scipy.sparse.rand

scipy.sparse.rand(m, n, density=0.01, format='coo', dtype=None, random_state=None)

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

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.

random_state : {numpy.random.RandomState, int}, optional

Random number generator or random seed. If not given, the singleton numpy.random will be used.

Returns:

res : sparse matrix

See also

scipy.sparse.random

Similar function that allows a user-specified random data source.

Notes

Only float types are supported for now.

Examples

>>> from scipy.sparse import rand
>>> matrix = rand(3, 4, density=0.25, format="csr", random_state=42)
>>> matrix
<3x4 sparse matrix of type '<class 'numpy.float64'>'
   with 3 stored elements in Compressed Sparse Row format>
>>> matrix.todense()
matrix([[ 0.        ,  0.59685016,  0.779691  ,  0.        ],
        [ 0.        ,  0.        ,  0.        ,  0.44583275],
        [ 0.        ,  0.        ,  0.        ,  0.        ]])