TEST_F(AnalysisDriverFixture,SimpleProject_Create) {
  openstudio::path projectDir = toPath("AnalysisDriverFixtureData");
  if (!boost::filesystem::exists(projectDir)) {
    boost::filesystem::create_directory(projectDir);
  }
  projectDir = projectDir / toPath("NewProject");
  boost::filesystem::remove_all(projectDir);

  OptionalSimpleProject project = SimpleProject::create(projectDir);

  ASSERT_TRUE(project);

  EXPECT_TRUE(boost::filesystem::exists(projectDir));
  EXPECT_TRUE(boost::filesystem::is_directory(projectDir));
  EXPECT_TRUE(boost::filesystem::exists(projectDir / toPath("project.osp")));
  EXPECT_TRUE(boost::filesystem::exists(projectDir / toPath("run.db")));
  EXPECT_TRUE(boost::filesystem::exists(projectDir / toPath("project.log")));

  Analysis analysis = project->analysis();
  EXPECT_EQ(0,analysis.problem().numVariables());
  EXPECT_FALSE(analysis.algorithm());
  EXPECT_EQ(0u,analysis.dataPoints().size());

  AnalysisRecord analysisRecord = project->analysisRecord();
  EXPECT_EQ(0u,analysisRecord.problemRecord().inputVariableRecords().size());
  EXPECT_EQ(0u,analysisRecord.dataPointRecords().size());
}
// Test not yet to scale re: total data points.
TEST_F(ProjectFixture,Profile_DeserializeAnalysis) {
  // ETH@20121108 - When this test is running reasonably well, replace the beginning of
  // UpdateAnalysis with this.
  ProjectDatabase db = getPopulatedDatabase(100,500,false,toPath("./UpdateAnalysis"));
  AnalysisRecordVector records = AnalysisRecord::getAnalysisRecords(db);
  ASSERT_EQ(1u,records.size());
  AnalysisRecord record = records[0];

  // time the process of deserializing an analysis
  ptime start = microsec_clock::local_time();
  Analysis analysis = record.analysis();
  time_duration deserializeTime = microsec_clock::local_time() - start;

  std::cout << "Time: " << to_simple_string(deserializeTime) << std::endl;
}
DesignOfExperimentsRecord::DesignOfExperimentsRecord(
    const analysis::DesignOfExperiments& designOfExperiments, AnalysisRecord& analysisRecord)
  : OpenStudioAlgorithmRecord(boost::shared_ptr<detail::DesignOfExperimentsRecord_Impl>(
        new detail::DesignOfExperimentsRecord_Impl(designOfExperiments, analysisRecord)),
        analysisRecord.projectDatabase(),
        designOfExperiments)
{
  OS_ASSERT(getImpl<detail::DesignOfExperimentsRecord_Impl>());
}
DDACEAlgorithmRecord::DDACEAlgorithmRecord(const analysis::DDACEAlgorithm& ddaceAlgorithm,
                                           AnalysisRecord& analysisRecord)
  : DakotaAlgorithmRecord(std::shared_ptr<detail::DDACEAlgorithmRecord_Impl>(
        new detail::DDACEAlgorithmRecord_Impl(ddaceAlgorithm, analysisRecord)),
        analysisRecord.projectDatabase(),
        ddaceAlgorithm)
{
  OS_ASSERT(getImpl<detail::DDACEAlgorithmRecord_Impl>());

  constructRelatedRecords(ddaceAlgorithm);
}
ParameterStudyAlgorithmRecord::ParameterStudyAlgorithmRecord(
    const analysis::ParameterStudyAlgorithm& parameterStudyAlgorithm,
    AnalysisRecord& analysisRecord)
  : DakotaAlgorithmRecord(std::shared_ptr<detail::ParameterStudyAlgorithmRecord_Impl>(
        new detail::ParameterStudyAlgorithmRecord_Impl(parameterStudyAlgorithm, analysisRecord)),
        analysisRecord.projectDatabase(),
        parameterStudyAlgorithm)
{
  OS_ASSERT(getImpl<detail::ParameterStudyAlgorithmRecord_Impl>());

  constructRelatedRecords(parameterStudyAlgorithm);
}
PSUADEDaceAlgorithmRecord::PSUADEDaceAlgorithmRecord(
    const analysis::PSUADEDaceAlgorithm& psuadedaceAlgorithm,
    AnalysisRecord& analysisRecord)
  : DakotaAlgorithmRecord(boost::shared_ptr<detail::PSUADEDaceAlgorithmRecord_Impl>(
        new detail::PSUADEDaceAlgorithmRecord_Impl(psuadedaceAlgorithm, analysisRecord)),
        analysisRecord.projectDatabase(),
        psuadedaceAlgorithm)
{
  BOOST_ASSERT(getImpl<detail::PSUADEDaceAlgorithmRecord_Impl>());

  constructRelatedRecords(psuadedaceAlgorithm);
}
TEST_F(AnalysisDriverFixture, DesignOfExperiments_MeshAnalysis) {

  openstudio::path rubyLibDirPath = openstudio::toPath(rubyLibDir());

