Slater-Victoroff

def fired(inputs, threshold):
    if sum(inputs) > threshold:
        return True
    else: 
        return 0

Slater-Victoroff

type NeuralNet
	weight_matrices::Array{Array{FloatingPoint}}

	NeuralNet(layer_sizes::Array{Int64}) = new([
		rand(layer_sizes[i], layer_sizes[i+1]) for i in [1:length(layer_sizes)-1]
	])
end

function predict(input_vector::Array{Float64}, net::NeuralNet)
	unshift!(net.weight_matrices, input_vector)

Slater-Victoroff

import numpy as np

def transfer_function(x, y):
    return np.power(np.prod(x, axis=1)[:, None] * np.prod(y, axis=0), 1./x.shape[1])

def gnn(c):
    return  normalize([np.random.random(c[i] * c[i + 1]).reshape((c[i], c[i + 1])) for i in range(len(c) - 1)])

def predict(weights, input_vector, reverse=False):
    current_net = [input_vector] + weights

Slater-Victoroff

import collections

def rec_dict():
    """
    Just a recursive dictionary
    """
    return collections.defaultdict(rec_dict)


class Tree(object):

Slater-Victoroff

import flask
import sys
from flask import Flask, request
import random
from lxml import etree
import xmltodict
import numpy as np
import operator

Slater-Victoroff

from pyfuzz.generator import random_regex
from guess_language import guessLanguageName
from collections import Counter

def randomness_histogram(iterations, length):
    return Counter((guessLanguageName(random_regex(regex="[a-z \n]", length=length)) for i in xrange(length)))

print randomness_histogram(1000, 200).most_common(10) # returns the 10 most common languages
        

Slater-Victoroff

from collections import Counter
import cPickle as pickle
import random
import itertools
import string

def words(entry):
    return [word.lower().decode('ascii', 'ignore') for word in entry.split()]

def letters(entry):

Slater-Victoroff

def random_document(document_layout, type, **kwargs):
    document_layout.append("dummy_item")
    doc = lambda l:{l[i]:doc(l[i+1]) if isinstance(l[i+1],list) else random_item(type,**kwargs) for i in range(len(l)-1)}
    return doc(document_layout)

Slater-Victoroff

{
	"mappings": {
		"properties": {
			"searchable_text": {
				"type": "multi_field",
				"fields": {
					"full_words": {
						"type": "string",
						"store": "yes",
						"index": "analyzed",

Slater-Victoroff

from flask import Blueprint, request, redirect, render_template, url_for
from flask.views import MethodView

from flask.ext.mongoengine.wtf import model_form

from SpoolEngine.auth import requires_auth
from SpoolEngine.models import Post, BlogPost, Video, Image, Quote, Comment

admin = Blueprint('admin', __name__, template_folder='templates')