def show_colorcircle(subject, contrast, depthBits, numStim):
if contrast is None:
contrast = 0.15
if depthBits is None:
depthBits = 10
if numStim is None:
numStim = 16
theta = np.linspace(0, 2 * np.pi, numStim, endpoint=False)
cp = ColorPicker(c=contrast,
sscale=2.6,
unit='rad',
depthBits=depthBits,
subject=None)
Msml = []
Mrgb = []
for t in theta:
sml, rgb = cp.newcolor(theta=t)
Msml.append(sml)
Mrgb.append(rgb)
sub_cp = ColorPicker(c=contrast,
sscale=2.6,
unit='rad',
depthBits=depthBits,
subject=subject)
sub_Msml = []
sub_Mrgb = []
for t in theta:
sml, rgb = sub_cp.newcolor(theta=t)
sub_Msml.append(sml)
sub_Mrgb.append(rgb)
winM = visual.Window(fullscr=True,
allowGUI=True,
bpc=(cp.depthBits, cp.depthBits, cp.depthBits),
depthBits=cp.depthBits,
colorSpace=cp.colorSpace,
color=cp.sml2rgb(cp.center()))
rectsize = 0.2 * winM.size[0] * 2 / numStim
radius = 0.1 * winM.size[0]
alphas = np.linspace(0, 360, numStim, endpoint=False)
rect = visual.Rect(win=winM,
units="pix",
width=int(rectsize),
height=int(rectsize))
winM.flip()
for t in range(50):
for wait_keys in event.waitKeys():
if wait_keys == 'left':
for i_rect in range(numStim):
rect.fillColorSpace = cp.colorSpace
rect.lineColorSpace = cp.colorSpace
rect.fillColor = Mrgb[i_rect]
rect.lineColor = Mrgb[i_rect]
rect.pos = misc.pol2cart(alphas[i_rect], radius)
rect.draw()
winM.flip()
elif wait_keys == 'right':
sub_rect = rect
for i_rect in range(numStim):
sub_rect.fillColorSpace = sub_cp.colorSpace
sub_rect.lineColorSpace = sub_cp.colorSpace
sub_rect.fillColor = sub_Mrgb[i_rect]
sub_rect.lineColor = sub_Mrgb[i_rect]
sub_rect.pos = misc.pol2cart(alphas[i_rect], radius)
sub_rect.draw()
text = visual.TextStim(winM,
text=subject,
pos=[0.3, -0.5],
height=0.05,
color='black')
text.draw()
winM.flip()
elif wait_keys == 'escape':
core.quit()
class Exp:
"""
Class for performing the experiment.
"""
def __init__(self, subject, par_file, cfg_file, res_dir, priors_file_path):
self.subject = subject
self.idx = time.strftime("%Y%m%dT%H%M",
time.localtime()) # add the current date
if not res_dir:
res_dir = 'data/'
self.res_dir = res_dir
self.priors_file_path = priors_file_path
self.cfg_file = cfg_file
self.cfg = config_tools.read_yml(cfg_file)
self.par_file = par_file
self.param = config_tools.read_yml(par_file)
self.patch_nmb = self.cfg['patch_nmb']
self.trial_nmb = self.cfg['trial_nmb']
self.trial_dur = self.cfg['trial_dur']
self.depthBits = self.cfg['depthBits']
self.ColorPicker = ColorPicker(c=self.param['c'],
sscale=self.param['sscale'],
unit='deg',
depthBits=self.depthBits,
subject=self.subject)
self.ColorSpace = self.ColorPicker.colorSpace
