There are two types of markup in Liquid: Output and Tag.
- Output markup (which may resolve to text) is surrounded by
{{ matched pairs of curly brackets (ie, braces) }}
- Tag markup (which cannot resolve to text) is surrounded by
#!/usr/bin/env Rscript | |
#----------------------------------------------------------------------------- | |
# How to run? | |
# In terminal enter: Rscript --vanilla r2jekyll.R my_RMarkdownFile.Rmd | |
#----------------------------------------------------------------------------- | |
# Problem while rendering Rmarkdown files with latex equation into markdown file | |
# -> Rmarkdown try to convert the equation into markdown instead of leaving them | |
# as latex equation. In consequences, the equations within the mardown file |
There are two types of markup in Liquid: Output and Tag.
{{ matched pairs of curly brackets (ie, braces) }}
polygonizer <- function(x, outshape=NULL, pypath=NULL, readpoly=TRUE, | |
fillholes=FALSE, aggregate=FALSE, | |
quietish=TRUE) { | |
# x: an R Raster layer, or the file path to a raster file recognised by GDAL | |
# outshape: the path to the output shapefile (if NULL, a temporary file will | |
# be created) | |
# pypath: the path to gdal_polygonize.py or OSGeo4W.bat (if NULL, the function | |
# will attempt to determine the location) | |
# readpoly: should the polygon shapefile be read back into R, and returned by | |
# this function? (logical) |
Having painstakingly performed the operation of migrating dual-boot systems to SSDs (without a fresh install of any of the systems) twice in the recent days, I've decided to write the steps down in case I ever need to repeat it. It may also benefit someone else on the internet. This is the most efficient and least error-prone workflow to the best of my knowledge, and discovering it was not as easy as it may seem.
Please excuse the somewhat short-hand form of this guide; I take the liberty to assume the reader is a power-user and is at least familiar with Linux.
Here are the specific conditions I worked under: