Restoring authorship annotation for <nkmakarov@yandex-team.ru>. Commit 2 of 2.

4 files changed, 90 insertions, 90 deletions

diff --git a/library/cpp/linear_regression/linear_model.h b/library/cpp/linear_regression/linear_model.h
index 4efd857374..8bb050cff7 100644
--- a/library/cpp/linear_regression/linear_model.h
+++ b/library/cpp/linear_regression/linear_model.h
@@ -5,8 +5,8 @@
 
 #include <util/ysaveload.h>
 
-#include <utility> 
- 
+#include <utility>
+
 class TLinearModel {
 private:
     TVector<double> Coefficients;
diff --git a/library/cpp/linear_regression/linear_regression_ut.cpp b/library/cpp/linear_regression/linear_regression_ut.cpp
index 0a31a6e25c..e71a16b67a 100644
--- a/library/cpp/linear_regression/linear_regression_ut.cpp
+++ b/library/cpp/linear_regression/linear_regression_ut.cpp
@@ -298,77 +298,77 @@ Y_UNIT_TEST_SUITE(TLinearRegressionTest) {
     Y_UNIT_TEST(SigmaTest10000000) {
         TransformationTest(ETransformationType::TT_SIGMA, 10000000);
     }
- 
+
     Y_UNIT_TEST(ResetCalculatorTest) {
         TVector<double> arguments;
         TVector<double> weights;
-        const double eps = 1e-10; 
- 
-        const size_t argumentsCount = 100; 
-        for (size_t i = 0; i < argumentsCount; ++i) { 
-            arguments.push_back(i); 
-            weights.push_back(i); 
-        } 
- 
-        TDeviationCalculator deviationCalculator1, deviationCalculator2; 
-        TMeanCalculator meanCalculator1, meanCalculator2; 
-        TCovariationCalculator covariationCalculator1, covariationCalculator2; 
-        for (size_t i = 0; i < arguments.size(); ++i) { 
-            meanCalculator1.Add(arguments[i], weights[i]); 
-            meanCalculator2.Add(arguments[i], weights[i]); 
-            deviationCalculator1.Add(arguments[i], weights[i]); 
-            deviationCalculator2.Add(arguments[i], weights[i]); 
-            covariationCalculator1.Add(arguments[i], arguments[arguments.size() - i - 1], weights[i]); 
-            covariationCalculator2.Add(arguments[i], arguments[arguments.size() - i - 1], weights[i]); 
-        } 
- 
-        UNIT_ASSERT_DOUBLES_EQUAL(meanCalculator1.GetMean(), meanCalculator2.GetMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(meanCalculator1.GetSumWeights(), meanCalculator2.GetSumWeights(), eps); 
- 
-        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetMean(), deviationCalculator2.GetMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetDeviation(), deviationCalculator2.GetDeviation(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetStdDev(), deviationCalculator2.GetStdDev(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetSumWeights(), deviationCalculator2.GetSumWeights(), eps); 
- 
-        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetFirstValueMean(), covariationCalculator2.GetFirstValueMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetSecondValueMean(), covariationCalculator2.GetSecondValueMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetCovariation(), covariationCalculator2.GetCovariation(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetSumWeights(), covariationCalculator2.GetSumWeights(), eps); 
- 
-        meanCalculator2.Reset(); 
-        deviationCalculator2.Reset(); 
-        covariationCalculator2.Reset(); 
- 
-        UNIT_ASSERT_DOUBLES_EQUAL(0.0, meanCalculator2.GetMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(0.0, meanCalculator2.GetSumWeights(), eps); 
- 
-        UNIT_ASSERT_DOUBLES_EQUAL(0.0, deviationCalculator2.GetMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(0.0, deviationCalculator2.GetDeviation(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(0.0, deviationCalculator2.GetStdDev(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(0.0, deviationCalculator2.GetSumWeights(), eps); 
- 
-        UNIT_ASSERT_DOUBLES_EQUAL(0.0, covariationCalculator2.GetFirstValueMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(0.0, covariationCalculator2.GetSecondValueMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(0.0, covariationCalculator2.GetCovariation(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(0.0, covariationCalculator2.GetSumWeights(), eps); 
- 
-        for (size_t i = 0; i < arguments.size(); ++i) { 
-            meanCalculator2.Add(arguments[i], weights[i]); 
-            deviationCalculator2.Add(arguments[i], weights[i]); 
-            covariationCalculator2.Add(arguments[i], arguments[arguments.size() - i - 1], weights[i]); 
-        } 
- 
-        UNIT_ASSERT_DOUBLES_EQUAL(meanCalculator1.GetMean(), meanCalculator2.GetMean(), 1e-10); 
-        UNIT_ASSERT_DOUBLES_EQUAL(meanCalculator1.GetSumWeights(), meanCalculator2.GetSumWeights(), 1e-10); 
- 
-        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetMean(), deviationCalculator2.GetMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetDeviation(), deviationCalculator2.GetDeviation(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetStdDev(), deviationCalculator2.GetStdDev(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetSumWeights(), deviationCalculator2.GetSumWeights(), eps); 
- 
