def test_S2L1C_float32_uint16(self):
""" Download S2L1C bands and dataMask
"""
test_dir = os.path.dirname(os.path.realpath(__file__))
cache_folder = os.path.join(test_dir, 'cache_test')
if os.path.exists(cache_folder):
shutil.rmtree(cache_folder)
task = SentinelHubInputTask(
bands_feature=(FeatureType.DATA, 'BANDS'),
additional_data=[(FeatureType.MASK, 'dataMask')],
size=self.size,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_collection=DataCollection.SENTINEL2_L1C,
max_threads=self.max_threads,
cache_folder=cache_folder)
eopatch = task.execute(bbox=self.bbox,
time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, 'BANDS')]
is_data = eopatch[(FeatureType.MASK, 'dataMask')]
self.assertTrue(
np.allclose(array_stats(bands), [0.0233, 0.0468, 0.0252]))
width, height = self.size
self.assertTrue(bands.shape == (4, height, width, 13))
self.assertTrue(is_data.shape == (4, height, width, 1))
self.assertTrue(len(eopatch.timestamp) == 4)
self.assertTrue(bands.dtype == np.float32)
self.assertTrue(os.path.exists(cache_folder))
# change task's bans_dtype and run it again
task.bands_dtype = np.uint16
eopatch = task.execute(bbox=self.bbox,
time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, 'BANDS')]
self.assertTrue(
np.allclose(array_stats(bands), [232.5769, 467.5385, 251.8654]))
self.assertTrue(bands.dtype == np.uint16)
shutil.rmtree(cache_folder)
def test_additional_data(self):
""" Download additional data, such as viewAzimuthMean, sunAzimuthAngles...
"""
task = SentinelHubInputTask(bands_feature=(FeatureType.DATA, 'BANDS'),
bands=['B01', 'B02', 'B05'],
additional_data=[
(FeatureType.MASK, 'dataMask',
'IS_DATA'), (FeatureType.MASK, 'CLM'),
(FeatureType.MASK, 'SCL'),
(FeatureType.MASK, 'SNW'),
(FeatureType.MASK, 'CLD'),
(FeatureType.DATA, 'CLP'),
(FeatureType.DATA, 'viewAzimuthMean',
'view_azimuth_mean'),
(FeatureType.DATA, 'sunAzimuthAngles'),
(FeatureType.DATA, 'sunZenithAngles')
],
size=self.size,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_source=DataSource.SENTINEL2_L2A,
max_threads=self.max_threads)
eopatch = task.execute(bbox=self.bbox,
time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, 'BANDS')]
is_data = eopatch[(FeatureType.MASK, 'IS_DATA')]
clm = eopatch[(FeatureType.MASK, 'CLM')]
scl = eopatch[(FeatureType.MASK, 'SCL')]
snw = eopatch[(FeatureType.MASK, 'SNW')]
cld = eopatch[(FeatureType.MASK, 'CLD')]
clp = eopatch[(FeatureType.DATA, 'CLP')]
view_azimuth_mean = eopatch[(FeatureType.DATA, 'view_azimuth_mean')]
sun_azimuth_angles = eopatch[(FeatureType.DATA, 'sunAzimuthAngles')]
sun_zenith_angles = eopatch[(FeatureType.DATA, 'sunZenithAngles')]
self.assertTrue(
np.allclose(array_stats(bands), [0.027, 0.0243, 0.0162]))
width, height = self.size
self.assertTrue(bands.shape == (4, height, width, 3))
self.assertTrue(is_data.shape == (4, height, width, 1))
self.assertTrue(is_data.dtype == np.bool)
self.assertTrue(clm.shape == (4, height, width, 1))
self.assertTrue(clm.dtype == np.uint8)
self.assertTrue(scl.shape == (4, height, width, 1))
self.assertTrue(snw.shape == (4, height, width, 1))
self.assertTrue(cld.shape == (4, height, width, 1))
self.assertTrue(clp.shape == (4, height, width, 1))
self.assertTrue(view_azimuth_mean.shape == (4, height, width, 1))
self.assertTrue(sun_azimuth_angles.shape == (4, height, width, 1))
self.assertTrue(sun_zenith_angles.shape == (4, height, width, 1))
self.assertTrue(len(eopatch.timestamp) == 4)
def test_additional_data(self):
task = SentinelHubInputTask(
bands_feature=(FeatureType.DATA, "BANDS"),
bands=["B01", "B02", "B05"],
additional_data=[
(FeatureType.MASK, "dataMask", "IS_DATA"),
(FeatureType.MASK, "CLM"),
(FeatureType.MASK, "SCL"),
(FeatureType.MASK, "SNW"),
(FeatureType.MASK, "CLD"),
