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Evaluate a 2-D Laguerre series at points (x, y). This function returns the values: .. math:: p(x,y) = \sum_{i,j} c_{i,j} * L_i(x) * L_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 lagval2d(x, y, c): """ Evaluate a 2-D Laguerre series at points (x, y). This function returns the values: .. math:: p(x,y) = \\sum_{i,j} c_{i,j} * L_i(x) * L_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`. See Also -------- lagval, laggrid2d, lagval3d, laggrid3d Notes ----- .. versionadded::1.7.0 """ try: x, y = np.array((x, y), copy=0) except: raise ValueError('x, y are incompatible') c = lagval(x, c) c = lagval(y, c, tensor=False) return c

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#test values tgt = y1*y2 res = lag.lagval2d(x1, x2, self.c2d) assert_almost_equal(res, tgt) #test shape z = np.ones((2,3)) res = lag.lagval2d(z, z, self.c2d)

c = np.random.random((2, 3)) van = lag.lagvander2d(x1, x2, [1, 2]) tgt = lag.lagval2d(x1, x2, c) res = np.dot(van, c.flat) assert_almost_equal(res, tgt)

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

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#test values tgt = y1*y2 res = lag.lagval2d(x1, x2, self.c2d) assert_almost_equal(res, tgt) #test shape z = np.ones((2, 3)) res = lag.lagval2d(z, z, self.c2d)

c = np.random.random((2, 3)) van = lag.lagvander2d(x1, x2, [1, 2]) tgt = lag.lagval2d(x1, x2, c) res = np.dot(van, c.flat) assert_almost_equal(res, tgt)