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*
* 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
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
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* KIND, either express or implied. See the License for the
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*************************************************************/
#ifndef CHART2_REGRESSIONCALCULATIONHELPER_HXX
#define CHART2_REGRESSIONCALCULATIONHELPER_HXX
#include <rtl/math.hxx>
#include <utility>
#include <functional>
#include <vector>
#include <rtl/math.hxx>
#define NUMBER_TO_STR(number) (::rtl::OStringToOUString(::rtl::math::doubleToString( \
number, rtl_math_StringFormat_G, 4, '.', true ),RTL_TEXTENCODING_ASCII_US ))
#define UC_SPACE (sal_Unicode(' '))
#define UC_MINUS_SIGN (sal_Unicode('-'))
// #define UC_MINUS_SIGN (sal_Unicode(0x2212))
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 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 );
}
};
} // namespace RegressionCalculationHelper
} // namespace chart
// CHART2_REGRESSIONCALCULATIONHELPER_HXX
#endif