问题描述
我正在编写带有02个小部件的代码，左侧的第一个小部件用于绘制信号，其FFT和log10。右边的第二个是处理和绘制滤波后的信号及其FFT log10。 我在Butterworth高通和低通之间选择了一个组合框。
但是当我在组合框中选择一个选项时，我得到了一个错误
ValueError: selected axis is out of range
如何解决此代码
我的代码在下面
链接到代码和GUI：https://drive.google.com/drive/folders/1eC15rh-1MLgNl948IpsUjZ773mMhTHlp?usp=sharing
import os,sys,math,pdb
from PyQt5 import QtCore,QtGui,QtWidgets
from PyQt5.QtCore import *
from PyQt5.QtGui import QColor,QIcon
from PyQt5.QtWidgets import QMainWindow,QApplication,QFileDialog,QMessageBox,QWidget
from PyQt5.uic import loadUi
from matplotlib.backends.backend_qt5agg import (NavigationToolbar2QT as NavigationToolbar)
from matplotlib.backends.backend_qt5agg import FigureCanvas
from matplotlib.figure import Figure
import numpy as np
from numpy import *
from scipy import signal
from gui3 import Ui_MainWindow
b_Canvas = b_Canvas2 = False
s = 0
class MyMainWindow(QMainWindow,Ui_MainWindow):
def __init__(self,parent=None):
super(MyMainWindow,self).__init__(parent)
QMainWindow.__init__(self,parent)
self.ui = Ui_MainWindow()
self.ui.setupUi(self)
self.ui.Show_Signals.clicked.connect(self.show_plot)
self.ui.cbfilter.currentIndexChanged.connect(self.show_filtering)
def rm_mpl(self):
global b_Canvas
self.ui.verticalLayout.removeWidget(self.canvas)
self.canvas.close()
self.ui.verticalLayout.removeWidget(self.toolbar)
self.toolbar.close()
b_Canvas = False
def rm_mpl2(self):
global b_Canvas2
self.ui.verticalLayout_2.removeWidget(self.canvas2)
self.canvas2.close()
self.ui.verticalLayout_2.removeWidget(self.toolbar2)
self.toolbar2.close()
b_Canvas2 = False
def show_plot(self):
global b_Canvas,b_Canvas2,s
if b_Canvas == True:
self.rm_mpl()
if b_Canvas2 == True:
self.rm_mpl2()
t_start = float(self.ui.le_time_start.text())
t_end = float(self.ui.le_time_end.text())
t_step = float(self.ui.le_time_step.text())
freq = float(self.ui.le_frequency.text())
amp = float(self.ui.le_amplitude.text())
phase = float(self.ui.le_phase.text())
poly = self.ui.le_poly.text()
if self.ui.rb_sin.isChecked() == True:
t = linspace(t_start,t_end,t_step)
s = amp * np.sin(2 * np.pi * freq * t + phase)
elif self.ui.rb_square.isChecked() == True:
t = linspace(t_start,t_step,endpoint=False)
s = amp * signal.square(2 * np.pi * freq * t)
elif self.ui.rb_poly.isChecked() == True:
ps = [float(i) for i in poly.split(',')]
p = np.poly1d(ps)
t = linspace(t_start,t_step)
s = amp * signal.sweep_poly(t,p)
elif self.ui.rb_sawtooth.isChecked() == True:
t = linspace(t_start,t_step)
s = amp * signal.sawtooth(2 * np.pi * freq * t)
if self.ui.rbNoise.isChecked():
s = s + np.random.randn(len(s)) * 0.1
fig = Figure()
self.canvas = FigureCanvas(fig)
self.ui.verticalLayout.addWidget(self.canvas)
fig.subplots_adjust(hspace = 1.0)
wc = float(self.ui.le_CutOff.text())
N = int(self.ui.le_FFTLength.text())
M = int(self.ui.le_SignalRange.text())
wc = wc * pi
w,Hh = signal.freqz(s,1,whole=True,worN=N) # to get entire frequency domain
wx = fft.fftfreq(len(w)) # to shift to center
# Input signal
ax1f1 = fig.add_subplot(311)
ax1f1.plot(s)
ax1f1.set_title('Input Signal')
# FFT Abs
ax1f2 = fig.add_subplot(312)
ax1f2.plot(w-pi,abs(fft.fftshift(Hh)))
ax1f2.set_title('Absolute FFT Graph')
ax1f2.set_xlabel(r"$\omega$",fontsize=14)
ax1f2.set_ylabel(r"$|H(\omega)| $",fontsize=14)
ax1f2.axis(xmin=-pi/2,xmax=pi/2)
# FFT Log
ax1f3 = fig.add_subplot(313)
ax1f3.plot(w-pi,20*log10(abs(fft.fftshift(Hh))))
ax1f3.set_title('Log Absolute FFT Graph')
ax1f3.set_xlabel(r"$\omega$",fontsize=14)
ax1f3.set_ylabel(r"$20\log_{10}|H(\omega)| $",fontsize=14)
ax1f3.axis(ymin=-40,xmin=-pi/2,xmax=pi/2)
self.canvas.draw()
self.toolbar = NavigationToolbar(self.canvas,self.ui.mplwindow,coordinates=True)
self.ui.verticalLayout.addWidget(self.toolbar)
b_Canvas = True
def show_filtering(self):
global b_Canvas,b_Canvas2
global filtered,s,pass_band,stop_band
if b_Canvas == True:
self.rm_mpl()
if b_Canvas2 == True:
self.rm_mpl2()
strcb = self.ui.cbfilter.currentText()
if strcb == 'Butterworth Highpass':
self.butterworth_filter('hp')
if strcb == 'Butterworth Lowpass':
self.butterworth_filter('lp')
fig1 = Figure()
self.canvas = FigureCanvas(fig1)
self.ui.verticalLayout_2.addWidget(self.canvas)
fig1.subplots_adjust(hspace = 1.0)
wc = float(self.ui.le_CutOff.text())
N = int(self.ui.le_FFTLength.text())
M = int(self.ui.le_SignalRange.text())
wc = wc * pi
w1,Hh1 = signal.freqz(filtered,worN=N) # to get entire frequency domain
wx1 = fft.fftfreq(len(w1)) # to shift to center
# Filter signal
ax1f1 = fig1.add_subplot(311)
ax1f1.plot(filtered)
ax1f1.set_title('Input Signal')
# FFT Abs Filter
ax1f2 = fig1.add_subplot(312)
ax1f2.plot(w1-pi,abs(fft.fftshift(Hh1)))
ax1f2.set_title('Absolute FFT Graph')
ax1f2.set_xlabel(r"$\omega$",xmax=pi/2)
# FFT Log Filter
ax1f3 = fig1.add_subplot(313)
ax1f3.plot(w1-pi,20*log10(abs(fft.fftshift(Hh1))))
ax1f3.set_title('Log Absolute FFT Graph')
ax1f3.set_xlabel(r"$\omega$",self.ui.mplwindow2,coordinates=True)
self.ui.verticalLayout_2.addWidget(self.toolbar)
b_Canvas2 = True
def butterworth_filter(self,param):
#extract line edit
global filtered,stop_band
pass_band = float(self.ui.pb.text())
stop_band = float(self.ui.sb.text())
#filtering
sos = signal.butter(stop_band,param,fs=1000,output='sos')
filtered = signal.sosfilt(sos,s)
if __name__ == '__main__':
import sys
app = QApplication(sys.argv)
window = MyMainWindow()
window.show()
sys.exit(app.exec_())
解决方法
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