Signal Processing with Python GUI: Part 4

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See Part 1    See Part 2   See Part 3

Tutorial Steps To Create GUI For Noisy Signal
Populate cbFiltering widget with two more items by double clicking on the widget as shown in figure below.

Then modify show_filtering() function to apply filtering based on what user choose in cbFiltering widget as follows:

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def show_filtering(self): strCB = self.cbFiltering.currentText() if strCB == 'Butterworth Highpass': self.butter_filter('hp') if strCB == 'Butterworth Lowpass': self.butter_filter('lp') if strCB == 'Chebyshev Highpass': self.cheby_filter('hp') if strCB == 'Chebyshev Lowpass': self.cheby_filter('lp') if strCB == 'Elliptic Highpass': self.ellip_filter('hp') if strCB == 'Elliptic Lowpass': self.ellip_filter('lp')

Define cheby_filter() and ellip_filter() functions to apply chebyshev and elliptic filtering on input signal as follows:

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def cheby_filter(self, param): global y fsampling=1000 x_start = float(self.leXStart.text()) x_end = float(self.leXEnd.text()) t = linspace(x_start, x_end, len(y)) pass_band = float(self.lePassBand.text()) stop_band = float(self.leStopBand.text()) #Butterworth filtering sos = signal.cheby1(stop_band, pass_band, 15, param, \ fs=fsampling, output='sos') filtered = signal.sosfilt(sos, y) self.widgetOutput.canvas.axis1.clear() self.widgetOutput.canvas.axis1.plot(t, filtered) self.widgetOutput.canvas.axis1.set_ylabel("$h$",fontsize=22) self.widgetOutput.canvas.axis1.set_xlabel("$sec$",fontsize=22) self.widgetOutput.canvas.axis1.set_title('Chebyshev Filtered Signal') self.widgetOutput.canvas.axis1.set_facecolor('lightblue') self.widgetOutput.canvas.axis1.grid() self.widgetOutput.canvas.draw() self.show_fft(filtered,self.widgetFFTAbsFiltered, \ self.widgetFFTLogFiltered)

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def ellip_filter(self, param): global y fsampling=1000 x_start = float(self.leXStart.text()) x_end = float(self.leXEnd.text()) t = linspace(x_start, x_end, len(y)) pass_band = float(self.lePassBand.text()) stop_band = float(self.leStopBand.text()) #Butterworth filtering sos = signal.ellip(8, 1, 100, stop_band, \ param, fs=1000, output='sos') filtered = signal.sosfilt(sos, y) self.widgetOutput.canvas.axis1.clear() self.widgetOutput.canvas.axis1.plot(t, filtered) self.widgetOutput.canvas.axis1.set_ylabel("$h$",fontsize=22) self.widgetOutput.canvas.axis1.set_xlabel("$sec$",fontsize=22) self.widgetOutput.canvas.axis1.set_title('Chebyshev Filtered Signal') self.widgetOutput.canvas.axis1.set_facecolor('lightblue') self.widgetOutput.canvas.axis1.grid() self.widgetOutput.canvas.draw() self.show_fft(filtered,self.widgetFFTAbsFiltered, \ self.widgetFFTLogFiltered)

Run main_fft2.py. Select one of signals and choose Noise radio button. Then, choose Chebyshev Lowpass from cbFiltering widget. The result is shown in figure below.

Then, choose Elliptic Highpass from cbFiltering widget. The result is shown in figure below.

Tutorial Steps To Create GUI For Wav Signal Filtering
At this point, you will open wav files and use it as signal samples to be filtered. In gui_fft.ui, Add one Push Button widget and set its objectName property to pbOpbenFile and set its text property to Open File.

Then, add three Label widgets on the form and set their text properties to x start, x end and File Name.

Next, add three Line Edit widgets and set their objectName properties to leXStartFile, leXEndFile, and leFileName. The newly modified version of gui_fft.ui is shown in figure below.

Next, add three Line Edit widgets and set their objectName properties to leXStartFile, leXEndFile, and leFileName. The newly modified version of gui_fft.ui is shown in figure below.

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def open_file(self): global filename filename = QFileDialog.getOpenFileName(self, 'OpenFile') self.leFileName.setText(filename[0]) x = np.fromfile(open(filename[0]),np.int16)[24:] print(len(x)) self.show_wav(x) return filename

Define show_wav() function to display wav samples and its absolute FFT and log absolute FFT on three Widgets as follows:

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def show_wav(self, x): global y x_start = int(self.leXStartFile.text()) x_end = int(self.leXEndFile.text()) x=x[x_start:x_end] # widgetSignal t = linspace(x_start, x_end, len(x)) # Noise if self.rbNoise.isChecked(): y = x + np.random.randn(len(x)) * 50 else : y = x self.widgetSignal.canvas.axis1.clear() self.widgetSignal.canvas.axis1.plot(t, y) self.widgetSignal.canvas.axis1.annotate('$n$', xy=(0.98, 0), \ ha='left', va='top', xycoords='axes fraction', fontsize=20) self.widgetSignal.canvas.axis1.annotate('$h$', xy=(0, 1), \ xytext=(-15,5), ha='left', va='top', xycoords='axes fraction', \ textcoords='offset points', fontsize=20) self.widgetSignal.canvas.axis1.set_title('Stem Graph') self.widgetSignal.canvas.axis1.set_facecolor('lightblue') self.widgetSignal.canvas.axis1.grid() self.widgetSignal.canvas.draw() self.show_fft(y,self.widgetFFTAbs, self.widgetFFTLog) return y

Connect clicked() signal in pbOpenFile  widget inside def __init__(self) method. This signal is sent whenever user click pbOpenFile button:

self.pbOpenFile.clicked.connect(self.open_file)

Run program. Click on Open File button, click Noise radio button, and choose one of filters to see the filtered version of wav signal, as shown in figure below.

The following is the final version of main_fft2.py:

