bayesnetgenerator.java

代码是一个分类器的实现,其中使用了部分weka的源代码。可以将项目导入eclipse运行

	            		if (nPs[iValue2] < nPs[iValue]) {
	            			int h = nPs[iValue2]; nPs[iValue2] = nPs[iValue]; nPs[iValue] = h;
	            		}
	            	}
            	}
            	// assign to probability tables
            	DiscreteEstimatorBayes d = new DiscreteEstimatorBayes(nValues, getEstimator().getAlpha());
            	for (int iValue = 0; iValue < nValues; iValue++)  {
            		d.addValue(iValue, nPs[iValue + 1] - nPs[iValue]);
            	}
	            m_Distributions[iAttribute][iParent] = d;
            } 
        } 
    } // GenerateRandomDistributions
    
	/**
	 * GenerateInstances generates random instances sampling from the
	 * distribution represented by the Bayes network structure. It assumes
	 * a Bayes network structure has been initialized
	 * 
	 * @throws Exception if something goes wrong
	 */
	public void generateInstances () throws Exception {
	    int [] order = getOrder();
		for (int iInstance = 0; iInstance < m_nNrOfInstances; iInstance++) {
		    int nNrOfAtts = m_Instances.numAttributes();
			Instance instance = new Instance(nNrOfAtts);
			instance.setDataset(m_Instances);
			for (int iAtt2 = 0; iAtt2 < nNrOfAtts; iAtt2++) {
			    int iAtt = order[iAtt2];

				double iCPT = 0;

				for (int iParent = 0; iParent < m_ParentSets[iAtt].getNrOfParents(); iParent++) {
				  int nParent = m_ParentSets[iAtt].getParent(iParent);
				  iCPT = iCPT * m_Instances.attribute(nParent).numValues() + instance.value(nParent);
				} 
	
				double fRandom = random.nextInt(1000) / 1000.0f;
				int iValue = 0;
				while (fRandom > m_Distributions[iAtt][(int) iCPT].getProbability(iValue)) {
					fRandom = fRandom - m_Distributions[iAtt][(int) iCPT].getProbability(iValue);
					iValue++ ;
				}
				instance.setValue(iAtt, iValue);
			}
			m_Instances.add(instance);
		}
	} // GenerateInstances

    /**
     * @throws Exception if there's a cycle in the graph
     */	
    int [] getOrder() throws Exception {
	int nNrOfAtts = m_Instances.numAttributes();
	int [] order = new int[nNrOfAtts];
	boolean [] bDone = new boolean[nNrOfAtts];
	for (int iAtt = 0; iAtt < nNrOfAtts; iAtt++) {
	    int iAtt2 = 0; 
	    boolean allParentsDone = false;
	    while (!allParentsDone && iAtt2 < nNrOfAtts) {
		if (!bDone[iAtt2]) {
		    allParentsDone = true;
		    int iParent = 0;
		    while (allParentsDone && iParent < m_ParentSets[iAtt2].getNrOfParents()) {
			allParentsDone = bDone[m_ParentSets[iAtt].getParent(iParent++)];
		    }
		    if (allParentsDone && iParent == m_ParentSets[iAtt2].getNrOfParents()) {
			order[iAtt] = iAtt2;
			bDone[iAtt2] = true;
		    } else {
			iAtt2++;
		    }
		} else {
		    iAtt2++;
		}
	    }
	    if (!allParentsDone && iAtt2 == nNrOfAtts) {
		throw new Exception("There appears to be a cycle in the graph");
	    }
	}
	return order;
    } // getOrder

    	/**
    	 * Returns either the net (if BIF format) or the generated instances
    	 * 
    	 * @return either the net or the generated instances
    	 */
  	public String toString() {
  	  if (m_bGenerateNet) {
  	    return toXMLBIF03();
  	  }
  	  return m_Instances.toString();
  	} // toString
  	

	boolean m_bGenerateNet = false;
	int m_nNrOfNodes = 10;
	int m_nNrOfArcs = 10;
	int m_nNrOfInstances = 10;
	int m_nCardinality = 2;
	String m_sBIFFile = "";

	void setNrOfNodes(int nNrOfNodes) {m_nNrOfNodes = nNrOfNodes;}
	void setNrOfArcs(int nNrOfArcs) {m_nNrOfArcs = nNrOfArcs;}
	void setNrOfInstances(int nNrOfInstances) {m_nNrOfInstances = nNrOfInstances;}
	void setCardinality(int nCardinality) {m_nCardinality = nCardinality;}
	void setSeed(int nSeed) {m_nSeed = nSeed;}

