Develop Reference

How do you properly use PDPageContentStream::setTextRise?

Using PDFBox, given data notated like this: [G]Glory be to [D]God [Em]the [C]Father,\n[G]And to [A]Christ the [D]Son,, I am creating a guitar chord sheet like this:
My approach was to iterate through each character in the song and check the current index against the map.. whenever the map has an entry to that character index, we "jump" to the line above, write the chord, then jump back down.
The method setTextRise looked promising, but still processes the horizontal spacing incorrectly:
Here's an SSCCE (needs PDFBox libraries) that produces the PDF above:
public static void main(String[] args) {
try {
String extracted_text = "Capo 1\n\n1\n[G]Glory be to [D]God [Em]the [C]Father,\n[G]And to [A]Christ the [D]Son,\n[B7]Glory to the [Em]Holy [C]Spirit—\n[D-D7]Ever [ G]One.\n\n2\nAs we view the vast creation,\nPlanned with wondrous skill,\nSo our hearts would move to worship,\nAnd be still.\n\n3\nBut, our God, how great Thy yearning\nTo have sons who love\nIn the Son e’en now to praise Thee,\nLove to prove!\n\n4\n’Twas Thy thought in revelation,\nTo present to men\nSecrets of Thine own affections,\nTheirs to win.\n\n5\nSo in Christ, through His redemption\n(Vanquished evil powers!)\nThou hast brought, in new creation,\nWorshippers!\n\n6\nGlory be to God the Father,\nAnd to Christ the Son,\nGlory to the Holy Spirit—\nEver One.\n".replaceAll("\n", "\r");
String[] lines = extracted_text.split("\\r");
ArrayList<SongLine> songlines = new ArrayList<>();
for(String s : lines) {
LinkedHashMap<Integer, String> chords = new LinkedHashMap();
StringBuilder line = new StringBuilder();
StringBuilder currentchord = null;
int index = 0;
for(char c : s.toCharArray()) {
if(currentchord != null) {
if(c == ']') {
chords.put(index, currentchord.toString());
currentchord = null;
} else {
currentchord.append(c);
}
} else {
if(c == '[') {
currentchord = new StringBuilder();
} else {
line.append(c);
index++;
}
}
}
SongLine sl = new SongLine();
if(chords.size() > 0)
sl.char_index_to_chords = chords;
sl.line = line.toString();
songlines.add(sl);
}
try (PDDocument doc = new PDDocument()) {
PDPage page = new PDPage();
PDPageContentStream pcs = new PDPageContentStream(doc, page);
int firstLineX = 25;
int firstLineY = 700;
boolean first = true;
float leading = 14.5f;
pcs.beginText();
pcs.newLineAtOffset(firstLineX, firstLineY);
pcs.setFont(PDType1Font.TIMES_ROMAN, 12);
pcs.setLeading(leading);
for(SongLine line : songlines) {
if(line.char_index_to_chords != null)
System.out.println(line.char_index_to_chords.toString());
System.out.println(line.line);
if(!first) {
pcs.newLine();
}
first = false;
if(line.char_index_to_chords != null) {
pcs.newLine();
}
for(int i = 0; i < line.line.length(); i++) {
pcs.showText(String.valueOf(line.line.charAt(i)));
if(line.char_index_to_chords != null && line.char_index_to_chords.containsKey(i)) {
pcs.setTextRise(12);
pcs.showText(line.char_index_to_chords.get(i));
pcs.setTextRise(0);
}
}
}
pcs.endText();
pcs.close();
doc.addPage(page);
String path = "0001.pdf";
doc.save(path);
Desktop.getDesktop().open(new File(path));
}
} catch (Exception e) {
e.printStackTrace();
}
}
static class SongLine {
Map<Integer, String> char_index_to_chords;
String line;
}
What would you do in PDFBox to create the text aligned with chords (like in the first image)?

I got it. The answer was not setTextRise, rather newLineAtOffset while using getStringWidth to calculate font size:
for(SongLine line : songlines) {
if(!first) {
pcs.newLine();
}
first = false;
if(line.char_index_to_chords != null) {
float offset = 0;
for(Entry<Integer, String> entry : line.char_index_to_chords.entrySet()) {
float offsetX = font.getStringWidth(line.char_index_to_leading_lyrics.get(entry.getKey())) / (float)1000 * fontSize;
pcs.newLineAtOffset(offsetX, 0);
offset += offsetX;
pcs.showText(entry.getValue());
}
pcs.newLineAtOffset(-offset, -leading);
}
pcs.showText(line.line);
}

