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## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |
# Copyright (C) 2012 - 2021 Reza Mohammadi |
# |
# This file is part of BDgraph package. |
# |
# BDgraph is free software: you can redistribute it and/or modify it under |
# the terms of the GNU General Public License as published by the Free |
# Software Foundation; see <https://cran.r-project.org/web/licenses/GPL-3>.|
# |
# Maintainer: Reza Mohammadi <a.mohammadi@uva.nl> |
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |
# Graph generator |
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |
graph.sim = function( p = 10, graph = "random", prob = 0.2, size = NULL,
class = NULL, vis = FALSE, rewire = 0.05 )
{
if( p < 2 ) stop( "'p' must be more than 1" )
if( ( prob < 0 ) || ( prob > 1 ) ) stop( "'prob' must be between ( 0, 1 )" )
if( ( rewire < 0 ) | ( rewire > 1 ) ) stop( "Value of 'rewire' must be between ( 0, 1 )" )
G <- matrix( 0, p, p )
# - - build the graph structure - - - - - - - - - - - - - - - - - - - - - |
if( ( graph == "random" ) | ( graph == "Random" ) )
{
if( is.null( size ) )
{
G[ upper.tri( G ) ] <- stats::rbinom( p * ( p - 1 ) / 2, 1, prob )
}else{
if( ( size < 0 ) | ( size > p * ( p - 1 ) / 2 ) ) stop( "'size' must be between ( 0, p * ( p - 1 ) / 2 )" )
smp <- sample( 1 : ( p * ( p - 1 ) / 2 ), size, replace = FALSE )
G[ upper.tri( G ) ][ smp ] <- 1
}
}
if( ( graph == "scale-free" ) | ( graph == "Scale-free" ) )
{
resultGraph = .C( "scale_free", G = as.integer( G ), as.integer( p ), PACKAGE = "BDgraph" )
G = matrix( resultGraph $ G, p, p )
#j = sample( 1:p, 1 )
#for( i in ( c( 1:p )[ -j ] ) ) { G[ i, j ] = 1; G[ j, i ] = 1 }
}
if( ( graph == "cluster" ) | ( graph == "Cluster" ) )
{
# partition variables
if( is.null( class ) )
{
#class = NULL
if( !is.null( size ) ) class = length( size )
if( length( prob ) > 1 ) class = length( prob )
if( is.null( class ) ) class = max( 2, ceiling( p / 20 ) )
#if( !is.null( size ) ) class <- length( size ) else class <- max( 2, ceiling( p / 20 ) )
}
g.large <- p %% class
g.small <- class - g.large
n.small <- floor( p / class )
n.large <- n.small + 1
vp <- c( rep( n.small, g.small ), rep( n.large, g.large ) )
if( is.null( size ) )
{
if( length( prob ) != class ) prob = rep( prob, class )
for( i in 1 : class )
{
tmp <- if( i == 1 ) ( 1 : vp[ 1 ] ) else ( ( sum( vp[ 1 : ( i - 1 ) ] ) + 1 ) : sum( vp[ 1 : i ] ) )
gg <- matrix( 0, vp[ i ], vp[ i ] )
gg[ upper.tri( gg ) ] <- stats::rbinom( vp[ i ] * ( vp[ i ] - 1 ) / 2, 1, prob[ i ] )
G[ tmp, tmp ] <- gg
}
}else{
if( class != length( size ) ) stop( "Number of graph sizes is not match with number of clusters" )
if( ( sum( size ) < 0 ) | ( sum( size ) > p * ( p - 1 ) / 2 ) ) stop( "Total graph sizes must be between ( 0, p * ( p - 1 ) / 2 )" )
for( i in 1 : class )
{
tmp <- if( i == 1 ) ( 1 : vp[ 1 ] ) else ( ( sum( vp[ 1 : ( i - 1 ) ] ) + 1 ) : sum( vp[ 1 : i ] ) )
gg <- matrix( 0, vp[ i ], vp[ i ] )
smp <- sample( 1 : ( vp[ i ] * ( vp[ i ] - 1 ) / 2 ), size[ i ], replace = FALSE )
