For more information about the examples, such as how the Python and Mojo files interact with each other, see the Examples Overview

BufOnsetsExample

Python Code

import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))

from mmm_python import *
import matplotlib.pyplot as plt
import numpy as np
import librosa

d = {
    "path":"/Users/ted/Documents/_TEACHING/_materials/flucoma/FluCoMa-Pedagogical-Materials-repo/media/Nicol-LoopE-M.wav",
     "thresh":68.0,
     "min_slice_len":0.1,# in seconds
     "window_size":1024,
     "hop_size":512
}
y, sr = librosa.load(d["path"], sr=None)
o = MBufAnalysis.spectral_flux_onsets(d)
print("spectral flux onsets shape:", o.shape)

plt.figure(figsize=(10, 4))
ax = plt.gca()
ax.plot(y, label="Waveform", alpha=1.0)
ax.vlines(o, ymin=y.min(), ymax=y.max(), color='red', label="Spectral Flux Onsets", linestyles="dotted", linewidths=0.5, alpha=0.9)

ax.set_title("Spectral Flux Onsets")
ax.set_xlabel("Sample")
ax.set_ylabel("Amplitude")

lines_1, labels_1 = ax.get_legend_handles_labels()
ax.legend(loc="upper right")

plt.tight_layout()
plt.show()

Mojo Code