List of usage examples for weka.core.converters CSVLoader getDataSet
@Override
public Instances getDataSet() throws IOException
From source file:classifyfromimage.java
private void jButton1ActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_jButton1ActionPerformed this.name3 = IJ.getImage().getTitle(); this.name4 = this.name3.replaceFirst("[.][^.]+$", ""); System.out.println("hola " + this.name4); selectWindow(this.name3); System.out.println(this.name4); System.out.println(this.name3); RoiManager rm = RoiManager.getInstance(); IJ.run("Duplicate...", this.name3); IJ.run("Set Measurements...", "area perimeter fit shape limit scientific redirect=None decimal=5"); selectWindow(this.name3); IJ.run("Subtract Background...", "rolling=1.5"); IJ.run("Enhance Contrast...", "saturated=25 equalize"); IJ.run("Subtract Background...", "rolling=1.5"); IJ.run("Convolve...", "text1=[-1 -3 -4 -3 -1\n-3 0 6 0 -3\n-4 6 50 6 -4\n-3 0 6 0 -3\n-1 -3 -4 -3 -1\n] normalize"); IJ.run("8-bit", ""); IJ.run("Restore Selection", ""); IJ.run("Make Binary", ""); Prefs.blackBackground = false;/* www . jav a2 s. co m*/ IJ.run("Convert to Mask", ""); IJ.run("Restore Selection", ""); this.valor1 = this.interval3.getText(); this.valor2 = this.interval4.getText(); System.out.println("VECTOR-> punctua: " + this.valor1 + " " + this.valor2); this.text = "size=" + this.valor1 + "-" + this.valor2 + " pixel show=Outlines display include summarize add"; IJ.run("Analyze Particles...", this.text); IJ.saveAs("tif", this.name3 + "_processed"); String dest_filename1, dest_filename2, full; selectWindow("Results"); //dest_filename1 = this.name2 + "_complete.txt"; dest_filename2 = this.name3 + "_complete.csv"; //IJ.saveAs("Results", prova + File.separator + dest_filename1); IJ.run("Input/Output...", "jpeg=85 gif=-1 file=.csv copy_row save_column save_row"); //IJ.saveAs("Results", dir + File.separator + dest_filename2); IJ.saveAs("Results", this.name3 + "_complete.csv"); IJ.run("Restore Selection"); IJ.run("Clear Results"); //txtarea.setText("Converting, please wait... "); try { CSVLoader loader = new CSVLoader(); loader.setSource(new File(this.name3 + "_complete.csv")); Instances data = loader.getDataSet(); System.out.println(data); // save ARFF String arffile = this.name3 + ".arff"; System.out.println(arffile); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File(arffile)); saver.writeBatch(); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } //txtdata2.setText(this.name3); //txtarea.setText("Succesfully converted " + this.name3); //txtarea.setText("Analysing your data, please wait... "); Instances data; try { data = new Instances(new BufferedReader(new FileReader(this.name3 + ".arff"))); Instances newData = null; Add filter; newData = new Instances(data); filter = new Add(); filter.setAttributeIndex("last"); filter.setNominalLabels("rods,punctua,networks"); filter.setAttributeName("target"); filter.setInputFormat(newData); newData = Filter.useFilter(newData, filter); System.out.print(newData); Vector vec = new Vector(); newData.setClassIndex(newData.numAttributes() - 1); if (!newData.equalHeaders(newData)) { throw new IllegalArgumentException("Train and test are not compatible!"); } URL urlToModel = this.getClass().getResource("/" + "Final.model"); InputStream stream = urlToModel.openStream(); Classifier cls = (Classifier) weka.core.SerializationHelper.read(stream); System.out.println("PROVANT MODEL.classifyInstance"); for (int i = 0; i < newData.numInstances(); i++) { double pred = cls.classifyInstance(newData.instance(i)); double[] dist = cls.distributionForInstance(newData.instance(i)); System.out.print((i + 