Update documentation with the changes.

Unify changes with test functions

doc/policies/functiontype.hpp

@@ -82,10 +82,12 @@ To evaluate the loss function at the given coordinates, same as the
 \c FunctionType interface.
 
 @code
-void FeatureGradient(const arma::mat& coordinates, const size_t j, double& gradient);
+void FeatureGradient(const arma::mat& coordinates, const size_t j, arma::sp_mat& gradient);
 @endcode
 
 To evaluate the gradient at the given coordinates, where \c gradient is an
-out-param for the required gradient. The out-param is a scalar value, for
-storing the gradient of the jth feature.
+out-param for the required gradient. The out-param is a sparse matrix(with
+dimensions equal to the decision variable), for storing the gradient of the
+jth feature.  The \c gradient matrix is supposed to be non-zero in the jth
+column, which contains the relavant partial gradient.
 */

src/mlpack/core/optimizers/parallel_sgd/sparse_test_function.hpp

@@ -67,7 +67,7 @@ class SparseTestFunction
                 const size_t i,
                 arma::sp_mat& gradient) const
   {
-    gradient = arma::sp_mat(1, coordinates.n_cols);
+    gradient.zeros(coordinates.size());
     gradient[i] = 2 * coordinates[i] + bi[i];
   }
 
@@ -76,8 +76,8 @@ class SparseTestFunction
                        const size_t j,
                        arma::sp_mat& gradient) const
   {
-    gradient.set_size(1);
-    gradient[0] = 2 * coordinates[j] + bi[j];
+    gradient.zeros(coordinates.size());
+    gradient[j] = 2 * coordinates[j] + bi[j];
   }
 
  private:

src/mlpack/core/optimizers/scd/scd_impl.hpp

@@ -53,7 +53,7 @@ double SCD<DescentPolicyType>::Optimize(ResolvableFunctionType& function,
     function.FeatureGradient(iterate, featureIdx, gradient);
 
     // Update the decision variable with the partial gradient.
-    iterate.col(featureIdx) -= stepSize * gradient;
+    iterate -= stepSize * gradient;
 
     // Check for convergence.
     if (i % updateInterval == 0)

src/mlpack/tests/scd_test.cpp

@@ -20,8 +20,8 @@
 #include "test_tools.hpp"
 
 using namespace std;
-using namespace arma;
 using namespace mlpack;
+using namespace mlpack::math;
 using namespace mlpack::optimization;
 using namespace mlpack::optimization::test;
 using namespace mlpack::regression;
@@ -135,7 +135,7 @@ BOOST_AUTO_TEST_CASE(SoftmaxRegressionFeatureGradientTest)
   // Create random class labels.
   arma::Row<size_t> labels(points);
   for (size_t i = 0; i < points; i++)
-    labels(i) = math::RandInt(0, numClasses);
+    labels(i) = RandInt(0, numClasses);
 
   // 2 objects for 2 terms in the cost function. Each term contributes towards
   // the gradient and thus need to be checked independently.