Finding Given Coordinate Positions in NumPy Array

Question

import numpy as np

ref_cols = [11, 5, 12, 13, 15]
ref_rows = [1, 11, 2, 3, 5]
rows, cols = np.mgrid[1:6, 11:16]
print cols

[[11 12 13 14 15]
 [11 12 13 14 15]
 [11 12 13 14 15]
 [11 12 13 14 15]
 [11 12 13 14 15]]
print rows

[[1 1 1 1 1]
 [2 2 2 2 2]
 [3 3 3 3 3]
 [4 4 4 4 4]
 [5 5 5 5 5]]

I want to get where the given cols and rows (11,1), (5,11), (12,2), (13,3), (15,5) exists. So the expected answer is follows:

[[True, False, False, False, False],
[False, True, False, False, False],
[False, False, True, False, False],
[False, False, False, False, False],
[False, False, False, False, True]]

I tried as:

rows_indices = np.in1d(rows, ref_rows).reshape(rows.shape)
cols_indices = np.in1d(cols, ref_cols).reshape(cols.shape)
answers = (rows_indices & cols_indices)
print answers

But answer is wrong.

How to do it guys?

Answer 1

The reason that your try goes wrong is that you first need to evaluate each pair separately and you cannot evaluate first all rows and columns separately and then combine them in a logical operation.

Here is one way to fix it:

out = np.zeros(rows.shape, dtype=bool)
for r, c in zip(ref_rows, ref_cols):
    out |= (r == rows) & (c == cols)
print out

Answer 2

Probably there exists a more elegent solution but this works for me and is written in an vectorized way ...

import numpy as np

ref_cols = np.array([11, 5, 12, 13, 15])
ref_rows = np.array([1, 11, 2, 3, 5])
rows, cols = np.mgrid[1:6, 11:16]

m = (cols[:,:,None]==ref_cols[None,None,:]) & (rows[:,:,None]==ref_rows[None,None,:])

answer = np.any(m,axis=2)
#array([[ True, False, False, False, False],
#       [False,  True, False, False, False],
#       [False, False,  True, False, False],
#       [False, False, False, False, False],
#       [False, False, False, False,  True]], dtype=bool)