def HDF5_ATL03_mask_write(IS2_atl03_mask,
IS2_atl03_attrs,
INPUT=None,
FILENAME='',
FILL_VALUE=None,
DIMENSIONS=None,
CLOBBER=True):
#-- setting HDF5 clobber attribute
if CLOBBER:
clobber = 'w'
else:
clobber = 'w-'
#-- open output HDF5 file
fileID = h5py.File(os.path.expanduser(FILENAME), clobber)
#-- create HDF5 records
h5 = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
h5['ancillary_data'] = {}
for k, v in IS2_atl03_mask['ancillary_data'].items():
#-- Defining the HDF5 dataset variables
val = 'ancillary_data/{0}'.format(k)
h5['ancillary_data'][k] = fileID.create_dataset(val,
np.shape(v),
data=v,
dtype=v.dtype,
compression='gzip')
#-- add HDF5 variable attributes
for att_name, att_val in IS2_atl03_attrs['ancillary_data'][k].items():
h5['ancillary_data'][k].attrs[att_name] = att_val
#-- write each output beam
beams = [
k for k in IS2_atl03_mask.keys() if bool(re.match(r'gt\d[lr]', k))
]
for gtx in beams:
fileID.create_group(gtx)
#-- add HDF5 group attributes for beam
for att_name in [
'Description', 'atlas_pce', 'atlas_beam_type',
'groundtrack_id', 'atmosphere_profile', 'atlas_spot_number',
'sc_orientation'
]:
fileID[gtx].attrs[att_name] = IS2_atl03_attrs[gtx][att_name]
#-- for each output data group
for key in ['heights', 'subsetting']:
#-- create group
fileID[gtx].create_group(key)
h5[gtx][key] = {}
for att_name in ['Description', 'data_rate']:
att_val = IS2_atl03_attrs[gtx][key][att_name]
fileID[gtx][key].attrs[att_name] = att_val
#-- all variables for group
groupkeys = set(IS2_atl03_mask[gtx][key].keys()) - set(
['delta_time'])
for k in ['delta_time', *sorted(groupkeys)]:
#-- values and attributes
v = IS2_atl03_mask[gtx][key][k]
attrs = IS2_atl03_attrs[gtx][key][k]
fillvalue = FILL_VALUE[gtx][key][k]
#-- Defining the HDF5 dataset variables
val = '{0}/{1}/{2}'.format(gtx, key, k)
if fillvalue:
h5[gtx][key][k] = fileID.create_dataset(
val,
np.shape(v),
data=v,
dtype=v.dtype,
fillvalue=fillvalue,
compression='gzip')
else:
h5[gtx][key][k] = fileID.create_dataset(val,
np.shape(v),
data=v,
dtype=v.dtype,
compression='gzip')
#-- create or attach dimensions for HDF5 variable
if DIMENSIONS[gtx][key][k]:
#-- attach dimensions
for i, dim in enumerate(DIMENSIONS[gtx][key][k]):
h5[gtx][key][k].dims[i].attach_scale(h5[gtx][key][dim])
else:
#-- make dimension
h5[gtx][key][k].make_scale(k)
#-- add HDF5 variable attributes
for att_name, att_val in attrs.items():
h5[gtx][key][k].attrs[att_name] = att_val
#-- HDF5 file title
fileID.attrs['featureType'] = 'trajectory'
fileID.attrs['title'] = 'ATLAS/ICESat-2 L2A Global Geolocated Photon Data'
fileID.attrs['summary'] = (
"The purpose of ATL03 is to provide along-track "
"photon data for all 6 ATLAS beams and associated statistics.")
fileID.attrs['description'] = (
"Photon heights determined by ATBD "
"Algorithm using POD and PPD. All photon events per transmit pulse per "
"beam. Includes POD and PPD vectors. Classification of each photon by "
"several ATBD Algorithms.")