hue_list_path = 'config/colorlist/' + self.subject
if not os.path.exists(hue_list_path):
self.ColorPicker.gencolorlist(0.2)
self.hue_list = hue_list_path + '/hue-list-10bit-res0.2-sub-' + self.subject + '.npy'
self.Csml = self.ColorPicker.center()
self.Crgb = self.ColorPicker.sml2rgb(self.ColorPicker.center())
self.mon = monitors.Monitor(name=self.cfg['monitor']['name'],
width=self.cfg['monitor']['width'],
distance=self.cfg['monitor']['distance'])
self.mon.setSizePix((self.cfg['monitor']['size']))
self.win = visual.Window(monitor=self.mon,
unit='deg',
colorSpace=self.ColorSpace,
color=self.Crgb,
allowGUI=True,
fullscr=True,
bpc=(self.depthBits, self.depthBits,
self.depthBits),
depthBits=self.depthBits)
"""stimulus features"""
def patch_ref(self, theta, pos): # reference patches
ref = visual.Circle(win=self.win,
units='deg',
pos=pos,
radius=self.cfg['ref_size'],
fillColorSpace=self.ColorSpace,
lineColorSpace=self.ColorSpace)
ref.fillColor = self.ColorPicker.newcolor(theta=theta)[1]
ref.lineColor = ref.fillColor
return ref
def patch_stim(self, xlim, ylim): # standard and test stimuli
n = int(np.sqrt(self.patch_nmb))
pos = [[x, y] for x in np.linspace(xlim[0], xlim[1], n)
for y in np.linspace(ylim[0], ylim[1], n)]
patch = visual.ElementArrayStim(win=self.win,
units='deg',
fieldSize=self.cfg['field_size'],
xys=pos,
nElements=self.patch_nmb,
elementMask='circle',
elementTex=None,
sizes=self.cfg['patch_size'],
colorSpace=self.ColorSpace)
return patch
"""color noise & noise conditions"""
def rand_color(self, theta, std, npatch): # generate color noise
noise = np.random.normal(theta, std, npatch)
color = [self.ColorPicker.newcolor(theta=n) for n in noise]
sml, rgb = zip(*color)
return sml, rgb
def choose_con(self, standard, test, std): # choose noise condition
sColor = None
tColor = None
if self.param['noise_condition'] == 'L-L': # low - low noise
sColor = self.ColorPicker.newcolor(theta=standard)[1]
tColor = self.ColorPicker.newcolor(theta=test)[1]
elif self.param[
'noise_condition'] == 'L-H': # low - high noise: only test stimulus has high noise
sColor = self.ColorPicker.newcolor(theta=standard)[1]
tColor = self.rand_color(test, std, self.patch_nmb)[1]
elif self.param['noise_condition'] == 'H-H': # high - high noise
sColor = self.rand_color(standard, std, self.patch_nmb)[1]
tColor = self.rand_color(test, std, self.patch_nmb)[1]
else:
print("No noise condition corresponds to the input!")
return sColor, tColor
"""tool fucntion"""
def take_closest(self, arr, val):
"""
Assumes arr is sorted. Returns closest value to val (could be itself).
If two numbers are equally close, return the smallest number.
