spyrit.core.recon.PinvNet.meas2img

PinvNet.meas2img(y)[source]

Returns images from raw measurement vectors

Args:

x: raw measurement vectors

Shape:

x: \((*,2M)\)

output: \((*,H,W)\)

Example:
>>> B, C, H, M = 10, 3, 64, 64**2
>>> Ord = torch.ones(H,H)
>>> meas = HadamSplit(M, H, Ord)
>>> noise = NoNoise(meas)
>>> prep = SplitPoisson(1.0, M, H**2)
>>> recnet = PinvNet(noise, prep)
>>> x = torch.rand((B,C,2*M), dtype=torch.float32)
>>> z = recnet.reconstruct(x)
>>> print(z.shape)
torch.Size([10, 3, 64, 64])