def test_min_time(self):
input = Pyramid({0: self.tiled_raster_rdd})
cube = GeopysparkDataCube(pyramid=input,
metadata=self.collection_metadata)
env = EvalEnv()
min_time = cube.reduce_dimension(reducer=reducer('min'),
dimension='t',
env=env)
max_time = cube.reduce_dimension(reducer=reducer('max'),
dimension='t',
env=env)
stitched = min_time.pyramid.levels[0].stitch()
print(stitched)
self.assertEquals(2.0, stitched.cells[0][0][0])
for p in self.points[1:3]:
result = min_time.timeseries(p.x, p.y, srs="EPSG:3857")
print(result)
print(cube.timeseries(p.x, p.y, srs="EPSG:3857"))
max_result = max_time.timeseries(p.x, p.y, srs="EPSG:3857")
self.assertEqual(1.0, result['NoDate'])
self.assertEqual(2.0, max_result['NoDate'])
def test_reduce_bands():
input = create_spacetime_layer()
input = gps.Pyramid({0: input})
collection_metadata = GeopysparkCubeMetadata({
"cube:dimensions": {
"my_bands": {
"type": "bands",
"values": ["B04", "B08"]
},
}
})
imagecollection = GeopysparkDataCube(pyramid=input,
metadata=collection_metadata)
visitor = GeotrellisTileProcessGraphVisitor()
graph = {
"sum": {
"arguments": {
"data": {
"from_argument": "dimension_data"
},
"ignore_nodata": True
},
"process_id": "sum"
},
"subtract": {
"arguments": {
"data": {
"from_argument": "dimension_data"
}
},
"process_id": "subtract"
},
"divide": {
"arguments": {
"data": [{
"from_node": "sum"
}, {
"from_node": "subtract"
}]
},
"process_id": "divide",
"result": True
}
}
visitor.accept_process_graph(graph)
stitched = imagecollection.reduce_dimension(
dimension='my_bands', reducer=visitor,
env=EvalEnv()).pyramid.levels[0].to_spatial_layer().stitch()
print(stitched)
assert 3.0 == stitched.cells[0][0][0]
def test_reduce(self):
input = Pyramid({0: self.tiled_raster_rdd})
cube = GeopysparkDataCube(pyramid=input,
metadata=self.collection_metadata)
env = EvalEnv()
stitched = cube.reduce_dimension(dimension="t",
reducer=reducer("max"),
env=env).pyramid.levels[0].stitch()
print(stitched)
self.assertEqual(2.0, stitched.cells[0][0][0])
self.assertEqual(2.0, stitched.cells[0][0][1])
stitched = cube.reduce_dimension(dimension="t",
reducer=reducer("min"),
env=env).pyramid.levels[0].stitch()
print(stitched)
self.assertEqual(2.0, stitched.cells[0][0][0])
self.assertEqual(1.0, stitched.cells[0][0][1])
stitched = cube.reduce_dimension(dimension="t",
reducer=reducer("sum"),
env=env).pyramid.levels[0].stitch()
print(stitched)
self.assertEqual(2.0, stitched.cells[0][0][0])
self.assertEqual(4.0, stitched.cells[0][0][1])
stitched = cube.reduce_dimension(dimension="t",
reducer=reducer("mean"),
env=env).pyramid.levels[0].stitch()
print(stitched)
self.assertEqual(2.0, stitched.cells[0][0][0])
self.assertAlmostEqual(1.3333333, stitched.cells[0][0][1])
stitched = cube.reduce_dimension(reducer=reducer("variance"),
dimension="t",
env=env).pyramid.levels[0].stitch()
print(stitched)
self.assertEqual(0.0, stitched.cells[0][0][0])
self.assertAlmostEqual(0.2222222, stitched.cells[0][0][1])
stitched = cube.reduce_dimension(reducer=reducer("sd"),
dimension="t",
env=env).pyramid.levels[0].stitch()
print(stitched)
self.assertEqual(0.0, stitched.cells[0][0][0])
self.assertAlmostEqual(0.4714045, stitched.cells[0][0][1])
def test_reduce_all_data(self):
input = Pyramid({
0:
self._single_pixel_layer({
datetime.datetime.strptime("2016-04-24T04:00:00Z", '%Y-%m-%dT%H:%M:%SZ'):
1.0,
datetime.datetime.strptime("2017-04-24T04:00:00Z", '%Y-%m-%dT%H:%M:%SZ'):
5.0
})
})
cube = GeopysparkDataCube(pyramid=input,
metadata=self.collection_metadata)
env = EvalEnv()
stitched = cube.reduce_dimension(reducer=reducer("min"),
dimension="t",
env=env).pyramid.levels[0].stitch()
self.assertEqual(1.0, stitched.cells[0][0][0])
stitched = cube.reduce_dimension(reducer=reducer("max"),
dimension="t",
env=env).pyramid.levels[0].stitch()
self.assertEqual(5.0, stitched.cells[0][0][0])
stitched = cube.reduce_dimension(reducer=reducer("sum"),
dimension="t",
env=env).pyramid.levels[0].stitch()
self.assertEqual(6.0, stitched.cells[0][0][0])
stitched = cube.reduce_dimension(reducer=reducer("mean"),
dimension="t",
env=env).pyramid.levels[0].stitch()
self.assertAlmostEqual(3.0, stitched.cells[0][0][0], delta=0.001)
stitched = cube.reduce_dimension(reducer=reducer("variance"),
dimension="t",
env=env).pyramid.levels[0].stitch()
self.assertAlmostEqual(4.0, stitched.cells[0][0][0], delta=0.001)
stitched = cube.reduce_dimension(reducer=reducer("sd"),
dimension="t",
env=env).pyramid.levels[0].stitch()
self.assertAlmostEqual(2.0, stitched.cells[0][0][0], delta=0.001)