def test_rct_stats(self):
"""Test the raster collection tile statistics UDF"""
dir = os.path.dirname(openeo_udf.functions.__file__)
file_name = os.path.join(dir, "raster_collections_statistics.py")
udf_code = UdfCode(language="python",
source=open(file_name, "r").read())
udf_data = PIXEL
udf_request = UdfRequest(data=udf_data, code=udf_code)
print(udf_request)
response = self.app.post('/udf',
data=json.dumps(udf_request),
content_type="application/json")
result = json.loads(response.data)
pprint.pprint(result)
self.assertEqual(len(result["feature_collection_tiles"]), 0)
self.assertEqual(len(result["raster_collection_tiles"]), 0)
self.assertEqual(len(result["structured_data_list"]), 1)
self.assertEqual(result["structured_data_list"][0]["type"], "dict")
self.assertEqual(result["structured_data_list"][0]["data"]["NIR"], {
'max': 9.0,
'mean': 6.0,
'min': 3.0,
'sum': 24.0
})
self.assertEqual(result["structured_data_list"][0]["data"]["RED"], {
'max': 10.0,
'mean': 7.0,
'min': 4.0,
'sum': 28.0
})
def test_buffer(self):
"""Test the feature collection buffering UDF"""
dir = os.path.dirname(openeo_udf.functions.__file__)
file_name = os.path.join(dir, "feature_collections_buffer.py")
udf_code = UdfCode(language="python",
source=open(file_name, "r").read())
udf_data = FEATURE
udf_request = UdfRequest(data=udf_data, code=udf_code)
print(udf_request)
response = self.app.post('/udf',
data=json.dumps(udf_request),
content_type="application/json")
result = json.loads(response.data)
pprint.pprint(result)
self.assertEqual(len(result["feature_collection_tiles"]), 1)
self.assertEqual(
len(result["feature_collection_tiles"][0]["data"]["features"]), 2)
self.assertEqual(
result["feature_collection_tiles"][0]["data"]["features"][0]
["properties"], {
'a': 1,
'b': 'a'
})
self.assertEqual(
result["feature_collection_tiles"][0]["data"]["features"][1]
["properties"], {
'a': 2,
'b': 'b'
})
def test_sampling(self):
"""Test the feature collection sampling UDF"""
dir = os.path.dirname(openeo_udf.functions.__file__)
file_name = os.path.join(dir, "raster_collections_sampling.py")
udf_code = UdfCode(language="python",
source=open(file_name, "r").read())
udf_data = PIXEL_FEATURE
udf_request = UdfRequest(data=udf_data, code=udf_code)
print(udf_request)
response = self.app.post('/udf',
data=json.dumps(udf_request),
content_type="application/json")
result = json.loads(response.data)
pprint.pprint(result)
self.assertEqual(len(result["feature_collection_tiles"]), 1)
self.assertEqual(
len(result["feature_collection_tiles"][0]["data"]["features"]), 3)
self.assertEqual(
result["feature_collection_tiles"][0]["data"]["features"][0]
["properties"], {
'NIR_0': 4,
'NIR_1': 6,
"NIR_2": 1,
"RED_0": 3,
"RED_1": 8
})
self.assertEqual(
result["feature_collection_tiles"][0]["data"]["features"][1]
["properties"], {
'NIR_0': 1,
'NIR_1': 8,
"NIR_2": 0,
"RED_0": 4,
"RED_1": 10
})
self.assertEqual(
result["feature_collection_tiles"][0]["data"]["features"][2]
["properties"], {
'NIR_0': None,
'NIR_1': None,
"NIR_2": None,
"RED_0": None,
"RED_1": None
})
def test_pytorch_linear_nn(self):
"""Test linear pytorch model training and UDF application"""
model = SimpleNetwork()
MachineLearningPytorchTestCase.train_pytorch_model(model=model)
dir = os.path.dirname(openeo_udf.functions.__file__)
file_name = os.path.join(dir, "raster_collections_pytorch_ml.py")
udf_code = UdfCode(language="python", source=open(file_name, "r").read())
udf_data = PIXEL
udf_request = UdfRequest(data=udf_data, code=udf_code)
response = self.app.post('/udf', data=json.dumps(udf_request), content_type="application/json")
result = json.loads(response.data)
pprint.pprint(result)
def test_hypercube_ndvi(self):
"""Test the hypercube NDVI computation"""
dir = os.path.dirname(openeo_udf.functions.__file__)
file_name = os.path.join(dir, "hypercube_ndvi.py")
udf_code = UdfCode(language="python", source=open(file_name, "r").read())
hc_red = create_hypercube(name="red", value=1, shape=(3, 3, 3))
hc_nir = create_hypercube(name="nir", value=3, shape=(3, 3, 3))
udf_data = UdfData(proj={"EPSG":4326}, hypercube_list=[hc_red, hc_nir])
udf_request = UdfRequest(data=udf_data.to_dict(), code=udf_code)
pprint.pprint(udf_request)
response = self.app.post('/udf', data=json.dumps(udf_request), content_type="application/json")
dict_data = json.loads(response.data)
pprint.pprint(dict_data)
self.checkHyperCube(dict_data=dict_data)
def test_hypercube_ndvi_message_pack(self):
"""Test the hypercube NDVI computation with the message pack protocol"""
