Archiving is done with metafor.getTimeStepManager(). An initial time and time step is set using setInitialTime(), then a series of subsequent steps are set using setNextTime(). Then number of archives between two time steps is given as argument to setNextTime().
tsm = metafor.getTimeStepManager() tsm.setInitialTime(t0, muli) tsm.setNextTime(t1, npas, mulm) ...
where
t0 | initial time |
t1 | next time |
muli | initial time step |
mulm | maximal time step between t0 and t1 |
npas | number of archives between t0 and t1 |
This section describes how to deal with Metafor output, which are called Fac files, and created by the object called Metafac (.bfac, .tfac).
Each time step is saved in a different file. This way, useless steps can be easily deleted, and a restart can be done.
By default, archiving is done in binary (.bfac - in opposition to .tfac, text version or ASCII). If zlib is available, files are compressed immediately (into .bfac.gz).
Note that a binary file is usually not portable between various OS.
By default, archiving files are sent to a folder called workspace/test_name/ and are called step_*.bfac.gz.
Some scripts, found in oo_meta/toolbox/utilities.py, were written to easily see the result of a simulation, to convert into a different format, … These files can be modified by the user to suit a particular application.
To load the 10th time step,
loadFac('rep1.rep2.mytest', 10)
(assuming that the file mytest.py is located in /rep1/rep2/). If no time step is specified, Metafor loads the one having the highest number.
To view it :
vizu('rep1.rep2.mytest')
Automatic conversion from bfac/tfac to bmp:
makeAnimation('rep1.rep2.mytest')VizWin window is opened with the first time step and the user is put on hold.VizWin window is not hidden by an object on the screen (otherwise it might appear in the screenshots).Automatic creation of the movie:
The time step is monitored using the commands:
tsm = metafor.getTimeStepManager() tsm.setTimeStepComputationMethod(meth) tsm.setTolOnFac(tolOnFac) tsm.setIntegrationErrorTolerance(prec) tsm.setExplicitTimeStepSecurity(secu) tsm.setNbOfStepsForCriticalTimeStepUpdate(nrit) tsm.setMaxNbOfItInAdaptOfTimeStep(nbIter) (option: used in implicit or quasi-static) tsm.setMinimumTimeStep(minTimeStep)
^ Parameter ^ Default value ^ Description ^
meth | = TSM_NBOFITERATIONSMETHOD : in implicit, the current time step depends on the number of iterations in the previous time step, when in explicit it only depends on the critical one and the parameter secu |
|
= TSM_INTEGRATIONERRORMETHOD : the current time step is computed based on an integration error (and based on the critical one and the parameter secu in explicit) |
||
prec | 1.E-4 | accuracy on the integration error |
secu | 2.0/3.0 | safety coefficient which multiplies the critical time step in explicit |
nrit | 1 | number of time steps before updating the critical time step |
nbIter | 5 | Minimal number of iterations in the algorithm in charge of reducing the time step. If the required number is greater than nbIter, the subsequent time step will be lower than the current one. Otherwise, it will be equal or greater. |
minTimeStep | 1.0E-10 | minimum time step below which metafor stops running. |
tolOnFac | 0.1 | tolerance on time step for the discrete times corresponding to archiving (FAC). |
Two possibilities are used to compute the time step:
Since these schemes are conditionally stable, the time step $\Delta t$ is given by :
$ \Delta t = \gamma_s \Delta t_{crit} $
Where $\Delta t_{crit}$ depends on the maximal eigenfrequency of the system (obtained using the method called “power iteration”, and updated regularly) and $\gamma_s$, a safety coefficient which can be computed two ways: