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save_hdfeos5.py
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save_hdfeos5.py
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############################################################
# Program is part of MintPy #
# Copyright (c) 2013, Zhang Yunjun, Heresh Fattahi #
# Author: Zhang Yunjun, 2016 #
############################################################
import datetime as dt
import os
import h5py
import numpy as np
from mintpy import info
from mintpy.objects import geometry, sensor, timeseries
from mintpy.utils import ptime, readfile, utils as ut
BOOL_ZERO = np.bool_(0)
INT_ZERO = np.int16(0)
FLOAT_ZERO = np.float32(0.0)
CPX_ZERO = np.complex64(0.0)
COMPRESSION = 'lzf'
################################################################
def read_template2inps(template_file, inps):
"""Read input template options into Namespace inps"""
if not template_file:
return inps, None
print('read options from template file: '+os.path.basename(template_file))
template = readfile.read_template(template_file)
# Coherence-based network modification
prefix = 'mintpy.save.hdfEos5.'
key = prefix+'update'
if key in template.keys() and template[key] == 'yes':
inps.update = True
key = prefix+'subset'
if key in template.keys() and template[key] == 'yes':
inps.subset = True
return inps, template
################################################################
def prep_metadata(ts_file, geom_file, template=None, print_msg=True):
"""Prepare metadata for HDF-EOS5 file."""
# read metadata from ts_file
ts_obj = timeseries(ts_file)
ts_obj.open(print_msg=False)
meta = dict(ts_obj.metadata)
# read metadata from template_file
if template:
for key, value in template.items():
if not key.startswith(('mintpy', 'isce')):
meta[key] = value
# grab unavco metadata
unavco_meta = metadata_mintpy2unavco(meta, ts_obj.dateList, geom_file)
if print_msg:
print('## UNAVCO Metadata:')
print('-----------------------------------------')
info.print_attributes(unavco_meta)
print('-----------------------------------------')
# update metadata from unavco metadata
meta.update(unavco_meta)
meta['FILE_TYPE'] = 'HDFEOS'
return meta
def metadata_mintpy2unavco(meta_in, dateList, geom_file):
"""Convert metadata from mintpy format into unavco format."""
# Extract UNAVCO format metadata from MintPy attributes dictionary and dateList
meta = {}
for key in meta_in.keys():
meta[key] = meta_in[key]
for prefix in ['unavco.', 'hdfeos5.']:
if prefix in key.lower():
key2 = key.lower().split(prefix)[1]
meta[key2] = meta_in[key]
unavco_meta = dict()
#################################
# Required metadata
#################################
# Given manually
# mission
# ERS,ENV,S1,RS1,RS2,CSK,TSX,JERS,ALOS,ALOS2
try:
unavco_meta['mission'] = sensor.get_unavco_mission_name(meta)
except ValueError:
print('Missing required attribute: mission')
# beam_mode/swath
unavco_meta['beam_mode'] = meta['beam_mode']
unavco_meta['beam_swath'] = int(meta.get('beam_swath', '0'))
# relative_orbit, or track number
unavco_meta['relative_orbit'] = int(meta['relative_orbit'])
# processing info
unavco_meta['processing_type'] = 'LOS_TIMESERIES'
unavco_meta['processing_software'] = meta.get('PROCESSOR', 'isce')
# Grabbed by script
# date info
unavco_meta['first_date'] = dt.datetime.strptime(dateList[0], '%Y%m%d').isoformat()[0:10]
unavco_meta['last_date'] = dt.datetime.strptime(dateList[-1], '%Y%m%d').isoformat()[0:10]
# footprint
lons = [meta['LON_REF1'],
meta['LON_REF3'],
meta['LON_REF4'],
meta['LON_REF2'],
meta['LON_REF1']]
lats = [meta['LAT_REF1'],
meta['LAT_REF3'],
meta['LAT_REF4'],
meta['LAT_REF2'],
meta['LAT_REF1']]
unavco_meta['scene_footprint'] = "POLYGON((" + ",".join(
[lon+' '+lat for lon, lat in zip(lons, lats)]) + "))"
unavco_meta['history'] = dt.datetime.utcnow().isoformat()[0:10]
#################################
# Recommended metadata
#################################
unavco_meta['first_frame'] = int(meta.get('first_frame', 0))
unavco_meta['last_frame'] = int(meta.get('last_frame', unavco_meta['first_frame']))
unavco_meta['atmos_correct_method'] = meta.get('atmos_correct_method', 'None')
unavco_meta['post_processing_method'] = 'MintPy'
unavco_meta['processing_dem'] = meta.get('processing_dem', 'Unknown')
unavco_meta['unwrap_method'] = meta.get('unwrap_method', 'Unknown')
# Grabbed by script
unavco_meta['flight_direction'] = meta.get('ORBIT_DIRECTION', 'Unknown')[0].upper()
if meta['ANTENNA_SIDE'] == '-1':
unavco_meta['look_direction'] = 'R'
else:
unavco_meta['look_direction'] = 'L'
unavco_meta['polarization'] = meta.get('POLARIZATION', 'Unknown')
unavco_meta['prf'] = float(meta.get('PRF', '0'))
unavco_meta['wavelength'] = float(meta['WAVELENGTH'])
