Core functionality Argmin Optimizaton toolbox core
This crate contains the core functionality of argmin. If you just want to run an optimization method, this is not what you are looking for. However, if you want to implement your own solver based on the argmin architecture, you should find all necessary tools here.
Output parameter vectors to file
Loggers based on the
Observer which visualizes the progress of the solver
The datastructure which is returned by the
A simple key-value storage
Final struct returned by the
This type is necessary in order to be able to implement
A logger based on
Maintains the state from iteration to iteration of a solver
Minimal No-op operator which does nothing, really.
Fake Operators for testing No-op operator with free choice of the types
Container for observers which acts just like a single
This wraps an operator and keeps track of how often the cost, gradient and Hessian have been computed and how often the modify function has been called. Usually, this is an implementation detail unless a solver is needed within another solver (such as a line search within a gradient descent method), then it may be necessary to wrap the operator in an OpWrapper.
Helper class for visualized surface
Visualize iterations of a solver for cost functions of type (x,y) -> cost , where x and y are real numbers. If the solver is population-based, The current population is also visualized.
Write parameter vectors to file
Argmin error type
Defines at which intervals a checkpoint is saved.
This is used to indicate how often the observer will observe the status.
Indicates why the optimization algorithm stopped
Different kinds of serializers
Return the conjugate
(Pointwise) Divide a
Dot/scalar product of
Trait alias to simplify common trait bounds
Compute the inverse (
Defines a common interface for line search methods.
Minimum and Maximum of type
(Pointwise) Multiply a
Common interface for beta update methods (Nonlinear-CG)
Compute the l2-norm (
This trait needs to be implemented for every operator/cost function.
Create a random number
Return the transpose (
Defines a common interface to methods which calculate approximate steps for trust region methods.
Dot/scalar product of
Return param vector of all zeros (for now, this is a hack. It should be done better)
Zero for dynamically sized objects
Defines the interface every Observer needs to expose
Load a checkpoint from disk