def registration(self, grid_points_x=3, grid_points_y=3):
galvothread = DAQmission()
readinchan = []
x_coords = np.linspace(-10, 10, grid_points_x + 2)[1:-1]
y_coords = np.linspace(-10, 10, grid_points_y + 2)[1:-1]
xy_mesh = np.reshape(np.meshgrid(x_coords, y_coords), (2, -1),
order='F').transpose()
galvo_coordinates = xy_mesh
camera_coordinates = np.zeros((galvo_coordinates.shape))
for i in range(galvo_coordinates.shape[0]):
galvothread.sendSingleAnalog('galvosx', galvo_coordinates[i, 0])
galvothread.sendSingleAnalog('galvosy', galvo_coordinates[i, 1])
time.sleep(1)
image = self.cam.SnapImage(0.06)
plt.imsave(
os.getcwd() +
'/CoordinatesManager/Registration_Images/2P/image_' + str(i) +
'.png', image)
camera_coordinates[i, :] = readRegistrationImages.gaussian_fitting(
image)
print('Galvo Coordinate')
print(galvo_coordinates)
print('Camera coordinates')
print(camera_coordinates)
del galvothread
self.cam.Exit()
transformation = CoordinateTransformations.polynomial2DFit(
camera_coordinates, galvo_coordinates, order=1)
print('Transformation found for x:')
print(transformation[:, :, 0])
print('Transformation found for y:')
print(transformation[:, :, 1])
return transformation
def gather_reference_coordinates_galvos(self):
galvothread = DAQmission()
readinchan = []
camera_coordinates = np.zeros((3, 2))
galvo_coordinates = np.array([[0, 3], [3, -3], [-3, -3]])
for i in range(3):
pos_x = galvo_coordinates[i, 0]
pos_y = galvo_coordinates[i, 1]
galvothread.sendSingleAnalog('galvosx', pos_x)
galvothread.sendSingleAnalog('galvosy', pos_y)
image = self.cam.SnapImage(0.04)
camera_coordinates[i, :] = gaussian_fitting(image)
del galvothread
return np.array([camera_coordinates, galvo_coordinates])
def execute_tread_single_sample_analog(self, channel):
daq = DAQmission()
if channel == '640AO':
self.lasers_status['640'][1] = self.slider640.value()
daq.sendSingleAnalog(channel, self.slider640.value() / 100)
elif channel == '532AO':
self.lasers_status['532'][1] = self.slider532.value()
daq.sendSingleAnalog(channel, self.slider532.value() / 100)
elif channel == '488AO':
self.lasers_status['488'][1] = self.slider488.value()
daq.sendSingleAnalog(channel, self.slider488.value() / 100)
self.sig_lasers_status_changed.emit(self.lasers_status)
class Servo:
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.sampling_rate = 10000
self.PWM_frequency = 50
self.mission = DAQmission()
def power_on(self):
self.mission.sendSingleDigital(channel='servo_power_1', value=True)
# time.sleep(1.5)
def power_off(self):
self.mission.sendSingleDigital(channel='servo_power_1', value=False)
def rotate(self, degree):
# Convert degree to duty cycle in PWM.
if degree >= 0 and degree <= 360:
dutycycle = 0.02 #round((degree/180) * 0.05 + 0.05, 6)
PWM_wave = self.blockWave(self.sampling_rate,
self.PWM_frequency,
dutycycle,
repeats=50)
PWM_wave = np.where(PWM_wave == 0, False, True)
# plt.figure()
# plt.plot(PWM_wave)
# plt.show()
PWM_wave_organized = np.array(
[('servo_modulation_1', PWM_wave),
('servo_power_1', np.ones(len(PWM_wave), dtype=bool))],
dtype=[('Sepcification', 'U20'),
('Waveform', bool, (len(PWM_wave), ))])
self.mission.runWaveforms(clock_source = "DAQ", sampling_rate = self.sampling_rate, analog_signals = {},\
digital_signals = PWM_wave_organized, readin_channels = {})
else:
print('Rotation degree out of range!')
def blockWave(self,
sampleRate,
frequency,
dutycycle,
repeats,
voltMin=0,
voltMax=5):
"""
Generates a one period blockwave.
sampleRate samplerate set on the DAQ (int)
frequency frequency you want for the block wave (int)
voltMin minimum value of the blockwave (float)
voltMax maximum value of the blockwave (float)
dutycycle duty cycle of the wave (wavelength at voltMax) (float)
"""
wavelength = int(sampleRate /
frequency) #Wavelength in number of samples
#The high values
high = np.ones(math.ceil(wavelength * dutycycle)) * voltMax
#Low values
low = np.ones(math.floor(wavelength * (1 - dutycycle))) * voltMin
#Adding them
single_period = np.append(high, low)
"""
Repeats the wave a set number of times and returns a new repeated wave.
"""
extendedWave = np.array([])
for i in range(repeats):
extendedWave = np.append(extendedWave, single_period)
return extendedWave
def control_for_registration(self, wavelength, value):
value = int(value)
daq = DAQmission()
if value == 0:
switch = False
else:
switch = True
if wavelength == '640':
print(wavelength + ':' + str(value))
print(str(switch))
daq.sendSingleAnalog('640AO', value)
daq.sendSingleDigital('640blanking', switch)
elif wavelength == '532':
print(wavelength + ':' + str(value))
print(str(switch))
daq.sendSingleAnalog('532AO', value)
daq.sendSingleDigital('640blanking', switch)
else:
print(wavelength + ':' + str(value))
print(str(switch))
daq.sendSingleAnalog('488AO', value)
daq.sendSingleDigital('640blanking', switch)
def execute_tread_single_sample_digital(self, channel):
daq = DAQmission()
if channel == '640blanking':
if self.switchbutton_blankingAll.isChecked():
self.lasers_status['640'][0] = True
daq.sendSingleDigital(channel, True)
else:
self.lasers_status['640'][0] = False
daq.sendSingleDigital(channel, False)
elif channel == '532blanking':
if self.switchbutton_532.isChecked():
self.lasers_status['532'][0] = True
daq.sendSingleDigital(channel, True)
else:
self.lasers_status['532'][0] = False
daq.sendSingleDigital(channel, False)
elif channel == '488blanking':
if self.switchbutton_488.isChecked():
self.lasers_status['488'][0] = True
daq.sendSingleDigital(channel, True)
else:
self.lasers_status['488'][0] = False
daq.sendSingleDigital(channel, False)
self.sig_lasers_status_changed.emit(self.lasers_status)
class PatchclampSealTestUI(QWidget):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.saving_dir = r'M:\tnw\ist\do\projects\Neurophotonics\Brinkslab\Data\Patch clamp\seal_test'
#------------------------Initiating patchclamp class-------------------
self.sealTest = PatchclampSealTest()
self.sealTest.measurementThread.measurement.connect(
self.handleMeasurement) #Connecting to the measurement signal
self.holdTest = PatchclampSealTest_hold()
self.holdTest.measurementThread_hold.measurement.connect(
self.handleMeasurement) #Connecting to the measurement signal
self.currentclampTest = PatchclampSealTest_currentclamp()
self.currentclampTest.measurementThread_currentclamp.measurement.connect(
self.handleMeasurement) #Connecting to the measurement signal
self.zapfunction = PatchclampSealTest_zap()
#----------------------------------------------------------------------
#----------------------------------GUI---------------------------------
#----------------------------------------------------------------------
self.setFixedHeight(700)
self.setWindowTitle("Patchclamp Seal Test")
self.ICON_RED_LED = "./Icons/off.png"
self.ICON_GREEN_LED = '/Icons/on.png'
self.is_sealtesting = False
#------------------------------Gains-----------------------------------
gainContainer = StylishQT.roundQGroupBox(title="Gains")
# gainContainer.setFixedWidth(320)
gainLayout = QGridLayout()
gainLayout.addWidget(QLabel("Input Voltage"), 0, 0)
self.inVolGainList = QComboBox()
self.inVolGainList.addItems(['1/10', '1', '1/50'])
gainLayout.addWidget(self.inVolGainList, 1, 0)
gainLayout.addWidget(QLabel("Output Voltage"), 0, 1)
self.outVolGainList = QComboBox()
self.outVolGainList.addItems(['10', '2', '5', '1', '20', '50', '100'])
gainLayout.addWidget(self.outVolGainList, 1, 1)
gainLayout.addWidget(QLabel("Output Current"), 0, 2)
self.outCurGainList = QComboBox()
self.outCurGainList.addItems(['1', '2', '5', '10', '20', '50', '100'])
gainLayout.addWidget(self.outCurGainList, 1, 2)
gainLayout.addWidget(QLabel("Probe"), 0, 3)
self.probeGainList = QComboBox()
self.probeGainList.addItems(['100M\u03A9', '10G\u03A9'])
gainLayout.addWidget(self.probeGainList, 1, 3)
gainContainer.setLayout(gainLayout)
#------------------------------Wavesettings-----------------------------------
WavesettingsContainer = StylishQT.roundQGroupBox(title="Wave settings")
# WavesettingsContainer.setFixedWidth(320)
WavesettingsContainerLayout = QGridLayout()
WavesettingsContainerLayout.addWidget(QLabel("Voltage step(mV)"), 0, 0)
self.DiffVoltagebox = QSpinBox(self)
self.DiffVoltagebox.setMaximum(2000)
self.DiffVoltagebox.setMinimum(-2000)
self.DiffVoltagebox.setValue(10)
self.DiffVoltagebox.setSingleStep(10)
WavesettingsContainerLayout.addWidget(self.DiffVoltagebox, 0, 1)
WavesettingsContainerLayout.addWidget(QLabel("Voltage baseline(mV)"),
0, 2)
self.LowerVoltagebox = QSpinBox(self)
self.LowerVoltagebox.setMaximum(2000)
self.LowerVoltagebox.setMinimum(-2000)
self.LowerVoltagebox.setValue(0)
self.LowerVoltagebox.setSingleStep(30)
WavesettingsContainerLayout.addWidget(self.LowerVoltagebox, 0, 3)
WavesettingsContainer.setLayout(WavesettingsContainerLayout)
#------------------------------Membrane potential-----------------------------------
Vm_measureContainer = StylishQT.roundQGroupBox(title="Vm measurement")
# Vm_measureContainer.setFixedWidth(320)
Vm_measureContainerLayout = QGridLayout()
Vm_measureContainerLayout.addWidget(QLabel("Clamping current(pA)"), 0,
0)
self.clampingcurrentbox = QSpinBox(self)
self.clampingcurrentbox.setMaximum(2000)
self.clampingcurrentbox.setMinimum(-2000)
self.clampingcurrentbox.setValue(0)
self.clampingcurrentbox.setSingleStep(100)
Vm_measureContainerLayout.addWidget(self.clampingcurrentbox, 0, 1)
self.membraneVoltLabel = QLabel("Vm: ")
Vm_measureContainerLayout.addWidget(self.membraneVoltLabel, 0, 2)
self.VmstartButton = StylishQT.runButton()
self.VmstartButton.clicked.connect(lambda: self.measure_currentclamp())
Vm_measureContainerLayout.addWidget(self.VmstartButton, 0, 3)
self.VmstopButton = StylishQT.stop_deleteButton()
self.VmstopButton.setEnabled(False)
self.VmstopButton.clicked.connect(
lambda: self.stopMeasurement_currentclamp())
Vm_measureContainerLayout.addWidget(self.VmstopButton, 0, 4)
Vm_measureContainer.setLayout(Vm_measureContainerLayout)
#------------------------------zap-----------------------------------
zapContainer = StylishQT.roundQGroupBox(title="ZAP")
# zapContainer.setFixedWidth(320)
zapContainerLayout = QGridLayout()
self.ICON_zap = './Icons/zap.jpg'
self.zapiconlabel = QLabel()
self.zapiconlabel.setPixmap(QPixmap(self.ICON_zap))
zapContainerLayout.addWidget(self.zapiconlabel, 0, 0)
self.zapButton = QPushButton("ZAP!")
