def generate_plots(IMGDIR, PLOTDIR, filename, fixations, saccades, data,
DISPSIZE, trialnr):
# cognitive load
if int(filename[4:5]) == 1:
cognitive_load = "LOW"
else:
cognitive_load = "HIGH"
#imgname = "screenshot.jpg"
#imagefile = os.path.join(IMGDIR,imgname)
# paths
rawplotfile = os.path.join(
PLOTDIR, "raw_data_%s_%s" % (filename[:3], cognitive_load))
scatterfile = os.path.join(
PLOTDIR, "fixations_%s_%s" % (filename[:3], cognitive_load))
scanpathfile = os.path.join(
PLOTDIR, "scanpath_%s_%s" % (filename[:3], cognitive_load))
heatmapfile = os.path.join(
PLOTDIR, "heatmap_%s_%s" % (filename[:3], cognitive_load))
# raw data points
draw_raw(data[trialnr]['x'],
data[trialnr]['y'],
DISPSIZE,
imagefile=None,
savefilename=rawplotfile)
# fixations
draw_fixations(fixations,
DISPSIZE,
imagefile=None,
durationsize=True,
durationcolour=False,
alpha=0.5,
savefilename=scatterfile)
# scanpath
draw_scanpath(fixations,
saccades,
DISPSIZE,
imagefile=None,
alpha=0.5,
savefilename=scanpathfile)
# heatmap
draw_heatmap(fixations,
DISPSIZE,
imagefile=None,
durationweight=True,
alpha=0.5,
savefilename=heatmapfile)
def save_all_raw(self, bar):
"""
Saves all positions in an image file, each position is represented by a dot on the image.
:return: None
"""
rgb_im = self.image.convert('RGB')
rgb_im.save('converted_image.jpg')
del rgb_im
dir = self.image_dir + "raw_points_images/"
if not os.path.exists(dir):
os.makedirs(dir)
for u_id in self.user_positions:
out = dir + u_id + "_points.png"
pos = self.user_positions[u_id]
draw_raw(pos, (self.rescaled_width, self.rescaled_height), imagefile='converted_image.jpg', savefilename=out)
bar.next()
#gc.collect()
os.remove('converted_image.jpg')
maxdist = ang2cm(FIXTHRESH, SCREENDIST) * PIXPERCM
# overwrite fixations
for i in range(len(imagedata)):
imagedata[i]['events']['Sfix'], imagedata[i]['events']['Efix'] = \
fixation_detection(imagedata[i]['x'], imagedata[i]['y'], imagedata[i]['trackertime'], missing=0.0, maxdist=maxdist, mindur=FIXMINDUR)
# PLOT DATA
for i in range(len(imagedata)):
# image name
imgname = os.path.splitext(os.path.basename(IMAGES[i]))[0]
# pickle fixation data
fixfile = open(os.path.join(outputdir, "fixations_%s.dat" % imgname), 'w')
pickle.dump(imagedata[i]['events']['Efix'], fixfile)
fixfile.close()
# plot raw data
fig = gazeplotter.draw_raw(imagedata[i]['x'], imagedata[i]['y'], DISPSIZE, imagefile=IMAGES[i], savefilename=os.path.join(outputdir, "image_%s_raw.png" % imgname))
pyplot.close(fig)
# plot fixations
fig = gazeplotter.draw_fixations(imagedata[i]['events']['Efix'], DISPSIZE, imagefile=IMAGES[i], durationsize=True, durationcolour=False, alpha=0.5, savefilename=os.path.join(outputdir, "image_%s_fixations.png" % imgname))
pyplot.close(fig)
# draw heatmap
fig = gazeplotter.draw_heatmap(imagedata[i]['events']['Efix'], DISPSIZE, imagefile=IMAGES[i], durationweight=True, alpha=0.5, savefilename=os.path.join(outputdir, "image_%s_heatmap.png" % imgname))
pyplot.close(fig)
# ROI ANALYSIS
if "01F_HA_O" in IMAGES[i]:
# empty dicts
Nfix = {}
fixdur = {}
dwelltime = {}
# go through all ROI names
# loop through all trials
for trialnr in range(len(gazedata)):
# find the image file name
for msg in gazedata[trialnr]['events']['msg']:
if '.jpg' in msg[1]:
imgname = os.path.splitext(msg[1])[0]
imgfile = os.path.join(IMGDIR, msg[1])
# get the fixations
fixations = gazedata[trialnr]['events']['Efix']
print "outdir:", outdir # plot the samples
gazeplotter.draw_raw(gazedata[trialnr]['x'],
gazedata[trialnr]['y'],
RESOLUTION,
imagefile=imgfile,
savefilename=os.path.join(outdir,
'%s_samples.png' % imgname))