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#main_fft2.py from PyQt5.QtWidgets import * from PyQt5.uic import loadUi from matplotlib.backends.backend_qt5agg import (NavigationToolbar2QT as NavigationToolbar) import numpy as np from scipy import signal from numpy import * import matplotlib as mpl from scipy.signal import chirp class DemoGUIFFT(QMainWindow): def __init__(self): QMainWindow.__init__(self) loadUi("gui_fft.ui",self) self.setWindowTitle("GUI Demo for FFT") self.pbShow.clicked.connect(self.show_graph) self.addToolBar(NavigationToolbar(self.widgetSignal.canvas, self)) self.rbChirp.toggled.connect(self.show_chirp) self.rbSawtooth.toggled.connect(self.show_sawtooth) self.rbSquare.toggled.connect(self.show_square) self.rbSweepPoly.toggled.connect(self.show_sweep_poly) self.cbFiltering.currentIndexChanged.connect(self.show_filtering) self.pbOpenFile.clicked.connect(self.open_file) def show_graph(self): global y wc = float(self.leCutOff.text()) N = int(self.leFFTLength.text()) M = int(self.leSignalRange.text()) wc = wc*pi # widgetSignal n = arange(-M, M) h = wc/pi * sinc(wc*(n)/pi) mpl.style.use('seaborn') # Noise if self.rbNoise.isChecked(): y = y + np.random.randn(len(h)) * 0.1 else: y = h self.widgetSignal.canvas.axis1.clear() self.widgetSignal.canvas.axis1.stem(n,y,\ basefmt='r-',use_line_collection=True) self.widgetSignal.canvas.axis1.annotate('$n$', xy=(0.98, 0), \ ha='left', va='top', xycoords='axes fraction', fontsize=20) self.widgetSignal.canvas.axis1.annotate('$h$', xy=(0, 1), \ xytext=(-15,5), ha='left', va='top', xycoords='axes fraction', \ textcoords='offset points', fontsize=20) self.widgetSignal.canvas.axis1.set_title('Stem Graph') self.widgetSignal.canvas.axis1.set_facecolor('lightblue') self.widgetSignal.canvas.axis1.grid() self.widgetSignal.canvas.draw() self.show_fft(y,self.widgetFFTAbs, self.widgetFFTLog) return y def show_fft(self, h, qwidget1, qwidget2): wc = float(self.leCutOff.text()) N = int(self.leFFTLength.text()) M = int(self.leSignalRange.text()) wc = wc*pi # widgetFFTAbs w,Hh = signal.freqz(h,1,whole=True, worN=N) # get entire frequency domain wx = fft.fftfreq(len(w)) # shift to center for plotting qwidget1.canvas.axis1.clear() qwidget1.canvas.axis1.plot(w-pi,abs(fft.fftshift(Hh)),\ color='red', linewidth=3.0) qwidget1.canvas.axis1.axis(xmax=pi/2,xmin=-pi/2) qwidget1.canvas.axis1.vlines(\ [-1.1,1.1],0,1.2,color='g',lw=2.,linestyle='--',) qwidget1.canvas.axis1.hlines(1,-pi,pi,color='g',lw=2.,linestyle='--',) qwidget1.canvas.axis1.annotate(r'$\omega$', xy=(0.98, 0), \ ha='left', va='top', xycoords='axes fraction', fontsize=22) qwidget1.canvas.axis1.set_ylabel(r"$|H(\omega)| $",fontsize=22) qwidget1.canvas.axis1.set_title('Absolute FFT Graph') qwidget1.canvas.axis1.set_facecolor('lightblue') qwidget1.canvas.axis1.grid() qwidget1.canvas.draw() # widgetFFTLog w,Hh = signal.freqz(h,1,whole=True, worN=N) # get entire frequency domain wx = fft.fftfreq(len(w)) # shift to center for plotting qwidget2.canvas.axis1.clear() qwidget2.canvas.axis1.plot(w-pi,\ 20*log10(abs(fft.fftshift(Hh))),color='red', linewidth=3.0) qwidget2.canvas.axis1.axis(ymin=-40,xmax=pi/2,xmin=-pi/2) qwidget2.canvas.axis1.vlines([-wc,wc],\ 10,-40,color='g',lw=2.,linestyle='--',) qwidget2.canvas.axis1.hlines(0,-pi,pi,color='g',lw=2.,linestyle='--',) qwidget2.canvas.axis1.annotate(r'$\omega$', xy=(0.98, 0), \ ha='left', va='top', xycoords='axes fraction', fontsize=22) qwidget2.canvas.axis1.set_ylabel(r"$20\log_{10}|H(\omega)| $",fontsize=18) qwidget2.canvas.axis1.set_title('Log Absolute FFT Graph') qwidget2.canvas.axis1.set_facecolor('lightblue') qwidget2.canvas.axis1.grid() qwidget2.canvas.draw() def show_chirp(self): global y x_start = float(self.leXStart.text()) x_end = float(self.leXEnd.text()) f_start = float(self.leFStart.text()) f_end = float(self.leFEnd.text()) # widgetSignal t = linspace(x_start, x_end, 5001) w = chirp(t, f0=f_start, f1=f_end, t1=10, method='linear') # Noise if self.rbNoise.isChecked(): y = w + np.random.randn(len(w)) * 0.1 else: y = w self.widgetSignal.canvas.axis1.clear() self.widgetSignal.canvas.axis1.plot(t,y,linewidth=3.0) self.widgetSignal.canvas.axis1.annotate('$sec$', xy=(0.98, 0), \ ha='left', va='top', xycoords='axes fraction', fontsize=20) self.widgetSignal.canvas.axis1.annotate('$h$', xy=(0, 1), \ xytext=(-15,5), ha='left', va='top', xycoords='axes fraction', \ textcoords='offset points', fontsize=20) self.widgetSignal.canvas.axis1.set_title('Chirp Graph') self.widgetSignal.canvas.axis1.set_facecolor('lightblue') self.widgetSignal.canvas.axis1.grid() self.widgetSignal.canvas.draw() self.show_fft(y,self.widgetFFTAbs, self.widgetFFTLog) return y def show_sawtooth(self): global y x_start = float(self.leXStart.text()) x_end = float(self.leXEnd.text()) # widgetSignal t = linspace(x_start, x_end, 5001) w = signal.sawtooth(2 * np.pi * 5 * t) # Noise if self.rbNoise.isChecked(): y = w + np.random.randn(len(w)) * 0.1 else: y = w self.widgetSignal.canvas.axis1.clear() self.widgetSignal.canvas.axis1.plot(t, y,linewidth=3.0) self.widgetSignal.canvas.axis1.annotate('$sec$', xy=(0.98, 0), \ ha='left', va='top', xycoords='axes fraction', fontsize=20) self.widgetSignal.canvas.axis1.annotate('$h$', xy=(0, 1), \ xytext=(-15,5), ha='left', va='top', xycoords='axes fraction', \ textcoords='offset points', fontsize=20) self.widgetSignal.canvas.axis1.set_title('Chirp Graph') self.widgetSignal.canvas.axis1.set_title('Sawtooth Graph') self.widgetSignal.canvas.axis1.set_facecolor('lightblue') self.widgetSignal.canvas.axis1.grid() self.widgetSignal.canvas.draw() self.show_fft(y,self.widgetFFTAbs, self.widgetFFTLog) return y def show_square(self): global y x_start = float(self.leXStart.text()) x_end = float(self.leXEnd.text()) # widgetSignal t = linspace(x_start, x_end, 500, endpoint=False) w = signal.square(2 * pi * 2 * t) # Noise if self.rbNoise.isChecked(): y = w + np.random.randn(len(w)) * 0.1 else: y = w self.widgetSignal.canvas.axis1.clear() self.widgetSignal.canvas.axis1.plot(t, y, linewidth=3.0) self.widgetSignal.canvas.axis1.annotate('$sec$', xy=(0.98, 0), \ ha='left', va='top', xycoords='axes fraction', \ fontsize=20) self.widgetSignal.canvas.axis1.annotate('$h$', xy=(0, 1), \ xytext=(-15,5), ha='left', va='top', \ xycoords='axes fraction', textcoords='offset points', \ fontsize=20) self.widgetSignal.canvas.axis1.set_title('Square Graph') self.widgetSignal.canvas.axis1.set_facecolor('lightblue') self.widgetSignal.canvas.axis1.grid() self.widgetSignal.canvas.draw() self.show_fft(y,self.widgetFFTAbs, self.widgetFFTLog) return y def show_sweep_poly(self): global y x_start = float(self.leXStart.text()) x_end = float(self.leXEnd.text()) # widgetSignal p = np.poly1d([0.025, -0.36, 1.25, 2.0]) t = np.linspace(x_start, x_end, 5001) y = signal.sweep_poly(t, p) # Noise if self.rbNoise.isChecked(): y = y + np.random.randn(len(y)) * 0.1 else: y = y self.widgetSignal.canvas.axis1.clear() self.widgetSignal.canvas.axis1.plot(t, y, linewidth=3.0) self.widgetSignal.canvas.axis1.annotate('$sec$', xy=(0.98, 0), \ ha='left', va='top', xycoords='axes fraction', \ fontsize=20) self.widgetSignal.canvas.axis1.annotate('$h$', xy=(0, 1), \ xytext=(-15,5), ha='left', va='top', \ xycoords='axes fraction', textcoords='offset points', \ fontsize=20) self.widgetSignal.canvas.axis1.set_title('Sweep Poly Graph') self.widgetSignal.canvas.axis1.set_facecolor('lightblue') self.widgetSignal.canvas.axis1.grid() self.widgetSignal.canvas.draw() self.show_fft(y,self.widgetFFTAbs, self.widgetFFTLog) return y def butter_filter(self, param): global y x_start = float(self.leXStart.text()) x_end = float(self.leXEnd.text()) t = linspace(x_start, x_end, len(y)) pass_band = float(self.lePassBand.text()) stop_band = float(self.leStopBand.text()) #Butterworth filtering sos = signal.butter(stop_band, pass_band, param, fs=1000, output='sos') filtered = signal.sosfilt(sos, y) self.widgetOutput.canvas.axis1.clear() self.widgetOutput.canvas.axis1.plot(t, filtered) self.widgetOutput.canvas.axis1.set_ylabel("$h$",fontsize=22) self.widgetOutput.canvas.axis1.set_xlabel("$sec$",fontsize=22) self.widgetOutput.canvas.axis1.set_title('Butterworth Filtered Signal') self.widgetOutput.canvas.axis1.set_facecolor('lightblue') self.widgetOutput.canvas.axis1.grid() self.widgetOutput.canvas.draw() self.show_fft(filtered,self.widgetFFTAbsFiltered, \ self.widgetFFTLogFiltered) def show_filtering(self): strCB = self.cbFiltering.currentText() if strCB == 'Butterworth Highpass': self.butter_filter('hp') if strCB == 'Butterworth Lowpass': self.butter_filter('lp') if strCB == 'Chebyshev Highpass': self.cheby_filter('hp') if strCB == 'Chebyshev Lowpass': self.cheby_filter('lp') if strCB == 'Elliptic Highpass': self.ellip_filter('hp') if strCB == 'Elliptic Lowpass': self.ellip_filter('lp') def cheby_filter(self, param): global y fsampling=1000 x_start = float(self.leXStart.text()) x_end = float(self.leXEnd.text()) t = linspace(x_start, x_end, len(y)) pass_band = float(self.lePassBand.text()) stop_band = float(self.leStopBand.text()) #Butterworth filtering sos = signal.cheby1(stop_band, pass_band, 15, \ param, fs=fsampling, output='sos') filtered = signal.sosfilt(sos, y) self.widgetOutput.canvas.axis1.clear() self.widgetOutput.canvas.axis1.plot(t, filtered) self.widgetOutput.canvas.axis1.set_ylabel("$h$",fontsize=22) self.widgetOutput.canvas.axis1.set_xlabel("$sec$",fontsize=22) self.widgetOutput.canvas.axis1.set_title('Chebyshev Filtered Signal') self.widgetOutput.canvas.axis1.set_facecolor('lightblue') self.widgetOutput.canvas.axis1.grid() self.widgetOutput.canvas.draw() self.show_fft(filtered,self.widgetFFTAbsFiltered, \ self.widgetFFTLogFiltered) def ellip_filter(self, param): global y fsampling=1000 x_start = float(self.leXStart.text()) x_end = float(self.leXEnd.text()) t = linspace(x_start, x_end, len(y)) pass_band = float(self.lePassBand.text()) stop_band = float(self.leStopBand.text()) #Butterworth filtering sos = signal.ellip(8, 1, 100, stop_band, param, fs=1000, output='sos') filtered = signal.sosfilt(sos, y) self.widgetOutput.canvas.axis1.clear() self.widgetOutput.canvas.axis1.plot(t, filtered) self.widgetOutput.canvas.axis1.set_ylabel("$h$",fontsize=22) self.widgetOutput.canvas.axis1.set_xlabel("$sec$",fontsize=22) self.widgetOutput.canvas.axis1.set_title('Chebyshev Filtered Signal') self.widgetOutput.canvas.axis1.set_facecolor('lightblue') self.widgetOutput.canvas.axis1.grid() self.widgetOutput.canvas.draw() self.show_fft(filtered,self.widgetFFTAbsFiltered, \ self.widgetFFTLogFiltered) def open_file(self): global filename filename = QFileDialog.getOpenFileName(self, 'OpenFile') self.leFileName.setText(filename[0]) x = np.fromfile(open(filename[0]),np.int16)[24:] print(len(x)) self.show_wav(x) return filename def show_wav(self, x): global y x_start = int(self.leXStartFile.text()) x_end = int(self.leXEndFile.text()) x=x[x_start:x_end] # widgetSignal t = linspace(x_start, x_end, len(x)) # Noise if self.rbNoise.isChecked(): y = x + np.random.randn(len(x)) * 50 else : y = x self.widgetSignal.canvas.axis1.clear() self.widgetSignal.canvas.axis1.plot(t, y) self.widgetSignal.canvas.axis1.annotate('$n$', xy=(0.98, 0), \ ha='left', va='top', xycoords='axes fraction', fontsize=20) self.widgetSignal.canvas.axis1.annotate('$h$', xy=(0, 1), \ xytext=(-15,5), ha='left', va='top', xycoords='axes fraction', \ textcoords='offset points', fontsize=20) self.widgetSignal.canvas.axis1.set_title('Stem Graph') self.widgetSignal.canvas.axis1.set_facecolor('lightblue') self.widgetSignal.canvas.axis1.grid() self.widgetSignal.canvas.draw() self.show_fft(y,self.widgetFFTAbs, self.widgetFFTLog) return y if __name__ == '__main__': import sys app = QApplication(sys.argv) ex = DemoGUIFFT() ex.show() sys.exit(app.exec_())