net_utils_example.cc

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/*
                          Aleph_w
 
  Data structures & Algorithms
  version 2.0.0b
  https://github.com/lrleon/Aleph-w
 
  This file is part of Aleph-w library
 
  Copyright (c) 2002-2026 Leandro Rabindranath Leon
 
  Permission is hereby granted, free of charge, to any person obtaining a copy
  of this software and associated documentation files (the "Software"), to deal
  in the Software without restriction, including without limitation the rights
  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  copies of the Software, and to permit persons to whom the Software is
  furnished to do so, subject to the following conditions:
 
  The above copyright notice and this permission notice shall be included in all
  copies or substantial portions of the Software.
 
  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  SOFTWARE.
*/
 
 
#include <iostream>
#include <string>
#include <vector>
#include <iomanip>
#include <fstream>
#include <sstream>
#include <chrono>
#include <limits>
#include <tpl_net.H>
#include <tpl_maxflow.H>
#include <net_utils.H>
 
using namespace std;
using namespace Aleph;
 
// Type definitions
using FlowType = double;
using Net = Net_Graph<Net_Node<string>, Net_Arc<Empty_Class, FlowType>>;
using Node = Net::Node;
 
static size_t density_to_num_arcs(size_t n, double density)
{
  if (n < 2)
    return 0;
 
  const double max_arcs = static_cast<double>(n) * (n - 1);
  size_t m = static_cast<size_t>(density * max_arcs);
  if (m < n - 1)
    m = n - 1;
  return m;
}
 
static void add_super_source_and_sink(Net& net)
{
  vector<Node*> nodes;
  for (auto it = net.get_node_it(); it.has_curr(); it.next())
    nodes.push_back(it.get_curr());
 
  FlowType total_cap = 0;
  for (auto it = net.get_arc_it(); it.has_curr(); it.next())
    total_cap += it.get_curr()->cap;
  if (total_cap <= FlowType{0})
    total_cap = FlowType{1};
 
  const FlowType cap = total_cap;
  auto s = net.insert_node("SuperSource");
  auto t = net.insert_node("SuperSink");
 
  for (Node* v : nodes)
    {
      net.insert_arc(s, v, cap);
      net.insert_arc(v, t, cap);
    }
}
 
void print_network_stats(Net& net, const string& title)
{
  cout << "\n=== " << title << " ===" << endl;
  cout << "Nodes: " << net.get_num_nodes() << endl;
  cout << "Arcs:  " << net.get_num_arcs() << endl;
  
  // Calculate density
  size_t n = net.get_num_nodes();
  size_t m = net.get_num_arcs();
  double max_arcs = n * (n - 1);  // Directed graph
  double density = (max_arcs > 0) ? 100.0 * m / max_arcs : 0;
  
  cout << "Density: " << fixed << setprecision(1) << density << "%" << endl;
  
  // Calculate total capacity
  FlowType total_cap = 0;
  for (auto it = net.get_arc_it(); it.has_curr(); it.next())
    total_cap += it.get_curr()->cap;
  
  cout << "Total capacity: " << total_cap << endl;
}
 
void demo_random_networks()
{
  cout << "\n" << string(60, '=') << endl;
  cout << "Demo 1: Random Network Generation" << endl;
  cout << string(60, '=') << endl;
  
  cout << "\nGenerating random networks with different parameters..." << endl;
  
  // Small sparse network
  {
    Net net = generate_random_network<Net>(10, density_to_num_arcs(10, 0.2), 1.0, 10.0);
    print_network_stats(net, "Small Sparse (n=10, density=20%)");
 
    add_super_source_and_sink(net);
    FlowType flow = dinic_maximum_flow(net);
    cout << "Max flow: " << flow << endl;
  }
  
  // Medium network
  {
    Net net = generate_random_network<Net>(20, density_to_num_arcs(20, 0.3), 5.0, 50.0);
    print_network_stats(net, "Medium (n=20, density=30%)");
 
    add_super_source_and_sink(net);
    FlowType flow = dinic_maximum_flow(net);
    cout << "Max flow: " << flow << endl;
  }
  
