def test_3d_backprop_real():
"""
Check if the real reconstruction matches the real part
of the complex reconstruction.
"""
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
parameters = get_test_parameter_set(2)
# complex
r = list()
for p in parameters:
f = odtbrain.backpropagate_3d(sino,
angles,
padval=0,
dtype=np.float64,
onlyreal=False,
**p)
r.append(f)
# real
r2 = list()
for p in parameters:
f = odtbrain.backpropagate_3d(sino,
angles,
padval=0,
dtype=np.float64,
onlyreal=True,
**p)
r2.append(f)
assert np.allclose(np.array(r).real, np.array(r2))
def test_angle_offset():
"""
Tests if things are still correct when there is a 2PI offset in the angles.
"""
sino, angles = create_test_sino_2d()
parameters = get_test_parameter_set(2)
# reference
r1 = []
for p in parameters:
f1 = odtbrain.backpropagate_2d(sino, angles, weight_angles=False, **p)
r1.append(f1)
# with offset
angles[::2] += 2*np.pi*np.arange(angles[::2].shape[0])
r2 = []
for p in parameters:
f2 = odtbrain.backpropagate_2d(sino, angles, weight_angles=False, **p)
r2.append(f2)
# with offset and weights
r3 = []
for p in parameters:
f3 = odtbrain.backpropagate_2d(sino, angles, weight_angles=True, **p)
r3.append(f3)
assert np.allclose(np.array(r1).flatten().view(float),
np.array(r2).flatten().view(float))
assert np.allclose(np.array(r2).flatten().view(float),
np.array(r3).flatten().view(float))
def test_angle_swap():
"""
Test if everything still works, when angles are swapped.
"""
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_2d()
# remove elements so that we can see that weighting works
angles = angles[:-2]
sino = sino[:-2,:]
parameters = get_test_parameter_set(2)
# reference
r1 = []
for p in parameters:
f1 = odtbrain._Back_2D.backpropagate_2d(sino, angles, weight_angles=True, **p)
r1.append(f1)
# change order of angles
order = np.argsort(angles % .5)
angles = angles[order]
sino = sino[order,:]
r2 = []
for p in parameters:
f2 = odtbrain._Back_2D.backpropagate_2d(sino, angles, weight_angles=True, **p)
r2.append(f2)
assert np.allclose(np.array(r1).flatten().view(float),
np.array(r2).flatten().view(float))
def test_back3d_tilted():
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
parameters = get_test_parameter_set(2)
# complex
r = list()
for p in parameters:
f = odtbrain.backpropagate_3d_tilted(sino,
angles,
padval=0,
dtype=np.float64,
save_memory=False,
**p)
r.append(f)
# real
r2 = list()
for p in parameters:
f = odtbrain.backpropagate_3d_tilted(sino,
angles,
padval=0,
dtype=np.float64,
save_memory=True,
**p)
r2.append(f)
assert np.allclose(np.array(r), np.array(r2))
def test_3d_backprop_real():
"""
Check if the real reconstruction matches the real part
of the complex reconstruction.
"""
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
parameters = get_test_parameter_set(2)
# complex
r = list()
for p in parameters:
f = odtbrain._Back_3D.backpropagate_3d(sino, angles, padval=0,
dtype=np.float64,
onlyreal=False, **p)
r.append(f)
# real
r2 = list()
for p in parameters:
f = odtbrain._Back_3D.backpropagate_3d(sino, angles, padval=0,
dtype=np.float64,
onlyreal=True, **p)
r2.append(f)
assert np.allclose(np.array(r).real, np.array(r2))
def test_correct_reproduce():
myframe = sys._getframe()
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
p = get_test_parameter_set(1)[0]
sryt = odtbrain.sinogram_as_rytov(uSin=sino, u0=1, align=False)
f = odtbrain.backpropagate_3d(sryt,
angles,
padval=0,
dtype=np.float64,
copy=False,
**p)
fc = odtbrain.apple.correct(f=f,
res=p["res"],
nm=p["nm"],
enforce_envelope=.95,
max_iter=100,
min_diff=0.01)
fo = cutout(fc)
fo = np.array(fo, dtype=np.complex128)
if WRITE_RES:
write_results(myframe, fo)
data = fo.flatten().view(float)
assert np.allclose(data, get_results(myframe))
def test_3d_backprop_plane_alignment_along_axes():
"""
Tests whether the reconstruction is always aligned with
the rotational axis (and not antiparallel).
