[mlpack-svn] r10357 - mlpack/trunk/src/mlpack/core/kernels

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

Author: rcurtin
Date: 2011-11-23 02:39:04 -0500 (Wed, 23 Nov 2011)
New Revision: 10357

Modified:
   mlpack/trunk/src/mlpack/core/kernels/cosine_distance.cpp
   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:
Adapt style per #153.


Modified: mlpack/trunk/src/mlpack/core/kernels/cosine_distance.cpp
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/cosine_distance.cpp	2011-11-23 07:37:39 UTC (rev 10356)
+++ mlpack/trunk/src/mlpack/core/kernels/cosine_distance.cpp	2011-11-23 07:39:04 UTC (rev 10357)
@@ -10,7 +10,8 @@
 using namespace mlpack::kernel;
 using namespace arma;
 
-double CosineDistance::Evaluate(const arma::vec& a, const arma::vec& b) {
+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	2011-11-23 07:37:39 UTC (rev 10356)
+++ mlpack/trunk/src/mlpack/core/kernels/cosine_distance.hpp	2011-11-23 07:39:04 UTC (rev 10357)
@@ -1,5 +1,5 @@
-/***
- * @file cosine_distance.h
+/**
+ * @file cosine_distance.hpp
  * @author Ryan Curtin
  *
  * This implements the cosine distance (or cosine similarity) between two
@@ -23,7 +23,8 @@
  * and this class assumes the standard L2 inner product.  In the future it may
  * support more.
  */
-class CosineDistance {
+class CosineDistance
+{
  public:
   /**
    * Default constructor does nothing, but is required to satisfy the Kernel

Modified: mlpack/trunk/src/mlpack/core/kernels/example_kernel.hpp
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/example_kernel.hpp	2011-11-23 07:37:39 UTC (rev 10356)
+++ mlpack/trunk/src/mlpack/core/kernels/example_kernel.hpp	2011-11-23 07:39:04 UTC (rev 10357)
@@ -76,7 +76,8 @@
  * is necessary.
  * @endnote
  */
-class ExampleKernel {
+class ExampleKernel
+{
  public:
   /**
    * The default constructor, which takes no parameters.  Because our simple

Modified: mlpack/trunk/src/mlpack/core/kernels/gaussian_kernel.hpp
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/gaussian_kernel.hpp	2011-11-23 07:37:39 UTC (rev 10356)
+++ mlpack/trunk/src/mlpack/core/kernels/gaussian_kernel.hpp	2011-11-23 07:39:04 UTC (rev 10357)
@@ -49,7 +49,8 @@
    * @return K(a, b) using the bandwidth (@f$\sigma at f$) specified in the
    *   constructor.
    */
-  double Evaluate(const arma::vec& a, const arma::vec& b) const {
+  double Evaluate(const arma::vec& a, const arma::vec& b) const
+  {
     // The precalculation of gamma saves us some little computation time.
     arma::vec diff = b - a;
     return exp(gamma * arma::dot(diff, diff));

Modified: mlpack/trunk/src/mlpack/core/kernels/linear_kernel.hpp
===================================================================
--- mlpack/trunk/src/mlpack/core/kernels/linear_kernel.hpp	2011-11-23 07:37:39 UTC (rev 10356)
+++ mlpack/trunk/src/mlpack/core/kernels/linear_kernel.hpp	2011-11-23 07:39:04 UTC (rev 10357)
@@ -24,7 +24,8 @@
  *
  * This kernel has no parameters and therefore the evaluation can be static.
  */
-class LinearKernel {
+class LinearKernel
+{
  public:
   /**
    * This constructor does nothing; the linear kernel has no parameters to
@@ -40,7 +41,8 @@
    * @param b Second vector.
    * @return K(a, b).
    */
-  static double Evaluate(const arma::vec& a, const arma::vec& b) {
+  static double Evaluate(const arma::vec& a, const arma::vec& b)
+  {
     return arma::dot(a, b);
   }
 };