CODEWITHSUNDEEP
pythonnumpy
A_Arnold
A_Arnold

Reputation: 3999

Find Closest 1D array in 2D numpy

I'm trying to find the best match of a 1D array from a 2D array.

arr1 = np.array([[1, 1, 1], [2, 2, 2]])

arr2 = np.array([1.1, 1.1, 1.1])

how can I get it to return the best match i.e. row 0 preferably as the index of the row?

Upvotes: 0

Views: 114

Answers (1)

Henry Ecker
Henry Ecker

Reputation: 35626

Assuming "closest" means smallest absolute difference to, try something like:

idx = np.abs(arr1 - arr2).sum(axis=1).argmin()  # 0

Absolute difference np.absolute:

np.abs(arr1 - arr2)

[[0.1 0.1 0.1]
 [0.9 0.9 0.9]]

Row-wise total difference sum:

np.abs(arr1 - arr2).sum(axis=1)

[0.3 2.7]

Min-Index argmin:

np.abs(arr1 - arr2).sum(axis=1).argmin()

0

Upvotes: 1

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