gg[ upper.tri( gg ) ][ smp ] <- 1
G[ tmp, tmp ] <- gg
}
}
}
if( ( graph == "hub" ) | ( graph == "Hub" ) )
{
if( is.null( size ) ) size = ceiling( p / 20 )
if( ( size < 0 ) | ( size > ( p - 1 ) ) ) stop( "'size' must be between ( 0, p - 1 ), for option 'graph = \"hub\"'" )
hub = sample( 1:p, size = size, replace = FALSE )
for( i in 1:size )
{
G[ hub[ i ], ] <- 1
G[ , hub[ i ] ] <- 1
}
}
if( ( graph == "star" ) | ( graph == "Star" ) )
{
hub = sample( 1:p, size = 1, replace = FALSE )
G[ hub, ] <- 1
G[ , hub ] <- 1
}
if( ( graph == "circle" ) | ( graph == "Circle" ) )
{
if( p < 3 ) stop( "'p' must be more than 2, for option 'graph = \"circle\"'" )
G <- stats::toeplitz( c( 0, 1, rep( 0, p - 2 ) ) )
G[ 1, p ] <- 1
}
if( ( graph == "smallworld" ) | ( graph == "Smallworld" ) | ( graph == "small-world" ) | ( graph == "Small-world" ) )
{
G_igraph = igraph::sample_smallworld( dim = 1, # One dimension
size = p, # Number of variables
nei = round( size / p ), # Neighborhood
p = rewire )
G = as.matrix( igraph::as_adj( G_igraph ) ) # Rewiring probability
}
if( ( graph == "lattice" ) | ( graph == "grid" ) )
{
if( is.null( size ) )
{
length_row = round( sqrt( p ) )
length_col = round( sqrt( p ) )
}else{
if( length( size ) == 1 )
{
length_row = size
length_col = size
}else{
length_row = size[ 1 ]
length_col = size[ 2 ]
}
}
for( row in 1:length_row )
{
for( col in 1:length_col )
{
if( ( row != length_row ) & ( col != length_col ) )
G[ col + ( row - 1 ) * length_col, c( col + ( row - 1 ) * length_col + 1, col + row * length_col ) ] = 1
if( ( row == length_row ) & ( col != length_col ) )
G[ col + ( row - 1 ) * length_col, col + ( row - 1 ) * length_col + 1 ] = 1
if( ( row != length_row ) & ( col == length_col ) )
G[ col + ( row - 1 ) * length_col, col + row * length_col ] = 1
}
}
}
G[ lower.tri( G, diag = TRUE ) ] = 0
G = G + t( G )
# - - graph visualization - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -|
if( vis == TRUE )
BDgraph::plot.graph( G, main = "Graph structure" )
class( G ) <- "graph"
return( G )
}
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |
# plot for class "graph" from graph.sim function
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |
plot.graph = function( x, cut = 0.5,
mode = "undirected", diag = FALSE, main = NULL,
layout = igraph::layout_with_fr,
vertex.size = 2,
vertex.color = "orange",
vertex.frame.color = "orange",
vertex.label = NULL,
vertex.label.dist = 0.5,
vertex.label.color = "blue",
edge.color = "lightblue", ... )
{
graph = BDgraph::get_graph( x, cut = cut )
if( is.null( vertex.label ) ) vertex.label = colnames( graph )
graph_ig <- igraph::graph.adjacency( graph, mode = mode, diag = diag )
igraph::plot.igraph( graph_ig,
main = main,
layout = layout,
vertex.size = vertex.size,
vertex.color = vertex.color,
vertex.frame.color = vertex.frame.color,
vertex.label = vertex.label,
vertex.label.dist = vertex.label.dist,
vertex.label.color = vertex.label.color,
edge.color = edge.color, ... )
}
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - |
|
