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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_random(self, size=10):
 """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. """

        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]