Merge pull request #1346 from votjakovr/feature/gp_refactoring

Move common methods from drived classes of inference methods to base class
shogun-toolbox · Aug 1, 2013 · ca5c973 · ca5c973
2 parents 5caa7db + f6b5c23
commit ca5c973
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Showing 4 changed files with 26 additions and 70 deletions.
diff --git a/src/shogun/machine/gp/ExactInferenceMethod.h b/src/shogun/machine/gp/ExactInferenceMethod.h
@@ -146,28 +146,6 @@ class CExactInferenceMethod: public CInferenceMethod
 	 */
 	virtual SGVector<float64_t> get_diagonal_vector();
 
-	/** get the gradient
-	 *
-	 * @return map of gradient: keys are names of parameters, values
-	 * are values of derivative with respect to that parameter.
-	 */
-	virtual CMap<TParameter*, SGVector<float64_t> > get_gradient(
-			CMap<TParameter*, CSGObject*>& para_dict)
-	{
-		return get_marginal_likelihood_derivatives(para_dict);
-	}
-
-	/** get the function value
-	 *
-	 * @return vector that represents the function value
-	 */
-	virtual SGVector<float64_t> get_quantity()
-	{
-		SGVector<float64_t> result(1);
-		result[0] = get_negative_marginal_likelihood();
-		return result;
-	}
-
 	/**
 	 * @return whether combination of exact inference method and given
 	 * likelihood function supports regression

diff --git a/src/shogun/machine/gp/FITCInferenceMethod.h b/src/shogun/machine/gp/FITCInferenceMethod.h
@@ -164,28 +164,6 @@ class CFITCInferenceMethod: public CInferenceMethod
 	 */
 	virtual SGVector<float64_t> get_diagonal_vector();
 
-	/** get the gradient
-	 *
-	 * @return map of gradient: keys are names of parameters, values
-	 * are values of derivative with respect to that parameter.
-	 */
-	virtual CMap<TParameter*, SGVector<float64_t> > get_gradient(
-			CMap<TParameter*, CSGObject*>& para_dict)
-	{
-		return get_marginal_likelihood_derivatives(para_dict);
-	}
-
-	/** get the function value
-	 *
-	 * @return vector that represents the function value
-	 */
-	virtual SGVector<float64_t> get_quantity()
-	{
-		SGVector<float64_t> result(1);
-		result[0] = get_negative_marginal_likelihood();
-		return result;
-	}
-
 	/**
 	 * @return whether combination of FITC inference method and given
 	 * likelihood function supports regression

diff --git a/src/shogun/machine/gp/InferenceMethod.h b/src/shogun/machine/gp/InferenceMethod.h
@@ -133,6 +133,28 @@ class CInferenceMethod : public CDifferentiableFunction
 	 */
 	virtual SGVector<float64_t> get_diagonal_vector()=0;
 
+	/** get the gradient
+	 *
+	 * @return map of gradient: keys are names of parameters, values
+	 * are values of derivative with respect to that parameter.
+	 */
+	virtual CMap<TParameter*, SGVector<float64_t> > get_gradient(
+			CMap<TParameter*, CSGObject*>& para_dict)
+	{
+		return get_marginal_likelihood_derivatives(para_dict);
+	}
+
+	/** get the function value
+	 *
+	 * @return vector that represents the function value
+	 */
+	virtual SGVector<float64_t> get_quantity()
+	{
+		SGVector<float64_t> result(1);
+		result[0]=get_negative_marginal_likelihood();
+		return result;
+	}
+
 	/** returns mean vector \f$\mu\f$ of the Gaussian distribution
 	 * \f$N(\mu,\Sigma)\f$, which is an approximation to the
 	 * posterior:

diff --git a/src/shogun/machine/gp/LaplacianInferenceMethod.h b/src/shogun/machine/gp/LaplacianInferenceMethod.h
@@ -173,28 +173,6 @@ class CLaplacianInferenceMethod: public CInferenceMethod
 	 */
 	virtual SGMatrix<float64_t> get_posterior_approximation_covariance();
 
-	/** get the gradient
-	 *
-	 * @return map of gradient: keys are names of parameters, values
-	 * are values of derivative with respect to that parameter.
-	 */
-	virtual CMap<TParameter*, SGVector<float64_t> > get_gradient(
-			CMap<TParameter*, CSGObject*>& para_dict)
-	{
-		return get_marginal_likelihood_derivatives(para_dict);
-	}
-
-	/** get the function value
-	 *
-	 * @return vector that represents the function value
-	 */
-	virtual SGVector<float64_t> get_quantity()
-	{
-		SGVector<float64_t> result(1);
-		result[0] = get_negative_marginal_likelihood();
-		return result;
-	}
-
 	/** get tolerance for newton iterations
 	 *
 	 * @return tolerance for newton iterations
@@ -231,15 +209,15 @@ class CLaplacianInferenceMethod: public CInferenceMethod
 	 */
 	virtual void set_minimization_tolerance(float64_t tol) { m_opt_tolerance=tol; }
 
-	/** get max for Brent's minimization method
+	/** get maximum for Brent's minimization method
 	 *
-	 * @return max for Brent's minimization method
+	 * @return maximum for Brent's minimization method
 	 */
 	virtual float64_t get_minimization_max() { return m_opt_max; }
 
-	/** set max for Brent's minimization method
+	/** set maximum for Brent's minimization method
 	 *
-	 * @param iter max for Brent's minimization method
+	 * @param max maximum for Brent's minimization method
 	 */
 	virtual void set_minimization_max(float64_t max) { m_opt_max=max; }