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| GitHub Action JW: I’ll take care of that right now and I’ll greatly increase the limit LW: How much is it? LW: Do we have a budgeted ceiling on this? Fun fact, the Mac runners are the most expensive LW: I’m not seeing any LFS costs JW: Fixed it! Added a $30/month limit for LFS here
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New Psi4 docker image | Jeff regrets being happy to help Updated PR to require QCFractal 0.61 (the most recent) or later version. Can Jeff approve? See GitHub Actions |
QDS handling of non-QCSubmit dataset. | New module in a PR for QCFractal: qcportal.external.scaffold.py to create a json of the dataset and recapitulate a json back into a QCFractal dataset. See notes QDS Lifecycle: Will tackle in May 18th June 2nd iteration since Sage dataset releases were pushed back by QCFractal release. |
Update on clean force field releases | QDS Submissions Sage 2.0.0 is Done, Sage 2.1.0 and Sage 2.20 will be submitted at the end of the week. Docker Image We should be able to use the same one generated for QDS (6 GB). From Last Meeting: JC: Even though I think this is a little high, I think we should put them together and include a python script in the image to easily process the data.
Action Item: JC needs to make this code/notebook to package in docker, permission to make a ticket? LW: I agree that 6 GB is not small but fine, yes go ahead and make a ticket. JC – I’ll try to do this this week so JW is still around. JW – I’d keep the notebook really general so the same format can be used for other entries with no/minimal modifications.
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Update Dataset Tracking | Project Board; Slides |
psi4_utilities | When contributing basis sets, Lori requests that a basis set with diffuse functions be separated into the base-basis set and an auxiliary set of basis functions. I made a module to do this and used it successfully to add additional atom support for aug-cc-pvtz (set for next release…last psi4 release was Feb 2024). Another module is meant to estimate the amount of memory needed for a psi4 calculation. I have a draft done and am running it on my TM Benchmarking dataset. There are two ways to estimate the number of basis functions, auxiliary, and virtual functions, an educated number, and explicitly with the wavefunction. The latter is not recommended due to the amount of time it takes but it’s required for the 3c methods which don’t use traditional basis sets like other methods…. my script is still running… Lily and I can discuss more at our check-in.
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MolSSI Info / Align Priorities on MolSSI Asks | 2025-05-13 QCArchive User Meeting New from last QCAUM meeting: Requests: I’m ran a notebook to benchmark the disparity between iterating over entries and records to make a case to Ben that the latter is prohibitive. (Just sent results today) It takes an order of magnitude longer to iterate through records than entries, even though I’ve fetched both to cache ahead of time. With this in mind, it takes ~90 min to fetch the entries for my large dataset, which would correspond to 15 hours for records JW: On one hand, we shouldn’t request a change in output since we want to consistently encourage BP to keep a stable API, but on the other hand this is a young function and we’re the only people who use this. JW: We had an issue with the new QCFractal release breaking our CI LW: What if we change our CI to pull from the main branch of QCPortal to foresee these issues before a release? MT: That’s an amazing idea, I’m making a Zenhub ticket for it now.
Can we have the spin density calculated and output without long term saving of the wavefunction.energy, wfn = psi4.energy("uhf/6-31G(d)", return_wfn=True) psi4.cubeprop(wfn) |
Old Issue of the Week | Decided to always leave a comment and a tag “reviewed-2025“. Skip this segment for this week |
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