(FeatureType.DATA, "CLP"),
(FeatureType.DATA, "viewAzimuthMean", "view_azimuth_mean"),
(FeatureType.DATA, "sunAzimuthAngles"),
(FeatureType.DATA, "sunZenithAngles"),
],
size=self.size,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_collection=DataCollection.SENTINEL2_L2A,
max_threads=self.max_threads,
)
eopatch = task.execute(bbox=self.bbox,
time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, "BANDS")]
is_data = eopatch[(FeatureType.MASK, "IS_DATA")]
clm = eopatch[(FeatureType.MASK, "CLM")]
scl = eopatch[(FeatureType.MASK, "SCL")]
snw = eopatch[(FeatureType.MASK, "SNW")]
cld = eopatch[(FeatureType.MASK, "CLD")]
clp = eopatch[(FeatureType.DATA, "CLP")]
view_azimuth_mean = eopatch[(FeatureType.DATA, "view_azimuth_mean")]
sun_azimuth_angles = eopatch[(FeatureType.DATA, "sunAzimuthAngles")]
sun_zenith_angles = eopatch[(FeatureType.DATA, "sunZenithAngles")]
assert calculate_stats(bands) == approx([0.027, 0.0243, 0.0162])
width, height = self.size
assert bands.shape == (4, height, width, 3)
assert is_data.shape == (4, height, width, 1)
assert is_data.dtype == bool
assert clm.shape == (4, height, width, 1)
assert clm.dtype == np.uint8
assert scl.shape == (4, height, width, 1)
assert snw.shape == (4, height, width, 1)
assert cld.shape == (4, height, width, 1)
assert clp.shape == (4, height, width, 1)
assert view_azimuth_mean.shape == (4, height, width, 1)
assert sun_azimuth_angles.shape == (4, height, width, 1)
assert sun_zenith_angles.shape == (4, height, width, 1)
assert len(eopatch.timestamp) == 4
def test_s2l1c_float32_uint16(self, cache_folder):
task = SentinelHubInputTask(
bands_feature=(FeatureType.DATA, "BANDS"),
additional_data=[(FeatureType.MASK, "dataMask")],
size=self.size,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_collection=DataCollection.SENTINEL2_L1C,
max_threads=self.max_threads,
cache_folder=cache_folder,
)
eopatch = task.execute(bbox=self.bbox,
time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, "BANDS")]
is_data = eopatch[(FeatureType.MASK, "dataMask")]
assert calculate_stats(bands) == approx([0.0233, 0.0468, 0.0252])
width, height = self.size
assert bands.shape == (4, height, width, 13)
assert is_data.shape == (4, height, width, 1)
assert len(eopatch.timestamp) == 4
assert bands.dtype == np.float32
assert os.path.exists(cache_folder)
# change task's bans_dtype and run it again
task.bands_dtype = np.uint16
eopatch = task.execute(bbox=self.bbox,
time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, "BANDS")]
assert calculate_stats(bands) == approx([232.5769, 467.5385, 251.8654])
assert bands.dtype == np.uint16
def test_no_data_input_task_request(self):
task = SentinelHubInputTask(
bands_feature=(FeatureType.DATA, "BANDS"),
additional_data=[(FeatureType.MASK, "dataMask")],
size=self.size,
maxcc=0.0,
data_collection=DataCollection.SENTINEL2_L1C,
)
eopatch = task.execute(bbox=self.bbox,
time_interval=("2021-01-01", "2021-01-20"))
bands = eopatch[FeatureType.DATA, "BANDS"]
assert bands.shape == (0, 101, 99, 13)
masks = eopatch[FeatureType.MASK, "dataMask"]
assert masks.shape == (0, 101, 99, 1)
def test_aux_request_args(self):
""" Download low resolution data with `PREVIEW` mode
"""
task = SentinelHubInputTask(
bands_feature=(FeatureType.DATA, 'BANDS'),
resolution=260,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_collection=DataCollection.SENTINEL2_L1C,
max_threads=self.max_threads,
aux_request_args={'dataFilter': {'previewMode': 'PREVIEW'}}
)
eopatch = task.execute(bbox=self.bbox, time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, 'BANDS')]
self.assertTrue(bands.shape == (4, 4, 4, 13))
self.assertTrue(np.allclose(array_stats(bands), [0.0, 0.0493, 0.0277]))
def test_scl_only(self):
