finally things work
@@ -476,28 +476,23 @@ class NetCDFtoZarrRecipe(BaseRecipe):
# also return the conflicts with other chunks
input_keys = self.inputs_for_chunk(chunk_key)
+
+ # TODO: refactor into a separate method
if self.nitems_per_input:
- stride = self.nitems_per_input * self.inputs_per_chunk
- start = self.chunk_position(chunk_key) * stride
- stop = start + stride
input_sequence_lens = (self.nitems_per_input,) * self._n_inputs_along_sequence
else:
input_sequence_lens = json.loads(
self.metadata_cache.get_mapper()[_GLOBAL_METADATA_KEY]
)["input_sequence_lens"]
- start = sum(input_sequence_lens[: self.input_position(input_keys[0])])
- chunk_len = sum([input_sequence_lens[self.input_position(k)] for k in input_keys])
- stop = start + chunk_len
chunk_bounds, all_chunk_conflicts = chunk_bounds_and_conflicts(
input_sequence_lens, self._sequence_dim_chunks
)
- computed_bounds = (
- chunk_bounds[self.input_position(input_keys[0])],
- chunk_bounds[self.input_position(input_keys[-1]) + 1],
- )
- print(chunk_key, (start, stop), computed_bounds)
- # assert (start, stop) == computed_bounds, "Consistency check for region bounds"
+ # for multi-variable recipes, there is something redunandt about this
+ # logic that feels error prone
+ start = chunk_bounds[self.input_position(input_keys[0])]
+ stop = chunk_bounds[self.input_position(input_keys[-1]) + 1]
+
this_chunk_conflicts = set()
for k in input_keys:
# for multi-variable recipes, the confilcts will usually be the same
