Inheritance diagram for NonDAdaptImpSampling:
Public Member Functions | |
| NonDAdaptImpSampling (Model &model, int samples, int seed, short sampling_type, const bool cdf_flag, const bool x_space_data, const bool x_space_model, const bool bounded_model) | |
| constructor | |
| ~NonDAdaptImpSampling () | |
| destructor | |
| void | quantify_uncertainty () |
| failure. | |
| void | initialize (const RealVectorArray &initial_points, int resp_fn, const Real &initial_prob, const Real &failure_threshold) |
| initial probability to refine, and flags to control transformations | |
| void | initialize (const RealVector &initial_point, int resp_fn, const Real &initial_prob, const Real &failure_threshold) |
| initial probability to refine, and flags to control transformations | |
| const Real & | get_probability () |
| returns the probability calculated by the importance sampling | |
Private Member Functions | |
| void | converge_cov () |
| until coefficient of variation converges | |
| void | converge_probability () |
| until probability converges | |
| void | select_init_rep_points (const RealVectorArray &samples) |
| select representative points from initial set of samples | |
| void | select_rep_points (const RealVectorArray &samples) |
| select representative points from a set of samples | |
| void | calculate_rep_weights () |
| calculate relative weights of representative points | |
| void | generate_samples (RealVectorArray &samples) |
| generate a set of samples based on multimodal sampling density | |
| void | calculate_statistics (const RealVectorArray &samples, const size_t &total_sample_number, Real &probability_sum, Real &probability, bool cov_flag, Real &variance_sum, Real &coeff_of_variation) |
| the coefficent of variation (if requested) | |
Private Attributes | |
| short | importanceSamplingType |
| integration type (is, ais, mmais) provided by input specification | |
| bool | invertProb |
| flag for inversion of probability values using 1.-p | |
| size_t | numRepPoints |
| the number of representative points around which to sample | |
| size_t | respFn |
| the response function in the model to be sampled | |
| RealVectorArray | initPoints |
| the original set of samples passed into the MMAIS routine | |
| RealVectorArray | repPoints |
| the set of representative points around which to sample | |
| RealVector | repWeights |
| the weight associated with each representative point | |
| RealVector | designPoint |
| design point at which uncertain space is being sampled | |
| bool | transInitPoints |
| initial points | |
| bool | transPoints |
| before evaluation | |
| bool | useModelBounds |
| flag to control if the sampler should respect the model bounds | |
| Real | initProb |
| the initial probability (from FORM or SORM) | |
| Real | finalProb |
| the final calculated probability (p) | |
| Real | failThresh |
| the failure threshold (z-bar) for the problem. | |
The NonDAdaptImpSampling implements the multi-modal adaptive importance sampling used for reliability calculations. (eventually we will want to broaden this). Need to add more detail to this description.
| void initialize | ( | const RealVectorArray & | initial_points, | |
| int | resp_fn, | |||
| const Real & | initial_prob, | |||
| const Real & | failure_threshold | |||
| ) |
initial probability to refine, and flags to control transformations
Initializes data using a set of starting points.
| void initialize | ( | const RealVector & | initial_point, | |
| int | resp_fn, | |||
| const Real & | initial_prob, | |||
| const Real & | failure_threshold | |||
| ) |
initial probability to refine, and flags to control transformations
Initializes data using only one starting point.
1.5.1