-        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetFirstValueMean(), covariationCalculator2.GetFirstValueMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetSecondValueMean(), covariationCalculator2.GetSecondValueMean(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetCovariation(), covariationCalculator2.GetCovariation(), eps); 
-        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetSumWeights(), covariationCalculator2.GetSumWeights(), eps); 
-    } 
+        const double eps = 1e-10;
+
+        const size_t argumentsCount = 100;
+        for (size_t i = 0; i < argumentsCount; ++i) {
+            arguments.push_back(i);
+            weights.push_back(i);
+        }
+
+        TDeviationCalculator deviationCalculator1, deviationCalculator2;
+        TMeanCalculator meanCalculator1, meanCalculator2;
+        TCovariationCalculator covariationCalculator1, covariationCalculator2;
+        for (size_t i = 0; i < arguments.size(); ++i) {
+            meanCalculator1.Add(arguments[i], weights[i]);
+            meanCalculator2.Add(arguments[i], weights[i]);
+            deviationCalculator1.Add(arguments[i], weights[i]);
+            deviationCalculator2.Add(arguments[i], weights[i]);
+            covariationCalculator1.Add(arguments[i], arguments[arguments.size() - i - 1], weights[i]);
+            covariationCalculator2.Add(arguments[i], arguments[arguments.size() - i - 1], weights[i]);
+        }
+
+        UNIT_ASSERT_DOUBLES_EQUAL(meanCalculator1.GetMean(), meanCalculator2.GetMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(meanCalculator1.GetSumWeights(), meanCalculator2.GetSumWeights(), eps);
+
+        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetMean(), deviationCalculator2.GetMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetDeviation(), deviationCalculator2.GetDeviation(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetStdDev(), deviationCalculator2.GetStdDev(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetSumWeights(), deviationCalculator2.GetSumWeights(), eps);
+
+        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetFirstValueMean(), covariationCalculator2.GetFirstValueMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetSecondValueMean(), covariationCalculator2.GetSecondValueMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetCovariation(), covariationCalculator2.GetCovariation(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetSumWeights(), covariationCalculator2.GetSumWeights(), eps);
+
+        meanCalculator2.Reset();
+        deviationCalculator2.Reset();
+        covariationCalculator2.Reset();
+
+        UNIT_ASSERT_DOUBLES_EQUAL(0.0, meanCalculator2.GetMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(0.0, meanCalculator2.GetSumWeights(), eps);
+
+        UNIT_ASSERT_DOUBLES_EQUAL(0.0, deviationCalculator2.GetMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(0.0, deviationCalculator2.GetDeviation(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(0.0, deviationCalculator2.GetStdDev(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(0.0, deviationCalculator2.GetSumWeights(), eps);
+
+        UNIT_ASSERT_DOUBLES_EQUAL(0.0, covariationCalculator2.GetFirstValueMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(0.0, covariationCalculator2.GetSecondValueMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(0.0, covariationCalculator2.GetCovariation(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(0.0, covariationCalculator2.GetSumWeights(), eps);
+
+        for (size_t i = 0; i < arguments.size(); ++i) {
+            meanCalculator2.Add(arguments[i], weights[i]);
+            deviationCalculator2.Add(arguments[i], weights[i]);
+            covariationCalculator2.Add(arguments[i], arguments[arguments.size() - i - 1], weights[i]);
+        }
+
+        UNIT_ASSERT_DOUBLES_EQUAL(meanCalculator1.GetMean(), meanCalculator2.GetMean(), 1e-10);
+        UNIT_ASSERT_DOUBLES_EQUAL(meanCalculator1.GetSumWeights(), meanCalculator2.GetSumWeights(), 1e-10);
+
+        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetMean(), deviationCalculator2.GetMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetDeviation(), deviationCalculator2.GetDeviation(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetStdDev(), deviationCalculator2.GetStdDev(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(deviationCalculator1.GetSumWeights(), deviationCalculator2.GetSumWeights(), eps);
+
+        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetFirstValueMean(), covariationCalculator2.GetFirstValueMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetSecondValueMean(), covariationCalculator2.GetSecondValueMean(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetCovariation(), covariationCalculator2.GetCovariation(), eps);
+        UNIT_ASSERT_DOUBLES_EQUAL(covariationCalculator1.GetSumWeights(), covariationCalculator2.GetSumWeights(), eps);
+    }
 }
diff --git a/library/cpp/linear_regression/welford.cpp b/library/cpp/linear_regression/welford.cpp
index 509e80e970..e27b1994f6 100644
--- a/library/cpp/linear_regression/welford.cpp
+++ b/library/cpp/linear_regression/welford.cpp
@@ -1,5 +1,5 @@
 #include "welford.h"
- 
+
 #include <util/generic/ymath.h>
 
