How to use both_true method in autotest

Best Python code snippet using autotest_python

world_truth_count.py

Source:world_truth_count.py

1import sys2import os3import minimal_proplogic as apl4import random5import numpy as np6import sys7import os8import time9import unittest10def generate_random_world(i):11	if type(i) == int:12		return [random.choice(["0","1"]) for j in range(i)]13	if type(i) == list:14		return {j:random.choice([True, False])for j in i}15def w2a(world):16	#world to array of bools17	return [True if x == "1" else False for x in world]18def a2w(world):19	#array of bools to str20	return "".join(["1" if x == True else "0" for x in world])21def arr_to_world(world):22	#Takes array of characters (optionally negated with "~")23	#returns bit vector of 0/1s in corresponding order24	ret_str = ""25	for symbol in world:26		if "~" in symbol:27			ret_str += "0"28		else:29			ret_str += "1"30	return ret_str31def get_relevant_variables(premise, idx=True):32	#return alphabetical pos of each var that is in the premise.33	cmap = "abcdefghijklmnopqrstuvwxyz"34	arr = []35	for i in range(len(cmap)):36		if cmap[i] in premise:37			if idx == True:38				arr.append(i)39			else: #return char itself40				arr.append(cmap[i])41	return arr#[i if (cmap[i] in premise) for i in range(len(cmap))]42def world_in_seen(world, relevant_variables, seen):43	#world: bool array size 26 corresponding to world bits44	#relevant_variables: int array, each int is var included in premise45	#seen: array of int arrays. each int array length of relevant_variables.46	#compares bit arrays, hopefully this is the fastest possible47	#print(world, relevant_variables, seen, True if [world[i] for i in relevant_variables] in seen else False)48	return True if [world[i] for i in relevant_variables] in seen else False49def assign_world(world, vars):50	ret_world = ["0"] * 2651	for i in range(0, len(world)):52		ret_world[vars[i]] = world[i]53	return "".join(ret_world)54def combine_vars(v1, v2):55	v = v156	for var in v2:57		if var not in v:58			v.append(var)59	return v60def in_both(v1, v2):61	v = []62	for var in v2:63		if var in v1:64			v.append(var)65	return v66def convert_sentence_pair_to_az(s1, s2):67	comb = s1 + "\t" + s268	comb_replaced, map = convert_sentence_to_az(comb)69	s1_new, s2_new = comb_replaced.split("\t")70	return s1_new, s2_new, map71def convert_sentence_to_az(sentence):72	if not "Symbol_" in sentence:73		return sentence, [] #already in az format74	else:75		split_sentence = sentence.split(" ")76		ind = 077		symb_to_az_list = [] #should be symb1 symb2 symb3 -> abc78		while ind < len(split_sentence):79			if "Symbol_" in split_sentence[ind]:80				current_symbol = split_sentence[ind]81				symb_to_az_list.append(current_symbol)82				char_mapped = chr(97 + len(symb_to_az_list) - 1)83				split_sentence = list(map(lambda x: x if x != current_symbol else char_mapped, split_sentence))84			elif len(split_sentence[ind]) > 1 and split_sentence[ind][0] in "()&|~>":85				split_sentence[ind] = split_sentence[ind][0]86			ind += 187	return "".join(split_sentence), symb_to_az_list88class TestConvertSentence(unittest.TestCase):89	def test_pass_forward(self):90		self.assertEqual(convert_sentence_to_az("((a&b)|c)")[0], "((a&b)|c)")91		self.assertEqual(convert_sentence_to_az("((a&b)|c)")[1], [])92	def test_convert(self):93		self.assertEqual(convert_sentence_to_az("( ( Symbol_1 & Symbol_2 ) | Symbol_3 )")[0], "((a&b)|c)")94		self.assertEqual(convert_sentence_to_az("( ( Symbol_1 & Symbol_2 ) | Symbol_1 )")[0], "((a&b)|a)")95def dict_to_world(az_map, symbol_map):96	cmap = "abcdefghijklmnopqrstuvwxyz"97	ret_world = ["0"] * 2698	for symbol in symbol_map.keys():99		if symbol_map[symbol] == True:100			bit = "1"101		else:102			bit = "0"103		ret_world[az_map.index(symbol)] = bit104	return ret_world105def sentence_satisfiable_in_world(sentence, world):106	az_sentence, az_mapping_list = convert_sentence_to_az(sentence)107	relevant_variables = get_relevant_variables(az_sentence)108	if type(world) == list:109		world = assign_world(world, relevant_variables)110	elif type(world) == dict:111		world = dict_to_world(az_mapping_list, world)112	truthval = apl.parse(az_sentence, world)113	return truthval114def satisfying_assignment_exists(sentence, symbols):115	"""116	Determine whether an assignment of symbols exists that satisifes the sentence117	input:118		sentence: space_split string of symbols, parens, and operators119		symbols: list of unique non-operator symbols in `sentence`120	output:121		truthval: True if assignment of symbols exists that satisfies sentence, False otherwise122		assignment: dict of {string : bool} values dictating the symbol:truth value variable assignment that satisfies sentence123	"""124	num_symbols = len(symbols)125	str_num_symbols = str(num_symbols)126	for i in range(2 ** num_symbols):127		world = ('{0:0' + str_num_symbols + 'b}').format(i)128		variable_assignment = apl.getdict_list(world, symbols)129		truthval = apl.eval_assignment_in_world(sentence, variable_assignment)130		if truthval == True:131			return True, variable_assignment132	return False, {}133def all_satisfying_assignments(sentence, symbols):134	"""135	Determine whether an assignment of symbols exists that satisifes the sentence136	input:137		sentence: space_split string of symbols, parens, and operators138		symbols: list of unique non-operator symbols in `sentence`139	output:140		assignments: list of dict of {string : bool}. each dict is values dictating the symbol:truth value variable assignment that satisfies sentence141					 if no assignments satisfy, then return empty list142	"""143	satisfying_assignments = []144	num_symbols = len(symbols)145	str_num_symbols = str(num_symbols)146	for i in range(2 ** num_symbols):147		world = ('{0:0' + str_num_symbols + 'b}').format(i)148		variable_assignment = apl.getdict_list(world, symbols)149		truthval = apl.eval_assignment_in_world(sentence, variable_assignment)150		if truthval == True:151			satisfying_assignments.append(variable_assignment)152	return satisfying_assignments153class TestFindSatisfyingArgument(unittest.TestCase):154	def test_true(self):155		self.assertTrue(satisfying_assignment_exists("( ( Symbol_1 & Symbol_2 ) | Symbol_3 )")[0])156		self.assertEqual(satisfying_assignment_exists("( Symbol_1 & Symbol_2 )")[1], {"Symbol_1": True, "Symbol_2": True})157	def test_false(self):158		self.assertFalse(satisfying_assignment_exists("( Symbol_1 & ~ ( Symbol_1 ) )")[0])159	def test_az(self):160		self.assertTrue(satisfying_assignment_exists("(a&b)"))161		self.assertFalse(satisfying_assignment_exists("(a&~(a))"))162def eval(split, verbose = False):163	prem_vars = get_relevant_variables(split[0])164	hyp_vars = get_relevant_variables(split[1])165	inb = in_both(prem_vars, hyp_vars)166	relevant_variables = combine_vars(prem_vars, hyp_vars)167	l_t = len(relevant_variables)168	s_lt = str(l_t)169	seen = [] #map of int (representing line # for train/test items) to seen worlds170	premise = split[0]171	hypothesis = split[1]172	prem_true = 0173	prem_false = 0174	hyp_true = 0175	hyp_false = 0176	both_true = 0177	#seen_ml = False #have we seen the most likely world yet?178	for i in range(2 ** l_t):179		world = ('{0:0' + s_lt + 'b}').format(i)180		world = assign_world(world, relevant_variables)181		truthval = apl.parse(premise, world)182		hyp_is_true = apl.parse(hypothesis, world)183		if hyp_is_true == True:184			hyp_true += 1185		else:186			hyp_false += 1187		if truthval == True:188			prem_true += 1189		else:190			prem_false += 1191		if hyp_is_true == True and truthval == True:192			both_true += 1193	p_p = prem_true * 1.0 / (prem_true + prem_false)194	p_h = hyp_true * 1.0 / (hyp_true + hyp_false)195	p_b = both_true * 1.0 / (hyp_true + hyp_false)196	try:197		p_cond = p_b / p_p198	except ZeroDivisionError:199		p_cond = 0200	if verbose == True:201		print("Premise true for:\t{}".format(prem_true))202		print("Premise false:\t{}".format(prem_false))203		print("Hypothesis true for:\t{}".format(hyp_true))204		print("Hypothesis false:\t{}".format(hyp_false))205		print("Both true:\t{}".format(both_true))206	return p_p, p_h, p_b, p_cond207def eval2(split, verbose = False):208	premise = split[0]209	hypothesis = split[1]210	'''if type(premise) == list:211		premise = " ".join(premise)212		hypothesis = " ".join(hypothesis)'''213	if "Symbol_" in premise:214		premise, hypothesis,map = convert_sentence_pair_to_az(premise,hypothesis)215	prem_vars = get_relevant_variables(premise)216	hyp_vars = get_relevant_variables(hypothesis)217	inb = in_both(prem_vars, hyp_vars)218	relevant_variables = combine_vars(prem_vars, hyp_vars)219	l_t = len(relevant_variables)220	s_lt = str(l_t)221	seen = [] #map of int (representing line # for train/test items) to seen worlds222	prem_true = 0223	prem_false = 0224	hyp_true = 0225	hyp_false = 0226	both_true = 0227	entailed = True228	equiv = True229	#seen_ml = False #have we seen the most likely world yet?230	for i in range(2 ** l_t):231		world = ('{0:0' + s_lt + 'b}').format(i)232		world = assign_world(world, relevant_variables)233		truthval = apl.parse(premise, world)234		hyp_is_true = apl.parse(hypothesis, world)235		if hyp_is_true == True:236			hyp_true += 1237		else:238			hyp_false += 1239		if truthval == True:240			if hyp_is_true == False:241				entailed = False242			prem_true += 1243		else:244			prem_false += 1245		if hyp_is_true == True and truthval == True:246			both_true += 1247		elif hyp_is_true != truthval:248			equiv = False249	p_p = prem_true * 1.0 / (prem_true + prem_false)250	p_h = hyp_true * 1.0 / (hyp_true + hyp_false)251	p_b = both_true * 1.0 / (hyp_true + hyp_false)252	try:253		p_cond = p_b / p_p254	except ZeroDivisionError:255		p_cond = 0256	if verbose == True:257		print("Premise true for:\t{}".format(prem_true))258		print("Premise false:\t{}".format(prem_false))259		print("Hypothesis true for:\t{}".format(hyp_true))260		print("Hypothesis false:\t{}".format(hyp_false))261		print("Both true:\t{}".format(both_true))262	return p_p, p_h, p_b, p_cond, entailed, equiv263if __name__ == "__main__":...

