spyrit.core.meas.HadamSplit.forward_H

HadamSplit.forward_H(x: tensor) → tensor

Applies linear transform to incoming images: \(m = Hx\).

This method uses the measurement matrix \(H\) to compute the linear measurements from incoming images.

Args:

x (torch.tensor): Batch of vectorized (flatten) images. If x has more than 1 dimension, the linear measurement is applied to each image in the batch.

Shape:

x: \((*, N)\) where * denotes the batch size and N the total number of pixels in the image.

Output: \((*, M)\) where * denotes the batch size and M the number of measurements.

Example:

>>> H = torch.randn(400, 1600)
>>> meas_op = LinearSplit(H)
>>> x = torch.randn(10, 1600)
>>> y = meas_op.forward_H(x)
>>> print(y.shape)
torch.Size([10, 400])