SVM Predict reading datatest

I have such a big problem with implementation the svm_predict function. I have trained svm, and prepare datatest. Both files are in .txt. file.Datatest are from LBP( Local Binary patterns) and it looks like:
-0.6448744548418511
-0.7862774302452588
1.7746263060948377
I'm loading it to the svm_predict function and at my console after compiling my program there is:
Accuracy = 0.0% (0/800) (classification)
So it's look like it can't read datatest?
import libsvm.*;
import java.io.*;
import java.util.*;
class svm_predict {
private static double atof(String s)
{
return Double.valueOf(s).doubleValue();
}
private static int atoi(String s)
{
return Integer.parseInt(s);
}
private static void predict(BufferedReader input, DataOutputStream output, svm_model model, int predict_probability) throws IOException
{
int correct = 0;
int total = 0;
double error = 0;
double sumv = 0, sumy = 0, sumvv = 0, sumyy = 0, sumvy = 0;
int svm_type=svm.svm_get_svm_type(model);
int nr_class=svm.svm_get_nr_class(model);
double[] prob_estimates=null;
if(predict_probability == 1)
{
if(svm_type == svm_parameter.EPSILON_SVR ||
svm_type == svm_parameter.NU_SVR)
{
System.out.print("Prob. model for test data: target value = predicted value + z,\nz: Laplace distribution e^(-|z|/sigma)/(2sigma),sigma="+svm.svm_get_svr_probability(model)+"\n");
}
else
{
int[] labels=new int[nr_class];
svm.svm_get_labels(model,labels);
prob_estimates = new double[nr_class];
output.writeBytes("labels");
for(int j=0;j<nr_class;j++)
output.writeBytes(" "+labels[j]);
output.writeBytes("\n");
}
}
while(true)
{
String line = input.readLine();
if(line == null) break;
StringTokenizer st = new StringTokenizer(line," \t\n\r\f:");
double target = atof(st.nextToken());
int m = st.countTokens()/2;
svm_node[] x = new svm_node[m];
for(int j=0;j<m;j++)
{
x[j] = new svm_node();
x[j].index = atoi(st.nextToken());
x[j].value = atof(st.nextToken());
}
double v;
if (predict_probability==1 && (svm_type==svm_parameter.C_SVC || svm_type==svm_parameter.NU_SVC))
{
v = svm.svm_predict_probability(model,x,prob_estimates);
output.writeBytes(v+" ");
for(int j=0;j<nr_class;j++)
output.writeBytes(prob_estimates[j]+" ");
output.writeBytes("\n");
}
else
{
v = svm.svm_predict(model,x);
output.writeBytes(v+"\n");
}
if(v == target)
++correct;
error += (v-target)*(v-target);
sumv += v;
sumy += target;
sumvv += v*v;
sumyy += target*target;
sumvy += v*target;
++total;
}
if(svm_type == svm_parameter.EPSILON_SVR ||
svm_type == svm_parameter.NU_SVR)
{
System.out.print("Mean squared error = "+error/total+" (regression)\n");
System.out.print("Squared correlation coefficient = "+
((total*sumvy-sumv*sumy)*(total*sumvy-sumv*sumy))/
((total*sumvv-sumv*sumv)*(total*sumyy-sumy*sumy))+
" (regression)\n");
}
else
System.out.print("Accuracy = "+(double)correct/total*100+
"% ("+correct+"/"+total+") (classification)\n");
}
private static void exit_with_help()
{
System.err.print("usage: svm_predict [options] test_file model_file output_file\n"
+"options:\n"
+"-b probability_estimates: whether to predict probability estimates, 0 or 1 (default 0); one-class SVM not supported yet\n");
System.exit(1);
}
public static void main(String argv[]) throws IOException
{
int i, predict_probability=0;
// parse options
for(i=0;i<argv.length;i++)
{
if(argv[i].charAt(0) != '-') break;
++i;
switch(argv[i-1].charAt(1))
{
case 'b':
predict_probability = atoi(argv[i]);
break;
default:
System.err.print("Unknown option: " + argv[i-1] + "\n");
exit_with_help();
}
}
if(i>=argv.length-2)
exit_with_help();
try
{
BufferedReader input = new BufferedReader(new FileReader(argv[i]));
DataOutputStream output = new DataOutputStream(new BufferedOutputStream(new FileOutputStream(argv[i+2])));
svm_model model = svm.svm_load_model(argv[i+1]);
if(predict_probability == 1)
{
if(svm.svm_check_probability_model(model)==0)
{
System.err.print("Model does not support probabiliy estimates\n");
System.exit(1);
}
}
else
{
if(svm.svm_check_probability_model(model)!=0)
{
System.out.print("Model supports probability estimates, but disabled in prediction.\n");
}
}
predict(input,output,model,predict_probability);
input.close();
output.close();
}
catch(FileNotFoundException e)
{
exit_with_help();
}
catch(ArrayIndexOutOfBoundsException e)
{
exit_with_help();
}
}
}

It's difficult to know becasue its a big process
make sure you follow their classification guide
the data should be scaled it seems it goes above 1 right now

How to use the 'svm_toy' Applet example in LibSVM?

