Python | Numpy np.hermfit() method
Last Updated :
29 Dec, 2019
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.
import numpy as np
from numpy.polynomial.hermite import hermfit
x = np.array([-3, -2, -1])
y = np.array([1, 2, 3])
deg = 2
gfg = hermfit(x, y, deg)
print(gfg)
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Output :
[4.00000000e+00 5.00000000e-01 1.56777498e-16]
Example #2 :
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
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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