Speichervorgang schneller + IIR-Notch 5ter Ordnung
Eigentlich müsste jetzt alles so programmiert sein, wie Herr Zwanger es nach dem 11ten Meeting wollte. IIR Filter 5ter Ordnung und der Speichrvorgang ist wesentlich schneller
This commit is contained in:
seyffejn
parent
dda42f6bc4
commit
5278521046
3
TinnitusAnalyse/.idea/dictionaries/Julian.xml
generated
3
TinnitusAnalyse/.idea/dictionaries/Julian.xml
generated
@ -7,6 +7,7 @@
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||||
<w>beide</w>
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||||
<w>beiden</w>
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||||
<w>definieren</w>
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<w>filterordnung</w>
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||||
<w>fontcolor</w>
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||||
<w>frequenz</w>
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<w>kommentar</w>
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@ -21,6 +22,7 @@
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<w>mittelfrequenz</w>
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<w>nachname</w>
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<w>ohren</w>
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<w>passband</w>
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<w>rauschen</w>
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<w>rauschens</w>
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<w>rechtem</w>
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||||
@ -30,6 +32,7 @@
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||||
<w>rechts</w>
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<w>speichere</w>
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||||
<w>speicherversuch</w>
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<w>sperrbereichs</w>
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<w>variablen</w>
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||||
<w>vorname</w>
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||||
<w>zwischen</w>
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||||
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||||
193
TinnitusAnalyse/.idea/workspace.xml
generated
193
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@ -2,16 +2,83 @@
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<option name="RECENT_TEMPLATES">
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<list>
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@ -43,6 +110,10 @@
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<find>StringVar</find>
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<find>Speichern</find>
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<find>csv</find>
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<find>order</find>
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<find>feedback</find>
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<find>musikTest</find>
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<find>Daten er</find>
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</findStrings>
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<dirStrings>
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<dir>C:\Users\Julian\PycharmProjects\TinnitusAnalyse</dir>
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@ -51,6 +122,20 @@
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@ -71,7 +156,19 @@
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<option name="INTERPRETER_OPTIONS" value="" />
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@ -200,6 +297,29 @@
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@ -210,4 +330,73 @@
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BIN
TinnitusAnalyse/MyTinnitusFreeSong.wav
Normal file
BIN
TinnitusAnalyse/MyTinnitusFreeSong.wav
Normal file
Binary file not shown.
@ -5,7 +5,9 @@ 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 time
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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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@ -168,97 +170,140 @@ class Sound:
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return outdata
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def musik_filtern(self):
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""" Die Tinnitus Frequenz aus der Musik Filtern... easy"""
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"""
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Diese Funktion filtert die Tinnitus Frequenz aus einer gewählten Musikdatei. Dabei geht sie in 3 großen
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Schritten vor:
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1. Die nötigen Informationen über den Tinnitus aus der .csv Datei herausholen
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2. Die digitalen Filter erstellen und die Tinnitus Frequenz aus der Audiodatei "herausschneiden"
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3. Die fertigen Audiodatei als .wav Datei speichern
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"""
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# Die Parameter des Tinnitus aus .csv Datei getten
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# ------------1. Die nötigen Informationen über den Tinnitus aus der .csv Datei herausholen---------------------
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csvstring = open("TinnitusDaten.csv").read()
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#print(csvstring)
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x = csvstring.split("\n")
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#print("\nx= ", x)
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tinnitus_data = csvstring.split("\n")
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# linke Frequenz aus csv Datei holen
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lf = x[2]
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lf = tinnitus_data[2]
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lf = lf.split(";")
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lf = float(lf[1])
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# rechte Frequenz aus csv Datei holen
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rf = x[7]
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rf = tinnitus_data[7]
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rf = rf.split(";")
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rf = float(rf[1])
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# linke Lautstärke aus cvs Datei holen
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ll = x[3]
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ll = tinnitus_data[3]
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ll = ll.split(";")
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ll = float(ll[1])
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# rechte Lautstärke aus cvs Datei holen
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rl = x[8]
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rl = tinnitus_data[8]
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rl = rl.split(";")
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rl = float(rl[1])
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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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Q = 30.0 # Quality factor. Dimensionless parameter that characterizes notch filter -3 dB bandwidth bw relative to its center frequency, Q = w0/bw.
