spyrit.core.meas.HadamSplit.inverse

HadamSplit.inverse(y: tensor) → tensor

Inverse transform of Hadamard-domain images \(x = H_{had}^{-1}G y\).

Args:

\(y\): batch of images in the Hadamard domain

Shape:

\(y\): \((b*c, N)\) with \(b\) the batch size, \(c\) the number of channels, and \(N\) the number of pixels in the image.

Output: math:(b*c, N)

Example:

>>> h = 32
>>> Ord = torch.randn(h, h)
>>> meas_op = HadamSplit(400, h, Ord)
>>> y = torch.randn(10, h**2)
>>> x = meas_op.inverse(y)
>>> print(x.shape)
torch.Size([10, 1024])