EvaluatedValues

Symbolica documentation for getting started, symbolic expressions, numerical evaluation, pattern matching, and APIs in Python and Rust.

EvaluatedValues

class EvaluatedValues

Numerical values returned by a custom model evaluator.

Values are complex numbers represented as (real, imaginary) pairs and are applied atomically to the model after the callback completes.

Examples

from symbolica.community import hepkit as hep
values = hep.EvaluatedValues(couplings={"GC_1": (0.3, 0.0)})

Parameters

• internal_parameters (dict[str, tuple[float, float]], optional) Evaluated internal parameter values keyed by name.
• couplings (dict[str, tuple[float, float]], optional) Evaluated coupling values keyed by name.

Attributes

Name	Description
couplings	Return the evaluated couplings keyed by name.
internal_parameters	Return the evaluated internal parameters keyed by name.

couplings

EvaluatedValues.couplings: builtins.dict[builtins.str, tuple[builtins.float, builtins.float]]

Return the evaluated couplings keyed by name.

Examples

Using the setup in the EvaluatedValues class example:

values = hep.EvaluatedValues(couplings={"GC_1": (0.3, 0.0)})
assert values.couplings["GC_1"] == (0.3, 0.0)

internal_parameters

EvaluatedValues.internal_parameters: builtins.dict[builtins.str, tuple[builtins.float, builtins.float]]

Return the evaluated internal parameters keyed by name.

Examples

Using the setup in the EvaluatedValues class example:

values = hep.EvaluatedValues(internal_parameters={"alpha": (0.1, 0.0)})
assert values.internal_parameters["alpha"] == (0.1, 0.0)

Methods

Name	Description
__new__	Create values returned by a custom model evaluator.

__new__

EvaluatedValues.__new__(
    *,
    internal_parameters: typing.Optional[typing.Mapping[builtins.str, tuple[builtins.float, builtins.float]]] = None,
    couplings: typing.Optional[typing.Mapping[builtins.str, tuple[builtins.float, builtins.float]]] = None,
) -> EvaluatedValues

Create values returned by a custom model evaluator.

Examples

Using the setup in the EvaluatedValues class example:

values = hep.EvaluatedValues(couplings={"GC_1": (1.0, 0.0)})

Parameters

• internal_parameters (dict[str, tuple[float, float]] or None) Evaluated internal parameters keyed by name.
• couplings (dict[str, tuple[float, float]] or None) Evaluated couplings keyed by name.