class Reward_PreTraining:
def __init__(self):
self.experiment_finished = False
self._trials_list = self.generate_trials_list(self._trials, 30)
self._iti_list = self.generate_iti_list(30)
self._iti_duration = 10
self._intertrial_timer = Timer(self._iti_duration)
self._process = SimpleProtocolProcess(self._trials)
self._chosen_trial = None
self._exp_timer = Timer(1800)
self._trial_counter = 0
self._print_check = False
def check_skeleton(self, frame, skeleton):
status, trial = self._process.get_status()
if status:
result = self._process.get_result()
if result is not None:
# if trial is finished, takes new ITI.
self._iti_duration = next(self._iti_list, False)
self._intertrial_timer = Timer(self._iti_duration)
elif self.check_triggers(
skeleton) and not self._intertrial_timer.check_timer():
# check trial end trigger and starts Timer
self._intertrial_timer.start()
if not self._print_check:
print("Reward was taken. Going into InterTrialTime for " +
str(self._iti_duration) + " sec.")
self._print_check = True
# resets chosen_trial
self._chosen_trial = None
elif not self._intertrial_timer.check_timer():
# if the timer ran out or was not started yet again
self._print_check = False
if self._chosen_trial is None:
# if the chosen_trial was reset or first time
self._chosen_trial = next(self._trials_list, False)
if not self._chosen_trial:
# if no more trials exist in iter
print("Experiment is finished due to max. trial number.")
exp_time = self._exp_timer.return_time()
print("Experiment took " + str(exp_time) + " sec")
self.stop_experiment()
self._trial_counter += 1
print("Stimulation: #", str(self._trial_counter))
self._process.set_trial(self._chosen_trial)
self.check_end_time()
def check_triggers(self, skeleton):
"""
checks stage dependent trigger dict
:param skeleton: bodypart coordinates
:return: returns whether all triggers were true
"""
result_list = []
result = False
for trigger in self._triggers.values():
trigger_result, _ = trigger.check_skeleton(skeleton)
result_list.append(trigger_result)
if all(result_list):
result = True
return result
@property
def _trials(self):
"""this is a dummy version of the more complex experiments to keep the general flow"""
trials = {"Pretraining": dict(stimulus_timer=None, count=0)}
return trials
@property
def _triggers(self):
"""
creates trial start condition triggers depending on the experimental stage"
:return: dict of triggers
"""
triggers = dict(region=RegionTrigger("circle", (648, 38), 30, "nose"))
return triggers
@staticmethod
def generate_trials_list(trials: dict, length: int):
trials_list = []
for trial in range(length):
trials_list.append(random.choice(list(trials.keys())))
return iter(trials_list)
@staticmethod
def generate_iti_list(length: int, min: int = 0):
iti_list = []
for i in range(length):
iti = random.randint(min, 30 + 1)
iti_list.append(iti)
return iter(iti_list)
def check_end_time(self):
if not self._exp_timer.check_timer():
# if experimental time ran out, finish experiments
print("Experiment is finished")
print("Time ran out.")
self.stop_experiment()
def start_experiment(self):
if not self.experiment_finished:
self._intertrial_timer.start()
self._exp_timer.start()
self._process.start()
def stop_experiment(self):
# stopping the experiment
self._process.end()
self.experiment_finished = True
def get_trial(self):
return self._chosen_trial
def get_info(self):
""" returns optional info"""
info = None
return info
class SecondExperiment:
def __init__(self):
self.experiment_finished = False
self._green_point = GREEN_POINT
self._blue_point = BLUE_POINT
self._radius = 20.5
self._event = None
self._stage = 3
self._count = {trial: 0 for trial in self._trials}
self._exp_timer = Timer(600)
# For automatic switches between stages:
# self._stages = 2
# self._completion_counter = {stage: False for stage in range(1, self._stages+1)}
def check_skeleton(self, frame, skeleton):
# if not all(self._completion_counter.values()):
# if not all stages are completed
for trial in self._trials:
# check for all trials if condition is met
result, response = self._trials[trial]["trigger"](
skeleton=skeleton)
if self._event is None:
# if there is no current trial as event already
if result:
# if condition is met set current trial as event
self._event = trial
self._count[trial] += 1
else:
# if there is a current trial set as event
if not result and self._event == trial:
# if the condition for current trial is not met, reset event
self._event = None
elif result and self._event != trial:
# if condition is met but event is not current trial(but last trial), set current trial as event
self._event = trial
self._count[trial] += 1
# plot_triggers_response(frame, response)
print(self._event)
print("green: {}".format(self._count["Greenbar_whiteback"]))
print("blue: {}".format(self._count["Bluebar_whiteback"]))
if self._event is not None:
# if there is a trial set as event, show stimulus
print("I am not none!")
