[mlpack] 07/207: Style fixes.

[Barak A. Pearlmutter]

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bap pushed a commit to branch master
in repository mlpack.

commit d9db269ac0f31a5ff2445e5e3befb9468bb69c03
Author: Ryan Curtin <ryan at ratml.org>
Date:   Tue Dec 27 11:21:28 2016 -0500

    Style fixes.
---
 src/mlpack/core/dists/gamma_distribution.cpp | 13 +++++----
 src/mlpack/tests/distribution_test.cpp       | 41 ++++++++++++++--------------
 2 files changed, 28 insertions(+), 26 deletions(-)

diff --git a/src/mlpack/core/dists/gamma_distribution.cpp b/src/mlpack/core/dists/gamma_distribution.cpp
index 0a46fed..900e4cb 100644
--- a/src/mlpack/core/dists/gamma_distribution.cpp
+++ b/src/mlpack/core/dists/gamma_distribution.cpp
@@ -69,7 +69,8 @@ void GammaDistribution::Train(const arma::mat& rdata, const double tol)
 }
 
 //Fits an alpha and beta parameter according to observation probabilities.
-void GammaDistribution::Train(const arma::mat& rdata, const arma::vec& probabilities,
+void GammaDistribution::Train(const arma::mat& rdata,
+                              const arma::vec& probabilities,
                               const double tol)
 {
   // If fittingSet is empty, nothing to do.
@@ -80,16 +81,16 @@ void GammaDistribution::Train(const arma::mat& rdata, const arma::vec& probabili
   arma::vec meanxVec(rdata.n_rows, arma::fill::zeros);
   arma::vec logMeanxVec(rdata.n_rows, arma::fill::zeros);
 
-  for(size_t i=0; i<rdata.n_cols; i++)
+  for (size_t i = 0; i < rdata.n_cols; i++)
   {
     meanLogxVec += probabilities(i) * arma::log(rdata.col(i));
     meanxVec += probabilities(i) * rdata.col(i);
   }
 
-  double tot_probabilty = arma::accu(probabilities);
+  double totProbability = arma::accu(probabilities);
 
-  meanLogxVec /= tot_probabilty;
-  meanxVec /= tot_probabilty;
+  meanLogxVec /= totProbability;
+  meanxVec /= totProbability;
   logMeanxVec = arma::log(meanxVec);
 
   // Call the statistics-only GammaDistribution::Train() function to fit the
@@ -98,7 +99,7 @@ void GammaDistribution::Train(const arma::mat& rdata, const arma::vec& probabili
 }
 
 // Fits an alpha and beta parameter to each dimension of the data.
-void GammaDistribution::Train(const arma::vec& logMeanxVec, 
+void GammaDistribution::Train(const arma::vec& logMeanxVec,
                               const arma::vec& meanLogxVec,
                               const arma::vec& meanxVec,
                               const double tol)
diff --git a/src/mlpack/tests/distribution_test.cpp b/src/mlpack/tests/distribution_test.cpp
index 9f01d89..9df3060 100644
--- a/src/mlpack/tests/distribution_test.cpp
+++ b/src/mlpack/tests/distribution_test.cpp
@@ -459,22 +459,22 @@ BOOST_AUTO_TEST_CASE(GammaDistributionTrainWithProbabilitiesTest)
   size_t d = 2;
   arma::mat rdata(d, N);
 
-  for(size_t j = 0; j < d; j++)
-    for(size_t i = 0; i < N; i++)
+  for (size_t j = 0; j < d; j++)
+    for (size_t i = 0; i < N; i++)
       rdata(j, i) = dist(generator);
 
   // create a uniform distribution random generator
   std::uniform_real_distribution<double> prob(0, 1);
   arma::vec probabilities(N);
 
-  for(size_t i = 0; i < N; i++)
+  for (size_t i = 0; i < N; i++)
     probabilities(i) = prob(generator);
 
-  // fit results with probabilities and data
+  // Fit results with probabilities and data.
   GammaDistribution gDist;
   gDist.Train(rdata, probabilities);
 
-  // fit results with only data
+  // Fit results with only data.
   GammaDistribution gDist2;
   gDist2.Train(rdata);
 
@@ -491,15 +491,16 @@ BOOST_AUTO_TEST_CASE(GammaDistributionTrainWithProbabilitiesTest)
   BOOST_REQUIRE_CLOSE(betaReal, gDist.Beta(1), 1);
 }
 
-
-// This test ensures that the same result is obtained when
-// trained with probabilities all set to 1 and with no probabilities at all.
-BOOST_AUTO_TEST_CASE(GammaDistributionTrainALLProbabilities1Test)
+/**
+ * This test ensures that the same result is obtained when trained with
+ * probabilities all set to 1 and with no probabilities at all.
+ */
+BOOST_AUTO_TEST_CASE(GammaDistributionTrainAllProbabilities1Test)
 {
   double alphaReal = 5.4;
   double betaReal = 6.7;
 
-  // Create a gamma distribution random generator
+  // Create a gamma distribution random generator.
   std::default_random_engine generator;
   std::gamma_distribution<double> dist(alphaReal, betaReal);
 
@@ -507,8 +508,8 @@ BOOST_AUTO_TEST_CASE(GammaDistributionTrainALLProbabilities1Test)
   size_t d = 2;
   arma::mat rdata(d, N);
 
-  for(size_t j = 0; j < d; j++)
-    for(size_t i = 0; i < N; i++)
+  for (size_t j = 0; j < d; j++)
+    for (size_t i = 0; i < N; i++)
       rdata(j, i) = dist(generator);
 
   // fit results with only data
@@ -541,7 +542,7 @@ BOOST_AUTO_TEST_CASE(GammaDistributionTrainTwoDistProbabilities1Test)
   double alphaReal2 = 1.9;
   double betaReal2 = 8.4;
 
-  // Create two gamma distribution random generators
+  // Create two gamma distribution random generators.
   std::default_random_engine generator;
   std::gamma_distribution<double> dist(alphaReal, betaReal);
   std::gamma_distribution<double> dist2(alphaReal2, betaReal2);
@@ -554,21 +555,21 @@ BOOST_AUTO_TEST_CASE(GammaDistributionTrainTwoDistProbabilities1Test)
   arma::mat rdata(d, N);
   arma::vec probabilities(N);
 
-  // draws points alternately from the two different distributions.
-  for(size_t j = 0; j < d; j++)
+  // Draw points alternately from the two different distributions.
+  for (size_t j = 0; j < d; j++)
   {
-    for(size_t i = 0; i < N; i++)
+    for (size_t i = 0; i < N; i++)
     {
-      if(i % 2 == 0)
+      if (i % 2 == 0)
         rdata(j, i) = dist(generator);
       else
         rdata(j, i) = dist2(generator);
     }
   }
 
-  for(size_t i = 0; i<N; i++)
+  for (size_t i = 0; i < N; i++)
   {
-    if(i % 2 == 0)
+    if (i % 2 == 0)
       probabilities(i) = lowProb(generator);
     else
       probabilities(i) = highProb(generator);
@@ -602,7 +603,7 @@ BOOST_AUTO_TEST_CASE(GammaDistributionFittingTest)
 
   /** Iteration 1 (first parameter set) **/
 
-  // Create a gamma-random generator and data
+  // Create a gamma-random generator and data.
   double alphaReal = 5.3;
   double betaReal = 1.5;
   std::default_random_engine generator;

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