Python | Numpy np.hermefit () method

NumPy | Python Methods and Functions

With the np.hermefit() method we can get the Hermite series least squares method using np.hermefit () .

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

Example # 1:
In this example, we can see that using np.hermefit () we can get the least squares method for the Hermite series using this method.

# NumPy and Hermefit imports

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 the 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:

# NumPy and Hermefit imports

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 the np method. hermefit ()

gfg = hermefit ( x, y, deg)

 

print (gfg)

Output:

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





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