	/**
	 * Returns an enumeration describing the available options
	 * 
	 * @return an enumeration of all the available options
	 */
	public Enumeration listOptions() {
		Vector newVector = new Vector(6);

		newVector.addElement(new Option("\tGenerate network (instead of instances)\n", "B", 0, "-B"));
		newVector.addElement(new Option("\tNr of nodes\n", "N", 1, "-N <integer>"));
		newVector.addElement(new Option("\tNr of arcs\n", "A", 1, "-A <integer>"));
		newVector.addElement(new Option("\tNr of instances\n", "M", 1, "-M <integer>"));
		newVector.addElement(new Option("\tCardinality of the variables\n", "C", 1, "-C <integer>"));
		newVector.addElement(new Option("\tSeed for random number generator\n", "S", 1, "-S <integer>"));
		newVector.addElement(new Option("\tThe BIF file to obtain the structure from.\n", "F", 1, "-F <file>"));

		return newVector.elements();
	} // listOptions

	/**
	 * Parses a given list of options. <p/>
	 * 
	 <!-- options-start -->
	 * Valid options are: <p/>
	 * 
	 * <pre> -B
	 *  Generate network (instead of instances)
	 * </pre>
	 * 
	 * <pre> -N &lt;integer&gt;
	 *  Nr of nodes
	 * </pre>
	 * 
	 * <pre> -A &lt;integer&gt;
	 *  Nr of arcs
	 * </pre>
	 * 
	 * <pre> -M &lt;integer&gt;
	 *  Nr of instances
	 * </pre>
	 * 
	 * <pre> -C &lt;integer&gt;
	 *  Cardinality of the variables
	 * </pre>
	 * 
	 * <pre> -S &lt;integer&gt;
	 *  Seed for random number generator
	 * </pre>
	 * 
	 * <pre> -F &lt;file&gt;
	 *  The BIF file to obtain the structure from.
	 * </pre>
	 * 
	 <!-- options-end -->
	 *
	 * @param options the list of options as an array of strings
	 * @exception Exception if an option is not supported
	 */
	public void setOptions(String[] options) throws Exception {
		m_bGenerateNet = Utils.getFlag('B', options);

		String sNrOfNodes = Utils.getOption('N', options);
		if (sNrOfNodes.length() != 0) {
		  setNrOfNodes(Integer.parseInt(sNrOfNodes));
		} else {
			setNrOfNodes(10);
		} 

		String sNrOfArcs = Utils.getOption('A', options);
		if (sNrOfArcs.length() != 0) {
		  setNrOfArcs(Integer.parseInt(sNrOfArcs));
		} else {
			setNrOfArcs(10);
		} 

		String sNrOfInstances = Utils.getOption('M', options);
		if (sNrOfInstances.length() != 0) {
		  setNrOfInstances(Integer.parseInt(sNrOfInstances));
		} else {
			setNrOfInstances(10);
		} 

		String sCardinality = Utils.getOption('C', options);
		if (sCardinality.length() != 0) {
		  setCardinality(Integer.parseInt(sCardinality));
		} else {
			setCardinality(2);
		} 

		String sSeed = Utils.getOption('S', options);
		if (sSeed.length() != 0) {
		  setSeed(Integer.parseInt(sSeed));
		} else {
			setSeed(1);
		} 

		String sBIFFile = Utils.getOption('F', options);
		if ((sBIFFile != null) && (sBIFFile != "")) {
			setBIFFile(sBIFFile);
		}
	} // setOptions

	/**
	 * Gets the current settings of the classifier.
	 * 
	 * @return an array of strings suitable for passing to setOptions
	 */
	public String[] getOptions() {
		String[] options = new String[13];
		int current = 0;
		if (m_bGenerateNet) {
		  options[current++] = "-B";
		} 

		options[current++] = "-N";
		options[current++] = "" + m_nNrOfNodes;

		options[current++] = "-A";
		options[current++] = "" + m_nNrOfArcs;

		options[current++] = "-M";
		options[current++] = "" + m_nNrOfInstances;

		options[current++] = "-C";
		options[current++] = "" + m_nCardinality;

		options[current++] = "-S";
		options[current++] = "" + m_nSeed;

                if (m_sBIFFile.length() != 0) {
                  options[current++] = "-F";
                  options[current++] = "" + m_sBIFFile;
                }

		// Fill up rest with empty strings, not nulls!
		while (current < options.length) {
			options[current++] = "";
		}

		return options;
	} // getOptions

    /**
     * prints all the options to stdout
     */
    protected static void printOptions(OptionHandler o) {
      Enumeration enm = o.listOptions();
      
      System.out.println("Options for " + o.getClass().getName() + ":\n");
      
      while (enm.hasMoreElements()) {
        Option option = (Option) enm.nextElement();
        System.out.println(option.synopsis());
        System.out.println(option.description());
      }
    }

    /**
     * Main method
     * 
     * @param args the commandline parameters
     */
    static public void main(String [] args) {
		BayesNetGenerator b = new BayesNetGenerator();
    	try {
		if ( (args.length == 0) || (Utils.getFlag('h', args)) ) {
                        printOptions(b);
                        return;
		}
	    	b.setOptions(args);
	    	
	    	b.generateRandomNetwork();
	    	if (!b.m_bGenerateNet) { // skip if not required
				b.generateInstances();
	    	}
	    	System.out.println(b.toString());
    	} catch (Exception e) {
    		e.printStackTrace();
    		printOptions(b);
    	}
    } // main
    
} // class BayesNetGenerator