  // Dense network
  {
    Net net = generate_random_network<Net>(15, density_to_num_arcs(15, 0.6), 1.0, 100.0);
    print_network_stats(net, "Dense (n=15, density=60%)");
 
    add_super_source_and_sink(net);
    FlowType flow = dinic_maximum_flow(net);
    cout << "Max flow: " << flow << endl;
  }
}
 
void demo_grid_networks()
{
  cout << "\n" << string(60, '=') << endl;
  cout << "Demo 2: Grid Network Generation" << endl;
  cout << string(60, '=') << endl;
  
  cout << "\nGrid networks are useful for benchmarking." << endl;
  cout << "Source is top-left, sink is bottom-right.\n" << endl;
  
  // Different grid sizes
  for (int size : {3, 5, 8})
  {
    Net net = generate_grid_network<Net>(size, size, 10.0, false);
    
    stringstream title;
    title << size << "x" << size << " Grid";
    print_network_stats(net, title.str());
    
    auto start = chrono::high_resolution_clock::now();
    FlowType flow = dinic_maximum_flow(net);
    auto end = chrono::high_resolution_clock::now();
    
    double ms = chrono::duration<double, milli>(end - start).count();
    cout << "Max flow: " << flow << " (computed in " 
         << fixed << setprecision(3) << ms << " ms)" << endl;
  }
}
 
void demo_layered_networks()
{
  cout << "\n" << string(60, '=') << endl;
  cout << "Demo 3: Layered Network Generation" << endl;
  cout << string(60, '=') << endl;
  
  cout << "\nLayered networks have nodes in discrete layers." << endl;
  cout << "Edges only go from one layer to the next (DAG structure).\n" << endl;
  
  vector<size_t> layers = {1, 3, 4, 3, 1};  // Source, 3, 4, 3, Sink
  
  Net net = generate_layered_network<Net>(layers, 20.0, 0.7);
  
  cout << "Layer structure: ";
  for (size_t l : layers)
    cout << l << " ";
  cout << endl;
  
  print_network_stats(net, "Layered Network");
  
  FlowType flow = dinic_maximum_flow(net);
  cout << "Max flow: " << flow << endl;
  
  cout << "\nLayered networks model:" << endl;
  cout << "  - Assembly lines (stages of production)" << endl;
  cout << "  - Communication protocols (network layers)" << endl;
  cout << "  - Project scheduling (phases)" << endl;
}
 
void demo_dot_export()
{
  cout << "\n" << string(60, '=') << endl;
  cout << "Demo 4: GraphViz DOT Export" << endl;
  cout << string(60, '=') << endl;
  
  cout << "\nCreating a small network and exporting to DOT format..." << endl;
  
  // Create a simple network
  Net net;
  
  auto s = net.insert_node("Source");
  auto a = net.insert_node("A");
  auto b = net.insert_node("B");
  auto c = net.insert_node("C");
  auto t = net.insert_node("Sink");
  
  net.insert_arc(s, a, 10);
  net.insert_arc(s, b, 8);
  net.insert_arc(a, b, 5);
  net.insert_arc(a, c, 7);
  net.insert_arc(b, c, 6);
  net.insert_arc(b, t, 9);
  net.insert_arc(c, t, 12);
  
  // Compute max flow first
  FlowType flow = dinic_maximum_flow(net);
  cout << "Max flow computed: " << flow << endl;
  
  // Export to DOT string
  DotExportOptions opts;
  opts.graph_name = "sample_network";
  opts.show_capacity = true;
  opts.show_flow = true;
  
  string dot = network_to_dot_string(net, opts);
  
  cout << "\nDOT output:" << endl;
  cout << string(40, '-') << endl;
  cout << dot;
  cout << string(40, '-') << endl;
  
  cout << "\nTo visualize, save to .dot file and run:" << endl;
  cout << "  dot -Tpng network.dot -o network.png" << endl;
  
  cout << "\nCommands to visualize DOT files:" << endl;
  cout << "  dot -Tpng network.dot -o network.png" << endl;
  cout << "  dot -Tsvg network.dot -o network.svg" << endl;
}
 
void demo_json_export()
{
  cout << "\n" << string(60, '=') << endl;
  cout << "Demo 5: JSON Serialization" << endl;
  cout << string(60, '=') << endl;
  
  cout << "\nExporting network to JSON format..." << endl;
  
