Graphe du FFT en échelle log et style ggplot

analyze-single.py

@@ -17,21 +17,26 @@ output_file = sys.argv[2]
 
 # Calcul du FFT
 signal = soundbox.load_signal(source_file)
-freqs = np.fft.fft(signal)
+freqs = np.fft.fft(signal)[:soundbox.samp_rate // 2]
+values = np.absolute(freqs) / np.max(np.absolute(freqs))
 
 # Génération du graphe
-ampl_scale = 1 / np.max(np.absolute(freqs))
+plt.style.use('ggplot')
-freq_scale = soundbox.samp_rate / len(signal)
-
 plt.rcParams.update({
-    'figure.figsize': (8, 4),
+    'figure.figsize': (10, 5),
     'font.size': 16,
     'font.family': 'Concourse T4',
 })
 
 fig, ax = plt.subplots()
 ax.tick_params(axis='both', which='major', labelsize=12)
-ax.plot(np.absolute(freqs))
+
+remove = values < 0.01
+x = np.arange(len(values))
+ax.plot(x[remove == False], values[remove == False])
+
+# Configuration des axes
+freq_scale = soundbox.samp_rate / len(signal)
 
 
 def freq_format(value, pos):
@@ -39,19 +44,19 @@ def freq_format(value, pos):
 
 
 def ampl_format(value, pos):
-    return f'{value * ampl_scale:.1f}'
+    return f'{value:.1f}'
 
 
-ax.set_xlabel('Fréquence')
+ax.set_xlabel('Fréquence', labelpad=10)
-ax.set_xlim(0 / freq_scale, 800 / freq_scale)
+ax.set_xscale('log', base=2)
 ax.xaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(freq_format))
 ax.xaxis.set_major_locator(plt.MultipleLocator(100 / freq_scale))
 
-ax.set_ylabel('Amplitude')
+ax.set_ylabel('Amplitude relative', labelpad=10)
 ax.yaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(ampl_format))
-ax.yaxis.set_major_locator(plt.MultipleLocator(.2 / ampl_scale))
+ax.yaxis.set_major_locator(plt.MultipleLocator(.2))
 
-# Rend le résultat
+# Rendu du résultat
 if output_file == '-':
     plt.show()
 else: