pytomography.transforms.shared.filters
#
Module Contents#
Classes#
Applies a Gaussian smoothing filter to the reconstructed object with the specified full-width-half-max (FWHM) |
- class pytomography.transforms.shared.filters.GaussianFilter(FWHM, n_sigmas=3)[source]#
Bases:
pytomography.transforms.Transform
Applies a Gaussian smoothing filter to the reconstructed object with the specified full-width-half-max (FWHM)
- Parameters:
FWHM (float) – Specifies the width of the gaussian
n_sigmas (float) – Number of sigmas to include before truncating the kernel.
- configure(object_meta, proj_meta)[source]#
Configures the transform to the object/proj metadata. This is done after creating the network so that it can be adjusted to the system matrix.
- Parameters:
object_meta (ObjectMeta) – Object metadata.
proj_meta (ProjMeta) – Projections metadata.
- Return type:
None
- forward(object)[source]#
Applies the Gaussian smoothing
- Parameters:
object (torch.tensor) – Object to smooth
- Returns:
Smoothed object
- Return type:
torch.tensor
- backward(object, norm_constant=None)[source]#
Applies Gaussian smoothing in back projection. Because the operation is symmetric, it is the same as the forward projection.
- Parameters:
object (torch.tensor) – Object to smooth
norm_constant (torch.tensor, optional) – Normalization constant used in iterative algorithms. Defaults to None.
- Returns:
Smoothed object
- Return type:
torch.tensor