- Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
- Models and Issues in Data Stream Systems
- Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
- Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
- [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t
;; 0: | |
(-> Math/E Math/toRadians Math/round) | |
;; 1: | |
(-> Math/E Math/log Math/round) | |
;; 2: | |
(-> Math/E Math/sqrt Math/round) | |
;; 3: | |
(-> Math/E Math/round) | |
;; 4: | |
(-> Math/PI Math/ceil Math/round) |
From Wikipedia:
In mathematics, a Fourier series decomposes periodic functions or periodic signals into the sum of a (possibly infinite) set of simple oscillating functions, namely sines and cosines (or complex exponentials).
Use the bottom right form to change the visualized serie.
// data comes from here http://stat-computing.org/dataexpo/2009/the-data.html | |
// download 1994.csv.bz2 and unpack by running: cat 1994.csv.bz2 | bzip2 -d > 1994.csv | |
// 1994.csv should be ~5.2 million lines and 500MB | |
// importing all rows into leveldb took ~50 seconds on my machine | |
// there are two main techniques at work here: | |
// 1: never create JS objects, leave the data as binary the entire time (binary-split does this) | |
// 2: group lines into 16 MB batches, to take advantage of leveldbs batch API (byte-stream does this) | |
var level = require('level') |
// This is *not* valid Go! | |
func Map(f func(A) B, xs []A) []B { | |
ys := make([]B, len(xs)) | |
for i, x := range xs { | |
ys[i] = f(x) | |
} | |
return ys | |
} | |
Map(func(x int) int { return x * x }, []int{1, 2, 3}) |
You could have postgre installed on localhost with password (or without user or password seted after instalation) but if we are developing we really don't need password, so configuring postgre server without password for all your rails project is usefull.
- postgresql
- postgresql-client
- libpq-dev
The range sliders at the top change the values for the force-directed algorithm and the buttons load new graphs and apply various techniques. This will hopefully serve as a tool for teaching network analysis and visualization principles during my Gephi courses and general Networks in the Humanities presentations.
Notice this includes a pretty straightforward way to load CSV node and edge lists as exported from Gephi.
It also includes a pathfinding algorithm built for the standard data structure of force-directed networks in D3. This requires the addition of .id attributes for the nodes, however.
Now with Clustering Coefficients!
Also, it loads images for nodes but the images are not in the gist. The code also refers to different network types but the data files on Gist only refer to the transportation network.
license: gpl-3.0 |
function sample(list, m) { | |
var n = list.length; | |
if (m > n) return void console && | |
console.log('list length must be > sample'); | |
var sampleList = []; | |
for (var i = n - m; i < n; i++) { | |
var item = list[~~(Math.random() * i)]; | |
if (sampleList.indexOf(item) !== -1) | |
sampleList.push(list[i]); | |
else |