class OdorGen(object):
def __init__(self,odorindex):
self.odorindex = odorindex
def assign_odor(self):
# initiate all the odor solenoids
self.odors_DAQ = DAQSimpleDOTask('Dev2_SELECT/port0/line{}'.format(self.odorindex))
print('Odor {} has been properly assigned'.format(self.odorindex))
def set_rewardodor(self,index):
reward_odor = self.odors_DAQ[index]
print('reward odor is odor {}'.format(index))
return reward_odor
def initiate(self):
self.odors_DAQ.low()
print('Odor initiation: status low')
def close(self):
self.odors_DAQ.close()
print('Connection has been closed')
class NuneTraining(Measurement):
# this is the name of the measurement that ScopeFoundry uses
# when displaying your measurement and saving data related to it
name = "nune_training"
interrupt_subthread = QtCore.Signal(())
def setup(self):
"""
Runs once during App initialization.
This is the place to load a user interface file,
define settings, and set up data structures.
"""
# Define ui file to be used as a graphical interface
# This file can be edited graphically with Qt Creator
# sibling_path function allows python to find a file in the same folder
# as this python module
self.ui_filename = sibling_path(__file__, "ant_watch_plot.ui")
#Load ui file and convert it to a live QWidget of the user interface
self.ui = load_qt_ui_file(self.ui_filename)
# Measurement Specific Settings
# This setting allows the option to save data to an h5 data file during a run
# All settings are automatically added to the Microscope user interface
self.settings.New('save_h5', dtype=bool, initial=True)
self.settings.New('save_video', dtype=bool, initial=False)
# x and y is for transmitting signal
# self.settings.New('x',dtype = float, initial = 32, ro = True, vmin = 0, vmax = 63.5)
# self.settings.New('y',dtype = float, initial = 32, ro = True, vmin = 0, vmax = 63.5)
# added by Nune
self.settings.New('filename', dtype=str, initial='trial')
self.settings.New('in_trial', dtype=bool, initial=False)
self.settings.New('view_only', dtype=bool, initial=False)
self.settings.New('lick_status', dtype=int, initial=0)
self.settings.New('play_frequency', dtype=int, initial=0)
# Define how often to update display during a run
self.display_update_period = 0.04
# Convenient reference to the hardware used in the measurement
self.wide_cam = self.app.hardware['wide_cam']
self.recorder = self.app.hardware['flirrec']
#setup experiment condition
self.wide_cam.settings.frame_rate.update_value(8)
self.wide_cam.read_from_hardware()
def setup_figure(self):
"""
Runs once during App initialization, after setup()
This is the place to make all graphical interface initializations,
build plots, etc.
"""
# connect ui widgets to measurement/hardware settings or functions
self.ui.start_pushButton.clicked.connect(self.start)
self.ui.interrupt_pushButton.clicked.connect(self.interrupt)
# Set up pyqtgraph graph_layout in the UI
self.wide_cam_layout = pg.GraphicsLayoutWidget()
self.ui.wide_cam_groupBox.layout().addWidget(self.wide_cam_layout)
#create camera image graphs
self.wide_cam_view = pg.ViewBox()
self.wide_cam_layout.addItem(self.wide_cam_view)
self.wide_cam_image = pg.ImageItem()
self.wide_cam_view.addItem(self.wide_cam_image)
#counter used for reducing refresh rate
self.wide_disp_counter = 0
def update_display(self):
"""
Displays (plots) the numpy array self.buffer.
This function runs repeatedly and automatically during the measurement run.
its update frequency is defined by self.display_update_period
"""
# check availability of display queue of the wide camera
if not hasattr(self, 'wide_disp_queue'):
pass
elif self.wide_disp_queue.empty():
pass
else:
try:
wide_disp_image = self.wide_disp_queue.get()
if type(wide_disp_image) == np.ndarray:
if wide_disp_image.shape == (
self.wide_cam.settings.height.value(),
self.wide_cam.settings.width.value()):
try:
self.wide_cam_image.setImage(wide_disp_image)
except Exception as ex:
print('Error: %s' % ex)
except Exception as ex:
print("Error: %s" % ex)
def run(self):
"""
Runs when measurement is started. Runs in a separate thread from GUI.
It should not update the graphical interface directly, and should only
focus on data acquisition.
"""
# # first, create a data file
# if self.settings['save_h5']:
# # if enabled will create an HDF5 file with the plotted data
# # first we create an H5 file (by default autosaved to app.settings['save_dir']
# # This stores all the hardware and app meta-data in the H5 file
# self.h5file = h5_io.h5_base_file(app=self.app, measurement=self)
#
# # create a measurement H5 group (folder) within self.h5file
# # This stores all the measurement meta-data in this group
# self.h5_group = h5_io.h5_create_measurement_group(measurement=self, h5group=self.h5file)
#
# # create an h5 dataset to store the data
# self.buffer_h5 = self.h5_group.create_dataset(name = 'buffer',
# shape = self.buffer.shape,
# dtype = self.buffer.dtype)
# We use a try/finally block, so that if anything goes wrong during a measurement,
# the finally block can clean things up, e.g. close the data file object.
#self.wide_cam._dev.set_buffer_count(500)
if self.settings.save_video.value():
save_dir = self.app.settings.save_dir.value()
data_path = os.path.join(save_dir,
self.app.settings.sample.value())
try:
os.makedirs(data_path)
except OSError:
print(
'directory already exists, writing to existing directory')
self.recorder.settings.path.update_value(data_path)
#frame_rate = self.wide_cam.settings.frame_rate.value()
#self.recorder.create_file('wide_mov',frame_rate)
#
# # create a subthread and connect it to the interrupt subthread signal
# self.wide_disp_queue = queue.Queue(1000)
# self.camera_thread = SubMeasurementQThread(self.camera_action)
# self.interrupt_subthread.connect(self.camera_thread.interrupt)
# #start camera
# self.wide_cam.start()
#
# #start camera subthread
# self.camera_thread.start()
# initiate all the odor solenoids
odor0 = DAQSimpleDOTask('Dev3/port0/line0')
clean0 = DAQSimpleDOTask('Dev3/port0/line1')
odor1 = DAQSimpleDOTask('Dev3/port0/line2')
clean1 = DAQSimpleDOTask('Dev3/port0/line3')
odor2 = DAQSimpleDOTask('Dev3/port0/line4')
clean2 = DAQSimpleDOTask('Dev3/port0/line5')
odor3 = DAQSimpleDOTask('Dev3/port0/line6')
clean3 = DAQSimpleDOTask('Dev3/port0/line7')
odor4 = DAQSimpleDOTask('Dev3/port1/line0')
clean4 = DAQSimpleDOTask('Dev3/port1/line1')
odor5 = DAQSimpleDOTask('Dev3/port1/line2')
clean5 = DAQSimpleDOTask('Dev3/port1/line3')
odor6 = DAQSimpleDOTask('Dev3/port1/line4')
clean6 = DAQSimpleDOTask('Dev3/port1/line5')
odor7 = DAQSimpleDOTask('Dev3/port1/line6')
clean7 = DAQSimpleDOTask('Dev3/port1/line7')
# # # D2-8
# reward_odor = odor5
# reward_odor_clean = clean5
# punish_odor = odor4
# punish_odor_clean = clean4
# reward_sound = 1
# punish_sound = 2
# events_filename = 'd2-8_7-11-2019_odor_sound.xlsx'
# #events_filename = 'test.xlsx'
# # D2-9
# reward_odor = odor4
# reward_odor_clean = clean4
# punish_odor = odor5
# punish_odor_clean = clean5
# reward_sound = 1
# punish_sound = 2
# events_filename = 'd2-9_7-11-2019_odor_sound.xlsx'
#
# # D2-10
# reward_odor = odor5
# reward_odor_clean = clean5
# punish_odor = odor4
# punish_odor_clean = clean4
# reward_sound = 2
# punish_sound = 1
# events_filename = 'd2-10_7-11-2019_odor_sound.xlsx'
# D1-7 rewards: odor4, sound 1
# reward_odor = odor4
# reward_odor_clean = clean4
# punish_odor = odor5
# punish_odor_clean = clean5
# reward_sound = 1
# punish_sound = 2
# events_filename = 'd1-7_7-12-2019_odor_sound.xlsx'
# events_filename = 'test.xlsx'
# # D1-12 rewards: odor5, sound 1
# reward_odor = odor5
# reward_odor_clean = clean5
# punish_odor = odor4
# punish_odor_clean = clean4
# reward_sound = 1
# punish_sound = 2
# events_filename = 'd1-12_7-11-2019_odor_sound.xlsx'
# D1-13 rewards: odor4, sound 2
# reward_odor = odor4
# reward_odor_clean = clean4
# punish_odor = odor5
# punish_odor_clean = clean5
# reward_sound = 2
# punish_sound = 1
# events_filename = 'd1-13_7-11-2019_odor_sound.xlsx'
# D1-14 rewards: odor5, sound 2
reward_odor = odor5
