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Various improvements #3

Merged
merged 15 commits into from
Apr 11, 2023
Merged

Various improvements #3

merged 15 commits into from
Apr 11, 2023

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joegilkes
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Added a number of extra features, including

  • Support for canonicalisation of radical SMILES with OBCanonicalRadicals
  • NN ensemble uncertainty quantification
  • Automated hyperparameter optimisation

Also fixed a number of bugs, allowing for smoother operation when called in an automated fashion (e.g. through a bash submission script on a cluster, where a headless environment is necessary).

Previously, running `KPM predict` on a single reactant/product pair would cause KPM to fail due to NumPy loading in the enthalpy as a 0-dimensional array which couldn't be indexed. Fixed by enforcing a 1D array be loaded.
KPM could not run headless (without a `DISPLAY` environment variable set) due to it loading the `TkAgg` backend for Matplotlib. This has been fixed, so if `DISPLAY` is not set or empty, KPM will instead load the `Agg` backend, allowing for headless running of both training and rediction modes.
Calling `KPM predict` with a direction of 'forward' or 'backward' was failing due to an incorrectly set `num_reacs` in `calc_diffs()`. This has now been set correctly based on the requested prediction directionality.
Fixed ensemble training procedure to enable uncertainty quantification on Ea predictions by taking the variance over `nn_ensemble_size`. Added support for outputting uncertainty in both train/test correlation plots and prediction outputs.
Also added ability to choose whether Eacts should be internally normalised.
@idilismail
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Great! Thanks for adding this. I actually added & removed some of these features on my local copy, but did not merge.

@idilismail idilismail merged commit cb734b9 into idilismail:main Apr 11, 2023
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2 participants