lowestCommonAnces.py

Source:lowestCommonAnces.py

1#!/usr/bin/python2"""3The lowest common ancestor is defined between two nodes v and w as the lowest node in T4that has both v and w as descendants (where we allow a node to be a descendant of itself).5Find the lowest common ancestor.6#2367REDDO: figure out the algo quick8"""9from btNode import BTNode10def lca(n, p, q):11    if n == None or n == p or n == q: return n12    lhs = lca(n.left, p, q)13    rhs = lca(n.right, p, q)14    if lhs and rhs: return n15    return lhs if lhs else rhs16def lca_non_valid_node(node, t1, t2):17    both_true = [False]*218    res = lca_nvn(node, t1, t2, both_true)19    if both_true[0] and both_true[1]:20        return res.val21    else:22        return -123def lca_nvn(node, t1, t2, both_true):24    if not node:25        return None26    ret_n = None27    if node == t1 or node == t2:28        if node == t1:29            both_true[0] = True30        else:31            both_true[1] = True32        ret_n = node33    lhs = lca_nvn(node.left, t1, t2, both_true)34    rhs = lca_nvn(node.right, t1, t2, both_true)35    if lhs and rhs:36        return node37    if not ret_n:38        ret_n = lhs if lhs else rhs39    return ret_n40def test1():41    n3 = BTNode(3)42    n5 = BTNode(5)43    n6 = BTNode(6)44    n2 = BTNode(2)45    n7 = BTNode(7)46    n4 = BTNode(4)47    n1 = BTNode(1)48    n0 = BTNode(0)49    n8 = BTNode(8)50    n3.left = n551    n5.left = n652    n3.right = n153    n5.right = n254    n2.left = n755    n2.right = n456    n1.left = n057    n1.right = n858    n_nonvalid = BTNode(13)59    print(lca(n3, n6, n2).val)60    print(lca_non_valid_node(n3, n6, n_nonvalid))61    print(lca_non_valid_node(n3, n6, n2))62    print(lca_non_valid_node(n3, n4, n2))63if __name__ == '__main__':...

correlation.py

Source:correlation.py

1# Add the functions in this file2import json3import math4def load_journal(file1):5  with open(file1) as j:6    data = json.load(j)7    return data  8def compute_phi(file1, event):9  data_dict = load_journal(file1)10  both_true=011  both_false=012  x_true=013  y_true=014  for i in range(len(data_dict)):15    if event in data_dict[i]["events"] and data_dict[i]["squirrel"]:16      both_true+=117    elif event in data_dict[i]["events"]:18      x_true+=119    elif data_dict[i]["squirrel"]:20      y_true+=121    else:22      both_false+=1  23  only_x = both_true + x_true24  only_y = both_true + y_true25  not_x = both_false + y_true26  not_y = both_false + x_true    27  corr = (both_true*both_false - x_true*y_true)/math.sqrt(only_x*only_y*not_x*not_y)28  return corr29def compute_correlations(file1):30  journal_file = load_journal(file1)31  events ={}32  event_lol=[]33  for i in range(len(journal_file)):34    event_x = journal_file[i]["events"]35    for j in event_x:36      if j not in event_lol:37        event_lol.append(j)38  for k in event_lol:39    events[k] = compute_phi(file1, k)40  return events41def diagnose(file1):42  journal_file = load_journal(file1)43  events = compute_correlations(file1)44  max_key = max(events, key=events.get)45  min_key = min(events, key=events.get)46  ...

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