reward_odor_clean = clean5
punish_odor = odor4
punish_odor_clean = clean4
reward_sound = 2
punish_sound = 1
events_filename = 'd1-14_7-11-2019_odor_sound.xlsx'
odor0.low()
odor1.low()
odor2.low()
odor3.low()
odor4.low()
odor5.low()
odor6.low()
odor7.low()
clean0.low()
clean1.low()
clean2.low()
clean3.high()
clean4.high()
clean5.high()
clean6.high()
clean7.high()
odor0.close()
odor1.close()
odor2.close()
odor3.close()
odor6.close()
odor7.close()
clean0.close()
clean1.close()
clean2.close()
clean3.close()
clean6.close()
clean7.close()
LED = DAQSimpleDOTask('Dev3/port2/line2')
LED.low()
self.OdorOnCopy = DAQSimpleDOTask('Dev3/port2/line5')
self.OdorOnCopy.low()
waterR = DAQSimpleDOTask('Dev3/port2/line0')
waterR.low()
airpuff1 = DAQSimpleDOTask('Dev3/port2/line3')
airpuff1.low()
airpuff2 = DAQSimpleDOTask('Dev3/port2/line6')
airpuff2.low()
self.lickR = DAQSimpleDITask('Dev3/port2/line4')
# EVENT CODES
# video recording start / start trial = 101
# lick on = 11, lick off = 10
# right water on = 51, right water off = 50
# airpuff on = 81, off = 80
# reward odor on = 131, off = 130
# punish odor on = 141, off = 140
# reward sound on = 151, off = 150
# punish sound on = 161, off = 160
#create excel workbook
self.wb = Workbook()
self.ws = self.wb.active
numtrials = 120
a = np.empty(int(numtrials / 4))
a.fill(2)
b = np.empty(int(numtrials / 4))
b.fill(3)
trialtypes = np.concatenate((np.ones(
(int(numtrials / 4))), np.zeros((int(numtrials / 4))), a, b))
random.shuffle(trialtypes)
print(trialtypes)
# # arrays to randomize skipped trials for each trial type
# num_to_skip = int((numtrials/5)*0.1)
# skip0 = np.concatenate((np.zeros(int(numtrials/10)-num_to_skip),np.ones(num_to_skip)))
# random.shuffle(skip0)
# skip0 = np.concatenate((np.zeros(int(numtrials/10)),skip0))
# skip1 = np.concatenate((np.zeros(int(numtrials/10)-num_to_skip),np.ones(num_to_skip)))
# random.shuffle(skip1)
# skip1 = np.concatenate((np.zeros(int(numtrials/10)),skip1))
# skip2 = np.concatenate((np.zeros(int(numtrials/10)-num_to_skip),np.ones(num_to_skip)))
# random.shuffle(skip2)
# skip2 = np.concatenate((np.zeros(int(numtrials/10)),skip2))
# skip3 = np.concatenate((np.zeros(int(numtrials/10)-num_to_skip),np.ones(num_to_skip)))
# random.shuffle(skip3)
# skip3 = np.concatenate((np.zeros(int(numtrials/10)),skip3))
# counters for each trial type
h = 0
i = 0
j = 0
k = 0
duration_rec_off = 6.5
duration_rec_on_before = 4
duration_odor_to_outcome = 1.3
duration_water_large = 0.2
duration_airpuff = 0.2
duration_rec_on_after = 8
sound_thread = SubMeasurementQThread(self.sound_action)
self.interrupt_subthread.connect(sound_thread.interrupt)
sound_thread.start()
for t in range(0, numtrials):
if bool(trialtypes[t]):
self.settings.filename.update_value('reward_trial' + str(t))
else:
self.settings.filename.update_value('punish_trial' + str(t))
self.recorder.create_file(
self.settings.filename.value(),
self.wide_cam.settings.frame_rate.value())
#print('turn on LED')
LED.high()
self.check_licking_1spout(1)
#self.settings.save_video.update_value(True):
print(t)
self.settings.in_trial.update_value(True)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=101)
self.check_licking_1spout(duration_rec_on_before)
if trialtypes[t] == 0:
print('odor reward trial ' + str(h))
print('opening odor port')
reward_odor.high()
self.OdorOnCopy.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=131)
reward_odor_clean.low()
self.check_licking_1spout(duration_odor_to_outcome)
print('opening water valve')
waterR.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=51)
self.check_licking_1spout(duration_water_large)
print('closing odor port')
reward_odor.low()
self.OdorOnCopy.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=130)
reward_odor_clean.high()
waterR.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=50)
h += 1
self.wb.save(events_filename)
elif trialtypes[t] == 1:
print('punish odor trial ' + str(i))
print('opening odor port')
punish_odor.high()
self.OdorOnCopy.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=141)
punish_odor_clean.low()
self.check_licking_1spout(duration_odor_to_outcome)
print('delivering airpuff')
airpuff1.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=81)
self.check_licking_1spout(duration_airpuff)
print('closing odor port')
punish_odor.low()
self.OdorOnCopy.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=140)
punish_odor_clean.high()
airpuff1.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=80)
i += 1
self.wb.save(events_filename)
elif trialtypes[t] == 2:
print('sound reward trial ' + str(j))
print('playing reward sound')
self.settings.play_frequency.update_value(reward_sound)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=151)
self.check_licking_1spout(duration_odor_to_outcome)
print('opening water valve')
waterR.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=51)
self.check_licking_1spout(duration_water_large)
waterR.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=50)
j += 1
self.wb.save(events_filename)
else:
print('sound punish trial ' + str(k))
print('playing punish sound')
self.settings.play_frequency.update_value(punish_sound)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=161)
self.check_licking_1spout(duration_odor_to_outcome)
print('delivering airpuff')
airpuff1.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=81)
self.check_licking_1spout(duration_airpuff)
airpuff1.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=80)
k += 1
self.wb.save(events_filename)
self.check_licking_1spout(duration_rec_on_after)
self.settings.in_trial.update_value(False)
#self.settings.save_video.update_value(False):
LED.low()
self.wb.save(events_filename)
self.check_licking_1spout(duration_rec_off)
if self.interrupt_measurement_called:
#tell subtherad to stop
self.interrupt_subthread.emit()
break
reward_odor.close()
reward_odor_clean.close()
punish_odor.close()
punish_odor_clean.close()
waterR.close()
waterR.close()
airpuff1.close()
airpuff2.close()
LED.close()
self.OdorOnCopy.close()
print('FINISHED ASSOCIATION TRAINING')
#sound_thread.stop()
del sound_thread
if self.settings.save_video.value():
self.recorder.close()
def check_licking_1spout(self, interval):
checkperiod = 0.02
timeout = time.time() + interval
right_lick_last = 0
while time.time() < timeout:
right_lick = self.lickR.read()
if right_lick != right_lick_last:
if right_lick:
self.settings.lick_status.update_value(11)
print('Lick')
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=11)
else:
self.settings.lick_status.update_value(10)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=10)
else:
self.settings.lick_status.update_value(0)
right_lick_last = right_lick
time.sleep(checkperiod)
def sound_action(self):
checkperiod = 0.02
time.sleep(checkperiod)
if self.settings.play_frequency.value() == 1:
self.settings.play_frequency.update_value(0)
self.OdorOnCopy.high()
winsound.Beep(5000, 1500)
#winsound.PlaySound('highsoundstimulus.wav', winsound.SND_ALIAS)
self.OdorOnCopy.low()
elif self.settings.play_frequency.value() == 2:
self.settings.play_frequency.update_value(0)
self.OdorOnCopy.high()
#winsound.PlaySound('lowsoundstimulus.wav', winsound.SND_ALIAS)
winsound.Beep(12000, 1500)
self.OdorOnCopy.low()
# def camera_action(self):
# '''
# format the image properly
# '''
# try:
# wide_image = self.wide_cam.read()
# wide_image_data = self.wide_cam.to_numpy(wide_image)
# self.wide_disp_queue.put(wide_image_data)
#
# if self.settings.save_video.value() and self.settings.in_trial.value() :
# self.recorder.save_frame(self.settings.filename.value(),wide_image)
#
# except Exception as ex:
# print('Error : %s' % ex)
def run(self):
"""
Runs when measurement is started. Runs in a separate thread from GUI.
