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ModKN.cs
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ModKN.cs
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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using Master.Utility;
namespace Master.Algorithms
{
/// <summary>
/// Implementation of modified Kneser-Ney smoothing algorithm
/// Author: Tomislav
/// </summary>
class ModKN : ISmoothingAlgorithm
{
private int order;
private Dictionary<List<int>, int> sequenceToInt;
private Mapper sequenceMap;
private List<Dictionary<List<int>, int>> numerators;
private List<Dictionary<List<int>, int>> denominators;
private List<Dictionary<List<int>, Dictionary<int, int>>> notZero;
private List<int[]> countOfCounts;
private List<double[]> discounts;
private Dictionary<int, int> unigramDict;
double UnigramTokenCount = 0;
private List<Dictionary<List<int>, double[]>> ngramProbs;
/// <summary>
/// Default constructor
/// </summary>
/// <param name="order">Max N-gram order</param>
/// <param name="sequenceToInt">N-grams found in input sequence</param>
/// <param name="sequenceMap">Sequence to int map </param>
public ModKN(int order, Dictionary<List<int>, int> sequenceToInt, Mapper sequenceMap) {
if (order > 3 || order < 2) {
throw new NLPException("Order must be 2 or 3");
}
this.order = order;
this.sequenceToInt = sequenceToInt;
this.sequenceMap = sequenceMap;
this.ngramProbs = new List<Dictionary<List<int>, double[]>>();
numerators = new List<Dictionary<List<int>, int>>();
denominators = new List<Dictionary<List<int>, int>>();
notZero = new List<Dictionary<List<int>, Dictionary<int, int>>>();
unigramDict = new Dictionary<int, int>();
for (int i = 0; i < order - 1; i++) {
numerators.Add(new Dictionary<List<int>, int>(new ListComparer<int>()));
denominators.Add(new Dictionary<List<int>, int>(new ListComparer<int>()));
notZero.Add(new Dictionary<List<int>, Dictionary<int, int>>(new ListComparer<int>()));
}
countOfCounts = new List<int[]>();
for (int i = 0; i < order; i++) {
int[] entry = new int[] { 0, 0, 0, 0 };
countOfCounts.Add(entry);
}
discounts = new List<double[]>();
for (int i = 0; i < order - 1; i++) {
double[] entry = new double[] { 0, 0, 0};
discounts.Add(entry);
}
}
/// <summary>
/// Method starts calculations
/// </summary>
public void calculate() {
foreach (KeyValuePair<List<int>, int> pair in sequenceToInt) {
List<int> key = pair.Key;
int ngramCount = pair.Value;
if (key.Count > 1 && key[1] == -1) {
List<int> subList = new List<int>(key);
subList.RemoveAt(0);
knModCount(subList, 0, ngramCount);
}
else {
int level = key.Count == 3 ? 1 : 0;
knModCount(key, level, ngramCount);
}
}
calcCountOfCounts();
calcDiscounts();
calcNgramProbs();
}
/// <summary>
/// Method recursively calculates lower order N-grams, numerators
/// and denominators
/// </summary>
/// <param name="ngram">N-gram</param>
/// <param name="i">Recursion level</param>
/// <param name="ngramCount">N-gram frequency</param>
private void knModCount(List<int> ngram, int i, int ngramCount, bool flag = false) {
List<int> numer = ngram;
List<int> denom = new List<int>(numer);
List<int> subList = new List<int>(numer);
denom.RemoveAt(ngram.Count - 1);
subList.RemoveAt(0);
Dict.addToDict(numerators[i], numer, ngramCount);
Dict.addToDict(denominators[i], denom, ngramCount);
if (!notZero[i].ContainsKey(denom)) {
Dictionary<int, int> dict = new Dictionary<int, int>();
dict.Add(ngram[ngram.Count - 1], ngramCount);
notZero[i].Add(denom, dict);
}
else {
Dict.addToDict(notZero[i][denom], ngram[ngram.Count - 1], ngramCount);
}
if (numerators[i][numer] == ngramCount) {
if (i > 0) {
knModCount(subList, i - 1, 1);
}
else {
int unigram = ngram[ngram.Count - 1];
Dict.addToDict(unigramDict, unigram, 1);
UnigramTokenCount++;
}
}
}
/// <summary>
/// Method calculates N-gram count of counts
/// </summary>
private void calcCountOfCounts() {
foreach (KeyValuePair<int, int> pair in unigramDict) {
if (pair.Value <= 4) {
countOfCounts[0][pair.Value - 1] += 1;
}
}
for (int i = 0; i < numerators.Count; i++) {
foreach (KeyValuePair<List<int>, int> pair in numerators[i]) {
if (pair.Value <= 4) {
countOfCounts[i + 1][pair.Value - 1] += 1;
}
}
}
}
/// <summary>
/// Method calculates discounts
/// </summary>
private void calcDiscounts() {
for (int i = 0; i < order - 1; i++) {
double Y = countOfCounts[i + 1][0] / (double)(countOfCounts[i + 1][0] + 2 * countOfCounts[i + 1][1]);
for (int j = 0; j < 3; j++) {
if (countOfCounts[i + 1][j] > 0) {
