public void Build(MetricDB db, Random rand, int num_refs, int K=7, int maxcand=1024, SequenceBuilder seq_builder=null)
{
var sample = new SampleSpace ("", db, num_refs, rand);
var sat = new SAT_Distal ();
sat.Build (sample, RandomSets.GetRandom());
this.Build (db, sat, K, maxcand, seq_builder);
}
public void Build(MetricDB db, int k, int num_refs, Random rand)
{
var sample = new SampleSpace("", db, num_refs, rand);
var I = new SAT_Distal();
I.Build(sample, rand);
this.Build(db, k, I);
}
public void Build(MetricDB db, int symbolsPerHash, int neighborhoodExpansion, Random rand)
{
this.DB = db;
int n = db.Count;
this.SymbolsPerHash = symbolsPerHash; // very small values, i.e., 2, 3, 4
this.NeighborhoodExpansion = neighborhoodExpansion; // neighborhoodExpansion >= symbolsPerHash
var numrefs = (int)(Math.Pow(n, 1.0 / this.SymbolsPerHash));
this.CountSymbolBits = countBits(numrefs);
var refs = new SampleSpace("", db, numrefs, rand);
var sat = new SAT_Distal ();
sat.Build (refs, new Random ());
this.R = sat;
var G = new KnrFP ();
G.Build (db, this.R, this.SymbolsPerHash);
var knrcopy = new int[this.SymbolsPerHash];
this.hashTable = new Dictionary<long, List<int>> ();
for (int objID = 0; objID < n; ++objID) {
var knr = G [objID] as int[];
knr.CopyTo (knrcopy, 0);
var hash = this.EncodeKnr (knrcopy); // EncodeKnr destroys the reference order
List<int> L;
if (!this.hashTable.TryGetValue(hash, out L)) {
L = new List<int>();
this.hashTable.Add(hash, L);
}
L.Add (objID);
}
double avg_len = 0;
double avg_len_sq = 0;
foreach (var list in this.hashTable.Values) {
avg_len += list.Count;
avg_len_sq += list.Count * list.Count;
}
avg_len /= this.hashTable.Count;
avg_len_sq /= this.hashTable.Count;
Console.WriteLine ("=== created hash table with {0} keys, items: {1}, popcount mean: {2}, popcount stddev: {3}",
this.hashTable.Count, n, avg_len, Math.Sqrt(avg_len_sq - avg_len * avg_len));
}
public void Build(MetricDB db, int K, int num_refs, Random rand)
{
this.DB = db;
int n = db.Count;
// valid values to be used as parameters
// numrefs <= 255
// K <= 4
if (K > 4) {
throw new ArgumentOutOfRangeException (String.Format("K should be between 1 to 4, K={0}", K));
}
if (num_refs > 255) {
throw new ArgumentOutOfRangeException (String.Format("num_refs should be between 1 to 255, num_refs={0}", num_refs));
}
this.K = K;
var refs = new SampleSpace("", db, num_refs);
var seq = new Sequential();
seq.Build(refs);
this.R = seq;
int[] G = new int[n];
for (int objID = 0; objID < n; ++objID) {
var u = this.DB[objID];
var useq = this.GetHashKnr(u);
G[objID] = useq;
if (objID % 10000 == 0) {
Console.WriteLine ("computing knrlsh {0}/{1} (adv. {2:0.00}%, db: {3}, K: {4}, curr. time: {5})", objID, n, objID*100.0/n, this.DB.Name, this.K, DateTime.Now);
}
}
this.TABLE = new Dictionary<int, List<int>> ();
for (int objID = 0; objID < n; ++objID) {
var hash = G[objID];
List<int> L;
if (!this.TABLE.TryGetValue(hash, out L)) {
L = new List<int>();
this.TABLE.Add(hash, L);
}
L.Add (objID);
}
}
public void Test(string nick, MetricDB db, string queries, int num_centers, int num_perms, int num_refs)
{
var qstream = new QueryStream (queries);
