sl8r000

import sys
import random

if __name__ == "__main__":
    state, num_steps = sys.argv[1], int(sys.argv[2])
    count = dict()
    count['a'], count['b'] = 0, 0

    for i in range(num_steps):
        count[state] += 1

sl8r000

$ python markov.py a 100
a 0.72
b 0.28
$ python markov.py a 200
a 0.74
b 0.26
$ python markov.py a 1000
a 0.748
b 0.252
$ python markov.py a 10000

sl8r000

$ python
>>> import numpy
>>> P = array([[1.0/3, 2.0/3], [1.0/4, 3.0/4]])
>>> P
array([[ 0.33333333,  0.66666667],
       [ 0.25      ,  0.75      ]])
>>> numpy.linalg.matrix_power(P, 2)
array([[ 0.27777778,  0.72222222],
       [ 0.27083333,  0.72916667]])
>>> numpy.linalg.matrix_power(P, 3)

sl8r000

import sys
import random
from numpy import *
import time

class Markov(object):
	def __init__(self, transition_matrix, start_state):
		self.P = transition_matrix
		self.state = start_state

sl8r000

$ python Theorem2_1.py 0 10
1.7
$ python Theorem2_1.py 0 100
1.88
$ python Theorem2_1.py 0 1000
1.832
$ python Theorem2_1.py 0 10000
1.8291
$ python Theorem2_1.py 0 100000
1.81673

sl8r000

Slaters-MacBook-Pro:~ sstich$ ssh ubuntu@ec2-184-73-13-20.compute-1.amazonaws.com
ubuntu@ec2-184-73-13-20.compute-1.amazonaws.com's password: 
Welcome to Ubuntu 12.04.1 LTS (GNU/Linux 3.2.0-31-virtual x86_64)

 * Documentation:  https://help.ubuntu.com/

  System information as of Sat Dec  1 19:59:27 UTC 2012

  System load:  0.0               Processes:           58
  Usage of /:   11.3% of 7.87GB   Users logged in:     0

sl8r000

import math

class NearestNeighbor(object):
    def __init__(self):
        self._known_rows = []
        
    def learn_from_row(self, row):
        self._known_rows.append(row)
        
    def predict_missing_column(

sl8r000

import urllib2
import json
import time

class QueryBuilder(object):
    BASE_URL = 'https://api.twitter.com/1/statuses/user_timeline.json?'
    DEFAULT_MAX_COUNT = 200
    
    def __init__(self):
        self._query_params = dict()

sl8r000

import random

import twitter_grab

SCREEN_NAMES = [
                'GineokwKoenig',
                'RealNichelle',
                'TheRealNimoy',
                'WilliamShatner',
                'GeorgeTakei',

sl8r000

import os
import sys
path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../..'))
if not path in sys.path:
    sys.path.insert(1, path)
del path

import knn
from knn.nearest_neighbor1 import NearestNeighbor