polynomial fitting of a signal and plotting the fitted signal-CodePudding

I am trying to use a polynomial expression that would fit my function (signal). I am using numpy.polynomial.polynomial.Polynomial.fit function to fit my function(signal) using the coefficients. Now, after generating the coefficients, I want to put those coefficients back into the polynomial equation - get the corresponding y-values - and plot them on the graph. But I am not getting what I want (orange line) . What am I doing wrong here?

Thanks.

import math
def getYValueFromCoeff(f,coeff_list): # low to high order
    y_plot_values=[]

    for j in range(len(f)):
        item_list= []
        for i in range(len(coeff_list)):
            item= (coeff_list[i])*((f[j])**i)
            item_list.append(item)
        y_plot_values.append(sum(item_list))
    print(len(y_plot_values))
    return y_plot_values

from numpy.polynomial import Polynomial as poly 
import numpy as np
import matplotlib.pyplot as plt     

no_of_coef= 10

#original signal
x = np.linspace(0, 0.01, 10)
period = 0.01
y = np.sin(np.pi * x / period)

#poly fit
test1= poly.fit(x,y,no_of_coef)
coeffs= test1.coef
#print(test1.coef)
coef_y= getYValueFromCoeff(x, test1.coef)
#print(coef_y)

plt.plot(x,y)
plt.plot(x, coef_y)

CodePudding user response：

If you check out the

CodePudding user response：

Here's the simple way of doing it if you didn't know that already...

import math
from numpy.polynomial import Polynomial as poly
import numpy as np
import matplotlib.pyplot as plt

no_of_coef= 10

#original signal
x = np.linspace(0, 0.01, 10)
period = 0.01
y = np.sin(np.pi * x / period)

#poly fit
test1= poly.fit(x,y,no_of_coef)

plt.plot(x, y, 'r', label='original y')
x = np.linspace(0, 0.01, 1000)
plt.plot(x, test1(x), 'b', label='y_fit')
plt.legend()
plt.show()