def __init__(self, parametres):
N_patche = parametres["Np"]
self.param = parametres
self.interaction = Interaction(N_patche)
self.fonctionsreponse = None
self.bulles = Bulles(parametres)
self.T0 = 0.0
def init_interaction(self):
self.interaction = Interaction()
self.interaction.register_callback('pick', self.pick)
self.interaction.register_callback('move', self.move)
self.interaction.register_callback('place', self.place)
self.interaction.register_callback('rotate_color', self.rotate_color)
self.interaction.register_callback('scale', self.scale)
def render(self):
utl.zero(self.img)
for _i, _j in ti.ndrange(self.cam.resolution_h, self.cam.resolution_w):
_ray = self.cam.get_ray(_i, _j)
_dir_t_max = utl.infinitesimal
_dir_t_min = utl.infinite
# 求光线从参与介质中穿过的最近_dir_t_min与最远_dir_t_max
for _k in ti.ndrange(self.shape.tri.shape[0]):
_tri = self.shape.tri[_k]
self.ver_3_tmp[0] = self.shape.ver[_tri.x]
self.ver_3_tmp[1] = self.shape.ver[_tri.y]
self.ver_3_tmp[2] = self.shape.ver[_tri.z]
# print(ti_ver_3_tmp[2])
_is_hit, _dir_t, _u, _v = _ray.intersect_triangle(self.ver_3_tmp)
if _is_hit == 1:
_dir_t_max = max(_dir_t_max, _dir_t)
_dir_t_min = min(_dir_t_min, _dir_t)
# 如果穿过了参与介质
if _dir_t_max - _dir_t_min > 0.00001:
_hit_p_max = _ray.origin + _dir_t_max * _ray.direction
_hit_p_min = _ray.origin + _dir_t_min * _ray.direction
# 最近-最远交点
_inter_p_max = Interaction(_hit_p_max, _ray.direction)
_inter_p_min = Interaction(_hit_p_min, _ray.direction)
self.img[_i, _j] = self.ray_marching(_inter_p_min, _inter_p_max) * 0.01
def what_happend(self):
nb = len(self.symb)
seqs = []
vas = -math.inf
if len(self.actions) > 2 * nb + 1:
lasts = self.actions[len(self.actions) - nb + 1:]
inds = self.subfinder(lasts)
for i in inds:
found = False
temp = []
tempi = 0
y = 0
while len(self.actions) - 3 > i + nb + y and (y == nb or self.vals[i + nb + y - 1] < 0):
temp.append(self.actions[i + nb + y])
potit = self.testint(seqs)
if potit is None:
tempi += self.vals[i + nb + y] -(0.5 * len(seqs))
else:
tempi += potit.proclivity -(0.5 * len(seqs))
y += 1
if self.vals[i + nb + y - 1] > 0:
found = True
# = pour prendre la dernière -> plus de chance d'être mieux
if found:
if tempi >= vas and tempi > -100:
seqs = temp[:]
vas = tempi
if len(seqs) > 0:
temp = self.testint(seqs)
if temp is None:
self.iter = Interaction(seqs[:], 0, 1)
self.inters.append(self.iter)
else:
self.iter = temp
elif random.randint(0, 1) == 0:
seqs = [random.randrange(0, self.nbacts, 1) for _ in range(random.randint(1,self.nbacts-1*2))]
temp = self.testint(seqs)
if temp is None:
self.iter = Interaction(seqs[:], vas, 1)
self.inters.append(self.iter)
else:
self.iter = temp
return seqs
def del_friend(self, username):
# update data
other_index = Data.users[Data.users['username'] == username].index[0]
Data.users.loc[self.index, 'friends'].remove(other_index)
Data.users.loc[other_index, 'friends'].remove(self.index)
if Interaction.is_connected(username):
other_client = Interaction.get_client(username)
send(other_client.conn, f'delfr|{self.username}')
def __init__(self, group, edgetype, bait_ids=None):
Interaction.__init__(self)
# We first set the putative bait so it can be used later for the
# ppiTrim_id
if bait_ids is not None:
self.set_template_baits(bait_ids)
self._create_complex(group, edgetype)
def __init__(self):
"""initializing variables for input user."""
