Perry samesense

A good commit message looks like this:

Header line: explaining the commit in one line

Body of commit message is a few lines of text, explaining things
in more detail, possibly giving some background about the issue
being fixed, etc etc.

The body of the commit message can be several paragraphs, and
please do proper word-wrap and keep columns shorter than about

Copy, with line wrapping!

If you've been trying to copy/paste text from a multi-pane tmux session with the mouse, you've probably been pretty pissed at the blissful ignorance a terminal application has of the rodent in your hand.

The alternative, which is quote-unqoute native copy/pasting using copy-mode takes a bit to get used to. So this is one solution for copying and pasting lines from a session with correct line wrapping behaviour, albeit keyboard only.

Disclaimer

Since copy-mode has similar concepts of marks, regions, and temp buffers to Emacs .. you'll probably find it straight forward if you're familar with Emacsen. For people using vi-mode in tmux, the same still applies but obviously the default key bindings will differ alot from what I show below.

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

Multiple SSH Keys settings for different github account

create different public key

create different ssh key according the article Mac Set-Up Git

$ ssh-keygen -t rsa -C "your_email@youremail.com"

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

A dendrogram is a common way to represent hierarchical data. For Python users, Scipy has a hierarchical clustering module that performs hierarchical clustering and outputs the results as dendrogram plots via matplotlib. When it's time to make a prettier, more customized, or web-version of the dendogram, however, it can be tricky to use Scipy's dendrogram to create a suitable visualization. My preferred method of visualizing data -- especially on the web -- is D3. This example includes a script to convert a Scipy dendrogram into JSON format used by D3's cluster method.

In the example, I cluster six genes by their expression values from two experiments. You can easily replace that data with your own, larger data set, to harness the power of both Scipy and D3 for analyzing hierarchical data. The D3 code I used to generate this example is straigh

	from paver.easy import *
	import os.path, os
	import csv
	import ruffus
	from collections import defaultdict
	from types import GeneratorType, DictType
	from itertools import ifilter


	options(

	<!DOCTYPE html>
	<html >
	<head>
	<script type="text/javascript" src="http://mbostock.github.com/d3/d3.js"></script>
	</head>
	<body>
	<div class="example_div"></div>
	<script type="text/javascript">
	var tooltip = d3.select("body")
	.append("div")

	# coding=UTF8
	#########################################################################
	# This class is to help sklearn to handle statistical process #
	# Author: Joon Lim from Master of Science in Analytics at Northwestern #
	# Date: 04.23.2013 #
	#########################################################################

	''' this Module is built on top of numpy and sklearn. '''

	infinite_defaultdict = lambda: defaultdict(infinite_defaultdict)
	d = infinite_defaultdict()
	d['x']['y']['z'] = 10