Test case generators using Boost Graph Library. More...

#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/graph_traits.hpp>
#include <py2cpp/nx2bgl.hpp>
#include <utility>

Include dependency graph for test_cases_boost.hpp:

Typedefs
using	graph_t = boost::adjacency_list< boost::listS, boost::vecS, boost::directedS, boost::no_property, boost::property< boost::edge_weight_t, int, boost::property< boost::edge_index_t, int > > >
	Type alias for Boost adjacency list with edge weights and indices.

using	Vertex = boost::graph_traits< graph_t >::vertex_descriptor
	Type alias for vertex descriptor.

using	Edge_it = boost::graph_traits< graph_t >::edge_iterator
	Type alias for edge iterator.

Functions
template<typename Mapping >
auto	create_test_case1 (const Mapping &weights) -> py::GraphAdaptor< graph_t >
	Create a simple 5-node cycle test graph.

template<typename Mapping >
auto	create_test_case_timing (const Mapping &weights) -> py::GraphAdaptor< graph_t >
	Create a 3-node timing test graph with parallel edges.

Detailed Description

Test case generators using Boost Graph Library.

This module provides factory functions for creating test graphs using the Boost Graph Library (BGL) adjacency list implementation. These test cases are designed for testing network optimization algorithms.

The graphs created are wrapped in py::GraphAdaptor for compatibility with the network optimization algorithms.

Typedef Documentation

◆ Edge_it

using Edge_it = boost::graph_traits<graph_t>::edge_iterator

Type alias for edge iterator.

◆ graph_t

using graph_t = boost::adjacency_list< boost::listS, boost::vecS, boost::directedS, boost::no_property, boost::property<boost::edge_weight_t, int, boost::property<boost::edge_index_t, int> >>

Type alias for Boost adjacency list with edge weights and indices.

◆ Vertex

using Vertex = boost::graph_traits<graph_t>::vertex_descriptor

Type alias for vertex descriptor.

Function Documentation

◆ create_test_case1()

template<typename Mapping >

auto create_test_case1 ( const Mapping & weights ) -> py::GraphAdaptor<graph_t>

inline

Create a simple 5-node cycle test graph.

This function creates a simple directed cycle with 5 vertices. The graph structure is: A -> B -> C -> D -> E -> A This is useful for testing basic cycle detection and ratio algorithms.

Template Parameters

Mapping Type of weight mapping (edge -> weight)

Parameters

[in] weights weights for the edges in order of creation

Returns: py::GraphAdaptor<graph_t> wrapped Boost graph

◆ create_test_case_timing()