1) + " - "); System.out.print(newData.classAttribute().value((int) pred) + " - "); //txtarea2.setText(Utils.arrayToString(dist)); System.out.println(Utils.arrayToString(dist)); vec.add(newData.classAttribute().value((int) pred)); } int p = 0, n = 0, r = 0; //txtarea2.append(Utils.arrayToString(this.target)); for (Object vec1 : vec) { if ("rods".equals(vec1.toString())) { r = r + 1; } if ("punctua".equals(vec1.toString())) { p = p + 1; } if ("networks".equals(vec1.toString())) { n = n + 1; } PrintWriter out = null; try { out = new PrintWriter(this.name3 + "_morphology.txt"); out.println(vec); out.close(); } catch (Exception ex) { ex.printStackTrace(); } //System.out.println(vec.get(i)); } System.out.println("VECTOR-> punctua: " + p + ", rods: " + r + ", networks: " + n); IJ.showMessage( "Your file:" + this.name3 + "arff" + "\nhas been analysed, and it is composed by-> punctua: " + p + ", rods: " + r + ", networks: " + n); this.txtarea2.setText( "Your file:" + this.name3 + ".arff" + "\nhas been analysed, and it is composed by-> punctua: " + p + ", rods: " + r + ", networks: " + n); A_MachineLearning nf1 = new A_MachineLearning(); A_MachineLearning.txtresults1.setText(this.txtarea2.getText()); A_MachineLearning.txtresults1.setText(this.txtarea2.getText()); A_MachineLearning.txtresults1.setText(this.txtarea2.getText()); A_MachineLearning.txtresults1.append(this.txtarea2.getText()); A_MachineLearning.txtresults1.append(this.txtarea2.getText()); A_MachineLearning.txtresults1.append(this.txtarea2.getText()); nf1.setVisible(true); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } catch (Exception ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } IJ.run("Clear Results"); //IJ.RoiManager("Delete"); IJ.run("Clear Results"); IJ.run("Close All", ""); if (WindowManager.getFrame("Results") != null) { IJ.selectWindow("Results"); IJ.run("Close"); } if (WindowManager.getFrame("Summary") != null) { IJ.selectWindow("Summary"); IJ.run("Close"); } if (WindowManager.getFrame("Results") != null) { IJ.selectWindow("Results"); IJ.run("Close"); } if (WindowManager.getFrame("ROI Manager") != null) { IJ.selectWindow("ROI Manager"); IJ.run("Close"); } IJ.run("Close All", "roiManager"); IJ.run("Close All", ""); setVisible(false); dispose();// TODO add your handling code here: setVisible(false); dispose();// TODO add your handling code here: // TODO add your handling code here: }
From source file:A_MachineLearningMenu.java
private void jMenuItem3ActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_jMenuItem3ActionPerformed JFileChooser chooser = new JFileChooser("."); chooser.setApproveButtonText("OK"); chooser.setFileSelectionMode(JFileChooser.DIRECTORIES_ONLY); chooser.setMultiSelectionEnabled(false); Component fileChooserDialog = null; chooser.showOpenDialog(fileChooserDialog); //ActionMap am = chooser.getActionMap(); //Action key = am.get("OK"); //key.setEnabled(false); this.pathway = chooser.getSelectedFile().getAbsolutePath(); File[] filesInDirectory = new File(this.pathway).listFiles(); for (File f : filesInDirectory) { String filepath2 = f.getAbsolutePath(); String fileExtenstion = filepath2.substring(filepath2.lastIndexOf(".") + 1, filepath2.length()); if ("csv".equals(fileExtenstion)) { System.out.println("CSV file found ->" + filepath2); try { String fipa = this.pathway + File.separator + file; System.out.println(filepath2); System.out.println(fipa); CSVLoader loader = new CSVLoader(); loader.setSource(new File(filepath2)); Instances data = loader.getDataSet(); System.out.println(data); // save ARFF String arffile = filepath2 + ".arff"; System.out.println(arffile); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File(arffile)); saver.writeBatch();// www . ja v a 2 s. c o m } catch (IOException ex) { Logger.getLogger(A_MachineLearningMenu.class.getName()).log(Level.SEVERE, null, ex); } } } IJ.showMessage("Conversion complete"); // TODO add your handling code here: }
