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face_morphed_congruency.py
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# -*- coding: utf-8 -*-
"""
Created on Fri Nov 27 13:04:04 2020
@author: user
"""
#===============
# Import modules
#===============
import os
import numpy as np
import numpy.matlib as npm # for file/folder operations
import numpy.random as rnd # for random number generators
import operator
from psychopy import visual, event, core, gui, data, monitors
from numpy import asarray
from PIL import Image, ImageEnhance
#===========================ssss===================
# Settings that we might want to tweak later on
#==============================================
datapath = 'data' # directory to save data in
pracpath = 'pracims'
instpath= 'InstScr'
exppath= 'expims' # directory where images can be found
scramblepath = 'scrambles'
pracscramblepath = 'pracscrambles'
TextVSize = 1
brightness=.5
brightdiv=1/brightness
explength = 768
explength2= explength
praclength = 96
tottri= praclength/2
tilt = [0,1]
imside=[0,1]
mencxts1 = ['123','125','145','24','2','49','146','7']
mencxts2 = ['44','17','52','160','46','151','147','25']
meneyes=['100_125','38_9','148_66','76_2','93_8','87_146','25_7','147_55']
womcxts1 = ['139','135','192','129','41','20','13','128']
womcxts2 = ['103','197','111','131','65','208','96','225']
womeyes = ['197_135','103_192','216_220','37_94','208_20','65_13','225_128','96_30']
praccxt1= ['223','209','78','203','224','226']
praccxt2= ['21','154','214','37','31','106']
praceyes=['154_209','21_78','37_203','214_224','106_226','31_163']
pracmorphs=['10','18','24','32','38','50','62','68','77','82','90']
morphs=['10','18','24','32','38','50','62','68','77','82','90']
# 0% dissimilarity pairs:
# 24% dissimilarity pairs: 38-62
# 36% dissimilarity pairs: 32-68
# 53% dissimilarity pairs: 24-77
# 80% dissimilarity pairs: 10-90
praclist=[]
imlistwom = []
imlistmen = [] # image names without the suffixes
asfx = '.png' # suffix for the image
timelimit = 3 # image freezing time in seconds
IBW=3 #the wait between the blocks
#IBW=0.1
ISI = [.7, .8, .9, 1, 1.1, 1.2]
#ISI=[.01, .02]
FixT = 500
IntT = 500
TargetT = 500
MaskT = 200
#========================================
# Store info about the experiment session
#========================================
# Get subject name, gender, age, handedness through a dialog box
exp_name = 'Discriminability and Congruency'
exp_info = {
'participant': '',
'gender': ('male', 'female'),
'age':'',
'screenwidth(cm)': '59',
'screenresolutionhori(pixels)': '1920',
'screenresolutionvert(pixels)': '1080',
'refreshrate(hz)': '60'
}
dlg = gui.DlgFromDict(dictionary=exp_info, title=exp_name)
# If 'Cancel' is pressed, quit
if dlg.OK == False:
core.quit()
# Get date and time
exp_info['date'] = data.getDateStr()
exp_info['exp_name'] = exp_name
# Create a unique filename for the experiment data
if not os.path.isdir(datapath):
os.makedirs(datapath)
data_fname = exp_info['participant'] + '_' + exp_info['date']
data_fname = os.path.join(datapath, data_fname)
#========================
# Prepare condition lists
#========================
#Check if all images exist
for cxt1, cxt2, eyes in zip(mencxts1, mencxts2,meneyes):
for morph in morphs:
if (not os.path.exists(os.path.join(exppath, cxt1+'-'+eyes+'-'+morph+asfx)) or
not os.path.exists(os.path.join(exppath, cxt2+'-'+eyes+'-'+morph+asfx))):
raise Exception('Image files not found in image folder: ' + str(cxt1+'-'+eyes+'-'+morph+asfx) + ' or ' + str(cxt2+'-'+eyes+'-'+morph+asfx))
if not os.path.exists(os.path.join(exppath, eyes+'-'+morph+asfx)):
raise Exception('Image files not found in image folder: ' + str(eyes+'-'+morph+asfx))
for cxt1, cxt2, eyes in zip(womcxts1, womcxts2,womeyes):
for morph in morphs:
if (not os.path.exists(os.path.join(exppath, cxt1+'-'+eyes+'-'+morph+asfx)) or
not os.path.exists(os.path.join(exppath, cxt2+'-'+eyes+'-'+morph+asfx))):
raise Exception('Image files not found in image folder: ' + str(cxt1+'-'+eyes+'-'+morph+asfx) + ' or ' + str(cxt2+'-'+eyes+'-'+morph+asfx))
if not os.path.exists(os.path.join(exppath, eyes+'-'+morph+asfx)):
raise Exception('Image files not found in image folder: ' + str(eyes+'-'+morph+asfx))
#
for cxt1, cxt2, eyes in zip(praccxt1,praccxt2,praceyes):
for morph in pracmorphs:
if (not os.path.exists(os.path.join(pracpath, cxt1+'-'+eyes+'-'+morph+asfx)) or
not os.path.exists(os.path.join(pracpath, cxt2+'-'+eyes+'-'+morph+asfx)) or
not os.path.exists(os.path.join(pracpath, eyes+'-'+morph+asfx))):
raise Exception('Image file not found in image folder:' + str(cxt1+'-'+eyes+'-'+morph+asfx))
#
# Randomize the image order
rnd.shuffle(imlistmen)
mon = monitors.Monitor('Dell')
mon.setDistance(57)
mon.setWidth(float(exp_info['screenwidth(cm)']))
horipix = exp_info['screenresolutionhori(pixels)']
vertpix = exp_info['screenresolutionvert(pixels)']
framerate = exp_info['refreshrate(hz)']
scrsize = (float(horipix),float(vertpix))
framelength = 1000/(float(framerate))
FixFrame = int(FixT/framelength)
IntFrame = int(IntT/framelength)
ImFrame = int(TargetT/framelength)
MaskFrame = int(MaskT/framelength)
mon.setSizePix(scrsize)
# Open a window
win = visual.Window(monitor = mon,
size = scrsize,
color=(-(1-brightness),-(1-brightness),-(1-brightness)),
units='deg',
fullscr=True)
win.mouseVisible=False
#frameRate = win.getActualFrameRate()
#print('framerate is', frameRate)
bitmapinst = visual.ImageStim(win,interpolate=True,units='norm', size=[1.5,1.5])
# Define trial start text
empty_scr = visual.TextStim(win,
text="Por.",
color='black', height=20)
