def find_file(path, ymd, reg):
'''
path: 要遍历的目录
reg: 符合条件的文件
'''
FileLst = []
try:
lst = os.walk(path)
for root, dirs, files in lst:
for name in files:
try:
m = re.match(reg, name)
except Exception as e:
print str(e)
continue
if m:
nameClass = pb_name.nameClassManager()
info = nameClass.getInstance(name)
if info == None:
continue
if info.dt_s.strftime('%Y%m%d') != ymd:
continue
FileLst.append(os.path.join(root, name))
except Exception as e:
print str(e)
return sorted(FileLst)
def MatchMoveList(mdir):
# 遍历要迁移的目录
Dict = {}
if not os.path.isdir(mdir):
return Dict
Lst = sorted(os.listdir(mdir), reverse=False)
# print mdir
for line in Lst:
FullPath = os.path.join(mdir, line)
if os.path.isfile(FullPath):
fileName = line.strip()
if '.lock' in fileName:
continue
else:
nameClass = pb_name.nameClassManager()
info = nameClass.getInstance(fileName)
if info is None:
continue
ymd = info.dt_s.strftime('%Y%m%d')
# hms = info.hms
# sec = info.totalSec
# 定义key为字典
if ymd not in Dict.keys():
Dict[ymd] = []
Dict[ymd].append(fileName + '\n')
return Dict
def _get_time(self):
shape = self._get_shape()
time = np.full(shape, -999.)
name_class = pb_name.nameClassManager()
info = name_class.getInstance(os.path.basename(self.l1_1000m))
secs = int((info.dt_s - datetime(1970, 1, 1, 0, 0, 0)).total_seconds())
time[:] = secs
if not self.Time:
self.Time = time
else:
self.Time = np.concatenate((self.Time, time))
def Find_data_FromCrossTime(FileList, start_crossTime, end_crossTime):
dataList = []
for FileName in FileList:
name = os.path.basename(FileName)
nameClass = pb_name.nameClassManager()
info = nameClass.getInstance(name)
if info is None:
continue
# 获取数据时间段
data_stime1 = info.dt_s
data_etime1 = info.dt_e
if InCrossTime(data_stime1, data_etime1, start_crossTime, end_crossTime):
dataList.append(FileName)
return dataList
def GetFileInfo(FtpList):
'''
通过正则类对数据进行解析
'''
FileInfoList = []
for ftpList in FtpList:
Filename = ftpList.split()[0].strip()
nameClass = pb_name.nameClassManager()
info = nameClass.getInstance(Filename)
if info is None:
continue
FileInfoList.append([Filename, info.dt_s, info.dt_e])
return FileInfoList
def Load(self, L1File):
print L1File
iname = os.path.basename(L1File)
i = 0
dataSahpe = []
try:
h5File_R = h5py.File(L1File, 'r')
for line in h5File_R.items():
print line[0]
i = i + 1
data = h5File_R.get(line[0])[:]
dataSahpe = data.shape
dataT = np.full(data.shape, np.nan)
condition = np.logical_and(data > 0, data < 65535)
dataT[condition] = data[condition]
self.SV['CH_%02d' % i] = None
self.BB['CH_%02d' % i] = None
if 'NOMChannelVIS' in line[0]:
self.Ref['CH_%02d' % i] = dataT / 10000.
print 'CH_%02d' % i
elif 'NOMChannelIRX' in line[0]:
print 'CH_%02d' % i
self.Tbb['CH_%02d' % i] = dataT / 100.
elif 'NOMSunAzimuth' in line[0]:
self.sunAzimuth = dataT / 100.
elif 'NOMSunZenith' in line[0]:
self.sunZenith = dataT / 100.
else:
i = i - 1
print 'not', i
data = 0
except Exception as e:
print str(e)
return
finally:
h5File_R.close()
self.Time = np.full(dataSahpe, -999.)
nameClass = pb_name.nameClassManager()
info = nameClass.getInstance(iname)
# print info.dt_s
secs = int((info.dt_s - datetime(1970, 1, 1, 0, 0, 0)).total_seconds())
self.Time[:] = secs
def use_ftp_getList(host, user, pawd, port, s_path, regList, ymd):
FileList = []
class MySession(ftplib.FTP):
def __init__(self, FTP, userid, password, port):
"""Act like ftplib.FTP's constructor but connect to another port."""
