pytomography.priors.prior
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Module Contents#
Classes#
Abstract class for implementation of prior \(V(f)\) where \(V\) is from the log-posterior probability \(\ln L(\tilde{f}, f) - \beta V(f)\). Any function inheriting from this class should implement a |
- class pytomography.priors.prior.Prior(beta)[source]#
Abstract class for implementation of prior \(V(f)\) where \(V\) is from the log-posterior probability \(\ln L(\tilde{f}, f) - \beta V(f)\). Any function inheriting from this class should implement a
foward
method that computes the tensor \(\frac{\partial V}{\partial f_r}\) where \(f\) is an object tensor.- Parameters:
beta (float) – Used to scale the weight of the prior
- set_object_meta(object_meta)[source]#
Sets object metadata parameters.
- Parameters:
object_meta (ObjectMeta) – Object metadata describing the system.
- Return type:
None
- set_beta_scale(factor)[source]#
Sets a scale factor for \(\beta\) required for OSEM when finite subsets are used per iteration.
- Parameters:
factor (float) – Value by which to scale \(\beta\)
- Return type:
None