pyPESTO 0.2.8

• 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)

pyPESTO 0.2.7

• 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)

pyPESTO 0.2.6

• Objective:

  • Basic finite differences (#666)
  • Fix factor 2 in res/fval values (#619)

• Optimization:

  • Sort optimization results when appending (#668)
  • Read optimizer result from HDF5 (previously only CSV) (#663)

• Storage:

  • Load ensemble from HDF5 (#640)

• CI:

  • Add flake8 checks as pre-commit hook (#662)
  • Add efficient biological conversion reaction test model (#619)

• General:

  • No automatic import of the predict module (#657)
  • Assert unique problem parameter names (#665)
  • Load ensemble from optimization result with and without history usage
    (#640)
  • Calculate validation profile significance (#658)
  • Set pypesto screen logger to "INFO" by default (#667)

• Minor fixes:

  • Fix axis variable overwriting in visualize.sampling_parameter_traces
    (#665)

pyPESTO 0.2.5

• Objectives:

  • New Aesara objectve (#623, #629, #635)

• Sampling:

  • New Emcee sampler (#606)
  • Fix compatibility to new Theano version (#650)

• Storage:

  • Improve hdf5 storage documentation (#612)
  • Hdf5 history for MultiProcessEngine (#650)
  • Minor fixes (#637, #638, #645, #649)

• Visualization:

  • Fix bounds of parameter plots (#601)
  • Fix waterfall plots with multiple results (#611)

• CI:

  • Move CI tests on GitHub Actions to python 3.9 (#598)
  • Add issue template (#604)
  • Update BionetGen Link (#630)
  • Introduce project.toml (#634)

• General:

  • Introduce progress bar for optimization, profiles and ensembles (#641)
  • Extend gradient checking functionality (#644)

• Minor fixes:

  • Fix installation of ipopt (#599)
  • Fix Zenodo link (#601)
  • Fix duplicates in documentation (#603)
  • Fix least squares optimizers (#617 #631 #632)
  • Fix trust region options (#616)
  • Fix slicing for new AMICI release (#621)
  • Refactor and document latin hypercube sampling (#647)
  • Fix missing SBML name in PEtab import (#648)

pyPESTO 0.2.4

• Ensembles/Sampling:

  • General ensemble analysis, visualization, storage (#557, #565, #568)
  • Calculate and plot MCMC parameter and prediction CIs via ensemble
    definition, parallelize ensemble predictions (#490)

• Optimization:

  • New optimizer: SciPy Differential Evolution (#543)
  • Set fides default to hybrid (#578)

• AMICI:

  • Make guess_steadystate less restrictive (#561) and have a more
    intuitive default behavior (#562, #582)
  • Customize time points (#490)

• Storage:

  • Save HDF5 history with SingleCoreEngine (#564)
  • Add read/write function for whole results (#589)

• Engines:

  • MPI based distributed parallelization (#542)

• Visualization:

  • Speed up waterfall plots by resizing scales only once (#577)
  • Change waterfall default offset to 1 - minimum (#593)

• CI:

  • Move GHA CI tests to pull request level for better cooperability (#574)
  • Streamline test environments using tox and pre-commit hooks (#579)
  • Test profile and sampling storage (#585)
  • Update for Ubuntu 20.04, add rerun on failure (#587)

• Minor fixes (release notes #558, nlop tests #559, close files #495,
  visualization #554, deployment #560, flakiness #570,
  aggregated deepcopy #572, respect user-provided offsets #576,
  update to SWIG 4 #591, check overwrite in profile writing #566)

pyPESTO 0.2.3

• New Optimizers:

  • FIDES (#506, #503 #500)
  • NLopt (#493)

• Extended PEtab support:

  • PySB import (#437)
  • Support of PEtab's initializationPriors (#535)
  • Support of prior parameterScale{Normal,Laplace} (#520)
  • Example notebook for synthetic data generation (#482)

• General new and improved functionality:

  • Predictions (#544)
  • Move tests to GitHub Actions (#524)
  • Parallelize profile calculation (#532)
  • Save x_guesses in pypesto.problem (#494)
  • Improved finite difference gradients (#464)
  • Support of unconstrained optimization (#519)
  • Additional NaN check for fval, grad and hessian (#521)
  • Add sanity checks for optimizer bounds (#516)

• Improvements in storage:

