Fix stacking buffer shape issue

This add stacking preparation which checks data across all stacking sources and prepares accordingly stacking buffers.

This fixes #31 (closed)

The original stacking code tries to assign data to the stacking buffer. If this assignment raises the IndexError then the code reallocates buffer with proper shape. The issue related to the numpy array broadcasting. If the current train has only one frame due to the filtering, then all arrays in image.* broadcast to buffer from previous train with any shape. If the previous train has zero frames than data just throw away.

@hammerd

src/calng/ShmemTrainMatcher.py

@@ -510,6 +510,8 @@ class ShmemTrainMatcher(TrainMatcher.TrainMatcher):
         )
         self._maybe_update_stacking_buffers(
             stacking_data_shapes, fill_missed_data, new_sources_map)
+        for (new_source, key), msg in ignore_stacking.items():
+            self.log.WARN(f"Failed to stack {new_source}.{key}: {msg}")
 
         if self._thread_pool is None:
             for source, (data, timestamp) in sources.items():