def do(action, args, config):
"""
Manage tasks.
"""
print("ACTION*: " + str(action))
print("ARGS*: " + str(args))
#=====================================================================================
if 'trials' in action:
try:
trials_per_condition = int(args[0])
except:
trials_per_condition = 500
model = config['model']
pg = model.get_pg(config['savefile'], config['seed'], config['dt'])
# Conditions
spec = model.spec
mods = spec.mods
freqs = spec.freqs
n_conditions = spec.n_conditions
n_trials = n_conditions * trials_per_condition
print("{} trials".format(n_trials))
task = model.Task()
trials = []
for n in xrange(n_trials):
k = tasktools.unravel_index(n, (len(mods), len(freqs)))
context = {'mod': mods[k.pop(0)], 'freq': freqs[k.pop(0)]}
trials.append(task.get_condition(pg.rng, pg.dt, context))
runtools.run(action, trials, pg, config['trialspath'])
#=====================================================================================
elif action == 'psychometric':
trialsfile = runtools.behaviorfile(config['trialspath'])
fig = Figure()
plot = fig.add()
psychometric(trialsfile, plot)
plot.vline(config['model'].spec.boundary)
fig.save(path=config['figspath'], name='psychometric')
fig.close()
#=====================================================================================
elif action == 'sort':
if 'value' in args:
network = 'v'
else:
network = 'p'
trialsfile = runtools.activityfile(config['trialspath'])
sort(trialsfile, (config['figspath'], 'sorted'), network=network)
def do(action, args, config):
print("ACTION*: " + str(action))
print("ARGS*: " + str(args))
#=====================================================================================
if 'trials' in action:
try:
trials_per_condition = int(args[0])
except:
trials_per_condition = 100
model = config['model']
pg = model.get_pg(config['savefile'], config['seed'], config['dt'])
spec = model.spec
wagers = spec.wagers
left_rights = spec.left_rights
cohs = spec.cohs
n_conditions = spec.n_conditions
n_trials = trials_per_condition * n_conditions
print("{} trials".format(n_trials))
task = model.Task()
trials = []
for n in xrange(n_trials):
k = tasktools.unravel_index(n, (len(wagers), len(left_rights), len(cohs)))
context = {
'wager': wagers[k.pop(0)],
'left_right': left_rights[k.pop(0)],
'coh': cohs[k.pop(0)]
}
trials.append(task.get_condition(pg.rng, pg.dt, context))
runtools.run(action, trials, pg, config['trialspath'])
#=====================================================================================
elif action == 'sure_stimulus_duration':
trialsfile = runtools.behaviorfile(config['trialspath'])
fig = Figure()
plot = fig.add()
sure_stimulus_duration(trialsfile, plot)
plot.xlabel('Stimulus duration (ms)')
plot.ylabel('Probability sure target')
fig.save(path=config['figspath'], name=action)
#=====================================================================================
elif action == 'correct_stimulus_duration':
trialsfile = runtools.behaviorfile(config['trialspath'])
fig = Figure()
plot = fig.add()
correct_stimulus_duration(trialsfile, plot)
plot.xlabel('Stimulus duration (ms)')
plot.ylabel('Probability correct')
fig.save(path=config['figspath'], name=action)
#=====================================================================================
elif action == 'value_stimulus_duration':
trialsfile = runtools.activityfile(config['trialspath'])
fig = Figure()
plot = fig.add()
value_stimulus_duration(trialsfile, plot)
plot.xlabel('Stimulus duration (ms)')
plot.ylabel('Expected reward')
fig.save(path=config['figspath'], name=action)
#=====================================================================================
elif action == 'sort':
if 'value' in args:
network = 'v'
else:
network = 'p'
trialsfile = runtools.activityfile(config['trialspath'])
sort(trialsfile, os.path.join(config['figspath'], 'sorted'), network=network)
def do(action, args, config):
print("ACTION*: " + str(action))
print("ARGS*: " + str(args))
#=====================================================================================
if 'trials' in action:
try:
trials_per_condition = int(args[0])
except:
trials_per_condition = 100
model = config['model']
pg = model.get_pg(config['savefile'], config['seed'], config['dt'])
spec = model.spec
wagers = spec.wagers
left_rights = spec.left_rights
cohs = spec.cohs
n_conditions = spec.n_conditions
n_trials = trials_per_condition * n_conditions
print("{} trials".format(n_trials))
task = model.Task()
trials = []
for n in xrange(n_trials):
k = tasktools.unravel_index(n, (len(wagers), len(left_rights), len(cohs)))
context = {
'wager': wagers[k.pop(0)],
'left_right': left_rights[k.pop(0)],
'coh': cohs[k.pop(0)]
}
trials.append(task.get_condition(pg.rng, pg.dt, context))
runtools.run(action, trials, pg, config['trialspath'])
#=====================================================================================
elif action == 'sure_stimulus_duration':
trialsfile = runtools.behaviorfile(config['trialspath'])
fig = Figure()
plot = fig.add()
sure_stimulus_duration(trialsfile, plot)
plot.xlabel('Stimulus duration (ms)')
plot.ylabel('Probability sure target')
fig.save(path=config['figspath'], name=action)
#=====================================================================================
elif action == 'correct_stimulus_duration':
trialsfile = runtools.behaviorfile(config['trialspath'])
fig = Figure()
plot = fig.add()
correct_stimulus_duration(trialsfile, plot)
plot.xlabel('Stimulus duration (ms)')
plot.ylabel('Probability correct')
fig.save(path=config['figspath'], name=action)
#=====================================================================================
elif action == 'value_stimulus_duration':
trialsfile = runtools.activityfile(config['trialspath'])
fig = Figure()
plot = fig.add()
value_stimulus_duration(trialsfile, plot)
plot.xlabel('Stimulus duration (ms)')
plot.ylabel('Expected reward')
fig.save(path=config['figspath'], name=action)
#=====================================================================================
elif action == 'sort':
if 'value' in args:
network = 'v'
else:
network = 'p'
trialsfile = runtools.activityfile(config['trialspath'])
sort(trialsfile, os.path.join(config['figspath'], 'sorted'), network=network)
def do(action, args, config):
"""
Manage tasks.
