Dataframe serialization, Transfer learning, Active Learning and Maintenance

What's Changed

• Make link to logo an url by @bertiqwerty in #416
• Readme example by @bertiqwerty in #419
• Remove polyfill.io (#417) by @DavidWalz in #420
• Add detergent to api by @bertiqwerty in #421
• remove try-catch from scipy import by @bertiqwerty in #418
• Types for bounds by @jduerholt in #423
• BNH and TNK by @jduerholt in #424
• Add arXiv reference to README by @TobyBoyne in #425
• Interpoint constraints for botorch strategies by @jduerholt in #426
• Feature Scaling in DoE by @jduerholt in #358
• Update CONTRIBUTING.md by @R-M-Lee in #432
• Make feature validation part of the constraints. by @jduerholt in #427
• new benchmark with sum of mvnorm pdfs by @R-M-Lee in #434
• Add default generators by @jduerholt in #431
• Update information on GAUCHE by @jduerholt in #437
• EqalityConstraint --> EqualityConstraint by @jduerholt in #440
• Use weights_only for load by @kit1980 in #429
• Tutorial on Transfer Learning Bayesian Optimisation by @jpfolch in #439
• Active Learning by @jdridder in #361
• Move variance of fixed features check to predictive strategy by @bertiqwerty in #441
• Moving Output Objective by @jduerholt in #442
• Applying linting to notebooks by @CompRhys in #445
• [QOL] Use LogEI by default in the Tutorials and unrelated tests. by @CompRhys in #449
• Linear Interpolation by @jduerholt in #443
• Serialization for Candidates and Experiments Data Frames by @jduerholt in #452

New Contributors

• @kit1980 made their first contribution in #429
• @CompRhys made their first contribution in #445

Full Changelog: v0.0.13...v0.0.14

BNN Surrogates, High dim BO, Logo, fixes

What's Changed

• Remove math.inf from ContinuousInput data model by @jduerholt in #387
• Add generic typing to Constraints by @TobyBoyne in #386
• Initial attempt to incorporate MultiTask GPs by @jpfolch in #353
• fixed wrong link in docu by @niklaswulkow in #391
• add to_candidates for stepwise strategy by @jkleinekorte in #392
• Remove get_features, get_feature_keys, and get_feature from Domain by @jduerholt in #393
• Make surrogates available in the Stepwise Strategy by @jduerholt in #394
• name construction in a method by @bertiqwerty in #395
• Feature type hints by @bertiqwerty in #396
• FractionalFactorialStrategy by @jduerholt in #397
• Fix bug in get_scaler by @jduerholt in #400
• ZDT1 Benchmark Tutorial by @jduerholt in #401
• Implement Priors from "Vanilla Bayesian Optimization Performs Great in High Dimensions" by @jduerholt in #402
• Refactor the fractional factorial strategy by @jduerholt in #403
• duplicates plot by @jduerholt in #404
• FIx warning in Iterative Trimming Module by @jduerholt in #406
• Compatibility fix for latest scipy by @jduerholt in #411
• Code example in README by @TobyBoyne in #410
• Infinite Width BNN Kernel and Surrogate by @jduerholt in #405
• Finally a Logo by @jduerholt in #412
• add icon by @jduerholt in #415
• Logo in docs intro by @R-M-Lee in #413
• add bofire logo to docs by @bertiqwerty in #414

New Contributors

• @jpfolch made their first contribution in #353

Full Changelog: v0.0.12...v0.0.13

Classification surrogates, Entmoot and LinearDeterministicSurrogate

What's Changed

• Classification surrogates by @gmancino in #297
• Automatic Hyperparameter Optimization for Mixed GPs by @jduerholt in #357
• Add Task Feature by @jduerholt in #360
• Refactoring of stepwise strategies and introduction of transforms by @bertiqwerty in #355, #365 and #363
• User guide for surrogates by @niklaswulkow in #370 and #371
• Implement ENTMOOT in Bofire by @TobyBoyne in #278
• Make batch_limit and maxiter configurable by @jduerholt in #380
• LinearDeterministicSurrogate by @jduerholt in #385

New Contributors

• @niklaswulkow made their first contribution in #370
• @TobyBoyne made their first contribution in #278

Full Changelog: v0.0.11...v.0.0.12

LSR-BO and Multiplicative Constraints

What's Changed

• LSR-BO by @jduerholt in #338
• Add mixed tanimoto gp surrogate by @xxEthene in #318
• Refactor random strategy by @jduerholt in #347
• Multilinear constraint by @jduerholt in #348

