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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
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_chart2.hxx"
26 #include "LogarithmicRegressionCurveCalculator.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
LogarithmicRegressionCurveCalculator()41 LogarithmicRegressionCurveCalculator::LogarithmicRegressionCurveCalculator() :
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
~LogarithmicRegressionCurveCalculator()49 LogarithmicRegressionCurveCalculator::~LogarithmicRegressionCurveCalculator()
50 {}
51
52 // ____ XRegressionCurve ____
recalculateRegression(const uno::Sequence<double> & aXValues,const uno::Sequence<double> & aYValues)53 void SAL_CALL LogarithmicRegressionCurveCalculator::recalculateRegression(
54 const uno::Sequence< double >& aXValues,
55 const uno::Sequence< double >& aYValues )
56 throw (uno::RuntimeException)
57 {
58 RegressionCalculationHelper::tDoubleVectorPair aValues(
59 RegressionCalculationHelper::cleanup(
60 aXValues, aYValues,
61 RegressionCalculationHelper::isValidAndXPositive()));
62
63 const size_t nMax = aValues.first.size();
64 if( nMax == 0 )
65 {
66 ::rtl::math::setNan( & m_fSlope );
67 ::rtl::math::setNan( & m_fIntercept );
68 ::rtl::math::setNan( & m_fCorrelationCoeffitient );
69 return;
70 }
71
72 double fAverageX = 0.0, fAverageY = 0.0;
73 size_t i = 0;
74 for( i = 0; i < nMax; ++i )
75 {
76 fAverageX += log( aValues.first[i] );
77 fAverageY += aValues.second[i];
78 }
79
80 const double fN = static_cast< double >( nMax );
81 fAverageX /= fN;
82 fAverageY /= fN;
83
84 double fQx = 0.0, fQy = 0.0, fQxy = 0.0;
85 for( i = 0; i < nMax; ++i )
86 {
87 double fDeltaX = log( aValues.first[i] ) - fAverageX;
88 double fDeltaY = aValues.second[i] - fAverageY;
89
90 fQx += fDeltaX * fDeltaX;
91 fQy += fDeltaY * fDeltaY;
92 fQxy += fDeltaX * fDeltaY;
93 }
94
95 m_fSlope = fQxy / fQx;
96 m_fIntercept = fAverageY - m_fSlope * fAverageX;
97 m_fCorrelationCoeffitient = fQxy / sqrt( fQx * fQy );
98 }
99
getCurveValue(double x)100 double SAL_CALL LogarithmicRegressionCurveCalculator::getCurveValue( double x )
101 throw (lang::IllegalArgumentException,
102 uno::RuntimeException)
103 {
104 double fResult;
105 ::rtl::math::setNan( & fResult );
106
107 if( ! ( ::rtl::math::isNan( m_fSlope ) ||
108 ::rtl::math::isNan( m_fIntercept )))
109 {
110 fResult = m_fSlope * log( x ) + m_fIntercept;
111 }
112
113 return fResult;
114 }
115
getCurveValues(double min,double max,::sal_Int32 nPointCount,const uno::Reference<chart2::XScaling> & xScalingX,const uno::Reference<chart2::XScaling> & xScalingY,::sal_Bool bMaySkipPointsInCalculation)116 uno::Sequence< geometry::RealPoint2D > SAL_CALL LogarithmicRegressionCurveCalculator::getCurveValues(
117 double min, double max, ::sal_Int32 nPointCount,
118 const uno::Reference< chart2::XScaling >& xScalingX,
119 const uno::Reference< chart2::XScaling >& xScalingY,
120 ::sal_Bool bMaySkipPointsInCalculation )
121 throw (lang::IllegalArgumentException,
122 uno::RuntimeException)
123 {
124 if( bMaySkipPointsInCalculation &&
125 isLogarithmicScaling( xScalingX ) &&
126 isLinearScaling( xScalingY ))
127 {
128 // optimize result
129 uno::Sequence< geometry::RealPoint2D > aResult( 2 );
130 aResult[0].X = min;
131 aResult[0].Y = this->getCurveValue( min );
132 aResult[1].X = max;
133 aResult[1].Y = this->getCurveValue( max );
134
135 return aResult;
136 }
137 return RegressionCurveCalculator::getCurveValues( min, max, nPointCount, xScalingX, xScalingY, bMaySkipPointsInCalculation );
138 }
139
ImplGetRepresentation(const uno::Reference<util::XNumberFormatter> & xNumFormatter,::sal_Int32 nNumberFormatKey) const140 OUString LogarithmicRegressionCurveCalculator::ImplGetRepresentation(
141 const uno::Reference< util::XNumberFormatter >& xNumFormatter,
142 ::sal_Int32 nNumberFormatKey ) const
143 {
144 OUStringBuffer aBuf( C2U( "f(x) = " ));
145
146 bool bHaveSlope = false;
147
148 if( m_fSlope != 0.0 )
149 {
150 if( ::rtl::math::approxEqual( fabs( m_fSlope ), 1.0 ))
151 {
152 if( m_fSlope < 0 )
153 aBuf.append( UC_MINUS_SIGN );
154 }
155 else
156 {
157 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fSlope ));
158 aBuf.append( UC_SPACE );
159 }
160 aBuf.appendAscii( RTL_CONSTASCII_STRINGPARAM( "ln(x)" ));
161 bHaveSlope = true;
162 }
163
164 if( bHaveSlope )
165 {
166 if( m_fIntercept < 0.0 )
167 {
168 aBuf.append( UC_SPACE );
169 aBuf.append( UC_MINUS_SIGN );
170 aBuf.append( UC_SPACE );
171 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, fabs( m_fIntercept )));
172 }
173 else if( m_fIntercept > 0.0 )
174 {
175 aBuf.appendAscii( RTL_CONSTASCII_STRINGPARAM( " + " ));
176 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept ));
177 }
178 }
179 else
180 {
181 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept ));
182 }
183
184 return aBuf.makeStringAndClear();
185 }
186
187 } // namespace chart
188