pystra.calibration.factors.FactorCalibrationProblem#

Use it: User guide · Worked example · Theory

class FactorCalibrationProblem(cases, *, nominal_values, design_parameter)[source]#

Bases: object

Explicit inputs to the separable resistance-scale factor methods.

Parameters:

  • cases (LoadCombination) – Cases with explicit roles and leading-action metadata.

  • nominal_values (Mapping[str, float]) – Positive nominal values for exactly the random-variable role names.

  • design_parameter (str) – Name of a common Constant multiplying the resistance term.

Notes

Inputs are snapshotted. Numerical operations use named coordinates and arrays; no DataFrame carries state between stages. The default design rule is z = load_effect / resistance_effect, evaluated at unit z with the opposite side set to zero. Every computed design is checked in the full limit state to reject incompatible decompositions.

Methods

design_from_point

Solve the separable design rule and verify its full residual.
property cases: LoadCombination#

Copy of the snapshotted cases.

property nominal_values: Mapping[str, float]#

Read-only nominal values in role order.

design_from_point(case_name, values)[source]#

Solve the separable design rule and verify its full residual.

Return type:

float