1 | // $Id: averager_test.cc 617 2006-08-31 08:58:05Z jari $ |
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2 | |
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3 | #include <c++_tools/statistics/Averager.h> |
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4 | #include <c++_tools/statistics/AveragerPair.h> |
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5 | #include <c++_tools/statistics/AveragerPairWeighted.h> |
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6 | #include <c++_tools/statistics/AveragerWeighted.h> |
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7 | #include <c++_tools/utility/vector.h> |
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8 | |
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9 | #include <fstream> |
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10 | #include <limits> |
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11 | #include <iostream> |
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12 | |
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13 | using namespace theplu::statistics; |
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14 | |
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15 | //Forward declarations |
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16 | bool equal(const Averager&, const Averager&); |
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17 | bool equal(const AveragerWeighted&, const AveragerWeighted&, const double, |
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18 | std::ostream* error); |
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19 | bool equal(const Averager&, const AveragerWeighted&, const double, |
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20 | std::ostream* error); |
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21 | bool equal(const AveragerPair&, const AveragerPair&, |
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22 | const double, std::ostream* error); |
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23 | bool equal(const AveragerPair&, const AveragerPairWeighted&, |
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24 | const double, std::ostream* error); |
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25 | bool equal(const AveragerPairWeighted&, const AveragerPairWeighted&, |
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26 | const double, std::ostream* error); |
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27 | |
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28 | |
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29 | int main(const int argc,const char* argv[]) |
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30 | { |
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31 | |
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32 | std::ostream* error; |
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33 | if (argc>1 && argv[1]==std::string("-v")) |
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34 | error = &std::cerr; |
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35 | else { |
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36 | error = new std::ofstream("/dev/null"); |
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37 | if (argc>1) |
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38 | std::cout << "averager_test -v : for printing extra information\n"; |
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39 | } |
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40 | bool ok = true; |
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41 | |
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42 | // Testing Averager |
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43 | *error << "testing Averager" << std::endl; |
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44 | Averager a; |
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45 | a.add(1); |
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46 | a.add(3); |
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47 | a.add(5); |
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48 | if (a.n()!=3 || a.mean()!=3 || a.sum_xx()!=35){ |
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49 | ok=false; |
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50 | *error << "error: add\n"; |
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51 | } |
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52 | |
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53 | Averager* a1 = new Averager(1+3+5,1+9+25,3); |
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54 | if (!equal(a,*a1)){ |
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55 | ok=false; |
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56 | std::cout << a.sum_x() << std::endl; |
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57 | std::cout << a.sum_xx() << std::endl; |
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58 | std::cout << a.n() << std::endl; |
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59 | std::cout << a.variance() << std::endl; |
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60 | std::cout << a.mean() << std::endl; |
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61 | std::cout << a1->sum_x() << std::endl; |
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62 | std::cout << a1->sum_xx() << std::endl; |
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63 | std::cout << a1->n() << std::endl; |
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64 | std::cout << a1->variance() << std::endl; |
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65 | std::cout << a1->mean() << std::endl; |
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66 | std::cout << a.mean() - a1->mean() << std::endl; |
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67 | std::cout << a.variance() - a1->variance() << std::endl; |
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68 | *error << "error: Averager(const double x,const double xx,const long n)\n"; |
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69 | } |
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70 | delete a1; |
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71 | |
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72 | a1 = new Averager(a); |
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73 | if (!equal(a,*a1)){ |
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74 | ok=false; |
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75 | *error << "error: Copy constructor\n"; |
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76 | } |
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77 | delete a1; |
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78 | |
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79 | a.add(3,5); |
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80 | if (! a.standard_error()==sqrt(a.variance()/a.n())){ |
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81 | ok=false; |
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82 | *error << "error: standard_error\n"; |
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83 | } |
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84 | |
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85 | |
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86 | if ( fabs(a.variance() - a.std()*a.std())> |
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87 | std::numeric_limits<double>().round_error() ){ |
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88 | ok=false; |
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89 | *error << "error: std squared should be variance" << std::endl; |
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90 | *error << "std2: " << a.std()*a.std() << std::endl; |
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91 | *error << "variance: " << a.variance() << std::endl; |
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92 | *error << "difference is: " << a.std()*a.std()-a.variance() << std::endl; |
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93 | } |
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94 | |
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95 | if ( a.variance() != a.variance(a.mean()) ){ |
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96 | ok=false; |
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97 | *error << "error: variance incorrect\n" << std::endl; |
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98 | *error << "variance: " << a.variance() << std::endl; |
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99 | *error << "mean: " << a.mean() << std::endl; |
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100 | *error << "variance(mean) " << a.variance(a.mean()) << std::endl; |
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101 | } |
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102 | |
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103 | // Testing AveragerWeighted |
