1 /* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
3 * This file is part of the LibreOffice project.
5 * This Source Code Form is subject to the terms of the Mozilla Public
6 * License, v. 2.0. If a copy of the MPL was not distributed with this
7 * file, You can obtain one at http://mozilla.org/MPL/2.0/.
9 * This file incorporates work covered by the following license notice:
11 * Licensed to the Apache Software Foundation (ASF) under one or more
12 * contributor license agreements. See the NOTICE file distributed
13 * with this work for additional information regarding copyright
14 * ownership. The ASF licenses this file to you under the Apache
15 * License, Version 2.0 (the "License"); you may not use this file
16 * except in compliance with the License. You may obtain a copy of
17 * the License at http://www.apache.org/licenses/LICENSE-2.0 .
20 #include <MeanValueRegressionCurveCalculator.hxx>
22 #include <osl/diagnose.h>
27 using namespace ::com::sun::star
;
32 MeanValueRegressionCurveCalculator::MeanValueRegressionCurveCalculator() :
33 m_fMeanValue( std::numeric_limits
<double>::quiet_NaN() )
37 MeanValueRegressionCurveCalculator::~MeanValueRegressionCurveCalculator()
40 // ____ XRegressionCurveCalculator ____
41 void SAL_CALL
MeanValueRegressionCurveCalculator::recalculateRegression(
42 const uno::Sequence
< double >& /*aXValues*/,
43 const uno::Sequence
< double >& aYValues
)
45 const sal_Int32 nDataLength
= aYValues
.getLength();
46 sal_Int32 nMax
= nDataLength
;
48 const double * pY
= aYValues
.getConstArray();
50 for( sal_Int32 i
= 0; i
< nDataLength
; ++i
)
52 if( std::isnan( pY
[i
] ) ||
59 m_fCorrelationCoefficient
= 0.0;
63 m_fMeanValue
= std::numeric_limits
<double>::quiet_NaN();
67 m_fMeanValue
= fSumY
/ static_cast< double >( nMax
);
69 // correlation coefficient: standard deviation
72 double fErrorSum
= 0.0;
73 for( sal_Int32 i
= 0; i
< nDataLength
; ++i
)
75 if( !std::isnan( pY
[i
] ) &&
78 double v
= m_fMeanValue
- pY
[i
];
82 OSL_ASSERT( fErrorSum
>= 0.0 );
83 m_fCorrelationCoefficient
= sqrt( fErrorSum
/ (nMax
- 1 ));
88 double SAL_CALL
MeanValueRegressionCurveCalculator::getCurveValue( double /*x*/ )
93 uno::Sequence
< geometry::RealPoint2D
> SAL_CALL
MeanValueRegressionCurveCalculator::getCurveValues(
94 double min
, double max
, ::sal_Int32 nPointCount
,
95 const uno::Reference
< chart2::XScaling
>& xScalingX
,
96 const uno::Reference
< chart2::XScaling
>& xScalingY
,
97 sal_Bool bMaySkipPointsInCalculation
)
99 if( bMaySkipPointsInCalculation
)
102 uno::Sequence
< geometry::RealPoint2D
> aResult
{ { min
, m_fMeanValue
},
103 { max
, m_fMeanValue
} };
107 return RegressionCurveCalculator::getCurveValues( min
, max
, nPointCount
, xScalingX
, xScalingY
, bMaySkipPointsInCalculation
);
110 OUString
MeanValueRegressionCurveCalculator::ImplGetRepresentation(
111 const uno::Reference
< util::XNumberFormatter
>& xNumFormatter
,
112 sal_Int32 nNumberFormatKey
, sal_Int32
* pFormulaLength
/* = nullptr */ ) const
114 OUString
aBuf(mYName
+ " = ");
115 if ( pFormulaLength
)
117 *pFormulaLength
-= aBuf
.getLength();
118 if ( *pFormulaLength
<= 0 )
121 return ( aBuf
+ getFormattedString( xNumFormatter
, nNumberFormatKey
, m_fMeanValue
, pFormulaLength
) );
126 /* vim:set shiftwidth=4 softtabstop=4 expandtab: */