# Example of using the Reshape package to make encounter histories for RMark

#Note: this only works if you capture at least one individual per trapping session.  If you didn't, add a blank row to the data set for each session in which you did not catch an individual.  An alternative approach to using Reshape is to create a dummy (null) list of all possible capture dates and then merge with your data.              

#Be sure to install the Reshape package!

#Make fake banding data that have a single row for each capture per individual
bn<-c("1","1","2","3","3","3","4","5","6","6","7","8","9") #fake band numbers
season<-c(1,2,3,1,2,3,1,4,3,4,1,1,1) #fake seasons 
recapture<-c(1,1,1,1,1,1,1,1,1,1,1,1,1) #extra column needed for data organization
bd<-data.frame(bn=bn, season=season, recapture=recapture) #banding data

#Reshape data from rows to table
library("reshape")
bdm=melt(bd, id = c("bn", "season"), measured = c("recapture")) # melt data
bdc=cast(bdm, bn ~ season, min) #casts the molten data into a new form. could use min, max, or ave, since all are 1s.
 bdc
#replace Inf with 0.
bdc=as.matrix(bdc) #matrix format is needed to remove Infs, but removes column "bn" for some reason(?). 
 head(bdc)
bdc[which(bdc==Inf)]<-0
bdc=as.data.frame(bdc) #adds column "bn" back in.
colnames(bdc)=c("Al.band", "S1", "S2", "S3", "S4") #Add 'S' so that column names are not numeric, which is important for RMark
 head(bdc)
bdc$ch=paste(bdc$S1, bdc$S2, bdc$S3, bdc$S4, sep='') #concatenate into new capture history (ch) column
bdc=subset(bdc, select = -c(2, 3, 4, 5)) #remove extra columns
#From here, you can merge() with covariates for each bird by using band number.  Before importing to RMark, you need to remove the band numbers.
chdata<-bdc[,-1]
chdata
str(chdata)