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Direct Ptycho #115 is merged.
@smribet shared a notebook and contained 5 to-do items:
- Use consistent angle/rad
direct_ptycho = em.diffractive_imaging.direct_ptychography.DirectPtychography.from_dataset4d(
dc,
energy=ENERGY,
semiangle_cutoff=PROBE_SEMIANGLE,
aberration_coefs={'C10':10}, # start close to focus
device="gpu",
rotation_angle=np.deg2rad(-169), # known rotation
max_batch_size=32
)direct ptycho uses angles in rad and iterative uses it in angles. @smribet prefers to have everything in angles.
- Add plotting function after direct pycho
todo add plotting funciton (something like this):
initial_parallax = direct_ptycho.reconstruct(
upsampling_factor=1,
deconvolution_kernel='quadratic',
).visualize(
show_fft = Trueadd
.visualize
- Plot after fitting - show whole grid of outcomes and print error/parameters
# todo plotting. it should show the whole grid of outcomes and print error/parameters.
direct_ptycho.grid_search_hyperparameters(
aberration_coefs={
"C10":-348,
"C12":OptimizationParameter(0, 40, n_points=5),
"phi12":OptimizationParameter(-np.pi/2, np.pi/2, n_points=5)
},
rotation_angle=np.deg2rad(-169),
deconvolution_kernel='quadratic',
)Pending after 1, 2, 3
- Optimization may need a bit more user-friendlyness
from quantem.diffractive_imaging.direct_ptychography import OptimizationParameter
direct_ptycho.optimize_hyperparameters(
aberration_coefs={
"C10":OptimizationParameter(-400,400),
"C12":OptimizationParameter(0, 100),
"phi12":OptimizationParameter(-np.pi/2, np.pi/2)
},
rotation_angle=OptimizationParameter(np.deg2rad(-180), np.deg2rad(-160)),
deconvolution_kernel='quadratic',
)5 Resolve ambiguity?
direct_ptycho.fit_hyperparameters(
# bin_factors=(5,5,5,5,5,4,4,4,3,3,3,2,2,2,1,1,1,),
# deconvolution_kernel='quadratic', # use parallax for post-fit reconstruction,
# pair_connectivity = 8,
# alignment_method = "reference",
)some way to force rotation to deal with 180 degree ambiguity?
I will first go through 1-3 and bring up a discussion on 4-5.
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