From source file:A_MachineLearningMenu.java
private void jMenuItem2ActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_jMenuItem2ActionPerformed JFileChooser chooser = new JFileChooser(); chooser.setMultiSelectionEnabled(true); //chooser.setMultiSelectionEnable(true); int result = chooser.showOpenDialog(this); if (result == JFileChooser.APPROVE_OPTION) { File selectedFile = chooser.getSelectedFile(); System.out.println("Selected file: " + selectedFile.getAbsolutePath()); this.file2 = chooser.getSelectedFile().getAbsolutePath(); try {//from ww w . jav a 2 s . co m CSVLoader loader = new CSVLoader(); loader.setSource(new File(this.file2)); Instances data = loader.getDataSet(); System.out.println(data); // save ARFF String arffile = this.file2 + ".arff"; System.out.println(arffile); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File(arffile)); saver.writeBatch(); } catch (IOException ex) { Logger.getLogger(A_MachineLearningMenu.class.getName()).log(Level.SEVERE, null, ex); } } // TODO add your handling code here: }
From source file:A_MachineLearning.java
private void jButton3ActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_jButton3ActionPerformed JFileChooser chooser = new JFileChooser(); FileNameExtensionFilter filter = new FileNameExtensionFilter("TEXT FILES", "csv", "text"); chooser.setFileFilter(filter);//from w ww . j a v a 2 s . c om chooser.setMultiSelectionEnabled(true); int result = chooser.showOpenDialog(this); if (result == JFileChooser.APPROVE_OPTION) { File selectedFile = chooser.getSelectedFile(); System.out.println("Selected file: " + selectedFile.getAbsolutePath()); this.file2 = chooser.getSelectedFile().getAbsolutePath(); try { CSVLoader loader = new CSVLoader(); loader.setSource(new File(this.file2)); Instances data = loader.getDataSet(); System.out.println(data); // save ARFF this.file2 = this.file2.replaceFirst("[.][^.]+$", ""); String arffile = this.file2 + ".arff"; System.out.println(arffile); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File(arffile)); saver.writeBatch(); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } System.out.println(this.file2); //txtdata2.setText(this.file2); } txtarea.setText("Succesfully converted " + this.file2); try { FileReader reader = new FileReader(this.file2 + ".arff"); BufferedReader br = new BufferedReader(reader); txtarea2.read(br, null); br.close(); txtarea2.requestFocus(); } catch (Exception e2) { System.out.println(e2); } txtdata.setText(chooser.getSelectedFile().getName()); txtarea.setText("You have choose to load the file: " + chooser.getSelectedFile().getName()); /** JFileChooser chooser = new JFileChooser(); FileNameExtensionFilter filter = new FileNameExtensionFilter("TEXT FILES", "csv", "text"); chooser.setFileFilter(filter); chooser.setMultiSelectionEnabled(true); //chooser.setMultiSelectionEnable(true); int result = chooser.showOpenDialog(this); if (result == JFileChooser.APPROVE_OPTION) { File selectedFile = chooser.getSelectedFile(); System.out.println("Selected file: " + selectedFile.getAbsolutePath()); this.file2 = chooser.getSelectedFile().getAbsolutePath(); try { CSVLoader loader = new CSVLoader(); loader.setSource(new File(this.file2)); Instances data = loader.getDataSet(); System.out.println(data); // save ARFF this.file2 = this.file2.replaceFirst("[.][^.]+$", ""); String arffile = this.file2 + ".arff"; System.out.println(arffile); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File(arffile)); saver.writeBatch(); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } //txtdata2.setText(this.file2); } txtarea.setText("Succesfully converted " + this.file2); try { FileReader reader = new FileReader(this.file2 + ".arff"); BufferedReader br = new BufferedReader(reader); txtarea2.read(br, null); br.close(); txtarea2.requestFocus(); } catch (Exception e2) { System.out.println(e2); } txtdata.setText(chooser.getSelectedFile().getName()); txtarea.setText("You have choose to load the file: " + chooser.getSelectedFile().getName()); **/ }
