This is a convenience function. If you want an interface that takes a tuple as the first argument, use `numpy.random.standard_normal` instead. 数字区间:(负无穷,正无穷) 分布:标准正态分布 形状:[d0,d1,...,dn] fromnumpyimportrandomprint(random.randn(3,2))'''result [[ 0.0456255 0.64865066...
where \mu is the mean and \sigma the standard deviation. The square of the standard deviation, \sigma^2, is called the variance. The function has its peak at the mean, and its “spread” increases with the standard deviation (the function reaches 0.607 times its maximum at x + \sigma ...
random.ranf() # numpy.random.ranf() is one of the function for doing random sampling in numpy. It returns an array of specified shape # and fills it with random floats in the half-open interval [0.0, 1.0). import numpy as np # output random float value out_val = np.random.ranf()...
numpy中有一些常用的用来产生随机数的函数,randn()和rand()就属于这其中。 numpy.random.randn(d0, d1, …, dn)是从标准正态分布中返回一个或多个样本值。 numpy.random.rand(d0, d1, …, dn)的随机样本位于[0, 1)中。 代码: import numpy as np arr1 = np.random.randn(2,4) print(arr1) pr...
numpy的random模块 随机抽样 (numpy.random)简单的随机数据 rand(d0, d1, ..., dn)随机值 >>> np.random.rand(3,2)array([[ 0.14022471, 0.96360618], #random [ 0.37601032, 0.25528411], #random [ 0.49313049, 0.94909878]]) #random randn(d0, d1, ..., dn)返回⼀个样本，...
Gaussian distribution.muis the mean, andsigmais the standard deviation. This is slightly faster than thenormalvariate()function defined below. [正态分布曲线性质] random.choice(sequence) random.choice从序列中获取一个随机元素。其函数原型为:random.choice(sequence)。参数sequence表示一个有序类型。这里要说...
TrueDisplay the histogram of the samples, along with the probability density function:>>> import matplotlib.pyplot as plt >>> count, bins, ignored = plt.hist(s, 30, normed=True) >>> plt.plot(bins, 1/(sigma * np.sqrt(2 * np.pi)) * ... np.exp...
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 ...
Similar to the function above, but the means are shared among all drawn elements. Parameters mean(float, optional) – the mean for all distributions std(Tensor) – the tensor of per-element standard deviations out(Tensor, optional) – the output tensor. ...
numpy.random.shuffle(x)Modify a sequence in-place by shuffling its contents.Parameters:x : array_like The array or list to be shuffled.Returns:None 举例 python>>> >>> arr = np.arange(10)>>> np.random.shuffle(arr)>>> arr [1 7 5 2 9 4 3 6 0 8]This function only shuffles the...