spyrit.core.meas.FreeformLinear.mask_vectorize

FreeformLinear.mask_vectorize(x: tensor) → tensor

Flatten a tensor along the measured dimensions, which are collapsed into one.

This method first selects the elements from the input tensor at the specified dimensions self.meas_dims and based on the mask. The selected elements are then flattened into a single dimension which is the last dimension of the output tensor.

Args:

x (torch.tensor): The input tensor to select the mask from. The dimensions indexed by self.meas_dims should match the measurement shape self.meas_shape.

Note

This function is an alias for the method apply_mask().

Returns:

torch.tensor: A tensor of shape (*, self.N) where * denotes all the dimensions of the input tensor not included in self.meas_dims.

Example: Select one every second point on the diagonal of a batch of images

# >>> images = torch.rand(17, 3, 40, 40) # b, c, h, w # >>> # create a (2,20) mask # >>> mask = torch.tensor([[i, i] for i in range(0,40,2)]).T # >>> H = torch.randn(13, 20) # >>> meas_op = FreeformLinear(H, mask, meas_shape=(40,40), dim=(-1,-2)) # >>> y = meas_op.mask_vectorize(images) # >>> print(y.shape) # torch.Size([17, 3, 20])