public void BKTree_SearchHamming()
{
var tree = new BKTree(BKTree.DistanceMetric.Hamming);
tree.Add("taxi");
tree.Add("Test2");
tree.Add("Text");
tree.Add("Test");
tree.Add("tttt");
// Hamming distance Test = Test2 (compare the length of the shorter word)
var results = tree.Search("Test", 0);
var result_d0 = results.Count;
Assert.AreEqual(2, result_d0);
// te-t max. 1 diff : teSt teSt2 teXt
var result_d1 = tree.Search("te-t", 1).Count;
Assert.AreEqual(3, result_d1);
// test max. 2 diff : test test2 teXt tTTt
var result_d2 = tree.Search("test", 2).Count;
Assert.AreEqual(4, result_d2);
}
public void BKTreeShouldThrowUponAddingNullNode()
{
BKTree <ExampleMetric> tree = new BKTree <ExampleMetric>();
tree.Add(new ExampleMetric(1, new int[] { 100, 200, 300 }));
tree.Add(new ExampleMetric(2, new int[] { 110, 210, 310 }));
tree.Add(new ExampleMetric(3, new int[] { 130, 230, 330 }));
tree.Add(new ExampleMetric(4, new int[] { 140, 240, 340 }));
tree.Add(null);
}
public void Load(BKTree bk)
{
try
{
DataTable dt = GetDataTable();
int current, progress = -1;
int rowCount = dt.Rows.Count;
for (int i = rowCount - 1; i > -1; i--)
{
bk.Add(dt.Rows[i]["Ad"].ToString());
dt.Rows.RemoveAt(i);
current = 100 - i * 100 / rowCount;
if (current != progress)
{
progress = current;
afterProgress(progress);
}
}
}
catch (Exception ex)
{
throw new Exception("Ağaç oluşturulamadı. " + ex.Message);
}
}
public void with_max_distance_0_should_return_exact_matches_only()
{
var tree = new BKTree<string>(new DamerauLevenshteinStringDistanceMeasurer());
tree.Add(new BKTreeNode<string>("book")); //root
tree.Add(new BKTreeNode<string>("rook")); //1
tree.Add(new BKTreeNode<string>("nooks")); //2
tree.Add(new BKTreeNode<string>("boon")); //1->2
const string query = "boon";
const int maxDistance = 0;
var matches = tree.Matches(query, maxDistance);
Assert.That(matches.Count, Is.EqualTo(1));
Assert.That(matches.Single(), Is.EqualTo(query));
}
public void BKTreeImage_Constructor()
{
var index = new Images.ImageIndex.Index();
var image_hashs = new ConcurrentDictionary <String, List <String> >();
var hash_algo = Images.ImageHashAlgorithm.Average;
ulong ahash1 = 181;
ulong ahash2 = 171;
var hash1 = new List <String> {
ahash1.ToString(), "1111111111"
};
index.Add("Test", hash1);
var hash2 = new List <String> {
ahash2.ToString(), "1111111110"
};
index.Add("Test2", hash2);
var tree = new BKTree(hash_algo, index);
var id = index.Id("Test");
tree.Add(id);
id = index.Id("Test2");
tree.Add(id);
// using Average tree algo
Assert.AreEqual("Average", tree.ImageHashAlgo());
Assert.AreEqual(ahash1.ToString(), tree.GetImageHash("Test"));
Assert.AreEqual(ahash2.ToString(), tree.GetImageHash("Test2"));
Assert.AreEqual(100.0, tree.GetImageSimilarity("Test", "Test"));
Assert.AreNotEqual(100.0, tree.GetImageSimilarity("Test", "Test2"));
// using PerceptiveColor tree algo
hash_algo = Images.ImageHashAlgorithm.PerceptiveColor;
image_hashs = new ConcurrentDictionary <String, List <String> >();
index = new Images.ImageIndex.Index();
tree = new BKTree(hash_algo, index);
Assert.AreEqual("PerceptiveColor", tree.ImageHashAlgo());
}
/// <summary>
/// Add image id to BKTrees
/// </summary>
/// <param name="image_id"></param>
private void UpdateBKTrees(string image_id)
{
averagehash_bktree.Add(image_id);
blockhash_bktree.Add(image_id);
differencehash_bktree.Add(image_id);
perceptivehash_bktree.Add(image_id);
histogramhash_bktree.Add(image_id);
colorhash_bktree.Add(image_id);
image_count++;
}
public void BKTreeShouldFindBestNodeWithDistance()
{
BKTree <ExampleMetric> tree = new BKTree <ExampleMetric>();
