def reconstruct(sname, rot_center, ovlpfind, s_start, s_end):
fname = dfolder + sname + '.h5'
print(fname)
start = s_start
end = s_end
chunks = 24
num_sino = (end - start) // chunks
for m in range(chunks):
sino_start = start + num_sino * m
sino_end = start + num_sino * (m + 1)
start_read_time = time.time()
proj, flat, dark, thetat = dxchange.read_aps_2bm(fname,
sino=(sino_start,
sino_end))
print(' done read in %0.1f min' %
((time.time() - start_read_time) / 60))
dark = proj[9001:9002]
flat = proj[0:1]
proj = proj[1:9000]
theta = tomopy.angles(proj.shape[0], 0., 360.)
proj = tomopy.sino_360_to_180(proj, overlap=ovlpfind, rotation='right')
proj = tomopy.remove_outlier(proj, dif=0.4)
proj = tomopy.normalize_bg(proj, air=10)
proj = tomopy.minus_log(proj)
center = rot_center
start_ring_time = time.time()
proj = tomopy.remove_stripe_fw(proj, wname='sym5', sigma=4, pad=False)
proj = tomopy.remove_stripe_sf(proj, size=3)
print(' done pre-process in %0.1f min' %
((time.time() - start_ring_time) / 60))
start_phase_time = time.time()
proj = tomopy.retrieve_phase(proj,
pixel_size=detector_pixel_size_x,
dist=sample_detector_distance,
energy=energy,
alpha=alpha,
pad=True,
ncore=None,
nchunk=None)
print(' done phase retrieval in %0.1f min' %
((time.time() - start_phase_time) / 60))
start_recon_time = time.time()
rec = tomopy.recon(proj,
theta,
center=center,
algorithm='gridrec',
filter_name='ramalk')
tomopy.circ_mask(rec, axis=0, ratio=0.95)
print("Reconstructed", rec.shape)
dxchange.write_tiff_stack(rec,
fname=dfolder + '/' + sname + '/' + sname,
overwrite=True,
start=sino_start)
print(' Chunk reconstruction done in %0.1f min' %
((time.time() - start_recon_time) / 60))
print("Done!")
def read_aps_2bm_custom(fname, sino):
# Read APS 2-BM raw data in temporary array to fix an acquisition error.
# All data (proj,dark and white) are stored in the proj array while flat/dark/theta arrays are invalid
tproj, tflat, tdark, ttheta = dxchange.read_aps_2bm(fname, sino=sino)
# Extracting from the tproj array proj, flat, dark and theta
ndark = 10
nflat = 10
last_projection = tproj.shape[0] - nflat - ndark
proj = tproj[0:last_projection, :, :]
flat = tproj[last_projection:last_projection+nflat, :, :]
dark = tproj[last_projection+nflat:last_projection+nflat+ndark, :, :]
theta_size = proj.shape[0]
theta = np.linspace(0. , np.pi, theta_size)
return proj, flat, dark, theta
def read_aps_2bm_custom(fname, sino):
# Read APS 2-BM raw data in temporary array to fix an acquisition error.
# All data (proj,dark and white) are stored in the proj array while flat/dark/theta arrays are invalid
tproj, tflat, tdark, ttheta = dxchange.read_aps_2bm(fname, sino=sino)
# Extracting from the tproj array proj, flat, dark and theta
ndark = 10
nflat = 10
last_projection = tproj.shape[0] - nflat - ndark
proj = tproj[0:last_projection, :, :]
flat = tproj[last_projection:last_projection+nflat, :, :]
dark = tproj[last_projection+nflat:last_projection+nflat+ndark, :, :]
theta_size = proj.shape[0]
theta = np.linspace(0. , np.pi, theta_size)
return proj, flat, dark, theta
def reconstruct(sname, rot_center, ovlpfind, s_start, s_end):
fname = dfolder + sname + '.h5'
print (fname)
start = s_start
end = s_end
chunks = 24
num_sino = (end - start) // chunks
for m in range(chunks):
sino_start = start + num_sino * m
sino_end = start + num_sino * (m + 1)
start_read_time = time.time()
proj, flat, dark, thetat = dxchange.read_aps_2bm(fname, sino=(sino_start, sino_end))
print(' done read in %0.1f min' % ((time.time() - start_read_time)/60))
dark = proj[9001:9002]
flat = proj[0:1]
proj = proj[1:9000]
theta = tomopy.angles(proj.shape[0], 0., 360.)