It should not update the graphical interface directly, and should only
focus on data acquisition.
"""
# # first, create a data file
# if self.settings['save_h5']:
# # if enabled will create an HDF5 file with the plotted data
# # first we create an H5 file (by default autosaved to app.settings['save_dir']
# # This stores all the hardware and app meta-data in the H5 file
# self.h5file = h5_io.h5_base_file(app=self.app, measurement=self)
#
# # create a measurement H5 group (folder) within self.h5file
# # This stores all the measurement meta-data in this group
# self.h5_group = h5_io.h5_create_measurement_group(measurement=self, h5group=self.h5file)
#
# # create an h5 dataset to store the data
# self.buffer_h5 = self.h5_group.create_dataset(name = 'buffer',
# shape = self.buffer.shape,
# dtype = self.buffer.dtype)
# We use a try/finally block, so that if anything goes wrong during a measurement,
# the finally block can clean things up, e.g. close the data file object.
#self.wide_cam._dev.set_buffer_count(500)
if self.settings.save_video.value():
save_dir = self.app.settings.save_dir.value()
data_path = os.path.join(save_dir,
self.app.settings.sample.value())
try:
os.makedirs(data_path)
except OSError:
print(
'directory already exists, writing to existing directory')
self.recorder.settings.path.update_value(data_path)
#frame_rate = self.wide_cam.settings.frame_rate.value()
#self.recorder.create_file('wide_mov',frame_rate)
#
# # create a subthread and connect it to the interrupt subthread signal
# self.wide_disp_queue = queue.Queue(1000)
# self.camera_thread = SubMeasurementQThread(self.camera_action)
# self.interrupt_subthread.connect(self.camera_thread.interrupt)
# #start camera
# self.wide_cam.start()
#
# #start camera subthread
# self.camera_thread.start()
# initiate all the odor solenoids
odor0 = DAQSimpleDOTask('Dev3/port0/line0')
clean0 = DAQSimpleDOTask('Dev3/port0/line1')
odor1 = DAQSimpleDOTask('Dev3/port0/line2')
clean1 = DAQSimpleDOTask('Dev3/port0/line3')
odor2 = DAQSimpleDOTask('Dev3/port0/line4')
clean2 = DAQSimpleDOTask('Dev3/port0/line5')
odor3 = DAQSimpleDOTask('Dev3/port0/line6')
clean3 = DAQSimpleDOTask('Dev3/port0/line7')
odor4 = DAQSimpleDOTask('Dev3/port1/line0')
clean4 = DAQSimpleDOTask('Dev3/port1/line1')
odor5 = DAQSimpleDOTask('Dev3/port1/line2')
clean5 = DAQSimpleDOTask('Dev3/port1/line3')
odor6 = DAQSimpleDOTask('Dev3/port1/line4')
clean6 = DAQSimpleDOTask('Dev3/port1/line5')
odor7 = DAQSimpleDOTask('Dev3/port1/line6')
clean7 = DAQSimpleDOTask('Dev3/port1/line7')
# # # D2-8
# reward_odor = odor5
# reward_odor_clean = clean5
# punish_odor = odor4
# punish_odor_clean = clean4
# reward_sound = 1
# punish_sound = 2
# events_filename = 'd2-8_7-11-2019_odor_sound.xlsx'
# #events_filename = 'test.xlsx'
# # D2-9
# reward_odor = odor4
# reward_odor_clean = clean4
# punish_odor = odor5
# punish_odor_clean = clean5
# reward_sound = 1
# punish_sound = 2
# events_filename = 'd2-9_7-11-2019_odor_sound.xlsx'
#
# # D2-10
# reward_odor = odor5
# reward_odor_clean = clean5
# punish_odor = odor4
# punish_odor_clean = clean4
# reward_sound = 2
# punish_sound = 1
# events_filename = 'd2-10_7-11-2019_odor_sound.xlsx'
# D1-7 rewards: odor4, sound 1
# reward_odor = odor4
# reward_odor_clean = clean4
# punish_odor = odor5
# punish_odor_clean = clean5
# reward_sound = 1
# punish_sound = 2
# events_filename = 'd1-7_7-12-2019_odor_sound.xlsx'
# events_filename = 'test.xlsx'
# # D1-12 rewards: odor5, sound 1
# reward_odor = odor5
# reward_odor_clean = clean5
# punish_odor = odor4
# punish_odor_clean = clean4
# reward_sound = 1
# punish_sound = 2
# events_filename = 'd1-12_7-11-2019_odor_sound.xlsx'
# D1-13 rewards: odor4, sound 2
# reward_odor = odor4
# reward_odor_clean = clean4
# punish_odor = odor5
# punish_odor_clean = clean5
# reward_sound = 2
# punish_sound = 1
# events_filename = 'd1-13_7-11-2019_odor_sound.xlsx'
# D1-14 rewards: odor5, sound 2
reward_odor = odor5
reward_odor_clean = clean5
punish_odor = odor4
punish_odor_clean = clean4
reward_sound = 2
punish_sound = 1
events_filename = 'd1-14_7-11-2019_odor_sound.xlsx'
odor0.low()
odor1.low()
odor2.low()
odor3.low()
odor4.low()
odor5.low()
odor6.low()
odor7.low()
clean0.low()
clean1.low()
clean2.low()
clean3.high()
clean4.high()
clean5.high()
clean6.high()
clean7.high()
odor0.close()
odor1.close()
odor2.close()
odor3.close()
odor6.close()
odor7.close()
clean0.close()
clean1.close()
clean2.close()
clean3.close()
clean6.close()
clean7.close()
LED = DAQSimpleDOTask('Dev3/port2/line2')
LED.low()
self.OdorOnCopy = DAQSimpleDOTask('Dev3/port2/line5')
self.OdorOnCopy.low()
waterR = DAQSimpleDOTask('Dev3/port2/line0')
waterR.low()
airpuff1 = DAQSimpleDOTask('Dev3/port2/line3')
airpuff1.low()
airpuff2 = DAQSimpleDOTask('Dev3/port2/line6')
airpuff2.low()
self.lickR = DAQSimpleDITask('Dev3/port2/line4')
# EVENT CODES
# video recording start / start trial = 101
# lick on = 11, lick off = 10
# right water on = 51, right water off = 50
# airpuff on = 81, off = 80
# reward odor on = 131, off = 130
# punish odor on = 141, off = 140
# reward sound on = 151, off = 150
# punish sound on = 161, off = 160
#create excel workbook
self.wb = Workbook()
self.ws = self.wb.active
numtrials = 120
a = np.empty(int(numtrials / 4))
a.fill(2)
b = np.empty(int(numtrials / 4))
b.fill(3)
trialtypes = np.concatenate((np.ones(
(int(numtrials / 4))), np.zeros((int(numtrials / 4))), a, b))
random.shuffle(trialtypes)
print(trialtypes)
# # arrays to randomize skipped trials for each trial type
# num_to_skip = int((numtrials/5)*0.1)
# skip0 = np.concatenate((np.zeros(int(numtrials/10)-num_to_skip),np.ones(num_to_skip)))
# random.shuffle(skip0)
# skip0 = np.concatenate((np.zeros(int(numtrials/10)),skip0))
# skip1 = np.concatenate((np.zeros(int(numtrials/10)-num_to_skip),np.ones(num_to_skip)))
# random.shuffle(skip1)
# skip1 = np.concatenate((np.zeros(int(numtrials/10)),skip1))
# skip2 = np.concatenate((np.zeros(int(numtrials/10)-num_to_skip),np.ones(num_to_skip)))
# random.shuffle(skip2)
# skip2 = np.concatenate((np.zeros(int(numtrials/10)),skip2))
# skip3 = np.concatenate((np.zeros(int(numtrials/10)-num_to_skip),np.ones(num_to_skip)))
# random.shuffle(skip3)
# skip3 = np.concatenate((np.zeros(int(numtrials/10)),skip3))
# counters for each trial type
h = 0
i = 0
j = 0
k = 0
duration_rec_off = 6.5
duration_rec_on_before = 4
duration_odor_to_outcome = 1.3
duration_water_large = 0.2
duration_airpuff = 0.2
duration_rec_on_after = 8
sound_thread = SubMeasurementQThread(self.sound_action)
self.interrupt_subthread.connect(sound_thread.interrupt)
sound_thread.start()
for t in range(0, numtrials):
if bool(trialtypes[t]):
self.settings.filename.update_value('reward_trial' + str(t))
else:
self.settings.filename.update_value('punish_trial' + str(t))
self.recorder.create_file(
self.settings.filename.value(),
self.wide_cam.settings.frame_rate.value())
#print('turn on LED')
LED.high()
self.check_licking_1spout(1)
#self.settings.save_video.update_value(True):
print(t)
self.settings.in_trial.update_value(True)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=101)
self.check_licking_1spout(duration_rec_on_before)
if trialtypes[t] == 0:
print('odor reward trial ' + str(h))
