Introduction

C-API to approximate response values based on their best metamodel using an optiSLang monitoring database file (*.omdb). Version 2.0 of the MOPSolver API was introduced to allow approximation of criteria values.

This API provides interfaces to approximate new desigs with the best metamodels:

Approximate the active response values (e.g. see dmop2_solve())

From the .omdb file, the following information can be extracted:

Names of inputs, responses and criteria (see dmop2_getNames() and dmop2_getNamesWithDelimiter())
Number of the inputs, responses and criteria (see dmop2_getDimensions())
Bounds of the input parameters (see dmop2_getInputBounds() and dmop2_getInputBoundsPerParameter())
Reference value per parameter (see dmop2_getReferenceValuePerParameter())
CoP values per response (see dmop2_getCoPValuesPerResponse())
Filtered states per response (see dmop2_getFilteredStatesPerResponse()) Based on the approximated designs, related information can be extracted via this API:
Gradient values per response (see dmop_gradients_per_response())
Error values per response (see dmop_errors_per_response() and dmop_errors_per_response_extrapolate())
Density values per response (see dmop_density_per_response() and dmop_density_per_response_extrapolate())

Usage example (using a C++ compiler)

#include <cstdlib>
#include <cstring>
#include <iostream>
#include <vector>
 
#include <mopsolver_api2.h>
 
int main( int argc, char *argv[] )
{
    if( argc != 2 )
    {
        std::cout << "\nUsage: " << argv[0] << " " << "[path/to/]file.omdb" << std::endl;
        return EXIT_FAILURE;
    }
 
    // using argv[1] as the path to the optiSLang monitoring database file
    const char *omdb = argv[1];
 
 
    // use flags to specify the dimensions you want to retrieve
    unsigned int flags = DIM_INPUTS | DIM_RESPONSES | DIM_CRITERIA;
    // each set flag adds 1 to the required size for the preallocated pointer
    unsigned int size_dimensions = 3;
    std::unique_ptr<unsigned int[]> dimensions (new unsigned int[size_dimensions]);
    // for the return order, see the order of DMOP2_DIMENSION_FLAG (mopsolver_api2_shared.h)
    dmop2_getDimensions( omdb, flags, dimensions.get(), size_dimensions );
 
    unsigned int nInputs = dimensions[0];
    unsigned int nResponses = dimensions[1];
    unsigned int nCriteria = dimensions[2];
 
    // print the number of active inputs and outputs
    std::cout << std::endl;
    std::cout << "Number of inputs: " << nInputs << std::endl;
    std::cout << "Number of outputs: " << nResponses << std::endl;
    std::cout << "Number of criteria: " << nCriteria << std::endl;
    std::cout << std::endl;
 
    if( nInputs < 1 )
    {
        std::cout << "Error: File does not contain any inputs. Unable to continue.\n" << std::endl;
        return EXIT_FAILURE;
    }
 
    // get the names of active inputs by setting the input flag
    // note that the char pointer must not be preallocated
    char *input_names;
    dmop2_getNames( omdb, NAME_INPUTS, &input_names );
 
    // print the names of the active inputs
    // ( names are splitted by '\0', e.g. par1\0par2\0par3\0\0 )
    std::cout << "INPUTS: (names plus sampling bounds)" << std::endl;
    char *input_names_cpy = input_names;
    while( *input_names_cpy )
    {
        // get input bounds
        std::vector< double > input_bounds( 2, 0.0 );
        double *p_input_bounds = &input_bounds[0];
        dmop2_getInputBoundsPerParameter(omdb, input_names_cpy, p_input_bounds);
        std::cout << "\t" << input_names_cpy << "\t " << input_bounds[0] << "\t" << input_bounds[1] << std::endl;
        input_names_cpy += strlen(input_names_cpy)+1;
    }
    std::cout << std::endl;
 
    if (nResponses < 0)
    {
        std::cout << "Error: File does not contain any outputs. Unable to continue.\n" << std::endl;
        return EXIT_FAILURE;
    }
 
