Releases: SUNCAT-Center/CatLearn
Releases · SUNCAT-Center/CatLearn
Version 0.6.2 (March 2020)
- Added module for site featurization and GA feature selection.
- Fixed ML-NEB compatibility issue with FHI-AIMS ase calculator.
- Compatibility updated for ASE 3.19.0
- Compatibility updated for Pandas 0.24.0
- Compatibility updated for Scikit-learn 0.22.0
- Dropped support for python 2.
- Dropped support for python 3.5
- Added testing for python 3.7 and 3.8
Version 0.6.1 (April 2019)
- Fixed compatibility issue with MLNEB and GPAW
- Various bugfixes
Version 0.6.0 (January 2019)
- Added ML-MIN algorithm for energy minimization.
- Added ML-NEB algorithm for transition state search.
- Changed input format for kernels in the GP.
Version 0.5.0 (October 2018)
- Restructure of fingerprint module
- Pandas DataFrame getter in FeatureGenerator
- CatMAP API using ASE database.
- New active learning module.
- Small fixes in adsorbate fingerprinter.
Version 0.4.4 (August 2018)
- Major modifications to adsorbates fingerprinter
- Bag of site neighbor coordinations numbers implemented.
- Bag of connections implemented for adsorbate systems.
- General bag of connections implemented.
- Data cleaning function now return a dictionary with 'index' of clean features.
- New clean function to discard features with excessive skewness.
- New adsorbate-chalcogenide fingerprint generator.
- Enhancements to automatic identification of adsorbate, site.
- Generalized coordination number for site.
- Formal charges utility.
- New sum electronegativity over bonds fingerprinter.
# Version 0.4.3 (May 2018)
ConvolutedFingerprintGeneratoradded for bulk and molecules.- Dropped support for Python3.4 as it appears to start causing problems.
Version 0.4.2 (May 2018)
- Genetic algorithm feature selection can parallelize over population within each generation.
- Default fingerprinter function sets accessible using
catlearn.fingerprint.setup.default_fingerprinters - New surrogate model utility
- New utility for evaluating cutoff radii for connectivity based fingerprinting.
default_catlearn_radiusimproved.
Version 0.4.1 (April 2018)
- AtoML renamed to CatLearn and moved to Github.
- Adsorbate fingerprinting again parallelizable.
- Adsorbate fingerprinting use atoms.tags to get layers if present.
- Adsorbate fingerprinting relies on connectivity matrix before neighborlist.
- New bond-electronegativity centered fingerprints for adsorbates.
- Fixed a bug that caused the negative log marginal likelihood to be attached to the gp class.
- Small speed improvement for initialize and updates to GaussianProcess.