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# -------- 2. Die digitalen Filter erstellen und die Tinnitus Frequenz aus der Audiodatei "herausschneiden------
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start_time = time.time() # einen Timer laufen lassen um zu sehen wie lange Filterung dauert
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self.music_data = self.music_data/32767 * 0.8 # convert array from int16 to float
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""" OLD IIR Notch Filter 2nd Order----------------------------------------------------------------------
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w0 = float(lf / (self.music_samplerate / 2)) # Frequency to remove from a signal. If fs is specified, this is
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in the same units as fs. By default, it is a normalized scalar that must satisfy 0 < w0 < 1, with w0 = 1
|
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corresponding to half of the sampling frequency.
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Q = 30.0 # Quality factor. Dimensionless parameter that characterizes notch filter -3 dB bandwidth bw relative
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to its center frequency, Q = w0/bw.
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b, a = signal.iirnotch(lf, Q, fs=self.music_samplerate)
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if ll != 0.0:
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print("Links wird gefiltert...")
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musicLinks = signal.lfilter(b, a , self.music_data[:, 0]) # links
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print("Filtern beendet")
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----------------------------------------------------------------------------------------------------------------
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"""
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""" New IIR Notch Filter 5th order--------------------------------------------------------------------------"""
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# ------------------------------------------LEFT EAR FILTERING-------------------------------------------------
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# Filterparameter festlegen------------
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order = 5 # Filterordnung
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bandwidth = 175 # Bandbreite des Sperrbereichs in Hz
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#stop_attenuation = 100 # minimum Attenuation (Damping, Reduction) in stop Band [only for elliptic filter necessary]
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cutoff_frequencies = [(lf - (bandwidth / 2)),(lf + (bandwidth / 2))] # the cutoff frequencies (lower and upper)
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max_ripple_passband = 50 # Maximal erlaubte Welligkeit im Passbereich
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# -------------------------------------
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if ll != 0.0: # nur wenn die Lautstärke des linken Tinnitus ungleich 0 ist, wird auf diesem Ohr auch gefiltert
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|
||||
b, a = signal.iirfilter(order, cutoff_frequencies, rp=max_ripple_passband, btype='bandstop', ftype='butter',
|
||||
fs=self.music_samplerate) # Diese Funktion erstellt den IIR-Bandpassfilter (links)
|
||||
|
||||
music_links = signal.lfilter(b, a, self.music_data[:, 0]) # diese Funktion filtert die Audiodaten
|
||||
else:
|
||||
musicLinks = self.music_data[:, 0] # ungefiltert, wenn kein Tinnitus angegeben wurde
|
||||
music_links = self.music_data[:, 0] # ungefiltert, wenn kein Tinnitus angegeben wurde
|
||||
|
||||
#Plot
|
||||
# freq, h = signal.freqz(b, a, fs=self.music_samplerate)
|
||||
# fig, ax = plt.subplots(2, 1, figsize=(8, 6))
|
||||
# ax[0].plot(freq, 20 * np.log10(abs(h)), color='blue')
|
||||
# ax[0].set_title("Frequency Response")
|
||||
# ax[0].set_ylabel("Amplitude (dB)", color='blue')
|
||||
# ax[0].set_xlim([0, 10000])
|
||||
# ax[0].set_ylim([-25, 10])
|
||||
# ax[0].grid()
|
||||
# ax[1].plot(freq, np.unwrap(np.angle(h)) * 180 / np.pi, color='green')
|
||||
# ax[1].set_ylabel("Angle (degrees)", color='green')
|
||||
# ax[1].set_xlabel("Frequency (Hz)")
|
||||
# ax[1].set_xlim([0, 10000])
|
||||
# ax[1].set_yticks([-90, -60, -30, 0, 30, 60, 90])
|
||||
# ax[1].set_ylim([-90, 90])
|
||||
# ax[1].grid()
|
||||
# plt.show()
|
||||
# ------------------------------------- RIGHT EAR FILTERING ------------------------------------------------
|
||||
if rl != 0.0: # nur wenn die Lautstärke des rechten Tinnitus ungleich 0 ist, wird auf diesem Ohr auch gefiltert
|
||||
cutoff_frequencies = [(rf - (bandwidth / 2)), (
|
||||
rf + (bandwidth / 2))] # change the cutoff frequencies to the tinnitus of the RIGHT EAR
|
||||
|
||||
b, a = signal.iirnotch(rf, Q, fs=self.music_samplerate)
|
||||
if rl != 0.0:
|
||||
print("Rechts wird gefiltert...")
|
||||
musicRechts = signal.lfilter(b, a, self.music_data[:, 1]) # rechts
|
||||
print("Filtern beendet")
|
||||
b, a = signal.iirfilter(order, cutoff_frequencies, rp=max_ripple_passband, btype='bandstop', ftype='butter',
|
||||
fs=self.music_samplerate) # Diese Funktion erstellt den IIR-Bandpassfilter (rechts)
|
||||
|
||||
music_rechts = signal.lfilter(b, a, self.music_data[:, 1]) # rechts
|
||||
else:
|
||||
musicRechts = self.music_data[:, 1] # ungefiltert, wenn kein Tinnitus angegeben wurde
|
||||
music_rechts = self.music_data[:, 1] # diese Funktion filtert die Audiodaten(die Tinnitusfreq wird entfernt)
|
||||
|
||||
endTimeFiltering = time.time()
|
||||
print("benötigte Zeit zum Filtern rechts Ohr =", endTimeFiltering - start_time, "s")
|
||||
|
||||
wav_obj = wave.open("musikTest.wav", "w")
|
||||
|
||||
# ------------------------- 3. Die fertigen Audiodatei als .wav Datei speichern --------------------------------
|
||||
start_time = time.time()
|
||||
wav_obj = wave.open("MyTinnitusFreeSong.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))
|
||||
"""The values are stored in a temporary list, and when the process is finished, they are joined together into
|
||||
an string which is then sent to the output with the traditional writeframes method."""
|
||||
|
||||
packedMusic = [] # Liste an die wir die einzelnen frames bereits in binär umgewandelt aneinanderreihen
|
||||
|
||||
# Die Audiosamples schreiben
|
||||
print("Musikdatei wird erstellt...")
|
||||
for x in range(self.music_samplerate * 20): #Kann mit nframes ersetzt werden, für den ganzen Song
|
||||
for tinnitus_data in range(self.music_samplerate * 60): #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
|
||||
if x % 10000 == 0:
|
||||
fortschritt = x/(self.music_samplerate*20)*100
|
||||
packedMusic.append(struct.pack('h', int(music_links[tinnitus_data] * 32767.0)))
|
||||
packedMusic.append(struct.pack('h', int(music_rechts[tinnitus_data] * 32767.0)))
|
||||
|
||||
# wav_obj.writeframes(struct.pack('h', int(music_links[x] * 32767.0))) # Werte für links und rechts werden bei
|
||||
# wav_obj.writeframes(struct.pack('h', int(musicRechts[x] * 32767.0))) # wav abwechselnd eingetragen
|
||||
if tinnitus_data % 10000 == 0:
|
||||
fortschritt = tinnitus_data/(self.music_samplerate*20)*100
|
||||
print(" ", round(fortschritt, 1), "%")
|
||||
|
||||
end_time = time.time()
|
||||
print("Zeitaufwand für das packen der einzelnen Samples =", end_time - start_time, "s")
|
||||
|
||||
|
||||
value_str = b"".join(packedMusic)
|
||||
|
||||
start = time.time()
|
||||
wav_obj.writeframes(value_str)
|
||||
end = time.time()
|
||||
print("Zeitaufwand für das schreiben aller Frames in die wav Datei =", end - start, "s")
|
||||
wav_obj.close()
|
||||
|
||||
print("Speichern beendet.")