# Define bitmap stimulus (contents can still change)
#they are 8.38 vertically, but actually when you calculate depending
# on head size vertically, the faces subtend a visual angle of 7 degrees.
#image size is different than average head size.
bitmap1 = visual.ImageStim(win, size=[7.05,8.38], interpolate=True)
bitmap2 = visual.ImageStim(win, size=[7.05,8.38], interpolate=True)
bitmap3 = visual.ImageStim(win, size=[7.05,8.38])
bitmap4 = visual.ImageStim(win, size=[7.05,8.38])
bitmap5 = visual.ImageStim(win, size=[7.05,8.38])
bitmap6 = visual.ImageStim(win, size=[7.05,8.38])
bitmap7 = visual.ImageStim(win, size=[7.05,8.38])
bitmap8 = visual.ImageStim(win, size=[7.05,8.38])
bitmap9 = visual.ImageStim(win, size=[7.05,8.38])
bitmap10 = visual.ImageStim(win, size=[7.05,8.38])
bitmap11 = visual.ImageStim(win, size=[7.05,8.38])
bitmap12 = visual.ImageStim(win, size=[7.05,8.38])
bitmap13 = visual.ImageStim(win, size=[7.05,8.38])
bitmap14 = visual.ImageStim(win, size=[7.05,8.38])
bitmap15 = visual.ImageStim(win, size=[7.05,8.38])
bitmap16 = visual.ImageStim(win, size=[7.05,8.38])
maskmap = visual.ImageStim(win, size=[7.05,8.38], interpolate=True)
#==========================
# Define the trial sequence
#==========================
# Define a list of trials with their properties:
# - Which image (without the suffix)
# - Which orientation
stim_order = []
morph1=npm.repmat((38, 32, 24, 10),1,int(len(praceyes)))
morph2=npm.repmat([62, 68, 77, 90],1,int(len(praceyes)))
morph31=npm.repmat([10, 24, 32, 38],1,int(len(praceyes)/2))
morph32=npm.repmat([62, 68, 77, 90],1,int(len(praceyes)/2))
morph3=np.append(morph31,morph32)
morph41=npm.repmat([62, 68, 77, 90],1,int(len(praceyes)/2))
morph42=npm.repmat([10, 24, 32, 38],1,int(len(praceyes)/2))
morph4=np.append(morph41,morph42)
morph51=npm.repmat([10, 32, 62, 77],1,int(len(praceyes)/2))
morph52=npm.repmat([24, 38, 68, 90],1,int(len(praceyes)/2))
morph5=np.append(morph51,morph52)
i=0
pracdiffdiff = []
pracdiffsame=[]
pracsamediff=[]
pracsamesame=[]
pracisodiff=[]
pracisosame=[]
ori= [0,180]
for cxt1, cxt2, eyes in zip(praccxt1, praccxt2, praceyes):
for itr in np.arange(4):
pracdiffdiff.append({'cxt1': cxt1, 'cxt2': cxt2, 'eyes': eyes, 'cond': 'DD', 'im1': str(cxt1+'-'+eyes+'-'+str(morph1[0][i])+asfx), 'im2': str(cxt2+'-'+eyes+'-'+str(morph2[0][i])+asfx), 'dissim': abs(morph1[0][i]-morph2[0][i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph1[0][i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph2[0][i])+'mask'+asfx)})
pracdiffsame.append({'cxt1': cxt1, 'cxt2': cxt2, 'eyes': eyes, 'cond': 'DS', 'im1': str(cxt1+'-'+eyes+'-'+str(morph3[i])+asfx), 'im2': str(cxt2+'-'+eyes+'-'+str(morph3[i])+asfx), 'dissim': abs(morph3[i]-morph3[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx)})
pracsamediff.append({'cxt1': cxt1, 'cxt2': cxt1, 'eyes': eyes, 'cond': 'SD', 'im1': str(cxt1+'-'+eyes+'-'+str(morph1[0][i])+asfx), 'im2': str(cxt1+'-'+eyes+'-'+str(morph2[0][i])+asfx), 'dissim': abs(morph1[0][i]-morph2[0][i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph1[0][i])+'mask'+asfx), 'mask2': str(cxt1+'-'+eyes+'-'+str(morph2[0][i])+'mask'+asfx)})
pracsamesame.append({'cxt1': cxt1, 'cxt2': cxt1, 'eyes': eyes, 'cond': 'SS', 'im1': str(cxt1+'-'+eyes+'-'+str(morph4[i])+asfx), 'im2': str(cxt1+'-'+eyes+'-'+str(morph4[i])+asfx), 'dissim': abs(morph4[i]-morph4[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph4[i])+'mask'+asfx), 'mask2': str(cxt1+'-'+eyes+'-'+str(morph4[i])+'mask'+asfx)})
