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23
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1 # wrapper
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2 wrapper <- function(table, columns, options) {
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3
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4 # initialize output list
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5 l <- list()
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6
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7 # loop through all columns
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8 m <- list()
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9 for (key in names(columns)) {
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10 # load column data
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11 column <- as.numeric(columns[key])
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50
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12 column_data <- suppressWarnings(as.numeric(as.character(table[column][[1]])))
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13
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23
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14 # collect vectors in list
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15 m <- append(m, list(column_data))
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16 }
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17
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45
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18 # identify optimal breaks
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19 hist_data <- hist(unlist(m), plot=FALSE)
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20 breaks <- hist_data$breaks;
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23
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21
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22 # add as first column
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45
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23 l <- append(l, list(breaks[2: length(breaks)]))
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23
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24
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25 # loop through all columns
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26 for (key in seq(m)) {
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27 # load column data
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28 column_data <- m[[key]]
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29
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30 # create hist data
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45
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31 hist_data <- hist(column_data, breaks=breaks, plot=FALSE)
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23
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32
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33 # normalize densities
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34 count_sum <- sum(hist_data$counts)
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35 if (count_sum > 0) {
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36 hist_data$counts = hist_data$counts / count_sum
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37 }
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45
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38
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23
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39 # collect vectors in list
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40 l <- append(l, list(hist_data$counts))
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41 }
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42
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43 # return
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44 return (l)
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45 }
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