def save_img(imgs, stri):
num = imgs.shape[0]
for i in range(num):
A = imgs[i].copy() * 255
A = np.reshape(np.ravel(A), (Handler().img_size, Handler().img_size))
new_p = Image.fromarray(A)
if new_p.mode != 'RGB':
new_p = new_p.convert('RGB')
new_p.save(os.path.join(stri, str(i) + ".png"))
def train(self, X, Y):
#print(X.shape)
#print(Y.shape)
# camada convolucional
self.model = tf.keras.models.Sequential([
tf.keras.layers.Conv2D(64, kernel_size=(3, 3), strides=(1, 1), activation='relu',
input_shape=(Handler().img_size, Handler().img_size, 1)),
tf.keras.layers.Conv2D(32, kernel_size=(3, 3), strides=(1, 1), activation='relu',
input_shape=(Handler().img_size, Handler().img_size, 1)),
tf.keras.layers.MaxPooling2D(pool_size=(2, 2), strides=None, padding='valid', data_format=None),
tf.keras.layers.Flatten(),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(512, activation=tf.nn.relu, kernel_initializer='random_uniform'),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(256, activation=tf.nn.relu, kernel_initializer='random_uniform'),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(128, activation=tf.nn.relu, kernel_initializer='random_uniform'),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(1, activation=tf.nn.sigmoid)
])
"""""
self.model.add(tf.keras.layers.Flatten())
self.model.add(tf.keras.layers.Dense(units=128, activation=tf.nn.relu, kernel_initializer='random_uniform', kernel_regularizer=regularizers.l1(self.reg_l1),
activity_regularizer=regularizers.l2(self.reg_l2),
bias_regularizer=regularizers.l1_l2(self.reg_l1, self.reg_l2)))
self.model.add(tf.keras.layers.Dropout(self.droput))
self.model.add(tf.keras.layers.Dense(units=128, activation=tf.nn.relu, kernel_initializer='random_uniform',
kernel_regularizer=regularizers.l1(self.reg_l1),
activity_regularizer=regularizers.l2(self.reg_l2),
bias_regularizer=regularizers.l1_l2(self.reg_l1, self.reg_l2)))
self.model.add(tf.keras.layers.Dropout(self.droput))
self.model.add(tf.keras.layers.Dense(units=Handler().img_size, activation=tf.nn.sigmoid))
self.model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['binary_accuracy'])
self.model.add(tf.keras.layers.Conv2D(64, kernel_size=(3, 3), strides=(1, 1), activation='relu', input_shape=(50, 50, 1)))
self.model.add(tf.keras.layers.Conv2D(32, kernel_size=(3, 3), strides=(1, 1), activation='relu', input_shape=(50, 50, 1)))
# adicionando camadas à rede neural
self.model.add(tf.keras.layers.Flatten()) # camada que transforma imagens em vetores
self.model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))
self.model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))
self.model.add(tf.keras.layers.Dropout(0.2))
self.model.add(tf.keras.layers.Dense(1, activation=tf.nn.softmax))
"""""
self.model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['binary_accuracy'])
self.model.fit(X, Y, epochs=20)
def __init__(self, p=0.75, p1=0.8, p2=0.5, iteration_count=100000):
self.current_tick = 0
self.handled_tasks = []
self.states = []
self.iteration_count = iteration_count
self.busy_count = 0
self.source = Source(p, LemerGenerator(209715120, 3, 7))
self.queue = TaskQueue(2)
self.handlers = [