"""
parameters = get_test_parameter_set(1)
p = parameters[0]
results = []
# These are specially selected angles that don't give high results.
# Probably due to phase-wrapping, errors >2 may appear. Hence, we
# call it a soft test.
tilts = [0, np.pi/2, np.pi, 3*np.pi/2, 2*np.pi]
for angz in tilts:
sino, angles = create_test_sino_3d_tilted(tilt_plane=angz, A=21)
rotmat = np.array([
[np.cos(angz), -np.sin(angz), 0],
[np.sin(angz), np.cos(angz), 0],
[0, 0, 1],
])
# rotate `tilted_axis` onto the y-z plane.
tilted_axis = np.dot(rotmat, [0, 1, 0])
fref = odtbrain.backpropagate_3d_tilted(sino, angles,
padval="edge",
tilted_axis=tilted_axis,
padding=(False, False),
dtype=np.float64,
onlyreal=True,
**p)
results.append(fref)
for ii in np.arange(len(results)):
assert np.allclose(results[ii], results[ii-1], atol=.2, rtol=.2)
def test_angle_offset():
"""
Tests if things are still correct when there is a 2PI offset in the angles.
"""
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_2d()
parameters = get_test_parameter_set(2)
# reference
r1 = []
for p in parameters:
f1 = odtbrain._Back_2D.backpropagate_2d(sino, angles, weight_angles=False, **p)
r1.append(f1)
# with offset
angles[::2] += 2*np.pi*np.arange(angles[::2].shape[0])
r2 = []
for p in parameters:
f2 = odtbrain._Back_2D.backpropagate_2d(sino, angles, weight_angles=False, **p)
r2.append(f2)
# with offset and weights
r3 = []
for p in parameters:
f3 = odtbrain._Back_2D.backpropagate_2d(sino, angles, weight_angles=True, **p)
r3.append(f3)
assert np.allclose(np.array(r1).flatten().view(float),
np.array(r2).flatten().view(float))
assert np.allclose(np.array(r2).flatten().view(float),
np.array(r3).flatten().view(float))
def test_2d_backprop_full():
myframe = sys._getframe()
sino, angles = create_test_sino_2d(ampl_range=(0.9, 1.1))
parameters = get_test_parameter_set(2)
r = list()
for p in parameters:
f = odtbrain.backpropagate_2d(sino, angles, **p)
r.append(cutout(f))
if WRITE_RES:
write_results(myframe, r)
assert np.allclose(np.array(r).flatten().view(float), get_results(myframe))
def test_fmp_2d():
sino, angles = create_test_sino_2d(N=10)
p = get_test_parameter_set(1)[0]
# complex
jmc = mp.Value("i", 0)
jmm = mp.Value("i", 0)
odtbrain.fourier_map_2d(sino, angles, count=jmc, max_count=jmm, **p)
assert jmc.value == jmm.value
assert jmc.value != 0
def test_2d_fmap():
myframe = sys._getframe()
sino, angles = create_test_sino_2d()
parameters = get_test_parameter_set(1)
r = []
for p in parameters:
f = odtbrain.fourier_map_2d(sino, angles, **p)
r.append(cutout(f))
if WRITE_RES:
write_results(myframe, r)
assert np.allclose(np.array(r).flatten().view(float), get_results(myframe))
def test_3d_backprop_weights_even():
"""
even weights
"""
platform.system = lambda: "Windows"
sino, angles = create_test_sino_3d()
p = get_test_parameter_set(1)[0]
f1 = odtbrain.backpropagate_3d(sino, angles, weight_angles=False, **p)
f2 = odtbrain.backpropagate_3d(sino, angles, weight_angles=True, **p)
data1 = np.array(f1).flatten().view(float)
