Remove kernelparam array in favour of explicit kernel parameters

This simplifies a lot of the code and will make it easier to link
to other languages.

3 files changed, 29 insertions, 15 deletions

diff --git a/include/gensvm_base.h b/include/gensvm_base.h
index 999bf2f..dee1d80 100644
--- a/include/gensvm_base.h
+++ b/include/gensvm_base.h
@@ -49,7 +49,9 @@
  * @param J 		pointer to regularization vector
  * @param Sigma 	eigenvalues from the reduced eigendecomposition
  * @param kerneltype 	kerneltype used in GenData::Z
- * @param *kernelparam 	kernel parameters used in GenData::Z
+ * @param gamma 	kernel parameter for RBF, poly, and sigmoid
+ * @param coef 		kernel parameter for poly and sigmoid
+ * @param degree 	kernel parameter for poly
  *
  */
 struct GenData {
@@ -75,9 +77,12 @@ struct GenData {
 	KernelType kerneltype;
 	///< kerneltype used to generate the kernel corresponding to the data 
 	///< in Z
- 	double *kernelparam;
-	///< kernelparameters used to generate the kernel corresponding to the 
-	///< data in Z
+	double gamma;
+	///< kernel parameter for RBF, poly, and sigmoid
+	double coef;
+	///< kernel parameter for poly and sigmoid
+	double degree;
+	///< kernel parameter for poly
 };
 
 /**
@@ -101,6 +106,12 @@ struct GenModel {
 	///< parameter for the Huber hinge function
 	double lambda;
 	///< regularization parameter in the loss function
+	double gamma;
+	///< kernel parameter for RBF, poly, and sigmoid
+	double coef;
+	///< kernel parameter for poly and sigmoid
+	double degree;
+	///< kernel parameter for poly
 	double *V;
 	///< augmented weight matrix
 	double *Vbar;
@@ -122,8 +133,6 @@ struct GenModel {
 	///< filename of the data
 	KernelType kerneltype;
 	///< type of kernel used in the model
-	double *kernelparam;
-	///< array of kernel parameters, size depends on kernel type
 	double kernel_eigen_cutoff;
 	///< cutoff value for the ratio of eigenvalues in the reduced 
 	//eigendecomposition.
diff --git a/include/gensvm_kernel.h b/include/gensvm_kernel.h
index 1d4f0d1..bb3e100 100644
--- a/include/gensvm_kernel.h
+++ b/include/gensvm_kernel.h
@@ -51,12 +51,11 @@ void gensvm_kernel_trainfactor(struct GenData *data, double *P, double *Sigma,
 		long r);
 void gensvm_kernel_testfactor(struct GenData *testdata,
 	       	struct GenData *traindata, double *K2);
-double gensvm_kernel_dot_rbf(double *x1, double *x2, double *kernelparam,
-		long n);
-double gensvm_kernel_dot_poly(double *x1, double *x2, double *kernelparam,
-		long n);
-double gensvm_kernel_dot_sigmoid(double *x1, double *x2, double *kernelparam,
-		long n);
+double gensvm_kernel_dot_rbf(double *x1, double *x2, long n, double gamma);
+double gensvm_kernel_dot_poly(double *x1, double *x2, long n, double gamma, 
+		double coef, double degree);
+double gensvm_kernel_dot_sigmoid(double *x1, double *x2, long n, double gamma, 
+		double coef);
 int dsyevx(char JOBZ, char RANGE, char UPLO, int N, double *A, int LDA,
 	       	double VL, double VU, int IL, int IU, double ABSTOL,
 		int *M, double *W, double *Z, int LDZ, double *WORK, int LWORK,
diff --git a/include/gensvm_task.h b/include/gensvm_task.h
index 03fcbb5..a791262 100644
--- a/include/gensvm_task.h
+++ b/include/gensvm_task.h
@@ -45,7 +45,9 @@
  * @param lambda 	parameter for the GenModel
  * @param epsilon 	parameter for the GenModel
  * @param kerneltype 	parameter for the GenModel
- * @param kernelparam 	kernel parameters for the GenModel
+ * @param gamma 	parameter for the GenModel
+ * @param coef 		parameter for the GenModel
+ * @param degree 	parameter for the GenModel
  * @param train_data 	pointer to the training data
  * @param test_data 	pointer to the test data (if any)
  * @param performance 	performance after cross validation
@@ -67,8 +69,12 @@ struct GenTask {
 	///< lambda parameter for the GenModel
 	double epsilon;
 	///< epsilon parameter for the GenModel
-	double *kernelparam;
-	///< kernelparam parameters for the GenModel
+	double gamma;
+	///< gamma parameter for the GenModel
+	double coef;
+	///< coef parameter for the GenModel
+	double degree;
+	///< degree parameter for the GenModel
 	struct GenData *train_data;
 	///< pointer to the training data
 	struct GenData *test_data;