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Is it possible to restrict the domain of a parameter such that it: > takes only integral values > takes only odd numbers (subset of above case) I do remember reading that: The PRAXIS optimizer used by NEURON requires a continuous objective function, so restricting parameter space can actually interf...

Yes, the three points are connected by straight line segments. I tried what you suggested about restricting regions. Firstly, I found that it was not possible to position the blue lines such that they were between two of our points of interest. I even tried using the weight panel and entering the st...

I took your last suggestion and created a custom function for logging data after each run. It appears to be working well after resolving some errors along the way. Posting it here for your confirmation and in case it would be handy for anyone else: optwrap.hoc needs to be updated to: begintemplate O...

Regarding the first question: > I followed your suggestion and set up a similar toy model (preferred 'hh' instead of 'pas' as I had it ready). The results were interesting but left me with further queries! The data to be fitted was a shape of an AP (with tweaked values of HH parameters) with just 3 ...

I found the two additional calls to "optwrap_efun()" from "prun()" in 'optwrap.hoc'... but as it is part of a different template (OptimizerWrap) I could not invoke "after_quad()". As the latter belongs to template "MulfitPraxWrap", I tried locating an instance...

I have two queries: 1> If the data (voltage vs time) to be fitted is sampled at irregular intervals, does MRF while evaluating the fitness consider only the points provided (loaded from file) or does it implicitly perform a linear interpolation between the data points - and then use all these values...

As savepath.fit (by default) 'does not save after every run but only the best result after each quadratic form', I wanted to make changes such that it logged data after each run. I tried the below: You can look at nrn/lib/hoc/mulfit/fitparm.hoc and put a call to saveval() in the praxis_efun() functi...

Yupp, its working now. Thanks! I thought I would post this for future reference (hoping I am right): savepath.fit saves several columns of date for each entry. Their meanings: Line 1: start (just a label) Line 2: Number of Lines and Columns Line 3 onwards: Column 1: Quadratic Expression Number Colum...

I was using the MRF and wanted to save the various parameter set combinations it was using in arriving at its final set. I clicked the "Append the path to savepath.fit" checkbox and ran the Optimizer but did not see any file being created. On going through "nrn/lib/hoc/mulfit/fitparm....

You could get it done using a variant of NEURON's 'for' loop. Check out the third variant mentioned in the documentation: http://www.neuron.yale.edu/neuron/static/new_doc/programming/ockeywor.html#index-8 : for (var) stmt Loops over all segments of the currently accessed section. var begins at 0 and...

Thanks for pointing that out. After seeing your post I tested some variations of the error function and I observed the following (might be handy for others starting with the Multiple Run Fitter): 1> The error function should return a value >= 0. If the above rin() is used to return just the differen...

I think I got the general idea on how to approach this from another post ( https://www.neuron.yale.edu/phpBB/viewtopic.php?f=23&t=501 ). Based on that, I have defined a function which computes the difference between my required value of Rin (say) and the model's run value of Rin and added to it ...

I recently went through the two tutorials for MRF (detailed and well laid out - perfect for beginners) and had one general query: Most (all?) of the fitting seems to be of the type "minimize the total deviation of the simulated curves from the experimental curves". I was wondering if and h...

Thanks a lot! That takes care of all the queries I had at the moment.

Thanks that clears everything for now. Maybe more (hopefully not) when I start shifting to parallel implementation of gap junctions!