print('opening odor port')
reward_odor.high()
self.OdorOnCopy.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=131)
reward_odor_clean.low()
self.check_licking_1spout(duration_odor_to_outcome)
print('opening water valve')
waterR.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=51)
self.check_licking_1spout(duration_water_large)
print('closing odor port')
reward_odor.low()
self.OdorOnCopy.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=130)
reward_odor_clean.high()
waterR.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=50)
h += 1
self.wb.save(events_filename)
elif trialtypes[t] == 1:
print('punish odor trial ' + str(i))
print('opening odor port')
punish_odor.high()
self.OdorOnCopy.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=141)
punish_odor_clean.low()
self.check_licking_1spout(duration_odor_to_outcome)
print('delivering airpuff')
airpuff1.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=81)
self.check_licking_1spout(duration_airpuff)
print('closing odor port')
punish_odor.low()
self.OdorOnCopy.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=140)
punish_odor_clean.high()
airpuff1.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=80)
i += 1
self.wb.save(events_filename)
elif trialtypes[t] == 2:
print('sound reward trial ' + str(j))
print('playing reward sound')
self.settings.play_frequency.update_value(reward_sound)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=151)
self.check_licking_1spout(duration_odor_to_outcome)
print('opening water valve')
waterR.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=51)
self.check_licking_1spout(duration_water_large)
waterR.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=50)
j += 1
self.wb.save(events_filename)
else:
print('sound punish trial ' + str(k))
print('playing punish sound')
self.settings.play_frequency.update_value(punish_sound)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=161)
self.check_licking_1spout(duration_odor_to_outcome)
print('delivering airpuff')
airpuff1.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=81)
self.check_licking_1spout(duration_airpuff)
airpuff1.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=80)
k += 1
self.wb.save(events_filename)
self.check_licking_1spout(duration_rec_on_after)
self.settings.in_trial.update_value(False)
#self.settings.save_video.update_value(False):
LED.low()
self.wb.save(events_filename)
self.check_licking_1spout(duration_rec_off)
if self.interrupt_measurement_called:
#tell subtherad to stop
self.interrupt_subthread.emit()
break
reward_odor.close()
reward_odor_clean.close()
punish_odor.close()
punish_odor_clean.close()
waterR.close()
waterR.close()
airpuff1.close()
airpuff2.close()
LED.close()
self.OdorOnCopy.close()
print('FINISHED ASSOCIATION TRAINING')
#sound_thread.stop()
del sound_thread
if self.settings.save_video.value():
self.recorder.close()
lick = lickR.read()
if not lick:
count_drop += 1
print(count_drop)
time.sleep(5)
water.high()
time.sleep(0.06)
water.low()
#else:
# continue
time.sleep(0.01)
water.close()
# from ScopeFoundry import Measurement
# from ScopeFoundry.measurement import MeasurementQThread
# from AntCamHW.daq_do.daq_do_dev import DAQSimpleDOTask
# from AntCamHW.daq_di.daq_di_dev import DAQSimpleDITask
# import time
#
#
# lick = DAQSimpleDITask('Dev2_SELECT/port1/line0')
#
# timeout = time.time() + 100
#
# while time.time() < timeout:
# odor0.high()
# time.sleep(0.5)
class SelinaTraining(Measurement):
def __init__(self):
# please change this according to mouse
self.mouse = 'C32' #OT-GC-2
self.phase = 'cond' #'cond', 'deg','C-control'
self.condition = 'Pav'
self.numtrials = 200
self.list = [7, 6]
self.events_path = "C:/Users/MurthyLab/Desktop/Selina_lab_computer_data/experiment_data_2020_3_{0}/{1}/".format(
self.condition, self.mouse)
self.events_filename = datetime.datetime.now().strftime(
"%Y-%m-%d-%H-%M") + '{}.xlsx'.format(self.phase)
self.reward_odor_index = [1,
0] #odor list index change according to mi
if self.condition == 'Operant':
self.operant = True
self.licknum = 1
else:
self.operant = False
self.licknum = 0
# pre training
self.p_go = 0.4 #0.5
self.p_reward_go = 0.75
self.p_no_go = 0.2 #0.2
self.p_empty = 0.4 #0.3
if self.phase == 'cond':
self.p_reward_empty = 0 # 0.3
else: # 'deg','C-control'
self.p_reward_empty = 0.75
self.counter = np.zeros(6)
self.duration_rec_on_before = 1
self.duration_odor_on = 1
self.duration_odor_to_action = 0
self.duration_action_window = 2.5
self.duration_water_large = 0.06 #0.1
self.duration_rec_on_after = 2
self.duration_ITI = np.random.exponential(2, size=self.numtrials)
self.waterline = 0
self.filename = self.events_path + self.events_filename
def run(self):
try:
os.makedirs(self.events_path)
except OSError:
print("The directory %s existed" % self.events_path)
else:
print("Successfully created the directory %s " % self.events_path)
logname = self.filename[0:-5] + '.log'
logging.basicConfig(filename=logname, level=logging.DEBUG)
logging.info(self.__dict__)
odors_cue = OdorGen(self.list)
odors_cue.assign_odor()
self.reward_odor, self.non_reward_odor = odors_cue.set_rewardodor(
index=self.reward_odor_index)
odors_cue.initiate()
# odors_cue.odors_DAQ[i]
print('odor done')
self.waterR = DAQSimpleDOTask('Dev2_SELECT/port0/line{}'.format(
self.waterline))
self.waterR.low()
# self.OdorOnCopy = DAQSimpleDOTask('Dev3/port2/line5')
# self.OdorOnCopy.low()
self.lickR = DAQSimpleDITask('Dev2_SELECT/port1/line0')
print('water done')
# EVENT CODES
# video recording start / start trial = 101
# end trial = 100
# lick on = 11, lick off = 10
# contingency reward odor on = 131, off = 130, water on = 51, right water off = 50
# contingency no reward odor on = 141, off = 140, water on = 61, right water off = 60
# non-contingency reward odor on = 151, off = 150, water on = 71, right water off = 70
# non-contingency no reward odor on = 161, off = 160, water on = 81, right water off = 80
# create excel workbook
self.wb = Workbook()
self.ws = self.wb.active
#generate trial type
# generate trial type
trialtypes = np.zeros(self.numtrials)
for i in range(int(self.numtrials / 20)):
train_go = np.zeros(int(round(20 * self.p_go *
self.p_reward_go))) # code 0
train_nogo = np.ones(int(20 * self.p_no_go)) # code 1
temp_comb1 = np.concatenate((train_go, train_nogo))
train_empty = np.ones(
int(20 * self.p_empty *
(1 - self.p_reward_empty))) * 2 # code 2
train_go_omission = np.ones(
int(round(20 * self.p_go *
(1 - self.p_reward_go)))) * 3 # code 3
train_unpredwater = np.ones(
int(20 * self.p_empty * self.p_reward_empty)) * 4 # code 4
temp_comb1 = np.concatenate((temp_comb1, train_empty))
temp_comb1 = np.concatenate((temp_comb1, train_unpredwater))
temp_comb2 = np.concatenate((temp_comb1, train_go_omission))
random.shuffle(temp_comb2)
trialtypes[20 * i:20 * (i + 1)] = temp_comb2
self.trialstype = trialtypes
print('================== Trial Types =================')
print(trialtypes)
for t in range(0, self.numtrials):
print('================================================')
print('trial number: ', t)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2,
value=101) #trial start
d = self.ws.cell(row=self.ws.max_row,
column=3,
value='trial{}'.format(int(
trialtypes[t]))) #trial type
