Indexes of elements in NumPy array that satisfy conditions on the value and the index

Question

I have a NumPy array, A. I want to know the indexes of the elements in A equal to a value and which indexes satisfy some condition:

import numpy as np
A = np.array([1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4])

value = 2
ind = np.array([0, 1, 5, 10])  # Index belongs to ind

Here is what I did:

B = np.where(A==value)[0]  # Gives the indexes in A for which value = 2
print(B)

[1 5 9]

mask = np.in1d(B, ind)  # Gives the index values that belong to the ind array
print(mask)
array([ True, True, False], dtype=bool)

print B[mask]  # Is the solution
[1 5]

The solution works, but I find it complicated. Also, in1d does a sort which is slow. Is there a better way of achieving this?

Answer 1

If you flip the operation order around you can do it in one line:

B = ind[A[ind]==value]
print B
[1 5]

Breaking that down:

#subselect first
print A[ind]
[1 2 2 3]

#create a mask for the indices
print A[ind]==value
[False  True  True False]

print ind
[ 0  1  5 10]

print ind[A[ind]==value]
[1 5]

Answer 2

B = np.where(A==value)[0]  #gives the indexes in A for which value = 2
print np.intersect1d(B, ind)
[1 5]