Sample Post - Jupyter Notebook embedding

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This post is for test purposes. It presents a sample jupyter notebook to test jupyter embedding in jekyll. The pipeline followed loads a wav file, plots it, calculates its fft transform and plots its FFT magnitude as well.

#import libraries
%matplotlib inline
import soundfile as sf
import librosa
import matplotlib.pyplot as plt
import numpy as np

#Load wav
filename = "./chainsaw-01.wav"
Sin, Sr = sf.read(filename)
#convert stereo to mono
Sin = np.mean(Sin, axis=1)
print(f"Signal array: \n{Sin}\n\nSignal Sampling Rate: {Sr}")

plt.plot(Sin)
plt.title("Signal")
plt.show()

Signal array: 
[ 3.05175781e-05 -1.52587891e-05  0.00000000e+00 ...  3.05175781e-05
 -1.52587891e-05  0.00000000e+00]

Signal Sampling Rate: 48000

N=1024

fft = librosa.stft(Sin, n_fft=N)
magnitude = np.abs(fft[:N//2])

plt.plot(magnitude)
plt.title("FFT magnitude")

plt.show()