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import numpy as np
import astra
import astra.experimental
import math
import pytest
DISPLAY=False
def VolumeGeometries(is3D,noncube,singleslice):
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)
if singleslice:
yield astra.create_vol_geom(64, 64, 1, -32*sx, 32*sx, -32*sy, 32*sy, -0.5*sz, 0.5*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,shortscan,singleslice):
if type == 'parallel':
for dU in [0.8, 1.0, 1.25]:
yield astra.create_proj_geom('parallel', dU, 256, np.linspace(0,np.pi,180,False))
elif type == 'fanflat':
for dU in [0.8, 1.0, 1.25]:
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]:
if singleslice:
yield astra.create_proj_geom('parallel3d', dU, dV, 1, 128, np.linspace(0,np.pi,180,False))
else:
yield astra.create_proj_geom('parallel3d', dU, dV, 128, 128, np.linspace(0,np.pi,180,False))
elif type == 'parallel3d_vec':
for j in range(10):
Vectors = np.zeros([180,12])
wu = 0.6 + 0.8 * np.random.random()
wv = 0.6 + 0.8 * np.random.random()
for i in range(Vectors.shape[0]):
l = 0.6 + 0.8 * np.random.random()
angle1 = 2*np.pi*np.random.random()
angle2 = angle1 + 0.5 * np.random.random()
angle3 = 0.1*np.pi*np.random.random()
detc = 10 * np.random.random(size=3)
detu = [ math.cos(angle1) * wu, math.sin(angle1) * wu, 0 ]
detv = [ -math.sin(angle1) * math.sin(angle3) * wv, math.cos(angle1) * math.sin(angle3) * wv, math.cos(angle3) * wv ]
ray = [ math.sin(angle2) * l, -math.cos(angle2) * l, 0 ]
Vectors[i, :] = [ ray[0], ray[1], ray[2], detc[0], detc[1], detc[2], detu[0], detu[1], detu[2], detv[0], detv[1], detv[2] ]
pg = astra.create_proj_geom('parallel3d_vec', 128, 128, Vectors)
yield pg
elif type == 'cone':
A = [1.5, 2] if shortscan else [ 2 ]
for dU in [0.8, 1.0]:
for dV in [0.8, 1.0]:
for src in [500, 1000]:
for det in [0, 250]:
for a in A:
if singleslice:
yield astra.create_proj_geom('cone', dU, dV, 1, 128, np.linspace(0,a*np.pi,180,False), src, det)
else:
yield astra.create_proj_geom('cone', dU, dV, 128, 128, np.linspace(0,a*np.pi,180,False), src, det)
elif type == 'cone_vec':
for j in range(10):
Vectors = np.zeros([180,12])
wu = 0.6 + 0.8 * np.random.random()
wv = 0.6 + 0.8 * np.random.random()
for i in range(Vectors.shape[0]):
l = 256 * (0.5 * np.random.random())
angle1 = 2*np.pi*np.random.random()
angle2 = angle1 + 0.5 * np.random.random()
angle3 = 0.1*np.pi*np.random.random()
detc = 10 * np.random.random(size=3)
detu = [ math.cos(angle1) * wu, math.sin(angle1) * wu, 0 ]
detv = [ -math.sin(angle1) * math.sin(angle3) * wv, math.cos(angle1) * math.sin(angle3) * wv, math.cos(angle3) * wv ]
src = [ math.sin(angle2) * l, -math.cos(angle2) * l, 0 ]
Vectors[i, :] = [ src[0], src[1], src[2], detc[0], detc[1], detc[2], detu[0], detu[1], detu[2], detv[0], detv[1], detv[2] ]
pg = astra.create_proj_geom('parallel3d_vec', 128, 128, Vectors)
yield pg
@pytest.mark.slow
class TestRecScale:
def single_test(self, geom_type, proj_type, alg, iters, vss, dss):
if alg == 'FBP' and 'fanflat' in geom_type:
pytest.skip('CPU FBP is parallel-beam only')
is3D = (geom_type in ['parallel3d', 'cone'])
for vg in VolumeGeometries(is3D, 'FDK' not in alg, False):
for pg in ProjectionGeometries(geom_type, 'FDK' in alg, False):
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
options = {}
if vss > 1:
options["VoxelSuperSampling"] = vss
if dss > 1:
options["DetectorSuperSampling"] = vss
