AlignNetworks {GraphAlignment}R Documentation

Align networks


Align networks A and B.


AlignNetworks(A, B, R, P, linkScore, selfLinkScore, nodeScore1,
  nodeScore0, lookupLink, lookupNode, bStart, bEnd, maxNumSteps, clamp=TRUE, 


A adjacency matrix for network A
B adjacency matrix for network B
R node similarity matrix
P permutation vector to be used as the initial alignment
linkScore link score matrix
selfLinkScore self link score matrix
nodeScore1 node score vector (s1)
nodeScore0 node score vector for unaligned nodes (s0)
lookupLink link bin lookup table
lookupNode node bin lookup table
bStart start scaling value for simulated annealing
bEnd end scaling value for simulated annealing
maxNumSteps maximum number of steps
clamp clamp values to range when performing bin lookups
directed whether input networks should be treated as directed graphs


The return value is a permutation vector p which aligns nodes from network a with nodes from network B (including dummy nodes). The returned permutation should be read in the following way: the node i in the network A is aligned to that node in the network B which label is at the i-th position of the permutation vector p. If the label at this position is larger than the size of the network B, the node i is not aligned.


  ex<-GenerateExample(dimA=22, dimB=22, filling=.5, covariance=.6,
    symmetric=TRUE, numOrths=10, correlated=seq(1,18))
  pinitial<-InitialAlignment(psize=34, r=ex$r, mode="reciprocal")
  linkParams<-ComputeLinkParameters(ex$a, ex$b, pinitial, lookupLink)
  nodeParams<-ComputeNodeParameters(dimA=22, dimB=22, ex$r,
    pinitial, lookupNode)
  al<-AlignNetworks(A=ex$a, B=ex$b, R=ex$r, P=pinitial,
    nodeScore1=nodeParams$s1, nodeScore0=nodeParams$s0,
    lookupLink=lookupLink, lookupNode=lookupNode,
    bStart=.1, bEnd=30,

[Package GraphAlignment version 1.0-0 Index]