pracisodiff.append({'cxt1': '0', 'cxt2': '0', 'eyes': eyes, 'cond': 'ISOD', 'im1': str(eyes+'-'+str(morph1[0][i])+asfx), 'im2': str(eyes+'-'+str(morph2[0][i])+asfx), 'dissim': abs(morph1[0][i]-morph2[0][i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph1[0][i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph2[0][i])+'mask'+asfx)})
pracisosame.append({'cxt1': '0', 'cxt2': '0', 'eyes': eyes, 'cond': 'ISOS', 'im1': str(eyes+'-'+str(morph5[i])+asfx), 'im2': str(eyes+'-'+str(morph5[i])+asfx), 'dissim': abs(morph5[i]-morph5[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph5[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph5[i])+'mask'+asfx)})
i=i+1
pddmat24=[]
pddmat36=[]
pddmat53=[]
pddmat80=[]
psdmat24=[]
psdmat36=[]
psdmat53=[]
psdmat80=[]
pisodmat24=[]
pisodmat36=[]
pisodmat53=[]
pisodmat80=[]
for j in np.arange(len(pracdiffdiff)):
if pracdiffdiff[j]['dissim'] == 24:
pddmat24.append(pracdiffdiff[j])
elif pracdiffdiff[j]['dissim'] == 36:
pddmat36.append(pracdiffdiff[j])
elif pracdiffdiff[j]['dissim'] == 53:
pddmat53.append(pracdiffdiff[j])
elif pracdiffdiff[j]['dissim'] == 80:
pddmat80.append(pracdiffdiff[j])
for j in np.arange(len(pracsamediff)):
if pracsamediff[j]['dissim'] == 24:
psdmat24.append(pracsamediff[j])
elif pracsamediff[j]['dissim'] == 36:
psdmat36.append(pracsamediff[j])
elif pracsamediff[j]['dissim'] == 53:
psdmat53.append(pracsamediff[j])
elif pracsamediff[j]['dissim'] == 80:
psdmat80.append(pracsamediff[j])
for j in np.arange(len(pracisodiff)):
if pracisodiff[j]['dissim'] == 24:
pisodmat24.append(pracisodiff[j])
elif pracisodiff[j]['dissim'] == 36:
pisodmat36.append(pracisodiff[j])
elif pracisodiff[j]['dissim'] == 53:
pisodmat53.append(pracisodiff[j])
elif pracisodiff[j]['dissim'] == 80:
pisodmat80.append(pracisodiff[j])
rnd.shuffle(pddmat24)
rnd.shuffle(pddmat36)
rnd.shuffle(pddmat53)
rnd.shuffle(pddmat80)
rnd.shuffle(psdmat24)
rnd.shuffle(psdmat36)
rnd.shuffle(psdmat53)
rnd.shuffle(psdmat80)
rnd.shuffle(pisodmat24)
rnd.shuffle(pisodmat36)
rnd.shuffle(pisodmat53)
rnd.shuffle(pisodmat80)
rnd.shuffle(pracdiffsame)
rnd.shuffle(pracsamesame)
rnd.shuffle(pracisosame)
adr=0
practrials=[]
for adder in np.arange(tottri/24):
slcr=slice(adr*4,(adr*4)+4,1)
practrials.append(pddmat24[adr])
practrials.append(pddmat36[adr])
practrials.append(pddmat53[adr])
practrials.append(pddmat80[adr])
practrials.extend(pracdiffsame[slcr])
practrials.append(psdmat24[adr])
practrials.append(psdmat36[adr])
practrials.append(psdmat53[adr])
practrials.append(psdmat80[adr])
practrials.extend(pracsamesame[slcr])
practrials.append(pisodmat24[adr])
practrials.append(pisodmat36[adr])
practrials.append(pisodmat53[adr])
practrials.append(pisodmat80[adr])
practrials.extend(pracisosame[slcr])
adr=adr+1
import copy
p1 = copy.deepcopy(practrials)
for ind in range(0,int(len(practrials))):
practrials[ind].update(ori=0)
for ind in range(0, int(len(p1))):
p1[ind].update(ori=180)
p2 = practrials + p1
p2.sort(key=operator.itemgetter('dissim'))
pracordtrials1=[]
slcr=slice(0,int(len(p2)/2),1)
pracordtrials1.extend(p2[slcr])
pracordtrials2=[]
slcr2=slice(int(len(p2)/2),len(p2),1)
pracordtrials2.extend(p2[slcr2])
rnd.shuffle(pracordtrials1)
rnd.shuffle(pracordtrials2)
pracnewtrials=[]
