np.random.rand() Create an array of the given shape and populate it with random samples from a uniform distribution (均匀分布) over [0, 1).Example:>>> np.random.rand(3,2) array([[ 0.14022471, 0.96360618], #random [ 0.37601032, 0.25528411], #random [ 0.49313049, 0.94909878]]) #randomnp.random.randn() Return a sample (or samples) from the “standard normal” distribution(标准正态分布).Notes For random samples from N(\mu, \sigma^2), use: >>> sigma * np.random.randn(…) + muExample: >>> np.random.randn() 2.1923875335537315 #randomTwo-by-four array of samples from N(3, 6.25):>>> 2.5 * np.random.randn(2, 4) + 3 array([[-4.49401501, 4.00950034, -1.81814867, 7.29718677], #random [ 0.39924804, 4.68456316, 4.99394529, 4.84057254]]) #random