Handler(p1, LemerGenerator(209715120, 3, 7)),
Handler(p2, LemerGenerator(209715120, 3, 7))
]
def __init__(self, p1=0.4, p2=0.5, iteration_count=100000):
self.iteration_count = iteration_count
self.task_in_system_count = 0
self.current_tick = 0
self.handled_count = 0
self.refused_count = 0
self.states = []
self.p1 = p1
self.source = Source()
self.queue = TaskQueue(2)
self.handlers = [
Handler(p1, LemerGenerator(209715120, 3, 7)),
Handler(p2, LemerGenerator(209715120, 3, 7))
]
def test_get_all(self):
url = "https://news.yahoo.com/rss/"
lim = 3
hand = Handler(url, lim)
self.assertIsInstance(hand.get_all(), list)
self.assertIsInstance(hand.get_all()[0], News)
self.assertEqual(len(hand.get_all()), lim)
def __init__(self,
target_dir,
task,
handler_type=Handler.FILE_WRITER,
buffer_size=128):
self.task = task
self.buffer_size = buffer_size
self.handler = Handler(target_dir, handler_type)
self.buffers = {}
def __init__(self, h, w):
self.win = Window(top=0, x=w, y=h)
self.buffer = Buffer()
self.filename = ""
self.cursor = Cursor()
self.mode = "normal"
self.exit = False
self.handlers = Handler()
self.command = ""
self.message = ""
def __init__(self):
self.display = GameFrame()
# Handler
self.handler = Handler(self)
# Events Listeners:
self.init_listeners()
# GameState
self.menu_state = MenuState(self.handler)
self.game_state = GameState(self.handler)
self.over_state = OverState(self.handler)
# Thread
self.thread = Thread(target=self.run)
def __init__(self):
self.fsm = dict()
self.currentState = "locked"
self.handler = Handler()
self.add("unlocked", "pass", "", "locked")
self.add("unlocked", "ticket", "eject", "unlocked")
self.add("locked", "pass", "alarm", "exception")
self.add("locked", "ticket", "collect", "unlocked")
self.add("exception", "pass", "", "exception")
self.add("exception", "mute", "", "exception")
self.add("exception", "ticket", "eject", "exception")
self.add("exception", "release", "", "locked")
def start(self, address):
try:
self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.socket.bind(address)
self.socket.listen(self.LISTEN_COUNT)
self.handlers = [Handler(self) for i in range(self.MAX_HANDLERS)]
self.loop()
except:
self.logError()
self.exit(-1)
def test_img_alt_2(self):
text = 'img src="http://l.yimg.com/uu/api/res/1.2/I4AtbbFWPM.66LesQWxLqQ--/YXBwaWQ9eXRhY2h5b247aD04Njt3PTEzM' \
'Ds-/https://media.zenfs.com/en/the_new_york_times_articles_158/101bec76cc1717d8bfd63460b9443fd1" width=' \
'"130" height="86" alt="She Texted About Dinner While Driving. Then a Pedestrian Was Dead." align="left" ' \
'title="She Texted About Dinner While Driving. Then a Pedestrian Was Dead." border="0" ></a>FREEHOLD, N.J.' \
' -- One woman was out for a walk and a taste of fresh air during a break from her job as a scientist at' \
' a New Jersey fragrance manufacturer. She and her husband had been trying to get pregnant, and brief' \
' bouts of exercise, away from the laboratory's smells and fumes, were part of that plan.A second ' \
'woman was behind the wheel of a black Mercedes-Benz, headed to work as chief executive of a nonprofit in '
img_alt = '="She Texted About Dinner While Driving. Then a Pedestrian Was Dead.'
