priority_queue is default

Author: tdhock

R/RcppExports.R

@@ -1,28 +1,28 @@
 # Generated by using Rcpp::compileAttributes() -> do not edit by hand
 # Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
 
-#' Efficient log-linear cumulative median.
+### Efficient log-linear cumulative median.
 cum_median_interface <- function(data_vec, weight_vec) {
     .Call(`_binsegRcpp_cum_median_interface`, data_vec, weight_vec)
 }
 
-#' Use depth first search to compute a data.frame
-#' with one row for each segment, and columns
-#' splits and depth, number/depth of candidate
-#' splits that need to be
-#' computed after splitting that segment.
+### Use depth first search to compute a data.frame
+### with one row for each segment, and columns
+### splits and depth, number/depth of candidate
+### splits that need to be
+### computed after splitting that segment.
 depth_first_interface <- function(n_data, min_segment_length) {
     .Call(`_binsegRcpp_depth_first_interface`, n_data, min_segment_length)
 }
 
-#' Compute a data.frame with one row for each distribution
-#' implemented in the C++ code, and columns distribution.str,
-#' parameters, description.
+### Compute a data.frame with one row for each distribution
+### implemented in the C++ code, and columns distribution.str,
+### parameters, description.
 get_distribution_info <- function() {
     .Call(`_binsegRcpp_get_distribution_info`)
 }
 
-#' Low-level interface to binary segmentation algorithm.
+### Low-level interface to binary segmentation algorithm.
 binseg_interface <- function(data_vec, weight_vec, max_segments, min_segment_length, distribution_str, container_str, is_validation_vec, position_vec) {
     .Call(`_binsegRcpp_binseg_interface`, data_vec, weight_vec, max_segments, min_segment_length, distribution_str, container_str, is_validation_vec, position_vec)
 }

R/binseg.R

@@ -25,10 +25,10 @@ binseg <- structure(function # Binary segmentation
   min.segment.length=NULL,
 ### Positive integer, minimum number of data points per
 ### segment. Default NULL means to use min given distribution.str.
-  container.str="multiset"
+  container.str="priority_queue"
 ### C++ container to use for storing breakpoints/cost. Most users
-### should leave this at the default "multiset" for efficiency but you
-### could use "list" if you want to study the time complexity of a
+### should leave this at the default "priority_queue" for efficiency, but you
+### could use "list" if you want to study the time complexity of an asymptotically
 ### slower implementation of binary segmentation.
 ){
   ##alias<< binsegRcpp

man/binseg.Rd

@@ -15,7 +15,7 @@ log-linear time, using coef method.}
     weight.vec = rep(1, 
         length(data.vec)), 
     min.segment.length = NULL, 
-    container.str = "multiset")}
+    container.str = "priority_queue")}
 \arguments{
   \item{distribution.str}{String indicating distribution/loss function, use
 \code{\link{get_distribution_info}} to see possible values.}
@@ -32,8 +32,8 @@ default=1:length(\code{data.vec}).}
   \item{min.segment.length}{Positive integer, minimum number of data points per
 segment. Default NULL means to use min given \code{distribution.str}.}
   \item{container.str}{C++ container to use for storing breakpoints/cost. Most users
-should leave this at the default "multiset" for efficiency but you
-could use "list" if you want to study the time complexity of a
+should leave this at the default "priority_queue" for efficiency, but you
+could use "list" if you want to study the time complexity of an asymptotically
 slower implementation of binary segmentation.}
 }
 \details{Each iteration involves first computing and storing the