60 lines
1.5 KiB
Python
60 lines
1.5 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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freqs = np.fft.fft(signal)
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# Génération du graphe
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ampl_scale = 1 / np.max(np.absolute(freqs))
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freq_scale = soundbox.samp_rate / len(signal)
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plt.rcParams.update({
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'figure.figsize': (8, 4),
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'font.size': 16,
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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(np.absolute(freqs))
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def freq_format(value, pos):
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return f'{value * freq_scale:.0f} Hz'
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def ampl_format(value, pos):
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return f'{value * ampl_scale:.1f}'
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ax.set_xlabel('Fréquence')
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ax.set_xlim(0 / freq_scale, 800 / freq_scale)
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ax.xaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(freq_format))
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ax.xaxis.set_major_locator(plt.MultipleLocator(100 / freq_scale))
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ax.set_ylabel('Amplitude')
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ax.yaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(ampl_format))
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ax.yaxis.set_major_locator(plt.MultipleLocator(.2 / ampl_scale))
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# Rend le 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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