hand = Handler("https://news.yahoo.com/rss/", 3)
self.assertNotEqual(hand.get_img_alt(text)[0], img_alt)
def run(self):
event_handler = Handler()
self.observer.schedule(event_handler,
self.DIRECTORY_TO_WATCH,
recursive=True)
self.observer.start()
try:
while True:
time.sleep(5)
except Exception as err:
self.observer.stop()
print(err)
self.observer.join()
def run(self):
event_handler = Handler(self.syncer)
self.observer.schedule(event_handler,
self.syncer.config['base_folder_dir'] +
self.syncer.config['target_folder_name'],
recursive=True)
self.observer.start()
try:
while True:
time.sleep(5)
except Exception as error:
self.observer.stop()
print(error)
def compile(p):
lexer = Lexer(p)
parser = Parser(lexer)
tokens = parser.parse()
handler = Handler()
nfa_stack = []
for t in tokens:
handler.handlers[t.name](t, nfa_stack)
assert len(nfa_stack) == 1
nfa = nfa_stack.pop()
nfa.num_of_states = handler.state_count
return nfa
def test_html_parse_2(self):
text = '<p><a href="https://news.yahoo.com/graham-trump-ukraine-incoherent-quid-pro-quo-192210175.html">' \
'<img src="http://l2.yimg.com/uu/api/res/1.2/aWhGys7_IW5qIjKaiJpPfg--/YXBwaWQ9eXRhY2h5b247aD04Njt' \
'3PTEzMDs-/https://media-mbst-pub-ue1.s3.amazonaws.com/creatr-uploaded-images/2019-11/5527ffe0-00' \
'ca-11ea-9f7d-d1e736c1315d" width="130" height="86" alt="Graham now says Trump's Ukraine poli' \
'cy was too 'incoherent' for quid pro quo" align="left" title="Graham now says Trump'' \
's Ukraine policy was too 'incoherent' for quid pro quo" border="0" ></a>A day after sayi' \
'ng he wouldn’t bother to read the testimony, Sen. Lindsey Graham now says he did read it, and hi' \
's conclusion is that the Trump administration’s Ukraine policy was too "incoherent" fo' \
'r it to have orchestrated the quid pro quo at the heart of the impeachment inquiry.<p><br clear="all">'
news = "A day after " \
"saying he wouldn’t bother to read the testimony, Sen. Lindsey Graham now says he did read it, and his " \
"conclusion is that the Trump administration’s Ukraine policy was too \"incoherent\" for it to have" \
" orchestrated the quid pro quo at the heart of the impeachment inquiry."
hand = Handler("https://news.yahoo.com/rss/", 3)
self.assertNotEqual(hand.parse_html(text), news)
def __init__(self, root: Tk, width: int, height: int, mediator: Mediator):
"""
initializes the canvas for further work with it.
creates instances of Board classes.
Generates the correct random playing field
"""
self._root = root
self._width = width
self._height = height
self._create_canvas()
self._score_points = 0
self.board_model = BoardModel(width, height)
self._board_view = BoardView(root, width, height, self._canvas,
mediator)
self._control = Handler(self)
self._set_random_board()
def main():
builder = Gtk.Builder()
builder.add_from_file("interface.glade")
window = builder.get_object("janelaPrincipal")
window.show_all()
window_object = builder.get_object("janelaNovoObjeto")
window_object.connect("delete-event", lambda w, e: w.hide() or True)
window_transform_object = builder.get_object("janelaTransformarObjeto")
window_transform_object.connect("delete-event",
lambda w, e: w.hide() or True)
window_choose_file = builder.get_object("janelaEscolherObj")
window_choose_file.connect("delete-event", lambda w, e: w.hide() or True)
drawing_area = builder.get_object("myDrawingArea")
builder.connect_signals(Handler(builder, drawing_area))
Gtk.main()
def __init__(self):
self.change = 0
self.handler = Handler()
self.handler.GetList()
self.top = tkinter.Tk()
self.b1 = Button(self.top, text="play", command=self.play)
self.label = tkinter.Label(self.top, text="")
self.text = Entry(self.top, bd=5)
self.b3 = Button(self.top,
text="delay",
command=lambda: self.delay(self.text.get()))
self.b4 = Button(self.top,
text="boost",
command=lambda: self.boost(self.text.get()))
self.b5 = Button(self.top, text="save", command=self.save)
self.b6 = Button(self.top, text="restart", command=self.restart)
self.b7 = Button(self.top,
text="detail_true",
command=lambda: self.detail(0))
self.b8 = Button(self.top,
text="detail_error",
command=lambda: self.detail(1))
self.b1.pack()
self.label.pack()
self.text.pack()
self.b3.pack()
self.b4.pack()
self.b5.pack()
self.b6.pack()
self.b7.pack()
self.b8.pack()
