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voiage

voiage.schema.ParameterSet

Container for parameter samples from a probabilistic sensitivity analysis.

Attributes

Section titled “Attributes”

frame : pl.DataFrame Wide Polars frame with one Float64 column per parameter in declared order. Column names are the parameter names. Sample count is the frame height.

Examples

Section titled “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

Section titled “Methods”

from_polars

Section titled “from_polars”
from_polars([positional or keyword] cls: None = None, [positional or keyword] frame: pl.DataFrame = None) -> ParameterSet

Create a ParameterSet from a wide Polars frame.

Parameters:

  • cls
  • frame pl.DataFrame

Returns: ParameterSet

to_polars

Section titled “to_polars”
to_polars([positional or keyword] self: ParameterSet = None) -> pl.DataFrame

Return a deep copy of the wide Polars frame.

Parameters:

  • self ParameterSet

Returns: pl.DataFrame

copy

Section titled “copy”
copy([positional or keyword] self: ParameterSet = None) -> ParameterSet

Return a deep copy of the ParameterSet.

Parameters:

  • self ParameterSet

Returns: ParameterSet

subset_by_parameters

Section titled “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

Section titled “from_numpy_or_dict”
from_numpy_or_dict([positional or keyword] cls: None = None, [positional or keyword] parameters: np.ndarray | dict[str, np.ndarray] | JaxArray | dict[str, JaxArray] = 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

Section titled “Returns”

ParameterSet: A new ParameterSet instance

Parameters:

  • cls
  • parameters np.ndarray | dict[str, np.ndarray] | JaxArray | dict[str, JaxArray]

Returns: ParameterSet

from_jax

Section titled “from_jax”
from_jax([positional or keyword] cls: None = None, [positional or keyword] parameters: JaxArray | dict[str, JaxArray] = 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

Section titled “Returns”

ParameterSet: A new ParameterSet instance

Parameters:

  • cls
  • parameters JaxArray | dict[str, JaxArray]

Returns: ParameterSet