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Diffstat (limited to 'tests/python/test_line2d.py')
| -rw-r--r-- | tests/python/test_line2d.py | 16 |
1 files changed, 4 insertions, 12 deletions
diff --git a/tests/python/test_line2d.py b/tests/python/test_line2d.py index 755bd27..5647053 100644 --- a/tests/python/test_line2d.py +++ b/tests/python/test_line2d.py @@ -486,17 +486,9 @@ class Test2DKernel(unittest.TestCase): for i, (center, edge1, edge2) in enumerate(gen_lines(pg)): (src, det) = center (xd, yd) = det - src - try: - detweight = pg['DetectorWidth'] - except KeyError: - if 'fan' not in type: - detweight = effective_detweight(src, det, pg['Vectors'][i//pg['DetectorCount'],4:6]) - else: - detweight = np.linalg.norm(pg['Vectors'][i//pg['DetectorCount'],4:6], ord=2) - l = 0.0 if np.abs(xd) > np.abs(yd): # horizontal ray - length = math.sqrt(1.0 + abs(yd/xd)**2) + length = math.sqrt(1.0 + abs(yd/xd)**2) * pixsize[0] y_seg = (ymin, ymax) for j in range(rect_min[0], rect_max[0]): x = origin[0] + (-0.5 * shape[0] + j + 0.5) * pixsize[0] @@ -504,9 +496,9 @@ class Test2DKernel(unittest.TestCase): # limited interpolation precision with cuda if CUDA_8BIT_LINEAR and proj_type == 'cuda': w = np.round(w * 256.0) / 256.0 - l += w * length * pixsize[0] * detweight + l += w * length else: - length = math.sqrt(1.0 + abs(xd/yd)**2) + length = math.sqrt(1.0 + abs(xd/yd)**2) * pixsize[1] x_seg = (xmin, xmax) for j in range(rect_min[1], rect_max[1]): y = origin[1] + (+0.5 * shape[1] - j - 0.5) * pixsize[1] @@ -514,7 +506,7 @@ class Test2DKernel(unittest.TestCase): # limited interpolation precision with cuda if CUDA_8BIT_LINEAR and proj_type == 'cuda': w = np.round(w * 256.0) / 256.0 - l += w * length * pixsize[1] * detweight + l += w * length a[i] = l a = a.reshape(astra.functions.geom_size(pg)) if not np.all(np.isfinite(a)): |