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bundles / scipy 1.18.0 / scipy / sparse / _construct / rand

function

scipy.sparse._construct:rand

source: /scipy/sparse/_construct.py:1784

Signature

def rand(m, n, density = 0.01, format = coo, dtype = None, rng = None, *, random_state = None)

Summary

Generate a sparse matrix of the given shape and density with uniformly distributed values.

Extended Summary

Parameters

m, n : int

shape of the matrix

density : real, optional

density of the generated matrix: density equal to one means a full matrix, density of 0 means a matrix with no non-zero items.

format : str, optional

sparse matrix format.

dtype : dtype, optional

type of the returned matrix values.

rng : {None, int, `numpy.random.Generator`}, optional

If rng is passed by keyword, types other than numpy.random.Generator are passed to numpy.random.default_rng to instantiate a Generator. If rng is already a Generator instance, then the provided instance is used. Specify rng for repeatable function behavior.

If this argument is passed by position or random_state is passed by keyword, legacy behavior for the argument random_state applies:

  • If random_state is None (or numpy.random), the numpy.random.RandomState singleton is used.

  • If random_state is an int, a new RandomState instance is used, seeded with random_state.

  • If random_state is already a Generator or RandomState instance then that instance is used.

Returns

res : sparse matrix

Random sparse matrix.

Notes

Only float types are supported for now.

Examples

from scipy.sparse import rand
matrix = rand(3, 4, density=0.25, format="csr", rng=42)
✓
matrix
matrix.toarray()
✗
array([[0.094, 0.   , 0.   , 0.   ],
       [0.   , 0.   , 0.697, 0.   ],
       [0.   , 0.   , 0.976, 0.   ]])

See also

random

Similar function allowing a custom random data sampler

random_array

Similar to random() but returns a sparse array

Aliases

  • scipy.sparse.rand

Referenced by

This package