I have two sorted arrays h and M:
h = np.array(['blue', 'red', 'white'])
M = np.array(['blue', 'green', 'orange', 'red', 'white'])
and would like to find the indices at which each element of h appears in M
Can I np.where for this?
Also, it can be the case that an element of h might not appear in M and in this case, I don't require the index for it. The elements do not repeat.
This is another way and is a one-liner that will return an ndarray of the indices of the matches.
np.nonzero(np.in1d(M, h))[0]
Output
array([0, 3, 4])
Simple for loop should do:
for value in h:
print(np.where(M==value))
Or
print(np.where([M==value for value in h]))
Here is how:
import numpy as np
h = np.array(['blue', 'red', 'white'])
M = np.array(['blue', 'green', 'orange', 'red', 'white'])
i = np.where([h == i for i in M])
print(i[0])
Output:
[0 3 4]
If you are looking for the indices I would use Python's built-in enumerate function. Like this:
indices = []
for ind, val in enumerate(M):
if val in h:
indices.append(ind)
Taking advantage of M and h being sorted:
h = np.array(['blue', 'red', 'white'])
M = np.array(['blue', 'green', 'orange', 'red', 'white'])
# find indices
idx = M.searchsorted(h)
# avoid index error if last entry of h is larger than last of M
idx = idx[:idx.searchsorted(len(M))]
# filter out unmatched elements
idx[M[idx]==h]
# array([0, 3, 4])
