PyPESTO Versions Save

Re-release to fix pypi issues.

• General
  • Include pymc in the documentation. (#1305)
  • Ruff Codechecks (#1307)
  • Support RoadRunner as simulator for PEtab problems (#1336, #1347, #1348, #1363)
• Hierarchical
  • Semiquant: Fix spline knot initialization (#1313, #1323)
  • Semiquant: Add spline knots to the optimization result (#1314)
  • Semiquant: fix inner opt tolerance (#1330)
  • Relative: Fix return of relative calculator if sim fails (#1315)
  • Relative: Hierarchical optimization: fix unnecessary simulation (#1327)
  • Relative: Fix return of inner parameters on objective call (#1333)
• Optimize
  • Support ipopt with gradient approximation (#1310)
  • Deprecate CmaesOptimizer in favor of CmaOptimizer (#1311)
  • ESSOptimizer: Respect local_n2 in case of failed initial local search (#1328)
  • Remove CESSOptimizer (#1320)
  • SacessOptimizer: use 'spawn' start method for multiprocessing (#1353)
• PEtab
  • Fix unwanted amici model recompilation in PEtab importer (#1319)
• Sample
  • Adding Thermodynamic Integration (#1326, #1361)
  • Dynesty warnings added (#1324)
  • Dynesty: method to save raw results (#1331)
• Ensembles
  • Ensembles: don't expect OptimizerResult.id to be convertible to int (#1351)
• Misc
  • Updated Code to match dependency updates (#1316, #1344, #1346, #1345)
  • Ignore code formatting in git blame (#1317)
  • Updated deployment method (#1341, #1371, #1373)
  • add pyupgrade to codechecks (#1352)
  • Temporarily require scipy<1.13.0 for pypesto[pymc] (#1360)

• General
  • Stabilize tests (#1240, #1254)
  • Update type annotations and documentations (#1239, #1248, #1255, #1258, #1251, #1268, #1275)
  • GHA/Codeowner changes (#1260, #1261, #1259, #1262, #1285)
  • Update utility functions (#1243)
  • Refactor progress bars (#1272)
  • Clear Notebook output(#1246, #1277, #1274, #1271, #1276, #1278,)
• Optimize
  • (Sac)ESSOptimizer: History of best objective values (#1212)
  • Fix missing fixed parameters in scatter search results (#1265)
  • Fix TypeError in pypesto.result.optimize.OptimizerResult.summary if x0 is None (#1266)
  • ESSOptimizer: Include results for local searches in OptimizeResult (#1270)
• New Feature: Spline Approximation (#1222)
• Select
  • Allow for hierarchical problems (#1241)
  • custom minimize method (#1264)
• Hierarchical
  • Log space startpoint sampling (#1242)
  • Support for box constraints on offset and scaling parameters (#1238)
  • restructuring and add relative to InnerCalculatorCollector (#1245)
• History
  • Support pathlib.Path for result/history files (#1247)
  • Extended Amici history (#1263)
• Visualize
  • Fix time trajectories for hierarchical problems (#1213)
  • Fix hierarchical parameter plotting for all optimizers (#1244)
  • Sacess history plot (#1250)
• Objective
  • Fix PEtab.jl version to before 2.5.0 (temporarily) (#1256)
• PEtab
  • Enable Importer passing verbose to create_model (#1269)
  • PetabImporter: version-specific amici model directories (#1283)
• Problem
  • Problem: add inner problem names, bounds and hierarchical flag (#1282)
  • Use warnings.warn instead of logging.warn when loading Problem from HDF5 without an Objective (#1253)
• Ensemble
  • EnsemblePrediction: remove "no predictor" warning (#1293)

• General
  • Documentation (#1214, #1227, #1223, #1230, #1229)
  • Update code to avoid deprecations and warnings (#1217, #1219)
  • Updated codeownership (#1232)
  • Update Citation (#1221)
  • Improved Testing (#1218, #1216, #1231)
• History:
  • Enable converting MemoryHistory to Hdf5History (#1211)
• Profile:
  • Code simplification and other clean up (#1225)
  • Fix incorrect indexing in pypesto.profile.profile_next_guess.get_reg_polynomial (#1226)
• Optimize
  • Warnings for scipy together with laplace prior (#1228)
• Visualization:
  • Skip the history trace, if trace is empty. Occurs for infinite initial values. (#1234)

