1 | #define BDMLIB // not an ideal way to prevent double registration of UI factories... |
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2 | #include "base/bdmbase.h" |
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3 | #include "base/user_info.h" |
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4 | #include "stat/exp_family.h" |
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5 | #include "itpp_ext.h" |
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6 | #include "epdf_harness.h" |
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7 | #include "mat_checks.h" |
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8 | #include "UnitTest++.h" |
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9 | |
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10 | const double epsilon = 0.00001; |
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11 | |
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12 | namespace UnitTest |
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13 | { |
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14 | |
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15 | inline void CheckClose(TestResults &results, const itpp::vec &expected, |
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16 | const itpp::vec &actual, double tolerance, |
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17 | TestDetails const &details) { |
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18 | if (!AreClose(expected, actual, tolerance)) { |
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19 | MemoryOutStream stream; |
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20 | stream << "Expected " << expected << " +/- " << tolerance << " but was " << actual; |
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21 | |
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22 | results.OnTestFailure(details, stream.GetText()); |
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23 | } |
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24 | } |
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25 | |
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26 | } |
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27 | |
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28 | using namespace bdm; |
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29 | |
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30 | template<> |
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31 | const ParticularUI<egiw> &ParticularUI<egiw>::factory( |
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32 | ParticularUI<egiw>("egiw")); |
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33 | |
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34 | TEST(test_egiw) { |
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35 | RV::clear_all(); |
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36 | UIFile in("egiw.cfg"); |
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37 | Array<epdf_harness *> input; |
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38 | UI::get(input, in, "data"); |
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39 | int sz = input.size(); |
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40 | CHECK(sz > 0); |
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41 | for (int i = 0; i < sz; ++i) { |
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42 | input(i)->test(); |
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43 | } |
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44 | } |
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45 | |
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46 | TEST(test_egiw_1_2) { |
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47 | // Setup model |
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48 | double mu = 1.1; //unit step parametr |
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49 | double b = 3.0; // sequence of <1 -1 1 -1...> |
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50 | double s = 0.1; |
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51 | |
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52 | |
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53 | // TEST 1x1 EGIW |
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54 | mat V(3, 3); |
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55 | V(0, 0) = pow(mu, 2) + pow(b, 2) + s; |
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56 | V(1, 0) = mu; |
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57 | V(2, 0) = b; |
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58 | |
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59 | V(0, 1) = V(1, 0); |
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60 | V(1, 1) = 1.0; |
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61 | V(2, 1) = 0.0; |
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62 | |
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63 | V(0, 2) = V(2, 0); |
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64 | V(1, 2) = V(2, 1); |
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65 | V(2, 2) = 1.0; |
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66 | |
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67 | double nu = 20; |
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68 | |
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69 | egiw E(1, nu * V, nu); |
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70 | CHECK_CLOSE(vec("1.1 3.0 0.142857"), E.mean(), epsilon); |
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71 | CHECK_CLOSE(7.36731, E.lognc(), epsilon); |
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72 | |
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73 | int n = 100; |
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74 | vec rgr(3); |
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75 | |
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76 | mat Tmp(2 * n, n); |
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77 | |
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78 | double summ = 0.0; |
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79 | for (int k = 0; k < n; k++) { // ALL b |
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80 | rgr(1) = 1 + k * (1.0 / n) * 4.0; |
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81 | for (int i = 0; i < 2*n; i++) { //ALL mu |
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82 | rgr(0) = -2 + i * (1.0 / n) * 3.0; |
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83 | for (int j = 0; j < n; j++) { // All sigma |
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84 | rgr(2) = (j + 1) * (1.0 / n) * 2.0; |
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85 | |
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86 | Tmp(i, j) = E.evallog(rgr); |
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87 | } |
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88 | } |
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89 | summ += sumsum(exp(Tmp)) / n / n / n * 3.0 * 2.0 * 4.0; |
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90 | } |
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91 | |
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92 | CHECK_CLOSE(1.0, summ, 0.1); |
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93 | } |
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