np.laggrid2d() method is used to evaluate a 2-D Laguerre series on the Cartesian product of x and y.
Syntax :
np.laggrid2d(x, y, c)
Parameters:
x, y :[array_like]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] 1-D arrays of Laguerre series coefficients ordered from low to high.Return : [ndarray] The values of the two dimensional Chebyshev series at points in the Cartesian product of x and y.
Code #1 :
# Python program explaining # numpy.laggrid2d() method   # importing numpy as np   import numpy as np from numpy.polynomial.laguerre import laggrid2d   # Input laguerre series coefficients c = np.array([[1, 3, 5], [2, 4, 6]])   # using np.laggrid2d() method ans = laggrid2d([7, 9], [8, 10], c) print(ans) |
Output:
[[ -391. -783.] [ -543. -1087.]]
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Code #2 :
# Python program explaining # numpy.laggrid2d() method   # importing numpy as np import numpy as np from numpy.polynomial.laguerre import laggrid2d   # Input laguerre series coefficients c = np.array([[1, 3, 5], [2, 4, 6]])   # using np.laggrid2d() method ans = laggrid2d(7, 8, c)   print(ans) |
Output:
-391.0
