[Jboost-cvs] jboost/src/jboost/atree AlternatingTree.java,1.2,1.3

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Update of /cvsroot/jboost/jboost/src/jboost/atree
In directory fdv4jf1.ch3.sourceforge.com:/tmp/cvs-serv2442/atree

Modified Files:
	AlternatingTree.java 
Log Message:
Added python to the code output options.

Index: AlternatingTree.java
===================================================================
RCS file: /cvsroot/jboost/jboost/src/jboost/atree/AlternatingTree.java,v
retrieving revision 1.2
retrieving revision 1.3
diff -C2 -d -r1.2 -r1.3
*** AlternatingTree.java	2 Oct 2007 02:28:06 -0000	1.2
--- AlternatingTree.java	3 Jan 2009 05:13:32 -0000	1.3
***************
*** 893,898 ****
    }

!   private static final boolean allDefined = false;
!   /* true if should assume all attributes are defined in Matlab code */

    /** Converts this AlternatingTree to Matlab.  Assumes that all
--- 893,1087 ----
    }

!   /** true if should assume all attributes are defined in Matlab code */
!   private boolean allDefined = false;
!   
!   /** Description of all attributes */
!   private AttributeDescription[] ad = null;
! 
!   /** Converts this AlternatingTree to Matlab.  Assumes that all
!    attributes are of type number or finite.  If allDefined = true
!    then all attributes are assumed to be defined.  */
!   public String toPython(String fname,
!       ExampleDescription exampleDescription) {
!     allDefined = true;
!     String code = "";
!     code += "# The map from index to spec file description is:\n\n";
!     code += "#      index    attr.type    data.type   name\n"
! 	  + "#    ------------------------------------------\n";
!     ad = exampleDescription.getAttributes();
!     for (int i = 0; i < ad.length; i++) {
!       String s;
!       String key = "";
!       String t = ad[i].getType();
!       if (t.equals("number")) {
!         s = "number       Double   ";
!       } else if (t.equals("text")) {
!         s = "text         String   ";
!       } else if (t.equals("finite")) {
!         s = "finite       Integer  ";
!         for (int j = 0; j < ad[i].getNoOfValues(); j++)
!           key += (j == 0
!               ? "#                 key: "
!                   : "#                      ")
!                   + padInteger(j, 5) + " = "
!                   + ad[i].getAttributeValue(j) + "\n";
!       } else {
!         System.err.println("Warning: unrecognized type for attribute "
!             + i + ": " + t);
!         s = "???          ???      ";
!       }
!       code += "#     " + padInteger(i, 5) + "     " + s + "    " + 
! 	  ad[i].getAttributeName() + "\n" + key;
!     }
!     code += ""
!       + "#return an array of scores correpsonding to the classes:\n"
!       + "#           index       class name\n"
!       + "#          ------------------------\n";
!     AttributeDescription la = exampleDescription.getLabelDescription();
!     
!     for (int j = 0; j < la.getNoOfValues(); j++)
!       code += "#          " + padInteger(j, 5) + "        "
!       + la.getAttributeValue(j) + "\n";
! 
!     code += "\n\n"
! 	+ "# This class evaluates a jboost-trained classifier.  The "
! 	+ (allDefined ? "" : "first ") + "\n"
! 	+ "# argument is an array of values corresponding to the formatted data\n"
! 	+ "# used during training."
! 	+ (allDefined
! 	   ? "\n" 
! 	   : "  The second argument is an array of values\n"
! 	   + "# indicating which of the attributes are defined (where non-zero means\n"
! 	   + "# that the corresponding attribute is defined).\n")
! 	+ "# This classifier was automatically generated by jboost on:\n"
! 	+ "# " + (new Date()) + "\n"
! 	+ "class ATree:\n"
! 	+ "\t\"\"\"\n"
! 	+ "\tThe ATree class provides access to scoring algorithms"
! 	+ "\tderived from an ATree data structure.  This class only\n"
! 	+ "\tprovides scores and does not learn the structure.\n"
! 	+ "\t\"\"\"\n"
! 	+ "\t\n"
! 	+ "\tdef __init__(self, datafile, specfile):\n"
