[Libreoffice-commits] core.git: chart2/source

[Laurent Balland-Poirier]

 chart2/source/tools/PolynomialRegressionCurveCalculator.cxx |   15 +++++++++++-
 1 file changed, 14 insertions(+), 1 deletion(-)

New commits:
commit 9e67015be6e9e53e19466117d692de17c18463da
Author: Laurent Balland-Poirier <laurent.balland-poirier at laposte.net>
Date:   Wed Jan 8 22:37:52 2014 +0100

    fdo#73374 Trendline: correct R^2 for forced intercept
    
    In case of forced intercept, R^2 must be calculated in a different way.
    This patch calculates R^2 of trend line in the same way as LINEST
    function.
    
    Change-Id: I3ac361f014569261f05d513acb3428de5c7641ab
    Reviewed-on: https://gerrit.libreoffice.org/7326
    Reviewed-by: Tomaž Vajngerl <quikee at gmail.com>
    Tested-by: Tomaž Vajngerl <quikee at gmail.com>

diff --git a/chart2/source/tools/PolynomialRegressionCurveCalculator.cxx b/chart2/source/tools/PolynomialRegressionCurveCalculator.cxx
index 951c071..21b564d 100644
--- a/chart2/source/tools/PolynomialRegressionCurveCalculator.cxx
+++ b/chart2/source/tools/PolynomialRegressionCurveCalculator.cxx
@@ -167,6 +167,8 @@ void SAL_CALL PolynomialRegressionCurveCalculator::recalculateRegression(
     // Calculate correlation coeffitient
     double aSumError = 0.0;
     double aSumTotal = 0.0;
+    double aSumYpred2 = 0.0;
+    double aSumYactual2 = 0.0;
 
     for( sal_Int32 i = 0; i < aNoValues; i++ )
     {
@@ -175,9 +177,20 @@ void SAL_CALL PolynomialRegressionCurveCalculator::recalculateRegression(
         double yPredicted = getCurveValue( xValue );
         aSumTotal += (yActual - yAverage) * (yActual - yAverage);
         aSumError += (yActual - yPredicted) * (yActual - yPredicted);
+        aSumYpred2 += yPredicted * yPredicted;
+        aSumYactual2 += yActual * yActual;
     }
 
-    double aRSquared = 1.0 - (aSumError / aSumTotal);
+    double aRSquared = 0.0;
+    if(mForceIntercept)
+    {
+        if(aSumYactual2 != 0.0)
+            aRSquared = aSumYpred2 / aSumYactual2;
+    }
+    else
+    {
+        aRSquared = 1.0 - (aSumError / aSumTotal);
+    }
 
     if (aRSquared > 0.0)
         m_fCorrelationCoeffitient = std::sqrt(aRSquared);