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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
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11 * http://www.apache.org/licenses/LICENSE-2.0
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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
LinearRegressionCurveCalculator()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
~LinearRegressionCurveCalculator()49 LinearRegressionCurveCalculator::~LinearRegressionCurveCalculator()
50 {}
51
52 // ____ XRegressionCurveCalculator ____
recalculateRegression(const uno::Sequence<double> & aXValues,const uno::Sequence<double> & aYValues)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
getCurveValue(double x)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
getCurveValues(double min,double max,::sal_Int32 nPointCount,const uno::Reference<chart2::XScaling> & xScalingX,const uno::Reference<chart2::XScaling> & xScalingY,::sal_Bool bMaySkipPointsInCalculation)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
ImplGetRepresentation(const uno::Reference<util::XNumberFormatter> & xNumFormatter,::sal_Int32 nNumberFormatKey) const126 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