var reslist = new List<string> ();
// Exhaustive search
{
Sequential seq = new Sequential ();
seq.Build (db);
var idxname = "Index.Sequential." + nick;
IndexGenericIO.Save (idxname, seq);
var resname = "Res." + idxname + "." + queries;
if (!File.Exists (resname)) {
Commands.Search (seq, qstream.Iterate (), new ShellSearchOptions (queries, idxname, resname));
}
reslist.Add (resname);
}
///
/// The List of Clusters and variants
///
// LC_RNN
reslist.Add (this.TestLC ("Index.LC_RNN." + nick, db, num_centers, new LC_RNN (), queries, qstream));
// LC
reslist.Add (this.TestLC ("Index.LC." + nick, db, num_centers, new LC (), queries, qstream));
// LC_IRNN
reslist.Add (this.TestLC ("Index.LC_IRNN." + nick, db, num_centers, new LC_IRNN (), queries, qstream));
// LC_PRNN
reslist.Add (this.TestLC ("Index.LC_PRNN." + nick, db, num_centers, new LC_PRNN (), queries, qstream));
// LC_ParallelBuild
reslist.Add (this.TestLC ("Index.LC_ParallelBuild." + nick, db, num_centers, new LC_ParallelBuild (), queries, qstream));
///
/// Permutation Based Indexes
///
// Permutations
reslist.Add (this.TestPI ("Index.Perms." + nick, db, num_perms, new Perms (), queries, qstream));
// Brief Index
reslist.Add (this.TestPI ("Index.BinPerms." + nick, db, num_perms, new BinPerms (), queries, qstream));
// BinPermsTwoBits
reslist.Add (this.TestPI ("Index.BinPermsTwoBits." + nick, db, num_perms, new BinPermsTwoBit (), queries, qstream));
///
/// KNR
///
{
KnrSeqSearch idx;
var idxname = "Index.KnrSeqSearch." + nick;
if (File.Exists (idxname)) {
idx = (KnrSeqSearch)IndexGenericIO.Load (idxname);
} else {
Console.WriteLine ("** Starting construction of '{0}'", idxname);
var knr = new KnrSeqSearch ();
var sample = RandomSets.GetRandomSubSet (num_refs, db.Count);
var refsdb = new SampleSpace ("", db, sample);
var refsidx = new LC ();
refsidx.Build (refsdb, refsdb.Count / 10);
knr.Build (db, refsidx, 7);
IndexGenericIO.Save (idxname, knr);
idx = knr;
}
idx.MAXCAND = 1024;
this.TestKNR(idx, idxname, queries, num_refs, reslist, (I) => I);
Console.WriteLine ("==== Working on a permuted space");
idxname = idxname + ".proximity-sorted";
if (!File.Exists(idxname)) {
idx = idx.GetSortedByPrefix();
idx.MAXCAND = 1024;
IndexGenericIO.Save(idxname, idx);
} else {
idx = (KnrSeqSearch)IndexGenericIO.Load(idxname);
}
this.TestKNR(idx, idxname, queries, num_refs, reslist, (I) => new PermutedIndex(I));
}
reslist.Add("--horizontal");
Commands.Check(reslist);
}
public void Build(MetricDB db, int num_refs, int maxcand=1024, double mod=0.5, bool permcenter=true)
{
var ss = new SampleSpace ("", db, num_refs);
this.Build (db, ss, maxcand, mod, permcenter);
}
public static List<string> ExecuteKNRSEQ(IndexArgumentSetup setup, string nick, int numrefs, int k, double maxcand_ratio)
{
var idxname = String.Format ("{0}/Index.knrseq-{1}-{2}", nick, numrefs, k);
MetricDB db = SpaceGenericIO.Load (setup.BINARY_DATABASE);
Index idx;
var suffix = "";
var resnamelist = new List<string> ();
if (!File.Exists (idxname)) {
Console.WriteLine ("*** creating index {0}", idxname);
var s = DateTime.Now.Ticks;
var c = db.NumberDistances;
var IDX = new KnrSeqSearch ();
