Fix .ndarray(module_gaps=True) for xtdf detector data

extra_data/components.py

@@ -998,7 +998,8 @@ def ndarray(self, *, fill_value=None, out=None, roi=(), astype=None, module_gaps
             # dim in raw data (except AGIPD, where it is data/gain)
             roi = np.index_exp[:] + roi
 
-        for mod_ix, (modno, kd) in enumerate(sorted(self.modno_to_keydata.items())):
+        for i, (modno, kd) in enumerate(sorted(self.modno_to_keydata.items())):
+            mod_ix = (modno - self.det._modnos_start_at) if module_gaps else i
             for chunk in kd._data_chunks:
                 self._read_chunk(chunk, reading_view[mod_ix], roi)
 

extra_data/tests/test_components.py

@@ -149,7 +149,6 @@ def test_get_array_gap(mock_lpd_mini_gap_run):
     np.testing.assert_array_equal(arr[1, :, 0, 0, 0], [1, 2, 0, 3, 4])
 
 
-
 def test_get_array_roi(mock_fxe_raw_run):
     run = RunDirectory(mock_fxe_raw_run)
     det = LPD1M(run.select_trains(by_index[:3]))
@@ -168,6 +167,18 @@ def test_get_array_roi_dssc(mock_scs_run):
     assert arr.shape == (1, 128, 64, 5, 12)
 
 
+def test_ndarray_module_gaps(mock_fxe_raw_run):
+    run = RunDirectory(mock_fxe_raw_run)
+    det = LPD1M(run, modules=[2]).select_trains(np.s_[:3])
+    det_data = det['image.data']
+    assert det_data.shape == (1, 128 * 3, 256, 256)
+    assert det_data.ndarray().shape == (1, 128 * 3, 256, 256)
+
+    arr_w_gaps = det_data.ndarray(module_gaps=True, fill_value=7)
+    assert arr_w_gaps.shape == (16, 128 * 3, 256, 256)
+    assert arr_w_gaps[:, 0, 0, 0].tolist() == ([7] * 2) + [0] + ([7] * 13)
+
+
 def test_get_array_lpd_parallelgain(mock_lpd_parallelgain_run):
     run = RunDirectory(mock_lpd_parallelgain_run)
     det = LPD1M(run.select_trains(by_index[:2]), parallel_gain=True)