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numpynumpy-ndarrayarray-broadcastingawkward-array
Nico
Nico

Reputation: 11

Awkward Array broadcasting and linear indexing, reshaping an Awkward Array

I'm trying to use numpy-like syntax on an awkward.Array with variable sizes in the second dimension, but it's still confusing..

In numpy i have

normals.shape # (N,3)
idcs.shape    # (m,k)
normals[idcs].shape # (m,k,3)

So the entries of the idcs 2d-array are obviously used as indices for the first dimension of my normals 2d-array and keep that shape.

If I try the same with an awkward.Array, it won't perform that numpy-trick of 'linear-indexing' or 'broadcasting' (whatever you may call it)

# awkward.Arrays here:
normals # N * 3 
idcs    # m * var <- variable sizes in second dimension
normals[idcs] # ERROR
# what I expected instead:
normals[idcs] # m * var * 3

EDIT: what I also thought about, is to reshape idcs to one long index vector, use it to index the normals 2d-array like normals[idcs_vector] and then reshape the result back to m * var * 3 by something like normals[idcs_vector].reshape((m,-1,3)), but since awkward hasn't implemented a reshape function, this is not easy

Upvotes: 1

Views: 83

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