  // GET SIMPLE PROJECT
  SimpleProject project = getCleanSimpleProject("DesignOfExperiments_MeshAnalysis");
  Analysis analysis = project.analysis();

  // SET PROBLEM
  Problem problem = retrieveProblem("MixedOsmIdf",false,false);
  analysis.setProblem(problem);

  // SET SEED
  Model model = model::exampleModel();
  openstudio::path p = toPath("./example.osm");
  model.save(p,true);
  FileReference seedModel(p);
  analysis.setSeed(seedModel);

  // SET ALGORITHM
  DesignOfExperimentsOptions algOptions(DesignOfExperimentsType::FullFactorial);
  DesignOfExperiments algorithm(algOptions);
  analysis.setAlgorithm(algorithm);

  // RUN ANALYSIS
  AnalysisDriver driver = project.analysisDriver();
  AnalysisRunOptions runOptions = standardRunOptions(project.projectDir());
  driver.run(analysis,runOptions);
  EXPECT_TRUE(driver.waitForFinished());

  // CHECK RESULTS
  AnalysisRecord analysisRecord = project.analysisRecord();
  EXPECT_EQ(4,analysisRecord.problemRecord().combinatorialSize(true).get());
  EXPECT_EQ(4u, analysisRecord.dataPointRecords().size());
  BOOST_FOREACH(const DataPointRecord& dataPointRecord, analysisRecord.dataPointRecords()) {
    EXPECT_TRUE(dataPointRecord.isComplete());
    EXPECT_FALSE(dataPointRecord.failed());
  }

  // get data points by perturbations and vice versa
  std::vector<DataPointRecord> testDataPoints;
  std::vector<QVariant> testVariableValues;

  // all data points are successful
  testDataPoints = analysisRecord.successfulDataPointRecords();
  EXPECT_EQ(4u,testDataPoints.size());

  // empty variableValues returns all data points
  testDataPoints = analysisRecord.getDataPointRecords(testVariableValues);
  EXPECT_EQ(4u, testDataPoints.size());

  // find the baseline
  testVariableValues.clear();
  testVariableValues.push_back(0);
  testVariableValues.push_back(QVariant(QVariant::Int)); // only one perturbation, null works too
  testVariableValues.push_back(0);
  ASSERT_TRUE(testVariableValues[1].isNull());
  testDataPoints = analysisRecord.getDataPointRecords(testVariableValues);
  ASSERT_EQ(1u, testDataPoints.size());

  // find model with improved wall and roof
  testVariableValues.clear();
  testVariableValues.push_back(1);
  testVariableValues.push_back(0);
  testVariableValues.push_back(1);
  testDataPoints = analysisRecord.getDataPointRecords(testVariableValues);
  ASSERT_EQ(1u, testDataPoints.size());
  DataPoint testDataPoint = testDataPoints[0].dataPoint();
  std::vector<OptionalDiscretePerturbation> perturbations =
      analysis.problem().getDiscretePerturbations(testVariableValues);
  ASSERT_EQ(3u,perturbations.size());
  ASSERT_TRUE(perturbations[0] && perturbations[1] && perturbations[2]);
  EXPECT_TRUE(perturbations[0]->uuid() == problem.variables()[0].cast<DiscreteVariable>().perturbations(false)[1].uuid());
  EXPECT_TRUE(perturbations[1]->uuid() == problem.variables()[1].cast<DiscreteVariable>().perturbations(false)[0].uuid());
  EXPECT_TRUE(perturbations[2]->uuid() == problem.variables()[2].cast<DiscreteVariable>().perturbations(false)[1].uuid());
  EXPECT_TRUE(perturbations[0]->optionalCast<RubyPerturbation>());
  EXPECT_TRUE(perturbations[1]->optionalCast<RubyPerturbation>());
  EXPECT_TRUE(perturbations[2]->optionalCast<RubyPerturbation>());

