# import matplotlib.pyplot as plt
# import numpy as no
# import pandas as pd
# from matplotlib import rcParams

# config = {"font.family":'serif',"font.size":15,"mathtext.fontset":'stix'}
# rcParams.update(config)

# data = pd.readexcel()

# t0 = data.iloc[:,1]
# A0 = data.iloc[:,2]

# t = [], A=[]

# def FFT_Data(x,N)
#     return np.abs(fft(x))/N*2.

# Am = []
# Am = FFT_Data(A,len(n))
import numpy as np
from scipy.fft import fft
import matplotlib.pyplot as plt

# Define the time domain
t = np.linspace(0, 2*np.pi, 200)

# Define the signal (a sine wave with frequency 10 Hz)
f = np.sin(10*t)

# Compute the FFT of the signal
F = fft(f)

# Define the frequency domain
freq = np.fft.fftfreq(len(t), d=t[1]-t[0])

# Plot the signal and its FFT
fig, (ax1, ax2) = plt.subplots(nrows=2, figsize=(8, 6))
ax1.plot(t, f)
ax1.set_xlabel('Time [s]')
ax1.set_ylabel('Amplitude')
ax2.plot(freq, np.abs(F))
ax2.set_xlabel('Frequency [Hz]')
ax2.set_ylabel('Amplitude')
plt.show()