def get_bounding_box(meta, geom_file=None):
"""Get lat/lon range (roughly), in the same order of data file
lat0/lon0 - starting latitude/longitude (first row/column)
lat1/lon1 - ending latitude/longitude (last row/column)
"""
length, width = int(meta['LENGTH']), int(meta['WIDTH'])
if 'Y_FIRST' in meta.keys():
# geo coordinates
lat0 = float(meta['Y_FIRST'])
lon0 = float(meta['X_FIRST'])
lat_step = float(meta['Y_STEP'])
lon_step = float(meta['X_STEP'])
lat1 = lat0 + lat_step * (length - 1)
lon1 = lon0 + lon_step * (width - 1)
# 'Y_FIRST' not in 'degree'
# e.g. meters for UTM projection from ASF HyP3
y_unit = meta.get('Y_UNIT', 'degrees').lower()
if not y_unit.startswith('deg'):
lat0, lon0 = ut.to_latlon(meta['OG_FILE_PATH'], lon0, lat0)
lat1, lon1 = ut.to_latlon(meta['OG_FILE_PATH'], lon1, lat1)
else:
# radar coordinates
if geom_file and os.path.isfile(geom_file):
geom_dset_list = readfile.get_dataset_list(geom_file)
else:
geom_dset_list = []
if 'latitude' in geom_dset_list:
lats = readfile.read(geom_file, datasetName='latitude')[0]
lons = readfile.read(geom_file, datasetName='longitude')[0]
lats[lats == 0] = np.nan
lons[lons == 0] = np.nan
lat0 = np.nanmin(lats)
lat1 = np.nanmax(lats)
lon0 = np.nanmin(lons)
lon1 = np.nanmax(lons)
else:
lats = [float(meta['LAT_REF{}'.format(i)]) for i in [1,2,3,4]]
lons = [float(meta['LON_REF{}'.format(i)]) for i in [1,2,3,4]]
lat0 = np.mean(lats[0:2])
lat1 = np.mean(lats[2:4])
lon0 = np.mean(lons[0:3:2])
lon1 = np.mean(lons[1:4:2])
return lat0, lat1, lon0, lon1
def prepare_los_geometry(geom_file):
"""Prepare LOS geometry data/info in geo-coordinates
Parameters: geom_file - str, path of geometry file
Returns: inc_angle - 2D np.ndarray, incidence angle in radians
head_angle - 2D np.ndarray, heading angle in radians
atr - dict, metadata in geo-coordinate
"""
print('prepare LOS geometry in geo-coordinates from file: {}'.format(
geom_file))
atr = readfile.read_attribute(geom_file)
print('read incidenceAngle from file: {}'.format(geom_file))
inc_angle = readfile.read(geom_file, datasetName='incidenceAngle')[0]
if 'azimuthAngle' in readfile.get_dataset_list(geom_file):
print('read azimuthAngle from file: {}'.format(geom_file))
print('convert azimuth angle to heading angle')
az_angle = readfile.read(geom_file, datasetName='azimuthAngle')[0]
head_angle = ut.azimuth2heading_angle(az_angle)
else:
print('use the HEADING attribute as the mean heading angle')
head_angle = np.ones(inc_angle.shape, dtype=np.float32) * float(
atr['HEADING'])
# geocode inc/az angle data if in radar-coord
if 'Y_FIRST' not in atr.keys():
print('-' * 50)
print('geocoding the incidence / heading angles ...')
res_obj = resample(lut_file=geom_file, src_file=geom_file)
res_obj.open()
res_obj.prepare()
# resample data
box = res_obj.src_box_list[0]
inc_angle = res_obj.run_resample(src_data=inc_angle[box[1]:box[3],
box[0]:box[2]])
head_angle = res_obj.run_resample(src_data=head_angle[box[1]:box[3],
box[0]:box[2]])
# update attribute
atr = attr.update_attribute4radar2geo(atr, res_obj=res_obj)
# for 'Y_FIRST' not in 'degree'
# e.g. meters for UTM projection from ASF HyP3
if not atr['Y_UNIT'].lower().startswith('deg'):
# get SNWE in meter
length, width = int(atr['LENGTH']), int(atr['WIDTH'])
N = float(atr['Y_FIRST'])
W = float(atr['X_FIRST'])
y_step = float(atr['Y_STEP'])
x_step = float(atr['X_STEP'])
S = N + y_step * length
E = W + x_step * width
# SNWE in meter --> degree
lat0, lon0 = ut.to_latlon(atr['OG_FILE_PATH'], W, N)
lat1, lon1 = ut.to_latlon(atr['OG_FILE_PATH'], E, S)
lat_step = (lat1 - lat0) / length
lon_step = (lon1 - lon0) / width
# update Y/X_FIRST/STEP/UNIT
atr['Y_FIRST'] = lat0
atr['X_FIRST'] = lon0
atr['Y_STEP'] = lat_step
atr['X_STEP'] = lon_step
atr['Y_UNIT'] = 'degrees'
atr['X_UNIT'] = 'degrees'
# unit: degree to radian
inc_angle *= np.pi / 180.
head_angle *= np.pi / 180.
return inc_angle, head_angle, atr
def calc_delay_timeseries(inps):
"""Calculate delay time-series and write it to HDF5 file.
