def _test_aggregate_temporal(self, interval_list):
input = Pyramid({0: self.tiled_raster_rdd})
imagecollection = GeopysparkDataCube(pyramid=input,
metadata=self.collection_metadata)
stitched = (imagecollection.aggregate_temporal(
interval_list, ["2017-01-03"], "min",
dimension="t").pyramid.levels[0].to_spatial_layer().stitch())
print(stitched)
expected_max = np.min([self.tile2.cells, self.tile.cells], axis=0)
assert_array_almost_equal(stitched.cells[0, 0:5, 0:5], expected_max)
def test_aggregate_temporal_median(self):
input = Pyramid({0: self.tiled_raster_rdd})
imagecollection = GeopysparkDataCube(pyramid=input,
metadata=self.collection_metadata)
stitched = (imagecollection.aggregate_temporal(
["2015-01-01", "2018-01-01"], ["2017-01-03"],
self._median_reducer(),
dimension="t").pyramid.levels[0].to_spatial_layer().stitch())
print(stitched)
expected_median = np.median(
[self.tile.cells, self.tile2.cells, self.tile.cells], axis=0)
#TODO nodata handling??
assert_array_almost_equal(stitched.cells[0, 1:2, 1:2],
expected_median[1:2, 1:2])