"""
print("ACTION*: " + str(action))
print("ARGS*: " + str(args))
if 'trials' in action:
try:
trials_per_condition = int(args[0])
except:
trials_per_condition = 100
model = config['model']
pg = model.get_pg(config['savefile'], config['seed'], config['dt'])
spec = model.spec
gt_lts = spec.gt_lts
fpairs = spec.fpairs
n_conditions = spec.n_conditions
n_trials = trials_per_condition * n_conditions
print("{} trials".format(n_trials))
task = model.Task()
trials = []
for n in xrange(n_trials):
k = tasktools.unravel_index(n, (len(gt_lts), len(fpairs)))
context = {
'delay': 3000,
'gt_lt': gt_lts[k.pop(0)],
'fpair': fpairs[k.pop(0)]
}
trials.append(task.get_condition(pg.rng, pg.dt, context))
runtools.run(action, trials, pg, config['trialspath'])
#=====================================================================================
elif action == 'performance':
trialsfile = runtools.behaviorfile(config['trialspath'])
fig = Figure()
plot = fig.add()
performance(trialsfile, plot)
plot.xlabel('$f_1$ (Hz)')
plot.ylabel('$f_2$ (Hz)')
fig.save(os.path.join(config['figspath'], action))
#=====================================================================================
elif action == 'sort':
if 'value' in args:
network = 'v'
else:
network = 'p'
trialsfile = runtools.activityfile(config['trialspath'])
sort(trialsfile, (config['figspath'], 'sorted'), network=network)
def do(action, args, config):
"""
Manage tasks.
"""
print("ACTION*: " + str(action))
print("ARGS*: " + str(args))
#=====================================================================================
if action == 'plot_trial':
try:
trials_per_condition = int(args[0])
except:
trials_per_condition = 1000
model = config['model']
pg = model.get_pg(config['savefile'], config['seed'], config['dt'])
spec = model.spec
juices = spec.juices
offers = spec.offers
n_conditions = spec.n_conditions
n_trials = trials_per_condition * n_conditions
print("{} trials".format(n_trials))
task = model.Task()
fig = Figure(axislabelsize=10, ticklabelsize=9)
plot = fig.add()
plot_trial()
performance(config['savefile'], plot)
fig.save(path=config['figspath'], name='performance')
fig.close()
#=====================================================================================
elif 'trials' in action:
try:
trials_per_condition = int(args[0])
except IndexError:
trials_per_condition = 100
model = config['model']
pg = model.get_pg(config['savefile'], config['seed'], config['dt'])
spec = model.spec
juices = spec.juices
offers = spec.offers
n_conditions = spec.n_conditions
n_trials = trials_per_condition * n_conditions
print("{} trials".format(n_trials))
task = model.Task()
trials = []
for n in xrange(n_trials):
k = tasktools.unravel_index(n, (len(juices), len(offers)))
context = {'juice': juices[k.pop(0)], 'offer': offers[k.pop(0)]}
trials.append(task.get_condition(pg.rng, pg.dt, context))
runtools.run(action, trials, pg, config['trialspath'])
#=====================================================================================
elif action == 'choice_pattern':
trialsfile = runtools.behaviorfile(config['trialspath'])
# print trialsfile
# fig = Figure()
# plot = fig.add()
savefile = config['figspath']
spec = config['model'].spec
#print spec.offers
choice_pattern(trialsfile, spec.offers, savefile, action)
#plot.xlabel('Offer (\#B : \#A)')
#plot.ylabel('Percent choice B')
#plot.text_upper_left('1A = {}B'.format(spec.A_to_B), fontsize=10)
#=====================================================================================
elif action == 'sort':
if 'value' in args:
network = 'v'
else:
network = 'p'
trialsfile = runtools.activityfile(config['trialspath'])
sort(trialsfile, (config['figspath'], 'sorted'), network=network)
#=====================================================================================
elif action == 'statespace':
trialsfile = runtools.activityfile(config['trialspath'])
statespace(trialsfile, (config['figspath'], 'statespace'))
def do(action, args, config):
"""
Manage tasks.
