Add support for raw weight vector in gensvm()

4 files changed, 27 insertions, 7 deletions

diff --git a/R/gensvm.R b/R/gensvm.R
index 8994d3a..5652a4c 100644
--- a/R/gensvm.R
+++ b/R/gensvm.R
@@ -139,13 +139,21 @@ gensvm <- function(x, y, p=1.0, lambda=1e-8, kappa=0.0, epsilon=1e-6,
     if (gamma == 'auto')
         gamma <- 1.0/n.features
 
+    raw.weights <- if (is.character(weights)) NULL else weights
+    weights <- if (is.character(weights)) weights else "raw"
+
+    if (weights == "raw" && length(raw.weights) != n.objects) {
+        cat("Error: length of weights vector unequal to number of objects\n")
+        return(invisible(NULL))
+    }
+
     if (!gensvm.validate.params(p=p, kappa=kappa, lambda=lambda,
                                 epsilon=epsilon, gamma=gamma, weights=weights,
                                 kernel=kernel))
         return(invisible(NULL))
 
     # Convert weights to index
-    weight.idx <- which(c("unit", "group") == weights)
+    weight.idx <- which(c("raw", "unit", "group") == weights) - 1
 
     # Convert kernel to index (remember off-by-one for R vs. C)
     kernel.idx <- which(c("linear", "poly", "rbf", "sigmoid") == kernel) - 1
@@ -162,6 +170,7 @@ gensvm <- function(x, y, p=1.0, lambda=1e-8, kappa=0.0, epsilon=1e-6,
                   kappa,
                   epsilon,
                   weight.idx,
+                  raw.weights,
                   as.integer(kernel.idx),
                   gamma,
                   coef,
diff --git a/R/validate.R b/R/validate.R
index b0f3f39..5960a38 100644
--- a/R/validate.R
+++ b/R/validate.R
@@ -64,7 +64,7 @@ gensvm.param.conditions <- function()
         lambda=function(x) {x > 0.0 },
         epsilon=function(x) { x > 0.0 },
         gamma=function(x) { x != 0.0 },
-        weights=function(x) { x %in% c("unit", "group") },
+        weights=function(x) { x %in% c("raw", "unit", "group") },
         kernel=function(x) { x %in% c("linear", "poly", "rbf", "sigmoid") }
         )
 }
diff --git a/src/gensvm b/src/gensvm
-Subproject d80d1570edd794c66be69f6d359c4947b7d7839
+Subproject 1fd9dad0ed6d5299c8d75de6213ed40b183c583
diff --git a/src/gensvm_wrapper.c b/src/gensvm_wrapper.c
index 46578d0..275f797 100644
--- a/src/gensvm_wrapper.c
+++ b/src/gensvm_wrapper.c
@@ -37,10 +37,11 @@
 
 SEXP R_gensvm_train( SEXP R_X, SEXP R_y, SEXP R_p, SEXP R_lambda, 
 		SEXP R_kappa, SEXP R_epsilon, SEXP R_weight_idx, 
-		SEXP R_kernel_idx, SEXP R_gamma, SEXP R_coef, SEXP R_degree, 
-		SEXP R_kernel_eigen_cutoff, SEXP R_verbose, SEXP R_max_iter, 
-		SEXP R_random_seed, SEXP R_seed_V, SEXP R_seed_rows, 
-		SEXP R_seed_cols, SEXP R_n, SEXP R_m, SEXP R_K);
+		SEXP R_raw_weights, SEXP R_kernel_idx, SEXP R_gamma, 
+		SEXP R_coef, SEXP R_degree, SEXP R_kernel_eigen_cutoff, 
+		SEXP R_verbose, SEXP R_max_iter, SEXP R_random_seed, 
+		SEXP R_seed_V, SEXP R_seed_rows, SEXP R_seed_cols, SEXP R_n, 
+		SEXP R_m, SEXP R_K);
 SEXP R_gensvm_predict(SEXP R_Xtest, SEXP R_V, SEXP R_n, SEXP R_m, SEXP R_K);
 SEXP R_gensvm_predict_kernels(
 		SEXP R_Xtest, SEXP R_Xtrain, SEXP R_V, SEXP R_V_row,
@@ -63,7 +64,7 @@ struct GenData *_build_gensvm_data(double *X, int *y, int n, int m, int K);
 // Start R package stuff
 
 R_CallMethodDef callMethods[] = {
-	{"R_gensvm_train", (DL_FUNC) &R_gensvm_train, 21},
+	{"R_gensvm_train", (DL_FUNC) &R_gensvm_train, 22},
 	{"R_gensvm_predict", (DL_FUNC) &R_gensvm_predict, 5},
 	{"R_gensvm_predict_kernels", (DL_FUNC) &R_gensvm_predict_kernels, 14},
 	{"R_gensvm_plotdata_kernels", (DL_FUNC) &R_gensvm_plotdata_kernels, 14},
@@ -171,6 +172,7 @@ SEXP R_gensvm_train(
 		SEXP R_kappa,
 		SEXP R_epsilon,
 		SEXP R_weight_idx,
+		SEXP R_raw_weights,
 		SEXP R_kernel_idx,
 		SEXP R_gamma,
 		SEXP R_coef,
@@ -194,6 +196,7 @@ SEXP R_gensvm_train(
 	double kappa = *REAL(R_kappa);
 	double epsilon = *REAL(R_epsilon);
 	int weight_idx = *INTEGER(R_weight_idx);
+	double *raw_weights = isNull(R_raw_weights) ? NULL : REAL(R_raw_weights);
 	int kernel_idx = *INTEGER(R_kernel_idx);
 	double gamma = *REAL(R_gamma);
 	double coef = *REAL(R_coef);
@@ -217,6 +220,9 @@ SEXP R_gensvm_train(
 	double value;
 
 	// Set model parameters from function input arguments
+	model->n = n;
+	model->m = m;
+	model->K = K;
 	model->p = p;
 	model->lambda = lambda;
 	model->kappa = kappa;
@@ -230,6 +236,11 @@ SEXP R_gensvm_train(
 	model->max_iter = max_iter;
 	model->seed = random_seed;
 
+	if (raw_weights != NULL) {
+		model->rho = Calloc(double, n);
+		for (i=0; i<n; i++) model->rho[i] = raw_weights[i];
+	}
+
 	if (seed_V != NULL) {
 		seed_model = gensvm_init_model();