use of org.cytoscape.work.TunableSetter in project cytoscape-impl by cytoscape.
the class LoadVizmapFileTaskFactoryTest method testObserver.
@Test
public void testObserver() throws Exception {
VizmapReaderManager vizmapReaderMgr = mock(VizmapReaderManager.class);
VizmapReader reader = mock(VizmapReader.class);
when(vizmapReaderMgr.getReader(any(URI.class), any(String.class))).thenReturn(reader);
VisualMappingManager vmMgr = mock(VisualMappingManager.class);
SynchronousTaskManager<?> syncTaskManager = mock(SynchronousTaskManager.class);
SyncTunableMutatorFactory mutatorFactory = new SyncTunableMutatorFactory(new SyncTunableHandlerFactory());
TunableRecorderManager recorderManager = new TunableRecorderManager();
TunableSetter tunableSetter = new TunableSetterImpl(mutatorFactory, recorderManager);
CyServiceRegistrar serviceRegistrar = mock(CyServiceRegistrar.class);
when(serviceRegistrar.getService(VizmapReaderManager.class)).thenReturn(vizmapReaderMgr);
when(serviceRegistrar.getService(VisualMappingManager.class)).thenReturn(vmMgr);
when(serviceRegistrar.getService(SynchronousTaskManager.class)).thenReturn(syncTaskManager);
when(serviceRegistrar.getService(TunableSetter.class)).thenReturn(tunableSetter);
LoadVizmapFileTaskFactory factory = new LoadVizmapFileTaskFactoryImpl(serviceRegistrar);
File file = new File("");
TaskObserver observer = mock(TaskObserver.class);
TaskIterator iterator = factory.createTaskIterator(file, observer);
TaskMonitor taskMonitor = mock(TaskMonitor.class);
while (iterator.hasNext()) {
Task t = iterator.next();
t.run(taskMonitor);
if (t instanceof ObservableTask)
observer.taskFinished((ObservableTask) t);
}
verify(observer, times(1)).taskFinished(any(ObservableTask.class));
}
use of org.cytoscape.work.TunableSetter in project PhenomeScape by soulj.
the class PhenomeExpress method run.
@Override
public void run(TaskMonitor taskMonitor) throws Exception {
taskMonitor.setTitle("Running PhenomeExpress");
taskMonitor.setStatusMessage("Preparing Networks");
long time = System.currentTimeMillis();
inputCheck();
setUpNetworks();
double[] relativeWeighting = { 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 };
double[] alphas = { 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 };
double[] piValues = proteinNetwork.getPivalues();
Map<String, Integer> phenotypeMap = phenomeNetwork.getName2IndexMap();
double[] phenoArray = new double[phenomeNetwork.getName2IndexMap().size()];
selectedPhenotypes = new ArrayList<Phenotype>();
boolean first = true;
for (Phenotype phenotype : phenotypes) {
if (phenotype.getSelected()) {
if (first) {
phenotypeSelected = phenotype.getID();
phenotypeNamesSelected = phenotype.getName();
selectedPhenotypes.add(phenotype);
phenoArray[phenotypeMap.get(phenotype.getID())] = 1.0;
first = false;
} else {
phenotypeSelected = phenotypeSelected + " ," + phenotype.getID();
phenotypeNamesSelected = phenotypeNamesSelected + " ," + phenotype.getName();
phenoArray[phenotypeMap.get(phenotype.getID())] = 1.0;
selectedPhenotypes.add(phenotype);
}
}
}
Map<CyNode, Integer> map = proteinNetwork.getNode2IndexMap();
int size = proteinNetwork.getNetwork().getNodeCount();
int[] occuranceArray = new int[size];
HashMap<CyNode, Protein> node2Protein = new HashMap<CyNode, Protein>();
if (cancelled) {
return;
}
taskMonitor.setStatusMessage("Calculating Activity Scores");
taskMonitor.setProgress(0.0);
double progress = 0.0;
