Added stats prefix to var to pass R CMD CHECK.

R/TDA.R

@@ -184,7 +184,7 @@ get_persistence_diagrams <- function(point.sets = NULL,
 #' @param Diag list of persistence diagrams as n x 3 matrices
 #' @param method which kernel or distance to compute. One of sWd (for sliced Wasserstein kernel) or pssk (for the persistence scale-space kernel)
 #' @param sigma kernel bandwidth
-#' @param return.dist logical (default: FALSE) whether to return the kernel matrix or the corresponding distance matrix. Set to TRUE to return the distance matrix.
+#' @param return.dist logical (default: FALSE) for method sWd, whether to return the sliced Wasserstein distance matrix instead of the kernel.
 #' @param M number of slices for the sliced Wasserstein kernel
 #' @param dimensions vector of the dimensions of the topological features to consider, if NULL (default) use all available dimensions
 #' @param ncpu number of parallel threads to use for computation

R/utils.R

@@ -103,7 +103,7 @@ locprec2cov <- function(point.sets, scale = FALSE) {
     ns <- nrow(point.sets[[i]])
     C[[i]] <- array(0, dim = c(d,d,ns))
     if(scale) {
-      v <- apply(point.sets[[i]], 2, var)
+      v <- apply(point.sets[[i]], 2, stats::var)
     }
     for(j in 1:ns) {
       if (d==3) {

man/get_kernel_matrix.Rd

@@ -21,7 +21,7 @@ get_kernel_matrix(
 
 \item{dimensions}{vector of the dimensions of the topological features to consider, if NULL (default) use all available dimensions}
 
-\item{return.dist}{logical (default: FALSE) whether to return the kernel matrix or the corresponding distance matrix. Set to TRUE to return the distance matrix.}
+\item{return.dist}{logical (default: FALSE) for method sWd, whether to return the sliced Wasserstein distance matrix instead of the kernel.}
 
 \item{M}{number of slices for the sliced Wasserstein kernel}