diff --git a/src/shared/algorithms/SFD/SFDAscent.cpp b/src/shared/algorithms/SFD/SFDAscent.cpp
index 8842f722197175f5c80a0c8c9362e6305d56c2a8..355faf8e2c7d5a1b9d09b51f6b2fe62721d9a423 100644
--- a/src/shared/algorithms/SFD/SFDAscent.cpp
+++ b/src/shared/algorithms/SFD/SFDAscent.cpp
@@ -29,13 +29,16 @@
 namespace Boardcore
 {
 
-SFDAscent::SFDAscent(const SFDAscentConfig& config) : svm(config.modelParameters) {}
+SFDAscent::SFDAscent(const SFDAscentConfig& config)
+    : svm(config.modelParameters)
+{
+}
 
 SFDAscent::FeaturesVec SFDAscent::getFeatures(const SFDVectorIn& input)
 {
     float delta, min, max, u, var, s2, m4, rfmean, rfvar;
     SFDVectorIn rfourier, x0;
-    SFDVectorIn data        = SFDVectorIn::Zero();
+    SFDVectorIn data     = SFDVectorIn::Zero();
     FeaturesVec features = FeaturesVec::Zero();
 
     min   = input.minCoeff();
@@ -51,7 +54,7 @@ SFDAscent::FeaturesVec SFDAscent::getFeatures(const SFDVectorIn& input)
 
     rfourier = FFT32::fft(data).real();  // TODO: fix complex -> float
     rfmean   = rfourier.mean();
-    rfvar    = (rfourier - rfmean * SFDVectorIn::Ones()).squaredNorm() / LEN_CHUNK;
+    rfvar = (rfourier - rfmean * SFDVectorIn::Ones()).squaredNorm() / LEN_CHUNK;
 
     features(0) = delta;
     features(1) = var;
diff --git a/src/shared/algorithms/SFD/SFDDescent.cpp b/src/shared/algorithms/SFD/SFDDescent.cpp
index 447d38812a3e24a1c09fbe007c5a7783451a35b7..ed7fad969cc3e702e7b6ef8895592b2dc4dcc679 100644
--- a/src/shared/algorithms/SFD/SFDDescent.cpp
+++ b/src/shared/algorithms/SFD/SFDDescent.cpp
@@ -27,7 +27,8 @@
 namespace Boardcore
 {
 
-SFDDescent::SFDDescent(const SFDDescentConfig& config) : svm(config.modelParameters)
+SFDDescent::SFDDescent(const SFDDescentConfig& config)
+    : svm(config.modelParameters)
 {
 }
 
@@ -35,7 +36,7 @@ SFDDescent::FeaturesVec SFDDescent::getFeatures(const SFDVectorIn& input)
 {
     float delta, min, max, u, s2, m3, m4, rms;
     SFDVectorIn rfourier, x0;
-    SFDVectorIn data        = SFDVectorIn::Zero();
+    SFDVectorIn data     = SFDVectorIn::Zero();
     FeaturesVec features = FeaturesVec::Zero();
 
     min   = input.minCoeff();