pystra.results.FORMResult#

Use it: User guide · Worked example · Theory

class FORMResult(*, method, status, message, n_limit_state_evaluations, variable_names, options=None, failure_probability, beta, design_index, design_point_x, design_point_u, alpha, standard_space, iterations, limit_state_error, direction_error)[source]#

Bases: _ProbabilityResult

Record of a FORM analysis.

beta is normal-equivalent, \(-\Phi^{-1}(p_f)\). design_index is the signed distance of the design point from the origin in standard_space; the two are equal in normal space and differ in Student-t standard space.

design_index#

Signed distance of the design point in standard_space.

Type:: float or None

design_point_x#

Design point in physical coordinates and original units.

Type:: ndarray or None

design_point_u#

The same point in standard coordinates.

Type:: ndarray or None

alpha#

Unit vector from the origin towards the design point in standard coordinates, the FORM importance direction.

Type:: ndarray or None

standard_space#

"normal" or "student_t".

Type:: str

iterations#

Iterations performed.

Type:: int

limit_state_error, direction_error

The final convergence residuals.

Type:: float or None

An unconverged record has no probability, index, design point or

direction; its diagnostics remain available.

Methods

`from_analysis`	Copy a completed solver's numerical results and diagnostics.
`summary`	Return a plain-text report of the principal results.
`to_dataframe`	Return the design point and direction as a table by variable.

classmethod from_analysis(analysis)[source]#

Copy a completed solver’s numerical results and diagnostics.

Return type:: FORMResult

to_dataframe()[source]#

Return the design point and direction as a table by variable.

Returns:: Columns design_point_x, design_point_u and alpha, indexed by variable name.
Return type:: DataFrame

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

summary()#

Return a plain-text report of the principal results.

Return type:: str