_array <- array(1:(side*side*dim(ch.t1)[3]), 
                            c(side, side, dim(ch.t1)[3]))
 
-    # Coordinates of pixels in channel1 (pixels)
-    ch1_add <- data.frame(which(ch.t1 == 1, T))
-    colnames(ch1_add) <- c("x", "y", "z")
-
-    # Coordinates of pixels in channel2 (pixels)
-    ch2_add <- data.frame(which(ch.t2 == 1, T))
-    colnames(ch2_add) <- c("x", "y", "z")
-
     # Coordinates of pixels in focal channel (pixels)
     chf_add <- data.frame(which(ch.f == 1, T))
     colnames(chf_add) <- c("x", "y", "z")
-
-    # Coordinates of all pixels (pixels)
-    ch_add <- data.frame(which(ch.t1 == 1 | ch.t1 == 0, T))
-    colnames(ch_add) <- c("x", "y", "z")
-
+
     # Randomly sample pixels (pixels)
-    these <- sample(1:dim(ch_add)[1], size = npixel)
+    these <- sample(1:dim(chf_add)[1], size = npixel)
 
     # Get their addresses
-    ch_pix <- ch_add[these,]
+    ch_pix <- chf_add[these,]
 
     # Matrix to collect results
     hits1 <- matrix(NA, length(ds), npixel)
@@ -141,11 +129,6 @@ cross_ratio.default <- function(imgs,focal.channel,target.channels,size,npixel,d
       # Focal pixel position
       p <- ch_pix[j,]
 
-      # Does the focal pixel have a colour?
-      test1 <- ch1_add[ch1_add$x == p$x & ch1_add$y == p$y & ch1_add$z == p$z,]
-      test2 <- ch2_add[ch2_add$x == p$x & ch2_add$y == p$y & ch2_add$z == p$z,]
-      testf <- chf_add[chf_add$x == p$x & chf_add$y == p$y & chf_add$z == p$z,]
-
       # Coordinates of the box (pixels)
       xrange <- c(p$x-(size/pwidth), p$x+(size/pwidth))
       yrange <- c(p$y-(size/pwidth), p$y+(size/pwidth))
@@ -187,16 +170,11 @@ cross_ratio.default <- function(imgs,focal.channel,target.channels,size,npixel,d
       }
 
       # Count hits
-      if(nrow(testf)==0) {
-        for(l in 1:(length(ds))){
-          hits1[l,j] <- length(which(id1[positions[[l]]]==1))
-          hits2[l,j] <- length(which(id2[positions[[l]]]==1))
-        }
-      } else {
-        hits1[,j] <- 0
-        hits2[,j] <- 0
+      for(l in 1:(length(ds))){
+        hits1[l,j] <- length(which(id1[positions[[l]]]==1))
+        hits2[l,j] <- length(which(id2[positions[[l]]]==1))
+
       }
-
     }
 
     # Sum hits for all pixels
@@ -206,7 +184,7 @@ cross_ratio.default <- function(imgs,focal.channel,target.channels,size,npixel,d
     # Calculate ratio and cross-ratio
     Ratio <- hits1.sum/hits2.sum
     CR <- Ratio/(d1/d2)
-    
+
     theseCR <- cbind(gsub(target.channels[1],"",sub(".*/", "", ch.t1_files[i])),ds, CR)
     theseCR <- as.data.frame(theseCR)
     colnames(theseCR) <- c("Img","Distance", "CR")

R/occupancy.R

@@ -103,14 +103,10 @@ occupancy.default <- function(imgs,focal.channel,target.channel,size,npixel,dste
     address_array <- array(1:(side*side*dim(ch.f)[3]), 
                            c(side, side, dim(ch.f)[3]))
 
-    # Coordinates of pixels in channel1 (pixels)
+    # Coordinates of pixels in focal channel (pixels)
     chf_add <- data.frame(which(ch.f == 1, T))
     colnames(chf_add) <- c("x", "y", "z")
 
-    # Coordinates of pixels in channel2 (pixels)
-    cht_add <- data.frame(which(ch.t == 1, T))
-    colnames(cht_add) <- c("x", "y", "z")
-
     # Randomly sample pixels (pixels)
     these <- sample(1:dim(chf_add)[1], size = npixel)
 

README.md

@@ -172,10 +172,9 @@ of both zstep and pwidth
     ##  [1]  0.0  1.5  3.0  4.5  6.0  7.5  9.0 10.5 12.0 13.5 15.0 16.5 18.0 19.5
     ## [15] 21.0 22.5 24.0 25.5 27.0 28.5 30.0
 
-Ok. lets try 21 microns then. As an example we pick 200 random pixels
-(should be higher for actual analysis), and we run the whole thing 5
-times to see how picking random pixels affect the variability of the
-result
+Ok. lets try 21 microns then. As an example we pick 200 random pixels,
+and we run the whole thing 5 times to see how picking random pixels
+affect the variability of the result
 
     mycc <- co_agg(imgs=myimg,channels=c("xan","ste"),size=21,npixel=200,dstep=1,pwidth=0.75,zstep=0.25,R=5)
 
@@ -210,9 +209,7 @@ expected from random chance
 
 We can also quantify how much space a channel (target) occupy at certain
 distances from another channel (focal). This is similar to
-co-aggregation, although this is directed. With set number of random
-pixels, `occupancy` is more precise than the `co_agg`, especially in
-images with low fill.
+co-aggregation, although this is directed.
 
 Lets run it until 21 microns. As an example we pick 200 random pixels,
 and we run the whole thing 5 times to see how picking random pixels
@@ -291,7 +288,7 @@ expected given random chance. A cross-ratio above 1 at some distance
 means that target channel 1 is more likely to be found than target
 channel 2 at that distance.
 
-    mycr <- cross_ratio(imgs=myimg,focal.channel="pan",target.channels=c("xan","ste"),size=21,npixel=200,dstep=1,pwidth=0.75,zstep=0.25,R=5)
+    mycr <- cross_ratio(imgs=myimg,focal.channel="mic",target.channels=c("xan","pan"),size=21,npixel=200,dstep=1,pwidth=0.75,zstep=0.25,R=5)
 
     ## 
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