ftplib.FTP.__init__(self)
self.connect(FTP, port)
self.login(userid, password)
try:
FTP = ftputil.FTPHost(host,
user,
pawd,
port=port,
session_factory=MySession)
FTP.chdir(s_path)
nameList = FTP.listdir(FTP.curdir)
for name in nameList:
for reg in regList: # 符合正则的进行处理
m = re.match(reg, name)
if m is not None:
nameClass = pb_name.nameClassManager()
info = nameClass.getInstance(name)
if info is None:
continue
if info.dt_s.strftime('%Y%m%d') != ymd:
continue
stat = FTP.lstat(name)
size = stat[6]
Line = name + ' ' + str(size)
FileList.append(Line)
FTP.close()
except Exception as e:
print(u'----%s' % str(e))
return FileList
def use_http_getList(pact, host, user, pawd, port, s_path, regList, ymd):
FileList = []
url = '%s://%s:%s' % (pact, host, port) + s_path
html = getHtml(url)
if html is None:
return FileList
dm = DM()
dm.feed(html)
dm.close()
htmlList = dm.getStr()
for Name in htmlList:
for reg in regList:
m = re.match(reg, Name)
if m is not None:
try:
nameClass = pb_name.nameClassManager()
info = nameClass.getInstance(Name)
if info is None:
continue
if info.dt_s.strftime('%Y%m%d') != ymd:
continue
# huangyj 2017/03/28 由于nasa无法通过身份验证，暂时通过网页抓取数据的大小
size = GetFileSize(html, Name)
# f = urllib2.urlopen(url + '/' + Name)
# if "Content-Length" in f.headers:
# print f.headers
# size = int (f.headers["Content-Length"])
# else:
# # 如果没有Length信息则把长度设置为0，无法做完整性检查
# # size = len (f.read ())
# size = 0
Line = Name + ' ' + str(size)
FileList.append(Line)
except Exception, e:
print "ERROR: ", e
FileList = []
def Load(self, L1File):
print(u'读取 L1 %s' % L1File)
iname = os.path.basename(L1File)
try:
h4File = SD(L1File, SDC.READ)
# 读取1-2通道数据
in_data_r250 = h4File.select('EV_250_Aggr1km_RefSB').get()
in_data_r250_s = h4File.select(
'EV_250_Aggr1km_RefSB').attributes()['reflectance_scales']
in_data_r250_o = h4File.select(
'EV_250_Aggr1km_RefSB').attributes()['reflectance_offsets']
# 读取 3-7通道数据
in_data_r500 = h4File.select('EV_500_Aggr1km_RefSB').get()
in_data_r500_s = h4File.select(
'EV_500_Aggr1km_RefSB').attributes()['reflectance_scales']
in_data_r500_o = h4File.select(
'EV_500_Aggr1km_RefSB').attributes()['reflectance_offsets']
# 读取8-20通道， 包含26通道
in_data_r1km = h4File.select('EV_1KM_RefSB').get()
in_data_r1km_s = h4File.select(
'EV_1KM_RefSB').attributes()['reflectance_scales']
in_data_r1km_o = h4File.select(
'EV_1KM_RefSB').attributes()['reflectance_offsets']
# 读取20-36通道 不包含26通道
in_data_t1km = h4File.select('EV_1KM_Emissive').get()
in_data_t1km_s = h4File.select(
'EV_1KM_Emissive').attributes()['radiance_scales']
in_data_t1km_o = h4File.select(
'EV_1KM_Emissive').attributes()['radiance_offsets']
except Exception as e:
print str(e)
finally:
h4File.end()
# 处理定位文件，默认和L1同一目录
geoFile = find_modis_geo_file(L1File)
print(u'读取geo %s' % geoFile)
try:
h4File = SD(geoFile, SDC.READ)
in_data_lon = h4File.select('Longitude').get()
