pushed dtw changes through JavaScript. Tested.

RapidAPI/RapidAPI/main.cpp

@@ -213,7 +213,7 @@ int main(int argc, const char * argv[]) {
     
         
     ///////////////////////////////////////////////////////////Testing with labels
-    seriesClassification myDtwLabel;
+    seriesClassification myDTW;
     std::vector<trainingSeries> seriesVector;
     trainingSeries tempSeries;
     
@@ -233,9 +233,10 @@ int main(int argc, const char * argv[]) {
     tempSeries.label = "second series";
     seriesVector.push_back(tempSeries);
     
-    myDtwLabel.trainLabel(seriesVector);
-    assert(myDtwLabel.runLabel(seriesOne) == "first series");
-    assert(myDtwLabel.runLabel(seriesTwo) == "second series");
+    myDTW.train(seriesVector);
+    assert(myDTW.run(seriesOne) == "first series");
+    assert(myDTW.run(seriesTwo) == "second series");
+    std::cout << myDTW.getCosts()[0] << std::endl;
 
     return 0;
 }

src/emscripten/rapidLibPost.js

@@ -437,15 +437,6 @@ Module.SeriesClassification = function () {
 };
 
 Module.SeriesClassification.prototype = {
-    /**
-     * Adds a series to the array examples
-     * @param {Object} newSeries - An array of arrays
-     * @returns {Number} - index of the example series that best matches the input
-     */
-    // addSeries: function (newSeries) {
-    //     newSeries = Module.checkOutput(newSeries);
-    //     return this.seriesClassification.addTrainingSet(Module.prepTrainingSet(newSeries));
-    // },
     /**
      * Resets the model, and adds a set of series to be evaluated
      * @param {Object} newSeriesSet - an array of objects, each with input: <array of arrays> and label: <string>
@@ -453,11 +444,7 @@ Module.SeriesClassification.prototype = {
      */
     train: function (newSeriesSet) {
         this.reset();
-        this.seriesClassification.trainLabel(Module.prepTrainingSeriesSet(newSeriesSet));
-        //     for (var i = 0; i < newSeriesSet.length; ++i) {
-        //         newSeriesSet[i] = Module.checkOutput(newSeriesSet[i]);
-        //         this.seriesClassification.addTrainingSet(Module.prepTrainingSet(newSeriesSet[i]));
-        //     }
+        this.seriesClassification.train(Module.prepTrainingSeriesSet(newSeriesSet));
         return true;
     },
     /**
@@ -481,7 +468,7 @@ Module.SeriesClassification.prototype = {
             }
             vecInputSeries.push_back(tempVector);
         }
-        return this.seriesClassification.runLabel(vecInputSeries);
+        return this.seriesClassification.run(vecInputSeries);
 
     },
     /**
@@ -494,14 +481,9 @@ Module.SeriesClassification.prototype = {
     },
     /**
      * Returns an array of costs to match the input series to each example series. A lower cost is a closer match
-     * @param {Array} [inputSeries] - An array of arrays to be evaluated. (Optional)
      * @returns {Array}
      */
-    getCosts: function (inputSeries) {
-        if (inputSeries) {
-            inputSeries = Module.checkOutput(inputSeries);
-            this.seriesClassification.runTrainingSet(Module.prepTrainingSet(inputSeries));
-        }
+    getCosts: function () {
         let returnArray = [];
         let VecDouble = this.seriesClassification.getCosts();
         for (let i = 0; i < VecDouble.size(); ++i) {

src/emscripten/seriesClassificationEmbindings.h

@@ -8,12 +8,9 @@ using namespace emscripten;
 EMSCRIPTEN_BINDINGS(seriesClassification_module) {
   class_<seriesClassification>("SeriesClassificationCpp") //name change so that I can wrap it in Javascript. -mz
     .constructor()
-    //.function("addTrainingSet", &seriesClassification::addTrainingSet)
-    //.function("train", &seriesClassification::train)
     .function("reset", &seriesClassification::reset)
-    .function("trainLabel", &seriesClassification::trainLabel)
-    .function("runLabel", &seriesClassification::runLabel)
-    //.function("runTrainingSet", &seriesClassification::runTrainingSet)
+    .function("train", &seriesClassification::train)
+    .function("run", &seriesClassification::run)
     .function("getCosts", select_overload<std::vector<double>()>(&seriesClassification::getCosts))
     ;
 

src/seriesClassification.cpp

@@ -15,7 +15,7 @@ seriesClassification::seriesClassification() {};
 
 seriesClassification::~seriesClassification() {};
 
-bool seriesClassification::trainLabel(const std::vector<trainingSeries> &seriesSet) {
+bool seriesClassification::train(const std::vector<trainingSeries> &seriesSet) {
     reset();
     bool trained = true;
     allTrainingSeries = seriesSet;
@@ -30,7 +30,7 @@ void seriesClassification::reset() {
     allTrainingSeries.clear();
 }
 
-std::string seriesClassification::runLabel(const std::vector<std::vector<double>> &inputSeries) {
+std::string seriesClassification::run(const std::vector<std::vector<double>> &inputSeries) {
     dtw dtw;
     int closestSeries = 0;
     allCosts.clear();
@@ -49,9 +49,10 @@ std::string seriesClassification::runLabel(const std::vector<std::vector<double>
 };
 
 
-//std::vector<double> seriesClassification::getCosts() {
-//    return allCosts;
-//}
+std::vector<double> seriesClassification::getCosts() {
+    return allCosts;
+}
+
 //
 //std::vector<double> seriesClassification::getCosts(const std::vector<trainingExample> &trainingSet) {
 //    run(trainingSet);

src/seriesClassification.h

@@ -20,12 +20,10 @@ public:
     seriesClassification();
     ~seriesClassification();
     
-    bool trainLabel(const std::vector<trainingSeries> &seriesSet);
-    
+    bool train(const std::vector<trainingSeries> &seriesSet);
     void reset();
-    
-    std::string runLabel(const std::vector<std::vector<double>> &inputSeries);
-    
+    std::string run(const std::vector<std::vector<double>> &inputSeries);
+    std::vector<double> getCosts();
     
 private:
     std::vector<trainingSeries> allTrainingSeries;

test/test.js

@@ -339,7 +339,7 @@ describe('RapidLib Machine Learning', function () {
         });
 
         it('should report costs', function () {
-            expect(myDTW.getCosts()[0]).to.equal(17.325403217417502);
+            expect(myDTW.getCosts()[0]).to.equal(14.621232784634294);
             expect(myDTW.getCosts()[1]).to.equal(0);
         });
         it('should report new costs');