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 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 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_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 from_raster(name, raster, **kwargs):
"""
Create site from a raster on disk
:param name: The name of the site
:param raster: The gdal raster
Optional arguments:
- shape_index_y: Select the band index for the Y-size
- shape_index_x: Select the band index for the X-size
:return: A site class given the infos from the raster.
"""
driver = GDalDatasetWrapper.from_file(raster)
shape_index_y = kwargs.get("shape_index_y", 0)
shape_index_x = kwargs.get("shape_index_x", 1)
ny, nx = driver.array.shape[shape_index_y], driver.array.shape[
shape_index_x]
epsg = driver.epsg
ulx, uly, lrx, lry = driver.ul_lr
ul = (ulx, uly)
lr = (lrx, lry)
xmin, xres, skx, ymax, sky, yres = driver.geotransform
return Site(name,
epsg,
ul=ul,
lr=lr,
px=nx,
py=ny,
res_x=xres,
res_y=yres)
def test_get_ndsi_float32(self):
swir = np.arange(0, 9).reshape(3, 3)
red = np.ones((3, 3))
swir[-1, -1] = 0
red[-1, -1] = 0
ds_swir = GDalDatasetWrapper(array=swir, projection=self.projection, geotransform=self.coordinates)
ds_red = GDalDatasetWrapper(array=red, projection=self.projection, geotransform=self.coordinates)
expected = np.array([[1, 0, -.3333333],
[-.5, -.6, -.6666667],
[-0.7142857, -0.75, -1]], dtype=np.float32)
calculated = ImageApps.get_ndsi(ds_red, ds_swir)
np.testing.assert_almost_equal(calculated.array, expected)
self.assertEqual(calculated.resolution, ds_swir.resolution)
self.assertEqual(calculated.resolution, ds_red.resolution)
self.assertEqual(calculated.extent, ds_red.extent)
self.assertEqual(calculated.extent, ds_swir.extent)
def test_write_nodata(self):
fname = "./test_write_nodata.tif"
img = np.ones((self.height, self.width), np.int16)
ds = GDalDatasetWrapper(array=img,
projection=self.projection,
geotransform=self.coordinates,
nodata_value=42)
ds.write(fname, options=["COMPRESS=DEFLATE"])
self.assertTrue(os.path.exists(fname))
ds_read = GDalDatasetWrapper.from_file(fname)
self.assertEqual(42, ds_read.nodata_value)
self.assertEqual(
"DEFLATE",
ds_read._info["metadata"]["IMAGE_STRUCTURE"]["COMPRESSION"])
np.testing.assert_almost_equal(ds_read.array, ds.array)
os.remove(fname)
self.assertFalse(os.path.exists(fname))
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_get_ndsi_int16(self):
swir = np.array(np.arange(0, 9).reshape(3, 3), dtype=np.int16)
red = np.ones((3, 3), dtype=np.int16)
swir[-1, -1] = 0
red[-1, -1] = 0
ds_swir = GDalDatasetWrapper(array=swir, projection=self.projection, geotransform=self.coordinates)
ds_red = GDalDatasetWrapper(array=red, projection=self.projection, geotransform=self.coordinates)
expected = np.array([[1000, 500, 333],
[250, 199, 166],
[142, 125, 0]], dtype=np.int16)
calculated = ImageApps.get_ndsi(ds_red, ds_swir, vrange=(0, 1000), dtype=np.int16)
np.testing.assert_almost_equal(calculated.array, expected)
self.assertEqual(calculated.resolution, ds_swir.resolution)
self.assertEqual(calculated.resolution, ds_red.resolution)
self.assertEqual(calculated.extent, ds_red.extent)
self.assertEqual(calculated.extent, ds_swir.extent)
