Dear Scilab users,
A new version 0.2 of sci-sundials has been just released:
https://atoms.scilab.org/toolboxes/sci_sundials/0.2
Among other internal improvements and code factorization
-the differential-algebraic solver IDA is now available
-the documentation is now exhaustive about the features of solvers and
the options
There has been an important change in the api. For example for CVODE,
the two gateways cvode_solve() and cvode_extend() have been fused in
cvode() and the extension is done by giving the solution as first argument:
[t,y] = cvode(f,tspan,y0,options)
[t,y,te,ye,ie] = cvode(f,tspan,y0,options)
sol = cvode(...)
solext = cvode(sol,tfinal,options)
Still no gateway for ARKODE but I will now focus on the upgrade of
SUNDIALS in Sscilab itself.
Merry Christmas (in advance).
S.
Le 25/10/2021 à 16:35, Stéphane Mottelet a écrit :
Hi all,
As discussed in this thread last month
https://www.mail-archive.com/users@lists.scilab.org/msg10679.html
I am glad to annouce that a first version of the sci-sundials toolbox
(maybe part of Scilab in the future) is available on Atoms in the
"Differential Equations" category (refresh the package list if you
don't see it). To have an idea of its features I pasted below the
content of the README.md file on the gitlab project of sci-sundials
(https://gitlab.com/mottelet/sci-sundials/).
If you appreciate the work and want to help, doc, demos, or even more
if you know how to code in C and C++ you are welcome !
S.
What has been done and what is to be done
Until now only CVODE has been interfaced but many common features have
been developped in the OdeManager class, hence interfacing IDA will be
quite easy. ARKODE (various modern explicit, implicit and mixed
explicit/implicit Runge-Kutta solvers) does not exist in the old 2.4.0
version of Sundials which is used in Scilab hence won't be interfaced
unless an upgrade is done (Sundials is now at version 5.7.0). The
support of Sparse Jacobians is also missing for the same reason.
Features
The CVODE gateway cvode_solve() implements the following features
which were missing by the legacy LSODE/LSODA/LSODAR/... ode() gateway :
* full a posteriori access to solver continuous extension of
solution at arbitrary points via a MList output when only one lhs
is given:
|sol = cvode_solve(f, [t0 tf], y0) t = linspace(t0, tf, 1000) plot(t,
sol(t)) |
The |sol| MList fields gathers all information related to the obtained
solution (time steps, solution at time steps, events, ...). The solver
can be restarted by giving the MLlist as first argument to
|cvode_extend| :
|sol2 = cvode_extend(sol, tx, ...)|
where |tx| is the time point to which solution has to be extended. The
options of the call that yielded |sol| are used and can be changed as
optional named parameters after |tx|.
* a user-friendly access to solver options via optional named
parameters in cvode_solve call, i.e.
|cvode_solve(f, tspan, y0, h0=0.01, rtol=1e-3)|
* a really simpler way to give time span of integration allowing to
choose between error driven solver internal time steps and user
fixed time steps, i.e.
|[t,y] = cvode_solve(f, [t0 tf], y0) [t,y] = cvode_solve(f, [t0 t1 ...
tf], y0) [t,t] = cvode_solve(f, tspan, y0, t0=0)|
the latter style being the closest to actual |ode()| behavior where
solution is by default given at user time steps and |t0| is not
necessarily equal to |tspan(1)|, which is the default in the two
former calls above.
* a better and user-friendly specification of events via a variable
number of outputs event function (giving value of event equations,
wheter to stop integration for a given event and event direction
selection), minimal style beeing a single output. Information
about events is also simpler to get:
|function [eq,term,dir] = evfun(t,y) eq = y(1)-1.7; term = %f; dir =
1; end [t,y,te,ye,ie] = cvode_solve(f, tspan, y0, events = evfun) sol
= cvode_solve(f, tspan, y0, events = evfun)|
in the latter call information about events is recovered in
|sol.te,sol.ye,sol.ie|.
* support of complex solution with detection of complexity in |y0|
or |f(t0,y0)|, e.g.
|function out = crhs(t,y) out = 10*exp(2*%i*%pi*t)*y; end [t,y] =
cvode_solve(crhs, [0,5], 1) plot(t,real(y),t,imag(y))|
* Support of a callback function called after each successfull step,
giving access to current solver statistics and allowing to stop
integration (e.g. by a "stop" button on a GUI), e.g.
|function stop = scicallback(t,y,flag,stats) stop = %f if flag ==
"step" mprintf("%s : hlast=%g\n", flag, stats.hlast) end end [t,y] =
cvode_solve(f, tspan, y0, intcb=scicallback);|
* support of an arbitrary number of dimensions of ode state
Performance
|cvode_solve()| is roughly two times faster than |ode()| for both
fixed methods (Adams and BDF). As |ode()| already did, compiled and
dynamically linked C,C++ or Fortran externals are supported by
|cvode_solve()|. When using such externals instead of Scilab functions
|cvode_solve()| is generally an order of magnitude faster.
--
Stéphane Mottelet
Ingénieur de recherche
EA 4297 Transformations Intégrées de la Matière Renouvelable
Département Génie des Procédés Industriels
Sorbonne Universités - Université de Technologie de Compiègne
CS 60319, 60203 Compiègne cedex
Tel : +33(0)344234688
http://www.utc.fr/~mottelet
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--
Stéphane Mottelet
Ingénieur de recherche
EA 4297 Transformations Intégrées de la Matière Renouvelable
Département Génie des Procédés Industriels
Sorbonne Universités - Université de Technologie de Compiègne
CS 60319, 60203 Compiègne cedex
Tel : +33(0)344234688
http://www.utc.fr/~mottelet
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