I'm using LIBSVM. In the download package is a svm_toy.java file. I could not find out how it works. Here is the source code:
import libsvm.*;
import java.applet.*;
import java.awt.*;
import java.util.*;
import java.awt.event.*;
import java.io.*;
/**
* SVM package
* #author unknown
*
*/
public class svm_toy extends Applet {
static final String DEFAULT_PARAM="-t 2 -c 100";
int XLEN;
int YLEN;
// off-screen buffer
Image buffer;
Graphics buffer_gc;
// pre-allocated colors
final static Color colors[] =
{
new Color(0,0,0),
new Color(0,120,120),
new Color(120,120,0),
new Color(120,0,120),
new Color(0,200,200),
new Color(200,200,0),
new Color(200,0,200)
};
class point {
point(double x, double y, byte value)
{
this.x = x;
this.y = y;
this.value = value;
}
double x, y;
byte value;
}
Vector<point> point_list = new Vector<point>();
byte current_value = 1;
public void init()
{
setSize(getSize());
final Button button_change = new Button("Change");
Button button_run = new Button("Run");
Button button_clear = new Button("Clear");
Button button_save = new Button("Save");
Button button_load = new Button("Load");
final TextField input_line = new TextField(DEFAULT_PARAM);
BorderLayout layout = new BorderLayout();
this.setLayout(layout);
Panel p = new Panel();
GridBagLayout gridbag = new GridBagLayout();
p.setLayout(gridbag);
GridBagConstraints c = new GridBagConstraints();
c.fill = GridBagConstraints.HORIZONTAL;
c.weightx = 1;
c.gridwidth = 1;
gridbag.setConstraints(button_change,c);
gridbag.setConstraints(button_run,c);
gridbag.setConstraints(button_clear,c);
gridbag.setConstraints(button_save,c);
gridbag.setConstraints(button_load,c);
c.weightx = 5;
c.gridwidth = 5;
gridbag.setConstraints(input_line,c);
button_change.setBackground(colors[current_value]);
p.add(button_change);
p.add(button_run);
p.add(button_clear);
p.add(button_save);
p.add(button_load);
p.add(input_line);
this.add(p,BorderLayout.SOUTH);
button_change.addActionListener(new ActionListener()
{ public void actionPerformed (ActionEvent e)
{ button_change_clicked(); button_change.setBackground(colors[current_value]); }});
button_run.addActionListener(new ActionListener()
{ public void actionPerformed (ActionEvent e)
{ button_run_clicked(input_line.getText()); }});
button_clear.addActionListener(new ActionListener()
{ public void actionPerformed (ActionEvent e)
{ button_clear_clicked(); }});
button_save.addActionListener(new ActionListener()
{ public void actionPerformed (ActionEvent e)
{ button_save_clicked(input_line.getText()); }});
button_load.addActionListener(new ActionListener()
{ public void actionPerformed (ActionEvent e)
{ button_load_clicked(); }});
input_line.addActionListener(new ActionListener()
{ public void actionPerformed (ActionEvent e)
{ button_run_clicked(input_line.getText()); }});
this.enableEvents(AWTEvent.MOUSE_EVENT_MASK);
}
void draw_point(point p)
{
Color c = colors[p.value+3];
Graphics window_gc = getGraphics();
buffer_gc.setColor(c);
buffer_gc.fillRect((int)(p.x*XLEN),(int)(p.y*YLEN),4,4);
window_gc.setColor(c);
window_gc.fillRect((int)(p.x*XLEN),(int)(p.y*YLEN),4,4);
}
void clear_all()
{
point_list.removeAllElements();
if(buffer != null)
{
buffer_gc.setColor(colors[0]);
buffer_gc.fillRect(0,0,XLEN,YLEN);
}
repaint();
}
void draw_all_points()
{
int n = point_list.size();
for(int i=0;i<n;i++)
draw_point(point_list.elementAt(i));
}
void button_change_clicked()
{
++current_value;
if(current_value > 3) current_value = 1;
}
private static double atof(String s)
{
return Double.valueOf(s).doubleValue();
}
private static int atoi(String s)
{
return Integer.parseInt(s);
}
void button_run_clicked(String args)
{
// guard
if(point_list.isEmpty()) return;
svm_parameter param = new svm_parameter();
// default values
param.svm_type = svm_parameter.C_SVC;
param.kernel_type = svm_parameter.RBF;
param.degree = 3;
param.gamma = 0;
param.coef0 = 0;
param.nu = 0.5;
param.cache_size = 40;
param.C = 1;
param.eps = 1e-3;
param.p = 0.1;
param.shrinking = 1;
param.probability = 0;
param.nr_weight = 0;
param.weight_label = new int[0];
param.weight = new double[0];
// parse options
StringTokenizer st = new StringTokenizer(args);
String[] argv = new String[st.countTokens()];
for(int i=0;i<argv.length;i++)
argv[i] = st.nextToken();
for(int i=0;i<argv.length;i++)
{
if(argv[i].charAt(0) != '-') break;
if(++i>=argv.length)
{
System.err.print("unknown option\n");
break;
}
switch(argv[i-1].charAt(1))
{
case 's':
param.svm_type = atoi(argv[i]);
break;
case 't':
param.kernel_type = atoi(argv[i]);
break;
case 'd':
param.degree = atoi(argv[i]);
break;
case 'g':
param.gamma = atof(argv[i]);
break;
case 'r':
param.coef0 = atof(argv[i]);
break;
case 'n':
param.nu = atof(argv[i]);
break;
case 'm':
param.cache_size = atof(argv[i]);
break;
case 'c':
param.C = atof(argv[i]);
break;
case 'e':
param.eps = atof(argv[i]);
break;
case 'p':
param.p = atof(argv[i]);
break;
case 'h':
param.shrinking = atoi(argv[i]);
break;
case 'b':
param.probability = atoi(argv[i]);
break;
case 'w':
++param.nr_weight;
{
int[] old = param.weight_label;
param.weight_label = new int[param.nr_weight];
System.arraycopy(old,0,param.weight_label,0,param.nr_weight-1);
}
{
double[] old = param.weight;
param.weight = new double[param.nr_weight];
System.arraycopy(old,0,param.weight,0,param.nr_weight-1);
}
param.weight_label[param.nr_weight-1] = atoi(argv[i-1].substring(2));
param.weight[param.nr_weight-1] = atof(argv[i]);
break;
default:
System.err.print("unknown option\n");
}
}
// build problem
svm_problem prob = new svm_problem();
prob.l = point_list.size();
prob.y = new double[prob.l];
if(param.kernel_type == svm_parameter.PRECOMPUTED)
