types module

class corrdim.types.CurveResult(sequence_length: 'int', epsilons: 'np.ndarray', corrints: 'np.ndarray')

Bases: object

Parameters:

• sequence_length (int)

• epsilons (numpy.ndarray)

• corrints (numpy.ndarray)

corrints: numpy.ndarray

epsilons: numpy.ndarray

sequence_length: int

class corrdim.types.DimensionResult(sequence_length: 'int', epsilons: 'np.ndarray', corrints: 'np.ndarray', corrdim: 'float', fit_r2: 'float', epsilons_linear_region: 'np.ndarray', corrints_linear_region: 'np.ndarray', linear_region_bounds: 'Tuple[Optional[float], Optional[float]]' = (None, None))

Bases: object

Parameters:

• sequence_length (int)

• epsilons (numpy.ndarray)

• corrints (numpy.ndarray)

• corrdim (float)

• fit_r2 (float)

• epsilons_linear_region (numpy.ndarray)

• corrints_linear_region (numpy.ndarray)

• linear_region_bounds (Tuple[float | None, float | None])

corrdim: float

corrints: numpy.ndarray

corrints_linear_region: numpy.ndarray

epsilons: numpy.ndarray

epsilons_linear_region: numpy.ndarray

fit_r2: float

linear_region_bounds: Tuple[float | None, float | None] = (None, None)

sequence_length: int

class corrdim.types.ProgressiveCurveResult(sequence_length: 'int', epsilons: 'np.ndarray', corrints_progressive: 'np.ndarray')

Bases: object

Parameters:

• sequence_length (int)

• epsilons (numpy.ndarray)

• corrints_progressive (numpy.ndarray)

corrints_progressive: numpy.ndarray

epsilons: numpy.ndarray

sequence_length: int

class corrdim.types.ProgressiveDimensionResult(sequence_length, epsilons, skip_prefix_tokens, measure_every_tokens, by_prefix)

Bases: object

Correlation dimensions fitted at subsampled prefix indices after one progressive pass.

Parameters:

• sequence_length (int)

• epsilons (numpy.ndarray)

• skip_prefix_tokens (int)

• measure_every_tokens (int)

• by_prefix (Dict[int, DimensionResult])

by_prefix: Dict[int, DimensionResult]

property corrdims: Dict[int, float]

epsilons: numpy.ndarray

measure_every_tokens: int

sequence_length: int

skip_prefix_tokens: int