#################################
# insarmaps metadata
#################################
# footprint for actual data coverage in lat/lon bounding box.
if 'Y_FIRST' in meta.keys():
# time-series in geo-coordinates
N = float(meta['Y_FIRST'])
W = float(meta['X_FIRST'])
S = N + float(meta['Y_STEP']) * int(meta['LENGTH'])
E = W + float(meta['X_STEP']) * int(meta['WIDTH'])
unavco_meta['data_footprint'] = ut.snwe_to_wkt_polygon([S, N, W, E])
else:
# time-series in radar-coordinates
geom_meta = readfile.read_attribute(geom_file)
geom_dset_list = readfile.get_dataset_list(geom_file)
# potential extra geometry file (for roipac/gamma)
geo_geom_file = os.path.join(os.path.dirname(geom_file), 'geometryGeo.h5')
if 'Y_FIRST' not in geom_meta.keys() and 'latitude' in geom_dset_list:
# geometry in radar-coodinates (isce/doris)
lat_data = readfile.read(geom_file, datasetName='latitude')[0]
lon_data = readfile.read(geom_file, datasetName='longitude')[0]
# set pixels with invalid value or zero to nan
lat_data[np.abs(lat_data) == 90] = np.nan
lat_data[lat_data == 0] = np.nan
lon_data[lon_data == 0] = np.nan
S, N = np.nanmin(lat_data), np.nanmax(lat_data)
W, E = np.nanmin(lon_data), np.nanmax(lon_data)
unavco_meta['data_footprint'] = ut.snwe_to_wkt_polygon([S, N, W, E])
elif os.path.isfile(geo_geom_file):
# geometry in geo-coordinates (roipac/gamma)
geom_meta = readfile.read_attribute(geo_geom_file)
N = float(geom_meta['Y_FIRST'])
W = float(geom_meta['X_FIRST'])
S = N + float(geom_meta['Y_STEP']) * int(geom_meta['LENGTH'])
E = W + float(geom_meta['X_STEP']) * int(geom_meta['WIDTH'])
unavco_meta['data_footprint'] = ut.snwe_to_wkt_polygon([S, N, W, E])
else:
msg = 'WARNING: "data_footprint" is NOT assigned, '
msg += 'due to the lack of X/Y_FIRST attributes and latitude/longitde datasets.'
print(msg)
return unavco_meta
def get_output_filename(metadata, suffix=None, update_mode=False, subset_mode=False):
"""Get output file name of HDF-EOS5 time-series file."""
SAT = metadata['mission']
SW = metadata['beam_mode']
if metadata['beam_swath']:
SW += str(metadata['beam_swath'])
RELORB = "{:03d}".format(int(metadata['relative_orbit']))
# First and/or Last Frame
frame1 = metadata['first_frame']
frame2 = metadata['last_frame']
FRAME = f"{int(frame1):04d}"
if frame2 != frame1:
FRAME += f"_{frame2:04d}"
DATE1 = dt.datetime.strptime(metadata['first_date'], '%Y-%m-%d').strftime('%Y%m%d')
DATE2 = dt.datetime.strptime(metadata['last_date'], '%Y-%m-%d').strftime('%Y%m%d')
if update_mode:
print('Update mode is ON, put endDate as XXXXXXXX.')