{
}
else if(param.svm_type == svm_parameter.EPSILON_SVR ||
param.svm_type == svm_parameter.NU_SVR)
{
if(param.gamma == 0) param.gamma = 1;
prob.x = new svm_node[prob.l][1];
for(int i=0;i<prob.l;i++)
{
point p = point_list.elementAt(i);
prob.x[i][0] = new svm_node();
prob.x[i][0].index = 1;
prob.x[i][0].value = p.x;
prob.y[i] = p.y;
}
// build model & classify
svm_model model = svm.svm_train(prob, param);
svm_node[] x = new svm_node[1];
x[0] = new svm_node();
x[0].index = 1;
int[] j = new int[XLEN];
Graphics window_gc = getGraphics();
for (int i = 0; i < XLEN; i++)
{
x[0].value = (double) i / XLEN;
j[i] = (int)(YLEN*svm.svm_predict(model, x));
}
buffer_gc.setColor(colors[0]);
buffer_gc.drawLine(0,0,0,YLEN-1);
window_gc.setColor(colors[0]);
window_gc.drawLine(0,0,0,YLEN-1);
int p = (int)(param.p * YLEN);
for(int i=1;i<XLEN;i++)
{
buffer_gc.setColor(colors[0]);
buffer_gc.drawLine(i,0,i,YLEN-1);
window_gc.setColor(colors[0]);
window_gc.drawLine(i,0,i,YLEN-1);
buffer_gc.setColor(colors[5]);
window_gc.setColor(colors[5]);
buffer_gc.drawLine(i-1,j[i-1],i,j[i]);
window_gc.drawLine(i-1,j[i-1],i,j[i]);
if(param.svm_type == svm_parameter.EPSILON_SVR)
{
buffer_gc.setColor(colors[2]);
window_gc.setColor(colors[2]);
buffer_gc.drawLine(i-1,j[i-1]+p,i,j[i]+p);
window_gc.drawLine(i-1,j[i-1]+p,i,j[i]+p);
buffer_gc.setColor(colors[2]);
window_gc.setColor(colors[2]);
buffer_gc.drawLine(i-1,j[i-1]-p,i,j[i]-p);
window_gc.drawLine(i-1,j[i-1]-p,i,j[i]-p);
}
}
}
else
{
if(param.gamma == 0) param.gamma = 0.5;
prob.x = new svm_node [prob.l][2];
for(int i=0;i<prob.l;i++)
{
point p = point_list.elementAt(i);
prob.x[i][0] = new svm_node();
prob.x[i][0].index = 1;
prob.x[i][0].value = p.x;
prob.x[i][1] = new svm_node();
prob.x[i][1].index = 2;
prob.x[i][1].value = p.y;
prob.y[i] = p.value;
}
// build model & classify
svm_model model = svm.svm_train(prob, param);
svm_node[] x = new svm_node[2];
x[0] = new svm_node();
x[1] = new svm_node();
x[0].index = 1;
x[1].index = 2;
Graphics window_gc = getGraphics();
for (int i = 0; i < XLEN; i++)
for (int j = 0; j < YLEN ; j++) {
x[0].value = (double) i / XLEN;
x[1].value = (double) j / YLEN;
double d = svm.svm_predict(model, x);
if (param.svm_type == svm_parameter.ONE_CLASS && d<0) d=2;
buffer_gc.setColor(colors[(int)d]);
window_gc.setColor(colors[(int)d]);
buffer_gc.drawLine(i,j,i,j);
window_gc.drawLine(i,j,i,j);
}
}
draw_all_points();
}
void button_clear_clicked()
{
clear_all();
}
void button_save_clicked(String args)
{
FileDialog dialog = new FileDialog(new Frame(),"Save",FileDialog.SAVE);
dialog.setVisible(true);
String filename = dialog.getDirectory() + dialog.getFile();
if (filename == null) return;
try {
DataOutputStream fp = new DataOutputStream(new BufferedOutputStream(new FileOutputStream(filename)));
int svm_type = svm_parameter.C_SVC;
int svm_type_idx = args.indexOf("-s ");
if(svm_type_idx != -1)
{
StringTokenizer svm_str_st = new StringTokenizer(args.substring(svm_type_idx+2).trim());
svm_type = atoi(svm_str_st.nextToken());
}
int n = point_list.size();
if(svm_type == svm_parameter.EPSILON_SVR || svm_type == svm_parameter.NU_SVR)
{
for(int i=0;i<n;i++)
{
point p = point_list.elementAt(i);
fp.writeBytes(p.y+" 1:"+p.x+"\n");
}
}
else
{
for(int i=0;i<n;i++)
{
point p = point_list.elementAt(i);
fp.writeBytes(p.value+" 1:"+p.x+" 2:"+p.y+"\n");
}
}
fp.close();
} catch (IOException e) { System.err.print(e); }
}
void button_load_clicked()
{
FileDialog dialog = new FileDialog(new Frame(),"Load",FileDialog.LOAD);
dialog.setVisible(true);
String filename = dialog.getDirectory() + dialog.getFile();
if (filename == null) return;
clear_all();
try {
BufferedReader fp = new BufferedReader(new FileReader(filename));
String line;
while((line = fp.readLine()) != null)
{
StringTokenizer st = new StringTokenizer(line," \t\n\r\f:");
if(st.countTokens() == 5)
{
byte value = (byte)atoi(st.nextToken());
st.nextToken();
double x = atof(st.nextToken());
st.nextToken();
double y = atof(st.nextToken());
point_list.addElement(new point(x,y,value));
}
else if(st.countTokens() == 3)
{
double y = atof(st.nextToken());
st.nextToken();
double x = atof(st.nextToken());
point_list.addElement(new point(x,y,current_value));
}else
break;
}
fp.close();
} catch (IOException e) { System.err.print(e); }
draw_all_points();
}
protected void processMouseEvent(MouseEvent e)
{
if(e.getID() == MouseEvent.MOUSE_PRESSED)
{
if(e.getX() >= XLEN || e.getY() >= YLEN) return;
point p = new point((double)e.getX()/XLEN,
(double)e.getY()/YLEN,
current_value);
point_list.addElement(p);
draw_point(p);
}
}
public void paint(Graphics g)
{
// create buffer first time
if(buffer == null) {
buffer = this.createImage(XLEN,YLEN);
buffer_gc = buffer.getGraphics();
buffer_gc.setColor(colors[0]);
buffer_gc.fillRect(0,0,XLEN,YLEN);
}
g.drawImage(buffer,0,0,this);
}
public Dimension getPreferredSize() { return new Dimension(XLEN,YLEN+50); }
public void setSize(Dimension d) { setSize(d.width,d.height); }
public void setSize(int w,int h) {
super.setSize(w,h);
XLEN = w;
YLEN = h-50;
clear_all();
}
public static void main(String[] argv)
{
new AppletFrame("svm_toy",new svm_toy(),500,500+50);
}
}
class AppletFrame extends Frame {
AppletFrame(String title, Applet applet, int width, int height)
{
super(title);
this.addWindowListener(new WindowAdapter() {
public void windowClosing(WindowEvent e) {
System.exit(0);
}
});
applet.init();
applet.setSize(width,height);
applet.start();
this.add(applet);
this.pack();
this.setVisible(true);
}
}
Could someone give me an example or explanation? I also would like to scale my training data. Where is the right place to scale?
Thanks

SVM-Toy
SVM Toy is - as the name suggests - a simple toy build by the LIBSVM dev team and is not recommended for "productive" visualization of the SVM's decision boundary.
Moreover looking into the source-code of svm_toy it becomes clear, that this tool only supports 2D vectors.
Relevant code fragment is taken from the button_load_clicked() Method:
while ((line = fp.readLine()) != null) {
StringTokenizer st = new StringTokenizer(line, " \t\n\r\f:");
if (st.countTokens() == 5) {
byte value = (byte) atoi(st.nextToken());
st.nextToken();
double x = atof(st.nextToken());
st.nextToken();
double y = atof(st.nextToken());
point_list.addElement(new point(x, y, value));
} else if (st.countTokens() == 3) {
double y = atof(st.nextToken());
st.nextToken();
double x = atof(st.nextToken());
point_list.addElement(new point(x, y, current_value));
} else {
break;
}
}
As you can see, the svm_toy implementation can only handle 2D vectors, which means it only supports vectors, which were constructed out of two features.
That means, you can only read and display files which are build from only two features like for example the fourclass dataset provided by the LIBSVM authors. However it seems, that this feature is not supported within this implementation.
I think, that the tool is designed for interactive visualization. You are able to change the color and click on the black application screen. After you set some points (each color representing an own class), you can click "run" and the decision boundary is displayed.
Displaying the desicion boundary in an high dimensional vector space is even nearly impossible. I would recommend to not use this tool implementation for any productive / scientific purpose.
Scaling
Scaling of your training data should be done after you transformed it into it's numeric representation and before you are going forward to train your SVM with this data.
In short that means, you have to do the following steps before using svm_train
Construct the numeric representation for each data point (with the help of feature selection, ...)
Analyse the resulting numeric representation for each data point
Scale your data for example to [-1,1]
Go ahead and train your SVM model. Note well, that you have to repeat 1-3 for predicting unknown data points. The only difference is, that you already know the necessary features, so there is no need for feature selection.

