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1 wrapper <- function(table, columns, options) {
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2
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3 # initialize output list
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4 l <- list()
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5
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6 # loop through all columns
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7
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7 m <- list()
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8 for (key in names(columns)) {
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9 # load column data
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10 column <- as.numeric(columns[key])
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11 column_data <- sapply( table[column], as.numeric )
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12
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7
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13 # collect vectors in list
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14 m <- append(m, list(column_data))
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15 }
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16
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17 # get min/max boundaries
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18 max_value <- max(unlist(m))
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19 min_value <- min(unlist(m))
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20
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21 # fix range and bins
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22 bin_seq = seq(min_value, max_value, by=10)
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23
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24 # add as first column
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25 l <- append(l, list(bin_seq[2: length(bin_seq)]))
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26
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27 # loop through all columns
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28 for (key in seq(m)) {
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29 # load column data
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30 column_data <- m[[key]]
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31
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32 # create hist data
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7
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33 hist_data <- hist(column_data, breaks=bin_seq, plot=FALSE)
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34
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35 # normalize densities
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5
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36 count_sum <- sum(hist_data$counts)
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37 if (count_sum > 0) {
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7
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38 hist_data$counts = hist_data$counts / count_sum
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5
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39 }
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40
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41 # collect vectors in list
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42 l <- append(l, list(hist_data$counts))
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43 }
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44
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45
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46 # return
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47 return (l)
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48 }
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