DATE2 = 'XXXXXXXX'
if suffix:
outName = f'{SAT}_{SW}_{RELORB}_{FRAME}_{DATE1}_{DATE2}_{suffix}.he5'
else:
outName = f'{SAT}_{SW}_{RELORB}_{FRAME}_{DATE1}_{DATE2}.he5'
if subset_mode:
print('Subset mode is enabled, put subset range info in output filename.')
lat1 = float(metadata['Y_FIRST'])
lon0 = float(metadata['X_FIRST'])
lat0 = lat1 + float(metadata['Y_STEP']) * int(metadata['LENGTH'])
lon1 = lon0 + float(metadata['X_STEP']) * int(metadata['WIDTH'])
lat0Str = f'N{round(lat0*1e3):05d}'
lat1Str = f'N{round(lat1*1e3):05d}'
lon0Str = f'E{round(lon0*1e3):06d}'
lon1Str = f'E{round(lon1*1e3):06d}'
if lat0 < 0.0: lat0Str = f'S{round(abs(lat0)*1e3):05d}'
if lat1 < 0.0: lat1Str = f'S{round(abs(lat1)*1e3):05d}'
if lon0 < 0.0: lon0Str = f'W{round(abs(lon0)*1e3):06d}'
if lon1 < 0.0: lon1Str = f'W{round(abs(lon1)*1e3):06d}'
SUB = f'_{lat0Str}_{lat1Str}_{lon0Str}_{lon1Str}'
fbase, fext = os.path.splitext(outName)
outName = f'{fbase}{SUB}{fext}'
return outName
def create_hdf5_dataset(group, dsName, data, max_digit=55, compression=COMPRESSION):
"""Create HDF5 dataset and print out message."""
msg = 'create dataset {d:<{w}}'.format(d=f'{group.name}/{dsName}', w=max_digit)
msg += f' of {str(data.dtype):<10} in size of {data.shape} with compression={compression}'
print(msg)
if data.ndim == 1:
dset = group.create_dataset(
dsName,
data=data,
compression=compression,
)
elif data.ndim == 2:
dset = group.create_dataset(
dsName,
data=data,
chunks=True,
compression=compression,
)
return dset
def write_hdf5_file(metadata, out_file, ts_file, tcoh_file, scoh_file, mask_file, geom_file):
"""Write HDF5 file in HDF-EOS5 format."""
ts_obj = timeseries(ts_file)
ts_obj.open(print_msg=False)
dateList = ts_obj.dateList
numDate = len(dateList)
# Open HDF5 File
print(f'create HDF5 file: {out_file} with w mode')
max_digit = 55
with h5py.File(out_file, 'w') as f:
##### Group - Observation
gName = 'HDFEOS/GRIDS/timeseries/observation'
print(f'create group /{gName}')
group = f.create_group(gName)
## O1 - displacement
dsName = 'displacement'
dsShape = (numDate, ts_obj.length, ts_obj.width)
dsDataType = np.float32
msg = 'create dataset /{d:<{w}}'.format(d=f'{gName}/{dsName}', w=max_digit)
msg += f' of {"float32":<10} in size of {dsShape} with compression={COMPRESSION}'
print(msg)
dset = group.create_dataset(
dsName,
shape=dsShape,
maxshape=(None, dsShape[1], dsShape[2]),
dtype=dsDataType,
chunks=True,
compression=COMPRESSION,
)
print('write data acquition by acquition ...')