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_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_without_ds(self):
img = np.ones((self.height, self.width), np.int16)
ds = GDalDatasetWrapper(array=img,
projection=self.projection,
geotransform=self.coordinates)
np.testing.assert_almost_equal(img, ds.array)
self.assertEqual(ds.geotransform, self.coordinates)
self.assertIsNone(ds.nodata_value)
self.assertEqual(ds.epsg, 32631)
np.testing.assert_almost_equal(np.ones_like(img), ds.nodata_mask)
# Compare projections by removing all spaces cause of multiline string
self.assertEqual(ds.projection.replace(" ", ""),
self.projection.replace(" ", ""))
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))
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 reproject(self, **kwargs):
out_dir = kwargs.get("out_dir", self.fpath)
assert os.path.isdir(out_dir)
out_dir = os.path.join(out_dir, self.base)
FileSystem.create_directory(out_dir)
patterns = kwargs.get("patterns", [r".(tif|jp2)$"])
imgs = [self.find_file(pattern=p) for p in patterns]
epsg = kwargs.get("epsg", None)
# Flatten
imgs = [i for img in imgs for i in img]
for img in imgs:
if not epsg:
drv = GDalDatasetWrapper.from_file(img)
epsg = drv.epsg
outpath = os.path.join(out_dir, os.path.basename(img))
self._reproject_to_epsg(img, outpath, epsg)
return out_dir
def __init__(self, site, dem_full_res):
self.name = site.nom
self.epsg = site.epsg_str
self.ulx = site.ul[0]
self.uly = site.ul[1]
self.resx = site.res_x
self.resy = site.res_y
self.lx = site.px
self.ly = site.py
self.alt = dem_full_res
driver = GDalDatasetWrapper.from_file(dem_full_res)
self.mean_alt = np.mean(driver.array)
self.std_dev_alt = np.std(driver.array)
self.short_description = driver.utm_description
self.nodata = driver.nodata_value
res_arr = driver.resolution
self.dem_subsampling_ratio = str(
int(float(res_arr[0]) / float(site.res_x)))
def get_ndvi(red, nir, vrange=(-1, 1), dtype=np.float32):
"""
Calculate the NDVI (Normalized-Difference Vegetation Index)
:param red: The red band dataset
:type red: :class:`Common.GDalDatasetWrapper.GDalDatasetWrapper`
:param nir: The nir band dataset
:type nir: :class:`Common.GDalDatasetWrapper.GDalDatasetWrapper`
:param vrange: The range of output values as tuple. By default: (-1, 1).
:type vrange: tuple of int
:param dtype: The output dtype.
:type dtype: :class`np.dtype`
:return: The NDVI as numpy array.
:rtype: :class:`Common.GDalDatasetWrapper.GDalDatasetWrapper`
"""
if nir.extent != red.extent or nir.epsg != red.epsg:
raise ValueError("Cannot calculate NDSI on two different extents.")
if nir.resolution != red.resolution:
# Resize to nir resolution in this case.
tr = " ".join([str(i) for i in nir.resolution])
ds_red = ImageTools.gdal_translate(red, tr=tr, r="cubic")
else:
ds_red = red
# TODO Add new test
img_red = np.array(ds_red.array, dtype=np.float32)
img_nir = np.array(nir.array, dtype=np.float32)
# Compensate for nan:
np.seterr(divide='ignore', invalid='ignore')
img_ndvi = np.where((img_red + img_nir) != 0,
(img_red - img_nir) / (img_red + img_nir), -1)
# Scale to vrange
img_ndvi_scaled = ImageTools.normalize(img_ndvi,
value_range_out=vrange,
value_range_in=(-1, 1),
dtype=dtype,
clip=True)
return GDalDatasetWrapper(ds=nir.get_ds(), array=img_ndvi_scaled)
