Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----setup--------------------------------------------------------------------
# Load required packages
library(tourr)
library(lionfish)
# Initialize python backend
if (check_venv()){
init_env(env_name = "r-lionfish", virtual_env = "virtual_env")
} else if (check_conda_env()){
init_env(env_name = "r-lionfish", virtual_env = "anaconda")
}
## ----Load and prepare flea data-----------------------------------------------
data("flea")
data <- apply(flea[,1:6], 2, function(x) (x-mean(x))/sd(x))
clusters <- as.numeric(flea$species)
flea_subspecies <- unique(flea$species)
guided_tour_history <- save_history(data,
tour_path=guided_tour(holes()))
grand_tour_history_1d <- save_history(data,
tour_path=grand_tour(d=1))
half_range <- max(sqrt(rowSums(data^2)))
feature_names <- colnames(data)
obj1 <- list(type="2d_tour", obj=guided_tour_history)
obj2 <- list(type="1d_tour", obj=grand_tour_history_1d)
obj3 <- list(type="scatter", obj=c("tars1", "tars2"))
obj4 <- list(type="hist", obj="head")
if (check_venv()){
init_env(env_name = "r-lionfish", virtual_env = "virtual_env")
} else if (check_conda_env()){
init_env(env_name = "r-lionfish", virtual_env = "anaconda")
}
if (interactive()){
interactive_tour(data=data,
plot_objects=list(obj1, obj2, obj3, obj4),
feature_names=feature_names,
half_range=half_range,
n_plot_cols=2,
preselection=clusters,
preselection_names=flea_subspecies,
n_subsets=5,
display_size=4.5)
}
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