  • Fix hdf5 export of optimizer history (#536)
  • Fix reading x_names from hdf5 history (#528)
  • Storage does not save empty arrays (#489)
  • hdf5 storage sampling (#546)
  • hdf5 storage parameter profiles (#546)

• Improvements in the visualization routines:

  • Plot parameter values as histogram (#485)
  • Fix y axis limits in waterfall plots (#503)
  • Fix color scheme in visualization (#498)
  • Improved visualization of optimization results (#486)

• Several small bug fixes (#547, #541, #538, #533, #512, #508)

pyPESTO 0.2.2

• New optimizer: CMA-ES (#457)
• New plot: Optimizer convergence summary (#446)
• Fixes in visualization:
  • Type checks for reference points (#460)
  • y_limits in waterfall plots with multiple results (#475)
• Support of new amici release (#469)
• Multiple fixes in optimization code:
  • Remove unused argument for dlib optimizer (#466)
  • Add check for installation of ipopt (#470)
  • Add maxiter as default option of dlib (#474)
• Numpy based subindexing in amici_util (#462)
• Check amici/PEtab installation (#477)

pyPESTO 0.2.1

• Example Notebook for prior functionality (#438)
• Changed parameter indexing in profiling routines (#419)
• Basic sanity checking for parameter fixing (#420)
• Bug fixes in:
  • Displaying of multi start optimization (#430)
  • AMICI error output (#428)
  • Axes scaling/limits in waterfall plots (#441)
  • Priors (PEtab impor, error handling) (#448, #452, #454)
• Improved sampling diagnostics (e.g. effective samples size) (#426)
• Improvements and bug fixes in parameter plots (#425)

pyPESTO 0.2.0

Major

• Modularize import, to import optimization, sampling and profiling separately (#413)

Minor

• Bug fixes in
  • sampling (#412)
  • visualization (#405)
  • PEtab import (#403)
  • Hessian computation (#390)
• Improve hdf5 error output (#409)
• Outlaw large new files in GitHub commits (#388)

pyPESTO 0.1.0

Objective

• Write solver settings to stream to enable serialization for distributed
  systems (#308)
• Refactor objective function (#347)
  • Removes necessity for all of the nasty binding/undbinding in AmiciObjective
  • Substantially reduces the complexity of the AggregatedObjective class
  • Aggregation of functions with inconsistent sensi_order/mode support
  • Introduce ObjectiveBase as an abstract Objective class
  • Introduce FunctionObjective for objectives from functions
• Implement priors with gradients, integrate with PEtab (#357)
• Fix minus sign in AmiciObjective.get_error_output (#361)
• Implement a prior class, derivatives for standard models, interface with
  PEtab (#357)
• Use amici.import_model_module to resolve module loading failure (#384)

Problem

• Tidy up problem vectors using properties (#393)

Optimization

• Interface IpOpt optimizer (#373)

Profiles

• Tidy up profiles (#356)
• Refactor profiles; add locally approximated profiles (#369)
• Fix profiling and visualization with fixed parameters (#393)

Sampling

• Geweke test for sampling convergence (#339)
• Implement basic Pymc3 sampler (#351)
• Make theano for pymc3 an optional dependency (allows using pypesto without
  pymc3) (#356)
• Progress bar for MCMC sampling (#366)
• Fix Geweke test crash for small sample sizes (#376)
• In parallel tempering, allow to only temperate the likelihood, not the prior
  (#396)

History and storage

• Allow storing results in a pre-filled hdf5 file (#290)
• Various fixes of the history (reduced vs. full parameters, read-in from file,
  chi2 values) (#315)
• Fix proper dimensions in result for failed start (#317)
• Create required directories before creating hdf5 file (#326)
• Improve storage and docs documentation (#328)
• Fix storing x_free_indices in hdf5 result (#334)
• Fix problem hdf5 return format (#336)
• Implement partial trace extraction, simplify History API (#337)
• Save really all attributes of a Problem to hdf5 (#342)

Visualization

• Customizable xLabels and tight layout for profile plots (#331)
• Fix non-positive bottom ylim on a log-scale axis in waterfall plots (#348)
• Fix "palette list has the wrong number of colors" in sampling plots (#372)
• Allow to plot multiple profiles from one result (#399)

Logging

• Allow easier specification of only logging for submodules (#398)

Tests

• Speed up travis build (#329)
• Update travis test system to latest ubuntu and python 3.8 (#330)
• Additional code quality checks, minor simplifications (#395)