/*
* 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.
*/
import java.io.File;
import java.io.FileReader;
import opennlp.maxent.BasicContextGenerator;
import opennlp.maxent.ContextGenerator;
import opennlp.maxent.DataStream;
import opennlp.maxent.PlainTextByLineDataStream;
import opennlp.model.GenericModelReader;
import opennlp.model.MaxentModel;
import opennlp.model.RealValueFileEventStream;
/**
* Test the model on some input.
*/
public class Predict {
MaxentModel _model;
ContextGenerator _cg = new BasicContextGenerator();
public Predict (MaxentModel m) {
_model = m;
}
private void eval (String predicates) {
eval(predicates,false);
}
private void eval (String predicates, boolean real) {
String[] contexts = predicates.split(" ");
double[] ocs;
if (!real) {
ocs = _model.eval(contexts);
}
else {
float[] values = RealValueFileEventStream.parseContexts(contexts);
ocs = _model.eval(contexts,values);
}
System.out.println("For context: " + predicates+ "\n" + _model.getAllOutcomes(ocs) + "\n");
}
private static void usage() {
}
/**
* Main method. Call as follows:
* <p>
* java Predict dataFile (modelFile)
*/
public static void main(String[] args) {
String dataFileName, modelFileName;
boolean real = false;
String type = "maxent";
int ai = 0;
if (args.length > 0) {
while (args[ai].startsWith("-")) {
if (args[ai].equals("-real")) {
real = true;
}
else if (args[ai].equals("-perceptron")) {
type = "perceptron";
}
else {
usage();
}
ai++;
}
dataFileName = args[ai++];
if (args.length > ai) {
modelFileName = args[ai++];
}
else {
modelFileName = dataFileName.substring(0,dataFileName.lastIndexOf('.')) + "Model.txt";
}
}
else {
dataFileName = "";
modelFileName = "weatherModel.txt";
}
Predict predictor = null;
try {
MaxentModel m = new GenericModelReader(new File(modelFileName)).getModel();
predictor = new Predict(m);
} catch (Exception e) {
e.printStackTrace();
System.exit(0);
}
if (dataFileName.equals("")) {
predictor.eval("Rainy Happy Humid");
predictor.eval("Rainy");
predictor.eval("Blarmey");
}
else {
try {
DataStream ds =
new PlainTextByLineDataStream(
new FileReader(new File(dataFileName)));
while (ds.hasNext()) {
String s = (String)ds.nextToken();
predictor.eval(s.substring(0, s.lastIndexOf(' ')),real);
}
return;
}
catch (Exception e) {
System.out.println("Unable to read from specified file: "+modelFileName);
System.out.println();
e.printStackTrace();
}
}
}
}