| /* |
| * 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 org.apache.opennlp.ml.maxent; |
| |
| import java.io.File; |
| import java.io.FileReader; |
| import java.text.DecimalFormat; |
| |
| import org.apache.opennlp.ml.model.Event; |
| import org.apache.opennlp.ml.model.EventStream; |
| import org.apache.opennlp.ml.model.GenericModelReader; |
| import org.apache.opennlp.ml.model.MaxentModel; |
| import org.apache.opennlp.ml.model.RealValueFileEventStream; |
| |
| /** |
| * Test the model on some input. |
| */ |
| public class ModelApplier { |
| MaxentModel _model; |
| ContextGenerator _cg = new BasicContextGenerator(","); |
| int counter = 1; |
| |
| // The format for printing percentages |
| public static final DecimalFormat ROUNDED_FORMAT = new DecimalFormat("0.000"); |
| |
| public ModelApplier(MaxentModel m) { |
| _model = m; |
| } |
| |
| private void eval(Event event) { |
| eval(event, false); |
| } |
| |
| private void eval(Event event, boolean real) { |
| |
| String outcome = event.getOutcome(); // Is ignored |
| String[] context = event.getContext(); |
| |
| double[] ocs; |
| if (!real) { |
| ocs = _model.eval(context); |
| } else { |
| float[] values = RealValueFileEventStream.parseContexts(context); |
| ocs = _model.eval(context, values); |
| } |
| |
| int numOutcomes = ocs.length; |
| DoubleStringPair[] result = new DoubleStringPair[numOutcomes]; |
| for (int i=0; i<numOutcomes; i++) |
| result[i] = new DoubleStringPair(ocs[i], _model.getOutcome(i)); |
| |
| java.util.Arrays.sort(result); |
| |
| // Print the most likely outcome first, down to the least likely. |
| for (int i=numOutcomes-1; i>=0; i--) |
| System.out.print(result[i].stringValue + " " + result[i].doubleValue + " "); |
| System.out.println(); |
| |
| } |
| |
| private static void usage() { |
| System.err.println("java ModelApplier [-real] modelFile dataFile"); |
| System.exit(1); |
| } |
| |
| /** |
| * Main method. Call as follows: |
| * <p> |
| * java ModelApplier modelFile dataFile |
| */ |
| public static void main(String[] args) { |
| |
| String dataFileName, modelFileName; |
| boolean real = false; |
| String type = "maxent"; |
| int ai = 0; |
| |
| if (args.length == 0) { |
| usage(); |
| } |
| |
| 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++; |
| } |
| |
| modelFileName = args[ai++]; |
| dataFileName = args[ai++]; |
| |
| ModelApplier predictor = null; |
| try { |
| MaxentModel m = new GenericModelReader(new File(modelFileName)).getModel(); |
| predictor = new ModelApplier(m); |
| } catch (Exception e) { |
| e.printStackTrace(); |
| System.exit(0); |
| } |
| |
| try { |
| EventStream es = new BasicEventStream(new PlainTextByLineDataStream( |
| new FileReader(new File(dataFileName))), ","); |
| |
| while (es.hasNext()) |
| predictor.eval(es.next(), real); |
| |
| return; |
| } catch (Exception e) { |
| System.out.println("Unable to read from specified file: " |
| + modelFileName); |
| System.out.println(); |
| e.printStackTrace(); |
| } |
| } |
| } |
| } |