def gen_color_file(input_file):
fp, temp_file = tempfile.mkstemp(suffix='.txt')
dem = DEM(input_file)
dem.open()
phase_data = dem.height_band.ReadAsArray()
max_ph = np.nanmax(phase_data)
min_ph = np.nanmin(phase_data)
range_ph = max_ph-min_ph
colors = ['black', 'blue', 'yellow', 'orange', 'red', 'white']
with open(temp_file, 'w') as f:
for i, c in enumerate(colors[:-1]):
f.write(str(int(min_ph + (i + 1)*range_ph/len(colors))) +
' ' + c + '\n')
f.write(str(int(max_ph - range_ph/len(colors))) +
' ' + colors[-1] + '\n')
os.close(fp)
return temp_file
def dem_or_ifg(data_path):
"""
Whether tif is a dem or an interferogram
:param: data_path: xxxxx
:return xxxx
"""
ds = gdal.Open(data_path)
md = ds.GetMetadata()
if 'DATE' in md: # ifg
return Ifg(data_path)
else:
return DEM(data_path)
def dem_or_ifg(data_path):
"""
Returns an Ifg or DEM class object from input geotiff file.
:param str data_path: file path name
:return: Interferogram or DEM object from input file
:rtype: Ifg or DEM class object
"""
ds = gdal.Open(data_path)
md = ds.GetMetadata()
if 'DATE' in md: # ifg
return Ifg(data_path)
else:
return DEM(data_path)
def parse(self, string):
"""
override of :py:meth:`DictParam.parse`.
"""
dct = super(RasterParam, self).parse(string)
raster_type = dct['type']
path = dct['path']
if raster_type == 'DEM':
return DEM(path)
elif raster_type == 'Ifg':
return Ifg(path)
elif raster_type == 'Incidence':
return Incidence(path)
else: # pragma: no cover
raise luigi.parameter.UnknownParameterException(
'rasterBase must be an inscance DEM, '
'Ifg or Incidence is valid')
def test_output_datatype(self):
"""Test resampling method using a scaling factor of 4"""
scale = 4 # assumes square cells
self.ifgs.append(DEM(SML_TEST_DEM_TIF))
self.ifg_paths = [i.data_path for i in self.ifgs] + [SML_TEST_DEM_TIF]
cext = self._custom_extents_tuple()
xlooks = ylooks = scale
prepare_ifgs(self.ifg_paths,
CUSTOM_CROP,
xlooks,
ylooks,
thresh=1.0,
user_exts=cext)
for i in self.ifg_paths:
mlooked_ifg = mlooked_path(i, xlooks, CUSTOM_CROP)
ds1 = DEM(mlooked_ifg)
ds1.open()
ds2 = DEM(i)
ds2.open()
self.assertEqual(
ds1.dataset.GetRasterBand(1).DataType,
ds2.dataset.GetRasterBand(1).DataType)
ds1 = ds2 = None
class DEMTests(unittest.TestCase):
'Unit tests to verify operations on GeoTIFF format DEMs'
def setUp(self):
self.ras = DEM(SML_TEST_DEM_TIF)
def test_create_raster(self):
# validate header path
self.assertTrue(os.path.exists(self.ras.data_path))
def test_headers_as_attr(self):
self.ras.open()
attrs = ['ncols', 'nrows', 'x_first', 'x_step', 'y_first', 'y_step' ]
# TODO: are 'projection' and 'datum' attrs needed?
for a in attrs:
self.assertTrue(getattr(self.ras, a) is not None)
def test_is_dem(self):
self.ras = DEM(join(SML_TEST_TIF, 'geo_060619-061002_unw.tif'))
self.assertFalse(hasattr(self.ras, 'datum'))
def test_open(self):
self.assertTrue(self.ras.dataset is None)
self.ras.open()
self.assertTrue(self.ras.dataset is not None)
self.assertTrue(isinstance(self.ras.dataset, Dataset))
# ensure open cannot be called twice
self.assertRaises(RasterException, self.ras.open)
def test_band(self):
# test accessing bands with open and unopened datasets
try:
_ = self.ras.height_band
self.fail("Should not be able to access band without open dataset")
except RasterException:
pass
self.ras.open()
data = self.ras.height_band.ReadAsArray()
self.assertEqual(data.shape, (72, 47))
def test_is_dem(self):
self.ras = DEM(join(SML_TEST_TIF, 'geo_060619-061002_unw.tif'))
self.assertFalse(hasattr(self.ras, 'datum'))
def setUp(self):
self.ras = DEM(SML_TEST_DEM_TIF)
def test_multilook(self):
"""Test resampling method using a scaling factor of 4"""
scale = 4 # assumes square cells
self.ifgs.append(DEM(SML_TEST_DEM_TIF))
self.ifg_paths = [i.data_path for i in self.ifgs]
cext = self._custom_extents_tuple()
xlooks = ylooks = scale
prepare_ifgs(self.ifg_paths,
CUSTOM_CROP,
xlooks,
ylooks,
thresh=1.0,
user_exts=cext)
for n, ipath in enumerate([self.exp_files[3], self.exp_files[7]]):
i = Ifg(ipath)
i.open()
self.assertEqual(i.dataset.RasterXSize, 20 / scale)
self.assertEqual(i.dataset.RasterYSize, 28 / scale)
# verify resampling
path = join(PREP_TEST_TIF, "%s.tif" % n)
ds = gdal.Open(path)
src_data = ds.GetRasterBand(2).ReadAsArray()
exp_resample = multilooking(src_data, scale, scale, thresh=0)
self.assertEqual(exp_resample.shape, (7, 5))
assert_array_almost_equal(exp_resample, i.phase_band.ReadAsArray())
ds = None
i.close()
os.remove(ipath)
# verify DEM has been correctly processed
# ignore output values as resampling has already been tested for phase
exp_dem_path = join(SML_TEST_DEM_DIR,
'roipac_test_trimmed_4rlks_3cr.tif')
self.assertTrue(exists(exp_dem_path))
orignal_dem = DEM(SML_TEST_DEM_TIF)
orignal_dem.open()
dem_dtype = orignal_dem.dataset.GetRasterBand(1).DataType
orignal_dem.close()
dem = DEM(exp_dem_path)
dem.open()
# test multilooked dem is of the same datatype as the original dem tif
self.assertEqual(dem_dtype, dem.dataset.GetRasterBand(1).DataType)
self.assertEqual(dem.dataset.RasterXSize, 20 / scale)
self.assertEqual(dem.dataset.RasterYSize, 28 / scale)
data = dem.height_band.ReadAsArray()
self.assertTrue(data.ptp() != 0)
# close ifgs
dem.close()
for i in self.ifgs:
i.close()
os.remove(exp_dem_path)