self.zapButton.setStyleSheet(
"QPushButton {color:white;background-color: blue; border-style: outset;border-radius: 10px;border-width: 2px;font: bold 14px;padding: 6px}"
"QPushButton:pressed {color:black;background-color: red; border-style: outset;border-radius: 10px;border-width: 2px;font: bold 14px;padding: 6px}"
"QPushButton:hover:!pressed {color:blue;background-color: white; border-style: outset;border-radius: 10px;border-width: 2px;font: bold 14px;padding: 6px}"
)
self.zapButton.setShortcut('z')
zapContainerLayout.addWidget(self.zapButton, 0, 1)
self.zapButton.clicked.connect(self.zap)
zapContainerLayout.addWidget(QLabel("ZAP voltage(V)"), 0, 2)
self.zapVbox = QDoubleSpinBox(self)
self.zapVbox.setMaximum(1)
self.zapVbox.setMinimum(-2000)
self.zapVbox.setValue(1)
self.zapVbox.setSingleStep(0.1)
zapContainerLayout.addWidget(self.zapVbox, 0, 3)
zapContainerLayout.addWidget(QLabel("ZAP duration(us)"), 0, 4)
self.zaptimebox = QSpinBox(self)
self.zaptimebox.setMaximum(200000000)
self.zaptimebox.setMinimum(-200000000)
self.zaptimebox.setValue(200)
self.zaptimebox.setSingleStep(200)
zapContainerLayout.addWidget(self.zaptimebox, 0, 5)
zapContainer.setLayout(zapContainerLayout)
#----------------------------Control-----------------------------------
controlContainer = StylishQT.roundQGroupBox(title="Control")
controlContainer.setFixedWidth(350)
controlLayout = QGridLayout()
# controlLayout.addWidget(QLabel("Holding Vm:"), 1, 0)
# self.HoldingList = QComboBox()
# self.HoldingList.addItems(['000 mV', '-30 mV', '-50 mV', '-40 mV', '-60 mV'])
# controlLayout.addWidget(self.HoldingList, 2, 0)
#
# self.iconlabel = QLabel(self)
# self.iconlabel.setPixmap(QPixmap(self.ICON_RED_LED))
# controlLayout.addWidget(self.iconlabel, 1, 1)
#
# self.holdingbutton = QPushButton("Hold")
# self.holdingbutton.setCheckable(True)
# #self.holdingbutton.toggle()
#
# self.holdingbutton.clicked.connect(lambda: self.btnstate())
# #self.holdingbutton.clicked.connect(lambda: self.hold())
# #self.holdingbutton.clicked.connect(self.setGreenlight)
# controlLayout.addWidget(self.holdingbutton, 2, 1)
# self.stopandholdbutton = QPushButton("Stop and Hold")
# self.stopandholdbutton.clicked.connect(lambda: self.stopMeasurement())
# self.stopandholdbutton.clicked.connect(lambda: self.measure_hold())
# self.stopandholdbutton.clicked.connect(self.setGreenlight)
# controlLayout.addWidget(self.stopandholdbutton, 0, 2)
'''
self.stopholdingbutton = QPushButton("Stop holding")
self.stopholdingbutton.clicked.connect(lambda: self.stophold())
self.stopholdingbutton.clicked.connect(self.setRedlight)
controlLayout.addWidget(self.stopholdingbutton, 2, 2)
'''
controlLayout.addWidget(gainContainer, 0, 0, 1, 2)
controlLayout.addWidget(WavesettingsContainer, 1, 0, 1, 2)
controlLayout.addWidget(Vm_measureContainer, 2, 0, 1, 2)
controlLayout.addWidget(zapContainer, 3, 0, 1, 2)
self.startButton = StylishQT.runButton("Start seal-test")
self.startButton.clicked.connect(lambda: self.measure())
# self.startButton.setFixedWidth(120)
# self.startButton.clicked.connect(self.setRedlight)
# self.startButton.clicked.connect(self.startUpdatingGUIThread)
controlLayout.addWidget(self.startButton, 4, 0, 1, 1)
self.stopButton = StylishQT.stop_deleteButton()
self.stopButton.setEnabled(False)
# self.stopButton.setFixedWidth(120)
self.stopButton.clicked.connect(lambda: self.stopMeasurement())
controlLayout.addWidget(self.stopButton, 4, 1, 1, 1)
controlContainer.setLayout(controlLayout)
#-----------------------------Plots------------------------------------
plotContainer = StylishQT.roundQGroupBox(title="Output")
plotContainer.setFixedWidth(350)
self.plotLayout = QGridLayout(
) #We set the plotLayout as an attribute of the object (i.e. self.plotLayout instead of plotLayout)
#This is to prevent the garbage collector of the C++ wrapper from deleting the layout and thus triggering errors.
#Derived from: https://stackoverflow.com/questions/17914960/pyqt-runtimeerror-wrapped-c-c-object-has-been-deleted
# and http://enki-editor.org/2014/08/23/Pyqt_mem_mgmt.html
# self.outVolPlotWidget = SlidingWindow(200, title = "Voltage", unit = "V") #Should be bigger than the readvalue
self.outCurPlotWidget = SlidingWindow(
200, title="Current",
unit="A") #Should be bigger than the readvalue
self.display_tab_widget = QTabWidget()
# self.plotLayout.addWidget(QLabel('Voltage (mV):'), 0, 0)
self.display_tab_widget.addTab(self.outCurPlotWidget, "Current")
# self.plotLayout.addWidget(self.outVolPlotWidget, 1, 0)
# self.plotLayout.addWidget(QLabel('Current (pA):'), 0, 1)
# self.display_tab_widget.addTab(self.outVolPlotWidget, "Voltage")
# self.plotLayout.addWidget(self.outCurPlotWidget, 1, 1)
valueContainer = QGroupBox("Resistance/Capacitance")
self.valueLayout = QGridLayout()
self.resistanceLabel = QLabel("Resistance: ")
self.capacitanceLabel = QLabel("Capacitance: ")
self.ratioLabel = QLabel("Ratio: ")
self.valueLayout.addWidget(self.resistanceLabel, 0, 0)
self.valueLayout.addWidget(self.capacitanceLabel, 0, 1)
self.valueLayout.addWidget(self.ratioLabel, 0, 2)
self.pipette_resistance = QLineEdit(self)
self.pipette_resistance.setPlaceholderText('Pipette resistance')
self.pipette_resistance.setFixedWidth(100)
self.valueLayout.addWidget(self.pipette_resistance, 1, 0)
self.savedataButton = QPushButton("Save figure")
self.savedataButton.clicked.connect(lambda: self.savePatchfigure())
self.valueLayout.addWidget(self.savedataButton, 1, 1)
self.resetButton = QPushButton("Reset Iplot")
self.resetButton.clicked.connect(lambda: self.ResetCurrentImgView())
self.valueLayout.addWidget(self.resetButton, 1, 2)
valueContainer.setLayout(self.valueLayout)
self.plotLayout.addWidget(self.display_tab_widget, 0, 0, 1, 1)
self.plotLayout.addWidget(valueContainer, 2, 0, 1, 1)
plotContainer.setLayout(self.plotLayout)
#---------------------------Adding to master---------------------------
master = QVBoxLayout()
master.addWidget(controlContainer)
master.addWidget(plotContainer)
self.setLayout(master)
#--------------------------Setting variables---------------------------
self.changeVolInGain(self.inVolGainList.currentText())
self.changeVolOutGain(self.outVolGainList.currentText())
self.changeCurOutGain(self.outCurGainList.currentText())
self.changeProbeGain(self.probeGainList.currentText())
self.inVolGainList.currentIndexChanged.connect(
lambda: self.changeVolInGain(self.inVolGainList.currentText()))
self.outVolGainList.currentIndexChanged.connect(
lambda: self.changeVolOutGain(self.outVolGainList.currentText()))
self.outCurGainList.currentIndexChanged.connect(
lambda: self.changeCurOutGain(self.outCurGainList.currentText()))
self.probeGainList.currentIndexChanged.connect(
lambda: self.changeProbeGain(self.probeGainList.currentText()))
def ResetCurrentImgView(self):
"""Closes the widget nicely, making sure to clear the graphics scene and release memory."""
self.outCurPlotWidget.close()
# self.outVolPlotWidget.close()
# Replot the imageview
self.outCurPlotWidget = SlidingWindow(200, title="Current", unit="A")
self.display_tab_widget.addTab(self.outCurPlotWidget, "Current")
# self.display_tab_widget.addTab(self.outVolPlotWidget, "Voltage")
def measure(self):
"""Pop up window asking to check the gains.
Returns
True if the measurement can be done
and
False if not.
"""
#check = QMessageBox.question(self, 'GAINS!', "Are all the gains corresponding?",
#QMessageBox.Yes | QMessageBox.No)
#if check == QMessageBox.Yes:
"""Start the patchclamp measurement"""
self.stopButton.setEnabled(True)
self.startButton.setEnabled(False)
self.diffvoltage = self.DiffVoltagebox.value() / 1000
self.lowervoltage = self.LowerVoltagebox.value() / 1000
self.sealTest.setWave(self.inVolGain, self.diffvoltage,
self.lowervoltage)
self.sealTest.start()
self.is_sealtesting = True
self.startUpdatingGUIThread()
def measure_hold(self):
"""Pop up window asking to check the gains.
Returns
True if the measurement can be done
and
False if not.
"""
self.holdTest.setWave(self.inVolGain,
float(self.HoldingList.currentText()[0:3]))
self.holdTest.start()
self.is_sealtesting = True
def measure_currentclamp(self):
"""Pop up window asking to check the gains.
Returns
True if the measurement can be done
and
False if not.
