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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
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
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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