pystra.calibration.normalized.CodeCalibrationResult#

Use it: User guide · Worked example · Theory

class CodeCalibrationResult(live_load_ratios, dead_load_ratios, factors, target_beta, cases, _model)[source]#

Bases: object

Snapshot of a factor-set study, with every grid point retained.

Cases are ordered by dead-load ratio then live-load ratio. beta is a fresh array with shape (n_dead_ratios, n_live_ratios); failed cases are NaN. The probability-model snapshot is held privately and returned by copy.

Methods

to_frame

Return an independent table including designs and failure status.

property model: NormalizedReliabilityModel#: Copy of the probability model used for this result.

property converged: bool#: Whether every grid-point analysis converged.

property beta: ndarray#: Normal-equivalent indices; failed cases are explicitly NaN.

to_frame()[source]#

Return an independent table including designs and failure status.

Return type:: DataFrame