|
||||
# # Plot (hilfreich für Filterentwurf)
|
||||
# freq, h = signal.freqz(b, a, fs=self.music_samplerate)
|
||||
# fig, ax = plt.subplots(2, 1, figsize=(8, 6))
|
||||
# ax[0].plot(freq, 20 * np.log10(abs(h)), color='blue')
|
||||
# ax[0].set_title("Frequency Response")
|
||||
# ax[0].set_ylabel("Amplitude (dB)", color='blue')
|
||||
# ax[0].set_xlim([0, 10000])
|
||||
# ax[0].set_ylim([-120, 10])
|
||||
# ax[0].grid()
|
||||
# ax[1].plot(freq, np.unwrap(np.angle(h)) * 180 / np.pi, color='green')
|
||||
# ax[1].set_ylabel("Angle (degrees)", color='green')
|
||||
# ax[1].set_xlabel("Frequency (Hz)")
|
||||
# ax[1].set_xlim([0, 10000])
|
||||
# ax[1].set_yticks([-90, -60, -30, 0, 30, 60, 90])
|
||||
# ax[1].set_ylim([-90, 90])
|
||||
# ax[1].grid()
|
||||
# plt.show()
|
||||
|
||||
@ -6,9 +6,6 @@ import sounddevice as sd
|
||||
from scipy.io import wavfile
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
"""--------------------------FUNKTIONEN DIE DURCH GUI KLICKS AUSGEFÜHRT WERDEN---------------------------------------"""
|
||||
"""-------Funktionen links-------------"""
|
||||
|
||||
@ -201,10 +198,15 @@ def unten_button_musikdatei_laden_press():
|
||||
|
||||
def unten_button_filtere_tinnitus_aus_musik():
|
||||
print("button filtere tinnitus aus musik pressed")
|
||||
feedback("Gefilterte Musikdatei erstellt", "blue")
|
||||
sound.musik_filtern()
|
||||
# except:
|
||||
# feedback("Fehlgeschlagener Filterversuch!", "red", "white")
|
||||
try:
|
||||
feedback("Starte Filtervorgang (dies kann einige Minuten dauern)...", "blue")
|
||||
sound.musik_filtern()
|
||||
feedback("Filtervorgang erfolgreich abgeschlossen. \n"
|
||||
"Audiodatei unter dem Namen MyTinnitusFreeSong.wav erstellt", "white", "green")
|
||||
except:
|
||||
feedback("Fehlgeschlagener Filterversuch. Drücke zuerst den Speichern Knopf"
|
||||
"Stelle sicher, dass die Lautstärke mindestens einer Seite über 0"
|
||||
"gestellt ist. Sonst gehen wir davon aus, dass auf diesem Ohr kein Tinnitus vorliegt.", "red", "white")
|
||||
|
||||
|
||||
""" Initialisierungen """
|
||||
|
||||
@ -1,13 +1,14 @@
|
||||
Vorname;asd
|
||||
Nachname;asd
|
||||
linke Frequenz;10000.0
|
||||
linke Lautstärke;0.2
|
||||
linke Frequenz;5040.0
|
||||
linke Lautstärke;0.04
|
||||
linkes Rauschen Lautstärke;0.0
|
||||
linkes Rauschen untere Grenzfrequenz;10.0
|
||||
linkes Rauschen obere Grenzfrequenz;20000.0
|
||||
rechte Frequenz;920.0
|
||||
rechte Lautstärke;0.28
|
||||
rechte Frequenz;5040.0
|
||||
rechte Lautstärke;0.02
|
||||
rechtes Rauschen Lautstärke;0.0
|
||||
rechtes Rauschen untere Grenzfrequenz;10.0
|
||||
rechtes Rauschen obere Grenzfrequenz;20000.0
|
||||
Kommentar;
|
||||
|
||||
|
||||
|
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Reference in New Issue
Block a user