graph_trust_transitivity.hh 8.68 KB
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// graph-tool -- a general graph modification and manipulation thingy
//
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// Copyright (C) 2006-2013 Tiago de Paula Peixoto <tiago@skewed.de>
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//
// This program 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; either version 3
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.

#ifndef GRAPH_TRUST_TRANSITIVITY_HH
#define GRAPH_TRUST_TRANSITIVITY_HH

#include "graph.hh"
#include "graph_filtering.hh"
#include "graph_util.hh"

#include <algorithm>

#include <boost/graph/dijkstra_shortest_paths.hpp>

#include <iostream>

namespace graph_tool
{
using namespace std;
using namespace boost;


struct stop_search {}; // exception to be thrown to stop search

template <class SourceMap, class WeightMap>
class source_counter:
    public boost::dijkstra_visitor<null_visitor>
{
public:
    source_counter(SourceMap source_map, WeightMap weight_map, size_t n_sources)
        : _source_map(source_map), _weight_map(weight_map),
          _n_sources(n_sources) {}

    template <class Graph>
    void examine_vertex(typename graph_traits<Graph>::vertex_descriptor u,
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                        Graph&)
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    {
        // stop if all sources are found
        if (_source_map[u])
        {
            _n_sources--;
            if (_n_sources == 0)
                throw stop_search();
        }
    }

private:
    SourceMap _source_map;
    WeightMap _weight_map;
    size_t _n_sources;
};

struct dist_compare
{
    template <class Type1, class Type2>
    bool operator()(const Type1& d1, const Type2& d2) const
    {
        return d1 > d2; // we want trust paths with _maximum_ "distance"
    }
};

struct dist_combine
{
    template <class DistType, class WeightType>
    DistType operator()(const DistType& d, const WeightType& w) const
    {
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        return DistType(d * w);
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    }
};

// predicate to filter a single vertex from the graph
struct filter_vertex_pred
{
    filter_vertex_pred() {}
    filter_vertex_pred(size_t v): _v(v) {}
    template <class Vertex>
    bool operator()(const Vertex& v) const { return v != _v; }
    size_t _v;
};

struct get_trust_transitivity
{
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    template <class Graph, class VertexIndex, class TrustMap,
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              class InferredTrustMap>
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    void operator()(Graph& g, VertexIndex vertex_index, int64_t source,
                    int64_t target, TrustMap c, InferredTrustMap t) const
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    {
        typedef typename graph_traits<Graph>::vertex_descriptor vertex_t;
        typedef typename graph_traits<Graph>::edge_descriptor edge_t;
        typedef typename property_traits<TrustMap>::value_type c_type;
        typedef typename
            property_traits<InferredTrustMap>::value_type::value_type t_type;

        int i, N = num_vertices(g);
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        #pragma omp parallel for default(shared) private(i) schedule(static, 100)
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        for (i = 0; i < N; ++i)
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        {
            vertex_t v = vertex(i, g);
            if (v == graph_traits<Graph>::null_vertex())
                continue;
            t[v].resize((source == -1 && target == -1) ? N : 1);
        }
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        N = (target == -1) ? num_vertices(g) : target + 1;
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        #pragma omp parallel for default(shared) private(i) schedule(static, 100)
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        for (i = (target == -1) ? 0 : target; i < N; ++i)
        {
            vertex_t tgt = vertex(i, g);
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            if (tgt == graph_traits<Graph>::null_vertex())
                continue;
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            // mark the sources
            typedef unchecked_vector_property_map<uint8_t, VertexIndex>
                source_map_t;
            source_map_t source_map(vertex_index, num_vertices(g));

            typename in_edge_iteratorS<Graph>::type e, e_end;
            for (tie(e, e_end) = in_edge_iteratorS<Graph>::get_edges(tgt, g);
                 e != e_end; ++e)
                source_map[boost::source(*e,g)] = true;

            // filter vertex w out of the graph
            typedef filtered_graph<Graph, boost::keep_all, filter_vertex_pred>
                fg_t;
            fg_t fg(g, boost::keep_all(), filter_vertex_pred(tgt));

            // distance map (target weight map)
            typedef unchecked_vector_property_map<t_type, VertexIndex>
                dist_map_t;
            dist_map_t dist_map(vertex_index, num_vertices(g));

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            // color map
            typedef unchecked_vector_property_map<default_color_type, VertexIndex>
                color_map_t;
            color_map_t color_map(vertex_index, num_vertices(g));

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            if (source != -1)
            {
                vertex_t src = vertex(source, g);

                // compute the targets weights
                try
                {
                    size_t k = in_degreeS()(tgt, g);
                    source_counter<source_map_t,dist_map_t>
                        visitor(source_map, dist_map, k);
                    dijkstra_shortest_paths(fg, src, weight_map(c).
                                            vertex_index_map(vertex_index).
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                                            color_map(color_map).
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                                            distance_map(dist_map).
                                            distance_compare(dist_compare()).
                                            distance_combine(dist_combine()).
                                            distance_inf(t_type(0)).
                                            distance_zero(t_type(1)).
                                            visitor(visitor));
                }
                catch (const stop_search&) {}

                // compute the target's trust
                t_type sum_w = 0, avg = 0;
                for (tie(e, e_end) =
                         in_edge_iteratorS<Graph>::get_edges(tgt, g);
                     e != e_end; ++e)
                {
                    t_type weight = dist_map[boost::source(*e,g)];
                    sum_w += weight;
                    avg += c[*e]*weight*weight;
                }
                if (sum_w > 0)
                    t[tgt][0] = avg/sum_w;
                if (tgt == src)
                    t[tgt][0] = 1.0;
            }
            else
            {
                typedef typename
                    mpl::if_<typename is_directed::apply<Graph>::type,
                             reverse_graph<fg_t>,
                             fg_t>::type rg_t;
                rg_t rg(fg);
                dist_map_t sum_w(vertex_index, num_vertices(g));
                int j, N2 = num_vertices(g);
                for (tie(e, e_end) =
                         in_edge_iteratorS<Graph>::get_edges(tgt, g);
                     e != e_end; ++e)
                {
                    // compute the weights to all sources
                    dijkstra_shortest_paths
                        (rg, boost::source(*e, g), weight_map(c).
                         vertex_index_map(vertex_index).
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                         color_map(color_map).
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                         distance_map(dist_map).
                         distance_compare(dist_compare()).
                         distance_combine(dist_combine()).
                         distance_inf(t_type(0)).
                         distance_zero(t_type(1)));

                    #pragma omp parallel for default(shared) private(j) \
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                        schedule(static, 100)
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                    for (j = 0; j < N2; ++j)
                    {
                        vertex_t src = vertex(j, g);
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                        if (src == graph_traits<Graph>::null_vertex())
                            continue;
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                        t_type weight = dist_map[src];
                        sum_w[src] += weight;
                        size_t tidx = (target == -1) ? vertex_index[tgt] : 0;
                        t[src][tidx] += c[*e]*weight*weight;
                    }
                }

                #pragma omp parallel for default(shared) private(j) \
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                    schedule(static, 100)
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                for (j = 0; j < N2; ++j)
                {
                    vertex_t src = vertex(j, g);
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                    if (src == graph_traits<Graph>::null_vertex())
                        continue;
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                    size_t tidx = (target == -1) ? vertex_index[tgt] : 0;
                    if (sum_w[src] > 0)
                        t[src][tidx] /= sum_w[src];
                    if (src == tgt)
                        t[src][tidx] = 1.0;
                }
            }
        }
    }
};

}

#endif