| 1 | #define BDMLIB // not an ideal way to prevent double registration of UI factories... |
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| 2 | #include "stat/exp_family.h" |
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| 3 | #include "stat/emix.h" |
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| 4 | #include "mat_checks.h" |
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| 5 | #include "test_util.h" |
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| 6 | #include "UnitTest++.h" |
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| 7 | |
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| 8 | using namespace bdm; |
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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 | inline void CheckClose(TestResults &results, const itpp::mat &expected, |
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| 27 | const itpp::mat &actual, double tolerance, |
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| 28 | TestDetails const& details) { |
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| 29 | if (!AreClose(expected, actual, tolerance)) { |
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| 30 | MemoryOutStream stream; |
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| 31 | stream << "Expected " << expected << " +/- " << tolerance << " but was " << actual; |
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| 32 | |
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| 33 | results.OnTestFailure(details, stream.GetText()); |
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| 34 | } |
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| 35 | } |
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| 36 | |
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| 37 | } |
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| 38 | |
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| 39 | TEST(test_enorm) { |
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| 40 | RNG_randomize(); |
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| 41 | |
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| 42 | // Setup model |
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| 43 | vec mu("1.1 -1"); |
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| 44 | ldmat R(mat("1 -0.5; -0.5 2")); |
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| 45 | |
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| 46 | RV x("{x }"); |
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| 47 | RV y("{y }"); |
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| 48 | |
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| 49 | enorm<ldmat> E; |
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| 50 | E.set_rv(concat(x,y)); |
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| 51 | E.set_parameters(mu, R); |
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| 52 | CHECK_EQUAL(mu, E.mean()); |
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| 53 | CHECK_CLOSE(2.11768, E.lognc(), epsilon); |
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| 54 | CHECK_CLOSE(1.0, normcoef(&E, vec("-5 5"), vec("-5 5")), 0.01); |
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| 55 | |
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| 56 | int N = 1000; |
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| 57 | vec ll(N); |
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| 58 | mat Smp = E.sample(1000); |
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| 59 | vec Emu = sum(Smp, 2) / N; |
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| 60 | CHECK_CLOSE(mu, Emu, 0.3); |
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| 61 | |
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| 62 | mat Er = (Smp * Smp.T()) / N - outer_product(Emu, Emu); |
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| 63 | CHECK_CLOSE(R.to_mat(), Er, 0.3); |
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| 64 | |
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| 65 | epdf *Mg = E.marginal(y); |
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| 66 | CHECK_CLOSE(vec("-1"), Mg->mean(), epsilon); |
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| 67 | |
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| 68 | // putting them back together |
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| 69 | mpdf *Cn = E.condition(x); |
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| 70 | mepdf mMg(Mg); |
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| 71 | Array<mpdf *> A(2); |
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| 72 | A(0) = Cn; |
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| 73 | A(1) = &mMg; |
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| 74 | mprod mEp(A); |
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| 75 | Smp = mEp.samplecond(vec(0), 1000); |
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| 76 | Emu = sum(Smp, 2) / N; |
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| 77 | CHECK_CLOSE(mu, Emu, 0.3); |
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| 78 | |
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| 79 | Er = (Smp * Smp.T()) / N - outer_product(Emu, Emu); |
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| 80 | CHECK_CLOSE(R.to_mat(), Er, 0.3); |
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| 81 | |
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| 82 | // test of pdflog at zero |
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| 83 | vec zero(0); |
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| 84 | vec zero2("0 0"); |
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| 85 | CHECK_CLOSE(E.evallog(zero2), mEp.evallogcond(zero2, zero), epsilon); |
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| 86 | } |
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| 87 | |
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| 88 | // from testEpdf |
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| 89 | TEST(test_enorm_sum) { |
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| 90 | vec x = "-10:0.1:10"; |
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| 91 | vec y = "-10:0.1:10"; |
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| 92 | |
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| 93 | RV rv("{x2 }", "2"); |
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| 94 | vec mu0 = "0.0 0.0"; |
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| 95 | mat V0 = "5 -0.05; -0.05 5.20"; |
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| 96 | fsqmat R(V0); |
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| 97 | |
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| 98 | enorm<fsqmat> eN; |
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| 99 | eN.set_rv(rv); |
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| 100 | eN.set_parameters(mu0, R); |
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| 101 | |
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| 102 | vec pom(2); |
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| 103 | double suma = 0.0; |
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| 104 | for (int i = 0; i < x.length(); i++) { |
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| 105 | for (int j=0; j<y.length(); j++) { |
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| 106 | pom(0) = x(i); |
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| 107 | pom(1) = y(j); |
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| 108 | suma += exp(eN.evallog(pom)); |
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| 109 | } |
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| 110 | } |
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| 111 | |
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| 112 | CHECK_CLOSE(100, suma, 0.1); |
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| 113 | } |
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