Funktioniert so grob.
Der Filter erhoeht manche Werte, deswegen kann es zu Errors kommen, evtl. muss die gesamte Musik etwas leiser gedreht werden. To Do: - Filter fürs Rauschen - Filterqualitäaet ueberdenken - GUI Benutzerfreundlicher machen: Feedback verbessern, Filterfunktion koennte in einen thread ausgelagert werden, weil sie ziemlich lange dauert bei einem ganzen Song, evtl. mit einer Art Ladebalken
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TinnitusAnalyse/.idea/workspace.xml
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231
TinnitusAnalyse/.idea/workspace.xml
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@ -5,7 +5,7 @@ import numpy as np
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import sys # für Fehlermeldungen
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from scipy import signal
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import csv
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import matplotlib.pyplot as plt
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#import matplotlib.pyplot as plt
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"""---------------------------------------------------------------------------------------------------------------------
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In .wav-Dateien wird der Ton in absoluten Werte eingetragen. Die Standart-framerate ist 44100
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das heißt für jede Sekunde an Ton gibt es 44100 Werte, die die Tonwelle über die Zeit beschreiben
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@ -198,10 +198,6 @@ class Sound:
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rl = rl.split(";")
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rl = float(rl[1])
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print("lf = ", lf)
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print("rf = ", rf)
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print("ll = ", ll)
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print("rl = ", rl)
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# Die Musik filtern
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w0 = float(lf/(self.music_samplerate/2)) # Frequency to remove from a signal. If fs is specified, this is in the same units as fs. By default, it is a normalized scalar that must satisfy 0 < w0 < 1, with w0 = 1 corresponding to half of the sampling frequency.
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@ -213,45 +209,46 @@ class Sound:
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if ll != 0.0:
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print(self.music_data[20000:20010])
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musicLinks = signal.lfilter(b, a , self.music_data[:, 0]) # links
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sd.play(musicLinks, self.music_samplerate)
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sd.wait()
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else:
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musicLinks = self.music_data[:, 0] # ungefiltert, wenn kein Tinnitus angegeben wurde
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print(musicLinks[20000:20010])
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freq, h = signal.freqz(b, a, fs=self.music_samplerate)
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# Plot
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fig, ax = plt.subplots(2, 1, figsize=(8, 6))
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ax[0].plot(freq, 20 * np.log10(abs(h)), color='blue')
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ax[0].set_title("Frequency Response")
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ax[0].set_ylabel("Amplitude (dB)", color='blue')
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ax[0].set_xlim([0, 10000])
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ax[0].set_ylim([-25, 10])
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ax[0].grid()
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ax[1].plot(freq, np.unwrap(np.angle(h)) * 180 / np.pi, color='green')
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ax[1].set_ylabel("Angle (degrees)", color='green')
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ax[1].set_xlabel("Frequency (Hz)")
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ax[1].set_xlim([0, 10000])
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ax[1].set_yticks([-90, -60, -30, 0, 30, 60, 90])
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ax[1].set_ylim([-90, 90])
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ax[1].grid()
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plt.show()
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#Plot
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# freq, h = signal.freqz(b, a, fs=self.music_samplerate)
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# fig, ax = plt.subplots(2, 1, figsize=(8, 6))
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# ax[0].plot(freq, 20 * np.log10(abs(h)), color='blue')
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# ax[0].set_title("Frequency Response")
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# ax[0].set_ylabel("Amplitude (dB)", color='blue')
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# ax[0].set_xlim([0, 10000])
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||||
# ax[0].set_ylim([-25, 10])
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# ax[0].grid()
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||||
# ax[1].plot(freq, np.unwrap(np.angle(h)) * 180 / np.pi, color='green')
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||||
# ax[1].set_ylabel("Angle (degrees)", color='green')
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||||
# ax[1].set_xlabel("Frequency (Hz)")
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||||
# ax[1].set_xlim([0, 10000])
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||||
# ax[1].set_yticks([-90, -60, -30, 0, 30, 60, 90])
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||||
# ax[1].set_ylim([-90, 90])
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||||
# ax[1].grid()
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||||
# plt.show()
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||||
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||||
|
||||
if rl != 0.0:
|
||||
musicRechts = signal.lfilter(b, a, self.music_data[:, 1]) # rechts
|
||||
|
||||
else:
|
||||
musicRechts = self.music_data[:, 1] # ungefiltert, wenn kein Tinnitus angegeben wurde
|
||||
|
||||
|
||||
wav_obj = wave.open("musikTest.wav", "w")
|
||||
|
||||
# Rahmenparameter für die .wav-Datei setzen
|
||||
nframes = len(self.music_data) #Gesamtanzahl der Frames in der Musikdatei
|
||||
wav_obj.setparams((self.nchannels, self.sampwidth, self.music_samplerate, nframes, self.comptype, self.compname))
|
||||
|
||||
print("Maximum musicLinks: ", max(musicLinks))
|
||||
print("Minimum musikLinks: ", min(musicLinks))
|
||||
|
||||
|
||||
self.nframes = len(musicLinks)
|
||||
wav_obj.setparams((self.nchannels, self.sampwidth, self.music_samplerate, self.nframes, self.comptype, self.compname))
|
||||
|
||||
frames = self.music_samplerate * 10
|
||||
# Die Audiosamples schreiben
|
||||
for x in range(frames):
|
||||
for x in range(self.music_samplerate*5): #Kann mit nframes ersetzt werden, für den ganzen Song
|
||||
# Die Audiodaten müssen von float in einen passenden int-Wert umgerechnet werden
|
||||
wav_obj.writeframes(struct.pack('h', int(musicLinks[x] * 32767.0))) # Werte für links und rechts werden bei
|
||||
wav_obj.writeframes(struct.pack('h', int(musicRechts[x] * 32767.0))) # wav abwechselnd eingetragen
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
Vorname;asd
|
||||
Nachname;asd
|
||||
linke Frequenz;950.0
|
||||
linke Frequenz;10000.0
|
||||
linke Lautstärke;0.2
|
||||
linkes Rauschen Lautstärke;0.0
|
||||
linkes Rauschen untere Grenzfrequenz;10.0
|
||||
@ -11,4 +11,3 @@ rechtes Rauschen Lautst
|
||||
rechtes Rauschen untere Grenzfrequenz;10.0
|
||||
rechtes Rauschen obere Grenzfrequenz;20000.0
|
||||
Kommentar;
|
||||
|
||||
|
||||
|
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Reference in New Issue
Block a user