SparseRowMatrix adjMatrix = SparseRowMatrix.create(size, size);
double[] transitionProbs = { 0.5, 0.6, 0.7, 0.8 };
for (double transitionProb : transitionProbs) {
TransitionMatrix transitionMatrix = new TransitionMatrix(phenomeNetwork.normalise(transitionProb, phenoGeneNetwork), proteinNetwork.normalise(transitionProb, phenoGeneNetwork), phenoGeneNetwork.normaliseT(transitionProb), phenoGeneNetwork.normalise(transitionProb));
for (double weighting : relativeWeighting) {
if (cancelled) {
return;
}
transitionMatrix.prepareVector(piValues, phenoArray, weighting);
for (double alpha : alphas) {
progress += 0.0051;
taskMonitor.setProgress(progress);
double[] pageRankResults = transitionMatrix.pageRank(alpha);
HashMap<Integer, Protein> index2ProteinMap = proteinNetwork.getIndex2ProteinMap();
for (int i = 0; i < index2ProteinMap.size(); i++) {
Protein protein = index2ProteinMap.get(i);
protein.setValue(pageRankResults[i]);
}
List<Protein> proteinList = new ArrayList<Protein>(index2ProteinMap.values());
Collections.sort(proteinList, new DescendingScoreComparator());
int rank = 0;
for (Protein protein : proteinList) {
rank++;
protein.setRank(rank);
node2Protein.put(protein.getNode(), protein);
}
Collections.sort(proteinList, new DescendingScoreComparator());
GIGA giga = new GIGA(proteinList, node2Protein, proteinNetwork, maxNetworkSize);
giga.compute();
for (GIGACluster cluster : giga.getClusters()) {
for (CyNode node : cluster.getCluster()) {
Integer index = map.get(node);
AVector row = adjMatrix.getRow(index);
if (!row.isMutable()) {
row = row.mutable();
}
for (CyNode node2 : cluster.getCluster()) {
Integer index2 = map.get(node2);
row.set(index2, row.get(index2) + 1.0);
occuranceArray[index2]++;
}
adjMatrix.replaceRow(index, row);
}
}
}
}
}
if (cancelled) {
return;
}
taskMonitor.setProgress(1.0);
taskMonitor.setStatusMessage("Creating Consensus Subnetworks");
AMatrix cooccuranceMat = adjMatrix.transposeInnerProduct(adjMatrix);
for (int i = 0; i < size; i++) {
AVector row = cooccuranceMat.getRow(i);
if (row.elementSum() > 0) {
row.divide(occuranceArray[i]);
Index nonSparse = row.nonSparseIndex();
for (int j = 0; j < nonSparse.length(); j++) {
if (row.get(nonSparse.get(j)) < 1.0) {
row.set(nonSparse.get(j), 0.0);
}
}
cooccuranceMat.replaceRow(i, row.sparse());
}
}
ConnectedComponentAnalyser CCA = new ConnectedComponentAnalyser(node2Protein);
ArrayList<PhenomeExpressSubnetwork> subnetworks = CCA.ccFromAdjMatrix(adjMatrix, proteinNetwork);
Iterator<PhenomeExpressSubnetwork> it = subnetworks.iterator();
while (it.hasNext()) {
PhenomeExpressSubnetwork subnetwork = it.next();
if (subnetwork.getNodeList().size() < this.minNetSize) {
it.remove();
}
}
if (cancelled) {
return;
}
taskMonitor.setStatusMessage("Calculating Subnetwork Significance");
subnetworksSignificance(subnetworks);
taskMonitor.setStatusMessage("Visualising Subnetworks");
List<Double> foldChangeValues = proteinNetwork.getNodeTable().getColumn(foldChange).getValues(Double.class);
double fcMax = Collections.max(foldChangeValues);
double fcMin = Collections.min(foldChangeValues);
// Apply the visual style to a NetworkView
VizStyle vizStyle = new VizStyle();
VisualStyle vs = vizStyle.createVizStyle(cyServiceRegistrar, geneName, foldChange, fcMax, fcMin);
this.property = getNodeLabelPositionProperty();
vs.setDefaultValue(property, property.parseSerializableString("N,S,c,0.0,0.0"));
