pytomography.projections.forward_projection
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Module Contents#
Classes#
Implements a forward projection of mathematical form \(g_j = \sum_{i} c_{ij} f_i\) where \(f_i\) is an object, \(g_j\) is the corresponding image, and \(c_{ij}\) is the system matrix given by the various phenonemon modeled (e.g. atteunation/PSF). |
- class pytomography.projections.forward_projection.ForwardProjectionNet(obj2obj_nets, im2im_nets, object_meta, image_meta, device='cpu')#
Bases:
pytomography.projections.projection.ProjectionNet
Implements a forward projection of mathematical form \(g_j = \sum_{i} c_{ij} f_i\) where \(f_i\) is an object, \(g_j\) is the corresponding image, and \(c_{ij}\) is the system matrix given by the various phenonemon modeled (e.g. atteunation/PSF).
- Parameters:
obj2obj_nets (list[pytomography.mappings.MapNet]) –
im2im_nets (list[pytomography.mappings.MapNet]) –
object_meta (pytomography.metadata.ObjectMeta) –
image_meta (pytomography.metadata.ImageMeta) –
device (str) –
- forward(object, angle_subset=None)#
Implements forward projection on an object
- Parameters:
object (torch.tensor[batch_size, Lx, Ly, Lz]) – The object to be forward projected
angle_subset (list, optional) – Only uses a subset of angles (i.e. only certain values of \(j\) in formula above) when back projecting. Useful for ordered-subset reconstructions. Defaults to None,
used. (which assumes all angles are) –
- Returns:
Forward projected image where Ltheta is specified by self.image_meta and angle_subset.
- Return type:
torch.tensor[batch_size, Ltheta, Lx, Lz]