 void TMeanCalculator::Multiply(const double value) {
@@ -28,10 +28,10 @@ double TMeanCalculator::GetSumWeights() const {
     return SumWeights.Get();
 }
 
-void TMeanCalculator::Reset() { 
-    *this = TMeanCalculator(); 
-} 
- 
+void TMeanCalculator::Reset() {
+    *this = TMeanCalculator();
+}
+
 void TCovariationCalculator::Add(const double firstValue, const double secondValue, const double weight /*= 1.*/) {
     SumWeights += weight;
     if (SumWeights.Get()) {
@@ -66,10 +66,10 @@ double TCovariationCalculator::GetSumWeights() const {
     return SumWeights.Get();
 }
 
-void TCovariationCalculator::Reset() { 
-    *this = TCovariationCalculator(); 
-} 
- 
+void TCovariationCalculator::Reset() {
+    *this = TCovariationCalculator();
+}
+
 void TDeviationCalculator::Add(const double value, const double weight /*= 1.*/) {
     const double lastMean = MeanCalculator.GetMean();
     MeanCalculator.Add(value, weight);
@@ -101,7 +101,7 @@ double TDeviationCalculator::GetStdDev() const {
 double TDeviationCalculator::GetSumWeights() const {
     return MeanCalculator.GetSumWeights();
 }
- 
-void TDeviationCalculator::Reset() { 
-    *this = TDeviationCalculator(); 
-} 
+
+void TDeviationCalculator::Reset() {
+    *this = TDeviationCalculator();
+}
diff --git a/library/cpp/linear_regression/welford.h b/library/cpp/linear_regression/welford.h
index 0706ac2cfa..ee865d6693 100644
--- a/library/cpp/linear_regression/welford.h
+++ b/library/cpp/linear_regression/welford.h
@@ -18,7 +18,7 @@ public:
     void Remove(const double value, const double weight = 1.);
     double GetMean() const;
     double GetSumWeights() const;
-    void Reset(); 
+    void Reset();
 
     bool operator<(const TMeanCalculator& other) const {
         return Mean < other.Mean;
@@ -51,8 +51,8 @@ public:
     double GetCovariation() const;
 
     double GetSumWeights() const;
- 
-    void Reset(); 
+
+    void Reset();
 };
 
 // accurately computes (w_1 * x_1 * x_1 + w_2 * x_2 * x_2 + ... + w_n * x_n * x_n) / (w_1 + w_2 + ... + w_n)
@@ -72,6 +72,6 @@ public:
     double GetStdDev() const;
 
     double GetSumWeights() const;
- 
-    void Reset(); 
+
+    void Reset();
 };