hpss.py

from __future__ import print_function
import librosa
import numpy as np
import matplotlib.pyplot as plt
import seaborn
import sys
from src import files
seaborn.set(style='ticks')

y, sr = files.load_audio(sys.argv[1])

y_harmonic, y_percussive = librosa.effects.hpss(y)

# What do the spectrograms look like?
# Let's make and display a mel-scaled power (energy-squared) spectrogram
S_harmonic   = librosa.cqt(y, sr=sr)
S_percussive = librosa.cqt(y_percussive, sr=sr)

# Convert to log scale (dB). We'll use the peak power as reference.
log_Sh = librosa.logamplitude(S_harmonic, ref_power=np.max)
log_Sp = librosa.logamplitude(S_percussive, ref_power=np.max)

# Make a new figure
plt.figure(figsize=(12,6))

plt.subplot(2,1,1)
# Display the spectrogram on a mel scale
librosa.display.specshow(log_Sh, sr=sr, y_axis='cqt_hz')

# Put a descriptive title on the plot
plt.title('mel power spectrogram (Harmonic)')

# draw a color bar
plt.colorbar(format='%+02.0f dB')

plt.subplot(2,1,2)
librosa.display.specshow(log_Sp, sr=sr, x_axis='time', y_axis='cqt_hz')

# Put a descriptive title on the plot
plt.title('mel power spectrogram (Percussive)')

# draw a color bar
plt.colorbar(format='%+02.0f dB')

# Make the figure layout compact
plt.tight_layout()
plt.show()