Merge pull request #235 from DiamondLightSource/detautopadfix

Detector autopad fix

Author: dkazanc

httomolibgpu/recon/algorithm.py

@@ -680,5 +680,5 @@ def _take_neg_log_np(data: np.ndarray) -> np.ndarray:
 def __estimate_detectorHoriz_padding(detX_size) -> int:
     det_half = detX_size // 2
     padded_value_exact = int(np.sqrt(2 * (det_half**2))) - det_half
-    padded_add_margin = int(0.1 * padded_value_exact)
+    padded_add_margin = padded_value_exact // 2
     return padded_value_exact + padded_add_margin

tests/test_recon/test_algorithm.py

@@ -168,9 +168,9 @@ def test_reconstruct_FBP3d_tomobar_3_detpad_true(
     )
 
     recon_data = recon_data.get()
-    assert_allclose(np.mean(recon_data), -0.00035695144, atol=1e-6)
+    assert_allclose(np.mean(recon_data), -0.00041842036, atol=1e-6)
     assert_allclose(
-        np.mean(recon_data, axis=(0, 2)).sum(), -0.045689818, rtol=1e-06, atol=1e-5
+        np.mean(recon_data, axis=(0, 2)).sum(), -0.05355779, rtol=1e-06, atol=1e-5
     )
     assert recon_data.dtype == np.float32
     assert recon_data.shape == (210, 128, 210)
@@ -257,8 +257,8 @@ def test_reconstruct_CGLS3d_tomobar_detpad_true(
     )
     assert recon_data.flags.c_contiguous
     recon_data = recon_data.get()
-    assert_allclose(np.mean(recon_data), 0.0021554278, rtol=1e-07, atol=1e-6)
-    assert_allclose(np.mean(recon_data, axis=(0, 2)).sum(), 0.27589476, rtol=1e-03)
+    assert_allclose(np.mean(recon_data), 0.0021257945, rtol=1e-07, atol=1e-6)
+    assert_allclose(np.mean(recon_data, axis=(0, 2)).sum(), 0.27210176, rtol=1e-03)
     assert recon_data.dtype == np.float32
 
 
@@ -306,8 +306,8 @@ def test_reconstruct_FISTA3d_tomobar_pd_tv_detpad_true(
     )
     assert recon_data.flags.c_contiguous
     recon_data = cp.asnumpy(recon_data)
-    assert_allclose(np.mean(recon_data), 0.0018338546, rtol=1e-07, atol=1e-6)
-    assert_allclose(np.mean(recon_data, axis=(0, 2)).sum(), 0.23473345, rtol=1e-04)
+    assert_allclose(np.mean(recon_data), 0.00183313, rtol=1e-07, atol=1e-6)
+    assert_allclose(np.mean(recon_data, axis=(0, 2)).sum(), 0.23464072, rtol=1e-04)
     assert recon_data.dtype == np.float32
 
 

zenodo-tests/test_recon/test_algorithm.py

@@ -125,7 +125,7 @@ def test_reconstruct_FBP3d_tomobar_i12_dataset1_autopad(i12_dataset1: tuple):
     )
     assert recon_data.flags.c_contiguous
     recon_data = recon_data.get()
-    assert_allclose(np.sum(recon_data), 6669.1274, rtol=1e-07, atol=1e-6)
+    assert_allclose(np.sum(recon_data), 7208.2295, rtol=1e-07, atol=1e-6)
     assert recon_data.dtype == np.float32
     assert recon_data.shape == (2560, 5, 2560)
 
@@ -517,6 +517,6 @@ def test_reconstruct_FISTA3d_tomobar_autopad_k11_dataset2(k11_dataset2: tuple):
     )
     assert recon_data.flags.c_contiguous
     recon_data = recon_data.get()
-    assert isclose(np.sum(recon_data), 1518.5251, abs_tol=10**-3)
+    assert isclose(np.sum(recon_data), 1355.4624, abs_tol=10**-3)
     assert recon_data.dtype == np.float32
     assert recon_data.shape == (2560, 5, 2560)