ExampleMetric search = new ExampleMetric(new int[] { 365, 422, 399 });
ExampleMetric best = new ExampleMetric(4, new int[] { 400, 400, 400 });
tree.Add(new ExampleMetric(1, new int[] { 100, 100, 100 }));
tree.Add(new ExampleMetric(2, new int[] { 200, 200, 200 }));
tree.Add(new ExampleMetric(3, new int[] { 300, 300, 300 }));
tree.Add(best);
tree.Add(new ExampleMetric(5, new int[] { 500, 500, 500 }));
Tuple <ExampleMetric, int> result = tree.FindClosestElement(search);
Assert.AreEqual(58, DistanceMetric.CalculateLeeDistance(search.Data, best.Data));
Assert.AreEqual(58, result.Item2);
Assert.AreEqual(4, result.Item1.Id);
Assert.AreEqual(best.Data, result.Item1.Data);
}
public void BKTree_SearchLevenshtein()
{
var tree = new BKTree();
tree.Add("Test");
tree.Add("Test");
tree.Add("Test2");
tree.Add("taxi");
tree.Add("Text");
tree.Add("tttt");
// test -> test
var result_d0 = tree.Search("Test", 0).Count;
Assert.AreEqual(1, result_d0);
// te-t -> teSt teXt
var result_d1 = tree.Search("te-t", 1).Count;
Assert.AreEqual(2, result_d1);
// test -> test test2 teXt tTTt
var result_d2 = tree.Search("test", 2).Count;
Assert.AreEqual(4, result_d2);
}
public void LoadFromFile(BKTree bk)
{
try
{
string line;
System.IO.StreamReader file = new System.IO.StreamReader(@"C:\Users\Firat\Desktop\All.txt");
while ((line = file.ReadLine()) != null)
{
bk.Add(line);
}
file.Close();
}
catch (Exception ex)
{
throw new Exception("Ağaç oluşturulamadı. " + ex.Message);
}
}
/// <summary>
/// Translate a metatable into a BKTree for easier querying
/// </summary>
/// <param name="metatable"></param>
/// <returns></returns>
public static BKTree <FrameMetricWrapper> CreateBKTree(VideoFingerPrintDatabaseMetaTableWrapper metatable)
{
var tree = new BKTree <FrameMetricWrapper>();
foreach (VideoFingerPrintWrapper video in MetaTableUtils.EnumerateVideoFingerPrints(metatable))
{
foreach (FrameFingerPrintWrapper frame in video.FingerPrints)
{
tree.Add(new FrameMetricWrapper
{
Frame = frame,
Video = video,
});
}
}
return(tree);
}
public void BKTreeShouldQueryBestMatchesBelowGivenThreshold()
{
BKTree <ExampleMetric> tree = new BKTree <ExampleMetric>();
ExampleMetric search = new ExampleMetric(new int[] { 399, 400, 400 });
ExampleMetric best1 = new ExampleMetric(41, new int[] { 400, 400, 400 });
ExampleMetric best2 = new ExampleMetric(42, new int[] { 403, 403, 403 });
ExampleMetric best3 = new ExampleMetric(43, new int[] { 406, 406, 406 });
tree.Add(new ExampleMetric(1, new int[] { 100, 100, 100 }));
tree.Add(new ExampleMetric(2, new int[] { 200, 200, 200 }));
tree.Add(new ExampleMetric(3, new int[] { 300, 300, 300 }));
tree.Add(best1);
tree.Add(best2);
tree.Add(new ExampleMetric(5, new int[] { 500, 500, 500 }));
// Query for match within distance of 1 (best1 is only expected result)
IDictionary <ExampleMetric, int> results = tree.Query(search, 1);
Assert.AreEqual(1, DistanceMetric.CalculateLeeDistance(search.Data, best1.Data));
Assert.AreEqual(1, results.Values.ElementAt(0));
Assert.AreEqual(41, results.Keys.ElementAt(0).Id);
Assert.AreEqual(best1.Data, results.Keys.ElementAt(0).Data);
// Query for match within distance of 10 (best1 & best2 are expected results)
tree.Add(best3); // exercise adding another node after already queried
results = tree.Query(search, 10);
Assert.AreEqual(2, results.Count);
Assert.AreEqual(1, DistanceMetric.CalculateLeeDistance(search.Data, best1.Data));
Assert.AreEqual(10, DistanceMetric.CalculateLeeDistance(search.Data, best2.Data));
Assert.IsTrue(results.Contains(new KeyValuePair <ExampleMetric, int>(best1, 1)));
Assert.IsTrue(results.Contains(new KeyValuePair <ExampleMetric, int>(best2, 10)));
