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?? mainmenu.java,v

?? 完整的模式識別庫
?? JAVA,V
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head	1.9;access;symbols;locks	rirwin:1.9; strict;comment	@# @;1.9date	2005.06.21.18.39.43;	author rirwin;	state Exp;branches;next	1.8;1.8date	2005.06.21.18.29.29;	author rirwin;	state Exp;branches;next	1.7;1.7date	2005.06.10.14.41.30;	author rirwin;	state Exp;branches;next	1.6;1.6date	2005.05.24.14.48.03;	author rirwin;	state Exp;branches;next	1.5;1.5date	2005.05.24.14.00.53;	author rirwin;	state Exp;branches;next	1.4;1.4date	2005.03.11.17.53.32;	author patil;	state Exp;branches;next	1.3;1.3date	2004.12.28.23.56.46;	author patil;	state Exp;branches;next	1.2;1.2date	2004.12.28.22.05.42;	author patil;	state Exp;branches;next	1.1;1.1date	2004.12.28.00.04.32;	author patil;	state Exp;branches;next	;desc@Changes made.@1.9log@Changed switching to Kalman from Particle.@text@/** * file: MainMenu.java * * last edited: Ryan Irwin */// import necessary java libraries//import java.awt.*;import javax.swing.*;import java.awt.event.ActionListener;import java.awt.event.*;import java.util.*;import java.io.*;import java.net.*;import java.applet.*;/** * * implement the menu driven system that drives the applet * * hierarchy: JPanel->SubPanel->MainMenu * */public class MainMenu extends SubPanel implements ActionListener{    // *********************************************************************    //    // declare global variables and components    //    // *********************************************************************    // declare the menu font layout    //    Font currentFont = getFont();    Font newFont = new Font(currentFont.getName(), currentFont.getStyle(), 12);    // declare the menu layout    //    JMenuBar menuBar;    JMenu menu;    JMenuItem menuItem;    JMenuItem prevMenuItem;    JMenuItem nextMenuItem;    JCheckBoxMenuItem nearestMenuItem;    JCheckBoxMenuItem euclideanMenuItem;    JCheckBoxMenuItem pcaMenuItem;    JCheckBoxMenuItem pca1MenuItem;    JCheckBoxMenuItem ldaMenuItem;    JCheckBoxMenuItem lda1MenuItem;    JCheckBoxMenuItem ldapcaMenuItem;       //I add here for lpa->pca 1    JCheckBoxMenuItem ldapca1MenuItem;    JCheckBoxMenuItem icaMenuItem;    JCheckBoxMenuItem ica1MenuItem;    JCheckBoxMenuItem svmMenuItem;    JCheckBoxMenuItem svm1MenuItem;    JCheckBoxMenuItem lpMenuItem;       //I add here for lp and particle    JCheckBoxMenuItem pfMenuItem;    JCheckBoxMenuItem kfMenuItem;    JRadioButtonMenuItem rbMenuItem;    // declare components for the help box    //    JFrame frame;    JTextArea textArea;    JScrollPane scrollPane;    JButton dismiss;    // declare components for the scales frame    //    JFrame scale;    JButton change;    // declare components for the gaussian frame    //    JFrame setgausdlg;    JButton applyb;    JButton cancel;    // declare components for the color selection frame    //    JFrame setccolorsdlg;    JLabel colorselection;    JLabel dset1color;    JLabel dset2color;    JLabel dset3color;    JLabel dset4color;    JButton setdset1;    JButton setdset2;    JButton setdset3;    JButton setdset4;    JButton setcolors;      JPanel paneldset1 = new JPanel();    JPanel paneldset2 = new JPanel();    JPanel paneldset3 = new JPanel();    JPanel paneldset4 = new JPanel();      // declare components for the k-mean algorithm    //    JFrame clusterpara;    JButton initcluster;    // declare components for the LBG algorithm    //    JFrame iterpara;    JButton inititer;    // declare components for the LP algorithm    //    JFrame lpsetorderpara;    JButton initlporder;    // declare components for the PF algorithm    //    JFrame pfsetorderpara;    JButton initpforder;    // declare components for the KF algorithm    //    JFrame kfsetorderpara;    JButton initkforder;        // declare components for the Kalman algorithm    //    JFrame set_meas_gain_frame;    JButton init_meas_gain;        // declare components for the Kalman algorithm    //    JFrame set_state_gain_frame;    JButton init_state_gain;        // declare components for the Kalman algorithm    //    JFrame set_var_meas_noise_frame;    JButton init_var_meas_noise;        // declare components for the Kalman algorithm    //    JFrame set_var_state_noise_frame;    JButton init_var_state_noise;        // declare componets for setting interpolation order in the LP algorithm     //    JFrame ipsetorderpara;    JButton initiporder;    // global variables for the k-means algorithm    //    int guesses = 4;    int iterations = 4;    // global variables for the LBG algorithm    //    int clusters = 10;    // global variables for setting linear and polation order in     // the LP  algorithm and particle filtering algorithm    //    int lporder = 8;    int iporder = 10;    int pforder = 