def attribute_init(self):
self.device_choice_ui = None
self.create_scene_view = None
self.a2dp_mac = None
default_config = read_config(constant.CONFIG_FILE)
self.channel_switch_interval = default_config['scene_tv']['channel_switch_interval']['val']*3600
self.performance_interval = default_config['scene_tv']['performance_interval']['val']*3600
self.performance_str = ''
self.check_interval = default_config['scene_tv']['check_interval']['val']*3600
def remove_scene(index: int) -> bool:
"""
通过索引移除场景
:param index:
:return:
"""
scenes = config_utils.read_config(constant.SCENE_FILE)
if 0 <= index < len(scenes):
scenes.pop(index)
config_utils.write_config(constant.SCENE_FILE, scenes)
return True
return False
def run(config, epochs, n_workers=1, resume=False, updates=None, verbose=1):
"""Main runner that dynamically imports and executes other modules
"""
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
cfg = config_utils.read_config(config)
if updates is not None:
cfg = config_utils.update_config(cfg, updates)
log_utils.print_experiment_info(cfg['experiment'], cfg['out_dir'])
tensorboard_logdir, checkpoints_logdir = \
log_utils.prepare_dirs(cfg['experiment'], cfg['out_dir'], resume)
train_loaders, test_loaders = import_data_loaders(cfg, n_workers, verbose)
model, model_manager = import_models(cfg, checkpoints_logdir, device,
verbose)
losses, metrics = import_losses_and_metrics(cfg)
tensorboard_writer = SummaryWriter(tensorboard_logdir)
trainer_def = trainers.load_trainer(cfg['trainer']['name'])
trainer = trainer_def(device=device,
model=model,
losses=losses,
metrics=metrics,
train_loaders=train_loaders,
test_loaders=test_loaders,
model_manager=model_manager,
tensorboard_writer=tensorboard_writer,
**cfg['trainer']['kwargs'])
starting_epoch = model_manager.last_epoch + 1
last_epoch = starting_epoch
for epoch in range(starting_epoch, starting_epoch + epochs):
eval_losses, eval_metrics = trainer.run_epoch(epoch)
last_epoch += 1
if 'saving_freq' in cfg:
if (epoch + 1) % cfg['saving_freq'] == 0:
model_manager.save_model(model, eval_losses, epoch)
if trainer.early_stop():
log_utils.print_early_stopping()
break
unzip(hydra=model,
losses=losses,
metrics=metrics,
loaders=train_loaders,
device=device,
from_epoch=last_epoch)
tensorboard_writer.close()
def _parse_profile(self) -> dict:
"""
解析默认逻辑monkey的配置文件
:return:
"""
ret = {}
settings = config_utils.read_config(self.profile)
packages = self.device.tv.send_cmd_get_result(
'pm list packages | busybox awk -F ":" \'{print $2}\'')
packages = packages.split('\r\n')
for key, value in settings.items():
if key in packages:
ret[key] = value
return ret
def __init__(self, brand_list: list, interval: int, device: dv.Device, local_video: dict, profile: str, mpf: pf.Performance):
super(MediaBrandSwitchThread, self).__init__()
self.brand_list = brand_list
self.interval = interval
self.device = device
self.cur_brand = ''
self.local_video = local_video
self.pf = mpf
self.settings = config_utils.read_config(profile)
logging.debug(f'brand_list {self.brand_list}\n'
f'interval {self.interval}\n'
f'local_video {self.local_video}\n'
f'settings {self.settings}')
if len(brand_list) < 1:
raise ValueError('brand list must not null')
def __init__(self):
super(Ui_MainWindow, self).__init__()
self.setupUi(self)
self.setWindowFlags(Qt.WindowCloseButtonHint)
self.setFixedSize(self.width(), self.height())
self.default_config = read_config(constant.CONFIG_FILE)
self.videomode = None
self.attribute_init()
self.online_list = [
self.checkBox, self.checkBox_2, self.checkBox_3, self.checkBox_4,
self.checkBox_8, self.checkBox_9, self.checkBox_10,
self.checkBox_11, self.checkBox_12, self.checkBox_14,
self.checkBox_17, self.checkBox_15, self.checkBox_20,
self.checkBox_18
]
self.online_dict = {
"腾讯视频": False,
"爱奇艺": False,
"酷喵": False,
"QQ音乐MV": False,
"QQ音乐": False,
"HDP": False,
"电视家": False,
"本地视频_大码率": False,
"信源": False,
"本地视频_混合编解码": False,
