# Temporary replacement of bad projections
if params["correct_bad"]:
stack_phasecorr = replace_bad(
stack_phasecorr, list_bad=params["bad_projs"], temporary=True
)
# find the residues and choose region to be unwrapped
rx, ry, airpix = chooseregiontounwrap(stack_phasecorr)
ansunw = input("Do you want to continue with the unwrapping?([y]/n)").lower()
if str(ansunw) == "" or str(ansunw) == "y":
stack_unwrap = unwrapping_phase(stack_phasecorr, rx, ry, airpix, **params)
else:
stack_unwrap = stack_phasecorr
print("The phases have not been unwrapped").lower()
# display the projections after the unwrapping
showmovie = input(
"Do you want to show all the unwrapped projections?([y]/n): "
).lower()
if str(showmovie) == "" or str(showmovie) == "y":
iterative_show(stack_unwrap, ry, rx, airpix, onlyroi=False)
# Save the unwrapped phase projections
SaveData.save("unwrapped_phases.h5", stack_unwrap, theta, **params)
# next step
print('You should run "vertical_alignment.py" now')
# =============================================================================#
# initializing params
params = dict()
### Edit section ###
# =========================
params["account"] = "ma3495"
params["samplename"] = "H2int_15000h_outlet"
params[
"pathfilename"
] = "/data/id16a/inhouse5/visitor/ma3495/id16a/H2int_15000h_outlet/H2int_15000h_outlet_25nm_holo_/H2int_15000h_outlet_25nm_holo_rec_0000.edf"
params["regime"] = "holoct"
params["showrecons"] = False
params["autosave"] = True
# =========================
# =============================================================================#
# Don't edit below this line, please #
# =============================================================================#
if __name__ == "__main__":
# loading the projections from files
stack_objs, theta, pixelsize, params = LoadProjections.loadedf(**params)
# Save reconstructed phase projections
SaveData.save("reconstructed_projections.h5", stack_objs, theta, **params)
# next step
print('You should run "vertical_alignment_holo.py" for phase tomogram')
# =============================================================================#
print("Tomo consistency on multiples slices not done")
# Shift projections (Only shift the horizontal)
print("Shifting the projections (only shifts in the horizontal direction)")
aligned_projections = compute_aligned_horizontal(
aligned_diff, shiftstack, shift_method=params["shiftmeth"]
)
# correcting bad projections after the alignment if needed
if params["correct_bad"]:
aligned_projections = replace_bad(
aligned_projections, list_bad=params["bad_projs"], temporary=False
)
a = input("Do you want to display the aligned projections? (y/[n]) :").lower()
if str(a) == "y":
iterative_show(
aligned_projections, vmin=-0.2, vmax=0.2
) # Show aligned projections derivatives
# calculate one slice for display
aligned_sinogram = np.transpose(aligned_projections[:, params["slicenum"], :])
oneslicefordisplay(aligned_sinogram, theta, **params)
# save horizontally aligned_projections
SaveData.save(
"aligned_projections.h5", aligned_projections, theta, shiftstack, **params
)
# next step
print('You should run "tomographic_reconstruction.py" now')
# =============================================================================#
normfreqs, T, FSC2Dcurve = FSC2D.plot()
print("The pixelsize of the data is {:.02f} nm".format(voxelsize[0] * 1e9))
a = input("\nPlease, input the value of the intersection: ")
params["resolution2D"] = voxelsize[0] * 1e9 / float(a)
print("------------------------------------------")
print("| Resolution is estimated to be {:.2f} nm |".format(
params["resolution2D"]))
print("------------------------------------------")
input("\n<Hit Return to close images>")
plt.close("all")
# save the 2D FSC data
SaveData.saveFSC("FSC2D.h5", normfreqs, T, FSC2Dcurve, tomogram1,
tomogram2, theta, voxelsize, **params)
# =========================
# 3D FSC calculation
# =========================
a = str(input("Do you want to calculate the 3D FSC?(y/n)")).lower()
if a == "" or a == "y":
# del tomo1, tomo2, image1, image2, sinogram_align, sinogram_align1, sinogram_align2#, sagital_slice1, sagital_slice2
limsyFSC = params["limsyFSC"]
nslices = limsyFSC[-1] - limsyFSC[0]
# initializing variables
tomogram1 = np.empty((nslices, nr, nc))
tomogram2 = np.empty((nslices, nr, nc))
sinogram1 = np.empty((nslices, sino1nr, sino1nc))
"reconstructed_projections.h5", **params)
# initializing shiftstack
if params["load_previous_shiftstack"]:
shiftstack = LoadData.loadshiftstack("vertical_alignment.h5", **params)
print("Using previous estimate of shiftstack")
else:
# initializing shiftstack with zeros
shiftstack[0] = np.zeros(stack_unwrap.shape[0])
