def set_ymd_hms(self):
"""
根据根据L1文件名 set self.level_1_ymd 和 self.level_1_ymd
:return:
"""
file_name = os.path.basename(self.in_file)
self.ymd = get_ymd(file_name)
self.hms = get_hm(file_name) + '00'
def _get_ymd(self):
if self.error:
return
try:
self.ymd = pb_time.get_ymd(self.l1_1000m)
self.hm = pb_time.get_hm(self.l1_1000m)
except Exception as why:
print why
self.error = True
def _get_out_file(in_file, out_path, suffix):
"""
通过输入的文件名和输出路径获取输出文件的完整路径
:return:
"""
try:
if isinstance(in_file, str):
ymd = pb_time.get_ymd(in_file)
out_path = pb_io.path_replace_ymd(out_path, ymd)
_name = os.path.basename(in_file)
name = _name.replace("_c", "") + suffix
out_file = os.path.join(out_path, name)
if not os.path.isdir(os.path.dirname(out_file)):
try:
os.makedirs(os.path.dirname(out_file))
except OSError as why:
print why
return out_file
except Exception as why:
print why
return
def Load(self, L1File):
ipath = os.path.dirname(L1File)
iname = os.path.basename(L1File)
self.file_attr = self.read_file_attr(L1File)
if 'FY3C' in iname[:4]:
# 根据输入的L1文件自动拼接GEO文件
geoFile = os.path.join(ipath, iname[0:-12] + 'GEOXX_MS.HDF')
obcFile = os.path.join(ipath, iname[0:-12] + 'OBCXX_MS.HDF')
print u'%s' % L1File
print u'%s' % geoFile
print u'%s' % obcFile
#################### 读取L1文件 ######################
try:
with h5py.File(L1File, 'r') as h5File_R:
ary_ch3 = h5File_R.get('/Data/EV_Emissive')[:]
ary_ch7 = h5File_R.get('/Data/EV_RefSB')[:]
ary_offsets = h5File_R.get(
'/Data/Emissive_Radiance_Offsets')[:]
ary_scales = h5File_R.get(
'/Data/Emissive_Radiance_Scales')[:]
ary_ref_cal = h5File_R.attrs['RefSB_Cal_Coefficients']
ary_Nonlinear = h5File_R.attrs[
'Prelaunch_Nonlinear_Coefficients']
try:
ary_tb_coeff = h5File_R.attrs[
'Emmisive_BT_Coefficients']
except Exception:
ary_tb_coeff = h5File_R.attrs[
'Emissive_BT_Coefficients']
except Exception as e:
self.error = True
print str(e)
return
#################### 读取GEO文件 ######################
try:
with h5py.File(geoFile, 'r') as h5File_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_height = h5File_R.get('/Geolocation/DEM')[:]
ary_LandCover = h5File_R.get('/Geolocation/LandCover')[:]
ary_LandSeaMask = h5File_R.get(
'/Geolocation/LandSeaMask')[:]
except Exception as e:
self.error = True
print str(e)
return
#################### 读取OBC文件 ####################
try:
with h5py.File(obcFile, 'r') as h5File_R:
ary_sv = h5File_R.get('/Calibration/Space_View')[:]
ary_bb = h5File_R.get('/Calibration/Blackbody_View')[:]
except Exception as e:
self.error = True
print str(e)
return
else:
# FY3A/FY3B VIRR
# 根据输入的L1文件自动拼接OBC文件
obcFile = os.path.join(ipath, iname[0:-12] + 'OBCXX_MS.HDF')
print u'%s' % L1File
print u'%s' % obcFile
