Reputation:
I have a numpy array, a
:
a = np.array([[-21.78878256, 97.37484004, -11.54228119],
[ -5.72592375, 99.04189958, 3.22814204],
[-19.80795922, 95.99377136, -10.64537733]])
I have another array, b
:
b = np.array([[ 54.64642121, 64.5172014, 44.39991983],
[ 9.62420892, 95.14361441, 0.67014312],
[ 49.55036427, 66.25136632, 40.38778238]])
I want to extract minimum value indices from the array, b
.
ixs = [[2],
[2],
[2]]
Then, want to extract elements from the array, a
using the indices, ixs
:
The expected answer is:
result = [[-11.54228119]
[3.22814204]
[-10.64537733]]
I tried as:
ixs = np.argmin(b, axis=1)
print ixs
[2,2,2]
result = np.take(a, ixs)
print result
Nope!
Any ideas are welcomed
Upvotes: 0
Views: 93
Reputation: 347
You can try using below code
np.take(a, ixs, axis = 1)[:,0]
The initial section will create a 3 by 3 array and slice the first column
>>> np.take(a, ixs, axis = 1)
array([[-11.54228119, -11.54228119, -11.54228119],
[ 3.22814204, 3.22814204, 3.22814204],
[-10.64537733, -10.64537733, -10.64537733]])
Upvotes: 0
Reputation: 16440
You can use
result = a[np.arange(a.shape[0]), ixs]
np.arange
will generate indices for each row and ixs
will have indices for each column. So effectively result will have required result.
Upvotes: 1