in_data_lat = h4File.select('Latitude').get()
# in_data_LandSeaMask = h4File.select('Land/SeaMask').get() #
# 多个/不知道是bug还是就这样
in_data_satz = h4File.select('SensorZenith').get()
in_data_satz_s = h4File.select(
'SensorZenith').attributes()['scale_factor']
in_data_sata = h4File.select('SensorAzimuth').get()
in_data_sata_s = h4File.select(
'SensorAzimuth').attributes()['scale_factor']
in_data_sunz = h4File.select('SolarZenith').get()
in_data_sunz_s = h4File.select(
'SolarZenith').attributes()['scale_factor']
in_data_suna = h4File.select('SolarAzimuth').get()
in_data_suna_s = h4File.select(
'SolarAzimuth').attributes()['scale_factor']
except Exception as e:
print(str(e))
finally:
h4File.end()
# 角度信息赋值
self.satZenith = in_data_satz * in_data_satz_s
self.satAzimuth = in_data_sata * in_data_sata_s
self.sunZenith = in_data_sunz * in_data_sunz_s
self.sunAzimuth = in_data_suna * in_data_suna_s
self.Lons = in_data_lon
self.Lats = in_data_lat
# 1-2通道
modis_shape2 = in_data_r250.shape[1:]
modis_shape3 = (38, ) + modis_shape2
data_ch38 = np.full(modis_shape3, np.nan)
for i in range(0, 2, 1):
# 过滤 无效值
condition = np.logical_and(in_data_r250[i] < 32767,
in_data_r250[i] > 0)
idx = np.where(condition)
data_ch38[i][idx] = (in_data_r250[i][idx] -
in_data_r250_o[i]) * in_data_r250_s[i]
# 3-7通道
for i in range(2, 7, 1):
# 过滤 无效值
condition = np.logical_and(in_data_r500[i - 2] < 32767,
in_data_r500[i - 2] > 0)
idx = np.where(condition)
data_ch38[i][idx] = (in_data_r500[i - 2][idx] -
in_data_r500_o[i - 2]) * in_data_r500_s[i - 2]
# 8-19 外加一个 26通道
for i in range(7, 22, 1):
# 过滤 无效值
condition = np.logical_and(in_data_r1km[i - 7] < 32767,
in_data_r1km[i - 7] > 0)
idx = np.where(condition)
data_ch38[i][idx] = (in_data_r1km[i - 7][idx] -
in_data_r1km_o[i - 7]) * in_data_r1km_s[i - 7]
# 20-36通道 不包括26通道
for i in range(22, 38, 1):
# 过滤 无效值
condition = np.logical_and(in_data_t1km[i - 22] < 32767,
in_data_t1km[i - 22] > 0)
idx = np.where(condition)
data_ch38[i][idx] = (in_data_t1km[i - 22][idx] -
in_data_t1km_o[i - 22]) * in_data_t1km_s[i -
22]
# 删除通道13hi 和 14 hi
data_ch36 = np.delete(data_ch38, (13, 15), 0)
newRad = np.full((16, ) + modis_shape2, np.nan)
# 对时间进行赋值
self.Time = np.full(modis_shape2, -999.)
nameClass = pb_name.nameClassManager()
info = nameClass.getInstance(iname)
ymd = info.dt_s.strftime('%Y%m%d')
print ymd
dsol = sun_earth_dis_correction(ymd)
# print info.dt_s
secs = int((info.dt_s - datetime(1970, 1, 1, 0, 0, 0)).total_seconds())
self.Time[:] = secs
# 把modis的rad转换和FY的单位一致
# 20,21, 22,23,24,25,27,28,29,30,31,32,33,34,35,36
cwn = [
2.647409E+03, 2.511760E+03, 2.517908E+03, 2.462442E+03,
2.248296E+03, 2.209547E+03, 1.474262E+03, 1.361626E+03,
1.169626E+03, 1.028740E+03, 9.076813E+02, 8.308411E+02,
7.482978E+02, 7.307766E+02, 7.182094E+02, 7.035007E+02
]
for i in xrange(16):
newRad[i] = data_ch36[i + 20] * \