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104 | *error << "testing AveragerWeighted" << std::endl; |
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105 | theplu::utility::vector x(3,0); |
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106 | x(0)=0; |
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107 | x(1)=1; |
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108 | x(2)=2; |
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109 | theplu::utility::vector w(3,1); |
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110 | theplu::statistics::AveragerWeighted aw; |
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111 | aw.add_values(x,w); |
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112 | a.reset(); |
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113 | a.add_values(x); |
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114 | const double tol=std::numeric_limits<double>().round_error(); |
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115 | if (!equal(a,aw,tol,error)){ |
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116 | *error << "error: AveragerWeighted with unitary weights should " |
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117 | << "be equal to Averager" << std::endl; |
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118 | ok=false; |
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119 | } |
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120 | |
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121 | AveragerWeighted* aw2 = new AveragerWeighted(aw); |
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122 | if (!equal(aw,*aw2,tol,error)){ |
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123 | *error << "error: AveragerWeighted copy constructor " << std::endl; |
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124 | ok=false; |
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125 | } |
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126 | |
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127 | aw2->add(12,0); |
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128 | if (!equal(aw,*aw2,tol,error)){ |
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129 | *error << "error: AveragerWeighted adding a data point with weight=0 " |
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130 | << "should make no change " << std::endl; |
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131 | ok=false; |
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132 | } |
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133 | |
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134 | aw2->reset(); |
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135 | w.scale(17); |
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136 | aw2->add_values(x,w); |
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137 | if (!equal(aw,*aw2,tol,error)){ |
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138 | *error << "error: AveragerWeighted rescaling weights " |
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139 | << "should make no change " << std::endl; |
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140 | ok=false; |
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141 | } |
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142 | delete aw2; |
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143 | |
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144 | |
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145 | *error << "testing AveragerPair" << std::endl; |
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146 | AveragerPair ap; |
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147 | for (int i=0; i<10; i++) |
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148 | ap.add(static_cast<double>(i),i); |
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149 | if (fabs(ap.correlation()-1)>tol){ |
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150 | ok=false; |
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151 | *error << "correlation: " << ap.correlation() << std::endl; |
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152 | *error << "error: correlation between identical vectors should be unity" |
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153 | << std::endl; |
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154 | } |
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155 | if (ap.x_averager().variance()!=ap.covariance()){ |
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156 | ok=false; |
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157 | *error << "error: covariance of identical vectors should equal to variance" |
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158 | << std::endl; |
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159 | } |
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160 | AveragerPair* ap2 = new AveragerPair(ap); |
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161 | delete ap2; |
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162 | |
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163 | *error << "testing AveragerPairWeighted" << std::endl; |
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164 | AveragerPairWeighted apw; |
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165 | x(0)=0; x(1)=1; x(2)=2; |
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166 | theplu::utility::vector y(3,0); |
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167 | x(0)=0; x(1)=0; x(2)=2; |
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168 | apw.add_values(x,y,w,w); |
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169 | ap.reset(); |
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170 | ap.add_values(x,y); |
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171 | if (!equal(ap,apw,tol,error)){ |
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172 | *error << "error: AveragerPairWeighted with unitary weights should " |
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173 | << "be equal to AveragerPair" << std::endl; |
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174 | ok=false; |
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175 | } |
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176 | |
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177 | AveragerPairWeighted* apw2 = new AveragerPairWeighted(apw); |
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178 | if (!equal(apw,*apw2,tol,error)){ |
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179 | *error << "error: AveragerPairWeighted copy constructor " << std::endl; |
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180 | ok=false; |
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181 | } |
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182 | |
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183 | apw2->add(12,23222.03,32.3,0); |
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184 | if (!equal(apw,*apw2,tol,error)){ |
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185 | *error << "error: AveragerWeighted adding a data point with weight=0 " |
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186 | << "should make no change " << std::endl; |
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187 | ok=false; |
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188 | } |
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189 | |
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190 | apw2->reset(); |
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191 | w.scale(17); |
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192 | apw2->add_values(x,y,w,w); |
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193 | if (!equal(apw,*apw2,tol,error)){ |
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194 | *error << "error: AveragerWeighted rescaling weights " |
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195 | << "should make no change " << std::endl; |
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196 | ok=false; |
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197 | } |
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198 | delete apw2; |
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199 | |
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200 | if (error!=&std::cerr) |
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201 | delete error; |
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202 | |
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203 | if (!ok) |
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204 | return -1; |
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205 | return 0; |
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206 | } |
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207 | |
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208 | bool equal(const Averager& a, const Averager& b) |
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209 | { |
