def __init__(self, parent=None):
QtGui.QWidget.__init__(self)
self.ui = Ui_Form_spike_rates()
self.ui.setupUi(self)
self.filename = ''
self.checkboxes = []
self.comboboxes = []
self.spnboxes = []
# TODO Enable when implemented
self.ui.pushButton_auto_threshold.setEnabled(False)
self.ui.horizontalSlider.setEnabled(False)
self.ui.doubleSpinBox.setEnabled(False)
QtCore.QObject.connect(self.ui.pushButton_spike_rates, QtCore.SIGNAL("clicked()"), self.graph_spike_rates)
QtCore.QObject.connect(self.ui.pushButton_auto_threshold, QtCore.SIGNAL("clicked()"), self.estimate_thresholds)
QtCore.QObject.connect(self.ui.horizontalSlider, QtCore.SIGNAL("valueChanged(int)"), self.update_spontaneous)
QtCore.QObject.connect(self.ui.doubleSpinBox, QtCore.SIGNAL("valueChanged(const QString&)"), self.update_spontaneous2)
class SpikeRatesDialog(QtGui.QMainWindow):
def __init__(self, parent=None):
QtGui.QWidget.__init__(self)
self.ui = Ui_Form_spike_rates()
self.ui.setupUi(self)
self.filename = ''
self.checkboxes = []
self.comboboxes = []
self.spnboxes = []
# TODO Enable when implemented
self.ui.pushButton_auto_threshold.setEnabled(False)
self.ui.horizontalSlider.setEnabled(False)
self.ui.doubleSpinBox.setEnabled(False)
QtCore.QObject.connect(self.ui.pushButton_spike_rates, QtCore.SIGNAL("clicked()"), self.graph_spike_rates)
QtCore.QObject.connect(self.ui.pushButton_auto_threshold, QtCore.SIGNAL("clicked()"), self.estimate_thresholds)
QtCore.QObject.connect(self.ui.horizontalSlider, QtCore.SIGNAL("valueChanged(int)"), self.update_spontaneous)
QtCore.QObject.connect(self.ui.doubleSpinBox, QtCore.SIGNAL("valueChanged(const QString&)"), self.update_spontaneous2)
def populate_checkboxes(self, filename):
self.filename = filename
self.ui.label_title.setText(str.split(str(filename), '/')[-1])
h_file = h5py.File(unicode(filename), 'r')
tests = {}
for key in h_file.keys():
if 'segment' in key:
for test in h_file[key].keys():
tests[test] = int(test.replace('test_', ''))
sorted_tests = sorted(tests.items(), key=operator.itemgetter(1))
# Create the layout to populate
layout = QtGui.QGridLayout()
title_test = QtGui.QLabel('Test')
title_chan = QtGui.QLabel('Channel')
title_thresh = QtGui.QLabel('Threshold')
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(True)
title_test.setFont(font)
title_chan.setFont(font)
title_thresh.setFont(font)
layout.addWidget(title_test, 0, 0)
layout.addWidget(title_chan, 0, 1)
layout.addWidget(title_thresh, 0, 2)
row_count = 1
for test in sorted_tests:
checkbox = QtGui.QCheckBox(test[0])
combobox = QtGui.QComboBox()
spnbox = QtGui.QDoubleSpinBox()
layout.addWidget(checkbox, row_count, 0)
self.checkboxes.append(checkbox)
# Find target segment
for segment in h_file.keys():
for s_test in h_file[segment].keys():
if test[0] == s_test:
target_seg = segment
target_test = s_test
if len(h_file[target_seg][target_test].value.shape) > 3:
channels = h_file[target_seg][target_test].value.shape[2]
else:
channels = 1
if channels == 1:
combobox.addItem('channel_1')
else:
for i in range(channels):
combobox.addItem('channel_' + str(i+1))
if combobox.count() < 2:
combobox.setEnabled(False)
layout.addWidget(combobox, row_count, 1)
self.comboboxes.append(combobox)
spnbox.setSuffix(' V')
spnbox.setDecimals(4)
spnbox.setSingleStep(0.0001)
spnbox.setMinimum(-100)
spnbox.setMaximum(100)
# spnbox.setValue(thresh)
# TODO Enable when implemented
spnbox.setEnabled(False)
