autoemulate.datasets

Contents

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.