""" Download just SCL, without any other bands
"""
task = SentinelHubInputTask(
bands_feature=None,
additional_data=[(FeatureType.DATA, 'SCL')],
size=self.size,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_collection=DataCollection.SENTINEL2_L2A,
max_threads=self.max_threads
)
eopatch = task.execute(bbox=self.bbox, time_interval=self.time_interval)
scl = eopatch[(FeatureType.DATA, 'SCL')]
width, height = self.size
self.assertTrue(scl.shape == (4, height, width, 1))
def test_aux_request_args(self):
"""Download low resolution data with `PREVIEW` mode"""
task = SentinelHubInputTask(
bands_feature=(FeatureType.DATA, "BANDS"),
resolution=260,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_collection=DataCollection.SENTINEL2_L1C,
max_threads=self.max_threads,
aux_request_args={"dataFilter": {
"previewMode": "PREVIEW"
}},
)
eopatch = task.execute(bbox=self.bbox,
time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, "BANDS")]
assert bands.shape == (4, 4, 4, 13)
assert calculate_stats(bands) == approx([0.0, 0.0493, 0.0277])
def test_specific_bands(self):
task = SentinelHubInputTask(
bands_feature=(FeatureType.DATA, "BANDS"),
bands=["B01", "B02", "B03"],
additional_data=[(FeatureType.MASK, "dataMask")],
size=self.size,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_collection=DataCollection.SENTINEL2_L1C,
max_threads=self.max_threads,
)
eopatch = task.execute(bbox=self.bbox,
time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, "BANDS")]
assert calculate_stats(bands) == approx([0.0648, 0.1193, 0.063])
width, height = self.size
assert bands.shape == (4, height, width, 3)
def test_specific_bands(self):
""" Download S2L1C bands and dataMask
"""
task = SentinelHubInputTask(
bands_feature=(FeatureType.DATA, 'BANDS'),
bands=["B01", "B02", "B03"],
additional_data=[(FeatureType.MASK, 'dataMask')],
size=self.size,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_collection=DataCollection.SENTINEL2_L1C,
max_threads=self.max_threads
)
eopatch = task.execute(bbox=self.bbox, time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, 'BANDS')]
self.assertTrue(np.allclose(array_stats(bands), [0.0648, 0.1193, 0.063]))
width, height = self.size
self.assertTrue(bands.shape == (4, height, width, 3))
def test_single_scene(self):
""" Download S2L1C bands and dataMask
"""
task = SentinelHubInputTask(
bands_feature=(FeatureType.DATA, 'BANDS'),
additional_data=[(FeatureType.MASK, 'dataMask')],
size=self.size,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_collection=DataCollection.SENTINEL2_L1C,
max_threads=self.max_threads,
single_scene=True,
mosaicking_order="leastCC"
)
eopatch = task.execute(bbox=self.bbox, time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, 'BANDS')]
is_data = eopatch[(FeatureType.MASK, 'dataMask')]
width, height = self.size
self.assertTrue(bands.shape == (1, height, width, 13))
self.assertTrue(is_data.shape == (1, height, width, 1))
self.assertTrue(len(eopatch.timestamp) == 1)
def test_S2L2A(self):
""" Download just SCL, without other bands
"""
task = SentinelHubInputTask(bands_feature=(FeatureType.DATA, 'BANDS'),
additional_data=[(FeatureType.MASK,
'dataMask')],
size=self.size,
maxcc=self.maxcc,
time_difference=self.time_difference,
data_source=DataSource.SENTINEL2_L2A,
max_threads=self.max_threads)
eopatch = task.execute(bbox=self.bbox,
time_interval=self.time_interval)
bands = eopatch[(FeatureType.DATA, 'BANDS')]
is_data = eopatch[(FeatureType.MASK, 'dataMask')]
self.assertTrue(
np.allclose(array_stats(bands), [0.0107, 0.0123, 0.0087]))
width, height = self.size
self.assertTrue(bands.shape == (4, height, width, 12))
self.assertTrue(is_data.shape == (4, height, width, 1))
self.assertTrue(len(eopatch.timestamp) == 4)