Baybe

Added
- Simulation user guide
- Example for transfer learning backtesting utility
- `pyupgrade` pre-commit hook
- Better human readable `__str__` representation of objective and targets
- Alternative dataframe deserialization from `pd.DataFrame` constructors

Changed
- More detailed and sophisticated search space user guide
- Support for Python 3.12
- Upgraded syntax to Python 3.9
- Bumped `onnx` version to fix vulnerability
- Increased threshold for low-dimensional GP priors
- Replaced `fit_gpytorch_mll_torch` with `fit_gpytorch_mll`

Fixed
- `telemetry` dependency is no longer a group (enables Poetry installation)

Added
- Better human readable `__str__` representation of campaign
- README now contains an example on substance encoding results
- Transfer learning user guide
- `from_simplex` constructor now also takes and applies optional constraints

Changed
- Full lookup backtesting example now tests different substance encodings
- Replaced unmaintained `mordred` dependency by `mordredcommunity`
- `SearchSpace`s now use `ndarray` instead of `Tensor`

Fixed
- `from_simplex` now efficiently validated in `Campaign.validate_config`

Changed
- BoTorch dependency bumped to `>=0.9.3`

Removed
- Workaround for BoTorch hybrid recommender data type
- Support for Python 3.8

Added
- Subpackages for the available recommender types
- Multi-style plotting capabilities for generated example plots
- JSON file for plotting themes
- Smoke testing in relevant tox environments
- `ContinuousParameter` base class
- New environment variable `BAYBE_CACHE_DIR` that can customize the disk cache directory
or turn off disk caching entirely
- Options to control the number of nonzero parameters in `SubspaceDiscrete.from_simplex`
- Temporarily ignore ONNX vulnerabilities
- Better human readable `__str__` representation of search spaces
- `pretty_print_df` function for printing shortened versions of dataframes
- Basic Transfer Learning example
- Repo now has reminders (https://github.com/marketplace/actions/issue-reminder) enabled
- `mypy` for recommenders

Changed
- `Recommender`s now share their core logic via their base class
- Remove progress bars in examples
- Strategies are now called `MetaRecommender`'s and part of the `recommenders.meta`
module
- `Recommender`'s are now called `PureRecommender`'s and part of the `recommenders.pure`
module
- `strategy` keyword of `Campaign` renamed to `recommender`
- `NaiveHybridRecommender` renamed to `NaiveHybridSpaceRecommender`

Fixed
- Unhandled exception in telemetry when username could not be inferred on Windows
- Metadata is now correctly updated for hybrid spaces
- Unintended deactivation of telemetry due to import problem
- Line wrapping in examples

Deprecations
- `TwoPhaseStrategy`
- `SequentialStrategy`
- `StreamingSequentialStrategy`

Added
- Copy button for code blocks in documentation
- `mypy` for campaign, constraints and telemetry
- Top-level example summaries
- `RecommenderProtocol` as common interface for `Strategy` and `Recommender`
- `SubspaceDiscrete.from_simplex` convenience constructor

Changed
- Order of README sections
- Imports from top level `baybe.utils` no longer possible
- Renamed `utils.numeric` to `utils.numerical`
- Optional `chem` dependencies are lazily imported, improving startup time

Fixed
- Several minor issues in documentation
- Visibility and constructor exposure of `Campaign` attributes that should be private
- `TaskParameter`s no longer disappear from computational representation when the
search space contains only one task parameter value
- Failing `baybe` import from environments containing only core dependencies caused by
eagerly loading `chem` dependencies
- `tox` `coretest` now uses correct environment and skips unavailable tests
- Basic serialization example no longer requires optional `chem` dependencies

Removed
- Detailed headings in table of contents of examples

Deprecations
- Passing `numerical_measurements_must_be_within_tolerance` to the `Campaign`
constructor is no longer supported. Instead, `Campaign.add_measurements` now
takes an additional parameter to control the behavior.
- `batch_quantity` replaced with `batch_size`
- `allow_repeated_recommendations` and `allow_recommending_already_measured` are now
attributes of `Recommender` and no longer attributes of `Strategy`

Added
- Target enums
- `mypy` for targets and intervals
- Tests for code blocks in README and user guides
- `hypothesis` strategies and roundtrip tests for targets, intervals, and dataframes
- De-/serialization of target subclasses via base class
- Docs building check now part of CI
- Automatic formatting checks for code examples in documentation
- Deserialization of classes with classmethod constructors can now be customized
by providing an optional `constructor` field
- `SearchSpace.from_dataframe` convenience constructor

Changed
- Renamed `bounds_transform_func` target attribute to `transformation`
- `Interval.is_bounded` now implements the mathematical definition of boundedness
- Moved and renamed target transform utility functions
- Examples have two levels of headings in the table of content
- Fix orders of examples in table of content
- `DiscreteCustomConstraint` validator now expects dataframe instead of series
- `ignore_example` flag builds but does not execute examples when building documentation
- New user guide versions for campaigns, targets and objectives
- Binarization of dataframes now happens via pickling

Fixed
- Wrong use of `tolerance` argument in constraints user guide
- Errors with generics and type aliases in documentation
- Deduplication bug in substance_data hypothesis
- Use pydoclint as flake8 plugin and not as a stand-alone linter
- Margins in documentation for desktop and mobile version
- `Interval`s can now also be deserialized from a bounds iterable
- `SubspaceDiscrete` and `SubspaceContinuous` now have de-/serialization methods

Removed
- Conda install instructions and version badge
- Early fail for different Python versions in regular pipeline

Deprecations
- `Interval.is_finite` replaced with `Interval.is_bounded`
- Specifying target configs without explicit type information is deprecated
- Specifying parameters/constraints at the top level of a campaign configuration JSON is
deprecated. Instead, an explicit `searchspace` field must be provided with an optional
`constructor` entry