Merged apply() and apply(CFeatures* data) into apply(CFeatures* data=…

…NULL)
shogun-toolbox · May 21, 2012 · ad7e86b · ad7e86b
1 parent ecc853c
commit ad7e86b
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Showing 28 changed files with 155 additions and 311 deletions.
diff --git a/src/shogun/classifier/GaussianNaiveBayes.cpp b/src/shogun/classifier/GaussianNaiveBayes.cpp
@@ -173,8 +173,13 @@ bool CGaussianNaiveBayes::train(CFeatures* data)
 	return true;
 }
 
-CLabels* CGaussianNaiveBayes::apply()
+CLabels* CGaussianNaiveBayes::apply(CFeatures* data)
 {
+	if (data)
+		set_features(data);
+
+	ASSERT(m_features);
+
 	// init number of vectors
 	int32_t num_vectors = m_features->get_num_vectors();
 
@@ -192,19 +197,6 @@ CLabels* CGaussianNaiveBayes::apply()
 	return result;
 };
 
-CLabels* CGaussianNaiveBayes::apply(CFeatures* data)
-{
-	// check data correctness
-	if (!data)
-		SG_ERROR("No features specified\n");
-
-	// set features to classify
-	set_features(data);
-
-	// classify using features
-	return apply();
-};
-
 float64_t CGaussianNaiveBayes::apply(int32_t idx)
 {
 	// get [idx] feature vector

diff --git a/src/shogun/classifier/GaussianNaiveBayes.h b/src/shogun/classifier/GaussianNaiveBayes.h
@@ -66,18 +66,13 @@ class CGaussianNaiveBayes : public CMachine
 	 * @param data train examples
 	 * @return true if successful
 	 */
-	virtual bool train(CFeatures* data = NULL);
-
-	/** classify all examples
-	 * @return labels
-	 */
-	virtual CLabels* apply();
+	virtual bool train(CFeatures* data=NULL);
 
 	/** classify specified examples
 	 * @param data examples to be classified
 	 * @return labels corresponding to data
 	 */
-	virtual CLabels* apply(CFeatures* data);
+	virtual CLabels* apply(CFeatures* data=NULL);
 
 	/** classifiy specified example
 	 * @param idx example index

diff --git a/src/shogun/classifier/PluginEstimate.cpp b/src/shogun/classifier/PluginEstimate.cpp
@@ -96,8 +96,19 @@ bool CPluginEstimate::train_machine(CFeatures* data)
 	return true;
 }
 
-CLabels* CPluginEstimate::apply()
+CLabels* CPluginEstimate::apply(CFeatures* data)
 {
+	if (data)
+	{
+		if (data->get_feature_class() != C_STRING ||
+			data->get_feature_type() != F_WORD)
+		{
+			SG_ERROR("Features not of class string type word\n");
+		}
+
+		set_features((CStringFeatures<uint16_t>*) data);
+	}
+
 	ASSERT(features);
 	CRealLabels* result=new CRealLabels(features->get_num_vectors());
 	ASSERT(result->get_num_labels()==features->get_num_vectors());
@@ -108,21 +119,6 @@ CLabels* CPluginEstimate::apply()
 	return result;
 }
 
-CLabels* CPluginEstimate::apply(CFeatures* data)
-{
-	if (!data)
-		SG_ERROR("No features specified\n");
-
-	if (data->get_feature_class() != C_STRING ||
-			data->get_feature_type() != F_WORD)
-	{
-		SG_ERROR("Features not of class string type word\n");
-	}
-
-	set_features((CStringFeatures<uint16_t>*) data);
-	return apply();
-}
-
 float64_t CPluginEstimate::apply(int32_t vec_idx)
 {
 	ASSERT(features);

diff --git a/src/shogun/classifier/PluginEstimate.h b/src/shogun/classifier/PluginEstimate.h
@@ -41,18 +41,12 @@ class CPluginEstimate: public CMachine
 		CPluginEstimate(float64_t pos_pseudo=1e-10, float64_t neg_pseudo=1e-10);
 		virtual ~CPluginEstimate();
 
-		/** classify objects using the currently set features
-		 *
-		 * @return classified labels
-		 */
-		CLabels* apply();
-
 		/** classify objects
 		 *
 		 * @param data (test)data to be classified
 		 * @return classified labels
 		 */
-		virtual CLabels* apply(CFeatures* data);
+		virtual CLabels* apply(CFeatures* data=NULL);
 
