Python | Numpy np.hermfit() method

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

Syntax : np.hermfit(x, y, deg)
Return : Return the least square fits of hermite series.

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

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

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Output :

[4.00000000e+00 5.00000000e-01 1.56777498e-16]



Example #2 :

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# import numpy and hermfit
import numpy as np
from numpy.polynomial.hermite import hermfit
  
x = np.array([-2, -1, 0, 1, 2])
y = np.array([0.1, 0.2, 0.3, 0.4, 0.5])
deg = 3
  
# using np.hermfit() method
gfg = hermfit(x, y, deg)
  
print(gfg)

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Output :

[ 3.00000000e-01 5.00000000e-02 2.76178300e-18 -1.46465661e-18]

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