opennlp-similarity/src/main/java/opennlp/tools/jsmlearning/TreeKernelRunner.java

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License. You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package opennlp.tools.jsmlearning;

import java.io.BufferedReader;
import java.io.File;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;

public class TreeKernelRunner {
	private void runEXE(String[] command, String runPath){
		Runtime r = Runtime.getRuntime();
		Process mStartProcess = null;
		try {
			mStartProcess = r.exec( command, null, new File(runPath));
		} catch (IOException e) {
			e.printStackTrace();
		}

		StreamLogger outputGobbler = new StreamLogger(mStartProcess.getInputStream());
		outputGobbler.start();

		try {
			int returnCode = mStartProcess.waitFor();
		} catch (InterruptedException e) {
			e.printStackTrace();
		}
	}

	public void runLearner(String dir, String learning_file, String  model_file)
	{
		dir = dir.replace('/', '\\');
		
		if (!dir.endsWith("\\"))
				dir+="\\";
		String[] runString = new String[]{dir+"svm_learn.exe","-t", "5", dir+learning_file,  dir+model_file};
		runEXE(runString, dir);
	}
	
	
	//svm_classify example_file model_file predictions_file
	public void runClassifier(String dir, String example_file, String  model_file, String predictions_file)
	{
		dir = dir.replace('/', '\\');
		
		if (!dir.endsWith("\\"))
				dir+="\\";
		String[] runString = new String[]{dir+"svm_classify.exe", dir+example_file,  dir+model_file, dir+predictions_file};
		runEXE(runString, dir);
	}

	static class StreamLogger extends Thread{

		private InputStream mInputStream;

		public StreamLogger(InputStream is) {
			this.mInputStream = is;
		}

		public void run() {
			try {
				InputStreamReader isr = new InputStreamReader(mInputStream);
				BufferedReader br = new BufferedReader(isr);
				String line = null;
				while ((line = br.readLine()) != null) {
					System.out.println(line);
				}
			} catch (IOException ioe) {
				ioe.printStackTrace();
			}
		}

	}
	
	public static void main(String[] args){
		TreeKernelRunner runner = new TreeKernelRunner();
		runner.runLearner("C:\\stanford-corenlp\\tree_kernel\\", "training.txt", "arg0.model1.txt");
		runner.runClassifier("C:\\stanford-corenlp\\tree_kernel\\", "arg0.test", "arg0.model1.txt", "arg0.output1.txt");
	}
}

	/*
exec:

public Process exec(String command, String envp[], File dir) 



   @param      command   a specified system command.
   @param      envp      array of strings, each element of which 
                         has environment variable settings in format
                         <i>name</i>=<i>value</i>.
   @param      dir       the working directory of the subprocess, or
                         <tt>null</tt> if the subprocess should inherit
                         the working directory of the current process.

                         В ди�трибутиве два exe-файла: svm_learn.exe и svm_classify.exe.

1.   svm_learn.exe берет файл � примерами, обрабатывает его, �троит файл model м правилами обучение.

Примеры запу�ка: 
svm_learn -t 5 learning_file model_file - �то �амый про�той вариант запу�ка, SubSetTreeKernel (допу�кают�� разрывы при обходе деревьев)

svm_learn -t 5 -D 0 learning_file model_file - другой вариант �дра, SubTreeKernel

Пример файла лежит на его �траничке. Там же опи�ание параметров.

2. svm_classify.exe берет файл � те�товыми примерами, файл � моделью, по�троенный svm_learn, и запи�ывает результаты обучени� в файл predictions_file.

Запу�к:     svm_classify example_file model_file predictions_file

Файл имеет тот же формат, что и входные примеры. Образец лежит в архиве на �траничке Мо�китти. 
Можно �разу же указывать, к какому кла��у отно�ит�� пример (1 или -1 в начале �троки). В �том �лучае точно�ть и полнота оценивают�� автоматиче�ки. Или �тавить там 0.
	 */