self.interaction = Interaction()
self.api_data = Data()
self.api_data.categories
self.sql_setup = Sqlconnection()
self.menu_selectable = False
self.menu_get_product = False
def on_log(self, username):
self.logged = True
Interaction.clients.append(self)
self.username = username
line = Data.users[Data.users['username'] == username]
self.friends = line['friends'].values[0]
self.index = line.index[0]
Interaction.manage_friends(self)
self.look_for_fr_request()
Data.send_stats(username, self.conn)
def __init__(self, client, interaction_spec):
self.client = client
self.cjar = {
"browser": cookielib.CookieJar(),
"rp": cookielib.CookieJar(),
"service": cookielib.CookieJar()
}
self.interaction = Interaction(self.client, interaction_spec)
self.features = None
self.login_time = 0
def init_interaction(self):
""" init user interaction and callbacks """
self.interaction = Interaction()
self.interaction.register_callback('pick', self.pick)
self.interaction.register_callback('move', self.move)
self.interaction.register_callback('place', self.place)
self.interaction.register_callback('rotate_color', self.rotate_color)
self.interaction.register_callback('scale', self.scale)
self.interaction.register_callback('close',self.close)
self.interaction.register_callback('setCameraMode',self.setCameraMode)
def heuristicDiversification(self):
for actions in self._actions:
if not self.exist_interaction(actions):
inter = Interaction(actions, 0, 1)
valence = self.bootstrap(inter)
if not valence is None:
inter.result = valence
self._interactions.append(inter)
return inter
return None
def create_env(self, username):
# check other is conn
if Interaction.is_connected(username):
other_client = Interaction.get_client(username)
self.env = Env((self, other_client),
(self.username, other_client.username))
other_client.env = self.env
Interaction.inform_inenv(other_client.username)
other_client.in_env = True
self.in_env = True
def init_interaction(self):
self.interaction = Interaction()
self.interaction.register_callback('pick', self.pick)
self.interaction.register_callback('move', self.move)
self.interaction.register_callback('place', self.place)
self.interaction.register_callback('rotate_color', self.rotate_color)
self.interaction.register_callback('scale', self.scale)
self.interaction.register_callback('close', self.close)
self.interaction.register_callback('reset', self.reset)
self.interaction.register_callback('nogrid', self.nogrid)
def get_all_interactions():
interactions = []
response = table.scan()
for s in response['Items']:
interaction = Interaction(s['sessionId'], s['time'], s['responses'],
s['deviceId'], s['userId'])
Interaction.print_interaction(interaction)
interactions.append(interaction)
return interactions
def check_env_rinv(self, username):
# check other is conn
if Interaction.is_connected(username):
other_client = Interaction.get_client(username)
# check if other client is already in env
if other_client.in_env:
other_client.env.add_client(self)
self.in_env = True
self.env = other_client.env
else:
self.create_env(username)
Interaction.inform_inenv(self.username)
def possible_actions(self): actions = [] if self.dead: actions.append(Interaction(self, "Loot", 1.5)) else: if self.interact_script: actions.append(Interaction(self, "Interact", 1.5)) if self.dialogue: actions.append(Interaction(self, "Talk", 5)) if self.killable: actions.append(Interaction(self, "Kill", 1.5)) return actions
def generate(self):
regenerateScene = True
while regenerateScene:
availableId = 1
regenerateScene = False
self.clear()
self.humans = []
self.objects = []
self.interactions = []
self.room = Room()
self.addItem(self.room)
# We generate a number of humans using the absolute of a normal
# variate with mean 1, sigma 4, capped to 15. If it's 15 we get
# the remainder of /15
humanCount = int(abs(random.normalvariate(1, 4))) % 15
if humanCount == 0:
humanCount = QtCore.qrand() % 3
for i in range(humanCount):
human = self.generateHuman(availableId)
availableId += 1
self.addItem(human)
self.humans.append(human)
if QtCore.qrand() % 3 == 0:
human2 = self.generateComplementaryHuman(
human, availableId)
availableId += 1
self.addItem(human2)
interaction = Interaction(human, human2)
self.interactions.append(interaction)
self.addItem(interaction)
self.humans.append(human2)
elif QtCore.qrand() % 2 == 0:
obj = self.generateComplementaryObject(human, availableId)
availableId += 1
interaction = Interaction(human, obj)
self.interactions.append(interaction)
self.addItem(interaction)
self.addItem(obj)
self.objects.append(obj)
self.robot = Robot()
self.robot.setPos(0, 0)
self.addItem(self.robot)
self.text = 'Humans:' + str(len(self.humans)) + ' ' + 'Objects:' + str(
len(self.objects))
def parse(dir_name):
print("#####PARSING#####")
arn_list = []
for filename in os.listdir(dir_name):
file = open(dir_name + filename, 'r')
print("file: " + dir_name + filename)
# On construit l'objet ARN
arn = ARN(filename.split("_")[0])
file.readline()
file.readline()
chain = file.readline().split(" ")[1].rsplit('\t')
chain_id = chain[0]
chain = chain[1].rsplit('\n')[0]
arn.chain = chain
arn.chain_id = chain_id
file.readline()
# On ajoute les interactions et bases a l'ARN
arn._set_bases()
for line in file:
line = line.rsplit('\t')
base1 = Base(line[2], int(line[5]))
base2 = Base(line[6], int(line[9].rsplit('\n')[0]))
interaction = Interaction(base1, line[1], base2)
arn._add_interaction(interaction)
# On ajoute les boucles a l'ARN
expr = "Catalog_results/loop." + arn.name + "*"
for loop_file_name in glob.glob(expr):
print("|\tloop file: " + loop_file_name)
loop_file = open(loop_file_name)
loop = Loop(arn.name, arn.chain_id, loop_file.readline().split(":")[1].rsplit('\n')[0])
loop_bases = loop_file.readline().split(": ")[1].split(", ")
loop_bases[-1] = loop_bases[-1].rsplit('\n')[0]
