Write a program that solves the classic “random writer” problem. This problem de

Question

Write a program that solves the classic “random writer” problem. This problem deals with reading input files of text and examining the frequencies of characters. On the basis of those frequencies, you can generate randomized output that appears to match the writing style of the original document. The longer the chains you link together, the more accurate the random text will sound. For example, level 4 random text (text with chains of 4 letters long) generated from Tom Sawyer might look like this: “en themself, Mr. Welshman, but him awoke, the balmy shore. I’ll give him that he couple overy because in the slated snufflindeed structure’s kind was rath. She said that the wound the door a fever eyes that WITH him.” Level 10 random text from the same source might look like this: “you understanding that they don’t come around in the cave should get the word beauteous was over-fondled, and that together and decided that he might as we used to do it’s nobby fun. I’ll learn you.” Search the internet for “Random Writer” to learn more about this problem, such as the specification posed by computer scientist Joseph Zachary.

Explanation / Answer

################### pyhton code to solve random writer probelm ################
##### make sure you have all the modules before running the code ###############

#!/usr/bin/env python

from pyquery import PyQuery as pq
from lxml import etree

import sys
import os
import re
import datetime
import operator

import random
PROJECT_PATH = os.path.realpath(os.path.dirname(__file__))

if len(sys.argv) != 3:
print 'usage: ./random_writer <text file> <order[1-10]>'

seed = ''
ORDER = int(sys.argv[2])
FILENAME = sys.argv[1]

# This is a dictionary that maps a phrase of ORDER length to a tuple of the number of
# times it has occured and a dictionary of characters that have followed and the number
# of times they've occured
#
# Example:
# occurrences[fragment] = (number_of_times_fragment_has_occured_in_text, {characters_that_follow_the_fragment: number_of_times_those_characters_occurred})
occurrences = {}

try:
# Open text file for reading
f = open(FILENAME, 'r')
except IOError:
print 'No file found. Exiting'
sys.exit()

text = f.read()
f.close()
# Go through each character in the inputted text
for index in range(len(text)-ORDER -1):
fragment = text[index:index+ORDER] #the size of the fragment depends on the ORDER entered, the higher the order the more "sense" the output will have
following_char = text[index+ORDER]
if fragment in occurrences:
n_occurrences_total, following_char_dict = occurrences[fragment]
n_occurrences_total += 1
if following_char in following_char_dict:
following_char_dict[following_char] += 1
else:
following_char_dict[following_char] = 1
occurrences[fragment] = (n_occurrences_total, following_char_dict)
else:
following_char_dict = {following_char:1}
occurrences[fragment] = (1, following_char_dict)

max_fragment = ''
max_occurrences = -1
# Find the most frequent frequently occurring fragment
for fragment in occurrences:
n_occurrences, following_char_dict = occurrences[fragment]
  
if n_occurrences > max_occurrences:
max_occurrences = n_occurrences
max_fragment = fragment

print max_fragment
seed = max_fragment
new_text = seed
random.seed()
max_iterations = 20000 # If you have large input this will cut off the number of iterations so the output isn't really long,
iterations = 0
# Create the output text
while True:
if seed not in occurrences or iterations == max_iterations:
break
n_occurrences, following_char_dict = occurrences[seed]
char_list = []
total_hits = 0
for char in following_char_dict:
total_hits += following_char_dict[char]
char_list.append((char, total_hits))
# Randomly determine the next seed
index = random.randint(0, total_hits)
for char, hits in char_list:
if index < hits:
new_text += char
# Take one char off the start and add the randomly chosen following character to create the new seed
seed = seed[1:] + char
break
iterations += 1

print new_text
  
  

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