spyrit.core.prep.RescaleEstim
- class spyrit.core.prep.RescaleEstim(meas_op: Linear, **pinv_kwargs)[source]
Bases:
ModuleRescale measurements as
\[m = \frac{y}{\alpha},\]where \(y\) is the measurement and \(\alpha\) represents some gain/intensity that needs to be estimated from \(y\).
- Args:
meas_op(spyrit.core.meas.Linear): Measurement operator used to get the measurements \(y\). It should not be a split measurement operator.**pinv_kwargs: Additional keyword arguments to pass to the pseudo-inverse computation.
- Attributes:
self.alpha(torch.tensor): Estimated gain/intensity.self.meas_op(spyrit.core.meas.Linear): Measurement operator used to simulate the measurements.self.estim_mode(str): Set to “pinv”.self.pinv_kwargs(dict): Additional keyword arguments to pass to the pseudo-inverse initialization.self.pinv(spyrit.core.inverse.PseudoInverse): Pseudo-inverse operator.
Methods
estim_alpha(y)Estimate gain from pseudo-inverse.
forward(y)Rescale measurements as
pinv_estim(y)Estimate gain from pseudo-inverse.