rename LogitPiecewiseBoundLikelihood class

examples/undocumented/libshogun/variational_approx_example.cpp

@@ -40,7 +40,7 @@
 #include <shogun/lib/config.h>
 #ifdef HAVE_EIGEN3
 #include <shogun/base/init.h>
-#include <shogun/machine/gp/LogitPiecewiseBoundLikelihood.h>
+#include <shogun/machine/gp/LogitVariationalPiecewiseBoundLikelihood.h>
 #include <shogun/distributions/classical/GaussianDistribution.h>
 #include <shogun/optimization/lbfgs/lbfgs.h>
 #include <shogun/mathematics/Math.h>
@@ -173,7 +173,7 @@ SGVector<float64_t> create_label(const char * fname, SGVector<float64_t> mu,
 //The following struct is used to pass information when using the build-in L-BFGS component
 struct Shared 
 {
-	CLogitPiecewiseBoundLikelihood *lik;
+	CLogitVariationalPiecewiseBoundLikelihood *lik;
 	SGVector<float64_t> y;
 	SGVector<float64_t> mu;
 	lbfgs_parameter_t lbfgs_param;
@@ -215,7 +215,7 @@ float64_t evaluate(void *obj, const float64_t *variable, float64_t *gradient,
 	Shared * obj_prt = static_cast<Shared *>(obj);
 
 	CBinaryLabels lab(obj_prt->y);
-	obj_prt->lik->set_distribution(obj_prt->m0, obj_prt->v, &lab);
+	obj_prt->lik->set_variational_distribution(obj_prt->m0, obj_prt->v, &lab);
 	Eigen::Map<Eigen::VectorXd> eigen_mu(obj_prt->mu.vector, obj_prt->mu.vlen);
 	Eigen::Map<Eigen::VectorXd> eigen_m(obj_prt->m0.vector, obj_prt->m0.vlen);
 
@@ -302,8 +302,8 @@ void run(const char * x_file, const char * y_file, const char * bound_file,
 
 	//load('llp.mat'); 
 	obj.bound = init_piecewise_bound(bound_file);
-	obj.lik = new CLogitPiecewiseBoundLikelihood();
-	obj.lik->set_bound(obj.bound);
+	obj.lik = new CLogitVariationalPiecewiseBoundLikelihood();
+	obj.lik->set_variational_bound(obj.bound);
 
 	//m0 = mu; % initial value all zero
 	obj.m0 = SGVector<float64_t> (num_sample);

src/shogun/machine/gp/LikelihoodModel.h

@@ -320,7 +320,7 @@ class CLikelihoodModel : public CSGObject
 	 * @param lab labels/data used
 	 *
 	 */
-	virtual void set_distribution(SGVector<float64_t> mu, SGVector<float64_t> s2, const CLabels* lab)
+	virtual void set_variational_distribution(SGVector<float64_t> mu, SGVector<float64_t> s2, const CLabels* lab)
 	{
 		SG_ERROR("Set variational distribution not implemented for %s\n", get_name());
 	}

src/shogun/machine/gp/LogitPiecewiseBoundLikelihood.cpp → src/shogun/machine/gp/LogitVariationalPiecewiseBoundLikelihood.cpp

@@ -40,27 +40,29 @@
 
 #ifdef HAVE_EIGEN3
 
-#include <shogun/machine/gp/LogitPiecewiseBoundLikelihood.h>
+#include <shogun/machine/gp/LogitVariationalPiecewiseBoundLikelihood.h>
 
-using namespace shogun;
 using namespace Eigen;
 
-CLogitPiecewiseBoundLikelihood::CLogitPiecewiseBoundLikelihood()
+namespace shogun
+{
+
+CLogitVariationalPiecewiseBoundLikelihood::CLogitVariationalPiecewiseBoundLikelihood()
 	: CLogitLikelihood()
 {
 	init();
 }
 
-CLogitPiecewiseBoundLikelihood::~CLogitPiecewiseBoundLikelihood()
+CLogitVariationalPiecewiseBoundLikelihood::~CLogitVariationalPiecewiseBoundLikelihood()
 {
 }
 
-void CLogitPiecewiseBoundLikelihood::set_bound(SGMatrix<float64_t> bound)
+void CLogitVariationalPiecewiseBoundLikelihood::set_variational_bound(SGMatrix<float64_t> bound)
 {
 	m_bound = bound;
 }
 
-SGVector<float64_t> CLogitPiecewiseBoundLikelihood::get_variational_expection()
+SGVector<float64_t> CLogitVariationalPiecewiseBoundLikelihood::get_variational_expection()
 {
 	//This function is based on the Matlab code,
 	//function [f, gm, gv] = Ellp(m, v, bound, ind), to compute f
@@ -127,7 +129,7 @@ SGVector<float64_t> CLogitPiecewiseBoundLikelihood::get_variational_expection()
 }
 
