def circulation_bak(self, code: str):
'''
循环写入
:return:
'''
x_index = 0
y_index = 0
for y_trajectory_temp in range(self.get_y_trajectory - 1):
# 0-99
for x_time_temp in range(self.get_x_time - 1):
# 0-24
wind_temp = model.WindModel(
x=self.ds['x_wind'][y_trajectory_temp, x_time_temp],
y=self.ds['y_wind'][y_trajectory_temp, x_time_temp])
current_temp = model.CurrentModel(
x=self.ds['x_sea_water_velocity'][y_trajectory_temp,
x_time_temp],
y=self.ds['x_sea_water_velocity'][y_trajectory_temp,
x_time_temp])
# point = [all_data['lon'][i], all_data['lat'][i]]
point_temp = [
round(self.ds['lon'][y_trajectory_temp,
x_time_temp].item()),
round(self.ds['lat'][y_trajectory_temp,
x_time_temp].item())
]
time_temp = self.get_time_data[x_time_temp]
status_temp = self.ds['status'][y_trajectory_temp, x_time_temp]
search_model = model.SearchRescueModel(
time=time_temp,
point=point_temp,
current=current_temp,
wind=wind_temp,
status=status_temp,
code=code,
num=str(y_trajectory_temp))
search_model.save()
x_index = x_index + 1
y_index = y_index + 1
pass
def insert_avg_data():
'''
插入当前的所有点的平均值
:return:
:rtype:
'''
# 对当前的时间对应的所有点进行平均
# 0-24
wind_temp = model.WindModel(
x=self._all_data_dict['x_wind'][:].T[x_time_temp].mean(),
y=self._all_data_dict['y_wind'][:].T[x_time_temp].mean())
current_temp = model.CurrentModel(
x=self._all_data_dict['x_sea_water_velocity']
[:].T[x_time_temp].mean(),
y=self._all_data_dict['x_sea_water_velocity']
[:].T[x_time_temp].mean())
point_temp = [
round(
self._all_data_dict['lon'][:].T[x_time_temp].mean().item(),
4),
round(
self._all_data_dict['lat'][:].T[x_time_temp].mean().item(),
4)
]
time_temp = self.get_time_data[x_time_temp]
status_temp = self._all_data_dict['status'][:].T[x_time_temp].mean(
)
# 质量model
mass_temp = model.MassModel(
oil=self._all_data_dict['mass_oil'][:].T[x_time_temp].mean(),
evaporated=self._all_data_dict['mass_evaporated']
[:].T[x_time_temp].mean(),
dispersed=self._all_data_dict['mass_dispersed']
[:].T[x_time_temp].mean())
# 油的model
oil_temp = model.OilModel(
density=self._all_data_dict['density']
[:].T[x_time_temp].mean(),
film_thickness=self._all_data_dict['oil_film_thickness']
[:].T[x_time_temp].mean())
wt_temp = self._all_data_dict['sea_water_temperature'][:].T[
x_time_temp].mean()
water_fraction = self._all_data_dict['water_fraction'][:].T[
x_time_temp].mean()
oil_avg_model = model.OilspillingAvgModel(
time=time_temp,
point=point_temp,
current=current_temp,
wind=wind_temp,
status=status_temp,
code=code,
wt=wt_temp,
mass=mass_temp,
water_fraction=water_fraction,
oil=oil_temp)
try:
oil_avg_model.save()
print(f'- 写入avg成功，当前位置[x:{x_time_temp}]')
except Exception as err:
print(f'x 保存avg异常，出现异常位置[x:{x_time_temp}]')
def circulation_trajectory_bak(self, x_time_temp: int, code: str):
for y_trajectory_temp in range(self.get_y_trajectory - 1):
# 0-73
wind_temp = model.WindModel(x=self.ds['x_wind'][y_trajectory_temp,
x_time_temp],
y=self.ds['y_wind'][y_trajectory_temp,
