Re: [Haskell-cafe] FRP, integration and differential equations.

21 Apr 2009


      Hey thanks for the Adam-Bashford tip, didn't know that one yet (although I
used similar techniques in the past, didn't know it had a name :-)

Well, solving the ODE is usually the task of a dedicated physics engine. But
IMHO with FRP we try to reuse small building blocks so we get very modular
systems; a big physics black box seems to be against this principle?
On Tue, Apr 21, 2009 at 1:24 PM, Paul L  wrote:
...
Adam-Bashford method can be easily implemented to replace Euler's. But
to really get higher accuracy, one may need variable time steps and
perhaps even back tracking, which is an interesting topic on its own.
But my question is, is FRP really the right setting in which to
explore a highly accurate ODE solver?
On 4/21/09, Peter Verswyvelen  wrote:
...
Well, the current FRP systems don't accurately solve this, since they
just
use an Euler integrator, as do many games. As long as the time steps are
tiny enough this usually works good enough. But I wouldn't use these FRPs
to
guide an expensive robot or spaceship at high precision :-)
On Tue, Apr 21, 2009 at 11:48 AM, jean-christophe mincke <
jeanchristophe.mincke@gmail.com> wrote:
...
Paul,
Thank you for your reply.
Integration is a tool to solve a some ODEs but ot all of them. Suppose
all
we have is a paper and a pencil and we need to symbolically solve:
/
t
de(t)/dt = f(t)  -> the solution is given by e(t) = |      f(t) dt +
e(t0)
/
...
t0
de(t)/dt = f(e(t), t) -> A simple integral cannot solve it, we need to
use
the dedicated technique appropriate to this type of ODE.
Thus, if the intention of the expression
e = integrate *something *
is "I absolutely want to integrate *something* using some integration
scheme", I am not convinced that this solution properly covers the
second
case above.
However if its the meaning is "I want to solve the ODE : de(t)/dt =*
something* " I would be pleased if the system should be clever enough to
analyse the *something expression* and to apply or propose the most
appropriate numerical method.
Since the two kinds of ODEs require 2 specific methematical solutions, I
do
not find suprising that this fact is also reflected in a program.
I have not the same experience as some poster/authors but I am curious
about the way the current FRPs are able to accurately solve the most
simple
ODE:
de(t)/dt = e
All I have seen/read seems to use the Euler method. I am really
interested
in knowing whether anybody has implemented a higher order method?
Regards
J-C
On Tue, Apr 21, 2009 at 5:03 AM, Paul L  wrote:
...
Trying to give different semantics to the same declarative definition
based
on whether it's recursively defined or not seems rather hack-ish,
although
I can understand what you are coming from from an implementation angle.
Mathematically an integral operator has only one semantics regardless
of what's put in front of it or inside. If our implementation can't
match
this
simplicity, then we got a problem!
The arrow FRP gets rid of the leak problem and maintains a single
definition
of integral by using a restricted form of recursion - the loop
operator.
If you'd rather prefer having signals as first class objects, similar
technique
existed in synchronous languages [1], i.e., by using a special rec
primitive.
Disclaimer: I was the co-author of the leak paper [2].
[1] A co-iterative characterization of synchronous stream functions, P
Caspi, M Pouzet.
[2] Plugging a space leak with an arrow, H. Liu, P. Hudak
--
Regards,
Paul Liu
Yale Haskell Group
http://www.haskell.org/yale
...
In a post in the *Elerea, another FRP library *thread*,* Peter
Verswyvelen
wrote:
*>I think it would be nice if we could make a "reactive benchmark" or
something: some tiny examples that capture the essence of reactive
systems,
and a way to compare each solution's >pros and cons.* *
*
*>For example the "plugging a space leak with an arrow" papers
reduces
...
recursive signal problem to
*
*
*
*>e = integral 1 e*
*
*
 *>Maybe the Nlift problem is a good example for dynamic collections,
but I
guess we'll need more examples.*
*
*
*>The reason why I'm talking about examples and not semantics is
because
...
latter seems to be pretty hard to get right for FRP?*
I would like to come back to this exemple. I am trying to write a
small
FRP
in F# (which is a strict language, a clone of Ocaml) and I also came
across
space and/or time leak. But maybe not for the same reasons...
Thinking about these problems and after some trials and errors, I
came
to
the following conclusions:
I believe that writing the expression
e = integral 1 *something*
where e is a Behavior (thus depends on a continuous time).
has really two different meanings.
1. if *something *is independent of e, what the above expression
means
is
the classical integration of a time dependent function between t0 and
t1.
Several numerical methods are available to compute this integral and,
as
far
as I know, they need to compute *something *at t0, t1 and, possibly,
at
intermediate times. In this case, *something *can be a Behavior.
2. If *something *depends directly or indirectly of e then we are
faced
with
a first order differential equation of the form:
de/dt = *something*(e,t)
where de/dt is the time derivative of e and  *something*(e,t)
indicates
that *something* depends, without loss of generality, on both e and
t.
There exist specific methods to numerically solve differential
equations
between t0 and t1. Some of them only require the knowledge of e at t0
(the
Euler method), some others needs  to compute *something *from
intermediate
times (in [t0, t1[ ) *and *estimates of e at those intermediary
times.
3. *something *depends (only) on one or more events that, in turns,
are
computed from e. This case seems to be the same as the first one
where
...
integrand can be decomposed into a before-event integrand and an
after-event
integrand (if any event has been triggered). Both integrands being
independent from e. But I have not completely investigated this case
 yet...
Coming back to my FRP, which is based on residual behaviors, I use a
specific solution for each case.
Solution to case 1 causes no problem and is similar to what is done
in
classical FRP (Euler method, without recursively defined behaviors).
Once
again as far as I know...
The second case has two solutions:
1. the 'integrate' function is replaced by a function 'solve' which
has
...
following signature
solve :: a -> (Behavior a -> Behavior a) -> Behavior a
In fact,  *something*(e,t) is represented by an integrand
function
from behavior to behavior, this function is called by the
integration           method. The integration method is then free to
...
estimates of e, as constant behaviors, to the integrand function.
The drawbacks of this solution are:
      - To avoid space/time leaks, it cannot be done without side
effects
(to be honest, I have not been able to  find a solution without
assignement). However these side effects are not visible from outside
of
On 4/20/09, jean-christophe mincke 
wrote:
the
the
the
the
pass
the
...
solve function. ..
      - If behaviors are defined within the integrand function, they
are
not
accessible from outside of this integrand function.
2. Introduce constructions that looks like to signal functions.
solve :: a -> SF a a -> Behavior a
where a SF is able to react to events and may manage an internal
state.
   This solution solves the two above problems but make the FRP a bit
more
complex.
Today, I tend to prefer the first solution, but what is important, in
my
opinion, is to recognize the fact that
e = integral 1 *something*
really addresses two different problems (integration and solving of
differential equations) and each problem should have their own
solution.
The consequences are :
1. There is no longer any need for my FRP to be able to define a
Behavior
   recursively. That is a good news for this is quite tricky in F#.
   Consequently, there is no need to introduce delays.
   2. Higher order methods for solving of diff. equations can be used
(i.e.
   Runge-Kutta). That is also good news for this was one of my main
goal
in
   doing the exercice of writing a FRP.
Regards,
J-C
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--
Regards,
Paul Liu
Yale Haskell Group
http://www.haskell.org/yale