Helper function for clustering methods

Helper function for clustering methods

Helper function for calculate distance

Add group names to hclust labels.

Add colors to dendrogram

Usage

cluster(x, c_method, d_method)

distance(x, d_method)

cls_add_group(cls, df, indiv, group, pad = TRUE)

cls_color(cls, df, indiv, group)

Arguments

x

A community data matrix. rownames: stands. colnames: species.

c_method

A string of clustering method. "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC), "centroid" (= UPGMC), or "diana".

d_method

A string of distance method. "correlation", "manhattan", "euclidean", "canberra", "clark", "bray", "kulczynski", "jaccard", "gower", "altGower", "morisita", "horn", "mountford", "raup", "binomial", "chao", "cao", "mahalanobis", "chisq", "chord", "aitchison", or "robust.aitchison".

cls

A result of cluster or dendrogram.

df

A data.frame to be added into ord scores

indiv, group

A string to specify individual and group name of column in df.

pad

A logical to specify padding strings.

Value

cluster() returns result of clustering. $clustering_method: c_method $distance_method: d_method

distance() returns distance matrix.

    Inputing cls return a color vector,
            inputing dend return a dend with color.

Examples

# \donttest{
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
df <- 
  tibble::tibble(
  stand = paste0("ST_", c("A", "A", "A", "B", "B", "C", "C", "C", "C")),
species = paste0("sp_", c("a", "e", "d", "e", "b", "e", "d", "b", "a")),
  abundance = c(3, 3, 1, 9, 5, 4, 3, 3, 1))
cls <- 
  df2table(df) %>%
  cluster(c_method = "average", d_method = "bray")
library(ggdendro)
# show standard cluster
ggdendro::ggdendrogram(cls)


# show cluster with group
data(dune, package = "vegan")
data(dune.env, package = "vegan")
cls <- 
  cluster(dune, c_method = "average", d_method = "bray")
df <- tibble::rownames_to_column(dune.env, "stand")
cls <- cls_add_group(cls, df, indiv = "stand", group = "Use")
#> Joining with `by = join_by(stand)`
ggdendro::ggdendrogram(cls)

# }