Module « scipy.linalg »

Fonction pinv2 - module scipy.linalg

Signature de la fonction pinv2

def pinv2(a, cond=None, rcond=None, return_rank=False, check_finite=True) 

Description

pinv2.__doc__

    Compute the (Moore-Penrose) pseudo-inverse of a matrix.

    `scipy.linalg.pinv2` is deprecated since SciPy 1.7.0, use
    `scipy.linalg.pinv` instead for better tolerance control.

    Calculate a generalized inverse of a matrix using its
    singular-value decomposition and including all 'large' singular
    values.

    Parameters
    ----------
    a : (M, N) array_like
        Matrix to be pseudo-inverted.
    cond, rcond : float or None
        Cutoff for 'small' singular values; singular values smaller than this
        value are considered as zero. If both are omitted, the default value
        ``max(M,N)*largest_singular_value*eps`` is used where ``eps`` is the
        machine precision value of the datatype of ``a``.

        .. versionchanged:: 1.3.0
            Previously the default cutoff value was just ``eps*f`` where ``f``
            was ``1e3`` for single precision and ``1e6`` for double precision.

    return_rank : bool, optional
        If True, return the effective rank of the matrix.
    check_finite : bool, optional
        Whether to check that the input matrix contains only finite numbers.
        Disabling may give a performance gain, but may result in problems
        (crashes, non-termination) if the inputs do contain infinities or NaNs.

    Returns
    -------
    B : (N, M) ndarray
        The pseudo-inverse of matrix `a`.
    rank : int
        The effective rank of the matrix. Returned if `return_rank` is True.

    Raises
    ------
    LinAlgError
        If SVD computation does not converge.