Re: [chimerax-users] Trajectory computation slowing down overtime

Hi Shubham,

Without seeing your code it's hard to comment more specifically, but are you perhaps appending to lists that are then growing through the course of the process. It can sometimes be better to initialise numpy arrays instead and add things to them by indexing.

For example,

x = np.array((3,2)) for i, frame in enumerate(list_frames): Set current frame to frame for j, pair in enumerate(specific_residue_pairs): x[i, j] = result of computation

Best wishes James

Shubham Devesh Ramgoolam via ChimeraX-users chimerax-users@cgl.ucsf.edu escribió:

I just wanted to specify that I am using the nogui mode of chimeraX for the computation. Shubham.

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From: Shubham Devesh Ramgoolam Sent: June 12, 2022 1:38 AM To: chimerax-users@cgl.ucsf.edu chimerax-users@cgl.ucsf.edu Subject: Trajectory computation slowing down overtime

Hi all,

I hope you are doing well.

I have a Python script for analyzing specific residue pairs for every frame in a trajectory.

It does so, by using 2 for loops:

For frame in list_frames:

           Set current frame to frame

           For pair in specific_residue_pairs:

                          Do computation

The computation involves defining geometric objects(centroids, axes, planes) and performing calculations with them(distance, angles).

The issue here is that as we move further in list_frames, the computation takes longer and longer. There is a somewhat linear increase in computation time, as illustrated below:

[cid:image003.png@01D87E37.C872FDF0]

Is there a way to maintain the same computation time for every frame in the trajectory?

Regards,

Shubham Ramgoolam

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