voiage.schema.ParameterSet

Container for parameter samples from a probabilistic sensitivity analysis.

Attributes

dataset : xarray.Dataset Canonical xarray Dataset with n_samples as the sample dimension and one data variable per parameter.

Examples

>>> import numpy as np >>> from voiage.schema import ParameterSet >>> params = ParameterSet.from_numpy_or_dict({“cost”: np.array([1.0, 2.0])}) >>> params.parameter_names [‘cost’]

Methods

from_dataset

from_dataset([positional or keyword] cls: None = None, [positional or keyword] dataset: xr.Dataset = None) -> ParameterSet

Create a ParameterSet from a canonical xarray Dataset.

Parameters:

• cls
• dataset xr.Dataset

Returns: ParameterSet

to_dataset

to_dataset([positional or keyword] self: ParameterSet = None) -> xr.Dataset

Return a deep copy of the canonical xarray Dataset.

Parameters:

• self ParameterSet

Returns: xr.Dataset

copy

copy([positional or keyword] self: ParameterSet = None) -> ParameterSet

Return a deep copy of the ParameterSet.

Parameters:

• self ParameterSet

Returns: ParameterSet

subset_by_parameters

subset_by_parameters([positional or keyword] self: ParameterSet = None, [positional or keyword] parameter_names: Sequence[str] = None) -> ParameterSet

Return a new ParameterSet containing only the requested parameters.

Parameters:

• self ParameterSet
• parameter_names Sequence[str]

Returns: ParameterSet

from_numpy_or_dict

from_numpy_or_dict([positional or keyword] cls: None = None, [positional or keyword] parameters: Union[np.ndarray, dict[str, np.ndarray], jnp.ndarray, dict[str, jnp.ndarray]] = None) -> ParameterSet

Create a ParameterSet from a numpy/JAX array or dictionary.

Args: parameters: Either a 2D array of shape (n_samples, n_parameters) or a dictionary mapping parameter names to 1D arrays. Supports both NumPy and JAX arrays.

Returns

ParameterSet: A new ParameterSet instance

Parameters:

• cls
• parameters Union[np.ndarray, dict[str, np.ndarray], jnp.ndarray, dict[str, jnp.ndarray]]

Returns: ParameterSet

from_jax

from_jax([positional or keyword] cls: None = None, [positional or keyword] parameters: Union[jnp.ndarray, dict[str, jnp.ndarray]] = None) -> ParameterSet

Create a ParameterSet from a JAX array or dictionary.

Args: parameters: Either a 2D JAX array of shape (n_samples, n_parameters) or a dictionary mapping parameter names to 1D JAX arrays

Returns

ParameterSet: A new ParameterSet instance

Parameters:

• cls
• parameters Union[jnp.ndarray, dict[str, jnp.ndarray]]

Returns: ParameterSet