disulfidebond

Overview

This markdown file contains the steps involved in configuring a new computer, runnning Ubuntu 16.04, to run ONT Guppy GPU basecalling.

Prerequisites

• CUDA must be installed, which can be simple or extremely difficult, depending on if the CUDA gods smile on you.
• The computer must be running Ubuntu 16.04 'xenial', with all updates installed.

Steps

• The steps in the installation manual were followed as directed.

thomasp85

---
title: "PDF Animation Test"
output: pdf_document
header-includes:
   - \usepackage{animate}
---

`gganimate` now supports animations inside PDF documents. This feature is only 
viewable with Acrobat Reader, however. Remember to include 
`\usepackage{animate}` in the preamble and set `fig.show='animate'` in the chunk

mohanpedala

Table of Contents

• set -e, -u, -x, -o pipefail
• set -e
• set -x
• set -u
• set -o pipefail
• Setting IFS
• Original Reference

set -e, -u, -x, -o pipefail

thomasp85

library(gganimate) # thomasp85/gganimate
library(cartogram)
library(geogrid) # Need github version jbaileyh/geogrid
library(rnaturalearth)
library(sf)
library(scico)

us <- ne_states('united states of america', returnclass = 'sf')
us <- us[!us$woe_name %in% c('Alaska', 'Hawaii'), ]
us <- st_transform(us, '+proj=eqdc +lat_0=39 +lon_0=-96 +lat_1=33 +lat_2=45 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs')

thomasp85

library(ggplot2)
library(gganimate)
library(sf)
earth <- sf::st_as_sf(rnaturalearth::countries110)
views <- data.frame(rbind(
  st_bbox(earth[earth$name == 'Denmark',]),
  st_bbox(earth[earth$name == 'Australia',])
))
p <- ggplot() + 
  geom_sf(data = earth, fill = 'white') + 

thomasp85

library(sf)
library(ggplot2)
library(gganimate)

# Data from personal correspondance

# Collapse all dates to the same year
d$year <- format(d$date, '%Y')
d$stand_time <- as.POSIXct(paste0('2000-', format(d$date, '%m-%d %T')))

thomasp85

library(gapminder)
library(ggplot2)
library(gganimate)

p <- ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, colour = country)) +
  geom_point(alpha = 0.7) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  facet_wrap(~continent) +

thomasp85

library(ggraph)
library(tidygraph)
library(gganimate)

# Data from http://konect.uni-koblenz.de/networks/sociopatterns-infectious
infect <- read.table('out.sociopatterns-infectious', skip = 2, sep = ' ', stringsAsFactors = FALSE)
infect$V3 <- NULL
names(infect) <- c('from', 'to', 'time')
infect$time <- as.POSIXct(infect$time, origin = Sys.time() - as.numeric(Sys.time()))

DavisVaughan

# This example demonstrates running furrr code distributed on 2 AWS instances ("nodes").

# The instances have already been created.

library(future)
library(furrr)

# Two t2.micro AWS instances
# Created from http://www.louisaslett.com/RStudio_AMI/
public_ip <- c("34.205.155.182", "34.201.26.217")

eliocamp

library(ggplot2)

url <- "https://ih0.redbubble.net/image.512523322.6908/flat,800x800,075,f.jpg"
file <- tempfile()
download.file(url, file)
im <- jpeg::readJPEG(file)
im <- apply(im, c(1, 2), sum)
im <- im/3
ys <- nrow(im)
xs <- ncol(im)