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https://github.com/jsta/dcir
Calculate Directional Connectivity Index without Matlab
https://github.com/jsta/dcir
Last synced: about 1 month ago
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Calculate Directional Connectivity Index without Matlab
- Host: GitHub
- URL: https://github.com/jsta/dcir
- Owner: jsta
- Created: 2015-04-23T00:39:40.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2016-07-31T00:16:05.000Z (over 8 years ago)
- Last Synced: 2024-06-11T17:07:48.012Z (7 months ago)
- Language: Matlab
- Homepage:
- Size: 295 KB
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
dciR
====
[](http://www.repostatus.org/#unsupported)
THIS VERSION ONLY WORKS ON LINUX DUE TO INCOMPATABILITY BETWEEN RcppOctave AND WINDOWS!
A modification of the directional connectivity index calculation from Larsen et al. (2012). Essentially replaces [MatlabBGL](http://dgleich.github.com/matlab-bgl/) with [RBGL](http://www.bioconductor.org/packages/release/bioc/html/RBGL.html). For convenience, Octave is called from R using [RcppOctave](http://cran.r-project.org/web/packages/RcppOctave/index.html).
Requires RBGL, Octave, and RcppOctave (verified to work with version 3.8.1 and 0.14.5 respectively)
## Installation
```R
install.packages('devtools') # package devtools needed
devtools::install_github('jsta/dciR')
source("http://bioconductor.org/biocLite.R")
biocLite("RBGL")
#biocLite("Rgraphviz")
```
## Examples
```R
#The example below reproduces figure 3 from Larsen et al. (2012)#####
library(dciR)
#load test matricies####
ma <- matrix(c(0,0,1,0,0,0,1,0,1,0,0,1,0,0,1,0,0,0,1,0,1,1,0,0,0),nrow=5,byrow=T)
mb <- matrix(c(1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,1,1,0,0),nrow=5,byrow=T)
mc <- matrix(c(1,0,1,0,1,1,0,1,0,1,1,0,1,0,1,1,0,1,0,1,1,0,1,0,1),nrow=5,byrow=T)
md <- matrix(c(1,0,0,0,1,1,0,1,0,1,0,0,1,0,0,1,0,0,0,1,1,0,0,0,1),nrow=5,byrow=T)
data.frame(cbind(letters[1:4],round(unlist(lapply(list(ma,mb,mc,md),function(x) dci(x,1,1))),3)))
#The example below reproduces Figure 4####
library(jpeg)
library(raster)
c1<-readJPEG(system.file("images","conserved1.jpg",package="dciR"))
c2<-readJPEG(system.file("images","conserved2.jpg",package="dciR"))
s1<-readJPEG(system.file("images","sim1.jpg",package="dciR"))
r1<-readJPEG(system.file("images","rotated1.jpg",package="dciR"))
d1<-readJPEG(system.file("images","degraded1.jpg",package="dciR"))
c1<-raster(matrix(c1,nrow=dim(c1)[1],ncol=dim(c1)[2]))<0.4
c2<-raster(matrix(c2,nrow=dim(c2)[1],ncol=dim(c2)[2]))<0.4
s1<-raster(matrix(s1,nrow=dim(s1)[1],ncol=dim(s1)[2]))<0.4
r1<-raster(matrix(r1,nrow=dim(r1)[1],ncol=dim(r1)[2]))<0.4
d1<-raster(matrix(d1,nrow=dim(d1)[1],ncol=dim(d1)[2]))<0.4
par(mfrow=c(1,5))
lapply(c(c1,c2,s1,r1,d1),function(x) plot(x,bty="n",box=FALSE,axes=FALSE,legend=FALSE))
```
```R
#The example below reproduces Figure 5####
ret<-list()
aglist<-4:22
ag_dci<-function(c1,ag){
c1r<-aggregate(c1,ag,fun=median)>0.7
c1mat<-as.matrix(c1r)
time<-system.time(val<-dci(c1mat,1,1))
list(time,val,sum(c1mat))
}
for(i in aglist){
ret[[i]]<-ag_dci(c1,i)
}
ret<-cbind(matrix(unlist(ret),ncol=7,byrow=T),aglist)
par(mfrow=c(1,2))
plot(ret[,7]/10000,ret[,1],log="y",yaxt="n",xlim=c(0,3),ylim=c(1,10000),xlab="Number of nodes x 10^4",ylab="Computation time (s)")
labels<-sapply(seq(0,3,1),function(i) as.expression(bquote(10^ .(i))))
axis(2,at=c(1,10,100,1000),labels=labels)
plot(ret[,7]/10000,ret[,1],xlab="Number of nodes x 10^4",ylab="")
```
```R
#The example below reproduces Figure 6
ret<-matrix(unlist(lapply(c(c1,c2,s1,d1),function(x) ag_dci(x,16))),ncol=7,byrow=T)
barplot(ret[,6],names.arg=c("Conserved1","Conserved2","Sim1","Degraded1"),ylim=c(0,1),las=2)
```
## References
**Larsen, L. G., Choi, J., Nungesser, M. K., & Harvey, J. W. (2012)**. Directional connectivity in hydrology and ecology. *Ecological applications*, **22**(8), 2204-2220.