Python numpy.zeros_like()用法及代码示例

numpy.zeros_like(array，dtype = None，order ='K'，subok = True)：将给定形状和类型的数组返回给定数组，并带有零，
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(byDeafult)] Data type of returned array.  

返回值：

ndarray of zeros having given shape, order and datatype.

代码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]

代码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.]

参考文献：
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.zeros_like.html#numpy.zeros_like
注意：
此外，这些代码也无法在online-ID上运行。请在您的系统上运行它们以探索工作原理