Restoring authorship annotation for <[email protected]>. Commit 2 of 2.

3 files changed, 23 insertions, 23 deletions

diff --git a/library/cpp/linear_regression/linear_regression.h b/library/cpp/linear_regression/linear_regression.h
index 20b3ae1e539..e57de5ff6cc 100644
--- a/library/cpp/linear_regression/linear_regression.h
+++ b/library/cpp/linear_regression/linear_regression.h
@@ -146,12 +146,12 @@ public:
     bool Add(const double* featuresBegin, const double* featuresEnd, const double* goalsBegin, const double* weightsBegin);
 
     bool Add(const TVector<double>& features, const TVector<double>& goals) {
-        Y_ASSERT(features.size() == goals.size()); 
+        Y_ASSERT(features.size() == goals.size());
         return Add(features.data(), features.data() + features.size(), goals.data());
     }
 
     bool Add(const TVector<double>& features, const TVector<double>& goals, const TVector<double>& weights) {
-        Y_ASSERT(features.size() == goals.size() && features.size() == weights.size()); 
+        Y_ASSERT(features.size() == goals.size() && features.size() == weights.size());
         return Add(features.data(), features.data() + features.size(), goals.data(), weights.data());
     }
 
@@ -239,7 +239,7 @@ struct TTransformationParameters {
     double FeatureOffset = 0.;
     double FeatureNormalizer = 1.;
 
-    Y_SAVELOAD_DEFINE(RegressionFactor, 
+    Y_SAVELOAD_DEFINE(RegressionFactor,
                       RegressionIntercept,
                       FeatureOffset,
                       FeatureNormalizer);
@@ -251,7 +251,7 @@ private:
     TTransformationParameters TransformationParameters;
 
 public:
-    Y_SAVELOAD_DEFINE(TransformationType, TransformationParameters); 
+    Y_SAVELOAD_DEFINE(TransformationType, TransformationParameters);
 
     TFeaturesTransformer() = default;
 
@@ -273,7 +273,7 @@ public:
                 return TransformationParameters.RegressionIntercept + TransformationParameters.RegressionFactor * transformedValue;
             }
         }
-        Y_ASSERT(0); 
+        Y_ASSERT(0);
         return 0.;
     }
 };
diff --git a/library/cpp/linear_regression/linear_regression_ut.cpp b/library/cpp/linear_regression/linear_regression_ut.cpp
index 991a95c0d09..e71a16b67a1 100644
--- a/library/cpp/linear_regression/linear_regression_ut.cpp
+++ b/library/cpp/linear_regression/linear_regression_ut.cpp
@@ -13,8 +13,8 @@ namespace {
     }
 }
 
-Y_UNIT_TEST_SUITE(TLinearRegressionTest) { 
-    Y_UNIT_TEST(MeanAndDeviationTest) { 
+Y_UNIT_TEST_SUITE(TLinearRegressionTest) {
+    Y_UNIT_TEST(MeanAndDeviationTest) {
         TVector<double> arguments;
         TVector<double> weights;
 
@@ -77,7 +77,7 @@ Y_UNIT_TEST_SUITE(TLinearRegressionTest) {
         ValueIsCorrect(deviationCalculator.GetDeviation(), checkRemovingDeviationCalculator.GetDeviation(), 1e-5);
     }
 
-    Y_UNIT_TEST(CovariationTest) { 
+    Y_UNIT_TEST(CovariationTest) {
         TVector<double> firstValues;
         TVector<double> secondValues;
         TVector<double> weights;
@@ -176,15 +176,15 @@ Y_UNIT_TEST_SUITE(TLinearRegressionTest) {
         }
     }
 
-    Y_UNIT_TEST(FastSLRTest) { 
+    Y_UNIT_TEST(FastSLRTest) {
         SLRTest<TFastSLRSolver>();
     }
 
-    Y_UNIT_TEST(KahanSLRTest) { 
+    Y_UNIT_TEST(KahanSLRTest) {
         SLRTest<TKahanSLRSolver>();
     }
 
