parameter_space

bojaxns.parameter_space

Module Contents

class ContinuousPrior[source]

Bases: pydantic.BaseModel

type: Literal[continuous_prior] = 'continuous_prior'[source]

lower: float[source]

upper: float[source]

mode: float[source]

uncert: confloat(gt=0.0)[source]

class IntegerPrior[source]

Bases: pydantic.BaseModel

type: Literal[integer_prior] = 'integer_prior'[source]

lower: int[source]

upper: int[source]

mode: float[source]

uncert: confloat(gt=0.0)[source]

class CategoricalPrior[source]

Bases: pydantic.BaseModel

type: Literal[categorical_prior] = 'categorical_prior'[source]

probs: List[confloat(ge=0.0)][source]

class Parameter[source]

Bases: pydantic.BaseModel

name: str[source]

prior: ParamPrior[source]

class ParameterSpace[source]

Bases: pydantic.BaseModel

parameters: List[Parameter][source]

unique_parameters(value)[source]

build_prior_model(parameter_space)[source]

Constructs a prior model given the parameter space.

Parameters:: parameter_space (ParameterSpace) –

Returns: