src.data package

Submodules

src.data.load_data module

src.data.load_data.download_gdrive_folder(fid='1NGfGcVpBarNtFMmdvQhq28hWBlVuxdQz', data_dir='data/')

Download all files from a Google Drive folder by ID and store them in a local directory.

Parameters:

  • fid (str) – Google Drive folder ID. Defaults to DEFAULT_GDRIVE_FOLDER.

  • data_dir (str) – Target directory where files will be stored. (default: “data/”).

Returns:

None

Return type:

None

src.data.load_data.load_file(path)

Load a numpy file into a Points object.

Parameters:

path (str) – Path to the .npy file.

Returns:

A Points object containing the loaded data.

Return type:

Points

src.data.load_data.load_gdrive_file(fid, cls, data_dir='data/')

Download a file from Google Drive using its file ID, move it into a data directory, and optionally load it into a class.

Parameters:

  • fid (str) – Google Drive file ID.

  • cls (Type[T] | None) – Class to wrap the loaded numpy array in. If None, no class is returned.

  • data_dir (str) – Target directory where the file will be stored. (default: “data/”).

Returns:

An instance of cls containing the loaded data, or None if cls is None.

Return type:

T | None

src.data.load_data.load_s_curve(n_samples=100, *, noise=0.0, random_state=None)

Generate a synthetic S-curve dataset.

Parameters:

  • n_samples (int) – Number of samples to generate. (default: 100).

  • noise (float) – Standard deviation of Gaussian noise added to the data. (default: 0.0).

  • random_state (int | None) – Seed for reproducibility. (default: None).

Returns:

A tuple (Points, Coordinates) where Points are the 3D data and Coordinates are the unrolled 1D parameters.

Return type:

Tuple[Points, Coordinates]

src.data.load_data.load_swiss_roll(n_samples=100, *, noise=0.0, random_state=None, hole=False)

Generate a synthetic Swiss roll dataset.

Parameters:

  • n_samples (int) – Number of samples to generate. (default: 100).

  • noise (float) – Standard deviation of Gaussian noise added to the data. (default: 0.0).

  • random_state (int | None) – Seed for reproducibility. (default: None).

  • hole (bool | None) – Whether to generate the Swiss roll with a hole. (default: False).

Returns:

A tuple (Points, Coordinates) where Points are the 3D data and Coordinates are the unrolled 1D parameters.

Return type:

Tuple[Points, Coordinates]

Module contents

src.data.download_gdrive_folder(fid='1NGfGcVpBarNtFMmdvQhq28hWBlVuxdQz', data_dir='data/')

Download all files from a Google Drive folder by ID and store them in a local directory.

Parameters:

  • fid (str) – Google Drive folder ID. Defaults to DEFAULT_GDRIVE_FOLDER.

  • data_dir (str) – Target directory where files will be stored. (default: “data/”).

Returns:

None

Return type:

None

src.data.load_file(path)

Load a numpy file into a Points object.

Parameters:

path (str) – Path to the .npy file.

Returns:

A Points object containing the loaded data.

Return type:

Points

src.data.load_gdrive_file(fid, cls, data_dir='data/')

Download a file from Google Drive using its file ID, move it into a data directory, and optionally load it into a class.

Parameters:

  • fid (str) – Google Drive file ID.

  • cls (Type[T] | None) – Class to wrap the loaded numpy array in. If None, no class is returned.

  • data_dir (str) – Target directory where the file will be stored. (default: “data/”).

Returns:

An instance of cls containing the loaded data, or None if cls is None.

Return type:

T | None

src.data.load_s_curve(n_samples=100, *, noise=0.0, random_state=None)

Generate a synthetic S-curve dataset.

Parameters:

  • n_samples (int) – Number of samples to generate. (default: 100).

  • noise (float) – Standard deviation of Gaussian noise added to the data. (default: 0.0).

  • random_state (int | None) – Seed for reproducibility. (default: None).

Returns:

A tuple (Points, Coordinates) where Points are the 3D data and Coordinates are the unrolled 1D parameters.

Return type:

Tuple[Points, Coordinates]

src.data.load_swiss_roll(n_samples=100, *, noise=0.0, random_state=None, hole=False)

Generate a synthetic Swiss roll dataset.

Parameters:

  • n_samples (int) – Number of samples to generate. (default: 100).

  • noise (float) – Standard deviation of Gaussian noise added to the data. (default: 0.0).

  • random_state (int | None) – Seed for reproducibility. (default: None).

  • hole (bool | None) – Whether to generate the Swiss roll with a hole. (default: False).

Returns:

A tuple (Points, Coordinates) where Points are the 3D data and Coordinates are the unrolled 1D parameters.

Return type:

Tuple[Points, Coordinates]