code: def get_random(self, size=10):
          
          bin_i = np.random.choice(np.arange(len(self.bin_centers)), size=size, p=self.normalized_histogram)
          return self.bin_centers[bin_i] + np.random.uniform(-0.5, 0.5, size=size) * self.bin_volumes()[bin_i]
docs: Returns random variates from the histogram.
          Note this assumes the histogram is an 'events per bin', not a pdf.
          Inside the bins, a uniform distribution is assumed.