roblanf

Below is a method to install Python 2.7 on Windows, using the Python distribution from python.org. Please note that THERE ARE EASIER WAYS THAN THIS. E.g. you can use the Anaconda distribution, which is one click, and has a nice windows installer. To do that, ignore everything below and just click here:

http://www.continuum.io/downloads

If for some reason you want to do it the slightly harder way:

1. Install Python ================= Download the Python installer from here: http://www.python.org/getit/. Make sure you download version 2.7. The instructions that follow assume you have installed python in its default folder, which is c:\Python27.

roblanf

# Create a scatterplot with any species as the data points.
# To choose your species, go here: http://phylopic.org/ , then enter the name of the spp you want. Click on the image and click 'thumbnail', click on the picture, and then copy the link in the address bar of your browser. It should end with 'thumb.png' Paste it in place of the link below.

library(TeachingDemos)
library(png)

# Paste a link to a png of your favourite animal here. This will be an aardvarkplot. Make sure it ends with .thumb.png.
# If it doesn't end with .thumb.png reread the instructions above and try again.
link = "http://phylopic.org/assets/images/submissions/cfee2dca-3767-46b8-8d03-bd8f46e79e9e.thumb.png"

roblanf

source("http://bioconductor.org/biocLite.R")
biocLite("genomes")

library(genomes)
library(ggplot2)

valid <- c("released", "created", "submitted")

data(proks)
update(proks)

roblanf

library(ggplot2)
library(reshape2)
library(plyr)

all = read.csv("genderdata.csv")

######################## Plot 1 ###############################################
# The raw data: number of men and women in each role, by year

# we need to do a bit of work so we can plot roles in the right order

roblanf

library(primes)
library(coda)
library(parallel)
library(ggplot2)

# set this to the number of processors on your machine
processors = 4

remainder <- function(number, divisor){ return(number%%divisor) }

roblanf

library(primes)
library(coda)
library(parallel)
library(ggplot2)

# set this to the number of processors on your machine
processors = 4

remainder <- function(number, divisor){ return(number%%divisor) }

roblanf

library(primes)
library(coda)
library(parallel)
library(ggplot2)


# set this to the number of processors on your machine
processors = 4

remainders <- function(divisor, numbers){

roblanf

roblanf

# build the map for R9.5 flowcell, as a long-form dataframe that translates
# channels into rows and columns on the flowcell. Good for plotting in R.
p1 = data.frame(channel=33:64, row=rep(1:4, each=8), col=rep(1:8, 4))
p2 = data.frame(channel=481:512, row=rep(5:8, each=8), col=rep(1:8, 4))
p3 = data.frame(channel=417:448, row=rep(9:12, each=8), col=rep(1:8, 4))
p4 = data.frame(channel=353:384, row=rep(13:16, each=8), col=rep(1:8, 4))
p5 = data.frame(channel=289:320, row=rep(17:20, each=8), col=rep(1:8, 4))
p6 = data.frame(channel=225:256, row=rep(21:24, each=8), col=rep(1:8, 4))
p7 = data.frame(channel=161:192, row=rep(25:28, each=8), col=rep(1:8, 4))
p8 = data.frame(channel=97:128, row=rep(29:32, each=8), col=rep(1:8, 4))

roblanf

echo "copying source pics"
mkdir source_pics
cp ~/pikrellcam/media/timelapse/* source_pics
cd source_pics

echo "renaming"
mkdir renamed
counter=1
ls -1tr *.jpg | while read filename; do cp $filename renamed/$(printf %05d $counter)_$filename; ((cou\
nter++)); done