| Copyright | Copyright (c) 2009-2016 David Sorokin <david.sorokin@gmail.com> |
|---|---|
| License | BSD3 |
| Maintainer | David Sorokin <david.sorokin@gmail.com> |
| Stability | experimental |
| Safe Haskell | None |
| Language | Haskell2010 |
Simulation.Aivika.Trans.Transform.Memo
Description
Tested with: GHC 8.0.1
This module defines memoization transforms. The memoization creates such Dynamics
computations, which values are cached in the integration time points. Then
these values are interpolated in all other time points.
- memoTransform :: MonadSD m => Transform m e e
- memo0Transform :: MonadSD m => Transform m e e
- iteratingTransform :: MonadSD m => Transform m () ()
Documentation
memoTransform :: MonadSD m => Transform m e e Source #
A transform that memoizes and order the computation in the integration time points
using the interpolation that knows of the Runge-Kutta method. The values are
calculated sequentially starting from starttime.
memo0Transform :: MonadSD m => Transform m e e Source #
A transform that memoizes and order the computation in the integration time points using
the discreteDynamics interpolation. It consumes less memory than the memoTransform
computation but it is not aware of the Runge-Kutta method. There is a subtle
difference when we request for values in the intermediate time points
that are used by this method to integrate. In general case you should
prefer the memo0Transform computation above memoTransform.
iteratingTransform :: MonadSD m => Transform m () () Source #
A transform that iterates sequentially the dynamic process with side effects in
the integration time points. It is equivalent to the memo0Transform computation
but significantly more efficient, for the internal array is not created.