Adhere to generic function signatures

1 files changed, 29 insertions, 29 deletions

diff --git a/R/print.gensvm.R b/R/print.gensvm.R
index 724806b..54397da 100644
--- a/R/print.gensvm.R
+++ b/R/print.gensvm.R
@@ -2,7 +2,7 @@
 #'
 #' @description Prints a short description of the fitted GenSVM model
 #'
-#' @param fit A \code{gensvm} object to print
+#' @param x A \code{gensvm} object to print
 #' @param \dots further arguments are ignored
 #'
 #' @return returns the object passed as input. This can be useful for chaining 
@@ -36,41 +36,41 @@
 #' fit <- gensvm(x, y)
 #' predict(print(fit), x)
 #'
-print.gensvm <- function(fit, ...)
+print.gensvm <- function(x, ...)
 {
     cat("Data:\n")
-    cat("\tn.objects:", fit$n.objects, "\n")
-    cat("\tn.features:", fit$n.features, "\n")
-    cat("\tn.classes:", fit$n.classes, "\n")
-    if (is.factor(fit$classes))
-        cat("\tclasses:", levels(fit$classes), "\n")
+    cat("\tn.objects:", x$n.objects, "\n")
+    cat("\tn.features:", x$n.features, "\n")
+    cat("\tn.classes:", x$n.classes, "\n")
+    if (is.factor(x$classes))
+        cat("\tclasses:", levels(x$classes), "\n")
     else
-        cat("\tclasses:", fit$classes, "\n")
+        cat("\tclasses:", x$classes, "\n")
     cat("Parameters:\n")
-    cat("\tp:", fit$p, "\n")
-    cat("\tlambda:", fit$lambda, "\n")
-    cat("\tkappa:", fit$kappa, "\n")
-    cat("\tepsilon:", fit$epsilon, "\n")
-    cat("\tweights:", fit$weights, "\n")
-    cat("\tmax.iter:", fit$max.iter, "\n")
-    cat("\trandom.seed:", fit$random.seed, "\n")
-    if (is.factor(fit$kernel)) {
-        cat("\tkernel:", levels(fit$kernel)[as.numeric(fit$kernel)], "\n")
+    cat("\tp:", x$p, "\n")
+    cat("\tlambda:", x$lambda, "\n")
+    cat("\tkappa:", x$kappa, "\n")
+    cat("\tepsilon:", x$epsilon, "\n")
+    cat("\tweights:", x$weights, "\n")
+    cat("\tmax.iter:", x$max.iter, "\n")
+    cat("\trandom.seed:", x$random.seed, "\n")
+    if (is.factor(x$kernel)) {
+        cat("\tkernel:", levels(x$kernel)[as.numeric(x$kernel)], "\n")
     } else {
-        cat("\tkernel:", fit$kernel, "\n")
+        cat("\tkernel:", x$kernel, "\n")
     }
-    if (fit$kernel %in% c("poly", "rbf", "sigmoid")) {
-        cat("\tkernel.eigen.cutoff:", fit$kernel.eigen.cutoff, "\n")
-        cat("\tgamma:", fit$gamma, "\n")
+    if (x$kernel %in% c("poly", "rbf", "sigmoid")) {
+        cat("\tkernel.eigen.cutoff:", x$kernel.eigen.cutoff, "\n")
+        cat("\tgamma:", x$gamma, "\n")
     }
-    if (fit$kernel %in% c("poly", "sigmoid"))
-        cat("\tcoef:", fit$coef, "\n")
-    if (fit$kernel == 'poly')
-        cat("\tdegree:", fit$degree, "\n")
+    if (x$kernel %in% c("poly", "sigmoid"))
+        cat("\tcoef:", x$coef, "\n")
+    if (x$kernel == 'poly')
+        cat("\tdegree:", x$degree, "\n")
     cat("Results:\n")
-    cat("\ttime:", fit$training.time, "\n")
-    cat("\tn.iter:", fit$n.iter, "\n")
-    cat("\tn.support:", fit$n.support, "\n")
+    cat("\ttime:", x$training.time, "\n")
+    cat("\tn.iter:", x$n.iter, "\n")
+    cat("\tn.support:", x$n.support, "\n")
 
-    invisible(fit)
+    invisible(x)
 }