def test_reproject_spatial(self):
input = Pyramid({0: self.tiled_raster_rdd})
imagecollection = GeopysparkDataCube(pyramid=input,
metadata=self.collection_metadata)
ref_path = str(self.temp_folder / "reproj_ref.tiff")
imagecollection.reduce('max',
dimension="t").save_result(ref_path,
format="GTIFF")
resampled = imagecollection.resample_spatial(resolution=0,
projection="EPSG:3395",
method="max")
metadata = resampled.pyramid.levels[0].layer_metadata
print(metadata)
self.assertTrue("proj=merc" in metadata.crs)
path = str(self.temp_folder / "reprojected.tiff")
res = resampled.reduce('max', dimension="t")
res.save_result(path, format="GTIFF")
with rasterio.open(ref_path) as ref_ds:
with rasterio.open(path) as ds:
print(ds.profile)
#this reprojection does not change the shape, so we can compare
assert ds.read().shape == ref_ds.read().shape
assert (ds.crs.to_epsg() == 3395)
def test_reduce_nontemporal(self):
input = Pyramid({0: self.tiled_raster_rdd})
imagecollection = GeopysparkDataCube(pyramid=input,
metadata=self.collection_metadata)
with self.assertRaises(FeatureUnsupportedException) as context:
imagecollection.reduce(
"max", dimension="gender").pyramid.levels[0].stitch()
print(context.exception)
def test_aggregate_max_time(self):
input = Pyramid({0: self.tiled_raster_rdd})
imagecollection = GeopysparkDataCube(pyramid=input,
metadata=self.collection_metadata)
layer = imagecollection.reduce('max', dimension='t').pyramid.levels[0]
stitched = layer.stitch()
assert CellType.FLOAT32.value == layer.layer_metadata.cell_type
print(stitched)
self.assertEqual(2.0, stitched.cells[0][0][0])
def test_reduce_some_nodata(self):
no_data = -1.0
input = Pyramid({
0:
self._single_pixel_layer(
{
datetime.datetime.strptime("2016-04-24T04:00:00Z", '%Y-%m-%dT%H:%M:%SZ'):
no_data,
datetime.datetime.strptime("2017-04-24T04:00:00Z", '%Y-%m-%dT%H:%M:%SZ'):
5.0
}, no_data)
})
imagecollection = GeopysparkDataCube(pyramid=input,
metadata=self.collection_metadata)
stitched = imagecollection.reduce(
"min", dimension="t").pyramid.levels[0].stitch()
#print(stitched)
self.assertEqual(5.0, stitched.cells[0][0][0])
stitched = imagecollection.reduce(
"max", dimension="t").pyramid.levels[0].stitch()
self.assertEqual(5.0, stitched.cells[0][0][0])
stitched = imagecollection.reduce(
"sum", dimension="t").pyramid.levels[0].stitch()
self.assertEqual(5.0, stitched.cells[0][0][0])
stitched = imagecollection.reduce(
"mean", dimension="t").pyramid.levels[0].stitch()
self.assertAlmostEqual(5.0, stitched.cells[0][0][0], delta=0.001)
stitched = imagecollection.reduce(
"variance", dimension="t").pyramid.levels[0].stitch()
self.assertAlmostEqual(0.0, stitched.cells[0][0][0], delta=0.001)
stitched = imagecollection.reduce(
"sd", dimension="t").pyramid.levels[0].stitch()
self.assertAlmostEqual(0.0, stitched.cells[0][0][0], delta=0.001)