axiak

var result = {}
_.each(input, function (key, value) { if (value !== false) this[key] = value; }, result);

axiak

SEGMENT_TABLE = {
    1: (39.5, 40),
    2: (40, 50),
}


def get_segment(position):
    for key, (lower, upper) in SEGMENT_TABLE.items():
        if lower <= position < upper:
            return key

axiak

return unless Modernizr.svg


class NavVisualization
  @links = [
    source: "_root"
    target: "Home"
    thickness: 7
  ,
    source: "Home"

axiak

pwned

axiak

border-color: #29447E #29447E #1A356E;
color: white;
background-color: #5B74A8;
background-image: -webkit-gradient(linear, 0 0, 0 100%, from(#637BAD), to(#5872A7));
background-image: -moz-linear-gradient(#637BAD, #5872A7);
background-image: -o-linear-gradient(#637BAD, #5872A7);
background-image: linear-gradient(#637BAD, #5872A7);

axiak

class String
    def incord(x)
        (self.ord + x).chr
    end
end


p 'a'.incord 2

axiak

class String
    def my_reverse
        reversed = []
        self.each_char do |char|
            reversed.unshift(char)
        end
        reversed.join('')
    end
end

axiak

def my_reverse(a)
    if a.empty?
        []
    else
        last = a.pop()
        [last] + my_reverse(a)
    end
end

p my_reverse([1, 2, 3])

axiak

from math import sqrt

def confidence_bounds(ups, downs):
    #stolen from reddit!
    n = ups + downs
    if n == 0:
        return 0, 0
    z = 1.0 #1.0 = 85%, 1.6 = 95%
    phat = float(ups) / n
    confidence_positive = sqrt(phat+z*z/(2*n)-z*((phat*(1-phat)+z*z/(4*n))/n))/(1+z*z/n)

axiak

class NameDenormalizer(object):
    def __init__(self, filename=None):
        filename = filename or 'names1.1.csv'
        lookup = collections.defaultdict(list)
        with open(filename) as f:
            reader = csv.reader(f)
            for line in reader:
                matches = set(line)
                for match in matches: