def subtest_render_mixed_json_to_layer_chunk(self, obj, chunk_size=100, empty_chunk=None):
with self.subTest(chunk_size=chunk_size):
layer = self.new_layer()
o = dict(obj)
obj_feat = obj["features"]
lst_map_feat = list()
map_fields = dict()
lst_chunk: list = [obj_feat[i0:i0+chunk_size]
for i0 in range(0,len(obj_feat), chunk_size)]
if empty_chunk:
step = max(2,len(lst_chunk)//empty_chunk)
for i in reversed(range(0, len(lst_chunk), step)):
lst_chunk.insert(i, list())
for chunk in lst_chunk:
o["features"] = chunk
map_feat, _ = parser.xyz_json_to_feature_map(o, map_fields)
test_parser.TestParser()._assert_parsed_map(chunk, map_feat, map_fields)
lst_map_feat.append(map_feat)
self._render_layer(layer, map_feat, map_fields)
# self._log_debug("len feat", len(chunk))
# self._log_debug("parsed feat", len_of_struct(map_feat))
# self._log_debug("parsed fields", len_of_struct(map_fields))
lst_feat = flatten([x.values() for x in lst_map_feat])
self.assertEqual(len(lst_feat), len(obj["features"]))
self.assert_layer(layer, obj, map_fields)
self.remove_layer(layer)
return map_fields
def subtest_parse_xyzjson_map_chunk(self, obj, chunk_size=100):
similarity_threshold = self.similarity_threshold
with self.subTest(chunk_size=chunk_size,
similarity_threshold=similarity_threshold):
o = dict(obj)
obj_feat = obj["features"]
lst_map_feat = list()
map_fields = dict()
for i0 in range(0, len(obj_feat), chunk_size):
chunk = obj_feat[i0:i0 + chunk_size]
o["features"] = chunk
map_feat, _ = parser.xyz_json_to_feature_map(
o, map_fields, similarity_threshold)
self._assert_parsed_map(chunk, map_feat, map_fields)
lst_map_feat.append(map_feat)
# self._log_debug("len feat", len(chunk))
# self._log_debug("parsed feat", len_of_struct(map_feat))
# self._log_debug("parsed fields", len_of_struct(map_fields))
lst_feat = flatten([x.values() for x in lst_map_feat])
self.assertEqual(len(lst_feat), len(obj["features"]))
return map_fields