"""
pos = bisect_left(arr, val)
if pos == 0:
return arr[0]
if pos == len(arr):
return arr[-1]
before = arr[pos - 1]
after = arr[pos]
if after - val < val - before:
return after
else:
return before
"""main experiment"""
def run_trial(self, rot, cond, std, count):
# set two reference
leftRef = self.patch_ref(theta=cond['leftRef'],
pos=self.cfg['leftRef.pos'])
rightRef = self.patch_ref(theta=cond['rightRef'],
pos=self.cfg['rightRef.pos'])
# randomly assign patch positions: upper (+) or lower (-)
patchpos = [self.cfg['standard.ylim'], self.cfg['test.ylim']]
rndpos = patchpos.copy()
np.random.shuffle(rndpos)
sPatch = self.patch_stim(self.cfg['standard.xlim'], rndpos[0])
tPatch = self.patch_stim(self.cfg['test.xlim'], rndpos[1])
# set colors of two stimuli
standard = cond['standard'] # standard should be fixed
test = standard + rot
sPatch.colors, tPatch.colors = self.choose_con(standard, test, std)
# fixation cross
fix = visual.TextStim(self.win,
text="+",
units='deg',
pos=[0, 0],
height=0.5,
color='black',
colorSpace=self.ColorSpace)
# number of trial
num = visual.TextStim(self.win,
text="trial " + str(count),
units='deg',
pos=[12, -10],
height=0.4,
color='black',
colorSpace=self.ColorSpace)
trial_time_start = time.time()
# first present references
fix.draw()
num.draw()
leftRef.draw()
rightRef.draw()
self.win.flip()
core.wait(1.0)
# then present the standard and the test stimuli as well
fix.draw()
num.draw()
leftRef.draw()
rightRef.draw()
sPatch.draw()
tPatch.draw()
self.win.flip()
core.wait(self.trial_dur)
fix.draw()
self.win.flip()
core.wait(0.2) # 0.2 sec gray background
react_time_start = time.time()
# refresh the window and show a colored checkerboard
horiz_n = 30
vertic_n = 20
rect = visual.ElementArrayStim(self.win,
units='norm',
nElements=horiz_n * vertic_n,
elementMask=None,
elementTex=None,
sizes=(2 / horiz_n, 2 / vertic_n),
colorSpace=self.ColorSpace)
rect.xys = [
(x, y)
for x in np.linspace(-1, 1, horiz_n, endpoint=False) + 1 / horiz_n
for y in np.linspace(-1, 1, vertic_n, endpoint=False) +
1 / vertic_n
]
rect.colors = [
self.ColorPicker.newcolor(theta=x)[1]
for x in np.random.randint(0, high=360, size=horiz_n * vertic_n)
]
rect.draw()
self.win.flip()
core.wait(0.5) # 0.5 sec checkerboard
judge = None
react_time_stop = -1
kb = keyboard.Keyboard()
get_keys = kb.getKeys(['right', 'left', 'escape'
]) # if response during the checkerboard
if ('left' in get_keys
and rot * rndpos[0][0] > 0) or ('right' in get_keys
and rot * rndpos[0][0] < 0):
judge = 1 # correct
react_time_stop = time.time()
elif ('left' in get_keys
and rot * rndpos[0][0] < 0) or ('right' in get_keys
and rot * rndpos[0][0] > 0):
judge = 0 # incorrect
react_time_stop = time.time()
if 'escape' in get_keys:
config_tools.write_xrl(self.subject, break_info='userbreak')
core.quit()
self.win.flip()
fix.draw()
self.win.flip()
if judge is None: # if response after the checkerboard
for wait_keys in event.waitKeys():
if (wait_keys == 'left' and rot * rndpos[0][0] > 0) or (
wait_keys == 'right' and rot * rndpos[0][0] < 0):
judge = 1 # correct
react_time_stop = time.time()
elif (wait_keys == 'left' and rot * rndpos[0][0] < 0) or (
wait_keys == 'right' and rot * rndpos[0][0] > 0):
judge = 0 # incorrect
react_time_stop = time.time()
elif wait_keys == 'escape':
config_tools.write_xrl(self.subject,
break_info='userbreak')
core.quit()
react_time = react_time_stop - react_time_start
return judge, react_time, trial_time_start
def run_session(self):
path = os.path.join(self.res_dir, self.subject)
if not os.path.exists(path):
os.makedirs(path)
psydat_path = os.path.join(path, 'psydat')
if not os.path.exists(psydat_path):
os.makedirs(psydat_path)
# welcome
msg = visual.TextStim(self.win,
'Welcome!' + '\n' +
' Press any key to start this session :)',
