wrapping DTW in seriesClassification, building with emscripten

Makefile

@@ -9,8 +9,9 @@ RL_KNN=src/knnClassification.cpp src/classification.cpp
 RL_SVM=src/svmClassification.cpp dependancies/libsvm/libsvm.cpp
 RL_NN=src/neuralNetwork.cpp src/regression.cpp
 RL_MS=src/modelSet.cpp
+RL_DTW = src/dtw.cpp src/seriesClassification.cpp
 RL_STREAM=src/rapidStream.cpp 
-SOURCE_RAPID = $(RL_MS) $(RL_NN) $(RL_KNN) $(RL_SVM) $(RL_STREAM)
+SOURCE_RAPID = $(RL_MS) $(RL_NN) $(RL_KNN) $(RL_SVM) $(RL_DTW) $(RL_STREAM)
 
 # destination .js file
 OUTPUT_RAPID=rapidLib/RapidLib.js

RapidAPI/RapidAPI.xcodeproj/project.pbxproj

@@ -15,6 +15,7 @@
 		BE325F501DB50BFE00F199A8 /* neuralNetwork.cpp in Sources */ = {isa = PBXBuildFile; fileRef = BE325F461DB50BFE00F199A8 /* neuralNetwork.cpp */; };
 		BE325F511DB50BFE00F199A8 /* regression.cpp in Sources */ = {isa = PBXBuildFile; fileRef = BE325F4A1DB50BFE00F199A8 /* regression.cpp */; };
 		BE3852881EE847730008E1BD /* dtw.cpp in Sources */ = {isa = PBXBuildFile; fileRef = BE3852871EE847730008E1BD /* dtw.cpp */; };
+		BE38528B1EE94D740008E1BD /* seriesClassification.cpp in Sources */ = {isa = PBXBuildFile; fileRef = BE3852891EE94D740008E1BD /* seriesClassification.cpp */; };
 		BE553E2C1EE05ED2004EB00F /* libsvm.cpp in Sources */ = {isa = PBXBuildFile; fileRef = BE553E2A1EE05ED2004EB00F /* libsvm.cpp */; };
 		BE553E2F1EE05FE1004EB00F /* svmClassification.cpp in Sources */ = {isa = PBXBuildFile; fileRef = BE553E2E1EE05FE1004EB00F /* svmClassification.cpp */; };
 /* End PBXBuildFile section */
@@ -50,6 +51,8 @@
 		BE325F4B1DB50BFE00F199A8 /* regression.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = regression.h; sourceTree = "<group>"; };
 		BE3852861EE8415E0008E1BD /* dtw.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = dtw.h; sourceTree = "<group>"; };
 		BE3852871EE847730008E1BD /* dtw.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; path = dtw.cpp; sourceTree = "<group>"; };
+		BE3852891EE94D740008E1BD /* seriesClassification.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; path = seriesClassification.cpp; sourceTree = "<group>"; };
+		BE38528A1EE94D740008E1BD /* seriesClassification.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = seriesClassification.h; sourceTree = "<group>"; };
 		BE553E2A1EE05ED2004EB00F /* libsvm.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; path = libsvm.cpp; sourceTree = "<group>"; };
 		BE553E2B1EE05ED2004EB00F /* libsvm.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = libsvm.h; sourceTree = "<group>"; };
 		BE553E2D1EE05F03004EB00F /* svmClassification.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = svmClassification.h; sourceTree = "<group>"; };
@@ -133,6 +136,8 @@
 				BE325F4B1DB50BFE00F199A8 /* regression.h */,
 				BE3852861EE8415E0008E1BD /* dtw.h */,
 				BE3852871EE847730008E1BD /* dtw.cpp */,
+				BE3852891EE94D740008E1BD /* seriesClassification.cpp */,
+				BE38528A1EE94D740008E1BD /* seriesClassification.h */,
 			);
 			name = src;
 			path = ../../src;
@@ -210,6 +215,7 @@
 				BE325F4F1DB50BFE00F199A8 /* modelSet.cpp in Sources */,
 				BE325F4D1DB50BFE00F199A8 /* classification.cpp in Sources */,
 				BE325F511DB50BFE00F199A8 /* regression.cpp in Sources */,
+				BE38528B1EE94D740008E1BD /* seriesClassification.cpp in Sources */,
 				BE325F501DB50BFE00F199A8 /* neuralNetwork.cpp in Sources */,
 				BE15ECE31DBA4E1000E88F7C /* jsoncpp.cpp in Sources */,
 				BE3852881EE847730008E1BD /* dtw.cpp in Sources */,

