Ismael-VC

#Importing Requests package
Pkg.add("Requests")
using Requests.get;

import JSON;

url = "http://query.yahooapis.com/v1/public/yql?q=select%20DaysRange%20from%20yahoo.finance.quotes%20where%20symbol%20in%20%28%22EBAY%22,%22GOOG%22%29%20&env=http://datatables.org/alltables.env&format=json";

#Reads the data from HTTP URL
es = get(url);

Ismael-VC

using SenseHat
import SenseHat: RGB565

function spooky(decay, arriv, refresh)
    x = rand()
    while true
        x *= exp(-decay*refresh)
        if rand() < arriv*refresh
            x += (1-x)*rand()
        end

Ismael-VC

using Plots;glvisualize()
using GLVisualize, FileIO, Colors, Images
using GeometryTypes, GLAbstraction

x = ["(｡◕‿◕｡)", "◔ ⌣ ◔","(づ｡◕‿‿◕｡)づ", "┬──┬ ノ( ゜-゜ノ)", "(╯°□°）╯︵ ┻━┻", "¯\\_(ツ)_/¯"]
y = [-4, -3, -2, -1, 6, 0]
scatter(x, y)
t = bounce(linspace(-1.0f0,1f0, 20))
translation = map(t) do t
    rotationmatrix_y(1f0)*rotationmatrix_z(deg2rad(90f0)) * translationmatrix(Vec3f0(3,3,t))

Ismael-VC

#upper triangular indices - iterates over upper triangular indices in a list of
#indices.
type uppertriangular; iterable; end

Base.start(x::uppertriangular) = (1, 1)
function Base.next(x::uppertriangular, state)
  (idx1, idx2) = state
  next1 = idx1
  next2 = idx2 + 1
  if next2 > length(x.iterable)

Ismael-VC

if VERSION > v"0.4.0-dev+4268"
	const marcoexpandkeys = Dict{Any,Any}("^I" => function (s,o...)
           if !isempty(s)
               
                   line = parse(Base.LineEdit.input_string(s))
                   s.kill_buffer=Base.LineEdit.input_string(s)
                   Base.LineEdit.edit_clear(s)
                   Base.LineEdit.edit_insert(s,string(macroexpand(line)))
               
           end

Ismael-VC

# Julia is fully unicode aware and if you use your variable and function
# names just right, you can express your anger like no other language.

⋰┛ಠДಠ┛⋱彡┻━┻(n) = n < 2 ? n : ⋰┛ಠДಠ┛⋱彡┻━┻(n - 1) + ⋰┛ಠДಠ┛⋱彡┻━┻(n - 2)

@elapsed ⋰┛ಠДಠ┛⋱彡┻━┻(25)  # 0.00266

Ismael-VC

# Fortran-like array with arbitrary starting indices
#
# usage:
#
# julia> include("FArray.jl")
# size (generic function with 51 methods)
# 
# julia> y = FArray(Float64, -1:1, -7:7, -128:512, -5:5, -1:1, -3:3, -2:2, -1:1);
# 
# julia> y[-1,-7,-128,-5,-1,-3,-2,-1] = 14

Ismael-VC

# Installation: 
# - Put this in your .bash_profile
# - Replace my directory with your exobrain directory on line 10
#
# What you get:
#    A Jupyter notebook open on a well-defined port that is always
#    on for exobrain-ing your ideas...

exec 6<>/dev/tcp/localhost/10000 || (
    source activate py27 && 

Ismael-VC

# Requested gist of code to produce:
#   https://www.scribd.com/doc/271871142/Julia-Type-Hierarchy
# 
# I just redirected the output to a dot file, then executed:
#    dot -Tpdf julia.dot -o julia.pdf
function print_type_tree(t, parent=Any, seen=Set{DataType}())
    # Avoid redundant edges.
    t ∈ seen && return 
    push!(seen, t)
    

Ismael-VC

# This code is part of a presentation on streaming analytics in Julia
# It was inspired by a number of individuals and makes use of some of their ideas
#     1. FastML.com got me thinking about inline processing after 
#        reading his great Vowpal Wabbit posts
#     2. John Lanford and his fantastic Vowpal Wabbit library. 
#        Check out his NYU video course to learn more (see below)
#     3. John Myles White's presentation on online SDG and his StreamStats.jl library 
# Thank you all!