mayblue9

Liquid Fill Gauge v1.1 - 7/14/2015

Changes:

Added support for updating the gauge value after loading is complete. The loadLiquidFillGauge method now returns an object with an update method which allows the gauge value to be changed. Click any of the gauges above to randomly update their value.

Configurable features include:

Changeable min/max values.
All colors.

The PopCha! Movie Network

A visualization of similarity between movies by means of a network graph

Similarity data taken from [PopCha!] 1 recommender engine (R*)
Movie info from [The Movie Database] [3]
Visualization done in JavaScript with [D3.js] [2]

This example shows how to interact with D3.js to create a Bi-Directional Tree (a variation of robschmuecker@7880033)

The tree shows the dependencies related to D3 development:

The upward branches are the repos that D3 is dependent on, from a direct dependency to further parent files that these repos were dependent on.
The lower branches are repos that are dependent on D3, and the children files that are dependent on these repos.

The main logic to pull these dependencies and generating tree data is in [my GitHub repo] (https://github.com/shunpochang/d3tree/tree/master/get_tree_from_git), where package.json and bower.json files (to include both NPM and Bower installation) are crawled to get the top matching libraries.

Tree interaction and display:

To quickly unfold all branches, click on the label "Click to unfold/expand all" twice to first collapse and then expand, and refresh the browser if it does not work properly.

An interactive version of a Reingold–Tilford tree. Click on the nodes to expand or collapse. From http://bl.ocks.org/mbostock/4339083

Added search, expand and styling of results and its ancestors. Visible from http://bl.ocks.org/PBrockmann/0f22818096428b12ea23

This is an example of using ReactJs to render a force directed network graph. D3 performs all the positional calculations for each node and React handles rendering.

	import gensim
	import codecs
	from gensim.models import Word2Vec
	import json

	def export_to_file(path_to_model, output_file):
	output = codecs.open(output_file, 'w' , 'utf-8')
	model = Word2Vec.load_word2vec_format(path_to_model, binary=True)
	vocab = model.vocab
	for mid in vocab:

	<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN"
	"http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">

	<html xmlns="http://www.w3.org/1999/xhtml"
	xml:lang="en-US"
	lang="en-US">
	<head profile="http://www.w3.org/2005/10/profile">
	<title>My Force Directed Graph</title>
	<meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1" />
	<meta name="Description" content="This page tries to mix charts with html formatting and layout constructs." />

	{
	"nodes":[
	{"name":"node1","group":1},
	{"name":"node2","group":2},
	{"name":"node3","group":2},
	{"name":"node4","group":3}
	],
	"links":[
	{"source":2,"target":1,"weight":1},
	{"source":0,"target":2,"weight":3}