Merge pull request #201 from elfi-dev/dev

Release 0.6

.gitignore

@@ -28,6 +28,12 @@ var/
 .installed.cfg
 *.egg
 
+# Images
+*.png
+*.svg
+*.jpg
+*.jpeg
+
 # PyInstaller
 #  Usually these files are written by a python script from a template
 #  before PyInstaller builds the exe, so as to inject date/other infos into it.

.travis.yml

@@ -1,13 +1,29 @@
-language: python
-python:
-  - "3.5"
+matrix:
+ include:
+  - os: linux
+    language: python
+    python: 3.5
+  - os: linux
+    language: python
+    python: 3.6
+  - os: osx
+    language: generic
+    before_install:
+    - mkdir -p /Users/travis/.matplotlib
+    - "echo 'backend: TkAgg' > /Users/travis/.matplotlib/matplotlibrc"
+    - brew update
+    - brew install python3
+    - virtualenv env -p python3
+    - source env/bin/activate
+
 cache: pip
-# command to install dependencies
+
 install:
   - pip install numpy
   - pip install -r requirements-dev.txt
   - pip install -e .
-# command to run tests
+
 script:
   - ipcluster start -n 2 --daemon
-  - travis_wait 20 make test
+  #- travis_wait 20 make test
+  - make test

CHANGELOG.md → CHANGELOG.rst

@@ -1,10 +1,32 @@
-# Change Log
+Changelog
+==========
+
+
+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
@@ -19,12 +41,14 @@ 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.

Makefile

@@ -1,4 +1,4 @@
-.PHONY: clean clean-test clean-pyc clean-build docs help
+.PHONY: clean clean-test clean-pyc clean-build docs notebook-docs help
 .DEFAULT_GOAL := help
 define BROWSER_PYSCRIPT
 import os, webbrowser, sys
@@ -64,16 +64,28 @@ coverage: ## check code coverage quickly with the default Python
 	$(BROWSER) htmlcov/index.html
 
 docs: ## generate Sphinx HTML documentation, including API docs
-	rm -f docs/elfi.rst
-	rm -f docs/elfi.bo.rst
-	rm -f docs/modules.rst
-	sphinx-apidoc -o docs/ elfi
 	$(MAKE) -C docs clean
+	$(MAKE) notebook-docs
 	$(MAKE) -C docs html
-	$(BROWSER) docs/_build/html/index.html
+	# $(BROWSER) docs/_build/html/index.html
 
-servedocs: docs ## compile the docs watching for changes
-	watchmedo shell-command -p '*.rst' -c '$(MAKE) -C docs html' -R -D .
+CONTENT_URL := http://research.cs.aalto.fi/pml/software/elfi/docs/0.6/
+
+notebook-docs: ## Conver notebooks to rst docs. Assumes you have them in `notebooks` directory.
+	jupyter nbconvert --to rst ../notebooks/quickstart.ipynb --output-dir docs
+	sed -i '' 's|\(quickstart_files/quickstart.*\.\)|'${CONTENT_URL}'\1|g' docs/quickstart.rst
+
+	jupyter nbconvert --to rst ../notebooks/tutorial.ipynb --output-dir docs/usage
+	sed -i '' 's|\(tutorial_files/tutorial.*\.\)|'${CONTENT_URL}usage/'\1|g' docs/usage/tutorial.rst
+
+	jupyter nbconvert --to rst ../notebooks/BOLFI.ipynb --output-dir docs/usage
+	sed -i '' 's|\(BOLFI_files/BOLFI.*\.\)|'${CONTENT_URL}usage/'\1|g' docs/usage/BOLFI.rst
+
+	jupyter nbconvert --to rst ../notebooks/parallelization.ipynb --output-dir docs/usage
+	sed -i '' 's|\(parallelization_files/parallelization.*\.\)|'${CONTENT_URL}usage/'\1|g' docs/usage/parallelization.rst
+
+	jupyter nbconvert --to rst ../notebooks/non_python_operations.ipynb --output-dir docs/usage --output=external
+	sed -i '' 's|\(external_files/external.*\.\)|'${CONTENT_URL}usage/'\1|g' docs/usage/external.rst
 
 # release: clean ## package and upload a release
 # 	python setup.py sdist upload
@@ -90,4 +102,4 @@ install: clean ## install the package to the active Python's site-packages
 	pip install -e .
 
 dev: install ## install the development requirements to the active Python's site-packages
-	pip install -Ur requirements-dev.txt
+	pip install -r requirements-dev.txt