# code: 0--go w rward; 1--no go; 2--empty; 3--go w/o reward
self.check_licking_1spout(self.duration_rec_on_before)
# main training program
self.run_trial_type(int(trialtypes[t]))
self.check_licking_1spout(self.duration_rec_on_after)
# self.settings.save_video.update_value(False):
self.check_licking_1spout(self.duration_ITI[t])
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=100) #end
self.wb.save(self.filename)
odors_cue.initiate()
odors_cue.close()
self.waterR.low()
self.waterR.close()
print('FINISHED ASSOCIATION TRAINING')
def check_licking_1spout(self, interval, check_action=False):
checkperiod = 0.005
timeout = time.time() + interval
reward_on = True # this is used for Pav or Operant
right_lick_last = 0
count = 0
while time.time() < timeout:
right_lick = self.lickR.read()
if right_lick != right_lick_last:
if right_lick:
print('Lick')
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=11)
# self.save_training()
if check_action:
count += 1
else:
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=10)
else:
pass
right_lick_last = right_lick
time.sleep(checkperiod)
if check_action and count >= self.licknum:
print('licking activate reward')
elif check_action and count < self.licknum:
print('not enough licking')
reward_on = False
return reward_on
def run_trial_type(self, types):
odor_on = False
reward_on = False
if types == 0:
print('go trial ' + str(int(self.counter[types])))
odor_on = True # contingency odor comes
is_go = True
r_code = [131, 130]
w_code = [51, 50]
self.run_odor_module(odor_on, is_go, r_code)
self.check_licking_1spout(self.duration_odor_to_action)
reward_on = self.check_licking_1spout(
self.duration_action_window,
self.operant) ### can be a problem
self.run_reward_module(reward_on, w_code)
elif types == 1:
print('no go trial ' + str(int(self.counter[types])))
odor_on = True
is_go = False
r_code = [141, 140]
w_code = [61, 60]
self.run_odor_module(odor_on, is_go, r_code)
self.check_licking_1spout(self.duration_odor_to_action +
self.duration_action_window)
reward_on = False
self.run_reward_module(reward_on, w_code)
elif types == 2:
print('empty trial ' + str(int(self.counter[types])))
# odor false: control odor comes
w_code = [71, 70] # not used
# self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(self.duration_odor_on)
self.check_licking_1spout(self.duration_odor_to_action +
self.duration_action_window)
reward_on = False
self.run_reward_module(reward_on, w_code)
elif types == 3:
print('go omission trial ' + str(int(self.counter[types])))
odor_on = True # contingency odor comes
is_go = True
r_code = [131, 130]
w_code = [51, 50]
self.run_odor_module(odor_on, is_go, r_code)
self.check_licking_1spout(self.duration_odor_to_action +
self.duration_action_window)
self.run_reward_module(reward_on, w_code)
elif types == 4:
print('unpredicted water trial ' + str(int(self.counter[types])))
w_code = [51, 50]
self.check_licking_1spout(self.duration_odor_on)
self.check_licking_1spout(self.duration_odor_to_action)
reward_on = self.check_licking_1spout(self.duration_action_window,
self.operant)
self.run_reward_module(reward_on, w_code)
self.counter[types] += 1
self.wb.save(self.filename)
def run_odor_module(self, odor_on, is_go, r_code):
if odor_on:
print('opening odor port')
if is_go:
self.reward_odor.high()
else:
self.non_reward_odor.high()
# self.OdorOnCopy.high() # ？？？
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[0])
# self.save_training()
self.check_licking_1spout(self.duration_odor_on)
print('closing odor port')
if is_go:
self.reward_odor.low()
else:
self.non_reward_odor.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[1])
else:
self.check_licking_1spout(self.duration_odor_on)
def run_reward_module(self, reward_on, w_code):
if reward_on:
# modify! give water if licks three times within 1 s
print('opening water valve')
self.waterR.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[0])
self.check_licking_1spout(
self.duration_water_large) # this parameter hasn't een defined
print('closing water valve')
self.waterR.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[1])
else:
self.check_licking_1spout(self.duration_water_large)
# def camera_action(self):
# '''
# format the image properly
# '''
# try:
# wide_image = self.wide_cam.read()
# wide_image_data = self.wide_cam.to_numpy(wide_image)
# self.wide_disp_queue.put(wide_image_data)
#
# if self.settings.save_video.value() and self.settings.in_trial.value() :
# self.recorder.save_frame(self.settings.filename.value(),wide_image)
#
# except Exception as ex:
# print('Error : %s' % ex)
def save_training(self):
with open(self.filename, 'wb') as output:
pickle.dump(self, output, pickle.HIGHEST_PROTOCOL)
class SelinaTraining(Measurement):
def __init__(self):
self.events_path = "C:/Users/MurthyLab/Desktop/Selina/experiment_data/C12/"
self.events_filename = datetime.datetime.now().strftime("%Y-%m-%d-%H-%M") +'.hdf5'
self.filename = self.events_path + self.events_filename
self.waterline = 0
self.list = [7, 6, 5, 4]
self.reward_odor_index = 0 #odor list index
self.numtrials = 4
self.p_cont_noncont = 0.5
self.p_USwCS = 0.5
self.p_USwoCS = 0.5
self.counter = np.zeros(4)
self.duration_rec_on_before = 2
self.duration_odor_on = 0.5
self.duration_odor_to_outcome = 1.5
self.duration_water_large = 0.02
self.duration_rec_on_after = 4
self.duration_ITI = np.random.poisson(lam=2, size=self.numtrials)
def run(self):
print('a ha')
odors_cue = OdorGen(self.list)
odors_cue.assign_odor()
self.reward_odor = odors_cue.set_rewardodor(index=self.reward_odor_index)
odors_cue.initiate()
# odors_cue.odors_DAQ[i]
print('odor done')
self.waterR = DAQSimpleDOTask('Dev2_SELECT/port0/line{}'.format(self.waterline))
self.waterR.low()
# self.OdorOnCopy = DAQSimpleDOTask('Dev3/port2/line5')
# self.OdorOnCopy.low()
self.lickR = DAQSimpleDITask('Dev2_SELECT/port1/line0')
print('water done')
# EVENT CODES
# video recording start / start trial = 101
# lick on = 11, lick off = 10
# contingency reward odor on = 131, off = 130, water on = 51, right water off = 50
# contingency no reward odor on = 141, off = 140, water on = 61, right water off = 60
# non-contingency reward odor on = 151, off = 150, water on = 71, right water off = 70
# non-contingency no reward odor on = 161, off = 160, water on = 81, right water off = 80
# create excel workbook
self.wb = Workbook()
self.ws = self.wb.active
print('book done')
#generate trial type
# generate trial type
cont_reward = np.zeros(int(self.numtrials * self.p_cont_noncont * self.p_USwCS)) # code 0
cont_noreward = np.ones(int(self.numtrials * self.p_cont_noncont * (1 - self.p_USwCS))) # code 1
temp_comb1 = np.concatenate((cont_reward, cont_noreward))
noncont_reward = np.ones(int(self.numtrials * (1 - self.p_cont_noncont) * self.p_USwoCS)) * 2 # code 2
noncont_noreward = np.ones(int(self.numtrials * (1 - self.p_cont_noncont) * (1 - self.p_USwoCS))) * 3 # code 3
temp_comb2 = np.concatenate((noncont_noreward, noncont_reward))
trialtypes = np.concatenate((temp_comb1, temp_comb2))
random.shuffle(trialtypes)
print('================== Trial Types =================')
print(trialtypes)
for t in range(0, self.numtrials):
print('================================================')
print('trial number: ', t)
print()
