autoemx.config.schema_models.ledger module

class autoemx.config.schema_models.ledger.LedgerConfigs(*, microscope_cfg: MicroscopeConfig, sample_cfg: SampleConfig, measurement_cfg: MeasurementConfig, sample_substrate_cfg: SampleSubstrateConfig, plot_cfg: PlotConfig)

Bases: BaseModel

Typed config bundle persisted in the ledger.

microscope_cfg: MicroscopeConfig

sample_cfg: SampleConfig

measurement_cfg: MeasurementConfig

sample_substrate_cfg: SampleSubstrateConfig

plot_cfg: PlotConfig

model_config = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod drop_legacy_quant_cfg(data: Any) → Any

classmethod move_legacy_exp_std_w_frs(data: Any) → Any

Legacy compatibility: move the standard’s mass fractions from exp_stds_cfg to sample_cfg.

Old ledgers stored them in measurement_cfg.exp_stds_cfg.w_frs.

set_exp_std_w_frs() → LedgerConfigs

Set the composition of an experimental standard from its formula, when not stored yet.

property powder_meas_cfg: PowderMeasurementConfig | None

property bulk_meas_cfg: BulkMeasurementConfig | None

property exp_stds_cfg: ExpStandardsConfig | None

exception autoemx.config.schema_models.ledger.LedgerVersionError

Bases: ValueError

Raised when a ledger written by a newer AutoEMX version cannot be read by the installed one.

class autoemx.config.schema_models.ledger.SampleLedger(*, autoemx_version: str = '1.8.0', sample_id: str, sample_path: str, configs: ~autoemx.config.schema_models.ledger.LedgerConfigs, spectra: ~typing.List[~autoemx.config.schema_models.acquisition.SpectrumEntry], particles: ~typing.List[~autoemx.config.schema_models.acquisition.ParticleInfo] = <factory>, frames: ~typing.List[~autoemx.config.schema_models.frames.FrameRecord] = <factory>, segmentations: ~typing.List[~autoemx.config.schema_models.segmentation.SegmentationConfig] = <factory>, size_measurements: ~typing.List[~autoemx.config.schema_models.particle_stats.SizeMeasurement] = <factory>, size_results: ~typing.List[~autoemx.config.schema_models.particle_stats.ParticleSizeStatsResult] = <factory>, active_size_result: int | None = None, active_quant: int | None = None, quantifications: ~typing.List[~autoemx.config.schema_models.quantification.QuantificationConfig] = <factory>)

Bases: BaseModel

Single-sample ledger with per-spectrum pointers and configuration bundle.

autoemx_version: str

sample_id: str

sample_path: str

configs: LedgerConfigs

spectra: List[SpectrumEntry]

particles: List[ParticleInfo]

frames: List[FrameRecord]

segmentations: List[SegmentationConfig]

size_measurements: List[SizeMeasurement]

size_results: List[ParticleSizeStatsResult]

active_size_result: int | None

active_quant: int | None

quantifications: List[QuantificationConfig]

model_config = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod move_legacy_size_statistics(data: Any) → Any

Legacy compatibility: particle size statistics saved before frames and segmentations were recorded.

classmethod move_legacy_known_phase_mixture(data: Any) → Any

Legacy compatibility: is_known_powder_mixture_meas (powder settings) is now the quantification setting is_known_phase_mixture, stored in the options of each quantification run.

classmethod validate_sample_path(v: str) → str

classmethod validate_active_quant_input(v: Any | None) → Any | None

classmethod validate_active_quant(v: int | None) → int | None

validate_ledger_integrity() → SampleLedger

property size_result: ParticleSizeStatsResult | None

The active particle size statistics result (None if there is none).

frame(frame_id: str) → FrameRecord | None

measurement(measurement_id: int | None) → SizeMeasurement | None

segmentation(segmentation_id: int | None) → SegmentationConfig | None

frames_of(purpose: str | None = None, measurement_id: int | None = None) → List[FrameRecord]

Frames acquired for a purpose (‘eds_search’ or ‘size_stats’), and/or by a measurement.

unique_frame_id(frame_id: str) → str

frame_id, made unique in the ledger with a #2, #3, … suffix (frame acquired again).

add_frame(frame: FrameRecord) → FrameRecord

Add an acquired frame (its id made unique if needed), returned as recorded.

append_segmentation(config: SegmentationConfig) → int

Id of the segmentation with these settings: an existing one, or config added with a new id.

add_frame_segmentation(frame_id: str, result: FrameSegmentation) → None

Add the result of a segmentation of a frame (never replacing one).

next_measurement_id() → int

append_size_result(result: ParticleSizeStatsResult) → ParticleSizeStatsResult

Add a statistics result and make it the active one: it replaces a result computed from the same inputs (measurement, segmentations, frames and particles left out), e.g. recalculated after more EDS frames; otherwise it gets a new id. Returns the result as recorded.

append_quantification_config(quant_config: QuantificationConfig) → None

Append a quantification config, enforcing unique config identifiers.

append_quantification_result(spectrum_index: int, result: QuantificationResult) → None

Append a quantification result to the requested spectrum entry.

classmethod from_json_file(file_path: str | Path) → SampleLedger

Load and validate a ledger from JSON in one call.

Raises:

LedgerVersionError – If the ledger cannot be read because it was written by a newer AutoEMX version.

to_dict(config_key_style: Literal['cfg', 'config'] = 'cfg', *, include_configs: bool = True) → Dict[str, Any]

Serialize ledger to a dict and choose config key suffix style.

to_json_file(file_path: str | Path, *, config_key_style: Literal['cfg', 'config'] = 'cfg', include_configs: bool = True, indent: int = 2) → None

Write ledger to JSON in one call, recording the AutoEMX version that saved it.