mplhisto.py

import numpy as np
import matplotlib.pyplot as plt
from histogram import Histogram

class MPLHisto(Histogram):
    def draw(self):
        bin_size = (self._b - self._a)*1./self._n_bins
        bins = [self._a + i*bin_size for i in range(len(self._data))]
        plt.hist(bins[:],bins,weights = self._data)
        plt.show()

if __name__ == "__main__":
    h2 = MPLHisto(100,-5,5)
    from random import gauss
    for i in range(int(100000)):
        h2.fill(gauss(0,1))
    h2.draw()