Python中的 numpy.zeros_like()

这个 numpy 方法返回一个给定形状和类型的数组作为给定数组，带有零。

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

参数 ：

array : array_like input
subok  : [optional, boolean]If true, then newly created array will be sub-class of array; 
                 otherwise, a base-class array
order  : C_contiguous or F_contiguous
         C-contiguous order in memory(last index varies the fastest)
         C order means that operating row-rise on the array will be slightly quicker
         FORTRAN-contiguous order in memory (first index varies the fastest).
         F order means that column-wise operations will be faster. 
dtype  : [optional, float(byDefault)] Data type of returned array.  

返回：

ndarray of zeros having given shape, order and datatype.

代码 1：

Python

# 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]

代码 2：

Python

# 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.]