"""
#check = QMessageBox.question(self, 'GAINS!', "Are all the gains corresponding?",
#QMessageBox.Yes | QMessageBox.No)
#if check == QMessageBox.Yes:
"""Start the patchclamp measurement"""
self.VmstartButton.setEnabled(False)
self.VmstopButton.setEnabled(True)
self.currentclamp_value = self.clampingcurrentbox.value()
self.currentclampTest.setWave(self.inVolGain, self.probeGain,
self.currentclamp_value)
self.currentclampTest.start()
self.is_sealtesting = True
def hold(self):
constant = float(self.HoldingList.currentText()[0:3])
self.executer = DAQmission()
self.executer.sendSingleAnalog('patchAO', constant / 1000 * 10)
print("Holding vm at " + str(constant) + ' mV')
def stophold(self):
self.executer.sendSingleAnalog('patchAO', 0)
print('Stop holding')
def btnstate(self):
#source = self.sender()
if self.holdingbutton.isChecked():
self.measure_hold()
self.setGreenlight()
else:
self.stop_hold_Measurement()
self.setRedlight()
def setRedlight(self):
self.iconlabel.setPixmap(QPixmap(self.ICON_RED_LED))
def setGreenlight(self):
self.iconlabel.setPixmap(QPixmap(self.ICON_GREEN_LED))
def startUpdatingGUIThread(self):
time.sleep(0.3)
StartGUIThread = threading.Thread(target=self.startUpdatingGUI)
StartGUIThread.start()
# else:
# .disconnect()
def handleMeasurement(self, voltOut, curOut):
"""Handle the measurement. Update the graph."""
#Rescaling using gains
self.voltOut = voltOut / self.outVolGain
self.curOut = curOut / self.outCurGain / self.probeGain
def startUpdatingGUI(self):
while self.is_sealtesting == True:
try:
# self.outVolPlotWidget.append_(self.voltOut)
self.outCurPlotWidget.append_(self.curOut)
self.updateGraphs()
self.updateLabels(self.curOut, self.voltOut)
time.sleep(0.05)
except:
pass
def updateGraphs(self):
"""Update graphs."""
self.outCurPlotWidget.updateWindow()
# self.outVolPlotWidget.updateWindow()
def updateLabels(self, curOut, voltOut):
"""Update the resistance and capacitance labels.
http://scipy-lectures.org/intro/scipy/auto_examples/plot_curve_fit.html
https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html"""
constants = MeasurementConstants()
sampPerCyc = int(constants.patchSealSampRate / constants.patchSealFreq)
try:
curOutCyc = curOut.reshape(int(curOut.size / sampPerCyc),
sampPerCyc)
curData = np.mean(curOutCyc, axis=0)
except:
curData = curOut
voltData = voltOut
try:
#Computing resistance
tres = np.mean(voltData)
dV = np.mean(voltData[voltData > tres]) - np.mean(
voltData[voltData < tres]) #Computing the voltage difference
dIss = np.mean(
curData[math.floor(0.15 *
sampPerCyc):math.floor(sampPerCyc / 2) -
2]) - np.mean(
curData[math.floor(0.65 * sampPerCyc):sampPerCyc -
2]) #Computing the current distance
membraneResistance = dV / (dIss * 1000000) #Ohms law (MegaOhm)
self.resistanceLabel.setText("Resistance: %.4f M\u03A9" %
membraneResistance)
self.estimated_size_resistance = 10000 / (
membraneResistance * 1000000
) #The resistance of a typical patch of membrane, RM is 10000 Omega/{cm}^2
except:
self.resistanceLabel.setText("Resistance: %s" % 'NaN')
try:
measured_vlotage = np.mean(voltData) * 1000
self.membraneVoltLabel.setText("Vm: %.2f mV" % measured_vlotage)
self.membraneVoltLabel.setStyleSheet('color: red')
except:
self.membraneVoltLabel.setText("Vm: %s" % 'NaN')
try:
#Computing capacitance
points = 10
maxCur = np.amax(curData)
maxCurIndex = np.where(curData == maxCur)[0][0]
curFit = curData[int(maxCurIndex + 1):int(
maxCurIndex + 1 + points - 1)] - 0.5 * (np.mean(curData[
math.floor(0.15 * sampPerCyc):math.floor(sampPerCyc / 2) -
2]) + np.mean(
curData[math.floor(0.65 * sampPerCyc):sampPerCyc - 2]))
timepoints = 1000 * np.arange(
3, points - 1 + 3) / constants.patchSealSampRate
#Fitting the data to an exponential of the form y=a*exp(-b*x) where b = 1/tau and tau = RC
#I(t)=I0*e^−t/τ, y=a*exp(-b*x), get log of both sides:log y = -bx + log a
fit = np.polyfit(
timepoints, curFit, 1
) #Converting the exponential to a linear function and fitting it
#Extracting data
current = fit[0]
resistance = dV * 1000 / current / 2 #Getting the resistance
tau = -1 / fit[1]
capacitance = 1000 * tau / resistance
self.capacitanceLabel.setText("Capacitance: %.4f" % capacitance)
self.estimated_size_capacitance = capacitance * (10**-12) * (10**6)
if self.estimated_size_capacitance > self.estimated_size_resistance:
self.estimated_ratio = self.estimated_size_capacitance / self.estimated_size_resistance
else:
self.estimated_ratio = self.estimated_size_resistance / self.estimated_size_capacitance
self.ratioLabel.setText(
"Ratio: %.4f" % self.estimated_ratio
) #http://www.cnbc.cmu.edu/~bard/passive2/node5.html
except:
self.capacitanceLabel.setText("Capacitance: %s" % 'NaN')
self.ratioLabel.setText("Ratio: %s" % 'NaN')
self.patch_parameters = "R_{}_C_{}".format(
round(membraneResistance, 3), round(capacitance, 3))
def stopMeasurement(self):
"""Stop the seal test."""
self.stopButton.setEnabled(False)
self.startButton.setEnabled(True)
self.sealTest.aboutToQuitHandler()
self.is_sealtesting = False
#constant = float(self.HoldingList.currentText()[0:3])
#self.executer = execute_constant_vpatch(constant/1000*10)
#print("Holding vm at "+str(constant)+' mV')
'''
def closeEvent(self, event):
"""On closing the application we have to make sure that the measuremnt
stops and the device gets freed."""
self.stopMeasurement()
'''
def stop_hold_Measurement(self):
"""Stop the seal test."""
self.holdTest.aboutToQuitHandler()
self.is_sealtesting = False
def close_hold_Event(self, event):
"""On closing the application we have to make sure that the measuremnt
stops and the device gets freed."""
self.stop_hold_Measurement()
def stopMeasurement_currentclamp(self):
"""Stop the seal test."""
self.VmstartButton.setEnabled(True)
self.VmstopButton.setEnabled(False)
self.currentclampTest.aboutToQuitHandler()
self.is_sealtesting = False
#Change gain
def changeVolInGain(self, gain):
if gain == '1':
self.inVolGain = 1
elif gain == '1/10':
self.inVolGain = 0.1
elif gain == '1/50':
self.inVolGain = 1. / 50
def changeVolOutGain(self, gain):
self.outVolGain = float(gain)
def changeCurOutGain(self, gain):
self.outCurGain = float(gain)
def changeProbeGain(self, gain):
if gain == '100M\u03A9':
self.probeGain = 100 * 10**6
elif gain == '10G\u03A9':
self.probeGain = 10 * 10**9
def zap(self):
self.zap_v = self.zapVbox.value()
self.zap_time = self.zaptimebox.value()
self.sealTest.aboutToQuitHandler()
self.zapfunction.setWave(self.inVolGain, self.zap_v, self.zap_time)
self.zapfunction.start()
time.sleep(0.06)
self.zapfunction.aboutToQuitHandler()
"""Start the patchclamp measurement"""
self.diffvoltage = self.DiffVoltagebox.value() / 1000
self.lowervoltage = self.LowerVoltagebox.value() / 1000
self.sealTest.setWave(self.inVolGain, self.diffvoltage,
self.lowervoltage)
self.sealTest.start()
def savePatchfigure(self):
# create an exporter instance, as an argument give it
# the item you wish to export
exporter = pg.exporters.ImageExporter(
self.outCurPlotWidget.getPlotItem())
# set export parameters if needed
exporter.parameters(
)['width'] = 500 # (note this also affects height parameter)
# save to file
exporter.export(
os.path.join(
self.saving_dir,
'SealTest_' + "Rpip_" + self.pipette_resistance.text() +
"Mohm_" + self.patch_parameters + '.png'))
def control_for_registration(self, wavelength, value):
value = int(value)
daq = DAQmission()
if value == 0:
switch = False
else:
switch = True
if wavelength == "640":
print(wavelength + ":" + str(value))
print(str(switch))
daq.sendSingleAnalog("640AO", value)
daq.sendSingleDigital("640blanking", switch)
elif wavelength == "532":
print(wavelength + ":" + str(value))
print(str(switch))
daq.sendSingleAnalog("532AO", value)
daq.sendSingleDigital("640blanking", switch)
else:
print(wavelength + ":" + str(value))
print(str(switch))
daq.sendSingleAnalog("488AO", value)
daq.sendSingleDigital("640blanking", switch)
def inidividual_coordinate_operation(self, EachRound, EachWaveform, RowIndex, ColumnIndex):
"""
Execute pre-set operations at each coordinate.
Parameters
----------
EachRound : int
Current round index.
EachWaveform : int
Current waveform package index.
RowIndex : int
Current sample stage row index.
ColumnIndex : int
Current sample stage row index.
Returns
-------
None.
"""
# Extract information
WaveformPackageToBeExecute = self.RoundQueueDict['RoundPackage_{}'.format(EachRound+1)][0]['WaveformPackage_{}'.format(EachWaveform+1)]
CameraPackageToBeExecute = self.RoundQueueDict['RoundPackage_{}'.format(EachRound+1)][1]["CameraPackage_{}".format(EachWaveform+1)]
WaveformPackageGalvoInfor = self.RoundQueueDict['GalvoInforPackage_{}'.format(EachRound+1)]['GalvoInfor_{}'.format(EachWaveform+1)]
self.readinchan = WaveformPackageToBeExecute[3]
self.RoundWaveformIndex = [EachRound+1, EachWaveform+1] # first is current round number, second is current waveform package number.
self.CurrentPosIndex = [RowIndex, ColumnIndex]
#----------------Camera operations-----------------
_camera_isUsed = False
if CameraPackageToBeExecute != {}: # if camera operations are configured
_camera_isUsed = True
CamSettigList = CameraPackageToBeExecute["Settings"]
self.HamamatsuCam.StartStreaming(BufferNumber = CameraPackageToBeExecute["Buffer_number"],
trigger_source = CamSettigList[CamSettigList.index("trigger_source")+1],
exposure_time = CamSettigList[CamSettigList.index("exposure_time")+1],
trigger_active = CamSettigList[CamSettigList.index("trigger_active")+1],
subarray_hsize = CamSettigList[CamSettigList.index("subarray_hsize")+1],
subarray_vsize = CamSettigList[CamSettigList.index("subarray_vsize")+1],
subarray_hpos = CamSettigList[CamSettigList.index("subarray_hpos")+1],
subarray_vpos = CamSettigList[CamSettigList.index("subarray_vpos")+1])
# HamamatsuCam starts another thread to pull out frames from buffer.
# Make sure that the camera is prepared before waveform execution.
# while self.HamamatsuCam.isStreaming == False:
# print('Waiting for camera...')
# time.sleep(0.5)
time.sleep(1)
print('Now start waveforms')
#----------------Waveforms operations--------------
if WaveformPackageGalvoInfor != 'NoGalvo': # Unpack the information of galvo scanning.