data2 = np.array(f2).flatten().view(float)
assert np.allclose(data1, data2)
def test_2d_backprop_full():
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_2d(ampl_range=(0.9,1.1))
parameters = get_test_parameter_set(2)
r = list()
for p in parameters:
f = odtbrain._Back_2D.backpropagate_2d(sino, angles, **p)
r.append(cutout(f))
if WRITE_RES:
write_results(myframe, r)
assert np.allclose(np.array(r).flatten().view(float), get_results(myframe))
def test_back3d_tilted():
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
p = get_test_parameter_set(1)[0]
f1 = odtbrain._Back_3D_tilted.backpropagate_3d_tilted(sino, angles, padval=0,
dtype=np.float64,
copy=False, **p)
f2 = odtbrain._Back_3D_tilted.backpropagate_3d_tilted(sino, angles, padval=0,
dtype=np.float64,
copy=True, **p)
assert np.allclose(f1, f2)
def test_3d_backprop_phase32():
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_3d()
parameters = get_test_parameter_set(2)
r = list()
for p in parameters:
f = odtbrain._Back_3D.backpropagate_3d(sino, angles,
dtype=np.float32, padval=0, **p)
r.append(cutout(f))
data32 = np.array(r).flatten().view(np.float32)
data64 = test_3d_backprop_phase()
assert np.allclose(data32, data64, atol=6e-7, rtol=0)
def test_3d_backprop_phase32():
sino, angles = create_test_sino_3d()
parameters = get_test_parameter_set(2)
r = list()
for p in parameters:
f = odtbrain.backpropagate_3d(sino,
angles,
dtype=np.float32,
padval=0,
**p)
r.append(cutout(f))
data32 = np.array(r).flatten().view(np.float32)
data64 = test_3d_backprop_phase()
assert np.allclose(data32, data64, atol=6e-7, rtol=0)
def test_bpp_2d():
sino, angles = create_test_sino_2d(N=10)
p = get_test_parameter_set(1)[0]
# complex
jmc = mp.Value("i", 0)
jmm = mp.Value("i", 0)
odtbrain.backpropagate_2d(sino,
angles,
padval=0,
count=jmc,
max_count=jmm,
**p)
assert jmc.value == jmm.value
assert jmc.value != 0
def test_back3d_tilted():
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
p = get_test_parameter_set(1)[0]
# complex
jmc = mp.Value("i", 0)
jmm = mp.Value("i", 0)
odtbrain.backpropagate_3d_tilted(sino,
angles,
padval=0,
dtype=np.float64,
count=jmc,
max_count=jmm,
**p)
assert jmc.value == jmm.value
assert jmc.value != 0
def test_back3d():
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
p = get_test_parameter_set(1)[0]
# complex
jmc = mp.Value("i", 0)
jmm = mp.Value("i", 0)
f = odtbrain._Back_3D.backpropagate_3d(sino, angles, padval=0,
dtype=np.float64,
jmc=jmc,
jmm=jmm,
**p)
assert jmc.value == jmm.value
assert jmc.value != 0
def test_3d_backprop_phase():
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_3d()
parameters = get_test_parameter_set(2)
r = list()
for p in parameters:
f = odtbrain._Back_3D.backpropagate_3d(sino, angles, padval=0,
dtype=np.float64, **p)
r.append(cutout(f))
if WRITE_RES:
write_results(myframe, r)
data = np.array(r).flatten().view(float)
assert np.allclose(data, get_results(myframe))
return data
def test_back3d_tilted():
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
