Update NEU: (DigitalFilterTest.py)

DigitalFilterTest.py hinzugefügt.
Dieses Skript beinhaltet die Differenzengleichung eines Bandpass nach Tobola MEM_C Vorlesung. Außerdem plottet es schnell die Frequenzen um zu testen ob der Filter funktioniert.

TinnitusAnalyse/.idea/workspace.xml

@@ -2,7 +2,6 @@
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       <change beforePath="$PROJECT_DIR$/SoundGenerator.py" beforeDir="false" afterPath="$PROJECT_DIR$/SoundGenerator.py" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/TinnitusDaten.csv" beforeDir="false" afterPath="$PROJECT_DIR$/TinnitusDaten.csv" afterDir="false" />
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@@ -14,11 +13,11 @@
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-      <file pinned="false" current-in-tab="false">
+      <file pinned="false" current-in-tab="true">
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@@ -35,11 +34,11 @@
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-      <file pinned="false" current-in-tab="true">
+      <file pinned="false" current-in-tab="false">
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@@ -50,8 +49,8 @@
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         <entry file="file://$PROJECT_DIR$/../../../DigitalFilter.py">
           <provider selected="true" editor-type-id="text-editor">
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@@ -127,7 +126,7 @@
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@@ -163,7 +162,7 @@
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     </option>
   </component>
-  <component name="RunManager" selected="Python.TinnitusAnalyse_GUI">
+  <component name="RunManager" selected="Python.DigitalFilter (1)">
     <configuration name="DigitalFilter (1)" type="PythonConfigurationType" factoryName="Python" temporary="true">
       <module name="TinnitusAnalyse" />
       <option name="INTERPRETER_OPTIONS" value="" />
@@ -271,8 +270,8 @@
     </configuration>
     <recent_temporary>
       <list>
-        <item itemvalue="Python.TinnitusAnalyse_GUI" />
         <item itemvalue="Python.DigitalFilter (1)" />
+        <item itemvalue="Python.TinnitusAnalyse_GUI" />
         <item itemvalue="Python.SoundGenerator" />
         <item itemvalue="Python.DigitalFilter" />
         <item itemvalue="Python.Noise Experiment" />
@@ -365,30 +364,30 @@
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-    <entry file="file://$PROJECT_DIR$/TinnitusAnalyse_GUI.py">
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-    <entry file="file://$PROJECT_DIR$/SoundGenerator.py">
+    <entry file="file://$PROJECT_DIR$/TinnitusAnalyse_GUI.py">
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TinnitusAnalyse/DigitalFilterTest.py

@@ -0,0 +1,98 @@
+import matplotlib.pyplot as plt  # For plotting
+from math import sin, pi, cos  # For generating input signals
+import numpy as np
+import sys  # For reading command line arguments
+
+
+fs = 44100  # sampling frequency (Abtastfrequenz)
+
+koeff = {
+    "b0": 0,
+    "b1": 0,
+    "b2": 0,
+    "a1": 0,
+    "a2": 0
+}
+
+
+def koeffizienten_berechnen(omega, r):
+    # Koeffizientenberechnung nach Tobola VL S.107 - IIR Filter, 2. Ordnung
+    koeff["b0"] = 1
+    koeff["b1"] = 0
+    koeff["b2"] = -1
+    koeff["a1"] = -2*r*cos(omega)
+    koeff["a2"] = r**2
+
+
+def filter(x):
+    y = [0]*len(x)
+    for k in range(4, len(x)):
+        y[k] = koeff["b0"]*x[k] + koeff["b1"]*x[k-1] + koeff["b2"]*x[k-2] - koeff["a1"]*y[k-1] - koeff["a2"]*y[k-2]
+
+    return y
+
+
+
+
+dauer_ms = 10000  # 10 Sekunden
+num_samples = dauer_ms * (fs / 1000)  # framerate -pro Sekunde- umgerechnet in -pro Millisekunde-
+
+t = np.linspace(0, 10, int(num_samples)) # array zum darstellen der x-Achse
+amp = 1
+
+f_input1 = 1
+f_input2 = 50
+f_input3 = 10
+
+input1 = []
+input2 = []
+input3 = []
+for x in range(int(num_samples)):  # einen einfachen Sinus ins array schreiben
+    input1.append(amp * sin(2 * pi * f_input1 * (x / fs)))
+    input2.append(amp * sin(2 * pi * f_input2 * (x / fs)))
+    #input3.append(amp * sin(2 * pi * f_input3 * (x / fs)))
+
+
+input_ges = np.add(input1, input2) # Sinus aufaddieren um ein halbwegs realistisches Audiosignal zu bekommen
+#input_ges = np.add(input_ges, input3)
+
+#Filterparameter hier einstellen
+fr = 5
+omega = 2*pi*fr/fs
+r = 0.95
+koeffizienten_berechnen(omega, r)   # Koeffizienten berechnen mit Mittelfrequenz 10Hz
+
+output = filter(input_ges)
+
+### Plot the signals for comparison
+plt.figure(1)
+plt.subplot(231)
+plt.ylabel('Amplitude')
+plt.xlabel('t [s]')
+plt.title('f_1=' + str(f_input1) + "Hz")
+plt.plot(t, input1)
+
+plt.subplot(232)
+plt.ylabel('Amplitude')
+plt.xlabel('t [s]')
+plt.title('f_2=' + str(f_input2) + "Hz")
+plt.plot(t, input2)
+
+# plt.subplot(233)
+# plt.ylabel('Amplitude')
+# plt.xlabel('t [s]')
+# plt.title('f_3=' + str(f_input3) + "Hz")
+# plt.plot(t, input3)
+
+plt.subplot(234)
+plt.ylabel('Amplitude')
+plt.xlabel('t [s]')
+plt.title('(input in Filter) f_ges = f_1 + f_2')
+plt.plot(t, input_ges)
+
+plt.subplot(235)
+plt.ylabel('Amplitude')
+plt.xlabel('Samples')
+plt.title('gefiltertes Signal, mit f_r = ' + str(fr) + "Hz und r=" + str(r))
+plt.plot(t, output)
+plt.show()

TinnitusAnalyse/SoundGenerator.py

@@ -74,7 +74,7 @@ class Sound:
         # zuerst muss ein Array mit Audiodaten gefüllt werden
         audio = []
         freq = self.tinnitus.linksFrequenz
-        dauer_ms = 1000.0  # 10 Sekunden
+        dauer_ms = 5000.0  # 10 Sekunden
         amp = self.tinnitus.linksLautstaerke
         rauschen = self.tinnitus.linksRauschenLautstaerke
 

TinnitusAnalyse/TinnitusDaten.csv

@@ -1,10 +1,10 @@
-Vorname;asd
-Nachname;asda
-linke Frequenz;770.0
-linke Lautstärke;0.01
+Vorname;asdas
+Nachname;asdas
+linke Frequenz;0.0
+linke Lautstärke;0.0
 linkes Rauschen;0.0
-rechte Frequenz;1410.0
-rechte Lautstärke;0.03
+rechte Frequenz;0.0
+rechte Lautstärke;0.0
 rechtes Rauschen;0.0
-Kommentar;asd
+Kommentar;asdas