From source file:classificationPLugin.java
private void ClassifyActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_ClassifyActionPerformed this.name = txtdirecotry2.getText(); System.out.println(this.name); try {/*from w w w .ja v a2 s. co m*/ CSVLoader loader = new CSVLoader(); loader.setSource(new File(this.name)); Instances data = loader.getDataSet(); System.out.println(data); // save ARFF String arffile = this.name + ".arff"; System.out.println(arffile); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File(arffile)); saver.writeBatch(); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } try { FileReader reader = new FileReader(this.name + ".arff"); BufferedReader br = new BufferedReader(reader); instance.read(br, null); br.close(); instance.requestFocus(); } catch (Exception e2) { System.out.println(e2); } Instances data; try { data = new Instances(new BufferedReader(new FileReader(this.name + ".arff"))); Instances newData = null; Add filter; newData = new Instances(data); filter = new Add(); filter.setAttributeIndex("last"); filter.setNominalLabels("rods,punctua,networks"); filter.setAttributeName("target"); filter.setInputFormat(newData); newData = Filter.useFilter(newData, filter); System.out.print(newData); Vector vec = new Vector(); newData.setClassIndex(newData.numAttributes() - 1); if (!newData.equalHeaders(newData)) { throw new IllegalArgumentException("Train and test are not compatible!"); } URL urlToModel = this.getClass().getResource("/" + "Final.model"); InputStream stream = urlToModel.openStream(); Classifier cls = (Classifier) weka.core.SerializationHelper.read(stream); System.out.println("PROVANT MODEL.classifyInstance"); for (int i = 0; i < newData.numInstances(); i++) { double pred = cls.classifyInstance(newData.instance(i)); double[] dist = cls.distributionForInstance(newData.instance(i)); System.out.print((i + 1) + " - "); System.out.print(newData.classAttribute().value((int) pred) + " - "); //txtarea2.setText(Utils.arrayToString(dist)); System.out.println(Utils.arrayToString(dist)); vec.add(newData.classAttribute().value((int) pred)); } int p = 0, n = 0, r = 0; //txtarea2.append(Utils.arrayToString(this.target)); for (Object vec1 : vec) { if ("rods".equals(vec1.toString())) { r = r + 1; } if ("punctua".equals(vec1.toString())) { p = p + 1; } if ("networks".equals(vec1.toString())) { n = n + 1; } PrintWriter out = null; try { out = new PrintWriter(this.name + "_morphology.txt"); out.println(vec); out.close(); } catch (Exception ex) { ex.printStackTrace(); } //System.out.println(vec.get(i)); } System.out.println("VECTOR-> punctua: " + p + ", rods: " + r + ", networks: " + n); IJ.showMessage( "Your file:" + this.name + "arff" + "\nhas been analysed, and it is composed by-> \npunctua: " + p + ", rods: " + r + ", networks: " + n); classi.setText( "Your file:" + this.name + "arff" + "\nhas been analysed, and it is composed by: \npunctua: " + p + ", rods: " + r + ", networks: " + n); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } catch (Exception ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } IJ.run("Clear Results"); IJ.run("Clear Results"); IJ.run("Close All", ""); if (WindowManager.getFrame("Results") != null) { IJ.selectWindow("Results"); IJ.run("Close"); } if (WindowManager.getFrame("Summary") != null) { IJ.selectWindow("Summary"); IJ.run("Close"); } if (WindowManager.getFrame("Results") != null) { IJ.selectWindow("Results"); IJ.run("Close"); } if (WindowManager.getFrame("ROI Manager") != null) { IJ.selectWindow("ROI Manager"); IJ.run("Close"); } IJ.run("Close All", "roiManager"); IJ.run("Close All", ""); }
