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)

• ConvolutedFingerprintGenerator added 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_radius improved.

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.