show_visual_stim_img(type=self._event, name="inside")
elif self._event is None:
# if there is no trial set as event, show background
show_visual_stim_img(name="inside")
if all(trials >= EXP_COMPLETION for trials in self._count.values()):
# if all trials reached number of repeats of completion criterion, set stage as completed and go higher
# self._completion_counter[self._stage] = True
# finish the experiment if stage is completed
print("Stage " + str(self._stage) + " completed!")
self.stop_experiment()
self.check_exp_timer()
# self._stage += 1
# else:
# # finish the experiment if all stages are completed
# self.stop_experiment()
@property
def _trials(self):
orientation_angle = 30
orientation_bodyparts = ["neck", "nose"]
region_bodyparts = "nose"
if self._stage == 1:
green_roi = RegionTrigger("circle", self._green_point,
self._radius * 2 + 7.5, region_bodyparts)
blue_roi = RegionTrigger("circle", self._blue_point,
self._radius * 2 + 7.5, region_bodyparts)
trials = {
"Greenbar_whiteback":
dict(trigger=green_roi.check_skeleton, count=0),
"Bluebar_whiteback":
dict(trigger=blue_roi.check_skeleton, count=0),
}
elif self._stage == 2:
green_roi = RegionTrigger(
"circle",
self._green_point,
self._radius * 2 + 7.5 * 5,
region_bodyparts,
)
blue_roi = RegionTrigger("circle", self._blue_point,
self._radius * 2 + 7.5 * 5,
region_bodyparts)
green_dir = DirectionTrigger(self._green_point, orientation_angle,
orientation_bodyparts, True)
blue_dir = DirectionTrigger(self._blue_point, orientation_angle,
orientation_bodyparts, True)
def res_func(roi, direct, skeleton):
res_roi, response_roi = roi.check_skeleton(skeleton)
res_dir, response_dir = direct.check_skeleton(skeleton)
final_result = all([res_roi, res_dir])
response_roi["plot"].update(response_dir["plot"])
return final_result, response_roi
trials = {
"Greenbar_whiteback":
dict(trigger=partial(res_func, roi=green_roi,
direct=green_dir),
count=0),
"Bluebar_whiteback":
dict(trigger=partial(res_func, roi=blue_roi, direct=blue_dir),
count=0),
}
elif self._stage == 3:
green_roi = RegionTrigger(
"circle",
self._green_point,
self._radius * 2 + 7.5 * 10,
region_bodyparts,
)
blue_roi = RegionTrigger(
"circle",
self._blue_point,
self._radius * 2 + 7.5 * 10,
region_bodyparts,
)
green_dir = DirectionTrigger(self._green_point, orientation_angle,
orientation_bodyparts, True)
blue_dir = DirectionTrigger(self._blue_point, orientation_angle,
orientation_bodyparts, True)
def res_func(roi, direct, skeleton):
res_roi, response_roi = roi.check_skeleton(skeleton)
res_dir, response_dir = direct.check_skeleton(skeleton)
final_result = all([res_roi, res_dir])
response_roi["plot"].update(response_dir["plot"])
return final_result, response_roi
trials = {
"Greenbar_whiteback":
dict(trigger=partial(res_func, roi=green_roi,
direct=green_dir),
count=0),
"Bluebar_whiteback":
dict(trigger=partial(res_func, roi=blue_roi, direct=blue_dir),
count=0),
}
# green_dir = DirectionTrigger(self._green_point, orientation_angle, orientation_bodyparts, True)
# blue_dir = DirectionTrigger(self._blue_point, orientation_angle, orientation_bodyparts, True)
#
# trials = {'Greenbar_whiteback': dict(trigger=green_dir.check_skeleton,
# count=0),
# 'Bluebar_whiteback': dict(trigger=blue_dir.check_skeleton,
# count=0)}
return trials
def check_exp_timer(self):
if not self._exp_timer.check_timer():
print("Experiment is finished")
print("Time ran out.")
