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font color: black
background color: #F5F2E7

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#algs4partI-class

def str2nums(s):
    return [ord(x)-ord('A') for x in s.split()]

def nums2str(l):
    return ' '.join(chr(x + ord('A')) for x in l)

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%s

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%s

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%s

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> This is a Quix Command File
>
> For the syntax of this file, please refer to http://quixapp.com/syntax/
>

@Basic commands
@These are the most basic commands Quix offers, but possibly also the most powerful ones.
a       http://www.amazon.com/s/?field-keywords=%s							Amazon Search
d       http://www.google.com/search?q=define:%s							Google Define a word
dict	http://www.google.com/dictionary?langpair=en%7Cen&q=%s&hl=en&aq=f	Google Dictionary for a word

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#!/usr/bin/env python
"""(c) gorlum0 [at] gmail.com"""
import random
from sys import maxsize as inf

def merge_sort(A):
    """merge-sort which counts inversions"""
    def merge(L, R):
        m = len(L)-1
        B = []

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#!/usr/bin/env python
from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from scipy import optimize
from numpy import newaxis, r_, c_, mat, e
from numpy.linalg import *

def plotData(X, y):
    pos = (y.ravel() == 1).nonzero()

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#!/usr/bin/env python
from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from scipy import optimize
from numpy import newaxis, r_, c_, mat, e
from numpy.linalg import *

def plotData(X, y):
    #pos = (y.ravel() == 1).nonzero()

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#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from numpy import newaxis, r_, c_, mat
from numpy.linalg import *

def featureNormalize(X):
    X_norm = X.A
    m = X.shape[0]