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@roblanf
roblanf / genome_plots.r
Last active September 4, 2016 09:23
Make plots about genome sequencing, size, and gene content
source("http://bioconductor.org/biocLite.R")
biocLite("genomes")
library(genomes)
library(ggplot2)
valid <- c("released", "created", "submitted")
data(proks)
update(proks)
curl -O -L http://sourceforge.net/projects/bowtie-bio/files/bowtie/0.12.7/bowtie-0.12.7-linux-x86_64.zip
@dan-blanchard
dan-blanchard / create_single_machine_sge.md
Last active March 20, 2022 10:40
How to setup a single-machine (Sun) Grid Engine installation for unit tests on Travis-CI

I recently needed a way to run unit tests on Travis for a project that uses Sun Grid Engine, Grid Map. Unfortunately, it seemed like no one had figured out how to set that up on Travis before (or simply create a single-machine installation without any user interaction). After hours of trial-and-error, I now know the secrets to making a single-machine installation of SGE that runs on Travis, and I'm sharing my script to prevent other people from going through the same frustrating experience.

To use the install_sge.sh script below, you just need to copy all of the files in this gist to a travis sub-directory directly under the root of your GitHub project, and add the following lines to your .travis.yml

before_install:
  - travis/install_sge.sh
  - export SGE_ROOT=/var/lib/gridengine
  - export SGE_CELL=default
  - export DRMAA_LIBRARY_PATH=/usr/lib/libdrmaa.so.1.0
@MohamedAlaa
MohamedAlaa / tmux-cheatsheet.markdown
Last active August 14, 2025 02:55
tmux shortcuts & cheatsheet

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname
@kohlmeier
kohlmeier / ka_bnet_numpy.py
Created March 26, 2012 21:59
Bayes net example in Python with Khan Academy data
#!/usr/bin/env python
from numpy import asmatrix, asarray, ones, zeros, mean, sum, arange, prod, dot, loadtxt
from numpy.random import random, randint
import pickle
MISSING_VALUE = -1 # a constant I will use to denote missing integer values
def impute_hidden_node(E, I, theta, sample_hidden):