color='black',
units='deg',
pos=(0, 0),
height=0.8)
msg.draw()
self.win.mouseVisible = False
self.win.flip()
event.waitKeys()
# read staircase parameters
conditions = [
dict({'stimulus': key}, **value)
for key, value in self.param.items() if key.startswith('stimulus')
]
if conditions[0]['stairType'] == 'simple':
stairs = data.MultiStairHandler(stairType='simple',
conditions=conditions,
nTrials=self.trial_nmb,
method='sequential')
elif conditions[0]['stairType'] == 'quest':
stairs = []
for cond in conditions:
if self.priors_file_path:
prior_file = self.priors_file_path + cond[
'label'] + '.psydat'
print(prior_file)
prior_handler = misc.fromFile(prior_file)
else:
prior_handler = None
cur_handler = data.QuestHandler(cond['startVal'],
cond['startValSd'],
pThreshold=cond['pThreshold'],
nTrials=self.trial_nmb,
minVal=cond['min_val'],
maxVal=cond['max_val'],
staircase=prior_handler,
extraInfo=cond,
grain=0.02)
stairs.append(cur_handler)
elif conditions[0]['stairType'] == 'psi':
stairs = []
for cond in conditions:
if self.priors_file_path:
prior_file = self.priors_file_path + cond['label'] + '.npy'
else:
prior_file = None
print(prior_file)
cur_handler = data.PsiHandler(nTrials=self.trial_nmb,
intensRange=[1, 10],
alphaRange=[1, 10],
betaRange=[0.01, 10],
intensPrecision=0.1,
alphaPrecision=0.1,
betaPrecision=0.01,
delta=0.01,
extraInfo=cond,
prior=prior_file,
fromFile=(prior_file
is not None))
stairs.append(cur_handler)
# write configuration files
xpp = config_tools.WriteXpp(self.subject, self.idx)
xpp_file = xpp.head(self.cfg_file, self.par_file)
config_tools.write_xrl(self.subject,
cfg_file=self.cfg_file,
par_file=self.par_file,
xpp_file=xpp_file)
xlsname = path + '/' + self.idx + self.param[
'noise_condition'] + '.xlsx'
""" running staircase """
if isinstance(stairs, data.MultiStairHandler):
# start running the staircase using the MultiStairHandler for the up-down method
count = 0
for rot, cond in stairs:
count += 1
direction = (-1)**(cond['label'].endswith('m')
) # direction as -1 if for minus stim
rot = rot * direction # rotation for this trial
judge, react_time, trial_time_start = self.run_trial(
rot, cond, cond['std'], count)
# check whether the theta is valid - if not, the rotation given by staircase should be corrected by
# realizable values
valid_theta = np.round(np.load(self.hue_list), decimals=1)
disp_standard = self.take_closest(
valid_theta, cond['standard']) # theta actually displayed
stair_test = cond[
'standard'] + stairs._nextIntensity * direction
if stair_test < 0:
stair_test += 360
disp_test = self.take_closest(valid_theta, stair_test)
disp_intensity = disp_test - disp_standard
if disp_intensity > 300:
disp_intensity = (disp_test + disp_standard) - 360
stairs.addResponse(judge, abs(disp_intensity))
xpp.task(count, cond, rot, float(disp_intensity), judge,
react_time, trial_time_start)
if 'escape' in event.waitKeys():
config_tools.write_xrl(self.subject,
break_info='userbreak')
core.quit()
config_tools.write_xrl(self.subject, xls_file=xlsname)
stairs.saveAsExcel(xlsname) # save results
misc.toFile(
os.path.join(
psydat_path,
self.idx + self.param['noise_condition'] + '.psydat'),
stairs)
elif isinstance(stairs, list):
# start running the staircase using custom interleaving stairs for the quest and psi methods
count = 0
rot_all = []
rot_all_disp = []
judge_all = []
estimates = {s.extraInfo['label']: [] for s in stairs}
for trial_n in range(self.trial_nmb):
for handler_idx, cur_handler in enumerate(stairs):
count += 1
direction = (-1)**(
cur_handler.extraInfo['label'].endswith('m')
) # direction as -1 if for minus stim
if cur_handler._nextIntensity >= 10.0:
sys.exit(
"Hue difference is out of range! Please enlarge the testing range or take more training!"
