numpy.zeros_like()函数

这个numpy方法返回给定形状和类型的数组，即给定数组，并带有0。

语法:

numpy.zeros_like(array, dtype = None, order = 'K', subok = True)

参数:

array : array_like 输入
subok  : [optional, boolean]如果为真，则新创建的array将是array的子类;否则，为基类数组
order  : C_contiguous 或 F_contiguous
         C-contiguous order in memory(last index varies the fastest)
         C order 意味着对数组进行行上升操作将会稍微快一些
         FORTRAN-contiguous order in memory (first index varies the fastest).
         F order 意味着按列操作将更快。
dtype  : [optional, float(byDefault)] 返回数组的数据类型。

返回值:

一组具有给定形状、顺序和数据类型的零。

示例1

# Python Programming illustrating
# numpy.zeros_like method
 
import numpy as geek
 
array = geek.arange(10).reshape(5, 2)
print("Original array : \n", array)
 
 
b = geek.zeros_like(array, float)
print("\nMatrix b : \n", b)
 
array = geek.arange(8)
c = geek.zeros_like(array)
print("\nMatrix c : \n", c)

输出:

Original array : 
 [[0 1]
 [2 3]
 [4 5]
 [6 7]
 [8 9]]

Matrix b : 
 [[ 0.  0.]
 [ 0.  0.]
 [ 0.  0.]
 [ 0.  0.]
 [ 0.  0.]]

Matrix c : 
 [0 0 0 0 0 0 0 0]

示例2

# Python Programming illustrating
# numpy.zeros_like method
 
import numpy as geek
 
array = geek.arange(10).reshape(5, 2)
print("Original array : \n", array)
 
array = geek.arange(4).reshape(2, 2)
c = geek.zeros_like(array, dtype = 'float')
print("\nMatrix  : \n", c)
 
array = geek.arange(8)
c = geek.zeros_like(array, dtype = 'float', order ='C')
print("\nMatrix  : \n", c)

输出:

Original array : 
 [[0 1]
 [2 3]
 [4 5]
 [6 7]
 [8 9]]

Matrix  : 
 [[ 0.  0.]
 [ 0.  0.]]

Matrix  : 
 [ 0.  0.  0.  0.  0.  0.  0.  0.]