def test_srtm_prepare_mnt_vns_maccanw2(self):
resx, resy = 5000, -5000
px, py = 11, 14
site = SiteInfo.Site("MACCANW2",
32633,
px=px,
py=py,
ul=(246439.500, 4672656.500),
lr=(299769.500, 4604231.500),
res_x=resx,
res_y=resy)
dem_dir = os.path.join(os.getcwd(),
"test_srtm_prepare_mnt_vns_maccanw2")
s = SRTM.SRTM(site,
dem_dir=dem_dir,
raw_dem=self.raw_srtm,
raw_gsw=self.raw_gsw,
wdir=dem_dir)
self.assertTrue(os.path.isdir(dem_dir))
srtm = s.prepare_mnt()
self.assertTrue(os.path.isfile(srtm))
driver = GDalDatasetWrapper.from_file(srtm)
expected_img = [[
293, 210, 337, 390, 238, 218, 237, 245, 270, 208, 132
], [302, 293, 277, 302, 182, 172, 237, 270, 262, 171, 60],
[155, 239, 239, 231, 238, 199, 164, 173, 137, 85, 33],
[0, 28, 94, 138, 150, 131, 116, 117, 72, 37, 73],
[0, 0, 18, 67, 81, 79, 84, 117, 72, 36, 59],
[0, 0, 0, 11, 38, 58, 68, 87, 68, 38, 33],
[0, 0, 0, 0, 6, 41, 52, 62, 52, 43, 41],
[0, 0, 0, 0, 1, 0, 30, 34, 30, 48, 68],
[0, 0, 0, 0, 0, -1, 12, 26, 42, 70, 101],
[0, 0, 0, 0, 0, 4, 11, 50, 59, 89, 136],
[0, 0, 0, 0, 0, 0, 0, 30, 76, 97, 130],
[0, 0, 0, 0, 0, 0, 0, 0, 44, 72, 86],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 28, 59],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 18, 54]]
self.assertEqual(driver.resolution, (resx, resy))
self.assertEqual(driver.array.shape, (site.py, site.px))
self.assertEqual(driver.nodata_value, 0)
np.testing.assert_allclose(expected_img, driver.array, atol=1.5)
FileSystem.remove_directory(dem_dir)
def gdal_translate(src, dst=None, **options):
"""
Translate a dataset.
:param src: The input filename or dataset.
:param dst: If specified, the output will be writen to
the given path on a physical disk.
Note: This overwrites a previous file at the same location.
:return: A :class:`Common.GDalDatasetWrapper.GDalDatasetWrapper` object
:rtype: `osgeo.gdal.dataset` or file on disk (see parameter ``dst``).
"""
gdal_common_params = ["optfile", "config", "debug"]
options_list = []
for k, v in options.items():
if k in gdal_common_params:
options_list += ["--%s" % k, "%s" % v]
elif type(v) is not bool:
options_list += ["-%s" % k, "%s" % v]
elif type(v) is bool and v is True:
options_list.append("-%s" % k)
else:
pass
options_list = " ".join(options_list)
if type(src) == GDalDatasetWrapper:
src = src.get_ds()
# Remove previous existing file if writing to disk is enabled:
if dst:
FileSystem.remove_file(dst)
# Note: De-allocation before file is actually written to disk
# cf. https://gdal.org/api/python_gotchas.html
_ = gdal.Translate(dst, src, options=options_list)
_ = None
ds_out = gdal.Open(dst)
else:
# Write directly into memory if no path specified (faster):
dst = "/vsimem/" + uuid.uuid4().hex
ds_out = gdal.Translate(dst, src, options=options_list)
arr_bands_last = np.array(ds_out.ReadAsArray())
if arr_bands_last.ndim == 3:
arr_bands_last = np.moveaxis(arr_bands_last, 0, -1)
return GDalDatasetWrapper(ds=ds_out, array=arr_bands_last)
def test_get_water_data_spain_s2(self):
"""
Download the given gsw file and project it to a 10km x 10km resolution (11x11 image)
"""
resx, resy = 10000, -10000
px, py = 11, 11
site = SiteInfo.Site("T30SYJ",
32630,
px=px,
py=py,
ul=(699960.000, 4400040.000),
