[436] | 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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[386] | 4 | #include "stat/exp_family.h" |
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[436] | 5 | #include "itpp_ext.h" |
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| 6 | #include "epdf_harness.h" |
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[440] | 7 | #include "egiw_harness.h" |
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[436] | 8 | #include "mat_checks.h" |
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| 9 | #include "UnitTest++.h" |
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[188] | 10 | |
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[436] | 11 | const double epsilon = 0.00001; |
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[188] | 12 | |
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[436] | 13 | using namespace bdm; |
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[188] | 14 | |
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[436] | 15 | template<> |
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[477] | 16 | const ParticularUI<egiw> &ParticularUI<egiw>::factory ( |
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| 17 | ParticularUI<egiw> ( "egiw" ) ); |
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[188] | 18 | |
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[440] | 19 | template<> |
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[477] | 20 | const ParticularUI<egiw_harness> &ParticularUI<egiw_harness>::factory ( |
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| 21 | ParticularUI<egiw_harness> ( "egiw_harness" ) ); |
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[440] | 22 | |
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[477] | 23 | TEST ( test_egiw ) { |
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| 24 | epdf_harness::test_config ( "egiw.cfg" ); |
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[436] | 25 | } |
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[188] | 26 | |
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[477] | 27 | TEST ( test_egiw_1_2 ) { |
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| 28 | // Setup model |
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| 29 | double mu = 1.1; //unit step parametr |
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| 30 | double b = 3.0; // sequence of <1 -1 1 -1...> |
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| 31 | double s = 0.1; |
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[188] | 32 | |
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| 33 | |
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[477] | 34 | // TEST 1x1 EGIW |
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| 35 | mat V ( 3, 3 ); |
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| 36 | V ( 0, 0 ) = pow ( mu, 2 ) + pow ( b, 2 ) + s; |
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| 37 | V ( 1, 0 ) = mu; |
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| 38 | V ( 2, 0 ) = b; |
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[188] | 39 | |
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[477] | 40 | V ( 0, 1 ) = V ( 1, 0 ); |
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| 41 | V ( 1, 1 ) = 1.0; |
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| 42 | V ( 2, 1 ) = 0.0; |
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[188] | 43 | |
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[477] | 44 | V ( 0, 2 ) = V ( 2, 0 ); |
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| 45 | V ( 1, 2 ) = V ( 2, 1 ); |
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| 46 | V ( 2, 2 ) = 1.0; |
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[188] | 47 | |
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[477] | 48 | double nu = 20; |
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[188] | 49 | |
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[477] | 50 | egiw E ( 1, nu * V, nu ); |
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| 51 | CHECK_CLOSE ( vec ( "1.1 3.0 0.142857" ), E.mean(), epsilon ); |
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| 52 | CHECK_CLOSE ( 7.36731, E.lognc(), epsilon ); |
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[188] | 53 | |
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[477] | 54 | int n = 100; |
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| 55 | vec rgr ( 3 ); |
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[188] | 56 | |
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[477] | 57 | mat Tmp ( 2 * n, n ); |
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[188] | 58 | |
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[477] | 59 | double summ = 0.0; |
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| 60 | for ( int k = 0; k < n; k++ ) { // ALL b |
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| 61 | rgr ( 1 ) = 1 + k * ( 1.0 / n ) * 4.0; |
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| 62 | for ( int i = 0; i < 2*n; i++ ) { //ALL mu |
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| 63 | rgr ( 0 ) = -2 + i * ( 1.0 / n ) * 3.0; |
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| 64 | for ( int j = 0; j < n; j++ ) { // All sigma |
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| 65 | rgr ( 2 ) = ( j + 1 ) * ( 1.0 / n ) * 2.0; |
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[188] | 66 | |
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[477] | 67 | Tmp ( i, j ) = E.evallog ( rgr ); |
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| 68 | } |
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| 69 | } |
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| 70 | summ += sumsum ( exp ( Tmp ) ) / n / n / n * 3.0 * 2.0 * 4.0; |
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[188] | 71 | } |
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[436] | 72 | |
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[477] | 73 | CHECK_CLOSE ( 1.0, summ, 0.1 ); |
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[188] | 74 | } |
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