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/*
* 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.tika.language;
// JDK imports
import static java.nio.charset.StandardCharsets.UTF_8;
import java.io.BufferedInputStream;
import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.io.OutputStream;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Date;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import org.apache.tika.exception.TikaException;
/**
* This class runs a ngram analysis over submitted text, results might be used
* for automatic language identification.
*
* The similarity calculation is at experimental level. You have been warned.
*
* Methods are provided to build new NGramProfiles profiles.
*
* @author Sami Siren
* @author Jerome Charron - http://frutch.free.fr/
* @deprecated
*/
@Deprecated
public class LanguageProfilerBuilder {
// public static final Log LOG =
// LogFactory.getLog(LanguageProfilerBuilder.class);
/** The minimum length allowed for a ngram. */
final static int ABSOLUTE_MIN_NGRAM_LENGTH = 3; /* was 1 */
/** The maximum length allowed for a ngram. */
final static int ABSOLUTE_MAX_NGRAM_LENGTH = 3; /* was 4 */
/** The default min length of ngram */
final static int DEFAULT_MIN_NGRAM_LENGTH = 3;
/** The default max length of ngram */
final static int DEFAULT_MAX_NGRAM_LENGTH = 3;
/** The ngram profile file extension */
final static String FILE_EXTENSION = "ngp";
/** The profile max size (number of ngrams of the same size) */
final static int MAX_SIZE = 1000;
/** separator char */
final static char SEPARATOR = '_';
/** The String form of the separator char */
private final static String SEP_CHARSEQ = new String(
new char[] { SEPARATOR });
/** The profile's name */
private String name = null;
/** The NGrams of this profile sorted on the number of occurrences */
private List sorted = null;
/** The min length of ngram */
private int minLength = DEFAULT_MIN_NGRAM_LENGTH;
/** The max length of ngram */
private int maxLength = DEFAULT_MAX_NGRAM_LENGTH;
/** The total number of ngrams occurences */
private int[] ngramcounts = null;
/** An index of the ngrams of the profile */
private Map ngrams = null;
/** A StringBuffer used during analysis */
private QuickStringBuffer word = new QuickStringBuffer();
/**
* Constructs a new ngram profile
*
* @param name is the name of the profile
* @param minlen is the min length of ngram sequences
* @param maxlen is the max length of ngram sequences
*/
public LanguageProfilerBuilder(String name, int minlen, int maxlen) {
// TODO: Compute the initial capacity using minlen and maxlen.
this.ngrams = new HashMap(4000);
this.minLength = minlen;
this.maxLength = maxlen;
this.name = name;
}
/**
* Constructs a new ngram profile where minlen=3, maxlen=3
*
* @param name is a name of profile, usually two length string
* @since Tika 1.0
*/
public LanguageProfilerBuilder(String name) {
this.ngrams = new HashMap(4000);
this.minLength = ABSOLUTE_MIN_NGRAM_LENGTH;
this.maxLength = ABSOLUTE_MAX_NGRAM_LENGTH;
this.name = name;
}
/**
* @return Returns the name.
*/
public String getName() {
return name;
}
// This method was commented because it depends on org.apache.lucene.analysis.Token
// that is not a part of the Tika
// /**
// * Adds ngrams from a token to this profile
// *
// * @param t is the Token to be added
// */
// public void add(Token t) {
// add(new StringBuffer().append(SEPARATOR)
// .append(t.term())
// .append(SEPARATOR));
// }
/**
* Adds ngrams from a single word to this profile
*
* @param word is the word to add
*/
public void add(StringBuffer word) {
for (int i = minLength; (i <= maxLength) && (i < word.length()); i++) {
add(word, i);
}
}
/**
* Adds the last NGrams from the specified word.
*/
private void add(QuickStringBuffer word) {
int wlen = word.length();
if (wlen >= minLength) {
int max = Math.min(maxLength, wlen);
for (int i = minLength; i <= max; i++) {
add(word.subSequence(wlen - i, wlen));
}
}
}
/**
* Adds ngrams from a single word in this profile
*
* @param cs char sequence to add
*/
private void add(CharSequence cs) {
if (cs.equals(SEP_CHARSEQ)) {
return;
}
NGramEntry nge = ngrams.get(cs);
if (nge == null) {
nge = new NGramEntry(cs);
ngrams.put(cs, nge);
}
nge.inc();
}
/**
* Analyzes a piece of text
*
* @param text
* the text to be analyzed
*/
public void analyze(StringBuilder text) {
if (ngrams != null) {
ngrams.clear();
sorted = null;
ngramcounts = null;
}
word.clear().append(SEPARATOR);
for (int i = 0; i < text.length(); i++) {
char c = Character.toLowerCase(text.charAt(i));
if (Character.isLetter(c)) {
add(word.append(c));
} else {
// found word boundary
if (word.length() > 1) {
// we have a word!
