Renamed liblinear structures to avoid name clashes in future

shogun-toolbox · Jun 8, 2013 · eca7941 · eca7941
1 parent 5aed350
commit eca7941
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Showing 9 changed files with 38 additions and 38 deletions.
diff --git a/src/shogun/classifier/svm/LibLinear.cpp b/src/shogun/classifier/svm/LibLinear.cpp
@@ -120,7 +120,7 @@ bool CLibLinear::train_machine(CFeatures* data)
 	else
 		w=SGVector<float64_t>(num_feat);
 
-	problem prob;
+	liblinear_problem prob;
 	if (use_bias)
 	{
 		prob.n=w.vlen+1;
@@ -250,7 +250,7 @@ bool CLibLinear::train_machine(CFeatures* data)
 // To support weights for instances, use GETI(i) (i)
 
 void CLibLinear::solve_l2r_l1l2_svc(
-			const problem *prob, double eps, double Cp, double Cn, LIBLINEAR_SOLVER_TYPE st)
+			const liblinear_problem *prob, double eps, double Cp, double Cn, LIBLINEAR_SOLVER_TYPE st)
 {
 	int l = prob->l;
 	int w_size = prob->n;
@@ -450,7 +450,7 @@ void CLibLinear::solve_l2r_l1l2_svc(
 // To support weights for instances, use GETI(i) (i)
 
 void CLibLinear::solve_l1r_l2_svc(
-	problem *prob_col, double eps, double Cp, double Cn)
+	liblinear_problem *prob_col, double eps, double Cp, double Cn)
 {
 	int l = prob_col->l;
 	int w_size = prob_col->n;
@@ -796,7 +796,7 @@ void CLibLinear::solve_l1r_l2_svc(
 // To support weights for instances, use GETI(i) (i)
 
 void CLibLinear::solve_l1r_lr(
-	const problem *prob_col, double eps,
+	const liblinear_problem *prob_col, double eps,
 	double Cp, double Cn)
 {
 	int l = prob_col->l;
@@ -1167,7 +1167,7 @@ void CLibLinear::solve_l1r_lr(
 #define GETI(i) (y[i]+1)
 // To support weights for instances, use GETI(i) (i)
 
-void CLibLinear::solve_l2r_lr_dual(const problem *prob, double eps, double Cp, double Cn)
+void CLibLinear::solve_l2r_lr_dual(const liblinear_problem *prob, double eps, double Cp, double Cn)
 {
 	int l = prob->l;
 	int w_size = prob->n;

diff --git a/src/shogun/classifier/svm/LibLinear.h b/src/shogun/classifier/svm/LibLinear.h
@@ -174,13 +174,13 @@ class CLibLinear : public CLinearMachine
 		/** set up parameters */
         void init();
 
-		void train_one(const problem *prob, const parameter *param, double Cp, double Cn);
+		void train_one(const liblinear_problem *prob, const liblinear_parameter *param, double Cp, double Cn);
 		void solve_l2r_l1l2_svc(
-			const problem *prob, double eps, double Cp, double Cn, LIBLINEAR_SOLVER_TYPE st);
+			const liblinear_problem *prob, double eps, double Cp, double Cn, LIBLINEAR_SOLVER_TYPE st);
 
-		void solve_l1r_l2_svc(problem *prob_col, double eps, double Cp, double Cn);
-		void solve_l1r_lr(const problem *prob_col, double eps, double Cp, double Cn);
-		void solve_l2r_lr_dual(const problem *prob, double eps, double Cp, double Cn);
+		void solve_l1r_l2_svc(liblinear_problem *prob_col, double eps, double Cp, double Cn);
+		void solve_l1r_lr(const liblinear_problem *prob_col, double eps, double Cp, double Cn);
+		void solve_l2r_lr_dual(const liblinear_problem *prob, double eps, double Cp, double Cn);
 
 
 	protected:

diff --git a/src/shogun/multiclass/MulticlassLibLinear.cpp b/src/shogun/multiclass/MulticlassLibLinear.cpp
@@ -102,7 +102,7 @@ bool CMulticlassLibLinear::train_machine(CFeatures* data)
 	int32_t num_classes = ((CMulticlassLabels*) m_labels)->get_num_classes();
 	int32_t bias_n = m_use_bias ? 1 : 0;
 
-	problem mc_problem;
+	liblinear_problem mc_problem;
 	mc_problem.l = num_vectors;
 	mc_problem.n = m_features->get_dim_feature_space() + bias_n;
 	mc_problem.y = SG_MALLOC(float64_t, mc_problem.l);

diff --git a/src/shogun/optimization/liblinear/shogun_liblinear.cpp b/src/shogun/optimization/liblinear/shogun_liblinear.cpp
@@ -46,7 +46,7 @@
 
 using namespace shogun;
 