 		/** set features
 		 *

diff --git a/src/shogun/classifier/QDA.cpp b/src/shogun/classifier/QDA.cpp
@@ -68,8 +68,16 @@ void CQDA::cleanup()
 	m_num_classes = 0;
 }
 
-CLabels* CQDA::apply()
+CLabels* CQDA::apply(CFeatures* data)
 {
+	if (data)
+	{
+		if (!data->has_property(FP_DOT))
+			SG_ERROR("Specified features are not of type CDotFeatures\n");
+
+		set_features((CDotFeatures*) data);
+	}
+
 	if ( !m_features )
 		return NULL;
 
@@ -135,17 +143,6 @@ CLabels* CQDA::apply()
 	return out;
 }
 
-CLabels* CQDA::apply(CFeatures* data)
-{
-	if ( !data )
-		SG_ERROR("No features specified\n");
-	if ( !data->has_property(FP_DOT) )
-		SG_ERROR("Specified features are not of type CDotFeatures\n");
-
-	set_features((CDotFeatures*) data);
-	return apply();
-}
-
 bool CQDA::train_machine(CFeatures* data)
 {
 	if ( !m_labels )

diff --git a/src/shogun/classifier/QDA.h b/src/shogun/classifier/QDA.h
@@ -54,18 +54,12 @@ class CQDA : public CMachine
 
 		virtual ~CQDA();
 
-		/** apply QDA to all examples
-		 *
-		 * @return resulting labels
-		 */
-		virtual CLabels* apply();
-
 		/** apply QDA to data
 		 *
 		 * @param data (test) data to be classified
 		 * @return labels result of classification
 		 */
-		virtual CLabels* apply(CFeatures* data);
+		virtual CLabels* apply(CFeatures* data=NULL);
 
 		/** set store_covs
 		 *

diff --git a/src/shogun/classifier/svm/WDSVMOcas.cpp b/src/shogun/classifier/svm/WDSVMOcas.cpp
@@ -98,8 +98,20 @@ CWDSVMOcas::~CWDSVMOcas()
 {
 }
 
-CLabels* CWDSVMOcas::apply()
+CLabels* CWDSVMOcas::apply(CFeatures* data)
 {
+	if (data)
+	{
+		if (data->get_feature_class() != C_STRING ||
+				data->get_feature_type() != F_BYTE)
+		{
+			SG_ERROR("Features not of class string type byte\n");
+		}
+
+		set_features((CStringFeatures<uint8_t>*) data);
+	}
+	ASSERT(features);
+
 	set_wd_weights();
 	set_normalization_const();
 
@@ -120,21 +132,6 @@ CLabels* CWDSVMOcas::apply()
 	return NULL;
 }
 
-CLabels* CWDSVMOcas::apply(CFeatures* data)
-{
-	if (!data)
-		SG_ERROR("No features specified\n");
-
-	if (data->get_feature_class() != C_STRING ||
-			data->get_feature_type() != F_BYTE)
-	{
-		SG_ERROR("Features not of class string type byte\n");
-	}
-
-	set_features((CStringFeatures<uint8_t>*) data);
-	return apply();
-}
-
 int32_t CWDSVMOcas::set_wd_weights()
 {
 	ASSERT(degree>0 && degree<=8);

diff --git a/src/shogun/classifier/svm/WDSVMOcas.h b/src/shogun/classifier/svm/WDSVMOcas.h
@@ -148,18 +148,12 @@ class CWDSVMOcas : public CMachine
 		 */
 		inline int32_t get_degree() { return degree; }
 
-		/** classify all examples
-		 *
-		 * @return resulting labels
-		 */
-		CLabels* apply();
-
 		/** classify objects
 		 *
 		 * @param data (test)data to be classified
 		 * @return classified labels
 		 */
-		virtual CLabels* apply(CFeatures* data);
+		virtual CLabels* apply(CFeatures* data=NULL);
 
 		/** classify one example
 		 *

diff --git a/src/shogun/clustering/Hierarchical.cpp b/src/shogun/clustering/Hierarchical.cpp
@@ -197,11 +197,6 @@ void CHierarchical::store_model_features()
 }
 
