JAVA 小程序调试的问题 请帮忙
NormalApplet小程序java编译成功，运行时出现错误，在网页中载入时失败，当前路径; d：\test\normal下有3个java文件（NormalGraphData；NormalControlPanel；NormalApplet）及转换的class文件，一个文包件夹 （edu.csusb.danby） ；classpath设置应该没有问题，运行其他小程序，没有问题，利用Jcreator调试的结果java.lang.NoSuchMethodError: main Exception in thread "main" 这个我估计是小程序在网页中才能运行，但在网页中测试，左下角显示，载入小程序失败（在网页中的代码没有问题）我是来鸟，清高手看一下 调用的其他文件在附件
源文件是：
package normal;
import java.awt.*;
import java.awt.event.*;
import javax.swing.*;
import java.applet.*;
import edu.csusb.danby.applet.*;
import edu.csusb.danby.math.ProbMath;
import edu.csusb.danby.graph.*;
/**
* Normal distribution applet
* @author Charles S. Stanton
* @version Sat Jul 27 08:45:01 PDT 2002
*/
public class NormalApplet extends DApplet{
NormalControlPanel controlPanel;
NormalGraphData ngd;
PdfPlot normalPlot;
public void init(){
ngd = new NormalGraphData();
normalPlot = new PdfPlot(ngd);
controlPanel = new NormalControlPanel(this);
dFrame = new DFrame("Normal Distribution Calculator", normalPlot);
dFrame.setControlPanel(controlPanel);
dFrame.validate();
setVisible(true);
}
public void doControlPanelButtonAction( ActionEvent e){
String buttonLabel = e.getActionCommand();
if (buttonLabel.equals("calculate")){
calculate();
}
}
public void calculate(){
double x1, x2, mu, sigma;
String t1, t2, tMu, tSigma; //text values for x1, x2;
tMu = controlPanel.textMu.getText();
tSigma = controlPanel.textSigma.getText();
t1 = controlPanel.textX1.getText();
t2 = controlPanel.textX2.getText();
try {
x1=Double.valueOf(t1).doubleValue();
x2=Double.valueOf(t2).doubleValue();
mu = Double.valueOf(tMu).doubleValue();
sigma = Double.valueOf(tSigma).doubleValue();
ngd.setX1((float)x1);
ngd.setX2((float)x2);
ngd.setMu((float)mu);
ngd.setSigma((float)sigma);
controlPanel.printProbability(ProbMath.normalCdf((x2-mu)/sigma)
-ProbMath.normalCdf((x1-mu)/sigma));
normalPlot.update(ngd);
normalPlot.repaint();
} catch ( NumberFormatException n) {
String msg = "z1 = "+t1+" z2 = "+t2+"\n mu = "+tMu+" sigma = "+tSigma+"\n are not proper numerical values";
String errTitle = "Numerical Input Error";
JOptionPane.showMessageDialog(dFrame, msg , errTitle,
JOptionPane.ERROR_MESSAGE);
}
repaint();
}
/**
* provides applet info
*/
public String getAppletInfo() {
return "A normal probability calculator.\nAuthor: Charles S. Stanton";
}
}
2.
package normal;
import javax.swing.*;
import java.awt.event.*;
import java.applet.*;
import java.awt.*;
import edu.csusb.danby.applet.*;
public class NormalControlPanel extends JPanel {
JTextField textMu, textSigma, textX1, textX2, textProb;
DControlPanelAction mApplet;
public NormalControlPanel(DControlPanelAction applet){
mApplet=applet;
setLayout(new FlowLayout());
textMu = new JTextField("0.0",7);
textSigma = new JTextField("1.0",7);
textX1 = new JTextField(7);
textX2 = new JTextField(7);
add(new JLabel("mu ="));
add(textMu);
add(new JLabel("sigma ="));
add(textSigma);
add(new JLabel("x1 ="));
add(textX1);
add(new JLabel("x2 ="));
add(textX2);
JButton submitButton = new JButton("calculate");
submitButton.addActionListener(new ActionListener(){
public void actionPerformed(ActionEvent e){
mApplet.doControlPanelButtonAction(e);
}
});
add(submitButton);
textProb = new JTextField(14);
add(new JLabel("P(x1 < X < x2)="));
add(textProb);
}
public void printProbability(double p){
//textProb.setColor(Color.blue);
textProb.setText(String.valueOf(p));
}
}
3.
