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Evaluate a 3-D Hermite series at points (x, y, z).

This function returns the values:

.. math:: p(x,y,z) = \sum_{i,j,k} c_{i,j,k} * H_i(x) * H_j(y) * H_k(z)

The parameters `x`, `y`, and `z` are converted to arrays only if
they are tuples or a lists, otherwise they are treated as a scalars and
they must have the same shape after conversion. In either case, either
`x`, `y`, and `z` or their elements must support multiplication and(more...)

        def hermval3d(x, y, z, c):
    """
    Evaluate a 3-D Hermite series at points (x, y, z).

    This function returns the values:

    .. math:: p(x,y,z) = \\sum_{i,j,k} c_{i,j,k} * H_i(x) * H_j(y) * H_k(z)

    The parameters `x`, `y`, and `z` are converted to arrays only if
    they are tuples or a lists, otherwise they are treated as a scalars and
    they must have the same shape after conversion. In either case, either
    `x`, `y`, and `z` or their elements must support multiplication and
    addition both with themselves and with the elements of `c`.

    If `c` has fewer than 3 dimensions, ones are implicitly appended to its
    shape to make it 3-D. The shape of the result will be c.shape[3:] +
    x.shape.

    Parameters
    ----------
    x, y, z : array_like, compatible object
        The three dimensional series is evaluated at the points
        `(x, y, z)`, where `x`, `y`, and `z` must have the same shape.  If
        any of `x`, `y`, or `z` is a list or tuple, it is first converted
        to an ndarray, otherwise it is left unchanged and if it isn't an
        ndarray it is  treated as a scalar.
    c : array_like
        Array of coefficients ordered so that the coefficient of the term of
        multi-degree i,j,k is contained in ``c[i,j,k]``. If `c` has dimension
        greater than 3 the remaining indices enumerate multiple sets of
        coefficients.

    Returns
    -------
    values : ndarray, compatible object
        The values of the multidimensional polynomial on points formed with
        triples of corresponding values from `x`, `y`, and `z`.

    See Also
    --------
    hermval, hermval2d, hermgrid2d, hermgrid3d

    Notes
    -----

    .. versionadded::1.7.0

    """
    try:
        x, y, z = np.array((x, y, z), copy=0)
    except:
        raise ValueError('x, y, z are incompatible')

    c = hermval(x, c)
    c = hermval(y, c, tensor=False)
    c = hermval(z, c, tensor=False)
    return c
        


src/n/u/nupic-linux64-HEAD/lib64/python2.6/site-packages/numpy/polynomial/tests/test_hermite.py   nupic-linux64(Download)
        #test values
        tgt = y1*y2*y3
        res = herm.hermval3d(x1, x2, x3, self.c3d)
        assert_almost_equal(res, tgt)
 
        #test shape
        z = np.ones((2,3))
        res = herm.hermval3d(z, z, z, self.c3d)
        c = np.random.random((2, 3, 4))
        van = herm.hermvander3d(x1, x2, x3, [1, 2, 3])
        tgt = herm.hermval3d(x1, x2, x3, c)
        res = np.dot(van, c.flat)
        assert_almost_equal(res, tgt)

src/n/u/numpy-1.8.1/numpy/polynomial/tests/test_hermite.py   numpy(Download)
        #test values
        tgt = y1*y2*y3
        res = herm.hermval3d(x1, x2, x3, self.c3d)
        assert_almost_equal(res, tgt)
 
        #test shape
        z = np.ones((2, 3))
        res = herm.hermval3d(z, z, z, self.c3d)
        c = np.random.random((2, 3, 4))
        van = herm.hermvander3d(x1, x2, x3, [1, 2, 3])
        tgt = herm.hermval3d(x1, x2, x3, c)
        res = np.dot(van, c.flat)
        assert_almost_equal(res, tgt)