    // get the names of active outputs by setting the responses flag
    // note that the char pointer must not be preallocated
    char *output_names;
    dmop2_getNames(omdb, NAME_RESPONSES, &output_names);
 
    // print the names of the active, scalar outputs
    // ( names are splitted by '\0', e.g. resp1\0resp2\0resp3\0\0 )
 
    std::vector< double > cop_vals( nInputs+1, 0.0 );
    double *p_cop_vals = &cop_vals[0];
 
    std::cout << "OUTPUTS: (names plus CoP values)" << std::endl;
    char *output_names_cpy = output_names;
    while( *output_names_cpy )
    {
        dmop2_getCoPValuesPerResponse( omdb, output_names_cpy, p_cop_vals );
        std::cout << "\t" << output_names_cpy;
 
        for(unsigned int p(0); p < nInputs; ++p )
        {
            std::cout << "\t" << p_cop_vals[p];
        }
        std::cout << "\t|\t" << p_cop_vals[nInputs] << std::endl;
        output_names_cpy += strlen(output_names_cpy)+1;
    }
    std::cout << std::endl;
 
    if (nCriteria < 0)
    {
        std::cout << "Error: File does not contain any criteria. Unable to continue.\n" << std::endl;
        return EXIT_FAILURE;
    }
 
    // get the names of active criteria by setting the criteria flag
    // note that the char pointer must not be preallocated
    char *criteria_names;
    dmop2_getNames(omdb, NAME_CRITERIA, &criteria_names);
 
    // print the names of the active criteria
    // ( names are splitted by '\0', e.g. crit1\0crit2\0crit3\0\0 )
    std::cout << "CRITERIA:" << std::endl;
    char *criteria_names_cpy = criteria_names;
    while (*criteria_names_cpy)
    {
        std::cout << "\t" << criteria_names_cpy;
        criteria_names_cpy += strlen(criteria_names_cpy) + 1;
    }
    std::cout << std::endl;
 
    int num_designs(3);
    // create an amount of design points i.e. an array of
    // nInputs * num_designs values of type double
    // to keep it simple, we set all of them to 10.0
    unsigned int size_inputs = nInputs * num_designs;
    std::vector< double > inputs(size_inputs, 10.0);
 
    // alignment of param values has to be [par1des1, par1des2, par1des3, par2des1, par2des2, par2des3 ...]
    // e.g.
    // std::vector< double > all_input_bounds( nInputs*2, 0.0 );
    // double *p_all_input_bounds = &all_input_bounds[0];
    // dmop2_getInputBounds( omdb, &p_all_input_bounds );
    // std::vector< double > inputs( num_designs * nInputs );
    // for( int p(0); p < nInputs; ++p )
    // {
    //     const double min_val(all_input_bounds[2*p]),
    //                   diff(all_input_bounds[2*p+1]-all_input_bounds[2*p]);
    //     for( int d(0); d < num_designs; ++d )
    //     {
    //         inputs[p*num_designs+d] = min_val + diff/2;
    //     }
    // }
 
    // preallocate a double array for storing the solve outputs
    // the required size and order depends on the set flags:
    //      Responses   : num_designs * nResponses * sizeof(double)
    //      Criteria    : num_designs * nCriteria  * sizeof(double)
    //      Density     : num_designs              * sizeof(double)
    //      Errors      : num_designs * 4          * sizeof(double)
    // In this example we want to retrieve the responses and
    // the evaluated criteria, also we activate extrapolation
    flags = SOLVE_EXTRAPOLATE | SOLVE_RESPONSES | SOLVE_CRITERIA;
    unsigned int size_results = (num_designs * nResponses) + (num_designs * nCriteria);
    std::unique_ptr<double[]> results(new double[size_results]);
 
