# reducedConnMat: Reduced connectivity matrix according to a set of... In ConnMatTools: Tools for Working with Connectivity Data

## Description

Reduces a connectivity matrix based on a set of subpopulations. If there are N subpopulations, then the reduced matrix will have dimensions NxN. The reduced matrix will be ordered according to the order of subpopulations in `subpops.lst`.

## Usage

 `1` ```reducedConnMat(subpops.lst, conn.mat) ```

## Arguments

 `subpops.lst` A list whose elements are vectors of indices for each subpopulation. If a vector of integers is given, then `subpopsVectorToList` is applied to convert it to a list of subpopulations. `conn.mat` A square connectivity matrix.

## Value

A reduced connectivity matrix. The sum of all elements of this reduced connectivity matrix will be equal to the sum of all elements of the original connectivity matrix.

## Author(s)

David M. Kaplan [email protected]

## References

Jacobi, M. N., Andre, C., Doos, K., and Jonsson, P. R. 2012. Identification of subpopulations from connectivity matrices. Ecography, 35: 1004-1016.

See also `qualitySubpops`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```library(ConnMatTools) data(chile.loco) num <- prod(dim(chile.loco)) / sum(chile.loco) betas <- betasVectorDefault(n=num,steps=4) chile.loco.split <- optimalSplitConnMat(chile.loco,normalize.cols=FALSE, betas=betas) # Extra 3rd division print(paste("Examining split with",names(chile.loco.split\$best.splits)[1], "subpopulations.")) pops <- subpopsVectorToList(chile.loco.split\$subpops[,chile.loco.split\$best.splits[[1]]\$index]) reduce.loco <- reducedConnMat(pops,chile.loco) sr <- selfRecruitment(reduce.loco) lr <- localRetention(reduce.loco) rlr <- relativeLocalRetention(reduce.loco) ```