PyPESTO Versions Save

• sacess optimizer (#988, #997)
• Warn only once if using ineffiecient objective settings (#996)
• Hierarchical Optimization (#1006)
• Fix cma documentation (#987)

• Improvement to create_startpoint_method() (#1018)

• Dynesty sampler (#1002)
• Fix test/sample/test_sample.py::test_samples_cis failures (#1004)

• 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)

• added option to profile the whole parameter bounds. (#1014)

• 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)

• 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)

• Remove fixed parameters from pymc sampling (#951)
• emcee sampler: initialize walkers near optimum (#961)
• dynesty Sampler (#963)
• Fix pymc>=5 aesara/pytensor issues (#983)

• 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)

• Support for jax objectives (#986)

• 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)

• Save and load weights and sigmay (#876)
• Define relative cutoff (#855)

• 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)

• Fides: Include message according to exitflag (#878)

• Added Pymc v4 Sampler (#818, #944, #948)

• 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)

• 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)

• 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)

• 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)

• 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)

• Added standard deviation to ensemble prediction plots (#853)

• 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)

• 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)

• 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 )

• Disable Pymc3 Sampler tests (#831 )

• Waterfall zoom (#808 )
• Reverse opacities of colors in prediction trajectories plots(#838)
• Model fit plots (#850)

• Summary method (#816 )
• Append method for OptimizeResult (#815 )
• added getattr function to OptimizeResult (#802 )

• 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 )
• Upgrad nbQA to 1.3.1 (#846)
• removed constantParameters for 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)

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)

Finite Differences:

• Adaptive finite differences (#671)
• Add helper function for checking gradients of objectives (#690)
• Small bug fixes (#711, #714)

Storage:

• Store representation of the objective (#669)
• Minor fixes in HDF5 history (#679)
• HDF5 reader for ensemble predictions (#681)
• Update storage demo jupyter notebook (#699)
• Option to trim trace to be monotonically decreasing (#705)

General:

• Improved tests and bug fixes of validation intervals (#676, #685)
• Add input file validation via PEtab linter for PEtab import (#678)
• Remove default values from docstring (#680)
• Minor fixes/improvements of ensembles (#687, #688)
• Fix sorting of optimization values including NaN values (#691)
• Specify axis limits for plotting (#693)
• Minor fixes in visualization (#696)
• Add installation option all_optimizers (#695)
• Improve installation documentation (#689)
• Update pysb and BNG version on GitHub Actions (#697)
• Bug fix in steady state guesses (#715)