def test_write_read_geotiff_kwoptions(self): img = np.ones((self.height, self.width), np.int16) nodata = 42 path = os.path.join(os.getcwd(), "test_write_read_geotiff.tif") ImageIO.gdal_write("GTiff", img, path, self.projection, self.coordinates, options=["COMPRESS=DEFLATE"], nodata=nodata) self.assertTrue(os.path.exists(path)) arr, ds = ImageIO.tiff_to_array(path, array_only=False) self.assertTrue((arr == img).all()) self.assertEqual( nodata, gdal.Info(ds, format="json")["bands"][0]["noDataValue"]) self.assertEqual( gdal.Info( ds, format="json")["metadata"]["IMAGE_STRUCTURE"]["COMPRESSION"], "DEFLATE") self.assertEqual(ds.GetGeoTransform(), self.coordinates) # Compare projections by removing all spaces cause of multiline string self.assertEqual(ds.GetProjection().replace(" ", ""), self.projection.replace(" ", "")) FileSystem.remove_file(path) self.assertFalse(os.path.exists(path))
def test_gdal_tile_untile(self): img = np.arange(0., 100.).reshape((10, 10)) path = os.path.join(os.getcwd(), "test_gdal_retile.tif") tile_folder = os.path.join(os.getcwd(), "tiled") ImageIO.write_geotiff(img, path, self.projection, self.coordinates) # Add parasitic file - It should not cause problems path_parasite = os.path.join(tile_folder, "tile_01_01.tif") FileSystem.create_directory(tile_folder) ImageIO.write_geotiff(img, path_parasite, self.projection, self.coordinates) ds_in = GDalDatasetWrapper.from_file(path) self.assertTrue(os.path.exists(path)) tiles = ImageTools.gdal_retile(ds_in, tile_folder, TileWidth=2, TileHeight=2, Overlap=1) self.assertTrue(os.path.isdir(tile_folder)) self.assertEqual(len(tiles), 81) img_read = np.array(ImageIO.tiff_to_array(tiles[-1])) expected = np.array([[88, 89], [98, 99]]) # Some gdal_retile versions are producing the following image: # [[87, 89], [97, 99]]. np.testing.assert_allclose(expected, img_read, atol=1) # Untile ds_untiled = ImageTools.gdal_buildvrt(*tiles) np.testing.assert_allclose(img, ds_untiled.array, atol=1) FileSystem.remove_file(path) FileSystem.remove_directory(tile_folder)
def test_write_read_geotiff(self): img = np.ones((self.height, self.width), np.int16) path = os.path.join(os.getcwd(), "test_write_read_geotiff.tif") ImageIO.write_geotiff(img, path, self.projection, self.coordinates) self.assertTrue(os.path.exists(path)) arr, ds = ImageIO.tiff_to_array(path, array_only=False) self.assertTrue((arr == img).all()) self.assertEqual(ds.GetGeoTransform(), self.coordinates) # Compare projections by removing all spaces cause of multiline string self.assertEqual(ds.GetProjection().replace(" ", ""), self.projection.replace(" ", "")) FileSystem.remove_file(path) self.assertFalse(os.path.exists(path))
def get_synthetic_band(self, synthetic_band, **kwargs): wdir = kwargs.get("wdir", self.fpath) output_folder = os.path.join(wdir, self.base) output_bname = "_".join([self.base.split(".")