AlignNetworks {GraphAlignment} R Documentation

## Align networks

### Description

Align networks A and B.

### Usage

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

### Arguments

 `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

### Value

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.

### Examples

```  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")

lookupNode<-c(-.5,.5,1.5)
nodeParams<-ComputeNodeParameters(dimA=22, dimB=22, ex\$r,
pinitial, lookupNode)

al<-AlignNetworks(A=ex\$a, B=ex\$b, R=ex\$r, P=pinitial,