diff --git a/src/machineLearning/rapidGVF/rapidGVF.cpp b/src/machineLearning/rapidGVF/rapidGVF.cpp
index cc1d39f18008e73f4ee83924f69a807f0c6253d3..80db1da302ff3ad72c0ca8af55cfe75ac21e595e 100644
--- a/src/machineLearning/rapidGVF/rapidGVF.cpp
+++ b/src/machineLearning/rapidGVF/rapidGVF.cpp
@@ -15,7 +15,8 @@ rapidGVF::~rapidGVF() {}
 bool rapidGVF::train(const rapidmix::trainingData &newTrainingData)
 {
     
-    if (newTrainingData.trainingSet.size() < 1) {
+    if (newTrainingData.trainingSet.size() < 1)
+    {
         // no recorded phrase
         return false;
     }
@@ -31,12 +32,13 @@ bool rapidGVF::train(const rapidmix::trainingData &newTrainingData)
     }
     
     //Go through every phrase
-    for (int h = 0; h < newTrainingData.trainingSet.size(); ++h) {
+    for (int h = 0; h < newTrainingData.trainingSet.size(); ++h)
+    {
         gvf.startGesture();
-        for (int i = 0; i < newTrainingData.trainingSet[h].elements.size(); ++i) {
-            
+        for (int i = 0; i < newTrainingData.trainingSet[h].elements.size(); ++i)
+        {
             std::vector<double> vd = newTrainingData.trainingSet[h].elements[i].input;
-            
+
             // Using template <class InputIterator> vector to change for vec<double> to vec<float>
             std::vector<float> vf(vd.begin(), vd.end());
             this->currentGesture.addObservation(vf);
@@ -49,7 +51,8 @@ bool rapidGVF::train(const rapidmix::trainingData &newTrainingData)
 std::vector<double> rapidGVF::run(const std::vector<double> &inputVector)
 {
     
-    if (inputVector.size() == 0) {
+    if (inputVector.size() == 0)
+    {
         return std::vector<double>();
     }
     
diff --git a/tests/src/test_RapidLib.cpp b/tests/src/test_RapidLib.cpp
index ebf2b79cba128aec58da8c94199fd09530341b79..2dd0e193f4a68f02dfa5337ce110e32844e732b1 100644
--- a/tests/src/test_RapidLib.cpp
+++ b/tests/src/test_RapidLib.cpp
@@ -69,7 +69,6 @@ SCENARIO("Test kNN classification", "[machineLearning]")
     GIVEN("kNN object and training dataset")
     {
         rapidmix::staticClassification myKnn;
-        
         rapidmix::trainingData myData;
         REQUIRE(myData.recordSingleElement("cat", { 0.2, 0.7 }) == 1);
         REQUIRE(myData.recordSingleElement("dog", { 2.0, 44.2 }) == 3); // This is not 2, because phrases get numbers, too.