pystra.results.SimulationResult

Use it: User guide · Worked example · Theory

class SimulationResult(*, method, status, message, n_limit_state_evaluations, variable_names, options=None, failure_probability, beta, coefficient_of_variation, n_samples, diagnostics=dict())

Bases: _ProbabilityResult

Record of a simulation estimate.

Returned by crude Monte Carlo, importance sampling, line sampling and subset simulation.

coefficient_of_variation

Estimated coefficient of variation of the failure probability; infinite when no failure was observed. Subset simulation’s value ignores correlation between Markov-chain samples, so it is a lower bound.

Type:

float

n_samples

Samples used: points for crude Monte Carlo and importance sampling, lines for line sampling, and the total over all levels for subset simulation.

Type:

int

diagnostics

Method-specific details. Crude Monte Carlo and importance sampling give history: n_samples, failure_probability and coefficient_of_variation after each block. Importance and line sampling give form, the FORM record they sample about; line sampling adds direction. Subset simulation gives thresholds, conditional_probabilities, n_levels and samples_per_level.

Type:

Mapping

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