converted guassian to .hpp

src/mlpack/core/dists/CMakeLists.txt

@@ -4,7 +4,7 @@ set(SOURCES
   discrete_distribution.hpp
   discrete_distribution_impl.hpp
   gaussian_distribution.hpp
-  gaussian_distribution.cpp
+  gaussian_distribution_impl.hpp
   laplace_distribution.hpp
   laplace_distribution.cpp
   regression_distribution.hpp

src/mlpack/core/dists/gaussian_distribution.hpp

@@ -16,7 +16,7 @@
 #include <mlpack/prereqs.hpp>
 
 namespace mlpack {
-namespace distribution {
+namespace distribution /** Probability distributions. */ {
 
 /**
  * A single multivariate Gaussian distribution.
@@ -194,4 +194,7 @@ class GaussianDistribution
 } // namespace distribution
 } // namespace mlpack
 
+// Include implementation.
+#include "gaussian_distribution_impl.hpp"
+
 #endif

src/mlpack/core/dists/gaussian_distribution_impl.hpp

@@ -1,5 +1,5 @@
 /**
- * @file core/dists/gaussian_distribution.cpp
+ * @file core/dists/gaussian_distribution_impl.hpp
  * @author Ryan Curtin
  * @author Michael Fox
  *
@@ -10,33 +10,35 @@
  * 3-clause BSD license along with mlpack.  If not, see
  * http://www.opensource.org/licenses/BSD-3-Clause for more information.
  */
+#ifndef MLPACK_CORE_DISTRIBUTIONS_GAUSSIAN_DISTRIBUTION_IMPL_HPP
+#define MLPACK_CORE_DISTRIBUTIONS_GAUSSIAN_DISTRIBUTION_IMPL_HPP
+
 #include "gaussian_distribution.hpp"
 #include <mlpack/methods/gmm/positive_definite_constraint.hpp>
 
-using namespace mlpack;
-using namespace mlpack::distribution;
+namespace mlpack {
+namespace distribution /** Probability distributions. */ {
 
-
-GaussianDistribution::GaussianDistribution(const arma::vec& mean,
+inline GaussianDistribution::GaussianDistribution(const arma::vec& mean,
                                            const arma::mat& covariance)
   : mean(mean), logDetCov(0.0)
 {
   Covariance(covariance);
 }
 
-void GaussianDistribution::Covariance(const arma::mat& covariance)
+inline void GaussianDistribution::Covariance(const arma::mat& covariance)
 {
   this->covariance = covariance;
   FactorCovariance();
 }
 
-void GaussianDistribution::Covariance(arma::mat&& covariance)
+inline void GaussianDistribution::Covariance(arma::mat&& covariance)
 {
   this->covariance = std::move(covariance);
   FactorCovariance();
 }
 
-void GaussianDistribution::FactorCovariance()
+inline void GaussianDistribution::FactorCovariance()
 {
   // On Armadillo < 4.500, the "lower" option isn't available.
 
@@ -68,7 +70,7 @@ void GaussianDistribution::FactorCovariance()
   logDetCov *= 2;
 }
 
-double GaussianDistribution::LogProbability(const arma::vec& observation) const
+inline double GaussianDistribution::LogProbability(const arma::vec& observation) const
 {
   const size_t k = observation.n_elem;
   const arma::vec diff = mean - observation;
@@ -76,7 +78,7 @@ double GaussianDistribution::LogProbability(const arma::vec& observation) const
   return -0.5 * k * log2pi - 0.5 * logDetCov - 0.5 * v(0);
 }
 
-arma::vec GaussianDistribution::Random() const
+inline arma::vec GaussianDistribution::Random() const
 {
   return covLower * arma::randn<arma::vec>(mean.n_elem) + mean;
 }
@@ -86,7 +88,7 @@ arma::vec GaussianDistribution::Random() const
  *
  * @param observations List of observations.
  */
-void GaussianDistribution::Train(const arma::mat& observations)
+inline void GaussianDistribution::Train(const arma::mat& observations)
 {
   if (observations.n_cols > 0)
   {
@@ -95,10 +97,7 @@ void GaussianDistribution::Train(const arma::mat& observations)
   }
   else // This will end up just being empty.
   {
-    // TODO(stephentu): why do we allow this case? why not throw an error?
-    mean.zeros(0);
-    covariance.zeros(0);
-    return;
+    Log::Fatal << "Observation columns equal to 0." << std::endl;
   }
 
   // Calculate the mean.
@@ -130,7 +129,7 @@ void GaussianDistribution::Train(const arma::mat& observations)
  * account the probability of each observation actually being from this
  * distribution.
  */
-void GaussianDistribution::Train(const arma::mat& observations,
+inline void GaussianDistribution::Train(const arma::mat& observations,
                                  const arma::vec& probabilities)
 {
   if (observations.n_cols > 0)
@@ -140,10 +139,7 @@ void GaussianDistribution::Train(const arma::mat& observations,
   }
   else // This will end up just being empty.
   {
-    // TODO(stephentu): same as above
-    mean.zeros(0);
-    covariance.zeros(0);
-    return;
+    Log::Fatal << "Observation columns equal to 0." << std::endl;
   }
 
   double sumProb = 0;
@@ -185,3 +181,8 @@ void GaussianDistribution::Train(const arma::mat& observations,
 
   FactorCovariance();
 }
+
+} // namespace distribution
+} // namespace mlpack
+
+#endif