New Contributors

• @xxEthene made their first contribution in #318

Full Changelog: v0.0.10...v0.0.11

Pydantic 2

What's Changed

• experiments and candidates can be None by @bertiqwerty in #311
• Interpoint Constraints by @jduerholt in #313
• gp output scaler by @simonsung06 in #309
• Botorch 0.9.5 by @jduerholt in #317
• DoE: Fix bug if fixed_experiments contain columns that are not in domain by @dlinzner-bcs in #321
• Seed handling for Sampling by @jduerholt in #323
• batch constraints for DoE and call for interpointEqualityConstraint by @Osburg in #322
• Refactor test suite for data models by @jduerholt in #327
• Tests for base.py by @jduerholt in #329
• Add noise prior by @jkeupp in #326
• Tests for CategoricalInput by @jduerholt in #330
• Compatibility PR for Formulaic 1.0.1 by @jduerholt in #332
• Universal constraint sampler by @Osburg in #328
• pydantic 2 - migration by @bertiqwerty in #279

Full Changelog: v0.0.8...v0.0.10

BoFire for BoTorch 0.9.5

What's Changed

• Interpoint constraints available both as data model and implemented in the PolytopeSampler by @jduerholt in #313
• Configurable output scalers for all surrogates by @simonsung06 in #309

Full Changelog: v0.0.8...v0.0.9

BoFire for BoTorch 0.9.4

What's Changed

• Fix number of experiments condition for zero experiments by @jduerholt in #266
• Smaller model dumps by @jduerholt in #267
• Added outlier detection tutorial by @swagataroy123 in #262
• Add generic benchmark module by @jduerholt in #269
• Add log single-objective ACQFs by @jduerholt in #271
• Bayesian optimization over molecules by @swagataroy123 in #268
• Change random seed behavior by @jduerholt in #276
• Sync the output of surrogate.predict and strategy.predict by @jduerholt in #282
• Fix infeasible cost calculation for categorical inputs by @jduerholt in #281
• Refactor get acquisition in SOBO strategies and adapt to new way of handling constraints by @gmancino in #275
• Feature/experiment validation by @jduerholt in #289
• Implement possibility to run hyperparameter opts in the strategy by @jduerholt in #287
• Refactor the candidates/experiments validators. by @jduerholt in #291
• Add possibility to compute feature importance over the lengthscales in a SingleTaskGPSurrogate by @jduerholt in #293
• Fix for categorical features that are fixed in fully categorical BO by @simonsung06 in #295
• Mapping happens outside of runner by @bertiqwerty in #296
• Add polynomial kernel by @dlinzner-bcs in #298
• 286 add surrogate models that can extrapolate by @dlinzner-bcs in #299
• Iterative branch and bound by @dlinzner-bcs in #302
• Updated rdkit fragment/descriptor list by @simonsung06 in #306
• Allow for max_active=#(variables in constraint) in n_choose_k_constraints_as_bounds() by @Osburg in #304
• Add output_scaler to mlp by @simonsung06 in #305
• Add multi-objective log ACQFs by @jduerholt in #308

New Contributors

• @gmancino made their first contribution in #275

Full Changelog: v0.0.7...v0.0.8

BoFire for BoTorch 0.9.2

This release includes a BoFire version which requires BoTorch 0.9.2. In addition the following things are new:

What's Changed

• relaxing error to a warning by @ufukguenes in #257
• Outlier detection in predictive strategies by @swagataroy123 in #235
• added calibration metric by @swagataroy123 in #253
• CategoricalMolecularFeature by @jduerholt in #260
• Fix for to and from categorical variable encoding by @simonsung06 in #261
• DoE for categorical features by @ufukguenes in #259
• stratified kfold for cv by @simonsung06 in #263
• Make compatible with latest botorch release and main branch by @jduerholt in #265

New Contributors

• @ufukguenes made their first contribution in #257

Full Changelog: v0.0.6...v0.0.7

BoFire for BoTorch 0.9.1

This release includes a BoFire version which is compatible with BoTorch 0.9.1 and therefore requires at least Python 3.9.

BoFire for Python 3.8

This release is the only BoFire release that supports Python 3.8. It uses BoTorch 0.8.5. Later releases will require at least Python 3.9 and use BoTorch >= 0.9.1.