dir = os.path.dirname(openeo_udf.functions.__file__)
file_name = os.path.join(dir, "hypercube_ndvi.py")
udf_code = UdfCode(language="python", source=open(file_name, "r").read())
hc_red = create_hypercube(name="red", value=1, shape=(3, 3, 3))
hc_nir = create_hypercube(name="nir", value=3, shape=(3, 3, 3))
udf_data = UdfData(proj={"EPSG":4326}, hypercube_list=[hc_red, hc_nir])
udf_request = UdfRequest(data=udf_data.to_dict(), code=udf_code)
# pprint.pprint(udf_request)
udf_request = base64.b64encode(msgpack.packb(udf_request, use_bin_type=True))
response = self.app.post('/udf_message_pack', data=udf_request, content_type="application/base64")
blob = base64.b64decode(response.data)
dict_data = msgpack.unpackb(blob, raw=False)
self.checkHyperCube(dict_data=dict_data)
def test_ndvi(self):
"""Test the time reduce sum UDF"""
dir = os.path.dirname(openeo_udf.functions.__file__)
file_name = os.path.join(dir, "raster_collections_ndvi.py")
udf_code = UdfCode(language="python",
source=open(file_name, "r").read())
udf_data = PIXEL
udf_request = UdfRequest(data=udf_data, code=udf_code)
print(udf_request)
response = self.app.post('/udf',
data=json.dumps(udf_request),
content_type="application/json")
result = json.loads(response.data)
pprint.pprint(result)
self.assertEqual(len(result["raster_collection_tiles"]), 1)
self.assertEqual(result["raster_collection_tiles"][0]["data"],
[[[-0.25, 0.0]], [[0.0, -0.1111111111111111]]])
def test_sklearn_extra_tree_message_pack(self):
"""Test extra tree training and UDF application"""
model = ExtraTreesRegressor(n_estimators=100,
max_depth=7,
max_features="log2",
min_samples_split=2,
min_samples_leaf=1,
verbose=0)
MachineLearningTestCase.train_sklearn_model(model=model)
dir = os.path.dirname(openeo_udf.functions.__file__)
file_name = os.path.join(dir, "raster_collections_sklearn_ml.py")
udf_code = UdfCode(language="python",
source=open(file_name, "r").read())
udf_data = PIXEL
udf_request = UdfRequest(data=udf_data, code=udf_code)
blob = base64.b64encode(msgpack.packb(udf_request, use_bin_type=True))
response = self.app.post('/udf_message_pack',
data=blob,
content_type="application/base64")
result = msgpack.unpackb(base64.b64decode(response.data), raw=False)
self.assertAlmostEqual(
result["raster_collection_tiles"][0]["data"][0][0][0], 3.0, 2)
self.assertAlmostEqual(
result["raster_collection_tiles"][0]["data"][1][0][0], 5.0, 2)
def test_sklearn_extra_tree(self):
"""Test extra tree training and UDF application"""
model = ExtraTreesRegressor(n_estimators=100,
max_depth=7,
max_features="log2",
min_samples_split=2,
min_samples_leaf=1,
verbose=0)
MachineLearningTestCase.train_sklearn_model(model=model)
dir = os.path.dirname(openeo_udf.functions.__file__)
file_name = os.path.join(dir, "raster_collections_sklearn_ml.py")
udf_code = UdfCode(language="python",
source=open(file_name, "r").read())
udf_data = PIXEL
udf_request = UdfRequest(data=udf_data, code=udf_code)
response = self.app.post('/udf',
data=json.dumps(udf_request),
content_type="application/json")
result = json.loads(response.data)
pprint.pprint(result)
self.assertAlmostEqual(
result["raster_collection_tiles"][0]["data"][0][0][0], 3.0, 2)
self.assertAlmostEqual(
result["raster_collection_tiles"][0]["data"][1][0][0], 5.0, 2)
def test_pixel_min_mean_max_sum(self):
"""Test the time reduce min, max, mean, sum UDF"""
dir = os.path.dirname(openeo_udf.functions.__file__)
file_name = os.path.join(
dir, "raster_collections_reduce_time_min_max_mean_sum.py")
udf_code = UdfCode(language="python",
source=open(file_name, "r").read())
udf_data = PIXEL
udf_request = UdfRequest(data=udf_data, code=udf_code)
print(udf_request)
response = self.app.post('/udf',
data=json.dumps(udf_request),
content_type="application/json")
result = json.loads(response.data)
pprint.pprint(result)
self.assertEqual(len(result["raster_collection_tiles"]), 8)
self.assertEqual(result["raster_collection_tiles"][0]["data"],
[[[5.0, 4.0]]])
self.assertEqual(result["raster_collection_tiles"][1]["data"],
[[[9.0, 10.0]]])
self.assertEqual(result["raster_collection_tiles"][2]["data"],
[[[14.0, 14.0]]])
self.assertEqual(result["raster_collection_tiles"][3]["data"],
[[[7.0, 7.0]]])
self.assertEqual(result["raster_collection_tiles"][4]["data"],
[[[3.0, 4.0]]])
self.assertEqual(result["raster_collection_tiles"][5]["data"],
[[[9.0, 8.0]]])
self.assertEqual(result["raster_collection_tiles"][6]["data"],
[[[12.0, 12.0]]])
self.assertEqual(result["raster_collection_tiles"][7]["data"],
[[[6.0, 6.0]]])
