* Update CI test system: latest Ubuntu, python 3.8, simplify R build (296). * Add weights logging to adaptive distances (295). * Migrate CI tests to GitHub Actions for speed-up, reliability and maintainability (297, 298).
0.10.1
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* Allow separate calibration population sizes, slightly reformulate PopulationStrategy class (278). * Allow specifying initial weights for adaptive distances, then without sampling from the prior (279). * Check PEtab test suite in tests (281).
0.10
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0.10.0
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* Exact inference via stochastic acceptor finalized and tested (developed throughout the 0.9 series). * Support basic PEtab functionality using AMICI ODE simulations (268). * Various error fixes (265, 267). * Log number of processes used by multiprocessing samplers (263). * Implement pyabc.acceptor.ScaledPDFNorm (269). * Implement list population size (274, 276). * On history loading, automatically find an id of a successful run (273).
0.9.26
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* Add optional check whether database is non-existent, to detect typos. * Set lower bound in 1-dim KDEs to <= 0 to not wrongly display near-uniform distributions. (both 257) * Implement redis password protection for sampler and manage routine (256). * Make samplers available in global namespace (249). * Implement ListTemperature (248). * Allow plotting the relative ESS (245). * Allow resampling of weighted particles (244). * Fix ABCSMC.load with rpy2 (242).
0.9.25
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* Add summary statistics callback plot function (231). * Add possibility to log employed norms in StochasticAcceptor (231) and temperature proposals in Temperature (232). * Implement optional early stopping in the MulticoreEvalParallelSampler and the SingleCoreSampler, when a maximum simulation number is exceeded (default behavior untouched). * Log stopping reason in ABCSMC.run (all 236). * Implement Poisson (237) and negative binomial (239) stochastic kernels. * Enable password protection for Redis sampler (238). * Fix scipy deprecations (234, 241).