Hopefully better handling of empty DAQ hashes

src/calng/base_correction.py

@@ -928,36 +928,30 @@ class BaseCorrection(PythonDevice):
             elif not data_hash.has(self._image_data_path):
                 self.log_status_info("Ignoring hash without image node")
                 return
-
-            train_id = metadata.getAttribute("timestamp", "tid")
-            self._train_ratio_tracker.update(train_id)
-            cell_table = data_hash.get(self._cell_table_path)
-            if (
-                isinstance(cell_table, np.ndarray)
-                and (len(cell_table.shape) == 0 or cell_table.size == 0)
-            ) or len(cell_table) == 0:
-                self.log_status_warn("Empty cell table, DAQ probably not sending data.")
+            elif len(self.input_data_shape) != len(data_hash.get(f"{self._image_data_path}.shape")):
+                self.log_status_info("DAQ probably not sending data")
                 return
 
-            cell_table = np.ravel(cell_table)
-
             # no more common reasons to skip input, so go to processing
             if state is State.ON:
                 self.updateState(State.PROCESSING)
                 self.log_status_info("Processing data")
 
-            correction_cell_num = self.unsafe_get("constantParameters.memoryCells")
-            cell_table_max = np.max(cell_table)
+            train_id = metadata.getAttribute("timestamp", "tid")
+            self._train_ratio_tracker.update(train_id)
+            cell_table = data_hash.get(self._cell_table_path).ravel()
+
+            if self.unsafe_get("constantParameters.memoryCells") <= cell_table.max():
+                self.log_status_warn("Input cell IDs out of range of constants")
 
-            image_data = data_hash.get(self._image_data_path)
             if cell_table.size != self.unsafe_get("dataFormat.memoryCells"):
                 self.log_status_info(
-                    f"Updating new input shape {image_data.shape}, updating buffers"
+                    f"Updating new input shape to account for {cell_table.size} cells"
                 )
                 self.set("dataFormat.memoryCells", cell_table.size)
-                with self._buffer_lock:
-                    self._update_frame_filter()
+                self._lock_and_update_in_background(self._update_frame_filter)
 
+            image_data = data_hash.get(self._image_data_path)
             # DataAggregator typically tells us the wrong axis order
             if self.unsafe_get("dataFormat.overrideInputAxisOrder"):
                 expected_shape = self.input_data_shape
@@ -986,7 +980,6 @@ class BaseCorrection(PythonDevice):
             self._rate_tracker.update()
 
     def _update_rate_and_state(self):
-
         if self.get("state") is State.PROCESSING:
             self._buffered_status_update.set(
                 "performance.rate", self._rate_tracker.get()