1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
|
/* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
* This file is part of the LibreOffice project.
*
* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/.
*
* This file incorporates work covered by the following license notice:
*
* 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 .
*/
#ifndef INCLUDED_CHART2_SOURCE_INC_REGRESSIONCALCULATIONHELPER_HXX
#define INCLUDED_CHART2_SOURCE_INC_REGRESSIONCALCULATIONHELPER_HXX
#include <rtl/math.hxx>
#include <utility>
#include <vector>
namespace chart
{
namespace RegressionCalculationHelper
{
typedef std::pair< std::vector< double >, std::vector< double > > tDoubleVectorPair;
/** takes the given x- and y-values and copies 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 function below provide a set of useful predicates that can be
used to pass as parameter aPred.</p>
*/
template< class Pred >
tDoubleVectorPair
cleanup( const css::uno::Sequence< double > & rXValues,
const css::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:
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:
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:
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 isValidAndYNegative
{
public:
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:
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 );
}
};
class isValidAndXPositiveAndYNegative
{
public:
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
// INCLUDED_CHART2_SOURCE_INC_REGRESSIONCALCULATIONHELPER_HXX
#endif
/* vim:set shiftwidth=4 softtabstop=4 expandtab: */
|
