eegdash.dataset.base module#

Data utilities and dataset classes for EEG data handling.

This module provides core dataset classes for working with EEG data in the EEGDash ecosystem, including classes for individual recordings and collections of datasets. It integrates with braindecode for machine learning workflows and handles data loading from both local and remote sources.

class eegdash.dataset.base.EEGDashRaw(record: dict[str, Any], cache_dir: str, **kwargs)[source]

Bases: RawDataset

A single EEG recording dataset.

Represents a single EEG recording, typically hosted on a remote server (like AWS S3) and cached locally upon first access. This class is a subclass of braindecode.datasets.BaseDataset and can be used with braindecode’s preprocessing and training pipelines.

Parameters:

  • record (dict) – A v2 record containing all metadata and storage information. Must have schema_version=2 and include storage.base (no default bucket).

  • cache_dir (str) – The local directory where the data will be cached.

  • **kwargs – Additional keyword arguments passed to the braindecode.datasets.BaseDataset constructor.

Raises:

ValueError – If the record is not a valid v2 record or is missing required fields.

property raw: BaseRaw

The MNE Raw object for this recording.

Accessing this property triggers the download and caching of the data if it has not been accessed before.

Returns:

The loaded MNE Raw object.

Return type:

mne.io.BaseRaw