)
rot = cur_handler._nextIntensity * direction # rotation for this trial
if trial_n >= 5: # avoid repeating an intensity more than 3 times
last_rots = [
np.round(r, decimals=1) for r in [
rot_all_disp[handler_idx][trial_n - 1],
rot_all_disp[handler_idx][trial_n - 2],
rot_all_disp[handler_idx][trial_n - 3]
]
]
last_resp = [
judge_all[handler_idx][trial_n - 1],
judge_all[handler_idx][trial_n - 2],
judge_all[handler_idx][trial_n - 3]
]
if last_rots[0] == last_rots[1] == last_rots[2] \
and last_resp[0] == last_resp[1] == last_resp[2]:
if cur_handler._nextIntensity > 0.5:
rot = (cur_handler._nextIntensity -
0.5) * direction
print('Intensity decreases by 0.5!')
if cur_handler._nextIntensity <= 0.5:
rot = (cur_handler._nextIntensity +
0.5) * direction
print('Intensity increases by 0.5!')
cond = cur_handler.extraInfo
judge, react_time, trial_time_start = self.run_trial(
rot, cond, cond['std'], count)
if len(rot_all) <= handler_idx:
rot_all.append([])
rot_all[handler_idx].append(rot)
if len(judge_all) <= handler_idx:
judge_all.append([])
judge_all[handler_idx].append(judge)
valid_theta = np.round(np.load(self.hue_list), decimals=1)
disp_standard = self.take_closest(valid_theta,
cond['standard'])
stair_test = cond[
'standard'] + rot # calculated test hue for this trial
if stair_test < 0:
stair_test += 360
disp_test = self.take_closest(
valid_theta,
stair_test) # actual displayed test hue for this trial
disp_intensity = disp_test - disp_standard # actual displayed hue difference
if disp_intensity > 300:
disp_intensity = (disp_test + disp_standard) - 360
cur_handler.addResponse(
judge, abs(disp_intensity)
) # only positive number is accepted by addResponse
if len(rot_all_disp
) <= handler_idx: # add displayed intensities
rot_all_disp.append([])
rot_all_disp[handler_idx].append(disp_intensity)
if isinstance(cur_handler, data.PsiHandler):
estimates[cur_handler.extraInfo['label']].append([
cur_handler.estimateLambda()[0], # location
cur_handler.estimateLambda768()[1], # slope
cur_handler.estimateThreshold(0.75)
])
elif isinstance(cur_handler, data.QuestHandler):
estimates[cur_handler.extraInfo['label']].append([
cur_handler.mean(),
cur_handler.mode(),
cur_handler.quantile(0.5)
])
xpp.task(count, cond, rot, disp_intensity, judge,
react_time, trial_time_start)
if 'escape' in event.waitKeys():
config_tools.write_xrl(self.subject,
break_info='userbreak')
core.quit()
config_tools.write_xrl(self.subject, xls_file=xlsname)
# save results in xls-file
workbook = xlsxwriter.Workbook(xlsname)
for handler_idx, cur_handler in enumerate(stairs):
worksheet = workbook.add_worksheet(
cur_handler.extraInfo['label'])
worksheet.write('A1', 'Reversal Intensities')
worksheet.write('B1', 'Reversal Indices')
worksheet.write('C1', 'All Intensities')
worksheet.write('D1', 'All Responses')
for i in range(len(rot_all[handler_idx])):
# worksheet.write('C' + str(i + 2), rot_all[handler_idx][i])
worksheet.write('C' + str(i + 2),
rot_all_disp[handler_idx][i])
worksheet.write('D' + str(i + 2),
judge_all[handler_idx][i])
workbook.close()
# print resulting parameters and estimates for each step
res_file_path = os.path.join(path, self.idx + '_estimates.csv')
res_writer = csv.writer(open(res_file_path, 'w'))
for res_stim, res_vals in estimates.items():
for res_val_id, res_val in enumerate(res_vals):
res_writer.writerow([
res_stim, res_val_id, res_val[0], res_val[1],
res_val[2]
])
# save each handler into a psydat-file and save posterior into a numpy-file
for cur_handler in stairs:
file_name = os.path.join(
psydat_path, self.idx + self.param['noise_condition'] +
cur_handler.extraInfo['label'])
misc.toFile(file_name + '.psydat', cur_handler)
if isinstance(cur_handler, data.PsiHandler):
cur_handler.savePosterior(file_name + '.npy')
class Exp:
"""
Class for performing the experiment.
