explore

R2026b

Class: OptimizationResult

Explore fixed-point implementations found during optimization process

Syntax

explore(result)

explore(result,Name=Value)

solution = explore(result,Name=Value)

Description

explore(result) applies the data types of the best solution found during the optimization process for the OptimizationResult object specified by result. If you have defined tolerances for logged signals in your system, explore opens the Simulation Data Inspector with logging data displayed for further exploration of numeric behavior. By default, the best solution and the first simulation scenario will be applied on the model and explored.

explore(result,Name=Value)specifies options using one or more name-value arguments.

solution = explore(result,Name=Value) returns the optimized fixed-point implementation of the system as an OptimizationSolution object, solution.

Input Arguments

result — Optimization result to explore

OptimizationResult object

Optimization result to explore, specified as an OptimizationResult object.

If the optimization finds a feasible solution, the vector of OptimizationSolution objects contained in the result object is sorted by cost, with the lowest cost (most optimal) solution as the first element of the vector. If the optimization does not find a feasible solution, the vector is sorted by least violation.

Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Example: solution = explore(result,SolutionIndex=1,ScenarioIndex=5,KeepOriginalModelParameters=false);

SolutionIndex — n^th best solution

1 (default) | positive integer

n^th best solution contained in result to apply to the model, specified as a positive integer. By default, the best solution is applied.

If optimization finds a feasible result, the best solution is defined as the solution with minimal cost that meets all behavioral constraints. If optimization finds only infeasible solutions, the best solution is defined as the least-violating solution.

Example: solution = explore(result,SolutionIndex=2);

ScenarioIndex — n^th simulation scenario

1 (default) | positive integer

n^th simulation scenario contained in result. If no simulation scenarios were used for optimization, this value is set to 1.

Example: solution = explore(result,SolutionIndex=2,ScenarioIndex=5);

KeepOriginalModelParameters — Whether to maintain original values of model parameters

false or 0 (default) | true or 1

Whether to maintain original values of model parameters that are altered during the optimization process, specified as a numeric or logical 1 (true) or 0 (false).

A value of true maintains the original model parameters, but may lead to inconsistencies with the results returned by fxpopt. For more information, see Model Configuration Changes Made During Data Type Optimization.

Example: solution = explore(result,KeepOriginalModelParameters=true)

Output Arguments

solution — Optimized fixed-point implementation of the system

OptimizationSolution object

Optimized fixed-point implementation of the system, returned as an OptimizationSolution object containing information related to the optimal fixed-point implementation for the system, including total cost of the implementation and the maximum difference between the baseline and the solution.

Version History

Introduced in R2018a

R2021b: Maintain original values of model parameters that are altered by fxpopt

Use the KeepOriginalModelParameters option of explore to maintain the original values of model configuration parameters during the optimization process.