// Query for matches within distance of 20 (best1, best2 & best3 are expected results)
results = tree.Query(search, 20);
Assert.AreEqual(3, results.Count);
Assert.AreEqual(1, DistanceMetric.CalculateLeeDistance(search.Data, best1.Data));
Assert.AreEqual(10, DistanceMetric.CalculateLeeDistance(search.Data, best2.Data));
Assert.AreEqual(19, DistanceMetric.CalculateLeeDistance(search.Data, best3.Data));
Assert.IsTrue(results.Contains(new KeyValuePair <ExampleMetric, int>(best1, 1)));
Assert.IsTrue(results.Contains(new KeyValuePair <ExampleMetric, int>(best2, 10)));
Assert.IsTrue(results.Contains(new KeyValuePair <ExampleMetric, int>(best3, 19)));
}
public void BKTree_InsertionOrder()
{
int iterations = 10;
var tree = new BKTree();
string[] array = { "Test", "TeSt", "AaaA", "TaaT", "TTTT", "Text", "TEXt", " ", "--", ":-)" };
for (int i = 1; i <= iterations; i++)
{
Shuffle(array);
Console.WriteLine("BKTree insertion: v{0}", i);
foreach (string value in array)
{
tree.Add(value);
Console.WriteLine(value);
}
Console.WriteLine(" ");
var result_d0 = tree.Search("Test", 0).Count;
Assert.AreEqual(1, result_d0);
result_d0 = tree.Search("Text", 0).Count;
Assert.AreEqual(1, result_d0);
result_d0 = tree.Search("aaaa", 0).Count;
Assert.AreEqual(1, result_d0);
result_d0 = tree.Search("taat", 0).Count;
Assert.AreEqual(1, result_d0);
result_d0 = tree.Search("tttt", 0).Count;
Assert.AreEqual(1, result_d0);
result_d0 = tree.Search("no match", 0).Count;
Assert.AreEqual(0, result_d0);
}
}
public void BKTreeImage_Search()
{
var index = new Images.ImageIndex.Index();
var hash_algo = Images.ImageHashAlgorithm.Average;
ulong ahash1 = 181;
ulong ahash2 = 171;
var hash1 = new List <String> {
ahash1.ToString(), "1111111111"
};
index.Add("Test", hash1);
var hash2 = new List <String> {
ahash2.ToString(), "1111111110"
};
index.Add("Test2", hash2);
var hash3 = new List <String> {
ahash1.ToString(), "1111111111"
};
index.Add("Test3", hash3);
var hash4 = new List <String> {
ahash1.ToString(), "1111111111"
};
index.Add("Test", hash4);
var tree = new BKTree(hash_algo, index);
var id = index.Id("Test");
tree.Add(id);
id = index.Id("Test2");
tree.Add(id);
id = index.Id("Test3");
tree.Add(id);
// index= test test2 test3
Assert.AreEqual(3, index.FileCount());
Assert.AreEqual(ahash1.ToString(), tree.GetImageHash("Test"));
Assert.AreEqual(ahash2.ToString(), tree.GetImageHash("Test2"));
Assert.AreEqual(100.0, tree.GetImageSimilarity("Test", "Test"));
Assert.AreNotEqual(100.0, tree.GetImageSimilarity("Test", "Test2"));
// test -> test test3
var result_d0 = tree.Search("Test", 100).Count;
Assert.AreEqual(2, result_d0);
// test2 block hash = 171
Assert.AreEqual(ahash2.ToString(), tree.GetImageHash("Test2"));
// using Average tree algo
Assert.AreEqual("Average", tree.ImageHashAlgo());
}
public void BKTreeImage_NoDuplicate()
{
var index = new Images.ImageIndex.Index();
var hash_algo = Images.ImageHashAlgorithm.Block;
ulong ahash1 = 181;
ulong ahash2 = 281;
var hash1 = new List <String> {
ahash1.ToString(), "1111111111"
};
index.Add("Test", hash1);
var hash2 = new List <String> {
ahash2.ToString(), "1111111111"
};
index.Add("Test3", hash2);
var hash3 = new List <String> {
ahash1.ToString(), "1111110000"
};
index.Add("Test2", hash3);
var hash4 = new List <String> {
ahash2.ToString(), "000000000000000000000000"
};
index.Add("dup", hash4);
var tree = new BKTree(hash_algo, index);
var id = index.Id("Test");
tree.Add(id);
tree.Add(id);
id = index.Id("Test2");
tree.Add(id);
tree.Add(id);
id = index.Id("Test3");
tree.Add(id);
tree.Add(id);
id = index.Id("dup");
tree.Add(id);
tree.Add(id);
tree.Add(id);