discounts[i][j] = (j + 1) - (j + 2) * Y * (countOfCounts[i + 1][j + 1] / (double)countOfCounts[i + 1][j]);
}
else {
discounts[i][j] = j + 1;
}
}
}
}
/// <summary>
/// Method calculates all N-grams absolute discounting probabilities
/// </summary>
public void calcNgramProbs() {
ngramProbs.Add(new Dictionary<List<int>, double[]>(new ListComparer<int>()));
List<int> key = new List<int>() { -1 };
double discount = getDiscount(0, key);
double lamda = discount / (double)denominators[0][key];
ngramProbs[0].Add(key, new double[] { 0, lamda });
var list = unigramDict.Keys.ToList();
list.Sort();
foreach (var entry in list) {
if (entry == -2) {
ngramProbs[0].Add(new List<int> { -2 }, new double[] { unigramDict[entry] / UnigramTokenCount, 0 });
continue;
}
key = new List<int>() { entry };
discount = getDiscount(0, key);
lamda = discount / (double)denominators[0][key];
ngramProbs[0].Add(key, new double[] { unigramDict[entry] / UnigramTokenCount, lamda });
}
for (int i = 0; i < order - 2; i++) {
ngramProbs.Add(new Dictionary<List<int>, double[]>(new ListComparer<int>()));
foreach (KeyValuePair<List<int>, int> pair in numerators[0]) {
List<int> entryKey = pair.Key;
if (entryKey[entryKey.Count - 1] == -2) {
ngramProbs[i + 1].Add(entryKey, new double[] { calcProbability(entryKey), Double.NaN });
continue;
}
discount = getDiscount(i + 1, entryKey);
lamda = discount / (double)denominators[i + 1][entryKey];
ngramProbs[i + 1].Add(entryKey, new double[] { calcProbability(entryKey), lamda });
}
}
ngramProbs.Add(new Dictionary<List<int>, double[]>(new ListComparer<int>()));
foreach (KeyValuePair<List<int>, int> pair in numerators[order - 2]) {
List<int> entryKey = pair.Key;
ngramProbs[order - 1].Add(entryKey, new double[] { calcProbability(entryKey), Double.NaN });
}
}
/// <summary>
/// Method calculates single N-gram probability
/// </summary>
/// <param name="ngram">N-gram</param>
/// <returns>N-gram probability</returns>
private double calcProbability(List<int> ngram) {
double prob = 0;
double[] probs = new double[ngram.Count];
for (int i = 0; i < ngram.Count; i++) {
probs[i] = Double.MinValue;
}
if (ngram[ngram.Count - 1] != -1) {
probs[0] = unigramDict[ngram[ngram.Count - 1]] / UnigramTokenCount;
}
for (int i = 0; i < ngram.Count - 1; i++) {
List<int> denom = new List<int>();
List<int> numer = new List<int>();
for (int j = ngram.Count - (i + 2); j < ngram.Count - 1; j++) {
denom.Add(ngram[j]);
numer.Add(ngram[j]);
}
numer.Add(ngram[ngram.Count - 1]);
if (denominators[i].ContainsKey(denom)) {
int count = numerators[i][numer];
int discountNum = count < 3 ? count : 3;
probs[i + 1] = (count - discounts[i][discountNum - 1]) / (double)denominators[i][denom];
double discount = getDiscount(i, denom);
double lamda = discount / (double)denominators[i][denom];
probs[i + 1] = probs[i + 1] + lamda * probs[i];
prob = probs[i + 1];
}
}
if (Math.Abs(prob - 0) <= 1e-15) {
prob = probs[0];
}
return prob;
}
/// <summary>
/// Method returns discount value for given N-gram
/// </summary>
/// <param name="order">N-gram order</param>
/// <param name="ngram">N-gram</param>
/// <returns>Discount value for given N-gram</returns>
private double getDiscount(int order, List<int> ngram) {
int[] counts = new int[] { 0, 0, 0 };
foreach (KeyValuePair<int, int> pair in notZero[order][ngram]) {
if (pair.Value == 1) {
counts[0]++;
}
else if (pair.Value == 2) {
counts[1]++;
}
else {
counts[2]++;
}
}
double discount = 0;
for (int i = 0; i < 3; i++) {
discount += discounts[order][i] * counts[i];
}
return discount;
}
/// <summary>
/// Method shows results of calculations on standard output
/// </summary>
public void showCalculations() {
Console.WriteLine("1-grams= " + (unigramDict.Count + 1));
for (int i = 0; i < order - 1; i++) {
Console.WriteLine((i + 2) + "-grams" + "= " + numerators[i].Count);
}
for (int i = 0; i < order; i++) {
Console.WriteLine("\n"+(i+1)+"-grams:");
foreach (KeyValuePair<List<int>, double[]> pair in ngramProbs[i]) {
List<int> key = pair.Key;
double[] values = pair.Value;
String keyString = "";
for (int j = 0; j < key.Count; j++) {
keyString += sequenceMap.getKey(key[j]) + " ";
}
Console.WriteLine(String.Format("{0,10:F6}", values[0]) + "\t"
+ keyString + "\t" + (Double.IsNaN(values[1]) ? "" : String.Format("{0,10:F6}", values[1])));
}
}
}
/// <summary>
/// Method returns all N-grams modified Kneser-Ney smoothed probabilities
/// </summary>
/// <returns>N-grams modified Kneser-Ney smoothed probabilities</returns>
public List<Dictionary<List<int>, double[]>> getNgramProbs() {
return this.ngramProbs;
}
}
}