# This is where we take equal number of same and diff trials and put them in a
# new list.
for indx in np.arange(0,int(len(p2)/2),3):
slcr=slice(indx,indx+3,1)
pracnewtrials.extend(pracordtrials1[slcr])
pracnewtrials.extend(pracordtrials2[slcr])
pracnewtrials2=[]
for indx in np.arange(0,len(p2),6):
slcr=slice(indx,indx+6,1)
pp=pracnewtrials[slcr]
rnd.shuffle(pp)
pracnewtrials2.extend(pp)
pp2= pracnewtrials2
prtrials = data.TrialHandler(pp2, nReps=1, method='sequential', originPath=datapath)
morph1=[]
morph2=[]
morph3=[]
morph4=[]
morph5=[]
morph11=npm.repmat([38, 32, 24, 10],1,int(len(meneyes)/4))
morph12=npm.repmat([32, 24, 10, 38],1,int(len(meneyes)/4))
morph13=npm.repmat([24, 10, 38, 32],1,int(len(meneyes)/4))
morph14=npm.repmat([10, 38, 32, 24],1,int(len(meneyes)/4))
morph1=np.append(morph11,morph12)
morph1=np.append(morph1, morph13)
morph1=np.append(morph1, morph14)
morph21=npm.repmat([62, 68, 77, 90],1,int(len(meneyes)/4))
morph22=npm.repmat([68, 77, 90, 62],1,int(len(meneyes)/4))
morph23=npm.repmat([77, 90, 62, 68],1,int(len(meneyes)/4))
morph24=npm.repmat([90, 62, 68, 77],1,int(len(meneyes)/4))
morph2=np.append(morph21,morph22)
morph2=np.append(morph2, morph23)
morph2=np.append(morph2, morph24)
morph31=npm.repmat([10, 32, 62, 77],1,int(len(meneyes)/4))
morph32=npm.repmat([77, 10, 32, 62],1,int(len(meneyes)/4))
morph33=npm.repmat([62, 77, 10, 32],1,int(len(meneyes)/4))
morph34=npm.repmat([32, 62, 77, 10],1,int(len(meneyes)/4))
morph3=np.append(morph31, morph32)
morph31=np.append(morph33, morph34)
morph3=np.append(morph3, morph31)
morph41=npm.repmat([77, 10, 32, 62],1,int(len(meneyes)/4))
morph42=npm.repmat([62, 77, 10, 32],1,int(len(meneyes)/4))
morph43=npm.repmat([32, 62, 77, 10],1,int(len(meneyes)/4))
morph44=npm.repmat([10, 32, 62, 77],1,int(len(meneyes)/4))
morph4=np.append(morph41, morph42)
morph41=np.append(morph43, morph44)
morph4=np.append(morph4, morph41)
morph51=npm.repmat([62, 77, 10, 32],1,int(len(meneyes)/4))
morph52=npm.repmat([77, 10, 32, 62],1,int(len(meneyes)/4))
morph53=npm.repmat([10, 32, 62, 77],1,int(len(meneyes)/4))
morph54=npm.repmat([32, 62, 77, 10],1,int(len(meneyes)/4))
morph5=np.append(morph51, morph52)
morph51=np.append(morph53, morph54)
morph5=np.append(morph5, morph51)
expdiffdiffmen=[]
expdiffsamemen=[]
expsamediffmen=[]
expsamesamemen=[]
expisodiffmen=[]
expisosamemen=[]
i=0
for cxt1, cxt2, eyes in zip(mencxts1, mencxts2, meneyes):
for itr in np.arange(4):
expdiffdiffmen.append({'cxt1': cxt1, 'cxt2': cxt2, 'eyes': eyes, 'cond': 'DD', 'im1': str(cxt1+'-'+eyes+'-'+str(morph1[i])+asfx), 'im2': str(cxt2+'-'+eyes+'-'+str(morph2[i])+asfx), 'dissim': abs(morph1[i]-morph2[i]), 'pair': str(morph1[i])+'-'+str(morph2[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph1[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph2[i])+'mask'+asfx), 'tno': i})
expdiffsamemen.append({'cxt1': cxt1, 'cxt2': cxt2, 'eyes': eyes, 'cond': 'DS', 'im1': str(cxt1+'-'+eyes+'-'+str(morph3[i])+asfx), 'im2': str(cxt2+'-'+eyes+'-'+str(morph3[i])+asfx), 'dissim': abs(morph3[i]-morph3[i]), 'pair': str(morph3[i])+'-'+str(morph3[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'tno': i})
expsamediffmen.append({'cxt1': cxt1, 'cxt2': cxt1, 'eyes': eyes, 'cond': 'SD', 'im1': str(cxt1+'-'+eyes+'-'+str(morph1[i])+asfx), 'im2': str(cxt1+'-'+eyes+'-'+str(morph2[i])+asfx), 'dissim': abs(morph1[i]-morph2[i]), 'pair': str(morph1[i])+'-'+str(morph2[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph1[i])+'mask'+asfx), 'mask2': str(cxt1+'-'+eyes+'-'+str(morph2[i])+'mask'+asfx), 'tno': i})
expsamesamemen.append({'cxt1': cxt1, 'cxt2': cxt1, 'eyes': eyes, 'cond': 'SS', 'im1': str(cxt1+'-'+eyes+'-'+str(morph4[i])+asfx), 'im2': str(cxt1+'-'+eyes+'-'+str(morph4[i])+asfx), 'dissim': abs(morph4[i]-morph4[i]), 'pair': str(morph4[i])+'-'+str(morph4[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph4[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph4[i])+'mask'+asfx), 'tno': i})