self.readinchan = WaveformPackageGalvoInfor[0]
self.repeatnum = WaveformPackageGalvoInfor[1]
self.PMT_data_index_array = WaveformPackageGalvoInfor[2]
self.averagenum = WaveformPackageGalvoInfor[3]
self.lenSample_1 = WaveformPackageGalvoInfor[4]
self.ScanArrayXnum = WaveformPackageGalvoInfor[5]
self.adcollector = DAQmission()
# self.adcollector.collected_data.connect(self.ProcessData)
self.adcollector.runWaveforms(clock_source = self.clock_source, sampling_rate = WaveformPackageToBeExecute[0],
analog_signals = WaveformPackageToBeExecute[1], digital_signals = WaveformPackageToBeExecute[2],
readin_channels = WaveformPackageToBeExecute[3])
self.adcollector.save_as_binary(self.scansavedirectory)
self.recorded_raw_data = self.adcollector.get_raw_data()
self.Process_raw_data()
#------------------Camera saving-------------------
if _camera_isUsed == True:
self.HamamatsuCam.isSaving = True
img_text = "_Cam_"+str(self.RoundWaveformIndex[1])+"_Zpos" + str(self.ZStackOrder)
self.cam_tif_name = self.generate_tif_name(extra_text = img_text)
self.HamamatsuCam.StopStreaming(saving_dir = self.cam_tif_name)
# Make sure that the saving process is finished.
while self.HamamatsuCam.isSaving == True:
print('Camera saving...')
time.sleep(0.5)
time.sleep(1)
time.sleep(0.5)
class ScanningExecutionThread(QThread):
ScanningResult = pyqtSignal(np.ndarray, np.ndarray, object, object) #The signal for the measurement, we can connect to this signal
#%%
def __init__(self, RoundQueueDict, RoundCoordsDict, GeneralSettingDict, *args, **kwargs):
super().__init__(*args, **kwargs)
self.RoundQueueDict = RoundQueueDict
self.RoundCoordsDict = RoundCoordsDict
self.GeneralSettingDict = GeneralSettingDict
self.Status_list = None
self.ludlStage = LudlStage("COM12")
self.watchdog_flag = True
self.clock_source = 'DAQ' # Should be set by GUI.
self.scansavedirectory = self.GeneralSettingDict['savedirectory']
self.meshgridnumber = int(self.GeneralSettingDict['Meshgrid'])
self.wavelength_offset = 0 # An offset of 0.002 mm is observed between 900 and 1280 nm.
#%%
def run(self):
"""~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Connect devices.
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"""
"""
# =============================================================================
# connect the Objective motor
# =============================================================================
"""
print('----------------------Starting to connect the Objective motor-------------------------')
self.pi_device_instance = PIMotor()
print('Objective motor connected.')
self.errornum = 0
self.init_focus_position = self.pi_device_instance.pidevice.qPOS(self.pi_device_instance.pidevice.axes)['1']
print("init_focus_position : {}".format(self.init_focus_position))
"""
# =============================================================================
# connect the Hmamatsu camera
# =============================================================================
"""
self._use_camera = False
# Check if camera is used.
for key in self.RoundQueueDict:
if "RoundPackage_" in key:
for waveform_and_cam_key in self.RoundQueueDict[key][1]:
if "CameraPackage_" in waveform_and_cam_key:
if len(self.RoundQueueDict[key][1][waveform_and_cam_key]) != 0:
self._use_camera = True
if self._use_camera:
print('Connecting camera...')
self.HamamatsuCam = CamActuator()
self.HamamatsuCam.initializeCamera()
else:
print('No camera involved.')
"""
# =============================================================================
# connect the Insight X3
# =============================================================================
"""
if len(self.RoundQueueDict['InsightEvents']) != 0:
self.Laserinstance = InsightX3('COM11')
try:
# querygap = 1.1
# self.Laserinstance.SetWatchdogTimer(0) # Disable the laser watchdog!
# Status_watchdog_thread = threading.Thread(target = self.Status_watchdog, args=[querygap], daemon=True)
# Status_watchdog_thread.start()
# time.sleep(1)
#-------------Initialize laser--------------
self.watchdog_flag = False
time.sleep(0.5)
warmupstatus = 0
while int(warmupstatus) != 100:
warmupstatus = self.Laserinstance.QueryWarmupTime()
time.sleep(0.6)
self.watchdog_flag = True
time.sleep(0.5)
except:
print('Laser not connected.')
# If turn on the laser shutter in the beginning
if 'Shutter_Open' in self.GeneralSettingDict['StartUpEvents']:
time.sleep(0.5)
self.Laserinstance.Open_TunableBeamShutter()
time.sleep(0.5)
"""
# =============================================================================
# Initialize ML
# =============================================================================
"""
self._use_ML = False
# Check if machine learning segmentation is used.
for key in self.RoundQueueDict:
if "RoundPackage_" in key:
for photocycle_key in self.RoundQueueDict[key][2]:
if "PhotocyclePackage_" in photocycle_key:
if len(self.RoundQueueDict[key][2][photocycle_key]) != 0:
self._use_ML = True
if self._use_ML:
from ImageAnalysis.ImageProcessing_MaskRCNN import ProcessImageML
self.Predictor = ProcessImageML()
print("ML loaded.")
#%%
"""~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Execution
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"""
GridSequence = 0
TotalGridNumber = self.meshgridnumber**2
for EachGrid in range(TotalGridNumber):
"""
#------------------------------------------------------------------------------
#:::::::::::::::::::::::::::::::: AT EACH GRID ::::::::::::::::::::::::::::::::
#------------------------------------------------------------------------------
"""
self.Grid_index = EachGrid
"""
# =============================================================================
# For each small repeat unit in the scanning meshgrid
# =============================================================================
"""
time.sleep(0.5)
for EachRound in range(int(len(self.RoundQueueDict)/2-1)): # EachRound is the round sequence number starting from 0, while the actual number used in dictionary is 1.
"""
#-------------------------------------------------------------------------------
#:::::::::::::::::::::::::::::::: AT EACH ROUND ::::::::::::::::::::::::::::::::
#-------------------------------------------------------------------------------
"""
print ('----------------------------------------------------------------------------')
print('Below is Grid {}, Round {}.'.format(EachGrid, EachRound+1)) # EachRound+1 is the corresponding round number when setting the dictionary starting from round 1.
"""
# =============================================================================
# Execute Insight event at the beginning of each round
# =============================================================================
"""
self.laser_init(EachRound)
"""
# =============================================================================
# Execute filter event at the beginning of each round
# =============================================================================
"""
self.filters_init(EachRound)
"""
# =============================================================================
# Generate focus position list at the beginning of each round
# =============================================================================
"""
if EachRound == 0:
ZStackinfor = self.GeneralSettingDict['FocusStackInfoDict']['RoundPackage_{}'.format(EachRound+1)]
ZStackNum = int(ZStackinfor[ZStackinfor.index('Focus')+5])
ZStackStep = float(ZStackinfor[ZStackinfor.index('Being')+5:len(ZStackinfor)])
# Generate position list.
ZStacklinspaceStart = self.init_focus_position - (math.floor(ZStackNum/2)) * ZStackStep
ZStacklinspaceEnd = self.init_focus_position + (ZStackNum - math.floor(ZStackNum/2)-1) * ZStackStep
self.ZStackPosList = np.linspace(ZStacklinspaceStart, ZStacklinspaceEnd, num = ZStackNum)
self.currentCoordsSeq = 0
#%%
#-------------Unpack infor for stage move.
CoordsNum = len(self.RoundCoordsDict['CoordsPackage_{}'.format(EachRound+1)])
for EachCoord in range(CoordsNum):
"""
#------------------------------------------------------------------------------------
#:::::::::::::::::::::::::::::::: AT EACH COORDINATE ::::::::::::::::::::::::::::::::
#------------------------------------------------------------------------------------
"""
self.error_massage = None
self.currentCoordsSeq += 1
"""
# =============================================================================
# Stage movement
# =============================================================================
"""
self.coord_array = self.RoundCoordsDict['CoordsPackage_{}'.format(EachRound+1)][EachCoord]
# Offset coordinate row value for each well.
ScanningGridOffset_Row = int(EachGrid % self.meshgridnumber) * (self.GeneralSettingDict['StageGridOffset'])
# Offset coordinate colunm value for each well.
ScanningGridOffset_Col = int(EachGrid/self.meshgridnumber) * (self.GeneralSettingDict['StageGridOffset'])
RowIndex = self.coord_array['row'] + ScanningGridOffset_Row
ColumnIndex = self.coord_array['col'] + ScanningGridOffset_Col
try:
# for _ in range(2): # Repeat twice
# self.ludlStage.moveAbs(RowIndex,ColumnIndex) # Row/Column indexs of np.array are opposite of stage row-col indexs.
# time.sleep(1)
self.ludlStage.moveAbs(RowIndex,ColumnIndex) # Row/Column indexs of np.array are opposite of stage row-col indexs.
time.sleep(1.2)
except:
self.error_massage = 'Fail_MoveStage'
self.errornum += 1
print('Stage move failed! Error number: {}'.format(int(self.errornum)))
time.sleep(0.2)
"""
# =============================================================================
# Focus position
# Unpack the focus stack information, conduct auto-focusing if set.
# =============================================================================
"""
# Here also generate the ZStackPosList.
self.ZStackNum = self.unpack_focus_stack(EachGrid, EachRound, EachCoord)
self.stack_focus_degree_list = []
print('*******************************************Round {}. Current index: {}.**************************************************'.format\
(EachRound+1, [RowIndex,ColumnIndex]))
#------------------Move to Z stack focus-------------------
for EachZStackPos in range(self.ZStackNum):
"""
#------------------------------------------------------------------------------------
#:::::::::::::::::::::::::::::::: AT EACH ZSTACK ::::::::::::::::::::::::::::::::::::
#------------------------------------------------------------------------------------
"""
print('--------------------------------------------Stack {}--------------------------------------------------'.format(EachZStackPos+1))
if self.ZStackNum > 1:
self.ZStackOrder = int(EachZStackPos +1) # Here the first one is 1, not starting from 0.
self.FocusPos = self.ZStackPosList[EachZStackPos]# + self.wavelength_offset
# Add the focus degree of previous image to the list.
# For stack of 3 only.
if EachZStackPos > 0:
try:
self.stack_focus_degree_list.append(self.FocusDegree_img_reconstructed)
except:
# FocusDegree_img_reconstructed is not generated with camera imaging.
pass
print('stack_focus_degree_list is {}'.format(self.stack_focus_degree_list))
#-----Suppose now it's the 3rd stack position-----
if len(self.stack_focus_degree_list) == 2:
if self.stack_focus_degree_list[-1] < self.stack_focus_degree_list[-2]:
self.FocusPos = self.ZStackPosList[0] - (self.ZStackPosList[1] - self.ZStackPosList[0])/2
print('Focus degree decreasing, run the other direction.')
