changing parameters when continuing from a backup file is not possible

Question

I think there might be a bug, or something strange when working with a backup.

I the link, you can find a minimal example of something that goes wrong:

First I ran the ./backup.py to make a simulation A in a 1 by 1 cm tissue of 25 ms.

Then I run ./test1.py to continue with simulation A but the change a parameter of the tt2 model

Then I run ./test2.py to continue with simulation A but the change another parameter of the tt2 model

However, both simulation give exactly the same results, meaning that the parameter did not change...

I think this might be a bug in the system,

you can find all the simulations and the minimal examples here

Thanks a lot!

Best

Nele

Answer 1

Hi!

The difference between your modifications is mostly in the repolarisation wavefront. You can check the cellular differences with bench.

I changed your .par files to run till 500ms. At 300ms, the difference is easy to see:

comparison image

I also compared everything against simulations without checkpoints and the solutions seem sound. I dont see an issue here.

Also, it is easier for us to track potential bugs if you add your observations to the issue tracker .

Bets wishes, Aurel

Comments

Hi Aurel,

I uploaded my question again. For me the problem still persists. You can see it in my question (please download it again) by comparing both test1/vm.igb and test2/vm.igb

$diff test1/vm.igb test2/vm.igb

and no output means they are exactly the same. I just recently installed openCARP from the source code.

Also with meshalyzer I see the outputs are exactly the same, there are no difference between the figures.

Do you want me to add this example to the issue tracker?


Thanks a lot,
Best
Nele

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The updated experiment only modifies a state variable (GKr), not a model parameter.

the im_param option is intended to modify model parameters, not state. Model parameters are (mostly constant) variables influencing how a model works. On the other hand, state variables change in time and contain a current state of a model. Some models have variables being parameters and state at the same time.

It is important to keep in mind that im_param modifies a model, as if the model specification would have been changed, therefore, before it is applied to the concrete experiment. As such, your experiment setup first redefines the starting value of GKr in the TT2 model, then chooses to restore a previously stored state, thus overwriting the state variable modification.

If you change GKr for GNa, which is a pure model parameter, you will see that the results are indeed different when restarting.

This is a very subtle thing. I will add an issue, to parse the user input for this setting and issue a warning.

Best wishes,
Aurel

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Hi Aurel,

I start to see it now.

How can I change GKr then? I mean, how can I also make it a model parameter? Is there some explanation on openCARP on that?

Related to that question, how can I make any constant of the model a model parameter?  Do I need to change the model itself?

If so, how can I recompile the model so I can also use that...

Thanks a lot!
Best
Nele