def reconstruct_p(self):
        n = len(self._cdf)
        p = np.zeros(n)
        p[0] = self._cdf[0]
        p[1:] = (self._cdf[1:] - self._cdf[:-1])
        return p
Return the original probability vector.
dataset/ETHPy150Open ml-slac/deep-jets/utils/sampling.py/MultinomialSampler.reconstruct_p