"遥控器是否回连成功": False,
"近场唤醒是否成功": False,
"蓝牙音箱是否回连成功": False,
"远场唤醒是否成功": False
}
self.to_screen_list = [
self.checkBox_19, self.checkBox_22, self.checkBox_23,
self.checkBox_21, self.checkBox_16, self.checkBox_31,
self.checkBox_32
]
self.to_screen_dict = {
"乐播投屏": False,
"dlna投屏": False,
"miracast（无线投屏）": False,
"遥控器是否回连成功 ": False,
"近场唤醒是否成功": False,
"蓝牙音箱是否回连成功": False,
"远场唤醒是否成功": False
}
self.buttton_init()
def create_kk_record_scene():
"""
创建脚本录制场景
:return:
"""
try:
directory, exe = _init()
except BaseException as e:
logging.exception(e)
return False, str(e)
scene_file = os.path.join(directory, 'src', 'scene')
file_utils.rm(scene_file)
cmd = exe + ' -c'
_run_cmd(cmd)
if not os.path.isfile(scene_file):
return False, f'录制脚本场景创建失败， 未发现文件:{scene_file}'
return True, config_utils.read_config(scene_file)
def __init__(self,
name: str,
exec_time: int,
checker: ck.Checker,
scripts: (list, str),
by: int = sc.BY_COUNT):
sc.Scene.__init__(self,
name=name,
exec_time=exec_time,
by=by,
checker=checker)
if isinstance(scripts, list):
self.scripts = scripts
elif isinstance(scripts, str):
if not os.path.isfile(scripts):
raise AssertionError(f'illegal scripts : {scripts}')
self.scripts = config_utils.read_config(scripts)
else:
raise AssertionError(f'illegal scripts : {scripts}')
def __init__(self):
super(Ui_MainWindow, self).__init__()
self.setupUi(self)
self.setWindowFlags(Qt.WindowCloseButtonHint)
self.setFixedSize(self.width(), self.height())
self.default_config = read_config(constant.CONFIG_FILE)
self.mode = 0
self.attribute_init()
self.monkeyGlobal_list = [
self.checkBox_23, self.checkBox_18, self.checkBox_15,
self.checkBox_24, self.checkBox_16, self.checkBox_21,
self.checkBox_20
]
self.monkeyGlobal_dict = {
"远场唤醒是否成功": False,
"网络连接是否正常": False,
"近场唤醒是否成功": False,
"蓝牙音箱是否回连成功": False,
"USB挂载正常,U盘个数：": False,
"摄像头是否正常": False,
"遥控器是否回连成功": False
}
self.monkeyLogic_list = [
self.checkBox_19, self.checkBox_17, self.checkBox_22,
self.checkBox_35, self.checkBox_36, self.checkBox_37,
self.checkBox_38
]
self.monkeyLogic_dict = {
"近场语音是否唤醒正常": False,
"网络连接是否正常": False,
"远场语音是否唤醒正常": False,
"摄像头是否正常": False,
"蓝牙遥控器是否回连成功": False,
"蓝牙音箱是否回连成功": False,
"USB挂载正常,U盘个数：": False
}
self.buttton_init()
from pathlib import Path
import pandas as pd
from utils import config_utils
config_path = "./config.yaml"
config = config_utils.read_config(config_path)
def merge_date_data():
train_path = Path(config["datas"]["train_path"])
for date_path in train_path.glob("*"):
df_non_ts = pd.read_csv(date_path / "non_ts.csv", index_col="id")
df_y = pd.read_csv(date_path / "y.csv")
merge_df = pd.merge(df_non_ts, df_y, on="id")
for ts_path in date_path.glob("ts_*.csv"):
ts_name = ts_path.name.split(".csv")[0]
df_ts = pd.read_csv(ts_path, index_col="id")
df_ts_std = get_std(df_ts, ts_name)
merge_df = pd.merge(merge_df, df_ts_std, on="id")
df_ts_mean_0_5 = get_mean_0_5(df_ts, ts_name)
merge_df = pd.merge(merge_df, df_ts_mean_0_5, on="id")
df_ts_mean_0_20 = get_mean_0_20(df_ts, ts_name)
merge_df = pd.merge(merge_df, df_ts_mean_0_20, on="id")
print(merge_df.head())
def scene_list():
"""
获取场景列表
:return:
"""
return config_utils.read_config(constant.SCENE_FILE)
def setUp(self):
self.config = config_utils.read_config("./config.yaml")
self.test_df = pd.read_csv(self.config["datas"]["origin_train_path"] + "/20130201/non_ts.csv", index_col="id")
self.du = data_utils.DataUtils(self.config)
from utils import log
from model.main_test_1 import Entrance_View
import sys
from PyQt5 import QtWidgets
from utils.config_utils import read_config
import constant
if __name__ == '__main__':
log_dir = read_config(constant.CONFIG_FILE)['tool_config']['log_dir']
output = True if read_config(
constant.CONFIG_FILE)['tool_config']['output'] == 'True' else False
log.init_logging_dir(log_dir, output=output)
app = QtWidgets.QApplication(sys.argv) # 外部参数列表
ui = Entrance_View()
ui.show()
sys.exit(app.exec_())