  // Create a small network
  Net net = generate_random_network<Net>(5, density_to_num_arcs(5, 0.4), 1.0, 10.0);
  add_super_source_and_sink(net);
  dinic_maximum_flow(net);
  
  string json = network_to_json_string(net);
  
  cout << "\nJSON output:" << endl;
  cout << string(40, '-') << endl;
  cout << json << endl;
  cout << string(40, '-') << endl;
  
  cout << "\nJSON format is useful for:" << endl;
  cout << "  - Web visualization (D3.js, vis.js)" << endl;
  cout << "  - Data exchange between systems" << endl;
  cout << "  - Storing network configurations" << endl;
}
 
void demo_benchmarking()
{
  cout << "\n" << string(60, '=') << endl;
  cout << "Demo 6: Algorithm Benchmarking" << endl;
  cout << string(60, '=') << endl;
  
  cout << "\nComparing max-flow algorithms on different network types...\n" << endl;
  
  cout << setw(20) << left << "Network Type"
       << setw(10) << "Nodes"
       << setw(10) << "Arcs"
       << setw(16) << "F-F (DFS) (ms)"
       << setw(12) << "Dinic (ms)"
       << setw(10) << "Flow" << endl;
  cout << string(74, '-') << endl;
  
  auto benchmark = [](Net& net, const string& name) {
    size_t n = net.get_num_nodes();
    size_t m = net.get_num_arcs();
    
    // Ford-Fulkerson (DFS augmenting paths)
    Net net1 = net;  // Copy
    add_super_source_and_sink(net1);
    auto t1 = chrono::high_resolution_clock::now();
    FlowType f1 = ford_fulkerson_maximum_flow(net1);
    auto t2 = chrono::high_resolution_clock::now();
    double ek_ms = chrono::duration<double, milli>(t2 - t1).count();
    
    // Dinic
    Net net2 = net;
    add_super_source_and_sink(net2);
    t1 = chrono::high_resolution_clock::now();
    dinic_maximum_flow(net2);
    t2 = chrono::high_resolution_clock::now();
    double dinic_ms = chrono::duration<double, milli>(t2 - t1).count();
    
    cout << setw(20) << left << name
         << setw(10) << n
         << setw(10) << m
         << setw(16) << fixed << setprecision(3) << ek_ms
         << setw(12) << dinic_ms
         << setw(10) << setprecision(0) << f1 << endl;
  };
  
  // Random sparse
  {
    Net net = generate_random_network<Net>(30, density_to_num_arcs(30, 0.15), 1.0, 100.0);
    benchmark(net, "Random Sparse");
  }
  
  // Random dense
  {
    Net net = generate_random_network<Net>(20, density_to_num_arcs(20, 0.5), 1.0, 100.0);
    benchmark(net, "Random Dense");
  }
  
  // Grid
  {
    Net net = generate_grid_network<Net>(8, 8, 50.0, false);
    benchmark(net, "Grid 8x8");
  }
  
  // Layered
  {
    vector<size_t> layers = {1, 5, 8, 8, 5, 1};
    Net net = generate_layered_network<Net>(layers, 50.0, 0.6);
    benchmark(net, "Layered (6 layers)");
  }
  
  cout << "\nNote: Times may vary based on random network structure." << endl;
  cout << "Dinic is generally faster, especially on dense networks." << endl;
}
 
int main()
{
  cout << "=== Network Utilities ===" << endl;
  cout << "Generation, Visualization, and Serialization\n" << endl;
  
  demo_random_networks();
  demo_grid_networks();
  demo_layered_networks();
  demo_dot_export();
  demo_json_export();
  demo_benchmarking();
  
  // Summary
  cout << "\n" << string(60, '=') << endl;
  cout << "Summary" << endl;
  cout << string(60, '=') << endl;
  
  cout << R"(
Network Utilities in Aleph-w:
 
Generation Functions:
  - generate_random_network(n, m, min_cap, max_cap)
  - generate_grid_network(rows, cols, capacity, bidirectional)
  - generate_layered_network(layers, capacity, edge_prob)
  - generate_bipartite_network(left, right, edge_prob)
 
Visualization (DOT/GraphViz):
  - export_network_to_dot(net, filename, options)
  - network_to_dot_string(net, options)
  
  Visualize with: dot -Tpng network.dot -o network.png
 
Serialization:
  - network_to_json_string(net)
  - export_network_to_dimacs(net, filename)
  - import_network_from_dimacs<Net>(filename)
 
Use Cases:
  - Algorithm testing and benchmarking
  - Educational demonstrations
  - Network visualization
  - Data exchange between systems
)" << endl;
  
  return 0;
}