Nothing
`check.datasets` <-
function(x, y) {
factor.count <- 0
factor.species <- NULL
na.count <- 0
na.species <- NULL
neg.count <- 0
neg.species <- NULL
all.good <- TRUE
for (i in 1:ncol(x)) {
if(is.factor(x[,i])) {
factor.count <- factor.count+1
factor.species <- c(factor.species, colnames(x)[i])
}
if(any(is.na(x[,i]))) {
na.count <- na.count+1
na.species <- c(na.species, colnames(x)[i])
}
if(any(x[,i] < 0, na.rm=T)) {
neg.count <- neg.count+1
neg.species <- c(neg.species, colnames(x)[i])
}
}
if (factor.count > 0) {
all.good <- FALSE
cat("Warning:", factor.count, "variable(s) of the community dataset ( out of a total of", ncol(x), ") are factors\n")
print(factor.species)
}
if (na.count > 0) {
all.good <- FALSE
cat("Warning:", na.count, "variable(s) of the community dataset ( out of a total of", ncol(x), ") with missing values\n")
print(na.species)
}
if (neg.count > 0) {
all.good <- FALSE
cat("Warning:", neg.count, "variable(s) of the community dataset ( out of a total of", ncol(x), ") with negative values\n")
print(neg.species)
}
if(nrow(x)!=nrow(y)){
all.good <- FALSE
cat("Warning: community and environmental datasets have different numbers of rows\n")
}else{
if(any(rownames(x)!=rownames(y))){
all.good <- FALSE
cat("Warning: rownames for community and environmental datasets are different\n")
}
}
if (all.good == TRUE) {cat("OK\n")}
}
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