# Package org.apache.commons.math3.ode

This package provides classes to solve Ordinary Differential Equations problems.

See: Description

- Interface Summary
  Interface | Description
  --- | ---
  FirstOrderDifferentialEquations | This interface represents a first order differential equations set.
  FirstOrderIntegrator | This interface represents a first order integrator for differential equations.
  MainStateJacobianProvider | Interface expanding `first order differential equations` in order to compute exactly the main state jacobian matrix for `partial derivatives equations`.
  MultistepIntegrator.NordsieckTransformer | Transformer used to convert the first step to Nordsieck representation.
  ODEIntegrator | This interface defines the common parts shared by integrators for first and second order differential equations.
  Parameterizable | This interface enables to process any parameterizable object.
  ParameterizedODE | Interface to compute by finite difference Jacobian matrix for some parameter when computing `partial derivatives equations`.
  ParameterJacobianProvider | Interface to compute exactly Jacobian matrix for some parameter when computing `partial derivatives equations`.
  SecondaryEquations | This interface allows users to add secondary differential equations to a primary set of differential equations.
  SecondOrderDifferentialEquations | This interface represents a second order differential equations set.
  SecondOrderIntegrator | This interface represents a second order integrator for differential equations.

- Class Summary
  Class | Description
  --- | ---
  AbstractIntegrator | Base class managing common boilerplate for all integrators.
  AbstractParameterizable | This abstract class provides boilerplate parameters list.
  ContinuousOutputModel | This class stores all information provided by an ODE integrator during the integration process and build a continuous model of the solution from this.
  EquationsMapper | Class mapping the part of a complete state or derivative that pertains to a specific differential equation.
  ExpandableStatefulODE | This class represents a combined set of first order differential equations, with at least a primary set of equations expandable by some sets of secondary equations.
  ExpandableStatefulODE.SecondaryComponent | Components of the compound stateful ODE.
  FirstOrderConverter | This class converts second order differential equations to first order ones.
  JacobianMatrices | This class defines a set of `secondary equations` to compute the Jacobian matrices with respect to the initial state vector and, if any, to some parameters of the primary ODE set.
  JacobianMatrices.MainStateJacobianWrapper | Wrapper class to compute jacobian matrices by finite differences for ODE which do not compute them by themselves.
  MultistepIntegrator | This class is the base class for multistep integrators for Ordinary Differential Equations.
  ParameterConfiguration | Simple container pairing a parameter name with a step in order to compute the associated Jacobian matrix by finite difference.
  ParameterizedWrapper | Wrapper class enabling `basic simple` ODE instances to be used when processing `JacobianMatrices`.
  ParameterJacobianWrapper | Wrapper class to compute Jacobian matrices by finite differences for ODE which do not compute them by themselves.

- Exception Summary
  Exception | Description
  --- | ---
  JacobianMatrices.MismatchedEquations | Special exception for equations mismatch.
  MultistepIntegrator.InitializationCompletedMarkerException | Marker exception used ONLY to stop the starter integrator after first step.
  UnknownParameterException | Exception to be thrown when a parameter is unknown.

## Package org.apache.commons.math3.ode Description

This package provides classes to solve Ordinary Differential Equations problems.

This package solves Initial Value Problems of the form `y'=f(t,y)` with `t0` and `y(t0)=y0` known. The provided integrators compute an estimate of `y(t)` from `t=t0` to `t=t1`. It is also possible to get thederivatives with respect to the initial state `dy(t)/dy(t0)` or the derivatives with respect to some ODE parameters `dy(t)/dp`.

All integrators provide dense output. This means that besides computing the state vector at discrete times, they also provide a cheap mean to get the state between the time steps. They do so through classes extending the `StepInterpolator` abstract class, which are made available to the user at the end of each step.

All integrators handle multiple discrete events detection based on switching functions. This means that the integrator can be driven by user specified discrete events. The steps are shortened as needed to ensure the events occur at step boundaries (even if the integrator is a fixed-step integrator). When the events are triggered, integration can be stopped (this is called a G-stop facility), the state vector can be changed, or integration can simply go on. The latter case is useful to handle discontinuities in the differential equations gracefully and get accurate dense output even close to the discontinuity.

The user should describe his problem in his own classes (`UserProblem` in the diagram below) which should implement the `FirstOrderDifferentialEquations` interface. Then he should pass it to the integrator he prefers among all the classes that implement the `FirstOrderIntegrator` interface.

The solution of the integration problem is provided by two means. The first one is aimed towards simple use: the state vector at the end of the integration process is copied in the `y` array of the `FirstOrderIntegrator.integrate` method. The second one should be used when more in-depth information is needed throughout the integration process. The user can register an object implementing the `StepHandler` interface or a `StepNormalizer` object wrapping a user-specified object implementing the `FixedStepHandler` interface into the integrator before calling the `FirstOrderIntegrator.integrate` method. The user object will be called appropriately during the integration process, allowing the user to process intermediate results. The default step handler does nothing.

`ContinuousOutputModel` is a special-purpose step handler that is able to store all steps and to provide transparent access to any intermediate result once the integration is over. An important feature of this class is that it implements the `Serializable` interface. This means that a complete continuous model of the integrated function throughout the integration range can be serialized and reused later (if stored into a persistent medium like a filesystem or a database) or elsewhere (if sent to another application). Only the result of the integration is stored, there is no reference to the integrated problem by itself.

Other default implementations of the `StepHandler` interface are available for general needs (`DummyStepHandler`, `StepNormalizer`) and custom implementations can be developed for specific needs. As an example, if an application is to be completely driven by the integration process, then most of the application code will be run inside a step handler specific to this application.

Some integrators (the simple ones) use fixed steps that are set at creation time. The more efficient integrators use variable steps that are handled internally in order to control the integration error with respect to a specified accuracy (these integrators extend the `AdaptiveStepsizeIntegrator` abstract class). In this case, the step handler which is called after each successful step shows up the variable stepsize. The `StepNormalizer` class can be used to convert the variable stepsize into a fixed stepsize that can be handled by classes implementing the `FixedStepHandler` interface. Adaptive stepsize integrators can automatically compute the initial stepsize by themselves, however the user can specify it if he prefers to retain full control over the integration or if the automatic guess is wrong.

Fixed Step Integrators
Name | Order
`Euler` | 1
`Midpoint` | 2
`Classical Runge-Kutta` | 4
`Gill` | 4
`3/8` | 4

Adaptive Stepsize Integrators
Name | Integration Order | Error Estimation Order
`Higham and Hall` | 5 | 4
`Dormand-Prince 5(4)` | 5 | 4
`Dormand-Prince 8(5,3)` | 8 | 5 and 3
`Gragg-Bulirsch-Stoer` | variable (up to 18 by default) | variable
`Adams-Bashforth` | variable | variable
`Adams-Moulton` | variable | variable

In the table above, the `Adams-Bashforth` and `Adams-Moulton` integrators appear as variable-step ones. This is an experimental extension to the classical algorithms using the Nordsieck vector representation.

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