CristinaSolana

1. Clone your fork:

git clone [email protected]:YOUR-USERNAME/YOUR-FORKED-REPO.git

2. Add remote from original repository in your forked repository:

cd into/cloned/fork-repo
git remote add upstream git://github.com/ORIGINAL-DEV-USERNAME/REPO-YOU-FORKED-FROM.git
git fetch upstream

henrik

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

neggert

import matplotlib.pyplot as plt
import numpy as np
import inspect

def hist_errorbars( data, xerrs=True, *args, **kwargs) :
    """Plot a histogram with error bars. Accepts any kwarg accepted by either numpy.histogram or pyplot.errorbar"""
    # pop off normed kwarg, since we want to handle it specially
    norm = False
    if 'normed' in kwargs.keys() :
        norm = kwargs.pop('normed')

sumardi

# New repository
mkdir <repo> && cd <repo>
git init
git remote add –f <name> <url>
git config core.sparsecheckout true
echo some/dir/ >> .git/info/sparse-checkout
echo another/sub/tree >> .git/info/sparse-checkout
git pull <remote> <branch>

# Existing repository

hofmannsven

Git

Global Settings

• Related Setup: https://gist.github.com/hofmannsven/6814278
• Related Pro Tips: https://ochronus.com/git-tips-from-the-trenches/
• Interactive Beginners Tutorial: http://try.github.io/
• Git Cheatsheet by GitHub: https://services.github.com/on-demand/downloads/github-git-cheat-sheet/

Reminder

Press minus + shift + s and return to chop/fold long lines!

DavidWalz

import scipy.stats
def clopper_pearson(k,n,alpha=0.32):
    """
    http://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval
    alpha confidence intervals for a binomial distribution of k expected successes on n trials
    Clopper Pearson intervals are a conservative estimate.
    """
    lo = scipy.stats.beta.ppf(alpha/2, k, n-k+1)
    hi = scipy.stats.beta.ppf(1 - alpha/2, k+1, n-k)
    return lo, hi

smithdanielle

# check.packages function: install and load multiple R packages.
# Check to see if packages are installed. Install them if they are not, then load them into the R session.
check.packages <- function(pkg){
    new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
    if (length(new.pkg)) 
        install.packages(new.pkg, dependencies = TRUE)
    sapply(pkg, require, character.only = TRUE)
}

# Usage example

nicktoumpelis

git clean -xfd
git submodule foreach --recursive git clean -xfd
git reset --hard
git submodule foreach --recursive git reset --hard
git submodule update --init --recursive

mitchwongho

# Assuming an Ubuntu Docker image
$ docker run -it <image> /bin/bash

cben