fix overlapping color breaks

heatmaps/h1_simple.R

@@ -8,7 +8,7 @@ library(RColorBrewer)
 data <- read.csv("dataset.csv", comment.char="#")
 rnames <- data[,1]                            # assign labels in column 1 to "rnames"
 mat_data <- data.matrix(data[,2:ncol(data)])  # transform column 2-5 into a matrix
-rownames(mat_data) <- rnames                  # assign row names 
+rownames(mat_data) <- rnames                  # assign row names
 
 
 
@@ -20,27 +20,44 @@ rownames(mat_data) <- rnames                  # assign row names
 my_palette <- colorRampPalette(c("red", "yellow", "green"))(n = 299)
 
 # (optional) defines the color breaks manually for a "skewed" color transition
-col_breaks = c(seq(-1,0,length=100),  # for red
-  seq(0,0.7,length=100),              # for yellow
-  seq(0.7,1,length=100))              # for green
+col_breaks = c(seq(-1,0,length=100),   # for red
+  seq(0.01,0.7,length=100),            # for yellow
+  seq(0.71,1,length=100))              # for green
 
 # creates a 5 x 5 inch image
-png("h1_simple.png",        
+png("h1_simple.png",
   width = 5*300,        # 5 x 300 pixels
   height = 5*300,
   res = 300,            # 300 pixels per inch
   pointsize = 8)        # smaller font size
 
-heatmap.2(mat_data, 
+heatmap.2(mat_data,
   cellnote = mat_data,  # same data set for cell labels
   main = "Correlation", # heat map title
   notecol="black",      # change font color of cell labels to black
   density.info="none",  # turns off density plot inside color legend
   trace="none",         # turns off trace lines inside the heat map
   margins =c(12,9),     # widens margins around plot
-  col=my_palette,       # use on color palette defined earlier 
+  col=my_palette,       # use on color palette defined earlier
   breaks=col_breaks,    # enable color transition at specified limits
   dendrogram="row",     # only draw a row dendrogram
   Colv="NA")            # turn off column clustering
 
+##############################################################################
+# NOTE
+##############################################################################
+# The color breaks above will yield a warning
+#    "...unsorted 'breaks' will be sorted before use" since they contain
+#    (due to the negative numbers). To avoid this warning, you can change the
+#    manual breaks to:
+#
+#  col_breaks = c(seq(0,1,length=100),   # for red
+#    seq(1.01,1.7,length=100),           # for yellow
+#    seq(1.71,2,length=100))             # for green
+#
+# However, the problem is then that our heatmap contains negative values
+# which will then not be colored correctly. Remember that you don't need to
+# provide manual color breaks at all, this is entirely optional.
+##############################################################################
+
 dev.off()

heatmaps/h2_default_clustering.R

@@ -8,7 +8,7 @@ library(RColorBrewer)
 data <- read.csv("dataset.csv", comment.char="#")
 rnames <- data[,1]                            # assign labels in column 1 to "rnames"
 mat_data <- data.matrix(data[,2:ncol(data)])  # transform column 2-5 into a matrix
-rownames(mat_data) <- rnames                  # assign row names 
+rownames(mat_data) <- rnames                  # assign row names
 
 
 
@@ -19,13 +19,8 @@ rownames(mat_data) <- rnames                  # assign row names
 # creates a own color palette from red to green
 my_palette <- colorRampPalette(c("red", "yellow", "green"))(n = 299)
 
-# (optional) defines the color breaks manually for a "skewed" color transition
-col_breaks = c(seq(-1,0,length=100),  # for red
-  seq(0,0.7,length=100),              # for yellow
-  seq(0.7,1,length=100))              # for green
-
 # creates a 5 x 5 inch image
-png("h2_default_clustering.png",        
+png("h2_default_clustering.png",
   width = 5*300,        # 5 x 300 pixels
   height = 5*300,
   res = 300,            # 300 pixels per inch
@@ -37,19 +32,19 @@ png("h2_default_clustering.png",
 # Distance options: euclidean (default), maximum, canberra, binary, minkowski, manhattan
 # Cluster options: complete (default), single, average, mcquitty, median, centroid, ward
 row_distance = dist(mat_data, method = "manhattan")
-row_cluster = hclust(row_distance, method = "ward")
+row_cluster = hclust(row_distance, method = "ward.D")
 col_distance = dist(t(mat_data), method = "manhattan")
-col_cluster = hclust(col_distance, method = "ward")
+col_cluster = hclust(col_distance, method = "ward.D")
 
-heatmap.2(mat_data, 
+heatmap.2(mat_data,
   cellnote = mat_data,  # same data set for cell labels
   main = "Correlation", # heat map title
   notecol = "black",      # change font color of cell labels to black#
   density.info = "none",  # turns off density plot inside color legend
   trace = "none",         # turns off trace lines inside the heat map
   margins = c(12,9),     # widens margins around plot
-  col = my_palette,       # use on color palette defined earlier 
-  breaks = col_breaks,    # enable color transition at specified limits
+  col = my_palette,       # use on color palette defined earlier
   Rowv = as.dendrogram(row_cluster), # apply default clustering method
   Colv = as.dendrogram(col_cluster)) # apply default clustering method
+
 dev.off()

heatmaps/h3_categorizing.R

@@ -8,7 +8,7 @@ library(RColorBrewer)
 data <- read.csv("dataset.csv", comment.char="#")
 rnames <- data[,1]                            # assign labels in column 1 to "rnames"
 mat_data <- data.matrix(data[,2:ncol(data)])  # transform column 2-5 into a matrix
-rownames(mat_data) <- rnames                  # assign row names 
+rownames(mat_data) <- rnames                  # assign row names
 
 
 
@@ -19,19 +19,14 @@ rownames(mat_data) <- rnames                  # assign row names
 # creates a own color palette from red to green
 my_palette <- colorRampPalette(c("red", "yellow", "green"))(n = 299)
 
-# (optional) defines the color breaks manually for a "skewed" color transition
-col_breaks = c(seq(-1,0,length=100),  # for red
-  seq(0,0.7,length=100),              # for yellow
-  seq(0.7,1,length=100))              # for green
-
 # creates a 5 x 5 inch image
-png("h3_categorizing.png",        
+png("h3_categorizing.png",
   width = 5*300,        # 5 x 300 pixels
   height = 5*300,
   res = 300,            # 300 pixels per inch
   pointsize = 8)        # smaller font size
 
-heatmap.2(mat_data, 
+heatmap.2(mat_data,
   cellnote = mat_data,  # same data set for cell labels
   RowSideColors = c(    # grouping row-variables into different
      rep("gray", 3),   # categories, Measurement 1-3: green
@@ -43,7 +38,6 @@ heatmap.2(mat_data,
   trace="none",         # turns off trace lines inside the heat map
   margins =c(12,9),     # widens margins around plot
   col=my_palette,       # use on color palette defined earlier 
-  breaks=col_breaks,    # enable color transition at specified limits
   dendrogram="row",     # only draw a row dendrogram
   Colv="NA")            # turn off column clustering
 
@@ -54,6 +48,6 @@ legend("topright",      # location of the legend on the heatmap plot
     col = c("gray", "blue", "black"),  # color key
     lty = 1,            # line style
     lwd = 10,           # line width
-   )          
+   )
 
 dev.off()