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_MixedOsmIdf_MoveProjectDatabase) { openstudio::path oldDir, newDir; { // GET SIMPLE PROJECT SimpleProject project = getCleanSimpleProject("DDACE_LatinHypercube_MixedOsmIdf"); Analysis analysis = project.analysis(); analysis.setName("DDACE Latin Hypercube Sampling - MixedOsmIdf"); // 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 DDACEAlgorithmOptions algOptions(DDACEAlgorithmType::lhs); algOptions.setSamples(12); // test reprinting results.out for copies of same point 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_TRUE(jobErrors->errors().empty()); EXPECT_TRUE(driver.currentAnalyses().empty()); Table summary = analysis.summaryTable(); EXPECT_EQ(5u,summary.nRows()); // 4 points (all combinations) summary.save(project.projectDir() / toPath("summary.csv")); EXPECT_EQ(4u,analysis.dataPoints().size()); BOOST_FOREACH(const DataPoint& dataPoint,analysis.dataPoints()) { EXPECT_TRUE(dataPoint.isComplete()); EXPECT_FALSE(dataPoint.failed()); EXPECT_TRUE(dataPoint.workspace()); // should be able to load data from disk } oldDir = project.projectDir(); newDir = project.projectDir().parent_path() / toPath("DDACELatinHypercubeMixedOsmIdfCopy"); // Make copy of project boost::filesystem::remove_all(newDir); ASSERT_TRUE(project.saveAs(newDir)); } // Blow away old project. // TODO: Reinstate. This was failing on Windows and isn't absolutely necessary. // try { // boost::filesystem::remove_all(oldDir); // } // catch (std::exception& e) { // EXPECT_TRUE(false) << "Boost filesystem was unable to delete the old folder, because " << e.what(); // } // Open new project SimpleProject project = getSimpleProject("DDACE_LatinHypercube_MixedOsmIdf_Copy"); EXPECT_TRUE(project.projectDir() == newDir); EXPECT_EQ(toString(newDir),toString(project.projectDir())); // After move, should be able to retrieve results. EXPECT_FALSE(project.analysisIsLoaded()); Analysis analysis = project.analysis(); EXPECT_TRUE(project.analysisIsLoaded()); EXPECT_EQ(4u,analysis.dataPoints().size()); BOOST_FOREACH(const DataPoint& dataPoint,analysis.dataPoints()) { EXPECT_TRUE(dataPoint.isComplete()); EXPECT_FALSE(dataPoint.failed()); LOG(Debug,"Attempting to load workspace for data point at '" << dataPoint.directory() << "'."); if (dataPoint.idfInputData()) { LOG(Debug,"Says there should be input data at " << toString(dataPoint.idfInputData()->path())); } EXPECT_TRUE(dataPoint.workspace()); // should be able to load data from disk if (!dataPoint.workspace()) { LOG(Debug,"Unsuccessful.") } } // Should be able to blow away results and run again project.removeAllDataPoints(); EXPECT_EQ(0u,analysis.dataPoints().size()); EXPECT_FALSE(analysis.algorithm()->isComplete()); EXPECT_FALSE(analysis.algorithm()->failed()); EXPECT_EQ(-1,analysis.algorithm()->iter()); EXPECT_FALSE(analysis.algorithm()->cast<DakotaAlgorithm>().restartFileReference()); EXPECT_FALSE(analysis.algorithm()->cast<DakotaAlgorithm>().outFileReference()); AnalysisRunOptions runOptions = standardRunOptions(project.projectDir()); AnalysisDriver driver = project.analysisDriver(); CurrentAnalysis currentAnalysis = driver.run(analysis,runOptions); EXPECT_TRUE(driver.waitForFinished()); boost::optional<runmanager::JobErrors> jobErrors = currentAnalysis.dakotaJobErrors(); ASSERT_TRUE(jobErrors); EXPECT_TRUE(jobErrors->errors().empty()); EXPECT_TRUE(driver.currentAnalyses().empty()); Table summary = analysis.summaryTable(); EXPECT_EQ(5u,summary.nRows()); // 4 points (all combinations) summary.save(project.projectDir() / toPath("summary.csv")); BOOST_FOREACH(const DataPoint& dataPoint,analysis.dataPoints()) { EXPECT_TRUE(dataPoint.isComplete()); EXPECT_FALSE(dataPoint.failed()); EXPECT_TRUE(dataPoint.workspace()); // should be able to load data from disk } }
