Python | Numpy np.lagtrim() method

Python | Numpy np.lagfit() method

Last Updated : 23 Jan, 2020

With the help of np.lagfit() method, we can get the least squares fit of laguerre series of a given data by using np.lagfit() method.

Syntax : np.lagfit(x, y, deg)
Return : Return the least squares fit of laguerre series to data.

Example #1 :
In this example we can see that by using np.lagfit() method, we are able to get the least squares fit of laguerre series of a given data.

# import numpy and lagfit 
import numpy as np 
from numpy.polynomial.laguerre import lagfit 
  
x, y = [1, 2], [3, 4] 
deg = 2
  
# import np.lagfit() method 
gfg = lagfit(x, y, deg) 
  
print(gfg) 

Output :

[2.125 -0.125 -1.75]

Example #2 :

# import numpy and lagfit 
import numpy as np 
from numpy.polynomial.laguerre import lagfit 
  
x, y = [1, 2, 3], [3, 4, 5] 
deg = 3
  
# import np.lagfit() method 
gfg = lagfit(x, y, deg) 
  
print(gfg) 

Output :

[3.06722689 -0.66386555 -0.40336134 0.40336134]

Python | Numpy np.lagtrim() method

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