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2 *
3 * Licensed to the Apache Software Foundation (ASF) under one
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8 * "License"); you may not use this file except in compliance
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11 * http://www.apache.org/licenses/LICENSE-2.0
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16 * KIND, either express or implied. See the License for the
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18 * under the License.
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21
22
23
24 // MARKER(update_precomp.py): autogen include statement, do not remove
25 #include "precompiled_charttools.hxx"
26 #include "PotentialRegressionCurveCalculator.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
PotentialRegressionCurveCalculator()41 PotentialRegressionCurveCalculator::PotentialRegressionCurveCalculator() :
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
~PotentialRegressionCurveCalculator()49 PotentialRegressionCurveCalculator::~PotentialRegressionCurveCalculator()
50 {}
51
52 // ____ XRegressionCurveCalculator ____
recalculateRegression(const uno::Sequence<double> & aXValues,const uno::Sequence<double> & aYValues)53 void SAL_CALL PotentialRegressionCurveCalculator::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::isValidAndBothPositive()));
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 double fAverageX = 0.0, fAverageY = 0.0;
72 size_t i = 0;
73 for( i = 0; i < nMax; ++i )
74 {
75 fAverageX += log( aValues.first[i] );
76 fAverageY += log( aValues.second[i] );
77 }
78
79 const double fN = static_cast< double >( nMax );
80 fAverageX /= fN;
81 fAverageY /= fN;
82
83 double fQx = 0.0, fQy = 0.0, fQxy = 0.0;
84 for( i = 0; i < nMax; ++i )
85 {
86 double fDeltaX = log( aValues.first[i] ) - fAverageX;
87 double fDeltaY = log( aValues.second[i] ) - fAverageY;
88
89 fQx += fDeltaX * fDeltaX;
90 fQy += fDeltaY * fDeltaY;
91 fQxy += fDeltaX * fDeltaY;
92 }
93
94 m_fSlope = fQxy / fQx;
95 m_fIntercept = fAverageY - m_fSlope * fAverageX;
96 m_fCorrelationCoeffitient = fQxy / sqrt( fQx * fQy );
97
98 m_fIntercept = exp( m_fIntercept );
99 }
100
getCurveValue(double x)101 double SAL_CALL PotentialRegressionCurveCalculator::getCurveValue( double x )
102 {
103 double fResult;
104 ::rtl::math::setNan( & fResult );
105
106 if( ! ( ::rtl::math::isNan( m_fSlope ) ||
107 ::rtl::math::isNan( m_fIntercept )))
108 {
109 fResult = m_fIntercept * pow( x, m_fSlope );
110 }
111
112 return fResult;
113 }
114
getCurveValues(double min,double max,::sal_Int32 nPointCount,const uno::Reference<chart2::XScaling> & xScalingX,const uno::Reference<chart2::XScaling> & xScalingY,::sal_Bool bMaySkipPointsInCalculation)115 uno::Sequence< geometry::RealPoint2D > SAL_CALL PotentialRegressionCurveCalculator::getCurveValues(
116 double min, double max, ::sal_Int32 nPointCount,
117 const uno::Reference< chart2::XScaling >& xScalingX,
118 const uno::Reference< chart2::XScaling >& xScalingY,
119 ::sal_Bool bMaySkipPointsInCalculation )
120 {
121 if( bMaySkipPointsInCalculation &&
122 isLogarithmicScaling( xScalingX ) &&
123 isLogarithmicScaling( xScalingY ))
124 {
125 // optimize result
126 uno::Sequence< geometry::RealPoint2D > aResult( 2 );
127 aResult[0].X = min;
128 aResult[0].Y = this->getCurveValue( min );
129 aResult[1].X = max;
130 aResult[1].Y = this->getCurveValue( max );
131
132 return aResult;
133 }
134 return RegressionCurveCalculator::getCurveValues( min, max, nPointCount, xScalingX, xScalingY, bMaySkipPointsInCalculation );
135 }
136
ImplGetRepresentation(const uno::Reference<util::XNumberFormatter> & xNumFormatter,::sal_Int32 nNumberFormatKey) const137 OUString PotentialRegressionCurveCalculator::ImplGetRepresentation(
138 const uno::Reference< util::XNumberFormatter >& xNumFormatter,
139 ::sal_Int32 nNumberFormatKey ) const
140 {
141 OUStringBuffer aBuf( C2U( "f(x) = " ));
142
143 if( m_fIntercept == 0.0 )
144 {
145 aBuf.append( sal_Unicode( '0' ));
146 }
147 else if( m_fSlope == 0.0 )
148 {
149 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept ));
150 }
151 else
152 {
153 if( ! rtl::math::approxEqual( m_fIntercept, 1.0 ) )
154 {
155 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept ));
156 aBuf.append( sal_Unicode( ' ' ));
157 }
158 if( m_fSlope != 0.0 )
159 {
160 aBuf.appendAscii( RTL_CONSTASCII_STRINGPARAM( "x^" ));
161 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fSlope ));
162 }
163 }
164
165 return aBuf.makeStringAndClear();
166 }
167
168 } // namespace chart
169