layout.addWidget(spnbox, row_count, 2)
self.spnboxes.append(spnbox)
row_count += 1
self.ui.scrollAreaWidgetContents.setLayout(layout)
# Add values to QSlider
window_time = h_file[target_seg][target_test].value.shape[-1] / h_file[target_seg].attrs['samplerate_ad']
self.ui.horizontalSlider.setMaximum(window_time * 1000)
self.ui.horizontalSlider.setValue(window_time * 500)
h_file.close()
def estimate_thresholds(self):
thresh_fraction = 0.7
h_file = h5py.File(unicode(self.filename), 'r')
for row in range(len(self.checkboxes)):
for segment in h_file.keys():
for test in h_file[segment].keys():
if self.checkboxes[row].text() == test:
target_seg = segment
target_test = test
trace_data = h_file[target_seg][target_test].value
if len(trace_data.shape) == 4:
trace_data = trace_data.squeeze()
# Still shape of 4
if len(trace_data.shape) == 4:
tchan = int(self.comboboxes[row].currentText().replace('channel_', '')) - 1
trace_data = trace_data[:, :, tchan, :]
trace_data = trace_data.squeeze()
# Compute threshold from average maximum of traces
max_trace = []
for n in range(len(trace_data[1, :, 0])):
max_trace.append(np.max(np.abs(trace_data[1, n, :])))
average_max = np.array(max_trace).mean()
thresh = thresh_fraction * average_max
self.spnboxes[row].setValue(thresh)
def get_spike_trains(self, h_file, test_num, spontStim=1):
for segment in h_file.keys():
for test in h_file[segment].keys():
if self.checkboxes[test_num].text() == test:
target_seg = segment
target_test = test
fs = h_file[target_seg].attrs['samplerate_ad']
reps = h_file[target_seg][target_test].attrs['reps']
startTime = h_file[target_seg][target_test].attrs['start']
trace_data = h_file[target_seg][target_test].value
if len(trace_data) == 4:
trace_data = trace_data.squeeze()
# Still shape of 4
if len(trace_data.shape) == 4:
tchan = int(self.comboboxes[test_num].currentText().replace('channel_', '')) - 1
trace_data = trace_data[:, :, tchan, :]
trace_data = trace_data.squeeze()
thresh = self.spnboxes[test_num].value()
# ----- AutoThreshold -----
maxTrace = []
for n in range(len(trace_data[0, :, 0])):
maxTrace.append(np.max(np.abs(trace_data[spontStim, n, :])))
aveMax = np.array(maxTrace).mean()
# if max(maxTrace) > 1 * np.std(maxTrace): # remove an extreme outlyer caused by an electrical glitch
# maxTrace.remove(max(maxTrace))
th = 0.7 * aveMax
thresh = th
spikeTrains = pd.DataFrame([])
nspk = 0
for n in range(len(trace_data[0, :, 0])):
spikes = spikestats.spike_times(trace_data[spontStim, n, :], threshold=thresh, fs=fs)
spikeTimes = 1000 * np.array(spikes)
spikeTimesS = pd.Series(spikeTimes)
if spikeTimesS.size > nspk:
spikeTrains = spikeTrains.reindex(spikeTimesS.index)
nspk = spikeTimesS.size
spikeTrains[str(n)] = spikeTimesS
# print 'thresh:', thresh, '\nspikes\n', spikes
duration = trace_data.shape[-1] / fs
return spikeTrains, duration, startTime
def graph_spike_rates(self):
print 'Spike Rates'
h_file = h5py.File(unicode(self.filename), 'r')
target_rows = []
for i in range(len(self.checkboxes)):
if self.checkboxes[i].checkState():
target_rows.append(i)
axes = []
timeStamp = []
spontAve = []
spontSTD = []
responseAve = []
responseSTD = []
for row in target_rows:
for segment in h_file.keys():
for test in h_file[segment].keys():
if self.checkboxes[row].text() == test:
target_seg = segment
target_test = test
stim_info = eval(h_file[target_seg][target_test].attrs['stim'])
