[mlpack-svn] r10798 - mlpack/trunk/src/mlpack/methods/pca

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

Author: rcurtin
Date: 2011-12-14 14:05:19 -0500 (Wed, 14 Dec 2011)
New Revision: 10798

Modified:
   mlpack/trunk/src/mlpack/methods/pca/pca.cpp
   mlpack/trunk/src/mlpack/methods/pca/pca.hpp
Log:
Change variable names to match code specifications and mark a couple functions
const.


Modified: mlpack/trunk/src/mlpack/methods/pca/pca.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/pca/pca.cpp	2011-12-14 18:17:27 UTC (rev 10797)
+++ mlpack/trunk/src/mlpack/methods/pca/pca.cpp	2011-12-14 19:05:19 UTC (rev 10798)
@@ -14,10 +14,9 @@
 namespace pca {
 
 PCA::PCA(const bool centerData, const bool scaleData) :
-      centerData_(centerData),
-      scaleData_(scaleData)
-{
-}
+    centerData(centerData),
+    scaleData(scaleData)
+{ }
 
 /**
  * Apply Principal Component Analysis to the provided data set.
@@ -27,33 +26,37 @@
  * @param eigVal - contains eigen values in a column vector
  * @param coeff - PCA Loadings/Coeffs/EigenVectors
  */
-void PCA::Apply(const arma::mat& data, arma::mat& transformedData,
-           arma::vec& eigVal, arma::mat& coeffs)
+void PCA::Apply(const arma::mat& data,
+                arma::mat& transformedData,
+                arma::vec& eigVal,
+                arma::mat& coeffs) const
 {
   arma::mat transData = trans(data);
 
-  if(centerData_)
+  if(centerData)
   {
     arma::rowvec means = arma::mean(transData, 0);
     transData = transData - arma::ones<arma::colvec>(transData.n_rows) * means;
   }
 
-  if(scaleData_)
+  if(scaleData)
   {
-    transData = transData / (arma::ones<arma::colvec>(transData.n_rows) * stddev(transData, 0, 0));
+    transData = transData / (arma::ones<arma::colvec>(transData.n_rows) *
+        stddev(transData, 0, 0));
   }
 
   arma::mat covMat = cov(transData);
   arma::eig_sym(eigVal, coeffs, covMat);
 
   int n_eigVal = eigVal.n_elem;
-  for(int i = 0; i < floor(n_eigVal / 2); i++)
+  for (int i = 0; i < floor(n_eigVal / 2); i++)
     eigVal.swap_rows(i, (n_eigVal - 1) - i);
 
   coeffs = arma::fliplr(coeffs);
   transformedData = trans(coeffs) * data;
   arma::colvec transformedDataMean = arma::mean(transformedData, 1);
-  transformedData = transformedData - (transformedDataMean * arma::ones<arma::rowvec>(transformedData.n_cols));
+  transformedData = transformedData - (transformedDataMean *
+      arma::ones<arma::rowvec>(transformedData.n_cols));
 }
 
 /**
@@ -63,12 +66,12 @@
  * @param transformedData - Data with PCA applied
  * @param eigVal - contains eigen values in a column vector
  */
-void PCA::Apply(const arma::mat& data, arma::mat& transformedData,
-           arma::vec& eigVal)
+void PCA::Apply(const arma::mat& data,
+                arma::mat& transformedData,
+                arma::vec& eigVal) const
 {
   arma::mat coeffs;
-  Apply(data, transformedData,
-              eigVal, coeffs);
+  Apply(data, transformedData, eigVal, coeffs);
 }
 
 /**
@@ -81,7 +84,7 @@
  * from data matrix onto the basis vectors contained in the columns of
  * coeff/eigen vector matrix with only newDimension number of columns chosen.
  */
-void PCA::Apply(arma::mat& data, const int newDimension)
+void PCA::Apply(arma::mat& data, const int newDimension) const
 {
   arma::mat coeffs;
   arma::vec eigVal;

Modified: mlpack/trunk/src/mlpack/methods/pca/pca.hpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/pca/pca.hpp	2011-12-14 18:17:27 UTC (rev 10797)
+++ mlpack/trunk/src/mlpack/methods/pca/pca.hpp	2011-12-14 19:05:19 UTC (rev 10798)
@@ -18,38 +18,6 @@
  public:
   PCA(const bool centerData = false, const bool scaleData = false);
 
-  /* Return whether or not this PCA object will center the data when PCA
-   *  is performed.
-   */
-  bool CenterData() const
-  {
-    return centerData_;
-  }
-
-  /* Modify whether or not this PCA object will center the data when PCA
-   * is performed.
-   */
-  bool& CenterData()
-  {
-    return centerData_;
-  }
-
-  /* Return whether or not this PCA object will scale(by standard deviation) the data when PCA
-   *  is performed.
-   */
-  bool ScaleData() const
-  {
-    return scaleData_;
-  }
-
-  /* Modify whether or not this PCA object will scale(by standard deviation) the data when PCA
-   * is performed.
-   */
-  bool& ScaleData()
-  {
-    return scaleData_;
-  }
-
   /**
    * Apply Principal Component Analysis to the provided data set.
    *
@@ -59,7 +27,7 @@
    * @param coeff - PCA Loadings/Coeffs/EigenVectors
    */
   void Apply(const arma::mat& data, arma::mat& transformedData, arma::vec&
-             eigVal, arma::mat& coeff);
+             eigVal, arma::mat& coeff) const;
 
   /**
    * Apply Principal Component Analysis to the provided data set.
@@ -69,7 +37,7 @@
    * @param eigVal - contains eigen values in a column vector
    */
   void Apply(const arma::mat& data, arma::mat& transformedData,
-             arma::vec& eigVal);
+             arma::vec& eigVal) const;
 
   /**
    * Apply Dimensionality Reduction using Principal Component Analysis
@@ -81,17 +49,29 @@
    * from data matrix onto the basis vectors contained in the columns of
    * coeff/eigen vector matrix with only newDimension number of columns chosen.
    */
-  void Apply(arma::mat& data, const int newDimension);
+  void Apply(arma::mat& data, const int newDimension) const;
 
   /**
    * Delete PCA object
    */
   ~PCA();
 
- private:
-   bool centerData_;
-   bool scaleData_;
+  //! Get whether or not this PCA object will center the data.
+  bool CenterData() const { return centerData; }
+  //! Modify whether or not this PCA object will center the data when PCA is
+  //! is performed.
+  bool& CenterData() {  return centerData; }
 
+  //! Get whether or not this PCA object will scale (by standard deviation) the
+  //! data when PCA is performed.
+  bool ScaleData() const { return scaleData; }
+  //! Modify whether or not this PCA object will scale (by standard deviation)
+  //! the data when PCA is performed.
+  bool& ScaleData() { return scaleData; }
+
+ private:
+  bool centerData;
+  bool scaleData;
 }; // class PCA
 
 }; // namespace pca