Elfi

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- Merge adaptive distance ABC-SMC and ABC-SMC functionalities
- Split `DensityRatioEstimation` from utils.py into separate file
- Refactor parameter_inferency.py into methodtype-wise individual files
- Rename `elfi.methods.mcmc.gelman_rubin` as `elfi.methods.mcmc.gelman_rubin_statistic`
- Refactor `class ModelPrior` from `methods.utils` to `model.extensions`.
- Add adaptive threshold selection method for ABC-SMC
- Modify ProgressBar-functionality
- Add constrains to ExpIntVar-acquisition so that no queries will be outside prior support
- Add ABC-SMC with adaptive distance
- Add Robust optimisation Monte Carlo method
- Fix small issues in ABC-SMC which did not work in 1-dimensional problems or with output names
- Update README.md

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- Update info to reflect setting python 3.6 as the default version
- Update documentation to setting python 3.6 as default
- Add dask support to elfi client options
- Add python 3.7 to travis tests and remove python 3.5 due to clash with dask
- Modify progress bar to better indicate ABC-SMC inference status
- Change networkx support from 1.X to 2.X
- Improve docstrings in elfi.methods.bo.acquisition
- Fix readthedocs-build by adding .readthedocs.yml and restricting the build to
python3.5, for now

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- Fix incompatibility with scipy>1.5 in bo.utils.stochastic_optimization
- Minor improvements to documentation

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- Improved the appearance of figures produced by `plot_gp` and added the option
to draw true parameter indicators on the subplots using the optional input
`true_params`
- Modified DCC model by taking into account that subject can't infect herself
- Added ability to set minimizer constrains for BOLFI
- Enable bolfi.fit using only pre-generated initial evidence points
- Fixed a bug causing random seed number to be deterministic
- Updated requirements-dev.txt with pytest>=4.4
- Minor changes to documentation and refactoring
- Added `make test-notslow` alternative

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- Add sampler option `algorithm` for bolfi-posterior-sampling
- Add a check whether the option given for `algorithm` is one if the
implemented samplers
- Add metropolis sampler `algorithm=metropolis` for bolfi-posterior-sampling
- Add option `warmup` to metropolis-sampler
- Add a small test of metropolis-sampler
- Fix bug in plot_discrepancy for more than 6 parameters
- Implement plot_gp for BayesianOptimization classes for plotting discrepancies
and pair-wise contours in case when we have arbitrary number of parameters
- Fix lint

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- Fix bug in plot_pairs which crashes in case of 1 parameter
- Fix bug in plot_marginals which outputs empty plots in case where we have
parameter more than 5
- Fix crashing summary and plots for samples with multivariate priors
- Add progress bar for inference methods
- Add method save to Sample objects
- Add support for giving seed to `generate`
- Implement elfi.plot_params_vs_node for plotting parameters vs. node output