var refsDB = new SampleSpace("", db, numrefs);
var refsIDX = new EPTable ();
refsIDX.Build(refsDB, 4, (_db, _rand) => new EPListOptimizedA(_db, 4, _rand));
if (k == 0) {
k = KnrEstimateParameters.EstimateKnrEnsuringSharedNeighborhoods (db, refsIDX, (int)Math.Abs (setup.QARG));
suffix = String.Format ("estimated-K={0}.", k);
}
IDX.Build (db, refsIDX, k, int.MaxValue);
SaveConstructionTime (idxname, DateTime.Now.Ticks - s, db.NumberDistances - c);
IndexGenericIO.Save (idxname, IDX);
idx = IDX;
} else {
Console.WriteLine ("*** loading index {0}", idxname);
idx = IndexGenericIO.Load (idxname);
if (k == 0) {
var _idx = idx as KnrSeqSearch;
suffix = String.Format ("estimated-K={0}.", _idx.K);
}
}
string resname;
// PPIndex
resname = GetResultName (nick, idxname, setup, String.Format(suffix + "maxcand={0}.PPI", maxcand_ratio));
resnamelist.Add(resname);
if (!File.Exists (resname)) {
var knr = idx as KnrSeqSearch;
knr.MAXCAND = (int)(idx.DB.Count * maxcand_ratio);
PerformSearch (resname, knr, idxname, setup);
}
// KnrSeqSearchCosine
resname = GetResultName (nick, idxname, setup, String.Format(suffix + "maxcand={0}.COS", maxcand_ratio));
resnamelist.Add(resname);
if (!File.Exists (resname)) {
var knr = new KnrSeqSearchCosine(idx as KnrSeqSearch);
knr.MAXCAND = (int)(idx.DB.Count * maxcand_ratio);
PerformSearch (resname, knr, idxname, setup);
}
// KnrSeqSearchFootrule
resname = GetResultName (nick, idxname, setup, String.Format(suffix + "maxcand={0}.FOOTRULE", maxcand_ratio));
resnamelist.Add(resname);
if (!File.Exists (resname)) {
var knr = new KnrSeqSearchFootrule(idx as KnrSeqSearch);
knr.MAXCAND = (int)(idx.DB.Count * maxcand_ratio);
PerformSearch (resname, knr, idxname, setup);
}
// KnrSeqSearchJaccLCS
resname = GetResultName (nick, idxname, setup, String.Format(suffix + "maxcand={0}.JACCLCS", maxcand_ratio));
resnamelist.Add(resname);
if (!File.Exists (resname)) {
var knr = new KnrSeqSearchJaccLCS(idx as KnrSeqSearch);
knr.MAXCAND = (int)(idx.DB.Count * maxcand_ratio);
PerformSearch (resname, knr, idxname, setup);
}
// KnrSeqSearchLCSv3
resname = GetResultName (nick, idxname, setup, String.Format(suffix + "maxcand={0}.LCSv3", maxcand_ratio));
resnamelist.Add(resname);
if (!File.Exists (resname)) {
var knr = new KnrSeqSearchLCSv3(idx as KnrSeqSearch);
knr.MAXCAND = (int)(idx.DB.Count * maxcand_ratio);
PerformSearch (resname, knr, idxname, setup);
}
// NAPP
foreach (var ksearch in setup.KNR_KSEARCH) {
var knr = new NAPP(idx as KnrSeqSearch);
knr.MAXCAND = (int)(idx.DB.Count * maxcand_ratio);
resname = GetResultName (nick, idxname, setup, String.Format(suffix + "maxcand={0}.NAPP.ksearch={1}", maxcand_ratio, ksearch));
resnamelist.Add(resname);
if (!File.Exists (resname)) {
PerformSearch (resname, knr, idxname, setup);
}
}
return resnamelist;
}
public void BuildApprox(MetricDB db, Random rand, int num_refs, int K=7, int maxcand=1024, SequenceBuilder seq_builder = null)
{
var sample = new SampleSpace ("", db, num_refs);
var inner = new KnrSeqSearch ();
inner.Build (sample, rand, 1024, K, int.MaxValue);
this.Build (db, new KnrSeqSearchFootrule(inner), K, maxcand, seq_builder);
}
