Skip to content

GitLab

P
py_tools_ds
Commit 0f073660 authored by Daniel Scheffler's avatar Daniel Scheffler
Browse files
Options

Merge branch 'bugfix/fix_bilinear_sensorgeo_gauss_3D_trafo' into 'master' 

Fixed issue where SensorMapGeometryTransformer raised an exception when trying...

See merge request !14
parents 4c725e9c 31ac77d7
Pipeline #5071 failed with stages
        in 42 minutes and 8 seconds
        Hide whitespace changes
        Inline Side-by-side
        Showing with 98 additions and 76 deletions
        py_tools_ds/geo/raster/reproject.py
        View file @ 0f073660
        ......@@ -585,6 +585,11 @@ class SensorMapGeometryTransformer(object):
        self.lats = lats
        self.lons = lons
        self.swath_definition = SwathDefinition(lons=lons, lats=lats)
        # use a projection string for local coordinates (https://gis.stackexchange.com/a/300407)
        # -> this is needed for bilinear resampling
        self.swath_definition.proj_str = '+proj=omerc +lat_0=51.6959777875 +lonc=7.0923165808 +alpha=-20.145 ' \
        '+gamma=0 +k=1 +x_0=50692.579 +y_0=81723.458 +ellps=WGS84 ' \
        '+towgs84=0,0,0,0,0,0,0 +units=m +no_defs'
        self.area_extent_ll = [np.min(lons), np.min(lats), np.max(lons), np.max(lats)]
        self.area_definition = None # type: AreaDefinition
        ......@@ -733,6 +738,15 @@ class SensorMapGeometryTransformer(object):
        elif self.resamp_alg == 'gauss':
        opts = {k: v for k, v in self.opts.items()}
        # ensure that sigmas are provided as list if data is 3-dimensional
        if data.ndim != 2:
        if not isinstance(opts['sigmas'], list):
        opts['sigmas'] = [opts['sigmas']] * data.ndim
        if not len(opts['sigmas']) == data.ndim:
        raise ValueError("The 'sigmas' parameter must have the same number of values like data.ndim."
        "n_sigmas: %d; data.ndim: %d" % (len(opts['sigmas']), data.ndim))
        result = resample_gauss(source_geo_def, data, target_geo_def, **opts)
        elif self.resamp_alg == 'custom':
        ......
        py_tools_ds/version.py
        View file @ 0f073660
        ......@@ -19,5 +19,5 @@
        # You should have received a copy of the GNU Lesser General Public License along
        # with this program. If not, see <http://www.gnu.org/licenses/>.
        __version__ = '0.14.22'
        __versionalias__ = '20191016_01'
        __version__ = '0.14.23'
        __versionalias__ = '20191017_01'
        tests/test_geo/test_raster/test_reproject.py
        View file @ 0f073660
        ......@@ -41,6 +41,7 @@ from py_tools_ds.geo.raster.reproject import SensorMapGeometryTransformer, Senso
        tests_path = os.path.abspath(os.path.join(__path__[0], "..", "tests"))
        rsp_algs = ['nearest', 'bilinear', 'gauss']
        class Test_SensorMapGeometryTransformer(TestCase):
        ......@@ -65,61 +66,66 @@ class Test_SensorMapGeometryTransformer(TestCase):
        5267203.56579] # UR_y
        def test_to_sensor_geometry(self):
        SMGT = SensorMapGeometryTransformer(lons=self.lons,
        lats=self.lats,
        resamp_alg='nearest')
        dem_sensors_geo = SMGT.to_sensor_geometry(self.dem_map_geo,
        src_prj=32632, src_extent=self.dem_area_extent_coarse_subset_utm)
        self.assertIsInstance(dem_sensors_geo, np.ndarray)
        self.assertFalse(np.array_equal(np.unique(dem_sensors_geo), np.array([0])))
        self.assertEquals(dem_sensors_geo.shape, (150, 1000))
        for rsp_alg in rsp_algs:
        SMGT = SensorMapGeometryTransformer(lons=self.lons,
        lats=self.lats,
        resamp_alg=rsp_alg,
        radius_of_influence=30 if rsp_alg != 'bilinear' else 45)
        dem_sensors_geo = SMGT.to_sensor_geometry(self.dem_map_geo,
        src_prj=32632, src_extent=self.dem_area_extent_coarse_subset_utm)
        self.assertIsInstance(dem_sensors_geo, np.ndarray)
        self.assertFalse(np.array_equal(np.unique(dem_sensors_geo), np.array([0])))
