random¶
-
sparse.
random
(shape, density=0.01, random_state=None, data_rvs=None, format='coo', fill_value=None)[source]¶ Generate a random sparse multidimensional array
Parameters: - shape (Tuple[int]) – Shape of the array
- density (float, optional) – Density of the generated array.
- random_state (Union[numpy.random.RandomState, int], optional) – Random number generator or random seed. If not given, the singleton numpy.random will be used. This random state will be used for sampling the sparsity structure, but not necessarily for sampling the values of the structurally nonzero entries of the matrix.
- data_rvs (Callable) – Data generation callback. Must accept one single parameter: number of
nnz
elements, and return one single NumPy array of exactly that length. - format (str) – The format to return the output array in.
- fill_value (scalar) – The fill value of the output array.
Returns: The generated random matrix.
Return type: See also
scipy.sparse.rand
- Equivalent Scipy function.
numpy.random.rand
- Similar Numpy function.
Examples
>>> from sparse import random >>> from scipy import stats >>> rvs = lambda x: stats.poisson(25, loc=10).rvs(x, random_state=np.random.RandomState(1)) >>> s = random((2, 3, 4), density=0.25, random_state=np.random.RandomState(1), data_rvs=rvs) >>> s.todense() # doctest: +NORMALIZE_WHITESPACE array([[[ 0, 0, 0, 0], [ 0, 34, 0, 0], [33, 34, 0, 29]], <BLANKLINE> [[30, 0, 0, 34], [ 0, 0, 0, 0], [ 0, 0, 0, 0]]])