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| 2 | #include <estim/kalman.h> |
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| 3 | #include <estim/particles.h> |
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| 4 | #include "../mat_checks.h" |
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| 5 | |
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| 6 | using namespace bdm; |
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| 7 | |
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| 8 | //These lines are needed for use of cout and endl |
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| 9 | using std::cout; |
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| 10 | using std::endl; |
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| 11 | |
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| 12 | TEST ( kalman_QR_stress ) { |
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| 13 | // Klaman filter |
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| 14 | mat A, B, C, D, R, Q, P0; |
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| 15 | vec mu0; |
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| 16 | mat Mu0;// read from matlab |
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| 17 | // input from Matlab |
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| 18 | it_file fin ( "kalman_stress.it" ); |
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| 19 | |
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| 20 | mat Dt, XQRt, eR, eQ; |
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| 21 | int Ndat; |
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| 22 | |
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| 23 | bool xxx = fin.seek ( "d" ); |
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| 24 | if ( !xxx ) { |
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| 25 | bdm_error ( "kalman_stress.it not found" ); |
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| 26 | } |
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| 27 | fin >> Dt; |
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| 28 | fin.seek ( "A" ); |
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| 29 | fin >> A; |
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| 30 | fin.seek ( "B" ); |
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| 31 | fin >> B; |
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| 32 | fin.seek ( "C" ); |
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| 33 | fin >> C; |
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| 34 | fin.seek ( "D" ); |
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| 35 | fin >> D; |
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| 36 | fin.seek ( "R" ); |
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| 37 | fin >> R; |
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| 38 | fin.seek ( "Q" ); |
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| 39 | fin >> Q; |
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| 40 | fin.seek ( "P0" ); |
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| 41 | fin >> P0; |
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| 42 | fin.seek ( "mu0" ); |
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| 43 | fin >> Mu0; |
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| 44 | mu0 = Mu0.get_col ( 0 ); |
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| 45 | |
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| 46 | Ndat = Dt.cols(); |
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| 47 | XQRt = zeros ( 5, Ndat ); |
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| 48 | mat Xt = zeros ( 2, Ndat ); |
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| 49 | |
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| 50 | // cout << KF; |
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| 51 | RV rx ( "{x }", "2" ); |
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| 52 | RV ru ( "{u }", "1" ); |
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| 53 | RV ry ( "{y }", "1" ); |
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| 54 | RV rQR ( "{Q,R }", "3" ); |
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| 55 | // |
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| 56 | KFcondQR KF; |
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| 57 | // KF with R unknown |
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| 58 | KF.set_parameters ( A, B, C, D, ldmat ( R ), ldmat ( Q ) ); |
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| 59 | KF.set_est ( mu0, ldmat ( P0 ) ); |
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| 60 | // |
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| 61 | Kalman<ldmat> KFtr; |
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| 62 | // KF with R unknown |
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| 63 | KFtr.set_parameters ( A, B, C, D, ldmat ( R ), ldmat ( Q ) ); |
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| 64 | KFtr.set_est ( mu0, ldmat ( P0 ) ); |
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| 65 | |
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| 66 | mgamma evolQR; |
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| 67 | evolQR.set_parameters ( 10.0, "1 1 1" ); //sigma = 1/10 mu |
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| 68 | |
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| 69 | MPF<KFcondQR> KF_QR; |
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| 70 | KF_QR.set_parameters ( &evolQR, &evolQR, 100 ); |
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| 71 | evolQR.condition ( "1 1 1" ); |
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| 72 | egamma kfinit=egamma("10 10 10","1 1 1"); |
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| 73 | KF_QR.set_statistics ( egamma("10 10 10","1 1 1"), &KF ); |
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| 74 | const epdf& mpost = KF_QR.posterior(); |
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| 75 | const epdf& mposttr = KFtr.posterior(); |
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| 76 | |
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| 77 | XQRt.set_col ( 0, mpost.mean() ); |
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| 78 | Xt.set_col ( 0, mposttr.mean() ); |
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| 79 | for ( int t = 1; t < Ndat; t++ ) { |
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| 80 | KF_QR.bayes ( Dt.get_col ( t ) ); |
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| 81 | KFtr.bayes ( Dt.get_col ( t ) ); |
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| 82 | |
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| 83 | XQRt.set_col ( t, mpost.mean() ); |
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| 84 | Xt.set_col ( t, mposttr.mean() ); |
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| 85 | } |
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| 86 | |
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| 87 | it_file fou ( "kalman_stress_QR_res.it" ); |
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| 88 | fou << Name ( "xqrth" ) << XQRt; |
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| 89 | fou << Name ( "xth" ) << Xt; |
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| 90 | } |
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