Element-wise broadcasting for comparing two NumPy arrays?

Question

Let\'s say I have an array like this:

import numpy as np

base_array = np.array([-13, -9, -11, -3, -3, -4,   2,  2,
                         2,  5,   7,  7,          


        

Answer 1

You can simply add a dimension to the comparison array, so that the comparison is "stretched" across all values along the new dimension.

>>> np.sum(comparison_array[:, None] < base_array)
228

This is the fundamental principle with broadcasting, and works for all kinds of operations.

If you need the sum done along an axis, you just specify the axis along which you want to sum after the comparison.

>>> np.sum(comparison_array[:, None] < base_array, axis=1)
array([15, 15, 14, 14, 13, 13, 13, 13, 13, 12, 10, 10, 10, 10, 10,  7,  7,
        7,  6,  6,  3,  2,  2,  2,  1,  0])