numpy.place(array,mask,vals):根据参数-条件和值在数组中进行更改(根据用户设置的掩码,使用第一个N-values放入数组中)。它与numpy.extract()相反。
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 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]]
参考文献:
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.place.html#numpy.place
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注:本文由纯净天空筛选整理自 numpy.place() in Python。非经特殊声明,原始代码版权归原作者所有,本译文未经允许或授权,请勿转载或复制。