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Alternative plotting unfinished

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This commit is contained in:
adamr 2023-04-13 15:23:25 +02:00
parent 2830c112f3
commit 714cd6dc58
1 changed files with 20 additions and 12 deletions
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32
EStiMo_GUI_0123.py → EStiMo_GUI_0123_alt.py
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@ -394,7 +394,8 @@ class AppForm(QMainWindow):
self.log_file.flush() #flushing is applying changes we made to the file self.log_file.flush() #flushing is applying changes we made to the file
self.Fs = 1000 #5000 self.Fs = 1000 #5000
self.size_of_up = 2*self.Fs #5000 how much data we get from NeurOne function self.size_of_up = 2*self.Fs #5000 how much data we get from NeurOne function
self.plot_par = 0
self.baseline_reg = 0
#file with settings and assigning variables to them #file with settings and assigning variables to them
settings_file = pd.read_csv('TMS_protocol.txt',sep=':', header=None) settings_file = pd.read_csv('TMS_protocol.txt',sep=':', header=None)
@ -786,16 +787,16 @@ class AppForm(QMainWindow):
self.loaded_full = self.loaded.copy() #keeps it for the next second self.loaded_full = self.loaded.copy() #keeps it for the next second
step2 = time.time()-time_start step2 = time.time()-time_start
# ZeroDivisionError means that data is not yet loaded # ZeroDivisionError means that data is not yet loaded
try: # try:
# [A,B] = ss.butter(2, 0.1/(self.Fs/2), 'highpass') # # [A,B] = ss.butter(2, 0.1/(self.Fs/2), 'highpass')
# self.loaded[:self.num_of_ch,-4*self.Fs:] = ss.filtfilt(A, B, self.loaded[:self.num_of_ch, -4*self.Fs:]) # # self.loaded[:self.num_of_ch,-4*self.Fs:] = ss.filtfilt(A, B, self.loaded[:self.num_of_ch, -4*self.Fs:])
# self.loaded[:self.num_of_ch,-4*self.Fs:] = self.loaded[:self.num_of_ch,-4*self.Fs:] - np.mean(self.loaded[:self.num_of_ch,-4*self.Fs:],1, keepdims=True) # # self.loaded[:self.num_of_ch,-4*self.Fs:] = self.loaded[:self.num_of_ch,-4*self.Fs:] - np.mean(self.loaded[:self.num_of_ch,-4*self.Fs:],1, keepdims=True)
self.loaded[:self.num_of_ch,-4*self.Fs:] = ss.detrend(self.loaded[:self.num_of_ch,-4*self.Fs:]) # self.loaded[:self.num_of_ch,-4*self.Fs:] = ss.detrend(self.loaded[:self.num_of_ch,-4*self.Fs:])
except ZeroDivisionError: # This error means that buffer is still not full # except ZeroDivisionError: # This error means that buffer is still not full
if self.qmbx == None: # if self.qmbx == None:
self.qmbx = Waiting_window() # Small window with a message to wait # self.qmbx = Waiting_window() # Small window with a message to wait
print('Waiting for data (should take up to few seconds)') # print('Waiting for data (should take up to few seconds)')
return(0) # Stop function here, because in this case rest of update is not needed # return(0) # Stop function here, because in this case rest of update is not needed
# Getting to this point of the code means there were no exception before # Getting to this point of the code means there were no exception before
# So the waiting window can be destroyed # So the waiting window can be destroyed
@ -837,7 +838,9 @@ class AppForm(QMainWindow):
# self.loaded[i,min(od+ind-int(int_from*self.Fs),30000-1)], # self.loaded[i,min(od+ind-int(int_from*self.Fs),30000-1)],
# self.loaded[i,max(od+ind+int(int_to*self.Fs),30000-1)], # self.loaded[i,max(od+ind+int(int_to*self.Fs),30000-1)],
# od+ind+int(int_to*self.Fs)-(od+ind-int(int_from*self.Fs))) # od+ind+int(int_to*self.Fs)-(od+ind-int(int_from*self.Fs)))
if self.plot_par%4==0:
self.baseline_reg = np.mean(self.loaded[:self.num_of_ch,-5*self.Fs:-4*self.Fs], 1)
self.loaded[:self.num_of_ch,-4*self.Fs:] = (self.loaded[:self.num_of_ch,-4*self.Fs:].T - self.baseline_reg).T
step6 = time.time()-time_start step6 = time.time()-time_start
# Eye regression for visualisation # Eye regression for visualisation
#plt.figure() #plt.figure()
@ -947,8 +950,13 @@ class AppForm(QMainWindow):
else: else:
plot_data = plot_data/self.plot_dividing_factor + self.num_of_ch - i plot_data = plot_data/self.plot_dividing_factor + self.num_of_ch - i
if self.plot_par%4!=0:
plot_data_c = plot_data.copy()
plot_data[:self.Fs*(self.plot_par%4)], plot_data[self.Fs*(self.plot_par%4):] = plot_data_c[4000-self.Fs*(self.plot_par%4):], plot_data_c[:4000-self.Fs*(self.plot_par%4)]
plot_data[self.Fs*(self.plot_par%4)-100:self.Fs*(self.plot_par%4)+100] = np.nan
# plot_data = plot_data/(3.5*np.max(np.abs(plot_data))) + self.num_of_ch - i # plot_data = plot_data/(3.5*np.max(np.abs(plot_data))) + self.num_of_ch - i
self.line[i].set_data(np.arange(0,self.plot_len*self.Fs), plot_data) self.line[i].set_data(np.arange(0,self.plot_len*self.Fs), plot_data)
self.plot_par+=1
self.axes.set_ylim(0, self.num_of_ch+1) self.axes.set_ylim(0, self.num_of_ch+1)
#self.axes.set_ylim(0,np.max(self.data[:,-self.plot_len*self.Fs:])+dif) #set ylim to fit everything on the plot #self.axes.set_ylim(0,np.max(self.data[:,-self.plot_len*self.Fs:])+dif) #set ylim to fit everything on the plot
if len(stim)>0: if len(stim)>0: