Pyabc

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Diverse:

* Shorten date-time log (456)
* Add look-ahead example notebook (461)
* Fix decoration of `plot_acceptance_rates_trajectory` (465)
* Hot-fix redis clean-up (475)

Semi-automatic summary statistics and robust sample weighting (429)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Breaking changes:

* API of the `(Adaptive)PNormDistance` was altered substantially to allow
cutom definition of update indices.
* Internal weighting of samples (should not affect users).

Semi-automatic summary statistics:

* Implement (Adaptive)PNormDistance with the ability to learn summary
statistics from simulations.
* Add `sumstat` submodule for generic mappings (id, trafos), and especially a
`PredictorSumstat` summary statistic that can make use of `Predictor` objects.
* Add subsetting routines that allow restricting predictor model training
samples.
* Add `predictor` submodule with generic `Predictor` class and concrete
implementations including linear regression, Lasso, Gaussian Process,
Neural Network.
* Add `InfoWeightedPNormDistance` that allows using predictor models to weight
data not only by scale, but also by information content.

Outlier-robust adaptive distances:

* Update documentation towards robust distances.
* Add section in the corresponding notebook.
* Implement PCMAD outlier correction scheme.

Changes to internal sample weighting:

* Do not normalize weights of in-memory particles by model; this allows to
more easily use the sampling weights and the list of particles for
adaptive components (e.g. distance functions)
* Normalization of population to 1 is applied on sample level in the
sampler wrapper function
* In the database, normalization is still by sample to not break old db
support; would be nicer to also there only normalize by total sum
-- requires a db update though.

Changes to internal object instruction from samples:

* Pass sample instead of weighted_sum_stats to distance function.
This is because thus the distance can choose on its own what it wants
-- all or only accepted particles; distances; weights; parameters;
summary statistics.

Visualization:

* Function to plot adaptive distance weights from log file.

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* Allow color customization for `plot_credible_intervals` plots (414)
* pyABC logo to grey to fit with both black and white backgrounds (453)
* Add style set to global figure parameters, enabling dark mode (454)

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Sampler:

* Allow redis dynamical sampler to only wait for relevant particles after
a generatio, giving a speed-up without drawbacks (448)
* Add option to limit number of delayed look-ahead samples to limit memory
usage (428)

Logging:

* Standardize output of floats (450)
* Use hierarchical logging (ABC.Submodule) (417)

General:

* Refactor: Remove deprecated `nr_samples_per_parameter`, internal
simplifications (422)
* Tidy up and minimize dependencies (436, 441)
* External: Remove simulation files after collecting results (434)
* Make feather/pyarrow dependency optional for older hardware (442)

Documentation:

* Add description of JupyterHub to documentation (439)

CI:

* Test webserver basic functionality
* Rerun stochastically failing tests (all 436)
* Test whether dataframe storage routines work properly (442)

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General:

* Speed up parameter handling (30% internal speed-up) (387)
* Streamline testing via tox and pre-commit hooks, add flake8 config file (408)
* Update to python 3.9 (411)
* Extract PEtab bounds and nominal parameters (416)
* Allow specifying parameter names in density plots (416)
* Normalize look-ahead sampling by subpopulation ESS (418, 421)

Documentation:

* Update contribution and issue guidelines (408)
* Add example on yaml2sbml usage (416)
* Clean up user docs on parallelization and storage (419)

Fixes:

* Fix redis for later started workers (410)
* Fix PEtab parameter scale import, support all PEtab prior distributions (413)

Database:

* Add database migration scheme based on alembic (419)
* Store proposal ids, increment database version to 0 (419)

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* Update branch name master -> main in agreement with
https://github.com/github/renaming (#406).
* Notebook improvements:

* Add ground truth to noise notebook.
* Rename notebook "quickstart" -> "model_selection".
* Split notebook tests in 2, extend, reduce test matrix (python 3.7).
* Improve output at the beginning and end (e.g. no `end_time` at beginning;
show duration).
* Add walltime plots (`plot_total_walltime`, `plot_walltime`,
`plot_eps_walltime`).
* Make sure `ABCSMC.run()` is always properly finished (sampler, history)
by a wrapper (all 401).
* Redis sampler with look-ahead mode:

* Fix insufficient logging of look-ahead samples.
* Log all accepted particles.
* Add `plot_lookahead_...` plots for look-ahead mode diagnostics.
* Add global figure parameter settings for pyABC (all 405).

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* Check components for their adaptivity for correct application of look-ahead
mode (397).