[mlpack-git] master: Fixes indentation & style (1ff84ed)

[gitdub at mlpack.org]

Repository : https://github.com/mlpack/mlpack
On branch  : master
Link       : https://github.com/mlpack/mlpack/compare/4185aa07bbdef80ccdc78a3a3e479499058933db...931ec74894dd2fe0218d0d7dd77fc0ad9be0954d

>---------------------------------------------------------------

commit 1ff84ed670d5814943e78e5d3331ea75bb0f6a1b
Author: Yannis Mentekidis <mentekid at gmail.com>
Date:   Sun Aug 7 10:54:22 2016 +0100

    Fixes indentation & style


>---------------------------------------------------------------

1ff84ed670d5814943e78e5d3331ea75bb0f6a1b
 src/mlpack/core/dists/gamma_distribution.cpp | 17 ++++++++---------
 src/mlpack/core/dists/gamma_distribution.hpp |  9 +++++----
 2 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/src/mlpack/core/dists/gamma_distribution.cpp b/src/mlpack/core/dists/gamma_distribution.cpp
index 664aa36..85a0933 100644
--- a/src/mlpack/core/dists/gamma_distribution.cpp
+++ b/src/mlpack/core/dists/gamma_distribution.cpp
@@ -41,7 +41,6 @@ inline bool GammaDistribution::Converged(const double aOld,
   return (std::abs(aNew - aOld) / aNew) < tol;
 }
 
-
 // Fits an alpha and beta parameter to each dimension of the data.
 void GammaDistribution::Train(const arma::mat& rdata, const double tol)
 {
@@ -156,10 +155,10 @@ void GammaDistribution::Probability(const arma::mat& observations,
     for (size_t d = 0; d < observations.n_rows; ++d)
     {
       // Compute probability using Multiplication Law.
-      probabilities(i) *= 
-        std::pow(observations(d, i), alpha(d) - 1) *
-        std::exp(-observations(d, i) / beta(d)) /
-        denominators(d);
+      double factor = std::exp(-observations(d, i) / beta(d));
+      double numerator = std::pow(observations(d, i), alpha(d) - 1);
+      
+      probabilities(i) *= factor * numerator / denominators(d);
     }
   }
 }
@@ -194,10 +193,10 @@ void GammaDistribution::LogProbability(const arma::mat& observations,
     {
       // Compute probability using Multiplication Law and Logarithm addition
       // property.
-      LogProbabilities(i) += std::log( 
-        std::pow(observations(d, i), alpha(d) - 1) 
-        * std::exp(-observations(d, i) / beta(d)) 
-        / denominators(d));
+      double factor = std::exp(-observations(d, i) / beta(d));
+      double numerator = std::pow(observations(d, i), alpha(d) - 1);
+
+      LogProbabilities(i) += std::log( numerator * factor / denominators(d));
     }
   }
 }
diff --git a/src/mlpack/core/dists/gamma_distribution.hpp b/src/mlpack/core/dists/gamma_distribution.hpp
index e10d3e8..55ed55c 100644
--- a/src/mlpack/core/dists/gamma_distribution.hpp
+++ b/src/mlpack/core/dists/gamma_distribution.hpp
@@ -86,7 +86,8 @@ class GammaDistribution
      */
     void Train(const arma::mat& rdata, const double tol = 1e-8);
     
-    /** Fits an alpha and beta parameter according to observation probabilities.
+    /** 
+     * Fits an alpha and beta parameter according to observation probabilities.
      * 
      * @param observations The reference data, one observation per column
      * @param probabilities The probability of each observation. One value per
@@ -96,8 +97,8 @@ class GammaDistribution
      *    smaller than tol.
      */
     void Train(const arma::mat& observations, 
-                                  const arma::vec& probabilities,
-                                  const double tol = 1e-8);
+               const arma::vec& probabilities,
+               const double tol = 1e-8);
     
     /**
      * This function trains (fits distribution parameters) to a dataset with
@@ -160,7 +161,7 @@ class GammaDistribution
      *     observation.
      */
     void LogProbability(const arma::mat& observations, 
-                     arma::vec& LogProbabilities) const;
+                        arma::vec& LogProbabilities) const;
 
     /**
      * This function returns an observation of this distribution