spyrit.core.prep.RescaleEstim.forward

RescaleEstim.forward(y: tensor) → tensor

Rescale 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:

y (torch.tensor): The measurements with shape \((*, M)\), where \(*\) can be any number of dimensions and \(M\) matches the number of measurements defined by meas_op.M.

Returns:

torch.tensor: Rescaled measurements of shape \((*, M)\).