def get_condition(rng, dt, context={}):
#-------------------------------------------------------------------------------------
# Wager or no wager?
#-------------------------------------------------------------------------------------
wager = context.get('wager')
if wager is None:
wager = rng.choice(wagers)
#-------------------------------------------------------------------------------------
# Epochs
#-------------------------------------------------------------------------------------
stimulus = context.get('stimulus')
if stimulus is None:
stimulus = stimulus_min + tasktools.truncated_exponential(rng, dt, stimulus_mean,
xmax=stimulus_max)
delay = context.get('delay')
if delay is None:
delay = tasktools.truncated_exponential(rng, dt, delay_mean,
xmin=delay_min, xmax=delay_max)
if wager:
sure_onset = context.get('sure_onset')
if sure_onset is None:
sure_onset = tasktools.truncated_exponential(rng, dt, sure_mean,
xmin=sure_min, xmax=sure_max)
durations = {
'fixation': (0, fixation),
'stimulus': (fixation, fixation + stimulus),
'delay': (fixation + stimulus, fixation + stimulus + delay),
'decision': (fixation + stimulus + delay, tmax),
'tmax': tmax
}
if wager:
durations['sure'] = (fixation + stimulus + sure_onset, tmax)
time, epochs = tasktools.get_epochs_idx(dt, durations)
#-------------------------------------------------------------------------------------
# Trial
#-------------------------------------------------------------------------------------
left_right = context.get('left_right')
if left_right is None:
left_right = rng.choice(left_rights)
coh = context.get('coh')
if coh is None:
coh = rng.choice(cohs)
return {
'durations': durations,
'time': time,
'epochs': epochs,
'wager': wager,
'left_right': left_right,
'coh': coh
}
def get_condition(rng, dt, context={}):
#-------------------------------------------------------------------------------------
# Wager or no wager?
#-------------------------------------------------------------------------------------
wager = context.get('wager')
if wager is None:
wager = rng.choice(wagers)
#-------------------------------------------------------------------------------------
# Epochs
#-------------------------------------------------------------------------------------
stimulus = context.get('stimulus')
if stimulus is None:
stimulus = stimulus_min + tasktools.truncated_exponential(rng, dt, stimulus_mean,
xmax=stimulus_max)
delay = context.get('delay')
if delay is None:
delay = tasktools.truncated_exponential(rng, dt, delay_mean,
xmin=delay_min, xmax=delay_max)
if wager:
sure_onset = context.get('sure_onset')
if sure_onset is None:
sure_onset = tasktools.truncated_exponential(rng, dt, sure_mean,
xmin=sure_min, xmax=sure_max)
durations = {
'fixation': (0, fixation),
'stimulus': (fixation, fixation + stimulus),
'delay': (fixation + stimulus, fixation + stimulus + delay),
'decision': (fixation + stimulus + delay, tmax),
'tmax': tmax
}
if wager:
durations['sure'] = (fixation + stimulus + sure_onset, tmax)
time, epochs = tasktools.get_epochs_idx(dt, durations)
#-------------------------------------------------------------------------------------
# Trial
#-------------------------------------------------------------------------------------
left_right = context.get('left_right')
if left_right is None:
left_right = rng.choice(left_rights)
coh = context.get('coh')
if coh is None:
coh = rng.choice(cohs)
return {
'durations': durations,
'time': time,
'epochs': epochs,
'wager': wager,
'left_right': left_right,
'coh': coh
}
def get_condition(rng,
dt,
context={},
choiceHis=[],
rewardHis=[],
trial_count=0):
#-------------------------------------------------------------------------------------
# Epochs
#-------------------------------------------------------------------------------------
#print "running here"
ITI = context.get('ITI')
if ITI is None:
ITI = tasktools.truncated_exponential(rng, dt, ITI_min, ITI_min,
ITI_max)
#print ITI
durations = {
'go': (0, go),
'decision': (go, go + decision),
#'reward': (go + decision, go + decision + reward),
'ITI': (go + decision, go + decision + ITI),
'tmax': tmax
}
time, epochs = tasktools.get_epochs_idx(dt, durations)
#-------------------------------------------------------------------------------------
# Trial
#-------------------------------------------------------------------------------------
juice = context.get('juice')
if juice is None:
juice = juices
offer = context.get('offer')
if offer is None:
pred_choice = binomial_test(choiceHis, rewardHis, trial_count)
#offer = tasktools.choice(rng, offers)
offer = offers[pred_choice - 2]
#juiceL, juiceR = juice
#nB, nA = offer
nL, nR = offer
#if juiceL == 'A':
# nL, nR = nA, nB
#else:
# nL, nR = nB, nA
return {
'durations': durations,
'time': time,
'epochs': epochs,
'juice': juices,
'offer': offer,
'nL': nL,
'nR': nR
}
def get_condition(rng, dt, context={}):
