def mirrorSkint(hours):
# 6.14.16测试
# 从cimiss中获取所有站点地温插值,hours控制选取的时间间隔
interfaceId = 'getSurfEleInRegionByTimeRange'
elements = "Station_Id_C,Lat,Lon,GST,Year,Mon,Day,Hour"
# 设定每天8：00、 20:00运行
lastime = datetime.datetime.now().replace(
minute=0, second=0) - datetime.timedelta(hours=8)
firstime = lastime - datetime.timedelta(hours=hours)
temp = ('[', firstime.strftime('%Y%m%d%H%M%S'), ',',
lastime.strftime('%Y%m%d%H%M%S'), ')')
Time = ''.join(temp)
params = {
'dataCode': "SURF_CHN_MUL_HOR", # 需更改为地面逐小时资料
'elements': elements,
'timeRange': Time,
'adminCodes': "630000"
}
initData = Datainterface.cimissdata(interfaceId, elements,
**params) # 获取出cimiss初始数据
initData.Time = pd.to_datetime(initData.Time)
# 需按时间进行划分插值，得到 地温网格数据
timeList = pd.to_datetime(initData.Time.unique()).strftime(
'%Y%m%d%H%M%S') # 此处可能存在问题，目的仅按顺序取出来时间
initData.set_index(initData.Time, inplace=True)
oneHourgrid = [
np.nan_to_num(
interp.interpolateGridData(
initData.loc[tm].GST.values.astype('float32'),
initData.loc[tm].Lat.values.astype('float32'),
initData.loc[tm].Lon.values.astype('float32'), glovar.lat,
glovar.lon)) for tm in timeList
]
return oneHourgrid # oneHourgrid 格点数据形状应为[12, newlat, newlon]
def mirrorskskt(newlat, newlon, hours=1):
# 6.14.16测试
# 从cimiss中获取所有站点地温插值,hours控制选取的时间间隔
interfaceId = 'getSurfEleInRegionByTimeRange'
elements = "Station_Id_C,Lat,Lon,GST,Year,Mon,Day,Hour"
# 设定每天8：00、 20:00运行
lastime = datetime.datetime.now().replace(
minute=0, second=0) - datetime.timedelta(hours=8)
firstime = lastime - datetime.timedelta(hours=hours)
temp = ('[', firstime.strftime('%Y%m%d%H%M%S'), ',',
lastime.strftime('%Y%m%d%H%M%S'), ']')
Time = ''.join(temp)
params = {
'dataCode': "SURF_CHN_MUL_HOR", # 需更改为地面逐小时资料
'elements': elements,
'timeRange': Time,
'adminCodes': "630000"
}
initData = Datainterface.cimissdata(interfaceId, elements,
**params) # 获取出cimiss初始数据
initData.Time = pd.to_datetime(initData.Time)
# 需按时间进行划分插值，得到 地温网格数据
timeList = pd.to_datetime(initData.Time.unique()).strftime(
'%Y%m%d%H%M%S') # 此处可能存在问题，目的仅按顺序取出来时间
initData.set_index(initData.Time, inplace=True)
oneHourgrid = [
np.nan_to_num(
interp.interpolateGridData(
initData.loc[tm].GST.values.astype('float32'),
initData.loc[tm].Lat.values.astype('float32'),
initData.loc[tm].Lon.values.astype('float32'), glovar.lat,
glovar.lon)) for tm in timeList
]
Time = datetime.datetime.now().strftime('%Y%m%d%H')
savepath = ''.join(r'/home/cqkj/QHTraffic/tmp/skt', Time, r'.pkl')
with open(savepath, 'rb') as f: # 文件名用时间区分精确到小时，供updateSnow使用
pickle.dump(oneHourgrid, f)
return oneHourgrid