Vectorize finding center of sets of points in multidimensional array in Numpy

Question

I've got a multidimensional array that has 1 million sets of 3 points, each point being a coordinate specified by x and y. Calling this array pointVec, what I mean is

np.shape(pointVec) = (1000000,3,2)

I want to find the center of each of the set of 3 points. One obvious way is to iterate through all 1 million sets, finding the center of each set at each iteration. However, I have heard that vectorization is a strong-suit of Numpy's, so I'm trying to adapt it to this problem. Since this problem fits so intuitively with iteration, I don't have a grasp of how one might do it with vectorization, or if using vectorization would even be useful.

pointVec.mean(axis=1)?

Quang Hoang
– Quang Hoang

2020-09-28 18:06:49 +00:00
Commented Sep 28, 2020 at 18:06 — Quang Hoang
– Quang Hoang, Commented Sep 28, 2020 at 18:06

Ehsan · Accepted Answer · 2020-09-28 18:36:20Z

1

It depends how you define a center of a three-point. However, if it is average coordinates, like @Quang mentioned in the comments, you can take the average along a specific axis in numpy:

pointVec.mean(1)

This will take the mean along axis=1 (which is second axis with 3 points) and return a (1000000,2) shaped array.

answered Sep 28, 2020 at 18:36

Ehsan

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