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)
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
#给定时间世界时大于17计算本天的，否则计算昨天的12点的
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')
#传入时间为00点或者是12点
downloadECdatafrombigdata(initial_datetime)
#2.解压EC数据
dirpath='/home/wlan_dev/mosdata'
print "-----------------------------------------------------------"
ecpath=unzipfile(initial_datetime,dirpath)
print ecpath+'==================================================================='
#3.DEM模型预测
# path = '/moji/ecdata'
outpath = '/home/wlan_dev/mos/mosresult'
csvfile = '/mnt/data/mosfile/stations.csv'
demcsv = '/mnt/data/mosfile/dem0.1.csv'
#modelProdict(ecpath, csvfile, demcsv,initial_datetime)
ecfilename= os.path.split(ecpath)[1]
readymodel(initial_datetime,dirpath)
#4.准确率计算
calculateAccuracy(initial_datetime)
calculateAccuracy2(initial_datetime)
# 模型预测和准确率计算
# modelpredict001(ecpath,outpath,csvfile,starttime)
# calculateAccuracy001(initial_datetime)
print ecpath
def runmodel(oldfilepath, dirpath):
starttime = datetime.datetime.now()
#这里还是开始时间
starttimestring = datetime.datetime.strftime(starttime,
'%Y-%m-%d %H:%M:%S')
#starttime=datetime.datetime.strptime('2018-09-15 20:00:00','%Y-%m-%d %H:%M:%S')
yearstr = starttime.year
monthstr = starttime.month
daystr = starttime.day
hourstr = starttime.hour
if hourstr < 17:
#把实时时间转成00时的时间传给计算准确率的函数
ppdatetime = datetime.datetime(yearstr, monthstr, daystr, 0, 0, 0)
starttimestring = datetime.datetime.strftime(ppdatetime,
'%Y-%m-%d %H:%M:%S')
dict = {}
nowdate = starttime + datetime.timedelta(days=-1)
datepath = datetime.datetime.strftime(nowdate, '%Y-%m-%d')
filepath = oldfilepath + '/' + str(yearstr) + '/' + datepath
midpath = dirpath + '/' + str(yearstr)
if not os.path.exists(midpath):
os.mkdir(midpath)
tofilepath = dirpath + '/' + str(yearstr) + '/' + datepath
if not os.path.exists(tofilepath):
os.mkdir(tofilepath)
for root, dirs, files in os.walk(filepath):
for file in files:
if file[:3] == 'D1D' and file[7:9] == '12' and file[
-7:-4] == '001' and file[-4:] == '.bz2':
filename = os.path.join(root, file)
logging.info(filename)
dict[filename] = tofilepath
#chain为串行，group并行
result = group(
simplemodelProdict.s(key, value, yearstr)
for key, value in dict.items())()
#logging.info(result)
else:
#传入的日期的时间
ppdatetime = datetime.datetime(yearstr, monthstr, daystr, 12, 0, 0)
starttimestring = datetime.datetime.strftime(ppdatetime,
'%Y-%m-%d %H:%M:%S')
dict00 = {}
datepath = datetime.datetime.strftime(starttime, '%Y-%m-%d')
filepath = oldfilepath + '/' + str(yearstr) + '/' + datepath
midpath = dirpath + '/' + str(yearstr)
if not os.path.exists(midpath):
os.mkdir(midpath)
tofilepath = dirpath + '/' + str(yearstr) + '/' + datepath
if not os.path.exists(tofilepath):
os.mkdir(tofilepath)
for root, dirs, files in os.walk(filepath):
for file in files:
if file[:3] == 'D1D' and file[7:9] == '00' and file[
-7:-4] == '001' and file[-4:] == '.bz2':
filename = os.path.join(root, file)
logging.info(filename)
dict00[filename] = tofilepath
#注意后面有个括号。
result = group(
simplemodelProdict.s(key, value, yearstr)
for key, value in dict00.items())()
#logging.info(result)
#然后计算准确率
calculateAccuracy(starttimestring)
deleteECMWF(dirpath)