lr=(809760.000, 4290240.000),
res_x=resx,
res_y=resy)
dem_dir = os.path.join(os.getcwd(), "test_get_water_data_spain_s2")
mnt = MNTBase.MNT(site,
dem_dir=dem_dir,
raw_dem=self.raw_dem,
raw_gsw=self.raw_gsw)
water_mask = mnt.gsw_dst
self.assertTrue(os.path.exists(dem_dir))
mnt.prepare_water_data()
self.assertTrue(os.path.exists(water_mask))
driver = GDalDatasetWrapper.from_file(water_mask)
img_expected = [[0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1],
[0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
[0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
[0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
[0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
[0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1],
[0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1],
[0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1],
[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1]]
self.assertEqual(driver.resolution, (resx, resy))
self.assertEqual(driver.epsg, 32630)
self.assertEqual(driver.array.shape, (py, px))
np.testing.assert_almost_equal(img_expected, driver.array)
self.assertIsNone(driver.nodata_value)
FileSystem.remove_directory(dem_dir)
def test_get_water_data_maccanw2_vns(self):
resx, resy = 5000, -5000
px, py = 11, 14
site = SiteInfo.Site("MACCANW2",
32633,
px=px,
py=py,
ul=(246439.500, 4672656.500),
lr=(299769.500, 4604231.500),
res_x=resx,
res_y=resy)
dem_dir = os.path.join(os.getcwd(), "test_get_water_data_maccanw2_vns")
mnt = MNTBase.MNT(site,
dem_dir=dem_dir,
raw_dem=self.raw_dem,
raw_gsw=self.raw_gsw)
water_mask = mnt.gsw_dst
self.assertTrue(os.path.exists(dem_dir))
mnt.prepare_water_data()
self.assertTrue(os.path.exists(water_mask))
driver = GDalDatasetWrapper.from_file(water_mask)
img_expected = [[0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0]]
self.assertEqual(driver.resolution, (resx, resy))
self.assertEqual(driver.epsg, 32633)
self.assertEqual(driver.array.shape, (py, px))
np.testing.assert_almost_equal(img_expected, driver.array)
self.assertIsNone(driver.nodata_value)
FileSystem.remove_directory(dem_dir)
def test_get_water_data_tls_l8(self):
resx, resy = 15000, -15000
px, py = 15, 14
site = SiteInfo.Site("19080",
32631,
px=px,
py=py,
ul=(285431.584, 4884950.507),
lr=(510124.885, 4680403.373),
res_x=resx,
res_y=resy)
dem_dir = os.path.join(os.getcwd(), "test_get_water_data_tls_l8")
mnt = MNTBase.MNT(site,
dem_dir=dem_dir,
raw_dem=self.raw_dem,
raw_gsw=self.raw_gsw)
water_mask = mnt.gsw_dst
self.assertTrue(os.path.exists(dem_dir))
mnt.prepare_water_data()
self.assertTrue(os.path.exists(water_mask))
driver = GDalDatasetWrapper.from_file(water_mask)
img_expected = [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
self.assertEqual(driver.resolution, (resx, resy))
self.assertEqual(driver.epsg, 32631)
self.assertEqual(driver.array.shape, (py, px))
self.assertIsNone(driver.nodata_value)
np.testing.assert_almost_equal(img_expected, driver.array)
FileSystem.remove_directory(dem_dir)
def gdal_merge(*src, dst=None, **options):
"""
Merge a dataset using a modified gdal_merge.
:param src: The list of input filenames or datasets.
:param dst: If specified, the output will be writen to
the given path on a physical disk.
