PostProcessingStrategyL2NormTest.cpp

Go to the documentation of this file.

//=======================================================================================
// ____          ____    __    ______     __________   __      __       __        __
// \    \       |    |  |  |  |   _   \  |___    ___| |  |    |  |     /  \      |  |
//  \    \      |    |  |  |  |  |_)   |     |  |     |  |    |  |    /    \     |  |
//   \    \     |    |  |  |  |   _   /      |  |     |  |    |  |   /  /\  \    |  |
//    \    \    |    |  |  |  |  | \  \      |  |     |   \__/   |  /  ____  \   |  |____
//     \    \   |    |  |__|  |__|  \__\     |__|      \________/  /__/    \__\  |_______|
//      \    \  |    |   ________________________________________________________________
//       \    \ |    |  |  ______________________________________________________________|
//        \    \|    |  |  |         __          __     __     __     ______      _______
//         \         |  |  |_____   |  |        |  |   |  |   |  |   |   _  \    /  _____)
//          \        |  |   _____|  |  |        |  |   |  |   |  |   |  | \  \   \_______
//           \       |  |  |        |  |_____   |   \_/   |   |  |   |  |_/  /    _____  |
//            \ _____|  |__|        |________|   \_______/    |__|   |______/    (_______/
//
//  This file is part of VirtualFluids. VirtualFluids is free software: you can
//  redistribute it and/or modify it under the terms of the GNU General Public
//  License as published by the Free Software Foundation, either version 3 of
//  the License, or (at your option) any later version.
//
//  VirtualFluids is distributed in the hope that it will be useful, but WITHOUT
//  ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
//  FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
//  for more details.
//
//  SPDX-License-Identifier: GPL-3.0-or-later
//  SPDX-FileCopyrightText: Copyright © VirtualFluids Project contributors, see AUTHORS.md in root folder
//
//=======================================================================================
#include "PostProcessingStrategyL2NormTest.h"
 
#include "Tests/L2NormTest/L2NormTestParameterStruct.h"
 
#include "Utilities/Calculator/L2NormCalculator/L2NormCalculatorFactory/L2NormCalculatorFactory.h"
#include "Utilities/Calculator/L2NormCalculator/L2NormCalculator.h"
 
#include "Utilities/Results/AnalyticalResults/AnalyticalResult.h"
#include "Utilities/Results/SimulationResults/SimulationResults.h"
 
std::shared_ptr<L2NormPostProcessingStrategy> L2NormPostProcessingStrategy::getNewInstance(std::shared_ptr<SimulationResults> simResult, std::shared_ptr<AnalyticalResults> analyticalResult, std::shared_ptr<L2NormTestParameterStruct> testPara, std::shared_ptr<L2NormCalculatorFactory> factory, std::vector<std::string> dataToCalcTests)
{
    return std::shared_ptr<L2NormPostProcessingStrategy>(new L2NormPostProcessingStrategy(simResult, analyticalResult, testPara, factory, dataToCalcTests));
}
 
L2NormPostProcessingStrategy::L2NormPostProcessingStrategy(std::shared_ptr<SimulationResults> simResult, std::shared_ptr<AnalyticalResults> analyticalResult, std::shared_ptr<L2NormTestParameterStruct> testPara, std::shared_ptr<L2NormCalculatorFactory> factory, std::vector<std::string> dataToCalcTests)
    : PostProcessingStrategyImp(simResult), analyticalResult(analyticalResult), dataToCalculate(dataToCalcTests)
{
    isEvaluated = false;
    basicTimeStep = testPara->basicTimeStep;
    divergentTimeStep = testPara->divergentTimeStep;
    normalizeData = testPara->normalizeData;
 
    l2NormBasic.resize(dataToCalculate.size());
    l2NormDivergent.resize(dataToCalculate.size());
    for (int i = 0; i < l2NormBasic.size(); i++) {
        l2NormBasic.at(i).resize(normalizeData.size());
        l2NormDivergent.at(i).resize(normalizeData.size());
    }
    
    for (int i = 0; i < normalizeData.size(); i++)
        l2Normcalculator.push_back(factory->makeL2NormCalculator(normalizeData.at(i)));
}
 
void L2NormPostProcessingStrategy::evaluate()
{
    if (!isEvaluated) {
        analyticalResult->calc(simResult);
        int bS = calcTimeStepInResults(basicTimeStep);
        int dS = calcTimeStepInResults(divergentTimeStep);
 
