egouldo

# remotes::install_github("egouldo/ManyEcoEvo") # install latest ManyEcoEvo
library(tidyverse)
library(ManyEcoEvo)
library(metafor)
library(remotes)


# ------ define data extraction / plotting functions ------

get_forest_plot_data <- function(model){

egouldo

Site,Habitat,Season,Chgouldii,Chmorio,CG/Mormlp,MormII,Mschocean,Nyctspp,Mmacropus,Nspp/Mmacr,Scotspp.,Taustralis,Vdarlingtoni,Vregulus,Vvulturnus,Unidentified,BatSpecies,BatActivity,Col,Dip,Eph,Hem,Lep,Hym,Tri,Manto,Psoc,Orth,Neur,Derm,Bla,Iso,Odo,Plec,Insectabundance,TotalOrder,Moon,NatEx,Bioregion,Size,SQQ,Water Depth,Imp 5km,Imp2km,Imp1km,Imp500m,NDVI2km,NDVI1km,NDVI500m,Trees 5km,Trees2km,Trees1km,Trees500m,House500,House1km,House2km,House5km,Light500m,Light1km,Light2km,Light5km,Road500m,Road1km,Road2km,Road5km,Distriver,Distwetland,Distwater,Distbushland,Aqvegcov,EphemVeg,TreeCoverage,TreesLarge>20dbh.plot,TreesSmall<20dbh.plot,Trees total.plot,Shrubs.plot,Hollows.total,Otherroostsnumber.total,TotalRoost,Distance1sttree,Temp,Humidity
Albert Park,1,1,151,0,6,0,0,10,0,10,8,1,0,0,1,8,7,185,6,20,48,0,13,1,16,0,0,0,0,0,0,0,0,0,104,6,2,2,1,508500,6.352532434,4,307.4648102,319.4008886,451.1150505,1693.27663,0.084813599,0.306702905,0.418516578,154467,16004,8789,1749,13147478.69,52767347.28,135155830.3,542156685

egouldo

title	author	date	output
Reprex: rendering fails or incomplete for list of pointblank tables in rmarkdown documents	Elliot Gould	08/03/2021	html_document keep_md true

egouldo

---
title: "Reprex: rendering fails or incomplete for list of pointblank tables in rmarkdown documents"
author: "Elliot Gould"
date: "08/03/2021"
output: 
  html_document:
  keep_md: yes
---

```{r setup, include=FALSE}

egouldo

gam_fun <- function(data, rabbit_var = c("rabbitwarrens", "warrenspretreatment"), df = integer(length = 1)){
  if(rabbit_var == "rabbitwarrens"){
    f <- substitute(gam(peren_chen_pc_cover ~ s(winterrain, df) + s(otherrain, df) + year + site + s(warrenspretreatment, df) + s(regionalroos, df) + landsystem, data=data, family=gaussian))
  } else{
    f <- substitute(gam(peren_chen_pc_cover ~ s(winterrain, df) + s(otherrain, df) + year + site + s(rabbitwarrens, df) + s(regionalroos, df) + landsystem, data=data, family=gaussian))
  }
  eval(f)
}

egouldo

  #https://github.com/ateucher/useful_code/blob/master/R/numbers2words.r
  numbers2words <- function(x){
    ## Function by John Fox found here: 
    ## http://tolstoy.newcastle.edu.au/R/help/05/04/2715.html
    ## Tweaks by AJH to add commas and "and"
    helper <- function(x){
      
      digits <- rev(strsplit(as.character(x), "")[[1]])
      nDigits <- length(digits)
      if (nDigits == 1) as.vector(ones[digits])

egouldo

create_latex <- function(f){
  knitr::knit(f, 'tmp-outputfile.md');
  newname <- paste0(tools::file_path_sans_ext(f), ".tex")
  mess <- paste('pandoc -f markdown -t latex -p -o', shQuote(newname),"tmp-outputfile.md")
  system(mess)}
  
# The function above takes an `Rmd` file as its input, knits the file to `md`, and then converts it to `TeX` by calling pandoc from the command-line. The secret ingredient lies in the pandoc call... When knitting using Rstudio, Rstudio calls the pandoc standalone `-s` flag when it compiles the pdf. This generates a 'standalone' document, i.e. one that contains latex preamble. This is obviously necessary when you want to view the PDF, but is problematic when you want to generate a latex fragment only from Rmd.

# I instead sought to generate a latex 'fragment' from `Rmd` with knitr, that can be later incorporated into a main TeX file. So the solution was simply to create a pandoc command line call that omits the `-s` standalone flag. I achieved this by calling pandoc from R with

egouldo

# Source: http://www.cookbook-r.com/Manipulating_data/Converting_between_data_frames_and_contingency_tables/#countstocases-function
# Convert from data frame of counts to data frame of cases.
# `countcol` is the name of the column containing the counts
countsToCases <- function(x, countcol = "Freq") {
    # Get the row indices to pull from x
    idx <- rep.int(seq_len(nrow(x)), x[[countcol]])

    # Drop count column
    x[[countcol]] <- NULL

egouldo

## FUNCTION - KfoldCASEFILE
# splits an R object of a case file into 5 Folds (When K is set to 5)
# Outputs the object into five pairs (When K = 5) of training and test case files in .cas format
# The input case file object must contain a column called "IDnum"
KfoldCASEFILE<-function(CaseFile, seed,k, path1, path2){
  # Renumber the IDnum column by order IF the case file is missing a number in a sequence
  CaseFile<-IDnumOrdered(CaseFile)
  #1. Setting the folds
  #2. Join the folds to the casefile object by dplyr::innerjoin (by cols are index in folds and idnum in casefile object)
  set.seed(seed)

egouldo

##' Modifies 'data' by adding new values supplied in newDataFileName
##'
##' newDataFileName is expected to have columns 
##' c(lookupVariable,lookupValue,newVariable,newValue,source)
##' 
##' Within the column 'newVariable', replace values that
##' match 'lookupValue' within column 'lookupVariable' with the value
##' newValue'.  If 'lookupVariable' is NA, then replace *all* elements
##' of 'newVariable' with the value 'newValue'.
##'