"""
def __init__(self, subject, par_file, cfg_file, res_dir, priors_file_path):
self.subject = subject
self.idx = time.strftime("%Y%m%dT%H%M",
time.localtime()) # add the current date
if not res_dir:
res_dir = 'data/'
self.res_dir = res_dir
self.priors_file_path = priors_file_path
self.cfg_file = cfg_file
self.cfg = config_tools.read_yml(cfg_file)
self.par_file = par_file
self.param = config_tools.read_yml(par_file)
self.patch_nmb = self.cfg['patch_nmb']
self.trial_nmb = self.cfg['trial_nmb']
self.trial_dur = self.cfg['trial_dur']
self.depthBits = self.cfg['depthBits']
self.ColorPicker = ColorPicker(c=self.param['c'],
sscale=self.param['sscale'],
unit='deg',
depthBits=self.depthBits,
subject=self.subject)
self.ColorSpace = self.ColorPicker.colorSpace
hue_list_path = 'config/colorlist/' + self.subject
if not os.path.exists(hue_list_path):
self.ColorPicker.gencolorlist(0.2)
self.hue_list = hue_list_path + '/hue-list-10bit-res0.2-sub-' + self.subject + '.npy'
self.Csml = self.ColorPicker.center()
self.Crgb = self.ColorPicker.sml2rgb(self.ColorPicker.center())
self.mon = monitors.Monitor(name=self.cfg['monitor']['name'],
width=self.cfg['monitor']['width'],
distance=self.cfg['monitor']['distance'])
self.mon.setSizePix((self.cfg['monitor']['size']))
self.win = visual.Window(monitor=self.mon,
unit='deg',
colorSpace=self.ColorSpace,
color=self.Crgb,
allowGUI=True,
fullscr=True,
bpc=(self.depthBits, self.depthBits,
self.depthBits),
depthBits=self.depthBits)
"""stimulus features"""
def patch_ref(self, theta, pos): # reference patches
ref = visual.Circle(win=self.win,
units='deg',
pos=pos,
radius=self.cfg['ref_size'],
fillColorSpace=self.ColorSpace,
lineColorSpace=self.ColorSpace)
ref.fillColor = self.ColorPicker.newcolor(theta=theta)[1]
ref.lineColor = ref.fillColor
return ref
def patch_stim(self, xlim, ylim): # standard and test stimuli
n = int(np.sqrt(self.patch_nmb))
pos = [[x, y] for x in np.linspace(xlim[0], xlim[1], n)
for y in np.linspace(ylim[0], ylim[1], n)]
patch = visual.ElementArrayStim(win=self.win,
units='deg',
fieldSize=self.cfg['field_size'],
xys=pos,
nElements=self.patch_nmb,
elementMask='circle',
elementTex=None,
sizes=self.cfg['patch_size'],
colorSpace=self.ColorSpace)
return patch
"""color noise & noise conditions"""
def rand_color(self, theta, std, npatch): # generate color noise
noise = np.random.normal(theta, std, npatch)
color = [self.ColorPicker.newcolor(theta=n) for n in noise]
sml, rgb = zip(*color)
return sml, rgb
def choose_con(self, standard, test, std): # choose noise condition
sColor = None
tColor = None
if self.param['noise_condition'] == 'L-L': # low - low noise
sColor = self.ColorPicker.newcolor(theta=standard)[1]
tColor = self.ColorPicker.newcolor(theta=test)[1]
elif self.param[
'noise_condition'] == 'L-H': # low - high noise: only test stimulus has high noise
sColor = self.ColorPicker.newcolor(theta=standard)[1]
tColor = self.rand_color(test, std, self.patch_nmb)[1]
elif self.param['noise_condition'] == 'H-H': # high - high noise
sColor = self.rand_color(standard, std, self.patch_nmb)[1]
tColor = self.rand_color(test, std, self.patch_nmb)[1]
else:
print("No noise condition corresponds to the input!")
return sColor, tColor
"""tool fucntion"""
def take_closest(self, arr, val):
"""
Assumes arr is sorted. Returns closest value to val (could be itself).
