Python | Numpy np.hermediv() method

Python | Numpy np.hermefit() method

Last Updated : 11 Dec, 2019

With the help of np.hermefit() method, we can get the least square fit of hermite series by using np.hermefit() method.

Syntax : np.hermefit(x, y, deg)
Return : Return the least square fit of given data.

Example #1 :
In this example we can see that by using np.hermefit() method, we are able to get the least square fit of hermite series by using this method.

# import numpy and hermefit 
import numpy as np 
from numpy.polynomial.hermite_e import hermefit 
  
x = np.array([1, 2, 3, 4]) 
y = np.array([-1, -2, -3, -4]) 
deg = 3
# using np.hermefit() method 
gfg = hermefit(x, y, deg) 
  
print(gfg) 

Output :

[6.52513495e-15 -1.00000000e+00 3.34430164e-15 -4.02985428e-16]

Example #2 :

# import numpy and hermefit 
import numpy as np 
from numpy.polynomial.hermite_e import hermefit 
  
x = np.array([11, 22, 33, 44]) 
y = np.array([1, 2, 3, 4]) 
deg = 2
# using np.hermefit() method 
gfg = hermefit(x, y, deg) 
  
print(gfg) 

Output :

[-1.00370716e-15 9.09090909e-02 -5.85610278e-19]

Python | Numpy np.hermediv() method

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