xpectra.pipeline.config

Configuration shared by the training and prediction pipelines.

Classes

PreprocessConfig([label_column, ...])

Notebook preprocessing defaults, exposed as CLI-overridable settings.

class xpectra.pipeline.config.PreprocessConfig(label_column='type', sample_id_column='sample_id', unknown_study='kedzierski_2019_u', labeled_studies=('jung_2018', 'kedzierski_2019', 'frond_2021', 'villegas_camacho_2024_c4'), external_studies=('openspecy', 'simple', 'awi2024'), denoising_method='wavelet', baseline_method='aspls', normalization_method='spectral_moments', interpolate_method='zero', flat_windows=((1880.0, 1900.0), (2400.0, 2700.0)), exclude_regions=((0.0, 679.0), (3201.0, 5000.0)), interpolate_regions=((2300.0, 2380.0),), wn_min=680.0, wn_max=3100.0, resolution=2.0, descending=True, combine_method='pchip', derivative_window_length=15, derivative_polyorder=3, derivative_delta=1.0, random_state=42, test_size=0.2, n_jobs=-1)

Bases: object

Notebook preprocessing defaults, exposed as CLI-overridable settings.

Parameters:

• label_column (str)

• sample_id_column (str)

• unknown_study (str)

• labeled_studies (tuple[str, ...])

• external_studies (tuple[str, ...])

• denoising_method (str)

• baseline_method (str)

• normalization_method (str)

• interpolate_method (str)

• flat_windows (tuple[tuple[float, float], ...])

• exclude_regions (tuple[tuple[float, float], ...])

• interpolate_regions (tuple[tuple[float, float], ...])

• wn_min (float)

• wn_max (float)

• resolution (float)

• descending (bool)

• combine_method (str)

• derivative_window_length (int)

• derivative_polyorder (int)

• derivative_delta (float)

• random_state (int)

• test_size (float)

• n_jobs (int)

label_column: str = 'type'

sample_id_column: str = 'sample_id'

unknown_study: str = 'kedzierski_2019_u'

labeled_studies: tuple[str, ...] = ('jung_2018', 'kedzierski_2019', 'frond_2021', 'villegas_camacho_2024_c4')

external_studies: tuple[str, ...] = ('openspecy', 'simple', 'awi2024')

denoising_method: str = 'wavelet'

baseline_method: str = 'aspls'

normalization_method: str = 'spectral_moments'

interpolate_method: str = 'zero'

flat_windows: tuple[tuple[float, float], ...] = ((1880.0, 1900.0), (2400.0, 2700.0))

exclude_regions: tuple[tuple[float, float], ...] = ((0.0, 679.0), (3201.0, 5000.0))

interpolate_regions: tuple[tuple[float, float], ...] = ((2300.0, 2380.0),)

wn_min: float = 680.0

wn_max: float = 3100.0

resolution: float = 2.0

descending: bool = True

combine_method: str = 'pchip'

derivative_window_length: int = 15

derivative_polyorder: int = 3

derivative_delta: float = 1.0

random_state: int = 42

test_size: float = 0.2

n_jobs: int = -1

to_dict()

Return type:

dict[str, Any]