# b1.grid(row=0,column=1)
# label.grid(row=1,column=0)
# text.grid(row=2,column=0)
# b3.grid(row=2,column=1)
# b4.grid(row=2,column=2)
# b5.grid(row=3,column=1)
# b6.grid(row=3,column=2)
tkinter.mainloop()
def main():
parser = argparse.ArgumentParser(
description='Run your desired search algorithm on a graph :)')
parser.add_argument('--algorithm',
type=str,
help='BFS / DFS / UniformCost / A* / GreedyBestFirst',
required=True)
parser.add_argument('--graphFile',
type=str,
help='The path to .txt file containing your graph.',
required=True)
parser.add_argument(
'--heuristicFile',
type=str,
help='The path to .txt file containing your heuristics.',
required=False,
default=None)
parser.add_argument('--startNode', type=str, required=True)
parser.add_argument('--goalNode', type=str, required=True)
parser.add_argument(
'--treeSearch',
help=
'Use this switch if you want to perform tree search rather than graph search',
action='store_true')
args = parser.parse_args()
algo = args.algorithm
graph_file = args.graphFile
heu_file = args.heuristicFile
start_node = args.startNode
goal_node = args.goalNode
graph_search = not args.treeSearch
gm = GraphMaker(graph_file, heu_file)
heuristic_dict = gm.get_heuristic_dictionary()
adjacency_list = gm.get_adjacency_list()
h = Handler(algo, adjacency_list, heuristic_dict, start_node, goal_node,
graph_search)
h.handle()
def __init__(self):
self.client_tcp=None
self.operator="INV"
self.operandes="MATRICE"
self.matrix_list={}
self.builder=Gtk.Builder()
self.builder.add_from_file("./glade/LAC_Applicationwindow.glade")
self.window=self.builder.get_object("window")
self.spinner=self.builder.get_object('spinner')
self.ajouter_resultat_button=self.builder.get_object('ajouter_resultat_button')
self.sendsms_button=self.builder.get_object('sendsms_button')
self.delete_matrix_button=self.builder.get_object('delete_matrix_button')
self.edit_matrix_button=self.builder.get_object('edit_matrix_button')
self.premiere_op_box=self.builder.get_object("premiere_op_box")
self.deuxieme_op_box=self.builder.get_object("deuxieme_op_box")
self.operation_label=self.builder.get_object("operation_label")
self.premiere_op_label=self.builder.get_object("premiere_op_label")
self.comboboxtext1=self.builder.get_object("comboboxtext1")
self.famille_box1=self.builder.get_object("famille_box1")
self.deuxieme_op_label=self.builder.get_object("deuxieme_op_label")
self.comboboxtext2=self.builder.get_object("comboboxtext2")
self.famille_box2=self.builder.get_object("famille_box2")
self.spinbutton=self.builder.get_object("spinbutton")
self.treeview=self.builder.get_object("treeview")
self.combobox=self.builder.get_object("combobox")
self.resultat_matrix_box=self.builder.get_object("resultat_matrix_box")
self.liststore=Gtk.ListStore(str,int,int)
self.treeview.set_model(self.liststore)
renderer=Gtk.CellRendererText()
column=Gtk.TreeViewColumn("Nom",renderer,text=0)
self.treeview.append_column(column)
column=Gtk.TreeViewColumn("Nbr Ligne",renderer,text=1)
self.treeview.append_column(column)
column=Gtk.TreeViewColumn("Nbr Col",renderer,text=2)
self.treeview.append_column(column)
self.window.show_all()
self.error_label=self.builder.get_object("error_label")
self.resultat_label1=self.builder.get_object("resultat_label1")
self.resultat_label2=self.builder.get_object("resultat_label2")
self.textbuffer1=self.builder.get_object("textbuffer1")
self.textbuffer2=self.builder.get_object("textbuffer2")
self.ajouter_resultat_button.hide()
self.deuxieme_op_box.set_visible(False)
self.premiere_op_label.set_text("Choisir une matrice")
self.famille_box1.set_visible(False)
self.error_label.hide()
self.resultat_label2.hide()
self.resultat_label1.hide()
self.combobox1_type="MATRICE"
self.combobox2_type=""
self.builder.connect_signals(Handler(self))
def create_client_handler(self, conn, id_client):
key_ = "client_" + str(id_client)
handler = Handler(self, conn, cnf.type_receivers['client'],
id_client) # тип возвращается функцией аутотификации
self.list_handlers[key_] = handler
handler.start()
import sys
import time
import logging
from watchdog.observers import Observer
from watchdog.events import LoggingEventHandler
from watchdog.events import FileSystemEventHandler
from Handler import Handler
import os.path
import json
from webapp import Server
path_lists = []
if __name__ == "__main__":
path = sys.argv[1] if len(sys.argv) > 1 else '.'
