pystra.results.SORMResult#

Use it: User guide · Worked example · Theory

class SORMResult(*, method, status, message, n_limit_state_evaluations, variable_names, options=None, failure_probability, beta, form, fit, curvatures, formula, approximations)[source]#

Bases: _ProbabilityResult

Record of a SORM analysis.

failure_probability and beta come from formula, Breitung’s asymptotic formula. approximations gives each formula’s failure probability by name: "breitung" and "modified_breitung" (Hohenbichler and Rackwitz’s modification). An entry is None when the fitted curvatures leave that formula undefined; if the primary formula is undefined, the status is "not_converged" and there is no estimate.

form#

The FORM design point that the fit is built on.

Type:: FORMResult

fit#

Curve fitting through the Hessian, or point fitting on the surface.

Type:: {“curve”, “point”}

curvatures#

Curve fitting: the sorted principal curvatures, shape (n - 1,). Point fitting: the curvatures on the negative and positive side of each principal axis, as rows of shape (2, n - 1).

Type:: ndarray

formula#

The approximation reported as the estimate.

Type:: str

approximations#

Failure probability from each formula.

Type:: Mapping[str, float or None]

Methods

summary

Return a plain-text report of the principal results.

property converged: bool#: Whether the method met its termination criteria.

summary()#

Return a plain-text report of the principal results.

Return type:: str