context("ordinationAxes")
test_that("ordinationAxes: use", {
# skip_on_cran()
set.seed(42)
n_traits <- 3
n_plots <- 10
num_species <- 10
x <- generate.Artificial.Data(n_species = num_species, n_traits = n_traits,
n_communities = n_plots,
occurence_distribution = 0.5,
average_richness = 10,
sd_richness = 1,
mechanism_random = TRUE)
data_species <- x$traits
data_abundances <- x$abundances
species <- scaleSpeciesvalues(data_species,n_traits)
abundances <- data_abundances
row.names(abundances) <- c(1:n_plots)
abundances2 <- as.data.frame(abundances)
species2 <- species[,c(2:(n_traits + 1))]
#species2 <- cbind(names(abundances2),species2)
species2 <- as.matrix(species2)
row.names(species2) <- names(abundances2)
# calculate observed FD values
Ord <- ordinationAxes(x = species2, stand.x = FALSE)
Ord <- ordinationAxes(x = species2, stand.x = TRUE)
v2 <- species2[1,]
v2[1:3] <- runif(3,0,1)
Ord <- ordinationAxes(x = v2, stand.x = FALSE)
v2[1:3] <- as.factor(c(1,1,2))
testthat::expect_warning(
v2 <- as.dist(v2)
)
testthat::expect_warning(
Ord <- ordinationAxes(x = v2, stand.x = FALSE)
)
set.seed(42)
n_traits <- 3
n_plots <- 10
num_species <- 10
x <- generate.Artificial.Data(n_species = num_species, n_traits = n_traits,
n_communities = n_plots,
occurence_distribution = 0.5,
average_richness = 10,
sd_richness = 1,
mechanism_random = TRUE)
data_species <- x$traits
data_species$trait4 <- c(rep("blue",3),
rep("red",2),
rep("yellow",2),
rep("black",3))
n_traits <- 4
# calculate observed FD values
Ord <- STEPCAM::ordinationAxes(x = data_species, stand.x = FALSE)
set.seed(42)
n_traits <- 1
n_plots <- 10
num_species <- 10
x <- generate.Artificial.Data(n_species = num_species, n_traits = n_traits,
n_communities = n_plots,
occurence_distribution = 0.5,
average_richness = 10,
sd_richness = 1,
mechanism_random = TRUE)
data_species <- x$traits
data_species$trait1 <- c(rep("blue",3),
rep("red",2),
rep("yellow",2),
rep("black",3))
# calculate observed FD values
testthat::expect_warning(
Ord <- ordinationAxes(x = data_species, stand.x = FALSE)
)
data_species$trait1 <- as.factor(data_species$trait1)
Ord <- ordinationAxes(x = data_species, stand.x = FALSE)
n_traits <- 1
n_plots <- 10
num_species <- 10
x <- generate.Artificial.Data(n_species = num_species, n_traits = n_traits,
n_communities = n_plots,
occurence_distribution = 0.5,
average_richness = 10,
sd_richness = 1,
mechanism_random = TRUE)
data_species <- x$traits
#data_species$trait1[4] <- NA
v <- data_species$trait1
names(v) <- data_species$species
Ord <- ordinationAxes(x = v, stand.x = FALSE)
v[4] <- NA
Ord <- ordinationAxes(x = v, stand.x = FALSE)
#character vector
v <- c(rep("blue",3),
rep("red",2),
rep("yellow",2),
rep("black",3))
names(v) <- data_species$species
testthat::expect_warning(
Ord <- ordinationAxes(x = v, stand.x = FALSE)
)
#character vector with one missing value
v[4] <- NA
testthat::expect_warning(
Ord <- ordinationAxes(x = v, stand.x = FALSE)
)
#vector factor
v <- as.factor(v)
testthat::expect_warning(
Ord <- ordinationAxes(x = v, stand.x = FALSE)
)
#with missing value
v[4] <- NA
testthat::expect_warning(
Ord <- ordinationAxes(x = v, stand.x = FALSE)
)
v <- data_species$trait1
names(v) <- data_species$species
v <- as.data.frame(v)
Ord <- ordinationAxes(x = v, stand.x = FALSE)
v <- data_species$trait1
names(v) <- data_species$species
v <- as.data.frame(v)
v$v <- c(rep("blue",3),rep("red",2),rep("yellow",2),rep("black",3))
testthat::expect_warning(
Ord <- ordinationAxes(x = v, stand.x = FALSE)
)
v <- data_species$trait1
names(v) <- data_species$species
v <- as.data.frame(v)
v$v <- c(rep("blue",3),rep("red",2),rep("yellow",2),rep("black",3))
v$v <- as.factor(v$v)
testthat::expect_warning(
Ord <- ordinationAxes(x = v, stand.x = FALSE)
)
})
test_that("ordinationAxes: abuse", {
set.seed(42)
n_traits <- 3
n_plots <- 10
num_species <- 10
x <- generate.Artificial.Data(n_species = num_species, n_traits = n_traits,
n_communities = n_plots,
occurence_distribution = 0.5,
average_richness = 10,
sd_richness = 1,
mechanism_random = TRUE)
data_species <- x$traits
data_abundances <- x$abundances
species <- scaleSpeciesvalues(data_species,n_traits)
abundances <- data_abundances
row.names(abundances) <- c(1:n_plots)
abundances2 <- as.data.frame(abundances)
species2 <- species[,c(2:(n_traits + 1))]
#species2 <- cbind(names(abundances2),species2)
species2 <- as.matrix(species2)
row.names(species2) <- names(abundances2)
#add some NA values
species2[5,1] <- NA
species2[7,2] <- NA
testthat::expect_error(
Ord <- ordinationAxes(x = species2, stand.x = FALSE)
)
})
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.