If two numbers are equally close, return the smallest number.
"""
pos = bisect_left(arr, val)
if pos == 0:
return arr[0]
if pos == len(arr):
return arr[-1]
before = arr[pos - 1]
after = arr[pos]
if after - val < val - before:
return after
else:
return before
"""main experiment"""
def run_trial(self, rot, cond, count):
ref = self.patch_ref(theta=cond['ref'], pos=self.cfg['ref.pos'])
# randomly assign patch positions: upper (+) or lower (-)
patchpos = [self.cfg['standard.ylim'], self.cfg['test.ylim']]
rndpos = patchpos.copy()
np.random.shuffle(rndpos)
sPatch = self.patch_stim(self.cfg['standard.xlim'], rndpos[0])
tPatch = self.patch_stim(self.cfg['test.xlim'], rndpos[1])
# set colors of two stimuli
standard = cond['standard'] # standard should be fixed
test = standard + rot
sPatch.colors, tPatch.colors = self.choose_con(standard, test,
cond['std'])
# fixation cross
fix = visual.TextStim(self.win,
text="+",
units='deg',
pos=[0, 0],
height=0.5,
color='black',
colorSpace=self.ColorSpace)
# number of trial
num = visual.TextStim(self.win,
text="trial " + str(count),
units='deg',
pos=[12, -10],
height=0.4,
color='black',
colorSpace=self.ColorSpace)
trial_time_start = time.time()
# present the standard and the test stimuli as well
fix.draw()
num.draw()
ref.draw()
sPatch.draw()
tPatch.draw()
self.win.flip()
core.wait(self.trial_dur)
fix.draw()
self.win.flip()
core.wait(0.2) # 0.2 sec gray background
react_time_start = time.time()
# refresh the window and show a colored checkerboard
horiz_n = 30
vertic_n = 20
rect = visual.ElementArrayStim(self.win,
units='norm',
nElements=horiz_n * vertic_n,
elementMask=None,
elementTex=None,
sizes=(2 / horiz_n, 2 / vertic_n),
colorSpace=self.ColorSpace)
rect.xys = [
(x, y)
for x in np.linspace(-1, 1, horiz_n, endpoint=False) + 1 / horiz_n
for y in np.linspace(-1, 1, vertic_n, endpoint=False) +
1 / vertic_n
]
rect.colors = [
self.ColorPicker.newcolor(theta=x)[1]
for x in np.random.randint(0, high=360, size=horiz_n * vertic_n)
]
rect.draw()
self.win.flip()
core.wait(0.5) # 0.5 sec checkerboard
judge = None
react_time_stop = -1
kb = keyboard.Keyboard()
get_keys = kb.getKeys(['up', 'down', 'escape'
]) # if response during the checkerboard
if ('up' in get_keys and rndpos[1][0] > 0) or ('down' in get_keys
and rndpos[1][0] < 0):
judge = 1 # correct
react_time_stop = time.time()
elif ('up' in get_keys and rndpos[1][0] < 0) or ('down' in get_keys
and rndpos[1][0] > 0):
judge = 0 # incorrect
react_time_stop = time.time()
if 'escape' in get_keys:
config_tools.write_xrl(self.subject, break_info='userbreak')
core.quit()
self.win.flip()
fix.draw()
self.win.flip()
if judge is None: # if response after the checkerboard
for wait_keys in event.waitKeys():
if (wait_keys == 'up'
and rndpos[1][0] > 0) or (wait_keys == 'down'
and rndpos[1][0] < 0):
judge = 1 # correct
react_time_stop = time.time()
elif (wait_keys == 'up'
and rndpos[1][0] < 0) or (wait_keys == 'down'
and rndpos[1][0] > 0):
judge = 0 # incorrect
react_time_stop = time.time()
elif wait_keys == 'escape':
