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-Optimisation framework
-======================
-
-This package allows rapid prototyping of optimisation-based
-reconstruction problems, i.e. defining and solving different
-optimization problems to enforce different properties on the
-reconstructed image.
-
-Firstly, it provides an object-oriented framework for defining
-mathematical operators and functions as well a collection of useful
-example operators and functions. Both smooth and non-smooth functions
-can be used.
-
-Further, it provides a number of high-level generic implementations of
-optimisation algorithms to solve genericlly formulated optimisation
-problems constructed from operator and function objects.
-
-The fundamental components are:
-
--   Operator: A class specifying a (currently linear) operator
--   Function: A class specifying mathematical functions such as a least
-    squares data fidelity.
--   Algorithm: Implementation of an iterative optimisation algorithm to
-    solve a particular generic optimisation problem. Algorithms are
-    iterable Python object which can be run in a for loop. Can be
-    stopped and warm restarted.
-
-Algorithm
----------
-
-A number of generic algorithm implementations are provided including
-Gradient Descent CGLS and FISTA. An algorithm is designed for a
-particular generic optimisation problem accepts and number of Functions
-and/or Operators as input to define a specific instance of the generic
-optimisation problem to be solved. They are iterable objects which can
-be run in a for loop. The user can provide a stopping criterion
-different than the default max\_iteration.
-
-New algorithms can be easily created by extending the Algorithm class.
-The user is required to implement only 4 methods: set\_up, \_\_init\_\_,
-update and update\_objective.
-
--   `set_up` and `__init__` are used to configure the algorithm
--   `update` is the actual iteration updating the solution
--   `update_objective` defines how the objective is calculated.
-
-For example, the implementation of the update of the Gradient Descent
-algorithm to minimise a Function will only be:
-
-The `Algorithm` provides the infrastructure to continue iteration, to
-access the values of the objective function in subsequent iterations,
-the time for each iteration.
-
-::: {.autoclass members="" private-members="" special-members=""}
-ccpi.optimisation.algorithms.Algorithm
-:::
-
-::: {.autoclass members=""}
-ccpi.optimisation.algorithms.GradientDescent
-:::
-
-::: {.autoclass members=""}
-ccpi.optimisation.algorithms.CGLS
-:::
-
-::: {.autoclass members=""}
-ccpi.optimisation.algorithms.FISTA
-:::
-
-Operator
---------
-
-The two most important methods are `direct` and `adjoint` methods that
-describe the result of applying the operator, and its adjoint
-respectively, onto a compatible `DataContainer` input. The output is
-another `DataContainer` object or subclass hereof. An important special
-case is to represent the tomographic forward and backprojection
-operations.
-
-::: {.autoclass members=""}
-ccpi.optimisation.operators.Operator
-:::
-
-::: {.autoclass members=""}
-ccpi.optimisation.operators.LinearOperator
-:::
-
-::: {.autoclass members=""}
-ccpi.optimisation.operators.ScaledOperator
-:::
-
-Function
---------
-
-A `Function` represents a mathematical function of one or more inputs
-and is intended to accept `DataContainers` as input as well as any
-additional parameters.
-
-Fixed parameters can be passed in during the creation of the function
-object. The methods of the function reflect the properties of it, for
-example, if the function represented is differentiable the function
-should contain a method `gradient` which should return the gradient of
-the function evaluated at an input point. If the function is not
-differentiable but allows a simple proximal operator, the method
-`proximal` should return the proximal operator evaluated at an input
-point. The function value is evaluated by calling the function itself,
-e.g. `f(x)` for a `Function f` and input point `x`.
-
-::: {.autoclass members=""}
-ccpi.optimisation.functions.Function
-:::
-
-`Return Home <mastertoc>`{.interpreted-text role="ref"}