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 |
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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
- prior – A tuple as obtained from
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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