-    Y_UNIT_TEST(SLRTest) { 
+    Y_UNIT_TEST(SLRTest) {
         SLRTest<TSLRSolver>();
     }
 
@@ -231,11 +231,11 @@ Y_UNIT_TEST_SUITE(TLinearRegressionTest) {
         UNIT_ASSERT_DOUBLES_EQUAL(lrSolver.SumSquaredErrors(), expectedSumSquaredErrors, expectedSumSquaredErrors * 0.01);
     }
 
-    Y_UNIT_TEST(FastLRTest) { 
+    Y_UNIT_TEST(FastLRTest) {
         LinearRegressionTest<TFastLinearRegressionSolver>();
     }
 
-    Y_UNIT_TEST(LRTest) { 
+    Y_UNIT_TEST(LRTest) {
         LinearRegressionTest<TLinearRegressionSolver>();
     }
 
@@ -275,31 +275,31 @@ Y_UNIT_TEST_SUITE(TLinearRegressionTest) {
         UNIT_ASSERT_DOUBLES_EQUAL(rmse, 0., 1e-3);
     }
 
-    Y_UNIT_TEST(SigmaTest100) { 
+    Y_UNIT_TEST(SigmaTest100) {
         TransformationTest(ETransformationType::TT_SIGMA, 100);
     }
 
-    Y_UNIT_TEST(SigmaTest1000) { 
+    Y_UNIT_TEST(SigmaTest1000) {
         TransformationTest(ETransformationType::TT_SIGMA, 1000);
     }
 
-    Y_UNIT_TEST(SigmaTest10000) { 
+    Y_UNIT_TEST(SigmaTest10000) {
         TransformationTest(ETransformationType::TT_SIGMA, 10000);
     }
 
-    Y_UNIT_TEST(SigmaTest100000) { 
+    Y_UNIT_TEST(SigmaTest100000) {
         TransformationTest(ETransformationType::TT_SIGMA, 100000);
     }
 
-    Y_UNIT_TEST(SigmaTest1000000) { 
+    Y_UNIT_TEST(SigmaTest1000000) {
         TransformationTest(ETransformationType::TT_SIGMA, 1000000);
     }
 
-    Y_UNIT_TEST(SigmaTest10000000) { 
+    Y_UNIT_TEST(SigmaTest10000000) {
         TransformationTest(ETransformationType::TT_SIGMA, 10000000);
     }
 
-    Y_UNIT_TEST(ResetCalculatorTest) { 
+    Y_UNIT_TEST(ResetCalculatorTest) {
         TVector<double> arguments;
         TVector<double> weights;
         const double eps = 1e-10;
diff --git a/library/cpp/linear_regression/welford.h b/library/cpp/linear_regression/welford.h
index a39800974c0..ee865d66937 100644
--- a/library/cpp/linear_regression/welford.h
+++ b/library/cpp/linear_regression/welford.h
@@ -11,7 +11,7 @@ private:
     TKahanAccumulator<double> SumWeights;
 
 public:
-    Y_SAVELOAD_DEFINE(Mean, SumWeights); 
+    Y_SAVELOAD_DEFINE(Mean, SumWeights);
 
     void Multiply(const double value);
     void Add(const double value, const double weight = 1.);
@@ -40,7 +40,7 @@ private:
     TKahanAccumulator<double> SumWeights;
 
 public:
-    Y_SAVELOAD_DEFINE(Covariation, FirstValueMean, SecondValueMean, SumWeights); 
+    Y_SAVELOAD_DEFINE(Covariation, FirstValueMean, SecondValueMean, SumWeights);
 
     void Add(const double firstValue, const double secondValue, const double weight = 1.);
     void Remove(const double firstValue, const double secondValue, const double weight = 1.);
@@ -62,7 +62,7 @@ private:
     TMeanCalculator MeanCalculator;
 
 public:
-    Y_SAVELOAD_DEFINE(Deviation, MeanCalculator); 
+    Y_SAVELOAD_DEFINE(Deviation, MeanCalculator);
 
     void Add(const double value, const double weight = 1.);
     void Remove(const double value, const double weight = 1.);