Use custom class in HashMap in android

EDIT: I have posted it earlier for java. But it working in Java but not in android. So I am posting the android code now.
I am trying to use a custom class into a HashMap in my android application. But it is not giving my desired output. Please help.
I want to do something like this...
//Code for android application:
//Point class
class Point{
private int x;
private int y;
public Point(){
}
public Point(int _x, int _y){
this.x = _x;
this.y = _y;
}
}
DataManager.java
public class DataManager {
private Vector<Integer> RSSI = null;
private int numOfRSSI;
private Map<Vector<Integer>, Point> SingleData = null;
private Vector<Map<Vector<Integer>, Point>> Data = null;
private Context context;
public DataManager(Context _context) {
this.context = _context;
Data = new Vector<Map<Vector<Integer>, Point>>();
}
public void loadData(String filename) {
if (Data == null) {
System.out.println("***ERROR: DataSet not initalized!!!\n");
}
readFile(filename);
}
public void printData(){
Vector<Integer> rssi = null;
Map<Vector<Integer>, Point> single = null;
Point point = null;
for(int i=0;i<Data.size();i++){
single = new HashMap<Vector<Integer>, Point>() ;
single = Data.get(0);
for (Map.Entry<Vector<Integer>, Point> entry :single.entrySet()) {
rssi = new Vector<Integer>();
point = new Point();
rssi = entry.getKey();
point = entry.getValue();
System.out.print("("+point.x+" "+point.y+") ");
for(int j = 0;j<rssi.size(); j++){
System.out.print(rssi.get(j)+" ");
}
System.out.println("");
}
}
}
private void readFile(String filename) {
InputStream is = null;
try {
is = context.getResources().getAssets().open("datasets.txt");
} catch (IOException e) {
e.printStackTrace();
System.out.println("error file reading");
}
if (is != null) {
StringBuilder text = new StringBuilder();
int flag = 0;
try {
BufferedReader br = new BufferedReader(
new InputStreamReader(is));
String line;
while ((line = br.readLine()) != null) {
if(flag==0){
flag=1;
this.numOfRSSI = Integer.parseInt(line);
System.out.println("number of RSSI: "+numOfRSSI);
}
else if(flag==1){
parseLine(line);
}
}
} catch (IOException e) {
// Error reading file
}
finally {
// myHelper.print(text.toString());
}
}
}
private void parseLine(String line) {
RSSI = new Vector<Integer>();
SingleData = new HashMap<Vector<Integer>, Point>();
StringTokenizer st = new StringTokenizer(line, ",");
int co = 0;
int x=0,y=0;
while (st.hasMoreTokens()) {
if(co < this.numOfRSSI){
RSSI.add(Integer.parseInt(st.nextToken()));
co++;
}
else{
x = Integer.parseInt(st.nextToken());
y = Integer.parseInt(st.nextToken());
}
}
Point point = new Point(x,y);
SingleData.put(RSSI, point);
Data.add(SingleData);
}
}
MainActivity.java
public class MainActivity extends Activity {
#Override
protected void onCreate(Bundle savedInstanceState) {
// TODO Auto-generated method stub
super.onCreate(savedInstanceState);
DataManager dataManager = new DataManager(MainActivity.this);
dataManager.loadData("datasets.txt");
dataManager.printData();
}
}
datasets.txt
5
-61,-51,-46,-41,-28,1,0
-60,-50,-51,-47,-34,2,0
-72,-52,-53,-55,-37,3,0
-60,-44,-58,-53,-40,3,1
-68,-55,-46,-47,-45,2,1
-66,-60,-48,-43,-37,1,1
-62,-57,-49,-45,-34,0,2
Output is showing.....
1 0 -61 -51 -46 -41-28
1 0 -60 -50 -51 -47 -34
1 0 -72 -52 -53 -55 -37
etc.....
But it should be...
1 0 -61 -51 -46 -41-28
2 0 -60 -50 -51 -47 -34
etc...
So this is my problem.