((10000 / cwn[i]) ** 2) / 10. * dsol
if i <= 5:
self.Rad['CH_%02d' % (i + 20)] = newRad[i]
else:
self.Rad['CH_%02d' % (i + 21)] = newRad[i]
# 把rad转亮温
radiance2tbb(data_ch36)
# 整理通道顺序，把26通道放在对应的26通道
# del26_data_ch35 = np.delete(data_ch36, 19, 0)
# order_data_ch36 = np.insert(del26_data_ch35, 25, data_ch36[19], 0)
for i in range(0, 36, 1):
# self.CA['CH_%02d' % (i + 1)] = order_data_ch36[i]
if i < 19:
self.Ref['CH_%02d' % (i + 1)] = data_ch36[i]
elif i == 19: # 26
self.Ref['CH_%02d' % (i + 7)] = data_ch36[i]
elif i > 19 and i <= 25:
self.Tbb['CH_%02d' % (i)] = data_ch36[i]
elif i > 25:
self.Tbb['CH_%02d' % (i + 1)] = data_ch36[i]
:return:
"""
d = {}
try:
with h5py.File(self.file_path, 'r') as hdf5_file:
for k, v in hdf5_file.attrs.items():
d[k] = v
except Exception as why:
print why
self.error = True
return d
@staticmethod
def read_dataset_attr(dataset):
"""
读取HDF5文件dataset的属性
:return:
"""
d = {}
for k, v in dataset.attrs.items():
d[k] = v
return d
if __name__ == '__main__':
g_test_file = r'D:\nsmc\fix_data\FY3ABC\FY3A_VIRRX_GBAL_L1_20131206_1355_1000M_MS.HDF'
name_class = nameClassManager()
g_info = name_class.getInstance(g_test_file)
g_sec = int((g_info.dt_s - datetime(1970, 1, 1, 0, 0, 0)).total_seconds())
print g_sec
def Load(self, L1File):
ipath = os.path.dirname(L1File)
iname = os.path.basename(L1File)
geoFile = os.path.join(ipath, iname[0:-12] + 'GEO1K_MS.HDF')
print L1File
print geoFile
if 'FY3C' in iname[:4]:
try:
h5File_R = h5py.File(L1File, 'r')
ary_ch1 = h5File_R.get('/Data/EV_250_Aggr.1KM_RefSB')[:]
ary_ch5 = h5File_R.get('/Data/EV_250_Aggr.1KM_Emissive')[:]
ary_ch6 = h5File_R.get('/Data/EV_1KM_RefSB')[:]
ary_Cal_Coeff = h5File_R.get('/Calibration/VIS_Cal_Coeff')[:]
ary_svdn = h5File_R.get('/Calibration/SV_DN_average')[:]
ary_bbdn = h5File_R.get('/Calibration/BB_DN_average')[:]
except Exception as e:
print str(e)
return
finally:
h5File_R.close()
print sys.getsizeof(ary_ch1) / 1024. / 1024.
try:
# 读取GEO文件
h5File_R = h5py.File(geoFile, 'r')
ary_satz = h5File_R.get('/Geolocation/SensorZenith')[:]
ary_sata = h5File_R.get('/Geolocation/SensorAzimuth')[:]
ary_sunz = h5File_R.get('/Geolocation/SolarZenith')[:]
ary_suna = h5File_R.get('/Geolocation/SolarAzimuth')[:]
ary_lon = h5File_R.get('/Geolocation/Longitude')[:]
ary_lat = h5File_R.get('/Geolocation/Latitude')[:]
ary_LandCover = h5File_R.get('/Geolocation/LandCover')[:]
ary_LandSeaMask = h5File_R.get('/Geolocation/LandSeaMask')[:]
ary_day = h5File_R.get('/Timedata/Day_Count')[:]
ary_time = h5File_R.get('/Timedata/Millisecond_Count')[:]
except Exception as e:
print str(e)
return
finally:
h5File_R.close()
else:
# FY3A/FY3B MERSI
# 读取L1文件
try:
h5File_R = h5py.File(L1File, 'r')
ary_lon = h5File_R.get('/Longitude')[:]
ary_lat = h5File_R.get('/Latitude')[:]
ary_svdn = np.full_like(ary_lon, -999.)
ary_bbdn = np.full_like(ary_lon, -999.)
