# R code for sampling from G-Wishart AND Wishart distribution
################################################################################
# sampling from G-Wishart distribution
rgwish = function( n = 1, adj.g = NULL, b = 3, D = NULL )
{
	if ( b <= 2 ) stop( "In G-Wishart distribution parameter 'b' has to be more than 2" )
	if( is.null(adj.g) ) stop( "Adjacency matrix should be determined" )

	G <- as.matrix( adj.g )
	if( sum( ( G == 1 ) * ( G == 0 ) ) != 0 ) stop( "Elements of matrix G should be zero or one" )	

	if( !isSymmetric(G) )
	{
		G[ lower.tri( G, diag(TRUE) ) ] <- 0
		G  = G + t(G)
	}
	
	p <- nrow(G)  
	
	if( is.null(D) ) 
	{
		D <- diag(p)
	} 
	else 
	{
		if( dim(D)[1] != p ) stop( "Dimension of matrix G and D must to be the same." )
	}
		
	Ti        = chol( solve(D) )
	samples   = array( 0, c( p, p, n ) )
	K         = matrix( 0, p, p )
	threshold = 1e-8
	
	for ( i in 1 : n )
	{
		result       = .C( "rgwish", as.integer(G), as.double(Ti), K = as.double(K), as.integer(b), as.integer(p), as.double(threshold), PACKAGE = "BDgraph" )
		samples[,,i] = matrix( result $ K, p, p ) 		
	}	

	return( samples )   
}