/src/libreoffice/chart2/source/inc/RegressionCalculationHelper.hxx

Source
/* -*- 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 .
 */
#pragma once

#include <com/sun/star/uno/Sequence.hxx>

#include <cmath>
#include <utility>
#include <vector>

namespace chart::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 ! ( std::isnan( x ) ||
                 std::isnan( y ) ||
                 std::isinf( x ) ||
                 std::isinf( y ) );
    }
};

class isValidAndXPositive
{
public:
    bool operator()( double x, double y )
    { return ! ( std::isnan( x ) ||
                 std::isnan( y ) ||
                 std::isinf( x ) ||
                 std::isinf( y ) ||
                 x <= 0.0 );
    }
};

class isValidAndYPositive
{
public:
    bool operator()( double x, double y )
    { return ! ( std::isnan( x ) ||
                 std::isnan( y ) ||
                 std::isinf( x ) ||
                 std::isinf( y ) ||
                 y <= 0.0 );
    }
};

class isValidAndYNegative
{
public:
    bool operator()( double x, double y )
    { return ! ( std::isnan( x ) ||
                 std::isnan( y ) ||
                 std::isinf( x ) ||
                 std::isinf( y ) ||
                 y >= 0.0 );
    }
};

class isValidAndBothPositive
{
public:
    bool operator()( double x, double y )
    { return ! ( std::isnan( x ) ||
                 std::isnan( y ) ||
                 std::isinf( x ) ||
                 std::isinf( y ) ||
                 x <= 0.0 ||
                 y <= 0.0 );
    }
};

class isValidAndXPositiveAndYNegative
{
public:
    bool operator()( double x, double y )
    { return ! ( std::isnan( x ) ||
                 std::isnan( y ) ||
                 std::isinf( x ) ||
                 std::isinf( y ) ||
                 x <= 0.0 ||
                 y >= 0.0 );
    }
};