add(word.append(SEPARATOR));
word.clear().append(SEPARATOR);
}
}
}
if (word.length() > 1) {
// we have a word!
add(word.append(SEPARATOR));
}
normalize();
}
/**
* @param word
* @param n sequence length
*/
private void add(StringBuffer word, int n) {
for (int i = 0; i <= word.length() - n; i++) {
add(word.subSequence(i, i + n));
}
}
/**
* Normalizes the profile (calculates the ngrams frequencies)
*/
protected void normalize() {
NGramEntry e = null;
Iterator i = ngrams.values().iterator();
// Calculates ngram count if not already done
if (ngramcounts == null) {
ngramcounts = new int[maxLength + 1];
while (i.hasNext()) {
e = i.next();
ngramcounts[e.size()] += e.count;
}
}
i = ngrams.values().iterator();
while (i.hasNext()) {
e = i.next();
e.frequency = (float) e.count / (float) ngramcounts[e.size()];
}
}
/**
* Returns a sorted list of ngrams (sort done by 1. frequency 2. sequence)
*
* @return sorted vector of ngrams
*/
public List getSorted() {
// make sure sorting is done only once
if (sorted == null) {
sorted = new ArrayList(ngrams.values());
Collections.sort(sorted);
// trim at NGRAM_LENGTH entries
if (sorted.size() > MAX_SIZE) {
sorted = sorted.subList(0, MAX_SIZE);
}
}
return sorted;
}
// Inherited JavaDoc
public String toString() {
StringBuffer s = new StringBuffer().append("NGramProfile: ")
.append(name).append("\n");
Iterator i = getSorted().iterator();
while (i.hasNext()) {
NGramEntry entry = i.next();
s.append("[").append(entry.seq).append("/").append(entry.count)
.append("/").append(entry.frequency).append("]\n");
}
return s.toString();
}
/**
* Calculates a score how well NGramProfiles match each other
*
* @param another
* ngram profile to compare against
* @return similarity 0=exact match
* @throws TikaException
* if could not calculate a score
*/
public float getSimilarity(LanguageProfilerBuilder another)
throws TikaException {
float sum = 0;
try {
Iterator i = another.getSorted().iterator();
while (i.hasNext()) {
NGramEntry other = i.next();
if (ngrams.containsKey(other.seq)) {
sum += Math.abs((other.frequency - ngrams.get(other.seq).frequency)) / 2;
} else {
sum += other.frequency;
}
}
i = getSorted().iterator();
while (i.hasNext()) {
NGramEntry other = i.next();
if (another.ngrams.containsKey(other.seq)) {
sum += Math.abs((other.frequency - another.ngrams
.get(other.seq).frequency)) / 2;
} else {
sum += other.frequency;
}
}
} catch (Exception e) {
throw new TikaException("Could not calculate a score how well NGramProfiles match each other");
}
return sum;
}
/**
* Loads a ngram profile from an InputStream (assumes UTF-8 encoded content)
*
* @param is the InputStream to read
*/
public void load(InputStream is) throws IOException {
ngrams.clear();
ngramcounts = new int[maxLength + 1];
BufferedReader reader = new BufferedReader(new InputStreamReader(is, UTF_8));
String line = null;
while ((line = reader.readLine()) != null) {
// # starts a comment line
if (line.charAt(0) != '#') {
int spacepos = line.indexOf(' ');
String ngramsequence = line.substring(0, spacepos).trim();
int len = ngramsequence.length();
if ((len >= minLength) && (len <= maxLength)) {
int ngramcount = Integer.parseInt(line.substring(spacepos + 1));
NGramEntry en = new NGramEntry(ngramsequence, ngramcount);
ngrams.put(en.getSeq(), en);
ngramcounts[len] += ngramcount;
}
}
}
normalize();
}
/**
* Creates a new Language profile from (preferably quite large - 5-10k of