8;    int kforder = 8;    // Kalman Filter    //    double meas_gain  = 1.0;    double state_gain = 1.0;    double var_meas_noise  = 10;    double var_state_noise = 10;    // flags    //    boolean drwptsf = true;    boolean drwgaussf = false;    boolean zoomi = false;    boolean zoomo = false;      // global variable for the gaussian distribution    //    int points = 25;    double meanx = 0.0;    double meany = 0.0;    double cov11 = 0.05;    double cov12 = 0.0;    double cov21 = 0.0;    double cov22 = 0.05;    // declare varaibles to read the help file    //    URL url;    Vector urlvec;    String document;    BufferedReader buff;    AppletContext context;    // declare components for the time scales    //    JLabel xMinLabel; // x-axis minimum label    JLabel xMaxLabel; // x-axis maximum label    JLabel yMinLabel; // y-axis minimum label    JLabel yMaxLabel; // y-axis maximum label    JTextField xMinField; // x-axis minimum text field    JTextField xMaxField; // x-axis maximum text field    JTextField yMinField; // y-axis minimum text field    JTextField yMaxField; // y-axis maximum text field    // declare components for the gaussian distribution    //    JLabel pointsLabel; // max points in distribution label    JLabel meanxLabel; // mean of distribution (x) label    JLabel meanyLabel; // mean of distribution (y) label    JLabel setgausLabel; //Gaussian Settings Label      JLabel covLabel;  //Covariance Lable    JLabel cov11Label; // covariance c11 of distribution label    JLabel cov12Label; // covariance c12 of distribution label    JLabel cov21Label; // covariance c21 of distribution label    JLabel cov22Label; // covariance c22 of distribution label    JTextField pointsField; // max points in distribution text field    JTextField meanxField; // mean of distribution (x) text field    JTextField meanyField; // mean of distribution (y) text field    JTextField cov11Field; // covariance c11 text field    JTextField cov12Field; // covariance c12 text field    JTextField cov21Field; // covariance c21 text field    JTextField cov22Field; // covariance c22 text field    // declare components for the k-means algorithm    //    JLabel guessesLabel; // number of initial guesses label    JLabel iterationsLabel; // max number of iterations label       JLabel clusterLabel; // max number of clusters    JTextField guessesField; // number of initial guesses field    JTextField iterationsField; // max number of iterations field      JTextField clusterField; // max number of clusters      // declare components for lp order in the LP algorithm    //    JLabel lporderLabel; // LP order label    JTextField lporderField; // LP order text field      // declare components for pf order in the PF algorithm    //    JLabel pforderLabel; // PF order label    JTextField pforderField; // PF order text field      // declare components for kf order in the KF algorithm    //    JLabel kforderLabel; // KF order label    JTextField kforderField; // KF order text field      // declare components for meas_gain in the Kalman algorithm    //    JLabel meas_gain_label;     JTextField meas_gain_field;    // declare components for state_gain in the Kalman algorithm    //    JLabel state_gain_label;    JTextField state_gain_field;       // declare components for var_meas_gain order in the Kalman algorithm    //    JLabel var_meas_noise_label;    JTextField var_meas_noise_field;    // declare components for var_state_gain in the Kalman algorithm    //    JLabel var_state_noise_label;     JTextField var_state_noise_field;    // declare components for interpolation in the LP and PF algorithm    //    JLabel iporderLabel; // interpolation order label    JTextField iporderField; // interpolation order text field     //  // declare a checkbox item listener    //  //    //  CheckBoxListener myListener = new CheckBoxListener();    // declare strings for the Help menu    //    String helpOption = new String("Help");    String tutorial = new String("Applet Tutorial");    String overview = new String("Applet Overview");    String release = new String("Release Notes");    String info = new String("Information and Support");    String plugins = new String("About Plug-ins");    String done = new String("Done");    String refresh = new String("Update");    String apply = new String("OK");    String destroy = new String("Cancel");    String setpara = new String("Set K-Means");    String newline = new String("\n");      // declare strings for the color changer dialog    //    String changeset = new String("Change");    String changeset1 = new String("Change1");      String changeset2 = new String("Change2");      String changeset3 = new String("Change3");      String changeset4 = new String("Change4");      // declare menu title strings    //    String drwpts = new