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File Content: _procrustes.cpython-35.pyc

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Solve the orthogonal Procrustes problem.

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    Compute the matrix solution of the orthogonal Procrustes problem.

Given matrices A and B of equal shape, find an orthogonal matrix R
    that most closely maps A to B [1]_.
    Note that unlike higher level Procrustes analyses of spatial data,
    this function only uses orthogonal transformations like rotations
    and reflections, and it does not use scaling or translation.

Parameters
    ----------
    A : (M, N) array_like
        Matrix to be mapped.
    B : (M, N) array_like
        Target matrix.
    check_finite : bool, optional
        Whether to check that the input matrices contain 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
    -------
    R : (N, N) ndarray
        The matrix solution of the orthogonal Procrustes problem.
        Minimizes the Frobenius norm of dot(A, R) - B, subject to
        dot(R.T, R) == I.
    scale : float
        Sum of the singular values of ``dot(A.T, B)``.

Raises
    ------
    ValueError
        If the input arrays are incompatibly shaped.
        This may also be raised if matrix A or B contains an inf or nan
        and check_finite is True, or if the matrix product AB contains
        an inf or nan.

Notes
    -----
    .. versionadded:: 0.15.0

References
    ----------
    .. [1] Peter H. Schonemann, "A generalized solution of the orthogonal
           Procrustes problem", Psychometrica -- Vol. 31, No. 1, March, 1996.

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__init__.cpython-35.opt-1.pyc

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