program--

Note

This is a work-in-progress.

This is an attempt at creating standalone R executables by embedding and evaluating R code through C via a static R build.

Currently, by using the below script, we receive libR.a and associated BLAS/LAPACK internal shared libraries. libR.A is ~6MiB, but is halved to ~3.3MiB when stripped. However, it's not completely static at this point, as some dependencies like PCRE are still dynamically linked (which, might be due to needing --enable-static=pcre or something?)

program--

---
Language: Cpp
BasedOnStyle: Mozilla
UseTab: Never
IndentWidth: 4
ColumnLimit: 80
DerivePointerAlignment: false
PointerAlignment: Left
AlignAfterOpenBracket: BlockIndent
AlignConsecutiveMacros: AcrossEmptyLines

program--

Description

This script installs GEOS, PROJ, and GDAL (with Python and NetCDF) from source on Fedora (Only tested with Fedora 33).

The user can specify versions and/or whether to install PROJ datum data with the flags below.

Partially credited to: https://gist.github.com/robinkraft/2a8ee4dd7e9ee9126030

It is generally recommended to install these libraries directly with yum/dnf.

This script should only be used if a specific version is needed.

program--

#' Download from CFIM
#' Download zipped HUC 6-digit HAND packages from CFIM Data Repository - https://cfim.ornl.gov/data/
#' @param huc6_codes character vector of HUC 6-digit codes, or "all" to download all available HUC 6-digit zip files.
#' @param dir character of directory path.
#' @param overwrite Overwrite already downloaded zip files? Defaults to FALSE.
#' @return No explicit return. Unzipped HUC 6-digit HAND packages can be found in `dir`
#' importsFrom RCurl getURL
#' importsFrom stringr str_extract_all
#' importsFrom magrittr %>%
download_hand_cfim <- function(huc6_codes = "all", dir, overwrite = FALSE, ...) {

program--

#' @title Build GBM Tree
#' @description Create a `data.tree` object from a GBM tree.
#' @param gbm_model Object of class `gbm`
#' @param i.tree Tree iteration to build from
#' @return A `data.tree` object from the `i.tree` tree of `gbm_model`.
build_tree <- function(gbm_model, i.tree = 1) {
    gbm_tree <- gbm::pretty.gbm.tree(gbm_model, i.tree = i.tree)
    pathString <- c("0" = "0")

    for (node in seq(1, nrow(gbm_tree) - 1)) {

program--

#' Also see: https://github.com/program--/plannr
#' importsFrom readxl read_excel
#' importsFrom tibble as_tibble

import_plan <- function(xlsx) {
    plan_data <- readxl::read_excel(xlsx)
    plan_name <- colnames(plan_data[[2]][2]) 
    plan_date <- plan_data[[2]][2]
    filtered_data <- setNames(plan_data, plan_data[4, ])
    filtered_data <- filtered_data[-c(1,2,3,4), ]