        for (int i = 0; i < dataToCalculate.size(); i++) {
            for (int j = 0; j < normalizeData.size(); j++) {
                if (dataToCalculate.at(i) == "Vx") {
                    l2NormBasic.at(i).at(j) = l2Normcalculator.at(j)->calc(analyticalResult->getVx().at(bS), simResult->getVx().at(bS), simResult->getLevels().at(bS), analyticalResult->getNumberOfXNodes(), analyticalResult->getNumberOfZNodes(), analyticalResult->getL0());
                    l2NormDivergent.at(i).at(j) = l2Normcalculator.at(j)->calc(analyticalResult->getVx().at(dS), simResult->getVx().at(dS), simResult->getLevels().at(dS), analyticalResult->getNumberOfXNodes(), analyticalResult->getNumberOfZNodes(), analyticalResult->getL0());
                }
                if (dataToCalculate.at(i) == "Vy") {
                    l2NormBasic.at(i).at(j) = l2Normcalculator.at(j)->calc(analyticalResult->getVy().at(bS), simResult->getVy().at(bS), simResult->getLevels().at(bS), analyticalResult->getNumberOfXNodes(), analyticalResult->getNumberOfZNodes(), analyticalResult->getL0());
                    l2NormDivergent.at(i).at(j) = l2Normcalculator.at(j)->calc(analyticalResult->getVy().at(dS), simResult->getVy().at(dS), simResult->getLevels().at(dS), analyticalResult->getNumberOfXNodes(), analyticalResult->getNumberOfZNodes(), analyticalResult->getL0());
                }
                if (dataToCalculate.at(i) == "Vz") {
                    l2NormBasic.at(i).at(j) = l2Normcalculator.at(j)->calc(analyticalResult->getVz().at(bS), simResult->getVz().at(bS), simResult->getLevels().at(bS), analyticalResult->getNumberOfXNodes(), analyticalResult->getNumberOfZNodes(), analyticalResult->getL0());
                    l2NormDivergent.at(i).at(j) = l2Normcalculator.at(j)->calc(analyticalResult->getVz().at(dS), simResult->getVz().at(dS), simResult->getLevels().at(dS), analyticalResult->getNumberOfXNodes(), analyticalResult->getNumberOfZNodes(), analyticalResult->getL0());
                }
                if (dataToCalculate.at(i) == "Press") {
                    l2NormBasic.at(i).at(j) = l2Normcalculator.at(j)->calc(analyticalResult->getPress().at(bS), simResult->getPress().at(bS), simResult->getLevels().at(bS), analyticalResult->getNumberOfXNodes(), analyticalResult->getNumberOfZNodes(), analyticalResult->getL0());
                    l2NormDivergent.at(i).at(j) = l2Normcalculator.at(j)->calc(analyticalResult->getPress().at(dS), simResult->getPress().at(dS), simResult->getLevels().at(dS), analyticalResult->getNumberOfXNodes(), analyticalResult->getNumberOfZNodes(), analyticalResult->getL0());
                }
                if (dataToCalculate.at(i) == "Rho") {
                    l2NormBasic.at(i).at(j) = l2Normcalculator.at(j)->calc(analyticalResult->getRho().at(bS), simResult->getRho().at(bS), simResult->getLevels().at(bS), analyticalResult->getNumberOfXNodes(), analyticalResult->getNumberOfZNodes(), analyticalResult->getL0());
                    l2NormDivergent.at(i).at(j) = l2Normcalculator.at(j)->calc(analyticalResult->getRho().at(dS), simResult->getRho().at(dS), simResult->getLevels().at(dS), analyticalResult->getNumberOfXNodes(), analyticalResult->getNumberOfZNodes(), analyticalResult->getL0());
                }
            }
        }
        isEvaluated = true;
    }
}
 
std::vector<double> L2NormPostProcessingStrategy::getL2Norm(std::string aDataToCalc, std::string aNormalizeData)
{
    for (int i = 0; i < dataToCalculate.size(); i++) {
        for (int j = 0; j < normalizeData.size(); j++) {
            if (aDataToCalc == dataToCalculate.at(i) && aNormalizeData == normalizeData.at(j)) {
                std::vector<double> v;
                v.push_back(l2NormBasic.at(i).at(j));
                v.push_back(l2NormDivergent.at(i).at(j));
                return v;
            }
        }
    }
 
    return std::vector<double>();
}
 
std::string L2NormPostProcessingStrategy::getErrorMessage(std::string aNormalizeData)
{
    for (int i = 0; i < normalizeData.size(); i++) {
        if (aNormalizeData == normalizeData.at(i))
            return l2Normcalculator.at(i)->getErrorMessage();
    }
    
    return std::string();
}