#-------------------------------------------------
print('Target focus pos: {}'.format(self.FocusPos))
self.pi_device_instance.move(self.FocusPos)
# self.auto_focus_positionInStack = self.pi_device_instance.pidevice.qPOS(self.pi_device_instance.pidevice.axes)
# print("Current position: {:.4f}".format(self.auto_focus_positionInStack['1']))
time.sleep(0.3)
else:
self.ZStackOrder = 1
self.FocusPos = self.init_focus_position
"""
# =============================================================================
# Execute waveform packages
# =============================================================================
"""
self.Waveform_sequence_Num = int(len(self.RoundQueueDict['RoundPackage_{}'.format(EachRound+1)][0]))
#------------For waveforms in each coordinate----------
for EachWaveform in range(self.Waveform_sequence_Num):
"""
# =============================================================================
# For photo-cycle
# =============================================================================
"""
# Get the photo cycle information
PhotocyclePackageToBeExecute = self.RoundQueueDict['RoundPackage_{}'.format(EachRound+1)][2] \
["PhotocyclePackage_{}".format(EachWaveform+1)]
# See if in this waveform sequence photo cycle is involved.
# PhotocyclePackageToBeExecute is {} if not configured.
if len(PhotocyclePackageToBeExecute) > 0:
# Load the previous acquired camera image
self.cam_tif_name = r"M:\tnw\ist\do\projects\Neurophotonics\Brinkslab\Data\Octoscope\2020-8-13 Screening Archon1 library V5 and 6\V6\Round2_Coords181_R19800C0_PMT_0Zmax.tif"
previous_cam_img = imread(self.cam_tif_name)
img_width = previous_cam_img.shape[1]
img_height = previous_cam_img.shape[0]
# Get the segmentation of full image.
fig, ax = plt.subplots()
MLresults = self.Predictor.DetectionOnImage(previous_cam_img, axis = ax)
ROI_number = len(MLresults["scores"])
print('roi number: {}'.format(ROI_number))
for each_ROI in range(ROI_number):
# if MLresults['class_ids'][each_ROI] == 3:
ROIlist = MLresults['rois'][each_ROI]
print(ROIlist)
# np array's column([1]) is the width of image, and is the row in stage coordinates.
ROI_center_width = int(ROIlist[1] + (ROIlist[3] - ROIlist[1])/2)
print('ROI_center_width '.format(ROIlist))
ROI_center_height = int(ROIlist[0] + (ROIlist[2] + ROIlist[0])/2)
print('ROI_center_height '.format(ROIlist))
cam_stage_transform_factor = 1.135
stage_move_col = (int((img_width)/2) - ROI_center_width) * cam_stage_transform_factor
print(stage_move_col)
stage_move_row = (int((img_height)/2) - ROI_center_height) * cam_stage_transform_factor
print(stage_move_row)
# Move cell of interest to the center of field of view
self.ludlStage.moveRel(xRel = stage_move_row, yRel= stage_move_col)
time.sleep(1)
# Move the cell back
self.ludlStage.moveRel(xRel = -1*stage_move_row, yRel= -1*stage_move_col)
time.sleep(1)
#--------------------------------------------------
"""
# =============================================================================
# Execute pre-set operations at EACH COORDINATE.
# =============================================================================
"""
self.inidividual_coordinate_operation(EachRound, EachWaveform, RowIndex, ColumnIndex)
time.sleep(0.6) # Wait for receiving data to be done.
time.sleep(0.5)
print('*************************************************************************************************************************')
#%%
"""~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Disconnect devices.
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"""
# Switch off laser
if len(self.RoundQueueDict['InsightEvents']) != 0:
self.watchdog_flag = False
time.sleep(0.5)
self.Laserinstance.Close_TunableBeamShutter()
time.sleep(0.5)
self.Laserinstance.SaveVariables()
self.Laserinstance.Turn_Off_PumpLaser()
# Disconnect camera
if self._use_camera == True:
self.HamamatsuCam.Exit()
# Disconnect focus motor
try:
self.pi_device_instance.CloseMotorConnection()
print('Objective motor disconnected.')
except:
pass
#%%
def laser_init(self, EachRound):
"""
Execute Insight event at the beginning of each round
Parameters
----------
EachRound : int
Round index.
Returns
-------
None.
"""
#-Unpack infor for Insight X3. In the list, the first one is for shutter event and the second one is for wavelength event.
InsightX3EventIndexList = [i for i,x in enumerate(self.RoundQueueDict['InsightEvents']) if 'Round_{}'.format(EachRound+1) in x]
if len(InsightX3EventIndexList) == 1:
print(InsightX3EventIndexList)
InsightText = self.RoundQueueDict['InsightEvents'][InsightX3EventIndexList[0]]
if 'Shutter_Open' in InsightText:
self.watchdog_flag = False
time.sleep(0.5)
self.Laserinstance.Open_TunableBeamShutter()
time.sleep(0.5)
print('Laser shutter open.')
self.watchdog_flag = True
time.sleep(0.5)
elif 'Shutter_Close' in InsightText:
self.watchdog_flag = False
time.sleep(0.5)
self.Laserinstance.Close_TunableBeamShutter()
time.sleep(0.5)
print('Laser shutter closed.')
self.watchdog_flag = True
time.sleep(0.5)
elif 'WavelengthTo' in InsightText:
self.watchdog_flag = False
time.sleep(0.5)
TargetWavelen = int(InsightText[InsightText.index('To_')+3:len(InsightText)])
if TargetWavelen == 1280:
self.wavelength_offset = -0.002 # give an offset if wavelength goes to 1280.
elif TargetWavelen == 900:
self.wavelength_offset = 0
self.Laserinstance.SetWavelength(TargetWavelen)
time.sleep(5)
self.watchdog_flag = True
time.sleep(0.5)
elif len(InsightX3EventIndexList) == 2:
InsightText_wl = self.RoundQueueDict['InsightEvents'][InsightX3EventIndexList[1]]
InsightText_st = self.RoundQueueDict['InsightEvents'][InsightX3EventIndexList[0]]
if 'WavelengthTo' in InsightText_wl and 'Shutter_Open' in InsightText_st:
self.watchdog_flag = False
time.sleep(0.5)
TargetWavelen = int(InsightText_wl[InsightText_wl.index('To_')+3:len(InsightText_wl)])
self.Laserinstance.SetWavelength(TargetWavelen)
if TargetWavelen == 1280:
self.wavelength_offset = -0.002 # give an offset if wavelength goes to 1280.
elif TargetWavelen == 900:
self.wavelength_offset = 0
time.sleep(5)
self.Laserinstance.Open_TunableBeamShutter()
print('Laser shutter open.')
self.watchdog_flag = True
time.sleep(0.5)
elif 'WavelengthTo' in InsightText_wl and 'Shutter_Close' in InsightText_st:
self.watchdog_flag = False
time.sleep(0.5)
TargetWavelen = int(InsightText_wl[InsightText_wl.index('To_')+3:len(InsightText_wl)])
self.Laserinstance.SetWavelength(TargetWavelen)
if TargetWavelen == 1280:
self.wavelength_offset = -0.002 # give an offset if wavelength goes to 1280.
elif TargetWavelen == 900:
self.wavelength_offset = 0
time.sleep(5)
self.Laserinstance.Close_TunableBeamShutter()
time.sleep(1)
print('Laser shutter closed.')
self.watchdog_flag = True
time.sleep(0.5)
time.sleep(2)
def filters_init(self, EachRound):
"""
Execute filter event at the beginning of each round.
Parameters
----------
EachRound : int
Round index.
Returns
-------
None.
"""
#-Unpack infor for filter event. In the list, the first one is for ND filter and the second one is for emission filter.
FilterEventIndexList = [i for i,x in enumerate(self.RoundQueueDict['FilterEvents']) if 'Round_{}'.format(EachRound+1) in x]
if len(FilterEventIndexList) > 0:
NDposText = self.RoundQueueDict['FilterEvents'][FilterEventIndexList[0]]
NDnumber = NDposText[NDposText.index('ToPos_')+6:len(NDposText)]
EMposText = self.RoundQueueDict['FilterEvents'][FilterEventIndexList[1]]
EMprotein = EMposText[EMposText.index('ToPos_')+6:len(EMposText)]
# "COM9" for filter 1 port, which has ND values from 0 to 3.
# "COM7" for filter 2 port, which has ND values from 0 to 0.5.
if NDnumber == '0':
ND_filter1_Pos = 0
ND_filter2_Pos = 0
elif NDnumber == '1':
ND_filter1_Pos = 1
ND_filter2_Pos = 0
elif NDnumber == '2':
ND_filter1_Pos = 2
ND_filter2_Pos = 0
elif NDnumber == '2.3':
ND_filter1_Pos = 2
ND_filter2_Pos = 2
elif NDnumber == '2.5':
ND_filter1_Pos = 2
ND_filter2_Pos = 3
elif NDnumber == '0.5':
ND_filter1_Pos = 0
ND_filter2_Pos = 3
elif NDnumber == '0.3':
ND_filter1_Pos = 0
ND_filter2_Pos = 2
if EMprotein == 'Arch':
EM_filter_Pos = 0
elif EMprotein == 'eGFP' or EMprotein == 'Citrine':
EM_filter_Pos = 1
# Execution
if ND_filter1_Pos != None and ND_filter2_Pos != None:
#Move filter 1
self.filter1 = ELL9Filter("COM9")
self.filter1.moveToPosition(ND_filter1_Pos)
time.sleep(1)
#Move filter 2
self.filter2 = ELL9Filter("COM7")
self.filter2.moveToPosition(ND_filter2_Pos)
time.sleep(1)
if EM_filter_Pos != None:
self.filter3 = ELL9Filter("COM15")
self.filter3.moveToPosition(EM_filter_Pos)
time.sleep(1)
def unpack_focus_stack(self, EachGrid, EachRound, EachCoord):
"""
Unpack the focus stack information.
Determine focus position either from pre-set numbers of by auto-focusing.
Parameters
----------
EachGrid : int
Current grid index.
EachRound : int
Current round index.
EachCoord : int
Current coordinate index.
Returns
-------
ZStackNum : int
Number of focus positions in stack.
ZStackPosList : list
List of focus stack positions for objective to go to.
