fix(std_daq): prevent division by zero in flat correction

tests/tests_devices/test_std_daq_live_processing.py

@@ -148,3 +148,25 @@ def test_std_daq_live_processing_apply_flat_dark_correction_with_dark(std_daq_li
     assert isinstance(corrected_image, np.ndarray)
     assert corrected_image.shape == (100, 100)
     assert np.all(corrected_image >= 0), "Corrected image should not have negative values"
+
+
+def test_std_daq_live_processing_apply_flat_correction_zero_division(std_daq_live_processing):
+
+    # Create a mock image
+    image = np.random.rand(100, 100) * 1000 + 10  # Scale to simulate a realistic image
+
+    # Set flat reference with epsilon values
+    flat = np.ones((100, 100)) * 2
+    std_daq_live_processing.references["flat_(100, 100)"] = flat
+
+    # Set dark reference to ones
+    dark = np.ones((100, 100)) * 2
+
+    std_daq_live_processing.references["dark_(100, 100)"] = dark
+
+    # Apply flat correction
+    corrected_image = std_daq_live_processing.apply_flat_dark_correction(image)
+    assert isinstance(corrected_image, np.ndarray)
+    assert corrected_image.shape == (100, 100)
+    assert np.all(corrected_image >= 0), "Corrected image should not have negative values"
+    assert np.any(corrected_image < np.inf), "Corrected image should not have infinite values"

tomcat_bec/devices/std_daq/std_daq_live_processing.py

@@ -121,7 +121,10 @@ class StdDaqLiveProcessing:
             corrected_data = data - dark
             return corrected_data
 
-        corrected_data = (data - dark) / (flat - dark)
+        # Ensure that the division does not lead to division by zero
+        corrected_data = np.divide(
+            data - dark, flat - dark, out=np.zeros_like(data), where=(flat - dark) != 0
+        )
         return corrected_data
 
     @typechecked