self.stop_experiment()
def start_experiment(self):
# not necessary as this experiment is not needing any multiprocessing
if not self.experiment_finished:
self._exp_timer.start()
def stop_experiment(self):
self.experiment_finished = True
print("Experiment completed!")
def get_trial(self):
return self._event
def get_info(self):
""" returns optional info"""
info = None
return info
class OptogenExperiment:
def __init__(self):
self.experiment_finished = False
self._point = POINT
self._start_angle, self._end_angle = ANGLE_WINDOW
self._intertrial_timer = Timer(15)
self._experiment_timer = Timer(1800)
self._event = False
self._event_start = None
self._results = []
self._max_trial_time = 5
self._min_trial_time = 1
self._max_total_time = 600
self._total_time = 0
self._trial_time = 0
def check_skeleton(self, frame, skeleton):
if self._experiment_timer.check_timer():
if self._total_time >= self._max_total_time:
# check if total time to stimulate per experiment is reached
print("Ending experiment, total event time ran out")
self.stop_experiment()
else:
# if not continue
if not self._intertrial_timer.check_timer():
# check if there is an intertrial time running right now, if not continue
# check if the headdirection angle is within limits
_, angle_point = angle_between_vectors(
*skeleton["neck"], *skeleton["nose"], *self._point)
if self._start_angle <= angle_point <= self._end_angle:
if not self._event:
# if a stimulation event wasn't started already, start one
print("Starting Stimulation")
self._event = True
# and activate the laser, start the timer and reset the intertrial timer
laser_switch(True)
self._event_start = time.time()
self._intertrial_timer.reset()
else:
if time.time(
) - self._event_start <= self._max_trial_time:
# if the total event time has not reached the maximum time per event
# self._trial_time = time.time() - self._event_start
pass
else:
# if the maximum event time was reached, reset the event,
# turn off the laser and start intertrial time
print(
"Ending Stimulation, Stimulation time ran out"
)
self._event = False
# laser_toggle(False)
laser_switch(False)
# self._trial_time = time.time() - self._event_start
trial_time = time.time() - self._event_start
self._total_time += trial_time
self._results.append(trial_time)
print("Stimulation duration", trial_time)
self._intertrial_timer.start()
else:
# if the headdirection is not within the parameters
if self._event:
# but the stimulation is still going
if time.time(
) - self._event_start < self._min_trial_time:
# check if the minimum event time was not reached, then pass
pass
else:
# if minumum event time has been reached, reset the event,
# turn of the laser and start intertrial time
print("Ending Stimulation, angle not in range")
self._event = False
# laser_toggle(False)
laser_switch(False)
# self._trial_time = time.time() - self._event_start
trial_time = time.time() - self._event_start
self._total_time += trial_time
self._results.append(trial_time)
print("Stimulation duration", trial_time)
self._intertrial_timer.start()
else:
# if maximum experiment time was reached, stop experiment
print("Ending experiment, timer ran out")
self.stop_experiment()
return self._event
def start_experiment(self):
# not necessary as this experiment is not needing any multiprocessing
self._experiment_timer.start()
def stop_experiment(self):
self.experiment_finished = True
print("Experiment completed!")
print("Total event duration", sum(self._results))
print(self._results)
def get_trial(self):
return self._event
def get_info(self):
""" returns optional info"""
info = None
return info
class FirstExperiment:
def __init__(self):
self.experiment_finished = False
self._trials_list = self.generate_trials_list(self._trials, EXP_LENGTH)
self._result_list = []
self._iti_list = self.generate_iti_list(EXP_LENGTH, min=10)
self._iti_duration = INTERTRIAL_TIME
self._intertrial_timer = Timer(self._iti_duration)
self._penalty_timer = Timer(PENALTY_TIME)
self._process = ClassicProtocolProcess(self._trials)
self._success_count = {trial: [] for trial in self._trials}
self._completion_counter = {trial: False for trial in self._trials}
self._event = None
self._chosen_trial = None
self._print_check = False
self._stage = 1
self._exp_timer = Timer(EXP_TIME)
def check_skeleton(self, frame, skeleton):
status, trial = self._process.get_status()
if status:
current_trial = self._trials[trial]
condition, response = current_trial["trigger"].check_skeleton(
skeleton)
self._process.pass_condition(condition)
result = self._process.get_result()
if result is not None:
self.process_result(result, trial)
self._chosen_trial = None
print(self._completion_counter)
# check if all trials were successful until completion
if all(self._completion_counter.values()):
print("Experiment is finished")
print("All trials reached required amount of successes")
self.stop_experiment()
# if not continue
self._iti_duration = next(self._iti_list, False)
self._intertrial_timer = Timer(self._iti_duration)
print(" Going into InterTrialTime for " +
str(self._iti_duration) + " sec.")