ary_ch1 = h5File_R.get('/EV_250_Aggr.1KM_RefSB')[:]
ary_ch5 = h5File_R.get('/EV_250_Aggr.1KM_Emissive')[:]
ary_ch6 = h5File_R.get('/EV_1KM_RefSB')[:]
ary_Cal_Coeff = h5File_R.attrs['VIR_Cal_Coeff']
ary_satz = h5File_R.get('/SensorZenith')[:]
ary_sata = h5File_R.get('/SensorAzimuth')[:]
ary_sunz = h5File_R.get('/SolarZenith')[:]
ary_suna = h5File_R.get('/SolarAzimuth')[:]
ary_LandCover = h5File_R.get('/LandCover')[:]
ary_LandSeaMask = h5File_R.get('/LandSeaMask')[:]
ary_svdn = h5File_R.get('/SV_DN_average')[:]
ary_bbdn = h5File_R.get('/BB_DN_average')[:]
except Exception as e:
print str(e)
return
finally:
h5File_R.close()
# 通道的中心波数和光谱响应
# for i in xrange(self.Band):
# BandName = 'CH_%02d' % (i + 1)
# srfFile = os.path.join(
# MainPath, 'SRF', '%s_%s_SRF_CH%02d_Pub.txt' % (self.sat, self.sensor, (i + 1)))
# dictWave = np.loadtxt(
# srfFile, dtype={'names': ('num', 'rad'), 'formats': ('f4', 'f4')})
# waveNum = 10 ** 7 / dictWave['num'][::-1]
# waveRad = dictWave['rad'][::-1]
# self.waveNum[BandName] = waveNum
# self.waveRad[BandName] = waveRad
# 数据大小 使用经度维度 ###############
dshape = ary_lon.shape
# 通道信息赋值 #######################
# 读取FY3C查找表
# LutAry = np.loadtxt(self.LutFile, dtype={'names': ('TBB', '05'),
# 'formats': ('i4', 'f4')})
# RefSB_Cal_Coefficients这个属性直接写到hdf中，FY3A/B 需要转成19*3
proj_Cal_Coeff = np.full((19, 3), -999.)
if 'FY3C' in iname[:4]:
proj_Cal_Coeff = ary_Cal_Coeff
else:
for i in range(19):
for j in range(3):
proj_Cal_Coeff[i, j] = ary_Cal_Coeff[i * 3 + j]
# 定标系数 19*3 转 20*3
values = np.array([0, 0, 0])
K = np.insert(proj_Cal_Coeff, 4, values, 0)
pat = u'\w{4}_\w{5}_\w{4}_L1_(\d{8})_(\d{4})_\w{5}_MS.HDF$'
g = re.match(pat, iname)
if g:
ymd = g.group(1)
hms = g.group(2)
else:
raise ValueError('Cant get the ymdhms from file name.')
# 可见
for i in xrange(self.Band):
BandName = 'CH_%02d' % (i + 1)
if i < 4:
DN = np.full(dshape, np.nan)
idx = np.logical_and(ary_ch1[i] < 10000, ary_ch1[i] > 0)
DN[idx] = ary_ch1[i][idx]
if int(ymd + hms) <= 201303060015:
Ref = (DN ** 2 * K[i, 2] + DN * K[i, 1] + K[i, 0]) / 100.
print 'ref', Ref, BandName
else:
Ref = (DN ** 2 * K[i, 2] + DN * K[i, 1] + K[i, 0]) / 10000.
self.Dn[BandName] = DN
self.Ref[BandName] = Ref
elif i > 4:
k = i - 5
DN = np.full(dshape, np.nan)
idx = np.logical_and(ary_ch6[k] < 10000, ary_ch6[k] > 0)
DN[idx] = ary_ch6[k][idx]
if int(ymd + hms) <= 201303060015:
Ref = (DN ** 2 * K[i, 2] + DN * K[i, 1] + K[i, 0]) / 100.
print 'ref', Ref, BandName
else:
Ref = (DN ** 2 * K[i, 2] + DN * K[i, 1] + K[i, 0]) / 10000.
self.Dn[BandName] = DN
self.Ref[BandName] = Ref
# 红外
elif i == 4:
# 数据空间
DN = np.full(dshape, np.nan)
Rad = np.full(dshape, np.nan)
Tbb = np.full(dshape, np.nan)
# 过滤无效值
idx = np.logical_and(ary_ch5 < 10000, ary_ch5 >= 0)
# dn
DN[idx] = ary_ch5[idx]
self.Dn[BandName] = DN
# rad
Rad = DN / 100.
idx1 = np.where(Rad <= 0.)
