def __init__(self, next_position_x=0, next_position_y=0, position_difference_x=0,
position_difference_y=0, is_two_dimensional=False, final_movement=False, count=0):
self.count = count
self.poppy = PoppyHumanoid()
self.is_two_dimensional=is_two_dimensional
if self.is_two_dimensional is True:
if self.count is 0:
self.speed_obj = speed.Speed()
self.initialize_robot()
else:
self.position_difference_x = position_difference_x
self.position_difference_y = position_difference_y
self.final_movement = final_movement
self.next_position_y = next_position_x
self.next_position_y = next_position_y
self.speed_obj = speed.Speed()
else:
if self.count is 0:
self.initialize_robot()
else:
self.position_difference_x = position_difference_x
self.final_movement = final_movement
self.next_position_x = next_position_x
self.speed_obj = speed.Speed()
def start_speed_mode(self, linear):
# Kill any previous Challenge / RC mode
self.stop_threads()
# Set Wiimote LED to RC Mode index
if linear:
self.current_mode = Mode.MODE_SPEED_LINEAR
style = "LINEAR"
else:
self.current_mode = Mode.MODE_SPEED
style = None # Default to whatever.
# Set sensible speed
self.core.set_speed_factor(0.35)
# Inform user we are about to start RC mode
logging.info("Entering into SPEED Mode")
self.challenge = speed.Speed(self.core, self.oled, style)
# Create and start a new thread
# running the remote control script
logging.info("Starting SPEED Thread")
self.challenge_thread = threading.Thread(target=self.challenge.run)
self.challenge_thread.start()
logging.info("SPEED Thread Running")
def __init__(self, options, config):
"""Initializes all of the submodules bitHopper uses"""
#Logging
logging.basicConfig(stream=sys.stdout, format="%(asctime)s|%(module)s: %(message)s", datefmt="%H:%M:%S", level = logging.INFO)
self.options = options
self.config = config
altercoins = ConfigParser.ConfigParser()
altercoins.read(os.path.join(sys.path[0], "whatevercoin.cfg"))
self.altercoins = {}
for coin in altercoins.sections():
self.altercoins[coin] = dict(altercoins.items(coin))
self.altercoins[coin]['recent_difficulty'] = float(self.altercoins[coin]['recent_difficulty'])
self.scheduler = None
self.lp_callback = lp_callback.LP_Callback(self)
self.difficulty = diff.Difficulty(self)
self.exchange = exchange.Exchange(self)
self.pool = None
self.db = database.Database(self)
self.pool = pool.Pool_Parse(self)
self.api = api.API(self)
self.pool.setup(self)
self.work = work.Work(self)
self.speed = speed.Speed()
self.getwork_store = getwork_store.Getwork_store(self)
self.data = data.Data(self)
self.lp = lp.LongPoll(self)
self.auth = None
self.website = website.bitSite(self)
self.pile = greenpool.GreenPool()
self.plugin = plugin.Plugin(self)
self.pile.spawn_n(self.delag_server)
matplotlib.use('pgf')
import matplotlib.pyplot as plt
#import mpl_toolkits.axisartist as axisartist
font_size = 8
fig_width = 3.0
font = {'family': 'serif', 'serif': ['Times'], 'size': font_size}
plt.rc('text', usetex=True)
plt.rc('font', family='serif')
plt.rcParams['text.latex.preamble'] = r'\usepackage{siunitx}'
#matplotlib.rc('font', **font)
speed_data = speed.Speed()
accuracy_data = accuracy.Accuracy()
speed_averages = {}
speed_per_mat_element = {}
accuracy_averages = {}
accuracy_per_mat_element = {}
series_to_rowcount = {}
series_to_rowcount[1000.0] = 3000.0
series_to_rowcount[2000.0] = 5400.0
series_to_rowcount[3000.0] = 8526.0
series_to_rowcount[4000.0] = 12288.0
series_to_rowcount[6000.0] = 18468.0
series_to_rowcount[8000.0] = 24000.0
series_to_rowcount[12000.0] = 33396.0
model.load_weights(weights_path, weights_path, by_name=True)
#model.load_weights(weights_path, weights_path, by_name=True, exclude=["ori_final"]) # tmp
dataset_dir = os.path.join(DATA_DIR, args.dataset)
# Train or evaluate
if args.command == "train":
# Load training and validation set
if args.dataset != "speed":
dataset_train = urso.Urso()
dataset_train.load_dataset(dataset_dir, model.config, "train")
dataset_val = urso.Urso()
dataset_val.load_dataset(dataset_dir, model.config, "val")
else:
dataset_train = speed.Speed()
dataset_train.load_dataset(dataset_dir, model.config,
"train_no_val") # 'train_total') #
dataset_val = speed.Speed()
dataset_val.load_dataset(dataset_dir, model.config, "val")
train(model, dataset_train, dataset_val)
elif args.command == "test":
if args.video:
dataset = urso.Urso()
dataset.load_dataset(dataset_dir, config, "test")
detect_video(model, dataset, args.video)
else:
# Load validation dataset