Method: MiniHistogram#edges

Defined in:
lib/mini_histogram.rb

#edges ⇒ Object Also known as: edge

Finds the “edges” of a given histogram that will mark the boundries for the histogram’s “bins”

Example:

a = [1,1,1, 5, 5, 5, 5, 10, 10, 10]
MiniHistogram.new(a).edges
# => [0.0, 2.0, 4.0, 6.0, 8.0, 10.0, 12.0]

There are multiple ways to find edges, this was taken from
https://github.com/mrkn/enumerable-statistics/issues/24

Another good set of implementations is in numpy
https://github.com/numpy/numpy/blob/d9b1e32cb8ef90d6b4a47853241db2a28146a57d/numpy/lib/histograms.py#L222



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# File 'lib/mini_histogram.rb', line 122

def edges
  return @edges if @edges

  return @edges = [0.0] if array.empty?

  lo = @min
  hi = @max

  nbins = sturges.to_f

  if hi == lo
    start = lo
    step = 1.0
    divisor = 1.0
    len = 1
  else
    bw = (hi - lo) / nbins
    lbw = Math.log10(bw)
    if lbw >= 0
      step = 10 ** lbw.floor * 1.0
      r = bw/step

      if r <= 1.1
        # do nothing
      elsif r <= 2.2
        step *= 2.0
      elsif r <= 5.5
        step *= 5.0
      else
        step *= 10
      end
      divisor = 1.0
      start = step * (lo/step).floor
      len = ((hi - start)/step).ceil
    else
      divisor = 10 ** - lbw.floor
      r = bw * divisor
      if r <= 1.1
        # do nothing
      elsif r <= 2.2
        divisor /= 2.0
      elsif r <= 5.5
        divisor /= 5.0
      else
        divisor /= 10.0
      end
      step = 1.0
      start = (lo * divisor).floor
      len = (hi * divisor - start).ceil
    end
  end

  if left_p
    while (lo < start/divisor)
      start -= step
    end

    while (start + (len - 1)*step)/divisor <= hi
      len += 1
    end
  else
    while lo <= start/divisor
      start -= step
    end
    while (start + (len - 1)*step)/divisor < hi
      len += 1
    end
  end

  @edges = []
  len.times.each do
    @edges << start/divisor
    start += step
  end

  return @edges
end