Nothing
wait <- function(vign=0) {
if (vign!=0) {
if (vign==1) {
ANSWER <- readline("Do you want to open the vignette? (y/n) ")
if (substr(tolower(ANSWER), 1, 1) == "y")
vignette("mefa", package = "mefa")}
if (vign==2) {
ANSWER <- readline("Do you want to check out mefa website? (y/n) ")
if (substr(tolower(ANSWER), 1, 1) == "y")
mefaweb()}
} else {
ANSWER <- readline("Please press ENTER to continue ... ")
}
}
cat("## Demo for the 'mefa' package")
wait(1)
cat("## Load the package and the example data set")
library(mefa)
data(dol.count, dol.samp, dol.taxa)
str(dol.count)
str(dol.samp)
str(dol.taxa)
wait()
cat("## Object classes")
cat("## 'stcs'")
x1 <- stcs(dol.count)
str(x1)
unique(x1$count)
wait()
x2 <- stcs(dol.count, expand = TRUE)
str(x2)
sum(x2$count)
unique(x2$count)
wait()
x3 <- stcs(dol.count, drop.zero = TRUE)
str(x3)
unique(x3$count)
wait()
cat("## 'mefa'")
m1 <- mefa(x1)
m1
m1$xtab["LT1", ]
wait()
str(m1$xtab)
str(m1$segm)
wait()
mefa(x1, nested = TRUE)
wait()
mefa(x1, segment = FALSE)
wait()
mefa(x1, dol.samp)
mefa(x1, , dol.taxa)
wait()
m2 <- mefa(x1, dol.samp, dol.taxa)
m2
str(m2$xtab)
str(m2$samp)
str(m2$taxa)
wait()
m2.sub <- mefa(x1, dol.samp[-c(1:5), ], dol.taxa[-c(1:80), ], xtab.fixed = FALSE)
m2.sub
str(m2.sub$xtab)
str(m2.sub$samp)
str(m2.sub$taxa)
wait()
mefalogo()
wait()
cat("## S3 methods")
dim(m2)
dimnames(m2)
wait()
summary(m2)
wait()
names(summary(m2))
summary(m2)$s.rich
summary(m2)$mfill
wait()
opar <- par(mfrow = c(1, 2))
plot(m2, 1, main="A")
plot(m2, 4, type="rank", trafo="log", main="B")
par(opar)
wait()
opar <- par(mfrow = c(1, 2))
boxplot(m2, 2, main = "A")
boxplot(m2, 3, main = "B")
par(opar)
wait()
molten <- melt(m2, "method")
str(molten)
wait()
m3 <- mefa(molten, dol.samp, dol.taxa)
m3
wait()
opar <- par(mfrow = c(1, 3))
image(m3, trafo = "log", sub = "all segments", main="A")
for (i in 1:2)
image(m3, segm = i, trafo = "log",
sub = dimnames(m3)$segm[i], main = LETTERS[i + 1])
par(opar)
wait()
ex1 <- m2[1:20, 11:15, "fresh"]
dim(ex1)
dim(ex1$samp)
dim(ex1$taxa)
wait()
ex2 <- m2[m2$samp$method == "time"]
levels(ex2$samp$method)
ex3 <- m2[m2$samp$method == "time", drop = TRUE]
levels(ex3$samp$method)
wait()
size.5 <- as.factor(is.na(m3$taxa$size) | m3$taxa$size < 5)
levels(size.5) <- c("large", "small")
m4 <- aggregate(m3, "microhab", size.5)
t(m4$xtab)
lapply(m4$segm, t)
wait()
cat("## Writing reports")
#set.seed(1234)
#m5 <- m2[ , sample(1:dim(m2)[2], 10)]
#report(m5, "report.tex", tex = TRUE,
# segment = TRUE, taxa.name = 1, author.name = 2,
# drop.redundant = 1)
cat("## see mefadocs(\"SampleReport\") also")
wait()
cat("## Data analysis")
mod.amin <- glm(m2$xtab[, "amin"] ~ .,
data = m2$samp, family = poisson)
summary(mod.amin)
wait()
library(MASS)
mod.abu <- glm.nb(summary(m2)$s.abu ~ .^2,
data = m2$samp)
summary(mod.abu)
wait()
prop.fr <- cbind(summary(m2[ , , "fresh"])$s.abu, summary(m2)$s.abu)
mod.fr <- glm(prop.fr ~ .^2,
data = m2$samp, family = binomial)
summary(mod.fr)
wait()
if (require(vegan)) {
m6 <- m2[summary(m2)$s.abu != 0, , ]
m6.ado <- adonis(m6$xtab ~ .^2,
data = m6$samp, permutations = 100)
m6.ado
}
wait()
if (require(vegan)) {
m2.cca <- cca(m2$segm[["fresh"]] ~ ., data=m2$samp,
subset=rowSums(m2$segm[["fresh"]]) > 0)
plot(m2.cca)
}
wait()
m.list <- list()
n1 <- rep(c("time", "quadrat"), each = 2)
n2 <- rep(c("fresh", "broken"), 2)
n3 <- paste(n1, n2, sep=".")
for (i in 1:4) {
m.list[[n3[i]]] <-
aggregate(m2[m2$samp$method == n1[i], , n2[i]], "microhab")
}
wait()
opar <- par(mfrow=c(2, 2))
for (i in 1:4) {
tmp <- hclust(dist(m.list[[i]]$xtab), "ward")
plot(tmp, main = LETTERS[i], sub = names(m.list)[i], xlab = "")
}
par(opar)
cat("## End of mefa demo\n")
wait(2)
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