Seriation in R: How to Optimally Order Objects in a Data Matrice

library(seriation)
# Load the data
data("iris")
df <- iris
head(df, 2)
# Remove the column `species` (column 5)
df <- df[, -5]
# Reorder the objects randomly
set.seed(123)
df <- df[sample(seq_len(nrow(df))),]
head(df, 2)
# Compute dissimilarity matrix
dist_result <- dist(df)
# Seriate objects, reorder rows based on their similarity
object_order <- seriate(dist_result)
# Extract object orders
head(get_order(object_order), 15)
pimage(dist_result, main = "Random order")

library(seriation)
# Load the data
data("iris")
df <- iris
head(df, 2)
# Remove the column `species` (column 5)
df <- df[, -5]
# Reorder the objects randomly
set.seed(123)
df <- df[sample(seq_len(nrow(df))),]
head(df, 2)
# Compute dissimilarity matrix
dist_result <- dist(df)
# Seriate objects, reorder rows based on their similarity
object_order <- seriate(dist_result)
# Extract object orders
head(get_order(object_order), 15)
pimage(dist_result, order = object_order, main = "Reordered")

library(seriation)
# Data preparation
# Load the dataset
data("USArrests")
# Replace original values by their ranks
df <- head(apply(USArrests, 2, rank), 30)

# Perform seriation on row and columns
row_order <- seriate(dist(df, "minkowski", p = 1),  method ="TSP")
col_order <- seriate(dist(t(df), "minkowski", p = 1),  method ="TSP")
orders <- c(row_order, col_order)

# Visualization: matrix of bars 
# Original matrix
bertinplot(df)

library(seriation)
# Data preparation
# Load the dataset
data("USArrests")
# Replace original values by their ranks
df <- head(apply(USArrests, 2, rank), 30)

# Perform seriation on row and columns
row_order <- seriate(dist(df, "minkowski", p = 1),  method ="TSP")
col_order <- seriate(dist(t(df), "minkowski", p = 1),  method ="TSP")
orders <- c(row_order, col_order)

# Visualization: matrix of bars 
# Original matrix
bertinplot(df, orders)

library(seriation)
# Load demo data
data("Townships")
# Visualize the original data
bertinplot(
  Townships, 
  options = list(panel = panel.circles)
)

library(seriation)
# Load demo data
data("Townships")
# Seriate rows and columns using the bond energy algorithm (BEA)
set.seed(1234)
orders <- seriate(Townships, method = "BEA", control = list(rep = 10))
bertinplot(
  Townships, order = orders, 
  options = list(panel = panel.circles)
)

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