def land(self):
from reame.utils import hdf_read
try:
return (self._lsf == 1).filled(False)
except AttributeError:
self._lsf, _ = hdf_read(self.filenames, "Land_sea_Flag")
return (self._lsf == 1).filled(False)
def _spectral_aod(self, i):
from reame.utils import hdf_read
land, land_metadata = hdf_read(self.filenames,
"Corrected_Optical_Depth_Land",
start=[i],
count=[1])
sea, sea_metadata = hdf_read(self.filenames,
"Effective_Optical_Depth_Average_Ocean",
start=[i],
count=[1])
data = np.ma.where(self.land, land, sea)
land_metadata.standard_name = "atmosphere_absorption_optical_thickness_due_to_ambient_aerosol"
land_metadata.long_name += "AND " + sea_metadata.long_name
return data, land_metadata
def AOD550(self):
from reame.utils import hdf_read
aod = []
for f in self.filenames:
data, meta = hdf_read([f], "Optical_Depth_055")
qc = self._read_qcmask(f)
aod.extend(data[np.logical_not(qc)].filled(np.nan))
return np.ma.masked_invalid(aod), meta
def _create_coord_list(self):
"""Read data coordinates into CIS object"""
from cis.data_io.Coord import Coord, CoordList
from reame.utils import hdf_read
lon_data, lon_metadata = hdf_read(self.filenames, "Longitude")
lon = Coord(lon_data, lon_metadata, "X")
lon.update_shape()
lon.update_range()
lat_data, lat_metadata = hdf_read(self.filenames, "Latitude")
lat = Coord(lat_data, lat_metadata, "Y")
lat.update_shape()
lat.update_range()
time_data, time_metadata = hdf_read(self.filenames, "Scan_Start_Time")
# Ensure the standard name is set
time_metadata.standard_name = "time"
time = Coord(time_data, time_metadata, "T")
time.convert_TAI_time_to_std_time(MODIS_REFERENCE_TIME)
time.update_shape()
time.update_range()
return CoordList([lat, lon, time])
def _read_qcmask(self, filename):
from reame.utils import hdf_read
qcdata, _ = hdf_read([filename], "AOD_QA")
# mask_val = sum((2**i for i in (0,1,2,5,6,7,8,9,10,11)))
mask = np.ma.bitwise_and(qcdata.astype("int64"), 4071) != 1
return mask.filled(True)
def _get_qcmask(self):
from reame.utils import hdf_read
qcdata, _ = hdf_read(self.filenames, "Land_Ocean_Quality_Flag")
mask = np.ma.where(self.land, qcdata != 3, qcdata < 1)
return mask.filled(True)
def _get_qcmask(self):
from reame.utils import hdf_read
qcdata, _ = hdf_read(
self.filenames, "Deep_Blue_Aerosol_Optical_Depth_550_Land_QA_Flag")
return (qcdata < 2).filled(True)
def _spectral_aod(self, i):
from reame.utils import hdf_read
return hdf_read(self.filenames,
"Deep_Blue_Spectral_Aerosol_Optical_Depth_Land",
start=[i],
count=[1])
def AOD550(self):
from reame.utils import hdf_read
return hdf_read(self.filenames,
"Deep_Blue_Aerosol_Optical_Depth_550_Land")
def SolZen(self):
from reame.utils import hdf_read
return hdf_read(self.filenames, "SolarZenith")