  // find models with improved wall
  testVariableValues.clear();
  testVariableValues.push_back(1);
  testDataPoints = analysisRecord.getDataPointRecords(testVariableValues);
  ASSERT_EQ(2u, testDataPoints.size());

  // infeasible
  testVariableValues.clear();
  testVariableValues.push_back(0);
  testVariableValues.push_back(0);
  testVariableValues.push_back(0);
  testVariableValues.push_back(0);
  testDataPoints = analysisRecord.getDataPointRecords(testVariableValues);
  ASSERT_EQ(0u, testDataPoints.size());
}
TEST_F(AnalysisDriverFixture, DDACE_LatinHypercube_Continuous) {
  {
    // GET SIMPLE PROJECT
    SimpleProject project = getCleanSimpleProject("DDACE_LatinHypercube_Continuous");
    Analysis analysis = project.analysis();

    // SET PROBLEM
    Problem problem = retrieveProblem("Continuous",true,false);
    analysis.setProblem(problem);

    // DEFINE SEED
    Model model = model::exampleModel();
    openstudio::path p = toPath("./example.osm");
    model.save(p,true);
    FileReference seedModel(p);
    analysis.setSeed(seedModel);

    // CREATE ANALYSIS
    DDACEAlgorithmOptions algOptions(DDACEAlgorithmType::lhs);
    DDACEAlgorithm algorithm(algOptions);
    analysis.setAlgorithm(algorithm);

    // RUN ANALYSIS
    AnalysisDriver driver = project.analysisDriver();
    AnalysisRunOptions runOptions = standardRunOptions(project.projectDir());
    CurrentAnalysis currentAnalysis = driver.run(analysis,runOptions);
    EXPECT_TRUE(driver.waitForFinished());
    boost::optional<runmanager::JobErrors> jobErrors = currentAnalysis.dakotaJobErrors();
    ASSERT_TRUE(jobErrors);
    EXPECT_FALSE(jobErrors->errors().empty()); // require specification of number of samples
    EXPECT_TRUE(driver.currentAnalyses().empty());
    Table summary = currentAnalysis.analysis().summaryTable();
    EXPECT_EQ(1u,summary.nRows()); // no points

    project.clearAllResults();
    algOptions.setSamples(4);
    EXPECT_EQ(4,analysis.algorithm()->cast<DDACEAlgorithm>().ddaceAlgorithmOptions().samples());
    currentAnalysis = driver.run(analysis,runOptions);
    EXPECT_TRUE(driver.waitForFinished());
    jobErrors = currentAnalysis.dakotaJobErrors();
    ASSERT_TRUE(jobErrors);
    EXPECT_TRUE(jobErrors->errors().empty());
    EXPECT_TRUE(driver.currentAnalyses().empty());
    summary = currentAnalysis.analysis().summaryTable();
    EXPECT_EQ(5u,summary.nRows());
    summary.save(project.projectDir() / toPath("summary.csv"));

    BOOST_FOREACH(const DataPoint& dataPoint,analysis.dataPoints()) {
      EXPECT_TRUE(dataPoint.isComplete());
      EXPECT_FALSE(dataPoint.failed());
      // EXPECT_FALSE(dataPoint.responseValues().empty());
    }

    ASSERT_TRUE(analysis.algorithm());
    EXPECT_TRUE(analysis.algorithm()->isComplete());
    EXPECT_FALSE(analysis.algorithm()->failed());

    {
      AnalysisRecord analysisRecord = project.analysisRecord();
      Analysis analysisCopy = analysisRecord.analysis();
      ASSERT_TRUE(analysisCopy.algorithm());
      EXPECT_TRUE(analysisCopy.algorithm()->isComplete());
      EXPECT_FALSE(analysisCopy.algorithm()->failed());
    }
  }

  LOG(Info,"Restart from existing project.");

  // Get existing project
  SimpleProject project = getSimpleProject("DDACE_LatinHypercube_Continuous");
  EXPECT_FALSE(project.analysisIsLoaded()); // make sure starting fresh
  Analysis analysis = project.analysis();
  EXPECT_FALSE(analysis.isDirty());

