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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>                          |
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#     Computing the probability of all possible graphs or one specific graph   |
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pgraph = function( bdgraph.obj, number.g = 4, adj = NULL )
{
	if( !is.null( bdgraph.obj $ p_links ) ) stop( "It needs object of 'bdgraph' with option 'save = TRUE'" ) 
	
	sample_graphs = bdgraph.obj $ sample_graphs
	graph_weights = bdgraph.obj $ graph_weights
	sort_gWeights = sort( graph_weights, decreasing = TRUE )
  
	if( is.null( adj ) )
	{
		p      <- nrow( bdgraph.obj $ last_graph )
		list_g <- list()
		vec_g  <- c( rep( 0, p * ( p - 1 ) / 2 ) )  

		for ( i in 1 : number.g )
		{
			vec_g <- 0 * vec_g
			indG_i = sample_graphs[ which( graph_weights == sort_gWeights[ i ] ) ]
			vec_g[ which( unlist( strsplit( as.character( indG_i ), "" ) ) == 1 ) ] <- 1
			list_g[[i]] <- matrix( 0, p, p )
			list_g[[i]][ upper.tri( list_g[[i]] ) ] <- vec_g
			#list_g[[i]] <- Matrix::Matrix( list_g[[i]], sparse = TRUE )
		}

		return( list( selected_g = list_g, prob_g = sort_gWeights[ 1 : number.g ] / sum( graph_weights ) ) )
		
	}else{
		if ( inherits( adj, "sim"   ) ) G <- as.matrix( adj $ G )
		if ( inherits( adj, "graph" ) ) G <- unclass( adj )		

		indG   = paste( G[ upper.tri( G ) ], collapse = '' )
		wh     = which( sample_graphs == indG )
		prob_g = ifelse( length( wh ) == 0, 0, graph_weights[ wh ] / sum( graph_weights ) )

		return( prob_g )
	}
}
    
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