VisualMappingManager visualMappingManager = cyServiceRegistrar.getService(VisualMappingManager.class);
visualMappingManager.setCurrentVisualStyle(vs);
ArrayList<CyNetworkView> networkViewList = new ArrayList<CyNetworkView>();
Iterator<PhenomeExpressSubnetwork> it2 = subnetworks.iterator();
CyNetworkManager networkManager = cyServiceRegistrar.getService(CyNetworkManager.class);
CyNetworkViewFactory networkViewFactory = cyServiceRegistrar.getService(CyNetworkViewFactory.class);
CyLayoutAlgorithmManager layoutManager = cyServiceRegistrar.getService(CyLayoutAlgorithmManager.class);
CyApplicationManager cyApplicationManager = cyServiceRegistrar.getService(CyApplicationManager.class);
CyLayoutAlgorithm layout = layoutManager.getLayout("force-directed");
Map<String, Object> settings = new HashMap<String, Object>();
settings.put("defaultSpringLength", 5.0);
settings.put("defaultSpringNodeMass", 2.0);
TunableSetter setter = cyServiceRegistrar.getService(TunableSetter.class);
Object context = layout.createLayoutContext();
setter.applyTunables(context, settings);
GOTermAnalyser2 goTermAnalyser = new GOTermAnalyser2(proteinNetwork, species);
while (it2.hasNext()) {
PhenomeExpressSubnetwork subnet = it2.next();
if (subnet.getPvalue() > this.threshold) {
it2.remove();
} else {
goTermAnalyser.calculateGOTermPValues(subnet, proteinNetwork);
String subnetworkName = NetworkUtils.getUniqueNetworkName(cyServiceRegistrar, networkName + "_" + subnet.getBestGOTerm());
subnet.setName(subnetworkName);
CySubNetwork subnetwork = NetworkUtils.createSubNetwork(((CySubNetwork) proteinNetwork.getNetwork()).getRootNetwork(), subnet.getNodeList());
subnetwork.getRow(subnetwork).set(CyNetwork.NAME, subnetworkName);
addSeedPhenotypes(subnetwork);
networkManager.addNetwork(subnetwork);
CyNetworkViewManager viewManager = cyServiceRegistrar.getService(CyNetworkViewManager.class);
CyNetworkView nv = networkViewFactory.createNetworkView(subnetwork);
viewManager.addNetworkView(nv);
cyApplicationManager.setCurrentNetworkView(nv);
for (CyNode phenoNode : phenotypesAdded) {
View<CyNode> nodeView = nv.getNodeView(phenoNode);
nodeView.setLockedValue(BasicVisualLexicon.NODE_SHAPE, NodeShapeVisualProperty.RECTANGLE);
nodeView.setLockedValue(BasicVisualLexicon.NODE_FILL_COLOR, Color.BLUE);
}
for (CyEdge phenoEdge : phenoEdges) {
View<CyEdge> edgeView = nv.getEdgeView(phenoEdge);
edgeView.setLockedValue(BasicVisualLexicon.EDGE_LINE_TYPE, LineTypeVisualProperty.DOT);
edgeView.setLockedValue(BasicVisualLexicon.EDGE_PAINT, Color.BLUE);
}
networkViewList.add(nv);
Set<View<CyNode>> nodeSet = Collections.emptySet();
cyServiceRegistrar.getService(TaskManager.class).execute(layout.createTaskIterator(nv, context, nodeSet, null));
}
}
CyEventHelper cyEventHelper = cyServiceRegistrar.getService(CyEventHelper.class);
for (CyNetworkView nv : networkViewList) {
visualMappingManager.setVisualStyle(vs, nv);
vs.apply(nv);
cyEventHelper.flushPayloadEvents();
cyApplicationManager.setCurrentNetworkView(nv);
nv.updateView();
}
phenomeNetwork = null;
proteinNetwork = null;
ResultsPanel resultsPanel = (ResultsPanel) CytoPanelUtils.getCytoPanel(cyServiceRegistrar, ResultsPanel.class, CytoPanelName.EAST);
resultsPanel.newTableData(getResultsSummary(subnetworks), getParameterList());
CytoPanelUtils.showCytoPanel(cyServiceRegistrar, CytoPanelName.EAST);
}
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