Peter M. Dahlgren peterdalle

Put caption above figure in knitr Rmarkdown LaTeX/PDF's

This is a hack to to put captions above figures (rather than below) when using Rmarkdown knitr and the output format is LaTeX/PDFs.

Other output formats has not been tested.

Setup:

git config --global user.name Namn
git config --global user.email [email protected]

A list of useful commands for the ffmpeg command line tool.

Command	Description
`ffmpeg -i in.mp4 out.avi`	Convert from one format to another
`ffmpeg -i in.mp4 -preset slower -crf 18 out.mp4`	Convert with custom quality: lower crf = higher quality (range: 0-51)
`ffmpeg -i in.mkv -c:v copy -c:a copy out.mp4`	Remux MKV file into MP4 (no quality loss)
`ffmpeg -i onlyvideo.mp4 -i onlyaudio.mp4 -c copy -map 0:0 -map 1:1 -shortest out.mp4`	Mux video and audio from different videos (no quality loss)
`ffmpeg -i in.mp4 -vf scale=640:480 out.mp4`	Resize video to 640 x 480
`ffmpeg -i in.mp4 -vf "transpose=1" out.mp4`	Rotate video 90 degrees clockwise (range: 0-3)

	$Url = "https://localhost:44399/cron.ashx?key=xxx"
	do{
	Write-Output "$(Get-Date)"
	(Invoke-WebRequest $Url).Content
	Write-Output ""
	Start-Sleep -Seconds 60
	}while(1 -eq 1)

	library(tidyverse)
	library(rio)

	xlsx_file <- "https://resource-cms.springernature.com/springer-cms/rest/v1/content/19770948/data/v8"

	df <- import(xlsx_file, skip=3)

	journal_apc <- df %>%
	mutate(cost = as.integer(str_extract(`APC EUR '22`, "\\d+"))) %>%
	select(journal = `Journal title`, cost)

	library(tidyverse)
	library(pwr)

	power_correlation <- function(n, r, alpha=0.05) {
	power <- pwr.r.test(n=n, r=r, sig.level=alpha)
	data.frame(n=n, r=r, alpha=alpha, power=power$power)
	}

	parameters <- expand.grid(n = seq.int(4, 200, by=2),
	r = seq.int(.1, .9, by=.1))

	library(dplyr)
	library(ggplot2)
	library(ggrepel)
	library(tidyr)
	library(helperutils) # https://github.com/peterdalle/helperutils

	# Fil nedladdad från:
	# https://www.vr.se/analys/svensk-forskning-i-siffror/vetenskapsradets-forskningsfinansiering-i-siffror.html
	file <- "Tillgängliggörande av data_2014-2021.xlsx"

	library(ggplot2)
	library(purrr)
	library(pwr2)

	power_analysis_go_brrr <- function(f, n) {
	res <- pwr.2way(a = 2, b = 2, f.A = f, f.B = f, alpha = .05, size.A = n/2, size.B = n/2)
	data.frame(f = f,
	n = n,
	power_a = res$power.A,
	power_b = res$power.B,