1 | // $Id: interpolation_test.cc 1666 2008-12-20 21:18:57Z peter $ |
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2 | |
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3 | /* |
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4 | Copyright (C) 2008 Jari Häkkinen |
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5 | |
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6 | This file is part of the yat library, http://dev.thep.lu.se/yat |
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7 | |
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8 | The yat library is free software; you can redistribute it and/or |
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9 | modify it under the terms of the GNU General Public License as |
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10 | published by the Free Software Foundation; either version 3 of the |
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11 | License, or (at your option) any later version. |
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12 | |
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13 | The yat library is distributed in the hope that it will be useful, |
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14 | but WITHOUT ANY WARRANTY; without even the implied warranty of |
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15 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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16 | General Public License for more details. |
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17 | |
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18 | You should have received a copy of the GNU General Public License |
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19 | along with yat. If not, see <http://www.gnu.org/licenses/>. |
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20 | */ |
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21 | |
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22 | #include "Suite.h" |
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23 | |
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24 | #include "yat/regression/AkimaInterpolation.h" |
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25 | #include "yat/regression/AkimaPeriodicInterpolation.h" |
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26 | #include "yat/regression/CSplineInterpolation.h" |
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27 | #include "yat/regression/CSplinePeriodicInterpolation.h" |
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28 | #include "yat/regression/LinearInterpolation.h" |
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29 | #include "yat/regression/PolynomialInterpolation.h" |
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30 | #include "yat/utility/Vector.h" |
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31 | #include "yat/utility/VectorConstView.h" |
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32 | |
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33 | #include <cmath> |
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34 | |
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35 | using namespace theplu::yat; |
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36 | void test_delete(test::Suite&); |
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37 | |
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38 | int main(int argc, char* argv[]) |
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39 | { |
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40 | using namespace theplu::yat::regression; |
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41 | |
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42 | test::Suite suite(argc, argv); |
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43 | test_delete(suite); |
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44 | |
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45 | /* |
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46 | The test data is computed with R version 2.7.2 (2008-08-25) on |
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47 | MacBook Pro Intel CPU running MacOSX 10.5.5 |
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48 | |
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49 | x <- c(13,17,19,22,27,35) |
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50 | y <- c(100,97,111,120,117,103) |
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51 | cspline <- splinefun(x,y,"natural") |
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52 | w <- seq(15,25,1) |
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53 | z <- cspline(w) |
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54 | z |
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55 | [1] 94.11579 93.91382 97.00000 103.66776 111.00000 116.02563 118.76822 |
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56 | [8] 120.00000 120.38499 120.15443 119.43138 |
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57 | */ |
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58 | |
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59 | utility::Vector x(6); |
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60 | utility::Vector y(6); |
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61 | x(0)= 13; x(1)= 17; x(2)= 19; x(3)= 22; x(4)= 27; x(5)= 35; |
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62 | y(0)=100; y(1)= 97; y(2)=111; y(3)=120; y(4)=117; y(5)=103; |
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63 | |
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64 | CSplineInterpolation cspline(x,y); |
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65 | |
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66 | utility::Vector w(11); |
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67 | utility::Vector z(11); |
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68 | w( 0)=15; z( 0)= 94.11579; |
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69 | w( 1)=16; z( 1)= 93.91382; |
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70 | w( 2)=17; z( 2)= 97; |
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71 | w( 3)=18; z( 3)=103.66776; |
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72 | w( 4)=19; z( 4)=111; |
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73 | w( 5)=20; z( 5)=116.02563; |
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74 | w( 6)=21; z( 6)=118.76822; |
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75 | w( 7)=22; z( 7)=120; |
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76 | w( 8)=23; z( 8)=120.38499; |
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77 | w( 9)=24; z( 9)=120.15443; |
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78 | w(10)=25; z(10)=119.43138; |
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79 | |
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80 | for (size_t i=0; i<w.size(); ++i) { |
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81 | if ( !suite.equal_fix(cspline.evaluate(w(i)), z(i), 1e-5) ) { |
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82 | suite.err() << "cspline test failed for i=" << i << std::endl; |
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83 | suite.err() << " difference between target and interpolation too large: " |
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84 | << fabs(cspline.evaluate(w(i))-z(i)) << std::endl; |
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85 | suite.add(false); |
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86 | } |
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87 | // Check for errors |
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88 | if (cspline.error_status()) { |
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89 | suite.err() << "cspline test failed with GSL_EDOM error" << std::endl; |
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90 | suite.add(false); |
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91 | } |
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92 | } |
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93 | |
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94 | // An error should be generated, if not test fails |
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95 | cspline.evaluate(w(0)-5); |
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96 | if (!cspline.error_status()) { |
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97 | suite.err() << "cspline test failed no GSL_EDOM error occured" << std::endl; |
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98 | suite.add(false); |
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99 | } |
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100 | |
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101 | // lazy testing, at least try to create the objects |
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102 | AkimaInterpolation(x,y); |
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103 | AkimaPeriodicInterpolation(x,y); |
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104 | CSplinePeriodicInterpolation(x,y); |
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105 | LinearInterpolation(x,y); |
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106 | PolynomialInterpolation(x,y); |
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107 | |
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108 | return suite.return_value(); |
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109 | } |
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110 | |
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111 | void test_delete(test::Suite& suite) |
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112 | { |
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113 | utility::Vector x(10); |
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114 | for (size_t i=0; i<x.size(); ++i) |
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115 | x(i)=i; |
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116 | regression::GSLInterpolation* ip = new regression::CSplineInterpolation(x,x); |
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117 | delete ip; |
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118 | } |
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119 | |
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