CoLAGaze

class pymovements.datasets.CoLAGaze(name: str = 'CoLAGaze', long_name: str = 'Corpus of Eye Movements for Linguistic Acceptability', mirrors: dict[str, Sequence[str]] = <factory>, resources: ResourceDefinitions = <factory>, experiment: Experiment = <factory>, extract: dict[str, bool] | None = None, custom_read_kwargs: dict[str, dict[str, Any]] = <factory>, column_map: dict[str, str] = <factory>, trial_columns: list[str] | None = None, time_column: str | None = None, time_unit: str | None = None, pixel_columns: list[str] | None = None, position_columns: list[str] | None = None, velocity_columns: list[str] | None = None, acceleration_columns: list[str] | None = None, distance_column: str | None = None, filename_format: dict[str, str] | None = None, filename_format_schema_overrides: dict[str, dict[str, type]] | None = None)

CoLAGaze dataset [Bondar et al., 2025].

This dataset includes eye-tracking data from native speakers of English reading sentences from the CoLA dataset. Eye movements are recorded at a sampling frequency of 2,000 Hz using an EyeLink 1000 eye tracker and are provided as pixel coordinates.

Check the respective paper for details [Bondar et al., 2025].

name

The name of the dataset.

Type:

str

long_name

The entire name of the dataset.

Type:

str

resources

A list of dataset gaze_resources. Each list entry must be a dictionary with the following keys: - resource: The url suffix of the resource. This will be concatenated with the mirror. - filename: The filename under which the file is saved as. - md5: The MD5 checksum of the respective file.

Type:

ResourceDefinitions

experiment

The experiment definition.

Type:

Experiment

filename_format

Regular expression which will be matched before trying to load the file. Namedgroups will appear in the fileinfo dataframe.

Type:

dict[str, str] | None

filename_format_schema_overrides

If named groups are present in the filename_format, this makes it possible to cast specific named groups to a particular datatype.

Type:

dict[str, dict[str, type]] | None

custom_read_kwargs

If specified, these keyword arguments will be passed to the file reading function.

Type:

dict[str, dict[str, Any]]

Examples

Initialize your Dataset object with the CoLAGaze definition:

>>> import pymovements as pm
>>>
>>> dataset = pm.Dataset("CoLAGaze", path='data/CoLAGaze')

Download the dataset resources:

>>> dataset.download()

Load the data into memory:

>>> dataset.load()

Methods

__init__([name, long_name, mirrors, ...])
from_yaml(path)	Load a dataset definition from a YAML file.
to_dict(*[, exclude_private, exclude_none])	Return dictionary representation.
to_yaml(path, *[, exclude_private, exclude_none])	Save a dataset definition to a YAML file.

Attributes

acceleration_columns
distance_column
extract
filename_format
filename_format_schema_overrides
has_resources	Checks for resources in resources.
long_name
name
pixel_columns
position_columns
time_column
time_unit
trial_columns
velocity_columns
resources
experiment
custom_read_kwargs
mirrors
column_map