* lines) text file
*
* @param name to be given for the profile
* @param is a stream to be read
* @param encoding is the encoding of stream
*
* @throws TikaException if could not create a language profile
*
*/
public static LanguageProfilerBuilder create(String name, InputStream is, String encoding) throws TikaException {
LanguageProfilerBuilder newProfile = new LanguageProfilerBuilder(name,
ABSOLUTE_MIN_NGRAM_LENGTH, ABSOLUTE_MAX_NGRAM_LENGTH);
BufferedInputStream bis = new BufferedInputStream(is);
byte buffer[] = new byte[4096];
StringBuilder text = new StringBuilder();
int len;
try {
while ((len = bis.read(buffer)) != -1) {
text.append(new String(buffer, 0, len, encoding));
}
} catch (IOException e) {
throw new TikaException("Could not create profile, " + e.getMessage());
}
newProfile.analyze(text);
return newProfile;
}
/**
* Writes NGramProfile content into OutputStream, content is outputted with
* UTF-8 encoding
*
* @param os the Stream to output to
*
* @throws IOException
*/
public void save(OutputStream os) throws IOException {
os.write(("# NgramProfile generated at " + new Date() +
" for Apache Tika Language Identification\n").getBytes(UTF_8));
// And then each ngram
// First dispatch ngrams in many lists depending on their size
// (one list for each size, in order to store MAX_SIZE ngrams for each
// size of ngram)
List list = new ArrayList();
List sublist = new ArrayList();
NGramEntry[] entries = ngrams.values().toArray(
new NGramEntry[ngrams.size()]);
for (int i = minLength; i <= maxLength; i++) {
for (int j = 0; j < entries.length; j++) {
if (entries[j].getSeq().length() == i) {
sublist.add(entries[j]);
}
}
Collections.sort(sublist);
if (sublist.size() > MAX_SIZE) {
sublist = sublist.subList(0, MAX_SIZE);
}
list.addAll(sublist);
sublist.clear();
}
for (int i = 0; i < list.size(); i++) {
NGramEntry e = list.get(i);
String line = e.toString() + " " + e.getCount() + "\n";
os.write(line.getBytes(UTF_8));
}
os.flush();
}
/**
* main method used for testing only
*
* @param args
*/
public static void main(String args[]) {
// -create he sample_he.txt utf-8
String usage = "Usage: NGramProfile "
+ "[-create profilename filename encoding] "
+ "[-similarity file1 file2] "
+ "[-score profile-name filename encoding]";
int command = 0;
final int CREATE = 1;
final int SIMILARITY = 2;
final int SCORE = 3;
String profilename = "";
String filename = "";
String filename2 = "";
String encoding = "";
if (args.length == 0) {
System.err.println(usage);
System.exit(-1);
}
for (int i = 0; i < args.length; i++) { // parse command line
if (args[i].equals("-create")) { // found -create option
command = CREATE;
profilename = args[++i];
filename = args[++i];
encoding = args[++i];
}
if (args[i].equals("-similarity")) { // found -similarity option
command = SIMILARITY;
filename = args[++i];
filename2 = args[++i];
encoding = args[++i];
}
if (args[i].equals("-score")) { // found -Score option
command = SCORE;
profilename = args[++i];
filename = args[++i];
encoding = args[++i];
}
}
try {
switch (command) {
case CREATE:
File f = new File(filename);
FileInputStream fis = new FileInputStream(f);
LanguageProfilerBuilder newProfile = LanguageProfilerBuilder
.create(profilename, fis, encoding);
fis.close();
f = new File(profilename + "." + FILE_EXTENSION);
FileOutputStream fos = new FileOutputStream(f);
newProfile.save(fos);
System.out.println("new profile " + profilename + "."
