def test_psydat_filename_collision_overwriting2(self):
for count in [1, 10, 20]:
trials = data.TrialHandler2([], 1, autoLog=False)
for trial in trials: #need to run trials or file won't be saved
trials.addData('trialType', 0)
base_data_filename = pjoin(self.temp_dir,
self.rootName + 'overwrite')
trials.saveAsPickle(base_data_filename,
fileCollisionMethod='overwrite')
# Make sure the file just saved is there
data_filename = base_data_filename + '.psydat'
assert os.path.exists(
data_filename
), "File not found: %s" % os.path.abspath(data_filename)
# Make sure the correct number of files for the loop are there. (No overwriting by default).
matches = len(
glob.glob(
os.path.join(self.temp_dir,
self.rootName + "*overwrite.psydat")))
assert matches == 1, "Found %d matching files, should be %d" % (
matches, count)
from random import random
from psychopy import data
# create your list of stimuli
# NB as of version 1.62 you could simply import an excel spreadsheet with this
# using data.importConditions('someFile.xlsx')
stimList = []
for ori in range(90, 180, 30):
for sf in [0.5, 1.0, 2.0]:
# append a python 'dictionary' to the list
stimList.append({'sf': sf, 'ori': ori})
# organize them with the trial handler
trials = data.TrialHandler2(stimList,
10,
extraInfo={
'participant': "Nobody",
'session': 1
})
# run the experiment
nDone = 0
for thisTrial in trials: # handler can act like a for loop
# simulate some data
thisReactionTime = random() + float(thisTrial['sf']) / 2.0
thisChoice = round(random())
trials.addData('RT', thisReactionTime) # add the data to our set
trials.addData('choice', thisChoice)
nDone += 1 # just for a quick reference
msg = 'trial %i had position %s in the list (sf=%.1f)'
print(msg % (nDone, trials.thisIndex, thisTrial['sf']))
def test_json_dump_to_file(self):
t = data.TrialHandler2(self.conditions, nReps=5)
t.saveAsJson(fileName=self.temp_dir, fileCollisionMethod='overwrite')
def test_comparison_not_equal_after_iteration(self):
t1 = data.TrialHandler2([dict(foo=1)], 2, seed=1)
t2 = data.TrialHandler2([dict(foo=1)], 3, seed=1)
t1.__next__()
t2.__next__()
assert t1 != t2
def test_comparison_not_equal(self):
t1 = data.TrialHandler2([dict(foo=1)], 2, seed=1)
t2 = data.TrialHandler2([dict(foo=1)], 3, seed=1)
assert t1 != t2
seconds = datetime.datetime.strftime(datetime.datetime.now(), "%H%M%S")
# # logging
logfilename = "info_%s_%d_%s.log" % (subjid, run, seconds)
logfile = os.path.join(logdir, logfilename)
lastLog = logging.LogFile(logfile, level=logging.INFO, filemode='w')
logging.log(level=logging.INFO,
msg='run %s, loading at epoch %s' % (run, seconds))
logging.flush() # when its okay to write
# trial settings and timing
sacc_trials = data.TrialHandler2(trialdf.T.to_dict().values(),
1,
method='sequential',
extraInfo={
'subjid': subjid,
'epoch': seconds,
})
# ## Run calibration if we need it
if calEyeScreen:
c = showCal(task.win)
c.calibrate()
# # run saccade trials
# blockstarttime=core.getTime()
eyetrackingfile = '%s_run%d_%s.txt' % (subjid, run, seconds)
task.eyetracking_newfile('%s' % eyetrackingfile)
blockstarttime = task.wait_for_scanner(scannerTriggerKeys, run_getReadyMsg)
logging.log(level=logging.INFO,
msg='scanner trigger recieved at %d' % blockstarttime)
def test_json_dump_to_file(self):
_, path = mkstemp(dir=self.temp_dir, suffix='.json')
t = data.TrialHandler2(self.conditions, nReps=5)
t.saveAsJson(fileName=path, fileCollisionMethod='overwrite')
def test_comparison_equals_after_iteration(self):
t1 = data.TrialHandler2([dict(foo=1)], 2, seed=self.random_seed)
t2 = data.TrialHandler2([dict(foo=1)], 2, seed=self.random_seed)
t1.__next__()
t2.__next__()
assert t1 == t2
def test_comparison_equals(self):
t1 = data.TrialHandler2([dict(foo=1)], 2, seed=self.random_seed)
t2 = data.TrialHandler2([dict(foo=1)], 2, seed=self.random_seed)
assert t1 == t2
(subjid, tasktype, imgset, timepoint) = getInfoFromDataPath(datadir)
trialdf = recallFromPickle(pckl, settings['lastrun'], settings['firstrun'] - 1)
# set correct keys and format for trialhandler
trialdict = trialdf.reset_index().T.to_dict().values()
trialdict = [
dict(x.items() +
{'corkeys': response_should_be(x['pos'], accept_keys)}.items())
for x in trialdict
]
seconds = datetime.datetime.strftime(datetime.datetime.now(), "%Y%m%d%H%M%S")
extraInfo = {'subjid': subjid, 'epoch': seconds}
recall_trials = data.TrialHandler2(trialdict, 1, extraInfo=extraInfo)
# # screen setup
win = create_window(settings['fullscreen'])
# win settings
win.winHandle.activate() # make sure the display window has focus
win.mouseVisible = False # and that we dont see the mouse
# task class
task = mgsTask(win, accept_keys)
task.init_recall_side()
if settings['instructions']:
task.recall_instructions()
# Press 'space' to and the run (will move on to the next run if there is one)
event.waitKeys(keyList=('space'))
# =====================
# MAIN
#
# - set up stimuli and runs
#sys.exit()
#################### MAIN ####################
for idx, this_run in enumerate(runs): # 2 runs in total
#print(run)
#note the the input 'run' has already been raddomized, so it is okay to use 'sequential' here
trials = data.TrialHandler2(this_run, 1, extraInfo=run_data)
#dataTypes=['stim_onset', 'resp_onset', 'rt', 'resp'],
#method='sequential')
#pdb.set_trace()
nextrun = idx + 1
#print(trials)
do_run(nextrun, trials)
#print("stopping program here at: " + str(random.randint(0,100)))
#sys.exit()
win.close()
core.quit()
#sys.exit()