        self.assertEquals(dem_sensors_geo.shape, (150, 1000))
        def test_to_sensor_geometry_3DInput(self):
        SMGT = SensorMapGeometryTransformer(lons=self.lons,
        lats=self.lats,
        resamp_alg='nearest')
        dem_sensors_geo = SMGT.to_sensor_geometry(np.dstack([self.dem_map_geo] * 2),
        src_prj=32632, src_extent=self.dem_area_extent_coarse_subset_utm)
        self.assertIsInstance(dem_sensors_geo, np.ndarray)
        self.assertFalse(np.array_equal(np.unique(dem_sensors_geo), np.array([0])))
        self.assertEquals(dem_sensors_geo.shape, (150, 1000, 2))
        self.assertTrue(np.array_equal(dem_sensors_geo[:, :, 0], dem_sensors_geo[:, :, 1]))
        for rsp_alg in rsp_algs:
        SMGT = SensorMapGeometryTransformer(lons=self.lons,
        lats=self.lats,
        resamp_alg=rsp_alg)
        dem_sensors_geo = SMGT.to_sensor_geometry(np.dstack([self.dem_map_geo] * 2),
        src_prj=32632, src_extent=self.dem_area_extent_coarse_subset_utm)
        self.assertIsInstance(dem_sensors_geo, np.ndarray)
        self.assertFalse(np.array_equal(np.unique(dem_sensors_geo), np.array([0])))
        self.assertEquals(dem_sensors_geo.shape, (150, 1000, 2))
        self.assertTrue(np.array_equal(dem_sensors_geo[:, :, 0], dem_sensors_geo[:, :, 1]))
        def test_to_map_geometry_lonlat(self):
        SMGT = SensorMapGeometryTransformer(lons=self.lons,
        lats=self.lats,
        resamp_alg='nearest')
        # to Lon/Lat
        dem_map_geo, dem_gt, dem_prj = SMGT.to_map_geometry(self.dem_sensor_geo, tgt_prj=4326)
        self.assertIsInstance(dem_map_geo, np.ndarray)
        self.assertEquals(dem_map_geo.shape, (SMGT.area_definition.height,
        SMGT.area_definition.width))
        xmin, xmax, ymin, ymax = corner_coord_to_minmax(get_corner_coordinates(gt=dem_gt,
        cols=dem_map_geo.shape[1],
        rows=dem_map_geo.shape[0]))
        self.assertTrue(False not in np.isclose(np.array([xmin, ymin, xmax, ymax]),
        np.array(self.expected_dem_area_extent_lonlat)))
        self.assertFalse(np.array_equal(np.unique(dem_map_geo), np.array([0])))
        with self.assertRaises(ValueError):
        SMGT.to_map_geometry(self.dem_sensor_geo[:10, :10], tgt_prj=4326) # must have the shape of lons/lats
        for rsp_alg in rsp_algs:
        SMGT = SensorMapGeometryTransformer(lons=self.lons,
        lats=self.lats,
        resamp_alg=rsp_alg)
        # to Lon/Lat
        dem_map_geo, dem_gt, dem_prj = SMGT.to_map_geometry(self.dem_sensor_geo, tgt_prj=4326)
        self.assertIsInstance(dem_map_geo, np.ndarray)
        self.assertEquals(dem_map_geo.shape, (SMGT.area_definition.height,
        SMGT.area_definition.width))
        xmin, xmax, ymin, ymax = corner_coord_to_minmax(get_corner_coordinates(gt=dem_gt,
        cols=dem_map_geo.shape[1],
        rows=dem_map_geo.shape[0]))
        self.assertTrue(False not in np.isclose(np.array([xmin, ymin, xmax, ymax]),
        np.array(self.expected_dem_area_extent_lonlat)))
        self.assertFalse(np.array_equal(np.unique(dem_map_geo), np.array([0])))
        with self.assertRaises(ValueError):
        SMGT.to_map_geometry(self.dem_sensor_geo[:10, :10], tgt_prj=4326) # must have the shape of lons/lats
        def test_to_map_geometry_utm(self):
        SMGT = SensorMapGeometryTransformer(lons=self.lons,
        lats=self.lats,
        resamp_alg='nearest')
        # to UTM32
        dem_map_geo, dem_gt, dem_prj = SMGT.to_map_geometry(self.dem_sensor_geo, tgt_prj=32632, tgt_res=(30, 30))
        self.assertIsInstance(dem_map_geo, np.ndarray)
        self.assertEquals(dem_map_geo.shape, (365, 975))
        xmin, xmax, ymin, ymax = corner_coord_to_minmax(get_corner_coordinates(gt=dem_gt,
        cols=dem_map_geo.shape[1],
        rows=dem_map_geo.shape[0]))
        self.assertTrue(False not in np.isclose(np.array([xmin, ymin, xmax, ymax]),
        np.array(self.expected_dem_area_extent_utm)))