Parameters: inps : namespace, all input parameters
Returns: tropo_file : str, file name of ECMWF.h5
"""
def get_dataset_size(fname):
atr = readfile.read_attribute(fname)
shape = (int(atr['LENGTH']), int(atr['WIDTH']))
return shape
def run_or_skip(grib_files, tropo_file, geom_file):
print('update mode: ON')
print('output file: {}'.format(tropo_file))
flag = 'skip'
# check existance and modification time
if ut.run_or_skip(out_file=tropo_file,
in_file=grib_files,
print_msg=False) == 'run':
flag = 'run'
print(
'1) output file either do NOT exist or is NOT newer than all GRIB files.'
)
else:
print('1) output file exists and is newer than all GRIB files.')
# check dataset size in space / time
date_list = [
str(re.findall('\d{8}', os.path.basename(i))[0])
for i in grib_files
]
if (get_dataset_size(tropo_file) != get_dataset_size(geom_file)
or any(i not in timeseries(tropo_file).get_date_list()
for i in date_list)):
flag = 'run'
print(
'2) output file does NOT have the same len/wid as the geometry file {} or does NOT contain all dates'
.format(geom_file))
else:
print(
'2) output file has the same len/wid as the geometry file and contains all dates'
)
# check if output file is fully written
with h5py.File(tropo_file, 'r') as f:
if np.all(f['timeseries'][-1, :, :] == 0):
flag = 'run'
print('3) output file is NOT fully written.')
else:
print('3) output file is fully written.')
# result
print('run or skip: {}'.format(flag))
return flag
if run_or_skip(inps.grib_files, inps.tropo_file, inps.geom_file) == 'skip':
return
## 1. prepare geometry data
geom_obj = geometry(inps.geom_file)
geom_obj.open()
inps.inc = geom_obj.read(datasetName='incidenceAngle')
inps.dem = geom_obj.read(datasetName='height')
# for testing
if inps.custom_height:
print(
'use input custom height of {} m for vertical integration'.format(
inps.custom_height))
inps.dem[:] = inps.custom_height
if 'latitude' in geom_obj.datasetNames:
# for lookup table in radar-coord (isce, doris)
inps.lat = geom_obj.read(datasetName='latitude')
inps.lon = geom_obj.read(datasetName='longitude')
elif 'Y_FIRST' in geom_obj.metadata:
# for lookup table in geo-coded (gamma, roipac) and obs. in geo-coord
inps.lat, inps.lon = ut.get_lat_lon(geom_obj.metadata)
# convert coordinates to lat/lon, e.g. from UTM for ASF HyPP3
if not geom_obj.metadata['Y_UNIT'].startswith('deg'):
inps.lat, inps.lon = ut.to_latlon(inps.atr['OG_FILE_PATH'],
inps.lon, inps.lat)
else:
# for lookup table in geo-coded (gamma, roipac) and obs. in radar-coord
inps.lat, inps.lon = ut.get_lat_lon_rdc(inps.atr)
# mask of valid pixels
mask = np.multiply(inps.inc != 0, ~np.isnan(inps.inc))
## 2. prepare output file
# metadata
atr = inps.atr.copy()
atr['FILE_TYPE'] = 'timeseries'
atr['UNIT'] = 'm'
# remove metadata related with double reference
# because absolute delay is calculated and saved
for key in ['REF_DATE', 'REF_X', 'REF_Y', 'REF_LAT', 'REF_LON']:
if key in atr.keys():
atr.pop(key)
# instantiate time-series
length, width = int(atr['LENGTH']), int(atr['WIDTH'])
num_date = len(inps.grib_files)
date_list = [
str(re.findall('\d{8}', os.path.basename(i))[0])
for i in inps.grib_files
]
dates = np.array(date_list, dtype=np.string_)
ds_name_dict = {
"date": [dates.dtype, (num_date, ), dates],
"timeseries": [np.float32, (num_date, length, width), None],
}
writefile.layout_hdf5(inps.tropo_file, ds_name_dict, metadata=atr)
## 3. calculate phase delay
print(
'\n------------------------------------------------------------------------------'
)
print(
'calculating absolute delay for each date using PyAPS (Jolivet et al., 2011; 2014) ...'
)
print('number of grib files used: {}'.format(num_date))
prog_bar = ptime.progressBar(maxValue=num_date, print_msg=~inps.verbose)
for i in range(num_date):
grib_file = inps.grib_files[i]
# calc tropo delay
tropo_data = get_delay(grib_file,
tropo_model=inps.tropo_model,
delay_type=inps.delay_type,
dem=inps.dem,
inc=inps.inc,
lat=inps.lat,
lon=inps.lon,
mask=mask,
verbose=inps.verbose)
# write tropo delay to file
block = [i, i + 1, 0, length, 0, width]
writefile.write_hdf5_block(inps.tropo_file,
data=tropo_data,
datasetName='timeseries',
block=block,
print_msg=False)
prog_bar.update(i + 1, suffix=os.path.basename(grib_file))
prog_bar.close()
return inps.tropo_file