spyrit.core.recon.DCNet.reconstruct_pinv

DCNet.reconstruct_pinv(y: tensor) → tensor

Reconstruct an image from measurements without denoising.

This method sucessively applies the preprocessing operator prep and the Tikhonov regularization operator tikho to the input measurement vectors x.

Args:

y: raw measurement vectors. Have shape \((b, c, m)\)

Returns:

torch.tensor: Reconstructed images. Have shape \((b,c,h,w)\)

Example:

>>> from spyrit.core.meas import HadamSplit2d
>>> from spyrit.core.prep import UnsplitRescale
>>> from spyrit.core.recon import DCNet
>>> import torch
>>> acqu = HadamSplit2d(32)
>>> prep = UnsplitRescale()
>>> sigma = torch.eye(32*32,32*32)
>>> dcnet = DCNet(acqu, prep, sigma)
>>> y = torch.randn(10, 1, 2048)
>>> z = dcnet.reconstruct_pinv(y)
>>> print(z.shape)
torch.Size([10, 1, 32, 32])