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To be discussed - I think some kind of diagramatic representation of the transformation might be worth it here? Like some kind of thermodynamic cycle figure?
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(I know it's in the inline comment, but maybe it would be worth moving it here under a sub-heading?): we should mention what the endstates are in terms of chemicalsystems, i.e. hydration free energy of ligand is ligand+water to water.
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It would be good to offer a short overview of what the default settings are and what we are changing here. Nothing too fancy, just a "by default we run N repeats with solvent & vacuum simulation lengths of Y and Z over L lambda windows, to speed things up here we instead do...".
Maybe also worth bringing down the number of repeats to 1 to speed up the notebook?
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You should be able to just call settings here and get the pprint dictionary output.
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We don't have a way to gather results from CLI right now. Maybe it's worth saving the Python API results to disk and then here we re-load them? Not sure if that's too complicated for users though.
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IAlibay
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Overall looks good! Just added some early comments (I know it's still WIP).
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Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
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@hannahbaumann I've added the results json by quick-running the |
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I added a short thing about reloading a json file, does this look good @IAlibay ? |
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- [enhancement] Something I found out recently, apparently you can use greek alphabet in jupyter notebooks using the
\command, so\Deltamight work (I never tried it in practice). - re: "decoupled", I'm not sure if it would be too complicated for readers so feel free to say no - do you think that setting this as "partially decoupled (annihilated coulombics, decoupled Lennard-Jones)" might be worth it? (it makes it quite the sentence, so maybe not)
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Added a sentence describing this.
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I've been trying to think about the information flow here, how about something like this:
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Finally now that we've run our simulations, let's go ahead and gather the free energies for both phases.
Python API
If you executed the simulations using the Python API, you will have generated a dag_results object. You can analyze these results by calling the Protocols' gather() method. This takes a list of completed DAG results and returns a AbsoluteSolvationProtocolResult which can return a free energy estimate and uncertainty by calling the get_estimate() and get_uncertainty() methods."
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Then above this cells we could say:
"You can save the AbsoluteSolvationProtocolResult to a JSON output file in the following manner:"
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And here above this one:
"
CLI / Quickrun
If you ran the simulation using the CLI (i.e. by calling openfe quickrun ) you will end up with the same JSON output file as the one created in the previous cell. To get your simulation results you can load them back into Python in the following manner:
"
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This is looking great! Just a couple of text suggestions for the last section (mostly trying to be a bit more verbose). |
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Just in case - I pushed 1fc6666 to update the settings outputs (the checkpoint default value changed) |
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