Rad[idx1] = np.nan
self.Rad[BandName] = Rad
# tbb
Tbb = pb_sat.planck_r2t(
Rad, self.WN[BandName], self.TeA[BandName], self.TeB[BandName])
self.Tbb[BandName] = Tbb
# CA = interpolate.InterpolatedUnivariateSpline(LutAry['%02d' % (i + 1)], LutAry['TBB'])(DN[idx])
# self.CA[BandName] = np.full(dshape, np.nan)
# self.CA[BandName][idx] = CA / 100.
# 全局信息赋值 ############################
# 对时间进行赋值合并
if 'FY3C' in iname[:4]:
v_ymd2seconds = np.vectorize(fy3_ymd2seconds)
T1 = v_ymd2seconds(ary_day, ary_time)
Time = np.full(dshape, -999)
for i in xrange(ary_lon.shape[0]):
Time[i, :] = T1[i / 10, 0]
if self.Time == []:
self.Time = Time
else:
self.Time = np.concatenate((self.Time, Time))
else:
time = np.full(dshape, -999.)
name_class = pb_name.nameClassManager()
info = name_class.getInstance(iname)
secs = int(
(info.dt_s - datetime(1970, 1, 1, 0, 0, 0)).total_seconds())
time[:] = secs
if not self.Time:
self.Time = time
else:
self.Time = np.concatenate((self.Time, time))
# SV, BB
for i in xrange(self.Band):
SV = np.full(dshape, np.nan)
BB = np.full(dshape, np.nan)
for j in xrange(ary_lon.shape[0]):
SV[j, :] = ary_svdn[i][j / 10]
BB[j, :] = ary_bbdn[i][j / 10]
SV = np.ma.masked_where(SV < 0, SV)
BB = np.ma.masked_where(BB < 0, BB)
np.ma.filled(SV, np.nan)
np.ma.filled(BB, np.nan)
# 数据合并
BandName = 'CH_%02d' % (i + 1)
if BandName not in self.SV.keys():
self.SV[BandName] = SV
self.BB[BandName] = BB
else:
self.SV[BandName] = np.concatenate((self.SV[BandName], SV))
self.BB[BandName] = np.concatenate((self.BB[BandName], BB))
# 土地覆盖
ary_LandCover_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_LandCover >= 0, ary_LandCover <= 254)
ary_LandCover_idx[condition] = ary_LandCover[condition]
if self.LandCover == []:
self.LandCover = ary_LandCover_idx
else:
self.LandCover = np.concatenate(
(self.LandCover, ary_LandCover_idx))
# 海陆掩码
ary_LandSeaMask_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_LandSeaMask >= 0, ary_LandSeaMask <= 7)
ary_LandSeaMask_idx[condition] = ary_LandSeaMask[condition]
if self.LandSeaMask == []:
self.LandSeaMask = ary_LandSeaMask_idx
else:
self.LandSeaMask = np.concatenate(
(self.LandSeaMask, ary_LandSeaMask_idx))
# 经纬度
ary_lon_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_lon > -180., ary_lon < 180.)
ary_lon_idx[condition] = ary_lon[condition]
if self.Lons == []:
self.Lons = ary_lon_idx
else:
self.Lons = np.concatenate((self.Lons, ary_lon_idx))
ary_lat_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_lat > -90., ary_lat < 90.)
ary_lat_idx[condition] = ary_lat[condition]
if self.Lats == []:
self.Lats = ary_lat_idx
else:
self.Lats = np.concatenate((self.Lats, ary_lat_idx))
# 卫星方位角 天顶角
ary_sata_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_sata > -18000, ary_sata < 18000)
ary_sata_idx[condition] = ary_sata[condition]
if self.satAzimuth == []:
self.satAzimuth = ary_sata_idx / 100.
else:
self.satAzimuth = np.concatenate(
(self.satAzimuth, ary_sata_idx / 100.))
ary_satz_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_satz > 0, ary_satz < 18000)
ary_satz_idx[condition] = ary_satz[condition]
if self.satZenith == []:
self.satZenith = ary_satz_idx / 100.
else:
self.satZenith = np.concatenate(
(self.satZenith, ary_satz_idx / 100.))
