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 __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)
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