Python中的 numpy.place()

numpy.place()方法根据参数 - 条件和值对数组进行更改（根据用户设置的掩码，使用前 N 个值放入数组中）。它与 numpy.extract() 相反。

句法：

numpy.place(array, mask, vals) 

参数 ：

array : [ndarray] Input array, we need to make changes into
mask  : [array_like]Boolean that must have same size as that of the input array
value : Values to put into the array. Based on the mask condition it adds only N-elements
    to the array. If in case values in val are smaller than the mask, same values get repeated.

返回 ：

Array with change elements i.e. new elements being put

Python

# Python Program illustrating
# numpy.place() method
  
import numpy as geek
  
array = geek.arange(12).reshape(3, 4)
print("Original array : \n", array)
  
# Putting new elements
a = geek.place(array, array > 5, [15, 25, 35])
print("\nPutting up elements to array: \n", array)
 
 
array1 = geek.arange(6).reshape(2, 3)
print("\n\nOriginal array1 : \n", array)
 
# Putting new elements
a = geek.place(array1, array1>2, [44, 55])
print("\nPutting new elements to array1 : \n", array1)

输出 ：

Original array : 
 [[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]

Putting up elements to array: 
 [[ 0  1  2  3]
 [ 4  5 15 25]
 [35 15 25 35]]


Original array1 : 
 [[ 0  1  2  3]
 [ 4  5 15 25]
 [35 15 25 35]]

Putting new elements to array1 : 
 [[ 0  1  2]
 [44 55 44]]

参考 ：
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.place.html#numpy.place
笔记 ：
这些代码不会在在线 IDE 上运行。因此，请在您的系统上运行它们以探索其工作原理。