TEST_F(AnalysisDriverFixture,RuntimeBehavior_StopAndRestartDakotaAnalysis) {
// RETRIEVE PROBLEM
Problem problem = retrieveProblem("SimpleHistogramBinUQ",true,false);
// DEFINE SEED
Model model = model::exampleModel();
openstudio::path p = toPath("./example.osm");
model.save(p,true);
FileReference seedModel(p);
// CREATE ANALYSIS
SamplingAlgorithmOptions algOptions;
algOptions.setSamples(10);
Analysis analysis("Stop and Restart Dakota Analysis",
problem,
SamplingAlgorithm(algOptions),
seedModel);
// RUN ANALYSIS
if (!dakotaExePath().empty()) {
ProjectDatabase database = getCleanDatabase("StopAndRestartDakotaAnalysis");
AnalysisDriver analysisDriver(database);
AnalysisRunOptions runOptions = standardRunOptions(analysisDriver.database().path().parent_path());
StopWatcher watcher(analysisDriver);
watcher.watch(analysis.uuid());
CurrentAnalysis currentAnalysis = analysisDriver.run(analysis,runOptions);
analysisDriver.waitForFinished();
EXPECT_FALSE(analysisDriver.isRunning());
// check conditions afterward
boost::optional<runmanager::JobErrors> jobErrors = currentAnalysis.dakotaJobErrors();
ASSERT_TRUE(jobErrors);
EXPECT_FALSE(jobErrors->errors().empty());
EXPECT_FALSE(currentAnalysis.analysis().dataPoints().empty());
EXPECT_FALSE(currentAnalysis.analysis().dataPointsToQueue().empty());
EXPECT_FALSE(currentAnalysis.analysis().completeDataPoints().empty());
EXPECT_FALSE(currentAnalysis.analysis().successfulDataPoints().empty());
EXPECT_TRUE(currentAnalysis.analysis().failedDataPoints().empty());
EXPECT_FALSE(currentAnalysis.analysis().algorithm()->isComplete());
EXPECT_FALSE(currentAnalysis.analysis().algorithm()->failed());
EXPECT_EQ(0u,analysisDriver.currentAnalyses().size());
LOG(Debug,"After initial stop, there are " << currentAnalysis.analysis().dataPoints().size()
<< " data points, of which " << currentAnalysis.analysis().completeDataPoints().size()
<< " are complete.");
// try to restart from database contents
Analysis analysis = AnalysisRecord::getAnalysisRecords(database)[0].analysis();
ASSERT_TRUE(analysis.algorithm());
EXPECT_FALSE(analysis.algorithm()->isComplete());
EXPECT_FALSE(analysis.algorithm()->failed());
currentAnalysis = analysisDriver.run(analysis,runOptions);
analysisDriver.waitForFinished();
EXPECT_EQ(10u,analysis.dataPoints().size());
EXPECT_EQ(0u,analysis.dataPointsToQueue().size());
EXPECT_EQ(10u,analysis.completeDataPoints().size());
EXPECT_EQ(10u,analysis.successfulDataPoints().size());
EXPECT_EQ(0u,analysis.failedDataPoints().size());
}
}
TEST_F(AnalysisFixture, DataPoint_Selected) {
// Create analysis
Analysis analysis = analysis1(PreRun);
// See how many to queue
unsigned totalToRun = analysis.dataPointsToQueue().size();
ASSERT_LT(0u,totalToRun);
// Turn one off
ASSERT_FALSE(analysis.dataPoints().empty());
EXPECT_EQ(totalToRun,analysis.dataPoints().size());
DataPoint dataPoint = analysis.dataPoints()[0];
dataPoint.setSelected(false);
EXPECT_FALSE(dataPoint.selected());
// Make sure shows up in "ToQueue"
EXPECT_EQ(totalToRun - 1u,analysis.dataPointsToQueue().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());
}
