graph_absolute_trust.hh 8.3 KB
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// graph-tool -- a general graph modification and manipulation thingy
//
// Copyright (C) 2007  Tiago de Paula Peixoto <tiago@forked.de>
//
// 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_ABSOLUTE_TRUST_HH
#define GRAPH_ABSOLUTE_TRUST_HH

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

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#include <tr1/unordered_set>
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#include <tr1/random>
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#include <boost/functional/hash.hpp>
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#include <iostream>

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namespace graph_tool
{
using namespace std;
using namespace boost;

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struct get_absolute_trust
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{
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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,
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                    TrustMap c, InferredTrustMap t, size_t n_iter,
                    bool reversed, rng_t& rng) const
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    {
        typedef typename property_traits<TrustMap>::value_type c_type;
        typedef typename property_traits<InferredTrustMap>::value_type
            ::value_type t_type;

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        unchecked_vector_property_map<vector<t_type>, VertexIndex>
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            t_count(vertex_index, num_vertices(g));
        unchecked_vector_property_map<vector<size_t>, VertexIndex>
            v_mark(vertex_index, num_vertices(g));

        // init inferred trust t
        int i, N = num_vertices(g);
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        #pragma omp parallel for default(shared) private(i) schedule(dynamic)
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        for (i = (source == -1) ? 0 : source;
             i < ((source == -1) ? N : source + 1); ++i)
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        {
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            typename graph_traits<Graph>::vertex_descriptor v =
                vertex(i, g);
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            if (v == graph_traits<Graph>::null_vertex())
                continue;
            t[v].resize(N);
            t_count[v].resize(N,0);
            v_mark[v].resize(N,0);
        }

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        #pragma omp parallel for default(shared) private(i) schedule(dynamic)
        for (i = (source == -1) ? 0 : source;
             i < ((source == -1) ? N : source + 1); ++i)
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        {
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            typename graph_traits<Graph>::vertex_descriptor v =
                vertex(i, g);
            if (v == graph_traits<Graph>::null_vertex())
                continue;

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            // walk hash set
            tr1::unordered_set<size_t> path_set;
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            tr1::uniform_int<size_t>
                random_salt(0, numeric_limits<size_t>::max());
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            size_t salt = random_salt(rng);

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            for (size_t bias = 0; bias < 3; ++bias)
                for (size_t iter = 0; iter < n_iter; ++iter)
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                {
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                    typename graph_traits<Graph>::vertex_descriptor pos = v;
                    t_type pos_t = 1.0;
                    t_type pweight = 1.0;
                    v_mark[v][vertex_index[v]] = bias*n_iter + iter + 1;

                    size_t path_hash = salt;
                    hash_combine(path_hash, i);

                    // start a self-avoiding walk from vertex v
                    vector<typename graph_traits<Graph>::edge_descriptor>
                        out_es;
                    vector<t_type> out_prob;
                    do
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                    {
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                        out_es.clear();
                        out_prob.clear();
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                        // obtain list of candidate edges to follow
                        typename graph_traits<Graph>::out_edge_iterator e,
                            e_end;
                        for (tie(e, e_end) = out_edges(pos, g); e != e_end; ++e)
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                        {
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                            typename graph_traits<Graph>::vertex_descriptor t =
                                target(*e,g);
                            if (v_mark[v][vertex_index[t]] <
                                bias*n_iter + iter + 1)
                            {
                                if (c[*e] < 0 || c[*e] > 1)
                                    continue;
                                out_es.push_back(*e);

                                if (bias != 1)
                                {
                                    double prob = c[*e];
                                    if (bias == 2)
                                        prob = 1.0 - prob;

                                    if (out_prob.empty())
                                        out_prob.push_back(prob);
                                    else
                                        out_prob.push_back(out_prob.back() +
                                                           prob);
                                }
                            }
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                        }
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                        if (!out_es.empty())
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                        {
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                            // select edge according to its probability
                            typename graph_traits<Graph>::edge_descriptor e;
                            if (bias != 1)
                            {
                                typedef tr1::uniform_real<t_type> dist_t;
                                tr1::variate_generator<rng_t&, dist_t>
                                    random(rng, dist_t(0, out_prob.back()));

                                t_type u;
                                {
                                    #pragma omp critical
                                    u = random();
                                }
                                e = out_es[upper_bound(out_prob.begin(),
                                                       out_prob.end(), u) -
                                           out_prob.begin()];
                            }
                            else
                            {
                                tr1::uniform_int<size_t>
                                    random(0, out_es.size()-1);
                                #pragma omp critical
                                e = out_es[random(rng)];
                            }

                            // new position in random walk
                            pos = target(e,g);
                            size_t posi = vertex_index[pos];

                            // update current path trust
                            pos_t *= c[e];

                            if (reversed && boost::source(e, g) != v)
                                pweight *= c[e];

                            // get path hash
                            hash_combine(path_hash, posi);
                            if (path_set.find(path_hash) == path_set.end())
                            {
                                // if new path, modify vertex trust score
                                path_set.insert(path_hash);

                                t_type old = 0;
                                if (t_count[v][posi] > 0)
                                    old = t[v][posi]/t_count[v][posi];
                                t[v][posi] += pos_t*pweight;
                                t_count[v][posi] += pweight;
                            }

                            if (!reversed)
                                pweight *= c[e];

                            // stop if weight drops to zero
                            if (pweight == 0)
                                break;

                            // mark vertex
                            v_mark[v][posi] = bias*n_iter + iter + 1;
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                        }
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                    }
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                    while (!out_es.empty());
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                }
        }

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        #pragma omp parallel for default(shared) private(i) schedule(dynamic)
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        for (i = (source == -1) ? 0 : source;
             i < ((source == -1) ? N : source + 1); ++i)
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        {
            typename graph_traits<Graph>::vertex_descriptor v = vertex(i, g);
            if (v == graph_traits<Graph>::null_vertex())
                continue;
            for (size_t j = 0; j < N; ++j)
                if (t_count[v][j] > 0)
                    t[v][j] /= t_count[v][j];
        }
    }
};

}

#endif