expisodiffmen.append({'cxt1': '0', 'cxt2': '0', 'eyes': eyes, 'cond': 'ISOD', 'im1': str(eyes+'-'+str(morph1[i])+asfx), 'im2': str(eyes+'-'+str(morph2[i])+asfx), 'dissim': abs(morph1[i]-morph2[i]), 'pair': str(morph1[i])+'-'+str(morph2[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph1[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph2[i])+'mask'+asfx), 'tno': i})
expisosamemen.append({'cxt1': '0', 'cxt2': '0', 'eyes': eyes, 'cond': 'ISOS', 'im1': str(eyes+'-'+str(morph5[i])+asfx), 'im2': str(eyes+'-'+str(morph5[i])+asfx), 'dissim': abs(morph5[i]-morph5[i]), 'pair': str(morph5[i])+'-'+str(morph5[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'tno': i})
i+=1
expdiffdiffwom = []
expdiffsamewom=[]
expsamediffwom=[]
expsamesamewom=[]
expisodiffwom=[]
expisosamewom=[]
i=0
for cxt1, cxt2, eyes in zip(womcxts1, womcxts2, womeyes):
for itr in np.arange(4):
expdiffdiffwom.append({'cxt1': cxt1, 'cxt2': cxt2, 'eyes': eyes, 'cond': 'DD', 'im1': str(cxt1+'-'+eyes+'-'+str(morph1[i])+asfx), 'im2': str(cxt2+'-'+eyes+'-'+str(morph2[i])+asfx), 'dissim': abs(morph1[i]-morph2[i]), 'pair': str(morph1[i])+'-'+str(morph2[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph1[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph2[i])+'mask'+asfx), 'tno': i})
expdiffsamewom.append({'cxt1': cxt1, 'cxt2': cxt2, 'eyes': eyes, 'cond': 'DS', 'im1': str(cxt1+'-'+eyes+'-'+str(morph3[i])+asfx), 'im2': str(cxt2+'-'+eyes+'-'+str(morph3[i])+asfx), 'dissim': abs(morph3[i]-morph3[i]), 'pair': str(morph3[i])+'-'+str(morph3[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'tno': i})
expsamediffwom.append({'cxt1': cxt1, 'cxt2': cxt1, 'eyes': eyes, 'cond': 'SD', 'im1': str(cxt1+'-'+eyes+'-'+str(morph1[i])+asfx), 'im2': str(cxt1+'-'+eyes+'-'+str(morph2[i])+asfx), 'dissim': abs(morph1[i]-morph2[i]), 'pair': str(morph1[i])+'-'+str(morph2[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'tno': i})
expsamesamewom.append({'cxt1': cxt1, 'cxt2': cxt1, 'eyes': eyes, 'cond': 'SS', 'im1': str(cxt1+'-'+eyes+'-'+str(morph4[i])+asfx), 'im2': str(cxt1+'-'+eyes+'-'+str(morph4[i])+asfx), 'dissim': abs(morph4[i]-morph4[i]), 'pair': str(morph4[i])+'-'+str(morph4[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph4[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph4[i])+'mask'+asfx), 'tno': i})
expisodiffwom.append({'cxt1': '0', 'cxt2': '0', 'eyes': eyes, 'cond': 'ISOD', 'im1': str(eyes+'-'+str(morph1[i])+asfx), 'im2': str(eyes+'-'+str(morph2[i])+asfx), 'dissim': abs(morph1[i]-morph2[i]), 'pair': str(morph1[i])+'-'+str(morph2[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph1[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph2[i])+'mask'+asfx), 'tno': i})
expisosamewom.append({'cxt1': '0', 'cxt2': '0', 'eyes': eyes, 'cond': 'ISOS', 'im1': str(eyes+'-'+str(morph5[i])+asfx), 'im2': str(eyes+'-'+str(morph5[i])+asfx), 'dissim': abs(morph5[i]-morph5[i]), 'pair': str(morph5[i])+'-'+str(morph5[i]), 'mask1': str(cxt1+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'mask2': str(cxt2+'-'+eyes+'-'+str(morph3[i])+'mask'+asfx), 'tno': i})
i+=1
eddmen24=[]
eddwom24=[]
eddmen36=[]
eddwom36=[]
eddmen53=[]
eddwom53=[]
eddmen80=[]
eddwom80=[]
esdmen24=[]
esdwom24=[]
esdmen36=[]
esdwom36=[]
esdmen53=[]
esdwom53=[]
esdmen80=[]
esdwom80=[]
eisodmen24=[]
eisodwom24=[]
eisodmen36=[]
eisodwom36=[]
eisodmen53=[]
eisodwom53=[]
eisodmen80=[]
eisodwom80=[]
for j in np.arange(len(expdiffdiffmen)):
if expdiffdiffmen[j]['dissim'] == 24:
eddmen24.append(expdiffdiffmen[j])
elif expdiffdiffmen[j]['dissim'] == 36:
eddmen36.append(expdiffdiffmen[j])
elif expdiffdiffmen[j]['dissim'] == 53:
eddmen53.append(expdiffdiffmen[j])
elif expdiffdiffmen[j]['dissim'] == 80:
eddmen80.append(expdiffdiffmen[j])
for j in np.arange(len(expdiffdiffwom)):
if expdiffdiffwom[j]['dissim'] == 24:
eddwom24.append(expdiffdiffwom[j])
elif expdiffdiffwom[j]['dissim'] == 36:
eddwom36.append(expdiffdiffwom[j])
elif expdiffdiffwom[j]['dissim'] == 53:
eddwom53.append(expdiffdiffwom[j])
elif expdiffdiffwom[j]['dissim'] == 80:
eddwom80.append(expdiffdiffwom[j])
for j in np.arange(len(expsamediffmen)):
if expsamediffmen[j]['dissim'] == 24:
esdmen24.append(expsamediffmen[j])
elif expsamediffmen[j]['dissim'] == 36:
esdmen36.append(expsamediffmen[j])
elif expsamediffmen[j]['dissim'] == 53:
esdmen53.append(expsamediffmen[j])
elif expsamediffmen[j]['dissim'] == 80:
esdmen80.append(expsamediffmen[j])
for j in np.arange(len(expsamediffwom)):
if expsamediffwom[j]['dissim'] == 24:
esdwom24.append(expsamediffwom[j])
elif expsamediffwom[j]['dissim'] == 36:
esdwom36.append(expsamediffwom[j])
elif expsamediffwom[j]['dissim'] == 53:
esdwom53.append(expsamediffwom[j])
elif expsamediffwom[j]['dissim'] == 80:
esdwom80.append(expsamediffwom[j])
for j in np.arange(len(expisodiffmen)):
if expisodiffmen[j]['dissim'] == 24:
eisodmen24.append(expisodiffmen[j])
elif expisodiffmen[j]['dissim'] == 36:
eisodmen36.append(expisodiffmen[j])
elif expisodiffmen[j]['dissim'] == 53:
eisodmen53.append(expisodiffmen[j])
elif expisodiffmen[j]['dissim'] == 80:
eisodmen80.append(expisodiffmen[j])
for j in np.arange(len(expisodiffwom)):
if expisodiffwom[j]['dissim'] == 24:
eisodwom24.append(expisodiffwom[j])
elif expisodiffwom[j]['dissim'] == 36:
eisodwom36.append(expisodiffwom[j])
elif expisodiffwom[j]['dissim'] == 53:
eisodwom53.append(expisodiffwom[j])
elif expisodiffwom[j]['dissim'] == 80:
eisodwom80.append(expisodiffwom[j])
rnd.shuffle(eddmen24)
rnd.shuffle(eddwom24)
rnd.shuffle(eddmen36)
rnd.shuffle(eddwom36)
rnd.shuffle(eddmen53)
rnd.shuffle(eddwom53)
rnd.shuffle(eddmen80)
rnd.shuffle(eddwom80)
rnd.shuffle(esdmen24)
rnd.shuffle(esdwom24)
rnd.shuffle(esdmen36)
rnd.shuffle(esdwom36)
rnd.shuffle(esdmen53)
rnd.shuffle(esdwom53)
rnd.shuffle(esdmen80)
rnd.shuffle(esdwom80)
rnd.shuffle(eisodmen24)
rnd.shuffle(eisodwom24)
rnd.shuffle(eisodmen36)
rnd.shuffle(eisodwom36)
rnd.shuffle(eisodmen53)
rnd.shuffle(eisodwom53)
rnd.shuffle(eisodmen80)
rnd.shuffle(eisodwom80)
rnd.shuffle(expdiffsamemen)
rnd.shuffle(expdiffsamewom)
rnd.shuffle(expsamesamemen)
rnd.shuffle(expsamesamewom)
rnd.shuffle(expisosamemen)
rnd.shuffle(expisosamewom)
adr=0
exptrials=[]
for adder in np.arange(explength2/96):
slcr=slice(adr*4,(adr*4)+4,1)
exptrials.append(eddmen24[adr])
exptrials.append(eddmen36[adr])
exptrials.append(eddmen53[adr])
exptrials.append(eddmen80[adr])
exptrials.extend(expdiffsamemen[slcr])
exptrials.append(eddwom24[adr])
exptrials.append(eddwom36[adr])
exptrials.append(eddwom53[adr])
exptrials.append(eddwom80[adr])
exptrials.extend(expdiffsamewom[slcr])
exptrials.append(esdmen24[adr])
exptrials.append(esdmen36[adr])
exptrials.append(esdmen53[adr])
exptrials.append(esdmen80[adr])
exptrials.extend(expsamesamemen[slcr])
exptrials.append(esdwom24[adr])
exptrials.append(esdwom36[adr])
exptrials.append(esdwom53[adr])
exptrials.append(esdwom80[adr])
exptrials.extend(expsamesamewom[slcr])
exptrials.append(eisodmen24[adr])
exptrials.append(eisodmen36[adr])
exptrials.append(eisodmen53[adr])
exptrials.append(eisodmen80[adr])
exptrials.extend(expisosamemen[slcr])
exptrials.append(eisodwom24[adr])
exptrials.append(eisodwom36[adr])
exptrials.append(eisodwom53[adr])
exptrials.append(eisodwom80[adr])
exptrials.extend(expisosamewom[slcr])
adr=adr+1
e1 = copy.deepcopy(exptrials)
for ind in range(0,int(len(exptrials))):
exptrials[ind].update(ori=0)
for ind in range(0, int(len(e1))):
e1[ind].update(ori=180)
e2 = exptrials + e1
e2.sort(key=operator.itemgetter('dissim'))
ordtrials1=[]
slcr=slice(0,int(len(e2)/2),1)
ordtrials1.extend(e2[slcr])
ordtrials2=[]
slcr2=slice(int(len(e2)/2),len(e2),1)
ordtrials2.extend(e2[slcr2])
rnd.shuffle(ordtrials1)
rnd.shuffle(ordtrials2)
ord1iso0=[]
ord1iso1=[]
ord1cong0=[]
ord1cong1=[]
ord1inc0=[]
ord1inc1=[]
for i in np.arange(0,len(ordtrials1)):
if ordtrials1[i]['cond'] == 'ISOS' and ordtrials1[i]['ori'] == 0:
ord1iso0.append(ordtrials1[i])
elif ordtrials1[i]['cond'] == 'ISOS' and ordtrials1[i]['ori'] == 180:
ord1iso1.append(ordtrials1[i])
