Added better docs
							parent
							
								
									e0a40b306d
								
							
						
					
					
						commit
						aed576ca0a
					
				| 
						 | 
				
			
			@ -38,8 +38,28 @@ typedef FastSet<FactorIndex> FactorIndexSet;
 | 
			
		|||
   * data other than its keys.  Derived classes store data such as matrices and
 | 
			
		||||
   * probability tables.
 | 
			
		||||
   *
 | 
			
		||||
   * Note that derived classes *must* redefine the `This` and `shared_ptr`
 | 
			
		||||
   * typedefs. See JacobianFactor, etc. for examples.
 | 
			
		||||
   * The `error` method is used to evaluate the factor, and is the only method
 | 
			
		||||
   * that is required to be implemented in derived classes, although it has a 
 | 
			
		||||
   * default implementation that throws an exception. The meaning of the error
 | 
			
		||||
   * is slightly different for factors and conditionals: in the former it is the
 | 
			
		||||
   * negative log-likelihood, and in the latter it is the negative log of the 
 | 
			
		||||
   * properly normalized conditional distribution or density.
 | 
			
		||||
   * 
 | 
			
		||||
   * There are five broad classes of factors that derive from Factor:
 | 
			
		||||
   *
 | 
			
		||||
   * - \b Nonlinear factors, such as \class NonlinearFactor and \class NoiseModelFactor, which
 | 
			
		||||
   *   represent a nonlinear likelihood function over a set of variables.
 | 
			
		||||
   * - \b Gaussian factors, such as \class JacobianFactor and \class HessianFactor, which
 | 
			
		||||
   *   represent a Gaussian likelihood over a set of variables.
 | 
			
		||||
   *   A \class GaussianConditional, which represent a Gaussian density over a set of
 | 
			
		||||
   *   variables conditioned on another set of variables.
 | 
			
		||||
   * - \b Discrete factors, such as \class DiscreteFactor and \class DiscreteConditional, which
 | 
			
		||||
   *   represent a discrete distribution over a set of variables.
 | 
			
		||||
   * - \b Hybrid factors, such as \class HybridFactor, which represent a mixture of
 | 
			
		||||
   *   Gaussian and discrete distributions over a set of variables.
 | 
			
		||||
   * - \b Symbolic factors, used to represent a graph structure, such as
 | 
			
		||||
   *   \class SymbolicFactor and \class SymbolicConditional. They do not override the
 | 
			
		||||
   *  `error` method, and are used only for symbolic elimination etc.
 | 
			
		||||
   *
 | 
			
		||||
   * This class is \b not virtual for performance reasons - the derived class
 | 
			
		||||
   * SymbolicFactor needs to be created and destroyed quickly during symbolic
 | 
			
		||||
| 
						 | 
				
			
			
 | 
			
		|||
		Loading…
	
		Reference in New Issue