RapidAPI/RapidAPI/main.cpp

@@ -5,7 +5,7 @@
 #include <algorithm>
 #include "regression.h"
 #include "classification.h"
-#include "dtw.h"
+#include "seriesClassification.h"
 #include "json.h"
 
 int main(int argc, const char * argv[]) {
@@ -134,24 +134,25 @@ int main(int argc, const char * argv[]) {
     
     ////////////
     
-    dtw myDtw;
-    
-    std::vector<std::vector<double>> trainingSeries;
-    trainingSeries.push_back( { 1., 5.} );
-    trainingSeries.push_back( { 2., 4.} );
-    trainingSeries.push_back( { 3., 3.} );
-    trainingSeries.push_back( { 4., 2.} );
-    trainingSeries.push_back( { 5., 1.} );
-    myDtw.setSeries(trainingSeries);
-    
-    std::vector<std::vector<double>> inputSeries;
-    inputSeries.push_back( { 1., 4. } );
-    inputSeries.push_back( { 2., 3. } );
-    inputSeries.push_back( { 3., 2. } );
-    inputSeries.push_back( { 4., 1. } );
-    
-    std::cout << "dtw: " << myDtw.process(inputSeries) << std::endl;
-    std::cout << "dtw: " << myDtw.process(trainingSeries) << std::endl;
+    seriesClassification myDtw;
+    
+    std::vector<std::vector<double>> seriesOne;
+    seriesOne.push_back( { 1., 5.} );
+    seriesOne.push_back( { 2., 4.} );
+    seriesOne.push_back( { 3., 3.} );
+    seriesOne.push_back( { 4., 2.} );
+    seriesOne.push_back( { 5., 1.} );
+    myDtw.addSeries(seriesOne);
+    
+    std::vector<std::vector<double>> seriesTwo;
+    seriesTwo.push_back( { 1., 4. } );
+    seriesTwo.push_back( { 2., -3. } );
+    seriesTwo.push_back( { 1., 5. } );
+    seriesTwo.push_back( { -2., 1. } );
+    myDtw.addSeries(seriesTwo);
+    
+    std::cout << "dtw: " << myDtw.process(seriesOne) << std::endl;
+    std::cout << "dtw: " << myDtw.process(seriesTwo) << std::endl;
     
     return 0;
 }

src/seriesClassification.cpp

+//
+//  seriesClassification.cpp
+//  RapidAPI
+//
+//  Created by mzed on 08/06/2017.
+//  Copyright © 2017 Goldsmiths. All rights reserved.
+//
+
+#include <vector>
+#include "seriesClassification.h"
+#ifdef EMSCRIPTEN
+#include "emscripten/seriesClassificationEmbindings.h"
+#endif
+
+
+seriesClassification::seriesClassification() {};
+
+seriesClassification::~seriesClassification() {};
+
+bool seriesClassification::addSeries(std::vector<std::vector<double>> newSeries) {
+    dtw newDTW;
+    newDTW.setSeries(newSeries);
+    dtwClassifiers.push_back(newDTW);
+    return true;
+}
+
+void seriesClassification::clear() {
+    dtwClassifiers.clear();
+}
+
+
+int seriesClassification::process(std::vector<std::vector<double>> inputSeries) {
+    //TODO: check vector sizes and reject bad data
+    int closestSeries = 0;
+    double lowestCost = dtwClassifiers[0].process(inputSeries);
+    for (int i = 1; i < dtwClassifiers.size(); ++i) {
+        double currentCost = dtwClassifiers[i].process(inputSeries);
+        if (currentCost < lowestCost) {
+            lowestCost = currentCost;
+            closestSeries = i;
+        }
+    }
+    
+    return closestSeries;
+};
\ No newline at end of file

src/seriesClassification.h

+//
+//  seriesClassification.hp
+//  RapidAPI
+//
+//  Created by mzed on 08/06/2017.
+//  Copyright © 2017 Goldsmiths. All rights reserved.
+//
+
+#ifndef seriesClassification_hpp
+#define seriesClassification_hpp
+
+#include <vector>
+#include "dtw.h"
+
+class seriesClassification {
+    
+public:
+    seriesClassification();
+    ~seriesClassification();
+    
+    bool addSeries(std::vector<std::vector<double>> newSeries);
+    void clear();
+    
+    int process(std::vector<std::vector<double>> inputSeries);
+    
+private:
+    std::vector<dtw> dtwClassifiers;
+
+};
+
+#endif