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/* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
* This file is part of the LibreOffice project.
*
* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/.
*
* This file incorporates work covered by the following license notice:
*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed
* with this work for additional information regarding copyright
* ownership. The ASF licenses this file to you under the Apache
* License, Version 2.0 (the "License"); you may not use this file
* except in compliance with the License. You may obtain a copy of
* the License at http://www.apache.org/licenses/LICENSE-2.0 .
*/
#ifndef INCLUDED_CHART2_SOURCE_INC_REGRESSIONCALCULATIONHELPER_HXX
#define INCLUDED_CHART2_SOURCE_INC_REGRESSIONCALCULATIONHELPER_HXX
#include <rtl/math.hxx>
#include <utility>
#include <algorithm>
#include <functional>
#include <vector>
#define UC_SPACE (sal_Unicode(' '))
#define UC_MINUS_SIGN (sal_Unicode('-'))
namespace chart
{
namespace RegressionCalculationHelper
{
typedef ::std::pair< ::std::vector< double >, ::std::vector< double > > tDoubleVectorPair;
/** takes the given x- and y-values and copyies them into the resulting pair,
which contains x-values in the first element and the y-values in the second
one. All tuples for which aPred is false are not copied.
<p>The functors below provide a set of useful predicates that can be
used to pass as parameter aPred.</p>
*/
template< class Pred >
tDoubleVectorPair
cleanup( const ::com::sun::star::uno::Sequence< double > & rXValues,
const ::com::sun::star::uno::Sequence< double > & rYValues,
Pred aPred )
{
tDoubleVectorPair aResult;
sal_Int32 nSize = ::std::min( rXValues.getLength(), rYValues.getLength());
for( sal_Int32 i=0; i<nSize; ++i )
{
if( aPred( rXValues[i], rYValues[i] ))
{
aResult.first.push_back( rXValues[i] );
aResult.second.push_back( rYValues[i] );
}
}
return aResult;
}
class isValid : 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 ) );
}
};
class isValidAndXPositive : 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 ) ||
x <= 0.0 );
}
};
class isValidAndYPositive : 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 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:
inline bool operator()( double x, double y )
{ return ! ( ::rtl::math::isNan( x ) ||
::rtl::math::isNan( y ) ||
::rtl::math::isInf( x ) ||
::rtl::math::isInf( y ) ||
x <= 0.0 ||
y <= 0.0 );
}
};
class isValidAndXPositiveAndYNegative : 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 ) ||
x <= 0.0 ||
y >= 0.0 );
}
};
} // namespace RegressionCalculationHelper
} // namespace chart
// INCLUDED_CHART2_SOURCE_INC_REGRESSIONCALCULATIONHELPER_HXX
#endif
/* vim:set shiftwidth=4 softtabstop=4 expandtab: */
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