[mlpack-svn] r10740 - mlpack/trunk/src/mlpack/core/kernels

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

Author: rcurtin
Date: 2011-12-13 04:20:14 -0500 (Tue, 13 Dec 2011)
New Revision: 10740

Added:
   mlpack/trunk/src/mlpack/core/kernels/cosine_distance_impl.hpp
Removed:
   mlpack/trunk/src/mlpack/core/kernels/cosine_distance.cpp
Modified:
   mlpack/trunk/src/mlpack/core/kernels/CMakeLists.txt
   mlpack/trunk/src/mlpack/core/kernels/cosine_distance.hpp
   mlpack/trunk/src/mlpack/core/kernels/example_kernel.hpp
   mlpack/trunk/src/mlpack/core/kernels/gaussian_kernel.hpp
   mlpack/trunk/src/mlpack/core/kernels/linear_kernel.hpp
Log:
Abstractize vector type.


Modified: mlpack/trunk/src/mlpack/core/kernels/CMakeLists.txt
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/CMakeLists.txt	2011-12-13 08:59:08 UTC (rev 10739)
+++ mlpack/trunk/src/mlpack/core/kernels/CMakeLists.txt	2011-12-13 09:20:14 UTC (rev 10740)
@@ -6,7 +6,7 @@
   gaussian_kernel.hpp
   linear_kernel.hpp
   cosine_distance.hpp
-  cosine_distance.cpp
+  cosine_distance_impl.hpp
 )
 
 # add directory name to sources

Deleted: mlpack/trunk/src/mlpack/core/kernels/cosine_distance.cpp
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/cosine_distance.cpp	2011-12-13 08:59:08 UTC (rev 10739)
+++ mlpack/trunk/src/mlpack/core/kernels/cosine_distance.cpp	2011-12-13 09:20:14 UTC (rev 10740)
@@ -1,17 +0,0 @@
-/**
- * @file cosine_distance.cpp
- * @author Ryan Curtin
- *
- * This implements the cosine distance.
- */
-#include "cosine_distance.hpp"
-
-using namespace mlpack;
-using namespace mlpack::kernel;
-using namespace arma;
-
-double CosineDistance::Evaluate(const arma::vec& a, const arma::vec& b)
-{
-  // Since we are using the L2 inner product, this is easy.
-  return 1 - dot(a, b) / (norm(a, 2) * norm(b, 2));
-}

Modified: mlpack/trunk/src/mlpack/core/kernels/cosine_distance.hpp
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/cosine_distance.hpp	2011-12-13 08:59:08 UTC (rev 10739)
+++ mlpack/trunk/src/mlpack/core/kernels/cosine_distance.hpp	2011-12-13 09:20:14 UTC (rev 10740)
@@ -39,10 +39,14 @@
    * @param b Second vector.
    * @return d(a, b).
    */
-  static double Evaluate(const arma::vec& a, const arma::vec& b);
+  template<typename VecType>
+  static double Evaluate(const VecType& a, const VecType& b);
 };
 
 }; // namespace kernel
 }; // namespace mlpack
 
+// Include implementation.
+#include "cosine_distance_impl.hpp"
+
 #endif

Copied: mlpack/trunk/src/mlpack/core/kernels/cosine_distance_impl.hpp (from rev 10737, mlpack/trunk/src/mlpack/core/kernels/cosine_distance.cpp)
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/cosine_distance_impl.hpp	                        (rev 0)
+++ mlpack/trunk/src/mlpack/core/kernels/cosine_distance_impl.hpp	2011-12-13 09:20:14 UTC (rev 10740)
@@ -0,0 +1,25 @@
+/**
+ * @file cosine_distance_impl.hpp
+ * @author Ryan Curtin
+ *
+ * This implements the cosine distance.
+ */
+#ifndef __MLPACK_CORE_KERNELS_COSINE_DISTANCE_IMPL_HPP
+#define __MLPACK_CORE_KERNELS_COSINE_DISTANCE_IMPL_HPP
+
+#include "cosine_distance.hpp"
+
+namespace mlpack {
+namespace kernel {
+
+template<typename VecType>
+double CosineDistance::Evaluate(const VecType& a, const VecType& b)
+{
+  // Since we are using the L2 inner product, this is easy.
+  return 1 - dot(a, b) / (norm(a, 2) * norm(b, 2));
+}
+
+}; // namespace kernel
+}; // namespace mlpack
+
+#endif