From source file:dialog1.java
private void jButton1ActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_jButton1ActionPerformed try {/*from www.j a v a2 s. c o m*/ CSVLoader loader = new CSVLoader(); loader.setSource(new File(txtfilename.getText() + "_complete.csv")); Instances data = loader.getDataSet(); System.out.println(data); // save ARFF String arffile = this.name3 + ".arff"; System.out.println(arffile); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File(arffile)); saver.writeBatch(); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } Instances data; try { data = new Instances(new BufferedReader(new FileReader(this.name3 + ".arff"))); Instances newData = null; Add filter; newData = new Instances(data); filter = new Add(); filter.setAttributeIndex("last"); filter.setNominalLabels("rods,punctua,networks"); filter.setAttributeName("target"); filter.setInputFormat(newData); newData = Filter.useFilter(newData, filter); System.out.print(newData); Vector vec = new Vector(); newData.setClassIndex(newData.numAttributes() - 1); if (!newData.equalHeaders(newData)) { throw new IllegalArgumentException("Train and test are not compatible!"); } /*URL urlToModel = this.getClass().getResource("/" + "Final.model"); InputStream stream = urlToModel.openStream();*/ InputStream stream = this.getClass().getResourceAsStream("/" + "Final.model"); Classifier cls = (Classifier) weka.core.SerializationHelper.read(stream); System.out.println("PROVANT MODEL.classifyInstance"); for (int i = 0; i < newData.numInstances(); i++) { double pred = cls.classifyInstance(newData.instance(i)); double[] dist = cls.distributionForInstance(newData.instance(i)); System.out.print((i + 1) + " - "); System.out.print(newData.classAttribute().value((int) pred) + " - "); //txtarea2.setText(Utils.arrayToString(dist)); System.out.println(Utils.arrayToString(dist)); vec.add(newData.classAttribute().value((int) pred)); //txtarea2.append(Utils.arrayToString(newData.classAttribute().value((int) pred))); //this.target2.add((i + 1) + " -); //this.target.add(newData.classAttribute().value((int) pred)); //for (String s : this.list) { //this.target2 += s + ","; } int p = 0, n = 0, r = 0; //txtarea2.append(Utils.arrayToString(this.target)); for (Object vec1 : vec) { if ("rods".equals(vec1.toString())) { r = r + 1; } if ("punctua".equals(vec1.toString())) { p = p + 1; } if ("networks".equals(vec1.toString())) { n = n + 1; } PrintWriter out = null; try { out = new PrintWriter(this.name3 + "_morphology.txt"); out.println(vec); out.close(); } catch (Exception ex) { ex.printStackTrace(); } //System.out.println(vec.get(i)); } System.out.println("VECTOR-> punctua: " + p + ", rods: " + r + ", networks: " + n); IJ.showMessage( "Your file:" + this.name3 + "arff" + "\nhas been analysed, and it is composed by-> punctua: " + p + ", rods: " + r + ", networks: " + n); //txtarea2.setText("Your file:" + this.name3 + ".arff" //+ "\nhas been analysed, and it is composed by-> punctua: " + p + ", rods: " + r + ", networks: " + n //+ "\n" //+ "\nAnalyse complete"); //txtarea.setText("Analyse complete"); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } catch (Exception ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } IJ.run("Clear Results"); IJ.run("Clear Results"); IJ.run("Close All", ""); if (WindowManager.getFrame("Results") != null) { IJ.selectWindow("Results"); IJ.run("Close"); } if (WindowManager.getFrame("Summary") != null) { IJ.selectWindow("Summary"); IJ.run("Close"); } if (WindowManager.getFrame("Results") != null) { IJ.selectWindow("Results"); IJ.run("Close"); } if (WindowManager.getFrame("ROI Manager") != null) { IJ.selectWindow("ROI Manager"); IJ.run("Close"); } IJ.run("Close All", "roiManager"); IJ.run("Close All", ""); setVisible(false); dispose();// TODO add your handling code here: setVisible(false); dispose();// TODO add your handling code here: // TODO add your handling code here: }