# 太阳方位角 天顶角
ary_suna_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_suna > -18000, ary_suna < 18000)
ary_suna_idx[condition] = ary_suna[condition]
if self.sunAzimuth == []:
self.sunAzimuth = ary_suna_idx / 100.
else:
self.sunAzimuth = np.concatenate(
(self.sunAzimuth, ary_suna_idx / 100.))
ary_sunz_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_sunz > 0, ary_sunz < 18000)
ary_sunz_idx[condition] = ary_sunz[condition]
if self.sunZenith == []:
self.sunZenith = ary_sunz_idx / 100.
else:
self.sunZenith = np.concatenate(
(self.sunZenith, ary_sunz_idx / 100.))
def create_leo_leo_fine(sat_pair, ymd, job_id):
'''
创建精匹配配置接口文件
'''
Log.info(u'[%s] [%s]' % (sat_pair, ymd))
# 解析mathcing: FY3A+MERSI_AQUA+MODIS ,根据下划线分割获取 卫星+传感器 ,再次分割获取俩颗卫星短名
shortsat1 = (sat_pair.split('_')[0]).split('+')[0]
shortsat2 = (sat_pair.split('_')[1]).split('+')[0]
# 解析global.cfg中的信息
NUM1 = inCfg['PAIRS'][sat_pair]['num1']
NUM2 = inCfg['PAIRS'][sat_pair]['num2']
sec1 = inCfg['PAIRS'][sat_pair]['sec1']
sec2 = inCfg['PAIRS'][sat_pair]['sec2']
# 根据编号在dm_odm.cfg中查找到对应的数据描述信息
sat1 = odmCfg['ORDER'][NUM1[0]]['SELF_SAT']
sensor1 = odmCfg['ORDER'][NUM1[0]]['SELF_SENSOR']
product1 = odmCfg['ORDER'][NUM1[0]]['SELF_PRODUCT']
interval1 = odmCfg['ORDER'][NUM1[0]]['SELF_INTERVAL']
reg1 = odmCfg['ORDER'][NUM1[0]]['SELF_REG'][0]
sat2 = odmCfg['ORDER'][NUM2[0]]['SELF_SAT']
sensor2 = odmCfg['ORDER'][NUM2[0]]['SELF_SENSOR']
product2 = odmCfg['ORDER'][NUM2[0]]['SELF_PRODUCT']
interval2 = odmCfg['ORDER'][NUM2[0]]['SELF_INTERVAL']
reg2 = odmCfg['ORDER'][NUM2[0]]['SELF_REG'][0]
# 存放俩颗卫星的原始数据目录位置
inpath1 = os.path.join(
DATA_DIR, '%s/%s/%s/%s' % (sat1, sensor1, product1, interval1),
ymd[:6])
inpath2 = os.path.join(
DATA_DIR, '%s/%s/%s/%s' % (sat2, sensor2, product2, interval2),
ymd[:6])
file_list1 = find_file(inpath1, ymd, reg1)
file_list2 = find_file(inpath2, ymd, reg2)
# file_list2是高光普数据，根据list2找list1符合条件的数据
for filename2 in file_list2:
name2 = os.path.basename(filename2)
nameClass = pb_name.nameClassManager()
info = nameClass.getInstance(filename2)
if info == None:
continue
# 获取数据时间段
data_stime2 = info.dt_s - timedelta(minutes=5)
data_etime2 = info.dt_e + timedelta(minutes=5)
ymdhms = info.dt_s.strftime('%Y%m%d%H%M%S')
new_file_list1 = Find_data_FromCrossTime(file_list1, data_stime2,
data_etime2)
yaml_file = os.path.join(JOBCFG_DIR, sat_pair, 'job_%s' % job_id,
ymdhms[:8],
'%s_%s_%s.yaml' % (ymdhms, sensor1, sensor2))
# 输出文件命名
filename = 'W_CN-CMA-NSMC,SATCAL+NRTC,GSICS+MATCHEDPOINTS,%s_C_BABJ_%s.hdf5' % (
sat_pair, ymdhms)
# 输出完整路径
full_filename = os.path.join(MATCH_DIR, sat_pair, ymdhms[:4],
ymdhms[:8], filename3)
if len(new_file_list1) > 0:
dict1 = {
'INFO': {
'sat1': sat1,
'sensor1': sensor1,
'sat2': sat2,
'sensor2': sensor2,
'ymd': ymdhms
},
'PATH': {
'opath': full_filename,
'ipath1': new_file_list1,
'ipath2': [filename2]
}
}
CreateYamlCfg(dict, yaml_file)