[mlpack-svn] r17284 - mlpack/trunk/src/mlpack/core/dists

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

Author: rcurtin
Date: Mon Nov  3 11:22:28 2014
New Revision: 17284

Log:
Minor formatting fixes: tabs->spaces, etc.


Modified:
   mlpack/trunk/src/mlpack/core/dists/regression_distribution.cpp
   mlpack/trunk/src/mlpack/core/dists/regression_distribution.hpp

Modified: mlpack/trunk/src/mlpack/core/dists/regression_distribution.cpp
==============================================================================
--- mlpack/trunk/src/mlpack/core/dists/regression_distribution.cpp	(original)
+++ mlpack/trunk/src/mlpack/core/dists/regression_distribution.cpp	Mon Nov  3 11:22:28 2014
@@ -13,8 +13,7 @@
 /**
  * Returns a string representation of this object.
  */
-std::string RegressionDistribution::ToString()
-    const
+std::string RegressionDistribution::ToString() const
 {
   std::ostringstream convert;
   convert << "HMMRegression [" << this << "]" << std::endl;
@@ -30,41 +29,41 @@
 }
 
 /**
-* Estimate parameters using provided observation weights
-*
-* @param observations List of observations.
-*/
+ * Estimate parameters using provided observation weights
+ *
+ * @param observations List of observations.
+ */
 void RegressionDistribution::Estimate(const arma::mat& observations)
 {
-  regression::LinearRegression lr(observations.rows(1, observations.n_rows-1),
+  regression::LinearRegression lr(observations.rows(1, observations.n_rows - 1),
       (observations.row(0)).t(), 0, true);
   rf = lr;
   arma::vec fitted;
-  lr.Predict(observations.rows(1, observations.n_rows-1), fitted);
-  err.Estimate(observations.row(0)-fitted.t());
+  lr.Predict(observations.rows(1, observations.n_rows - 1), fitted);
+  err.Estimate(observations.row(0) - fitted.t());
 }
 
 /**
-* Estimate parameters using provided observation weights
-*
-* @param weights probability that given observation is from distribution
-*/
+ * Estimate parameters using provided observation weights.
+ *
+ * @param weights probability that given observation is from distribution
+ */
 void RegressionDistribution::Estimate(const arma::mat& observations,
                              const arma::vec& weights)
 {
-  regression::LinearRegression lr(observations.rows(1, observations.n_rows-1),
+  regression::LinearRegression lr(observations.rows(1, observations.n_rows - 1),
       (observations.row(0)).t(), 0, true, weights);
   rf = lr;
   arma::vec fitted;
-  lr.Predict(observations.rows(1, observations.n_rows-1), fitted);
-  err.Estimate(observations.row(0)-fitted.t(), weights);
+  lr.Predict(observations.rows(1, observations.n_rows - 1), fitted);
+  err.Estimate(observations.row(0) - fitted.t(), weights);
 }
 
 /**
-* Evaluate probability density function of given observation  
-*
-* @param observation point to evaluate probability at
-*/
+ * Evaluate probability density function of given observation.
+ *
+ * @param observation point to evaluate probability at
+ */
 double RegressionDistribution::Probability(const arma::vec& observation) const
 {
   arma::vec fitted;
@@ -73,7 +72,7 @@
 }
 
 void RegressionDistribution::Predict(const arma::mat& points,
-				                             arma::vec& predictions) const
+                                     arma::vec& predictions) const
 {
-	rf.Predict(points, predictions);
-}
\ No newline at end of file
+  rf.Predict(points, predictions);
+}

Modified: mlpack/trunk/src/mlpack/core/dists/regression_distribution.hpp
==============================================================================
--- mlpack/trunk/src/mlpack/core/dists/regression_distribution.hpp	(original)
+++ mlpack/trunk/src/mlpack/core/dists/regression_distribution.hpp	Mon Nov  3 11:22:28 2014
@@ -20,16 +20,16 @@
  * regression (HMMR) as described in
  * https://www.ima.umn.edu/preprints/January1994/1195.pdf
  * The hmm observations should have the dependent variable in the first row,
- * with the independent variables in the other rows. 
+ * with the independent variables in the other rows.
  */
 class RegressionDistribution
 {
  private:
-  //! Regression function for representing conditional mean.   
-  regression::LinearRegression rf;   
+  //! Regression function for representing conditional mean.
+  regression::LinearRegression rf;
   //! Error distribution
   GaussianDistribution err;
-  
+
  public:
   /**
    * Default constructor, which creates a Gaussian with zero dimension.
@@ -38,24 +38,24 @@
 
   /**
    * Create a Conditional Gaussian distribution with conditional mean function
-   * obtained by running RegressionFunction on predictors, responses. 
-   * 
+   * obtained by running RegressionFunction on predictors, responses.
+   *
    * @param predictors Matrix of predictors (X).
    * @param responses Vector of responses (y).
    */
   RegressionDistribution(const arma::mat& predictors,
-                                  const arma::vec& responses) :
-      rf(regression::LinearRegression(predictors, responses))    
+                         const arma::vec& responses) :
+      rf(regression::LinearRegression(predictors, responses))
   {
-      err = GaussianDistribution(1);
-      err.Covariance() = rf.ComputeError(predictors, responses);
+    err = GaussianDistribution(1);
+    err.Covariance() = rf.ComputeError(predictors, responses);
   }
 
   /**
    * Returns a string representation of this object.
    */
   std::string ToString() const;
- 
+
   // Return regression function
   const regression::LinearRegression& Rf() {return rf;}
 
@@ -65,21 +65,21 @@
    * @param observations List of observations.
    */
   void Estimate(const arma::mat& observations);
-  
+
   /**
    * Estimate parameters using provided observation weights
    *
    * @param weights probability that given observation is from distribution
    */
   void Estimate(const arma::mat& observations, const arma::vec& weights);
-  
+
   /**
-  * Evaluate probability density function of given observation  
+  * Evaluate probability density function of given observation
   *
   * @param observation point to evaluate probability at
   */
   double Probability(const arma::vec& observation) const;
-  
+
   /**
    * Calculate y_i for each data point in points.
    *
@@ -87,8 +87,8 @@
    * @param predictions y, will contain calculated values on completion.
    */
   void Predict(const arma::mat& points, arma::vec& predictions) const;
-  
-   //! Return the parameters (the b vector).
+
+  //! Return the parameters (the b vector).
   const arma::vec& Parameters() const { return rf.Parameters(); }
 
   //! Return the dimensionality (2) NEED TO FIX THIS