[Maxent-commit] CVS: maxent/src/java/opennlp/maxent TrainEval.java,1.2,1.3

[Jason B. <jas...@us...>]

Update of /cvsroot/maxent/maxent/src/java/opennlp/maxent
In directory usw-pr-cvs1:/tmp/cvs-serv23879/src/java/opennlp/maxent

Modified Files:
	TrainEval.java 
Log Message:
Added usage message to TrainEval's eval() method.

Index: TrainEval.java
===================================================================
RCS file: /cvsroot/maxent/maxent/src/java/opennlp/maxent/TrainEval.java,v
retrieving revision 1.2
retrieving revision 1.3
diff -C2 -d -r1.2 -r1.3
*** TrainEval.java	14 Nov 2001 17:39:56 -0000	1.2
--- TrainEval.java	25 Apr 2002 15:01:07 -0000	1.3
***************
*** 96,115 ****
  	    }
  	}
  	
! 	FileReader datafr = new FileReader(args[g.getOptind()]);
! 	
! 	if(train) {
  	    MaxentModel m =
  		train(new EventCollectorAsStream(e.getEventCollector(datafr)),
  		      cutoff);
! 	    new BinaryGISModelWriter((GISModel)m, new File(dir+stem)).persist();
  	}
  	else {
  	    MaxentModel model =
! 		new BinaryGISModelReader(new File(dir+stem)).getModel();
! 	    if(local)
  		e.localEval(model, datafr, e, verbose);
! 	    else
  		eval(model, datafr, e, verbose);
  	}
      }
--- 96,139 ----
  	    }
  	}
+ 
+ 	int lastIndex = g.getOptind();
+ 	if (lastIndex >= args.length) {
+ 	    System.out.println("This is a usage message from opennlp.maxent.TrainEval. You have called the training procedure for a maxent application with the incorrect arguments.  These are the options:");
+ 
+ 	    System.out.println("\nOptions for defining the model location and name:");
+ 	    System.out.println(" -d <directoryName>");
+ 	    System.out.println("\tThe directory in which to store the model.");
+ 	    System.out.println(" -s <modelName>");
+ 	    System.out.println("\tThe name of the model, e.g. EnglishPOS.bin.gz or NameFinder.txt.");
+ 	    
+ 	    System.out.println("\nOptions for training:");
+ 	    System.out.println(" -c <cutoff>");
+ 	    System.out.println("\tAn integer cutoff level to reduce infrequent contextual predicates.");
+ 	    System.out.println(" -t\tTrain a model. If absent, the given model will be loaded and evaluated.");
+ 	    System.out.println("\nOptions for evaluation:");
+ 	    System.out.println(" -l\t the evaluation method of class that uses the model. If absent, TrainEval's eval method is used.");
+ 	    System.out.println(" -v\t verbose.");
+ 	    System.out.println("\nThe final argument is the data file to be loaded and used for either training or evaluation.");
+ 	    System.out.println("\nAs an example for training:\n java opennlp.grok.preprocess.postag.POSTaggerME -t -d ./ -s EnglishPOS.bin.gz -c 7 postag.data");
+ 	    System.exit(0);
+ 	}
+ 
+ 	FileReader datafr = new FileReader(args[lastIndex]);
  	
! 	if (train) {
  	    MaxentModel m =
  		train(new EventCollectorAsStream(e.getEventCollector(datafr)),
  		      cutoff);
! 	    new SuffixSensitiveGISModelWriter((GISModel)m,
! 					      new File(dir+stem)).persist();
  	}
  	else {
  	    MaxentModel model =
! 		new SuffixSensitiveGISModelReader(new File(dir+stem)).getModel();
! 	    if (local) {
  		e.localEval(model, datafr, e, verbose);
! 	    } else {
  		eval(model, datafr, e, verbose);
+ 	    }
  	}
      }