# plot the fixations
gazeplotter.draw_fixations(fixations,
RESOLUTION,
imagefile=imgfile,
durationsize=True,
durationcolour=False,
alpha=0.5,
savefilename=os.path.join(
outdir, '%s_fixations.png' % imgname))
# plot a heatmap
gazeplotter.draw_heatmap(fixations,
RESOLUTION,
imagefile=imgfile,
# PLOTS
print("plotting gaze data")
# loop through trials
for trialnr in range(len(data)):
# load image name, saccades, and fixations
imgname = data[trialnr][header.index("image")]
saccades = edfdata[trialnr]['events']['Esac'] # [starttime, endtime, duration, startx, starty, endx, endy]
fixations = edfdata[trialnr]['events']['Efix'] # [starttime, endtime, duration, endx, endy]
# paths
imagefile = os.path.join(IMGDIR,imgname)
rawplotfile = os.path.join(pplotdir, "raw_data_%s_%d" % (ppname,trialnr))
scatterfile = os.path.join(pplotdir, "fixations_%s_%d" % (ppname,trialnr))
scanpathfile = os.path.join(pplotdir, "scanpath_%s_%d" % (ppname,trialnr))
heatmapfile = os.path.join(pplotdir, "heatmap_%s_%d" % (ppname,trialnr))
# raw data points
draw_raw(edfdata[trialnr]['x'], edfdata[trialnr]['y'], DISPSIZE, imagefile=imagefile, savefilename=rawplotfile)
# fixations
draw_fixations(fixations, DISPSIZE, imagefile=imagefile, durationsize=True, durationcolour=False, alpha=0.5, savefilename=scatterfile)
# scanpath
draw_scanpath(fixations, saccades, DISPSIZE, imagefile=imagefile, alpha=0.5, savefilename=scanpathfile)
# heatmap
draw_heatmap(fixations, DISPSIZE, imagefile=imagefile, durationweight=True, alpha=0.5, savefilename=heatmapfile)
def read_files(reduced, csvonly):
# Loop through all files
for ppname in PPS:
print("loading gaze data")
# path
fp = os.path.join(DATADIR, '%s.tsv' % ppname)
# check if the path exist
if not os.path.isfile(fp):
raise Exception(
"No eye data file file found for participant '%s'" % (ppname))
# read the file
tobiidata = read_tobii(fp, reduced, missing=0.0, debug=True)
#save_csv(tobiidata)
pplotdir = os.path.join(PLOTDIR, ppname[:3])
if not csvonly:
print("plotting gaze data")
# Loop through trials
for trialnr in range(len(tobiidata)):
# Load image name, saccades, and fixations
imgname = "screenshot.jpg"
imagefile = os.path.join(IMGDIR, imgname)
print(imagefile)
# [starttime, endtime, duration, startx, starty, endx, endy]
saccades = tobiidata[trialnr]['events']['Esac']
# [starttime, endtime, duration, endx, endy]
fixations = tobiidata[trialnr]['events']['Efix']
# cognitive load
if int(ppname[4:5]) == 1:
cognitive_load = "LOW"
else:
cognitive_load = "HIGH"
if reduced:
suffix = "_reduced"
else:
suffix = ""
# Save the fixation and saccades in csv format for MATLAB
save_csv(fixations, saccades, ppname, suffix)
if not csvonly:
# paths
rawplotfile = os.path.join(
pplotdir,
"raw_data_%s_%s%s" % (ppname[:3], cognitive_load, suffix))
scatterfile = os.path.join(
pplotdir,
"fixations_%s_%s%s" % (ppname[:3], cognitive_load, suffix))
scanpathfile = os.path.join(
pplotdir,
"scanpath_%s_%s%s" % (ppname[:3], cognitive_load, suffix))
heatmapfile = os.path.join(
pplotdir,
"heatmap_%s_%s%s" % (ppname[:3], cognitive_load, suffix))
# raw data points
draw_raw(tobiidata[trialnr]['x'],
tobiidata[trialnr]['y'],
DISPSIZE,
imagefile=None,
savefilename=rawplotfile)
# fixations
draw_fixations(fixations,
DISPSIZE,
imagefile=None,
durationsize=True,
durationcolour=False,
alpha=0.5,
savefilename=scatterfile)
# scanpath
draw_scanpath(fixations,
saccades,
DISPSIZE,
imagefile=None,
alpha=0.5,
savefilename=scanpathfile)
# heatmap
draw_heatmap(fixations,
DISPSIZE,
imagefile=None,
durationweight=True,
alpha=0.5,
savefilename=heatmapfile)