 
-SGVector<float64_t> CLogitPiecewiseBoundLikelihood::get_variational_first_derivative(
+SGVector<float64_t> CLogitVariationalPiecewiseBoundLikelihood::get_variational_first_derivative(
 		const TParameter* param) const
 {
 	//This function is based on the Matlab code
@@ -237,7 +239,7 @@ SGVector<float64_t> CLogitPiecewiseBoundLikelihood::get_variational_first_deriva
 	return result;
 }
 
-void CLogitPiecewiseBoundLikelihood::set_distribution(SGVector<float64_t> mu,
+void CLogitVariationalPiecewiseBoundLikelihood::set_variational_distribution(SGVector<float64_t> mu,
 	SGVector<float64_t> s2, const CLabels* lab)
 {
 	REQUIRE(lab, "Labels are required (lab should not be NULL)\n");
@@ -267,7 +269,7 @@ void CLogitPiecewiseBoundLikelihood::set_distribution(SGVector<float64_t> mu,
 	precompute();
 }
 
-void CLogitPiecewiseBoundLikelihood::init()
+void CLogitVariationalPiecewiseBoundLikelihood::init()
 {
 	SG_ADD(&m_bound, "bound", 
 		"Variational piecewise bound for logit likelihood",
@@ -305,7 +307,7 @@ void CLogitPiecewiseBoundLikelihood::init()
 		MS_NOT_AVAILABLE);
 }
 
-void CLogitPiecewiseBoundLikelihood::precompute()
+void CLogitVariationalPiecewiseBoundLikelihood::precompute()
 {
 	//This function is based on the Matlab code
 	//function [f, gm, gv] = Ellp(m, v, bound, ind), to compute common variables later
@@ -413,4 +415,5 @@ void CLogitPiecewiseBoundLikelihood::precompute()
 	eigen_h(eigen_h.size()-1) = h_bak;
 }
 
+} /* namespace shogun */
 #endif /* HAVE_EIGEN3 */

src/shogun/machine/gp/LogitPiecewiseBoundLikelihood.h → src/shogun/machine/gp/LogitVariationalPiecewiseBoundLikelihood.h

@@ -34,8 +34,8 @@
  * "Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models." ICML. 2011.
  */
 
-#ifndef _LOGITPIECEWISEBOUNDLIKELIHOOD_H_
-#define _LOGITPIECEWISEBOUNDLIKELIHOOD_H_
+#ifndef _LOGITVARIATIONALPIECEWISEBOUNDLIKELIHOOD_H_
+#define _LOGITVARIATIONALPIECEWISEBOUNDLIKELIHOOD_H_
 
 #include <shogun/lib/config.h>
 
@@ -65,24 +65,24 @@ namespace shogun
  * m is the size of the pre-defined bound, which is the num_rows of bound passed in set_bound
  * (In the reference Matlab code, m is 20)
  */
-class CLogitPiecewiseBoundLikelihood : public CLogitLikelihood
+class CLogitVariationalPiecewiseBoundLikelihood : public CLogitLikelihood
 {
 public:
-	CLogitPiecewiseBoundLikelihood();
+	CLogitVariationalPiecewiseBoundLikelihood();
 
-	virtual ~CLogitPiecewiseBoundLikelihood();
+	virtual ~CLogitVariationalPiecewiseBoundLikelihood();
 
 	/** returns the name of the likelihood model
 	 *
 	 * @return name LogitPiecewiseBoundLikelihood
 	 */
-	virtual const char* get_name() const { return "LogitPiecewiseBoundLikelihood"; }
+	virtual const char* get_name() const { return "LogitVariationalPiecewiseBoundLikelihood"; }
 
 	/** set the variational piecewise bound for logit likelihood
 	 *
 	 *  @param bound variational piecewise bound
 	 */
-	virtual void set_bound(SGMatrix<float64_t> bound);
+	virtual void set_variational_bound(SGMatrix<float64_t> bound);
 
 	/** set the variational normal distribution given data and parameters
 	 *
@@ -91,7 +91,7 @@ class CLogitPiecewiseBoundLikelihood : public CLogitLikelihood
 	 * @param lab labels/data used
 	 *
 	 */
-	virtual void set_distribution(SGVector<float64_t> mu, SGVector<float64_t> s2, const CLabels* lab);
+	virtual void set_variational_distribution(SGVector<float64_t> mu, SGVector<float64_t> s2, const CLabels* lab);
 
 	/** returns the expection of the logarithm of a logit distribution 
 	 * wrt the variational distribution using piecewise bound
@@ -124,7 +124,7 @@ class CLogitPiecewiseBoundLikelihood : public CLogitLikelihood
 
 	/** compute common variables later used in get_variational_expection
 	 * and get_variational_first_derivative.
-	 * Note that this method will automatically be called when set_distribution is called
+	 * Note that this method will automatically be called when set_variational_distribution is called
 	 */
 	void precompute();
 