"""
print("ACTION*: " + str(action))
print("ARGS*: " + str(args))
#=====================================================================================
if 'trials' in action:
try:
trials_per_condition = int(args[0])
except IndexError:
trials_per_condition = 100
model = config['model']
pg = model.get_pg(config['savefile'], config['seed'], config['dt'])
spec = model.spec
juices = spec.juices
offers = spec.offers
n_conditions = spec.n_conditions
n_trials = trials_per_condition * n_conditions
print("{} trials".format(n_trials))
task = model.Task()
trials = []
for n in xrange(n_trials):
k = tasktools.unravel_index(n, (len(juices), len(offers)))
context = {'juice': juices[k.pop(0)], 'offer': offers[k.pop(0)]}
trials.append(task.get_condition(pg.rng, pg.dt, context))
runtools.run(action, trials, pg, config['trialspath'])
#=====================================================================================
elif action == 'choice_pattern':
trialsfile = runtools.behaviorfile(config['trialspath'])
fig = Figure()
plot = fig.add()
spec = config['model'].spec
choice_pattern(trialsfile, spec.offers, plot)
plot.xlabel('Offer (\#B : \#A)')
plot.ylabel('Percent choice B')
plot.text_upper_left('1A = {}B'.format(spec.A_to_B), fontsize=10)
fig.save(path=config['figspath'], name=action)
fig.close()
elif action == 'indifference_point':
trialsfile = runtools.behaviorfile(config['trialspath'])
fig = Figure()
plot = fig.add()
spec = config['model'].spec
indifference_point(trialsfile, spec.offers, plot)
plot.xlabel('$(n_B - n_A)/(n_B + n_A)$')
plot.ylabel('Percent choice B')
#plot.text_upper_left('1A = {}B'.format(spec.A_to_B), fontsize=10)
fig.save(path=config['figspath'], name=action)
fig.close()
#=====================================================================================
elif action == 'sort_epoch':
behaviorfile = runtools.behaviorfile(config['trialspath'])
activityfile = runtools.activityfile(config['trialspath'])
epoch = args[0]
if 'value' in args:
network = 'v'
else:
network = 'p'
separate_by_choice = ('separate-by-choice' in args)
sort_epoch(behaviorfile,
activityfile,
epoch,
config['model'].spec.offers,
os.path.join(config['figspath'], 'sorted'),
network=network,
separate_by_choice=separate_by_choice)
def do(action, args, config):
"""
Manage tasks.
"""
print("ACTION*: " + str(action))
print("ARGS*: " + str(args))
#=====================================================================================
if 'trials' in action:
try:
trials_per_condition = int(args[0])
except IndexError:
trials_per_condition = 100
model = config['model']
pg = model.get_pg(config['savefile'], config['seed'], config['dt'])
spec = model.spec
juices = spec.juices
offers = spec.offers
n_conditions = spec.n_conditions
n_trials = trials_per_condition * n_conditions
print("{} trials".format(n_trials))
task = model.Task()
trials = []
for n in xrange(n_trials):
k = tasktools.unravel_index(n, (len(juices), len(offers)))
context = {
'juice': juices[k.pop(0)],
'offer': offers[k.pop(0)]
}
trials.append(task.get_condition(pg.rng, pg.dt, context))
runtools.run(action, trials, pg, config['trialspath'])
#=====================================================================================
elif action == 'choice_pattern':
trialsfile = runtools.behaviorfile(config['trialspath'])
fig = Figure()
plot = fig.add()
spec = config['model'].spec
choice_pattern(trialsfile, spec.offers, plot)
plot.xlabel('Offer (\#B : \#A)')
plot.ylabel('Percent choice B')
plot.text_upper_left('1A = {}B'.format(spec.A_to_B), fontsize=10)
fig.save(path=config['figspath'], name=action)
fig.close()
elif action == 'indifference_point':
trialsfile = runtools.behaviorfile(config['trialspath'])
fig = Figure()
plot = fig.add()
spec = config['model'].spec
indifference_point(trialsfile, spec.offers, plot)
plot.xlabel('$(n_B - n_A)/(n_B + n_A)$')
plot.ylabel('Percent choice B')
#plot.text_upper_left('1A = {}B'.format(spec.A_to_B), fontsize=10)
fig.save(path=config['figspath'], name=action)
fig.close()
#=====================================================================================
elif action == 'sort_epoch':
behaviorfile = runtools.behaviorfile(config['trialspath'])
activityfile = runtools.activityfile(config['trialspath'])
epoch = args[0]
if 'value' in args:
network = 'v'
else:
network = 'p'
separate_by_choice = ('separate-by-choice' in args)
sort_epoch(behaviorfile, activityfile, epoch, config['model'].spec.offers,
os.path.join(config['figspath'], 'sorted'),
network=network, separate_by_choice=separate_by_choice)
