R/RcppExports.R

In binsegRcpp: Efficient Implementation of Binary Segmentation

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

### 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.
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.
get_distribution_info <- function() {
    .Call(`_binsegRcpp_get_distribution_info`)
}

### 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)
}