x_time_temp])
current_temp = model.CurrentModel(
x=self.ds['x_sea_water_velocity'][y_trajectory_temp,
x_time_temp],
y=self.ds['y_sea_water_velocity'][y_trajectory_temp,
x_time_temp])
# point = [all_data['lon'][i], all_data['lat'][i]]
point_temp = [
round(self.ds['lon'][y_trajectory_temp, x_time_temp].item(),
6),
round(self.ds['lat'][y_trajectory_temp, x_time_temp].item(), 6)
]
time_temp = self.get_time_data[x_time_temp]
status_temp = self.ds['status'][y_trajectory_temp, x_time_temp]
# 质量model
mass_temp = model.MassModel(
oil=self.ds['mass_oil'][y_trajectory_temp, x_time_temp],
evaporated=self.ds['mass_evaporated'][y_trajectory_temp,
x_time_temp],
dispersed=self.ds['mass_dispersed'][y_trajectory_temp,
x_time_temp])
# 油的model
# TODO:[*] 19-09-19 注意self.ds['density']对数组进行索引是一个masked_array
# 有可能是masked的，所以需要判断
oil_temp = model.OilModel(
density=self.ds['density'][y_trajectory_temp, x_time_temp]
if self.ds['density'][y_trajectory_temp,
x_time_temp].mask == True else None,
film_thickness=self.ds['oil_film_thickness'][y_trajectory_temp,
x_time_temp]
if self.ds['oil_film_thickness'][y_trajectory_temp,
x_time_temp].mask == True else
None)
wt_temp = self.ds['sea_water_temperature'][y_trajectory_temp, x_time_temp] if \
self.ds['sea_water_temperature'][
y_trajectory_temp, x_time_temp].mask == True else None
water_fraction = self.ds['water_fraction'][
y_trajectory_temp, x_time_temp] if self.ds['water_fraction'][
y_trajectory_temp, x_time_temp].mask == True else None
# TODO:[*] 19-09-19 此处的思路 若出现--的这种情况，直接跳过，不用save了
# 若为np.nan 的话直接跳过，不处理
if (wt_temp == np.nan) is False:
oil_model = model.OilSpillingModel(
time=time_temp,
point=point_temp,
current=current_temp,
wind=wind_temp,
status=status_temp,
code=code,
wt=wt_temp,
mass=mass_temp,
water_fraction=water_fraction,
oil=oil_temp)
try:
oil_model.save()
except Exception as err:
print(
f'保存 oil_model 出现异常，出现异常位置[x:{x_time_temp},y:{y_trajectory_temp}]'
)
# y_index = y_index + 1
# 对当前的时间对应的所有点进行平均
# 0-24
wind_temp = model.WindModel(
x=self.ds['x_wind'][:].T[x_time_temp].mean(),
y=self.ds['y_wind'][:].T[x_time_temp].mean())
current_temp = model.CurrentModel(
x=self.ds['x_sea_water_velocity'][:].T[x_time_temp].mean(),
y=self.ds['x_sea_water_velocity'][:].T[x_time_temp].mean())
point_temp = [
round(self.ds['lon'][:].T[x_time_temp].mean().item(), 4),
round(self.ds['lat'][:].T[x_time_temp].mean().item(), 4)
]
time_temp = self.get_time_data[x_time_temp]
status_temp = self.ds['status'][:].T[x_time_temp].mean()
# 质量model
mass_temp = model.MassModel(
oil=self.ds['mass_oil'][:].T[x_time_temp].mean(),
evaporated=self.ds['mass_evaporated'][:].T[x_time_temp].mean(),
dispersed=self.ds['mass_dispersed'][:].T[x_time_temp].mean())
# 油的model
oil_temp = model.OilModel(
density=self.ds['density'][:].T[x_time_temp].mean(),
film_thickness=self.ds['oil_film_thickness']
[:].T[x_time_temp].mean())
wt_temp = self.ds['sea_water_temperature'][:].T[x_time_temp].mean()