-l2r_lr_fun::l2r_lr_fun(const problem *p, float64_t* Cs)
+l2r_lr_fun::l2r_lr_fun(const liblinear_problem *p, float64_t* Cs)
 {
 	int l=p->l;
 
@@ -161,7 +161,7 @@ void l2r_lr_fun::XTv(double *v, double *res_XTv)
 	}
 }
 
-l2r_l2_svc_fun::l2r_l2_svc_fun(const problem *p, double* Cs)
+l2r_l2_svc_fun::l2r_l2_svc_fun(const liblinear_problem *p, double* Cs)
 {
 	int l=p->l;
 
@@ -299,7 +299,7 @@ void l2r_l2_svc_fun::subXTv(double *v, double *XTv)
 	}
 }
 
-l2r_l2_svr_fun::l2r_l2_svr_fun(const problem *prob, double *Cs, double p):
+l2r_l2_svr_fun::l2r_l2_svr_fun(const liblinear_problem *prob, double *Cs, double p):
 	l2r_l2_svc_fun(prob, Cs)
 {
 	m_p = p;
@@ -387,7 +387,7 @@ void l2r_l2_svr_fun::grad(double *w, double *g)
 #define GETI(i) (prob->y[i])
 // To support weights for instances, use GETI(i) (i)
 
-Solver_MCSVM_CS::Solver_MCSVM_CS(const problem *p, int n_class,
+Solver_MCSVM_CS::Solver_MCSVM_CS(const liblinear_problem *p, int n_class,
                                  double *weighted_C, double *w0_reg,
                                  double epsilon, int max_it, double max_time,
                                  mcsvm_state* given_state)
@@ -695,14 +695,14 @@ void Solver_MCSVM_CS::solve()
 // Interface functions
 //
 
-void destroy_model(struct model *model_)
+void destroy_model(struct liblinear_model *model_)
 {
 	SG_FREE(model_->w);
 	SG_FREE(model_->label);
 	SG_FREE(model_);
 }
 
-void destroy_param(parameter* param)
+void destroy_param(liblinear_parameter* param)
 {
 	SG_FREE(param->weight_label);
 	SG_FREE(param->weight);

diff --git a/src/shogun/optimization/liblinear/shogun_liblinear.h b/src/shogun/optimization/liblinear/shogun_liblinear.h
@@ -49,7 +49,7 @@ extern "C" {
 #endif
 
 /** problem */
-struct problem
+struct liblinear_problem
 {
 	/** l */
 	int32_t l;
@@ -64,7 +64,7 @@ struct problem
 };
 
 /** parameter */
-struct parameter
+struct liblinear_parameter
 {
 	/** solver type */
 	int32_t solver_type;
@@ -83,10 +83,10 @@ struct parameter
 };
 
 /** model */
-struct model
+struct liblinear_model
 {
 	/** parameter */
-	struct parameter param;
+	struct liblinear_parameter param;
 	/** number of classes */
 	int32_t nr_class;
 	/** number of features */
@@ -99,8 +99,8 @@ struct model
 	float64_t bias;
 };
 
-void destroy_model(struct model *model_);
-void destroy_param(struct parameter *param);
+void destroy_model(struct liblinear_model *model_);
+void destroy_param(struct liblinear_parameter *param);
 #ifdef __cplusplus
 }
 #endif
@@ -115,7 +115,7 @@ class l2loss_svm_fun : public function
 	 * @param Cp Cp
 	 * @param Cn Cn
 	 */
-	l2loss_svm_fun(const problem *prob, float64_t Cp, float64_t Cn);
+	l2loss_svm_fun(const liblinear_problem *prob, float64_t Cp, float64_t Cn);
 	~l2loss_svm_fun();
 
 	/** fun
@@ -155,7 +155,7 @@ class l2loss_svm_fun : public function
 	float64_t *D;
 	int32_t *I;
 	int32_t sizeI;
-	const problem *prob;
+	const liblinear_problem *prob;
 };
 
 /** class l2r_lr_fun */
@@ -168,7 +168,7 @@ class l2r_lr_fun : public function
 	 * @param Cp Cp
 	 * @param Cn Cn
 	 */
-	l2r_lr_fun(const problem *prob, float64_t* C);
+	l2r_lr_fun(const liblinear_problem *prob, float64_t* C);
 	~l2r_lr_fun();
 
