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_gdal_buildvrt_concatenate(self):
from Common import FileSystem
paths = []
for i in range(1, 3, 1):
img = np.ones((i, i, 2), np.int16) * i
path = os.path.join(os.getcwd(), "test_gdal_merge_%s.tif" % i)
ImageIO.write_geotiff(img, path, self.projection, self.coordinates)
self.assertTrue(os.path.exists(path))
paths.append(path)
empty = os.path.join(os.getcwd(), "empty.vrt")
driver = ImageTools.gdal_buildvrt(*paths, dst=empty,
separate=True,
srcnodata=0)
expected = np.array([[[1, 0],
[0, 0]],
[[2, 2],
[2, 2]]], dtype=np.int16)
np.testing.assert_almost_equal(driver.array, expected)
self.assertEqual(driver.nodata_value, 0)
self.assertEqual(driver.epsg, 32631)
[FileSystem.remove_file(path) for path in paths]
FileSystem.remove_file(empty)
[self.assertFalse(os.path.exists(path)) for path in paths]
self.assertFalse(os.path.exists(empty))
def test_get_s2_epsg_code(self):
epsg_ref = 32631
projection = 'PROJCS["WGS 84 / UTM zone 31N",\
GEOGCS["WGS 84",DATUM["WGS_1984",\
SPHEROID["WGS 84",6378137,298.257223563,\
AUTHORITY["EPSG","7030"]],\
AUTHORITY["EPSG","6326"]],\
PRIMEM["Greenwich",0,\
AUTHORITY["EPSG","8901"]],\
UNIT["degree",0.0174532925199433,\
AUTHORITY["EPSG","9122"]],\
AUTHORITY["EPSG","4326"]],\
PROJECTION["Transverse_Mercator"],\
PARAMETER["latitude_of_origin",0],\
PARAMETER["central_meridian",3],\
PARAMETER["scale_factor",0.9996],\
PARAMETER["false_easting",500000],\
PARAMETER["false_northing",0],\
UNIT["metre",1,AUTHORITY["EPSG","9001"]],\
AXIS["Easting",EAST],AXIS["Northing",NORTH],\
AUTHORITY["EPSG","%s"]]' % epsg_ref
img = np.ones((self.height, self.width), np.int16)
path = os.path.join(os.getcwd(), "test_epsg.tif")
ImageIO.write_geotiff(img, path, projection, self.coordinates)
self.assertTrue(os.path.exists(path))
ds = GDalDatasetWrapper.from_file(path)
epsg_new = ds.epsg
self.assertEqual(epsg_new, epsg_ref)
FileSystem.remove_file(path)
self.assertFalse(os.path.exists(path))
def test_get_nodata(self):
expected_nodata = 42.0
img = np.ones((self.height, self.width), np.int16)
path = os.path.join(os.getcwd(), "test_get_nodata_init.tif")
ImageIO.write_geotiff(img, path, self.projection, self.coordinates)
ds = ImageTools.gdal_buildvrt(path, VRTNodata=expected_nodata)
self.assertEqual(expected_nodata, ds.nodata_value)
np.testing.assert_almost_equal(ds.nodata_mask, np.ones_like(img))
FileSystem.remove_file(path)
self.assertFalse(os.path.exists(path))
def test_get_utm_description(self):
img = np.ones((self.height, self.width), np.int16)
path = os.path.join(os.getcwd(), "test_get_utm_description.tif")
ImageIO.write_geotiff(img, path, self.projection, self.coordinates)
self.assertTrue(os.path.exists(path))
ds = GDalDatasetWrapper.from_file(path)
utm = ds.utm_description
utm_expected = "WGS 84 / UTM zone 31N"
self.assertEqual(utm_expected, utm)
FileSystem.remove_file(path)
self.assertFalse(os.path.exists(path))
def test_get_resolution(self):
img = np.ones((self.height, self.width), np.int16)
path = os.path.join(os.getcwd(), "test_get_resolution.tif")
ImageIO.write_geotiff(img, path, self.projection, self.coordinates)
self.assertTrue(os.path.exists(path))
ds = GDalDatasetWrapper.from_file(path)
res_expected = (self.coordinates[1], self.coordinates[-1])
self.assertEqual(res_expected, ds.resolution)
FileSystem.remove_file(path)
self.assertFalse(os.path.exists(path))
def test_gdal_buildvrt(self):
path = os.path.join(os.getcwd(), "test_gdal_buildvrt.tif")
vrt = os.path.join(os.getcwd(), "test_vrt.vrt")
img = np.arange(-4, 5).reshape(3, 3) / 5