// index= test test2 test3 dup
Assert.AreEqual(4, index.FileCount());
// test -> test test3
var result_d100 = tree.Search("Test", 100).Count;
Assert.AreEqual(2, result_d100);
// dup -> dup
var result_d100_2 = tree.Search("dup", 100).Count;
Assert.AreEqual(1, result_d100_2);
// dup block hash
Assert.AreEqual("000000000000000000000000", tree.GetImageHash("dup"));
// tree algo
Assert.AreEqual("Block", tree.ImageHashAlgo());
}
static void Main(string[] args)
{
Stopwatch stopWatch = new Stopwatch();
BKTree bkTree = new BKTree(Ratio, 8);
DBHelper dbHelper = new DBHelper();
TimeSpan timeSpan;
List <Match> result;
dbHelper.afterProgress += ProgressEvent;
Console.WriteLine("Veriler alınıyor...");
dbHelper.LoadFromFile(bkTree);
Console.WriteLine("\nHazır!");
dbHelper = null;
while (true)
{
GC.Collect();
try
{
string input = Console.ReadLine();
stopWatch.Start();
string[] array = input.Split(' ');
if (array.Length == 2 && array[0] == "add")
{
input = ValidString(String.Join("", array).Substring(3));
bkTree.Add(input);
bkTree.CheckAndRemoveCache(input);
Console.WriteLine("Eklendi: " + input);
}
else
{
result = bkTree.Search(ValidString(input));
if (result.Count > 0)
{
Console.WriteLine("Eşleşmeler: " + String.Join(", ", result.ToArray()));
Console.WriteLine("Döngü sayısı: " + bkTree.src.count);
}
else
{
Console.WriteLine("Eşleşme bulunamadı.");
}
}
stopWatch.Stop();
timeSpan = stopWatch.Elapsed;
Console.WriteLine("Süre: " + String.Format("{0:00}:{1:00}:{2:00}.{3:00}", timeSpan.Hours, timeSpan.Minutes, timeSpan.Seconds, timeSpan.Milliseconds / 10));
}
catch (Exception ex)
{
stopWatch.Stop();
Console.WriteLine("Hata Oluştu: " + ex.Message);
}
finally
{
stopWatch.Reset();
}
}
}
public void BKTree_NoDuplicate()
{
var tree = new BKTree();
tree.Add("AaaA");
tree.Add("TaaT");
tree.Add("TTTT");
tree.Add("Test");
tree.Add("Test");
tree.Add("TEST");
tree.Add("TeSt");
tree.Add("TeST");
tree.Add("Text");
tree.Add("Text");
tree.Add("TEXt");
var result_d0 = tree.Search("Test", 0).Count;
Assert.AreEqual(1, result_d0);
result_d0 = tree.Search("Text", 0).Count;
Assert.AreEqual(1, result_d0);
result_d0 = tree.Search("aaaa", 0).Count;
Assert.AreEqual(1, result_d0);
result_d0 = tree.Search("taat", 0).Count;
Assert.AreEqual(1, result_d0);
result_d0 = tree.Search("tttt", 0).Count;
Assert.AreEqual(1, result_d0);
result_d0 = tree.Search("zzzz", 0).Count;
Assert.AreEqual(0, result_d0);
}
static void Main(string[] args)
{
string line;
List <string> listnames = new List <string>();
List <string> listsurnames = new List <string>();
BKTree bk = new BKTree();
System.IO.StreamReader file1 = new System.IO.StreamReader(@"c:\names.txt");
while ((line = file1.ReadLine()) != null)
{
listnames.Add(line);
}
file1.Close();
System.IO.StreamReader file2 = new System.IO.StreamReader(@"c:\surnames.txt");
while ((line = file2.ReadLine()) != null)
{
listsurnames.Add(line);
}
file2.Close();
//foreach (string name in listnames){
// foreach (string surname in listsurnames)
// {
// listall.Add(name + surname);
// }
//}
for (int i = 0; i < 1000; i++)
{
for (int j = 0; j < 1000; j++)
{
bk.Add(listnames[i] + listsurnames[j]);
}
}
bk.Add("fetullahgülen");
bk.Add("firatkaptan");
Console.WriteLine("Ready!");
while (true)
{
var l = Console.ReadLine();
Stopwatch stopWatch = new Stopwatch();
stopWatch.Start();
var x = (l.Length * 15 / 100) + 1;
var a = bk.Search(l, x);
stopWatch.Stop();
TimeSpan ts = stopWatch.Elapsed;
string elapsedTime = String.Format("{0:00}:{1:00}:{2:00}.{3:00}",
ts.Hours, ts.Minutes, ts.Seconds,
ts.Milliseconds / 10);
Console.WriteLine("RunTime " + elapsedTime);
Console.WriteLine(String.Join(", ", a.ToArray()));
}
}