 CLabels* CHierarchical::apply(CFeatures* data)
-{
-	return apply();
-}
-
-CLabels* CHierarchical::apply()
 {
 	SG_ERROR("apply(...) not implemented for %s!\n", get_name());
 	return NULL;

diff --git a/src/shogun/clustering/Hierarchical.h b/src/shogun/clustering/Hierarchical.h
@@ -119,10 +119,7 @@ class CHierarchical : public CDistanceMachine
 		virtual void store_model_features();
 
 		/** NOT IMPLEMENTED */
-		virtual CLabels* apply();
-
-		/** NOT IMPLEMENTED */
-		virtual CLabels* apply(CFeatures* data);
+		virtual CLabels* apply(CFeatures* data=NULL);
 
 		/** NOT IMPLEMENTED */
 		virtual float64_t apply(int32_t num);

diff --git a/src/shogun/lib/external/shogun_liblinear.cpp b/src/shogun/lib/external/shogun_liblinear.cpp
@@ -642,24 +642,6 @@ void Solver_MCSVM_CS::solve()
 	if (iter >= max_iter)
 		SG_SINFO("Warning: reaching max number of iterations\n");
 
-	// calculate objective value
-	/*
-	double v = 0;
-	int nSV = 0;
-	for(i=0;i<w_size*nr_class;i++)
-		v += w[i]*w[i];
-	v = 0.5*v;
-	for(i=0;i<l*nr_class;i++)
-	{
-		v += alpha[i];
-		if(fabs(alpha[i]) > 0)
-			nSV++;
-	}
-	for(i=0;i<l;i++)
-		v -= alpha[i*nr_class+prob->y[i]];
-	SG_SINFO("Objective value = %f\n",v);
-	SG_SINFO("nSV = %d\n",nSV);
-	*/
 	SG_FREE(tx);
 }
 

diff --git a/src/shogun/machine/DistanceMachine.cpp b/src/shogun/machine/DistanceMachine.cpp
@@ -206,28 +206,28 @@ void* CDistanceMachine::run_distance_thread_rhs(void* p)
 
 CLabels* CDistanceMachine::apply(CFeatures* data)
 {
-	ASSERT(data);
-
-	/* set distance features to given ones and apply to all */
-	CFeatures* lhs=distance->get_lhs();
-	distance->init(lhs, data);
-	SG_UNREF(lhs);
-
-	/* build result labels and classify all elements of procedure */
-	CRealLabels* result=new CRealLabels(data->get_num_vectors());
-	for (index_t i=0; i<data->get_num_vectors(); ++i)
-		result->set_label(i, apply(i));
-
-	return result;
-}
-
-CLabels* CDistanceMachine::apply()
-{
-	/* call apply on complete right hand side */
-	CFeatures* all=distance->get_rhs();
-	CLabels* result=apply(all);
-	SG_UNREF(all);
-	return result;
+	if (data)
+	{
+		/* set distance features to given ones and apply to all */
+		CFeatures* lhs=distance->get_lhs();
+		distance->init(lhs, data);
+		SG_UNREF(lhs);
+
+		/* build result labels and classify all elements of procedure */
+		CRealLabels* result=new CRealLabels(data->get_num_vectors());
+		for (index_t i=0; i<data->get_num_vectors(); ++i)
+			result->set_label(i, apply(i));
+		return result;
+	}
+	else
+	{
+		/* call apply on complete right hand side */
+		CFeatures* all=distance->get_rhs();
+		CLabels* result=apply(all);
+		SG_UNREF(all);
+		return result;
+	}
+	return NULL;
 }
 
 float64_t CDistanceMachine::apply(int32_t num)

diff --git a/src/shogun/machine/DistanceMachine.h b/src/shogun/machine/DistanceMachine.h
@@ -84,22 +84,14 @@ class CDistanceMachine : public CMachine
 		 */
 		virtual const char* get_name() const { return "DistanceMachine"; }
 
-		/** Classify all rhs features using the built clusters.
-		 * Cluster index with smallest distance to to be classified element is
-		 * returned
-		 *
-		 * @return classified labels
-		 */
-		virtual CLabels* apply();
-
 		/** Classify all provided features.
 		 * Cluster index with smallest distance to to be classified element is
 		 * returned
 		 *
 		 * @param data (test)data to be classified
 		 * @return classified labels
 		 */
-		virtual CLabels* apply(CFeatures* data);
+		virtual CLabels* apply(CFeatures* data=NULL);
 
 		/** Apply machine to one example.
 		 * Cluster index with smallest distance to to be classified element is