def test_parse_gamma_dem_header(self):
path = join(GAMMA_TEST_DIR, 'dem16x20raw.dem.par')
hdrs = gamma.parse_dem_header(path)
self.assertEqual(hdrs[ifc.PYRATE_NCOLS], 16)
self.assertEqual(hdrs[ifc.PYRATE_NROWS], 20)
self.assertEqual(hdrs[ifc.PYRATE_LAT], -33.3831945)
self.assertEqual(hdrs[ifc.PYRATE_LONG], 150.3870833)
self.assertEqual(hdrs[ifc.PYRATE_X_STEP], 6.9444445e-05)
self.assertEqual(hdrs[ifc.PYRATE_Y_STEP], -6.9444445e-05)
def setUpClass(cls):
# create common combined header obj so the headers are only read once
# tricker: needs both ifg headers, and DEM one for the extents
filenames = ['r20090713_VV.slc.par', 'r20090817_VV.slc.par']
hdr_paths = [join(GAMMA_TEST_DIR, f) for f in filenames]
hdrs = [gamma.parse_epoch_header(p) for p in hdr_paths]
dem_hdr_path = join(GAMMA_TEST_DIR, 'dem16x20raw.dem.par')
cls.DEM_HDR = gamma.parse_dem_header(dem_hdr_path)
cls.COMBINED = gamma.combine_headers(*hdrs, dem_hdr=cls.DEM_HDR)
def test_to_geotiff_dem(self):
hdr_path = join(GAMMA_TEST_DIR, 'dem16x20raw.dem.par')
hdr = gamma.parse_dem_header(hdr_path)
data_path = join(GAMMA_TEST_DIR, 'dem16x20raw.dem')
self.dest = os.path.join(TEMPDIR, "tmp_gamma_dem.tif")
write_geotiff(hdr, data_path, self.dest, nodata=0)
exp_path = join(GAMMA_TEST_DIR, 'dem16x20_subset_from_gamma.tif')
exp_ds = gdal.Open(exp_path)
ds = gdal.Open(self.dest)
# compare data and geographic headers
# HACK: round expected to nearest integer
assert_array_almost_equal(np.rint(exp_ds.ReadAsArray()),
ds.ReadAsArray())
self.compare_rasters(exp_ds, ds)
md = ds.GetMetadata()
self.assertTrue(md['AREA_OR_POINT'] == 'Area')
def read_dem(params):
dem_file = params[cf.DEM_FILE]
geotif_dem = os.path.join(
params[cf.OUT_DIR],
os.path.basename(dem_file).split('.')[0] + '.tif')
mlooked_dem = prepifg.mlooked_path(geotif_dem,
looks=params[cf.IFG_LKSX],
crop_out=params[cf.IFG_CROP_OPT])
# make sure mlooked dem exist
if not os.path.exists(mlooked_dem):
raise prepifg.PreprocessError('mlooked dem was not found.'
'Please run prepifg.')
dem_header = gamma.parse_dem_header(params[cf.DEM_HEADER_FILE])
lat, lon, nx, ny = return_pyaps_lat_lon(dem_header)
ds = gdal.Open(mlooked_dem, gdalconst.GA_ReadOnly)
dem = ds.ReadAsArray()
ds = None
return lat, lon, nx, ny, dem, mlooked_dem
def geo_correction_original(date_pair, params, incidence_angle_or_map):
dem_file = params[cf.DEM_FILE]
geotif_dem = os.path.join(
params[cf.OUT_DIR],
os.path.basename(dem_file).split('.')[0] + '.tif')
mlooked_dem = prepifg.mlooked_path(geotif_dem,
looks=params[cf.IFG_LKSX],
crop_out=params[cf.IFG_CROP_OPT])
# make sure mlooked dem exist
if not os.path.exists(mlooked_dem):
raise prepifg.PreprocessError('mlooked dem was not found.'
'Please run prepifg.')
dem_header = gamma.parse_dem_header(params[cf.DEM_HEADER_FILE])
lat, lon, nx, ny = return_pyaps_lat_lon(dem_header)
""" using geo coordinates to remove APS """
aps1 = pa.PyAPS_geo(os.path.join(ECMWF_DIR,
ECMWF_PRE + date_pair[0] + ECMWF_EXT),
mlooked_dem,
grib=ECMWF,
verb=True,
demfmt=GEOTIFF,
demtype=np.float32,
dem_header=(lon, lat, nx, ny))
aps2 = pa.PyAPS_geo(os.path.join(ECMWF_DIR,
ECMWF_PRE + date_pair[1] + ECMWF_EXT),
mlooked_dem,
grib=ECMWF,
verb=True,
demfmt=GEOTIFF,
demtype=np.float32,
dem_header=(lon, lat, nx, ny))
phs1 = np.zeros((aps1.ny, aps1.nx))
phs2 = np.zeros((aps2.ny, aps2.nx))
print('Without Lat Lon files')
aps1.getdelay(phs1, inc=incidence_angle_or_map)
aps2.getdelay(phs2, inc=incidence_angle_or_map)
aps_delay = phs2 - phs1 # delay in meters as we don't provide wavelength
return aps_delay
def test_unw_contains_same_data_as_numpy_array(self):
from datetime import time
temp_unw = tempfile.mktemp(suffix='.unw')
temp_tif = tempfile.mktemp(suffix='.tif')
# setup some header files for use in write_geotif
dem_header_file = common.SML_TEST_DEM_HDR_GAMMA
dem_header = gamma.parse_dem_header(dem_header_file)
header = gamma.parse_epoch_header(
os.path.join(common.SML_TEST_GAMMA, '20060828_slc.par'))
header.update(dem_header)
# insert some dummy data so we are the dem in write_geotiff is not
# not activated and ifg write_geotiff operation works
header[ifc.PYRATE_TIME_SPAN] = 0
header[ifc.SLAVE_DATE] = 0
header[ifc.DATA_UNITS] = 'degrees'
header[ifc.DATA_TYPE] = ifc.ORIG
header[ifc.SLAVE_TIME] = time(10)
# now create aritrary data
data = np.random.rand(dem_header[ifc.PYRATE_NROWS],
dem_header[ifc.PYRATE_NCOLS])
# convert numpy array to .unw
shared.write_unw_from_data_or_geotiff(geotif_or_data=data,
dest_unw=temp_unw,
ifg_proc=1)
# convert the .unw to geotif
shared.write_geotiff(header=header,
data_path=temp_unw,
dest=temp_tif,
nodata=np.nan)
# now compare geotiff with original numpy array
ds = gdal.Open(temp_tif, gdal.GA_ReadOnly)
data_lv_theta = ds.ReadAsArray()
ds = None
np.testing.assert_array_almost_equal(data, data_lv_theta)
os.remove(temp_tif)
os.remove(temp_unw)
def setUp(self):
self.err = gamma.GammaException
dem_hdr_path = join(GAMMA_TEST_DIR, 'dem16x20raw.dem.par')
self.dh = gamma.parse_dem_header(dem_hdr_path)