        self.assertFalse(np.array_equal(np.unique(dem_map_geo), np.array([0])))
        for rsp_alg in rsp_algs:
        SMGT = SensorMapGeometryTransformer(lons=self.lons,
        lats=self.lats,
        resamp_alg=rsp_alg)
        # to UTM32
        dem_map_geo, dem_gt, dem_prj = SMGT.to_map_geometry(self.dem_sensor_geo, tgt_prj=32632, tgt_res=(30, 30))
        self.assertIsInstance(dem_map_geo, np.ndarray)
        self.assertEquals(dem_map_geo.shape, (365, 975))
        xmin, xmax, ymin, ymax = corner_coord_to_minmax(get_corner_coordinates(gt=dem_gt,
        cols=dem_map_geo.shape[1],
        rows=dem_map_geo.shape[0]))
        self.assertTrue(False not in np.isclose(np.array([xmin, ymin, xmax, ymax]),
        np.array(self.expected_dem_area_extent_utm)))
        self.assertFalse(np.array_equal(np.unique(dem_map_geo), np.array([0])))
        class Test_SensorMapGeometryTransformer3D(TestCase):
        ......@@ -150,30 +156,32 @@ class Test_SensorMapGeometryTransformer3D(TestCase):
        5267203.56579] # UR_y
        def test_to_map_geometry_lonlat_3D_geolayer(self):
        SMGT = SensorMapGeometryTransformer3D(lons=self.lons_3D,
        lats=self.lats_3D,
        # resamp_alg='nearest',
        resamp_alg='bilinear',
        )
        # to Lon/Lat
        data_mapgeo_3D, dem_gt, dem_prj = SMGT.to_map_geometry(self.data_sensor_geo_3D, tgt_prj=4326)
        self.assertIsInstance(data_mapgeo_3D, np.ndarray)
        # only validate number of bands (height and width are validated in 2D version
        # fixed numbers may fail here due to float uncertainty errors
        self.assertEquals(data_mapgeo_3D.shape[2], 2)
        xmin, xmax, ymin, ymax = corner_coord_to_minmax(get_corner_coordinates(gt=dem_gt,
        cols=data_mapgeo_3D.shape[1],
        rows=data_mapgeo_3D.shape[0]))
        self.assertTrue(False not in np.isclose(np.array([xmin, ymin, xmax, ymax]),
        np.array(self.expected_dem_area_extent_lonlat)))
        for rsp_alg in rsp_algs:
        SMGT = SensorMapGeometryTransformer3D(lons=self.lons_3D,
        lats=self.lats_3D,
        # resamp_alg='nearest',
        resamp_alg=rsp_alg,
        )
        # to Lon/Lat
        data_mapgeo_3D, dem_gt, dem_prj = SMGT.to_map_geometry(self.data_sensor_geo_3D, tgt_prj=4326)
        self.assertIsInstance(data_mapgeo_3D, np.ndarray)
        # only validate number of bands (height and width are validated in 2D version
        # fixed numbers may fail here due to float uncertainty errors
        self.assertEquals(data_mapgeo_3D.shape[2], 2)
        xmin, xmax, ymin, ymax = corner_coord_to_minmax(get_corner_coordinates(gt=dem_gt,
        cols=data_mapgeo_3D.shape[1],
        rows=data_mapgeo_3D.shape[0]))
        self.assertTrue(False not in np.isclose(np.array([xmin, ymin, xmax, ymax]),
        np.array(self.expected_dem_area_extent_lonlat)))
        def test_to_sensor_geometry(self):
        SMGT = SensorMapGeometryTransformer3D(lons=self.lons_3D,
        lats=self.lats_3D,
        resamp_alg='nearest',
        )
        dem_sensors_geo = SMGT.to_sensor_geometry(self.data_map_geo_3D,
        src_prj=32632, src_extent=self.dem_area_extent_coarse_subset_utm)
        self.assertIsInstance(dem_sensors_geo, np.ndarray)
        self.assertEquals(dem_sensors_geo.shape, (150, 1000, 2))
        for rsp_alg in rsp_algs:
        SMGT = SensorMapGeometryTransformer3D(lons=self.lons_3D,
        lats=self.lats_3D,
        resamp_alg=rsp_alg,
        )
        dem_sensors_geo = SMGT.to_sensor_geometry(self.data_map_geo_3D,
        src_prj=32632, src_extent=self.dem_area_extent_coarse_subset_utm)
        self.assertIsInstance(dem_sensors_geo, np.ndarray)
        self.assertEquals(dem_sensors_geo.shape, (150, 1000, 2))
        Markdown is supported
        0% or .
        You are about to add 0 people to the discussion. Proceed with caution.
        Finish editing this message first!
        Please register or to comment