pymovements.datasets.dataset.Dataset#

class pymovements.datasets.dataset.Dataset(root: str | Path, experiment: Experiment | None = None, filename_regex: str = '.*', filename_regex_dtypes: dict[str, type] | None = None, custom_read_kwargs: dict[str, Any] | None = None, dataset_dirname: str = '.', raw_dirname: str = 'raw', preprocessed_dirname: str = 'preprocessed', events_dirname: str = 'events')[source]#

Dataset base class.

__init__(root: str | Path, experiment: Experiment | None = None, filename_regex: str = '.*', filename_regex_dtypes: dict[str, type] | None = None, custom_read_kwargs: dict[str, Any] | None = None, dataset_dirname: str = '.', raw_dirname: str = 'raw', preprocessed_dirname: str = 'preprocessed', events_dirname: str = 'events')[source]

Initialize the dataset object.

You can set up a custom directory structure by populating the particular dirname attributes. See dataset_dirname, raw_dirname, preprocessed_dirname and events_dirname for details.

Parameters:
  • root (str, Path) – Path to the root directory of the dataset.

  • experiment (Experiment) – The experiment definition.

  • filename_regex (str) – Regular expression which needs to be matched before trying to load the file. Named groups will appear in the fileinfo dataframe.

  • filename_regex_dtypes (dict[str, type], optional) – If named groups are present in the filename_regex, this makes it possible to cast specific named groups to a particular datatype.

  • custom_read_kwargs (dict[str, Any], optional) – If specified, these keyword arguments will be passed to the file reading function.

  • dataset_dirname (str, optional) – Dataset directory name under root path. Can be . if dataset is located in root path. Default: .

  • str (raw_dirname ;) – Name of directory under dataset path that contains raw data. Can be . if raw data is located in dataset path. We advise the user to keep the original raw data separate from the preprocessed / event data. Default: raw

  • optional – Name of directory under dataset path that contains raw data. Can be . if raw data is located in dataset path. We advise the user to keep the original raw data separate from the preprocessed / event data. Default: raw

  • preprocessed_dirname (str, optional) – Name of directory under dataset path that will be used to store preprocessed data. We advise the user to keep the preprocessed data separate from the original raw data. Default: preprocessed

  • events_dirname (str, optional) – Name of directory under dataset path that will be used to store event data. We advise the user to keep the event data separate from the original raw data. Default: events

Methods

__init__(root[, experiment, filename_regex, ...])

Initialize the dataset object.

clear_events()

Clear event DataFrame.

compute_event_properties(event_properties[, ...])

Calculate an event property for and add it as a column to the event dataframe.

detect_events(method[, eye, clear, verbose])

Detect events by applying a specific event detection method.

infer_fileinfo()

Infer information from filepaths and filenames.

load([events, preprocessed, subset, ...])

Parse file information and load all gaze files.

load_event_files([events_dirname])

Load all available event files.

load_gaze_files([preprocessed, ...])

Load all available gaze data files.

pix2deg([verbose])

Compute gaze positions in degrees of visual angle from pixel coordinates.

pos2vel([method, verbose])

Compute gaze velocites in dva/s from dva coordinates.

save([events_dirname, preprocessed_dirname, ...])

Save preprocessed gaze and event files.

save_events([events_dirname, verbose])

Save events to files.

save_preprocessed([preprocessed_dirname, ...])

Save preprocessed gaze files.

take_subset(fileinfo[, subset])

Take a subset of the dataset.

Attributes

events_rootpath

The path to the directory of the event data.

path

The path to the dataset directory.

preprocessed_rootpath

The path to the directory of the preprocessed gaze data.

raw_rootpath

The path to the directory of the raw data.

root

The root path to your dataset.