Parmoo

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:Date: Sep 25, 2023

Bug-fixes and minor restructuring for future releases.

Fixed several serious bugs/limitations:

- Introduced in v0.3.0: when generating batches, a bug was introduced into
the lines of code that filter out duplicate candidates, resulting in
significantly decreased performance but no errors being raised
- Allow for ParMOO to still generate target points for the
``AcqusitionFunction``, even when there are no feasible points in the
database
- Increase the number of characters allowed in a name when working with
libEnsemble from 10 to 40 characters
- Broke the ``MOOP.iterate()`` method apart into 2 functions (``iterate``
and ``filterBatch``), which makes the code more maintainable and allows
for future improvements to the ``libE_MOOP`` parallelism
- Updated deprecated keys in ``.readthedocs.yml`` config file

-------------

:Date: Jul 6, 2023

Significant structural changes for long-term support of future solvers,
bug-fixes, and significant improvements to documentation.

Major Changes:

- ``surrogates.GaussRBF`` and ``surrogates.LocalGaussRBF`` now
calculate model-form uncertainties
- structural changes to ``MOOP`` class to support propagation of
uncertainty information
- added ``EI_RandomConstraint`` acquisition, which can be used to
implement Bayesian optimization -- note that for large budgets,
this is not currently recommended due to computational expense
of numerical integration
- updated ``LocalGPS`` to use trust regions, when provided, and
perform multiple restarts
- ``SurrogateOptimizer`` class now has access to more information about
the objective, including raw simulation outputs, in order to support
more diverse structure-exploiting solvers
- Added additional stopping criteria to both ``MOOP.solve()`` and
``libE_MOOP.solve()`` -- all stopping criteria are now optional
(although at least one must be specified) but they are ordered such
that calling ``MOOP.solve(k)``, where ``k`` is a positional input,
will pass to the ``iter_max`` criteria and produce the same behavior
as before -- closes 18

API Changes:

- In most cases, none. However, it is possible that if users were previously
passing arguments to the ``MOOP.solve()`` method explicitly, then the
name of the first positional argument has changed:
``budget`` -> ``max_iters``
- For users implementing their own ``searches``, ``surrogates``,
``optimizers``, or ``acquisitions``, several classes in the ``structs``
module have been updated to support the present restructuring of
the ``MOOP`` class

Docs:

- Updated Quickstart guide and README to demonstrate recommended inputs
and settings for ParMOO -- this includes no more ``lambda`` functions,
which closes 50
- Added a FAQ page with additional usage details and responses to frequent
questions -- the answers in which close 61
- Added a new tutorial on how to perform high-dimensional multiobjective
optimization on a limited budget with ParMOO
- Changed examples and documentation to use and discuss pandas dataframes,
which generally produce more legible outputs
- Updated ``libE_MOOP`` example to demonstrate how to retrieve data in a
way that is threadsafe for both Python MP and MPI usage

Requirements:

- We now require scipy v1.10 or newer, due to usage of qmc integration tools
- At the time of this release, libEnsemble is using a deprecated version of
Pydantic -- for this release only we have fixed the requirement on
libEnsemble to v0.9.2, but we will relax this requirement in the future
once they have patched the issue

Bug-fixes:

- Fixed an issue where in rare cases, problems with too many categorical
variables could produce unexpected batch sizes
- Errors in definition of test problems: DTLZ5, 6, and 7 (new implementations
have been confirmed against ``pymoo``)
- Fixed an issue which occasionally caused the ``libE_MOOP`` class to error
out during post-run cleanup when used with MPI
- Patched an issue with ``format="pandas"`` option for
``MOOP.getSimulationData()`` class and added a similar option to
all ``libE_MOOP`` "getter" functions

Minor changes:

- Fixed typos in docs/doc-strings
- Updated styles to comply with new ``flake8`` recommendations
- New unit tests added
- Added warnings when ParMOO is run with bad budget settings

-------------

:Date: Apr 25, 2023

Hot-fix for a minor issue in the plotting library without workaround.

- Resolves 58

-------------

:Date: Apr 10, 2023

Minor performance improvements, maintenance, and restructuring of test cases.

- Both Gaussian RBF surrogates in ``parmoo/surrogates/gaussian_proc.py``
now use the current mean of the response values as the prior instead
of the zero function. This greatly improves convergence rates in practice,
especially for our structure-exploiting methods.
- Using an old version of ``plotly/dash`` for now because of a dash issue
described in plotly/dash2460
- Added additional tests to check gradient calculations of ``GaussRBF``
surrogates.
- Added whitespace to pass new ``flake8`` standards.
- Added year to JOSS publication in several places
- Added "et al." to our docs configuration file after author names, to
credit additional contributors in our documentation.

-------------

:Date: Feb 2, 2023

Official release corresponding to accepted JOSS article.

- Added support for a wider variety of design variables (including integer
types), as well as support for "custom" design variables that use
user-provided custom embedders/extractors
Documentation on design variables has been expanded accordingly.
Although design variables are still specified through dicts not classes,
this addresses and therefore closes the primary issue raised in
parmoo/parmoo28
- Updated ``extras/libe.py`` corresponding to interface changes made in
libEnsemble Release 0.8.0. This also addresses the issues on MacOS,
referenced in parmoo/parmoo34
- Added a post-run visualization library and corresponding
documentation, closing issue parmoo/parmoo27
- Allow solvers to start from an initial point that is infeasible, so that
problems with relaxable constraints and a very small feasible set can
still be solved
- Various style changes and additional usage environments requested by
JOSS reviewers openjournals/joss-reviews4468 including parmoo/parmoo32
- Added support for multistarting optimization solvers when solving
surrogate problems. This is particularly important for the global
``GaussRBF`` surrogate
- Fixed an issue in how model improvement points are calculated, as
implemented in the ``surrogate.improve`` method for each GaussRBF variation
in ``surrogates/gaussian_proc.py``, which was created when adding support
for custom design variables
- The default design tolerance for continuous variables now depends upon
the value of ``ub - lb``

Note:

- Dropped support for Python 3.6, due to changes to GitHub Actions documented
on actions/setup-python544

Known issues:

- The visualization library uses advanced plotly/dash features, which may
not support the chrome browser, as described in parmoo/parmoo37

-------------

:Date: May 10, 2022

Initial release.

Known issues and desired features will be raised on GitHub post-release.

Known issues:

- update unit tests to use sim/obj/const libraries
- restructure test suite, unit tests are currently not usable as
additional documentation
- ``solve()`` method(s) should support additional stopping criteria
- allow for maximizing objectives and constraint lower bounds without
"hacky" solution (negating values)
- missing functions from DTLZ libraries
- ``README.md`` needs a code coverage badge

Desired features:

- update, test, and merge-in MDML interface
- allow user to choose whether or not to use named variables via ``useNames``
method, or similar
- add a funcx simulation interface, using libEnsemble release 0.9
- add predicter interface and standalone module
- a GUI interface for creating MOOPs
- static visualization tools for plotting results
(from ``MOOP.getPF()`` method)
- a visualization dashboard for viewing progress interactively
- design variable types should be a class, with embed/extract methods
that can be called by ``MOOP.__embed__()`` and ``MOOP.__extract__()``