remove unneeded replace_pixels_wrong_gain_badpixel

src/cal_tools/jungfraulib.py

@@ -211,50 +211,14 @@ def sort_runs_by_gain(
     return runs
 
 
-def replace_pixels_wrong_gain_badpixel(
-    gain_arr,
-    new_gain_value,
-    badpixel_map,
-    memory_cells,
-):
-    """Replace the gain value with the given new gain value for pixels
-    indicated as bad with WRONG_GAIN_VALUE bit.
-
-    Args:
-        gain_arr (ndarray): The raw gain array to be updated.
-        new_gain_value (int): The new gain value to replace the gain value
-            for the pixels with WRONG_GAIN_VALUE badpixel.
-        badpixel_map (ndarray): The badpixel map for a cell.
-        memory_cells (int): Number of memory cells for the processed detector.
-
-    Returns:
-        ndarray: The updated gain_arr
-    """
-    import numpy as np
-    from cal_tools.enums import BadPixels
-
-    # replace gain with WRONG_GAIN_VALUE pixels in the badpixel mask
-    wrong_gain_mask = BadPixels.WRONG_GAIN_VALUE.value
-
-    # Create a boolean mask to identify the elements that meet the condition
-    condition_mask = (badpixel_map[..., new_gain_value] & wrong_gain_mask) == wrong_gain_mask
-
-    if memory_cells == 1:
-        condition_mask = condition_mask[np.newaxis, :, :]  # gain_arr.shape = [1, 512, 1024]
-
-    gain_arr[condition_mask] = new_gain_value
-    return gain_arr
-
-
 def replace_pixels_gain_values(
     gain_arr,
     new_gain_value,
     wrong_gain_pixels,
     karabo_da,
-    badpixel_map,
-    memory_cells
 ):
     """Replace gain values with the chosen new gain value
+    for a single module.
 
     Args:
         gain_arr (ndarray): The raw gain array to be updated.
@@ -262,7 +226,6 @@ def replace_pixels_gain_values(
         wrong_gain_pixels (list): [module_index, row1, row12, col1, col2].
             e.g. [4, 0, 255, 896, 1024] for JNGFR04 slicing module [0:255, 896:1024].
         karabo_da (str): _description_
-        badpixel_map (ndarray): The badpixel map for one cell.
         memory_cells (int): Number of memory cells.
 
     Returns:
@@ -278,12 +241,4 @@ def replace_pixels_gain_values(
             gain_arr[:, x1:x2, y1:y2] = new_gain_value
             return gain_arr
         else:  # No gain replacement
-            return gain_arr
-
-    else: # replace gain with WRONG_GAIN_VALUE pixels in the badpixel mask
-        return replace_pixels_wrong_gain_badpixel(
-            gain_arr,
-            new_gain_value,
-            badpixel_map,
-            memory_cells,
-        )
\ No newline at end of file
+            return gain_arr
\ No newline at end of file

tests/test_jungfraulib.py

@@ -86,18 +86,6 @@ REPLACE_WRONG_GAIN_VALUE = 0
 WRONG_GAIN_PIXELS = [4, 0, 255, 896, 1024]
 
 
-def test_replace_pixels_wrong_gain_badpixel():
-    assert np.allclose(
-        NEW_GAIN,
-        replace_pixels_wrong_gain_badpixel(
-            gain_arr=GAIN,
-            new_gain_value=REPLACE_WRONG_GAIN_VALUE,
-            badpixel_map=BP,
-            memory_cells=MEM_CELLS,
-        )
-    )
-
-
 def test_replace_pixels_gain_values():
     assert np.allclose(
         NEW_GAIN,
@@ -106,8 +94,6 @@ def test_replace_pixels_gain_values():
             new_gain_value=REPLACE_WRONG_GAIN_VALUE,
             wrong_gain_pixels=WRONG_GAIN_PIXELS,
             karabo_da=KARABO_DA,
-            badpixel_map=BP,
-            memory_cells=MEM_CELLS,
         )
     )
     assert np.allclose(
@@ -117,8 +103,6 @@ def test_replace_pixels_gain_values():
             new_gain_value=REPLACE_WRONG_GAIN_VALUE,
             wrong_gain_pixels=WRONG_GAIN_PIXELS,
             karabo_da=KARABO_DA,
-            badpixel_map=BP,
-            memory_cells=MEM_CELLS,
         )
     )
     assert np.allclose(
@@ -128,7 +112,5 @@ def test_replace_pixels_gain_values():
             new_gain_value=REPLACE_WRONG_GAIN_VALUE,
             wrong_gain_pixels=WRONG_GAIN_PIXELS,
             karabo_da="JNGFR01",
-            badpixel_map=BP,
-            memory_cells=MEM_CELLS,
         )
     )