elif ordtrials1[i]['cond'] == 'SS' and ordtrials1[i]['ori'] == 0:
ord1cong0.append(ordtrials1[i])
elif ordtrials1[i]['cond'] == 'SS' and ordtrials1[i]['ori'] == 180:
ord1cong1.append(ordtrials1[i])
elif ordtrials1[i]['cond'] == 'DS' and ordtrials1[i]['ori'] == 0:
ord1inc0.append(ordtrials1[i])
elif ordtrials1[i]['cond'] == 'DS' and ordtrials1[i]['ori'] == 180:
ord1inc1.append(ordtrials1[i])
for i in np.arange(0,len(ordtrials1)):
if ordtrials1[i]['cond'] == 'DS'and ordtrials1[i]['ori'] == 0:
ord1inc0.append(ordtrials1[i])
ord24iso0=[]
ord24iso1=[]
ord24cong0=[]
ord24cong1=[]
ord24inc0=[]
ord24inc1=[]
ord36iso0=[]
ord36iso1=[]
ord36cong0=[]
ord36cong1=[]
ord36inc0=[]
ord36inc1=[]
ord53iso0=[]
ord53iso1=[]
ord53cong0=[]
ord53cong1=[]
ord53inc0=[]
ord53inc1=[]
ord80iso0=[]
ord80iso1=[]
ord80cong0=[]
ord80cong1=[]
ord80inc0=[]
ord80inc1=[]
for i in np.arange(0,len(ordtrials2)):
if ordtrials2[i]['dissim'] == 24:
if ordtrials2[i]['ori'] == 0:
if ordtrials2[i]['cond'] == 'ISOD':
ord24iso0.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'DD':
ord24cong0.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'SD':
ord24inc0.append(ordtrials2[i])
else:
if ordtrials2[i]['cond'] == 'ISOD':
ord24iso1.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'DD':
ord24cong1.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'SD':
ord24inc1.append(ordtrials2[i])
if ordtrials2[i]['dissim'] == 36:
if ordtrials2[i]['ori'] == 0:
if ordtrials2[i]['cond'] == 'ISOD':
ord36iso0.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'DD':
ord36cong0.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'SD':
ord36inc0.append(ordtrials2[i])
else:
if ordtrials2[i]['cond'] == 'ISOD':
ord36iso1.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'DD':
ord36cong1.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'SD':
ord36inc1.append(ordtrials2[i])
if ordtrials2[i]['dissim'] == 53:
if ordtrials2[i]['ori'] == 0:
if ordtrials2[i]['cond'] == 'ISOD':
ord53iso0.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'DD':
ord53cong0.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'SD':
ord53inc0.append(ordtrials2[i])
else:
if ordtrials2[i]['cond'] == 'ISOD':
ord53iso1.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'DD':
ord53cong1.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'SD':
ord53inc1.append(ordtrials2[i])
if ordtrials2[i]['dissim'] == 80:
if ordtrials2[i]['ori'] == 0:
if ordtrials2[i]['cond'] == 'ISOD':
ord80iso0.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'DD':
ord80cong0.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'SD':
ord80inc0.append(ordtrials2[i])
else:
if ordtrials2[i]['cond'] == 'ISOD':
ord80iso1.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'DD':
ord80cong1.append(ordtrials2[i])
elif ordtrials2[i]['cond'] == 'SD':
ord80inc1.append(ordtrials2[i])
newtrials=[]
# This is where we take equal number of same and diff trials and put them in a
# new list.
adr=0
for indx in np.arange(0,16):
slcr=slice(adr*4,(adr*4)+4,1)
newtrials.extend(ord1iso0[slcr])
newtrials.extend(ord1iso1[slcr])
newtrials.extend(ord1inc0[slcr])
newtrials.extend(ord1inc1[slcr])
newtrials.extend(ord1cong0[slcr])
newtrials.extend(ord1cong1[slcr])
newtrials.append(ord24iso0[indx])
newtrials.append(ord24iso1[indx])
newtrials.append(ord24inc0[indx])
newtrials.append(ord24inc1[indx])
newtrials.append(ord24cong0[indx])
newtrials.append(ord24cong1[indx])
newtrials.append(ord36iso0[indx])
newtrials.append(ord36iso1[indx])
newtrials.append(ord36inc0[indx])
newtrials.append(ord36inc1[indx])
newtrials.append(ord36cong0[indx])
newtrials.append(ord36cong1[indx])
newtrials.append(ord53iso0[indx])
newtrials.append(ord53iso1[indx])
newtrials.append(ord53inc0[indx])
newtrials.append(ord53inc1[indx])
newtrials.append(ord53cong0[indx])
newtrials.append(ord53cong1[indx])
newtrials.append(ord80iso0[indx])
newtrials.append(ord80iso1[indx])
newtrials.append(ord80inc0[indx])
newtrials.append(ord80inc1[indx])
newtrials.append(ord80cong0[indx])
newtrials.append(ord80cong1[indx])
