[FIXED] return indices from filtered, sorted array with numpy

Issue

What is the most straightforward way to do the following in python/numpy?

• begin with random array x
• filter out elements x < .5
• sort the remaining values by size
• return indices of (original) x corresponding to these values

Solution

One solution:

• created sorted index array (argsort)
• create mask for sorted x less than threshold
• apply mask to sorted index array

example:

import numpy as np

# x = np.random.rand(4)
x = np.array([0.96924269, 0.30592608, 0.03338015, 0.64815553])
solution = np.array([2, 1])

sorted_idx = np.argsort(x)
idx_mask = (x[sorted_idx] < 0.5)
sorted_filtered_idx = sorted_idx[idx_mask]

assert np.all(sorted_filtered_idx == solution)

Answered By - anon01