Matthew Skiffington MattSkiff

Shortcut — Action

CTRL + A — Move to the beginning of the line
CTRL + E — Move to the end of the line
CTRL + [left arrow] — Move one word backward (on some systems this is ALT + B)
CTRL + [right arrow] — Move one word forward (on some systems this is ALT + F)
CTRL + U — (bash) Clear the characters on the line before the current cursor position
CTRL + U —(zsh) If you're using the zsh, this will clear the entire line
CTRL + K — Clear the characters on the line after the current cursor position
ESC + [backspace] — Delete the word in front of the cursor

Latency numbers every programmer should know

1 typical CPU instruction ..................   1 ns
L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs

SSD random read ........................ 150,000 ns = 150 µs

	library(raster)
	library(rayshader)
	#Load QGIS georeference image (see https://www.qgistutorials.com/en/docs/3/georeferencing_basics.html)
	testindia = raster::stack("1870_southern-india_modified.tif")

	#Set bounding box for final map (cut off edges without data, introduced via reprojection)
	india_bb = raster::extent(c(68,92,1,20))
	cropped_india = raster::crop(testindia, india_bb)

	#Convert to RGB array

	/********************
	* crispsContest.js *
	********************
	*
	* The Algorithm is almost in our grasp!
	* At long last, we will definitively establish
	* that 3SAT is solvable in polynomial time. It's
	* been a long, strange journey, but it will all be
	* worth it.
	*

	library(tidyverse)

	# using expression() for the text formatting:
	ggplot(mtcars,
	aes(disp,
	mpg)) +
	geom_point() +
	# ~ for spaces, and * for no-space between (unquoted) expressions
	ylab(expression(Anthropogenic~SO[4]^{"2-"}~(ngm^-3))) +
	xlab(expression(italic(delta)^13C[ap]"‰")) +

	require(ncdf4)
	require(ncdf4.helpers)
	require(data.table)

	## Get the name of the value vars in the nc file
	get_nc_value_name <- function(nc_file) {

	## Get names
	nc_obj <- nc_open(nc_file)
	name<-names(nc_obj$var)

	# Adapted from https://stackoverflow.com/a/7267364/1036500 by Andrie de Vries

	# This is it: theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))

	library(ggplot2)

	td <- expand.grid(
	hjust=c(0, 0.5, 1),
	vjust=c(0, 0.5, 1),
	angle=c(0, 45, 90),

	There are two ways for using tensorboard on a remote server:
	--1. Use sshfs.
	However, I found that this method is pretty slow, in particular if you want to compare several different long runs in tensorboard.
	--2. ssh with a port forwarding:
	ssh -L 16006:127.0.0.1:6006 user@remote
	Then, on your local machine simply open
	http://127.0.0.1:16006/

	#' When plotting multiple data series that share a common x axis but different y axes,
	#' we can just plot each graph separately. This suffers from the drawback that the shared axis will typically
	#' not align across graphs due to different plot margins.
	#' One easy solution is to reshape2::melt() the data and use ggplot2's facet_grid() mapping. However, there is
	#' no way to label individual y axes.
	#' facet_grid() and facet_wrap() were designed to plot small multiples, where both x- and y-axis ranges are
	#' shared acros all plots in the facetting. While the facet_ calls allow us to use different scales with
	#' the \code{scales = "free"} argument, they should not be used this way.
	#' A more robust approach is to the grid package grid.draw(), rbind() and ggplotGrob() to create a grid of
	#' individual plots where the plot axes are properly aligned within the grid.

	Byobu Commands
	==============

	byobu Screen manager


	Level 0 Commands (Quick Start)
	------------------------------

	<F2> Create a new window