loop.bases = [Base(b[:1], b[1:]) for b in loop_bases]
loop_file.readline()
for line in loop_file:
line = line.rsplit('\t')
base1 = Base(line[0][:1], int(line[0][1:]))
base2 = Base(line[2][:1], int(line[2][1:].rsplit('\n')[0]))
interaction = Interaction(base1, line[1], base2)
print("|\t|\tadding interaction " + str(interaction))
loop.add_interaction(interaction)
arn._add_loop(loop)
loop_file.close()
file.close()
arn_list.append(arn)
print("#####FINISHED PARSING#####")
return arn_list
def addget_primitive_interaction(self,
experiment,
result,
valence=None,
meaning=None):
label = experiment.get_label() + result.get_label()
if label not in self.INTERACTIONS:
interaction = Interaction(label)
interaction.set_experiment(experiment)
interaction.set_result(result)
interaction.set_valence(valence)
interaction.set_meaning(meaning)
self.INTERACTIONS[label] = interaction
return self.INTERACTIONS[label]
def process_ppi1(irefindex_file,
id_logfile,
output_logfile,
biochem_file,
binary_file,
complexes_file,
obo_file,
biogrid_ptm_codes_file,
filtered_pmids_file=None,
accepted_taxids=None):
counts = Phase1Counts()
filtered_pmids = read_filtered_pmids(filtered_pmids_file)
id_map = read_id_mapping(id_logfile)
obo_fp = open(obo_file, 'rU')
ontology = obo.OBOntology(obo_fp)
biochem_filter = _BiochemFilter(ontology, biogrid_ptm_codes_file)
complex_filter = _ComplexFilter(ontology)
input_fp = open(irefindex_file, 'rU')
removed_fp = NullFile()
biochem_fp = open(biochem_file, 'w')
binary_fp = open(binary_file, 'w')
complex_fp = open(complexes_file, 'w')
logfile_fp = open(output_logfile, 'w')
output_fps = (removed_fp, binary_fp, complex_fp, biochem_fp)
for fp in output_fps:
Interaction.write_header(fp)
scanner = parse_mitab_file(input_fp, full_mitab_iterator, None,
iRefIndexInteraction)
for interaction, lines in scanner:
line_numbers = lines[1]
res = _process_interaction(interaction, id_map, filtered_pmids,
logfile_fp, counts, line_numbers, ontology,
biochem_filter, complex_filter,
accepted_taxids)
interaction.to_file(output_fps[res])
counts.to_file(logfile_fp)
input_fp.close()
obo_fp.close()
logfile_fp.close()
for fp in output_fps:
fp.close()
def add_primitive_interaction(self, experiment, result, valence):
label = experiment.get_label() + result.get_label()
if label not in self.INTERACTIONS:
interaction = Interaction(label, valence)
interaction.set_experiment(experiment)
interaction.set_result(result)
interaction.set_valence(valence)
self.INTERACTIONS[label] = interaction
def initialize_interactions(self, primitive_interactions):
for interaction in primitive_interactions:
meaning = interaction
experiment_label = primitive_interactions[interaction][0]
result_label = primitive_interactions[interaction][1]
valence = primitive_interactions[interaction][2]
experiment = self.addget_abstract_experiment(experiment_label)
result = self.addget_result(result_label)
self.addget_primitive_interaction(experiment, result, valence, meaning)
for experiment in self.EXPERIMENTS.values():
interaction = Interaction(experiment.get_label() + "r2")
interaction.set_valence(1)
interaction.set_experiment(experiment)
experiment.set_intended_interaction(interaction)
def learn_composite_interaction(self, context_interaction, enacted_interaction):
if context_interaction is not None:
label = context_interaction.get_label() + enacted_interaction.get_label()
if label not in self.INTERACTIONS:
valence = context_interaction.get_valence() + enacted_interaction.get_valence()
interaction = Interaction(label, valence)
interaction.set_pre_interaction(context_interaction)
interaction.set_post_interaction(enacted_interaction)
interaction.set_valence(valence)
self.INTERACTIONS[label] = interaction
print "Learn " + label
else:
interaction = self.INTERACTIONS[label]
print 'Incrementing weight for ' + interaction.__repr__()
interaction.increment_weight()
def chooseExperience(self, ite, ite_max):
if len(self.actions) == 0:
self.last_action = random.randint(0, self.nbacts - 1)
return self.last_action
elif self.last_reward < 0:
if len(self.todo) == 0:
if self.iter is not None:
self.iter.maj(
sum(self.vals[len(self.vals) -
len(self.iter.action):]))
if random.randint(0, 25) > 1:
self.todo = self.what_happend()
if len(self.todo) == 0:
self.last_action = swap(self.last_action,
self.nbacts - 1)
else:
print(self.last_action)
seqs = [
random.randrange(0, self.nbacts, 1)
for _ in range(random.randint(1, self.nbacts - 1 * 2))
]
temp = self.testint(seqs)
if temp is None:
self.iter = Interaction(seqs[:], 0, 1)
self.inters.append(self.iter)
else:
self.iter = temp
self.todo = self.iter.action[:]
self.last_action = self.todo.pop(0)
else:
self.last_action = self.todo.pop(0)
return self.last_action
elif len(self.todo) > 0:
self.last_action = self.todo.pop(0)
return self.last_action
else:
if self.iter is not None:
self.iter.maj(
sum(self.vals[len(self.vals) - len(self.iter.action):]))
return self.last_action
def generateObject(self):
self.interactions = []
self.objects = []
obj = None
for human in self.humans:
if human is not None:
if QtCore.qrand(
) % 3 == 0: #The constant can be updated acoording to need for more or less number of objects in the world
try:
obj = self.generateComplementaryObject(
human, self.availableId)
except RuntimeError:
#Handling the time generation error
obj = None
pass
print("Took more time to create a random object")
#Returning so that too much time is not wasted in creating a random object which is inside the room
return
if obj is not None:
self.availableId += 1
print("Object")
print(obj)
try:
interaction = Interaction(human, obj)
self.interactions.append(
copy.deepcopy(interaction))
except Exception:
print(Exception)
pass
if obj not in self.objects:
self.objects.append(copy.deepcopy(obj))
else:
print("Repeated object which will fail")
def merge(self): # TODO: FUSION NOT APPEND ?
