CHANGELOG.rst

Changelog

• Update README.md

0.7.7 (2020-10-12)

• 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

0.7.6 (2020-08-29)

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

0.7.5 (2019-12-18)

• 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

0.7.4 (2019-03-07)

• 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

0.7.3 (2018-08-30)

• 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

0.7.2 (2018-06-20)

• Added support for kwargs in elfi.set_client
• Added new example: inference of transmission dynamics of bacteria in daycare centers
• Added new example: Lorenz model

0.7.1 (2018-04-11)

• Implemented model selection (elfi.compare_models). See API documentation.
• Fix threshold=0 in rejection sampling
• Set default batch_size to 1 in ParameterInference base class

0.7 (2017-11-30)

• Added new example: the stochastic Lotka-Volterra model
• Fix methods.bo.utils.minimize to be strictly within bounds
• Implemented the Two Stage Procedure, a method of summary-statistics diagnostics
• Added the MaxVar acquisition method
• Added the RandMaxVar acquisition method
• Added the ExpIntVar acquisition method
• Implemented the Two Stage Procedure, a method of summary-statistics diagnostics
• Added new example: the stochastic Lotka-Volterra model
• Fix methods.bo.utils.minimize to be strictly within bounds
• Fix elfi.Distance to support scipy 1.0.0

0.6.3 (2017-09-28)

• Further performance improvements for rerunning inference using stored data via caches
• Added the general Gaussian noise example model (fixed covariance)
• restrict NetworkX to versions < 2.0

0.6.2 (2017-09-06)

• Easier saving and loading of ElfiModel
• Renamed elfi.set_current_model to elfi.set_default_model
• Renamed elfi.get_current_model to elfi.get_default_model
• Improved performance when rerunning inference using stored data
• Change SMC to use ModelPrior, use to immediately reject invalid proposals

0.6.1 (2017-07-21)

• Fix elfi.Prior and NoneType error #203
• Fix a bug preventing the reuse of ArrayPool data with a new inference
• Added pickling for OutputPool:s
• Added OutputPool.open to read a closed pool from disk
• Refactored Sample and SmcSample classes
• Added elfi.new_model method
• Made elfi.set_client method to accept clients as strings for easier client switching
• Fixed a bug in NpyArray that would lead to an inconsistent state if multiple simultaneous instances were opened.
• Added the ability to move the pool data folder
• Sample.summary is now a method instead of a property
• SmcSample methods takes the keyword argument 'all' to show results of all populations
• Added a section about iterative advancing to documentation

0.6 (2017-07-03)

• Changed some of the internal variable names in methods.py. Most notable outputs is now output_names.
• methods.py renamed to parameter_inference.py
• Changes in elfi.methods.results module class names: - OptimizationResult (a new result type) - Result -> Sample - ResultSMC -> SmcSample - ResultBOLFI -> BolfiSample
• Changes in BO/BOLFI: - take advantage of priors - take advantage of seed - improved optimization scheme - bounds must be a dict
• two new toy examples added: Gaussian and the Ricker model

0.5 (2017-05-19)

Major update, a lot of code base rewritten.

Most important changes:

• revised syntax for model definition (esp. naming)
• scheduler-independent parallelization interface (currently supports native & ipyparallel)
• methods can now be run iteratively
• persistence to .npy files
• Bayesian optimization as a separate method
• sampling in BOLFI
• MCMC sampling using the No-U-Turn-Sampler (NUTS)
• Result object for BOLFI
• virtual vectorization of external operations

See the updated notebooks and documentation for examples and details.

0.3.1 (2017-01-31)

• Clean up requirements
• Set graphviz and unqlite optional
• PyPI release (pip install elfi)

0.2.2 - 0.3

• The inference problem is now contained in an Inference Task object.
• SMC-ABC has been reimplemented.
• Results from inference are now contained in a Result object.
• Integrated basic visualization.
• Added a notebook demonstrating usage with external simulators and operations.
• Lot's of refactoring and other minor changes.