package normal;
import java.awt.*;
import javax.swing.*;
//import cern.jet.stat.*;
import java.awt.geom.Point2D;
import edu.csusb.danby.graph.*;
/**
* This class graphs a normal curve and shows the area
* under the curve specified
*
* @author Charles S. Stanton
* @version Mon Jul 29 19:10:03 PDT 2002
*/
public class NormalGraphData implements PdfPlotable {
static final float c = (float)(1.0/(Math.sqrt(2.0*Math.PI)));
float mu, sigma, x1, x2;
//add a few extra points near zero so that the graph is smoother
float[] normalAbcissa ={ 4.000000000f, 3.800000000f, 3.600000000f,
3.400000000f, 3.200000000f, 3.000000000f,
2.800000000f, 2.600000000f, 2.400000000f,
2.200000000f, 2.000000000f, 1.800000000f,
1.600000000f, 1.400000000f, 1.200000000f,
1.100000000f, 1.000000000f, .900000000f,
.800000000f, .700000000f, .600000000f,
.500000000f, .400000000f, .300000000f,
.200000000f, .100000000f, 0.f};
float[] normalOrdinate = {.1338302258e-3f, .2919469256e-3f, .6119019298e-3f,
.1232219168e-2f, .2384088201e-2f, .4431848411e-2f,
.7915451578e-2f, .1358296922e-1f, .2239453029e-1f,
.3547459283e-1f, .5399096648e-1f, .7895015828e-1f,
.1109208346f, .1497274656f, .1941860549f, .2178521769f,
.2419707244f, .2660852498f, .2896915527f, .3122539332f,
.3332246028f, .3520653266f, .3682701402f, .3813878153f,
.3910426938f, .3969525473f, .3989422802f};
boolean inverseSelected;
int tailChoice; //PDFPlotable.LEFT_TAIL, PDFPlotable.RIGHT_TAIL, or PDFPlotable.BOTH_TAILS
/**
* constructs standard mu=0 sigma = 1<code>NormalGraphData</code>
*
*/
public NormalGraphData(){
mu =0;
sigma = 1;
x1 = -21.01f;
x2 =1.01f;
}
/**
* constructs <code>NormalGraphData</code>
*
* @param mu is the mean
* @param sigma is the standard deviation
* @parm aX0 is the left end of the probability interval
* @param aX1 is the right end of the probability interval
*/
public NormalGraphData( float aMu, float aSigma, float aX1, float aX2){
this( aMu, aSigma, aX1, aX2, false, PdfPlotable.BOTH_TAILS);
}
/**
* constructs <code>NormalGraphData</code>
*
* @param mu is the mean
* @param sigma is the standard deviation* @param n is the degrees of freedom
* @parm aX0 is the left end of the probability interval
* @param aX1 is the right end of the probability interval
* @param aInverseSelected sets the inverse mode
* @param aTailChoice sets the tail choice for inverse mode
*/
public NormalGraphData( float aMu, float aSigma, float ax1, float ax2,
boolean aInverseSelected, int aTailChoice){
mu = aMu;
sigma = aSigma;
x1 = ax1;
x2 = ax2;
inverseSelected = aInverseSelected;
tailChoice = aTailChoice;
}
private float f(float x){
return (float)(c/Math.sqrt(sigma)*Math.exp(-1*(x-mu)*(x-mu)/(2*sigma*sigma)));
}
public Point2D.Float[] getPlotPoints() {
Point2D.Float[] returnData = new Point2D.Float[53];
//add a few extra points near zero so that the graph is smoother
for (int i=0; i<27; i++) {
returnData[i] = new Point2D.Float( -1*normalAbcissa[i]*sigma+mu, normalOrdinate[i]/(float)Math.sqrt(sigma));
returnData[53-i-1] = new Point2D.Float( normalAbcissa[i]*sigma+mu, normalOrdinate[i]/(float)Math.sqrt(sigma));
}
return returnData;
}
// PdfPlotable viewport methods
public float getLowX(){return -4.0f*sigma+mu;}
public float getHighX(){ return 4.0f*sigma+mu;}
public float getLowY(){ return 0.0f;} //usually should be 0
public float getHighY() {return 0.5f/(float)Math.sqrt(sigma);}
// PdfPlotable interval methods
public Point2D.Float getLowXInterval() {return new Point2D.Float(x1,f(x1));}
public Point2D.Float getHighXInterval() {return new Point2D.Float(x2, f(x2));}
// PdfPlotable String information
public String getXAxisLabel(){return "x";}
public String getTitle() {
String title = new String("Normal Plot, mu = "+mu+" sigma = "+sigma);
return title;
}
public void reset(){;}
public boolean isInverseSelected(){return inverseSelected;}
public void setInverseSelected(boolean aInverseSelected){ inverseSelected = aInverseSelected;}
public int getTailChoice(){return tailChoice;}
public void setTailChoice(int aTailChoice){ tailChoice=aTailChoice;}
public void setX1(float aX1){ x1 = aX1;}
public void setX2(float aX2){ x2 = aX2;}
public void setMu(float aMu){ mu = aMu;}
public void setSigma(float aSigma){ sigma = aSigma;}
}
edu.rar
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