petitRADTRANS.sbi.preprocessing

petitRADTRANS.sbi.preprocessing#

Preprocessing helpers and normalization metadata for SBI observation blocks.

Classes#

`BlockNormalizationStats`	Normalization statistics for one observation block family.
`TaskPreprocessingMetadata`	Serializable preprocessing metadata for an SBI task family.

Functions#

`compute_block_normalization_stats`(→ dict[str, ...)	Compute per-block normalization statistics from training observations.
`fit_task_preprocessing`(→ TaskPreprocessingMetadata)	Fit preprocessing statistics from training observation blocks.
`normalize_observation_block`(...)	Normalize one observation block with fitted preprocessing statistics.
`normalize_observation_blocks`(...)	Normalize a list of observation blocks.

Module Contents#

class petitRADTRANS.sbi.preprocessing.BlockNormalizationStats#

Normalization statistics for one observation block family.

name: str#

modality: str#

value_mean: float#

value_std: float#

uncertainty_mean: float | None = None#

uncertainty_std: float | None = None#

coordinate_mean: float | None = None#

coordinate_std: float | None = None#

n_samples: int = 0#

n_values: int = 0#

value_median: float | None = None#

value_iqr: float | None = None#

uncertainty_median: float | None = None#

uncertainty_iqr: float | None = None#

value_median_per_wl: list[float] | None = None#

value_iqr_per_wl: list[float] | None = None#

uncertainty_median_per_wl: list[float] | None = None#

uncertainty_iqr_per_wl: list[float] | None = None#

log_median_flux: float | None = None#

to_payload() → dict[str, Any]#

class petitRADTRANS.sbi.preprocessing.TaskPreprocessingMetadata#

Serializable preprocessing metadata for an SBI task family.

version: str#

blocks: Mapping[str, BlockNormalizationStats]#

metadata: Mapping[str, Any]#

to_payload() → dict[str, Any]#

classmethod from_payload(payload: Mapping[str, Any]) → TaskPreprocessingMetadata#

petitRADTRANS.sbi.preprocessing.compute_block_normalization_stats(blocks: list[petitRADTRANS.sbi.observation.ObservationBlock]) → dict[str, BlockNormalizationStats]#: Compute per-block normalization statistics from training observations.

petitRADTRANS.sbi.preprocessing.fit_task_preprocessing(training_observations: list[list[petitRADTRANS.sbi.observation.ObservationBlock]], version: str = '0.5.0', metadata: Mapping[str, Any] | None = None) → TaskPreprocessingMetadata#: Fit preprocessing statistics from training observation blocks.

petitRADTRANS.sbi.preprocessing.normalize_observation_block(block: petitRADTRANS.sbi.observation.ObservationBlock, preprocessing_metadata: TaskPreprocessingMetadata) → petitRADTRANS.sbi.observation.ObservationBlock#

Normalize one observation block with fitted preprocessing statistics.

Uses robust (median/IQR) normalization for values and uncertainties when available, falling back to mean/std for backward compatibility with older preprocessing metadata. Coordinates always use mean/std normalization.

petitRADTRANS.sbi.preprocessing.normalize_observation_blocks(blocks: list[petitRADTRANS.sbi.observation.ObservationBlock], preprocessing_metadata: TaskPreprocessingMetadata) → list[petitRADTRANS.sbi.observation.ObservationBlock]#: Normalize a list of observation blocks.