chart2/source/inc/RegressionCalculationHelper.hxx

   1 /* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
   2 /*
   3  * This file is part of the LibreOffice project.
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   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 {
  45     tDoubleVectorPair aResult;
  46     sal_Int32 nSize = std::min( rXValues.getLength(), rYValues.getLength());
  47     for( sal_Int32 i=0; i<nSize; ++i )
  48     {
  49         if( aPred( rXValues[i], rYValues[i] ))
  50         {
  51             aResult.first.push_back( rXValues[i] );
  52             aResult.second.push_back( rYValues[i] );
  53         }
  54     }
  55
  56     return aResult;
  57 }
  58
  59 class isValid
  60 {
  61 public:
  62     bool operator()( double x, double y )
  63     { return ! ( std::isnan( x ) ||
  64                  std::isnan( y ) ||
  65                  std::isinf( x ) ||
  66                  std::isinf( y ) );
  67     }
  68 };
  69
  70 class isValidAndXPositive
  71 {
  72 public:
  73     bool operator()( double x, double y )
  74     { return ! ( std::isnan( x ) ||
  75                  std::isnan( y ) ||
  76                  std::isinf( x ) ||
  77                  std::isinf( y ) ||
  78                  x <= 0.0 );
  79     }
  80 };
  81
  82 class isValidAndYPositive
  83 {
  84 public:
  85     bool operator()( double x, double y )
  86     { return ! ( std::isnan( x ) ||
  87                  std::isnan( y ) ||
  88                  std::isinf( x ) ||
  89                  std::isinf( y ) ||
  90                  y <= 0.0 );
  91     }
  92 };
  93
  94 class isValidAndYNegative
  95 {
  96 public:
  97     bool operator()( double x, double y )
  98     { return ! ( std::isnan( x ) ||
  99                  std::isnan( y ) ||
 100                  std::isinf( x ) ||
 101                  std::isinf( y ) ||
 102                  y >= 0.0 );
 103     }
 104 };
 105
 106 class isValidAndBothPositive
 107 {
 108 public:
 109     bool operator()( double x, double y )
 110     { return ! ( std::isnan( x ) ||
 111                  std::isnan( y ) ||
 112                  std::isinf( x ) ||
 113                  std::isinf( y ) ||
 114                  x <= 0.0 ||
 115                  y <= 0.0 );
 116     }
 117 };
 118
 119 class isValidAndXPositiveAndYNegative
 120 {
 121 public:
 122     bool operator()( double x, double y )
 123     { return ! ( std::isnan( x ) ||
 124                  std::isnan( y ) ||
 125                  std::isinf( x ) ||
 126                  std::isinf( y ) ||
 127                  x <= 0.0 ||
 128                  y >= 0.0 );
 129     }
 130 };
 131
 132 } //  namespace chart::RegressionCalculationHelper
 133
 134 /* vim:set shiftwidth=4 softtabstop=4 expandtab: */