xpectra.TrustConfig

class xpectra.TrustConfig(routes: 'tuple[str, ...]'=('norm', 'deriv1', 'deriv2'), model_names: 'tuple[str, ...]'=('Logistic Regression', 'SVM (RBF)', 'Random Forest (200)', 'XGBoost (100)', 'MLP (128, 64)'), calibration_methods: 'tuple[str, ...]'=('none', 'sigmoid', 'isotonic', 'temperature'), cv_folds: 'int' = 5, test_size: 'float' = 0.2, ece_bins: 'int' = 15, dedupe_spectra: 'bool' = True, pca_components_ood: 'int' = 20, knn_k: 'int' = 5, target_coverage: 'float' = 0.9, pca_components_ssl: 'int' = 50, self_train_threshold: 'float' = 0.9, self_train_max_iter: 'int' = 3, label_spread_neighbors: 'int' = 10, carbonyl_band: 'tuple[float, float]'=(1650.0, 1800.0), reference_band: 'tuple[float, float]'=(1420.0, 1470.0), random_state: 'int' = 42, processed_dir: 'Path' = <factory>, results_dir: 'Path' = <factory>, figures_dir: 'Path' = <factory>, cache_dir: 'Path' = <factory>)

Bases: object

Parameters:

• routes (tuple[str, ...])

• model_names (tuple[str, ...])

• calibration_methods (tuple[str, ...])

• cv_folds (int)

• test_size (float)

• ece_bins (int)

• dedupe_spectra (bool)

• pca_components_ood (int)

• knn_k (int)

• target_coverage (float)

• pca_components_ssl (int)

• self_train_threshold (float)

• self_train_max_iter (int)

• label_spread_neighbors (int)

• carbonyl_band (tuple[float, float])

• reference_band (tuple[float, float])

• random_state (int)

• processed_dir (Path)

• results_dir (Path)

• figures_dir (Path)

• cache_dir (Path)

__init__(routes=('norm', 'deriv1', 'deriv2'), model_names=('Logistic Regression', 'SVM (RBF)', 'Random Forest (200)', 'XGBoost (100)', 'MLP (128, 64)'), calibration_methods=('none', 'sigmoid', 'isotonic', 'temperature'), cv_folds=5, test_size=0.2, ece_bins=15, dedupe_spectra=True, pca_components_ood=20, knn_k=5, target_coverage=0.9, pca_components_ssl=50, self_train_threshold=0.9, self_train_max_iter=3, label_spread_neighbors=10, carbonyl_band=(1650.0, 1800.0), reference_band=(1420.0, 1470.0), random_state=42, processed_dir=<factory>, results_dir=<factory>, figures_dir=<factory>, cache_dir=<factory>)

Parameters:

• routes (tuple[str, ...])

• model_names (tuple[str, ...])

• calibration_methods (tuple[str, ...])

• cv_folds (int)

• test_size (float)

• ece_bins (int)

• dedupe_spectra (bool)

• pca_components_ood (int)

• knn_k (int)

• target_coverage (float)

• pca_components_ssl (int)

• self_train_threshold (float)

• self_train_max_iter (int)

• label_spread_neighbors (int)

• carbonyl_band (tuple[float, float])

• reference_band (tuple[float, float])

• random_state (int)

• processed_dir (Path)

• results_dir (Path)

• figures_dir (Path)

• cache_dir (Path)

Return type:

None

Methods

__init__([routes, model_names, ...])
ensure_dirs()

Attributes

calibration_methods
carbonyl_band
cv_folds
dedupe_spectra
ece_bins
knn_k
label_spread_neighbors
model_names
pca_components_ood
pca_components_ssl
random_state
reference_band
routes
self_train_max_iter
self_train_threshold
target_coverage
test_size
processed_dir
results_dir
figures_dir
cache_dir

routes: tuple[str, ...] = ('norm', 'deriv1', 'deriv2')

model_names: tuple[str, ...] = ('Logistic Regression', 'SVM (RBF)', 'Random Forest (200)', 'XGBoost (100)', 'MLP (128,64)')

calibration_methods: tuple[str, ...] = ('none', 'sigmoid', 'isotonic', 'temperature')

cv_folds: int = 5

test_size: float = 0.2

ece_bins: int = 15

dedupe_spectra: bool = True

pca_components_ood: int = 20

knn_k: int = 5

target_coverage: float = 0.9

pca_components_ssl: int = 50

self_train_threshold: float = 0.9

self_train_max_iter: int = 3

label_spread_neighbors: int = 10

carbonyl_band: tuple[float, float] = (1650.0, 1800.0)

reference_band: tuple[float, float] = (1420.0, 1470.0)

random_state: int = 42

processed_dir: Path

results_dir: Path

figures_dir: Path

cache_dir: Path

ensure_dirs()

Return type:

None