fix #19

nicolaspanel · Feb 9, 2015 · 4168c8f · 4168c8f
1 parent ff350a7
commit 4168c8f
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Showing 7 changed files with 40 additions and 82 deletions.
diff --git a/.travis.yml b/.travis.yml
@@ -1,5 +1,7 @@
 language: node_js
 node_js:
   - 0.10
+  - 0.11
+  - 0.12
 script:
   - grunt travis
diff --git a/src/addon.cc b/src/addon.cc
@@ -4,8 +4,6 @@
 
 extern "C" {
   void InitAll(Handle<Object> exports) {
-    //Isolate* isolate = Isolate::GetCurrent();
-    //HandleScope scope(isolate);
     NodeSvm::Init(exports);
   }
 }

diff --git a/src/node-svm/node-svm.cc b/src/node-svm/node-svm.cc
@@ -23,7 +23,7 @@ NAN_METHOD(NodeSvm::New) {
         // Invoked as constructor: `new MyObject(...)`
         NodeSvm* obj = new NodeSvm();
         obj->Wrap(args.This());
-        return args.This();
+        NanReturnValue(args.This());
     }
     else {
         // Invoked as plain function `MyObject(...)`, turn into construct call.
@@ -34,7 +34,8 @@ NAN_METHOD(NodeSvm::New) {
 #else
     Local<Value> argv[argc];
 #endif
-        return scope.Close(constructor->NewInstance(argc, argv));
+        Local<Function> cons = NanNew<Function>(constructor);
+        NanReturnValue(cons->NewInstance(argc, argv));
     }
 }
 
@@ -43,7 +44,7 @@ NAN_METHOD(NodeSvm::SetParameters) {
     NodeSvm *obj = node::ObjectWrap::Unwrap<NodeSvm>(args.This());
 
     assert(args[0]->IsObject());
-    Local<Object> params = *args[0]->ToObject();
+    Local<Object> params = args[0].As<Object>();
     obj->setParameters(params);
 
     NanReturnUndefined();
@@ -58,7 +59,7 @@ NAN_METHOD(NodeSvm::Train) {
     // chech params
     assert(args[0]->IsObject());
 
-    Local<Array> dataset = Array::Cast(*args[0]->ToObject());
+    Local<Array> dataset = args[0].As<Array>();
     obj->setSvmProblem(dataset);
     obj->train();
 
@@ -84,7 +85,7 @@ NAN_METHOD(NodeSvm::TrainAsync) {
     assert(args[0]->IsObject());
     assert(args[1]->IsFunction());
 
-    Local<Array> dataset = Array::Cast(*args[0]->ToObject());
+    Local<Array> dataset = args[0].As<Array>();
     NanCallback *callback = new NanCallback(args[1].As<Function>());
 
     NanAsyncQueueWorker(new TrainingWorker(obj, dataset, callback));
@@ -96,22 +97,22 @@ NAN_METHOD(NodeSvm::GetKernelType) {
     NodeSvm *obj = node::ObjectWrap::Unwrap<NodeSvm>(args.This());
     // check obj
     assert(obj->hasParameters());
-    NanReturnValue(Number::New(obj->getKernelType()));
+    NanReturnValue(NanNew<Number>(obj->getKernelType()));
 }
 
 NAN_METHOD(NodeSvm::GetSvmType) {
     NanScope();
     NodeSvm *obj = node::ObjectWrap::Unwrap<NodeSvm>(args.This());
     // check obj
     assert(obj->hasParameters());
-    NanReturnValue(Number::New(obj->getSvmType()));
+    NanReturnValue(NanNew<Number>(obj->getSvmType()));
 }
 
 NAN_METHOD(NodeSvm::IsTrained) {
     NanScope();
     NodeSvm *obj = node::ObjectWrap::Unwrap<NodeSvm>(args.This());
     // check obj
-    NanReturnValue(Boolean::New(obj->isTrained()));
+    NanReturnValue(NanNew<Boolean>(obj->isTrained()));
 }
 
 NAN_METHOD(NodeSvm::GetLabels) {
@@ -125,53 +126,18 @@ NAN_METHOD(NodeSvm::GetLabels) {
     int nbClasses = obj->getClassNumber();
     Handle<Array> labels = NanNew<Array>(nbClasses);
     for (int j=0; j < nbClasses; j++){
-        labels->Set(j, Number::New(obj->getLabel(j)));
+        labels->Set(j, NanNew<Number>(obj->getLabel(j)));
     }
     NanReturnValue(labels);
 }
 