#-------------------------------------------------------------------------------------
# Epochs
#-------------------------------------------------------------------------------------
delay = context.get('delay')
if delay is None:
delay = delay_min + tasktools.truncated_exponential(
rng, dt, delay_mean, xmax=delay_max)
durations = {
'fixation': (0, fixation),
'stimulus': (fixation, fixation + stimulus),
'delay': (fixation + stimulus, fixation + stimulus + delay),
'decision': (fixation + stimulus + delay, tmax),
'tmax': tmax
}
time, epochs = tasktools.get_epochs_idx(dt, durations)
#-------------------------------------------------------------------------------------
# Trial
#-------------------------------------------------------------------------------------
context_ = context.get('context')
if context_ is None:
context_ = rng.choice(contexts)
left_right_m = context.get('left_right_m')
if left_right_m is None:
left_right_m = rng.choice(left_rights)
left_right_c = context.get('left_right_c')
if left_right_c is None:
left_right_c = rng.choice(left_rights)
coh_m = context.get('coh_m')
if coh_m is None:
coh_m = rng.choice(cohs)
coh_c = context.get('coh_c')
if coh_c is None:
coh_c = rng.choice(cohs)
return {
'durations': durations,
'time': time,
'epochs': epochs,
'context': context_,
'left_right_m': left_right_m,
'left_right_c': left_right_c,
'coh_m': coh_m,
'coh_c': coh_c
}
def get_condition(rng, dt, context={}):
#-------------------------------------------------------------------------------------
# Epochs
#-------------------------------------------------------------------------------------
delay = context.get('delay')
if delay is None:
delay = delay_min + tasktools.truncated_exponential(rng, dt, delay_mean,
xmax=delay_max)
durations = {
'fixation': (0, fixation),
'stimulus': (fixation, fixation + stimulus),
'delay': (fixation + stimulus, fixation + stimulus + delay),
'decision': (fixation + stimulus + delay, tmax),
'tmax': tmax
}
time, epochs = tasktools.get_epochs_idx(dt, durations)
#-------------------------------------------------------------------------------------
# Trial
#-------------------------------------------------------------------------------------
context_ = context.get('context')
if context_ is None:
context_ = rng.choice(contexts)
left_right_m = context.get('left_right_m')
if left_right_m is None:
left_right_m = rng.choice(left_rights)
left_right_c = context.get('left_right_c')
if left_right_c is None:
left_right_c = rng.choice(left_rights)
coh_m = context.get('coh_m')
if coh_m is None:
coh_m = rng.choice(cohs)
coh_c = context.get('coh_c')
if coh_c is None:
coh_c = rng.choice(cohs)
return {
'durations': durations,
'time': time,
'epochs': epochs,
'context': context_,
'left_right_m': left_right_m,
'left_right_c': left_right_c,
'coh_m': coh_m,
'coh_c': coh_c
}
def get_condition(rng, dt, context={}):
#-------------------------------------------------------------------------------------
# Epochs
#-------------------------------------------------------------------------------------
stimulus = context.get('stimulus')
if stimulus is None:
stimulus = tasktools.truncated_exponential(rng,
dt,
stimulus_mean,
xmin=stimulus_min,
xmax=stimulus_max)
durations = {
'fixation': (0, fixation),
'stimulus': (fixation, fixation + stimulus),
'decision': (fixation + stimulus, fixation + stimulus + decision),
'tmax': tmax
}
time, epochs = tasktools.get_epochs_idx(dt, durations)
#-------------------------------------------------------------------------------------
# Trial
#-------------------------------------------------------------------------------------
left_right = context.get('left_right')
if left_right is None:
left_right = rng.choice(left_rights)
coh = context.get('coh')
if coh is None:
coh = rng.choice(cohs)
return {
'durations': durations,
'time': time,
'epochs': epochs,
'left_right': left_right,
'coh': coh
}
def get_condition(rng, dt, context={}):
#-------------------------------------------------------------------------------------
# Epochs
#-------------------------------------------------------------------------------------
stimulus = context.get('stimulus')
if stimulus is None:
stimulus = tasktools.truncated_exponential(rng, dt, stimulus_mean,
xmin=stimulus_min, xmax=stimulus_max)
durations = {
'fixation': (0, fixation),
'stimulus': (fixation, fixation + stimulus),
'decision': (fixation + stimulus, fixation + stimulus + decision),
'tmax': tmax
}
time, epochs = tasktools.get_epochs_idx(dt, durations)
#-------------------------------------------------------------------------------------
# Trial
#-------------------------------------------------------------------------------------
left_right = context.get('left_right')
if left_right is None:
left_right = rng.choice(left_rights)
coh = context.get('coh')
if coh is None:
coh = rng.choice(cohs)
return {
'durations': durations,
'time': time,
'epochs': epochs,
'left_right': left_right,
'coh': coh
}