p = get_test_parameter_set(1)[0]
f1 = odtbrain.backpropagate_3d_tilted(sino,
angles,
padval=0,
dtype=np.float64,
copy=False,
**p)
f2 = odtbrain.backpropagate_3d_tilted(sino,
angles,
padval=0,
dtype=np.float64,
copy=True,
**p)
assert np.allclose(f1, f2)
def test_3d_backprop_phase():
myframe = sys._getframe()
sino, angles = create_test_sino_3d()
parameters = get_test_parameter_set(2)
r = list()
for p in parameters:
f = odtbrain.backpropagate_3d(sino,
angles,
padval=0,
dtype=np.float64,
**p)
r.append(cutout(f))
if WRITE_RES:
write_results(myframe, r)
data = np.array(r).flatten().view(float)
assert np.allclose(data, get_results(myframe))
return data
def test_fmap2d():
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_2d(N=10)
p = get_test_parameter_set(1)[0]
# complex
jmc = mp.Value("i", 0)
jmm = mp.Value("i", 0)
f = odtbrain._Back_2D.fourier_map_2d(sino, angles,
jmc=jmc,
jmm=jmm,
**p)
assert jmc.value == jmm.value
assert jmc.value != 0
def test_3d_backprop_phase_real():
sino, angles = create_test_sino_3d()
parameters = get_test_parameter_set(2)
# reference
rref = list()
for p in parameters:
fref = odtbrain.backpropagate_3d(sino, angles, padval=0,
dtype=np.float64, onlyreal=True, **p)
rref.append(cutout(fref))
dataref = np.array(rref).flatten().view(float)
r = list()
for p in parameters:
f = odtbrain.backpropagate_3d_tilted(sino, angles, padval=0,
dtype=np.float64, onlyreal=True,
**p)
r.append(cutout(f))
data = np.array(r).flatten().view(float)
assert np.allclose(data, dataref)
def test_correct_values():
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
p = get_test_parameter_set(1)[0]
f = odtbrain.backpropagate_3d(sino,
angles,
padval=0,
dtype=np.float64,
copy=False,
**p)
try:
odtbrain.apple.correct(
f=f,
res=p["res"],
nm=p["nm"],
enforce_envelope=1.05,
)
except ValueError:
pass
else:
assert False, "`enforce_envelope` must be in [0, 1]"
def test_3d_backprop_nopadreal():
"""
- no padding
- only real result
"""
platform.system = lambda:"Windows"
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_3d()
parameters = get_test_parameter_set(2)
r = list()
for p in parameters:
f = odtbrain._Back_3D.backpropagate_3d(sino, angles, padding=(False,False),
dtype=np.float64, onlyreal=True, **p)
r.append(cutout(f))
if WRITE_RES:
write_results(myframe, r)
data = np.array(r).flatten().view(float)
assert np.allclose(data, get_results(myframe))
def test_3d_backprop_plane_rotation():
"""
A very soft test to check if planar rotation works fine
in the reconstruction with tilted angles.
"""
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
parameters = get_test_parameter_set(1)
results = []
# These are specially selected angles that don't give high results.
# Probably due to phase-wrapping, errors >2 may appear. Hence, we
# call it a soft test.
tilts = [1.1, 0.0, 0.234, 2.80922, -0.29, 9.87]
for angz in tilts:
sino, angles = create_test_sino_3d_tilted(tilt_plane=angz, A=21)
rotmat = np.array([[np.cos(angz), -np.sin(angz), 0], [np.sin(angz), np.cos(angz), 0], [0, 0, 1]])