From source file:task2.java
/** * Processes requests for both HTTP <code>GET</code> and <code>POST</code> * methods.//from w ww. ja va2s.c o m * * @param request servlet request * @param response servlet response * @throws ServletException if a servlet-specific error occurs * @throws IOException if an I/O error occurs */ protected void processRequest(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException { response.setContentType("text/html;charset=UTF-8"); try (PrintWriter out = response.getWriter()) { /* TODO output your page here. You may use following sample code. */ out.println("<!DOCTYPE html>"); out.println("<html>"); out.println("<head>"); out.println("<title>Servlet selection</title>"); out.println("</head>"); out.println("<body>"); CSVLoader loader = new CSVLoader(); loader.setSource(new File("C:/Users//Raguvinoth/Desktop/5339.csv")); Instances data = loader.getDataSet(); //Save ARFF ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File("\"C:/Users/Raguvinoth/Desktop/5339_converted.arff")); saver.writeBatch(); BufferedReader reader = new BufferedReader( new FileReader("C://Users//Raguvinoth//Desktop//weka1//5339_nominal.arff")); Instances data1 = new Instances(reader); if (data1.classIndex() == -1) data1.setClassIndex(data1.numAttributes() - 14); // 1. meta-classifier // useClassifier(data); // 2. AttributeSelector try { AttributeSelection attsel = new AttributeSelection(); GreedyStepwise search = new GreedyStepwise(); CfsSubsetEval eval = new CfsSubsetEval(); attsel.setEvaluator(eval); attsel.setSearch(search); attsel.SelectAttributes(data); int[] indices = attsel.selectedAttributes(); System.out.println("selected attribute indices:\n" + Utils.arrayToString(indices)); System.out.println("\n 4. Linear-Regression on above selected attributes"); long time1 = System.currentTimeMillis(); long sec1 = time1 / 1000; BufferedReader reader1 = new BufferedReader( new FileReader("C://Users//Raguvinoth//Desktop//weka1//5339_linear2.arff")); Instances data2 = new Instances(reader1); data2.setClassIndex(0); LinearRegression lr = new LinearRegression(); lr.buildClassifier(data2); System.out.println(lr.toString()); long time2 = System.currentTimeMillis(); long sec2 = time2 / 1000; long timeTaken = sec2 - sec1; System.out.println("Total time taken for building the model: " + timeTaken + " seconds"); for (int i = 0; i < 5; i++) { out.println("<p>" + "selected attribute indices:\n" + Utils.arrayToString(indices[i]) + "</p>"); } out.println("<p>" + "\n 4. Linear-Regression on above selected attributes" + "</p>"); out.println("<p>" + lr.toString() + "</p>"); out.println("<p>" + "Total time taken for building the model: " + timeTaken + " seconds" + "</p>"); out.println("</body>"); out.println("</html>"); } catch (Exception e) { // TODO Auto-generated catch block e.printStackTrace(); } } }
From source file:classifyfromimage1.java