water_fraction = self.ds['water_fraction'][:].T[x_time_temp].mean()
oil_avg_model = model.OilspillingAvgModel(
time=time_temp,
point=point_temp,
current=current_temp,
wind=wind_temp,
status=status_temp,
code=code,
wt=wt_temp,
mass=mass_temp,
water_fraction=water_fraction,
oil=oil_temp)
try:
oil_avg_model.save()
except Exception as err:
print(f'保存avg出现异常，出现异常位置[x:{x_time_temp},y:{y_trajectory_temp}]')
print(f'[-] 当前处理第:{x_time_temp},共:{self.get_x_time - 1}')
def insert_real_data():
'''
插入实时数据(每个散点的值)
:return:
:rtype:
'''
for y_trajectory_temp in range(self.get_y_trajectory - 1):
# 0-73
wind_temp = model.WindModel(
x=self._all_data_dict['x_wind'][y_trajectory_temp,
x_time_temp],
y=self._all_data_dict['y_wind'][y_trajectory_temp,
x_time_temp])
current_temp = model.CurrentModel(
x=self._all_data_dict['x_sea_water_velocity'][
y_trajectory_temp, x_time_temp],
y=self._all_data_dict['y_sea_water_velocity'][
y_trajectory_temp, x_time_temp])
# point = [all_data['lon'][i], all_data['lat'][i]]
point_temp = [
round(
self._all_data_dict['lon'][y_trajectory_temp,
x_time_temp].item(), 6),
round(
self._all_data_dict['lat'][y_trajectory_temp,
x_time_temp].item(), 6)
]
time_temp = self.get_time_data[x_time_temp]
status_temp = self._all_data_dict['status'][y_trajectory_temp,
x_time_temp]
# 质量model
mass_temp = model.MassModel(
oil=self._all_data_dict['mass_oil'][y_trajectory_temp,
x_time_temp],
evaporated=self._all_data_dict['mass_evaporated'][
y_trajectory_temp, x_time_temp],
dispersed=self._all_data_dict['mass_dispersed'][
y_trajectory_temp, x_time_temp])
# 油的model
# TODO:[*] 19-09-19 注意self.ds['density']对数组进行索引是一个masked_array
# 有可能是masked的，所以需要判断
oil_temp = model.OilModel(
density=self._all_data_dict['density'][y_trajectory_temp,
x_time_temp]
if self._all_data_dict['density'][y_trajectory_temp,
x_time_temp].mask == True
else None,
film_thickness=self._all_data_dict['oil_film_thickness']
[y_trajectory_temp,
x_time_temp] if self._all_data_dict['oil_film_thickness'][
y_trajectory_temp,
x_time_temp].mask == True else None)
wt_temp = self._all_data_dict['sea_water_temperature'][y_trajectory_temp, x_time_temp] if \
self._all_data_dict['sea_water_temperature'][
y_trajectory_temp, x_time_temp].mask == True else None
water_fraction = self._all_data_dict['water_fraction'][y_trajectory_temp, x_time_temp] if \
self._all_data_dict['water_fraction'][
y_trajectory_temp, x_time_temp].mask == True else None
# TODO:[*] 19-09-19 此处的思路 若出现--的这种情况，直接跳过，不用save了
# 若为np.nan 的话直接跳过，不处理
if (wt_temp == np.nan) is False:
# TODO:[*] 20-04-20 : DatetimeGregorian 2020-04-19 12:00:00
oil_model = model.OilSpillingModel(
time=time_temp,
point=point_temp,
current=current_temp,
wind=wind_temp,
status=status_temp,
code=code,
wt=wt_temp,
mass=mass_temp,
water_fraction=water_fraction,
oil=oil_temp)
try:
oil_model.save()
except Exception as err:
print(
f'保存 oil_model 出现异常，出现异常位置[x:{x_time_temp},y:{y_trajectory_temp}]'
)
# y_index = y_index + 1
pass