r1 = self.interactions[random.randint(0, len(self.interactions) - 1)]
r2 = self.interactions[random.randint(0, len(self.interactions) - 1)]
inter = Interaction(r1.action + r2.action, r1.result + r2.result, 1)
return inter
def chooseExperience(self, ite, ite_max): # TODO : Greatter babillage
# babillage
if len(self.actions) < 40:
action = random.randint(0, self.nbacts - 1)
self.last_action = action
self.inter = Interaction([action], 0, 1)
return action
else:
if len(self.todo) == 0:
threshold = curiosity(ite, ite_max)
epsilon = random.random()
if epsilon < threshold:
self.whats_next()
self.last_action = self.todo.pop(0)
# print("DO -----> ",self.last_action)
return self.last_action
else:
self.inter = self.purge()
self.todo = self.inter.action[:]
self.last_action = self.todo.pop(0)
# print("PURGE ----> ",self.last_action)
return self.last_action
# TODO: Increase positivity
else:
if len(self.todo) == 1:
self.last = True
self.last_action = self.todo.pop(0)
# print("TODO ------> ",self.last_action)
return self.last_action
def setUp(self):
self.browser = webdriver.Chrome(executable_path='./driver/chromedriver')
self.browser.get("https://dhaka.mrbjarke.com/")
self.interaction = Interaction(self.browser)
self.interaction.insert_email("*****@*****.**")
self.interaction.click_email_next_button()
self.interaction.insert_password("P@ssw0rd1")
self.interaction.click_login()
self.interaction.expand_setting_dropdown()
self.interaction.select_tanant_setting()
self.interaction.click_config_user_button()
self.interaction.wait_for_user_table_page()
del self.browser.requests
self.interaction.serach_user("rony")
self.interaction.busy_wait_for_table_update()
def __init__(self, client, interaction_spec):
self.client = client
self.cjar = {"browser": cookielib.CookieJar(),
"rp": cookielib.CookieJar(),
"service": cookielib.CookieJar()}
self.interaction = Interaction(self.client, interaction_spec)
self.features = None
self.login_time = 0
def get_splits(self, df, dict, y):
"""For list of attributes, find best split for each and return dict
of results"""
result = []
#For each attribute find the split that maximizes IV
for d in dict:
#Unpack the dictionary:
attr, corr, mincnt = (d['attr'], d['corr'], d['mincnt'])
try:
print "Length of x: %s, y: %s" % (len(df[attr]), len(y))
i = Interaction(df[attr], y)
split = i.split(mincnt, corr, verbose=False)
result.append(split)
except TypeError:
pass
return result
def init_interaction(self):
""" init user interaction and callbacks """
self.interaction = Interaction()
self.interaction.register_callback('pick', self.pick)
self.interaction.register_callback('move', self.move)
self.interaction.register_callback('place', self.place)
self.interaction.register_callback('rotate_color', self.rotate_color)
self.interaction.register_callback('scale', self.scale)
def main(player_first=True):
WIDTH = 3
HEIGHT = 3
board = Board(WIDTH, HEIGHT)
interaction = Interaction(WIDTH, HEIGHT)
computer = Computer()
turn = 'X'
if player_first:
computer_tile = 'O'
else:
computer_tile = 'X'
while board.get_winner() is None and not board.is_cat_game():
if turn == computer_tile:
x, y = computer.get_move(board, computer_tile)
board.place_tile(turn, x, y)
else:
x, y = interaction.get_move(turn, board)
board.place_tile(turn, x, y)
if turn == 'X':
turn = 'O'
else:
turn = 'X'
if board.is_cat_game():
interaction.display_cat_game(board)
else:
interaction.display_winner(board, board.get_winner() != computer_tile)
def saveOrUpdate(self, action, res):
update = False
for i in range(0, len(self.interactions)):
if self.interactions[i].action == action:
self.interactions[i].maj(res)
update = True
if not update:
self.interactions.append(Interaction(action, res, 1)) # TODO : Put inter sum
def addInteractions(self, actions, valence, type = True):
if not type:
if not self.exist_interaction(actions, type):
self._interactions.append(actions)
else:
if not self.exist_interaction(actions, type):
#Bootstrap de l'interaction avec des valeurs connues
new_interaction = Interaction(actions, valence, 1)