:param options: Optional keyword arguments
:return:
"""
gdal_common_params = ["optfile"]
options_list = [""]
for k, v in options.items():
if k in gdal_common_params:
options_list += ["--%s" % k, "%s" % v]
elif type(v) is not bool:
options_list += ["-%s" % k, "%s" % v]
elif type(v) is bool and v is True:
options_list.append("-%s" % k)
else:
pass
#src = [i.get_ds() if type(i) == GDalDatasetWrapper else i for i in src]
# Remove previous existing file if writing to disk is enabled:
if dst and type(dst) == str:
FileSystem.remove_file(dst)
# Note: De-allocation before file is actually written to disk
# cf. https://gdal.org/api/python_gotchas.html
options_list += ["-o", "%s" % dst]
_ = merge.run_merge(*[s for s in src], argv=options_list)
_ = None
ds_out = gdal.Open(dst)
else:
# Write directly into memory if no path specified (faster):
ds_out = merge.run_merge(*[s for s in src], argv=options_list)
arr_bands_last = np.array(ds_out.ReadAsArray())
if arr_bands_last.ndim == 3:
arr_bands_last = np.moveaxis(arr_bands_last, 0, -1)
return GDalDatasetWrapper(ds=ds_out, array=arr_bands_last)
def test_srtm_prepare_mnt_s2_tls(self):
resx, resy = 10000, -10000
site = SiteInfo.Site("T31TCJ",
32631,
px=11,
py=11,
ul=(300000.000, 4900020.000),
lr=(409800.000, 4790220.000),
res_x=resx,
res_y=resy)
dem_dir = os.path.join(os.getcwd(), "test_srtm_prepare_mnt_s2_tls")
s = SRTM.SRTM(site,
dem_dir=dem_dir,
raw_dem=self.raw_srtm,
raw_gsw=self.raw_gsw,
wdir=dem_dir)
self.assertTrue(os.path.isdir(dem_dir))
srtm = s.prepare_mnt()
self.assertTrue(os.path.isfile(srtm))
driver = GDalDatasetWrapper.from_file(srtm)
expected_img = [
[85, 85, 115, 142, 138, 147, 151, 163, 162, 258, 282],
[136, 98, 96, 90, 101, 91, 120, 118, 121, 243, 302],
[137, 133, 135, 137, 101, 89, 92, 131, 162, 246, 294],
[139, 144, 170, 184, 157, 115, 108, 132, 176, 210, 212],
[148, 140, 161, 162, 206, 138, 133, 134, 150, 164, 160],
[169, 173, 168, 171, 222, 168, 128, 158, 162, 151, 164],
[193, 199, 181, 186, 186, 193, 158, 147, 189, 204, 199],
[209, 223, 207, 195, 215, 215, 166, 161, 187, 214, 228],
[240, 247, 225, 206, 268, 211, 172, 203, 195, 213, 242],
[281, 268, 246, 272, 282, 216, 216, 208, 231, 211, 220],
[335, 302, 319, 311, 265, 234, 262, 251, 236, 259, 250]
]
self.assertEqual(driver.resolution, (resx, resy))
self.assertEqual(driver.array.shape, (site.py, site.px))
self.assertEqual(driver.nodata_value, 0)
np.testing.assert_allclose(expected_img, driver.array, atol=1.5)
FileSystem.remove_directory(dem_dir)
def gdal_buildvrt(*inputs, dst=None, **options):
"""
Build a gdalvrt using in memory bindings.
:param inputs: The list of input filenames or datasets.
:param dst: If specified, the vrt will be writen to
the given path on a physical disk.
Note: This overwrites a previous vrt at the same location.
:return: VRT of the given inputs, by default as an in-memory file.
:type: `osgeo.gdal.dataset` or .vrt on disk (see param ``dst``).
