Module « scipy.linalg »

Fonction invpascal - module scipy.linalg

Signature de la fonction invpascal

def invpascal(n, kind='symmetric', exact=True) 

Description

invpascal.__doc__

    Returns the inverse of the n x n Pascal matrix.

    The Pascal matrix is a matrix containing the binomial coefficients as
    its elements.

    Parameters
    ----------
    n : int
        The size of the matrix to create; that is, the result is an n x n
        matrix.
    kind : str, optional
        Must be one of 'symmetric', 'lower', or 'upper'.
        Default is 'symmetric'.
    exact : bool, optional
        If `exact` is True, the result is either an array of type
        ``numpy.int64`` (if `n` <= 35) or an object array of Python integers.
        If `exact` is False, the coefficients in the matrix are computed using
        `scipy.special.comb` with `exact=False`. The result will be a floating
        point array, and for large `n`, the values in the array will not be the
        exact coefficients.

    Returns
    -------
    invp : (n, n) ndarray
        The inverse of the Pascal matrix.

    See Also
    --------
    pascal

    Notes
    -----

    .. versionadded:: 0.16.0

    References
    ----------
    .. [1] "Pascal matrix", https://en.wikipedia.org/wiki/Pascal_matrix
    .. [2] Cohen, A. M., "The inverse of a Pascal matrix", Mathematical
           Gazette, 59(408), pp. 111-112, 1975.

    Examples
    --------
    >>> from scipy.linalg import invpascal, pascal
    >>> invp = invpascal(5)
    >>> invp
    array([[  5, -10,  10,  -5,   1],
           [-10,  30, -35,  19,  -4],
           [ 10, -35,  46, -27,   6],
           [ -5,  19, -27,  17,  -4],
           [  1,  -4,   6,  -4,   1]])

    >>> p = pascal(5)
    >>> p.dot(invp)
    array([[ 1.,  0.,  0.,  0.,  0.],
           [ 0.,  1.,  0.,  0.,  0.],
           [ 0.,  0.,  1.,  0.,  0.],
           [ 0.,  0.,  0.,  1.,  0.],
           [ 0.,  0.,  0.,  0.,  1.]])

    An example of the use of `kind` and `exact`:

    >>> invpascal(5, kind='lower', exact=False)
    array([[ 1., -0.,  0., -0.,  0.],
           [-1.,  1., -0.,  0., -0.],
           [ 1., -2.,  1., -0.,  0.],
           [-1.,  3., -3.,  1., -0.],
           [ 1., -4.,  6., -4.,  1.]])