Pypesto

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

* Optimize:
* sacess optimizer (988, 997)
* Warn only once if using ineffiecient objective settings (996)
* Hierarchical Optimization (1006)
* Fix cma documentation (987)
* Petab
* Improvement to create_startpoint_method() (1018)
* Sampling:
* Dynesty sampler (1002)
* Fix test/sample/test_sample.py::test_samples_cis failures (1004)
* Visualization:
* Fix misuse of start indices in waterfall plot (1000)
* Fix large function values in clustering for visualizations (999)
* parameter correlation diverging color scheme (1009)
* Optimization Parameter scatter plot (1015)
* Profiling:
* added option to profile the whole parameter bounds. (1014)
* General
* Add CODEOWNERS (1001)
* Add list of publications using pypesto (1008)
* allow passing results to __init__ of pypesto.Result (998)
* Updated flake8 to ignore Error B028 from bugbear until support for python 3.8 runs out. (1005)
* black update (1010)
* Doc typo fixes (995)
* Doc: Install amici on RTD (1016)
* Add getting_started notebook (1023)
* remove alernative formats build (1022)

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

* Optimize:
* Add an Enhanced Scatter Search optimizer (941, 972)
* Cooperative enhanced scatter search (954)
* Hierarchical optimization (952, 975 )
* Allow scipy optimizer to use fun with integrated grad (979)
* Sampling:
* Remove fixed parameters from pymc sampling (951)
* emcee sampler: initialize walkers near optimum (961)
* dynesty Sampler (963)
* Fix pymc>=5 aesara/pytensor issues (983)
* Visualization:
* Multi-result waterfall plot (966)
* Model fit visualization: use problem.objective to simulate, instead of AMICI directly (969)
* Unfix matplotlib version (977)
* Plot measurements in sampling_prediction_trajectories (976)
* Objective definition:
* Support for jax objectives (986)
* General
* Fix license_file SetuptoolsDeprecationWarning (965)
* Remove benchmark-models-petab requirement (964)
* Github Actions(958, 989 )
* Fix typehint for problem.x_priors_defs (962)
* Fix tox4-related issues (981)
* Fix AMICI deprecation warning (956)
* Add pypesto.visualize.model_fit to API doc (991)
* Exclude numpy==1.24.0 (993)

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

* Ensembles:
* Save and load weights and sigmay (876)
* Define relative cutoff (855)
* PEtab:
* Pass problem kwargs via petab importer (874)
* Use `benchmark-models-petab` instead of manual download (915)
* Use fake RData in in prediction_to_petab_measurement_df (925)
* Optimize:
* Fides: Include message according to exitflag (878)
* Sampling:
* Added Pymc v4 Sampler (818, 944, 948)
* Visualization:
* Fix waterfall plot limits for non-offsetted log-plots (891)
* Plot unflattened model fit from flattened PEtab problems (914)
* Added the offset value to waterfall plot for better intuitive understanding (910, 945)
* Visualize parameter correlation (888)
* History and storage:
* Fix history-result reconstruction mismatch (902)
* Move history to own module (903)
* Remove chi2, schi2 except for history convenience function (904)
* Clean up history hierarchy (908)
* Fix `read_result` with history (907)
* Improve hdf5 history file lock (909, 921)
* Fix message in `check_overwrite` (894)
* Deactivate automatic saving (930, 932)
* Allow problem=None in read_result_from_file (936)
* Remove superfluous get_or_create_group (937)
* Extract read_history_from_file from read_result_from_file (939)
* Select: use model ID in save postprocessor filename, by default (943)
* Select:
* Clean up use of `minimize_options` in model problem (918)
* User-supplied method to produce pyPESTO problem (884)
* Report, and binary model ID post-processors (900)
* Move method.py functionalities to ui.py in petab_select (919)
* Objective and Result:
* Julia objective (927)
* Fix set of keys to aggregate results in aggregated objective (883)
* Nicer `OptimizeResult.summary` (895, 916, 935, 942, )
* Fix disjoint IDs check in `OptimizerResult.append` (922)
* Fix OptimizeResult pickling (953)
* General:
* Remove version from `CITATION.cff` (887)
* Fix CI and docs (892, 893)
* Literal typehints for `mode` (899)
* Fix pandas deprecation warning (896)
* Document NEP 29 (time-window based python support) (905)
* Fix `get_for_key` deprecation warning (906)
* Fix multiple warnings from existing AMICI model (912)
* Fix warning from AMICI fixed overrides (912)
* Fix flaky test `CRFunModeHistoryTest.test_trace_all` (917)
* Fix novel B024 ABC without abstract methods (923)
* Improve API docs and add overview notebook (911)
* Fix typos (926)
* Fix julia tests (929, 933)
* Fix flaky test_mpipoolengine (938)
* More informative test IDs in test_optimize (940)
* Speed-up import via lazy imports (946)