Modified: mlpack/trunk/src/mlpack/core/kernels/example_kernel.hpp
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/example_kernel.hpp	2011-12-13 08:59:08 UTC (rev 10739)
+++ mlpack/trunk/src/mlpack/core/kernels/example_kernel.hpp	2011-12-13 09:20:14 UTC (rev 10740)
@@ -93,11 +93,13 @@
    * function static.  For a more complex example which cannot be declared
    * static, see the GaussianKernel, which stores an internal parameter.
    *
+   * @tparam VecType Type of vector (arma::vec, arma::spvec should be expected).
    * @param a First vector.
    * @param b Second vector.
    * @return K(a, b).
    */
-  static double Evaluate(const arma::vec& a, const arma::vec& b) { return 0; }
+  template<typename VecType>
+  static double Evaluate(const VecType& a, const VecType& b) { return 0; }
 };
 
 }; // namespace kernel

Modified: mlpack/trunk/src/mlpack/core/kernels/gaussian_kernel.hpp
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/gaussian_kernel.hpp	2011-12-13 08:59:08 UTC (rev 10739)
+++ mlpack/trunk/src/mlpack/core/kernels/gaussian_kernel.hpp	2011-12-13 09:20:14 UTC (rev 10740)
@@ -48,16 +48,17 @@
    * distance metric, not the Euclidean distance, but for now, the Euclidean
    * distance is used.
    *
+   * @tparam VecType Type of vector (likely arma::vec or arma::spvec).
    * @param a First vector.
    * @param b Second vector.
    * @return K(a, b) using the bandwidth (@f$\bandwidth at f$) specified in the
    *   constructor.
    */
-  double Evaluate(const arma::vec& a, const arma::vec& b) const
+  template<typename VecType>
+  double Evaluate(const VecType& a, const VecType& b) const
   {
-    // The precalculation of gamma saves us some little computation time.
-    arma::vec diff = b - a;
-    return exp(gamma * arma::dot(diff, diff));
+    // The precalculation of gamma saves us a little computation time.
+    return exp(gamma * metric::SquaredEuclideanDistance::Evaluate(a, b));
   }
   /**
    * Evaluation of the Gaussian kernel using a double precision argument
@@ -66,8 +67,9 @@
    * @return K(t) using the bandwidth (@f$\bandwidth at f$) specified in the
    *   constructor.
    */
-  double Evaluate(double t) const {
-    // The precalculation of gamma saves us some little computation time.
+  double Evaluate(double t) const
+  {
+    // The precalculation of gamma saves us a little computation time.
     return exp(gamma * t * t);
   }
 
@@ -75,18 +77,14 @@
   const double& Bandwidth() { return bandwidth; }
 
  private:
-  /**
-   * kernel bandwidth
-   * */
+  //! Kernel bandwidth.
   double bandwidth;
-  /**
-   * normalizing constant
-   */
+
+  //! Normalizing constant.
   double normalizer;
-  /**
-   * Precalculated constant depending on the bandwidth; @f$ \gamma =
-   * -\frac{1}{2 \bandwidth^2} @f$.
-   */
+
+  //! Precalculated constant depending on the bandwidth;
+  //! @f$ \gamma = -\frac{1}{2 \bandwidth^2} @f$.
   double gamma;
 };
 

Modified: mlpack/trunk/src/mlpack/core/kernels/linear_kernel.hpp
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/linear_kernel.hpp	2011-12-13 08:59:08 UTC (rev 10739)
+++ mlpack/trunk/src/mlpack/core/kernels/linear_kernel.hpp	2011-12-13 09:20:14 UTC (rev 10740)
@@ -37,11 +37,13 @@
    * Simple evaluation of the dot product.  This evaluation uses Armadillo's
    * dot() function.
    *
+   * @tparam VecType Type of vector (should be arma::vec or arma::spvec).
    * @param a First vector.
    * @param b Second vector.
    * @return K(a, b).
    */
-  static double Evaluate(const arma::vec& a, const arma::vec& b)
+  template<typename VecType>
+  static double Evaluate(const VecType& a, const VecType& b)
   {
     return arma::dot(a, b);
   }