def get(self, feats=()):
from json_param import Parameters
from riglib import experiment
Exp = experiment.make(self.task.get(), tuple(f.get() for f in self.feats.all())+feats)
params = Parameters(self.params)
params.trait_norm(Exp.class_traits())
if issubclass(Exp, experiment.Sequence):
gen, gp = self.sequence.get()
seq = gen(Exp, **gp)
exp = Exp(seq, **params.params)
else:
exp = Exp(**params.params)
exp.event_log = json.loads(self.report)
return exp
class TaskWrapper(object):
'''
Wrapper for Experiment classes launched from the web interface
'''
def __init__(self, subj, task_rec, feats, params, seq=None, seq_params=None, saveid=None):
'''
Parameters
----------
subj : tracker.models.Subject instance
Database record for subject performing the task
task_rec : tracker.models.Task instance
Database record for base task being run (without features)
feats : list
List of features to enable for the task
params : json_param.Parameters, or string representation of JSON object
user input on configurable task parameters
seq : models.Sequence instance, or tuple
Database record of Sequence parameters/static target sequence
If passed in as a tuple, then it's the result of calling 'seq.get' on the models.Sequence instance
seq_params: params from seq (see above)
saveid : int, optional
ID number of db.tracker.models.TaskEntry associated with this task
if None specified, then the data saved will not be linked to the
database entry and will be lost after the program exits
'''
self.saveid = saveid
self.taskname = task_rec.name
self.subj = subj
if isinstance(params, Parameters):
self.params = params
elif isinstance(params, (string, str)):
self.params = Parameters(params)
base_class = task_rec.get()
if None in feats:
raise Exception("Features not found properly in database!")
else:
Task = experiment.make(base_class, feats=feats)
# Run commands which must be executed before the experiment class can be instantiated (e.g., starting neural recording)
Task.pre_init(saveid=saveid)
self.params.trait_norm(Task.class_traits())
if issubclass(Task, experiment.Sequence):
# retreive the sequence data from the db, or from the input argument if the input arg was a tuple
if isinstance(seq, tuple):
gen_constructor, gen_params = seq
elif isinstance(seq, models.Sequence):
gen_constructor, gen_params = seq.get()
# Typically, 'gen_constructor' is the experiment.generate.runseq function (not an element of namelist.generators)
else:
raise ValueError("Unrecognized type for seq")
gen = gen_constructor(Task, **gen_params)
self.params.params['seq_params'] = seq_params
# 'gen' is now a true python generator usable by experiment.Sequence
self.task = Task(gen, **self.params.params)
with open(log_filename, 'a') as f:
f.write("instantiating task with a generator\n")
else:
self.task = Task(**self.params.params)
self.task.start()
def report(self):
return experiment.report(self.task)
def pause(self):
self.task.pause = not self.task.pause
return "pause" if self.task.pause else "running"
def end_task(self):
self.task.end_task()
def enable_clda(self):
self.task.enable_clda()
def disable_clda(self):
self.task.disable_clda()
def get_state(self):
return self.task.state
def __getattr__(self, attr):
# This function is only defined because __getattr__ is not defined
# for children of 'object' by default, but the TaskObjProxy always calles '__getattr__'
# when trying to remotely retreive an attribute. Might be avoidable if TaskObjProxy were
# to use '__getattribute__' instead
return getattr(self, attr)
def set_task_attr(self, attr, value):
setattr(self.task, attr, value)
def cleanup(self):
self.task.join()
print("Calling saveout/task cleanup code")
if self.saveid is not None:
# get object representing function calls to the remote database
# returns the result of tracker.dbq.rpc_handler
database = xmlrpc.client.ServerProxy("http://localhost:8000/RPC2/", allow_none=True)
cleanup_successful = self.task.cleanup(database, self.saveid, subject=self.subj)
# if not self.task._task_init_complete:
# from tracker import dbq
# dbq.hide_task_entry(self.saveid)
# print 'hiding task entry!'
# else:
# print 'not hiding task entry!'
else:
cleanup_successful = True
self.task.terminate()
return cleanup_successful
class TaskWrapper(object):
'''
Wrapper for Experiment classes launched from the web interface
'''
def __init__(self, subj, task_rec, feats, params, seq=None, seq_params=None, saveid=None):
'''
Parameters
----------
subj : tracker.models.Subject instance
Database record for subject performing the task
task_rec : tracker.models.Task instance
Database record for base task being run (without features)
feats : list
List of features to enable for the task
params : json_param.Parameters, or string representation of JSON object
user input on configurable task parameters
seq : models.Sequence instance, or tuple
Database record of Sequence parameters/static target sequence
If passed in as a tuple, then it's the result of calling 'seq.get' on the models.Sequence instance
seq_params: params from seq (see above)
saveid : int, optional
ID number of db.tracker.models.TaskEntry associated with this task
if None specified, then the data saved will not be linked to the
database entry and will be lost after the program exits
'''
self.saveid = saveid
self.taskname = task_rec.name
self.subj = subj
if isinstance(params, Parameters):
self.params = params
elif isinstance(params, (string, unicode)):
self.params = Parameters(params)
base_class = task_rec.get()
if None in feats:
raise Exception("Features not found properly in database!")
else:
Task = experiment.make(base_class, feats=feats)
# Run commands which must be executed before the experiment class can be instantiated (e.g., starting neural recording)
Task.pre_init(saveid=saveid)
self.params.trait_norm(Task.class_traits())
if issubclass(Task, experiment.Sequence):
# retreive the sequence data from the db, or from the input argument if the input arg was a tuple
if isinstance(seq, tuple):
gen_constructor, gen_params = seq
elif isinstance(seq, models.Sequence):
gen_constructor, gen_params = seq.get()
# Typically, 'gen_constructor' is the experiment.generate.runseq function (not an element of namelist.generators)
else:
raise ValueError("Unrecognized type for seq")
gen = gen_constructor(Task, **gen_params)
self.params.params['seq_params'] = seq_params
# 'gen' is now a true python generator usable by experiment.Sequence
self.task = Task(gen, **self.params.params)
with open(log_filename, 'a') as f:
f.write("instantiating task with a generator\n")
else:
self.task = Task(**self.params.params)
self.task.start()
def report(self):
return experiment.report(self.task)
def pause(self):
self.task.pause = not self.task.pause
return "pause" if self.task.pause else "running"
def end_task(self):
self.task.end_task()
def enable_clda(self):
self.task.enable_clda()
def disable_clda(self):
self.task.disable_clda()
def get_state(self):
return self.task.state
def __getattr__(self, attr):
# This function is only defined because __getattr__ is not defined
# for children of 'object' by default, but the TaskObjProxy always calles '__getattr__'
# when trying to remotely retreive an attribute. Might be avoidable if TaskObjProxy were
# to use '__getattribute__' instead
return getattr(self, attr)
def set_task_attr(self, attr, value):
setattr(self.task, attr, value)
def cleanup(self):
self.task.join()
print "Calling saveout/task cleanup code"
if self.saveid is not None:
# get object representing function calls to the remote database
# returns the result of tracker.dbq.rpc_handler
database = xmlrpclib.ServerProxy("http://localhost:8000/RPC2/", allow_none=True)
cleanup_successful = self.task.cleanup(database, self.saveid, subject=self.subj)
# if not self.task._task_init_complete:
# from tracker import dbq
# dbq.hide_task_entry(self.saveid)
# print 'hiding task entry!'
# else:
# print 'not hiding task entry!'
else:
cleanup_successful = True
self.task.terminate()
return cleanup_successful