Elfi

----------------

- 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

----------------

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.

------------------

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

-----------

- 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.