public void TestClusterization()
{
const int W = 16;
var img = ImageHelper.LoadImageAsInt(TestResources._1);
Normalizer.Normalize(100, 500, img);
var info = RidgeFrequencyGenerator.GenerateBlocksInfo(img);
var centers = new ClustersGenerator.ClusterPoint[6];
img = ImageHelper.LoadImageAsInt(TestResources._1);
Normalizer.Normalize(100, 500, img);
info.AddRange(RidgeFrequencyGenerator.GenerateBlocksInfo(img));
img = ImageHelper.LoadImageAsInt(TestResources._2);
Normalizer.Normalize(100, 500, img);
info.AddRange(RidgeFrequencyGenerator.GenerateBlocksInfo(img));
img = ImageHelper.LoadImageAsInt(TestResources._3);
Normalizer.Normalize(100, 500, img);
info.AddRange(RidgeFrequencyGenerator.GenerateBlocksInfo(img));
img = ImageHelper.LoadImageAsInt(TestResources._4);
Normalizer.Normalize(100, 500, img);
info.AddRange(RidgeFrequencyGenerator.GenerateBlocksInfo(img));
img = ImageHelper.LoadImageAsInt(TestResources._5);
Normalizer.Normalize(100, 500, img);
var middle = new ClustersGenerator.ClusterPoint(0, 0, 0);
foreach (var bl in info)
{
middle.Amplitude += bl.Amplitude;
middle.Frequency += bl.Frequency;
middle.Variance += bl.Variance;
}
middle.Amplitude /= info.Count;
middle.Frequency /= info.Count;
middle.Variance /= info.Count;
Random rand = new Random();
for (int i = 0; i < 6; i++)
{
centers[i] = info[rand.Next(0, info.Count)];
}
var centroids = ClustersGenerator.Clusterization(info, centers);
// Writing result to file
var path = ClustersGenerator.ClusterPath;
using (StreamWriter file = new StreamWriter(path))
{
for (int i = 0; i < centers.Length; i++)
{
file.WriteLine(i);
file.WriteLine(centroids[i].Amplitude);
file.WriteLine(centroids[i].Frequency);
file.WriteLine(centroids[i].Variance);
file.WriteLine();
}
}
Process.Start(path);
img = ImageHelper.LoadImageAsInt(TestResources._1);
ShowClusters(img, centroids, W);
img = ImageHelper.LoadImageAsInt(TestResources._2);
ShowClusters(img, centroids, W);
img = ImageHelper.LoadImageAsInt(TestResources._3);
ShowClusters(img, centroids, W);
img = ImageHelper.LoadImageAsInt(TestResources._4);
ShowClusters(img, centroids, W);
img = ImageHelper.LoadImageAsInt(TestResources._5);
ShowClusters(img, centroids, W);
}
static void Main(string[] args)
{
//Console.WriteLine();
//Console.ReadLine();
try
{
Console.WriteLine("Ingrese minSupport :");
double minSupport = 0.005;//Convert.ToDouble(Console.ReadLine()) / 100;
Console.WriteLine("Ingrese minConfidence :");
double minConfidence = Convert.ToDouble(Console.ReadLine()) / 100;
Data data = new Data(false);
FIGeneration fIGeneration = new FIGeneration();
fIGeneration.minSupport = minSupport;
RuleGenerator ruleGenerator = new RuleGenerator();
ruleGenerator.minConfidence = minConfidence;
ClustersGenerator clustersGenerator = new ClustersGenerator();
clustersGenerator.minPertencia = 0.60;
data.LoadTransactions();
data.LoadClientes();
Console.WriteLine("--> " + data.transactions.Count);
data.PodarTransacciones(0.003);
Console.WriteLine("--> " + data.transactions.Count);
data.PodarClientes();
Console.WriteLine("Clientes -> " + data.clientes.Count);
data.PodarArticulos();
Console.WriteLine("Items Podados.- " + data.items.Count);
data.PodarItemsPorSupport(minSupport);
fIGeneration.AprioriFrequentItemGeneration(3, data);
List <ItemSet> fi = fIGeneration.candidates.Where(x => x.items.Count > 1).ToList();
List <ItemSet> fiTotales = fIGeneration.candidates.ToList();
Console.WriteLine("Itemsets totales: " + fi.Count);
Console.WriteLine("---------------------------------------- \n Frequents ItemSe Generados... \n Creando Reglas de asociacion ...");
//Generando Reglas
ruleGenerator.GenerarReglas(fi, fIGeneration);
Console.WriteLine(ruleGenerator.associationRules.Count + "++++++++");
foreach (Rule rule in ruleGenerator.associationRules)
{
Console.WriteLine(rule.antecedente.ToStringItems() + " ->" + rule.consecuente.ToStringItems() + " " + rule.confidence);
}
//Generando CLusters
clustersGenerator.GenerarClusters(data.transactions, data.clientes, fi);
/*
* Analyzer analyzer = new Analyzer();
* analyzer.minPertenencia = 0.75;
* analyzer.minPertenencia = 0.75;
* analyzer.minSupport = 0.01;
* analyzer.LoadData();
* analyzer.PodarDatos(0.1/100);
* //analyzer.data.PodarItemsPorSupport(0.1);
*
* analyzer.GenerarFrequentItemSets(2);
* Console.WriteLine(analyzer.fIGeneration.candidates.Count);*/
foreach (ItemSet itemset in fIGeneration.candidates)
{
String cods = "";
itemset.items.ToList().ForEach(x => cods += x.Value.cod + " ");
Console.WriteLine("Conjunto frecuente -> Support: " + itemset.support + " Conjunto: " + cods);
}
// List<ItemSet> fi = fIGeneration.candidates.Where(x => x.items.Count > 1).ToList();
// clustersGenerator.GenerarClusters(data.transactions, data.clientes, fi);
foreach (Cluster c in clustersGenerator.clusters)
{
Console.WriteLine("Cluster: " + c.agrupador.ToStringItems());
foreach (Elemento e in c.elementos)
{
Console.WriteLine("Elemento: " + e.id + " pertenece un " + e.pertenencia + " al cluster");
}
}
Console.WriteLine(" Clusters final " + clustersGenerator.clusters.Count);
Console.WriteLine("Terminó!");
Console.ReadLine();
}
catch (Exception e)
{
Console.WriteLine("Error main: " + e.Message + "\n" + e.StackTrace);
Console.ReadLine();
}
}