proj = tomopy.sino_360_to_180(proj, overlap=ovlpfind, rotation='right')
proj = tomopy.remove_outlier(proj, dif=0.4)
proj = tomopy.normalize_bg(proj, air=10)
proj = tomopy.minus_log(proj)
center = rot_center
start_ring_time = time.time()
proj = tomopy.remove_stripe_fw(proj, wname='sym5', sigma=4, pad=False)
proj = tomopy.remove_stripe_sf(proj, size=3)
print(' done pre-process in %0.1f min' % ((time.time() - start_ring_time)/60))
start_phase_time = time.time()
proj = tomopy.retrieve_phase(proj, pixel_size=detector_pixel_size_x, dist=sample_detector_distance, energy=energy, alpha=alpha, pad=True, ncore=None, nchunk=None)
print(' done phase retrieval in %0.1f min' % ((time.time() - start_phase_time)/60))
start_recon_time = time.time()
rec = tomopy.recon(proj, theta, center=center, algorithm='gridrec', filter_name='ramalk')
tomopy.circ_mask(rec, axis=0, ratio=0.95)
print ("Reconstructed", rec.shape)
dxchange.write_tiff_stack(rec, fname = dfolder + '/' + sname + '/' + sname, overwrite=True, start=sino_start)
print(' Chunk reconstruction done in %0.1f min' % ((time.time() - start_recon_time)/60))
print ("Done!")
for iChunk in range(0,chunks):
print('\n -- chunk # %i' % (iChunk+1))
sino_chunk_start = sino_start + nSino_per_chunk*iChunk
sino_chunk_end = sino_start + nSino_per_chunk*(iChunk+1)
print('\n --------> [%i, %i]' % (sino_chunk_start, sino_chunk_end))
if sino_chunk_end > sino_end:
break
sino = (int(sino_chunk_start), int(sino_chunk_end))
# Read APS 2-BM raw data.
if (int(key) > 6):
proj, flat, dark, theta = read_aps_2bm_custom(fname, sino=sino)
else:
proj, flat, dark, theta = dxchange.read_aps_2bm(fname, sino=sino)
# zinger_removal
proj = tomopy.misc.corr.remove_outlier(proj, zinger_level, size=15, axis=0)
flat = tomopy.misc.corr.remove_outlier(flat, zinger_level_w, size=15, axis=0)
# Flat-field correction of raw data.
data = tomopy.normalize(proj, flat, dark, cutoff=1.4)
# remove stripes
#proj = tomopy.remove_stripe_fw(proj,level=5,wname='sym16',sigma=1,pad=True)
proj = tomopy.remove_stripe_ti(proj,2)
proj = tomopy.remove_stripe_sf(proj,10)
# phase retrieval
##data = tomopy.prep.phase.retrieve_phase(data,pixel_size=detector_pixel_size_x,dist=sample_detector_distance,energy=monochromator_energy,alpha=8e-3,pad=True)
fname = top + prefix + h5name + '/proj_' + h5name + '.hdf'
rot_center = dict2[h5name]
##print(fname, rot_center)
# Select sinogram range to reconstruct.
sino = None
start = 1000
end = 1001
sino = (start, end)
# Read APS 2-BM raw data.
if (int(key) > 6):
proj, flat, dark, theta = read_aps_2bm_custom(fname, sino=sino)
else:
proj, flat, dark, theta = dxchange.read_aps_2bm(fname, sino=sino)
# zinger_removal
proj = tomopy.misc.corr.remove_outlier(proj, zinger_level, size=15, axis=0)
flat = tomopy.misc.corr.remove_outlier(flat, zinger_level_w, size=15, axis=0)
# Flat-field correction of raw data.
data = tomopy.normalize(proj, flat, dark, cutoff=1.4)
# remove stripes
#data = tomopy.remove_stripe_fw(data,level=5,wname='sym16',sigma=1,pad=True)
##data = tomopy.prep.stripe.remove_stripe_ti(data,alpha=7)
##data = tomopy.prep.stripe.remove_stripe_sf(data,size=51)
# phase retrieval
##data = tomopy.prep.phase.retrieve_phase(data,pixel_size=detector_pixel_size_x,dist=sample_detector_distance,energy=monochromator_energy,alpha=alpha,pad=True)