#################### 读取L1文件 ####################
try:
with h5py.File(L1File, 'r') as h5File_R:
ary_ch3 = h5File_R.get('/EV_Emissive')[:, 0:1800, 0:2048]
ary_ch7 = h5File_R.get('/EV_RefSB')[:, 0:1800, 0:2048]
ary_offsets = h5File_R.get('/Emissive_Radiance_Offsets')[
0:1800, :]
ary_scales = h5File_R.get('/Emissive_Radiance_Scales')[
0:1800, :]
ary_ref_cal = h5File_R.attrs['RefSB_Cal_Coefficients']
ary_Nonlinear = h5File_R.attrs[
'Prelaunch_Nonlinear_Coefficients']
try:
ary_tb_coeff = h5File_R.attrs[
'Emmisive_BT_Coefficients']
except Exception:
ary_tb_coeff = h5File_R.attrs[
'Emissive_BT_Coefficients']
ary_satz = h5File_R.get('/SensorZenith')[0:1800, 0:2048]
ary_sata = h5File_R.get('/SensorAzimuth')[0:1800, 0:2048]
ary_sunz = h5File_R.get('/SolarZenith')[0:1800, 0:2048]
ary_suna = h5File_R.get('/SolarAzimuth')[0:1800, 0:2048]
ary_lon = h5File_R.get('/Longitude')[0:1800, 0:2048]
ary_lat = h5File_R.get('/Latitude')[0:1800, 0:2048]
ary_height = h5File_R.get('/Height')[0:1800, 0:2048]
ary_LandCover = h5File_R.get('/LandCover')[0:1800, 0:2048]
ary_LandSeaMask = h5File_R.get('/LandSeaMask')[0:1800,
0:2048]
except Exception as e:
self.error = True
print str(e)
return
#################### 读取OBC文件 ####################
try:
with h5py.File(obcFile, 'r') as h5File_R:
ary_sv = h5File_R.get('Space_View')[:]
ary_bb = h5File_R.get('Blackbody_View')[:]
except Exception as e:
self.error = True
print(str(e))
return
# 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')
})
if BandName in ['CH_03', 'CH_04', 'CH_05']:
waveNum = 10**4 / dictWave['num'][::-1]
else:
waveNum = 10**7 / dictWave['num'][::-1]
waveRad = dictWave['rad'][::-1]
if BandName not in self.waveNum:
self.waveNum[BandName] = waveNum
self.waveRad[BandName] = waveRad
else:
self.waveNum[BandName] = np.concatenate(
(self.waveNum[BandName], waveNum))
self.waveRad[BandName] = np.concatenate(
(self.waveRad[BandName], waveRad))
############### 数据大小 使用经度维度 ###############
dshape = ary_lon.shape
##################可见光数据进行定标 ########
# LutAry = np.loadtxt(self.LutFile, dtype={'names': ('TBB', 'CH_03', 'CH_04', 'CH_05'),
# 'formats': ('i4', 'f4', 'f4', 'f4')})
# 定标系数b,a
proj_Cal_Coeff = np.full((7, 2), np.nan)
for i in range(7):
for j in range(2):
proj_Cal_Coeff[i, j] = ary_ref_cal[i * 2 + j - 1]
# 1 - 6 通道的ref
for i in xrange(self.Band):
BandName = 'CH_%02d' % (i + 1)
if i < 2 or i >= 5:
# 下标k (1 2 6 7 8 9 10存放在一个三维数组中)
if i < 2:
k = i
elif i >= 5:
k = i - 3
# DN值存放无效值用nan填充
DN = np.full(dshape, np.nan)
idx = np.logical_and(ary_ch7[k] < 32767, ary_ch7[k] > 0)
DN[idx] = ary_ch7[k][idx]
# 反射率值存放无效值用nan填充
k0 = proj_Cal_Coeff[k][1]
k1 = proj_Cal_Coeff[k][0]
Ref = (DN * k0 + k1) / 100.