self._interactions.append(new_interaction)
def process_ppi2(input_file,
output_file,
output_logfile,
skipped_pmids_file=None,
max_complex_size=120,
min_complex_size=3):
counts = Phase2Counts()
logfile_fp = open(output_logfile, 'w')
skipped_pmids = read_filtered_pmids(skipped_pmids_file)
skipped_pmids.add(0) # this is invalid pmid - not really a paper
input_fp = open(input_file, 'rU')
output_fp = open(output_file, 'w')
Interaction.write_header(output_fp)
deflator = ComplexDeflator(logfile_fp, max_complex_size, min_complex_size)
for pmid, pairs, complexes in _parse_by_pmid(input_fp):
counts.initial_pairs += len(pairs)
counts.C += len(complexes)
counts.pmids += 1
if pmid in skipped_pmids or len(pairs) < (min_complex_size - 1):
new_complexes = []
unused_pairs = pairs
else:
new_complexes, unused_pairs = deflator(pmid, pairs, complexes)
_write_unused_pairs(output_fp, unused_pairs)
_write_existing_complexes(output_fp, complexes)
_write_new_complexes(output_fp, new_complexes)
counts.unused_pairs += len(unused_pairs)
for intr in new_complexes:
code = intr.edgetype
counter = getattr(counts, code)
counter += 1
setattr(counts, code, counter)
counts.to_file(logfile_fp)
input_fp.close()
output_fp.close()
logfile_fp.close()
def add_primitive_interaction(self, experiment, result, valence):
label = experiment.get_label() + result.get_label()
if label not in self.INTERACTIONS:
interaction = Interaction(label, valence)
interaction.set_experiment(experiment)
interaction.set_result(result)
interaction.set_valence(valence)
self.INTERACTIONS[label] = interaction
def quit(self, username):
client = Interaction.get_client(username)
# update client attributes
client.in_env = False
client.env = None
send(client.conn, f'env|stop')
# send to friends: out env
Interaction.inform_outenv(client.username)
# update env attributes
self.clients.remove(client)
self.usernames.remove(username)
self.n_clients -= 1
# check if there is still someone
if self.n_clients == 0:
self.active = False
else:
# inform other user in env
for client in self.clients:
send(client.conn, f'env|quit|{username}')
def main(player_first = True):
WIDTH = 3
HEIGHT = 3
board = Board(WIDTH, HEIGHT)
interaction = Interaction(WIDTH, HEIGHT)
computer = Computer()
turn = 'X'
if player_first:
computer_tile = 'O'
else:
computer_tile = 'X'
while board.get_winner() is None and not board.is_cat_game():
if turn == computer_tile:
x, y = computer.get_move(board, computer_tile)
board.place_tile(turn, x, y)
else:
x, y = interaction.get_move(turn, board)
board.place_tile(turn, x, y)
if turn == 'X':
turn = 'O'
else:
turn = 'X'
if board.is_cat_game():
interaction.display_cat_game(board)
else:
interaction.display_winner(board, board.get_winner() != computer_tile)
def addget_primitive_interaction(self, experiment, result, valence=None, meaning=None):
"""
If a primitive interaction is not in the INTERACTIONS dictionary, add it. Otherwise just return it.
:param experiment: (str) primitive experiment
:param result: (str) primitive result
:param valence: (int) valence of the interaction
:param meaning: (str) observer's meaning of the interaction
:return: (interaction) primitive interaction from the INTERACTIONS dictionary
"""
label = experiment.get_label() + result.get_label()
if label not in self.INTERACTIONS:
interaction = Interaction(label)
interaction.set_experiment(experiment)
interaction.set_result(result)
interaction.set_valence(valence)
interaction.set_meaning(meaning)
self.INTERACTIONS[label] = interaction
return self.INTERACTIONS[label]
def create_interaction():
"""Validate the posted json object
"""
request = flask.request
if not request.json:
print("Not json")
print(request)
flask.abort(400)
if not Interaction.validate_interaction(request.json):
flask.abort(400)
interaction = Interaction(request.json)
interaction_db.insertInteraction(interaction)
return json.dumps(interaction, default = lambda obj: obj.__dict__), 201
def learn_composite_interaction(self, context_interaction, enacted_interaction):
"""
Learn a new composite interaction or reinforce it if already known.
