cogpy.datasets

Sample data loaders and synthetic signal generators for testing and tutorials. Use cogpy.datasets.load_sample() to get started quickly.

Tutorial: Quickstart | Schemas: Entity Collection: Expected Schemas

Submodules

cogpy.datasets.load

Load bundled sample ECoG recordings for quick testing and demos.

cogpy.datasets.tensor

Sample ECoG datasets for testing and tutorials.

Functions: load_sample, load_raw_sample — load bundled sample recordings. GUI bundles: ieeg_grid_bundle, spectrogram_bursts_bundle — pre-packaged data + layout for interactive visualization demos.

cogpy.datasets.ieeg_grid_bundle(*, mode='small', seed=0, with_atlas=False, large_backend='numpy')

Bundle for developing the iEEG grid + stacked-trace GUIs.

Notes

large_backend=”dask” is supported only if dask is installed, and currently wraps a generated numpy array into a dask array. True end-to-end lazy viewing requires viewer support (implemented in later phases).

Parameters:

  • mode (Literal['small', 'large'])

  • seed (int)

  • with_atlas (bool)

  • large_backend (Literal['numpy', 'dask'])

Return type:

IEEGGridGuiBundle

cogpy.datasets.load_raw_sample()

Load the raw (unprocessed) sample signal as an xarray.DataArray.

cogpy.datasets.load_sample()

Load the preprocessed sample signal as an xarray.DataArray.

Returns:

Grid ECoG signal with dims ("AP", "ML", "time").

Return type:

xarray.DataArray

cogpy.datasets.spectrogram_bursts_bundle(*, mode='small', seed=0, kind='toy')
Parameters:

  • mode (Literal['small', 'large'])

  • seed (int)

  • kind (Literal['toy', 'ar_grid'])

Return type:

SpectrogramGuiBundle