Below is working fine on my machine :-
import java.util.Map;
import java.util.Vector;
public class Demo {
public static void main(String[] args) {
Map<Vector<Integer>, Point> vectorPointMap = new HashMap<Vector<Integer>, Point>();
Vector<Integer> vector1 = new Vector<Integer>();
vector1.add(1);
vector1.add(2);
vector1.add(3);
vectorPointMap.put(vector1, new Point(10, 10));
Vector<Integer> vector2 = new Vector<Integer>();
vector2.add(4);
vector2.add(5);
vector2.add(6);
vectorPointMap.put(vector2, new Point(20, 20));
// Print data
for (Map.Entry<Vector<Integer>, Point> entry : vectorPointMap.entrySet()) {
Vector<Integer> keyVector = entry.getKey();
Point valuePoint = entry.getValue();
System.out.print("(" + valuePoint.x + " " + valuePoint.y + ") ");
for (int j = 0; j < keyVector.size(); j++) {
System.out.print(keyVector.get(j) + " ");
}
System.out.println("");
}
}
}

You should change this from
for(int i=0;i<Data.size();i++){
single = new HashMap<Vector<Integer>, Point>() ;
single = Data.get(0);
}
to
for(int i=0;i<Data.size();i++){
single = new HashMap<Vector<Integer>, Point>() ;
single = Data.get(i);
}

try changing:
single = Data.get(0);
to
single = Data.get(i);

What does it mean, "it does not give right"?
You can put your own classes to Map, there is no problem. But remember, when you put items to HashMap in some order, there is no guarantee, it will come out in the same order. If you need to have same order on output, as on input, instead HashMap use LinkedHashMap. You can use it in the same way as HashMap, but it preserves order of inserted items.

Dijkstra and FileInput. Java

I have this Dijkstra algorithm java code below. I downloaded the code. I want to make changes to this program and store the data in file and read it in rather than put it in the source code. What would be the best ways to do this?
import java.util.PriorityQueue;
import java.util.List;
import java.util.ArrayList;
import java.util.Collections;
class Vertex implements Comparable<Vertex>
{
public final String name;
public Edge[] adjacencies;
public double minDistance = Double.POSITIVE_INFINITY;
public Vertex previous;
public Vertex(String argName) {
name = argName;
}
public String toString() {
return name;
}
public int compareTo(Vertex other)
{
return Double.compare(minDistance, other.minDistance);
}
}
class Edge
{
public final Vertex target;
public final double weight;
public Edge(Vertex argTarget, double argWeight) {
target = argTarget;
weight = argWeight;
}
}
public class Dijkstra
{
public static void computePaths(Vertex source)
{
source.minDistance = 0.;
PriorityQueue<Vertex> vertexQueue = new PriorityQueue<Vertex>();
vertexQueue.add(source);
while (!vertexQueue.isEmpty()) {
Vertex u = vertexQueue.poll();
// Visit each edge exiting u
for (Edge e : u.adjacencies)
{
Vertex v = e.target;
double weight = e.weight;
double distanceThroughU = u.minDistance + weight;
if (distanceThroughU < v.minDistance) {
vertexQueue.remove(v);
v.minDistance = distanceThroughU ;
v.previous = u;
vertexQueue.add(v);
}
}
}
}
public static List<Vertex> getShortestPathTo(Vertex target)
{
List<Vertex> path = new ArrayList<Vertex>();
for (Vertex vertex = target; vertex != null; vertex = vertex.previous)
path.add(vertex);
Collections.reverse(path);
return path;
}
public static void main(String[] args)
{
Vertex v0 = new Vertex("Nottinghill_Gate");
Vertex v1 = new Vertex("High_Street_kensignton");
Vertex v2 = new Vertex("Glouchester_Road");
Vertex v3 = new Vertex("South_Kensignton");
Vertex v4 = new Vertex("Sloane_Square");
Vertex v5 = new Vertex("Victoria");
Vertex v6 = new Vertex("Westminster");
v0.adjacencies = new Edge[]{new Edge(v1, 79.83), new Edge(v6, 97.24)};
v1.adjacencies = new Edge[]{new Edge(v2, 39.42), new Edge(v0, 79.83)};
v2.adjacencies = new Edge[]{new Edge(v3, 38.65), new Edge(v1, 39.42)};
v3.adjacencies = new Edge[]{new Edge(v4, 102.53), new Edge(v2, 38.65)};
v4.adjacencies = new Edge[]{new Edge(v5, 133.04), new Edge(v3, 102.53)};
v5.adjacencies = new Edge[]{new Edge(v6, 81.77), new Edge(v4, 133.04)};
v6.adjacencies = new Edge[]{new Edge(v0, 97.24), new Edge(v5, 81.77)};
Vertex[] vertices = { v0, v1, v2, v3, v4, v5, v6 };
computePaths(v0);
for (Vertex v : vertices)
{
System.out.println("Distance to " + v + ": " + v.minDistance);
List<Vertex> path = getShortestPathTo(v);
System.out.println("Path: " + path);
}
}
}
The code is based on http://en.literateprograms.org/Special:Downloadcode/Dijkstra%27s_algorithm_%28Java%29 [last accessed on 6th January 2011]