private void jButton1ActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_jButton1ActionPerformed selectWindow(this.name3); this.name3 = IJ.getImage().getTitle(); this.name4 = this.name3.replaceFirst("[.][^.]+$", ""); RoiManager rm = RoiManager.getInstance(); IJ.run("Duplicate...", this.name4); IJ.run("Set Measurements...", "area perimeter fit shape limit scientific redirect=None decimal=5"); selectWindow(this.name3); IJ.run("Subtract Background...", "rolling=1.5"); IJ.run("Enhance Contrast...", "saturated=25 equalize"); IJ.run("Subtract Background...", "rolling=1.5"); IJ.run("Convolve...", "text1=[-1 -3 -4 -3 -1\n-3 0 6 0 -3\n-4 6 50 6 -4\n-3 0 6 0 -3\n-1 -3 -4 -3 -1\n] normalize"); IJ.run("8-bit", ""); IJ.run("Restore Selection", ""); IJ.run("Make Binary", ""); Prefs.blackBackground = false;/* w w w . ja v a 2 s. c om*/ IJ.run("Convert to Mask", ""); IJ.run("Restore Selection", ""); this.valor1 = this.interval3.getText(); this.valor2 = this.interval4.getText(); this.text = "size=" + this.valor1 + "-" + this.valor2 + " pixel show=Outlines display include summarize add"; IJ.saveAs("tif", this.name3 + "_processed"); String dest_filename1, dest_filename2, full; selectWindow("Results"); //dest_filename1 = this.name2 + "_complete.txt"; dest_filename2 = this.name3 + "_complete.csv"; //IJ.saveAs("Results", prova + File.separator + dest_filename1); IJ.run("Input/Output...", "jpeg=85 gif=-1 file=.csv copy_row save_column save_row"); //IJ.saveAs("Results", dir + File.separator + dest_filename2); IJ.saveAs("Results", this.name3 + "_complete.csv"); IJ.run("Restore Selection"); IJ.run("Clear Results"); try { CSVLoader loader = new CSVLoader(); loader.setSource(new File(this.name3 + "_complete.csv")); Instances data = loader.getDataSet(); System.out.println(data); // save ARFF String arffile = this.name3 + ".arff"; System.out.println(arffile); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File(arffile)); saver.writeBatch(); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } Instances data; try { data = new Instances(new BufferedReader(new FileReader(this.name3 + ".arff"))); Instances newData = null; Add filter; newData = new Instances(data); filter = new Add(); filter.setAttributeIndex("last"); filter.setNominalLabels(txtlabel.getText()); filter.setAttributeName(txtpath2.getText()); filter.setInputFormat(newData); newData = Filter.useFilter(newData, filter); System.out.print(newData); Vector vec = new Vector(); newData.setClassIndex(newData.numAttributes() - 1); if (!newData.equalHeaders(newData)) { throw new IllegalArgumentException("Train and test are not compatible!"); } Classifier cls = (Classifier) weka.core.SerializationHelper.read(txtpath.getText()); System.out.println("PROVANT MODEL.classifyInstance"); for (int i = 0; i < newData.numInstances(); i++) { double pred = cls.classifyInstance(newData.instance(i)); double[] dist = cls.distributionForInstance(newData.instance(i)); System.out.print((i + 1) + " - "); System.out.print(newData.classAttribute().value((int) pred) + " - "); //txtarea2.setText(Utils.arrayToString(dist)); System.out.println(Utils.arrayToString(dist)); vec.add(newData.classAttribute().value((int) pred)); //txtarea2.append(Utils.arrayToString(dist)); classif.add(newData.classAttribute().value((int) pred)); } classif.removeAll(Arrays.asList("", null)); System.out.println(classif); String vecstring = ""; for (Object s : classif) { vecstring += s + ","; System.out.println("Hola " + vecstring); } Map<String, Integer> seussCount = new HashMap<String, Integer>(); for (String t : classif) { Integer i = seussCount.get(t); if (i == null) { i = 0; } seussCount.put(t, i + 1); } String s = vecstring; int counter = 0; for (int i = 0; i < s.length(); i++) { if (s.charAt(i) == '$') { counter++; } } System.out.println(seussCount); System.out.println("hola " + counter++); IJ.showMessage("Your file:" + this.name3 + "arff" + "\n is composed by" + seussCount); txtpath2.setText("Your file:" + this.name3 + "arff" + "\n is composed by" + seussCount); A_MachineLearning nf2 = new A_MachineLearning(); A_MachineLearning.txtresult2.append(this.txtpath2.getText()); nf2.setVisible(true); } catch (Exception ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } IJ.run("Close All", ""); if (WindowManager.getFrame("Results") != null) { IJ.selectWindow("Results"); IJ.run("Close"); } if (WindowManager.getFrame("Summary") != null) { IJ.selectWindow("Summary"); IJ.run("Close"); } if (WindowManager.getFrame("Results") != null) { IJ.selectWindow("Results"); IJ.run("Close"); } if (WindowManager.getFrame("ROI Manager") != null) { IJ.selectWindow("ROI Manager"); IJ.run("Close"); } setVisible(false); dispose();// TODO add your handling code here: // TODO add your handling code here: }
