我有一个函数(bobB)似乎陷入了一个while循环。当我点击转义并查看 warnings() 时,出现以下错误:
Warning message:
In min(xf, yf) : no non-missing arguments to min; returning Inf
一些示例代码:
#I have the data:
x<-"A03"
y<-"A24"
sitex<-c("Sp1","Sp1","Sp3","Sp3")
sitey<-c("Sp2","Sp4","Sp2","Sp4")
gsim<-c(0.2,0.3,0.4,0.1)
gsim<-data.frame(sitex,sitey,gsim)
site<-c("A03","A03","A03","A03","A24","A24","A24","A24")
species<-c("Sp1","Sp1","Sp3","Sp4","Sp1","Sp1","Sp3","Sp4")
freq<-c(0.2,0.3,0.4,0.1,0.3,0.3,0,0.4)
ssf<-data.frame(site,species,freq,stringsAsFactors=FALSE)
#My function:
bobB <- function (x, y, ssf, gsim) {
#*Step 1.* Create an empty matrix 'specfreq' to fill
#Selects the species frequency data greater than 0 for the two sites being compared
ssfx <- ssf[ssf$site == x & ssf$freq >0,]
ssfy <- ssf[ssf$site == y & ssf$freq >0,]
#pull out the species that are present at site x and/or site y using a merge,
#this is needed to create the initial empty matrix
m<-(merge(ssfx,ssfy,all=TRUE))
species<-unique(m$species)
#Creates an empty matrix of the frequency of each species at site x and y
specfreq <- matrix(0, length(species), 2, dimnames=list(species,c(x,y)))
#*Step 2.* Fill empty matrix 'specfreq' with data from data.frame 'ssf'
for(i in 1:nrow(ssf{specfreq[rownames(specfreq)==ssf[i,"species"],colnames(specfreq)==ssf[i,"site"]] <- ssf[i,"freq"]}
#*Step 3.* For species present at site x and y remove the minimum of the two from both
#find minimum frequency for each species for site x and y
a <- pmin(specfreq[,x], specfreq[,y])
#subtract 'a' from current 'specfreq'
specfreq <- specfreq - a
#*Step 4.* Calulate variable B
#Set answer to 0
answer <- 0
#while 'specfreq' contains data (i.e. is >0) keep doing the following
while(sum(specfreq) > 1e-10) {
#Find species remaining at site x
sx <- species[specfreq[,1] > 0]
#Find species remaining at site y
sy <- species[specfreq[,2] > 0]
#Pull out the gsim value for sx and sy
gsimre <-gsim[gsim$sitex %in% sx & gsim$sitey %in% sy,]
#determines the row containing the maximum value for remaining gsim and assigns it to i
i <- which.max(gsimre$gsim)
#once the max gsim value has been found (i) we go back to the specfreq matrix and filter
#out the frequency of the site x species associated with i
xf <- specfreq[(gsimre$sitex[i]),x]
#and the frequency of the site y species associated with i
yf <- specfreq[(gsimre$sitey[i]),y]
#The frequency of the species at site x associated with the greatest i is multiplied by i
answer <- answer + xf * gsimre$gsim[i]
#Then take the minimum common frequency for the two species associated with i
f <- min(xf,yf)
#Subtract theminimum common frequency from both the site x and site y column
specfreq[gsimre$sitex[i],x] <- specfreq[gsimre$sitex[i],x]-f
specfreq[gsimre$sitey[i],y] <- specfreq[gsimre$sitey[i],y]-f
}
answer
}
bobB(x, y, ssf, gsim)