"""
ZStackinfor = self.GeneralSettingDict['FocusStackInfoDict']['RoundPackage_{}'.format(EachRound+1)]
ZStackNum = int(ZStackinfor[ZStackinfor.index('Focus')+5])
ZStackStep = float(ZStackinfor[ZStackinfor.index('Being')+5:len(ZStackinfor)])
# If manual focus correction applies, unpact the target focus infor.
if len(self.GeneralSettingDict['FocusCorrectionMatrixDict']) > 0:
FocusPosArray = self.GeneralSettingDict['FocusCorrectionMatrixDict']['RoundPackage_{}_Grid_{}'.format(EachRound+1, EachGrid)]
FocusPosArray = FocusPosArray.flatten('F')
FocusPos_fromCorrection = FocusPosArray[EachCoord]
ZStacklinspaceStart = FocusPos_fromCorrection - (math.floor(ZStackNum/2))* ZStackStep
ZStacklinspaceEnd = FocusPos_fromCorrection + (ZStackNum - math.floor(ZStackNum/2)-1) * ZStackStep
# With auto-focus correction
else:
# If go for auto-focus at this coordinate
auto_focus_flag = self.coord_array['auto_focus_flag']
# auto_focus_flag = False
print('focus_position {}'.format(self.coord_array['focus_position']))
#-----------------------Auto focus---------------------------------
if auto_focus_flag == "yes":
if self.coord_array['focus_position'] == -1.:
instance_FocusFinder = FocusFinder(motor_handle = self.pi_device_instance)
print("--------------Start auto-focusing-----------------")
# instance_FocusFinder.total_step_number = 7
# instance_FocusFinder.init_step_size = 0.013
# self.auto_focus_position = instance_FocusFinder.gaussian_fit()
self.auto_focus_position = instance_FocusFinder.bisection()
relative_move_coords = [[1550,0],[0,1550],[1550,1550]]
trial_num = 0
while self.auto_focus_position == False: # If there's no cell in FOV
if trial_num <= 2:
print('No cells found. move to next pos.')
# Move to next position in real scanning coordinates.
self.ludlStage.moveRel(relative_move_coords[trial_num][0],relative_move_coords[trial_num][1])
time.sleep(1)
print('Now stage pos is {}'.format(self.ludlStage.getPos()))
self.auto_focus_position = instance_FocusFinder.bisection()
# Move back
self.ludlStage.moveRel(-1*relative_move_coords[trial_num][0],-1*relative_move_coords[trial_num][1])
trial_num += 1
else:
print('No cells in neighbouring area.')
self.auto_focus_position = self.ZStackPosList[int(len(self.ZStackPosList)/2)]
break
print("--------------End of auto-focusing----------------")
time.sleep(1)
# Record the position, try to write it in the NEXT round dict.
try:
self.RoundCoordsDict['CoordsPackage_{}'.format(EachRound + 2)][EachCoord]['focus_position'] = self.auto_focus_position
except:# If it's already the last round, skip.
pass
# Generate position list.
ZStacklinspaceStart = self.auto_focus_position - (math.floor(ZStackNum/2)) * ZStackStep
ZStacklinspaceEnd = self.auto_focus_position + (ZStackNum - math.floor(ZStackNum/2)-1) * ZStackStep
else: # If there's already position from last round, move to it.
self.previous_auto_focus_position = self.RoundCoordsDict['CoordsPackage_{}'.format(EachRound+1)][EachCoord]['focus_position']
try:
# Record the position, try to write it in the NEXT round dict.
self.RoundCoordsDict['CoordsPackage_{}'.format(EachRound + 2)][EachCoord]['focus_position'] = self.previous_auto_focus_position
except:
pass
# Generate position list.
ZStacklinspaceStart = self.previous_auto_focus_position - (math.floor(ZStackNum/2)) * ZStackStep
ZStacklinspaceEnd = self.previous_auto_focus_position + (ZStackNum - math.floor(ZStackNum/2)-1) * ZStackStep
# self.previous_auto_focus_position = self.auto_focus_position
# print("=====================Move to last recorded position=================")
# self.pi_device_instance.move(self.previous_auto_focus_position)
# time.sleep(0.2)
# instance_FocusFinder = FocusFinder(motor_handle = self.pi_device_instance)
# print("--------------Start auto-focusing-----------------")
# self.auto_focus_position = instance_FocusFinder.bisection()
# try:
# if self.auto_focus_position[0] == False: # If there's no cell in FOV
# # Skip? mid_position = [False, self.current_pos]
# self.auto_focus_position = self.auto_focus_position[1]
# except:
# pass
# print("--------------End of auto-focusing----------------")
# time.sleep(1)
# # Record the position, try to write it in the NEXT round dict.
# try:
# self.RoundCoordsDict['CoordsPackage_{}'.format(EachRound + 2)][EachCoord]['focus_position'] = self.auto_focus_position
# except:# If it's already the last round, skip.
# pass
# Generate the position list, for none-auto-focus coordinates they will use the same list variable.
self.ZStackPosList = np.linspace(ZStacklinspaceStart, ZStacklinspaceEnd, num = ZStackNum)
print('ZStackPos is : {}'.format(self.ZStackPosList))
#------------------------------------------------------------------
# If not auto focus, use the same list variable self.ZStackPosList.
else:
pass
return ZStackNum
def inidividual_coordinate_operation(self, EachRound, EachWaveform, RowIndex, ColumnIndex):
"""
Execute pre-set operations at each coordinate.
Parameters
----------
EachRound : int
Current round index.
EachWaveform : int
Current waveform package index.
RowIndex : int
Current sample stage row index.
ColumnIndex : int
Current sample stage row index.
Returns
-------
None.
"""
# Extract information
WaveformPackageToBeExecute = self.RoundQueueDict['RoundPackage_{}'.format(EachRound+1)][0]['WaveformPackage_{}'.format(EachWaveform+1)]
CameraPackageToBeExecute = self.RoundQueueDict['RoundPackage_{}'.format(EachRound+1)][1]["CameraPackage_{}".format(EachWaveform+1)]
WaveformPackageGalvoInfor = self.RoundQueueDict['GalvoInforPackage_{}'.format(EachRound+1)]['GalvoInfor_{}'.format(EachWaveform+1)]
self.readinchan = WaveformPackageToBeExecute[3]
self.RoundWaveformIndex = [EachRound+1, EachWaveform+1] # first is current round number, second is current waveform package number.
self.CurrentPosIndex = [RowIndex, ColumnIndex]
#----------------Camera operations-----------------
_camera_isUsed = False
if CameraPackageToBeExecute != {}: # if camera operations are configured
_camera_isUsed = True
CamSettigList = CameraPackageToBeExecute["Settings"]
self.HamamatsuCam.StartStreaming(BufferNumber = CameraPackageToBeExecute["Buffer_number"],
trigger_source = CamSettigList[CamSettigList.index("trigger_source")+1],
exposure_time = CamSettigList[CamSettigList.index("exposure_time")+1],
trigger_active = CamSettigList[CamSettigList.index("trigger_active")+1],
subarray_hsize = CamSettigList[CamSettigList.index("subarray_hsize")+1],
subarray_vsize = CamSettigList[CamSettigList.index("subarray_vsize")+1],
subarray_hpos = CamSettigList[CamSettigList.index("subarray_hpos")+1],
subarray_vpos = CamSettigList[CamSettigList.index("subarray_vpos")+1])
# HamamatsuCam starts another thread to pull out frames from buffer.
# Make sure that the camera is prepared before waveform execution.
# while self.HamamatsuCam.isStreaming == False:
# print('Waiting for camera...')
# time.sleep(0.5)
time.sleep(1)
print('Now start waveforms')
#----------------Waveforms operations--------------
if WaveformPackageGalvoInfor != 'NoGalvo': # Unpack the information of galvo scanning.
self.readinchan = WaveformPackageGalvoInfor[0]
self.repeatnum = WaveformPackageGalvoInfor[1]
self.PMT_data_index_array = WaveformPackageGalvoInfor[2]
self.averagenum = WaveformPackageGalvoInfor[3]
self.lenSample_1 = WaveformPackageGalvoInfor[4]
self.ScanArrayXnum = WaveformPackageGalvoInfor[5]
self.adcollector = DAQmission()
# self.adcollector.collected_data.connect(self.ProcessData)
self.adcollector.runWaveforms(clock_source = self.clock_source, sampling_rate = WaveformPackageToBeExecute[0],
analog_signals = WaveformPackageToBeExecute[1], digital_signals = WaveformPackageToBeExecute[2],
readin_channels = WaveformPackageToBeExecute[3])
self.adcollector.save_as_binary(self.scansavedirectory)
self.recorded_raw_data = self.adcollector.get_raw_data()
self.Process_raw_data()
#------------------Camera saving-------------------
if _camera_isUsed == True:
self.HamamatsuCam.isSaving = True
img_text = "_Cam_"+str(self.RoundWaveformIndex[1])+"_Zpos" + str(self.ZStackOrder)
self.cam_tif_name = self.generate_tif_name(extra_text = img_text)
self.HamamatsuCam.StopStreaming(saving_dir = self.cam_tif_name)
# Make sure that the saving process is finished.
while self.HamamatsuCam.isSaving == True:
print('Camera saving...')
time.sleep(0.5)
time.sleep(1)
time.sleep(0.5)
def Process_raw_data(self):
self.channel_number = len(self.recorded_raw_data)
self.data_collected_0 = self.recorded_raw_data[0][0:len(self.recorded_raw_data[0])-1]*-1
print(len(self.data_collected_0))
if self.channel_number == 1:
if 'Vp' in self.readinchan:
pass
elif 'Ip' in self.readinchan:
pass
elif 'PMT' in self.readinchan: # repeatnum, PMT_data_index_array, averagenum, ScanArrayXnum
# Reconstruct the image from np array and save it.
self.PMT_image_processing()
elif self.channel_number == 2:
if 'PMT' not in self.readinchan:
pass
elif 'PMT' in self.readinchan:
self.PMT_image_processing()
print('ProcessData executed.')
# def ProcessData(self, data_waveformreceived):
# print('ZStackOrder is:'+str(self.ZStackOrder)+'numis_'+str(self.ZStackNum))
# self.adcollector.save_as_binary(self.scansavedirectory)
# self.channel_number = len(data_waveformreceived)
# self.data_collected_0 = data_waveformreceived[0]*-1
# self.data_collected_0 = self.data_collected_0[0:len(self.data_collected_0)-1]
# print(len(self.data_collected_0))
# if self.channel_number == 1:
# if 'Vp' in self.readinchan:
# pass
# elif 'Ip' in self.readinchan:
# pass
# elif 'PMT' in self.readinchan: # repeatnum, PMT_data_index_array, averagenum, ScanArrayXnum
# # Reconstruct the image from np array and save it.
# self.PMT_image_processing()
# elif self.channel_number == 2:
# if 'PMT' not in self.readinchan:
# pass
# elif 'PMT' in self.readinchan:
# self.PMT_image_processing()
# print('ProcessData executed.')
def PMT_image_processing(self):
"""
Reconstruct the image from np array and save it.
Returns
-------
None.
