#filenames = ['/Volumes/backup/2017/Michael/Axopatch/20170512/10mMKClInFlowCellORingPore1mm.dat']
#filenames = ['/Volumes/backup/2017/Michael/Axopatch/20170512/bmimpf6lInFlowCellORingPore1mm.dat']
expname = 'Gradient'
filenames = askopenfilenames(
) # show an "Open" dialog box and return the path to the selected file
for filename in filenames:
print(filename)
#Make Dir to save images
output = uf.OpenFile(filename)
directory = (str(os.path.split(filename)[0]) + os.sep + expname +
'_SavedImages')
if not os.path.exists(directory):
os.makedirs(directory)
AllData = uf.MakeIVData(output, delay=2)
if AllData == 0:
print('!!!! No Sweep in: ' + filename)
continue
#Plot Considered Part
#figExtracteParts = plt.figure(1)
#ax1 = figExtracteParts.add_subplot(211)
#ax2 = figExtracteParts.add_subplot(212, sharex=ax1)
#(ax1, ax2) = uf.PlotExtractedPart(output, AllData, current = 'i1', unit=1e9, axis = ax1, axis2=ax2)
#figExtracteParts.savefig(directory + os.sep + 'PlotExtracted_' + str(os.path.split(filename)[1])[:-4] + '.eps')
#figExtracteParts.savefig(directory + os.sep + 'PlotExtracted_' + str(os.path.split(filename)[1])[:-4] + '.png', dpi=150)
# Plot IV
if output['graphene']:
figIV2 = plt.figure(3)
from tkinter.filedialog import askopenfilenames
from matplotlib.font_manager import FontProperties
fontP = FontProperties()
fontP.set_size('small')
Tk().withdraw()
os.system(
'''/usr/bin/osascript -e 'tell app "Finder" to set frontmost of process "python" to true' '''
)
expname = 'Gradient'
filename = '/Users/migraf/Desktop/Roche meetings/30B_1MKCl_AxoIV_FemtoOff_1.dat'
output = uf.OpenFile(filename)
directory = (str(os.path.split(filename)[0]) + os.sep + expname +
'_SavedImages')
AllData = uf.MakeIVData(output, delay=0.642)
# Plot all the Fits
time = np.arange(len(output['i1'])) / output['samplerate']
fig1, ax = plt.subplots(1)
ax.plot(time, output['i1'])
ax2 = ax.twinx()
ax2.plot(time, output['v1'], 'y')
ch = 'i1'
#Loop through the parts
for idx, val in enumerate(AllData[ch]['StartPoint']):
timepart = np.arange(AllData[ch]['EndPoint'][idx] -
val) / output['samplerate']
ax.plot(
val / output['samplerate'] + timepart,
uf.ExpFunc(timepart, AllData[ch]['ExponentialFitValues'][0][idx],
