Eye tracking experiments
August 29th, 2014
Daniel Schreij
VU Cognitive Psychology departement
http://ems.psy.vu.nl/userpages/data-analysis-course
Today
• Creating eye tracking experiments using
OpenSesame and PyGaze
• Get from EDF (Eyelink Data Format) to other
more easily usable data formats
• Analyze data with Pandas and Python
PyGaze
• Download from http://www.pygaze.org
• Standalone Python module to communicate
with any Eyetracker, with a unified interface
(so the code for each eye tracker is the same)
• Has OpenSesame plug-in
Pygaze | Items
Initialize Eyetracker (connection & calibration)
Drift correct
Log message(s)
Start recording
Stop recording
Pause recording
PyGaze | Typical experiment
Basic steps
• Calibrate
• Per trial/block
– Drift correct
• Per trial
– Start recording
– Log variables
– Stop recording
PyGaze | Another way
• Start recording at
beginning of
experiment and stop
at the end
• Drift correct is done
afterwards
• Preferable for pupil
dilation data, or similar
experiments that
require a constant dat
stream (even in
between trials)
PyGaze | Initialize
PyGaze | Logging messages
Data files
• After you have run your experiment you often
get data files in proprietary formats (.EDF)
• Developers like you to use their tools...
• You can then either
– Use proprietary tools to look at data
– export them to a textual format
• Working with the data in textual format
enables you to use your own tool chain such
as Python and all its modules
Data Files | EDF
• Eyelink data format
• You can import them to Eyelink Data viewer
and then create reports
– Saccade, fixation, etc.
• You can use the tool EDF2ASC to convert the
EDF file to an ASCII format and then parse it
yourself (or with available scripts
https://github.com/tknapen/analysis_tools/ )
Data Files | EDF2ASC
MSG
2436129 TRIALID T1Rg200 0 0
START
2436164 LEFT RIGHT EVENTS
PRESCALER 1
VPRESCALER 1
EVENTS GAZE LEFT RIGHT
SFIX L 2436164
SFIX R 2436164
MSG
2436678 SYNCTIME
MSG
2436678 DRAWN NEW TARGET
EFIX L 2436164 2436832
672
EFIX R 2436164 2436832
672
SSACC L 2436836
SSACC R 2436836
ESACC R 2436836 2436872 40 323.6
SFIX R 2436876
ESACC L 2436836 2436876 44 324.3
MSG
2436878 ERASED OLD TARGET
SFIX L 2436880
EFIX R 2436876 2437000 128 492.7
SSACC R 2437004
EFIX L 2436880 2437004 128 499.8
SSACC L 2437008
ESACC L 2437008 2437028 24 506.6
ESACC R 2437004 2437028 28 493.9
220 200
321.7
321.7
246.8
242.1
1422
1683
247.4
496.5
250.2
6.75
276.4
251.6
500.5
247.4
6.93
273.3
249.2
1682
245.0
1323
242.2
248.5
565.4
551.7
251.1
258.4
2.35
2.29
151.4
147.2
Eyelink Data Viewer
Eyelink Data Viewer | Fixations
Eyelink Data Viewer | Saccades
Eyelink Data Viewer | Samples
Eyelink Data Viewer | Heatmap
EDF | Saving variables
• During the experiment, you can send trial
variables to the Eyelink to be stored in the EDF
file
• If you use the appropriate syntax, the EDV will
recognize them as variables (and not as random
messages)
• These variables can be included in reports which
you subject to your analysis scripts later
• ALWAYS SAVE AS MUCH OPENSESAME VARIABLE
DATA AS POSSIBLE TO THE EDF FILE
EDF | Variable syntax
!V TRIAL_VAR <variable_name> <variable_value>
In OpenSesame, send this with send_command() in script
exp.eyetracker.send_command("!V TRIAL_VAR RespTime 350")
• Alternatively, you can use the pygaze_log item
Example experiment
Example Experiment | log variables
Setting background image:
!V IMGLOAD FILL <path/to/image>
Eyelink Data Viewer | Variables
Eyelink Data Viewer | Variables
Eyelink Data Viewer | Interest Periods
• Example OpenSesame script for showing stimuli
self.fix_canvas.show()
self.sleep(1000)
exp.eyetracker.send_command("SHOWING target display")
self.target_canvas.show()
• Right before target display is shown, Eyelink
receives the message "SHOWING target display"
Eyelink Data Viewer | Interest Periods
Eyelink Data Viewer | Interest Periods
Eyelink Data Viewer | Interest Periods
Full trial period
From Target presentation
Eyelink Data Viewer | Interest Areas
• Just like variables, you can send commands
during your experiment to define interest
areas in your display area
• It is also possible to draw these interest areas
after all data has been collected (but this is
much more work)
Eyelink Data Viewer | Interest Areas
• Basic syntax
!V IAREA <shape> <index> <left x> <top y> <right x> <bottom y> [label]
• For a rectangle
!V IAREA RECTANGLE 1 10 5 20 15 cue
• For a circle
!V IAREA ELLIPSE 2 300 200 400 300 target
• For a custom shaped polygon
!V IAREA FREEHAND <id> <x1, y1> <x2, y2 > ... <xn, yn> [label]
Eyelink Data Viewer | Interest Areas
Eyelink Data Viewer | Reports
• EDV has options to export EDF data to other
tabular formats as csv or Excel
• You can create reports containing lists of
– Saccades
– Fixations
– Interest areas
– Samples
– Trials
Eyelink Data Viewer | Reports
Eyelink Data Viewer | Reports
Reports | Analysis
• You can use your favorite software to read in
and start analyzing these report files
– Excel, MatLab, R, SPSS, Pandas, etc.
• For pandas
raw_data = pd.read_csv("SaccadeReport.csv")
Analysis example
try:
raw_data
except:
raw_data = pd.read_csv("ExampleData.csv",sep=";")
# Drop empty columns (don't know why these are there....)
raw_data = raw_data.drop(raw_data.columns[-10:],axis=1)
# Filter data to only contain real and correct trials
work_data = raw_data.query("TRIAL_INDEX > 96 and correct==1")
# Only get first saccades
criteria = "CURRENT_SAC_INDEX == 1 and "
criteria += "CURRENT_SAC_NEAREST_END_INTEREST_AREA_LABEL != '.'"
first_saccades = work_data.query(criteria)
# Create pivot table
cols = ["onset","CURRENT_SAC_NEAREST_END_INTEREST_AREA_LABEL"]
fs_pt = first_saccades.pivot_table("rt",index="cue",
columns=cols, aggfunc="count")
# Plot data
(fs_pt/fs_pt.sum().sum()).plot(kind="bar")
Analysis example
# RT pivot table
cols = ["onset","CURRENT_SAC_NEAREST_END_INTEREST_AREA_LABEL"]
fs_pt = first_saccades.pivot_table("rt",index="cue",
columns=cols,aggfunc="mean")
fs_pt.plot(xlim=[-0.5,1.5],ylim=[650,1000],style="o-")