Pypesto

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* 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)

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* 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)

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* 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)

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

* AMICI:
* Make AMICI objective report only what is being asked for (777)

* Optimization:
* (Breaking) Refactor startpoint generation with clear assignments;
allow checking gradients (769)
* (Breaking) Prioritize history vs optimize result (775)

* Storage:
* Fix loading empty history and result generation from multiple
histories (764)
* Fix autosave function for single-core (770)
* Fix potential autosave overwriting and typehints (772)
* Allow loading of partial results from history file (783)

* CI:
* Compile AMICI models without gradients in test suite (774)

* General:
* (Breaking) Create result sub-module; shift storage+result related
functionality (784)
* Fix finite difference constant mode (786)
* Refactor ensemble module (788)
* Introduce general C constants file (788)
* Apply isort for automatic imports formatting (785)
* Reduce run log output (789)
* Various minor fixes (765, 766, 768, 771)

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

* General:
* Automatically save results (749)
* Update all docstrings to numpy standard (750)
* Add Google Colab and nbviewer links to all notebooks for online
execution (758)
* Option to not save hess and sres in result (760)
* Set minimum supported python version to 3.7 (755)

* Visualization:
* Parameterize start index in optimized model fit (744)

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

* PEtab:
* Use correct measurement column name in `rdatas_to_simulation_df` (721)
* Visualize optimized model fit via PEtab problem (725)
* Un-ignore observable scaling tests (742)
* New function to plot model trajectory with custom time points (739)

* Optimization:
* OOD Refactor startpoint generation (732)
* Update to fides 0.6.0 (733)
* Correctly report FVAL vs CHI2 values in fides (741)

* Ensemble:
* Option for using weighted ensemble means (702)
* Default names and bounds for `Ensemble.from_sample` (730)

* Storage:
* Load optimization result from HDF5 history (726)

* General:
* Enable use of priors with least squares optimizers (745)
* Add temporary CITATION.cff file (734)
* Regular scheduled CI runs (754)
* Allow to not copy objective in problem (756)

* Fixes:
* Fix non-exported visualization in notebook (729)
* Mark some more tests as flaky (704)
* Fix minor data type and OOD issues in parameter and waterfall plots
(731)