torchcell.datasets.scerevisiae.kuzmin2018.TmfKuzmin2018Dataset

class TmfKuzmin2018Dataset(root: str = 'data/torchcell/tmf_kuzmin2018', subset_n: int | None = None, io_workers: int = 0, transform: Callable[[...], Any] | None = None, pre_transform: Callable[[...], Any] | None = None, **kwargs: Any)

Bases: ExperimentDataset

Triple-mutant fitness experiments from Kuzmin 2018.

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]

Return the experiment model class for this dataset.

property reference_class: type[ExperimentReference]

Return the experiment-reference model class for this dataset.

property raw_file_names: list[str]

Additional Data S1, from the hosted zip.

download() → None

Download the Kuzmin 2018 archive and extract it into the raw directory.

process() → None

Preprocess the raw table and write experiment records to the LMDB store.

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

Clean and reshape the raw Kuzmin table into per-genotype rows.

static create_experiment(dataset_name: str, row: Series, phenotype_reference_std: float) → tuple[FitnessExperiment, FitnessExperimentReference, Publication]

Build the experiment, reference, and publication objects from a data row.