import numpy as np
from pyfar.dsp import fft
import matplotlib.pyplot as plt
# properties
fft_normalization = "rms"
n_samples = 1024
sampling_rate = 48e3
frequency = 100
times = np.linspace(0, 10, n_samples)
freqs = fft.rfftfreq(n_samples, 48e3)
# generate data
sine = np.sin(times * 2*np.pi * frequency)
spec = fft.rfft(sine, n_samples, sampling_rate, fft_normalization)
# plot time and frequency data
plt.subplot(1, 2, 1)
plt.plot(times, sine)
ax = plt.gca()
ax.set_xlabel('Time in s')
plt.subplot(1, 2, 2)
plt.plot(freqs, np.abs(spec))
ax = plt.gca()
ax.set_xlabel('Frequency in Hz')
plt.show()