start_time = h_file[target_seg][target_test].attrs['start']
spikeTrains, dur, time = self.get_spike_trains(h_file, row, spontStim=0)
# print '\n----------\n1 SPIKETRAINS:', row, '\n', spikeTrains, '\n----------'
# --- SpontaneousStats ---
spontSpikeCount = []
for k in spikeTrains.keys():
spk = spikeTrains[k]
spontSpikeCount.append(len(spk.dropna()) / float(dur))
if len(spontSpikeCount) > 0:
spontStats = [np.mean(spontSpikeCount), np.std(spontSpikeCount)]
else:
spontStats = [0, 0]
spikeTrains, dur, time = self.get_spike_trains(h_file, row, spontStim=1)
# print '\n----------\n2 SPIKETRAINS:', row, '\n', spikeTrains, '\n----------'
# Assumes all stim are the same for the test
# print 'stim start:', stim_info[1]['components'][0]['start_s']
# print 'stim duration:', stim_info[1]['components'][0]['duration']
stimStart = stim_info[1]['components'][0]['start_s']
stimDuration = stim_info[1]['components'][0]['duration']
# --- ResponseStats ---
dur = stimDuration
responseSpikeCount = []
for k in spikeTrains.keys():
spk = spikeTrains[k]
responseSpikeCount.append(len(spk[spk < stimStart*1000 + stimDuration*1000 + 10]) / dur)
if len(responseSpikeCount) > 0:
responseStats = [np.mean(responseSpikeCount), np.std(responseSpikeCount)]
else:
responseStats = [0, 0]
timeStamp.append(time)
spontAve.append(spontStats[0])
spontSTD.append(spontStats[1])
responseAve.append(responseStats[0])
responseSTD.append(responseStats[1])
# --- Plot the time dependent change in rates ---
if target_rows:
# print 'target_rows:', target_rows
# print self.ui.timeEdit_on_time.date(), self.ui.timeEdit_on_time.time()
# print self.ui.timeEdit_off_time.date(), self.ui.timeEdit_off_time.time()
timeOn = str(self.ui.timeEdit_on_time.time().hour()) + ':' \
+ str(self.ui.timeEdit_on_time.time().minute()) + ':' \
+ str(self.ui.timeEdit_on_time.time().second())
timeOff = str(self.ui.timeEdit_off_time.time().hour()) + ':' \
+ str(self.ui.timeEdit_off_time.time().minute()) \
+ ':' + str(self.ui.timeEdit_off_time.time().second())
rateEffects = pd.DataFrame({'Spontaneous': spontAve, 'spontSTD': spontSTD, 'Response': responseAve,
'responseSTD': responseSTD}, index=pd.to_datetime(timeStamp))
if len(target_rows) > 1:
fig = plt.figure()
rateEffects['Response'].plot(yerr=rateEffects['responseSTD'], capthick=1)
rateEffects['Spontaneous'].plot(yerr=rateEffects['spontSTD'], capthick=1)
plt.legend(loc='upper right', fontsize=12, frameon=True)
sns.despine()
plt.grid(False)
plt.xlabel('Time (ms)', size=14)
plt.ylabel('Rate (Hz)', size=14)
plt.title(str.split(str(self.filename), '/')[-1].replace('.hdf5', ''), size=14)
plt.tick_params(axis='both', which='major', labelsize=14)
ax = plt.gca()
lineY = ax.get_ylim()[1] - 0.01 * ax.get_ylim()[1]
if timeOff == timeOn: timeOff = rateEffects.index[-1]
if timeOn != 0 and (isinstance(timeOn, str) and isinstance(timeOff, str)):
plt.plot((timeOn, timeOff), (lineY, lineY), 'k-', linewidth=4)
for i, n in enumerate(target_rows):
plt.annotate(str(n), (rateEffects.index[i], rateEffects['Spontaneous'][i]))
plt.show()
h_file.close()
elif len(target_rows) > 0:
return rateEffects
else:
return []
def get_pharma_times(self, data):
pass
def update_spontaneous(self):
# print self.ui.horizontalSlider.value()
self.ui.doubleSpinBox.setValue(self.ui.horizontalSlider.value())
def update_spontaneous2(self):
# print self.ui.doubleSpinBox.value()
self.ui.horizontalSlider.setValue(self.ui.doubleSpinBox.value())
