[mlpack-svn] r12578 - mlpack/trunk/src/mlpack/methods/sparse_coding

[fastlab-svn at coffeetalk-1.cc.gatech.edu]

Author: rcurtin
Date: 2012-04-30 17:22:26 -0400 (Mon, 30 Apr 2012)
New Revision: 12578

Modified:
   mlpack/trunk/src/mlpack/methods/sparse_coding/sparse_coding.cpp
Log:
Don't use a pointer for LARS objects; no need to do memory allocation on our
own.  Adapt to new constructor calls, so there is no more need for
SetGramMatrix().


Modified: mlpack/trunk/src/mlpack/methods/sparse_coding/sparse_coding.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/sparse_coding/sparse_coding.cpp	2012-04-30 21:21:58 UTC (rev 12577)
+++ mlpack/trunk/src/mlpack/methods/sparse_coding/sparse_coding.cpp	2012-04-30 21:22:26 UTC (rev 12578)
@@ -122,20 +122,14 @@
       Log::Debug << "Optimization at point " << i << "." << endl;
 
     bool useCholesky = true;
-    LARS* lars;
-    if(lambda2 > 0)
-      lars = new LARS(useCholesky, lambda1, lambda2);
-    else
-      lars = new LARS(useCholesky, lambda1);
+    LARS lars(useCholesky, matGram, lambda1, lambda2);
 
-    lars->SetGramMem(matGram.memptr(), matGram.n_rows);
-    lars->DoLARS(dictionary, data.unsafe_col(i));
+    //lars->SetGramMem(matGram.memptr(), matGram.n_rows);
+    lars.DoLARS(dictionary, data.unsafe_col(i));
 
     vec beta;
-    lars->Solution(beta);
+    lars.Solution(beta);
     codes.col(i) = beta;
-
-    delete lars;
   }
 }