Daniel Borek danieltomasz

Quarto callouts

Callouts are a great way to add more attention ot certain details of the text (in the form of a box). Quarto provides 5 different types of callouts:

A naive proof of the concept Lua filter for removing [[ wikilinks from markdown file.

function Str (str)
    return (str.text:gsub('%[%[', '')
                    :gsub('%]%]', ''))
end

When the filter is saved under name cleanwiki.lua it might be used with the flag --lua-filter=cleanwiki.lua

Code for reproducible example around github functions

library(stringi)
library(tidyr)
library(dplyr)
library(stringr)

example <- data.frame(LP=1:10000)  %>%
  rowwise() %>%

List of helpful shortcuts for faster coding

If you have any other helpful shortcuts, feel free to add in the comments of this gist :)

install pyenv
install pyenv-virtualenv plugin
- https://github.com/pyenv/pyenv-virtualenv
Use pyenv to manage environment

pyenv install  3.8.10
pyenv virtualenv 3.8.10 example-env-name
pyenv local cognitive-reserve

	window.addEventListener("DOMContentLoaded", () => {
	const highlightResults = (text, color) => {
	document.designMode = "on"; // https://stackoverflow.com/a/5887719
	var selection = window.getSelection();
	selection.collapse(document.body, 0);
	while (window.find(text)) {
	document.execCommand("HiliteColor", false, color);
	selection.collapseToEnd();
	}
	document.designMode = "off";

	create_models <- function(datame_name, cog_vars, eeg_components) {
	list_models <- list()
	for (cogvar in cog_vars) { # ,eeg_components
	for (eegvar in eeg_components) { # ,eeg_components
	models <- glue("model1.{cogvar}.{eegvar} <- glm({cogvar} ~ GM_Normalised + {eegvar}, {datame_name}, family = gaussian)
	list_models[['model.{cogvar}.{eegvar}']] <- model5.{cogvar}.{eegvar}") # nolint
	eval(str2expression(models))
	}
	}
	return(list_models)