burchill

# an updated version of https://pastebin.com/0BRwUzpu by SO user mo-seph (https://stackoverflow.com/a/14692588/4560765)
# The version above no longer works

#' # The example:
#' points <- data.frame( x=runif(10), y=runif(10),class=1:10, size=runif(10,min=1000,max=100000) )
#' trans <- data.frame( from=rep(1:10,times=10), to=rep(1:10,each=10), amount=runif(100)^3 )
#' trans <- merge( trans, points, by.x="from", by.y="class" )
#' trans <- merge( trans, points, by.x="to", by.y="class", suffixes=c(".to",".from") )
#' ggplot( points, aes( x=x, y=y ) ) + geom_point(aes(size=size),color="red",shape=1) + 
#'   scale_size_continuous(range=c(4,20)) +

burchill

# Check https://www.zachburchill.ml/constant_scales/ for a walkthrough.  
#  Note that this code is slightly "better" than the code in the post, since it checks 
#   to see if the scales being supplied and used are all continuous.

# Examples included after the function definitions.

# Given a bunch of plots and a scale you want to apply to them, this returns that scale,
#   but with limits that encompass the union of all the ranges of values in those plots
# Meant to be for users
get_shared_scale <- function(..., scale) {

burchill

# Imitating Python 3 unpacking in R. (requires `rlang`)
# The following code lets you unpack variables for assignment in R like you do in Python
# Examples:  python  ~>  R
#  - `a, *b, c = [1,2,3,4]`  ~>  `a %,*% b %,% c <- c(1,2,3,4)`
#      - variables now: a = 1, b = c(2,3), c = 4
#  - `a, *b, c =  1, "C"`       ~>  `a %,*% b %,% c <- 1 %,% "C"`
#      - variables now: a = 1, b = NULL, c = "C"
#
# If you are using the `%,%` operator on the righthand side of the assignment, remember that the order of
#   order of operations in R is weird with infix operators. You should add parentheses to any values that are calls.

burchill

#' Set knitr hooks for htmlwidgets with Jekyll/GitHub Pages
#' 
#' This functions sets a `knitr` hook so that any HTML widgets that were
#'  printed (i.e., objects that inherit the `'htmlwidget'`, like those from 
#'  the `htmlwidgets` or `plotly` packages) will work with a Jekyll system, 
#'  like the one used for GitHub Pages. 
#' 
#' It essentially sets a hook so that, when the document is finished being
#'  knitted, it moves all the dependencies necessary for the widgets to a 
#'  directory, and then adds HTML code to the document to load those files 

burchill

plotly_manager <- function(
  postdir = knitr::opts_chunk$get("plotly.savepath"), # I have this as a default knitr option. Either change or specify your own when you call it 
  basedir = knitr::opts_chunk$get("proj.basedir"),    # Ditto. See: https://www.zachburchill.ml/plotly_with_jekyll/ for explanation
  libdirname = "js_files/",
  hrefFilter = function(x) paste0("/", x)) {
  
  deps <- list()
  libdir <- paste0(postdir, libdirname)
  
  render_deps <- function(l) {

burchill

# Created by Zachary Burchill, 2019-2021
# Feel free to use/modify however you want, but be nice and
#   please give me credit/attribution.
#
# Put this file in your jupyter directory and load it in the first cell with:
#   %load_ext zachmagic
# After that, you can use %beep, %%beep, %hook, %%hook, %time_beep, %%time_beep, %% %hide_all, 
#   %show_all, %keep_input and %%keep_input in the cells.

from IPython.core.magic import Magics, magics_class, line_magic, cell_magic, line_cell_magic

burchill

if (packageVersion("ggplot2") < "3.1.0") {
    stop("Need to use new version of ggplot!")
} else { 
    library(ggplot2)
}

UniquePanelCoords <- ggplot2::ggproto(
  "UniquePanelCoords", ggplot2::CoordCartesian,

burchill

library(dplyr)

# Copied from magrittr
is_pipe <- function (pipe) {
  identical(pipe, quote(`%>%`)) || identical(pipe, quote(`%T>%`)) || 
    identical(pipe, quote(`%<>%`)) || identical(pipe, quote(`%$%`))
}

get_og_lhs <- function(expr) {
  # While the expression is a call and the first element is a pipe

burchill

Keep figures and text in the order you wrote them

Want to keep the order of figures and text the way you wrote them in R Markdown when you convert to LaTeX? Tired of having to insert \FloatBarrier after every chunk you want plotted?

Just use knitr's hooks! Let's look at how we can do it:

Adding the placeins LaTeX package

First, you need to add the placeins LaTeX package to the header of your R Markdown file with \usepackage{placeins}. This lets you use the \FloatBarrier LaTeX command.

burchill

# Dplyr's `case_when` function is great for doing nested `ifelse()` functions:
#   it requires less keystrokes and is somewhat faster as well.
# The only "problem" is that it requires "strict typing," which can pose a problem because of NAs.
# Let's see how this works

# A data frame 
df <- data.frame(
  x = runif(100),
  y = runif(100)+0.2 # So we have a few values > 1
)