python: create numpy array from dictionary, where key is coordinates

Question

I have a dictionary of the following form:

{(2, 2): 387, (1, 2): 25, (0, 1): 15, (2, 1): 12, (2, 6): 5, (6, 2): 5, (4, 2): 4, (3, 4): 4, (5, 2): 2, (0, 2): 1}

where key represents coordinates to the matrix, and value is actual value to be added at the coordinates.

At the moment I create and populate matrix in the following way:

import numpy as np

def build_matrix(data, n):
   M = np.zeros(shape=(n, n), dtype=np.float64)
   for key, val in data.items():
      (row, col) = key
      M[row][col] = val

Is there a way to do it shorter, using numpy'a API? I looked at np.array(), np.asarray() bit none seem to fit my needs.

Divakar · Accepted Answer · 2019-12-09 22:13:20Z

1

The shortest version given n and the input dictionary itself seems to be -

M = np.zeros(shape=(n, n), dtype=np.float64)
M[tuple(zip(*d.keys()))] = list(d.values())

That tuple(zip(*d.keys())) is basically transposing nested items and then packing into tuples as needed for integer-indexing into NumPy arrays. More info on transposing nested items.

Generic case

To handle generic cases, when n is not given and is required to generated based on the extents of the keys alongwith dtype from dictionary values, it would be -

idx_ar = np.array(list(d.keys()))
out_shp = idx_ar.max(0)+1
data = np.array(list(d.values()))
M = np.zeros(shape=out_shp, dtype=data.dtype)
M[tuple(idx_ar.T)] = data

edited Dec 9, 2019 at 22:13

answered Dec 9, 2019 at 21:52

Divakar

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2 Comments

Mark Over a year ago

thanks for feedback. Could you explain the meaning of *list(d.keys() ? So I understand that list() turns its input into a list, given the input is iterative, but what does * do?

Divakar Over a year ago

@Mark Added some comments on it.

Daniel F · Accepted Answer · 2019-12-10 09:17:47Z

0

If you don't mind using scipy, what you've basically created is a sparse dok_matrix (Dictionary of Keys)

from scipy.sparse import dok_matrix

out = dok_matrix((n, n))
out.update(data)
out = out.todense()

answered Dec 10, 2019 at 9:17

Daniel F

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