"""
gdal_common_params = ["optfile"]
options_list = []
for k, v in options.items():
if k in gdal_common_params:
options_list += ["--%s" % k, "%s" % v]
elif type(v) is not bool:
options_list += ["-%s" % k, "%s" % v]
elif type(v) is bool and v is True:
options_list.append("-%s" % k)
else:
pass
options_list = " ".join(options_list)
inputs = [i.get_ds() if type(i) == GDalDatasetWrapper else i for i in inputs]
# Remove previous existing file if writing to disk is enabled:
if dst:
FileSystem.remove_file(dst)
# Note: De-allocation before file is actually written to disk
# cf. https://gdal.org/api/python_gotchas.html
_ = gdal.BuildVRT(dst, [i for i in inputs], options=options_list)
_ = None
ds_out = gdal.Open(dst)
else:
# Write directly into memory if no path specified (faster):
dst = "/vsimem/" + uuid.uuid4().hex
ds_out = gdal.BuildVRT(dst, [i for i in inputs], options=options_list)
return GDalDatasetWrapper(ds=ds_out)
def test_eudem_prepare_mnt_s2_tls(self):
resx, resy = 10000, -10000
site = SiteInfo.Site("T31TCJ",
32631,
ul=(300000.000, 4900020.000),
lr=(409800.000, 4790220.000),
px=11,
py=11,
res_x=resx,
res_y=resy)
dem_dir = os.path.join(os.getcwd(), "test_eudem_prepare_mnt_s2_31ucr")
s = EuDEM.EuDEM(site,
dem_dir=dem_dir,
raw_dem=self.raw_eudem,
raw_gsw=self.raw_gsw,
wdir=dem_dir)
self.assertTrue(os.path.isdir(dem_dir))
srtm = s.prepare_mnt()
self.assertTrue(os.path.isfile(srtm))
driver = GDalDatasetWrapper.from_file(srtm)
expected_img = [[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]]
self.assertEqual(driver.resolution, (resx, resy))
self.assertEqual(driver.array.shape, (site.py, site.px))
self.assertEqual(driver.nodata_value, 0)
np.testing.assert_allclose(expected_img, driver.array)
FileSystem.remove_directory(dem_dir)
def test_srtm_prepare_mnt_l8_tls(self):
resx, resy = 15000, -15000
px, py = 15, 14
site = SiteInfo.Site("19080",
32631,
px=px,
py=py,
ul=(285431.584, 4884950.507),
lr=(510124.885, 4680403.373),
res_x=resx,
res_y=resy)
dem_dir = os.path.join(os.getcwd(), "test_srtm_prepare_mnt_l8_tls")
s = SRTM.SRTM(site,
dem_dir=dem_dir,
raw_dem=self.raw_srtm,
raw_gsw=self.raw_gsw,
wdir=dem_dir)
self.assertTrue(os.path.isdir(dem_dir))
srtm = s.prepare_mnt()
self.assertTrue(os.path.isfile(srtm))
driver = GDalDatasetWrapper.from_file(srtm)
expected_img = np.array([[
126, 134, 125, 114, 88, 104, 144, 265, 266, 283, 388, 487, 592,
571, 617
],
[
144, 139, 161, 177, 134, 117, 161, 198,
189, 205, 328, 487, 457, 444, 634
],
[
166, 163, 164, 189, 177, 137, 156, 153,
198, 231, 384, 619, 698, 707, 638
],
[
194, 201, 194, 188, 198, 154, 178, 205,
218, 196, 303, 634, 898, 925, 586
],
[
216, 235, 223, 223, 226, 175, 194, 220,
234, 318, 462, 637, 752, 547, 275
],
[
273, 287, 268, 283, 234, 222, 226, 227,
215, 423, 581, 548, 404, 246, 86
],
[
429, 383, 352, 315, 277, 283, 265, 274,
269, 170, 148, 120, 72, 43, 27
],
[
598, 472, 402, 387, 427, 379, 362, 328,
365, 291, 270, 328, 186, 114, 42
],
[
1151, 897, 977, 763, 647, 814, 708, 596,
514, 458, 458, 576, 383, 231, 0
],
[
1591, 1303, 1697, 1728, 1229, 1342, 1085,
1173, 1137, 829, 685, 513, 289, 158, 27
],
[
2261, 2075, 1964, 2052, 1916, 2087, 1923,
1634, 1741, 1576, 1185, 490, 198, 36, -24
],
[
1671, 1898, 2127, 2148, 1475, 1992, 2126,
2301, 2098, 1749, 1235, 1060, 448, 135,
159
],
[
1264, 1283, 1496, 1520, 1529, 1398, 1684,
1735, 1472, 2044, 1949, 1344, 684, 374,
302
],
[
871, 980, 988, 1052, 1401, 1051, 1526,
1479, 1487, 1457, 1253, 753, 567, 179, 32
]])
self.assertEqual(driver.resolution, (resx, resy))
self.assertEqual(driver.array.shape, (site.py, site.px))
self.assertEqual(driver.nodata_value, 0)
np.testing.assert_allclose(expected_img, driver.array, atol=1.5)
FileSystem.remove_directory(dem_dir)