Merge branch 'master' of git://github.com/shogun-toolbox/shogun into …

…refactoring
shogun-toolbox · Apr 14, 2012 · 9a4214c · 9a4214c
2 parents da846bd + 1f77383
commit 9a4214c
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Showing 7 changed files with 42 additions and 18 deletions.
diff --git a/src/configure b/src/configure
@@ -3833,7 +3833,7 @@ test_modular()
 		echocheck "SWIG"
 		if ${SWIG} -version >/dev/null 2>&1
 		then
-			_swig_version=`swig -version 2>/dev/null | grep Version | cut -f 3 -d ' '`
+			_swig_version=`${SWIG} -version 2>/dev/null | grep Version | cut -f 3 -d ' '`
 			if assert_version swig $_swig $_swig_version 2.0.4; then
 				echores "$_swig_version"
 				_swig=yes

diff --git a/src/interfaces/modular/Features.i b/src/interfaces/modular/Features.i
@@ -47,6 +47,7 @@
 %rename(LBPPyrDotFeatures) CLBPPyrDotFeatures;
 %rename(ExplicitSpecFeatures) CExplicitSpecFeatures;
 %rename(ImplicitWeightedSpecFeatures) CImplicitWeightedSpecFeatures;
+%rename(Subset) CSubset;
 
 /* Include Class Headers to make them visible from within the target language */
 %include <shogun/features/FeatureTypes.h>
@@ -372,3 +373,4 @@ namespace shogun
 %include <shogun/features/LBPPyrDotFeatures.h>
 %include <shogun/features/ExplicitSpecFeatures.h>
 %include <shogun/features/ImplicitWeightedSpecFeatures.h>
+%include <shogun/features/Subset.h>
diff --git a/src/interfaces/modular/Features_includes.i b/src/interfaces/modular/Features_includes.i
@@ -32,4 +32,5 @@
 #include <shogun/features/LBPPyrDotFeatures.h>
 #include <shogun/features/ExplicitSpecFeatures.h>
 #include <shogun/features/ImplicitWeightedSpecFeatures.h>
+#include <shogun/features/Subset.h>
 %}
diff --git a/src/shogun/classifier/GaussianNaiveBayes.cpp b/src/shogun/classifier/GaussianNaiveBayes.cpp
@@ -126,6 +126,13 @@ bool CGaussianNaiveBayes::train(CFeatures* data)
 	m_label_prob.zero();
 	m_rates.zero();
 
+	// number of iterations in all cycles
+	int32_t max_progress = 2 * train_labels.vlen + 2 * m_num_classes;
+
+	// current progress
+	int32_t progress = 0;	
+	SG_PROGRESS(progress, 0, max_progress);
+
 	// get sum of features among labels
 	for (i=0; i<train_labels.vlen; i++)
 	{
@@ -135,13 +142,19 @@ bool CGaussianNaiveBayes::train(CFeatures* data)
 		fea.free_vector();
 
 		m_label_prob.vector[train_labels.vector[i]]+=1.0;
+
+		progress++;
+		SG_PROGRESS(progress, 0, max_progress);
 	}
 
 	// get means of features of labels
 	for (i=0; i<m_num_classes; i++)
 	{
 		for (j=0; j<m_dim; j++)
 			m_means(j, i) /= m_label_prob.vector[i];
+
+		progress++;
+		SG_PROGRESS(progress, 0, max_progress);
 	}
 
 	// compute squared residuals with means available
@@ -154,20 +167,24 @@ bool CGaussianNaiveBayes::train(CFeatures* data)
 				CMath::sq(fea[j]-m_means(j, train_labels.vector[i]));
 		}
 		fea.free_vector();
-	}
+
+		progress++;
+		SG_PROGRESS(progress, 0, max_progress);
+	}	
 
