def _create_coord_list(self):
from cis.data_io.Coord import Coord, CoordList
from cis.data_io.ungridded_data import Metadata
from cis.time_util import cis_standard_time_unit as cstu
# These implement a lot of what is necessary, but aren't in CIS style
from acp_utils import rolling_window
from orbit import ATSR
lat_data = []
lon_data = []
time_data = []
for fname in self.filenames:
prod = ATSR(fname)
lat_data.append(prod.lat)
lon_data.append(prod.lon)
time_data.append(prod.get_time())
# TODO: Properly define metadata
lat_meta = Metadata(standard_name="latitude", units="degrees")
lon_meta = Metadata(standard_name="longitude", units="degrees")
time_meta = Metadata(standard_name="time", units=cstu)
lat = Coord(concatenate(lat_data), lat_meta, "Y")
lat.update_shape()
lat.update_range()
lon = Coord(concatenate(lon_data), lon_meta, "Y")
lon.update_shape()
lon.update_range()
time = Coord(concatenate(time_data), time_meta, "T")
time.update_shape()
time.update_range()
return CoordList([lat, lon, time])
def _create_coord_list(self):
"""Read file coordinates into a CIS object"""
from cis.data_io.Coord import Coord, CoordList
from reame.utils import ncdf_read
try:
lon_data, lon_metadata = ncdf_read(self.filenames, "longitude")
lat_data, lat_metadata = ncdf_read(self.filenames, "latitude")
except IndexError:
lon_data, lon_metadata = ncdf_read(self.filenames, "lon")
lat_data, lat_metadata = ncdf_read(self.filenames, "lat")
lat = Coord(lat_data, lat_metadata, "Y")
lat.update_shape()
lat.update_range()
lon = Coord(lon_data, lon_metadata, "X")
lon.update_shape()
lat.update_range()
time_data, time_metadata = ncdf_read(self.filenames, "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(ATSR_REFERENCE_TIME)
time.update_shape()
time.update_range()
return CoordList([lat, lon, time])
def _create_coord_list(self):
from cis.data_io.Coord import Coord, CoordList
from cis.data_io.ungridded_data import Metadata
from cis.time_util import convert_sec_since_to_std_time
from os.path import basename
lat_all = []
lon_all = []
time_all = []
for fname in self.filenames:
var_name = self.gdal_variable_name(fname, "Optical_Depth_055")
if self.grid_path:
granule = basename(fname).split(".")[2]
lat_data, lon_data = self._read_grid_centres(granule)
else:
lat_data, lon_data = self._calculate_grid_centres(var_name)
time_data = self._calculate_grid_time(var_name, lat_data, lon_data)
# Workaround files containing only one day
sh = (-1, ) + lat_data.shape
time_data = time_data.reshape(sh)
keep = np.logical_not(self._read_qcmask(fname)).reshape(sh)
for time_slice, keep_slice in zip(time_data, keep):
lat_all.extend(lat_data[keep_slice])
lon_all.extend(lon_data[keep_slice])
time_all.extend(time_slice[keep_slice])
if len(lat_all) == 0:
raise NotImplementedError("It's empty!")
lat = Coord(
np.ma.array(lat_all),
Metadata(name="lat",
standard_name="latitude",
units="degrees",
range=(-90., 90.)), "Y")
lat.update_shape()
lon = Coord(
np.ma.array(lon_all),
Metadata(name="lon",
standard_name="longitude",
units="degrees",
range=(-180., 180.)), "X")
lon.update_shape()
time = Coord(
np.ma.array(time_all),
Metadata(name="time",
standard_name="time",
units="Seconds since 1993-1-1 00:00:00.0 0"), "T")
time.convert_TAI_time_to_std_time(MODIS_REFERENCE_TIME)
time.update_shape()
# Set the QC mask as we now know how many points we have
self._qcmask = np.full(lat.shape, False)
return CoordList([lat, lon, time])
def _create_bounded_coord_list(self):
from cis.data_io.Coord import Coord, CoordList
from cis.data_io.ungridded_data import Metadata
from cis.time_util import cis_standard_time_unit as cstu
# These implement a lot of what is necessary, but aren't in CIS style
from acp_utils import rolling_window
from orbit import MODIS
lat_data = []
lat_bounds = []
lon_data = []
lon_bounds = []
time_data = []
time_bounds = []
for fname in self.filenames:
prod = MODIS(fname)
lat_data.append(prod.lat)
lon_data.append(prod.lon)
lat_c = rolling_window(prod.lat_corner, (2, 2))
lat_bounds.append(lat_c.reshape(prod.shape + (4, )))
lon_c = rolling_window(prod.lon_corner, (2, 2))
lon_bounds.append(lon_c.reshape(prod.shape + (4, )))
t = prod.get_time()
time_data.append(t)
b = np.stack([t, np.roll(t, -1)], axis=2)
b[-1, :, 1] = 2 * t[-1, :] - t[-2, :]
time_bounds.append(b)
# TODO: Properly define metadata
lat_meta = Metadata(standard_name="latitude", units="degrees")
lon_meta = Metadata(standard_name="longitude", units="degrees")
time_meta = Metadata(standard_name="time", units=cstu)
lat = Coord(concatenate(lat_data), lat_meta, "Y")
lat.update_shape()
lat.update_range()
lat.bounds = concatenate(lat_bounds).reshape(lat.shape + (4, ))
lat.bounds[..., 2:4] = lat.bounds[..., [3, 2]]
lon = Coord(concatenate(lon_data), lon_meta, "Y")
lon.update_shape()
lon.update_range()
lon.bounds = concatenate(lon_bounds).reshape(lon.shape + (4, ))
lon.bounds[..., 2:4] = lon.bounds[..., [3, 2]]
time = Coord(concatenate(time_data), time_meta, "T")
time.update_shape()
time.update_range()
time.bounds = concatenate(time_bounds)
return CoordList([lat, lon, time])
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])
