import itertools
import Utterance
import PossibleWorld
#this table contains all the possible worlds
class Table:
	def __init__(self, possible_worlds, U, W):
		self.size=len(possible_worlds)
		self.possible_worlds=possible_worlds
		self.column_sums=[0]*self.size
		self.row_sums=[0]*self.size
		self.utterances=U
		self.worlds=W
		self.fill_sums(possible_worlds)

	#this adds up all of the possible world probabilities in the rows and columns of a table
	def fill_sums(self, possible_worlds):
		for world in possible_worlds:
			row=world.row
			column=world.column
			self.column_sums[column]+=world.probability
			self.row_sums[row]+=world.probability


	#re-adds up all of the columns and rows so that normalization is accurate
	def re_sum(self):
		self.column_sums=[0]*self.size
		self.row_sums=[0]*self.size
		self.fill_sums(self.possible_worlds)


	#important function for normalizing so that we can look at probability distributions
	def normalize(self, column):
		self.re_sum()
		for world in self.possible_worlds:
			if column:
				n=world.column 
				if world.probability==0 or self.column_sums[n]==0:
					pass
				else:
					world.probability=(world.probability)/(self.column_sums[n])
			else:
				n=world.row 
				if world.probability==0 or self.row_sums[n]==0:
					pass
				else:
					world.probability=(world.probability)/(self.row_sums[n])

	def copy(self):
		output=Table(self.possible_worlds, self.utterances, self.worlds)
		return output

67a1c9e1705d00baf90eafe7394b0f28ace2f82e
<mask token>


class Table:
    <mask token>

    def fill_sums(self, possible_worlds):
        for world in possible_worlds:
            row = world.row
            column = world.column
            self.column_sums[column] += world.probability
            self.row_sums[row] += world.probability
    <mask token>

    def normalize(self, column):
        self.re_sum()
        for world in self.possible_worlds:
            if column:
                n = world.column
                if world.probability == 0 or self.column_sums[n] == 0:
                    pass
                else:
                    world.probability = world.probability / self.column_sums[n]
            else:
                n = world.row
                if world.probability == 0 or self.row_sums[n] == 0:
                    pass
                else:
                    world.probability = world.probability / self.row_sums[n]

    def copy(self):
        output = Table(self.possible_worlds, self.utterances, self.worlds)
        return output

<mask token>


class Table:
    <mask token>

    def fill_sums(self, possible_worlds):
        for world in possible_worlds:
            row = world.row
            column = world.column
            self.column_sums[column] += world.probability
            self.row_sums[row] += world.probability

    def re_sum(self):
        self.column_sums = [0] * self.size
        self.row_sums = [0] * self.size
        self.fill_sums(self.possible_worlds)

    def normalize(self, column):
        self.re_sum()
        for world in self.possible_worlds:
            if column:
                n = world.column
                if world.probability == 0 or self.column_sums[n] == 0:
                    pass
                else:
                    world.probability = world.probability / self.column_sums[n]
            else:
                n = world.row
                if world.probability == 0 or self.row_sums[n] == 0:
                    pass
                else:
                    world.probability = world.probability / self.row_sums[n]

    def copy(self):
        output = Table(self.possible_worlds, self.utterances, self.worlds)
        return output

<mask token>


class Table:

    def __init__(self, possible_worlds, U, W):
        self.size = len(possible_worlds)
        self.possible_worlds = possible_worlds
        self.column_sums = [0] * self.size
        self.row_sums = [0] * self.size
        self.utterances = U
        self.worlds = W
        self.fill_sums(possible_worlds)

    def fill_sums(self, possible_worlds):
        for world in possible_worlds:
            row = world.row
            column = world.column
            self.column_sums[column] += world.probability
            self.row_sums[row] += world.probability

    def re_sum(self):
        self.column_sums = [0] * self.size
        self.row_sums = [0] * self.size
        self.fill_sums(self.possible_worlds)

    def normalize(self, column):
        self.re_sum()
        for world in self.possible_worlds:
            if column:
                n = world.column
                if world.probability == 0 or self.column_sums[n] == 0:
                    pass
                else:
                    world.probability = world.probability / self.column_sums[n]
            else:
                n = world.row
                if world.probability == 0 or self.row_sums[n] == 0:
                    pass
                else:
                    world.probability = world.probability / self.row_sums[n]

    def copy(self):
        output = Table(self.possible_worlds, self.utterances, self.worlds)
        return output

import itertools
import Utterance
import PossibleWorld


class Table:

    def __init__(self, possible_worlds, U, W):
        self.size = len(possible_worlds)
        self.possible_worlds = possible_worlds
        self.column_sums = [0] * self.size
        self.row_sums = [0] * self.size
        self.utterances = U
        self.worlds = W
        self.fill_sums(possible_worlds)

    def fill_sums(self, possible_worlds):
        for world in possible_worlds:
            row = world.row
            column = world.column
            self.column_sums[column] += world.probability
            self.row_sums[row] += world.probability

    def re_sum(self):
        self.column_sums = [0] * self.size
        self.row_sums = [0] * self.size
        self.fill_sums(self.possible_worlds)

    def normalize(self, column):
        self.re_sum()
        for world in self.possible_worlds:
            if column:
                n = world.column
                if world.probability == 0 or self.column_sums[n] == 0:
                    pass
                else:
                    world.probability = world.probability / self.column_sums[n]
            else:
                n = world.row
                if world.probability == 0 or self.row_sums[n] == 0:
                    pass
                else:
                    world.probability = world.probability / self.row_sums[n]

    def copy(self):
        output = Table(self.possible_worlds, self.utterances, self.worlds)
        return output

import itertools
import Utterance
import PossibleWorld
#this table contains all the possible worlds
class Table:
	def __init__(self, possible_worlds, U, W):
		self.size=len(possible_worlds)
		self.possible_worlds=possible_worlds
		self.column_sums=[0]*self.size
		self.row_sums=[0]*self.size
		self.utterances=U
		self.worlds=W
		self.fill_sums(possible_worlds)

	#this adds up all of the possible world probabilities in the rows and columns of a table
	def fill_sums(self, possible_worlds):
		for world in possible_worlds:
			row=world.row
			column=world.column
			self.column_sums[column]+=world.probability
			self.row_sums[row]+=world.probability


	#re-adds up all of the columns and rows so that normalization is accurate
	def re_sum(self):
		self.column_sums=[0]*self.size
		self.row_sums=[0]*self.size
		self.fill_sums(self.possible_worlds)


	#important function for normalizing so that we can look at probability distributions
	def normalize(self, column):
		self.re_sum()
		for world in self.possible_worlds:
			if column:
				n=world.column 
				if world.probability==0 or self.column_sums[n]==0:
					pass
				else:
					world.probability=(world.probability)/(self.column_sums[n])
			else:
				n=world.row 
				if world.probability==0 or self.row_sums[n]==0:
					pass
				else:
					world.probability=(world.probability)/(self.row_sums[n])

	def copy(self):
		output=Table(self.possible_worlds, self.utterances, self.worlds)
		return output