From source file:MachinLearningInterface.java
private void jButton3ActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_jButton3ActionPerformed txtarea.setText("Converting, please wait... "); JFileChooser chooser = new JFileChooser(); FileNameExtensionFilter filter = new FileNameExtensionFilter("TEXT FILES", "csv", "text"); chooser.setFileFilter(filter);/*ww w.ja va 2s .co m*/ chooser.setMultiSelectionEnabled(true); //chooser.setMultiSelectionEnable(true); int result = chooser.showOpenDialog(this); if (result == JFileChooser.APPROVE_OPTION) { File selectedFile = chooser.getSelectedFile(); System.out.println("Selected file: " + selectedFile.getAbsolutePath()); this.file2 = chooser.getSelectedFile().getAbsolutePath(); try { CSVLoader loader = new CSVLoader(); loader.setSource(new File(this.file2)); Instances data = loader.getDataSet(); System.out.println(data); // save ARFF this.file2 = this.file2.replaceFirst("[.][^.]+$", ""); String arffile = this.file2 + ".arff"; System.out.println(arffile); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File(arffile)); saver.writeBatch(); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } //txtdata2.setText(this.file2); } txtarea.setText("Succesfully converted " + this.file2); try { FileReader reader = new FileReader(this.file2 + ".arff"); BufferedReader br = new BufferedReader(reader); txtarea2.read(br, null); br.close(); txtarea2.requestFocus(); } catch (Exception e2) { System.out.println(e2); } txtdata.setText(chooser.getSelectedFile().getName()); txtarea.setText("You have choose to load the file: " + chooser.getSelectedFile().getName()); }
From source file:A_AdvanceMachineLearning.java
private void jButton3ActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_jButton3ActionPerformed JFileChooser chooser = new JFileChooser(); FileNameExtensionFilter filter = new FileNameExtensionFilter("TEXT FILES", "csv", "text"); chooser.setFileFilter(filter);//from ww w . j ava 2 s.co m chooser.setMultiSelectionEnabled(true); int result = chooser.showOpenDialog(this); if (result == JFileChooser.APPROVE_OPTION) { File selectedFile = chooser.getSelectedFile(); System.out.println("Selected file: " + selectedFile.getAbsolutePath()); this.file2 = chooser.getSelectedFile().getAbsolutePath(); try { CSVLoader loader = new CSVLoader(); loader.setSource(new File(this.file2)); Instances data = loader.getDataSet(); System.out.println(data); // save ARFF this.file2 = this.file2.replaceFirst("[.][^.]+$", ""); String arffile = this.file2 + ".arff"; System.out.println(arffile); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(new File(arffile)); saver.writeBatch(); } catch (IOException ex) { Logger.getLogger(MachinLearningInterface.class.getName()).log(Level.SEVERE, null, ex); } System.out.println(this.file2); //txtdata2.setText(this.file2); } txtarea.setText("Succesfully converted " + this.file2); try { FileReader reader = new FileReader(this.file2 + ".arff"); BufferedReader br = new BufferedReader(reader); txtarea2.read(br, null); br.close(); txtarea2.requestFocus(); } catch (Exception e2) { System.out.println(e2); } txtdata.setText(chooser.getSelectedFile().getName()); txtarea.setText("You have choose to load the file: " + chooser.getSelectedFile().getName()); }