here's a shortened version of my code:
`dist_array = ssd.cdist(test[y], training)`
test[y] printed is
[ 0.00000000e+00 1.79900000e+01 1.03800000e+01 1.22800000e+02
1.00100000e+03 1.18400000e-01 2.77600000e-01 3.00100000e-01
1.47100000e-01 2.41900000e-01 7.87100000e-02 1.09500000e+00
9.05300000e-01 8.58900000e+00 1.53400000e+02 6.39900000e-03
4.90400000e-02 5.37300000e-02 1.58700000e-02 3.00300000e-02
6.19300000e-03 2.53800000e+01 1.73300000e+01 1.84600000e+02
2.01900000e+03 1.62200000e-01 6.65600000e-01 7.11900000e-01
2.65400000e-01 4.60100000e-01 1.18900000e-01]
training printed (shortened) is:
[[ 0.00000000e+00 1.92100000e+01 1.85700000e+01 ..., 2.09100000e-01
3.53700000e-01 8.29400000e-02]
[ 0.00000000e+00 1.47100000e+01 2.15900000e+01 ..., 1.83400000e-01
3.69800000e-01 1.09400000e-01]
[ 1.00000000e+00 1.30500000e+01 1.93100000e+01 ..., 1.11100000e-02
2.43900000e-01 6.28900000e-02]
...,
[ 0.00000000e+00 1.66000000e+01 2.80800000e+01 ..., 1.41800000e-01
2.21800000e-01 7.82000000e-02]
[ 0.00000000e+00 2.06000000e+01 2.93300000e+01 ..., 2.65000000e-01
4.08700000e-01 1.24000000e-01]
[ 1.00000000e+00 7.76000000e+00 2.45400000e+01 ..., 0.00000000e+00
2.87100000e-01 7.03900000e-02]]
Both have 31 columns. Is there a way to find the distances between array XA and each row of array XB and have the distances outputted into another array?
Thank you very much!
You need to change them into 2-D arrays:
import numpy as np
np.array([1,2,3,4]).shape
--(4,)
np.array([1,2,3,4]).reshape(-1,1).shape
--(4,1)
np.array([1,2,3,4]).reshape(1,-1).shape
--(1,4)
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