Merge branch 'main' into iterative_reg

Author: dkazanc

httomolibgpu/prep/stripe.py

@@ -143,8 +143,8 @@ def remove_stripe_ti(
 
     _, _, dx_orig = data.shape
     if (dx_orig % 2) != 0:
-        # the horizontal detector size is odd, data needs to be padded/cropped, for now raising the error
-        raise ValueError("The horizontal detector size must be even")
+        # if the horizontal detector size is odd, the data needs to be padded
+        data = cp.pad(data, ((0, 0), (0, 0), (0, 1)), mode="edge")
 
     gamma = beta * ((1 - beta) / (1 + beta)) ** cp.abs(
         cp.fft.fftfreq(data.shape[-1]) * data.shape[-1]
@@ -154,7 +154,11 @@ def remove_stripe_ti(
     v = v - v[:, 0:1]
     v = cp.fft.irfft(cp.fft.rfft(v) * cp.fft.rfft(gamma)).astype(data.dtype)
     data[:] += v
-    return data
+    if (dx_orig % 2) != 0:
+        # unpad
+        return data[:, :, :-1]
+    else:
+        return data
 
 
 ######## Optimized version for Vo-all ring removal in tomopy########

tests/test_prep/test_stripe.py

@@ -34,6 +34,15 @@ def test_remove_stripe_ti_on_data(data, flats, darks):
     assert data_after_stripe_removal.dtype == np.float32
 
 
+@pytest.mark.parametrize("angles", [180, 181])
+@pytest.mark.parametrize("det_x", [11, 18])
+@pytest.mark.parametrize("det_y", [5, 7, 8])
+def test_remove_stripe_ti_dims_change(angles, det_y, det_x):
+    data = cp.random.random_sample(size=(angles, det_y, det_x)).astype(cp.float32) * 2.0
+    corrected_data = remove_stripe_ti(data.copy())
+    assert corrected_data.shape == (angles, det_y, det_x)
+
+
 def test_stripe_removal_sorting_cupy(data, flats, darks):
     # --- testing the CuPy port of TomoPy's implementation ---#
     data = normalize(data, flats, darks, cutoff=10, minus_log=True)