if species in adjacencyProbs:
adjacencyProbs[species][adj] = weight
else:
adjacencyProbs[species]={adj:weight}
line=f.readline()
f.close()
#dictionary for all scj distances
dict_SCJ={}
#compute CCs in global adjacency graph
ccs = globalAdjacencyGraph.createGraph(extantAdjacencies,nodesPerAdjacency)
if (not args.skip_first):
conflicts = globalAdjacencyGraph.analyseConnectedComponents(ccs)
globalAdjacencyGraph.outputConflicts(conflicts,args.output+"/conflicts")
jointLabels, first = SR.enumJointLabelings(ccs)
validLabels, validAtNode = SR.validLabels(jointLabels,first)
topDown = SR.computeLabelings(tree, ccs, validAtNode, extantAdjacencies, adjacencyProbs, args.alpha)
reconstructedAdj = SR.reconstructedAdjacencies(topDown)
SR.outputReconstructedAdjacencies(reconstructedAdj,args.output+"/reconstructed_adjacencies")
for node in reconstructedAdj:
print node
print "Number of reconstructed adjacencies: "+str(len(reconstructedAdj[node]))
scaffolds = scaffolding.scaffoldAdjacencies(reconstructedAdj)
undoubled = scaffolding.undoubleScaffolds(scaffolds)
def test_analyseConnectedComponents(self): globalAdjacencyGraph.analyseConnectedComponents(self.graphs)
