petab.v1.sampling
Functions related to parameter sampling
Functions
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Creates samples for one parameter based on prior |
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Create |
- petab.v1.sampling.sample_from_prior(prior: tuple[str, list, str, list], n_starts: int) array [source]
Creates samples for one parameter based on prior
- Parameters:
prior – A tuple as obtained from
petab.parameter.get_priors_from_df()
n_starts – Number of samples
- Returns:
Array with sampled values
- petab.v1.sampling.sample_parameter_startpoints(parameter_df: DataFrame, n_starts: int = 100, seed: int | None = None, parameter_ids: Sequence[str] | None = None) array [source]
Create
numpy.array
with starting points for an optimization- Parameters:
parameter_df – PEtab parameter DataFrame
n_starts – Number of points to be sampled
seed – Random number generator seed (see
numpy.random.seed()
)parameter_ids – A sequence of parameter IDs for which to sample starting points. For subsetting or reordering the parameters. Defaults to all estimated parameters.
- Returns:
Array of sampled starting points with dimensions n_startpoints x n_optimization_parameters