在 numpy 二维数组中查找元素索引的最有效方法

Question

Out of huge matrix in numpy (currently 1000x1000 ) only a few elements are relevant for me. Say these elements are >1000 in value and others are way lower. I need to find indices of all such elements in the most efficient way because the search will be repeated often and the matrix can become even bigger.

For now I have two different approaches which should be about the same complexity (I omit possible solutions with for as inefficient):

import numpy as np
A = np.zeros((1000,1000))
#do something with the matrix

#first solution with np.where
np.where(A > 999).T
# array([[0, 0],[1, 20]....[785, 445]], dtype=int64) - made up numbers 

#another solution with np.argwhere
np.argwhere(A > 999)
# array([[0, 0],[1, 20]....[785, 445]], dtype=int64) - outputs the same

Is there any possible way to speed up this search or is my solution the most efficient?

Thanks for any advices and suggestion!

Answer 1

You can try this, the filter directly included in the numpy array!

import numpy as np

arr = np.array([998, 999, 1000, 1001])

filter_arr = arr > 999

newarr = arr[filter_arr]

print(filter_arr)
print(newarr) 

https://www.w3schools.com/python/numpy_array_filter.asp