/* Copyright (C) 2010 Univ. of Massachusetts Amherst, Computer Science Dept.
This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit).
http://www.cs.umass.edu/~mccallum/mallet
This software is provided under the terms of the Common Public License,
version 1.0, as published by http://www.opensource.org. For further
information, see the file `LICENSE' included with this distribution. */
package cc.mallet.classify.tui;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.logging.*;
import java.util.regex.*;
import java.io.*;
import java.nio.charset.Charset;
import cc.mallet.classify.*;
import cc.mallet.pipe.Pipe;
import cc.mallet.pipe.SerialPipes;
import cc.mallet.pipe.SvmLight2FeatureVectorAndLabel;
import cc.mallet.pipe.iterator.*;
import cc.mallet.types.*;
import cc.mallet.util.*;
/**
* Command line tool for classifying a sequence of instances directly from text
* input, without creating an instance list.
* <p>
*
* @author David Mimno
* @author Gregory Druck
* @author Siddhartha Jonnalagadda
*/
public class SvmLight2Classify {
private static Logger logger = MalletLogger.getLogger(SvmLight2Classify.class.getName());
static CommandOption.File inputFile = new CommandOption.File(
SvmLight2Classify.class, "input", "FILE", true, null,
"The file containing data to be classified, one instance per line", null);
static CommandOption.File outputFile = new CommandOption.File(
SvmLight2Classify.class, "output", "FILE", true,
new File("text.vectors"),
"Write the instance list to this file; Using - indicates stdout.", null);
static CommandOption.String lineRegex = new CommandOption.String(
SvmLight2Classify.class, "line-regex", "REGEX", true,
"^(\\S*)[\\s,]*(.*)$",
"Regular expression containing regex-groups for label, name and data.", null);
static CommandOption.Integer nameOption = new CommandOption.Integer(
SvmLight2Classify.class, "name", "INTEGER", true, 1,
"The index of the group containing the instance name.\n"
+ " Use 0 to indicate that the name field is not used.", null);
static CommandOption.Integer dataOption = new CommandOption.Integer(
SvmLight2Classify.class, "data", "INTEGER", true, 2,
"The index of the group containing the data.", null);
static CommandOption.File classifierFile = new CommandOption.File(
SvmLight2Classify.class, "classifier", "FILE", true, new File("classifier"),
"Use the pipe and alphabets from a previously created vectors file.\n"
+ " Allows the creation, for example, of a test set of vectors that are\n"
+ " compatible with a previously created set of training vectors", null);
static CommandOption.String encoding = new CommandOption.String(
SvmLight2Classify.class, "encoding", "STRING", true, Charset.defaultCharset().displayName(),
"Character encoding for input file", null);
public static void main(String[] args) throws FileNotFoundException, IOException {
// Process the command-line options
CommandOption.setSummary(SvmLight2Classify.class,
"A tool for classifying a stream of unlabeled instances");
CommandOption.process(SvmLight2Classify.class, args);
// Print some helpful messages for error cases
if (args.length == 0) {
CommandOption.getList(SvmLight2Classify.class).printUsage(false);
System.exit(-1);
}
if (inputFile == null) {
throw new IllegalArgumentException(
"You must include `--input FILE ...' in order to specify a"
+ "file containing the instances, one per line.");
}
// Read classifier from file
Classifier classifier = null;
try {
ObjectInputStream ois = new ObjectInputStream(new BufferedInputStream(
new FileInputStream(classifierFile.value)));
classifier = (Classifier) ois.readObject();
ois.close();
} catch (Exception e) {
throw new IllegalArgumentException(
"Problem loading classifier from file " + classifierFile.value + ": "+ e.getMessage());
}
Pipe instancePipe;
// Build a new pipe
ArrayList<Pipe> pipeList = new ArrayList<Pipe>();
pipeList.add(new SvmLight2FeatureVectorAndLabel());
instancePipe = new SerialPipes(pipeList);
InstanceList instances = new InstanceList(instancePipe);
Reader fileReader;
if (inputFile.equals("-")) {
fileReader = new InputStreamReader(System.in);
} else {
fileReader = new InputStreamReader(new FileInputStream(inputFile.value),encoding.value);
}
// Read instances from the file
instances.addThruPipe(new SelectiveFileLineIterator(fileReader, "^\\s*#.+"));
Iterator<Instance> iterator = instances.iterator();
// Write classifications to the output file
PrintStream out = null;
if (outputFile.value.toString().equals("-")) {
out = System.out;
} else {
out = new PrintStream(outputFile.value, encoding.value);
}
// gdruck@cs.umass.edu
// Stop growth on the alphabets. If this is not done and new
// features are added, the feature and classifier parameter
// indices will not match.
classifier.getInstancePipe().getDataAlphabet().stopGrowth();
classifier.getInstancePipe().getTargetAlphabet().stopGrowth();
while (iterator.hasNext()) {
Instance instance = iterator.next();
Labeling labeling = classifier.classify(instance).getLabeling();
StringBuilder output = new StringBuilder();
output.append(instance.getName());
for (int location = 0; location < labeling.numLocations(); location++) {
output.append("\t" + labeling.labelAtLocation(location));
output.append("\t" + labeling.valueAtLocation(location));
}
out.println(output);
}
if (!outputFile.value.toString().equals("-")) {
out.close();
}
}
}