-// NAN_METHOD(NodeSvm::SaveToFile) {
-//     NanScope();
-//     NodeSvm *obj = node::ObjectWrap::Unwrap<NodeSvm>(args.This());
-//     if (args.Length() != 1 || !args[0]->IsString())
-//         return ThrowException(Exception::Error(String::New("usage: NodeSvm.saveToFile(\'filename.model\'')")));
-//         // check obj
-//     assert(obj->isTrained());
-
-//     char *name = new char[4096];
-//     String::Cast(*args[0])->WriteAscii(name, 0, 4096);
-//     name[4095] = 0;
-
-//     // Create a new empty array.
-//     int result = obj->saveModel(name);
-//     delete[] name;
-//     NanReturnValue(Number::New(result));
-// }
-
-// NAN_METHOD(NodeSvm::LoadFromFile) {
-//     NanScope();
-//     NodeSvm *obj = node::ObjectWrap::Unwrap<NodeSvm>(args.This());
-//     if (args.Length() != 1 || !args[0]->IsString()){
-//         return ThrowException(Exception::Error(String::New("usage: NodeSvm.loadFromFile(\'filename.model\'')")));
-//     }
-
-//     char *name = new char[4096];
-//     String::Cast(*args[0])->WriteAscii(name, 0, 4096);
-//     name[4095] = 0;
-
-//     // Create a new empty array.
-//     obj->loadModelFromFile(name);
-//     delete[] name;
-//     NanReturnUndefined();
-// }
-
 NAN_METHOD(NodeSvm::SetModel) {
     NanScope();
     NodeSvm *obj = node::ObjectWrap::Unwrap<NodeSvm>(args.This());
     assert(args.Length() == 1);
     assert(args[0]->IsObject());
 
-    Local<Array> model = Array::Cast(*args[0]->ToObject());
+    Local<Array> model = args[0].As<Array>();
     obj->setModel(model);
     NanReturnUndefined();
 }
@@ -185,14 +151,14 @@ NAN_METHOD(NodeSvm::Predict) {
     // chech params
     assert(args[0]->IsObject());
 
-    Local<Array> inputs = Array::Cast(*args[0]->ToObject());
+    Local<Array> inputs = args[0].As<Array>();
     assert(inputs->IsArray());
     assert(inputs->Length() > 0);
     svm_node *x = new svm_node[inputs->Length() + 1];
     obj->getSvmNodes(inputs, x);
     double prediction = obj->predict(x);
     delete[] x;
-    NanReturnValue(Number::New(prediction));
+    NanReturnValue(NanNew<Number>(prediction));
 }
 
 NAN_METHOD(NodeSvm::PredictAsync) {
@@ -203,7 +169,7 @@ NAN_METHOD(NodeSvm::PredictAsync) {
     assert(obj->isTrained());
     // chech params
     assert(args[0]->IsObject());
-    Local<Array> inputs = Array::Cast(*args[0]->ToObject());
+    Local<Array> inputs = args[0].As<Array>();
     assert(inputs->IsArray());
     assert(inputs->Length() > 0);
     assert(args[1]->IsFunction());
@@ -223,7 +189,7 @@ NAN_METHOD(NodeSvm::PredictProbabilities) {
     // chech params
     assert(args[0]->IsObject());
 
-    Local<Array> inputs = Array::Cast(*args[0]->ToObject());
+    Local<Array> inputs = args[0].As<Array>();
     assert(inputs->IsArray());
     assert(inputs->Length() > 0);
     svm_node *x = new svm_node[inputs->Length() + 1];
@@ -237,7 +203,7 @@ NAN_METHOD(NodeSvm::PredictProbabilities) {
     // Create the result array
     Handle<Array> probs = NanNew<Array>(nbClass);
     for (int j=0; j < nbClass; j++){
-        probs->Set(j, Number::New(prob_estimates[j]));
+        probs->Set(j, NanNew<Number>(prob_estimates[j]));
     }
     delete[] prob_estimates;
     delete[] x;
@@ -252,7 +218,7 @@ NAN_METHOD(NodeSvm::PredictProbabilitiesAsync) {
     assert(obj->isTrained());
     // chech params
     assert(args[0]->IsObject());
-    Local<Array> inputs = Array::Cast(*args[0]->ToObject());
+    Local<Array> inputs = args[0].As<Array>();
     assert(inputs->IsArray());
     assert(inputs->Length() > 0);
     assert(args[1]->IsFunction());
@@ -301,19 +267,14 @@ void NodeSvm::Init(Handle<Object> exports){
 
     tpl->PrototypeTemplate()->Set(NanNew<String>("predictProbabilitiesAsync"),
     NanNew<FunctionTemplate>(NodeSvm::PredictProbabilitiesAsync)->GetFunction());
-
-    // tpl->PrototypeTemplate()->Set(NanNew<String>("saveToFile"),
-    // NanNew<FunctionTemplate>(NodeSvm::SaveToFile)->GetFunction());
-
-    // tpl->PrototypeTemplate()->Set(NanNew<String>("loadFromFile"),
-    // NanNew<FunctionTemplate>(NodeSvm::LoadFromFile)->GetFunction());
 
     tpl->PrototypeTemplate()->Set(NanNew<String>("loadFromModel"),
     NanNew<FunctionTemplate>(NodeSvm::SetModel)->GetFunction());
 
     tpl->PrototypeTemplate()->Set(NanNew<String>("getModel"),
     NanNew<FunctionTemplate>(NodeSvm::GetModel)->GetFunction());
 