  // Add custom data point
  std::vector<QVariant> values;
  values.push_back(0.0);
  values.push_back(0.8);
  values.push_back(int(0));
  OptionalDataPoint dataPoint = analysis.problem().createDataPoint(values);
  ASSERT_TRUE(dataPoint);
  analysis.addDataPoint(*dataPoint);
  EXPECT_EQ(1u,analysis.dataPointsToQueue().size());
  ASSERT_TRUE(analysis.algorithm());
  EXPECT_TRUE(analysis.algorithm()->isComplete());
  EXPECT_FALSE(analysis.algorithm()->failed());
  EXPECT_TRUE(analysis.isDirty());
  EXPECT_FALSE(analysis.resultsAreInvalid());
  EXPECT_FALSE(analysis.dataPointsAreInvalid());

  // get last modified time of a file in a completed data point to make sure nothing is re-run
  DataPointVector completePoints = analysis.completeDataPoints();
  ASSERT_FALSE(completePoints.empty());
  OptionalFileReference inputFileRef = completePoints[0].osmInputData();
  ASSERT_TRUE(inputFileRef);
  QFileInfo inputFileInfo(toQString(inputFileRef->path()));
  QDateTime inputFileModifiedTestTime = inputFileInfo.lastModified();
  EXPECT_EQ(1u,analysis.dataPointsToQueue().size());

  AnalysisDriver driver = project.analysisDriver();
  CurrentAnalysis currentAnalysis = driver.run(
        analysis,
        standardRunOptions(project.projectDir()));
  EXPECT_TRUE(driver.waitForFinished());
  boost::optional<runmanager::JobErrors> jobErrors = currentAnalysis.dakotaJobErrors();
  EXPECT_FALSE(jobErrors); // should not try to re-run DakotaAlgorithm
  EXPECT_TRUE(driver.currentAnalyses().empty());
  EXPECT_TRUE(analysis.dataPointsToQueue().empty());
  Table summary = currentAnalysis.analysis().summaryTable();
  EXPECT_EQ(6u,summary.nRows());
  summary.save(project.projectDir() / toPath("summary_post_restart.csv"));
  // RunManager should not re-run any data points
  EXPECT_EQ(inputFileModifiedTestTime,inputFileInfo.lastModified());
}
示例#9
0
TEST_F(ProjectFixture, DataPointTagRecords) {
  // create Analysis with one DataPoint with one Tag ("test tag")
  analysis::Problem problem("problem",analysis::VariableVector(),runmanager::Workflow());
  FileReference seed(toPath("in.osm"));
  analysis::Analysis analysis("analysis",problem,seed);
  analysis::DataPoint dataPoint = problem.createDataPoint(std::vector<QVariant>()).get();
  dataPoint.addTag("test tag");
  analysis.addDataPoint(dataPoint);

  // make sure tag records follow data points around.
  // trying to replicate issue where data point tag records get repointed to
  // file reference record with id 0.
  {
    // save analysis to a new database
    ProjectDatabase database = getCleanDatabase("DataPointTagRecords");
    AnalysisRecord analysisRecord(analysis,database);
    database.save();
    ASSERT_EQ(1u,analysisRecord.dataPointRecords().size());
    DataPointRecord dataPointRecord = analysisRecord.dataPointRecords()[0];
    ASSERT_EQ(1u,dataPointRecord.tagRecords().size());
    TagRecord tagRecord = dataPointRecord.tagRecords()[0];
    EXPECT_EQ("test tag",tagRecord.name());
    analysis::DataPoint dataPoint = dataPointRecord.dataPoint();
    ASSERT_EQ(1u,dataPoint.tags().size());
    EXPECT_EQ("test tag",dataPoint.tags()[0].name());
    analysis::Analysis analysis = analysisRecord.analysis();
    ASSERT_EQ(1u,analysis.dataPoints().size());
    dataPoint = analysis.dataPoints()[0];
    ASSERT_EQ(1u,dataPoint.tags().size());
    EXPECT_EQ("test tag",dataPoint.tags()[0].name());
  }

  NameFinder<TagRecord> testRecordFinder("test tag");
  NameFinder<TagRecord> anotherTestRecordFinder("another test");
  NameFinder<Tag> testTagFinder("test tag");
  NameFinder<Tag> anotherTestTagFinder("another test");