:param context_interaction: (Interaction) at time t-1
:param enacted_interaction: (Interaction) just performed
"""
if context_interaction is not None:
label = context_interaction.get_label() + enacted_interaction.get_label()
if label not in self.INTERACTIONS:
# valence is a sum of primitive interactions
valence = context_interaction.get_valence() + enacted_interaction.get_valence()
interaction = Interaction(label)
interaction.set_pre_interaction(context_interaction)
interaction.set_post_interaction(enacted_interaction)
interaction.set_valence(valence)
self.INTERACTIONS[label] = interaction
print "Learn " + label
else:
interaction = self.INTERACTIONS[label]
print 'Incrementing weight for ', interaction
interaction.increment_weight()
def chooseExperience(self, ite, ite_max):
if len(self.actions) == 0:
self.last_action = random.randint(0, self.nbacts - 1)
return self.last_action
elif self.last_reward < 0:
if len(self.todo) == 0:
if self.iter is not None:
self.iter.maj(sum(self.vals[len(self.vals) - len(self.iter.action):]))
if random.randint(0, 25) > 1:
self.todo = self.what_happend()
if len(self.todo) == 0:
self.last_action = swap(self.last_action, self.nbacts - 1)
else:
print(self.last_action)
seqs = [random.randrange(0, self.nbacts, 1) for _ in range(random.randint(1,self.nbacts-1*2))]
temp = self.testint(seqs)
if temp is None:
self.iter = Interaction(seqs[:], 0, 1)
self.inters.append(self.iter)
else:
self.iter = temp
self.todo = self.iter.action[:]
self.last_action = self.todo.pop(0)
else:
self.last_action = self.todo.pop(0)
return self.last_action
elif len(self.todo) > 0:
self.last_action = self.todo.pop(0)
return self.last_action
else:
if self.iter is not None:
self.iter.maj(sum(self.vals[len(self.vals) - len(self.iter.action):]))
return self.last_action
class Check(object):
def __init__(self, client, interaction_spec):
self.client = client
self.cjar = {"browser": cookielib.CookieJar(),
"rp": cookielib.CookieJar(),
"service": cookielib.CookieJar()}
self.interaction = Interaction(self.client, interaction_spec)
self.features = None
self.login_time = 0
def my_endpoints(self):
"""
:returns: All the assertion consumer service endpoints this
SP publishes.
"""
return [e for e, b in self.client.config.getattr("endpoints", "sp")[
"assertion_consumer_service"]]
def intermit(self, response):
"""
This method is supposed to handle all needed interactions.
It also deals with redirects.
:param response: A response from the IdP
"""
_response = response
_last_action = None
_same_actions = 0
if _response.status_code >= 400:
done = True
else:
done = False
url = _response.url
content = _response.text
while not done:
rdseq = []
while _response.status_code in [302, 301, 303]:
url = _response.headers["location"]
if url in rdseq:
raise Exception("Loop detected in redirects")
else:
rdseq.append(url)
if len(rdseq) > 8:
raise Exception(
"Too long sequence of redirects: %s" % rdseq)
# If back to me
for_me = False
for redirect_uri in self.my_endpoints():
if url.startswith(redirect_uri):
# Back at the RP
self.client.cookiejar = self.cjar["rp"]
for_me = True
try:
base, query = url.split("?")
except ValueError:
pass
else:
_response = parse_qs(query)
return _response
if for_me:
done = True
break
else:
_response = self.client.send(url, "GET")
if _response.status_code >= 400:
done = True
break
if done or url is None:
break
_base = url.split("?")[0]
try:
_spec = self.interaction.pick_interaction(_base, content)
except InteractionNeeded:
cnt = content.replace("\n", '').replace("\t", '').replace("\r",
'')
raise Exception(cnt)
except KeyError:
cnt = content.replace("\n", '').replace("\t", '').replace("\r",
'')
raise Exception(cnt)
if _spec == _last_action:
_same_actions += 1
if _same_actions >= 3:
print >> sys.stderr, "URL: %s" % url
print >> sys.stderr, content
raise Exception("Interaction loop detection")
else:
_last_action = _spec
login_start = 0
try:
page_type = _spec["page-type"]
except KeyError:
page_type = ""
else:
if page_type == "login":
login_start = time.time()
if page_type == "discovery":
_op = Discovery(_spec["control"])
elif page_type == "js_redirect":
