chart2/source/inc/ExponentialRegressionCurveCalculator.hxx | 3 -
chart2/source/inc/RegressionCalculationHelper.hxx | 12 ++++
chart2/source/tools/ExponentialRegressionCurveCalculator.cxx | 27 +++++++----
3 files changed, 32 insertions(+), 10 deletions(-)
New commits:
commit cad19fa8414b419f2e0f9ee88139e9b7a2dd4ff4
Author: Laurent Balland-Poirier <laurent.balland-poir...@laposte.net>
Date: Thu Apr 16 21:45:58 2015 +0200
tdf#70673 Exponential trendline: enable negative Y values
With a negative intercept, Y values can be negative
Rebase with forced intercept fec037e68f0dea164915fbfe1db4699a3861adf4
Conflicts:
chart2/source/tools/ExponentialRegressionCurveCalculator.cxx
Change-Id: Ie351c006fb1688ef3e657da7ce0789a9da1317f0
Reviewed-on: https://gerrit.libreoffice.org/15353
Reviewed-by: Philippe Jung <phil.j...@free.fr>
Tested-by: Philippe Jung <phil.j...@free.fr>
diff --git a/chart2/source/inc/ExponentialRegressionCurveCalculator.hxx
b/chart2/source/inc/ExponentialRegressionCurveCalculator.hxx
index 1247d41..782fb57 100644
--- a/chart2/source/inc/ExponentialRegressionCurveCalculator.hxx
+++ b/chart2/source/inc/ExponentialRegressionCurveCalculator.hxx
@@ -56,10 +56,11 @@ private:
throw (css::lang::IllegalArgumentException,
css::uno::RuntimeException, std::exception) SAL_OVERRIDE;
- // formula is: f(x) = exp(m_fLogIntercept) * exp( m_fLogSlope * x )
+ // formula is: f(x) = m_fSign * exp(m_fLogIntercept) * exp( m_fLogSlope *
x )
// mathematical model f(x) = Intercept * Slope^x
double m_fLogSlope;
double m_fLogIntercept;
+ double m_fSign;
};
} // namespace chart
diff --git a/chart2/source/inc/RegressionCalculationHelper.hxx
b/chart2/source/inc/RegressionCalculationHelper.hxx
index 32456cf..2e0e3a4 100644
--- a/chart2/source/inc/RegressionCalculationHelper.hxx
+++ b/chart2/source/inc/RegressionCalculationHelper.hxx
@@ -102,6 +102,18 @@ public:
}
};
+class isValidAndYNegative : public ::std::binary_function< double, double,
bool >
+{
+public:
+ inline bool operator()( double x, double y )
+ { return ! ( ::rtl::math::isNan( x ) ||
+ ::rtl::math::isNan( y ) ||
+ ::rtl::math::isInf( x ) ||
+ ::rtl::math::isInf( y ) ||
+ y >= 0.0 );
+ }
+};
+
class isValidAndBothPositive : public ::std::binary_function< double, double,
bool >
{
public:
diff --git a/chart2/source/tools/ExponentialRegressionCurveCalculator.cxx
b/chart2/source/tools/ExponentialRegressionCurveCalculator.cxx
index 3738d68..2e1dedd 100644
--- a/chart2/source/tools/ExponentialRegressionCurveCalculator.cxx
+++ b/chart2/source/tools/ExponentialRegressionCurveCalculator.cxx
@@ -50,25 +50,34 @@ void SAL_CALL
ExponentialRegressionCurveCalculator::recalculateRegression(
RegressionCalculationHelper::cleanup(
aXValues, aYValues,
RegressionCalculationHelper::isValidAndYPositive()));
+ m_fSign = 1.0;
- const size_t nMax = aValues.first.size();
+ size_t nMax = aValues.first.size();
if( nMax == 0 )
{
- ::rtl::math::setNan( & m_fLogSlope );
- ::rtl::math::setNan( & m_fLogIntercept );
- ::rtl::math::setNan( & m_fCorrelationCoeffitient );// actual it is
coefficient of determination
- return;
+ aValues = RegressionCalculationHelper::cleanup(
+ aXValues, aYValues,
+ RegressionCalculationHelper::isValidAndYNegative());
+ nMax = aValues.first.size();
+ if( nMax == 0 )
+ {
+ ::rtl::math::setNan( & m_fLogSlope );
+ ::rtl::math::setNan( & m_fLogIntercept );
+ ::rtl::math::setNan( & m_fCorrelationCoeffitient );// actual it is
coefficient of determination
+ return;
+ }
+ m_fSign = -1.0;
}
double fAverageX = 0.0, fAverageY = 0.0;
- double fLogIntercept = mForceIntercept ? log(mInterceptValue) : 0.0;
+ double fLogIntercept = ( mForceIntercept && (m_fSign * mInterceptValue)>0
) ? log(m_fSign * mInterceptValue) : 0.0;
std::vector<double> yVector;
yVector.resize(nMax, 0.0);
size_t i = 0;
for( i = 0; i < nMax; ++i )
{
- double yValue = log(aValues.second[i]);
+ double yValue = log( m_fSign *aValues.second[i] );
if (mForceIntercept)
{
yValue -= fLogIntercept;
@@ -111,7 +120,7 @@ double SAL_CALL
ExponentialRegressionCurveCalculator::getCurveValue( double x )
if( ! ( ::rtl::math::isNan( m_fLogSlope ) ||
::rtl::math::isNan( m_fLogIntercept )))
{
- fResult = exp(m_fLogIntercept + x * m_fLogSlope);
+ fResult = m_fSign * exp(m_fLogIntercept + x * m_fLogSlope);
}
return fResult;
@@ -146,7 +155,7 @@ OUString
ExponentialRegressionCurveCalculator::ImplGetRepresentation(
const uno::Reference< util::XNumberFormatter >& xNumFormatter,
::sal_Int32 nNumberFormatKey ) const
{
- double fIntercept = exp(m_fLogIntercept);
+ double fIntercept = m_fSign * exp(m_fLogIntercept);
double fSlope = exp(m_fLogSlope);
bool bHasSlope = !rtl::math::approxEqual( fSlope, 1.0 );
bool bHasIntercept = !rtl::math::approxEqual( fIntercept, 1.0 );
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