ImageIO.write_geotiff(img, path, self.projection, self.coordinates)
self.assertTrue(os.path.exists(path))
driver = ImageTools.gdal_buildvrt(path, dst=vrt)
self.assertTrue(os.path.exists(vrt))
np.testing.assert_almost_equal(driver.array, img)
FileSystem.remove_file(vrt)
FileSystem.remove_file(path)
def test_get_ul_lr(self):
img = np.ones((1000, 1000), np.int16)
path = os.path.join(os.getcwd(), "test_get_ul_lr.tif")
ImageIO.write_geotiff(img, path, self.projection, self.coordinates)
self.assertTrue(os.path.exists(path))
ds = GDalDatasetWrapper.from_file(path)
ulx, uly, lrx, lry = ds.ul_lr
self.assertEqual((ulx, uly), (300000.0, 4900020.0))
self.assertEqual((lrx, lry), (310000.0, 4890020.0))
self.assertEqual(ds.extent, (300000.0, 4890020.0, 310000.0, 4900020.0))
FileSystem.remove_file(path)
self.assertFalse(os.path.exists(path))
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 test_faulty_geotransform_projection(self):
coordinates = (652594.9112913811, 10.00887639510383, 0,
5072876.717295351, 0) # Missing one value
projection = '' # Empty
height = 200
width = 100
img = np.ones((height, width), np.int16)
path = os.path.join(os.getcwd(),
"test_faulty_geotransform_projection.tif")
# Check geotransform wrong:
with self.assertRaises(TypeError):
ImageIO.write_geotiff(img, path, projection, coordinates)
FileSystem.remove_file(path)
self.assertFalse(os.path.exists(path))
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))
ds = GDalDatasetWrapper.from_file(path)
self.assertTrue((ds.array == img).all())
self.assertEqual(ds.geotransform, self.coordinates)
# Compare projections by removing all spaces cause of multiline string
self.assertEqual(ds.projection.replace(" ", ""), self.projection.replace(" ", ""))
self.assertIsNone(ds.nodata_value)
self.assertEqual(ds.epsg, 32631)
FileSystem.remove_file(path)
self.assertFalse(os.path.exists(path))
def test_gdal_translate(self):
img = np.ones((self.height, self.width, 2), np.int16)
path = os.path.join(os.getcwd(), "test_gdal_translate.tif")
scaled = os.path.join(os.getcwd(), "scaled.tif")
out_resolution = (20, -20)
ImageIO.write_geotiff(img, path, self.projection, self.coordinates)
self.assertTrue(os.path.exists(path))
ds = ImageTools.gdal_translate(path, scaled,
tr=" ".join([str(i) for i in out_resolution]),
scale="0 1 0 255")
self.assertEqual(ds.resolution, out_resolution)
self.assertEqual(ds.array.shape, (self.height // 2, self.width // 2, 2))
np.testing.assert_almost_equal(ds.array, 255)
FileSystem.remove_file(path)
FileSystem.remove_file(scaled)
def test_gdal_warp(self):
img = np.ones((self.height, self.width, 2), np.int16)
img_rescaled = np.ones((int(self.height/2), int(self.width/2), 2), np.int16)
out_resolution = (20, -20)
path = os.path.join(os.getcwd(), "test_gdal_warp.tif")
scaled = os.path.join(os.getcwd(), "res_changed.tif")
ImageIO.write_geotiff(img, path, self.projection, self.coordinates)
self.assertTrue(os.path.exists(path))
ds = ImageTools.gdal_warp(path, scaled,
tr=" ".join(str(e) for e in out_resolution),
r="max", q=True)
self.assertTrue(os.path.isfile(scaled))
self.assertEqual(ds.resolution, out_resolution)
self.assertEqual(ds.array.shape, (self.height // 2, self.width // 2, 2))
np.testing.assert_almost_equal(ds.array, img_rescaled)
FileSystem.remove_file(path)
FileSystem.remove_file(scaled)
def test_merge_then_translate(self):
datasets = []
init = np.zeros((2, 2), np.int16)
path = os.path.join(os.getcwd(), "test_gdal_merge.tif")
ImageIO.write_geotiff(init, path, self.projection, self.coordinates)