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=101)
self.check_licking_1spout(self.duration_rec_on_before)
# main training program
self.run_trial_type(int(trialtypes[t]))
self.check_licking_1spout(self.duration_rec_on_after)
# self.settings.save_video.update_value(False):
self.wb.save(self.events_path+'.xlsm')
self.check_licking_1spout(self.duration_ITI[t])
odors_cue.initiate()
odors_cue.close()
self.waterR.low()
self.waterR.close()
print('FINISHED ASSOCIATION TRAINING')
def check_licking_1spout(self, interval):
checkperiod = 0.01
timeout = time.time() + interval
right_lick_last = 0
while time.time() < timeout:
right_lick = self.lickR.read()
if right_lick != right_lick_last:
if right_lick:
print('Lick')
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=11)
# self.save_training()
else:
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=10)
# self.save_training()
else:
pass
right_lick_last = right_lick
time.sleep(checkperiod)
def run_trial_type(self,types):
odor_on = False
reward_on = False
if types == 0:
print('contingency reward trial ' + str(int(self.counter[types])))
print('opening odor port')
odor_on = True
reward_on = True
r_code = [131, 130]
w_code = [51, 50]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(self.duration_odor_to_outcome) ### can be a problem
self.run_reward_module(reward_on, w_code)
elif types == 1:
print('contingency no reward trial ' + str(int(self.counter[types])))
print('opening odor port')
odor_on = True
r_code = [141, 140]
w_code = [61, 60]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(self.duration_odor_to_outcome) ### can be a problem
self.run_reward_module(reward_on, w_code)
elif types == 2:
print('non-contingency reward trial ' + str(int(self.counter[types])))
reward_on = True
r_code = [151, 150]
w_code = [71, 70]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(self.duration_odor_to_outcome) ### can be a problem
self.run_reward_module(reward_on, w_code)
else:
print('non-contingency no reward trial ' + str(int(self.counter[types])))
r_code = [161, 160]
w_code = [71, 70]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(self.duration_odor_to_outcome) ### can be a problem
self.run_reward_module(reward_on, w_code)
self.counter[types] += 1
self.wb.save(self.events_path+'.xlsm')
def run_odor_module(self,odor_on, r_code):
if odor_on:
self.reward_odor.high()
# self.OdorOnCopy.high() # ？？？
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[0])
# self.save_training()
time.sleep(self.duration_odor_on)
print('closing odor port')
self.reward_odor.low()
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[1])
# self.save_training()
else:
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[0])
# self.save_training()
time.sleep(self.duration_odor_on)
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[1])
# self.save_training()
def run_reward_module(self ,reward_on, w_code):
if reward_on:
# modify! give water if licks three times within 1 s
print('opening water valve')
self.waterR.high()
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[0])
# self.save_training()
self.check_licking_1spout(self.duration_water_large) # this parameter hasn't een defined
print('closing water valve')
self.waterR.low()
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[1])
# self.save_training()
else:
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[0])
# self.save_training()
time.sleep(self.duration_water_large)
d = self.ws.cell(row=(self.ws.max_row + 1), column=1, value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[1])
# self.save_training()
# def camera_action(self):
# '''
# format the image properly
# '''
# try:
# wide_image = self.wide_cam.read()
# wide_image_data = self.wide_cam.to_numpy(wide_image)
# self.wide_disp_queue.put(wide_image_data)
#
# if self.settings.save_video.value() and self.settings.in_trial.value() :
# self.recorder.save_frame(self.settings.filename.value(),wide_image)
#
# except Exception as ex:
# print('Error : %s' % ex)
def save_training(self):
'''save object in hdf5 file format
Args:
filename: str
path to the hdf5 file containing the saved object
'''
if '.hdf5' in self.filename:
save_dict_to_hdf5(self.__dict__, self.filename)
else:
raise Exception("Filename not supported")
clean0.low() clean1.low() clean2.low() clean3.low() clean6.low() clean7.low() # testing clean4.high() odor4.low() clean5.high() odor5.low() # closing program odor0.close() odor1.close() odor2.close() odor3.close() odor4.close() odor5.close() odor6.close() odor7.close() clean0.close() clean1.close() clean2.close() clean3.close() clean4.close() clean5.close() clean6.close() clean7.close()
class SelinaTraining(Measurement):
def __init__(self):
# please change this according to mouse
self.mouse = 'C22' #OT-GC-2
self.phase = 'deg'
self.condition = 'Pav'
self.numtrials = 160
self.list = [7, 6]
self.events_path = "C:/Users/MurthyLab/Desktop/Selina/experiment_data_2020_2_{0}/{1}/".format(
self.condition,
self.mouse) + datetime.datetime.now().strftime("%Y-%m-%d") + "/"
self.events_filename = datetime.datetime.now().strftime(
"%Y-%m-%d-%H-%M") + '{}.xlsx'.format(self.phase)
self.reward_odor_index = [1,
0] #odor list index change according to mi
if self.condition == 'Operant':
self.operant = True
self.licknum = 1
else:
self.operant = False
self.licknum = 0
#C22, C21
# self.p_conbynoncon = 0.5 # total water volumn should keep the same
# self.p_reward_USwCS = 0.8 #self.p_conbynoncon*self.p_reward_USwCS + (1-self.p_conbynoncon)*self.p_USwoCs = p_pretraining_go
# self.p_reward_USwoCS = 0.4
#C17, 19, 20, 18
self.p_conbynoncon = 0.5 # total water volumn should keep the same
self.p_reward_USwCS = 0.8 # self.p_conbynoncon*self.p_reward_USwCS + (1-self.p_conbynoncon)*self.p_USwoCs = p_pretraining_go
self.p_reward_USwoCS = 0.8
self.counter = np.zeros(4)
self.duration_rec_on_before = 2.5
self.duration_odor_on = 1
self.duration_odor_to_action = 0
self.duration_action_window = 2.5
self.duration_water_large = 0.08
self.duration_rec_on_after = 3
self.duration_ITI = np.random.exponential(2, size=self.numtrials)
self.waterline = 0
self.filename = self.events_path + self.events_filename
def generate_trial(self):
total_num = 20 #trial type distribution for every 20 trials are the same, the order is shuffled
## 0: trial type 1; 1: trial type 2; 2: trial type 3; 3: trial type 4
percent_1 = round((1 - self.p_conbynoncon) * self.p_reward_USwoCS,
2) #non-cont rewarded#
percent_3 = round(
(1 - self.p_conbynoncon) * (1 - self.p_reward_USwoCS),
2) # non-cont no reward
percent_4 = round(self.p_conbynoncon * (1 - self.p_reward_USwCS),
2) # cont no reward #go omission
percent_2 = round(1 - percent_1 - percent_3 - percent_4,
2) # cont reward #type 2
assert percent_2 >= 0, print("invalid ratio")
sum_freq = percent_1 + percent_2 + percent_3 + percent_4
assert abs(sum_freq - 1) < 1e-3, print(
"Sum of frequent ({}) not equal to 1".format(sum_freq))
num_1 = int(total_num * percent_1)
num_3 = int(total_num * percent_3)
num_4 = int(total_num * percent_4)
num_2 = int(total_num * percent_2)
print('Type0:non-contingency reward', num_1,
'\nType1:contingency reward', 20 - num_1 - num_3 - num_4,
'\nType2:non-contingency non reward', num_3,
'\nType3:contingency non reward', num_4,
' \nin every 20 trials.')
