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