I'd recommend describing your graph in Trivial Graph Format.
This is what it will look like:
v0 Harrisburg
v1 Baltimore
v2 Washington
v3 Philadelphia
v4 Binghamton
v5 Allentown
v6 New York
#
v0 v1 79.83
v0 v5 81.15
v1 v0 79.75
v1 v2 39.42
v1 v3 103.00
v2 v1 38.65
v3 v1 102.53
v3 v5 61.44
v3 v6 96.79
v4 v5 133.04
v5 v0 81.77
v5 v3 62.05
v5 v4 134.47
v5 v6 91.63
v6 v3 97.24
v6 v5 87.94
You can then parse this file and create the Vertex and Edge objects.
Here is the complete code:
class Vertex implements Comparable<Vertex> {
public final String name;
public List<Edge> adjacencies;
public double minDistance = Double.POSITIVE_INFINITY;
public Vertex previous;
public Vertex(String argName) {
name = argName;
adjacencies = new ArrayList<Edge>();
}
public void addEdge(Edge e) {
adjacencies.add(e);
}
public String toString() {
return name;
}
public int compareTo(Vertex other) {
return Double.compare(minDistance, other.minDistance);
}
}
class Edge {
public final Vertex target;
public final double weight;
public Edge(Vertex argTarget, double argWeight) {
target = argTarget;
weight = argWeight;
}
}
public class Dijkstra {
public static void computePaths(Vertex source) {
source.minDistance = 0.;
PriorityQueue<Vertex> vertexQueue = new PriorityQueue<Vertex>();
vertexQueue.add(source);
while (!vertexQueue.isEmpty()) {
Vertex u = vertexQueue.poll();
// Visit each edge exiting u
for (Edge e : u.adjacencies) {
Vertex v = e.target;
double weight = e.weight;
double distanceThroughU = u.minDistance + weight;
if (distanceThroughU < v.minDistance) {
vertexQueue.remove(v);
v.minDistance = distanceThroughU;
v.previous = u;
vertexQueue.add(v);
}
}
}
}
public static List<Vertex> getShortestPathTo(Vertex target) {
List<Vertex> path = new ArrayList<Vertex>();
for (Vertex vertex = target; vertex != null; vertex = vertex.previous)
path.add(vertex);
Collections.reverse(path);
return path;
}
public static void main(String args[]) {
Map<String, Vertex> vertexMap = new HashMap<String, Vertex>();
BufferedReader in = null;
try {
in = new BufferedReader(new FileReader("graph.txt"));
String line;
boolean inVertex = true;
while ((line = in.readLine()) != null) {
if (line.charAt(0) == '#') {
inVertex = false;
continue;
}
if (inVertex) {
//store the vertices
int indexOfSpace = line.indexOf(' ');
String vertexId = line.substring(0, indexOfSpace);
String vertexName = line.substring(indexOfSpace + 1);
Vertex v = new Vertex(vertexName);
vertexMap.put(vertexId, v);
} else {
//store the edges
String[] parts = line.split(" ");
String vFrom = parts[0];
String vTo = parts[1];
double weight = Double.parseDouble(parts[2]);
Vertex v = vertexMap.get(vFrom);
if (v != null) {
v.addEdge(new Edge(vertexMap.get(vTo), weight));
}
}
}
} catch (IOException e) {
e.printStackTrace();
return;
}
finally{
if(in!= null)
try {
in.close();
} catch (IOException ignore) {
}
}
//get a list of all the vertices
Collection<Vertex> vertices = vertexMap.values();
Vertex source = vertices.iterator().next();
System.out.println("Computing paths from " + source);
computePaths(source);
for (Vertex v : vertices) {
System.out.println("Distance to " + v + ": " + v.minDistance);
List<Vertex> path = getShortestPathTo(v);
System.out.println("Path: " + path);
}
}
}

Basically you can store the data in the text file in a methodical manner, such as leave a space between every other data. Thereafter you can use the Java File Reader and read the contents of that file into an array. Once its in the array you can pass the array index into the respective places where the data has to be added in your code.
For example it would look similar to this, (here the String type array as is used to store the data from the text file. Therefore you can use its indexes to add the data to your code.
FileInputStream fileinputstream = new FileInputStream("FileName.txt");
DataInputStream datainputstream = new DataInputStream(fileinputstream);
BufferedReader bufferedreader1 = new BufferedReader(new InputStreamReader(datainputstream));
do{
String s1;
if((s1 = bufferedreader1.readLine()) == null){
break;
}
String as[] = s1.split(" ");
} while(true);
datainputstream.close();
}