simulate

glotaran.simulation.simulation.simulate(model: Model, dataset: str, parameters: Parameters, coordinates: dict[str, ArrayLike], clp: xr.DataArray | None = None, noise: bool = False, noise_std_dev: float = 1.0, noise_seed: int | None = None) → xr.Dataset[source]

Simulate a dataset using a model.

Parameters:

  • model (Model) – The model containing the dataset model.

  • dataset (str) – Label of the dataset to simulate

  • parameters (Parameters) – The parameters for the simulation.

  • coordinates (dict[str, ArrayLike]) – A dictionary with the coordinates used for simulation (e.g. time, wavelengths, …).

  • clp (xr.DataArray | None) – A matrix with conditionally linear parameters (e.g. spectra, pixel intensity, …). Will be used instead of the dataset’s global megacomplexes if not None.

  • noise (bool) – Add noise to the simulation.

  • noise_std_dev (float) – The standard deviation for noise simulation.

  • noise_seed (int | None) – The seed for the noise simulation.

Returns:

The simulated dataset.

Return type:

xr.Dataset

Raises:

ValueError – Raised if dataset model has no global megacomplex and no clp are provided.