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3D rendering engine. Plus modeling. Expected glsl textures 3d and 2d rendering
/*
* Copyright (c) 2022-2023. Manuel Daniel Dahmen
*
*
* Copyright 2012-2023 Manuel Daniel Dahmen
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/*
DBSCAN(D, eps, MinPts)
C = 0
pour chaque point P non visité des données D
marquer P comme visité
PtsVoisins = epsilonVoisinage(D, P, eps)
si tailleDe(PtsVoisins) < MinPts
marquer P comme BRUIT
sinon
C++
etendreCluster(D, P, PtsVoisins, C, eps, MinPts)
etendreCluster(D, P, PtsVoisins, C, eps, MinPts)
ajouter P au cluster C
pour chaque point P' de PtsVoisins
si P' n'a pas été visité
marquer P' comme visité
PtsVoisins' = epsilonVoisinage(D, P', eps)
si tailleDe(PtsVoisins') >= MinPts
PtsVoisins = PtsVoisins U PtsVoisins'
si P' n'est membre d'aucun cluster
ajouter P' au cluster C
epsilonVoisinage(D, P, eps)
*/
package one.empty3.feature;
import one.empty3.io.ProcessFile;
import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Vector;
import java.io.File;
public class Clusters extends ProcessFile {
public boolean process(File in, File out) {
return false;
}
public static List Data;
public static List Clusters;
public static List Pvisited;
public static List clustered;
public static List neighborpts;
public static List neighbors;
public static List noise;
public static void read(int String) {
String[] values;
//Logger.getAnonymousLogger().log(Level.INFO, "Working Directory = " +
// System.getProperty("user.dir"));
Data = new ArrayList();
Pvisited = new ArrayList();
Double ve;
try {
BufferedReader in = new BufferedReader(new FileReader("wholesale.csv"));
String line;
Vector v = null;
int j = 0;
while ((line = in.readLine()) != null) {
values = line.split(",");
v = new Vector();
for (int i = 0; i < values.length; i++) {
ve = Double.parseDouble(values[i]);
v.add(ve);
}
Data.add(v);
//Logger.getAnonymousLogger().log(Level.INFO, Data);
Pvisited.add(false);
//Logger.getAnonymousLogger().log(Level.INFO, Pvisited.get(j));
v = null;
j++;
}
in.close();
} catch (IOException ioException) {
}
}
public static void DBSCAN(int esp, int minPts) {
int c = 0;
//Logger.getAnonymousLogger().log(Level.INFO, c);
Clusters = new ArrayList();
neighborpts = new ArrayList();
for (int i = 0; i < Data.size(); i++) {
neighborpts.add(null);
}
noise = new ArrayList();
for (int i = 0; i < Data.size(); i++) {
//Logger.getAnonymousLogger().log(Level.INFO, "The size of the file is: "+ Data.size());
if (!Pvisited.get(i)) {
Pvisited.set(i, true);
neighborpts.set(i, regionQuery(Data.get(i), esp));
//Logger.getAnonymousLogger().log(Level.INFO, neighborpts);
int size = neighborpts.size();
//Logger.getAnonymousLogger().log(Level.INFO, minPts);
if (size < minPts)
//Logger.getAnonymousLogger().log(Level.INFO, noise);
noise.add(i);
//Logger.getAnonymousLogger().log(Level.INFO, noise.get(i));
else {
//Logger.getAnonymousLogger().log(Level.INFO, "HEy");
Clusters.addAll(Data.get(i));
//Logger.getAnonymousLogger().log(Level.INFO, c);
c++;
//Logger.getAnonymousLogger().log(Level.INFO, "This is c" + c);
// Clusters C = new Clusters(c);
// C.setPoint(Data.get(c));
// Clusters.add(C);
//Logger.getAnonymousLogger().log(Level.INFO, size);
//C.printC().toString();//System.out.print(C.printC());
for (int j = 0; j < size; j++) {
//if P' is not visited
if (!Pvisited.get(neighborpts.indexOf(j))) {
Pvisited.set(j, true);
neighbors.add(regionQuery((Vector) neighborpts.get(j), esp));
//Logger.getAnonymousLogger().log(Level.INFO, neighbors);
int nSize = neighbors.size();
//Logger.getAnonymousLogger().log(Level.INFO, nSize);
if (nSize >= minPts) {
neighborpts.add(neighbors);
}
}
// if P' is not yet a member of any cluster
// add P' to cluster c
if (!clustered.get(neighborpts.indexOf(j))) {
int x = (int) neighborpts.get(j);
Clusters f = Clusters.get(c);
((List) f).add(x);
}
}
}
}
}//end of the main for loop
}
public static double ecluediean(Vector center, Vector L) {
Double result = (double) 0;
for (int i = 0; i < center.size(); i++) {
result += Math.pow(((double) center.get(i)) - (double) (L.get(i)), 2);
}
return Math.sqrt(result);
}
public static List regionQuery(Vector p, int eps) {
List n = new ArrayList();
for (int i = 0; i < Data.size(); i++) {
n.add(null);
}
double dis = 0;
for (int i = 0; i < Data.size(); i++) {
dis = ecluediean(p, Data.get(i));
if (dis <= eps) {
n.set(i, Data.get(i));
}
}
//Logger.getAnonymousLogger().log(Level.INFO, n);
return n;
}
public static void main(String[] args) {
int N = 3;
read(1);
DBSCAN(3, 5);
//Logger.getAnonymousLogger().log(Level.INFO, ((List) Clusters.get(0)).get(1));
}
}