FourierSeries.py

import numpy as np
import matplotlib.pyplot as plt

plt.style.use("ggplot")

# Setup
x_ = np.linspace(-20,20,10000)

T = 8
#for a more accurate wave approximation increase armonics (number of haronics)
armonics = 100

def squareWave(x):
    global T
    lowerBoundLeft = (-T/2)
    lowerBoundRight = 0
    upperBoundLeft = 0
    upperBoundRight = (T/2)
    one = 1
    negativeOne = -1

    while True:
        if (x >= lowerBoundLeft) and (x <= lowerBoundRight):
            return negativeOne
        elif (x >= upperBoundLeft) and (x <= upperBoundRight):
            return one
        else:
            lowerBoundLeft -= T/2
            lowerBoundRight -= T/2
            upperBoundLeft += T/2
            upperBoundRight += T/2
            if one == 1:
                one = -1
                negativeOne = 1
            else:
                one = 1
                negativeOne = -1


# Bn coefficients
def bn(n):
    n = int(n)
    if (n%2 != 0):
        return 4/(np.pi*n)
    else:
        return 0

# Wn
def wn(n):
    global T
    wn = (2*np.pi*n)/T
    return wn

# Fourier Series function
def fourierSeries(n_max,x):
    a0 = 0
    partialSums = a0
    for n in range(1,n_max):
        try:
            partialSums = partialSums + bn(n)*np.sin(wn(n)*x)
        except:
            print("pass")
            pass
    return partialSums


y = []
f = []
for i in x_:
    y.append(squareWave(i))
    f.append(fourierSeries(armonics,i))


plt.plot(x_,y,color="blue",label="Signal")
plt.plot(x_,f,color="red",label="Fourier series approximation")
plt.title("Fourier Series approximation number of armonics: "+str(armonics))
plt.legend()
plt.show()