# Vertical alignment
shiftstack, aligned = alignprojections_vertical(stack_unwrap, shiftstack,
**params)
a = input("Do you want to refine further the alignment? (y/[n]): ").lower()
if str(a) == "y":
shiftstack, aligned = alignprojections_vertical(
stack_unwrap, shiftstack, **params)
a = input(
"Do you want to display the aligned projections? (y/[n]) :").lower()
if str(a) == "y":
iterative_show(aligned) # Show aligned projections
# save vertically aligned_projections
SaveData.save("vertical_alignment.h5", aligned, theta, shiftstack,
**params)
# next step
print('You should run "projections_derivatives.py" now')
# =============================================================================#
params = dict()
### Edit section ###
# =========================
params["samplename"] = "v97_v_nfptomo2_15nm"
params["crop_reg"] = None # [20,0,20,0] # left, bottom, right, top
params["autosave"] = False
params["vmin"] = -1.6
params["vmax"] = 1.6
params["amponly"] = True # ensuring that we are loading only amplitude
# =========================
# =============================================================================#
# Don't edit below this line, please #
# =============================================================================#
if __name__ == "__main__":
# loading the data
stack_objs, theta, shiftstack, params = LoadData.load(
"reconstructed_projections.h5", **params
)
# correcting phase ramp
stack_phasecorr = gui_plotamp(stack_objs, **params)
# Save the corrected phase projections
SaveData.save("air_corrected_amplitude.h5", stack_phasecorr, theta, **params)
# next step
print('You should run "phase_unwrapping.py" now')
# =============================================================================#
params = dict()
### Edit section ###
# =========================
params["samplename"] = "v97_v_nfptomo2_15nm"
params["crop_reg"] = None # [20,0,20,0] # left, bottom, right, top
params["autosave"] = False
params["vmin"] = -1.6
params["vmax"] = 1.6
params["phaseonly"] = True # ensuring that we are loading only phase
# =========================
# =============================================================================#
# Don't edit below this line, please #
# =============================================================================#
if __name__ == "__main__":
# loading the data
stack_objs, theta, shiftstack, params = LoadData.load(
"reconstructed_projections.h5", **params)
# correcting phase ramp
stack_phasecorr = gui_plotphase(stack_objs, **params)
# Save the corrected phase projections
SaveData.save("linear_phase_corrected.h5", stack_phasecorr, theta,
**params)
# next step
print('You should run "phase_unwrapping.py" now')
# =============================================================================#
# =============================================================================#
if __name__ == "__main__":
# loading the data
aligned, theta, shiftstack, params = LoadData.load("vertical_alignment.h5",
**params)
# chosse the region to apply the derivatives
roix, roiy = chooseregiontoderivatives(aligned, **params)
# calculating the projection derivatives
aligned_diff = calculate_derivatives(aligned,
roiy,
roix,
shift_method=params["shift_method"])
# display the projections after the unwrapping
showmovie = input(
"Do you want to show all the projection derivatives?([y]/n): ").lower(
)
if str(showmovie) == "" or str(showmovie) == "y":
iterative_show(aligned_diff, onlyroi=False, vmin=-0.2, vmax=0.2)
# Save the projection derivatives
SaveData.save("aligned_derivatives.h5", aligned_diff, theta, shiftstack,
**params)
# next step
print('You should run "sinogram_inspection.py" now')
# =============================================================================#
# local packages
from toupy.io import LoadData, SaveData, load_paramsh5
# initializing dictionaries
params = dict()
# Edit section
# =========================
params["samplename"] = "v97_v_nfptomo2_15nm"
# =========================
# =============================================================================#
# Don't edit below this line, please #
# =============================================================================#
if __name__ == "__main__":
# update params
paramsh5 = load_paramsh5(**params)
params.update(paramsh5)
# loading theta and shiftstack for the saving
shiftstack = LoadData.loadshiftstack("aligned_projections.h5", **params)
theta = LoadData.loadtheta("aligned_projections.h5", **params)
# actual saving
SaveData.save_vol_to_h5("tomogramVOL.h5", theta, **params)
# next step
print('You can now run "tiff_convertion.py" if needed')
# =============================================================================#