/*
****Test to assess the quality of the Add member of the Stats
****class which is designed to add a gpstk::Vector or an individual
****sample to an instance of Stats
**** This test partially indirectly tests Minimum, Maximum
**** Average,Variance,StdDev which are all memebers of the
**** Stats class
*/
void xStats :: addTest (void)
{
gpstk::Stats<double> addTest;
CPPUNIT_ASSERT_NO_THROW(addTest.Add(10.,1));
addTest.Add(20.,1);
addTest.Add(30.,1);
//Create a vector of 1 member with a value of 40.0
gpstk::Vector<double> one(1,40.);
//Create a vector with one member with a value of 1
gpstk::Vector<double> weight(1,1);
CPPUNIT_ASSERT_NO_THROW(addTest.Add(one,weight));
CPPUNIT_ASSERT_EQUAL((unsigned) 4, addTest.N());
CPPUNIT_ASSERT_EQUAL(10., addTest.Minimum());
CPPUNIT_ASSERT_EQUAL(40., addTest.Maximum());
CPPUNIT_ASSERT_DOUBLES_EQUAL(25., addTest.Average(),1E-6);
CPPUNIT_ASSERT_DOUBLES_EQUAL(166.66667, addTest.Variance(),1E-3);
CPPUNIT_ASSERT_DOUBLES_EQUAL(12.9099445, addTest.StdDev(),1E-6);
CPPUNIT_ASSERT_EQUAL(4., addTest.Normalization());
CPPUNIT_ASSERT_EQUAL(true, addTest.Weighted());
gpstk::Stats<double> addTest0;
gpstk::Vector<double> weight0(0,1);
addTest0.Add(10.,0);
addTest0.Add(20.,0);
addTest0.Add(30.,0);
addTest0.Add(one,weight0);
CPPUNIT_ASSERT_EQUAL((unsigned) 4, addTest0.N());
CPPUNIT_ASSERT_EQUAL(10., addTest0.Minimum());
CPPUNIT_ASSERT_EQUAL(40., addTest0.Maximum());
CPPUNIT_ASSERT_DOUBLES_EQUAL(25., addTest0.Average(),1E-6);
CPPUNIT_ASSERT_DOUBLES_EQUAL(166.66667, addTest0.Variance(),1E-3);
CPPUNIT_ASSERT_DOUBLES_EQUAL(12.9099445, addTest0.StdDev(),1E-6);
CPPUNIT_ASSERT_EQUAL(0., addTest0.Normalization());
CPPUNIT_ASSERT_EQUAL(false, addTest0.Weighted());
gpstk::Vector<double> two(4,20.);
gpstk::Vector<double> weight2(1,0);
try
{
CPPUNIT_ASSERT_THROW(addTest.Add(two,weight2),gpstk::Exception);
}
catch(gpstk::Exception& e)
{
}
}
int main(int, char *[])
{
typedef boost::property<boost::edge_weight_t, float> EdgeWeightProperty;
typedef boost::adjacency_list < boost::listS, boost::vecS, boost::directedS,
boost::no_property, EdgeWeightProperty > Graph;
typedef boost::graph_traits < Graph >::vertex_descriptor vertex_descriptor;
typedef boost::graph_traits < Graph >::edge_descriptor edge_descriptor;
typedef std::pair<int, int> Edge;
// Create a graph
Graph g;
boost::graph_traits<Graph>::vertex_descriptor v0 = add_vertex(g);
boost::graph_traits<Graph>::vertex_descriptor v1 = add_vertex(g);
boost::graph_traits<Graph>::vertex_descriptor v2 = add_vertex(g);
// Add weighted edges
EdgeWeightProperty weight0(5);
add_edge(v0, v1, weight0, g);
EdgeWeightProperty weight1 = 3;
add_edge(v1, v2, weight1, g);
EdgeWeightProperty weight2 = 2;
add_edge(v2, v0, weight2, g);
// At this point the graph is
/* v0
.
5 / \ 2
/___\
v1 3 v2
*/
// Create things for Dijkstra
std::vector<vertex_descriptor> parents(num_vertices(g)); // To store parents
std::vector<int> distances(num_vertices(g)); // To store distances
// Compute shortest paths from v0 to all vertices, and store the output in parents and distances
boost::dijkstra_shortest_paths(g, v0, boost::predecessor_map(&parents[0]).distance_map(&distances[0]));
// Output results
std::cout << "distances and parents:" << std::endl;
boost::graph_traits < Graph >::vertex_iterator vertexIterator, vend;
for (boost::tie(vertexIterator, vend) = vertices(g); vertexIterator != vend; ++vertexIterator)
{
std::cout << "distance(" << *vertexIterator << ") = " << distances[*vertexIterator] << ", ";
std::cout << "parent(" << *vertexIterator << ") = " << parents[*vertexIterator] << std::endl;
}
std::cout << std::endl;
/*
The output is:
distance(0) = 0, parent(0) = 0
distance(1) = 5, parent(1) = 0
distance(2) = 8, parent(2) = 1
which means:
the distance from v0 to v0 is 0
the distance from v0 to v1 is 5
the distance from v0 to v2 is 8
*/
return EXIT_SUCCESS;
}
