np.random.rand()用法

numpy.random.rand

numpy.random.rand(d0, d1, …, dn)

Random values in a given shape.(指定类型的)

Create an array of the given shape and populate it with random samples from a uniform distribution over [0, 1).(创建一个给定类型的数组，将其填充在一个均匀分布的随机样本[0, 1)中)

Parameters:	d0, d1, …, dn : int, optional The dimensions of the returned array, should all be positive. If no argument is given a single Python float is returned.(返回数组的尺寸，都应该是正的。如果没有给定一个单一的类型，将要返回float)
Returns:	out : ndarray, shape (d0, d1, …, dn) Random values.

See also

random

Notes

This is a convenience function. If you want an interface that takes a shape-tuple as the first argument, refer to np.random.random_sample .

Examples

>>>

>>> np.random.rand(3,2)
array([[ 0.14022471,  0.96360618],  #random
       [ 0.37601032,  0.25528411],  #random
       [ 0.49313049,  0.94909878]]) #random

numpy.random.rand

numpy.random.rand(d0, d1, …, dn)

Random values in a given shape.(指定类型的)

Create an array of the given shape and populate it with random samples from a uniform distribution over [0, 1).(创建一个给定类型的数组，将其填充在一个均匀分布的随机样本[0, 1)中)

Parameters:	d0, d1, …, dn : int, optional The dimensions of the returned array, should all be positive. If no argument is given a single Python float is returned.(返回数组的尺寸，都应该是正的。如果没有给定一个单一的类型，将要返回float)
Returns:	out : ndarray, shape (d0, d1, …, dn) Random values.

See also

random

Notes

This is a convenience function. If you want an interface that takes a shape-tuple as the first argument, refer to np.random.random_sample .

Examples

>>>

>>> np.random.rand(3,2)
array([[ 0.14022471,  0.96360618],  #random
       [ 0.37601032,  0.25528411],  #random
       [ 0.49313049,  0.94909878]]) #random