markovStat

#Markov and stat anaylsis

class markovStat:
	def __init__(self):
		self.table = {} # This has key:pair value of letter -> list of letters most probable
	def buildMarkovChains(self, wordList):

	def anaylseWord(self, word, threshold):
		#Take word. For every time that it each letter follows the most probable word, score is 1.
		#If the word follows the next most probable, the score is (1/(number of letters in chain) * position) in the chain
		wordScore = 0.0		
		for i in range(len(word)):
			if i == 0 or i == len(word)-1:
				continue
			wordScore+=self.getScore(word, i)
		wordScore = wordScore/len(word)
		print "[-] Word \'{0}\' scored {1} (Closer to 1 is more human, smaller is less human)".format(word, 

	def getScore(self, word, index):
		currentChar = word[index]
		nextChar = word[index+1]
		chain = self.table.get(currentChar)
		if (chain != None):
			score = -1.00
			for i in range(len(chain)):#Go through the possible characters and check to see if ours is there
				if chain[i] == nextChar:
					score = len(chain) - i
					break
			return score