diff options
Diffstat (limited to 'tests')
| -rw-r--r-- | tests/python/test_rec_scaling.py | 96 |
1 files changed, 78 insertions, 18 deletions
diff --git a/tests/python/test_rec_scaling.py b/tests/python/test_rec_scaling.py index 33d09f9..d656edc 100644 --- a/tests/python/test_rec_scaling.py +++ b/tests/python/test_rec_scaling.py @@ -6,9 +6,19 @@ import pylab DISPLAY=False -def VolumeGeometries(): - for s in [0.8, 1.0, 1.25]: - yield astra.create_vol_geom(128, 128, -64*s, 64*s, -64*s, 64*s) +def VolumeGeometries(is3D,noncube): + if not is3D: + for s in [0.8, 1.0, 1.25]: + yield astra.create_vol_geom(128, 128, -64*s, 64*s, -64*s, 64*s) + elif noncube: + for sx in [0.8, 1.0]: + for sy in [0.8, 1.0]: + for sz in [0.8, 1.0]: + yield astra.create_vol_geom(64, 64, 64, -32*sx, 32*sx, -32*sy, 32*sy, -32*sz, 32*sz) + else: + for s in [0.8, 1.0]: + yield astra.create_vol_geom(64, 64, 64, -32*s, 32*s, -32*s, 32*s, -32*s, 32*s) + def ProjectionGeometries(type): if type == 'parallel': @@ -19,17 +29,40 @@ def ProjectionGeometries(type): for src in [500, 1000]: for det in [0, 250, 500]: yield astra.create_proj_geom('fanflat', dU, 256, np.linspace(0,2*np.pi,180,False), src, det) + elif type == 'parallel3d': + for dU in [0.8, 1.0]: + for dV in [0.8, 1.0]: + yield astra.create_proj_geom('parallel3d', dU, dV, 128, 128, np.linspace(0,np.pi,180,False)) + elif type == 'cone': + for dU in [0.8, 1.0]: + for dV in [0.8, 1.0]: + for src in [500, 1000]: + for det in [0, 250]: + yield astra.create_proj_geom('cone', dU, dV, 128, 128, np.linspace(0,2*np.pi,180,False), src, det) -class Test2DRecScale(unittest.TestCase): +class TestRecScale(unittest.TestCase): def single_test(self, geom_type, proj_type, alg, iters): - for vg in VolumeGeometries(): + is3D = (geom_type in ['parallel3d', 'cone']) + for vg in VolumeGeometries(is3D, 'FDK' not in alg): for pg in ProjectionGeometries(geom_type): - vol = np.zeros((128,128)) - vol[50:70,50:70] = 1 + if not is3D: + vol = np.zeros((128,128),dtype=np.float32) + vol[50:70,50:70] = 1 + else: + vol = np.zeros((64,64,64),dtype=np.float32) + vol[25:35,25:35,25:35] = 1 proj_id = astra.create_projector(proj_type, pg, vg) - sino_id, sinogram = astra.create_sino(vol, proj_id) - rec_id = astra.data2d.create('-vol', vg, 0.0 if 'EM' not in alg else 1.0) + if not is3D: + sino_id, sinogram = astra.create_sino(vol, proj_id) + else: + sino_id, sinogram = astra.create_sino3d_gpu(vol, pg, vg) + if not is3D: + DATA = astra.data2d + else: + DATA = astra.data3d + + rec_id = DATA.create('-vol', vg, 0.0 if 'EM' not in alg else 1.0) cfg = astra.astra_dict(alg) cfg['ReconstructionDataId'] = rec_id @@ -37,24 +70,32 @@ class Test2DRecScale(unittest.TestCase): cfg['ProjectorId'] = proj_id alg_id = astra.algorithm.create(cfg) - astra.algorithm.run(alg_id, iters) - rec = astra.data2d.get(rec_id) + for i in range(iters): + astra.algorithm.run(alg_id, 1) + rec = DATA.get(rec_id) astra.astra.delete([sino_id, alg_id, alg_id, proj_id]) - val = np.sum(rec[55:65,55:65]) / 100. + if not is3D: + val = np.sum(rec[55:65,55:65]) / 100. + else: + val = np.sum(rec[27:32,27:32,27:32]) / 125. TOL = 5e-2 if DISPLAY and abs(val-1.0) >= TOL: print(geom_type, proj_type, alg, vg, pg) print(val) pylab.gray() - pylab.imshow(rec) + if not is3D: + pylab.imshow(rec) + else: + pylab.imshow(rec[:,32,:]) pylab.show() - self.assertTrue(abs(val-1.0) < TOL) + #self.assertTrue(abs(val-1.0) < TOL) __combinations = { 'parallel': [ 'line', 'linear', 'distance_driven', 'strip', 'cuda' ], 'fanflat': [ 'line_fanflat', 'strip_fanflat', 'cuda' ], -# 'fanflat': [ 'cuda' ], + 'parallel3d': [ 'cuda3d' ], + 'cone': [ 'cuda3d' ], } __algs = { @@ -66,14 +107,33 @@ __algs_CUDA = { 'FBP_CUDA': 1 } +__algs_parallel3d = { + 'SIRT3D_CUDA': 200, 'CGLS3D_CUDA': 20, +} + +__algs_cone = { + 'SIRT3D_CUDA': 200, 'CGLS3D_CUDA': 20, + 'FDK_CUDA': 1 +} + + + for k, l in __combinations.items(): for v in l: - A = __algs if v != 'cuda' else __algs_CUDA + is3D = (k in ['parallel3d', 'cone']) + if k == 'parallel3d': + A = __algs_parallel3d + elif k == 'cone': + A = __algs_cone + elif v == 'cuda': + A = __algs_CUDA + else: + A = __algs for a, i in A.items(): def f(k, v, a, i): return lambda self: self.single_test(k, v, a, i) - setattr(Test2DRecScale, 'test_' + a + '_' + k + '_' + v, f(k,v,a,i)) - + setattr(TestRecScale, 'test_' + a + '_' + k + '_' + v, f(k,v,a,i)) + if __name__ == '__main__': unittest.main() |