Handle more badpixels shapes

src/calng/agipd_gpu.py

@@ -151,14 +151,40 @@ class AgipdGpuRunner(base_gpu.BaseGpuRunner):
     def load_badpixels_map(self, badpixels_map):
         print(f"Loading bad pixels with shape: {badpixels_map.shape}")
         # will simply OR with already loaded, does not take into account which ones
-        # TODO: simple loading
         # TODO: allow configuring subset of bad pixels to care about
         # TODO: allow configuring value for masked pixels
         # TODO: inquire what "mask for double size pixels" means
         if len(badpixels_map.shape) == 3:
-            # BadPixelsFF is not per gain stage...
-            # TODO: broadcast?
-            ...
+            if badpixels_map.shape == (
+                self.pixels_y,
+                self.pixels_x,
+                self.constant_memory_cells,
+            ):
+                # BadPixelsFF is not per gain stage - broadcasting along gain dimension
+                self.badpixel_map_gpu |= cupy.asarray(
+                    np.broadcast_to(
+                        np.transpose(badpixels_map)[..., np.newaxis],
+                        self.gm_map_shape,
+                    ),
+                    dtype=np.uint32,
+                )
+            elif badpixels_map.shape == (
+                self.constant_memory_cells,
+                self.pixels_y,
+                self.pixels_x,
+            ):
+                # oh, can also be old bad pixels pc?
+                self.badpixel_map_gpu |= cupy.asarray(
+                    np.broadcast_to(
+                        np.transpose(badpixels_map, (0, 2, 1))[..., np.newaxis],
+                        self.gm_map_shape,
+                    ),
+                    dtype=np.uint32,
+                )
+            else:
+                raise ValueError(
+                    f"What in the world is this shape? {badpixels_map.shape}"
+                )
         else:
             self.badpixel_map_gpu |= cupy.asarray(
                 np.transpose(badpixels_map, (2, 1, 0, 3)), dtype=np.uint32
@@ -221,24 +247,24 @@ class BadPixelValues(enum.IntFlag):
 
     Straight from pycalibration's enum.py"""
 
-    OFFSET_OUT_OF_THRESHOLD = 0b000000000000000000001  # bit 1
-    NOISE_OUT_OF_THRESHOLD = 0b000000000000000000010  # bit 2
-    OFFSET_NOISE_EVAL_ERROR = 0b000000000000000000100  # bit 3
-    NO_DARK_DATA = 0b000000000000000001000  # bit 4
-    CI_GAIN_OF_OF_THRESHOLD = 0b000000000000000010000  # bit 5
-    CI_LINEAR_DEVIATION = 0b000000000000000100000  # bit 6
-    CI_EVAL_ERROR = 0b000000000000001000000  # bit 7
-    FF_GAIN_EVAL_ERROR = 0b000000000000010000000  # bit 8
-    FF_GAIN_DEVIATION = 0b000000000000100000000  # bit 9
-    FF_NO_ENTRIES = 0b000000000001000000000  # bit 10
-    CI2_EVAL_ERROR = 0b000000000010000000000  # bit 11
-    VALUE_IS_NAN = 0b000000000100000000000  # bit 12
-    VALUE_OUT_OF_RANGE = 0b000000001000000000000  # bit 13
-    GAIN_THRESHOLDING_ERROR = 0b000000010000000000000  # bit 14
-    DATA_STD_IS_ZERO = 0b000000100000000000000  # bit 15
-    ASIC_STD_BELOW_NOISE = 0b000001000000000000000  # bit 16
-    INTERPOLATED = 0b000010000000000000000  # bit 17
-    NOISY_ADC = 0b000100000000000000000  # bit 18
-    OVERSCAN = 0b001000000000000000000  # bit 19
-    NON_SENSITIVE = 0b010000000000000000000  # bit 20
-    NON_LIN_RESPONSE_REGION = 0b100000000000000000000  # bit 21
+    OFFSET_OUT_OF_THRESHOLD = 2 ** 0
+    NOISE_OUT_OF_THRESHOLD = 2 ** 1
+    OFFSET_NOISE_EVAL_ERROR = 2 ** 2
+    NO_DARK_DATA = 2 ** 3
+    CI_GAIN_OF_OF_THRESHOLD = 2 ** 4
+    CI_LINEAR_DEVIATION = 2 ** 5
+    CI_EVAL_ERROR = 2 ** 6
+    FF_GAIN_EVAL_ERROR = 2 ** 7
+    FF_GAIN_DEVIATION = 2 ** 8
+    FF_NO_ENTRIES = 2 ** 9
+    CI2_EVAL_ERROR = 2 ** 10
+    VALUE_IS_NAN = 2 ** 11
+    VALUE_OUT_OF_RANGE = 2 ** 12
+    GAIN_THRESHOLDING_ERROR = 2 ** 13
+    DATA_STD_IS_ZERO = 2 ** 14
+    ASIC_STD_BELOW_NOISE = 2 ** 15
+    INTERPOLATED = 2 ** 16
+    NOISY_ADC = 2 ** 17
+    OVERSCAN = 2 ** 18
+    NON_SENSITIVE = 2 ** 19
+    NON_LIN_RESPONSE_REGION = 2 ** 20