Skip to content
Related Articles

Related Articles

Improve Article

Python | Numpy np.laggrid2d() method

  • Last Updated : 29 Dec, 2019

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.]]

 

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

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course




My Personal Notes arrow_drop_up
Recommended Articles
Page :