Restoring authorship annotation for <nkmakarov@yandex-team.ru>. Commit 1 of 2.

1 files changed, 70 insertions, 70 deletions

diff --git a/library/cpp/linear_regression/linear_regression_ut.cpp b/library/cpp/linear_regression/linear_regression_ut.cpp
index e71a16b67a..0a31a6e25c 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); 
+    } 
 }