String("Draw Points");    String drwgauss = new String("Draw Gaussian");    String pearEllipse = new String("Pear And Ellipse");    String twoEllipse = new String("Two Ellipse");    String twoGaussian = new String("Two Gaussian");    String fourGaussian = new String("Four Gaussian");    String overGaussian = new String("Overlapping Gaussian");    String twoEllipses = new String("Two Ellipses");    String fourEllipses = new String("Four Ellipses");    String rotatedEllipses = new String("Rotated Ellipses");    String toroidal = new String("Toroidal");    String yinYang = new String("Yin and Yang");    String class1 = new String("Input Class 0");    String class2 = new String("Input Class 1");    String class3 = new String("Input Class 2");    String class4 = new String("Input Class 3");    String euclidean = new String("Euclidean Distance");    String nearest = new String("Nearest Neighbor");    String kmeans = new String("Clustering: K-Means");    String binary = new String("Clustering: LBG");    String LDA1 = new String("LDA: Class-Independent");    String LDA2 = new String("LDA: Class-Dependent");    String PCA1 = new String("PCA: Class-Independent");    String PCA2 = new String("PCA: Class-Dependent");    String LDAPCA1 = new String("LDA->PCA: Class-Independent");    String LDAPCA2 = new String("LDA->PCA: Class-Dependent");    String ICA1 = new String("ICA: Class-Independent");    String ICA2 = new String("ICA: Class-Dependent");    String SVM1 = new String("SVM: Class-Independent");    String SVM2 = new String("RVM: Relevance Vector Machine");    String LP = new String("LP: Linear Prediction");    String PF = new String("PF: Particle Filtering");    String KF = new String("KF: Kalman Filtering");    String previous = new String("Previous");    String setgaus = new String ("Set Gaussian");    String setccolors = new String ("Set Class Colors");    String setiterations = new String ("Set Iterations");    String setclusters = new String ("Set Clusters");    String setlporders = new String ("Set LP Order");    String setpforders = new String ("Set PF Order");    String setkforders = new String ("Set KF Order");    String setiporders = new String ("Set Interpolation");    String set_meas_gain = new String ("Set Measurement Gain");    String set_state_gain = new String ("Set State Gain");    String set_var_meas_noise = new String("Set Variance of Measurement Noise");    String set_var_state_noise = new String ("Set Variance of State Noise");    String saveiporders = new String ("Save Interpolation Order");    String saveiterations = ("Save Iterations");    String saveclusters = ("Save Clusters");    String savelporders = ("Save LP Order");    String savepforders = ("Save PF Order");    String savekforders = ("Save KF Order");    String save_meas_gain = new String ("Save Measurement Gain");    String save_state_gain = new String ("Save State Gain");    String save_var_meas_noise = new String("Save Variance of Measurement Noise");    String save_var_state_noise = new String ("Save Variance of State Noise");    String clearAll = new String("Clear All");    String clearPlots = new String("Clear Display");    String clearInput = new String("Clear Input");    String clearOutput = new String("Clear Output");    String clearTxt = new String("Clear Description");    String erase = new String("Erase");    String zoomin = new String("Zoom In");      String zoomout = new String("Zoom Out");      String limit = new String("Set Ranges");    String next = new String("Next");    String load = new String("Load");    String save = new String("Save");    String initialize = new String("Initialize");    String viewEuclidean = new String("View Euclidean");    String viewNearest = new String("View Nearest Neighbor");    String viewPCA1 = new String("PCA: Class Independent PCA");    String viewPCA2 = new String("PCA: Class Dependent PCA");    String viewLDA1 = new String("LDA: Class Independent LDA");    String viewLDA2 = new String("LDA: Class Dependent LDA");    String viewLDAPCA1 = new String("LDA->PCA: Class Independent LDA->PCA");    String viewLDAPCA2 = new String("LDA->PCA: Class Dependent LDA->PCA");    String viewICA1 = new String("ICA: Class Independent PCA");    String viewICA2 = new String("ICA: Class Dependent LDA");    String viewSVM1 = new String("SVM: Class Independent PCA");    //String viewSVM2 = new String("SVM: Class Dependent LDA");    String viewSVM2 = new String("SVM: Relevance Vector Machine");    String viewLP = new String("LP: Linear Prediction");    String viewPF = new String("PF: Particle Filtering");    String viewKF = new String("KF: Kalman Filtering");    String viewKMeans = new String("Clustering : K-Means");    String viewLBG = new String("Clustering : LBG");

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