TEST_F(AnalysisDriverFixture,DataPersistence_DataPointErrors) { { // Create and populate project SimpleProject project = getCleanSimpleProject("DataPersistence_DataPointErrors"); Analysis analysis = project.analysis(); Problem problem = retrieveProblem(AnalysisDriverFixtureProblem::BuggyBCLMeasure, true, false); EXPECT_EQ(5u,problem.workflow().size()); analysis.setProblem(problem); model::Model model =fastExampleModel(); openstudio::path p = toPath("./example.osm"); model.save(p,true); FileReference seedModel(p); project.setSeed(seedModel); DataPoint dataPoint = problem.createDataPoint(std::vector<QVariant>(problem.numVariables(),0)).get(); analysis.addDataPoint(dataPoint); // Run analysis AnalysisRunOptions runOptions = standardRunOptions(project.projectDir()); project.analysisDriver().run(analysis,runOptions); project.analysisDriver().waitForFinished(); // Check DataPoint job and error information ASSERT_EQ(1u,analysis.dataPoints().size()); dataPoint = analysis.dataPoints()[0]; EXPECT_TRUE(dataPoint.isComplete()); EXPECT_TRUE(dataPoint.failed()); EXPECT_TRUE(dataPoint.topLevelJob()); WorkflowStepJobVector jobResults = problem.getJobsByWorkflowStep(dataPoint); EXPECT_EQ(problem.workflow().size(),jobResults.size()); ASSERT_EQ(5u,jobResults.size()); WorkflowStepJob jobResult = jobResults[0]; ASSERT_TRUE(jobResult.job); EXPECT_TRUE(jobResult.measure); Job job = jobResult.job.get(); ASSERT_TRUE(jobResult.mergedJobIndex); EXPECT_EQ(0u,jobResult.mergedJobIndex.get()); EXPECT_FALSE(job.running()); EXPECT_FALSE(job.outOfDate()); EXPECT_FALSE(job.canceled()); EXPECT_TRUE(job.lastRun()); JobErrors treeErrors = job.treeErrors(); // get all tree errors now, test later JobErrors errors = jobResult.errors().get(); EXPECT_EQ(OSResultValue(OSResultValue::NA),errors.result); EXPECT_TRUE(errors.succeeded()); EXPECT_TRUE(errors.errors().empty()); EXPECT_TRUE(errors.warnings().empty()); EXPECT_FALSE(errors.infos().empty()); jobResult = jobResults[1]; ASSERT_TRUE(jobResult.job); EXPECT_FALSE(jobResult.measure); ASSERT_TRUE(jobResult.step.isWorkItem()); EXPECT_EQ(JobType(JobType::UserScript),jobResult.step.workItemType()); job = jobResult.job.get(); ASSERT_TRUE(jobResult.mergedJobIndex); EXPECT_EQ(1u,jobResult.mergedJobIndex.get()); EXPECT_FALSE(job.running()); EXPECT_FALSE(job.outOfDate()); EXPECT_FALSE(job.canceled()); EXPECT_TRUE(job.lastRun()); errors = jobResult.errors().get(); EXPECT_EQ(OSResultValue(OSResultValue::Success),errors.result); EXPECT_TRUE(errors.succeeded()); EXPECT_TRUE(errors.errors().empty()); EXPECT_FALSE(errors.warnings().empty()); EXPECT_TRUE(errors.infos().empty()); jobResult = jobResults[2]; ASSERT_TRUE(jobResult.job); EXPECT_TRUE(jobResult.measure); job = jobResult.job.get(); ASSERT_TRUE(jobResult.mergedJobIndex); EXPECT_EQ(2u,jobResult.mergedJobIndex.get()); EXPECT_FALSE(job.running()); EXPECT_FALSE(job.outOfDate()); EXPECT_FALSE(job.canceled()); EXPECT_TRUE(job.lastRun()); errors = jobResult.errors().get(); EXPECT_EQ(OSResultValue(OSResultValue::Fail),errors.result); EXPECT_FALSE(errors.succeeded()); EXPECT_FALSE(errors.errors().empty()); EXPECT_TRUE(errors.warnings().empty()); EXPECT_TRUE(errors.infos().empty()); jobResult = jobResults[3]; ASSERT_TRUE(jobResult.job); EXPECT_FALSE(jobResult.measure); ASSERT_TRUE(jobResult.step.isWorkItem()); EXPECT_EQ(JobType(JobType::UserScript),jobResult.step.workItemType()); job = jobResult.job.get(); ASSERT_TRUE(jobResult.mergedJobIndex); EXPECT_EQ(3u,jobResult.mergedJobIndex.get()); EXPECT_FALSE(job.running()); EXPECT_FALSE(job.outOfDate()); // now all four scripts are in same job EXPECT_FALSE(job.canceled()); EXPECT_TRUE(job.lastRun()); // now all four scripts are in same job errors = jobResult.errors().get(); // this script not actually run, so result in default state EXPECT_EQ(OSResultValue(OSResultValue::Fail),errors.result); EXPECT_FALSE(errors.succeeded()); EXPECT_EQ(1u, errors.errors().size()); EXPECT_TRUE(errors.warnings().empty()); EXPECT_TRUE(errors.infos().empty()); jobResult = jobResults[4]; ASSERT_TRUE(jobResult.job); EXPECT_FALSE(jobResult.measure); ASSERT_TRUE(jobResult.step.isWorkItem()); EXPECT_EQ(JobType(JobType::ModelToIdf),jobResult.step.workItemType()); job = jobResult.job.get(); EXPECT_FALSE(jobResult.mergedJobIndex); EXPECT_TRUE(job.outOfDate()); // never run EXPECT_FALSE(job.canceled()); EXPECT_FALSE(job.lastRun()); errors = jobResult.errors().get(); EXPECT_EQ(OSResultValue(OSResultValue::Fail),errors.result); EXPECT_FALSE(errors.succeeded()); EXPECT_TRUE(errors.errors().empty()); EXPECT_TRUE(errors.warnings().empty()); EXPECT_TRUE(errors.infos().empty()); EXPECT_EQ(OSResultValue(OSResultValue::Fail),treeErrors.result); EXPECT_FALSE(treeErrors.succeeded()); EXPECT_FALSE(treeErrors.errors().empty()); EXPECT_FALSE(treeErrors.warnings().empty()); EXPECT_FALSE(treeErrors.infos().empty()); } { // Re-open project SimpleProject project = getSimpleProject("DataPersistence_DataPointErrors"); Analysis analysis = project.analysis(); Problem problem = analysis.problem(); // Verify job and error information still there // Check DataPoint job and error information ASSERT_EQ(1u,analysis.dataPoints().size()); DataPoint dataPoint = analysis.dataPoints()[0]; EXPECT_TRUE(dataPoint.isComplete()); EXPECT_TRUE(dataPoint.failed()); EXPECT_TRUE(dataPoint.topLevelJob()); WorkflowStepJobVector jobResults = problem.getJobsByWorkflowStep(dataPoint); EXPECT_EQ(problem.workflow().size(),jobResults.size()); ASSERT_EQ(5u,jobResults.size()); WorkflowStepJob jobResult = jobResults[0]; ASSERT_TRUE(jobResult.job); EXPECT_TRUE(jobResult.measure); Job job = jobResult.job.get(); EXPECT_FALSE(job.running()); EXPECT_FALSE(job.outOfDate()); EXPECT_FALSE(job.canceled()); EXPECT_TRUE(job.lastRun()); JobErrors treeErrors = job.treeErrors(); // get all tree errors now, test later JobErrors errors = jobResult.errors().get(); EXPECT_EQ(OSResultValue(OSResultValue::NA),errors.result); EXPECT_TRUE(errors.succeeded()); EXPECT_TRUE(errors.errors().empty()); EXPECT_TRUE(errors.warnings().empty()); EXPECT_FALSE(errors.infos().empty()); jobResult = jobResults[1]; ASSERT_TRUE(jobResult.job); EXPECT_FALSE(jobResult.measure); ASSERT_TRUE(jobResult.step.isWorkItem()); EXPECT_EQ(JobType(JobType::UserScript),jobResult.step.workItemType()); job = jobResult.job.get(); EXPECT_FALSE(job.running()); EXPECT_FALSE(job.outOfDate()); EXPECT_FALSE(job.canceled()); EXPECT_TRUE(job.lastRun()); errors = jobResult.errors().get(); EXPECT_EQ(OSResultValue(OSResultValue::Success),errors.result); EXPECT_TRUE(errors.succeeded()); EXPECT_TRUE(errors.errors().empty()); EXPECT_FALSE(errors.warnings().empty()); EXPECT_TRUE(errors.infos().empty()); jobResult = jobResults[2]; ASSERT_TRUE(jobResult.job); EXPECT_TRUE(jobResult.measure); job = jobResult.job.get(); EXPECT_FALSE(job.running()); EXPECT_FALSE(job.outOfDate()); EXPECT_FALSE(job.canceled()); EXPECT_TRUE(job.lastRun()); errors = jobResult.errors().get(); EXPECT_EQ(OSResultValue(OSResultValue::Fail),errors.result); EXPECT_FALSE(errors.succeeded()); EXPECT_FALSE(errors.errors().empty()); EXPECT_TRUE(errors.warnings().empty()); EXPECT_TRUE(errors.infos().empty()); jobResult = jobResults[3]; ASSERT_TRUE(jobResult.job); EXPECT_FALSE(jobResult.measure); ASSERT_TRUE(jobResult.step.isWorkItem()); EXPECT_EQ(JobType(JobType::UserScript),jobResult.step.workItemType()); job = jobResult.job.get(); EXPECT_FALSE(job.running()); EXPECT_FALSE(job.outOfDate()); // now all four scripts are in same job EXPECT_FALSE(job.canceled()); EXPECT_TRUE(job.lastRun()); // now all four scripts are in same job errors = jobResult.errors().get(); EXPECT_EQ(OSResultValue(OSResultValue::Fail),errors.result); EXPECT_FALSE(errors.succeeded()); EXPECT_EQ(1u, errors.errors().size()); EXPECT_TRUE(errors.warnings().empty()); EXPECT_TRUE(errors.infos().empty()); jobResult = jobResults[4]; ASSERT_TRUE(jobResult.job); EXPECT_FALSE(jobResult.measure); ASSERT_TRUE(jobResult.step.isWorkItem()); EXPECT_EQ(JobType(JobType::ModelToIdf),jobResult.step.workItemType()); job = jobResult.job.get(); EXPECT_TRUE(job.outOfDate()); // never run EXPECT_FALSE(job.canceled()); EXPECT_FALSE(job.lastRun()); errors = jobResult.errors().get(); EXPECT_EQ(OSResultValue(OSResultValue::Fail),errors.result); EXPECT_FALSE(errors.succeeded()); EXPECT_TRUE(errors.errors().empty()); EXPECT_TRUE(errors.warnings().empty()); EXPECT_TRUE(errors.infos().empty()); EXPECT_EQ(OSResultValue(OSResultValue::Fail),treeErrors.result); EXPECT_FALSE(treeErrors.succeeded()); EXPECT_FALSE(treeErrors.errors().empty()); EXPECT_FALSE(treeErrors.warnings().empty()); EXPECT_FALSE(treeErrors.infos().empty()); } }
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()); }
TEST_F(AnalysisDriverFixture,DataPersistence_DakotaErrors) { { // Create and populate project SimpleProject project = getCleanSimpleProject("DataPersistence_DakotaErrors"); Analysis analysis = project.analysis(); Problem problem = retrieveProblem(AnalysisDriverFixtureProblem::BuggyBCLMeasure, true, false); analysis.setProblem(problem); model::Model model = model::exampleModel(); openstudio::path p = toPath("./example.osm"); model.save(p,true); FileReference seedModel(p); project.setSeed(seedModel); DDACEAlgorithmOptions algOpts(DDACEAlgorithmType::lhs); // do not set samples so Dakota job will have errors DDACEAlgorithm alg(algOpts); analysis.setAlgorithm(alg); // Run analysis AnalysisRunOptions runOptions = standardRunOptions(project.projectDir()); project.analysisDriver().run(analysis,runOptions); project.analysisDriver().waitForFinished(); // Check Dakota job and error information ASSERT_TRUE(alg.job()); Job job = alg.job().get(); EXPECT_FALSE(job.running()); EXPECT_FALSE(job.outOfDate()); EXPECT_FALSE(job.canceled()); EXPECT_TRUE(job.lastRun()); JobErrors errors = job.errors(); EXPECT_EQ(OSResultValue(OSResultValue::Fail),errors.result); EXPECT_FALSE(errors.succeeded()); EXPECT_FALSE(errors.errors().empty()); EXPECT_TRUE(errors.warnings().empty()); EXPECT_TRUE(errors.infos().empty()); } { // Re-open project SimpleProject project = getSimpleProject("DataPersistence_DakotaErrors"); Analysis analysis = project.analysis(); DDACEAlgorithm alg = analysis.algorithm()->cast<DDACEAlgorithm>(); // Verify job and error information still there ASSERT_TRUE(alg.job()); Job job = alg.job().get(); EXPECT_FALSE(job.running()); EXPECT_FALSE(job.outOfDate()); EXPECT_FALSE(job.canceled()); EXPECT_TRUE(job.lastRun()); JobErrors errors = job.errors(); EXPECT_EQ(OSResultValue(OSResultValue::Fail),errors.result); EXPECT_FALSE(errors.succeeded()); EXPECT_FALSE(errors.errors().empty()); EXPECT_TRUE(errors.warnings().empty()); EXPECT_TRUE(errors.infos().empty()); } }