pedroj

# Example of setting row and column names
mdat <- matrix(c(1,2,3, 11,12,13), nrow = 2, ncol=3, byrow=TRUE,
               dimnames = list(c("row1", "row2"),
                               c("C.1", "C.2", "C.3")))
mdat

pedroj

# Order columns in a table
fakedata <- data.frame(A=c(0,0,0), X2=c(2,2,2), X1=c(1,1,1), X3=c(3,3,3))

fakedata
 A X2 X1 X3
1 0  2  1  3
2 0  2  1  3
3 0  2  1  3

pos <- colnames(fakedata)[2:ncol(fakedata)]

pedroj

# For larger graphs calculate the intersection 
# of the two graphs, this is reasonably fast, and then 
# the Hamming distance is the number of edges in the 
# symmetric difference. (If i'm right...)

int <- graph.intersection(g1,g2)
ecount(g1)+ecount(g2)-2*ecount(int)

pedroj

#--------------------------------------------------
# Contingency table
#--------------------------------------------------
# Productivity Smoking   No smoking
# High         13        44
# Low          25        29

count<-c(13,25,44,29)
smoking<-factor(c("Yes","Yes","No","No"))
productivity<-factor(c("High","High","Low","Low"))

pedroj

##############################################################################
### Read network data
# network
mont1<-read.paj("Monteverde.net",verbose=T)
nch1<-read.paj("nch.net",verbose=T)
hr1<-read.paj("hr.net",verbose=T)
# Initializing bipartite webs for library network
nch1<-network.initialize(dim(nch_lab)[1]+dim(nch_lab)[2],
                         bipartite=c(dim(nch_lab)[1]),directed=F)
nch1 <-network.bipartite(as.matrix(nch_lab),nch1)

pedroj

##############################################################################
# Code for plotting the networks. Library bipartite.
# Pedro Jordano. 2 Mar 2007. Rev 4 Apr 2008
#
#-----------------------------------------------------------------------------
# Initializing the datasets
###
# Enter the adjacency matrix directly
myweb1<- read.delim("myweb.txt", row.names=1,,header=F,sep="\t")
plotweb(nch1, method="cca", text.rot="90", labsize=0.8, col.low="green",

pedroj

##############################################################################
# Code for plotting the networks. Library bipartite.
# Pedro Jordano. 2 Mar 2007. Rev 4 Apr 2008
#-----------------------------------------------------------------------------
# Initializing the datasets
# Enter the adjacency matrix directly
myweb1<- read.delim("myweb.txt", row.names=1,,header=F,sep="\t")
plotweb(nch1, method="cca", text.rot="90", labsize=0.8, col.low="green",
col.high="yellow", col.interaction="blue")

pedroj

#--------------------------------------------------------------
# Ordering matrices. Web must be a matrix with 'dimnames'
#--------------------------------------------------------------
mat.ord <- function(web) {
        web.ord <- web[order(rowSums(web), decreasing = TRUE), 
            order(colSums(web), decreasing = TRUE)]
            web.ord
            }

pedroj

##############################################################################
# Plotting the degree distribution.
#-----------------------------------------------------------------------------
# Assign the matrix to be analized
#-----------------------------------------------------------------------------
mat<-as.matrix(nch_lab)
#-----------------------------------------------------------------------------
# Degree
#-----------------------------------------------------------------------------
# Animals

pedroj

#################################################################
# Network analyses.
# Pedro. 7 Dec 2007
#################################################################
# NOTE: These matrices have rows are animals, columns are plants. 
# NOTE: JORDI's datasets for NESTEDNESS have Rows are plants, 
# columns are animals.
library(bipartite)
library(networksis)
library(igraph)