torchcell.datasets.scerevisiae.mota2024.EnvChemgenMota2024Dataset

class EnvChemgenMota2024Dataset(root: str = 'data/torchcell/env_chemgen_mota2024', io_workers: int = 0, transform: Callable[[...], Any] | None = None, pre_transform: Callable[[...], Any] | None = None, **kwargs: Any)

Bases: ExperimentDataset

Acetic/butyric/octanoic acid chemogenomic env x geno -> ordinal susceptibility.

organism: ClassVar[Organism] = 'scerevisiae'

each loader declares its own, the build’s organism switch reads it off the class (dataset_organism), and a loader that forgot it is refused by name instead of inheriting an organism it may not have.

Type:

The host organism every record describes. Annotated here WITHOUT a value

property experiment_class: type[Experiment]

Experiment schema class produced by this dataset.

property reference_class: type[ExperimentReference]

Experiment-reference schema class produced by this dataset.

property raw_file_names: list[str]

The three BMC supplementary spreadsheets required before processing.

download() → None

Take the three spreadsheets from the raw mirror; verify each pinned sha256.

The mirror is the source of record. The Springer ESM CDN is scriptable and is used only when the mirror does not hold the file yet, so a rebuild does not depend on a live URL surviving.

process() → None

Parse the three acid spreadsheets into ordinal records; write LMDB + drop log.

preprocess_raw(df: Any, preprocess: dict[str, Any] | None = None) → Any

Preprocessing is handled inside process() for this dataset.

create_experiment() → None

Experiment construction is handled inline in process() for this dataset.