data = [0] * num_1 + [2] * num_3 + [1] * num_2 + [3] * num_4
trial_data = []
for token in range(int(self.numtrials / 20)):
random.shuffle(data)
trial_data += data
return trial_data
def run(self):
try:
os.makedirs(self.events_path)
except OSError:
print("The directory %s existed" % self.events_path)
else:
print("Successfully created the directory %s " % self.events_path)
logname = self.filename[0:-5] + '.log'
logging.basicConfig(filename=logname, level=logging.DEBUG)
logging.info(self.__dict__)
odors_cue = OdorGen(self.list)
odors_cue.assign_odor()
self.reward_odor, self.non_reward_odor = odors_cue.set_rewardodor(
index=self.reward_odor_index)
odors_cue.initiate()
# odors_cue.odors_DAQ[i]
print('odor done')
self.waterR = DAQSimpleDOTask('Dev2_SELECT/port0/line{}'.format(
self.waterline))
self.waterR.low()
# self.OdorOnCopy = DAQSimpleDOTask('Dev3/port2/line5')
# self.OdorOnCopy.low()
self.lickR = DAQSimpleDITask('Dev2_SELECT/port1/line0')
print('water done')
# EVENT CODES
# video recording start / start trial = 101
# end trial = 100
# lick on = 11, lick off = 10
# contingency reward odor on = 131, off = 130, water on = 51, right water off = 50
# contingency no reward odor on = 141, off = 140, water on = 61, right water off = 60
# non-contingency reward odor on = 151, off = 150, water on = 71, right water off = 70
# non-contingency no reward odor on = 161, off = 160, water on = 81, right water off = 80
# create excel workbook
self.wb = Workbook()
self.ws = self.wb.active
#generate trial type
# generate trial type
trialtypes = self.generate_trial()
self.trialtype = trialtypes
print('================== Trial Types =================')
print(trialtypes)
for t in range(0, self.numtrials):
print('================================================')
print('trial number: ', t)
print()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=101)
if int(trialtypes[t]) == 0:
trialcode = "noncontR"
elif int(trialtypes[t]) == 1:
trialcode = 'contR'
elif int(trialtypes[t]) == 2:
trialcode = "noncontNR"
else:
trialcode = 'contNR'
d = self.ws.cell(row=self.ws.max_row,
column=3,
value='trial_{}'.format(trialcode)) #trial type
self.check_licking_1spout(self.duration_rec_on_before)
# main training program
self.run_trial_type(int(trialtypes[t]), t)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=100)
self.wb.save(self.filename)
odors_cue.initiate()
odors_cue.close()
self.waterR.low()
self.waterR.close()
print('FINISHED ASSOCIATION TRAINING')
def check_licking_1spout(self, interval, check_action=False):
checkperiod = 0.01
timeout = time.time() + interval
reward_on = True
right_lick_last = 0
count = 0
while time.time() < timeout:
right_lick = self.lickR.read()
if right_lick != right_lick_last:
if right_lick:
print('Lick')
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=11)
# self.save_training()
if check_action:
count += 1
else:
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=10)
else:
pass
right_lick_last = right_lick
time.sleep(checkperiod)
if check_action and count >= self.licknum:
print('licking activate reward')
elif check_action and count < self.licknum:
print('not enough licking')
reward_on = False
return reward_on
def run_trial_type(self, types, t):
odor_on = False
reward_on = False
if types == 0:
print('non-contingency odor reward trial ' +
str(int(self.counter[types])))
# contingency odor comes
r_code = [151, 150]
w_code = [51, 50]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(self.duration_odor_to_action +
self.duration_action_window)
reward_on = True
self.run_reward_module(reward_on, w_code)
self.check_licking_1spout(self.duration_rec_on_after)
self.check_licking_1spout(self.duration_ITI[t])
elif types == 1:
print('contingency odor reward trial ' +
str(int(self.counter[types])))
odor_on = True
r_code = [131, 130]
w_code = [51, 50]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(self.duration_odor_to_action)
reward_on = self.check_licking_1spout(self.duration_action_window,
self.operant)
self.run_reward_module(reward_on, w_code)
self.check_licking_1spout(self.duration_rec_on_after)
self.check_licking_1spout(self.duration_ITI[t])
elif types == 2:
print(' non-contingency no reward trial ' +
str(int(self.counter[types])))
# odor false: control odor comes
w_code = [51, 50]
self.check_licking_1spout(self.duration_odor_on)
self.check_licking_1spout(self.duration_odor_to_action +
self.duration_action_window)
self.run_reward_module(reward_on, w_code)
self.check_licking_1spout(self.duration_rec_on_after)
self.check_licking_1spout(self.duration_ITI[t])
elif types == 3:
print('contingency odor no reward trial ' +
str(int(self.counter[types])))
odor_on = True
r_code = [131, 130]
w_code = [51, 50]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(
self.duration_odor_to_action) ### can be a problem
self.check_licking_1spout(self.duration_action_window)
self.run_reward_module(reward_on, w_code)
self.check_licking_1spout(self.duration_rec_on_after)
self.check_licking_1spout(self.duration_ITI[t])
self.counter[types] += 1
self.wb.save(self.filename)
def run_odor_module(self, odor_on, r_code):
if odor_on:
print('opening odor port')
self.reward_odor.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[0])
# self.save_training()
self.check_licking_1spout(self.duration_odor_on)
print('closing odor port')
self.reward_odor.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[1])
else:
self.check_licking_1spout(self.duration_odor_on)
def run_reward_module(self, reward_on, w_code):
if reward_on:
# modify! give water if licks three times within 1 s
print('opening water valve')
self.waterR.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[0])
self.check_licking_1spout(
self.duration_water_large) # this parameter hasn't een defined
print('closing water valve')
self.waterR.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[1])
else:
self.check_licking_1spout(self.duration_water_large)
# def camera_action(self):
# '''
# format the image properly
# '''
# try:
# wide_image = self.wide_cam.read()
# wide_image_data = self.wide_cam.to_numpy(wide_image)
# self.wide_disp_queue.put(wide_image_data)
#
# if self.settings.save_video.value() and self.settings.in_trial.value() :
# self.recorder.save_frame(self.settings.filename.value(),wide_image)
#
# except Exception as ex:
# print('Error : %s' % ex)
def save_training(self):
with open(self.filename, 'wb') as output:
pickle.dump(self, output, pickle.HIGHEST_PROTOCOL)
class SelinaTraining(Measurement):
# this is the name of the measurement that ScopeFoundry uses
# when displaying your measurement and saving data related to it
name = "selina_training"
interrupt_subthread = QtCore.Signal(())
# def __init__(self):
# super().__init__()
# # EVENT CODES
# # video recording start / start trial = 101
# # lick on = 11, lick off = 10
# # right
# # airpuff on = 81, off = 80
#
# # contingency reward odor on = 131, off = 130, water on = 51, right water off = 50
# # contingency no reward odor on = 141, off = 140, water on = 61, right water off = 60
# # non-contingency reward odor on = 151, off = 150, water on = 71, right water off = 70
# # non-contingency no reward odor on = 161, off = 160, water on = 81, right water off = 80
#
# self.events_filename = '2019-7-17-test.xlsx'
# self.reward_odor_index = 0
#
# self.duration_rec_off = 6.5
# self.duration_rec_on_before = 4 # change this to exponential decay
# self.duration_odor_to_outcome = 1.3
# self.duration_water_large = 0.2
# self.duration_rec_on_after = 8
# self.duration_odor_on = 0.5
#
# self.lines = [0, 1, 2, 3]
# self.counter = np.zeros(len(self.lines))
#
# self.numtrials = 200
# self.p_cont_noncont = 0.5
# self.p_USwCS = 0.5
# self.p_USwoCS = 0.5
def setup(self):
"""
Runs once during App initialization.
This is the place to load a user interface file,
define settings, and set up data structures.
"""
# Define ui file to be used as a graphical interface
# This file can be edited graphically with Qt Creator
# sibling_path function allows python to find a file in the same folder
# as this python module
self.ui_filename = sibling_path(__file__, "ant_watch_plot.ui")
# Load ui file and convert it to a live QWidget of the user interface
self.ui = load_qt_ui_file(self.ui_filename)
# Measurement Specific Settings
# This setting allows the option to save data to an h5 data file during a run
# All settings are automatically added to the Microscope user interface
self.settings.New('save_h5', dtype=bool, initial=True)
self.settings.New('save_video', dtype=bool, initial=False)
# x and y is for transmitting signal
self.settings.New('x',
dtype=float,
initial=32,
ro=True,
vmin=0,
vmax=63.5)
self.settings.New('y',
dtype=float,
initial=32,
ro=True,
vmin=0,
vmax=63.5)
# added by Nune
self.settings.New('filename', dtype=str, initial='trial')
self.settings.New('in_trial', dtype=bool, initial=False)
self.settings.New('view_only', dtype=bool, initial=False)
self.settings.New('lick_status', dtype=int, initial=0)
# added for Selina
# connect lick indicator to settings
self.settings.New('lick_on', dtype=bool, initial=False, ro=True)
# change the lick indicator into blue light
self.ui.right_lick_ind_checkBox.setStyleSheet(
'QCheckBox{color:blue;}QCheckBox::indicator:checked{image: url(./icons/c_b.png);}QCheckBox::indicator:unchecked{image: url(./icons/uc_b.png);}'
)
# Define how often to update display during a run
self.display_update_period = 0.01
# Convenient reference to the hardware used in the measurement
self.wide_cam = self.app.hardware['HD Webcam C270']
# self.recorder = self.app.hardware['flirrec']
# setup experiment condition
#self.wide_cam.settings.frame_rate.update_value(8)
self.wide_cam.read_from_hardware()
self.vc = cv2.VideoCapture(0)
self.vc.set(cv2.CAP_FFMPEG, True)
self.vc.set(cv2.CAP_PROP_FPS, 30)
def setup_figure(self):
"""
Runs once during App initialization, after setup()
This is the place to make all graphical interface initializations,
build plots, etc.
"""
# connect ui widgets to measurement/hardware settings or functions
self.ui.start_pushButton.clicked.connect(self.start)
self.ui.interrupt_pushButton.clicked.connect(self.interrupt)
# Set up pyqtgraph graph_layout in the UI
self.wide_cam_layout = pg.GraphicsLayoutWidget()
self.ui.wide_cam_groupBox.layout().addWidget(self.wide_cam_layout)
# added by selina
# Set up pyqtgraph graph_layout in the UI
self.licking_layout = pg.GraphicsLayoutWidget()
self.ui.plot_groupBox.layout().addWidget(self.licking_layout)
# Create PlotItem object (a set of axes)
self.plot = self.licking_layout.addPlot(title="Sine Wave Readout Plot")
# Create PlotDataItem object ( a scatter plot on the axes )
self.optimize_plot_line = self.plot.plot([0])
# create camera image graphs
self.wide_cam_view = pg.ViewBox()
# rval, frame = self.vc.read()
self.wide_cam_layout.addItem(self.wide_cam_view)
self.wide_cam_image = pg.ImageItem()
self.wide_cam_view.addItem(self.wide_cam_image)
# counter used for reducing refresh rate
self.wide_disp_counter = 0
# connect setting to user interface
self.settings.lick_on.connect_to_widget(self.ui.lick_checkBox)
def update_display(self):
"""
Displays (plots) the numpy array self.buffer.
