def mosrun_live(starttime):
#1. 首先是下载EC数据，
# yearint=datetime.datetime.now().year
# hours=datetime.datetime.now().hour
yearint = starttime.year
hours = starttime.hour
if hours >= 17:
datestr = datetime.datetime.strftime(starttime, '%Y-%m-%d')
pdatetimestring00 = datestr + " 00:00:00"
print "2018-08-21 00:00:00"
else:
nowdate = starttime + datetime.timedelta(days=-1)
datestr = datetime.datetime.strftime(nowdate, '%Y-%m-%d')
pdatetimestring00 = datestr + ' 12:00:00'
initial_datetime = datetime.datetime.strptime(pdatetimestring00,
'%Y-%m-%d %H:%M:%S')
#2.拷贝解压EC数据,线上的数据是拷贝的
oldfilepath = '/opt/meteo/cluster/data/ecmwf/orig'
dirpath = '/moji/ecdata'
print "2018-08-21 00:00:00-----------------------------------------------------------"
ecpath = copyAndUnzipfile(initial_datetime, oldfilepath, dirpath)
logger.info(ecpath)
#3.DEM模型预测
# path = '/moji/ecdata'
outpath = '/home/wlan_dev/result'
csvfile = '/home/wlan_dev/stations.csv'
demcsv = '/mnt/data/dem.csv'
modelProdict(ecpath, outpath, csvfile, demcsv, starttime)
#4.准确率计算
calculateAccuracy(initial_datetime)
# 模型预测和准确率计算
modelpredict001(ecpath, outpath, csvfile, starttime)
calculateAccuracy001(initial_datetime)
print ecpath
def run():
#1. 首先是下载EC数据，
starttime = datetime.datetime.now()
yearint = datetime.datetime.now().year
hours = datetime.datetime.now().hour
if hours > 17:
datestr = datetime.datetime.strftime(starttime, '%Y-%m-%d')
pdatetimestring00 = datestr + " 00:00:00"
else:
nowdate = starttime + datetime.timedelta(days=-1)
datestr = datetime.datetime.strftime(nowdate, '%Y-%m-%d')
pdatetimestring00 = datestr + ' 12:00:00'
initial_datetime = datetime.datetime.strptime(pdatetimestring00,
'%Y-%m-%d %H:%M:%S')
downloadECdatafrombigdata_processing(initial_datetime)
#2.解压EC数据
oldfilepath = '/opt/meteo/cluster/data/ecmwf/orig'
dirpath = '/moji/ecdata'
ecpath = unzipfile(oldfilepath, dirpath)
logger.info(ecpath)
#3.DEM模型预测
# path = '/moji/ecdata'
outpath = '/home/wlan_dev/result'
csvfile = '/home/wlan_dev/stations.csv'
demcsv = '/mnt/data/dem.csv'
modelProdict(ecpath, outpath, csvfile, demcsv, starttime)
#4.准确率计算
calculateAccuracy(initial_datetime)
# 模型预测和准确率计算
modelpredict001(ecpath, outpath, csvfile, starttime)
calculateAccuracy001(initial_datetime)
#5.删除EC数据
if hours < 12:
print ecpath
deleteECMWF(ecpath)
def mosrun_history(starttime):
#1. 首先是下载EC数据，
# yearint=datetime.datetime.now().year
# hours=datetime.datetime.now().hour
yearint = starttime.year
hours = starttime.hour
if hours > 17:
datestr = datetime.datetime.strftime(starttime, '%Y-%m-%d')
pdatetimestring00 = datestr + " 00:00:00"
print "2018-08-21 00:00:00"
else:
nowdate = starttime + datetime.timedelta(days=-1)
datestr = datetime.datetime.strftime(nowdate, '%Y-%m-%d')
pdatetimestring00 = datestr + ' 12:00:00'
initial_datetime = datetime.datetime.strptime(pdatetimestring00,
'%Y-%m-%d %H:%M:%S')
logger.info(initial_datetime)
#传入时间为00点或者是12点
downloadECdatafrombigdata(initial_datetime)
#2.解压EC数据
dirpath = '/moji/ecdata'
print "2018-08-21 00:00:00-----------------------------------------------------------"
ecpath = unzipfile(initial_datetime, dirpath)
print ecpath + '==================================================================='
#3.DEM模型预测
# path = '/moji/ecdata'
outpath = '/home/wlan_dev/result'
csvfile = '/home/wlan_dev/stations.csv'
demcsv = '/mnt/data/dem.csv'
modelProdict(ecpath, outpath, csvfile, demcsv, initial_datetime)
#4.准确率计算
calculateAccuracy(initial_datetime)
# 模型预测和准确率计算
modelpredict001(ecpath, outpath, csvfile, starttime)
calculateAccuracy001(initial_datetime)
print ecpath
#5.删除EC数据
if hours < 12:
deleteECMWF(ecpath)