_op = JSRedirect(_spec["control"])
else:
_op = Action(_spec["control"])
try:
_response = _op(self.client, self, url, _response)
if page_type == "login":
self.login_time = time.time() - login_start
if isinstance(_response, dict):
logger.debug("response: %s" % (_response,))
return _response
content = _response.text
logger.debug("content: %s" % content)
if _response.status_code >= 400:
txt = "Got status code '%s', error: %s" % (
_response.status_code, content)
raise Exception(txt)
except InteractionNeeded:
raise
except Exception, err:
logger.error("%s" % err)
raise
class DullAgent:
def __init__(self, strategy, symb):
self.strategy = strategy
self.last_action = None
self.actions = []
self.inters = []
self.iter = None
self.results = []
self.vals = []
self.todo = []
self.best_seq = []
self.symb = symb
self.motiv = 0
self.nbacts = len(symb)
self.trace = ""
self.ite = ""
self._name = "dull"
def chooseExperience(self, ite, ite_max):
if len(self.actions) == 0:
self.last_action = random.randint(0, self.nbacts - 1)
return self.last_action
elif self.last_reward < 0:
if len(self.todo) == 0:
if self.iter is not None:
self.iter.maj(sum(self.vals[len(self.vals) - len(self.iter.action):]))
if random.randint(0, 25) > 1:
self.todo = self.what_happend()
if len(self.todo) == 0:
self.last_action = swap(self.last_action, self.nbacts - 1)
else:
print(self.last_action)
seqs = [random.randrange(0, self.nbacts, 1) for _ in range(random.randint(1,self.nbacts-1*2))]
temp = self.testint(seqs)
if temp is None:
self.iter = Interaction(seqs[:], 0, 1)
self.inters.append(self.iter)
else:
self.iter = temp
self.todo = self.iter.action[:]
self.last_action = self.todo.pop(0)
else:
self.last_action = self.todo.pop(0)
return self.last_action
elif len(self.todo) > 0:
self.last_action = self.todo.pop(0)
return self.last_action
else:
if self.iter is not None:
self.iter.maj(sum(self.vals[len(self.vals) - len(self.iter.action):]))
return self.last_action
def get_reward(self, result):
self.last_result = result
self.last_reward = self.strategy.get_reward(result, self.last_action)
self.motiv += self.last_reward
self.ev()
return self.last_reward
def memory(self):
action = self.last_action
reward = self.last_reward
self.actions.append(action)
self.vals.append(reward)
self.results.append(self.last_result)
def what_happend(self):
nb = len(self.symb)
seqs = []
vas = -math.inf
if len(self.actions) > 2 * nb + 1:
lasts = self.actions[len(self.actions) - nb + 1:]
inds = self.subfinder(lasts)
for i in inds:
found = False
temp = []
tempi = 0
y = 0
while len(self.actions) - 3 > i + nb + y and (y == nb or self.vals[i + nb + y - 1] < 0):
temp.append(self.actions[i + nb + y])
potit = self.testint(seqs)
if potit is None:
tempi += self.vals[i + nb + y] -(0.5 * len(seqs))
else:
tempi += potit.proclivity -(0.5 * len(seqs))
y += 1
if self.vals[i + nb + y - 1] > 0:
found = True
# = pour prendre la dernière -> plus de chance d'être mieux
if found:
if tempi >= vas and tempi > -100:
seqs = temp[:]
vas = tempi
if len(seqs) > 0:
temp = self.testint(seqs)
if temp is None:
self.iter = Interaction(seqs[:], 0, 1)
self.inters.append(self.iter)
else:
self.iter = temp
elif random.randint(0, 1) == 0:
seqs = [random.randrange(0, self.nbacts, 1) for _ in range(random.randint(1,self.nbacts-1*2))]
temp = self.testint(seqs)
if temp is None:
self.iter = Interaction(seqs[:], vas, 1)
self.inters.append(self.iter)
else:
self.iter = temp
return seqs
''' Test if int exist in mem'''
def testint(self, acts):
for i in range(0, len(self.inters) - 1):
if self.inters[i].action == acts:
return self.inters[i]
return None
def subfinder(self, pattern):
todo = self.actions[:]
nb = 0
pos = []
for i in range(0, len(todo)):
if todo[i] == pattern[0] and todo[i:i + len(pattern)] == pattern:
pos.append(i)
nb += 1
if len(pos) > 1:
return pos[:-1]
else:
return []
''' -------------------- Debug & Display --------------------'''
def show_trace(self):
print(self.trace)
print(self.ite)
def pres(self):
print("Salut, ", end="")
if len(self.todo) > 0:
print("j'ai ", end="")
print('\x1b[6;30;42m' + str(self.todo) + '\x1b[0m', end="")
print("a faire.")