} //  namespace chart::RegressionCalculationHelper

/* vim:set shiftwidth=4 softtabstop=4 expandtab: */

Line	Count	Source
1		/* -- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -- */
2		/*
3		* This file is part of the LibreOffice project.
4		*
5		* This Source Code Form is subject to the terms of the Mozilla Public
6		* License, v. 2.0. If a copy of the MPL was not distributed with this
7		* file, You can obtain one at http://mozilla.org/MPL/2.0/.
8		*
9		* This file incorporates work covered by the following license notice:
10		*
11		* Licensed to the Apache Software Foundation (ASF) under one or more
12		* contributor license agreements. See the NOTICE file distributed
13		* with this work for additional information regarding copyright
14		* ownership. The ASF licenses this file to you under the Apache
15		* License, Version 2.0 (the "License"); you may not use this file
16		* except in compliance with the License. You may obtain a copy of
17		* the License at http://www.apache.org/licenses/LICENSE-2.0 .
18		*/
19		#pragma once
20
21		#include <com/sun/star/uno/Sequence.hxx>
22
23		#include <cmath>
24		#include <utility>
25		#include <vector>
26
27		namespace chart::RegressionCalculationHelper
28		{
29
30		typedef std::pair< std::vector< double >, std::vector< double > > tDoubleVectorPair;
31
32		/** takes the given x- and y-values and copies them into the resulting pair,
33		which contains x-values in the first element and the y-values in the second
34		one. All tuples for which aPred is false are not copied.
35
36		<p>The function below provide a set of useful predicates that can be
37		used to pass as parameter aPred.</p>
38		*/
39		template< class Pred >
40		tDoubleVectorPair
41		cleanup( const css::uno::Sequence< double > & rXValues,
42		const css::uno::Sequence< double > & rYValues,
43		Pred aPred )
44	0	{
45	0	tDoubleVectorPair aResult;
46	0	sal_Int32 nSize = std::min( rXValues.getLength(), rYValues.getLength());
47	0	for( sal_Int32 i=0; i<nSize; ++i )
48	0	{
49	0	if( aPred( rXValues[i], rYValues[i] ))
50	0	{
51	0	aResult.first.push_back( rXValues[i] );
52	0	aResult.second.push_back( rYValues[i] );
53	0	}
54	0	}
55
56	0	return aResult;
57	0	} Unexecuted instantiation: std::__1::pair<std::__1::vector<double, std::__1::allocator<double> >, std::__1::vector<double, std::__1::allocator<double> > > chart::RegressionCalculationHelper::cleanup<chart::RegressionCalculationHelper::isValidAndYPositive>(com::sun::star::uno::Sequence<double> const&, com::sun::star::uno::Sequence<double> const&, chart::RegressionCalculationHelper::isValidAndYPositive) Unexecuted instantiation: std::__1::pair<std::__1::vector<double, std::__1::allocator<double> >, std::__1::vector<double, std::__1::allocator<double> > > chart::RegressionCalculationHelper::cleanup<chart::RegressionCalculationHelper::isValidAndYNegative>(com::sun::star::uno::Sequence<double> const&, com::sun::star::uno::Sequence<double> const&, chart::RegressionCalculationHelper::isValidAndYNegative) Unexecuted instantiation: std::__1::pair<std::__1::vector<double, std::__1::allocator<double> >, std::__1::vector<double, std::__1::allocator<double> > > chart::RegressionCalculationHelper::cleanup<chart::RegressionCalculationHelper::isValidAndXPositive>(com::sun::star::uno::Sequence<double> const&, com::sun::star::uno::Sequence<double> const&, chart::RegressionCalculationHelper::isValidAndXPositive) Unexecuted instantiation: std::__1::pair<std::__1::vector<double, std::__1::allocator<double> >, std::__1::vector<double, std::__1::allocator<double> > > chart::RegressionCalculationHelper::cleanup<chart::RegressionCalculationHelper::isValid>(com::sun::star::uno::Sequence<double> const&, com::sun::star::uno::Sequence<double> const&, chart::RegressionCalculationHelper::isValid) Unexecuted instantiation: std::__1::pair<std::__1::vector<double, std::__1::allocator<double> >, std::__1::vector<double, std::__1::allocator<double> > > chart::RegressionCalculationHelper::cleanup<chart::RegressionCalculationHelper::isValidAndBothPositive>(com::sun::star::uno::Sequence<double> const&, com::sun::star::uno::Sequence<double> const&, chart::RegressionCalculationHelper::isValidAndBothPositive) Unexecuted instantiation: std::__1::pair<std::__1::vector<double, std::__1::allocator<double> >, std::__1::vector<double, std::__1::allocator<double> > > chart::RegressionCalculationHelper::cleanup<chart::RegressionCalculationHelper::isValidAndXPositiveAndYNegative>(com::sun::star::uno::Sequence<double> const&, com::sun::star::uno::Sequence<double> const&, chart::RegressionCalculationHelper::isValidAndXPositiveAndYNegative)
58
59		class isValid
60		{
61		public:
62		bool operator()( double x, double y )
63	0	{ return ! ( std::isnan( x ) \|\|
64	0	std::isnan( y ) \|\|
65	0	std::isinf( x ) \|\|
66	0	std::isinf( y ) );
67	0	}
68		};
69
70		class isValidAndXPositive
71		{
72		public:
73		bool operator()( double x, double y )
74	0	{ return ! ( std::isnan( x ) \|\|
75	0	std::isnan( y ) \|\|
76	0	std::isinf( x ) \|\|
77	0	std::isinf( y ) \|\|
78	0	x <= 0.0 );
79	0	}
80		};
81
82		class isValidAndYPositive
83		{
84		public:
85		bool operator()( double x, double y )
86	0	{ return ! ( std::isnan( x ) \|\|
87	0	std::isnan( y ) \|\|
88	0	std::isinf( x ) \|\|
89	0	std::isinf( y ) \|\|
90	0	y <= 0.0 );
91	0	}
92		};
93
94		class isValidAndYNegative
95		{
96		public:
97		bool operator()( double x, double y )
98	0	{ return ! ( std::isnan( x ) \|\|
99	0	std::isnan( y ) \|\|
100	0	std::isinf( x ) \|\|
101	0	std::isinf( y ) \|\|
102	0	y >= 0.0 );
103	0	}
104		};
105
106		class isValidAndBothPositive
107		{
108		public:
109		bool operator()( double x, double y )
110	0	{ return ! ( std::isnan( x ) \|\|
111	0	std::isnan( y ) \|\|
112	0	std::isinf( x ) \|\|
113	0	std::isinf( y ) \|\|
114	0	x <= 0.0 \|\|
115	0	y <= 0.0 );
116	0	}
117		};
118
119		class isValidAndXPositiveAndYNegative
120		{
121		public:
122		bool operator()( double x, double y )
123	0	{ return ! ( std::isnan( x ) \|\|
124	0	std::isnan( y ) \|\|
125	0	std::isinf( x ) \|\|
126	0	std::isinf( y ) \|\|
127	0	x <= 0.0 \|\|
128	0	y >= 0.0 );
129	0	}
130		};
131
132		} // namespace chart::RegressionCalculationHelper
133
134		/* vim:set shiftwidth=4 softtabstop=4 expandtab: */

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Created: 2025-12-08 09:28