self._intertrial_timer.start()
result = None
plot_triggers_response(frame, response)
# elif not self._intertrial_timer.check_timer() and not self._penalty_timer.check_timer():
elif not self._intertrial_timer.check_timer():
# chosen_trial = random.choice(list(self._experiment['possible_trials'].keys()))
if self._chosen_trial is None:
self._chosen_trial = next(self._trials_list, False)
elif not self._chosen_trial:
print("Experiment is finished due to max. trial number.")
print(self._result_list)
self.stop_experiment()
elif self._counter["result"][("Greenbar_whiteback", True)] >= 20:
print("Reached max amount of CS+ trial successes!")
print(self._result_list)
self.stop_experiment()
else:
# if self._counter['trial']['Greenbar_whiteback'] >= 10:
# # check if 10 green trials have passed and change trigger stage
# self._stage = 2
if self.check_triggers(skeleton):
# check trial start triggers
self._process.set_trial(self._chosen_trial)
self._print_check = False
elif not self._print_check:
print("Next trial: #" + str(len(self._result_list) + 1) +
" " + self._chosen_trial)
print(
"Animal is not meeting trial start criteria, the start of trial is delayed."
)
self._print_check = True
# self._penalty_timer.reset()
# self._penalty_timer.start()
# if experimental time ran out, finish experiments
self.check_exp_timer()
def process_result(self, result, trial):
"""
Will add result if TRUE or reset comp_counter if FALSE
:param result: bool if trial was successful
:param trial: str name of the trial
:return:
"""
self._result_list.append((trial, result))
if result is True:
if (trial == "Bluebar_whiteback" and
self._completion_counter["Greenbar_whiteback"] is False):
self._success_count[trial] = []
print("Success ignored. Waiting for Green.")
else:
self._success_count[trial].append(result)
self.check_completion()
print("Trial successful")
print("Successful trials in a row so far:" +
str(len(self._success_count[trial])))
else:
self._success_count[trial] = []
print("Trial failed, resetting completion criterion")
trial_counter = self._counter["trial"]
result_counter = self._counter["result"]
print(trial_counter)
print(result_counter)
def check_completion(self):
"""
Check the stored successes count for required amount of successes in a row
"""
pass
# for trial in self._trials:
# if len(self._success_count[trial]) >= EXP_COMPLETION:
# if trial == 'Bluebar_whiteback' and self._completion_counter['Greenbar_whiteback'] is True:
# self._completion_counter[trial] = True
# elif trial == 'Greenbar_whiteback':
# self._completion_counter[trial] = True
def check_triggers(self, skeleton):
"""
checks stage dependent trigger dict
:param skeleton: bodypart coordinates
:return: returns whether all triggers were true
"""
result_list = []
result = False
for trigger in self._triggers.values():
trigger_result, _ = trigger.check_skeleton(skeleton)
result_list.append(trigger_result)
if all(result_list):
result = True
return result
@staticmethod
def generate_trials_list(trials: dict, length: int):
trials_list = []
for trial in range(length):
trials_list.append(random.choice(list(trials.keys())))
return iter(trials_list)
@staticmethod
def generate_iti_list(length: int, min: int = 0):
iti_list = []
for i in range(length):
iti = random.randint(min, INTERTRIAL_TIME + 1)
iti_list.append(iti)
return iter(iti_list)
@property
def _trials(self):
# self.triggers['orient'] = ScreenTrigger('North', 90, ['neck', 'nose'])
region_trigger = RegionTrigger("circle", (650, 37), 50, "nose")
outside_trigger = OutsideTrigger("circle", (650, 37), 50, "nose")
if not CTRL:
trials = {
"Greenbar_whiteback":
dict(
stimulus_timer=Timer(10),
collection_timer=Timer(10),
success_timer=Timer(7),
trigger=region_trigger,
result_func=any,