# rotate `tilted_axis` onto the y-z plane.
tilted_axis = np.dot(rotmat, [0, 1, 0])
rref = list()
for p in parameters:
fref = odtbrain._Back_3D_tilted.backpropagate_3d_tilted(
sino,
angles,
padval=None,
tilted_axis=tilted_axis,
padding=(False, False),
dtype=np.float64,
onlyreal=False,
**p
)
rref.append(cutout(fref))
data = np.array(rref).flatten().view(float)
results.append(data)
for ii in np.arange(len(results)):
assert np.allclose(results[ii], results[ii - 1], atol=0.2, rtol=0.2)
def test_3d_backprop_phase_real():
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_3d()
parameters = get_test_parameter_set(2)
# reference
rref = list()
for p in parameters:
fref = odtbrain._Back_3D.backpropagate_3d(sino, angles, padval=0, dtype=np.float64, onlyreal=True, **p)
rref.append(cutout(fref))
dataref = np.array(rref).flatten().view(float)
r = list()
for p in parameters:
f = odtbrain._Back_3D_tilted.backpropagate_3d_tilted(
sino, angles, padval=0, dtype=np.float64, onlyreal=True, **p
)
r.append(cutout(f))
data = np.array(r).flatten().view(float)
assert np.allclose(data, dataref)
def test_back3d():
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
parameters = get_test_parameter_set(2)
# complex
r = list()
for p in parameters:
f = odtbrain._Back_3D.backpropagate_3d(sino, angles, padval=0,
dtype=np.float64,
save_memory=False, **p)
r.append(f)
# real
r2 = list()
for p in parameters:
f = odtbrain._Back_3D.backpropagate_3d(sino, angles, padval=0,
dtype=np.float64,
save_memory=True, **p)
r2.append(f)
assert np.allclose(np.array(r), np.array(r2))
def test_correct_counter():
count = mp.Value("I", lock=True)
max_count = mp.Value("I", lock=True)
sino, angles = create_test_sino_3d(Nx=10, Ny=10)
p = get_test_parameter_set(1)[0]
f = odtbrain.backpropagate_3d(sino,
angles,
padval=0,
dtype=np.float64,
copy=False,
**p)
odtbrain.apple.correct(f=f,
res=p["res"],
nm=p["nm"],
enforce_envelope=.95,
max_iter=100,
min_diff=0.01,
count=count,
max_count=max_count)
assert count.value == max_count.value
def test_3d_backprop_nopadreal():
"""
- no padding
- only real result
"""
platform.system = lambda: "Windows"
myframe = sys._getframe()
sino, angles = create_test_sino_3d()
parameters = get_test_parameter_set(2)
r = list()
for p in parameters:
f = odtbrain.backpropagate_3d(sino,
angles,
padding=(False, False),
dtype=np.float64,
onlyreal=True,
**p)
r.append(cutout(f))
if WRITE_RES:
write_results(myframe, r)
data = np.array(r).flatten().view(float)
assert np.allclose(data, get_results(myframe))
def test_3d_backprop_plane_rotation():
"""
A very soft test to check if planar rotation works fine
in the reconstruction with tilted angles.
"""
parameters = get_test_parameter_set(1)
results = []
# These are specially selected angles that don't give high results.
# Probably due to phase-wrapping, errors >2 may appear. Hence, we
# call it a soft test.
tilts = [1.1, 0.0, 0.234, 2.80922, -.29, 9.87]
for angz in tilts:
sino, angles = create_test_sino_3d_tilted(tilt_plane=angz, A=21)
rotmat = np.array([
[np.cos(angz), -np.sin(angz), 0],
[np.sin(angz), np.cos(angz), 0],
[0, 0, 1],
])
# rotate `tilted_axis` onto the y-z plane.
tilted_axis = np.dot(rotmat, [0, 1, 0])
rref = list()
for p in parameters:
fref = odtbrain.backpropagate_3d_tilted(sino, angles,
padval="edge",
tilted_axis=tilted_axis,
padding=(False, False),
dtype=np.float64,
onlyreal=False,
**p)
rref.append(cutout(fref))
data = np.array(rref).flatten().view(float)
results.append(data)
for ii in np.arange(len(results)):
assert np.allclose(results[ii], results[ii-1], atol=.2, rtol=.2)
def test_angle_swap():
"""
Test if everything still works, when angles are swapped.
"""
sino, angles = create_test_sino_2d()
# remove elements so that we can see that weighting works
angles = angles[:-2]
sino = sino[:-2, :]
parameters = get_test_parameter_set(2)
# reference
r1 = []
for p in parameters:
f1 = odtbrain.backpropagate_2d(sino, angles, weight_angles=True, **p)
r1.append(f1)
# change order of angles
order = np.argsort(angles % .5)
angles = angles[order]
sino = sino[order, :]
r2 = []
for p in parameters:
f2 = odtbrain.backpropagate_2d(sino, angles, weight_angles=True, **p)
r2.append(f2)
assert np.allclose(np.array(r1).flatten().view(float),
np.array(r2).flatten().view(float))