  {
    ProjectDatabase database = getExistingDatabase("DataPointTagRecords");
    ASSERT_EQ(1u,AnalysisRecord::getAnalysisRecords(database).size());
    AnalysisRecord analysisRecord = AnalysisRecord::getAnalysisRecords(database)[0];
    ASSERT_EQ(1u,analysisRecord.dataPointRecords().size());
    DataPointRecord dataPointRecord = analysisRecord.dataPointRecords()[0];
    ASSERT_EQ(1u,dataPointRecord.tagRecords().size());
    TagRecord tagRecord = dataPointRecord.tagRecords()[0];
    EXPECT_EQ("test tag",tagRecord.name());
    analysis::DataPoint dataPoint = dataPointRecord.dataPoint();
    ASSERT_EQ(1u,dataPoint.tags().size());
    EXPECT_EQ("test tag",dataPoint.tags()[0].name());
    analysis::Analysis analysis = analysisRecord.analysis();
    ASSERT_EQ(1u,analysis.dataPoints().size());
    dataPoint = analysis.dataPoints()[0];
    ASSERT_EQ(1u,dataPoint.tags().size());
    EXPECT_EQ("test tag",dataPoint.tags()[0].name());

    // adding a second tag and resaving the analysis
    dataPoint.addTag("another test");
    analysisRecord = AnalysisRecord(analysis,database);
    bool test = database.save();
    EXPECT_TRUE(test);
    ASSERT_EQ(1u,analysisRecord.dataPointRecords().size());
    dataPointRecord = analysisRecord.dataPointRecords()[0];
    TagRecordVector tagRecords = dataPointRecord.tagRecords();
    EXPECT_EQ(2u,tagRecords.size());
    EXPECT_FALSE(std::find_if(tagRecords.begin(),tagRecords.end(),testRecordFinder) == tagRecords.end());
    EXPECT_FALSE(std::find_if(tagRecords.begin(),tagRecords.end(),anotherTestRecordFinder) == tagRecords.end());
    dataPoint = dataPointRecord.dataPoint();
    TagVector tags = dataPoint.tags();
    EXPECT_EQ(2u,tags.size());
    EXPECT_FALSE(std::find_if(tags.begin(),tags.end(),testTagFinder) == tags.end());
    EXPECT_FALSE(std::find_if(tags.begin(),tags.end(),anotherTestTagFinder) == tags.end());
    analysis = analysisRecord.analysis();
    ASSERT_EQ(1u,analysis.dataPoints().size());
    dataPoint = analysis.dataPoints()[0];
    tags = dataPoint.tags();
    EXPECT_EQ(2u,tags.size());
    EXPECT_FALSE(std::find_if(tags.begin(),tags.end(),testTagFinder) == tags.end());
    EXPECT_FALSE(std::find_if(tags.begin(),tags.end(),anotherTestTagFinder) == tags.end());
    tagRecords = TagRecord::getTagRecords(database);
    EXPECT_EQ(2u,tagRecords.size());
    EXPECT_FALSE(std::find_if(tagRecords.begin(),tagRecords.end(),testRecordFinder) == tagRecords.end());
    EXPECT_FALSE(std::find_if(tagRecords.begin(),tagRecords.end(),anotherTestRecordFinder) == tagRecords.end());
  }

  {
    ProjectDatabase database = getExistingDatabase("DataPointTagRecords");
    ASSERT_EQ(1u,AnalysisRecord::getAnalysisRecords(database).size());
    AnalysisRecord analysisRecord = AnalysisRecord::getAnalysisRecords(database)[0];
    ASSERT_EQ(1u,analysisRecord.dataPointRecords().size());
    DataPointRecord dataPointRecord = analysisRecord.dataPointRecords()[0];
    TagRecordVector tagRecords = dataPointRecord.tagRecords();
    EXPECT_EQ(2u,tagRecords.size());
    EXPECT_FALSE(std::find_if(tagRecords.begin(),tagRecords.end(),testRecordFinder) == tagRecords.end());
    EXPECT_FALSE(std::find_if(tagRecords.begin(),tagRecords.end(),anotherTestRecordFinder) == tagRecords.end());
    dataPoint = dataPointRecord.dataPoint();
    TagVector tags = dataPoint.tags();
    EXPECT_FALSE(std::find_if(tags.begin(),tags.end(),testTagFinder) == tags.end());
    EXPECT_FALSE(std::find_if(tags.begin(),tags.end(),anotherTestTagFinder) == tags.end());
    analysis = analysisRecord.analysis();
    ASSERT_EQ(1u,analysis.dataPoints().size());
    dataPoint = analysis.dataPoints()[0];
    tags = dataPoint.tags();
    EXPECT_FALSE(std::find_if(tags.begin(),tags.end(),testTagFinder) == tags.end());
    EXPECT_FALSE(std::find_if(tags.begin(),tags.end(),anotherTestTagFinder) == tags.end());
  }

}