! 	+ "\t\tself.datafile = datafile\n"
! 	+ "\t\tself.specfile = specfile\n"
! 	+ "\t\tself.data = self.__read_in_data()\n"
! 	+ "\t\tself.spec_dict = self.__read_in_spec()\n"
! 	+ "\t\n"
! 	+ "\tdef get_scores(self):\n"
! 	+ "\t\tret = []\n"
! 	+ "\t\tfor i,x in enumerate(self.data):\n"
! 	+ "\t\t\tret.append(self.__score(i))\n"
! 	+ "\t\treturn ret\n"
! 	+ "\t\n"
! 	+ "\tdef __score(self, i):\n"
! 	+ "\t\treturn self.__predict(i)\n"
! 	+ "\t\n"
! 	+ "\tdef get_data_value(self, x, feature):\n"
! 	+ "\t\tidx = self.spec_dict[feature]\n"
! 	+ "\t\treturn float(x[idx])\n"
! 	+ "\t\n"
! 	+ "\tdef __read_in_data(self):\n"
! 	+ "\t\t\"\"\"\n"
! 	+ "\t\tReads in the datafile.\n"
! 	+ "\t\t\"\"\"\n"
! 	+ "\t\tf = open(self.datafile)\n"
! 	+ "\t\tlines = f.readlines()\n"
! 	+ "\t\tf.close()\n"
! 	+ "\t\tret = []\n"
! 	+ "\t\tfor line in lines:\n"
! 	+ "\t\t\tline = line[:-2]\n"
! 	+ "\t\t\tret.append([x.strip() for x in line.split(',')])\n"
! 	+ "\t\treturn ret\n"
! 	+ "\t\n"
! 	+ "\tdef __read_in_spec(self):\n"
! 	+ "\t\t\"\"\"\n"
! 	+ "\t\tReturns a dictionary with feature names => data index\n"
! 	+ "\t\t\"\"\"\n"
! 	+ "\t\tf = open(self.specfile)\n"
! 	+ "\t\tlines = f.readlines()\n"
! 	+ "\t\tf.close()\n"
! 	+ "\t\tret = {}\n"	
! 	+ "\t\ti = 0\n"	
! 	+ "\t\tfor line in lines:\n"	
! 	+ "\t\t\tif '=' in line:\n"	
! 	+ "\t\t\t\tcontinue\n"
! 	+ "\t\t\tdescription = line.split()[0]\n"	
! 	+ "\t\t\tret[description] = i\n"
! 	+ "\t\t\ti += 1\n"
! 	+ "\t\treturn ret\n"
! 	+ "\t\n"
! 	+ "\tdef __predict(self, i"
! 	+ (allDefined ? "" : ", def") + "):\n"
! 	+ "\t\tx=self.data[i]\n"
! 	+ "\t\tpred = [0  for i in range(" + root.prediction.toCodeArray().length + ")]\n"
! 	+ makePythonCode(root, "\t\t")
! 	+ "\t\treturn pred"
! 	+ "\n"
! 	+ "\n"
! 	+ "import sys\n"
! 	+ "def main():\n"
! 	+ "\tdatafile = sys.argv[1]\n"
! 	+ "\tspecfile = sys.argv[2]\n"
! 	+ "\tatree = ATree(datafile, specfile)\n"
! 	+ "\tscores = atree.get_scores()\n"
! 	+ "\tprint scores\n"
! 	+ "if __name__=='__main__':\n"
! 	+ "\tmain()\n"
! 	+ "\n"
! 	+ "\n";
!     return code;
!   }
!   
! 
!   private String makePythonCode(PredictorNode pn, String tab) {
!     String code = "";
!     code += tab + "newpred = [ # " + pn.id + "\n";
!     double[] v = pn.prediction.toCodeArray();
!     for (int i = 0; i < v.length; i++)
!       code += tab + "           " + v[i] + 
!       (i < v.length - 1 ? "\n" : "]\n");
!     code += tab + "pred = [n+p for n,p in zip(newpred,pred)]\n";
!     int size = pn.splitterNodes.size();
!     for (int i = 0; i < size; i++)
!       code += makePythonCode((SplitterNode)pn.splitterNodes.get(i), tab);
!     return code;
!   }
!   
!   private String makePythonCode(SplitterNode sn, String tab) {
!     String code = "";
!     
!     Summary summary=sn.splitter.getSummary();
!     
!     code += tab + (allDefined
! 		   ? "    " 
! 		   : "if def(" + (summary.index+1) + "):")
!             + " # " + sn.id + "\n";
!     String stab = (allDefined ? tab : tab);
!     switch(summary.type) {
!       case Summary.EQUALITY:
!         code += stab + "if self.get_data_value(x,'" + ad[(summary.index)].getAttributeName() + "') == " +
!         ((Integer)summary.val) + ":\n";
!       code += makeMatlabCode(sn.predictorNodes[0], stab + "\t");
!       code += stab + "else:\n";
!       code += makeMatlabCode(sn.predictorNodes[1], stab + "\t");
!       break;
!       case Summary.LESS_THAN:
!         code += stab + "if self.get_data_value(x,'" + ad[(summary.index)].getAttributeName() + "') <= " +
!         ((Double) summary.val) + ":\n";
!       code += makePythonCode(sn.predictorNodes[0], stab + "\t");
!       code += stab + "else:\n";
!       code += makePythonCode(sn.predictorNodes[1], stab + "\t");
!       break;
!       default:
!         throw new RuntimeException("Type of split not allowed");
!     }
!     
!     return code;
!   }
! 
! 
! 
! 

    /** Converts this AlternatingTree to Matlab.  Assumes that all