random_reward=False,
),
"Bluebar_whiteback":
dict(
stimulus_timer=Timer(10),
collection_timer=Timer(10),
success_timer=Timer(7),
trigger=outside_trigger,
result_func=all,
random_reward=False,
),
}
else:
trials = {
"CTRL":
dict(
stimulus_timer=Timer(10),
collection_timer=Timer(7),
success_timer=Timer(10),
trigger=region_trigger,
result_func=any,
random_reward=False,
)
}
return trials
@property
def _triggers(self):
"""
creates trial start condition triggers depending on the experimental stage"
:return: dict of triggers
"""
if self._stage == 1:
triggers = dict(
orient=ScreenTrigger("North", 90, ["neck", "nose"]))
# if self._stage == 2:
# triggers = dict(orient = ScreenTrigger('North', 90, ['neck', 'nose']),
# region = OutsideTrigger('circle', (650, 50), 50, 'nose'))
return triggers
@property
def _counter(self):
"""
counts instances of each past trial as saved in result_list dict
:return: dictionary of all trial types (key) and number of past occurences (value)
"""
trial_list = [i[0] for i in self._result_list]
trial_counter = Counter(trial_list)
res_counter = Counter(self._result_list)
return {"trial": trial_counter, "result": res_counter}
def check_exp_timer(self):
if not self._exp_timer.check_timer():
print("Experiment is finished")
print("Time ran out.")
self.stop_experiment()
def start_experiment(self):
if not self.experiment_finished:
self._exp_timer.start()
self._intertrial_timer.start()
self._process.start()
def stop_experiment(self):
# stopping the experiment
self._process.end()
self.experiment_finished = True
def get_trial(self):
return self._chosen_trial
def get_info(self):
""" returns optional info"""
info = None
return info
class SpeedExperiment:
"""
Simple class to contain all of the experiment properties
Uses multiprocess to ensure the best possible performance and
to showcase that it is possible to work with any type of equipment, even timer-dependent
"""
def __init__(self):
self.experiment_finished = False
self._threshold = 10
self._event = None
self._current_trial = None
self._event_count = 0
self._trigger = SpeedTrigger(threshold=self._threshold,
bodypart="tailroot",
timewindow_len=5)
self._exp_timer = Timer(600)
def check_skeleton(self, frame, skeleton):
"""
Checking each passed animal skeleton for a pre-defined set of conditions
Outputting the visual representation, if exist
Advancing trials according to inherent logic of an experiment
:param frame: frame, on which animal skeleton was found
:param skeleton: skeleton, consisting of multiple joints of an animal
"""
self.check_exp_timer() # checking if experiment is still on
if not self.experiment_finished:
result, response = self._trigger.check_skeleton(skeleton=skeleton)
plot_triggers_response(frame, response)
if result:
laser_switch(True)
self._event_count += 1
print(self._event_count)
print("Light on")
else:
laser_switch(False)
print("Light off")
return result, response
def check_exp_timer(self):
"""
Checking the experiment timer
"""
if not self._exp_timer.check_timer():
print("Experiment is finished")
print("Time ran out.")
self.stop_experiment()
def start_experiment(self):
"""
Start the experiment
"""
if not self.experiment_finished:
self._exp_timer.start()
def stop_experiment(self):
"""
Stop the experiment and reset the timer
"""
self.experiment_finished = True
print("Experiment completed!")
self._exp_timer.reset()
# don't forget to stop the laser for safety!
laser_switch(False)
def get_trial(self):
"""
Check which trial is going on right now
"""
return self._current_trial
class ExampleSocialInteractionExperiment:
"""
In this experiment the skeleton/instance of each animal will be considers for the trigger,
any animal can trigger the stimulation (the first one to result in TRUE).
