def test_zonal_statistics_median_datacube(self):
layer = self.create_spacetime_layer()
imagecollection = GeotrellisTimeSeriesImageCollection(gps.Pyramid({0: layer}), InMemoryServiceRegistry())
polygon = Polygon(shell=[
(0.0, 0.0),
(1.0, 0.0),
(1.0, 1.0),
(0.0, 1.0),
(0.0, 0.0)
])
result = imagecollection.zonal_statistics(polygon, "median")
assert result.data == {'2017-09-25T11:37:00Z': [[1.0, 2.0]]}
covjson = result.to_covjson()
assert covjson["ranges"] == {
"band0": {
"type": "NdArray", "dataType": "float", "axisNames": ["t", "composite"],
"shape": (1, 1),
"values": [1.0]
},
"band1": {
"type": "NdArray", "dataType": "float", "axisNames": ["t", "composite"],
"shape": (1, 1),
"values": [2.0]
}
}
def test_zonal_statistics_datacube(self):
layer = self.create_spacetime_layer()
imagecollection = GeotrellisTimeSeriesImageCollection(gps.Pyramid({0: layer}), InMemoryServiceRegistry())
polygon = Polygon(shell=[
(0.0, 0.0),
(1.0, 0.0),
(1.0, 1.0),
(0.0, 1.0),
(0.0, 0.0)
])
polygon2 = Polygon(shell=[
(2.0, 2.0),
(3.0, 2.0),
(3.0, 3.0),
(2.0, 3.0),
(2.0, 2.0)
])
regions = GeometryCollection([polygon, MultiPolygon([polygon2])])
for use_file in [True,False]:
with self.subTest():
if use_file:
with NamedTemporaryFile(delete=False,suffix='.json',mode='r+') as fp:
json.dump(mapping(regions),fp)
regions_serialized = fp.name
else:
regions_serialized = regions
result = imagecollection.zonal_statistics(regions_serialized, "mean")
assert result.data == {
'2017-09-25T11:37:00Z': [[1.0, 2.0], [1.0, 2.0]]
}
result._regions = regions
covjson = result.to_covjson()
assert covjson["ranges"] == {
"band0": {
"type": "NdArray", "dataType": "float", "axisNames": ["t", "composite"],
"shape": (1, 2),
"values": [1.0, 1.0]
},
"band1": {
"type": "NdArray", "dataType": "float", "axisNames": ["t", "composite"],
"shape": (1, 2),
"values": [2.0, 2.0]
},
}
def test_zonal_statistics_for_unsigned_byte_layer(self):
layer = self.create_spacetime_unsigned_byte_layer()
# layer.to_spatial_layer().save_stitched('/tmp/unsigned_byte_layer.tif')
imagecollection = GeotrellisTimeSeriesImageCollection(gps.Pyramid({0: layer}), InMemoryServiceRegistry())
polygon = Polygon(shell=[
(0.0, 0.0),
(2.0, 0.0),
(2.0, 4.0),
(0.0, 4.0),
(0.0, 0.0)
])
result = imagecollection.zonal_statistics(polygon, "mean")
# FIXME: the Python implementation doesn't return a time zone (Z)
assert result.data == {'2017-09-25T11:37:00': [[220.0]]}
covjson = result.to_covjson()
assert covjson["ranges"] == {
"band0": {
"type": "NdArray", "dataType": "float", "axisNames": ["t", "composite"],
"shape": (1, 1),
"values": [220.0]
}
}