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function RawBlock (raw)
  local caption = raw.text:match("\\caption%{[^%}]+%}")
  if caption then
    captions:insert(caption)
  end
end

function Pandoc (doc)
  -- append collected captions at the end
  doc.meta.figures = captions -- This works but latex is escaped by \textbackslash

bakaburg1

library(stringr)
library(dplyr)

check_logfile <- ...

readLines(check_logfile) %>% paste(collapse = '\n') %>%
   str_extract_all("[\\w_]+ ?:( <anonymous>:)?[\\s\\n]+no[\\s\\n]+visible[\\s\\n]+binding[\\s\\n]+for[\\s\\n]+global[\\s\\n]+variable[\\s\\n]+‘.*’") %>%
   lapply(function(x) {
    fun <- str_extract(x, '^[\\w_]+')
    

bakaburg1

library(shiny)
print(paste('Inline Julia pID:', sys::exec_background('nohup', c("julia", "-e sleep(3000)"))))
print(paste('Julia script pID:', sys::exec_background('nohup', c("julia", "test.jl", "&"))))

# Define UI for application that draws a histogram
ui <- fluidPage(

    # Application title
    titlePanel("Old Faithful Geyser Data"),

bakaburg1

#' Extract ctree rules.
#'
#' Extract the tree rules, optionally formatting them in order to be ready to
#' use for data filtering.
#'
#' @param tree An object produced by \code{partikit::ctree()}.
#' @param rule.as.text Whether to collapse rule conditions into a string or
#'   leave them as a character vector.
#' @param eval.ready Whether to format rules in order to be easily eval() for
#'   data filtering. Turns \code{rule.as.text} automatically on.

bakaburg1

brms.mod.nprest.nb <<- brm(bf(N.prest ~ Mesi + (Mesi|Context), family = negbinomial()), data = TdA, prior = c(
    set_prior('normal(0, 2.5)', class = 'Intercept'),
    set_prior("cauchy(0, 2.5)", class = 'b')#,
    #set_prior("normal(0, 2.5)", class = 'sd')
), init_r = 0.1, cores = 8, chains = 8, iter = 8000, warmup = 2000, control = list(max_treedepth = 15, adapt_delta = .90))

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brms.mod.attesa.prior <- brm(bf(Attesa ~ log(N.prest) + (log(N.prest)|Context), shape ~ log(N.prest) + (log(N.prest)|Context), family = Gamma('log')), data = TdA, prior = c(
    set_prior('normal(0, 2.5)', class = 'Intercept'),
    set_prior("cauchy(0, 2.5)", class = 'b'),
    set_prior("normal(0, 1.5)", class = 'sd',  group = 'Context'),
    set_prior("normal(0, 1.5)", class = 'sd'),
    set_prior("student_t(3, 0, 2.5)", class = 'sd', dpar = 'shape'),
    set_prior("student_t(3, 0, 2.5)", class = 'sd', group = 'Context', dpar = 'shape')
), init_r = 0.1, cores = 8, chains = 8, iter = 8000, warmup = 2000, control = list(max_treedepth = 15, adapt_delta = .90))

Error in stan_base_prior(prior) : length(base_prior) == 1L is not TRUE

bakaburg1

library(parallel)
library(pbmcapply)
library(dplyr)

mcdo <- function(.data, ...) {
	if (progress.bar) {
		pkg.require(c('pbmcapply'))
		pfun <- pbmclapply
	} else pfun <- mclapply

bakaburg1

<div style="
    position: relative;
">
    <span style="
        position: absolute;
        top: -900%;
        left: 3%;
        background: white;
        padding: 0 10px;
    ">Blah Blah</span>