"""
for imageSequence in range(self.repeatnum):
try:
self.PMT_image_reconstructed_array = self.data_collected_0[np.where(self.PMT_data_index_array == imageSequence+1)]
Dataholder_average = np.mean(self.PMT_image_reconstructed_array.reshape(self.averagenum, -1), axis=0)
Value_yPixels = int(self.lenSample_1/self.ScanArrayXnum)
self.PMT_image_reconstructed = np.reshape(Dataholder_average, (Value_yPixels, self.ScanArrayXnum))
self.PMT_image_reconstructed = self.PMT_image_reconstructed[:, 50:550] # Crop size based on: M:\tnw\ist\do\projects\Neurophotonics\Brinkslab\Data\Xin\2019-12-30 2p beads area test 4um
# self.PMT_image_reconstructed = self.PMT_image_reconstructed[:, 70:326] # for 256*256 images
# Evaluate the focus degree of re-constructed image.
self.FocusDegree_img_reconstructed = ProcessImage.local_entropy(self.PMT_image_reconstructed.astype('float32'))
print('FocusDegree_img_reconstructed is {}'.format(self.FocusDegree_img_reconstructed))
# Save the individual file.
with skimtiff.TiffWriter(os.path.join(self.scansavedirectory, 'Round'+str(self.RoundWaveformIndex[0]) + '_Grid' + str(self.Grid_index) +'_Coords'+str(self.currentCoordsSeq)+'_R'+str(self.CurrentPosIndex[0])+'C'+str(self.CurrentPosIndex[1])+'_PMT_'+str(imageSequence)+'Zpos'+str(self.ZStackOrder)+'.tif'), imagej = True) as tif:
tif.save(self.PMT_image_reconstructed.astype('float32'), compress=0, metadata = {"FocusPos: " : str(self.FocusPos)})
plt.figure()
plt.imshow(self.PMT_image_reconstructed, cmap = plt.cm.gray) # For reconstructed image we pull out the first layer, getting 2d img.
plt.show()
#---------------------------------------------For multiple images in one z pos, Stack the arrays into a 3d array--------------------------------------------------------------------------
# if imageSequence == 0:
# self.PMT_image_reconstructed_stack = self.PMT_image_reconstructed[np.newaxis, :, :] # Turns into 3d array
# else:
# self.PMT_image_reconstructed_stack = np.concatenate((self.PMT_image_reconstructed_stack, self.PMT_image_reconstructed[np.newaxis, :, :]), axis=0)
# print(self.PMT_image_reconstructed_stack.shape)
#---------------------------------------------Calculate the z max projection-----------------------------------------------------------------------
if self.repeatnum == 1: # Consider one repeat image situlation
if self.ZStackNum > 1:
if self.ZStackOrder == 1:
self.PMT_image_maxprojection_stack = self.PMT_image_reconstructed[np.newaxis, :, :]
else:
self.PMT_image_maxprojection_stack = np.concatenate((self.PMT_image_maxprojection_stack, self.PMT_image_reconstructed[np.newaxis, :, :]), axis=0)
else:
self.PMT_image_maxprojection_stack = self.PMT_image_reconstructed[np.newaxis, :, :]
# Save the max projection image
if self.ZStackOrder == self.ZStackNum:
self.PMT_image_maxprojection = np.max(self.PMT_image_maxprojection_stack, axis=0)
# Save the zmax file.
with skimtiff.TiffWriter(os.path.join(self.scansavedirectory, 'Round'+str(self.RoundWaveformIndex[0])+ '_Grid' + str(self.Grid_index) + '_Coords'+str(self.currentCoordsSeq)+'_R'+str(self.CurrentPosIndex[0])+'C'+str(self.CurrentPosIndex[1])+'_PMT_'+str(imageSequence)+'Zmax'+'.tif'), imagej = True) as tif:
tif.save(self.PMT_image_maxprojection.astype('float32'), compress=0, metadata = {"FocusPos: " : str(self.FocusPos)})
except:
print('No.{} image failed to generate.'.format(imageSequence))
def generate_tif_name(self, extra_text = "_"):
tif_name = os.path.join(self.scansavedirectory, 'Round'+str(self.RoundWaveformIndex[0])+'_Coords'+str(self.currentCoordsSeq)+ \
'_R'+str(self.CurrentPosIndex[0])+'C'+str(self.CurrentPosIndex[1])+ extra_text +'.tif')
return tif_name
#----------------------------------------------------------------WatchDog for laser----------------------------------------------------------------------------------
def Status_watchdog(self, querygap):
while True:
if self.watchdog_flag == True:
self.Status_list = self.Laserinstance.QueryStatus()
time.sleep(querygap)
else:
print('Watchdog stopped')
time.sleep(querygap)
def hold(self):
constant = self.HoldingList.value()
self.executer = DAQmission()
self.executer.sendSingleAnalog("patchAO", constant / 1000 * 10)
print("Holding vm at " + str(constant) + " mV")
class FocusFinder():
def __init__(self, source_of_image = "PMT", init_search_range = 0.010, total_step_number = 5, imaging_conditions = {'edge_volt':5}, \
motor_handle = None, camera_handle = None, twophoton_handle = None, *args, **kwargs):
"""
Parameters
----------
source_of_image : string, optional
The input source of image. The default is PMT.
init_search_range : int, optional
The step size when first doing coarse searching. The default is 0.010.
total_step_number : int, optional
Number of steps in total to find optimal focus. The default is 5.
imaging_conditions : list
Parameters for imaging.
For PMT, it specifies the scanning voltage.
For camera, it specifies the AOTF voltage and exposure time.
motor_handle : TYPE, optional
Handle to control PI motor. The default is None.
twophoton_handle : TYPE, optional
Handle to control Insight X3. The default is None.
Returns
-------
None.
"""
super().__init__(*args, **kwargs)
# The step size when first doing coarse searching.
self.init_search_range = init_search_range
# Number of steps in total to find optimal focus.
self.total_step_number = total_step_number
# Parameters for imaging.
self.imaging_conditions = imaging_conditions
if motor_handle == None:
# Connect the objective if the handle is not provided.
self.pi_device_instance = PIMotor()
else:
self.pi_device_instance = motor_handle
# Current position of the focus.
self.current_pos = self.pi_device_instance.GetCurrentPos()
# Number of steps already tried.
self.steps_taken = 0
# The focus degree of previous position.
self.previous_degree_of_focus = 0
# Number of going backwards.
self.turning_point = 0
# The input source of image.
self.source_of_image = source_of_image
if source_of_image == "PMT":
self.galvo = RasterScan(Daq_sample_rate = 500000, edge_volt = self.imaging_conditions['edge_volt'])
elif source_of_image == "Camera":
if camera_handle == None:
# If no camera instance fed in, initialize camera.
self.HamamatsuCam_ins = CamActuator()
self.HamamatsuCam_ins.initializeCamera()
else:
self.HamamatsuCam_ins = camera_handle
def gaussian_fit(self, move_to_focus = True):
# The upper edge.
upper_position = self.current_pos + self.init_search_range
# The lower edge.
lower_position = self.current_pos - self.init_search_range
# Generate the sampling positions.
sample_positions = np.linspace(lower_position, upper_position, self.total_step_number)
degree_of_focus_list = []
for each_pos in sample_positions:
# Go through each position and write down the focus degree.
degree_of_focus = self.evaluate_focus(round(each_pos, 6))
degree_of_focus_list.append(degree_of_focus)
print(degree_of_focus_list)
try:
interpolated_fitted_curve = ProcessImage.gaussian_fit(degree_of_focus_list)
# Generate the inpterpolated new focus position axis.
x_axis_new = np.linspace(lower_position, upper_position, len(interpolated_fitted_curve))
# Generate a dictionary and find the position where has the highest focus degree.
max_focus_pos = dict(zip(interpolated_fitted_curve, x_axis_new))[np.amax(interpolated_fitted_curve)]
if True: # Plot the fitting.
plt.plot(sample_positions, np.asarray(degree_of_focus_list),'b+:',label='data')
plt.plot(x_axis_new, interpolated_fitted_curve,'ro:',label='fit')
plt.legend()
plt.title('Fig. Fit for focus degree')
plt.xlabel('Position')
plt.ylabel('Focus degree')
plt.show()
max_focus_pos = round(max_focus_pos, 6)
print(max_focus_pos)
self.pi_device_instance.move(max_focus_pos)
# max_focus_pos_focus_degree = self.evaluate_focus(round(max_focus_pos, 6))
except:
print("Fitting failed. Find max in the list.")
max_focus_pos = sample_positions[degree_of_focus_list.index(max(degree_of_focus_list))]
print(max_focus_pos)
if move_to_focus == True:
self.pi_device_instance.move(max_focus_pos)
return max_focus_pos
def bisection(self):
"""
Bisection way of finding focus.
Returns
-------
mid_position : float
DESCRIPTION.
"""
# The upper edge in which we run bisection.
upper_position = self.current_pos + self.init_search_range
# The lower edge in which we run bisection.
lower_position = self.current_pos - self.init_search_range
for step_index in range(1, self.total_step_number + 1):
# In each step of bisection finding.
# In the first round, get degree of focus at three positions.
if step_index == 1:
# Get degree of focus in the mid.
mid_position = (upper_position + lower_position)/2
degree_of_focus_mid = self.evaluate_focus(mid_position)
print("mid focus degree: {}".format(round(degree_of_focus_mid, 5)))
# Break the loop if focus degree is below threshold which means
# that there's no cell in image.
if not ProcessImage.if_theres_cell(self.galvo_image.astype('float32')):
print('no cell')
mid_position = False
break
# Move to top and evaluate.
degree_of_focus_up = self.evaluate_focus(obj_position = upper_position)
print("top focus degree: {}".format(round(degree_of_focus_up, 5)))
# Move to bottom and evaluate.
degree_of_focus_low = self.evaluate_focus(obj_position = lower_position)
print("bot focus degree: {}".format(round(degree_of_focus_low, 5)))
# Sorting dicitonary of degrees in ascending.
biesection_range_dic = {"top":[upper_position, degree_of_focus_up],
"bot":[lower_position, degree_of_focus_low]}
# In the next rounds, only need to go to center and update boundaries.
elif step_index > 1:
# The upper edge in which we run bisection.
upper_position = biesection_range_dic["top"][0]
# The lower edge in which we run bisection.
lower_position = biesection_range_dic["bot"][0]
# Get degree of focus in the mid.
mid_position = (upper_position + lower_position)/2
degree_of_focus_mid = self.evaluate_focus(mid_position)
print("Current focus degree: {}".format(round(degree_of_focus_mid, 5)))
# If sits in upper half, make the middle values new bottom.
if biesection_range_dic["top"][1] > biesection_range_dic["bot"][1]:
biesection_range_dic["bot"] = [mid_position, degree_of_focus_mid]
else:
biesection_range_dic["top"] = [mid_position, degree_of_focus_mid]
print("The upper pos: {}; The lower: {}".format(biesection_range_dic["top"][0], biesection_range_dic["bot"][0]))
return mid_position
def evaluate_focus(self, obj_position = None):
"""
Evaluate the focus degree of certain objective position.
Parameters
----------
obj_position : float, optional
The target objective position. The default is None.
Returns
-------
degree_of_focus : float
Degree of focus.
