/*Run Online (Liu method)*/ private void btnRunOnl_Click(List <double> training_data, List <double> streaming_data, int period, int NLength, int maxEntry, int minEntry, int R, int D) { //create a new buffer. In this demo, the buffer is training_data (edit later): List <double> this_buffer = new List <double>(); this_buffer.AddRange(training_data); // Store furnitures in RTree int this_id_item = int.MinValue; List <int> this_id_itemList = new List <int>(); RTree <int> this_RTree = new RTree <int>(maxEntry, minEntry); List <Rectangle> this_recList = new List <Rectangle>(); // Call 'Run Offline' for the first time, store results into variables ("this" object): List <double> discord_firsttime = RunOfflineMinDist(training_data, NLength, maxEntry, minEntry, R, D, ref this_id_item, ref this_id_itemList, ref this_recList, ref this_RTree, true); // Store current discord in buffer double this_best_so_far_dist = discord_firsttime[0]; double this_best_so_far_loc = discord_firsttime[1]; //store the last subsequence of the buffer: List <double> last_sub = this_buffer.GetRange(this_buffer.Count - NLength, NLength); // STREAMING: keep streaming until we have no more data points for (int index_stream = 0; index_stream < streaming_data.Count; index_stream++) { var watch = System.Diagnostics.Stopwatch.StartNew();///calc execution time double new_data_point = streaming_data[index_stream]; //update last_sub at time t to get new_sub at time (t+1): last_sub.Add(new_data_point); last_sub.RemoveAt(0); List <double> new_sub = last_sub; // the same object // Insert the new entry into the tree: this_id_item++; // Add the new rec to the tree: Rectangle new_rec = new Rectangle(Utils.MathFuncs.PAA_Lower(new_sub, D, R).ToArray(), Utils.MathFuncs.PAA_Upper(new_sub, D, R).ToArray(), this_buffer.Count - NLength + 1 + index_stream); this_RTree.Add(new_rec, this_id_item); this_recList.Add(new_rec); this_id_itemList.Add(this_id_item); //remove the oldest entry: this_RTree.Delete(this_recList[index_stream], this_id_itemList[index_stream]); //get the first sub before update the buffer (help to find the small match in Liu's method) List <double> first_sub = this_buffer.GetRange(0, NLength); // update buffer: this_buffer.Add(new_data_point); this_buffer.RemoveAt(0); /* 'til now, we have already updated the tree. * from now on, almost just copy the offline code: */ //Method 1: just re-order the 2 loops: //RunOnline_Method1(this_buffer, index_stream); //Method 2: Liu's algorithm: //Note: Method_2 includes method_1 (case a) //RunOnline_LiuMethod_origin(this_buffer, index_stream, first_sub); //Method 3: motified_Liu's List <double> discord_Liu = RunOnline_LiuMethod_edited(this_buffer, index_stream, first_sub, this_RTree, this_best_so_far_dist, (int)this_best_so_far_loc, NLength, D); this_best_so_far_dist = discord_Liu[0]; this_best_so_far_loc = discord_Liu[1]; watch.Stop(); //stop timer long elapsedMs = watch.ElapsedMilliseconds; //this.txtExeTime.Text = elapsedMs.ToString(); Console.WriteLine("ExeTime_Online=" + elapsedMs.ToString()); // Useless variable to pass parameter int dumb = 0; List <int> dumb_list = new List <int>(); List <Rectangle> dumb_rectlist = new List <Rectangle>(); RTree <int> dumb_rtree = new RTree <int>(maxEntry, minEntry); //call offline version to assure the results and compare the time executions: var watch2 = System.Diagnostics.Stopwatch.StartNew();///calc execution time offline List <double> discord_offline = RunOfflineMinDist(training_data, NLength, maxEntry, minEntry, R, D, ref dumb, ref dumb_list, ref dumb_rectlist, ref dumb_rtree, false); double this_best_so_far_dist_offline = discord_offline[0]; watch2.Stop(); //stop timer long this_exeTimeOffline = watch2.ElapsedMilliseconds; //check: if (Math.Abs(this_best_so_far_dist - this_best_so_far_dist_offline) < 10e-7) { Console.WriteLine("checked, ok."); if (elapsedMs > this_exeTimeOffline) { Console.WriteLine("Online takes more time than Offline !!!"); } } else { Console.WriteLine("this.best_so_far_dist = " + this_best_so_far_dist); Console.WriteLine("this.best_so_far_dist_Offline = " + this_best_so_far_dist_offline); Console.WriteLine("The results are different. Stop Streaming !!!"); return; } Console.WriteLine("------------------------"); } // end For loop (streaming) Console.WriteLine("--- Streaming's done (run out of data) ---"); } //end btnRunOnl_Click function
