def test_julian(YEAR, MONTH):
#-- days per month in a leap and a standard year
#-- only difference is February (29 vs. 28)
dpm_leap = np.array([31, 29, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31])
dpm_stnd = np.array([31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31])
DPM = dpm_stnd if np.mod(YEAR, 4) else dpm_leap
#-- calculate Modified Julian Day (MJD) from calendar date
DAY = np.random.randint(1, DPM[MONTH - 1] + 1)
HOUR = np.random.randint(0, 23 + 1)
MINUTE = np.random.randint(0, 59 + 1)
SECOND = 60.0 * np.random.random_sample(1)
MJD = icesat2_toolkit.time.convert_calendar_dates(YEAR,
MONTH,
DAY,
hour=HOUR,
minute=MINUTE,
second=SECOND,
epoch=(1858, 11, 17, 0,
0, 0))
#-- convert MJD to calendar date
YY, MM, DD, HH, MN, SS = convert_julian(MJD + 2400000.5, FORMAT='tuple')
#-- assert dates
eps = np.finfo(np.float16).eps
assert (YY == YEAR)
assert (MM == MONTH)
assert (DD == DAY)
assert (HH == HOUR)
assert (MN == MINUTE)
assert (np.abs(SS - SECOND) < eps)
def convert_delta_time(delta_time, gps_epoch=1198800018.0):
"""
converts ICESat-2 delta_times into into Julian and year-decimal
Arguments
---------
delta_time: seconds since gps_epoch
Keyword arguments
-----------------
gps_epoch: seconds between delta_time and GPS epoch (1980-01-06T00:00:00)
Returns
-------
julian: time in Julian days
decimal: time in year-decimal
"""
#-- convert to array if single value
if (np.ndim(delta_time) == 0):
delta_time = np.array([delta_time])
#-- calculate gps time from delta_time
gps_seconds = gps_epoch + delta_time
time_leaps = count_leap_seconds(gps_seconds)
#-- calculate Julian time (UTC)
time_julian = 2444244.5 + (gps_seconds - time_leaps)/86400.0
#-- convert to calendar date with convert_julian.py
Y,M,D,h,m,s = convert_julian(time_julian,FORMAT='tuple')
#-- calculate year-decimal time (UTC)
time_decimal = convert_calendar_decimal(Y,M,DAY=D,HOUR=h,MINUTE=m,SECOND=s)
#-- return both the Julian and year-decimal formatted dates
return dict(julian=np.squeeze(time_julian),decimal=np.squeeze(time_decimal))
def convert_delta_time(delta_time, gps_epoch=1198800018.0):
"""
converts ICESat-2 delta_times into into Julian and year-decimal
Arguments
---------
delta_time: seconds since gps_epoch
Keyword arguments
-----------------
gps_epoch: seconds between delta_time and GPS epoch (1980-01-06T00:00:00)
Returns
-------
julian: time in Julian days
decimal: time in year-decimal
"""
#-- convert to array if single value
delta_time = np.atleast_1d(delta_time)
#-- calculate gps time from delta_time
gps_seconds = gps_epoch + delta_time
time_leaps = icesat2_toolkit.time.count_leap_seconds(gps_seconds)
#-- calculate Julian time (UTC) by converting to MJD and then adding offset
time_julian = 2400000.5 + icesat2_toolkit.time.convert_delta_time(
gps_seconds - time_leaps,
epoch1=(1980, 1, 6, 0, 0, 0),
epoch2=(1858, 11, 17, 0, 0, 0),
scale=1.0 / 86400.0)
#-- convert to calendar date with convert_julian.py
Y, M, D, h, m, s = convert_julian(time_julian, FORMAT='tuple')
#-- calculate year-decimal time (UTC)
time_decimal = convert_calendar_decimal(Y,
M,
DAY=D,
HOUR=h,
MINUTE=m,
SECOND=s)
#-- return both the Julian and year-decimal formatted dates
return dict(julian=np.squeeze(time_julian),
decimal=np.squeeze(time_decimal))
