autoemulate.datasets#
- fetch_data(dataset, split=False, test_size=0.2, random_state=42)[source]#
Fetch a dataset by name.
- Parameters:
dataset (str) –
Dataset to load. Can be any of the following strings:
cardiac1: ionic atrial cell model data from LH sampling.
cardiac2: isotonic contraction ventricular cell model, no LH sampling.
cardiac3: CircAdapt: four-chamber pressure and volume CircAdapt ODE model from LH sampling.
cardiac4: four chamber: 3D-0D four-chamber electromechanics model to predict pressure and volume biomarkers for cardiac function.
cardiac5: passive mechanics: inflated volumes and mean atrial and ventricular fiber strains for a passive inflation.
cardiac6: tissue electrophysiology: predict total atrial and ventricular activation times with an Eikonal model.
climate1: GENIE model: predict climate variables SAT, ACC, VEGC, SOILC, MAXPMOC, OCN_O2, fCaCO3, SIAREA_S.
engineering1: Cantilever truss simulation.
split (bool, optional) – Whether to split the data into training and testing sets. Default is False.
test_size (float, optional) – The proportion of the dataset to include in the test split. Default is 0.2.
random_state (int, optional) – Controls the shuffling applied to the data before applying the split. Default is 42.
- Returns:
X (array-like) – Simulation parameters / inputs.
y (array-like) – Simulation outputs.