113 lines
		
	
	
		
			2.4 KiB
		
	
	
	
		
			Matlab
		
	
	
			
		
		
	
	
			113 lines
		
	
	
		
			2.4 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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| %-----------------------------------------------------------------------
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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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| % combine_factors_x1
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| fg = createGaussianFactorGraph();
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| %actual = fg.combine_factors('x1');
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| actual = fg.combined('x1');
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| Al1 = [
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|    0., 0.
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|    0., 0.
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|    0., 0.
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|    0., 0.
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|    5., 0.
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|    0., 5.
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|   ];
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|                      
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| Ax1 = [
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|   10.,   0.
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|   0.00, 10.
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|   -10.,  0.
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|   0.00,-10.
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|   -5.,   0.
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|   00.,  -5.
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|   ];
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| 
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| Ax2 = [
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|    0., 0.
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|    0., 0.
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|    10., 0.
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|    +0.,10.
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|    0., 0.
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|    0., 0.
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|   ];
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| 
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| b=[-1;-1;2;-1;0;1];
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| 
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| expected = GaussianFactor('l1',Al1,'x1',Ax1,'x2',Ax2,b);
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| CHECK('combine_factors_x1', actual.equals(expected,1e-9));
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| 
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| %-----------------------------------------------------------------------
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| % combine_factors_x2
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| fg = createGaussianFactorGraph();
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| actual = fg.combine_factors('x2');
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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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| %-----------------------------------------------------------------------
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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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| %-----------------------------------------------------------------------
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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 = ConditionalGaussian('x1',d1, R1,sigma1);
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| 
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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 = ConditionalGaussian('l1',d2, R2, 'x1', A1,sigma2);
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| 
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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 = ConditionalGaussian('x2',d3, R3, 'l1', A21, 'x1', A22, sigma3);
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| 
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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_();
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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();
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| %CHECK('eliminateAll', actual1.equals(expected));
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| 
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| %-----------------------------------------------------------------------
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| % matrix
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| 
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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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| 
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| A = fg.matrix(ord);
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| 
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