Simple class to contain all of the experiment properties
Uses multiprocess to ensure the best possible performance and
to showcase that it is possible to work with any type of equipment, even timer-dependent
"""
def __init__(self):
self.experiment_finished = False
self._process = ExampleProtocolProcess()
self._proximity_threshold = 30
self._min_animals = 2
self._event = None
self._current_trial = None
self._max_reps = 999
self._trial_count = {trial: 0 for trial in self._trials}
self._trial_timers = {trial: Timer(10) for trial in self._trials}
self._exp_timer = Timer(600)
def check_skeleton(self, frame, skeletons):
"""
Checking passed animal skeletons for a pre-defined set of conditions
Outputting the visual representation, if exist
Advancing trials according to inherent logic of an experiment
:param frame: frame, on which animal skeleton was found
:param skeletons: skeletons, consisting of multiple joints of an animal
"""
self.check_exp_timer() # checking if experiment is still on
for trial in self._trial_count:
# checking if any trial hit a predefined cap
if self._trial_count[trial] >= self._max_reps:
self.stop_experiment()
if not self.experiment_finished:
result, response = False, None
# checking if enough animals were detected
if len(skeletons) >= self._min_animals:
for trial in self._trials:
# check if social interaction trigger is true
result, response = self._trials[trial]["trigger"](
skeletons=skeletons)
plot_triggers_response(frame, response)
if result:
if self._current_trial is None:
if not self._trial_timers[trial].check_timer():
self._current_trial = trial
self._trial_timers[trial].reset()
self._trial_count[trial] += 1
print(trial, self._trial_count[trial])
else:
if self._current_trial == trial:
self._current_trial = None
self._trial_timers[trial].start()
self._process.set_trial(self._current_trial)
else:
pass
return result, response
@property
def _trials(self):
"""
Defining the trials
"""
identification_dict = dict(active={
"animal": 1,
"bp": ["bp0"]
},
passive={
"animal": 0,
"bp": ["bp2"]
})
interaction_trigger = SocialInteractionTrigger(
threshold=self._proximity_threshold,
identification_dict=identification_dict,
interaction_type="proximity",
debug=True,
)
trials = {
"DLStream_test":
dict(trigger=interaction_trigger.check_skeleton, count=0)
}
return trials
def check_exp_timer(self):
"""
Checking the experiment timer
"""
if not self._exp_timer.check_timer():
print("Experiment is finished")
print("Time ran out.")
self.stop_experiment()
def start_experiment(self):
"""
Start the experiment
"""
self._process.start()
if not self.experiment_finished:
self._exp_timer.start()
def stop_experiment(self):
"""
Stop the experiment and reset the timer
"""
self.experiment_finished = True
print("Experiment completed!")
self._exp_timer.reset()
# don't forget to end the process!
self._process.end()
def get_trial(self):
"""
Check which trial is going on right now
"""
return self._current_trial
class ExampleExperiment:
"""
Simple class to contain all of the experiment properties
Uses multiprocess to ensure the best possible performance and
to showcase that it is possible to work with any type of equipment, even timer-dependent
"""
def __init__(self):
self.experiment_finished = False
self._process = ExampleProtocolProcess()
self._green_point = (550, 163)
self._blue_point = (372, 163)
self._radius = 40
self._event = None
self._current_trial = None
self._trial_count = {trial: 0 for trial in self._trials}
self._trial_timers = {trial: Timer(10) for trial in self._trials}
self._exp_timer = Timer(600)
def check_skeleton(self, frame, skeleton):
"""
Checking each passed animal skeleton for a pre-defined set of conditions
Outputting the visual representation, if exist
Advancing trials according to inherent logic of an experiment
:param frame: frame, on which animal skeleton was found
:param skeleton: skeleton, consisting of multiple joints of an animal
"""
self.check_exp_timer() # checking if experiment is still on
for trial in self._trial_count:
# checking if any trial hit a predefined cap
if self._trial_count[trial] >= 10:
self.stop_experiment()
if not self.experiment_finished:
result, response = False, None
for trial in self._trials:
# check for all trials if condition is met
result, response = self._trials[trial]["trigger"](
skeleton=skeleton)
plot_triggers_response(frame, response)
if result:
if self._current_trial is None:
if not self._trial_timers[trial].check_timer():
self._current_trial = trial
self._trial_timers[trial].reset()
self._trial_count[trial] += 1
print(trial, self._trial_count[trial])
else:
if self._current_trial == trial:
self._current_trial = None
self._trial_timers[trial].start()
self._process.set_trial(self._current_trial)
return result, response
@property
def _trials(self):
"""
Defining the trials
"""
green_roi = RegionTrigger("circle", self._green_point,
self._radius * 2 + 7.5, "neck")
blue_roi = RegionTrigger("circle", self._blue_point,
self._radius * 2 + 7.5, "neck")
trials = {
"Greenbar_whiteback": dict(trigger=green_roi.check_skeleton,
count=0),
"Bluebar_whiteback": dict(trigger=blue_roi.check_skeleton,
count=0),
}
return trials
def check_exp_timer(self):
"""
Checking the experiment timer
"""
if not self._exp_timer.check_timer():
print("Experiment is finished")
print("Time ran out.")
