Merge pull request #588 from cwidmer/master

syntactic sugar for SGSparseVector
shogun-toolbox · Jun 19, 2012 · 43ea7ab · 43ea7ab
2 parents aa9ad6a + b89a58b
commit 43ea7ab
Show file tree

Hide file tree

Showing 5 changed files with 79 additions and 10 deletions.
diff --git a/src/interfaces/octave_modular/swig_typemaps.i b/src/interfaces/octave_modular/swig_typemaps.i
@@ -346,6 +346,7 @@ TYPEMAP_STRINGFEATURES_OUT(float64_t,     Matrix)
 		}
 		else
 			matrix[i].features=NULL;
+	    matrix[i].create_idx_map();
 	}
 	ASSERT(offset=nnz);
 	$1 = shogun::SGSparseMatrix<type>(matrix, num_feat, num_vec, true);

diff --git a/src/interfaces/python_modular/swig_typemaps.i b/src/interfaces/python_modular/swig_typemaps.i
@@ -625,6 +625,7 @@ static bool spmatrix_from_numpy(SGSparseMatrix<type>& sg_matrix, PyObject* obj,
             }
             sfm[i-1].num_feat_entries=num;
             sfm[i-1].features=features;
+            sfm[i-1].create_idx_map();
         }
     }
 

diff --git a/src/shogun/lib/SGSparseVector.h b/src/shogun/lib/SGSparseVector.h
@@ -5,6 +5,7 @@
  * (at your option) any later version.
  *
  * Written (W) 2012 Fernando José Iglesias García
+ * Written (W) 2012 Christian Widmer
  * Written (W) 2010,2012 Soeren Sonnenburg
  * Copyright (C) 2010 Berlin Institute of Technology
  * Copyright (C) 2012 Soeren Sonnenburg
@@ -15,10 +16,12 @@
 
 #include <shogun/lib/config.h>
 #include <shogun/lib/DataType.h>
+#include <map>
 
 namespace shogun
 {
 
+
 /** @brief template class SGSparseVectorEntry */
 template <class T> struct SGSparseVectorEntry
 {
@@ -40,7 +43,10 @@ template <class T> class SGSparseVector
 	SGSparseVector(SGSparseVectorEntry<T>* feats, index_t num_entries,
 			index_t index, bool free_v=false) :
 			num_feat_entries(num_entries), features(feats),
-			do_free(free_v) {}
+			do_free(free_v)
+	{
+		create_idx_map();
+	}
 
 	/** constructor to create new vector in memory */
 	SGSparseVector(index_t num_entries, index_t index, bool free_v=false) :
@@ -52,14 +58,18 @@ template <class T> class SGSparseVector
 	/** copy constructor */
 	SGSparseVector(const SGSparseVector& orig) :
 			num_feat_entries(orig.num_feat_entries),
-			features(orig.features), do_free(orig.do_free) {}
+			features(orig.features), do_free(orig.do_free)
+	{
+		create_idx_map();
+	}
 
 	/** free vector */
 	void free_vector()
 	{
 		if (do_free)
 			SG_FREE(features);
 
+		dense_to_sparse_idx.clear();
 		features=NULL;
 		do_free=false;
 		num_feat_entries=0;
@@ -72,6 +82,55 @@ template <class T> class SGSparseVector
 		free_vector();
 	}
 
+	/** create mapping from dense idx to sparse idx */
+	void create_idx_map()
+	{
+		dense_to_sparse_idx.clear();
+		for (int32_t i=0; i!=num_feat_entries; i++)
+		{
+			dense_to_sparse_idx[features[i].feat_index] = i;
+		}
+	}
+
+	/** operator overload for vector read only access
+	 *
+	 * @param index dimension to access
+	 *
+	 */
+	inline const T& operator[](index_t index) const
+	{
+		// lookup complexity is O(log n)
+		std::map<index_t, index_t>::const_iterator it = dense_to_sparse_idx.find(index);
+
+		if (it != dense_to_sparse_idx.end())
+		{
+			// use mapping for lookup
+			return features[it->second].entry;
+		} else {
+			return zero;
+		}
+	}
+
+
+	/** TODO: operator overload for vector r/w access
+	 *
+	 * @param index dimension to access
+	 *
+	inline T& operator[](index_t index)
+	{
+		return dense_to_sparse_idx[index];
+		// lookup complexity is O(log n)
+		typename std::map<index_t, T>::iterator it = dense_to_sparse_idx.find(index);
+
+		if (it != dense_to_sparse_idx.end())
+		{
+			return it->second;
+		} else {
+			return dense_to_sparse_idx.insert(index, 0);
+		}
+	}
+		*/
+
 public:
 	/** number of feature entries */
 	index_t num_feat_entries;
@@ -81,6 +140,20 @@ template <class T> class SGSparseVector
 
 	/** whether vector needs to be freed */
 	bool do_free;
+
+protected:	
+	/** store mapping of indices */
+	std::map<index_t, index_t> dense_to_sparse_idx;
+
+	/** zero element */
+	static const T zero;
+
 };
+
+// inititalize static member in template class
+template <typename T>
+const T SGSparseVector<T>::zero = T(0);
+
 }
+
 #endif // __SGSPARSEVECTOR_H__
diff --git a/src/shogun/transfer/multitask/LibLinearMTL.cpp b/src/shogun/transfer/multitask/LibLinearMTL.cpp
@@ -520,14 +520,11 @@ return obj
 			// look up task similarity
 			int32_t ti_j = task_indicator_lhs[j];
 
-            //TODO: same interface for sparse matrix
-            /*
-			float64_t ts = task_similarity_matrix.matrix[ti_i*num_tasks+ti_j];
+			const float64_t ts = task_similarity_matrix.sparse_matrix[ti_i][ti_j];
 
 			// compute objective
 			obj -= 0.5 * ts * alphas[i] * alphas[j] * ((CBinaryLabels*)m_labels)->get_label(i) * 
 				((CBinaryLabels*)m_labels)->get_label(j) * features->dot(i, features,j);
-            */
 		}
 	}
 

diff --git a/src/shogun/transfer/multitask/LibLinearMTL.h b/src/shogun/transfer/multitask/LibLinearMTL.h
@@ -192,14 +192,11 @@ class CLibLinearMTL : public CLinearMachine
                 float64_t* v_s = V.get_column_vector(s);
                 for (int32_t t=0; t<num_tasks; t++)
                 {
-                    //TODO: same interface for SparseMatrix!
-                    /*
-                    float64_t sim_ts = task_similarity_matrix.matrix[s*num_tasks+t];
+                    float64_t sim_ts = task_similarity_matrix.sparse_matrix[s][t];
                     for(int32_t i=0; i<w_size; i++)
                     {
                         W.matrix[t*w_size + i] += sim_ts * v_s[i];
                     }
-                    */
                 }
             }