date_created = datetime.datetime.today()
fileID.attrs['date_created'] = date_created.isoformat()
project = 'ICESat-2 > Ice, Cloud, and land Elevation Satellite-2'
fileID.attrs['project'] = project
platform = 'ICESat-2 > Ice, Cloud, and land Elevation Satellite-2'
fileID.attrs['project'] = platform
#-- add attribute for elevation instrument and designated processing level
instrument = 'ATLAS > Advanced Topographic Laser Altimeter System'
fileID.attrs['instrument'] = instrument
fileID.attrs['source'] = 'Spacecraft'
fileID.attrs['references'] = 'https://nsidc.org/data/icesat-2'
fileID.attrs['processing_level'] = '4'
#-- add attributes for input ATL03 and ATL09 files
fileID.attrs['input_files'] = ','.join(
[os.path.basename(i) for i in INPUT])
#-- find geospatial and temporal ranges
lnmn, lnmx, ltmn, ltmx, tmn, tmx = (np.inf, -np.inf, np.inf, -np.inf,
np.inf, -np.inf)
for gtx in beams:
lon = IS2_atl03_mask[gtx]['heights']['longitude']
lat = IS2_atl03_mask[gtx]['heights']['latitude']
delta_time = IS2_atl03_mask[gtx]['heights']['delta_time']
#-- setting the geospatial and temporal ranges
lnmn = lon.min() if (lon.min() < lnmn) else lnmn
lnmx = lon.max() if (lon.max() > lnmx) else lnmx
ltmn = lat.min() if (lat.min() < ltmn) else ltmn
ltmx = lat.max() if (lat.max() > ltmx) else ltmx
tmn = delta_time.min() if (delta_time.min() < tmn) else tmn
tmx = delta_time.max() if (delta_time.max() > tmx) else tmx
#-- add geospatial and temporal attributes
fileID.attrs['geospatial_lat_min'] = ltmn
fileID.attrs['geospatial_lat_max'] = ltmx
fileID.attrs['geospatial_lon_min'] = lnmn
fileID.attrs['geospatial_lon_max'] = lnmx
fileID.attrs['geospatial_lat_units'] = "degrees_north"
fileID.attrs['geospatial_lon_units'] = "degrees_east"
fileID.attrs['geospatial_ellipsoid'] = "WGS84"
fileID.attrs['date_type'] = 'UTC'
fileID.attrs['time_type'] = 'CCSDS UTC-A'
#-- convert start and end time from ATLAS SDP seconds into UTC time
time_utc = convert_delta_time(np.array([tmn, tmx]))
#-- convert to calendar date
YY, MM, DD, HH, MN, SS = icesat2_toolkit.time.convert_julian(
time_utc['julian'], FORMAT='tuple')
#-- add attributes with measurement date start, end and duration
tcs = datetime.datetime(int(YY[0]), int(MM[0]), int(DD[0]), int(HH[0]),
int(MN[0]), int(SS[0]), int(1e6 * (SS[0] % 1)))
fileID.attrs['time_coverage_start'] = tcs.isoformat()
tce = datetime.datetime(int(YY[1]), int(MM[1]), int(DD[1]), int(HH[1]),
int(MN[1]), int(SS[1]), int(1e6 * (SS[1] % 1)))
fileID.attrs['time_coverage_end'] = tce.isoformat()
fileID.attrs['time_coverage_duration'] = '{0:0.0f}'.format(tmx - tmn)
#-- Closing the HDF5 file
fileID.close()
def HDF5_ATL06_mask_write(IS2_atl06_mask,
IS2_atl06_attrs,
INPUT=None,
FILENAME='',
FILL_VALUE=None,
CLOBBER=True):
#-- setting HDF5 clobber attribute
if CLOBBER:
clobber = 'w'
else:
clobber = 'w-'
#-- open output HDF5 file
fileID = h5py.File(os.path.expanduser(FILENAME), clobber)
#-- create HDF5 records
h5 = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
h5['ancillary_data'] = {}
for k, v in IS2_atl06_mask['ancillary_data'].items():
#-- Defining the HDF5 dataset variables
val = 'ancillary_data/{0}'.format(k)
h5['ancillary_data'][k] = fileID.create_dataset(val,
np.shape(v),
data=v,
dtype=v.dtype,
compression='gzip')
#-- add HDF5 variable attributes
for att_name, att_val in IS2_atl06_attrs['ancillary_data'][k].items():
h5['ancillary_data'][k].attrs[att_name] = att_val
