ProbabilisticModel.py 文件源码

def sample(self, n=1):
        counts = np.random.multinomial(n, self.weights, size=1)
        samples = np.empty((n, len(self.means[0])))

        j = 0
        for i in range(len(self.means)):
            samples[j:j+counts[i]] = stats.multivariate_normal.rvs(mean=self.means[i], cov=self.covs[i], size=counts[i])
            j += counts[i]

        np.shuffle(samples)

        return samples