Did I find the right examples for you? yes no

# numpy.polynomial.hermite.hermval2d

All Samples(6)  |  Call(6)  |  Derive(0)  |  Import(0)
Evaluate a 2-D Hermite series at points (x, y).

This function returns the values:

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

The parameters x and y 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
and y or their elements must support multiplication and addition both(more...)


        def hermval2d(x, y, c):
"""
Evaluate a 2-D Hermite series at points (x, y).

This function returns the values:

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

The parameters x and y 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
and y or their elements must support multiplication and addition both
with themselves and with the elements of c.

If c is a 1-D array a one is implicitly appended to its shape to make
it 2-D. The shape of the result will be c.shape[2:] + x.shape.

Parameters
----------
x, y : array_like, compatible objects
The two dimensional series is evaluated at the points (x, y),
where x and y must have the same shape. If x or y 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 is contained in c[i,j]. If c has
dimension greater than two the remaining indices enumerate multiple
sets of coefficients.

Returns
-------
values : ndarray, compatible object
The values of the two dimensional polynomial at points formed with
pairs of corresponding values from x and y.

--------
hermval, hermgrid2d, hermval3d, hermgrid3d

Notes
-----

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

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


        #test values
tgt = y1*y2
res = herm.hermval2d(x1, x2, self.c2d)
assert_almost_equal(res, tgt)

#test shape
z = np.ones((2,3))
res = herm.hermval2d(z, z, self.c2d)

        c = np.random.random((2, 3))
van = herm.hermvander2d(x1, x2, [1, 2])
tgt = herm.hermval2d(x1, x2, c)
res = np.dot(van, c.flat)
assert_almost_equal(res, tgt)


        #test values
tgt = y1*y2
res = herm.hermval2d(x1, x2, self.c2d)
assert_almost_equal(res, tgt)

#test shape
z = np.ones((2, 3))
res = herm.hermval2d(z, z, self.c2d)

        c = np.random.random((2, 3))
van = herm.hermvander2d(x1, x2, [1, 2])
tgt = herm.hermval2d(x1, x2, c)
res = np.dot(van, c.flat)
assert_almost_equal(res, tgt)