"""
if obj_position != None:
self.pi_device_instance.move(obj_position)
# Get the image.
if self.source_of_image == "PMT":
self.galvo_image = self.galvo.run()
plt.figure()
plt.imshow(self.galvo_image)
plt.show()
if False:
with skimtiff.TiffWriter(os.path.join(r'M:\tnw\ist\do\projects\Neurophotonics\Brinkslab\Data\Xin\2020-11-17 gaussian fit auto-focus cells\trial_11', str(obj_position).replace(".", "_")+ '.tif')) as tif:
tif.save(self.galvo_image.astype('float32'), compress=0)
degree_of_focus = ProcessImage.local_entropy(self.galvo_image.astype('float32'))
elif self.source_of_image == "Camera":
# First configure the AOTF.
self.AOTF_runner = DAQmission()
# Find the AOTF channel key
for key in self.imaging_conditions:
if 'AO' in key:
# like '488AO'
AOTF_channel_key = key
# Set the AOTF first.
self.AOTF_runner.sendSingleDigital('blankingall', True)
self.AOTF_runner.sendSingleAnalog(AOTF_channel_key, self.imaging_conditions[AOTF_channel_key])
# Snap an image from camera
self.camera_image = self.HamamatsuCam_ins.SnapImage(self.imaging_conditions['exposure_time'])
time.sleep(0.5)
# Set back AOTF
self.AOTF_runner.sendSingleDigital('blankingall', False)
self.AOTF_runner.sendSingleAnalog(AOTF_channel_key, 0)
plt.figure()
plt.imshow(self.camera_image)
plt.show()
if False:
with skimtiff.TiffWriter(os.path.join(r'M:\tnw\ist\do\projects\Neurophotonics\Brinkslab\Data\Xin\2021-03-06 Camera AF\beads', str(obj_position).replace(".", "_")+ '.tif')) as tif:
tif.save(self.camera_image.astype('float32'), compress=0)
degree_of_focus = ProcessImage.variance_of_laplacian(self.camera_image.astype('float32'))
time.sleep(0.2)
return degree_of_focus
def evaluate_focus(self, obj_position = None):
"""
Evaluate the focus degree of certain objective position.
Parameters
----------
obj_position : float, optional
The target objective position. The default is None.
Returns
-------
degree_of_focus : float
Degree of focus.
"""
if obj_position != None:
self.pi_device_instance.move(obj_position)
# Get the image.
if self.source_of_image == "PMT":
self.galvo_image = self.galvo.run()
plt.figure()
plt.imshow(self.galvo_image)
plt.show()
if False:
with skimtiff.TiffWriter(os.path.join(r'M:\tnw\ist\do\projects\Neurophotonics\Brinkslab\Data\Xin\2020-11-17 gaussian fit auto-focus cells\trial_11', str(obj_position).replace(".", "_")+ '.tif')) as tif:
tif.save(self.galvo_image.astype('float32'), compress=0)
degree_of_focus = ProcessImage.local_entropy(self.galvo_image.astype('float32'))
elif self.source_of_image == "Camera":
# First configure the AOTF.
self.AOTF_runner = DAQmission()
# Find the AOTF channel key
for key in self.imaging_conditions:
if 'AO' in key:
# like '488AO'
AOTF_channel_key = key
# Set the AOTF first.
self.AOTF_runner.sendSingleDigital('blankingall', True)
self.AOTF_runner.sendSingleAnalog(AOTF_channel_key, self.imaging_conditions[AOTF_channel_key])
# Snap an image from camera
self.camera_image = self.HamamatsuCam_ins.SnapImage(self.imaging_conditions['exposure_time'])
time.sleep(0.5)
# Set back AOTF
self.AOTF_runner.sendSingleDigital('blankingall', False)
self.AOTF_runner.sendSingleAnalog(AOTF_channel_key, 0)
plt.figure()
plt.imshow(self.camera_image)
plt.show()
if False:
with skimtiff.TiffWriter(os.path.join(r'M:\tnw\ist\do\projects\Neurophotonics\Brinkslab\Data\Xin\2021-03-06 Camera AF\beads', str(obj_position).replace(".", "_")+ '.tif')) as tif:
tif.save(self.camera_image.astype('float32'), compress=0)
degree_of_focus = ProcessImage.variance_of_laplacian(self.camera_image.astype('float32'))
time.sleep(0.2)
return degree_of_focus
def control_for_registration(self, wavelength, value):
value = int(value)
daq = DAQmission()
if value == 0:
switch = False
else:
switch = True
if wavelength == '640':
print(wavelength + ':' + str(value))
print(str(switch))
daq.sendSingleAnalog('640AO', value)
# execute_tread_singlesample_AOTF_analog = execute_tread_singlesample_analog()
# execute_tread_singlesample_AOTF_analog.set_waves('640AO', value)
# execute_tread_singlesample_AOTF_analog.start()
daq.sendSingleDigital('640blanking', switch)
# execute_tread_singlesample_AOTF_digital = execute_tread_singlesample_digital()
# execute_tread_singlesample_AOTF_digital.set_waves('640blanking', switch)
# execute_tread_singlesample_AOTF_digital.start()
elif wavelength == '532':
print(wavelength + ':' + str(value))
print(str(switch))
daq.sendSingleAnalog('532AO', value)
daq.sendSingleDigital('640blanking', switch)
# execute_tread_singlesample_AOTF_analog = execute_tread_singlesample_analog()
# execute_tread_singlesample_AOTF_analog.set_waves('532AO', value)
# execute_tread_singlesample_AOTF_analog.start()
# execute_tread_singlesample_AOTF_digital = execute_tread_singlesample_digital()
# execute_tread_singlesample_AOTF_digital.set_waves('640blanking', switch)
# execute_tread_singlesample_AOTF_digital.start()
else:
print(wavelength + ':' + str(value))
print(str(switch))
daq.sendSingleAnalog('488AO', value)
daq.sendSingleDigital('640blanking', switch)
def execute_tread_single_sample_digital(self, channel):
daq = DAQmission()
if channel == '640blanking':
if self.switchbutton_640.isChecked():
self.lasers_status['640'][0] = True
daq.sendSingleDigital(channel, True)
# execute_tread_singlesample_AOTF_digital = execute_tread_singlesample_digital()
# execute_tread_singlesample_AOTF_digital.set_waves(channel, 1)
# execute_tread_singlesample_AOTF_digital.start()
else:
self.lasers_status['640'][0] = False
daq.sendSingleDigital(channel, False)
# execute_tread_singlesample_AOTF_digital = execute_tread_singlesample_digital()
# execute_tread_singlesample_AOTF_digital.set_waves(channel, 0)
# execute_tread_singlesample_AOTF_digital.start()
elif channel == '532blanking':
if self.switchbutton_532.isChecked():
self.lasers_status['532'][0] = True
daq.sendSingleDigital(channel, True)
# execute_tread_singlesample_AOTF_digital = execute_tread_singlesample_digital()
# execute_tread_singlesample_AOTF_digital.set_waves(channel, 1)
# execute_tread_singlesample_AOTF_digital.start()
else:
self.lasers_status['532'][0] = False
daq.sendSingleDigital(channel, False)
# execute_tread_singlesample_AOTF_digital = execute_tread_singlesample_digital()
# execute_tread_singlesample_AOTF_digital.set_waves(channel, 0)
# execute_tread_singlesample_AOTF_digital.start()
elif channel == '488blanking':
if self.switchbutton_488.isChecked():
self.lasers_status['488'][0] = True
daq.sendSingleDigital(channel, True)
# execute_tread_singlesample_AOTF_digital = execute_tread_singlesample_digital()
# execute_tread_singlesample_AOTF_digital.set_waves(channel, 1)
# execute_tread_singlesample_AOTF_digital.start()
else:
self.lasers_status['488'][0] = False
daq.sendSingleDigital(channel, False)
# execute_tread_singlesample_AOTF_digital = execute_tread_singlesample_digital()
# execute_tread_singlesample_AOTF_digital.set_waves(channel, 0)
# execute_tread_singlesample_AOTF_digital.start()
elif channel == 'LED':
if self.switchbutton_LED.isChecked():
execute_tread_singlesample_AOTF_digital = execute_tread_singlesample_digital(
)
execute_tread_singlesample_AOTF_digital.set_waves(channel, 1)
execute_tread_singlesample_AOTF_digital.start()
else:
execute_tread_singlesample_AOTF_digital = execute_tread_singlesample_digital(
)
execute_tread_singlesample_AOTF_digital.set_waves(channel, 0)
execute_tread_singlesample_AOTF_digital.start()
self.sig_lasers_status_changed.emit(self.lasers_status)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.sampling_rate = 10000
self.PWM_frequency = 50
self.mission = DAQmission()
def hold(self):
constant = float(self.HoldingList.currentText()[0:3])
self.executer = DAQmission()
self.executer.sendSingleAnalog('patchAO', constant / 1000 * 10)
print("Holding vm at " + str(constant) + ' mV')
def registration(self, grid_points_x=3, grid_points_y=3):
"""
By default, generate 9 galvo voltage coordinates from (-5,-5) to (5,5),
take the camera images of these points, return a function matrix that
transforms camera_coordinates into galvo_coordinates using polynomial transform.
Parameters
----------
grid_points_x : TYPE, optional
DESCRIPTION. The default is 3.
grid_points_y : TYPE, optional
DESCRIPTION. The default is 3.
Returns
-------
transformation : TYPE
DESCRIPTION.
"""
galvothread = DAQmission()
readinchan = []
x_coords = np.linspace(-10, 10, grid_points_x + 2)[1:-1]
y_coords = np.linspace(-10, 10, grid_points_y + 2)[1:-1]
xy_mesh = np.reshape(np.meshgrid(x_coords, y_coords), (2, -1),
order='F').transpose()
galvo_coordinates = xy_mesh
camera_coordinates = np.zeros((galvo_coordinates.shape))
for i in range(galvo_coordinates.shape[0]):
galvothread.sendSingleAnalog('galvosx', galvo_coordinates[i, 0])
galvothread.sendSingleAnalog('galvosy', galvo_coordinates[i, 1])
time.sleep(1)
image = self.cam.SnapImage(0.06)
plt.imsave(
os.getcwd() +
'/CoordinatesManager/Registration_Images/2P/image_' + str(i) +
'.png', image)
camera_coordinates[i, :] = readRegistrationImages.gaussian_fitting(
image)
print('Galvo Coordinate')
print(galvo_coordinates)
print('Camera coordinates')
print(camera_coordinates)
del galvothread
self.cam.Exit()
transformation_cam2galvo = CoordinateTransformations.polynomial2DFit(
camera_coordinates, galvo_coordinates, order=1)
transformation_galvo2cam = CoordinateTransformations.polynomial2DFit(
galvo_coordinates, camera_coordinates, order=1)
print('Transformation found for x:')
print(transformation_cam2galvo[:, :, 0])
print('Transformation found for y:')
print(transformation_cam2galvo[:, :, 1])
print('galvo2cam found for x:')
print(transformation_galvo2cam[:, :, 0])
print('galvo2cam found for y:')
print(transformation_galvo2cam[:, :, 1])
return transformation_cam2galvo