#-- write each output beam
beams = [
k for k in IS2_atl06_mask.keys() if bool(re.match(r'gt\d[lr]', k))
]
for gtx in beams:
fileID.create_group(gtx)
#-- add HDF5 group attributes for beam
for att_name in [
'Description', 'atlas_pce', 'atlas_beam_type',
'groundtrack_id', 'atmosphere_profile', 'atlas_spot_number',
'sc_orientation'
]:
fileID[gtx].attrs[att_name] = IS2_atl06_attrs[gtx][att_name]
#-- create land_ice_segments group
fileID[gtx].create_group('land_ice_segments')
h5[gtx] = dict(land_ice_segments={})
for att_name in ['Description', 'data_rate']:
att_val = IS2_atl06_attrs[gtx]['land_ice_segments'][att_name]
fileID[gtx]['land_ice_segments'].attrs[att_name] = att_val
#-- segment_id
v = IS2_atl06_mask[gtx]['land_ice_segments']['segment_id']
attrs = IS2_atl06_attrs[gtx]['land_ice_segments']['segment_id']
#-- Defining the HDF5 dataset variables
val = '{0}/{1}/{2}'.format(gtx, 'land_ice_segments', 'segment_id')
h5[gtx]['land_ice_segments']['segment_id'] = fileID.create_dataset(
val, np.shape(v), data=v, dtype=v.dtype, compression='gzip')
#-- add HDF5 variable attributes
for att_name, att_val in attrs.items():
h5[gtx]['land_ice_segments']['segment_id'].attrs[
att_name] = att_val
#-- geolocation, time and height variables
for k in ['latitude', 'longitude', 'delta_time']:
#-- values and attributes
v = IS2_atl06_mask[gtx]['land_ice_segments'][k]
attrs = IS2_atl06_attrs[gtx]['land_ice_segments'][k]
fillvalue = FILL_VALUE[gtx]['land_ice_segments'][k]
#-- Defining the HDF5 dataset variables
val = '{0}/{1}/{2}'.format(gtx, 'land_ice_segments', k)
h5[gtx]['land_ice_segments'][k] = fileID.create_dataset(
val,
np.shape(v),
data=v,
dtype=v.dtype,
fillvalue=fillvalue,
compression='gzip')
#-- attach dimensions
for dim in ['segment_id']:
h5[gtx]['land_ice_segments'][k].dims.create_scale(
h5[gtx]['land_ice_segments'][dim], dim)
h5[gtx]['land_ice_segments'][k].dims[0].attach_scale(
h5[gtx]['land_ice_segments'][dim])
#-- add HDF5 variable attributes
for att_name, att_val in attrs.items():
h5[gtx]['land_ice_segments'][k].attrs[att_name] = att_val
#-- add to subsetting variables
key = 'subsetting'
fileID[gtx]['land_ice_segments'].create_group(key)
h5[gtx]['land_ice_segments'][key] = {}
for att_name in ['Description', 'data_rate']:
att_val = IS2_atl06_attrs[gtx]['land_ice_segments'][key][att_name]
fileID[gtx]['land_ice_segments'][key].attrs[att_name] = att_val
for k, v in IS2_atl06_mask[gtx]['land_ice_segments'][key].items():
#-- attributes
attrs = IS2_atl06_attrs[gtx]['land_ice_segments'][key][k]
#-- Defining the HDF5 dataset variables
val = '{0}/{1}/{2}/{3}'.format(gtx, 'land_ice_segments', key, k)
h5[gtx]['land_ice_segments'][key][k] = \
fileID.create_dataset(val, np.shape(v), data=v,
dtype=v.dtype, compression='gzip')
#-- attach dimensions
for dim in ['segment_id']:
h5[gtx]['land_ice_segments'][key][k].dims.create_scale(
h5[gtx]['land_ice_segments'][dim], dim)
h5[gtx]['land_ice_segments'][key][k].dims[0].attach_scale(
h5[gtx]['land_ice_segments'][dim])
#-- add HDF5 variable attributes
for att_name, att_val in attrs.items():
h5[gtx]['land_ice_segments'][key][k].attrs[att_name] = att_val
#-- HDF5 file title
fileID.attrs['featureType'] = 'trajectory'
fileID.attrs['title'] = 'ATLAS/ICESat-2 Land Ice Height'
fileID.attrs['summary'] = (
'Subsetting masks for ice-sheets segments '
'needed to interpret and assess the quality of land height estimates.')
