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Python | Numpy np.laggrid2d() method

Last Updated : 29 Dec, 2019
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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 : Python3
# 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.]]
  Code #2 : Python3
# 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

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