ds_in = GDalDatasetWrapper.from_file(path)
for i in range(1, 3, 1):
img = np.ones((i*2, i*2), np.int16) * i
ds_n = GDalDatasetWrapper(ds=ds_in.get_ds(), array=img)
self.assertTrue(os.path.exists(path))
datasets.append(ds_n)
ds_merged = ImageTools.gdal_merge(*datasets, dst="out.tif",
separate=True,
q=True,
a_nodata=0)
# Array of shape (4, 4, 2):
expected = np.array([[[1, 2],
[1, 2],
[0, 2],
[0, 2]],
[[1, 2],
[1, 2],
[0, 2],
[0, 2]],
[[0, 2],
[0, 2],
[0, 2],
[0, 2]],
[[0, 2],
[0, 2],
[0, 2],
[0, 2]]], dtype=np.int16)
FileSystem.remove_file("out.tif")
np.testing.assert_equal(expected.dtype, ds_merged.array.dtype)
np.testing.assert_almost_equal(expected, ds_merged.array)
self.assertEqual(ds_merged.nodata_value, 0)
self.assertEqual(ds_merged.epsg, 32631)
ds_translate = ImageTools.gdal_translate(ds_merged,
a_nodata=0)
FileSystem.remove_file(path)
np.testing.assert_equal(expected.dtype, ds_translate.array.dtype)
np.testing.assert_almost_equal(ds_translate.array, expected)
self.assertEqual(ds_translate.nodata_value, 0)
self.assertEqual(ds_translate.epsg, 32631)
def test_gdal_merge_optfile(self):
datasets, written = [], []
init = np.zeros((2, 2), np.int16)
path = os.path.join(os.getcwd(), "test_gdal_merge_optfile.tif")
ImageIO.write_geotiff(init, path, self.projection, self.coordinates)
ds_in = GDalDatasetWrapper.from_file(path)
for i in range(1, 3, 1):
img = np.ones((i*2, i*2), np.int16) * i
ds_n = GDalDatasetWrapper(ds=ds_in.get_ds(), array=img)
p_out = "test_gdal_merge_optfile_%s.tif" % i
ImageIO.write_geotiff_existing(img, p_out, ds_in.get_ds())
self.assertTrue(os.path.exists(path))
datasets.append(ds_n)
written.append(p_out)
optfile = "test_gdal_merge_optfile.txt"
with open(optfile, 'w') as file_handler:
for item in written:
file_handler.write("{}\n".format(item))
ds_merged = ImageTools.gdal_merge(*datasets,
q=True,
a_nodata=0)
ds_optfile = ImageTools.gdal_merge(optfile=optfile,
q=True,
a_nodata=0)
# Array of shape (4, 4):
expected = np.array([[2, 2, 2, 2],
[2, 2, 2, 2],
[2, 2, 2, 2],
[2, 2, 2, 2]], dtype=np.int16)
FileSystem.remove_file(path)
[FileSystem.remove_file(p) for p in written]
FileSystem.remove_file(optfile)
np.testing.assert_equal(expected.dtype, ds_merged.array.dtype)
np.testing.assert_almost_equal(expected, ds_merged.array)
self.assertEqual(ds_merged.nodata_value, 0)
self.assertEqual(ds_merged.epsg, 32631)
np.testing.assert_equal(expected.dtype, ds_optfile.array.dtype)
np.testing.assert_almost_equal(expected, ds_optfile.array)
self.assertEqual(ds_optfile.nodata_value, 0)
self.assertEqual(ds_optfile.epsg, 32631)
def test_override_array(self):
img = np.ones((self.height, self.width), np.int16)
img_new = np.array(np.arange(0, 40200).reshape(201, 200), dtype=np.uint8)
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))
ds = GDalDatasetWrapper.from_file(path)
self.assertTrue((ds.array == img).all())
self.assertEqual(ds.geotransform, self.coordinates)
self.assertEqual(ds.projection.replace(" ", ""), self.projection.replace(" ", ""))
self.assertIsNone(ds.nodata_value)
self.assertEqual(ds.epsg, 32631)
ds_new = GDalDatasetWrapper(ds=ds.get_ds(), array=img_new, nodata_value=123)
FileSystem.remove_file(path)
np.testing.assert_almost_equal(img_new, ds_new.array)
self.assertEqual(ds_new.geotransform, self.coordinates)
self.assertEqual(ds_new.projection.replace(" ", ""), self.projection.replace(" ", ""))
self.assertEqual(ds_new.nodata_value, 123)
self.assertEqual(ds_new.epsg, 32631)
self.assertFalse(os.path.exists(path))
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