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Evaluate a 2-D Laguerre series on the Cartesian product of x and y. This function returns the values: .. math:: p(a,b) = \sum_{i,j} c_{i,j} * L_i(a) * L_j(b) where the points `(a, b)` consist of all pairs formed by taking `a` from `x` and `b` from `y`. The resulting points form a grid with `x` in the first dimension and `y` in the second. (more...)

def laggrid2d(x, y, c): """ Evaluate a 2-D Laguerre series on the Cartesian product of x and y. This function returns the values: .. math:: p(a,b) = \sum_{i,j} c_{i,j} * L_i(a) * L_j(b) where the points `(a, b)` consist of all pairs formed by taking `a` from `x` and `b` from `y`. The resulting points form a grid with `x` in the first dimension and `y` in the second. The parameters `x` and `y` are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars. 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` has fewer than two dimensions, ones are implicitly appended to its shape to make it 2-D. The shape of the result will be c.shape[2:] + x.shape + y.shape. Parameters ---------- x, y : array_like, compatible objects The two dimensional series is evaluated at the points in the Cartesian product of `x` and `y`. 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 Chebyshev series at points in the Cartesian product of `x` and `y`. See Also -------- lagval, lagval2d, lagval3d, laggrid3d Notes ----- .. versionadded::1.7.0 """ c = lagval(x, c) c = lagval(y, c) return c

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#test values tgt = np.einsum('i,j->ij', y1, y2) res = lag.laggrid2d(x1, x2, self.c2d) assert_almost_equal(res, tgt) #test shape z = np.ones((2,3)) res = lag.laggrid2d(z, z, self.c2d)

src/n/u/numpy-1.8.1/numpy/polynomial/tests/test_laguerre.py

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#test values tgt = np.einsum('i,j->ij', y1, y2) res = lag.laggrid2d(x1, x2, self.c2d) assert_almost_equal(res, tgt) #test shape z = np.ones((2, 3)) res = lag.laggrid2d(z, z, self.c2d)