 	/** fun
@@ -201,13 +201,13 @@ class l2r_lr_fun : public function
 	float64_t *C;
 	float64_t *z;
 	float64_t *D;
-	const problem *m_prob;
+	const liblinear_problem *m_prob;
 };
 
 class l2r_l2_svc_fun : public function
 {
 public:
-	l2r_l2_svc_fun(const problem *prob, float64_t* Cs);
+	l2r_l2_svc_fun(const liblinear_problem *prob, float64_t* Cs);
 	~l2r_l2_svc_fun();
 
 	double fun(double *w);
@@ -226,13 +226,13 @@ class l2r_l2_svc_fun : public function
 	double *D;
 	int *I;
 	int sizeI;
-	const problem *m_prob;
+	const liblinear_problem *m_prob;
 };
 
 class l2r_l2_svr_fun: public l2r_l2_svc_fun
 {
 public:
-	l2r_l2_svr_fun(const problem *prob, double *Cs, double p);
+	l2r_l2_svr_fun(const liblinear_problem *prob, double *Cs, double p);
 
 	double fun(double *w);
 	void grad(double *w, double *g);
@@ -296,7 +296,7 @@ struct mcsvm_state
 class Solver_MCSVM_CS
 {
 	public:
-		Solver_MCSVM_CS(const problem *prob, int nr_class, double *C,
+		Solver_MCSVM_CS(const liblinear_problem *prob, int nr_class, double *C,
 		                double *w0, double eps, int max_iter,
 		                double train_time, mcsvm_state* given_state);
 		~Solver_MCSVM_CS();
@@ -311,7 +311,7 @@ class Solver_MCSVM_CS
 		double eps;
 		double max_train_time;
 		double* w0;
-		const problem *prob;
+		const liblinear_problem *prob;
 		mcsvm_state* state;
 };
 

diff --git a/src/shogun/regression/svr/LibLinearRegression.cpp b/src/shogun/regression/svr/LibLinearRegression.cpp
@@ -81,7 +81,7 @@ bool CLibLinearRegression::train_machine(CFeatures* data)
 	else
 		w=SGVector<float64_t>(num_feat);
 
-	problem prob;
+	liblinear_problem prob;
 	if (m_use_bias)
 	{
 		prob.n=w.vlen+1;
@@ -154,7 +154,7 @@ bool CLibLinearRegression::train_machine(CFeatures* data)
 #define GETI(i) (0)
 // To support weights for instances, use GETI(i) (i)
 
-void CLibLinearRegression::solve_l2r_l1l2_svr(const problem *prob)
+void CLibLinearRegression::solve_l2r_l1l2_svr(const liblinear_problem *prob)
 {
 	int l = prob->l;
 	double C = m_C;

diff --git a/src/shogun/regression/svr/LibLinearRegression.h b/src/shogun/regression/svr/LibLinearRegression.h
@@ -143,7 +143,7 @@ class CLibLinearRegression : public CLinearMachine
 
 private:
 		/** solve svr with l1 or l2 loss */
-		void solve_l2r_l1l2_svr(const problem *prob);
+		void solve_l2r_l1l2_svr(const liblinear_problem *prob);
 
 		/** init defaults */
 		void init_defaults();

diff --git a/src/shogun/transfer/multitask/LibLinearMTL.cpp b/src/shogun/transfer/multitask/LibLinearMTL.cpp
@@ -103,7 +103,7 @@ bool CLibLinearMTL::train_machine(CFeatures* data)
 	else
 		training_w=SG_MALLOC(float64_t, num_feat+0);
 
-	problem prob;
+	liblinear_problem prob;
 	if (use_bias)
 	{
 		prob.n=num_feat+1;
@@ -181,7 +181,7 @@ bool CLibLinearMTL::train_machine(CFeatures* data)
 // To support weights for instances, use GETI(i) (i)
 
 
-void CLibLinearMTL::solve_l2r_l1l2_svc(const problem *prob, double eps, double Cp, double Cn)
+void CLibLinearMTL::solve_l2r_l1l2_svc(const liblinear_problem *prob, double eps, double Cp, double Cn)
 {
 
 

diff --git a/src/shogun/transfer/multitask/LibLinearMTL.h b/src/shogun/transfer/multitask/LibLinearMTL.h
@@ -304,7 +304,7 @@ class CLibLinearMTL : public CLinearMachine
         void init();
 
 		void solve_l2r_l1l2_svc(
-			const problem *prob, double eps, double Cp, double Cn);
+			const liblinear_problem *prob, double eps, double Cp, double Cn);
 
 
 	protected: