给定相同长度的布尔向量，最快的方法来屏蔽2D numpy数组的行？

Question

I have a numpy boolean vector of shape 1 x N, and an 2d array with shape 160 x N. What is a fast way of subsetting the columns of the 2d array such that for each index of the boolean vector that has True in it, the column is kept, and for each index of the boolean vector that has False in it, the column is discarded?

If you call the vector mask and the array features, i've found the following to be far too slow: np.array([f[mask] for f in features])

Is there a better way? I feel like there has to be, right?

Answer 1

You can try this,

    new_array = 2d_array[:,bool_array==True]

So depending on the axes you can select which one you want to remove. In case you get a 1-d array, then you can just reshape it and get the required array. This method will be faster also.