self.stop_experiment()
def start_experiment(self):
"""
Start the experiment
"""
self._process.start()
if not self.experiment_finished:
self._exp_timer.start()
def stop_experiment(self):
"""
Stop the experiment and reset the timer
"""
self.experiment_finished = True
print("Experiment completed!")
self._exp_timer.reset()
# don't forget to end the process!
self._process.end()
def get_trial(self):
"""
Check which trial is going on right now
"""
return self._current_trial
class ExampleMultipleAnimalExperiment:
"""
In this experiment the skeleton/instance of each animal will be considers for the trigger,
any animal can trigger the stimulation (the first one to result in TRUE).
Simple class to contain all of the experiment properties
Uses multiprocess to ensure the best possible performance and
to showcase that it is possible to work with any type of equipment, even timer-dependent
"""
def __init__(self):
self.experiment_finished = False
self._process = ExampleProtocolProcess()
self._green_point = (550, 163)
self._radius = 40
self._dist_threshold = 80
self._event = None
self._current_trial = None
self._max_reps = 10
self._trial_count = {trial: 0 for trial in self._trials}
self._trial_timers = {trial: Timer(10) for trial in self._trials}
self._exp_timer = Timer(600)
def check_skeleton(self, frame, skeletons):
"""
Checking each passed animal skeleton for a pre-defined set of conditions
Outputting the visual representation, if exist
Advancing trials according to inherent logic of an experiment
:param frame: frame, on which animal skeleton was found
:param skeletons: skeletons, consisting of multiple joints of an animal
"""
self.check_exp_timer() # checking if experiment is still on
for trial in self._trial_count:
# checking if any trial hit a predefined cap
if self._trial_count[trial] >= self._max_reps:
self.stop_experiment()
if not self.experiment_finished:
result, response = False, None
for trial in self._trials:
# check for all trials if condition is met
result_list = []
for skeleton in skeletons:
# checking each skeleton for trigger success
result, response = self._trials[trial]['trigger'](
skeleton=skeleton)
# if one of the triggers is true, break the loop and continue (the first True)
if result:
break
plot_triggers_response(frame, response)
if result:
if self._current_trial is None:
if not self._trial_timers[trial].check_timer():
self._current_trial = trial
self._trial_timers[trial].reset()
self._trial_count[trial] += 1
print(trial, self._trial_count[trial])
else:
if self._current_trial == trial:
self._current_trial = None
self._trial_timers[trial].start()
self._process.set_trial(self._current_trial)
return result, response
@property
def _trials(self):
"""
Defining the trials
"""
green_roi = RegionTrigger('circle', self._green_point,
self._radius * 2 + 7.5, 'bp1')
trials = {
'Greenbar_whiteback': dict(trigger=green_roi.check_skeleton,
count=0)
}
return trials
def check_exp_timer(self):
"""
Checking the experiment timer
"""
if not self._exp_timer.check_timer():
print("Experiment is finished")
print("Time ran out.")
self.stop_experiment()
def start_experiment(self):
"""
Start the experiment
"""
self._process.start()
if not self.experiment_finished:
self._exp_timer.start()
def stop_experiment(self):
"""
Stop the experiment and reset the timer
"""
self.experiment_finished = True
print('Experiment completed!')
self._exp_timer.reset()
# don't forget to end the process!
self._process.end()
def get_trial(self):
"""
Check which trial is going on right now
"""
return self._current_trial