test(live_processing): change test mode to something more unlikely to be implemented

tests/tests_devices/test_std_daq_live_processing.py

@@ -53,7 +53,7 @@ def test_std_daq_live_processing_set_mode(std_daq_live_processing):
     std_daq_live_processing.set_mode("sum")
     assert std_daq_live_processing.get_mode() == "sum"
     with pytest.raises(TypeCheckError):
-        std_daq_live_processing.set_mode("average")
+        std_daq_live_processing.set_mode("mode_that_does_not_exist")
     with pytest.raises(TypeCheckError):
         std_daq_live_processing.set_mode(123)
 

tomcat_bec/devices/std_daq/std_daq_live_processing.py

@@ -45,14 +45,14 @@ class StdDaqLiveProcessing:
         return self._mode
 
     @typechecked
-    def set_mode(self, mode: Literal["sum"]):
+    def set_mode(self, mode: Literal["sum", "average"]):
         """
         Set the processing mode.
         Args:
-            mode (str): Processing mode, currently only "sum" is supported.
+            mode (str): Processing mode, currently only "sum" and "average" are supported.
         """
-        if mode not in ["sum"]:
-            raise ValueError("Unsupported mode. Only 'sum' is currently supported.")
+        if mode not in ["sum", "average"]:
+            raise ValueError("Unsupported mode. Only 'sum' and 'average' are currently supported.")
         self._mode = mode
 
     def set_enabled(self, value: bool):
@@ -83,6 +83,8 @@ class StdDaqLiveProcessing:
         match self._mode:
             case "sum":
                 self.process_sum(data)
+            case "average":
+                self.process_average(data)
             case _:
                 raise ValueError(f"Unknown mode: {self._mode}")
 
@@ -98,6 +100,18 @@ class StdDaqLiveProcessing:
         summed_data = np.sum(np.sum(data))
         self.signal.put(summed_data)
 
+    def process_average(self, data: np.ndarray):
+        """
+        Process data by averaging it.
+        Args:
+            data (np.ndarray): Data to average.
+        """
+        if not isinstance(data, np.ndarray):
+            raise ValueError("Data must be a numpy array.")
+
+        averaged_data = np.mean(data)
+        self.signal.put(averaged_data)
+
     ########################################
     ## Flat and Dark Field References ######
     ########################################