prog_bar = ptime.progressBar(maxValue=numDate)
for i in range(numDate):
dset[i, :, :] = readfile.read(ts_file, datasetName=dateList[i])[0]
prog_bar.update(i+1, suffix=f'{i+1}/{numDate} {dateList[i]}')
prog_bar.close()
# attributes
dset.attrs['Title'] = dsName
dset.attrs['MissingValue'] = FLOAT_ZERO
dset.attrs['_FillValue'] = FLOAT_ZERO
dset.attrs['Units'] = 'meters'
## O2 - date
dsName = 'date'
data = np.array(dateList, dtype=np.string_)
dset = create_hdf5_dataset(group, dsName, data)
## O3 - perp baseline
dsName = 'bperp'
data = np.array(ts_obj.pbase, dtype=np.float32)
dset = create_hdf5_dataset(group, dsName, data)
##### Group - Quality
gName = 'HDFEOS/GRIDS/timeseries/quality'
print(f'create group /{gName}')
group = f.create_group(gName)
## Q1 - temporalCoherence
dsName = 'temporalCoherence'
# read
data = readfile.read(tcoh_file)[0]
# write
dset = create_hdf5_dataset(group, dsName, data)
# attributes
dset.attrs['Title'] = dsName
dset.attrs['MissingValue'] = FLOAT_ZERO
dset.attrs['_FillValue'] = FLOAT_ZERO
dset.attrs['Units'] = '1'
## Q2 - avgSpatialCoherence
dsName = 'avgSpatialCoherence'
# read
data = readfile.read(scoh_file)[0]
# write
dset = create_hdf5_dataset(group, dsName, data)
# attributes
dset.attrs['Title'] = dsName
dset.attrs['MissingValue'] = FLOAT_ZERO
dset.attrs['_FillValue'] = FLOAT_ZERO
dset.attrs['Units'] = '1'
## Q3 - mask
dsName = 'mask'
# read
data = readfile.read(mask_file, datasetName='mask')[0]
# write
dset = create_hdf5_dataset(group, dsName, data)
# attributes
dset.attrs['Title'] = dsName
dset.attrs['MissingValue'] = BOOL_ZERO
dset.attrs['_FillValue'] = BOOL_ZERO
dset.attrs['Units'] = '1'
##### Group - Write Geometry
# Required: height, incidenceAngle
# Optional: rangeCoord, azimuthCoord, azimuthAngle, slantRangeDistance,
# waterMask, shadowMask
gName = 'HDFEOS/GRIDS/timeseries/geometry'
print(f'create group /{gName}')
group = f.create_group(gName)
geom_obj = geometry(geom_file)
geom_obj.open(print_msg=False)
# add latitude/longitude if missing, e.g. ARIA/HyP3
dsNames = geom_obj.datasetNames + ['latitude', 'longitude']
dsNames = list(set(dsNames))
for dsName in dsNames:
# read
if dsName in geom_obj.datasetNames:
data = geom_obj.read(datasetName=dsName, print_msg=False)
elif dsName == 'latitude':
data = ut.get_lat_lon(metadata, dimension=2)[0]
elif dsName == 'longitude':
data = ut.get_lat_lon(metadata, dimension=2)[1]
else:
raise ValueError(f'Un-recognized dataset name: {dsName}!')
# write
dset = create_hdf5_dataset(group, dsName, data)
# attributes
dset.attrs['Title'] = dsName
if dsName in ['height', 'slantRangeDistance', 'bperp']:
dset.attrs['MissingValue'] = FLOAT_ZERO
dset.attrs['_FillValue'] = FLOAT_ZERO
dset.attrs['Units'] = 'meters'
elif dsName in ['incidenceAngle', 'azimuthAngle', 'latitude', 'longitude']:
dset.attrs['MissingValue'] = FLOAT_ZERO
dset.attrs['_FillValue'] = FLOAT_ZERO
dset.attrs['Units'] = 'degrees'
elif dsName in ['rangeCoord', 'azimuthCoord']:
dset.attrs['MissingValue'] = FLOAT_ZERO
dset.attrs['_FillValue'] = FLOAT_ZERO
dset.attrs['Units'] = '1'
elif dsName in ['waterMask', 'shadowMask']:
dset.attrs['MissingValue'] = BOOL_ZERO
dset.attrs['_FillValue'] = BOOL_ZERO
dset.attrs['Units'] = '1'
# Write Attributes to the HDF File
print('write metadata to root level')
for key, value in iter(metadata.items()):
f.attrs[key] = value
print(f'finished writing to {out_file}')
return out_file
################################################################
def save_hdfeos5(inps):
inps, template = read_template2inps(inps.template_file, inps)
# prepare metadata
meta = prep_metadata(
ts_file=inps.ts_file,
geom_file=inps.geom_file,
template=template,
print_msg=True)
# get output filename
out_file = get_output_filename(
metadata=meta,
suffix=inps.suffix,
update_mode=inps.update,
subset_mode=inps.subset)
# write HDF5 File
write_hdf5_file(
metadata=meta,
out_file=out_file,
ts_file=inps.ts_file,
tcoh_file=inps.tcoh_file,
scoh_file=inps.scoh_file,
mask_file=inps.mask_file,
geom_file=inps.geom_file)
return