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Module « scipy.sparse »

Fonction rand - module scipy.sparse

Signature de la fonction rand

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

Description

help(scipy.sparse.rand)

    


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

.. warning::

    This function returns a sparse matrix -- not a sparse array.
    You are encouraged to use ``random_array`` to take advantage
    of the sparse array functionality.

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.

    .. versionchanged:: 1.15.0
        As part of the `SPEC-007 <https://scientific-python.org/specs/spec-0007/>`_
        transition from use of `numpy.random.RandomState` to
        `numpy.random.Generator`, this keyword was changed from `random_state` to `rng`.
        For an interim period, both keywords will continue to work, although only one
        may be specified at a time. After the interim period, function calls using the
        `random_state` keyword will emit warnings. The behavior of both `random_state` and
        `rng` are outlined above, but only the `rng` keyword should be used in new code.
        

Returns
-------
res : sparse matrix

See Also
--------

:func:`random`
    Similar function allowing a custom random data sampler
:func:`random_array`
    Similar to random() but returns a sparse array


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
<Compressed Sparse Row sparse matrix of dtype 'float64'
    with 3 stored elements and shape (3, 4)>
>>> matrix.toarray()
array([[0.05641158, 0.        , 0.        , 0.65088847],  # random
       [0.        , 0.        , 0.        , 0.14286682],
       [0.        , 0.        , 0.        , 0.        ]])

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