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 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
gfg = hermefit(x, y, deg)
print (gfg)
|
Output :
[6.52513495e-15 -1.00000000e+00 3.34430164e-15 -4.02985428e-16]
Example #2 :
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
gfg = hermefit(x, y, deg)
print (gfg)
|
Output :
[-1.00370716e-15 9.09090909e-02 -5.85610278e-19]
Share your thoughts in the comments
Please Login to comment...