Mercurial > repos > iuc > charts

comparison histogramdiscrete.r @ 1:344ac3ca7557 draft default tip

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/charts/ commit 4494db13b69987fbc97d47177d2a5956e46e927b"
author iuc
date Wed, 17 Nov 2021 09:06:59 +0000
parents a87a3773d8ed
children
comparison
equal deleted inserted replaced
0:a87a3773d8ed 1:344ac3ca7557
1 zero <- function(v) {
2 0
3 }
4
1 # wrapper 5 # wrapper
2 wrapper <- function(table, columns, options) { 6 wrapper <- function(table, columns, options) {
3 7
4 # initialize output list 8 # initialize output list
5 l <- list() 9 l <- list()
7 # loop through all columns 11 # loop through all columns
8 m <- list() 12 m <- list()
9 for (key in names(columns)) { 13 for (key in names(columns)) {
10 # load column data 14 # load column data
11 column <- as.numeric(columns[key]) 15 column <- as.numeric(columns[key])
12 16
13 # ensure string column 17 # ensure string column
14 column_data <- as.character(table[column][[1]]) 18 column_data <- as.character(table[column][[1]])
15 19
16 # collect vectors in list 20 # collect vectors in list
17 m <- append(m, list(column_data)) 21 m <- append(m, list(column_data))
18 } 22 }
19 23
20 # get alphabetically sorted bins 24 # get alphabetically sorted bins
21 bins <- sort(unique(unlist(m))) 25 bins <- sort(unique(unlist(m)))
22 26
23 # add first column 27 # add first column
24 l <- append(l, list(bins)) 28 l <- append(l, list(bins))
25 29
26 # loop through all columns 30 # loop through all columns
27 for (key in seq(m)) { 31 for (key in seq(m)) {
28 # reset bins 32 # reset bins
29 bins = sapply(bins, function(v) { 0 }) 33 bins <- sapply(bins, zero)
30 34
31 # load column data 35 # load column data
32 column_data <- m[[key]] 36 column_data <- m[[key]]
33 37
34 # create hist data 38 # create hist data
35 table_data <- table(column_data) 39 table_data <- table(column_data)
36 40
37 # transfer counts to bins 41 # transfer counts to bins
38 for (id in names(table_data)) { 42 for (id in names(table_data)) {
39 bins[id] <- table_data[id] 43 bins[id] <- table_data[id]
40 } 44 }
41 45
42 # normalize densities 46 # normalize densities
43 total <- length(column_data) 47 total <- length(column_data)
44 if (total > 0) { 48 if (total > 0) {
45 bins = bins / total 49 bins <- bins / total
46 } 50 }
47 51
48 # collect vectors in list 52 # collect vectors in list
49 l <- append(l, list(bins)) 53 l <- append(l, list(bins))
50 } 54 }
51 55
52 # return 56 # return
53 return (l) 57 return(l)
54 } 58 }