fileID.attrs['description'] = (
'Land ice parameters for each beam. All '
'parameters are calculated for the same along-track increments for '
'each beam and repeat.')
date_created = datetime.datetime.today()
fileID.attrs['date_created'] = date_created.isoformat()
project = 'ICESat-2 > Ice, Cloud, and land Elevation Satellite-2'
fileID.attrs['project'] = project
platform = 'ICESat-2 > Ice, Cloud, and land Elevation Satellite-2'
fileID.attrs['project'] = platform
#-- add attribute for elevation instrument and designated processing level
instrument = 'ATLAS > Advanced Topographic Laser Altimeter System'
fileID.attrs['instrument'] = instrument
fileID.attrs['source'] = 'Spacecraft'
fileID.attrs['references'] = 'http://nsidc.org/data/icesat2/data.html'
fileID.attrs['processing_level'] = '4'
#-- add attributes for input ATL06 files
fileID.attrs['input_files'] = ','.join(
[os.path.basename(i) for i in INPUT])
#-- find geospatial and temporal ranges
lnmn, lnmx, ltmn, ltmx, tmn, tmx = (np.inf, -np.inf, np.inf, -np.inf,
np.inf, -np.inf)
for gtx in beams:
lon = IS2_atl06_mask[gtx]['land_ice_segments']['longitude']
lat = IS2_atl06_mask[gtx]['land_ice_segments']['latitude']
delta_time = IS2_atl06_mask[gtx]['land_ice_segments']['delta_time']
#-- setting the geospatial and temporal ranges
lnmn = lon.min() if (lon.min() < lnmn) else lnmn
lnmx = lon.max() if (lon.max() > lnmx) else lnmx
ltmn = lat.min() if (lat.min() < ltmn) else ltmn
ltmx = lat.max() if (lat.max() > ltmx) else ltmx
tmn = delta_time.min() if (delta_time.min() < tmn) else tmn
tmx = delta_time.max() if (delta_time.max() > tmx) else tmx
#-- add geospatial and temporal attributes
fileID.attrs['geospatial_lat_min'] = ltmn
fileID.attrs['geospatial_lat_max'] = ltmx
fileID.attrs['geospatial_lon_min'] = lnmn
fileID.attrs['geospatial_lon_max'] = lnmx
fileID.attrs['geospatial_lat_units'] = "degrees_north"
fileID.attrs['geospatial_lon_units'] = "degrees_east"
fileID.attrs['geospatial_ellipsoid'] = "WGS84"
fileID.attrs['date_type'] = 'UTC'
fileID.attrs['time_type'] = 'CCSDS UTC-A'
#-- convert start and end time from ATLAS SDP seconds into UTC time
time_utc = convert_delta_time(np.array([tmn, tmx]))
#-- convert to calendar date with convert_julian.py
YY, MM, DD, HH, MN, SS = convert_julian(time_utc['julian'], FORMAT='tuple')
#-- add attributes with measurement date start, end and duration
tcs = datetime.datetime(np.int(YY[0]), np.int(MM[0]), np.int(DD[0]),
np.int(HH[0]), np.int(MN[0]), np.int(SS[0]),
np.int(1e6 * (SS[0] % 1)))
fileID.attrs['time_coverage_start'] = tcs.isoformat()
tce = datetime.datetime(np.int(YY[1]), np.int(MM[1]), np.int(DD[1]),
np.int(HH[1]), np.int(MN[1]), np.int(SS[1]),
np.int(1e6 * (SS[1] % 1)))
fileID.attrs['time_coverage_end'] = tce.isoformat()
fileID.attrs['time_coverage_duration'] = '{0:0.0f}'.format(tmx - tmn)
#-- Closing the HDF5 file
fileID.close()
def HDF5_ATL11_mask_write(IS2_atl11_mask,
IS2_atl11_attrs,
INPUT=None,
FILENAME='',
FILL_VALUE=None,
DIMENSIONS=None,
CLOBBER=True):
#-- setting HDF5 clobber attribute
if CLOBBER:
clobber = 'w'
else:
clobber = 'w-'
#-- open output HDF5 file
fileID = h5py.File(os.path.expanduser(FILENAME), clobber)
