Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

mannually increase maxfev #605

Open
hguo28 opened this issue Apr 23, 2024 · 1 comment
Open

mannually increase maxfev #605

hguo28 opened this issue Apr 23, 2024 · 1 comment

Comments

@hguo28
Copy link

hguo28 commented Apr 23, 2024

Hi Dear Developers

I just begin to use MDsuite. When I try to simulate MSD and distinct MSD. I received the error like:
"/gpfs/fs1/home/ac.hguo/myopt/MDSuite/tensorflow/lib/python3.8/site-packages/scipy/optimize/_minpack_py.py", line 864, in curve_fit
raise RuntimeError("Optimal parameters not found: " + errmsg)
RuntimeError: Optimal parameters not found: Number of calls to function has reached maxfev = 600.
It seems hard to received fitting. Could I mannually set maxfev or deal with this problem by some way?

And by the way, do you have any suggestions about how many frames to be used in MSD simulation in MDsuite?

Sincerely,
Hanzeng GUO

@SamTov
Copy link
Member

SamTov commented Apr 23, 2024

Hi Hanzeng,

Thanks for the comment! I have not seen this error message before but it seems like the line could not be fit. This could mean that your data is way too noisy or not long enough such that the fitting could not be performed.

By number of frames are you talking about the time in each MSD function or the number of MSD ensembles you should use? In both cases, this is very system dependant. For slow moving systems you will find you need much longer MSDs as they take a long time to enter into a diffusive regime. They will also typically need better statistics which means more ensembles.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants