pystra.results.StrongMaximumResult#

Use it: User guide · Worked example · Theory

class StrongMaximumResult(*, method, status, message, n_limit_state_evaluations, variable_names, options=None, has_competing_points, design_point_u, design_index, radius, point_number, confidence_level, cap_probability, points_u, points_x, limit_state_values, regions)[source]#

Bases: _Result

Record of a Strong Maximum Test, a diagnostic of a FORM design point.

It is not a probability estimate, and finding no competing region does not certify the design point.

has_competing_points#

Whether the far failure region contains sample points.

Type:: bool

design_point_u#

The candidate design point in standard coordinates.

Type:: ndarray

design_index#

Its distance from the origin.

Type:: float

radius#

Radius of the test sphere.

Type:: float

point_number#

Points sampled on the sphere.

Type:: int

confidence_level#

Nominal probability of detecting the reference cap.

Type:: float

cap_probability#

Probability that one point falls in the reference cap.

Type:: float

points_u, points_x

The sphere points in standard and physical coordinates, one per row.

Type:: ndarray

limit_state_values#

Limit-state value at each point.

Type:: ndarray

regions#

Boolean masks over the points: far_failure, near_failure, far_safe and near_safe.

Type:: Mapping[str, ndarray]

Methods

`points`	Return the points of one region as rows.
`summary`	Return a plain-text report of the principal results.

points(region='far_failure', space='u')[source]#

Return the points of one region as rows.

Parameters:

region (str) – far_failure, near_failure, far_safe or near_safe.
space (str) – Standard or physical coordinates.

Return type:

ndarray

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

summary()#

Return a plain-text report of the principal results.

Return type:: str