This function runs repeatedly and automatically during the measurement run.
its update frequency is defined by self.display_update_period
"""
# check availability of display queue of the wide camera
try:
ret, frame = self.vc.read()
self.wide_cam_image.setImage(
np.flipud(np.fliplr(frame[:, :, 2::-1].transpose(1, 0, 2))))
except Exception as ex:
print("Error: %s" % ex)
def run(self):
"""
Runs when measurement is started. Runs in a separate thread from GUI.
It should not update the graphical interface directly, and should only
focus on data acquisition.
"""
# # first, create a data file
# if self.settings['save_h5']:
# # if enabled will create an HDF5 file with the plotted data
# # first we create an H5 file (by default autosaved to app.settings['save_dir']
# # This stores all the hardware and app meta-data in the H5 file
# self.h5file = h5_io.h5_base_file(app=self.app, measurement=self)
#
# # create a measurement H5 group (folder) within self.h5file
# # This stores all the measurement meta-data in this group
# self.h5_group = h5_io.h5_create_measurement_group(measurement=self, h5group=self.h5file)
#
# # create an h5 dataset to store the data
# self.buffer_h5 = self.h5_group.create_dataset(name = 'buffer',
# shape = self.buffer.shape,
# dtype = self.buffer.dtype)
# We use a try/finally block, so that if anything goes wrong during a measurement,
# the finally block can clean things up, e.g. close the data file object.
# self.wide_cam._dev.set_buffer_count(500)
# if self.settings.save_video.value():
# save_dir = self.app.settings.save_dir.value()
# data_path = os.path.join(save_dir, self.app.settings.sample.value())
# try:
# os.makedirs(data_path)
# except OSError:
# print('directory already exists, writing to existing directory')
#
# self.recorder.settings.path.update_value(data_path)
# frame_rate = self.wide_cam.settings.frame_rate.value()
# self.recorder.create_file('wide_mov',frame_rate)
#
# # create a subthread and connect it to the interrupt subthread signal
# self.wide_disp_queue = queue.Queue(1000)
# self.camera_thread = SubMeasurementQThread(self.camera_action)
# self.interrupt_subthread.connect(self.camera_thread.interrupt)
# #start camera
# self.wide_cam.start()
#
# #start camera subthread
# self.camera_thread.start()
self.events_filename = '2019-7-17-test.xlsx'
self.reward_odor_index = 0
self.duration_rec_off = 6.5
self.duration_rec_on_before = 4 # change this to exponential decay
self.duration_odor_to_outcome = 1.3
self.duration_water_large = 0.2
self.duration_rec_on_after = 8
self.duration_odor_on = 0.5
self.lines = [0, 1, 2, 3]
self.counter = np.zeros(4)
self.numtrials = 200
self.p_cont_noncont = 0.5
self.p_USwCS = 0.5
self.p_USwoCS = 0.5
odors_cue = OdorGen(self.lines)
odors_cue.assign_odor()
self.reward_odor = odors_cue.set_rewardodor(
index=self.reward_odor_index)
odors_cue.initiate()
# odors_cue.odors_DAQ[i]
print('odor ready')
self.waterR = DAQSimpleDOTask('Dev1/port0/line2')
self.waterR.low()
# self.OdorOnCopy = DAQSimpleDOTask('Dev3/port2/line5')
# self.OdorOnCopy.low()
self.lickR = DAQSimpleDITask('Dev2_SELECT/port1/line0')
print('water ready')
# create excel workbook
self.wb = Workbook()
self.ws = self.wb.active
print('book ready')
#generate trial type
cont_reward = np.zeros(
int(self.numtrials * self.p_cont_noncont * self.p_USwCS)) # code 0
cont_noreward = np.ones(
int(self.numtrials * self.p_cont_noncont *
(1 - self.p_USwCS))) # code 1
temp_comb1 = np.concatenate((cont_reward, cont_noreward))
noncont_reward = np.ones(
int(self.numtrials *
(1 - self.p_cont_noncont) * self.p_USwoCS)) * 2 # code 2
noncont_noreward = np.ones(
int(self.numtrials * (1 - self.p_cont_noncont) *
(1 - self.p_USwoCS))) * 3 # code 3
temp_comb2 = np.concatenate((noncont_noreward, noncont_reward))
trialtypes = np.concatenate((temp_comb1, temp_comb2))
random.shuffle(trialtypes)
print('================== Trial Types =================')
print(trialtypes)
for t in range(0, self.numtrials):
print('================================================')
print('trial number: ', t)
print()
self.settings.in_trial.update_value(True)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=101)
# check lisking
self.check_licking_1spout(self.duration_rec_on_before)
# main training program
self.run_trial_type(int(trialtypes[t]))
# check licking
self.check_licking_1spout(self.duration_rec_on_after)
self.settings.in_trial.update_value(False)
# self.settings.save_video.update_value(False):
self.wb.save(self.events_filename)
self.check_licking_1spout(self.duration_rec_off)
if self.interrupt_measurement_called:
# tell subtherad to stop
self.interrupt_subthread.emit()
break
odors_cue.initiate()
odors_cue.close()
self.waterR.low()
self.waterR.close()
print('FINISHED ASSOCIATION TRAINING')
if self.settings.save_video.value:
self.recorder.close()
def check_licking_1spout(self, interval):
checkperiod = 0.01
timeout = time.time() + interval
right_lick_last = 0
while time.time() < timeout:
right_lick = self.lickR.read()
if right_lick != right_lick_last:
if right_lick:
self.settings.lick_status.update_value(11)
print('Lick')
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=11)
self.settings.lick_on.update_value(True)
else:
self.settings.lick_status.update_value(10)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=10)
self.settings.lick_on.update_value(False)
else:
self.settings.lick_status.update_value(0)
right_lick_last = right_lick
time.sleep(checkperiod)
def run_trial_type(self, types):
odor_on = False
reward_on = False
if types == 0:
print('contingency reward trial ' + str(int(self.counter[types])))
print('opening odor port')
odor_on = True
reward_on = True
r_code = [131, 130]
w_code = [51, 50]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(
self.duration_odor_to_outcome) ### can be a problem
self.run_reward_module(reward_on, w_code)
elif types == 1:
print('contingency no reward trial ' +
str(int(self.counter[types])))
print('opening odor port')
odor_on = True
r_code = [141, 140]
w_code = [61, 60]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(
self.duration_odor_to_outcome) ### can be a problem
self.run_reward_module(reward_on, w_code)
elif types == 2:
print('non-contingency reward trial ' +
str(int(self.counter[types])))
reward_on = True
r_code = [151, 150]
w_code = [71, 70]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(
self.duration_odor_to_outcome) ### can be a problem
self.run_reward_module(reward_on, w_code)
else:
print('non-contingency no reward trial ' +
str(int(self.counter[types])))
r_code = [161, 160]
w_code = [71, 70]
self.run_odor_module(odor_on, r_code)
self.check_licking_1spout(
self.duration_odor_to_outcome) ### can be a problem
self.run_reward_module(reward_on, w_code)
self.counter[types] += 1
self.wb.save(self.events_filename)
def run_odor_module(self, odor_on, r_code):
if odor_on:
self.reward_odor.high()
# self.OdorOnCopy.high() # ？？？
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[0])
time.sleep(self.duration_odor_on)
print('closing odor port')
self.reward_odor.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[1])
else:
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[0])
time.sleep(self.duration_odor_on)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=r_code[1])
def run_reward_module(self, reward_on, w_code):
if reward_on:
# modify! give water if licks three times within 1 s
print('opening water valve')
self.waterR.high()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[0])
self.check_licking_1spout(
self.duration_water_large) # this parameter hasn't een defined
print('closing water valve')
self.waterR.low()
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[1])
else:
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[0])
time.sleep(self.duration_water_large)
d = self.ws.cell(row=(self.ws.max_row + 1),
column=1,
value=time.clock())
d = self.ws.cell(row=self.ws.max_row, column=2, value=w_code[1])