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Python 中的 numpy.ones _ like()

原文:https://www.geeksforgeeks.org/numpy-ones_like-python/

numpy.one_like() 函数返回一个给定形状和类型的数组作为给定数组，带 1。

Syntax: numpy.ones_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-wise 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 ones having given shape, order and datatype.

# Python Programming illustrating
# numpy.ones_like method

import numpy as geek

array = geek.arange(10).reshape(5, 2)
print("Original array : \n", array)

b = geek.ones_like(array, float)
print("\nMatrix b : \n", b)

array = geek.arange(8)
c = geek.ones_like(array)
print("\nMatrix c : \n", c)

输出:

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

Matrix b : 
 [[ 1\.  1.]
 [ 1\.  1.]
 [ 1\.  1.]
 [ 1\.  1.]
 [ 1\.  1.]]

Matrix c : 
 [1 1 1 1 1 1 1 1]

参考文献: https://docs . scipy . org/doc/numpy-dev/reference/generated/numpy . ones _ like . html 注意: 同样，这些代码不会在 online-ID 上运行。请在您的系统上运行它们来探索工作

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