@@ -163,4 +163,4 @@ class CLogitPiecewiseBoundLikelihood : public CLogitLikelihood
 };
 }
 #endif /* HAVE_EIGEN3 */
-#endif /* _LOGITPIECEWISEBOUNDLIKELIHOOD_H_ */
+#endif /* _LOGITVARIATIONALPIECEWISEBOUNDLIKELIHOOD_H_ */

tests/unit/machine/gp/LogitPiecewiseBoundLikelihood_unittest.cc → tests/unit/machine/gp/LogitVariationalPiecewiseBoundLikelihood_unittest.cc

@@ -43,7 +43,7 @@
 #ifdef HAVE_EIGEN3
 
 #include <shogun/labels/BinaryLabels.h>
-#include <shogun/machine/gp/LogitPiecewiseBoundLikelihood.h>
+#include <shogun/machine/gp/LogitVariationalPiecewiseBoundLikelihood.h>
 #include <shogun/mathematics/Math.h>
 #include <gtest/gtest.h>
 
@@ -164,7 +164,7 @@ SGMatrix<float64_t> init_bound()
 	return bound;
 }
 
-TEST(LogitPiecewiseBoundLikelihood,get_variational_expection)
+TEST(LogitVariationalPiecewiseBoundLikelihood,get_variational_expection)
 {
 	float64_t rel_tolorance = 1e-2;
 	float64_t abs_tolorance;
@@ -209,10 +209,10 @@ TEST(LogitPiecewiseBoundLikelihood,get_variational_expection)
 	v[8] = 64;
 	v[9] = 625;
 
-	CLogitPiecewiseBoundLikelihood *lik = new CLogitPiecewiseBoundLikelihood();
-	lik->set_bound(bound);
+	CLogitVariationalPiecewiseBoundLikelihood *lik = new CLogitVariationalPiecewiseBoundLikelihood();
+	lik->set_variational_bound(bound);
 	CBinaryLabels* lab = new CBinaryLabels(y);
-	lik->set_distribution(m, v, lab);
+	lik->set_variational_distribution(m, v, lab);
 
 	SGVector<float64_t> fi = lik->get_variational_expection();
 
@@ -243,7 +243,7 @@ TEST(LogitPiecewiseBoundLikelihood,get_variational_expection)
 	SG_UNREF(lik);
 }
 
-TEST(LogitPiecewiseBoundLikelihood,get_variational_first_derivative_wrt_sigma2)
+TEST(LogitVariationalPiecewiseBoundLikelihood,get_variational_first_derivative_wrt_sigma2)
 {
 	float64_t rel_tolorance = 1e-2;
 	float64_t abs_tolorance;
@@ -288,10 +288,10 @@ TEST(LogitPiecewiseBoundLikelihood,get_variational_first_derivative_wrt_sigma2)
 	v[8] = 64;
 	v[9] = 625;
 
-	CLogitPiecewiseBoundLikelihood *lik = new CLogitPiecewiseBoundLikelihood();
-	lik->set_bound(bound);
+	CLogitVariationalPiecewiseBoundLikelihood *lik = new CLogitVariationalPiecewiseBoundLikelihood();
+	lik->set_variational_bound(bound);
 	CBinaryLabels* lab = new CBinaryLabels(y);
-	lik->set_distribution(m, v, lab);
+	lik->set_variational_distribution(m, v, lab);
 
 	TParameter* s2_param=lik->m_gradient_parameters->get_parameter("sigma2");
 
@@ -324,7 +324,7 @@ TEST(LogitPiecewiseBoundLikelihood,get_variational_first_derivative_wrt_sigma2)
 	SG_UNREF(lik);
 }
 
-TEST(LogitPiecewiseBoundLikelihood,get_variational_first_derivative_wrt_mu)
+TEST(LogitVariationalPiecewiseBoundLikelihood,get_variational_first_derivative_wrt_mu)
 {
 	float64_t rel_tolorance = 1e-2;
 	float64_t abs_tolorance;
@@ -369,10 +369,10 @@ TEST(LogitPiecewiseBoundLikelihood,get_variational_first_derivative_wrt_mu)
 	v[8] = 64;
 	v[9] = 625;
 
-	CLogitPiecewiseBoundLikelihood *lik = new CLogitPiecewiseBoundLikelihood();
-	lik->set_bound(bound);
+	CLogitVariationalPiecewiseBoundLikelihood *lik = new CLogitVariationalPiecewiseBoundLikelihood();
+	lik->set_variational_bound(bound);
 	CBinaryLabels* lab = new CBinaryLabels(y);
-	lik->set_distribution(m, v, lab);
+	lik->set_variational_distribution(m, v, lab);
 
 	TParameter* mu_param=lik->m_gradient_parameters->get_parameter("mu");