根据阈值将NumPy数组转换为0或1 [英] Convert NumPy array to 0 or 1 based on threshold

问题描述

我在下面有一个数组:

a=np.array([0.1, 0.2, 0.3, 0.7, 0.8, 0.9])

我想要的是基于阈值将此向量转换为二进制向量. 以threshold = 0.5为例，大于0.5的元素转换为1，否则为0.
输出向量应如下所示:

What I want is to convert this vector to a binary vector based on a threshold. take threshold=0.5 as an example, element that greater than 0.5 convert to 1, otherwise 0.
The output vector should like this:

a_output = [0, 0, 0, 1, 1, 1]

我该怎么做?

推荐答案

np.where

np.where(a > 0.5, 1, 0)
# array([0, 0, 0, 1, 1, 1])

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使用astype

的布尔取暖

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Boolean basking with astype

(a > .5).astype(int)
# array([0, 0, 0, 1, 1, 1])

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np.select

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np.select

np.select([a <= .5, a>.5], [np.zeros_like(a), np.ones_like(a)])
# array([ 0.,  0.,  0.,  1.,  1.,  1.])

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特殊情况:np.round

如果您的数组值是介于0和1之间的浮动值并且您的阈值为0.5，则这是最佳解决方案.

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Special case: np.round

This is the best solution if your array values are floating values between 0 and 1 and your threshold is 0.5.

a.round()
# array([0., 0., 0., 1., 1., 1.])

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