proj_id = astra.create_projector(proj_type, pg, vg, options=options)
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
cfg['ProjectionDataId'] = sino_id
cfg['ProjectorId'] = proj_id
if 'FDK' in alg and geom_type == "cone" and pg["ProjectionAngles"][-1] < 1.8*np.pi:
cfg['option'] = { 'ShortScan': True }
alg_id = astra.algorithm.create(cfg)
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])
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:
import pylab
print(geom_type, proj_type, alg, vg, pg)
print(val)
pylab.gray()
if not is3D:
pylab.imshow(rec)
else:
pylab.imshow(rec[:,32,:])
pylab.show()
assert abs(val-1.0) < TOL
def single_test_adjoint3D(self, geom_type, proj_type):
for vg in VolumeGeometries(True, True, 'vec' not in geom_type):
for pg in ProjectionGeometries(geom_type, False, vg['GridSliceCount'] == 1):
for i in range(5):
X = np.random.random(astra.geom_size(vg)).astype(np.float32)
Y = np.random.random(astra.geom_size(pg)).astype(np.float32)
projector_cfg = astra.astra_dict('cuda3d')
projector_cfg['ProjectionGeometry'] = pg
projector_cfg['VolumeGeometry'] = vg
if vg['GridSliceCount'] == 1:
projector_cfg['ProjectionKernel'] = '2d_weighting'
projector_id = astra.projector3d.create(projector_cfg)
fX = np.zeros(astra.geom_size(pg), dtype=np.float32)
astra.experimental.direct_FP3D(projector_id, X, fX)
fTY = np.zeros(astra.geom_size(vg), dtype=np.float32)
astra.experimental.direct_BP3D(projector_id, fTY, Y)
astra.projector3d.delete(projector_id)
da = np.dot(fX.ravel(), Y.ravel())
db = np.dot(X.ravel(), fTY.ravel())
m = np.abs(da - db)
TOL = 1e-1
if m / da >= TOL:
print(vg)
print(pg)
print(m/da, da/db, da, db)
assert m / da < TOL
__combinations = {
'parallel': [ 'line', 'linear', 'distance_driven', 'strip', 'cuda' ],
'fanflat': [ 'line_fanflat', 'strip_fanflat', 'cuda' ],
'parallel3d': [ 'cuda3d' ],
'cone': [ 'cuda3d' ],
}
__combinations_adjoint = {
'parallel3d': [ 'cuda3d' ],
'cone': [ 'cuda3d' ],
'parallel3d_vec': [ 'cuda3d' ],
'cone_vec': [ 'cuda3d' ],
}
__algs = {
'SIRT': 50, 'SART': 10*180, 'CGLS': 30,
'FBP': 1
}
__algs_CUDA = {
'SIRT_CUDA': 50, 'SART_CUDA': 10*180, 'CGLS_CUDA': 30, 'EM_CUDA': 50,
'FBP_CUDA': 1
}
__algs_parallel3d = {
'SIRT3D_CUDA': 200, 'CGLS3D_CUDA': 20,
}
__algs_cone = {
'SIRT3D_CUDA': 200, 'CGLS3D_CUDA': 20,
'FDK_CUDA': 1
}
__combinations_ss = {
'parallel': [ { 'projector': 'cuda', 'alg': 'SIRT_CUDA', 'iters': 50 } ],
'fanflat': [ { 'projector': 'cuda', 'alg': 'SIRT_CUDA', 'iters': 50 } ],
'parallel3d': [ { 'projector': 'cuda3d', 'alg': 'SIRT3D_CUDA', 'iters': 200 } ],
'cone': [ { 'projector': 'cuda3d', 'alg': 'SIRT3D_CUDA', 'iters': 200 } ]
}
for k, l in __combinations.items():
for v in l:
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, 1, 1)
setattr(TestRecScale, 'test_' + a + '_' + k + '_' + v, f(k,v,a,i))
for k, l in __combinations_adjoint.items():
for v in l:
def g(k, v):
return lambda self: self.single_test_adjoint3D(k, v)
setattr(TestRecScale, 'test_adjoint_' + k + '_' + v, g(k,v))
for k, l in __combinations_ss.items():
for A in l:
for vss in [1, 2]:
for dss in [1, 2]:
def h(k, v, a, i, vss, dss):
return lambda self: self.single_test(k, v, a, i, vss, dss)
setattr(TestRecScale, 'test_ss_' + a + '_' + k + '_' + v + '_' + str(vss) + '_' + str(dss), h(k, A['projector'], A['alg'], A['iters'], vss, dss))
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