+ FILE_EXTENSION + " was created.");
break;
case SIMILARITY:
f = new File(filename);
fis = new FileInputStream(f);
newProfile = LanguageProfilerBuilder.create(filename, fis,
encoding);
newProfile.normalize();
f = new File(filename2);
fis = new FileInputStream(f);
LanguageProfilerBuilder newProfile2 = LanguageProfilerBuilder
.create(filename2, fis, encoding);
newProfile2.normalize();
System.out.println("Similarity is "
+ newProfile.getSimilarity(newProfile2));
break;
case SCORE:
f = new File(filename);
fis = new FileInputStream(f);
newProfile = LanguageProfilerBuilder.create(filename, fis,
encoding);
f = new File(profilename + "." + FILE_EXTENSION);
fis = new FileInputStream(f);
LanguageProfilerBuilder compare = new LanguageProfilerBuilder(
profilename, DEFAULT_MIN_NGRAM_LENGTH,
DEFAULT_MAX_NGRAM_LENGTH);
compare.load(fis);
System.out.println("Score is "
+ compare.getSimilarity(newProfile));
break;
}
} catch (Exception e) {
e.printStackTrace();
// throw new TikaException("");
}
}
/**
* Inner class that describes a NGram
*/
static class NGramEntry implements Comparable {
/** The NGRamProfile this NGram is related to */
private LanguageProfilerBuilder profile = null;
/** The sequence of characters of the ngram */
CharSequence seq = null;
/** The number of occurences of this ngram in its profile */
private int count = 0;
/** The frequency of this ngram in its profile */
private float frequency = 0.0F;
/**
* Constructs a new NGramEntry
*
* @param seq is the sequence of characters of the ngram
*/
public NGramEntry(CharSequence seq) {
this.seq = seq;
}
/**
* Constructs a new NGramEntry
*
* @param seq is the sequence of characters of the ngram
* @param count is the number of occurrences of this ngram
*/
public NGramEntry(String seq, int count) {
this.seq = new StringBuffer(seq).subSequence(0, seq.length());
this.count = count;
}
/**
* Returns the number of occurrences of this ngram in its profile
*
* @return the number of occurrences of this ngram in its profile
*/
public int getCount() {
return count;
}
/**
* Returns the frequency of this ngram in its profile
*
* @return the frequency of this ngram in its profile
*/
public float getFrequency() {
return frequency;
}
/**
* Returns the sequence of characters of this ngram
*
* @return the sequence of characters of this ngram
*/
public CharSequence getSeq() {
return seq;
}
/**
* Returns the size of this ngram
*
* @return the size of this ngram
*/
public int size() {
return seq.length();
}
// Inherited JavaDoc
public int compareTo(NGramEntry ngram) {
int diff = Float.compare(ngram.getFrequency(), frequency);
if (diff != 0) {
return diff;
} else {
return (toString().compareTo(ngram.toString()));
}
}
/**
* Increments the number of occurrences of this ngram.
*/
public void inc() {
count++;
}
/**
* Associated a profile to this ngram
*
* @param profile
* is the profile associated to this ngram
*/
public void setProfile(LanguageProfilerBuilder profile) {
this.profile = profile;
}
/**
* Returns the profile associated to this ngram
*
* @return the profile associated to this ngram
*/
public LanguageProfilerBuilder getProfile() {
return profile;
}
// Inherited JavaDoc
public String toString() {
return seq.toString();
}
// Inherited JavaDoc
public int hashCode() {
return seq.hashCode();
}
// Inherited JavaDoc
public boolean equals(Object obj) {
NGramEntry ngram = null;
try {
ngram = (NGramEntry) obj;
return ngram.seq.equals(seq);
} catch (Exception e) {
return false;
}
}
}
private static class QuickStringBuffer implements CharSequence {
private char value[];
private int count;
QuickStringBuffer() {
this(16);
}
QuickStringBuffer(char[] value) {
this.value = value;
count = value.length;
}
QuickStringBuffer(int length) {
value = new char[length];
}
QuickStringBuffer(String str) {
this(str.length() + 16);
append(str);
}
public int length() {
return count;
}
private void expandCapacity(int minimumCapacity) {
int newCapacity = (value.length + 1) * 2;
if (newCapacity < 0) {
newCapacity = Integer.MAX_VALUE;
} else if (minimumCapacity > newCapacity) {
newCapacity = minimumCapacity;
}
char newValue[] = new char[newCapacity];
System.arraycopy(value, 0, newValue, 0, count);
value = newValue;
}
QuickStringBuffer clear() {
count = 0;
return this;
}
public char charAt(int index) {
return value[index];
}
QuickStringBuffer append(String str) {
if (str == null) {
str = String.valueOf(str);
}
int len = str.length();
int newcount = count + len;
if (newcount > value.length) {
expandCapacity(newcount);
}
str.getChars(0, len, value, count);
count = newcount;
return this;
}
QuickStringBuffer append(char c) {
int newcount = count + 1;
if (newcount > value.length) {
expandCapacity(newcount);
}
value[count++] = c;
return this;
}
public CharSequence subSequence(int start, int end) {
return new String(value, start, end - start);
}
public String toString() {
return new String(this.value);
}
}
}
