Dictionary of Keys Format (DOK)

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import numpy as np
import scipy as sp

Dictionary of Keys Format (DOK)#

  • subclass of Python dict

    • keys are (row, column) index tuples (no duplicate entries allowed)

    • values are corresponding non-zero values

  • efficient for constructing sparse arrays incrementally

  • constructor accepts:

    • dense array/matrix

    • sparse array/matrix

    • shape tuple (create empty array)

  • efficient O(1) access to individual elements

  • flexible slicing, changing sparsity structure is efficient

  • can be efficiently converted to a coo_array once constructed

  • slow arithmetic (for loops with dict.items())

  • use:

    • when sparsity pattern is not known apriori or changes

Examples#

Create a DOK array element by element:#

mtx = sp.sparse.dok_array((5, 5), dtype=np.float64)
mtx

<Dictionary Of Keys sparse array of dtype 'float64'
	with 0 stored elements and shape (5, 5)>

for ir in range(5):
    for ic in range(5):
        mtx[ir, ic] = 1.0 * (ir != ic)
mtx

<Dictionary Of Keys sparse array of dtype 'float64'
	with 20 stored elements and shape (5, 5)>

mtx.toarray()

array([[0., 1., 1., 1., 1.],
       [1., 0., 1., 1., 1.],
       [1., 1., 0., 1., 1.],
       [1., 1., 1., 0., 1.],
       [1., 1., 1., 1., 0.]])

Slicing and indexing:#

mtx[1, 1]

np.float64(0.0)

mtx[[1], 1:3]

<Dictionary Of Keys sparse array of dtype 'float64'
	with 1 stored elements and shape (1, 2)>

mtx[[1], 1:3].toarray()

array([[0., 1.]])

mtx[[2, 1], 1:3].toarray()

array([[1., 0.],
       [0., 1.]])
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