petab.sampling

Functions related to parameter sampling

Functions

sample_from_prior(prior, list, str, list], …) Creates samples for one parameter based on prior
sample_parameter_startpoints(parameter_df, …) Create numpy.array with starting points for an optimization
petab.sampling.sample_from_prior(prior: Tuple[str, list, str, list], n_starts: int) → numpy.array

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.sampling.sample_parameter_startpoints(parameter_df: pandas.core.frame.DataFrame, n_starts: int = 100, seed: int = None) → numpy.array

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)
Returns:

Array of sampled starting points with dimensions n_startpoints x n_optimization_parameters