72 lines
1.8 KiB
Matlab
72 lines
1.8 KiB
Matlab
%-----------------------------------------------------------------------
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% equals
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fg = createGaussianFactorGraph();
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fg2 = createGaussianFactorGraph();
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CHECK('equals',fg.equals(fg,fg2));
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%-----------------------------------------------------------------------
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% error
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cfg = createZeroDelta();
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actual = fg.error(cfg);
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DOUBLES_EQUAL( 5.625, actual, 1e-9 );
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%-----------------------------------------------------------------------
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%-----------------------------------------------------------------------
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% eliminate_x1
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fg = createGaussianFactorGraph();
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actual = fg.eliminateOne('x1');
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%-----------------------------------------------------------------------
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% eliminate_x2
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fg = createGaussianFactorGraph();
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actual = fg.eliminateOne('x2');
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%-----------------------------------------------------------------------
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% eliminateAll
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sigma1=.1;
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R1 = eye(2);
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d1=[-.1;-.1];
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cg1 = GaussianConditional('x1',d1, R1,sigma1);
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sigma2=0.149071;
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R2 = eye(2);
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A1= -eye(2);
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d2=[0; .2];
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cg2 = GaussianConditional('l1',d2, R2, 'x1', A1,sigma2);
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sigma3=0.0894427;
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R3 = eye(2);
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A21 = [ -.2, 0.0
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0.0, -.2];
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A22 = [-.8, 0.0
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0.0, -.8];
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d3 =[.2; -.14];
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cg3 = GaussianConditional('x2',d3, R3, 'l1', A21, 'x1', A22, sigma3);
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expected = GaussianBayesNet;
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expected.push_back(cg1);
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expected.push_back(cg2);
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expected.push_back(cg3);
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expected.print('expected');
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% Check one ordering
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fg1 = createGaussianFactorGraph();
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ord1 = Ordering;
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ord1.push_back('x2');
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ord1.push_back('l1');
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ord1.push_back('x1');
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actual1 = fg1.eliminate_(ord1);
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actual1.print('actual');
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%CHECK('eliminateAll', actual1.equals(expected));
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%-----------------------------------------------------------------------
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% matrix
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fg = createGaussianFactorGraph();
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ord = Ordering;
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ord.push_back('x2');
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ord.push_back('l1');
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ord.push_back('x1');
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A = fg.matrix(ord);
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