[0], synthetic_band.upper() + ".tif"]) output_filename = kwargs.get("output_filename", os.path.join(output_folder, output_bname)) max_value = kwargs.get("max_value", 10000.) # Skip existing: if os.path.exists(output_filename): return output_filename if synthetic_band.lower() == "ndvi": FileSystem.create_directory(output_folder) b4 = self.find_file(pattern=r"*B0?4(_10m)?.jp2$")[0] b8 = self.find_file(pattern=r"*B0?8(_10m)?.jp2$")[0] ds_red = GDalDatasetWrapper.from_file(b4) ds_nir = GDalDatasetWrapper.from_file(b8) ds_ndvi = ImageApps.get_ndvi(ds_red, ds_nir, vrange=(0, max_value), dtype=np.int16) ds_ndvi.write(output_filename, options=["COMPRESS=DEFLATE"]) elif synthetic_band.lower() == "ndsi": FileSystem.create_directory(output_folder) b3 = self.find_file(pattern=r"*B0?3(_10m)?.jp2$")[0] b11 = self.find_file(pattern=r"*B11(_20m)?.jp2$")[0] ds_green = ImageTools.gdal_translate(b3, tr="20 20", r="cubic") ds_swir = GDalDatasetWrapper.from_file(b11) ds_ndsi = ImageApps.get_ndsi(ds_green, ds_swir, vrange=(0, max_value), dtype=np.int16) ds_ndsi.write(output_filename, options=["COMPRESS=DEFLATE"]) elif synthetic_band.lower() == "mca_sim": FileSystem.create_directory(output_folder) b4 = self.find_file(pattern=r"*B0?4(_10m)?.jp2$")[0] b3 = self.find_file(pattern=r"*B0?3(_10m)?.jp2$")[0] img_red, drv = ImageIO.tiff_to_array(b4, array_only=False) img_green = ImageIO.tiff_to_array(b3) img_mcasim = (img_red + img_green) / 2 ImageIO.write_geotiff_existing(img_mcasim, output_filename, drv, options=["COMPRESS=DEFLATE"]) else: raise ValueError("Unknown synthetic band %s" % synthetic_band) return output_filename
def to_maja_format(self, platform_id, mission_field, mnt_resolutions, coarse_res, full_res_only=False): """ Writes an MNT in Maja (=EarthExplorer) format: A folder .DBL.DIR containing the rasters and an accompanying .HDR xml-file. The two files follow the maja syntax:: *AUX_REFDE2*.(HDR|DBL.DIR) :param platform_id: The platform ID of two digits (e.g. S2_ for Sentinel2A/B; VS for Venus) :param mission_field: Similar to the platform ID, this is used in the <Mission>-field for the HDR file. e.g. SENTINEL-2 for S2 :param mnt_resolutions: A dict containing the resolutions for the given sensor. E.g.:: {"XS": (10, -10)} :param coarse_res: A tuple of int describing the coarse resolution. E.g.:: (240, -240). :param full_res_only: If True, no coarse_res rasters will be created. :return: Writes the .DBL.DIR and .HDR into the specified self.dem_dir """ assert len(mnt_resolutions) >= 1 basename = str( "%s_TEST_AUX_REFDE2_%s_%s" % (platform_id, self.site.nom, str(self.dem_version).zfill(4))) # Get mnt data mnt_max_res = self.prepare_mnt() # Water mask not needed with optional coarse_res writing: if coarse_res and not full_res_only: # Get water data self.prepare_water_data() mnt_res = (self.site.res_x, self.site.res_y) dbl_base = basename + ".DBL.DIR" dbl_dir = os.path.join(self.dem_dir, dbl_base) FileSystem.create_directory(dbl_dir) hdr = os.path.join(self.dem_dir, basename + ".HDR") # Calulate gradient mask at MNT resolution: mnt_in, drv = ImageIO.tiff_to_array(mnt_max_res, array_only=False) grad_y_mnt, grad_x_mnt = self.calc_gradient(mnt_in, self.site.res_x, self.site.res_y) full_res = (int(mnt_resolutions[0]["val"].split(" ")[0]), int(mnt_resolutions[0]["val"].split(" ")[1])) grad_x = self.resample_to_full_resolution(grad_x_mnt, mnt_resolution=mnt_res, full_resolution=full_res, order=3) grad_y = self.resample_to_full_resolution(grad_y_mnt, mnt_resolution=mnt_res, full_resolution=full_res, order=3) slope, aspect = self.calc_slope_aspect(grad_y, grad_x) # Write full res slope and