Data classes#

See Data objects for an introduction. The methods for pupil and gaze data are in the namespaces d.pupil (Pupil methods (d.pupil)) and d.gaze (Gaze methods (d.gaze)), the plots in d.plot (Plotting (d.plot)).

Main class#

EyeData holds the data. Its methods for any channel (crop, downsample, masks and layers, events, intervals, segments, saving, …) are listed on its page.

EyeData

Class for eye-tracking and pupillometric data: pupil size and/or gaze position (x, y) of one or two eyes.

Channels, layers and mask policies#

The time series (d["left_pupil"]) and their mask layers are stored in an EyeDataDict (d.data). A MaskPolicy says which layers make a sample unusable ("default", "strict", "raw").

`EyeDataDict`	A dictionary that contains 1-dimensional ndarrays of equal length and with the same datatype (float).
`MaskPolicy`	Which samples count as unusable (masked).

Simulated data and history#

FakeEyeData

EyeData with simulation metadata for testing and validation.

keephistory

Decorator that records a method call in the history of the returned object.

Quality report#

See EyeData.quality_report().

`QualityReport`	Data-quality report for an eyedata object.
`QualityMetric`	A single quality measure.

Tables#

Some results are dicts that are displayed as a table (pandas.DataFrame):

results with one row per event or trial (e.g., Events.to_table(), SegmentedEyeData.gaze.dwell_time) are a Table, a dict of numpy columns
results per channel (e.g., EyeData.layer_stats(): channel -> layer -> statistics) and the list of example datasets are a RecordDict, a dict of records

`Table`	A table: a dict of columns (column name -> numpy array), all of the same length (one value per row).
`RecordDict`	A dict of records that is displayed as a table.