如何使用Python获取布尔值或两个numpy掩码

Question

Given two numpy array masks, created with the 3rd and 4th columns of data of 7 columns total:

exp_mask = np.repeat(data[:,2]>7., data.shape[1])
loggf_mask = np.repeat(data[:,3]<-7., data.shape[1])

How can I mask data which are masked by either exp_mask or loggf_mask ?

The logic of what I am trying to describe is:

mask = exp_mask or loggf_mask

Answer 1

我相信您正在寻找按位或，即|。

Answer 2

您可以使用np.any（）评估布尔值或掩码：

mask = np.any([exp_mask,loggf_mask],axis=0)

Answer 3

You can use either bitwise_or , which also has the | shorthand, or logical_or . Both will work since your array will be of type bool :

mask = exp_mask | loggf_mask