-    constructor = Persistent<Function>::New(tpl->GetFunction());
-    exports->Set(NanNew<String>("NodeSvm"), constructor);
+    //constructor = Persistent<Function>::New(tpl->GetFunction());
+    exports->Set(NanNew<String>("NodeSvm"), tpl->GetFunction());
+    NanAssignPersistent(constructor, tpl->GetFunction());
 }
diff --git a/src/node-svm/node-svm.h b/src/node-svm/node-svm.h
@@ -191,7 +191,7 @@ class NodeSvm : public node::ObjectWrap
             // rho
             assert(obj->Has(NanNew<String>("rho")));
             assert(obj->Get(NanNew<String>("rho"))->IsArray());
-            Local<Array> rho = Array::Cast(*obj->Get(NanNew<String>("rho"))->ToObject());
+            Local<Array> rho = obj->Get(NanNew<String>("rho")).As<Array>();
             assert(rho->Length()==n);
             new_model->rho = new double[n];
             for(unsigned int i=0;i<n;i++){
@@ -203,7 +203,7 @@ class NodeSvm : public node::ObjectWrap
             // classes
             if (obj->Has(NanNew<String>("labels"))){
                 assert(obj->Get(NanNew<String>("labels"))->IsArray());
-                Local<Array> labels = Array::Cast(*obj->Get(NanNew<String>("labels"))->ToObject());
+                Local<Array> labels = obj->Get(NanNew<String>("labels")).As<Array>();
                 //assert(labels->Length()==new_model->nr_class);
                 new_model->label = new int[new_model->nr_class];
                 for(int i=0;i<new_model->nr_class;i++){
@@ -214,7 +214,7 @@ class NodeSvm : public node::ObjectWrap
                 // nSV
                 assert(obj->Has(NanNew<String>("nbSupportVectors")));
                 assert(obj->Get(NanNew<String>("nbSupportVectors"))->IsArray());
-                Local<Array> nbSupportVectors = Array::Cast(*obj->Get(NanNew<String>("nbSupportVectors"))->ToObject());
+                Local<Array> nbSupportVectors = obj->Get(NanNew<String>("nbSupportVectors")).As<Array>();
                 assert((int)nbSupportVectors->Length() == new_model->nr_class);
                 new_model->nSV = new int[new_model->nr_class];
                 for (int i=0;i<new_model->nr_class;i++){
@@ -227,7 +227,7 @@ class NodeSvm : public node::ObjectWrap
             // probA
             if (obj->Has(NanNew<String>("probA"))){
                 assert(obj->Get(NanNew<String>("probA"))->IsArray());
-                Local<Array> probA = Array::Cast(*obj->Get(NanNew<String>("probA"))->ToObject());
+                Local<Array> probA = obj->Get(NanNew<String>("probA")).As<Array>();
                 assert(probA->Length()==n);
                 new_model->probA = new double[n];
                 for(unsigned int i=0;i<n;i++){
@@ -240,7 +240,7 @@ class NodeSvm : public node::ObjectWrap
             // probB
             if (obj->Has(NanNew<String>("probB"))){
                 assert(obj->Get(NanNew<String>("probB"))->IsArray());
-                Local<Array> probB = Array::Cast(*obj->Get(NanNew<String>("probB"))->ToObject());
+                Local<Array> probB = obj->Get(NanNew<String>("probB")).As<Array>();
                 assert(probB->Length()==n);
                 new_model->probB = new double[n];
                 for(unsigned int i=0;i<n;i++){
@@ -255,7 +255,7 @@ class NodeSvm : public node::ObjectWrap
             // SV
             assert(obj->Has(NanNew<String>("supportVectors")));
             assert(obj->Get(NanNew<String>("supportVectors"))->IsArray());
-            Local<Array> supportVectors = Array::Cast(*obj->Get(NanNew<String>("supportVectors"))->ToObject());
+            Local<Array> supportVectors = obj->Get(NanNew<String>("supportVectors")).As<Array>();
             assert((int)supportVectors->Length() == new_model->l);
             int m = new_model->nr_class - 1;
             int l = new_model->l;
@@ -265,10 +265,10 @@ class NodeSvm : public node::ObjectWrap
 