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210 | // std::cout << (a.n()==b.n()) << std::endl; |
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211 | // std::cout << (a.mean()==b.mean()) << std::endl; |
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212 | // std::cout << (a.variance()==b.variance()) << std::endl; |
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213 | return (a.n()==b.n() && a.mean()==b.mean() && a.variance()==b.variance()); |
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214 | } |
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215 | |
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216 | bool equal(const AveragerWeighted& a, const AveragerWeighted& b, |
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217 | const double tol, std::ostream* error) |
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218 | { |
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219 | bool equal = true; |
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220 | if ( fabs(a.mean()-b.mean())>tol){ |
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221 | equal=false; |
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222 | *error << "mean:\t" << a.mean() << "\t" << b.mean() << std::endl; |
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223 | } |
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224 | if ( fabs(a.variance()-b.variance())>tol ) { |
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225 | equal=false; |
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226 | *error << "error for variance:\t" << a.variance() << " " << b.variance() |
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227 | << std::endl; |
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228 | } |
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229 | if ( fabs(a.standard_error()-b.standard_error())>tol ) { |
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230 | equal =false; |
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231 | *error << "error for standard error:\t" << std::endl; |
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232 | } |
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233 | return equal; |
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234 | } |
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235 | |
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236 | bool equal(const Averager& a, const AveragerWeighted& b, const double tol, |
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237 | std::ostream* error) |
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238 | { |
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239 | bool equal = true; |
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240 | if ( fabs(a.mean()-b.mean())>tol){ |
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241 | equal=false; |
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242 | *error << "mean:\t" << a.mean() << "\t" << b.mean() << std::endl; |
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243 | } |
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244 | if ( fabs(a.variance()-b.variance())>tol ) { |
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245 | equal=false; |
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246 | *error << "error for variance:\t" << a.variance() << " " << b.variance() |
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247 | << std::endl; |
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248 | } |
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249 | if ( fabs(a.standard_error()-b.standard_error())>tol ) { |
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250 | equal =false; |
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251 | *error << "error for standard error:\t" << std::endl; |
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252 | } |
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253 | return equal; |
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254 | } |
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255 | |
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256 | bool equal(const AveragerPair& a, const AveragerPair& b, |
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257 | const double tol, std::ostream* error) |
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258 | { |
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259 | bool ok = true; |
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260 | if ( fabs(a.covariance()-b.covariance())>tol){ |
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261 | ok=false; |
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262 | *error << "error covariance: " << a.covariance() << "\t" |
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263 | << b.covariance() << std::endl; |
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264 | } |
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265 | if ( fabs(a.correlation()-b.correlation())>tol ) { |
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266 | ok=false; |
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267 | *error << "error correlation" << std::endl; |
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268 | } |
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269 | return ok; |
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270 | } |
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271 | |
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272 | bool equal(const AveragerPair& a, const AveragerPairWeighted& b, |
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273 | const double tol, std::ostream* error) |
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274 | { |
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275 | bool ok = true; |
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276 | if ( fabs(a.covariance()-b.covariance())>tol){ |
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277 | ok=false; |
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278 | *error << "error covariance: " << a.covariance() << "\t" |
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279 | << b.covariance() << std::endl; |
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280 | } |
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281 | if ( fabs(a.correlation()-b.correlation())>tol ) { |
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282 | ok=false; |
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283 | *error << "error correlation" << std::endl; |
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284 | } |
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285 | if ( !equal(a.x_averager(),b.x_averager(),tol,error)) { |
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286 | ok =false; |
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287 | *error << "error for x_averager():\t" << std::endl; |
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288 | } |
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289 | return ok; |
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290 | } |
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291 | bool equal(const AveragerPairWeighted& a, const AveragerPairWeighted& b, |
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292 | const double tol, std::ostream* error) |
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293 | { |
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294 | bool ok = true; |
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295 | if ( fabs(a.covariance()-b.covariance())>tol){ |
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296 | ok=false; |
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297 | *error << "error covariance: " << a.covariance() << "\t" |
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298 | << b.covariance() << std::endl; |
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299 | } |
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300 | if ( fabs(a.correlation()-b.correlation())>tol ) { |
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301 | ok=false; |
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302 | *error << "error correlation" << std::endl; |
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303 | } |
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304 | if ( !equal(a.x_averager(),b.x_averager(),tol,error)) { |
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305 | ok =false; |
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306 | *error << "error for x_averager():\t" << std::endl; |
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307 | } |
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308 | return ok; |
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309 | } |
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310 | |
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311 | |
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312 | |
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