• General
  • Documentation (#1140, #1146, #1152, #1149, #1192)
  • Updated Jupyter Notebooks (#1141)
  • Update code to avoid deprecations/warnings (#1158, #1184)
  • Updated maintainers and codeownership (#1171, #1170)
  • Improve tests and GHA (#1178, #1185, #1188, #1190, #1193, #1199, #1198, #1197, #1208)
• Profile:
  • Fix problem overwrite of profiling (#1153)
  • Add warning, trying to profile fixed parameter (#1155)
  • ProfileOptions: add some basic integrity checking (#1163)
  • Fix pypesto.profile.parameter_profile incorrectly assuming symmetric bounds (#1166)
  • Improve pypesto/profile/profile_next_guess.py (#1167)
  • Parameter profile: retry optimization in case of failure (#1168)
  • Fix incorrect types in pypesto.result.profile.ProfilerResult (#1210)
• Problem:
  • Add/forward startpoint_kwargs in PetabImporter.create_problem (#1135)
  • Support valid AMICI noise distributions that are invalid in PEtab (#1157)
  • Fix startpoint sampling for PEtab-derived problems with fixed parameters (#1169)
• Optimize
  • Log traceback in case of exceptions during optimizations (#1156)
  • Saccess optimizer improvements (#1177, #1187, #1194, #1195, #1201, #1202, #1204)
  • ESS optimizer improvements (#1176, #1181, #1182)
  • Fix check for allow_failed_starts (#1180)
  • Handle message and exitflag in histories (#1203)
  • Fix indexing error for 0-dimensional HDF5 datasets (#1206)
• Hierarchical:
  • Fix HierarchicalAmiciCalculator.__call__ not setting 'hess' in result (#1161)
• Visualization:
  • Fix legend argument checking for waterfall/parameter/history plots (#1139)
  • Fix waterfall start indices for multiple results (#1200)

• Visualize:
  • Get optimization result by id (#1116)
• Storage:
  • allow "{id}" in history storage filename (#1118)
• Objective:
  • adjusted PEtab.jl syntax to new release (#1128, #1131)
  • Documentation on PEtab importer updated (#1126)
• Ensembles
  • Additional option for cutoff calculation (#1124)
  • Ensembles from optimization endpoints now only takes free parameters (#1130)
• General
  • Added How to Cite (#1125)
  • Additional summary option (#1134)
  • Speed up base tests (#1127)

• General
  • Added new entry to bib (#1100)
  • PetabJL integration (#1089)
  • Other platform tests (#1113)
  • Dokumentation fixes (#1120)
  • Updated CODEOWNER (#1123)
• Visualize:
  • Restrict fval magnitude in waterfall with order_by_id (#1090)
  • Hierarchical parameter plot fix (#1106)
  • Fix y-limits on waterfall (#1109)
• Sampling:
  • Use cloudpickle for pickling dynesty sampler (#1094)
• Optimize
  • Small fix on hierarchical initialise (#1095)
  • Fix startpoint sampling for hierarchical optimization (#1105)
  • SacessOptimizer: retry reading, delay deleting (#1110)
  • SacessOptimizer: Fix logging with multiprocessing (#1112)
  • SacessOptimizer: tmpdir option (#1115)
• Storage:
  • fix storage (#1099)
• Examples
  • Notebook on differences (#1098)
• Problem
  • Add startpoint_method to Problem (#1093)

• Visualize:
  • Parameter plot w/ hier. pars, noise estimation for splines (#1061)
• Sampling:
  • AdaptiveMetropolis failure fix for bounded priors (#1065)
• Ensembles
  • Speed up Ensemble from History (#1063)
• PEtab support:
  • Support for petab 0.2.x (#1073)
  • Remove PetabImporterPysb #1082)
• Objective
  • AggregatedObjective: objective-specific kwargs for call_unprocessed (#1068)
• Select
  • Use predecessor stored in file (#1059)
  • support petab-select version 0.1.8 (#1070)
• Examples
  • Synthetic data: update for libpetab-python v0.2.0 (#1060)
  • Fix error in sampling_diagnostics which led to test failure(#1092)
• General
  • Test fixes (#1064)
  • Fix numpy DeprecationWarnings (#1076)
  • GHA: Fix deprecation warnings (#1075)
  • Fixed bug on existing file and no overwrite (#1046)
  • Fix error in bound checking (#1081)

New functionalities compared to 0.2.0:

• New supported data types for parameter estimation:
  • ordinal data
  • censored data
  • unbounded parameter optimization
• New optimization approaches:
  • Hierarchical optimization
  • Spline approximation
• New optimizers: CMA-ES, Enhanced Scatter Search, Fides, NLopt, SACESS, SciPy Differential Evolution
• New samplers: Emcee, Dynesty, Pymc v4
• New Objectives: Aesara objective, Julia objective, Jax objective
• Ensemble analysis
• Model selection
• Predictions
• Hdf5 Storage

Not supported functionalities and versions compared to 0.2.0:

• Removed Python 3.8 and older support
• Pymc (v3)
• Removed Theano objective
• Changed parameter indexing from boolean to int in profiling routines

• Optimize:
  • Parameter estimation from ordinal data (#971)
  • Parameter estimation from nonlinear-monotone data using spline approximation (#1028)
  • Parameter estimation using censored data (#1041)
  • Fix optimizer start point handling. (#1027)
  • Add option to summary to print full or reduced vectors. (#1040, #1045)
• Sampling:
  • Dynesty sampler parallelization: changed the nested loglikelihood function to a class method (#1037)
  • Dynesty sampler docs (#1039)
• Engine
  • Allow custom multiprocessing context (#1032)
• General
  • Updated example notebooks (#1050, #1026, #1051, #1056)
  • Refactor docs (#1052)
  • Update Dockerfile (#1034)
  • proper bound handling for x_guesses (#1029)
  • Updated to flake8 standards (#1042, #1049)
  • Removed Python 3.8 support according to NEP29 (#1056)