comparison histogram.r @ 36:524184c2f524 draft

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35:f294f5c9608c

# utilities
boundary <- function(x, increment) {
    return (floor(x / increment) * increment)
}

roundup <- function(x) {
    return (sign(x) * 10^ceiling(log10(abs(x))))
}

# wrapper
wrapper <- function(table, columns, options) {

    # initialize output list
    l <- list()

    # loop through all columns
    m <- list()

    
    # get min/max boundaries
    min_value <- min(unlist(m))
    max_value <- max(unlist(m))
    
    # identify increment
    increment <- roundup((max_value - min_value) / 10)
    
    # fix min value
    min_value <- boundary(min_value, increment)
    
    # fix max value
    max_value <- min_value + increment * 10
    
    # check if single bin is enough
    if (min_value == max_value) {
        l <- append(l, max_value)
        for (key in seq(m)) {

        # collect vectors in list
        l <- append(l, list(hist_data$counts))
    }
    

    # return
    return (l)
}

36:524184c2f524

# binsize
min_binsize = 10

# lower boundary
lowerboundary <- function(x, increment) {
    return (floor(x / increment) * increment)
}

# upper boundary
upperboundary <- function(x, increment) {
    return (ceiling(x / increment) * increment)
}

# round to decimals
roundup <- function(x) {
    return (sign(x) * 10^ceiling(log10(abs(x))))
}

# wrapper
wrapper <- function(table, columns, options) {

    # get binsize
    binsize = max(as.integer(options$binsize), min_binsize)
    
    # initialize output list
    l <- list()

    # loop through all columns
    m <- list()

    
    # get min/max boundaries
    min_value <- min(unlist(m))
    max_value <- max(unlist(m))
    
    # identify range
    diff <- max_value - min_value
    
    # identify increment
    increment <- roundup(diff / binsize)
    
    # fix min value
    min_value <- lowerboundary(min_value, increment)
    max_value <- upperboundary(max_value, increment)
    
    # update range
    diff <- max_value - min_value
    
    # fix bin size
    binsize = round(diff / increment)
    
    # fix max value
    max_value <- min_value + binsize * increment
    
    # check if single bin is enough
    if (min_value == max_value) {
        l <- append(l, max_value)
        for (key in seq(m)) {

        # collect vectors in list
        l <- append(l, list(hist_data$counts))
    }
    
    # return
    return (l)
}