1 /************************************************************** 2 * 3 * Licensed to the Apache Software Foundation (ASF) under one 4 * or more contributor license agreements. See the NOTICE file 5 * distributed with this work for additional information 6 * regarding copyright ownership. The ASF licenses this file 7 * to you under the Apache License, Version 2.0 (the 8 * "License"); you may not use this file except in compliance 9 * with the License. You may obtain a copy of the License at 10 * 11 * http://www.apache.org/licenses/LICENSE-2.0 12 * 13 * Unless required by applicable law or agreed to in writing, 14 * software distributed under the License is distributed on an 15 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY 16 * KIND, either express or implied. See the License for the 17 * specific language governing permissions and limitations 18 * under the License. 19 * 20 *************************************************************/ 21 22 23 24 // MARKER(update_precomp.py): autogen include statement, do not remove 25 #include "precompiled_charttools.hxx" 26 #include "LinearRegressionCurveCalculator.hxx" 27 #include "macros.hxx" 28 #include "RegressionCalculationHelper.hxx" 29 30 #include <rtl/math.hxx> 31 #include <rtl/ustrbuf.hxx> 32 33 using namespace ::com::sun::star; 34 35 using ::rtl::OUString; 36 using ::rtl::OUStringBuffer; 37 38 namespace chart 39 { 40 41 LinearRegressionCurveCalculator::LinearRegressionCurveCalculator() : 42 m_fSlope( 0.0 ), 43 m_fIntercept( 0.0 ) 44 { 45 ::rtl::math::setNan( & m_fSlope ); 46 ::rtl::math::setNan( & m_fIntercept ); 47 } 48 49 LinearRegressionCurveCalculator::~LinearRegressionCurveCalculator() 50 {} 51 52 // ____ XRegressionCurveCalculator ____ 53 void SAL_CALL LinearRegressionCurveCalculator::recalculateRegression( 54 const uno::Sequence< double >& aXValues, 55 const uno::Sequence< double >& aYValues ) 56 { 57 RegressionCalculationHelper::tDoubleVectorPair aValues( 58 RegressionCalculationHelper::cleanup( 59 aXValues, aYValues, 60 RegressionCalculationHelper::isValid())); 61 62 const size_t nMax = aValues.first.size(); 63 if( nMax == 0 ) 64 { 65 ::rtl::math::setNan( & m_fSlope ); 66 ::rtl::math::setNan( & m_fIntercept ); 67 ::rtl::math::setNan( & m_fCorrelationCoeffitient ); 68 return; 69 } 70 71 const double fN = static_cast< double >( nMax ); 72 double fSumX = 0.0, fSumY = 0.0, fSumXSq = 0.0, fSumYSq = 0.0, fSumXY = 0.0; 73 for( size_t i = 0; i < nMax; ++i ) 74 { 75 fSumX += aValues.first[i]; 76 fSumY += aValues.second[i]; 77 fSumXSq += aValues.first[i] * aValues.first[i]; 78 fSumYSq += aValues.second[i] * aValues.second[i]; 79 fSumXY += aValues.first[i] * aValues.second[i]; 80 } 81 82 m_fSlope = (fN * fSumXY - fSumX * fSumY) / ( fN * fSumXSq - fSumX * fSumX ); 83 m_fIntercept = (fSumY - m_fSlope * fSumX) / fN; 84 85 m_fCorrelationCoeffitient = ( fN * fSumXY - fSumX * fSumY ) / 86 sqrt( ( fN * fSumXSq - fSumX * fSumX ) * 87 ( fN * fSumYSq - fSumY * fSumY ) ); 88 } 89 90 double SAL_CALL LinearRegressionCurveCalculator::getCurveValue( double x ) 91 { 92 double fResult; 93 ::rtl::math::setNan( & fResult ); 94 95 if( ! ( ::rtl::math::isNan( m_fSlope ) || 96 ::rtl::math::isNan( m_fIntercept ))) 97 { 98 fResult = m_fSlope * x + m_fIntercept; 99 } 100 101 return fResult; 102 } 103 104 uno::Sequence< geometry::RealPoint2D > SAL_CALL LinearRegressionCurveCalculator::getCurveValues( 105 double min, double max, ::sal_Int32 nPointCount, 106 const uno::Reference< chart2::XScaling >& xScalingX, 107 const uno::Reference< chart2::XScaling >& xScalingY, 108 ::sal_Bool bMaySkipPointsInCalculation ) 109 { 110 if( bMaySkipPointsInCalculation && 111 isLinearScaling( xScalingX ) && 112 isLinearScaling( xScalingY )) 113 { 114 // optimize result 115 uno::Sequence< geometry::RealPoint2D > aResult( 2 ); 116 aResult[0].X = min; 117 aResult[0].Y = this->getCurveValue( min ); 118 aResult[1].X = max; 119 aResult[1].Y = this->getCurveValue( max ); 120 121 return aResult; 122 } 123 return RegressionCurveCalculator::getCurveValues( min, max, nPointCount, xScalingX, xScalingY, bMaySkipPointsInCalculation ); 124 } 125 126 OUString LinearRegressionCurveCalculator::ImplGetRepresentation( 127 const uno::Reference< util::XNumberFormatter >& xNumFormatter, 128 ::sal_Int32 nNumberFormatKey ) const 129 { 130 OUStringBuffer aBuf( C2U( "f(x) = " )); 131 132 bool bHaveSlope = false; 133 134 if( m_fSlope != 0.0 ) 135 { 136 if( ::rtl::math::approxEqual( fabs( m_fSlope ), 1.0 )) 137 { 138 if( m_fSlope < 0 ) 139 aBuf.append( UC_MINUS_SIGN ); 140 } 141 else 142 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fSlope )); 143 aBuf.append( sal_Unicode( 'x' )); 144 bHaveSlope = true; 145 } 146 147 if( bHaveSlope ) 148 { 149 if( m_fIntercept < 0.0 ) 150 { 151 aBuf.append( UC_SPACE ); 152 aBuf.append( UC_MINUS_SIGN ); 153 aBuf.append( UC_SPACE ); 154 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, fabs( m_fIntercept ))); 155 } 156 else if( m_fIntercept > 0.0 ) 157 { 158 aBuf.appendAscii( RTL_CONSTASCII_STRINGPARAM( " + " )); 159 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept )); 160 } 161 } 162 else 163 { 164 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept )); 165 } 166 167 return aBuf.makeStringAndClear(); 168 } 169 170 } // namespace chart 171