adr+=1
# This part shuffles every 36 within itself.
newtrials2=[]
for indx in np.arange(0,len(e2),48):
slcr=slice(indx,indx+48,1)
a=newtrials[slcr]
rnd.shuffle(a)
newtrials2.extend(a)
fintrials = copy.deepcopy(newtrials2)
ttno=0
for ind in range(int(len(fintrials))):
fintrials[ttno].update(ttno=ttno)
ttno+=1
# creating two sessions.
ses1=[]
slcr3=slice(0,int(len(fintrials)/2),1)
ses1.extend(fintrials[slcr3])
ses2=[]
slcr4=slice(int(len(fintrials)/2),len(fintrials),1)
ses2.extend(fintrials[slcr4])
import pickle
trials_fname = exp_info['participant'] + '_' + 'trials'
trials_fname = os.path.join(datapath, trials_fname)
pickle_fname = exp_info['participant'] + '-' + 'pickle'
pickle_fname = os.path.join(datapath, pickle_fname)
subinfo_fname = exp_info['participant'] + '-' + 'subinfo'
subinfo_fname = os.path.join(datapath, subinfo_fname)
pickled=False
if os.path.exists(pickle_fname):
pickled=True
print('pickled')
if not pickled:
print('unpickled, pickling now')
with open(trials_fname, 'wb') as pickle_file:
pickle.dump([fintrials], pickle_file)
with open(pickle_fname, 'wb') as pickle_file2:
pickle.dump([pickled], pickle_file2)
with open(subinfo_fname, 'wb') as pickle_file3:
pickle.dump([exp_info], pickle_file3)
exTrials = data.TrialHandler(ses1, nReps=1, method='sequential', originPath=datapath)
print('ses1')
else:
with open(trials_fname, 'rb') as pickle_file:
fintrials=pickle.load(pickle_file)
fintrials=fintrials[0][:]
with open(pickle_fname, 'rb') as pickle_file2:
pickled=pickle.load(pickle_file2)
ses2=[]
slcr4=slice(int(len(fintrials)/2),len(fintrials),1)
ses2.extend(fintrials[slcr4])
exTrials= data.TrialHandler(ses2, nReps=1, method='sequential', originPath=datapath)
#=====================
# Start the experiment
#=====================
# Initialize two clocks:
# - for image change time
# - for response time
change_clock = core.Clock()
rt_clock = core.Clock()
trialCount=0
training=0
trainingAccTot=0
trainingAccBlock=0
pracCount=0
pracDone=0
pracblockno=1
# Run through the trials PRACTICE
for trial in prtrials:
pracCount=pracCount+1
# Display trial start text
if pracCount == 1:
##Instruction Screen 1: Before starting, make sure to find ...
inst1_imname=os.path.join(instpath, 'instscr1.png')
inst1=Image.open(inst1_imname)
enh1=ImageEnhance.Brightness(inst1)
inst1_end=enh1.enhance(brightness)
bitmapinst.setImage(inst1_end)
bitmapinst.draw()
win.flip()
# Wait for a spacebar press to start the trial, or escape to quit
keys = event.waitKeys()
if 'escape' in keys:
break
keys = []
event.clearEvents()
##Instruction Screen 2: In this experiment, pictures of faces ...
inst2_imname=os.path.join(instpath, 'instscr2.png')
inst2=Image.open(inst2_imname)
enh1=ImageEnhance.Brightness(inst2)
inst2_end=enh1.enhance(brightness)
bitmapinst.setImage(inst2_end)
bitmapinst.draw()
win.flip()
# Wait for a spacebar press to start the trial, or escape to quit
keys = event.waitKeys()
if 'escape' in keys:
break
keys = []
event.clearEvents()
##Instruction Screen 6: The task is difficult since...
inst5_imname=os.path.join(instpath, 'instscr5.png')
bitmapinst.setImage(inst5_imname)
inst5=Image.open(inst5_imname)
enh1=ImageEnhance.Brightness(inst5)
inst5_end=enh1.enhance(brightness)
bitmapinst.setImage(inst5_end)
bitmapinst.draw()
win.flip()
# Wait for a spacebar press to start the trial, or escape to quit
keys = event.waitKeys()
if 'escape' in keys:
break
keys = []
event.clearEvents()
##Instruction Screen 7: IDENTICAL eyes = "S", DIFFERENT...
inst6_imname=os.path.join(instpath, 'instscr6.png')
inst6=Image.open(inst6_imname)
enh1=ImageEnhance.Brightness(inst6)
inst6_end=enh1.enhance(brightness)
bitmapinst.setImage(inst6_end)
bitmapinst.draw()
win.flip()
# Wait for a spacebar press to start the trial, or escape to quit
keys = event.waitKeys()
if 'escape' in keys:
break
keys = []
event.clearEvents()
# Set the images