    // request the approximation of the outputs of all given design points at once
    if( dmop2_solve(omdb, num_designs, &inputs[0], size_inputs, flags, results.get(), size_results) != 0 )
    {
        std::cout << "Error in approximation: " << dmop2_getLastError() << std::endl;
        return EXIT_FAILURE;
    }
 
    // print the results
    std::cout << std::endl;
    std::cout << "Results:" << std::endl;
    for (unsigned int d(0); d < size_results; ++d)
    {
        if (d < num_designs * nResponses) {
            std::cout << "\tResponse " << (d % nResponses + 1) << " for Design " << (d / nResponses + 1) << ": " << results[d];
        }
        else {
            unsigned int d_2 = d - (num_designs * nResponses);
            std::cout << "\tCriteria " << (d_2 % nCriteria + 1) << " for Design " << (d_2 / nCriteria + 1) << ": " << results[d];
        }
        std::cout << std::endl;
    }
    // clean up
    // it is required to manually free the name-pointers allocated by the API
    dmop2_free(input_names);
    dmop2_free(output_names);
    dmop2_free(criteria_names);
 
    dmop2_cleanup();
 
    return EXIT_SUCCESS;
}

Output generated by the code above for a sample .omdb file

Number of inputs: 5
Number of outputs: 1
Number of criteria: 7
 
INPUTS: (names plus sampling bounds)
        X1       -3.12744       3.12744
        X1       -3.12744       3.12744
        X1       -3.12744       3.12744
        X1       -3.12744       3.12744
        X1       -3.12744       3.12744
 
OUTPUTS: (names plus CoP values)
        Y       0.180069        0.306036        0.632022        0       0       |       0.985943
 
CRITERIA:
        test_criteria   test_objective  test_criteria_2 invalid_test_criteria   test_lim_st     test_var        test_obj_max
 
Results:
        Response 1 for Design 1: 0.0518705
        Response 1 for Design 2: 0.0518705
        Response 1 for Design 3: 0.0518705
        Criteria 1 for Design 1: 11.9222
        Criteria 2 for Design 1: 0.0518705
        Criteria 3 for Design 1: 0.0518705
        Criteria 4 for Design 1: nan
        Criteria 5 for Design 1: 9.94813
        Criteria 6 for Design 1: 0.103741
        Criteria 7 for Design 1: -0.0518705
        Criteria 1 for Design 2: 11.9222
        Criteria 2 for Design 2: 0.0518705
        Criteria 3 for Design 2: 0.0518705
        Criteria 4 for Design 2: nan
        Criteria 5 for Design 2: 9.94813
        Criteria 6 for Design 2: 0.103741
        Criteria 7 for Design 2: -0.0518705
        Criteria 1 for Design 3: 11.9222
        Criteria 2 for Design 3: 0.0518705
        Criteria 3 for Design 3: 0.0518705
        Criteria 4 for Design 3: nan
        Criteria 5 for Design 3: 9.94813
        Criteria 6 for Design 3: 0.103741
        Criteria 7 for Design 3: -0.0518705

Prerequisites

Windows

x86_64 architecture, Microsoft Visual Studio ™ 2017 Professional is recommended

Linux

x86_64 architecture, GCC 7.3+, glibc version 2.12+, Kernel version 2.6 or above

Installation

Extract the archive and set the include (-I) and library (-L) paths appropriate to the new location.

Compile and link

Windows

cl /I../include /I. /DDYNARDO_MOPSOLVER_SHARED ms_api2_sample01_cpp.cpp mopsolver_dll.lib

Linux

g++ -I../include -I. -DDYNARDO_MOPSOLVER_SHARED ms_api2_sample01_cpp.cpp -o ms_api2_sample01 libmopsolver_dll.so

optiSLang MOPSolver API 2024 R1

Introduction

Usage example (using a C++ compiler)

Output generated by the code above for a sample .omdb file

Prerequisites

Windows

Linux

Installation

Compile and link

Windows

Linux

Connect with Ansys