K0 = np.full(dshape, k0, dtype=np.float32)
K1 = np.full(dshape, k1, dtype=np.float32)
if BandName not in self.Dn:
self.Dn[BandName] = DN
self.Ref[BandName] = Ref
self.K0[BandName] = K0
self.K1[BandName] = K1
else:
self.Dn[BandName] = np.concatenate((self.Dn[BandName], DN))
self.Ref[BandName] = np.concatenate(
(self.Ref[BandName], Ref))
self.K0[BandName] = np.concatenate((self.K0[BandName], K0))
self.K1[BandName] = np.concatenate((self.K1[BandName], K1))
if 2 <= i <= 4:
# DN Rad Tbb 值存放,默认 nan填充
k = i - 2
DN = np.full(dshape, np.nan)
Rad_pre = np.full(dshape, np.nan)
condition = np.logical_and(ary_ch3[k] < 32767, ary_ch3[k] > 0)
idx = np.where(condition)
# 下标i-2 (3,4,5通道DN存放在一个三维数组中)
DN[idx] = ary_ch3[k][idx]
Rad_pre[idx] = DN[idx] * ary_scales[idx[0], k] + \
ary_offsets[idx[0], k]
k0 = ary_Nonlinear[k]
k1 = ary_Nonlinear[3 + k]
k2 = ary_Nonlinear[6 + k]
Rad_nonlinearity = Rad_pre**2 * k2 + Rad_pre * k1 + k0
K0 = np.full(dshape, np.nan)
K0[:] = ary_scales[:, k].reshape(-1, 1)
K1 = np.full(dshape, np.nan)
K1[:] = ary_offsets[:, k].reshape(-1, 1)
self.Rad_pre[BandName] = Rad_pre
Rad = Rad_pre + Rad_nonlinearity
Tbb = pb_sat.planck_r2t(Rad, self.WN[BandName])
Tbb = Tbb * self.TeA[BandName] + self.TeB[BandName]
k0_coeff = ary_tb_coeff[k * 2 + 1]
k1_coeff = ary_tb_coeff[k * 2]
Tbb_coeff = Tbb * k0_coeff + k1_coeff
if BandName not in self.Dn:
self.Dn[BandName] = DN
self.Rad[BandName] = Rad
self.K0[BandName] = K0
self.K1[BandName] = K1
self.Tbb[BandName] = Tbb
self.Tbb_coeff[BandName] = Tbb_coeff
else:
self.Dn[BandName] = np.concatenate((self.Dn[BandName], DN))
self.Rad[BandName] = np.concatenate(
(self.Rad[BandName], Rad))
self.K0[BandName] = np.concatenate((self.K0[BandName], K0))
self.K1[BandName] = np.concatenate((self.K1[BandName], K1))
self.Tbb[BandName] = np.concatenate(
(self.Tbb[BandName], Tbb))
self.Tbb_coeff[BandName] = np.concatenate(
(self.Tbb_coeff[BandName], Tbb_coeff))
# SV, BB
for i in xrange(self.Band):
BandName = 'CH_%02d' % (i + 1)
SV = np.full(dshape, np.nan)
BB = np.full(dshape, np.nan)
SV[:] = ary_sv[i, :, 0].reshape(-1, 1)
BB[:] = ary_bb[i, :, 0].reshape(-1, 1)
if BandName not in self.SV:
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))
##################### 全局信息赋值 ############################
# 对时间进行赋值合并
Time = np.full(dshape, np.nan)
ymd = get_ymd(L1File)
hm = get_hm(L1File)
file_date = datetime.strptime(ymd + hm, '%Y%m%d%H%M')
secs = (file_date - datetime(1970, 1, 1, 0, 0, 0)).total_seconds()
Time[:] = secs
if self.Time == []:
self.Time = Time
else:
self.Time = np.concatenate((self.Time, Time))
# 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))
# 高度
ary_height_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_height > -1000., ary_height < 10000.)
ary_height_idx[condition] = ary_height[condition]
if self.Height == []:
self.Height = ary_height_idx
else:
self.Height = np.concatenate((self.Height, ary_height_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.))
self.get_extract_data()