1level.hpp

/*********************************************************************
 *
 * Linear Arrangement Library - A library that implements a collection
 * algorithms for linear arrangments of graphs.
 *
 * Copyright (C) 2019 - 2024
 *
 * This file is part of Linear Arrangement Library. The full code is available
 * at:
 *      https://github.com/LAL-project/linear-arrangement-library.git
 *
 * Linear Arrangement Library is free software: you can redistribute it
 * and/or modify it under the terms of the GNU Affero General Public License
 * as published by the Free Software Foundation, either version 3 of the
 * License, or (at your option) any later version.
 *
 * Linear Arrangement Library 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 Affero General Public License for more details.
 *
 * You should have received a copy of the GNU Affero General Public License
 * along with Linear Arrangement Library.  If not, see <http://www.gnu.org/licenses/>.
 *
 * Contact:
 *
 *     Lluís Alemany Puig (lluis.alemany.puig@upc.edu)
 *         LQMC (Quantitative, Mathematical, and Computational Linguisitcs)
 *         CQL (Complexity and Quantitative Linguistics Lab)
 *         Jordi Girona St 1-3, Campus Nord UPC, 08034 Barcelona.   CATALONIA, SPAIN
 *         Webpage: https://cqllab.upc.edu/people/lalemany/
 *
 *     Ramon Ferrer i Cancho (rferrericancho@cs.upc.edu)
 *         LQMC (Quantitative, Mathematical, and Computational Linguisitcs)
 *         CQL (Complexity and Quantitative Linguistics Lab)
 *         Office 220, Omega building
 *         Jordi Girona St 1-3, Campus Nord UPC, 08034 Barcelona.   CATALONIA, SPAIN
 *         Webpage: https://cqllab.upc.edu/people/rferrericancho/
 *
 ********************************************************************/
 
#pragma once
 
// C++ includes
#if defined DEBUG
#include <cassert>
#endif
#include <vector>
 
// lal includes
#include <lal/linear_arrangement.hpp>
#include <lal/numeric/rational.hpp>
#include <lal/graphs/graph.hpp>
#include <lal/linarr/D/D.hpp>
#include <lal/utilities/aggregations.hpp>
 
namespace lal {
namespace linarr {
 
/* 1-LEVEL METRICS */
 
// **DEVELOPER NOTE**
// This function's documentation has to be updated manually in the python
// interface file '.i' 'python-interface/submodules/linarr.i'
template <class graph_t>
[[nodiscard]] numeric::rational mean_dependency_distance_1level_rational
(const std::vector<graph_t>& L, const std::vector<linear_arrangement>& P = {})
noexcept
{
    static_assert(std::is_base_of_v<graphs::graph, graph_t>);
 
#if defined DEBUG
    // the number of graphs and number of linear arrangements
    // must coincide unless no arrangement was given.
    assert(P.size() == 0 or L.size() == P.size());
#endif
 
    typedef numeric::rational ratio;
    typedef linear_arrangement ARR;
    typedef std::pair<uint64_t, uint64_t> DD_m;
 
    if (P.size() == 0) {
 
        return utilities::one_level_aggregation<ratio, true>
        (
            L.begin(), L.end(), nullptr, nullptr,
            // make values Q,R
            [](const graph_t& G) {
                return DD_m{
                    sum_edge_lengths(G, linear_arrangement::identity(G.get_num_nodes())),
                    G.get_num_edges()
                };
            },
            // accumulate Q
            [](uint64_t& total, uint64_t new_value) { total += new_value; },
            // accumulate R
            [](uint64_t& total, uint64_t new_value) { total += new_value; },
            // average accumulated Q
            [](uint64_t DDs, std::size_t) { return DDs; },
            // average accumulated R
            [](uint64_t num_edges, std::size_t) { return num_edges; },
            // average accumulated Q,R
            [](uint64_t DDs, uint64_t sum_num_edges) { return ratio(DDs, sum_num_edges); }
        );
 
    }
    else {
        return utilities::one_level_aggregation<ratio, false>
        (
            L.begin(), L.end(), P.begin(), P.end(),
            // make values Q,R
            [](const graph_t& G, const ARR& arr) {
                return DD_m(sum_edge_lengths(G, arr), G.get_num_edges());
            },
            // accumulate Q
            [](uint64_t& total, uint64_t new_value) { total += new_value; },
            // accumulate R
            [](uint64_t& total, uint64_t new_value) { total += new_value; },
            // average accumulated Q
            [](uint64_t DDs, std::size_t) { return DDs; },
            // average accumulated R
            [](uint64_t num_edges, std::size_t) { return num_edges; },
            // average Q,R
            [](uint64_t DDs, uint64_t sum_num_edges) { return ratio(DDs, sum_num_edges); }
        );
    }
}
 
// **DEVELOPER NOTE**
// This function's documentation has to be updated manually in the python
// interface file '.i' 'python-interface/submodules/linarr.i'
template <class graph_t>
[[nodiscard]] double mean_dependency_distance_1level
(const std::vector<graph_t>& L, const std::vector<linear_arrangement>& P = {})
noexcept
{
    static_assert(std::is_base_of_v<graphs::graph, graph_t>);
    return mean_dependency_distance_1level_rational(L, P).to_double();
}
 
} // -- namespace linarr
} // -- namespace lal