 	// get variance of features of labels
 	for (i=0; i<m_num_classes; i++)
 	{
 		for (j=0; j<m_dim; j++)
 			m_variances(j, i) /= m_label_prob.vector[i] > 1 ? m_label_prob.vector[i]-1 : 1;
-	}
-
-	// get a priori probabilities of labels
-	for (i=0; i<m_num_classes; i++)
-	{
+
+		// get a priori probabilities of labels
 		m_label_prob.vector[i]/= m_num_classes;
+
+		progress++;
+		SG_PROGRESS(progress, 0, max_progress);
 	}
+	SG_DONE();
 
 	train_labels.free_vector();
 
@@ -177,15 +194,19 @@ bool CGaussianNaiveBayes::train(CFeatures* data)
 CLabels* CGaussianNaiveBayes::apply()
 {
 	// init number of vectors
-	int32_t n = m_features->get_num_vectors();
+	int32_t num_vectors = m_features->get_num_vectors();
 
 	// init result labels
-	CLabels* result = new CLabels(n);
+	CLabels* result = new CLabels(num_vectors);
 
 	// classify each example of data
-	for (int i=0; i<n; i++)
+	SG_PROGRESS(0, 0, num_vectors);
+	for (int i = 0; i < num_vectors; i++)
+	{
 		result->set_label(i,apply(i));
-
+		SG_PROGRESS(i + 1, 0, num_vectors);
+	}
+	SG_DONE();
 	return result;
 };
 

diff --git a/src/shogun/preprocessor/PNorm.cpp b/src/shogun/preprocessor/PNorm.cpp
@@ -117,7 +117,7 @@ void CPNorm::register_param ()
 
 inline float64_t CPNorm::get_pnorm (float64_t* vec, int32_t vec_len) const
 {
-	float64_t norm;
+	float64_t norm = 0.0;
 	if (m_p == 1.0)
 	{
 		for (int i = 0; i < vec_len; ++i)

diff --git a/src/shogun/preprocessor/PNorm.h b/src/shogun/preprocessor/PNorm.h
@@ -34,6 +34,9 @@ class CPNorm : public CSimplePreprocessor<float64_t>
 		/** default PNorm Constructor */
 		CPNorm ();
 
+    /** constructor
+     * @param p the norm to calculate. NOTE: has to be greater or equal than 1.0
+     */
 		CPNorm (double p);
 
 		/** destructor */
@@ -65,12 +68,12 @@ class CPNorm : public CSimplePreprocessor<float64_t>
 
 		/**
 		 * Set norm
-		 * @param p norm value
+		 * @param pnorm norm value
 		 */
 		void set_pnorm (double pnorm);
 
 		/**
-		 * Get norm
+		 * Get norm value
 		 * @return norm
 		 */
 		double get_pnorm () const;

diff --git a/src/shogun/regression/GaussianProcessRegression.cpp b/src/shogun/regression/GaussianProcessRegression.cpp
@@ -218,14 +218,11 @@ SGMatrix<float64_t> CGaussianProcessRegression::getCovarianceMatrix(CFeatures* d
 	//Indices used to solve Lv=K(X_test, X_train) for v
 	SGVector< int32_t > ipiv(CMath::min(m_L.num_rows, m_L.num_cols));
 
-	int info;
-
-
 	memcpy(temp1.matrix, kernel_test_matrix.matrix, 
 		kernel_test_matrix.num_cols*kernel_test_matrix.num_rows*sizeof(float64_t));
 
 	//Get indices used to solve Lv=K(X_test, X_train) for v
-	dgetrf_(&m_L.num_rows, &m_L.num_cols, m_L.matrix, &m_L.num_cols, ipiv.vector, &info);
+	clapack_dgetrf(CblasColMajor, m_L.num_rows, m_L.num_cols, m_L.matrix, m_L.num_cols, ipiv.vector);
 
 	//Solve Lv=K(X_test, X_train) for v
 	clapack_dgetrs(CblasColMajor, CblasNoTrans,