diff options
Diffstat (limited to 'Wrappers/Python/ccpi/optimisation/operators/GradientOperator.py')
| -rw-r--r-- | Wrappers/Python/ccpi/optimisation/operators/GradientOperator.py | 32 |
1 files changed, 21 insertions, 11 deletions
diff --git a/Wrappers/Python/ccpi/optimisation/operators/GradientOperator.py b/Wrappers/Python/ccpi/optimisation/operators/GradientOperator.py index 8e07802..2ff0b20 100644 --- a/Wrappers/Python/ccpi/optimisation/operators/GradientOperator.py +++ b/Wrappers/Python/ccpi/optimisation/operators/GradientOperator.py @@ -35,7 +35,9 @@ CORRELATION_SPACECHANNEL = "SpaceChannels" class Gradient(LinearOperator): - """This is a class to compute the first-order forward/backward differences on ImageData + + r'''Gradient Operator: Computes first-order forward/backward differences on + 2D, 3D, 4D ImageData under Neumann/Periodic boundary conditions :param gm_domain: Set up the domain of the function :type gm_domain: `ImageGeometry` @@ -50,17 +52,17 @@ class Gradient(LinearOperator): 'Space' or 'SpaceChannels', defaults to 'Space' * *backend* (``str``) -- 'c' or 'numpy', defaults to 'c' if correlation is 'SpaceChannels' or channels = 1 - """ + + + Example (2D): - r'''Gradient Operator: .. math:: \nabla : X -> Y - - Computes first-order forward/backward differences - on 2D, 3D, 4D ImageData - under Neumann/Periodic boundary conditions - - Example (2D): u\in X, \nabla(u) = [\partial_{y} u, \partial_{x} u] - u^{*}\in Y, \nabla^{*}(u^{*}) = \partial_{y} v1 + \partial_{x} v2 + .. math:: + \nabla : X -> Y \\ + u\in X, \nabla(u) = [\partial_{y} u, \partial_{x} u] \\ + u^{*}\in Y, \nabla^{*}(u^{*}) = \partial_{y} v1 + \partial_{x} v2 + + ''' #kept here for backwards compatability @@ -126,7 +128,15 @@ class Gradient(LinearOperator): class Gradient_numpy(LinearOperator): def __init__(self, gm_domain, bnd_cond = 'Neumann', **kwargs): - + '''creator + + :param gm_domain: domain of the operator + :type gm_domain: :code:`AcquisitionGeometry` or :code:`ImageGeometry` + :param bnd_cond: boundary condition, either :code:`Neumann` or :code:`Periodic`. + :type bnd_cond: str, optional, default :code:`Neumann` + :param correlation: optional, :code:`SpaceChannel` or :code:`Space` + :type correlation: str, optional, default :code:`Space` + ''' super(Gradient_numpy, self).__init__() self.gm_domain = gm_domain # Domain of Grad Operator |