solvers¶
Contains different solver implementations.
Solve the ptychography problem using conjugate gradient. |
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Solve the ptychography problem using Odstrcil et al’s approach. |
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tike.ptycho.solvers.cgrad(op, comm, data, probe, scan, psi, recover_psi=True, recover_probe=True, recover_positions=False, cg_iter=4, cost=None, eigen_probe=None, eigen_weights=None, num_batch=1, subset_is_random=None, step_length=1, probe_is_orthogonal=False)[source]¶ Solve the ptychography problem using conjugate gradient.
- Parameters
op (
tike.operators.Ptycho) – A ptychography operator.comm (
tike.communicators.Comm) – An object which manages communications between both GPUs and nodes.
See also
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tike.ptycho.solvers.lstsq_grad(op, comm, data, probe, scan, psi, recover_psi=True, recover_probe=False, recover_positions=False, cg_iter=4, cost=None, eigen_probe=None, eigen_weights=None, num_batch=1, subset_is_random=True, probe_is_orthogonal=False)[source]¶ Solve the ptychography problem using Odstrcil et al’s approach.
The near- and farfield- ptychography problems are solved separately using gradient descent in the farfield and linear-least-squares in the nearfield.
- Parameters
op (tike.operators.Ptycho) – A ptychography operator.
comm (tike.communicators.Comm) – An object which manages communications between GPUs and nodes.
References
Michal Odstrcil, Andreas Menzel, and Manuel Guizar-Sicaros. Iterative least-squares solver for generalized maximum-likelihood ptychography. Optics Express. 2018.