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

* Ensembles:
* Added standard deviation to ensemble prediction plots (853)
* Storage
* Distinguish between scalar and vector values in Hdf5History._get_hdf5_entries (856)
* Fix hdf5 history overwrite (861)
* Updated optimization storage format. Made attributes explicit. (863)
* Added problem to result from read_results_from_file (862)
* General
* Various additions to Optimize(r)Result summary method (859, 865, 866, 867)
* Fixed optimizer history fval offset (834)
* Updated the profile, minimize, sample and added overwrite as argument. (864)
* Fixed y-labels in pypesto.visualize.optimizer_history (869)
* Created show_bounds, to display proper sampling scatter plots. (868)
* Enabled saving messages and exit flags in hdf5 history in case of finished run (873)
* Select: use objective function evaluation time as optimization time for models with no estimated parameters (872)
* removed checking for equality and checking for np.allclose in test_aesara (877)

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

* AMICI:
* Update to renamed steady state sensitivity modes (843)
* Set amici.Solver.setReturnDataReportingMode (835)
* Optimize `pypesto/objective/amici_util.py::par_index_slices` (845)
* Remove Solver.getPreequilibration (830)
* fix n_res size for error output with parameter dependent sigma (812)
* PetabImporter: Auto-regenerate AMICI models in case of version mismatch (848)
* Pymc3
* Disable Pymc3 Sampler tests (831)
* Visualizations:
* Waterfall zoom (808)
* Reverse opacities of colors in prediction trajectories plots(838)
* Model fit plots (850)
* OptimizeResult:
* Summary method (816)
* Append method for OptimizeResult (815)
* added __getattr__ function to OptimizeResult (802)
* General:
* disable progress bar in tests (799)
* Make Fides work with objectives, that do not have a hessian (807)
* removed ftol in favor of tol (803)
* Fix pyPESTO Select test; Update to stable black version (810)
* Fix id assignment in case of large number of starts (825)
* Temporarily fix jinja2 version (826)
* Upgrade black to be compatible with latest click (829)
* Fix wrong link in doc/example/hdf5_storage.ipynb (827)
* Mark test/base/test_prior.py::test_mode as flaky (833)
* Custom methods for autosave filenames (822)
* fix saving ensemble predictions to hdf5 (840)
* Upgrade nbQA to 1.3.1 (846)
* Replaced constantParameters with constant_parameters in notebook (852)

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

* Model selection (397):
* Automated model selection with forward/backward/brute force methods and
AIC/AICc/BIC criteria
* Much functionality (methods, criteria, model space, problem
specification) via `PEtab Select <https://github.com/PEtab-dev/petab_select>`
* Plotting routines
* `Example notebook <https://github.com/ICB-DCM/pyPESTO/blob/main/doc/example/model_selection.ipynb>`
* Model calibration postprocessors
* Select first model that improves on predecessor model
* Use previous MLE as startpoint
* Tests

* AMICI:
* Maintain model settings when pickling for multiprocessing (747)

* General:
* Apply nbqa black and isort to auto-format all notebooks via
pre-commit hook (794)
* Apply black formatting via pre-commit hook (796)
* Require Python >= 3.8 (795)
* Fix various warnings (778)
* Minor fixes (792)