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37
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1 # load sparse matrix package
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2 suppressPackageStartupMessages(library('Matrix'))
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3
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4 # access a numeric column
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5 get_numeric <- function(table, column_key) {
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6 column <- as.numeric(column_key)
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53
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7 column_data <- suppressWarnings(as.numeric(as.character(table[column][[1]])))
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37
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8 return (c(column_data))
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9 }
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10
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11 # access a label column
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12 get_label <- function(table, column_key) {
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13 column <- as.numeric(column_key)
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55
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14 column_data <- as.character(table[column][[1]])
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15 return (c(column_data))
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37
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16 }
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17
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18 # inflate three columns into matrix
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19 matrify <- function (data) {
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20 if (ncol(data) != 3)
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21 stop('Data frame must have three column format')
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22 plt <- data[, 1]
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23 spc <- data[, 2]
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24 abu <- data[, 3]
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25 plt.codes <- levels(factor(plt))
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26 spc.codes <- levels(factor(spc))
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27 taxa <- Matrix(0, nrow=length(plt.codes), ncol=length(spc.codes), sparse=TRUE)
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28 row <- match(plt, plt.codes)
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29 col <- match(spc, spc.codes)
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30 for (i in 1:length(abu)) {
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31 taxa[row[i], col[i]] <- abu[i]
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32 }
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33 colnames(taxa) <- spc.codes
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34 rownames(taxa) <- plt.codes
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35 taxa
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36 }
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37
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38 # flatten data.frame into three column format
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39 flatten <- function(my_matrix) {
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40 summ <-summary(my_matrix)
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41 summ <- data.frame(i=rownames(my_matrix)[summ$i], j=colnames(my_matrix)[summ$j], x=summ$x)
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42 summ
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43 }
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44
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45 # wrapper
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46 wrapper <- function(table, columns, options) {
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47
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48 # initialize output list
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49 l <- list()
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50
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51 # get number of columns
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52 n = length(columns)
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53
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54 # consistency check
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55 if (n %% 3 != 0) {
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56 print ('heatmap::wrapper() - Data not consistent (n mod 3 != 0)')
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57 return (l)
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58 }
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59
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60 # create index sequence
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61 index = seq(1, n, by=3)
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62
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63 # get keys
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64 keys = names(columns)
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65
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66 # loop through blocks
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67 for (i in index) {
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68 # create columns
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69 ci <- get_label(table, columns[keys[i]])
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70 cj <- get_label(table, columns[keys[i+1]])
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71 cx <- get_numeric(table, columns[keys[i+2]])
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72
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73 # create a frame from columns
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74 my_frame <- data.frame(ci=ci, cj=cj, cx=cx)
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75
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76 # create matrix out of the frame
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77 my_matrix <- matrify(my_frame)
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78
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79 # create/cluster matrix
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80 row_order <- hclust(dist(my_matrix))$order
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81 col_order <- hclust(dist(t(my_matrix)))$order
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82
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83 # reorder matrix
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84 my_matrix <- my_matrix[row_order, col_order]
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85
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86 # transform back to three columns
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53
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87 my_flatmatrix = flatten(my_matrix)
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37
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88
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89 # append to result list
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90 l <- append(l, list(my_flatmatrix$i))
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91 l <- append(l, list(my_flatmatrix$j))
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92 l <- append(l, list(my_flatmatrix$x))
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93 }
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94
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95 # return
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96 return (l)
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97 }
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