## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup--------------------------------------------------------------------
# install.packages('devtools')
# devtools::install_github('csqsiew/hood2net')

# alternatively
# install.packages('pak')
# pak::pkg_install("csqsiew/hootnet")

# then load the package
library(hood2net)

## ----setup2-------------------------------------------------------------------
# install.packages('hood2net')

# then load the package
library(hood2net)

## -----------------------------------------------------------------------------
sample1

## -----------------------------------------------------------------------------
g1 <- make_network(sample1)

library(igraph)

plot(g1, vertex.frame.color = 'white', vertex.label.dist = 2.5,
     frame = TRUE, main = 'Single character, 1-edit Levenshtein distance')

## -----------------------------------------------------------------------------
g2 <- make_network(sample1, neighbor_type = 'hamming') # sub-only

plot(g2, vertex.frame.color = 'white', vertex.label.dist = 2.5,
     frame = TRUE, main = 'Single character, Hamming distance of 1')

## -----------------------------------------------------------------------------
g3 <- make_network(sample1, edit_size = 2)

plot(g3, vertex.frame.color = 'white', vertex.label.dist = 2.5,
     frame = TRUE, main = 'Single character, 2-edist Levenshtein distance')

## -----------------------------------------------------------------------------
sample2

g4 <- make_network_sep(sample2, separator = '.')

plot(g4, vertex.frame.color = 'white', vertex.label.dist = 2.5,
     frame = TRUE, main = 'Period separator, 1-edit Levenshtein distance')

## -----------------------------------------------------------------------------
# # save
# saveRDS(g1, file = 'my-network.RDS')
# 
# # load
# readRDS('my-network.RDS')

## -----------------------------------------------------------------------------
get_network_info(g1)

## -----------------------------------------------------------------------------
library(igraph)

edge_density(g1)

## -----------------------------------------------------------------------------
get_neighbor_size(g1)

## -----------------------------------------------------------------------------
get_neighbor_clustering(g1)

## -----------------------------------------------------------------------------
sample1

## -----------------------------------------------------------------------------
summary(g1)

## -----------------------------------------------------------------------------
get_neighbor_mean(g1, attribute = 'length')