def test_silent(self):
"""
Test that the silent method does not return any output in console
"""
fn_img = datasets.get_path("landsat_B4")
# let's capture stdout
# cf https://stackoverflow.com/questions/16571150/how-to-capture-stdout-output-from-a-python-function-call
class Capturing(list):
def __enter__(self):
self._stdout = sys.stdout
sys.stdout = self._stringio = StringIO()
return self
def __exit__(self, *args):
self.extend(self._stringio.getvalue().splitlines())
del self._stringio # free up some memory
sys.stdout = self._stdout
with Capturing() as output1:
img = si.SatelliteImage(fn_img)
# check the metadata reading outputs to console
assert len(output1) > 0
with Capturing() as output2:
img = si.SatelliteImage(fn_img, silent=True)
# check nothing outputs to console
assert len(output2) == 0
def test_init(self):
"""
Test that inputs work properly in SatelliteImage class init
"""
fn_img = datasets.get_path("landsat_B4")
# from filename, checking option
img = si.SatelliteImage(fn_img, read_from_fn=False)
img = si.SatelliteImage(fn_img)
assert isinstance(img, si.SatelliteImage)
# from SatelliteImage
img2 = si.SatelliteImage(img)
assert isinstance(img2, si.SatelliteImage)
# from Raster
r = gr.Raster(fn_img)
img3 = si.SatelliteImage(r)
assert isinstance(img3, si.SatelliteImage)
assert np.logical_and.reduce((np.array_equal(img.data, img2.data, equal_nan=True),
np.array_equal(img2.data, img3.data, equal_nan=True)))
assert np.logical_and.reduce((np.all(img.data.mask == img2.data.mask),
np.all(img2.data.mask == img3.data.mask)))
def test_init(self):
"""
Test that inputs work properly in DEM class init
"""
fn_img = xdem.examples.get_path("longyearbyen_ref_dem")
# from filename
dem = DEM(fn_img)
assert isinstance(dem, DEM)
# from DEM
dem2 = DEM(dem)
assert isinstance(dem2, DEM)
# from Raster
r = gr.Raster(fn_img)
dem3 = DEM(r)
assert isinstance(dem3, DEM)
# from SatelliteImage
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore", "Parse metadata from file not implemented")
img = si.SatelliteImage(fn_img)
dem4 = DEM(img)
assert isinstance(dem4, DEM)
list_dem = [dem, dem2, dem3, dem4]
attrs = [
at for at in r._get_rio_attrs()
if at not in ['name', 'dataset_mask', 'driver']
]
all_attrs = attrs + si.satimg_attrs + xdem.dem.dem_attrs
for attr in all_attrs:
attrs_per_dem = [idem.__getattribute__(attr) for idem in list_dem]
assert all(at == attrs_per_dem[0] for at in attrs_per_dem)
assert np.logical_and.reduce((np.array_equal(dem.data,
dem2.data,
equal_nan=True),
np.array_equal(dem2.data,
dem3.data,
equal_nan=True),
np.array_equal(dem3.data,
dem4.data,
equal_nan=True)))
assert np.logical_and.reduce(
(np.all(dem.data.mask == dem2.data.mask),
np.all(dem2.data.mask == dem3.data.mask),
np.all(dem3.data.mask == dem4.data.mask)))
def test_copy(self) -> None:
"""
Test that the copy method works as expected for SatelliteImage. In particular
when copying r to r2:
- if r.data is modified and r copied, the updated data is copied
- if r is copied, r.data changed, r2.data should be unchanged
"""
# Open dataset, update data and make a copy
r = si.SatelliteImage(datasets.get_path("landsat_B4"))
r.data += 5
r2 = r.copy()
# Objects should be different (not pointing to the same memory)
assert r is not r2
# Check the object is a SatelliteImage
assert isinstance(r2, geoutils.satimg.SatelliteImage)
# check all immutable attributes are equal
# georaster_attrs = ['bounds', 'count', 'crs', 'dtypes', 'height', 'indexes', 'nodata',
# 'res', 'shape', 'transform', 'width']
# satimg_attrs = ['satellite', 'sensor', 'product', 'version', 'tile_name', 'datetime']
# using list directly available in Class
attrs = [
at for at in r._get_rio_attrs()
if at not in ["name", "dataset_mask", "driver"]
]
all_attrs = attrs + si.satimg_attrs
for attr in all_attrs:
assert r.__getattribute__(attr) == r2.__getattribute__(attr)
# Check data array
assert geoutils.misc.array_equal(r.data, r2.data, equal_nan=True)
# Check dataset_mask array
assert np.all(r.data.mask == r2.data.mask)
# Check that if r.data is modified, it does not affect r2.data
r.data += 5
assert not geoutils.misc.array_equal(r.data, r2.data, equal_nan=True)