// Use this for initialization
void Start()
{
//利用LazyPrim算法计算稀疏有权图的最短路径
print("求稀疏有权图的最小生成树");
string name = "";
string url = "";
name = "testWeightG1.txt";
url = FileHelper.FileNameHelper(name);
WeightSpareGraph <float> wsGraph = null;
ReadWeightGraph.ReadGraphFromFile(url, out wsGraph, false);
wsGraph.print();
LazyPrimMST lazyPrim = new LazyPrimMST(wsGraph);
lazyPrim.print();
print("最小生成树的长度为：" + lazyPrim.length());
print("使用深度优先搜索的方法得到一棵生成树");
lazyPrim = new LazyPrimMST(wsGraph, true);
lazyPrim.printOneTree();
print("*********************");
//利用Prim算法计算稀疏有权图的最短路径
PrimMST prim = new PrimMST(wsGraph);
prim.print();
}
void Start()
{
EdgeWeightedGraph G = new EdgeWeightedGraph(txt, ' ');
PrimMST mst = new PrimMST(G);
foreach (Edge e in mst.Edges())
{
print(e);
}
print(mst.weight());
}
public void TestPrimMST()
{
PrimMST mst = graph.PrimMST();
Edge[] edges = mst.Edges();
foreach (Edge edge in edges)
{
// TestContext.WriteLine(edge.ToString());
}
TestContext.WriteLine(mst.Weight().ToString());
}
public void TestPrimMST()
{
string fileName = @"Graph\testG1.txt";
var g1 = new SparseGraph <double>(8, false);
var gr1 = new ReadGraph <double>(g1, fileName);
g1.Show();
// test prim
Console.WriteLine("Test Prim MST: ");
var primMST = new PrimMST <double>(g1);
var mst = primMST.MSTEdges;
foreach (var edge in mst)
{
Console.WriteLine(edge);
}
Console.WriteLine("The MST weight is: " + primMST.MSTWeight);
}
void MinTreeTest()
{
EdgeWeightedGraph g = new EdgeWeightedGraph(5);
g.AddEdge(new Edge(0, 1, 1));
g.AddEdge(new Edge(1, 2, 2));
g.AddEdge(new Edge(1, 3, 6));
g.AddEdge(new Edge(2, 4, 4));
g.AddEdge(new Edge(3, 4, 5));
LazyPrimMST mst = new LazyPrimMST(g);
//Debug.Log("延迟:" + mst.Weight());
PrimMST primMst = new PrimMST(g);
//Debug.Log("即时:" + primMst.Weight());
KruskalMST kruskalMst = new KruskalMST(g);
Debug.Log(kruskalMst.Weight());
}
public void SolveTest()
{
string[] lines = File.ReadAllLines("MSTTestGraph.txt");
int n = int.Parse(lines[0].Split(' ')[0]);
int m = int.Parse(lines[0].Split(' ')[1]);
int mstCost = int.Parse(lines[lines.Length - 1]);
UndirectedGraph undirectedGraph = new UndirectedGraph(new WeightedMatrixRepresentation(n));
for (int i = 0; i < m; i++)
{
string[] tokens = lines[i + 1].Split(' ');
int from = int.Parse(tokens[0]);
int to = int.Parse(tokens[1]);
double cost = double.Parse(tokens[2]);
undirectedGraph.AddEdge(new Edge(from, to, cost));
}
PrimMST primMST = new PrimMST();
undirectedGraph.MSTSolver = primMST;
var mst = undirectedGraph.GetMinimumSpanningTree();
if (mst.Count != n - 1)
{
Assert.Fail();
}
int totalCost = 0;
foreach (Edge baseEdge in mst)
{
totalCost += (int)baseEdge.Cost;
}
if (totalCost != mstCost)
{
Assert.Fail();
}
}
static void Main(string[] args)
{
// 使用两种图的储存方式来读取文件
string fileName = "TextG1.txt";
SparseGraph graph = new SparseGraph(13, false);
ReadGraph readGraph = new ReadGraph(graph, fileName);
Console.WriteLine("test g1 in sparse graph ");
graph.Show();
Console.WriteLine();
DenseGraph graph1 = new DenseGraph(13, false);
ReadGraph readGraph1 = new ReadGraph(graph1, fileName);
Console.WriteLine("test g1 in dense graph ");
graph1.Show();
Console.WriteLine("===========================================");
DenseGraph graph2 = new DenseGraph(13, false);
ReadGraph readGraph2 = new ReadGraph(graph2, fileName);
Path path = new Path(graph2, 0);
Console.WriteLine("test path g1 in dense graph ");
path.ShowPath(4);
Console.WriteLine("===========================================");
WeightedDenseGraph <double> wgraph3 = new WeightedDenseGraph <double>(8, false);
