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)