config_tools.write_xrl(self.subject,
break_info='userbreak')
core.quit()
react_time = react_time_stop - react_time_start
return judge, react_time, trial_time_start
def run_session(self):
path = os.path.join(self.res_dir, self.subject)
if not os.path.exists(path):
os.makedirs(path)
psydat_path = os.path.join(path, 'psydat')
if not os.path.exists(psydat_path):
os.makedirs(psydat_path)
# welcome
msg = visual.TextStim(self.win,
'Welcome!' + '\n' +
' Press any key to start this session :)',
color='black',
units='deg',
pos=(0, 0),
height=0.8)
msg.draw()
self.win.mouseVisible = False
self.win.flip()
event.waitKeys()
# read staircase parameters
conditions = [
dict({'stimulus': key}, **value)
for key, value in self.param.items() if key.startswith('stimulus')
]
if conditions[0]['stairType'] == 'constant':
stimuli = []
rot_all_disp = []
judge_all = []
for cond in conditions:
for diff in np.linspace(cond['minVal'], 0, 3, endpoint=False):
stimuli.append({'cond': cond, 'diff': diff})
for diff in np.linspace(0, cond['maxVal'], 3, endpoint=False):
stimuli.append({'cond': cond, 'diff': diff})
stimuli.append({'cond': cond, 'diff': 0})
repeats_nmb = 20
stairs = data.TrialHandler(stimuli, repeats_nmb, method='random')
else:
sys.exit("The stimuli are not constant!")
# write configuration files
xpp = config_tools.WriteXpp(self.subject, self.idx)
xpp_file = xpp.head(self.cfg_file, self.par_file)
config_tools.write_xrl(self.subject,
cfg_file=self.cfg_file,
par_file=self.par_file,
xpp_file=xpp_file)
xlsname = path + '/' + self.idx + self.param[
'noise_condition'] + '.xlsx'
""" running staircase """
if isinstance(stairs, data.TrialHandler):
count = 0
results = {cond['label']: [] for cond in conditions}
for trial in stairs:
count += 1
judge, react_time, trial_time_start = self.run_trial(
trial['diff'], trial['cond'], count)
valid_theta = np.round(np.load(self.hue_list), decimals=1)
disp_standard = self.take_closest(valid_theta,
cond['standard'])
stair_test = cond['standard'] + trial['diff']
if stair_test < 0:
stair_test += 360
disp_test = self.take_closest(valid_theta, stair_test)
disp_intensity = disp_test - disp_standard
if disp_intensity > 300:
disp_intensity = (disp_test + disp_standard) - 360
xpp.task(count, cond, cond['diff'], float(disp_intensity),
judge, react_time, trial_time_start)
results[trial['label']].append((trial['diff'], judge))
if 'escape' in event.waitKeys():
config_tools.write_xrl(self.subject,
break_info='userbreak')
core.quit()
config_tools.write_xrl(self.subject, xls_file=xlsname)
# save results in xls-file
workbook = xlsxwriter.Workbook(xlsname)
for res_label, res_data in results.items():
worksheet = workbook.add_worksheet(res_label)
worksheet.write('A1', 'Reversal Intensities')
worksheet.write('B1', 'Reversal Indices')
worksheet.write('C1', 'All Intensities')
worksheet.write('D1', 'All Responses')
for i, (res_diff, res_resp) in enumerate(res_data):
worksheet.write('C' + str(i + 2), res_diff)
worksheet.write('D' + str(i + 2), res_resp)
workbook.close()
else:
sys.exit("The stimuli are not constant!")