ministat.rb

require 'mathn'

module MiniStat
  VERSION = '1.0.0'   
  class Data
    attr_reader :data

    def initialize(data)
      @data = data.collect {|data| data.to_f}.sort
      @sorted = true
    end

    # Return the median of your dataset. Naive implementaion
    # -- does a sort on the data.
    def median(data=@data)
      unless @sorted and data == @data
        data.sort!
        @sort = true
      end
      if data.size == 0
        return 0
      end
      if data.size % 2 == 0
        return (data[data.size / 2 - 1] + data[(data.size / 2)]) / 2
      else 
        split = (data.size + 1) / 2
        return (data[split - 1.5] + data[split - 0.5]) / 2
      end
    end

    def partition(pivot, data=@data)
      low  = []
      high = []
      data.each do |i|
        high.push(i) if i > pivot
        low.push(i)  if i < pivot
      end
      return {:low => low, :high => high}
    end

    # First quartile.
    def q1
      @q1 ||= median(partition(median(@data), @data)[:low])
    end

    # Third quartile
    def q3
      @q3 ||= median(partition(median(@data), @data)[:high])
    end

    # Interquartile range, ie the middle 50% of the data.
    def iqr
      @iqr ||= q3 - q1
    end

    # Returns an array of outlying data points.
    def outliers
      @outliers ||= 
        @data.collect do |i|
          i if (i < q1 - (1.5 * iqr) or i > q3 + (1.5 * iqr))
        end.compact
    end

    # Computes arthmetic mean (most common average).
    def mean(data=@data)
      (data.inject(0) {|i,j| i += j}) / data.size
    end

    # Computes mode and a histogram.
    def mode
      @hist     ||= {}
      @max_freq ||= 0
      @mode     ||= nil
      unless @mode
        @data.each do |val|
          @hist[val] ||= 0
          @hist[val] += 1
          @max_freq, @mode = @hist[val], val if @hist[val] > @max_freq
         end
      end
      @mode
    end

    # Computes variance. Used to measure degree of spread 
    # in dataset.
    def variance
      @variance ||= 
        @data.inject(0) { |i,j| i += (j - mean(@data)) ** 2}  / (@data.size)
    end

    # Standard deviation. Square root of variance, measure of the
    # spread of the data about the mean.
    def std_dev
      @std_dev ||= Math.sqrt(variance)
    end

    # Geometric mean. Only applies to non-negative numbers, and
    # relates to log-normal distribution.
    def geometric_mean
      @geoeteric_mean ||= 
        (@data.inject(1) {|i,j| i *= j})**(1.0/@data.size)
    end

    # Harmonic or subcontrary mean. Tends strongly toward the least
    # elements of the dataset.
    def harmonic_mean
      @harmonic_mean ||=
         @data.size.to_f / (@data.inject(0) {|i,j| i += (1.0/j)})
    end

    # Return a string with statisical info about a dataset.
    def to_s
      s = ""
      s += "%.3f " % data.min
      s += "%.3f " % q1
      s += "%.3f " % median
      s += "%.3f " % q3
      s += "%.3f " % data.max
      s += "%.3f " % mean
      s += "%.3f " % variance
      s += "%.3f " % std_dev
      s
    end
  end  
end