#-- create HDF5 records
h5 = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
h5['ancillary_data'] = {}
for k, v in IS2_atl11_mask['ancillary_data'].items():
#-- Defining the HDF5 dataset variables
val = 'ancillary_data/{0}'.format(k)
h5['ancillary_data'][k] = fileID.create_dataset(val,
np.shape(v),
data=v,
dtype=v.dtype,
compression='gzip')
#-- add HDF5 variable attributes
for att_name, att_val in IS2_atl11_attrs['ancillary_data'][k].items():
h5['ancillary_data'][k].attrs[att_name] = att_val
#-- write each output beam pair
pairs = [k for k in IS2_atl11_mask.keys() if bool(re.match(r'pt\d', k))]
for ptx in pairs:
fileID.create_group(ptx)
#-- add HDF5 group attributes for beam pair
for att_name in [
'description', 'beam_pair', 'ReferenceGroundTrack',
'first_cycle', 'last_cycle', 'equatorial_radius',
'polar_radius'
]:
fileID[ptx].attrs[att_name] = IS2_atl11_attrs[ptx][att_name]
#-- ref_pt, cycle number, geolocation and delta_time variables
for k in [
'ref_pt', 'cycle_number', 'delta_time', 'latitude', 'longitude'
]:
#-- values and attributes
v = IS2_atl11_mask[ptx][k]
attrs = IS2_atl11_attrs[ptx][k]
fillvalue = FILL_VALUE[ptx][k]
#-- Defining the HDF5 dataset variables
val = '{0}/{1}'.format(ptx, k)
if fillvalue:
h5[ptx][k] = fileID.create_dataset(val,
np.shape(v),
data=v,
dtype=v.dtype,
fillvalue=fillvalue,
compression='gzip')
else:
h5[ptx][k] = fileID.create_dataset(val,
np.shape(v),
data=v,
dtype=v.dtype,
compression='gzip')
#-- create or attach dimensions for HDF5 variable
if DIMENSIONS[ptx][k]:
#-- attach dimensions
for i, dim in enumerate(DIMENSIONS[ptx][k]):
h5[ptx][k].dims[i].attach_scale(h5[ptx][dim])
else:
#-- make dimension
h5[ptx][k].make_scale(k)
#-- add HDF5 variable attributes
for att_name, att_val in attrs.items():
h5[ptx][k].attrs[att_name] = att_val
#-- add to subsetting variables
fileID[ptx].create_group('subsetting')
h5[ptx]['subsetting'] = {}
for att_name in ['Description', 'data_rate']:
att_val = IS2_atl11_attrs[ptx]['subsetting'][att_name]
fileID[ptx]['subsetting'].attrs[att_name] = att_val
for k, v in IS2_atl11_mask[ptx]['subsetting'].items():
#-- attributes
attrs = IS2_atl11_attrs[ptx]['subsetting'][k]
fillvalue = FILL_VALUE[ptx]['subsetting'][k]
#-- Defining the HDF5 dataset variables
val = '{0}/{1}/{2}'.format(ptx, 'subsetting', k)
if fillvalue:
h5[ptx]['subsetting'][k] = fileID.create_dataset(
val,
np.shape(v),
data=v,
dtype=v.dtype,
fillvalue=fillvalue,
compression='gzip')
else:
h5[ptx]['subsetting'][k] = fileID.create_dataset(
val,
np.shape(v),
data=v,
dtype=v.dtype,
compression='gzip')
#-- attach dimensions
for i, dim in enumerate(DIMENSIONS[ptx]['subsetting'][k]):
h5[ptx]['subsetting'][k].dims[i].attach_scale(h5[ptx][dim])
#-- add HDF5 variable attributes
for att_name, att_val in attrs.items():
h5[ptx]['subsetting'][k].attrs[att_name] = att_val
#-- HDF5 file title
fileID.attrs['featureType'] = 'trajectory'
fileID.attrs['title'] = 'ATLAS/ICESat-2 Land Ice Height'
fileID.attrs['summary'] = (
'Subsetting masks and geophysical parameters '
'for land ice segments needed to interpret and assess the quality '
'of annual land height estimates.')
