仅获取满足numpy数组中条件的那些值 [英] Getting only those values that fulfill a condition in a numpy array

问题描述

必须有一种(非常)快速有效的方法来从numpy数组中获取元素，或者更有趣的是从它的切片中获取元素. 假设我有一个numpy数组:

There must a be a (very) quick and efficient way to get only elements from a numpy array, or even more interestingly from a slice of it. Suppose I have a numpy array:

import numpy as np
a = np.arange(-10,10)

现在，如果我有一个列表:

Now if I have a list:

s = [9, 12, 13, 14]

我可以从以下元素中选择元素:

I can select elements from a:

a[s]  #array([-1,  2,  3,  4])

如何从满足条件的a [s]元素中构成一个(numpy)数组，即是正数(或负数)? 结果应该

How can I have an (numpy) array made of the elements from a[s] that fulfill a condition, i.e. are positive (or negative)? It should result

np.ifcondition(a[s]>0, a[s])  #array([2,  3,  4])

它看起来微不足道，但我无法找到一个简单而简洁的表达方式.我敢肯定，口罩可以，但是对我来说看起来并不是很直接. 但是，都没有:

It looks trivial but I was not able to find a simple and condensed expression. I'm sure masks do but it's doesn't look really direct to me. However, neither:

a[a[s]>0]
a[s[a[s]>0]]

实际上是不错的选择.

推荐答案

怎么样:

In [19]: b = a[s]

In [20]: b[b > 0]
Out[20]: array([2, 3, 4])

这篇关于仅获取满足numpy数组中条件的那些值的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！