event_handler = Handler()
event_handler.load_handler()
observer = Observer()
observer.schedule(event_handler, path, recursive=True)
observer.start()
if (len(sys.argv) < 4):
print("Please specify a host and port")
exit()
try:
Server.start(sys.argv[len(sys.argv) - 2], sys.argv[len(sys.argv) - 1])
except KeyboardInterrupt:
observer.stop()
observer.join()
from xml.sax import make_parser
from Handler import Handler
f = open('partial.xml')
hd = Handler()
saxparser = make_parser()
saxparser.setContentHandler(hd)
saxparser.setDTDHandler(hd)
saxparser.parse(f)
import Parser as par
from Handler import Handler
import textpool
from Exceptions import *
import os
import time
handler = Handler()
class Goda:
def __init__(self):
self.name = "Main"
self.cmd = " "
self.ds = " "
self.usercmd = " "
self.names = {}
def simple_help():
print(textpool.help_txt)
def cmd_help(cmd):
if cmd == 'run':
handler.imp_cmd_help()
else:
print(textpool.help_cmd.get(cmd))
def run_cmd(ds):
with open(stri + hist_json_file, mode='w') as f:
hist_df.to_json(f)
# or save to csv:
hist_csv_file = 'history.csv'
with open(stri + hist_csv_file, mode='w') as f:
hist_df.to_csv(f)
if __name__ == '__main__':
#x_train1, x_test1 = configureDataset()
dir_train = "C:\\Users\\lucas\\PycharmProjects\\Autoencoder\\data\\training"
dir_test = "C:\\Users\\lucas\\PycharmProjects\\Autoencoder\\data\\test"
Handler(dir_train).write_data(0)
Handler(dir_test).write_data(1)
x_train = Handler().read_datafile("X_train")
x_test = Handler().read_datafile("X_test")
if not os.path.isdir('IN/'):
os.makedirs('IN/')
save_img(x_test, 'IN/')
filters = []
x = 8
while x <= 32:
y = 8
from Handler import Handler
handle = Handler()
handle.createLibraryDirectory('changoma')
handle.createLibraryDirectory('pinche_putito')
obj = ['changoma', 'chango', 'paloma']
handle.addObjectToLibrary('changoma', obj)
def __init__(self):
self.Handler = Handler()
def receiver(conn):
while True:
request = conn.recv(4096)
Handler(request)
data = "received"
conn.send(data)
def create_PP_handler(self, conn, id_pp):
key_ = str(id_pp) + "_pp"
handler = Handler(self, conn, cnf.type_receivers['pp'],
id_pp) # тип возвращается функцией аутотификации
self.list_handlers[key_] = handler
handler.start()
def __init__(self):
self.__handler = Handler()
self.__has_presc = None
self.__order_type = None