fileID.attrs['description'] = (
'Land ice parameters for each beam pair. '
'All parameters are calculated for the same along-track increments '
'for each beam pair and repeat.')
date_created = datetime.datetime.today()
fileID.attrs['date_created'] = date_created.isoformat()
project = 'ICESat-2 > Ice, Cloud, and land Elevation Satellite-2'
fileID.attrs['project'] = project
platform = 'ICESat-2 > Ice, Cloud, and land Elevation Satellite-2'
fileID.attrs['project'] = platform
#-- add attribute for elevation instrument and designated processing level
instrument = 'ATLAS > Advanced Topographic Laser Altimeter System'
fileID.attrs['instrument'] = instrument
fileID.attrs['source'] = 'Spacecraft'
fileID.attrs['references'] = 'https://nsidc.org/data/icesat-2'
fileID.attrs['processing_level'] = '4'
#-- add attributes for input ATL11 files
fileID.attrs['input_files'] = ','.join(
[os.path.basename(i) for i in INPUT])
#-- find geospatial and temporal ranges
lnmn, lnmx, ltmn, ltmx, tmn, tmx = (np.inf, -np.inf, np.inf, -np.inf,
np.inf, -np.inf)
for ptx in pairs:
lon = IS2_atl11_mask[ptx]['longitude']
lat = IS2_atl11_mask[ptx]['latitude']
delta_time = IS2_atl11_mask[ptx]['delta_time']
valid = np.nonzero(delta_time != FILL_VALUE[ptx]['delta_time'])
#-- setting the geospatial and temporal ranges
lnmn = lon.min() if (lon.min() < lnmn) else lnmn
lnmx = lon.max() if (lon.max() > lnmx) else lnmx
ltmn = lat.min() if (lat.min() < ltmn) else ltmn
ltmx = lat.max() if (lat.max() > ltmx) else ltmx
tmn = delta_time[valid].min() if (
delta_time[valid].min() < tmn) else tmn
tmx = delta_time[valid].max() if (
delta_time[valid].max() > tmx) else tmx
#-- add geospatial and temporal attributes
fileID.attrs['geospatial_lat_min'] = ltmn
fileID.attrs['geospatial_lat_max'] = ltmx
fileID.attrs['geospatial_lon_min'] = lnmn
fileID.attrs['geospatial_lon_max'] = lnmx
fileID.attrs['geospatial_lat_units'] = "degrees_north"
fileID.attrs['geospatial_lon_units'] = "degrees_east"
fileID.attrs['geospatial_ellipsoid'] = "WGS84"
fileID.attrs['date_type'] = 'UTC'
fileID.attrs['time_type'] = 'CCSDS UTC-A'
#-- convert start and end time from ATLAS SDP seconds into UTC time
time_utc = convert_delta_time(np.array([tmn, tmx]))
#-- convert to calendar date
YY, MM, DD, HH, MN, SS = icesat2_toolkit.time.convert_julian(
time_utc['julian'], FORMAT='tuple')
#-- add attributes with measurement date start, end and duration
tcs = datetime.datetime(np.int(YY[0]), np.int(MM[0]), np.int(DD[0]),
np.int(HH[0]), np.int(MN[0]), np.int(SS[0]),
np.int(1e6 * (SS[0] % 1)))
fileID.attrs['time_coverage_start'] = tcs.isoformat()
tce = datetime.datetime(np.int(YY[1]), np.int(MM[1]), np.int(DD[1]),
np.int(HH[1]), np.int(MN[1]), np.int(SS[1]),
np.int(1e6 * (SS[1] % 1)))
fileID.attrs['time_coverage_end'] = tce.isoformat()
fileID.attrs['time_coverage_duration'] = '{0:0.0f}'.format(tmx - tmn)
#-- Closing the HDF5 file
fileID.close()
