SangHee Kim sangheestyle

wget http://hivelocity.dl.sourceforge.net/project/math-atlas/Stable/3.10.2/atlas3.10.2.tar.bz2
tar jxf atlas3.10.2.tar.bz2

  288  tar jxf atlas3.10.2.tar.bz2 
  289  ls
  290  cd ATLAS/
  291  ls
  292  cd ..
  293  clear

Object selection is tough, particularly when the things you'd like to select are moving around (like nodes in a force-directed layout, perhaps). Allowing a user the fudge factor of an area cursor helps, but can get in the way when targets are small enough. The use of a Voronoi tessellation promises a map of closest node for any given point.

This example illustrates the use of a Voronoi overlay to clip nodes in a force-directed simulation. By using the Voronoi shapes as the clipping path the nodes themselves can be drawn much simpler.

This builds on these two examples from Mike Bostock on force-directed graphs and voronoi tesselation, as well as Nate Vack's Voronoi selection example here and this first pass at an integration from Christopher Manning.

A simple editor to allow the manipulation of force-directed graph parameters.

This example is based on Mike Bostock's block 4062045.

This simple force-directed graph shows character co-occurence in Les Misérables. A physical simulation of charged particles and springs places related characters in closer proximity, while unrelated characters are farther apart. Layout algorithm inspired by Tim Dwyer and Thomas Jakobsen. Data based on character coappearence in Victor Hugo's Les Misérables, compiled by Donald Knuth.

A simple example to show developers' relationship by analyzing commits in AOSP frameworks/base repository. Only commits submitted within past 2 months were used for generating this relationship. You might want to click 'open in a new window' link (right) to see this on larger window.

This graph was built by the following.

making edges by developer to his or her modified file (bipartite graph)
making projection by developer nodes

Each dot shows each developer and each color of circle represents each company which hires the developer. You can generate the json file by flatiron.

This example is based on Couchand's block 6495846.

	authors=(`git log --format='%ae' \| sort -u`)
	for author in ${author[*]}
	do
	files=(`git log --no-merges --stat --author="$author" --name-only --pretty=format:"" \| sort -u`)
	for file in ${files[*]}
	do
	echo $author $file
	done
	done

	2 1
	3 1
	3 2
	4 1
	4 2
	4 3
	5 1
	6 1
	7 1
	7 5

	from pylab import *
	import pandas as pd


	df =pd.read_csv("PS04_1a.dat", names=range(1,35))
	p1 = pd.DataFrame({'max': df.max(), 'mean':df.mean()})
	p1.plot(marker='.', markersize=10, title='')

	CREATE KEYSPACE unittest WITH REPLICATION = { 'class' : 'SimpleStrategy', 'replication_factor' : 1 };

	USE unittest;

	CREATE TABLE commits (
	id text,
	path text,
	author_email text,
	author_name text,
	subject text,

	import numpy as np
	import scipy as sc
	import networkx as nx
	from matplotlib.colors import LogNorm
	from pylab import *


	def sample(n):
	m = sc.misc.comb(n, 2)
	r_vals = np.random.random(m)

	#!/bin/bash
	# Get the scope of given class in a given file
	# Then show the evelution of the class via git log -L
	# usage: show_scope [classname] [filename]
	# cname='class HttpAuthHandler'
	# fname='HttpAuthHandler.java'

	cname=$1
	fname=$2
	begin=$(grep -n ".$cname." $fname \| grep -Eo "^[0-9]{1,5}")