[mlpack-svn] r17085 - mlpack/trunk/src/mlpack/methods/gmm

fastlab-svn at coffeetalk-1.cc.gatech.edu fastlab-svn at coffeetalk-1.cc.gatech.edu
Wed Aug 20 15:58:11 EDT 2014


Author: rcurtin
Date: Wed Aug 20 15:58:10 2014
New Revision: 17085

Log:
Remove trailing spaces thanks to vimrc, and fix comment correctness.


Modified:
   mlpack/trunk/src/mlpack/methods/gmm/gmm.hpp
   mlpack/trunk/src/mlpack/methods/gmm/gmm_impl.hpp

Modified: mlpack/trunk/src/mlpack/methods/gmm/gmm.hpp
==============================================================================
--- mlpack/trunk/src/mlpack/methods/gmm/gmm.hpp	(original)
+++ mlpack/trunk/src/mlpack/methods/gmm/gmm.hpp	Wed Aug 20 15:58:10 2014
@@ -77,14 +77,14 @@
   size_t gaussians;
   //! The dimensionality of the model.
   size_t dimensionality;
-  
+
   //! Vector of Gaussians
   std::vector<distribution::GaussianDistribution> dists;
-  
+
   //! Legacy member data, not used.
   std::vector<arma::vec> means;
   std::vector<arma::mat> covariances;
-  
+
   //! Vector of a priori weights for each Gaussian.
   arma::vec weights;
 
@@ -214,7 +214,7 @@
    * @param SaveRestoreUtility object to save to.
    */
   void Save(util::SaveRestoreUtility& sr) const;
-    
+
   //! Return the number of gaussians in the model.
   size_t Gaussians() const { return gaussians; }
   //! Modify the number of gaussians in the model.  Careful!  You will have to
@@ -231,14 +231,14 @@
    * Return a const reference to a component distribution.
    *
    * @param i index of component.
-   */  
+   */
   const distribution::GaussianDistribution& Component(size_t i) const {
       return dists[i]; }
   /**
    * Return a reference to a component distribution.
    *
    * @param i index of component.
-   */  
+   */
   distribution::GaussianDistribution& Component(size_t i) { return dists[i]; }
 
   //! Functions from earlier releases give errors
@@ -382,7 +382,7 @@
    * Returns a string representation of this object.
    */
   std::string ToString() const;
-  
+
   /**
    * Returns a string indicating the type.
    */

Modified: mlpack/trunk/src/mlpack/methods/gmm/gmm_impl.hpp
==============================================================================
--- mlpack/trunk/src/mlpack/methods/gmm/gmm_impl.hpp	(original)
+++ mlpack/trunk/src/mlpack/methods/gmm/gmm_impl.hpp	Wed Aug 20 15:58:10 2014
@@ -33,8 +33,7 @@
     localFitter(FittingType()),
     fitter(localFitter)
 {
-  // Set weights to 0.  Technically this model is still valid, but
-  // only barely.
+  // Set equal weights.  Technically this model is still valid, but only barely.
   weights.fill(1.0 / gaussians);
 }
 
@@ -58,12 +57,11 @@
     weights(gaussians),
     fitter(fitter)
 {
-  // Set weights to 0.  Technically this model is still valid, but
-  // only barely.
+  // Set equal weights.  Technically this model is still valid, but only barely.
   weights.fill(1.0 / gaussians);
 }
 
-  
+
 // Copy constructor.
 template<typename FittingType>
 template<typename OtherFittingType>
@@ -132,7 +130,7 @@
     Log::Warn << "GMM::Save(): error saving to '" << filename << "'.\n";
 }
 
-  
+
 // Save a GMM to a SaveRestoreUtility.
 template<typename FittingType>
 void GMM<FittingType>::Save(util::SaveRestoreUtility& sr) const
@@ -149,7 +147,7 @@
     std::stringstream o;
     o << i;
     std::string gaussianName = "gaussian" + o.str();
-    
+
     // Now save them.
     dists[i].Save(child);
     sr.AddChild(child, gaussianName);
@@ -163,7 +161,7 @@
     sr.LoadParameter(gaussians, "gaussians");
     sr.LoadParameter(dimensionality, "dimensionality");
     sr.LoadParameter(weights, "weights");
-    
+
     // We need to do a little error checking here.
     if (weights.n_elem != gaussians)
     {
@@ -171,9 +169,9 @@
       << " gaussians but weights vector only contains " << weights.n_elem
       << " elements!" << std::endl;
     }
-  
+
     dists.resize(gaussians);
-    
+
     for (size_t i = 0; i < gaussians; ++i)
     {
       std::stringstream o;
@@ -193,7 +191,7 @@
   double sum = 0;
   for (size_t i = 0; i < gaussians; i++)
     sum += weights[i] * dists[i].Probability(observation);
-  
+
   return sum;
 }
 



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