66 lines
1.9 KiB
Python
66 lines
1.9 KiB
Python
import soundbox
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import numpy as np
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import matplotlib
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import matplotlib.pyplot as plt
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import sys
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if len(sys.argv) != 3:
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print(f"""Utilisation: {sys.argv[0]} [source] [output]
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Affiche la transformée de Fourier du fichier [source] sur un graphe
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dans le fichier [output]. Passer - comme [output] fait s’afficher le
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graphe dans une fenêtre.""")
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sys.exit(1)
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source_file = sys.argv[1]
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output_file = sys.argv[2]
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# Calcul du FFT
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signal = soundbox.load_signal(source_file)
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freq_scale = soundbox.samp_rate / len(signal)
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vecs = np.fft.fft(signal)[:soundbox.samp_rate // 2]
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values = np.absolute(vecs) / np.max(np.absolute(vecs))
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freq = np.arange(len(values))
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# Calcul de la fenêtre des fréquences intéressantes
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high_enough = np.where(values >= 0.01)
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left = high_enough[0][0]
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right = high_enough[0][-1]
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freq = freq[left:right]
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values = values[left:right]
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# Génération du graphe
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plt.rcParams.update({
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'figure.figsize': (10, 5),
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'font.size': 18,
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'font.family': 'Concourse T4',
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})
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fig, ax = plt.subplots()
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ax.tick_params(axis='both', which='major', labelsize=12)
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ax.plot(freq, values)
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ax.grid(alpha=.3)
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# Configuration des axes
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ax.set_xlabel('Fréquence', labelpad=10)
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ax.set_xscale('log', base=2)
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ax.xaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(lambda x, pos: f'{x * freq_scale:.0f} Hz'))
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ax.xaxis.set_major_locator(matplotlib.ticker.MultipleLocator(100 / freq_scale))
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ax.xaxis.set_minor_formatter(matplotlib.ticker.NullFormatter())
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ax.xaxis.set_minor_locator(matplotlib.ticker.MultipleLocator(10 / freq_scale))
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ax.set_ylabel('Amplitude relative', labelpad=10)
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ax.yaxis.set_major_formatter(matplotlib.ticker.StrMethodFormatter('{x:.1f}'))
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ax.yaxis.set_major_locator(matplotlib.ticker.MultipleLocator(.2))
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ax.yaxis.set_minor_formatter(matplotlib.ticker.NullFormatter())
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ax.yaxis.set_minor_locator(matplotlib.ticker.MultipleLocator(.05))
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# Rendu du résultat
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if output_file == '-':
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plt.show()
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else:
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plt.tight_layout()
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plt.savefig(output_file)
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