print("Mon historique est de : " + str(self.actions))
print("pour : " + str(self.vals))
def tracer(self, reward, i):
if reward > 0:
mess = '\x1b[0;30;46m'
else:
mess = '\x1b[5;30;41m'
space = ""
for y in range(0, len(str(i))):
space += " "
self.trace += mess + str(self.symb[self.last_action]) + '\x1b[0m' + space
self.ite += str(i) + " "
'''
Objectif : @debug
'''
def print_interactions(self, max=False):
print("----------------------------------")
for i in self.inters:
if max:
if i.result > 0:
print(i)
else:
print(i)
print("----------------------------------")
def ev(self):
for it in self.inters:
it.evaporate()
class Viewer(object):
def __init__(self):
""" Initialize the viewer. """
self.init_interface()
self.init_opengl()
self.init_scene()
self.init_interaction()
init_primitives()
def init_interface(self):
""" initialize the window and register the render function """
glutInit()
glutInitWindowSize(640, 480)
glutCreateWindow("3D Modeller")
glutInitDisplayMode(GLUT_SINGLE | GLUT_RGB)
glutDisplayFunc(self.render)
def init_interaction(self):
""" init user interaction and callbacks """
self.interaction = Interaction()
self.interaction.register_callback('pick', self.pick)
self.interaction.register_callback('move', self.move)
self.interaction.register_callback('place', self.place)
self.interaction.register_callback('rotate_color', self.rotate_color)
self.interaction.register_callback('scale', self.scale)
def init_scene(self):
""" initialize the scene object and initial scene """
self.scene = Scene()
self.initial_scene()
def init_opengl(self):
""" initialize the opengl settings to render the scene """
self.inverseModelView = numpy.identity(4)
self.modelView = numpy.identity(4)
glEnable(GL_CULL_FACE)
glCullFace(GL_BACK)
glEnable(GL_DEPTH_TEST)
glDepthFunc(GL_LESS)
glEnable(GL_LIGHT0)
glLightfv(GL_LIGHT0, GL_POSITION, GLfloat_4(0, 0, 1, 0))
glLightfv(GL_LIGHT0, GL_SPOT_DIRECTION, GLfloat_3(0, 0, -1))
glColorMaterial(GL_FRONT_AND_BACK, GL_AMBIENT_AND_DIFFUSE)
glEnable(GL_COLOR_MATERIAL)
glClearColor(1.0, 1.0, 1.0, 0.0)
def main_loop(self):
glutMainLoop()
def render(self):
""" The render pass for the scene """
self.init_view()
# Enable lighting and color
glEnable(GL_LIGHTING)
glClearColor(0.4, 0.4, 0.4, 0.0)
glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT)
# Load the modelview matrix from the current state of the trackball
glMatrixMode(GL_MODELVIEW)
glPushMatrix()
glLoadIdentity()
loc = self.interaction.translation
glTranslated(-loc[0], -loc[1], -loc[2])
glMultMatrixf(self.interaction.trackball.matrix)
# store the inverse of the current modelview.
currentModelView = numpy.array(glGetFloatv(GL_MODELVIEW_MATRIX))
self.modelView = numpy.transpose(currentModelView)
self.inverseModelView = inv(numpy.transpose(currentModelView))
# render the scene. This will call the render function for each object in the scene
self.scene.render()
# draw the grid
glDisable(GL_LIGHTING)
glCallList(G_OBJ_PLANE)
glPopMatrix()
# flush the buffers so that the scene can be drawn
glFlush()
def init_view(self):
""" initialize the projection matrix """
xSize, ySize = glutGet(GLUT_WINDOW_WIDTH), glutGet(GLUT_WINDOW_HEIGHT)
aspect_ratio = float(xSize) / float(ySize)
# load the projection matrix. Always the same
glMatrixMode(GL_PROJECTION)
glLoadIdentity()
glViewport(0, 0, xSize, ySize)
gluPerspective(70, aspect_ratio, 0.1, 1000.0)
glTranslated(0, 0, -15)
def initial_scene(self):
cube_node = Cube()
cube_node.translate(2, 0, 2)
cube_node.color_index = 2
self.scene.add_node(cube_node)
sphere_node = Sphere()
sphere_node.translate(-2, 0, 2)
sphere_node.color_index = 3
self.scene.add_node(sphere_node)
sphere_node_2 = Sphere()
sphere_node_2.translate(-2, 0, -2)
sphere_node_2.color_index = 1
self.scene.add_node(sphere_node_2)
def get_ray(self, x, y):
""" Generate a ray beginning at the near plane, in the direction that the x, y coordinates are facing
Consumes: x, y coordinates of mouse on screen
Return: start, direction of the ray """
self.init_view()
glMatrixMode(GL_MODELVIEW)
glLoadIdentity()
# get two points on the line.
start = numpy.array(gluUnProject(x, y, 0.001))
end = numpy.array(gluUnProject(x, y, 0.999))
# convert those points into a ray
direction = end - start
direction = direction / norm(direction)
return (start, direction)
def pick(self, x, y):
""" Execute pick of an object. Selects an object in the scene. """
start, direction = self.get_ray(x, y)
self.scene.pick(start, direction, self.modelView)
def move(self, x, y):
""" Execute a move command on the scene. """
start, direction = self.get_ray(x, y)
self.scene.move(start, direction, self.inverseModelView)
def place(self, shape, x, y):
""" Execute a placement of a new primitive into the scene. """
start, direction = self.get_ray(x, y)
self.scene.place(shape, start, direction, self.inverseModelView)
def rotate_color(self, forward):
""" Rotate the color of the selected Node. Boolean 'forward' indicates direction of rotation. """
self.scene.rotate_color(forward)
def scale(self, up):
""" Scale the selected Node. Boolean up indicates scaling larger."""
self.scene.scale(up)
