use of ubic.gemma.model.expression.bioAssayData.ProcessedExpressionDataVector in project Gemma by PavlidisLab.
the class LinkAnalysisCli method doWork.
@Override
protected Exception doWork(String[] args) {
Exception err = this.processCommandLine(args);
if (err != null) {
return err;
}
if (initializeFromOldData) {
AbstractCLI.log.info("Initializing links from old data for " + this.taxon);
LinkAnalysisPersister s = this.getBean(LinkAnalysisPersister.class);
s.initializeLinksFromOldData(this.taxon);
return null;
} else if (updateNodeDegree) {
// we waste some time here getting the experiments.
this.loadTaxon();
this.getBean(CoexpressionService.class).updateNodeDegrees(this.taxon);
return null;
}
this.linkAnalysisService = this.getBean(LinkAnalysisService.class);
if (this.dataFileName != null) {
/*
* Read vectors from file. Could provide as a matrix, but it's easier to provide vectors (less mess in later
* code)
*/
ArrayDesignService arrayDesignService = this.getBean(ArrayDesignService.class);
ArrayDesign arrayDesign = arrayDesignService.findByShortName(this.linkAnalysisConfig.getArrayName());
if (arrayDesign == null) {
return new IllegalArgumentException("No such array design " + this.linkAnalysisConfig.getArrayName());
}
this.loadTaxon();
arrayDesign = arrayDesignService.thawLite(arrayDesign);
Collection<ProcessedExpressionDataVector> dataVectors = new HashSet<>();
Map<String, CompositeSequence> csMap = new HashMap<>();
for (CompositeSequence cs : arrayDesign.getCompositeSequences()) {
csMap.put(cs.getName(), cs);
}
QuantitationType qtype = this.makeQuantitationType();
SimpleExpressionDataLoaderService simpleExpressionDataLoaderService = this.getBean(SimpleExpressionDataLoaderService.class);
ByteArrayConverter bArrayConverter = new ByteArrayConverter();
try (InputStream data = new FileInputStream(new File(this.dataFileName))) {
DoubleMatrix<String, String> matrix = simpleExpressionDataLoaderService.parse(data);
BioAssayDimension bad = this.makeBioAssayDimension(arrayDesign, matrix);
for (int i = 0; i < matrix.rows(); i++) {
byte[] bData = bArrayConverter.doubleArrayToBytes(matrix.getRow(i));
ProcessedExpressionDataVector vector = ProcessedExpressionDataVector.Factory.newInstance();
vector.setData(bData);
CompositeSequence cs = csMap.get(matrix.getRowName(i));
if (cs == null) {
continue;
}
vector.setDesignElement(cs);
vector.setBioAssayDimension(bad);
vector.setQuantitationType(qtype);
dataVectors.add(vector);
}
AbstractCLI.log.info("Read " + dataVectors.size() + " data vectors");
} catch (Exception e) {
return e;
}
this.linkAnalysisService.processVectors(this.taxon, dataVectors, filterConfig, linkAnalysisConfig);
} else {
/*
* Do in decreasing order of size, to help capture more links earlier - reduces fragmentation.
*/
List<BioAssaySet> sees = new ArrayList<>(expressionExperiments);
if (expressionExperiments.size() > 1) {
AbstractCLI.log.info("Sorting data sets by number of samples, doing large data sets first.");
Collection<ExpressionExperimentValueObject> vos = eeService.loadValueObjects(EntityUtils.getIds(expressionExperiments), true);
final Map<Long, ExpressionExperimentValueObject> idMap = EntityUtils.getIdMap(vos);
Collections.sort(sees, new Comparator<BioAssaySet>() {
@Override
public int compare(BioAssaySet o1, BioAssaySet o2) {
ExpressionExperimentValueObject e1 = idMap.get(o1.getId());
ExpressionExperimentValueObject e2 = idMap.get(o2.getId());
assert e1 != null : "No valueobject: " + e2;
assert e2 != null : "No valueobject: " + e1;
return -e1.getBioMaterialCount().compareTo(e2.getBioMaterialCount());
}
});
}
for (BioAssaySet ee : sees) {
if (ee instanceof ExpressionExperiment) {
this.processExperiment((ExpressionExperiment) ee);
} else {
throw new UnsupportedOperationException("Can't handle non-EE BioAssaySets yet");
}
}
this.summarizeProcessing();
}
return null;
}
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