             new_model->SV = new svm_node*[l];
             for(int i = 0; i < l; i++) {
-                Local<Array> ex = Array::Cast(*supportVectors->Get(i));
+                Local<Array> ex = supportVectors->Get(i).As<Array>();
                 assert(ex->Length()==2);
-                Local<Array> x = Array::Cast(*ex->Get(0));
-                Local<Array> y = Array::Cast(*ex->Get(1));
+                Local<Array> x = ex->Get(0).As<Array>();
+                Local<Array> y = ex->Get(1).As<Array>();
 
                 new_model->SV[i] = new svm_node[x->Length() + 1];
                 for(unsigned j = 0; j < x->Length(); ++j) {
@@ -287,7 +287,7 @@ class NodeSvm : public node::ObjectWrap
             assert(model!=NULL);
         };
 
-        Handle<Value> setSvmProblem(Local<Array> dataset){
+        void setSvmProblem(Local<Array> dataset){
             NanScope();
             struct svm_problem *prob = new svm_problem();
             prob->l = 0;
@@ -301,15 +301,15 @@ class NodeSvm : public node::ObjectWrap
             for (unsigned i=0; i < dataset->Length(); i++) {
                 Local<Value> t = dataset->Get(i);
                 assert(t->IsArray());
-                Local<Array> ex = Array::Cast(*t);
+                Local<Array> ex = t.As<Array>();
                 assert(ex->Length() == 2);
 
                 Local<Value> tin = ex->Get(0);
                 Local<Value> tout = ex->Get(1);
                 assert(tin->IsArray());
                 assert(tout->IsNumber());
 
-                Local<Array> x = Array::Cast(*tin);
+                Local<Array> x = tin.As<Array>();
                 if (nb_features == -1){
                     nb_features = x->Length();
                 }
@@ -322,8 +322,8 @@ class NodeSvm : public node::ObjectWrap
             prob->x = new svm_node*[dataset->Length()];
             for (unsigned i = 0; i < dataset->Length(); i++) {
                 prob->x[i] = new svm_node[nb_features + 1];
-                Local<Array> ex = Array::Cast(*dataset->Get(i));
-                Local<Array> x = Array::Cast(*ex->Get(0));
+                Local<Array> ex = dataset->Get(i).As<Array>();
+                Local<Array> x = ex->Get(0).As<Array>();
                 for (unsigned j = 0; j < x->Length(); ++j) {
                     double xi = x->Get(j)->NumberValue();
                     prob->x[i][j].index = j+1;
@@ -335,7 +335,6 @@ class NodeSvm : public node::ObjectWrap
                 prob->y[i] = y;
             }
             trainingProblem = prob;
-            NanReturnUndefined();
         };
 
         void train(){
@@ -478,7 +477,6 @@ class NodeSvm : public node::ObjectWrap
                 model->param.kernel_type == SIGMOID){
                 parameters->Set(NanNew<String>("r"), NanNew<Number>(model->param.coef0));
             }
-
 
             // Handle<Array> weightLabels = NanNew<Array>(model->param.nr_weight);
             // Handle<Array> weights = NanNew<Array>(model->param.nr_weight);

diff --git a/src/node-svm/prediction-worker.h b/src/node-svm/prediction-worker.h
@@ -31,7 +31,7 @@ class PredictionWorker : public NanAsyncWorker {
   void HandleOKCallback () {
     NanScope();
     Local<Value> argv[] = {
-      Number::New(prediction)
+      NanNew<Number>(prediction)
     };
     callback->Call(1, argv);
   };

diff --git a/src/node-svm/probability-prediction-worker.h b/src/node-svm/probability-prediction-worker.h
@@ -36,12 +36,12 @@ class ProbabilityPredictionWorker : public NanAsyncWorker {
   void HandleOKCallback () {
     NanScope();
     // Create the result array
-    Handle<Array> probs = Array::New(nbClass);
+    Handle<Array> probs = NanNew<Array>(nbClass);
     for (int j=0; j < nbClass; j++){
-      probs->Set(j, Number::New(prob_estimates[j]));
+      probs->Set(j, NanNew<Number>(prob_estimates[j]));
     }
     Local<Value> argv[] = {
-      Local<Value>::New(probs)
+      NanNew<Value>(probs)
     };
     callback->Call(1, argv);
   };

diff --git a/src/node-svm/training-worker.h b/src/node-svm/training-worker.h
@@ -35,7 +35,6 @@ class TrainingWorker : public NanAsyncWorker {
     Local<Value> argv[0];
 #endif
 
-
     callback->Call(0, argv);
   };