/**
* 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.mahout.classifier.naivebayes;
import java.io.IOException;
import java.util.Collection;
import java.util.HashMap;
import java.util.Map;
import java.util.regex.Pattern;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.SequenceFile;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.mahout.classifier.naivebayes.training.ThetaMapper;
import org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob;
import org.apache.mahout.common.HadoopUtil;
import org.apache.mahout.common.Pair;
import org.apache.mahout.common.iterator.sequencefile.PathFilters;
import org.apache.mahout.common.iterator.sequencefile.PathType;
import org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterable;
import org.apache.mahout.common.iterator.sequencefile.SequenceFileIterable;
import org.apache.mahout.math.Matrix;
import org.apache.mahout.math.SparseMatrix;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.VectorWritable;
import org.apache.mahout.math.map.OpenObjectIntHashMap;
import com.google.common.base.Preconditions;
import com.google.common.collect.Maps;
import com.google.common.collect.Sets;
import com.google.common.io.Closeables;
public final class BayesUtils {
private static final Pattern SLASH = Pattern.compile("/");
private BayesUtils() {}
public static NaiveBayesModel readModelFromDir(Path base, Configuration conf) {
float alphaI = conf.getFloat(ThetaMapper.ALPHA_I, 1.0f);
// read feature sums and label sums
Vector scoresPerLabel = null;
Vector scoresPerFeature = null;
for (Pair<Text,VectorWritable> record : new SequenceFileDirIterable<Text, VectorWritable>(
new Path(base, TrainNaiveBayesJob.WEIGHTS), PathType.LIST, PathFilters.partFilter(), conf)) {
String key = record.getFirst().toString();
VectorWritable value = record.getSecond();
if (key.equals(TrainNaiveBayesJob.WEIGHTS_PER_FEATURE)) {
scoresPerFeature = value.get();
} else if (key.equals(TrainNaiveBayesJob.WEIGHTS_PER_LABEL)) {
scoresPerLabel = value.get();
}
}
Preconditions.checkNotNull(scoresPerFeature);
Preconditions.checkNotNull(scoresPerLabel);
Matrix scoresPerLabelAndFeature = new SparseMatrix(scoresPerLabel.size(), scoresPerFeature.size());
for (Pair<IntWritable,VectorWritable> entry : new SequenceFileDirIterable<IntWritable,VectorWritable>(
new Path(base, TrainNaiveBayesJob.SUMMED_OBSERVATIONS), PathType.LIST, PathFilters.partFilter(), conf)) {
scoresPerLabelAndFeature.assignRow(entry.getFirst().get(), entry.getSecond().get());
}
Vector perlabelThetaNormalizer = scoresPerLabel.like();
/* for (Pair<Text,VectorWritable> entry : new SequenceFileDirIterable<Text,VectorWritable>(
new Path(base, TrainNaiveBayesJob.THETAS), PathType.LIST, PathFilters.partFilter(), conf)) {
if (entry.getFirst().toString().equals(TrainNaiveBayesJob.LABEL_THETA_NORMALIZER)) {
perlabelThetaNormalizer = entry.getSecond().get();
}
}
Preconditions.checkNotNull(perlabelThetaNormalizer);
*/
return new NaiveBayesModel(scoresPerLabelAndFeature, scoresPerFeature, scoresPerLabel, perlabelThetaNormalizer,
alphaI);
}
/** Write the list of labels into a map file */
public static int writeLabelIndex(Configuration conf, Iterable<String> labels, Path indexPath)
throws IOException {
FileSystem fs = FileSystem.get(indexPath.toUri(), conf);
SequenceFile.Writer writer = new SequenceFile.Writer(fs, conf, indexPath, Text.class, IntWritable.class);
int i = 0;
try {
for (String label : labels) {
writer.append(new Text(label), new IntWritable(i++));
}
} finally {
Closeables.close(writer, false);
}
return i;
}
public static int writeLabelIndex(Configuration conf, Path indexPath,
Iterable<Pair<Text,IntWritable>> labels) throws IOException {
FileSystem fs = FileSystem.get(indexPath.toUri(), conf);
SequenceFile.Writer writer = new SequenceFile.Writer(fs, conf, indexPath, Text.class, IntWritable.class);
Collection<String> seen = Sets.newHashSet();
int i = 0;
try {
for (Object label : labels) {
String theLabel = SLASH.split(((Pair<?, ?>) label).getFirst().toString())[1];
if (!seen.contains(theLabel)) {
writer.append(new Text(theLabel), new IntWritable(i++));
seen.add(theLabel);
}
}
} finally {
Closeables.close(writer, false);
}
return i;
}
public static Map<Integer, String> readLabelIndex(Configuration conf, Path indexPath) {
Map<Integer, String> labelMap = new HashMap<Integer, String>();
for (Pair<Text, IntWritable> pair : new SequenceFileIterable<Text, IntWritable>(indexPath, true, conf)) {
labelMap.put(pair.getSecond().get(), pair.getFirst().toString());
}
return labelMap;
}
public static OpenObjectIntHashMap<String> readIndexFromCache(Configuration conf) throws IOException {
OpenObjectIntHashMap<String> index = new OpenObjectIntHashMap<String>();
for (Pair<Writable,IntWritable> entry
: new SequenceFileIterable<Writable,IntWritable>(HadoopUtil.getSingleCachedFile(conf), conf)) {
index.put(entry.getFirst().toString(), entry.getSecond().get());
}
return index;
}
public static Map<String,Vector> readScoresFromCache(Configuration conf) throws IOException {
Map<String,Vector> sumVectors = Maps.newHashMap();
for (Pair<Text,VectorWritable> entry
: new SequenceFileDirIterable<Text,VectorWritable>(HadoopUtil.getSingleCachedFile(conf),
PathType.LIST, PathFilters.partFilter(), conf)) {
sumVectors.put(entry.getFirst().toString(), entry.getSecond().get());
}
return sumVectors;
}
}