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