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_ATL03_dem_write(IS2_atl03_dem, IS2_atl03_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_atl03_dem['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_dem.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]
#-- create heights group
fileID[gtx].create_group('heights')
h5[gtx] = dict(heights={})
for att_name in ['Description','data_rate']:
att_val = IS2_atl03_attrs[gtx]['heights'][att_name]
fileID[gtx]['heights'].attrs[att_name] = att_val
#-- delta_time
v = IS2_atl03_dem[gtx]['heights']['delta_time']
attrs = IS2_atl03_attrs[gtx]['heights']['delta_time']
#-- Defining the HDF5 dataset variables
val = '{0}/{1}/{2}'.format(gtx,'heights','delta_time')
h5[gtx]['heights']['delta_time'] = 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]['heights']['delta_time'].attrs[att_name] = att_val
#-- geolocation and height variables
for k in ['latitude','longitude','dem_h']:
#-- values and attributes
v = IS2_atl03_dem[gtx]['heights'][k]
attrs = IS2_atl03_attrs[gtx]['heights'][k]
fillvalue = FILL_VALUE[gtx]['heights'][k]
#-- Defining the HDF5 dataset variables
val = '{0}/{1}/{2}'.format(gtx,'heights',k)
if fillvalue:
h5[gtx]['heights'][k] = fileID.create_dataset(val, np.shape(v),
data=v,dtype=v.dtype,fillvalue=fillvalue,compression='gzip')
else:
h5[gtx]['heights'][k] = fileID.create_dataset(val, np.shape(v),
data=v, dtype=v.dtype, compression='gzip')
#-- attach dimensions
for dim in ['delta_time']:
h5[gtx]['heights'][k].dims.create_scale(
h5[gtx]['heights'][dim], dim)
h5[gtx]['heights'][k].dims[0].attach_scale(
h5[gtx]['heights'][dim])
#-- add HDF5 variable attributes
for att_name,att_val in attrs.items():
h5[gtx]['heights'][k].attrs[att_name] = att_val
#-- create subsetting group
fileID[gtx].create_group('subsetting')
h5[gtx]['subsetting'] = {}
for att_name in ['Description','data_rate']:
att_val = IS2_atl03_attrs[gtx]['subsetting'][att_name]
fileID[gtx]['subsetting'].attrs[att_name] = att_val
#-- add to subsetting variables
for k,v in IS2_atl03_dem[gtx]['subsetting'].items():
#-- attributes
attrs = IS2_atl03_attrs[gtx]['subsetting'][k]
#-- Defining the HDF5 dataset variables
val = '{0}/{1}/{2}'.format(gtx,'subsetting',k)
h5[gtx]['subsetting'][k] = fileID.create_dataset(val, np.shape(v),
data=v, dtype=v.dtype, compression='gzip')
#-- attach dimensions
for dim in ['delta_time']:
h5[gtx]['subsetting'][k].dims.create_scale(
h5[gtx]['heights'][dim], dim)
h5[gtx]['subsetting'][k].dims[0].attach_scale(
h5[gtx]['heights'][dim])
#-- add HDF5 variable attributes
for att_name,att_val in attrs.items():
h5[gtx]['subsetting'][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'] = 'http://nsidc.org/data/icesat2/data.html'
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_dem[gtx]['heights']['longitude']
lat = IS2_atl03_dem[gtx]['heights']['latitude']
delta_time = IS2_atl03_dem[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 Julian days
atlas_sdp_gps_epoch=IS2_atl03_dem['ancillary_data']['atlas_sdp_gps_epoch']
gps_seconds = atlas_sdp_gps_epoch + np.array([tmn,tmx])
time_leaps = count_leap_seconds(gps_seconds)
time_julian = 2444244.5 + (gps_seconds - time_leaps)/86400.0
#-- convert to calendar date with convert_julian.py
YY,MM,DD,HH,MN,SS = convert_julian(time_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()