} //end btnRunOnl_Click function /*Run Online - new method (inner loop only)*/ private void Btn_NewOnline_Click(List <double> training_data, List <double> streaming_data, int period, int NLength, int maxEntry, int minEntry, int R, int D) { //create a new buffer. In this demo, the buffer is training_data (edit later): List <double> this_buffer = new List <double>(); this_buffer.AddRange(training_data); // Store furnitures in RTree int this_id_item = int.MinValue; List <int> this_id_itemList = new List <int>(); RTree <int> this_RTree = new RTree <int>(maxEntry, minEntry); List <Rectangle> this_recList = new List <Rectangle>(); // Call 'Run Offline' for the first time, store results into variables ("this" object): List <double> discord_firsttime = RunOfflineMinDist(training_data, NLength, maxEntry, minEntry, R, D, ref this_id_item, ref this_id_itemList, ref this_recList, ref this_RTree, true); double this_best_so_far_dist_TheMostDiscord = discord_firsttime[0]; //store the last subsequence of the buffer: List <double> last_sub = this_buffer.GetRange(this_buffer.Count - NLength, NLength); // STREAMING: keep streaming until we have no more data points for (int index_stream = 0; index_stream < streaming_data.Count; index_stream++) { var watch = System.Diagnostics.Stopwatch.StartNew();///calc execution time double new_data_point = streaming_data[index_stream]; //update last_sub at time t to get new_sub at time (t+1): last_sub.Add(new_data_point); last_sub.RemoveAt(0); List <double> new_sub = last_sub; // the same object // Insert the new entry into the tree: this_id_item++; // Add the new rec to the tree: Rectangle new_rec = new Rectangle(Utils.MathFuncs.PAA_Lower(new_sub, D, R).ToArray(), Utils.MathFuncs.PAA_Upper(new_sub, D, R).ToArray(), this_buffer.Count - NLength + 1 + index_stream); this_RTree.Add(new_rec, this_id_item); this_recList.Add(new_rec); this_id_itemList.Add(this_id_item); //remove the oldest entry: this_RTree.Delete(this_recList[index_stream], this_id_itemList[index_stream]); // update buffer: this_buffer.Add(new_data_point); this_buffer.RemoveAt(0); /* 'til now, we have already updated the tree. * from now on, almost just copy the offline code: */ //Run new_online_algorithm: NewOnlineAlgorithm(this_buffer, 2 * period, index_stream, period, new_sub, this_RTree, NLength, D, R, maxEntry, minEntry, ref this_best_so_far_dist_TheMostDiscord); watch.Stop(); //stop timer long elapsedMs = watch.ElapsedMilliseconds; //this.txtExeTime.Text = elapsedMs.ToString(); Console.WriteLine("ExeTime_Online=" + elapsedMs.ToString()); Console.WriteLine("------------------------"); } // end For loop (streaming) Console.WriteLine("--- Streaming's done (run out of data) ---"); }
////////////// Main Functions ////////////// /*Run new offline (minDist) */ public static List <double> RunOfflineMinDist(List <double> inputData, int NLength, int maxEntry, int minEntry, int R, int D, ref int this_id_item, ref List <int> this_id_itemList, ref List <Rectangle> this_rectList, ref RTree <int> this_RTree, bool is_first_time) { int id_item = int.MinValue; RTree <int> rtree = new RTree <int>(maxEntry, minEntry); List <int> candidateList = new List <int>(); List <int> beginIndexInner = new List <int>(); List <int> indexOfLeafMBRS = new List <int>(); double best_so_far_dist = 0; int best_so_far_loc = -1; double nearest_neighbor_dist = 0; double dist = 0; bool break_to_outer_loop = false; bool[] is_skipped_at_p = new bool[inputData.Count]; for (int i = 0; i < inputData.Count; i++) { is_skipped_at_p[i] = false; } if (minEntry > maxEntry / 2) { MessageBox.Show("Requirement: MinNodePerEntry <= MaxNodePerEntry/2"); return(new List <double> { best_so_far_dist, best_so_far_loc }); } List <Rectangle> recList = new List <Rectangle>(); List <int> id_itemList = new List <int>(); for (int i = 0; i <= inputData.Count - NLength; i++) { List <double> subseq = inputData.GetRange(i, NLength); id_item++; Rectangle new_rec = new Rectangle(MathFuncs.PAA_Lower(subseq, D, R).ToArray(), MathFuncs.PAA_Upper(subseq, D, R).ToArray(), i); rtree.Add(new_rec, id_item); recList.Add(new_rec); id_itemList.Add(id_item); } Dictionary <int, Node <int> > nodeMap = rtree.getNodeMap(); List <Node <int> > leafNodes = nodeMap.Values.Where(node => node.level == 1).OrderBy(node => node.entryCount).ToList(); List <Rectangle> leafMBRs = leafNodes.Select(node => node.mbr).ToList(); // List rectangle of leaf nodes in order of list leafNodes for (int i = 0; i < leafNodes.Count; i++) { List <Rectangle> leafEntries = leafNodes[i].entries.Where(mbr => mbr != null).Select(mbr => mbr).ToList(); if (leafEntries.Count > 0) { int beginIndex = candidateList.Count; candidateList.AddRange(leafEntries.Select(mbr => mbr.getIndexSubSeq())); beginIndexInner.AddRange(Enumerable.Repeat(beginIndex, leafEntries.Count)); indexOfLeafMBRS.AddRange(Enumerable.Repeat(i, leafEntries.Count)); } } for (int i = 0; i < candidateList.Count; i++)//outer loop { int p = candidateList[i]; // rectangle of subseq in p postion if (is_skipped_at_p[p]) { //p was visited at inner loop before continue; } else { List <double> subseq_p = inputData.GetRange(p, NLength); //Rectangle p_rectangle = recList[p]; List <double> P_PAA = MathFuncs.PAA(subseq_p, D); nearest_neighbor_dist = Constants.INFINITE; List <bool> eliminatedMBR = new List <bool>(); for (int k = 0; k < leafMBRs.Count; k++) { eliminatedMBR.Add(false); } int indexMBRLeaf = -1; int num_leaf_skips = 0; for (int j = 0; j < candidateList.Count; j++)// inner loop { // int q = innerList[j]; int index_inner = (beginIndexInner[i] + j) % candidateList.Count; int q = candidateList[index_inner]; int index_MBRInnner = (beginIndexInner[i] + j) % candidateList.Count; int MBRInnner = indexOfLeafMBRS[index_MBRInnner]; if (indexMBRLeaf < MBRInnner)//the first entry of the next node ? { indexMBRLeaf++; /* Test: * if (indexMBRInnner[j] == MBRInnner) * Console.WriteLine("OK");*/ //calc minDist: //double minDist = MathFuncss.MINDIST(p_rectangle, leafMBRs[MBRInnner], (NLength / (double)(D))); double minDist = MathFuncs.MINDIST(P_PAA, leafMBRs[MBRInnner], (NLength / (double)(D))); //if (minDist_keo > minDist) //{ // Console.WriteLine("STOPPP"); // return; //} if (minDist >= nearest_neighbor_dist) { num_leaf_skips++; eliminatedMBR[MBRInnner] = true; continue;// pruned => skip to the next one } else { if (Math.Abs(p - q) < NLength) { continue;// self-match => skip to the next one } //calculate the Distance between p and q dist = MathFuncs.EuDistance(subseq_p, inputData.GetRange(q, NLength)); if (dist < best_so_far_dist) { //skip the element q at oute_loop, 'cuz if (p,q) is not a solution, neither is (q,p). is_skipped_at_p[q] = true; break_to_outer_loop = true; //break, to the next loop at outer_loop break; // break at inner_loop first } if (dist < nearest_neighbor_dist) { nearest_neighbor_dist = dist; } } } else // still the same node { if (eliminatedMBR[MBRInnner]) // can prune ? { continue; } else //do it normally { if (Math.Abs(p - q) < NLength) { continue;// self-match => skip to the next one } else { //calculate the Distance between p and q dist = MathFuncs.EuDistance(subseq_p, inputData.GetRange(q, NLength)); if (dist < best_so_far_dist) { //skip the element q at oute_loop, 'cuz if (p,q) is not a solution, neither is (q,p). is_skipped_at_p[q] = true; break_to_outer_loop = true; //break, to the next loop at outer_loop break; // break at inner_loop first } if (dist < nearest_neighbor_dist) { nearest_neighbor_dist = dist; } } } } //end ELSE } //end for inner loop //Console.WriteLine("num_leaf_skips="+ num_leaf_skips); if (break_to_outer_loop) { break_to_outer_loop = false; //reset continue; //go to the next p in outer loop } if (nearest_neighbor_dist > best_so_far_dist) { best_so_far_dist = nearest_neighbor_dist; best_so_far_loc = p; } } }//end outer loop if (is_first_time) { this_id_item = id_item; this_id_itemList = id_itemList; this_RTree = rtree; this_rectList = recList; } return(new List <double> { best_so_far_dist, best_so_far_loc }); }