aspect geotransform = list(drv.GetGeoTransform()) geotransform[1] = float(full_res[0]) geotransform[-1] = float(full_res[1]) projection = drv.GetProjection() tmp_asp = tempfile.mktemp(dir=self.wdir, suffix="_asp.tif") ImageIO.write_geotiff(aspect, tmp_asp, projection, tuple(geotransform)) tmp_slp = tempfile.mktemp(dir=self.wdir, suffix="_slp.tif") ImageIO.write_geotiff(slope, tmp_slp, projection, tuple(geotransform)) # Full resolution: write_resolution_name = True if len(mnt_resolutions) > 1 else False # Names for R1, R2 etc. rasters_written = [] path_alt, path_asp, path_slp = "", "", "" all_paths_alt = [] for res in mnt_resolutions: # ALT: bname_alt = basename + "_ALT" bname_alt += "_" + str( res["name"]) if write_resolution_name else "" bname_alt += ".TIF" rel_alt = os.path.join(dbl_base, bname_alt) path_alt = os.path.join(self.dem_dir, rel_alt) all_paths_alt.append(path_alt) ImageTools.gdal_warp(mnt_max_res, dst=path_alt, tr=res["val"], r="cubic", multi=True) rasters_written.append(rel_alt) # ASP: bname_asp = basename + "_ASP" bname_asp += "_" + res["name"] if write_resolution_name else "" bname_asp += ".TIF" rel_asp = os.path.join(dbl_base, bname_asp) path_asp = os.path.join(self.dem_dir, rel_asp) ImageTools.gdal_warp(tmp_asp, dst=path_asp, tr=res["val"], r="cubic", multi=True) rasters_written.append(rel_asp) # SLP: bname_slp = basename + "_SLP" bname_slp += "_" + res["name"] if write_resolution_name else "" bname_slp += ".TIF" rel_slp = os.path.join(dbl_base, bname_slp) path_slp = os.path.join(self.dem_dir, rel_slp) ImageTools.gdal_warp(tmp_slp, dst=path_slp, tr=res["val"], r="cubic", multi=True) rasters_written.append(rel_slp) # Optional coarse_res writing: if coarse_res and not full_res_only: # Resize all rasters for coarse res. coarse_res_str = str(coarse_res[0]) + " " + str(coarse_res[1]) # ALC: bname_alc = basename + "_ALC.TIF" rel_alc = os.path.join(dbl_base, bname_alc) path_alc = os.path.join(self.dem_dir, rel_alc) ImageTools.gdal_warp(path_alt, dst=path_alc, tr=coarse_res_str, multi=True) rasters_written.append(rel_alc) # ALC: bname_asc = basename + "_ASC.TIF" rel_asc = os.path.join(dbl_base, bname_asc) path_asc = os.path.join(self.dem_dir, rel_asc) ImageTools.gdal_warp(path_asp, dst=path_asc, tr=coarse_res_str, multi=True) rasters_written.append(rel_asc) # ALC: bname_slc = basename + "_SLC.TIF" rel_slc = os.path.join(dbl_base, bname_slc) path_slc = os.path.join(self.dem_dir, rel_slc) ImageTools.gdal_warp(path_slp, dst=path_slc, tr=coarse_res_str, multi=True) rasters_written.append(rel_slc) # Water mask: bname_msk = basename + "_MSK.TIF" rel_msk = os.path.join(dbl_base, bname_msk) path_msk = os.path.join(self.dem_dir, rel_msk) ImageTools.gdal_warp(self.gsw_dst, dst=path_msk, tr=coarse_res_str, multi=True) rasters_written.append(rel_msk) # Write HDR Metadata: date_start = datetime(1970, 1, 1) date_end = datetime(2100, 1, 1) dem_info = DEMInfo(self.site, all_paths_alt[0]) root = self._get_root() self._create_hdr(root, mission_field, basename, rasters_written, dem_info, date_start, date_end, self.dem_version) XMLTools.write_xml(root, hdr) # Remove temp files: FileSystem.remove_file(tmp_asp) FileSystem.remove_file(tmp_slp) FileSystem.remove_file(mnt_max_res) return hdr, dbl_dir