edgeAB.pairwiseScore3 = spectralPlotting.associateMassDeltasEps(
candidateDeltas, massDeltaValue, .02)
totalPairwiseScore += edgeAB.pairwiseScore
totalPairwiseScore2 += edgeAB.pairwiseScore2
totalPairwiseScore3 += edgeAB.pairwiseScore3
candidateEdgeList.append(edgeAB)
candidateNetwork.pairwiseScore = totalPairwiseScore
candidateNetwork.pairwiseScore2 = totalPairwiseScore2
candidateNetwork.pairwiseScore3 = totalPairwiseScore3
candidateNetwork.candidateEdges = candidateEdgeList
#Using the set of edges in the candidate network, construct an Maximum Spanning Tree using pairwiseScore as the edge weight.
maximalSpanningTree = MST.spanningTree(candidateEdgeList,
lambda x: x.pairwiseScore,
maximal=True)
mstScore = 0
for edge in maximalSpanningTree:
mstScore += edge.pairwiseScore
candidateNetwork.mstScore = mstScore
candidateNetwork.mstEdges = maximalSpanningTree
#Double check results before sending to bahar :D
totalEdgesSG = 0
for nodeID in group:
totalEdgesSG += len(SG.nodes[nodeID].neighbors)
for candidateNetwork in allSequences[1]:
candidateSet = set([])