ReadWeightedGraph readGraph3 = new ReadWeightedGraph(wgraph3, "testG1.txt");
Console.WriteLine("test in weighted dense graph ");
wgraph3.Show();
Console.WriteLine("===========================================");
SparseWeightedGraph <double> wgraph4 = new SparseWeightedGraph <double>(8, false);
ReadWeightedGraph readGraph4 = new ReadWeightedGraph(wgraph4, "testG1.txt");
Console.WriteLine("test in weighted sparse graph ");
wgraph4.Show();
Console.WriteLine("Test MinHeap");
int n = 100000;
MinHeap <int> heap = new MinHeap <int>(n);
Random rand = new Random();
for (int i = 0; i < n; i++)
{
heap.Add(rand.Next(n));
}
List <int> list = new List <int>();
for (int i = 0; i < n; i++)
{
list.Add(heap.ExtractMin());
}
for (int i = 0; i < n - 1; i++)
{
if (list[i] > list[i + 1])
{
throw new Exception("MinHeap error");
}
}
Console.WriteLine("===========================================");
Console.WriteLine("Test MST");
SparseWeightedGraph <double> wgraph5 = new SparseWeightedGraph <double>(8, false);
ReadWeightedGraph readGraph5 = new ReadWeightedGraph(wgraph5, "testG1.txt");
LazyPrimeMST <double> mst = new LazyPrimeMST <double>(wgraph5);
List <Edge <double> > mstPath = mst.MstEdges();
for (int i = 0; i < mstPath.Count; i++)
{
Console.WriteLine(mstPath[i]);
}
Console.WriteLine("Test Index MinHeap");
IndexMinHeap <int> heap1 = new IndexMinHeap <int>(n);
for (int i = 0; i < n; i++)
{
heap1.Add(i, rand.Next(n));
}
for (int i = 0; i < n / 2; i++)
{
heap1.Update(i, rand.Next(n));
}
List <int> list1 = new List <int>();
for (int i = 0; i < n; i++)
{
list1.Add(heap1.ExtractMin());
}
for (int i = 0; i < n - 1; i++)
{
if (list1[i] > list1[i + 1])
{
throw new Exception("IndexMinHeap error");
}
}
Console.WriteLine("===========================================");
Console.WriteLine("Test MST Optimization");
SparseWeightedGraph <double> wgraph6 = new SparseWeightedGraph <double>(8, false);
ReadWeightedGraph readGraph6 = new ReadWeightedGraph(wgraph6, "testG1.txt");
PrimMST <double> mst1 = new PrimMST <double>(wgraph6);
List <Edge <double> > mstPath1 = mst1.MstEdges();
for (int i = 0; i < mstPath1.Count; i++)
{
Console.WriteLine(mstPath1[i]);
}
}
public void Run()
{
Console.WriteLine("Choose file:"); // Prompt
Console.WriteLine("1 - tinyEWG.txt"); // Prompt
Console.WriteLine("2 - mediumEWG.txt"); // Prompt
//Console.WriteLine("3 - mediumEWG.txt"); // Prompt
Console.WriteLine("or quit"); // Prompt
var fileNumber = Console.ReadLine();
string fileName;
switch (fileNumber)
{
case "1":
fileName = "tinyEWG.txt";
break;
case "2":
fileName = "mediumEWG.txt";
break;
//case "3":
// fileName = "largeEWG.zip";
// break;
case "quit":
return;
default:
return;
}
var @in = new In($"Files\\Graphs\\{fileName}");
var lines = @in.ReadAllLines();
var lineIterator = 0;
var v = 0;
var e = 0;
var edges = new List <EdgeW>();
foreach (var line in lines)
{
if (lineIterator == 0)
{
v = Convert.ToInt32(line);
}
if (lineIterator == 1)
{
e = Convert.ToInt32(line);
}
if (lineIterator > 1)
{
var lineSplitted = line.Split(new[] { ' ' }, StringSplitOptions.RemoveEmptyEntries);
var ve = Convert.ToInt32(lineSplitted[0]);
var we = Convert.ToInt32(lineSplitted[1]);
var weight = Convert.ToDouble(lineSplitted[2], CultureInfo.InvariantCulture);
var edge = new EdgeW(ve, we, weight);
edges.Add(edge);
}
lineIterator++;
}
var edgeWeightedGraph = new EdgeWeightedGraph(v, e, edges);
Console.WriteLine(edgeWeightedGraph);
var mst = new PrimMST(edgeWeightedGraph);
foreach (var edge in mst.Edges())
{
Console.WriteLine(edge);
}
Console.Write($"{$"{mst.Weight():0.00000}"}{Environment.NewLine}");
Console.ReadLine();
}
