R: Examples for 'stats::heatmap'

### ** Examples

require(graphics); require(grDevices)
x  <- as.matrix(mtcars)
rc <- rainbow(nrow(x), start = 0, end = .3)
cc <- rainbow(ncol(x), start = 0, end = .3)
hv <- heatmap(x, col = cm.colors(256), scale = "column",
              RowSideColors = rc, ColSideColors = cc, margins = c(5,10),
              xlab = "specification variables", ylab =  "Car Models",
              main = "heatmap(<Mtcars data>, ..., scale = \"column\")")

utils::str(hv) # the two re-ordering index vectors

List of 4
 $ rowInd: int [1:32] 31 17 16 15 5 25 29 24 7 6 ...
 $ colInd: int [1:11] 2 9 8 11 6 5 10 7 1 4 ...
 $ Rowv  : NULL
 $ Colv  : NULL

## no column dendrogram (nor reordering) at all:
heatmap(x, Colv = NA, col = cm.colors(256), scale = "column",
        RowSideColors = rc, margins = c(5,10),
        xlab = "specification variables", ylab =  "Car Models",
        main = "heatmap(<Mtcars data>, ..., scale = \"column\")")

## Don't show: 
## no row dendrogram (nor reordering) at all:
heatmap(x, Rowv = NA, col = cm.colors(256), scale = "column",
        ColSideColors = cc, margins = c(5,10),
        xlab = "xlab", ylab =  "ylab")  # no main

## End(Don't show)
## "no nothing"
heatmap(x, Rowv = NA, Colv = NA, scale = "column",
        main = "heatmap(*, NA, NA) ~= image(t(x))")

round(Ca <- cor(attitude), 2)

           rating complaints privileges learning raises critical advance
rating       1.00       0.83       0.43     0.62   0.59     0.16    0.16
complaints   0.83       1.00       0.56     0.60   0.67     0.19    0.22
privileges   0.43       0.56       1.00     0.49   0.45     0.15    0.34
learning     0.62       0.60       0.49     1.00   0.64     0.12    0.53
raises       0.59       0.67       0.45     0.64   1.00     0.38    0.57
critical     0.16       0.19       0.15     0.12   0.38     1.00    0.28
advance      0.16       0.22       0.34     0.53   0.57     0.28    1.00

symnum(Ca) # simple graphic

           rt cm p l rs cr a
rating     1                
complaints +  1             
privileges .  .  1          
learning   ,  .  . 1        
raises     .  ,  . , 1      
critical             .  1   
advance          . . .     1
attr(,"legend")
[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1

heatmap(Ca,               symm = TRUE, margins = c(6,6)) # with reorder()

heatmap(Ca, Rowv = FALSE, symm = TRUE, margins = c(6,6)) # _NO_ reorder()

## slightly artificial with color bar, without and with ordering:
cc <- rainbow(nrow(Ca))
heatmap(Ca, Rowv = FALSE, symm = TRUE, RowSideColors = cc, ColSideColors = cc,
        margins = c(6,6))

heatmap(Ca,             symm = TRUE, RowSideColors = cc, ColSideColors = cc,
        margins = c(6,6))

## For variable clustering, rather use distance based on cor():
symnum( cU <- cor(USJudgeRatings) )

     CO I DM DI CF DE PR F O W PH R
CONT 1                             
INTG    1                          
DMNR    B 1                        
DILG    + +  1                     
CFMG    + +  B  1                  
DECI    + +  B  B  1               
PREP    + +  B  B  B  1            
FAMI    + +  B  *  *  B  1         
ORAL    * *  B  B  *  B  B 1       
WRIT    * +  B  *  *  B  B B 1     
PHYS    , ,  +  +  +  +  + + + 1   
RTEN    * *  *  *  *  B  * B B *  1
attr(,"legend")
[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1

hU <- heatmap(cU, Rowv = FALSE, symm = TRUE, col = topo.colors(16),
             distfun = function(c) as.dist(1 - c), keep.dendro = TRUE)

## The Correlation matrix with same reordering:
round(100 * cU[hU[[1]], hU[[2]]])

     CONT INTG DMNR PHYS DILG CFMG DECI RTEN ORAL WRIT PREP FAMI
CONT  100  -13  -15    5    1   14    9   -3   -1   -4    1   -3
INTG  -13  100   96   74   87   81   80   94   91   91   88   87
DMNR  -15   96  100   79   84   81   80   94   91   89   86   84
PHYS    5   74   79  100   81   88   87   91   89   86   85   84
DILG    1   87   84   81  100   96   96   93   95   96   98   96
CFMG   14   81   81   88   96  100   98   93   95   94   96   94
DECI    9   80   80   87   96   98  100   92   95   95   96   94
RTEN   -3   94   94   91   93   93   92  100   98   97   95   94
ORAL   -1   91   91   89   95   95   95   98  100   99   98   98
WRIT   -4   91   89   86   96   94   95   97   99  100   99   99
PREP    1   88   86   85   98   96   96   95   98   99  100   99
FAMI   -3   87   84   84   96   94   94   94   98   99   99  100

## The column dendrogram:
utils::str(hU$Colv)

--[dendrogram w/ 2 branches and 12 members at h = 1.15]
  |--leaf "CONT" 
  `--[dendrogram w/ 2 branches and 11 members at h = 0.258]
     |--[dendrogram w/ 2 branches and 2 members at h = 0.0354]
     |  |--leaf "INTG" 
     |  `--leaf "DMNR" 
     `--[dendrogram w/ 2 branches and 9 members at h = 0.187]
        |--leaf "PHYS" 
        `--[dendrogram w/ 2 branches and 8 members at h = 0.075]
           |--[dendrogram w/ 2 branches and 3 members at h = 0.0438]
           |  |--leaf "DILG" 
           |  `--[dendrogram w/ 2 branches and 2 members at h = 0.0189]
           |     |--leaf "CFMG" 
           |     `--leaf "DECI" 
           `--[dendrogram w/ 2 branches and 5 members at h = 0.0584]
              |--leaf "RTEN" 
              `--[dendrogram w/ 2 branches and 4 members at h = 0.0187]
                 |--[dendrogram w/ 2 branches and 2 members at h = 0.00657]
                 |  |--leaf "ORAL" 
                 |  `--leaf "WRIT" 
                 `--[dendrogram w/ 2 branches and 2 members at h = 0.0101]
                    |--leaf "PREP" 
                    `--leaf "FAMI"

Examples for 'stats::heatmap'

Draw a Heat Map