README.md

@@ -1,26 +1,22 @@
+**Version 0.6 released!** See the CHANGELOG and [notebooks](https://github.com/elfi-dev/notebooks).
+
 ELFI - Engine for Likelihood-Free Inference
 ===========================================
 
 [![Build Status](https://travis-ci.org/elfi-dev/elfi.svg?branch=master)](https://travis-ci.org/elfi-dev/elfi)
-[![Code Health](https://landscape.io/github/elfi-dev/elfi/master/landscape.svg?style=flat)](https://landscape.io/github/elfi-dev/elfi/master)
+[![Code Health](https://landscape.io/github/elfi-dev/elfi/dev/landscape.svg?style=flat)](https://landscape.io/github/elfi-dev/elfi/dev)
 [![Documentation Status](https://readthedocs.org/projects/elfi/badge/?version=latest)](http://elfi.readthedocs.io/en/latest/?badge=latest)
 [![Gitter](https://badges.gitter.im/elfi-dev/elfi.svg)](https://gitter.im/elfi-dev/elfi?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
 
 <img src="https://cloud.githubusercontent.com/assets/1233418/20178983/6e22ee44-a75c-11e6-8345-5934b55b9dc6.png" width="15%" align="right"></img>
 
-ELFI is a statistical software package written in Python for performing inference with 
-generative models. The term "likelihood-free inference" refers to a family of inference
-methods that replace the use of the likelihood function with a data generating simulator 
-function. This is useful when the likelihood function is not computable or otherwise
-available but it is possible to make simulations of the process.
-
-Other names or related approaches to likelihood-free inference include Approximative 
-Bayesian Computation ([ABC](https://en.wikipedia.org/wiki/Approximate_Bayesian_computation)), 
-simulator-based inference, approximative Bayesian inference, indirect inference, etc. 
-
-**Note:** Versions 0.5+ introduce small but significant changes in syntax. See the [notebooks](https://github.com/elfi-dev/notebooks).
+ELFI is a statistical software package written in Python for likelihood-free inference (LFI) such as Approximate 
+Bayesian Computation ([ABC](https://en.wikipedia.org/wiki/Approximate_Bayesian_computation)). 
+The term LFI refers to a family of inference methods that replace the use of the likelihood function with a data 
+generating simulator function. ELFI features an easy to use generative modeling syntax and supports parallelized 
+inference out of the box.
 
-Currently implemented ABC methods:
+Currently implemented LFI methods:
 - ABC Rejection sampler
 - Sequential Monte Carlo ABC sampler
 - [Bayesian Optimization for Likelihood-Free Inference (BOLFI)](http://jmlr.csail.mit.edu/papers/v17/15-017.html)
@@ -29,12 +25,6 @@ Other notable included algorithms and methods:
 - Bayesian Optimization
 - [No-U-Turn-Sampler](http://jmlr.org/papers/volume15/hoffman14a/hoffman14a.pdf), a Hamiltonian Monte Carlo MCMC sampler
 
-ELFI includes an easy to use generative modeling syntax, where the generative model is 
-specified as a directed acyclic graph (DAG). The data generation process can then be 
-automatically parallelized from multiple cores up to a cluster environment. ELFI also 
-handles seeding the random number generators and storing of the generated data for you so
-that you can easily repeat or fine tune your inference.
-
 See examples under [notebooks](https://github.com/elfi-dev/notebooks) to get started. Full
 documentation can be found at http://elfi.readthedocs.io/. Limited user-support may be
 asked from elfi-support.at.hiit.fi, but the 
@@ -45,11 +35,15 @@ is preferable.
 Installation
 ------------
 
-ELFI requires and is tested with Python 3.5.
+ELFI requires and is tested with Python 3.5-3.6. You can install ELFI by typing in your terminal:
 
 ```
 pip install elfi
 ```
+or on some platforms using Python 3 specific syntax:
+```
+pip3 install elfi
+``` 
 
 Note that in some environments you may need to first install `numpy` with 
 `pip install numpy`. This is due to our dependency to `GPy` that uses `numpy` in its installation.
@@ -59,9 +53,8 @@ Note that in some environments you may need to first install `numpy` with
 - `graphviz` for drawing graphical models (needs [Graphviz](http://www.graphviz.org)), highly recommended
 
 
-### Python 3
+### Installing Python 3
 
-On some platforms you may have to use `pip3 install elfi`, in order to use Python 3. 
 If you are new to Python, perhaps the simplest way to install a specific version of Python
 is with [Anaconda](https://www.continuum.io/downloads).
 
@@ -85,5 +78,5 @@ Resolving these may sometimes go wrong:
 - If you receive an error about `yaml.load`, install `pyyaml`.
 - On OS X with Anaconda virtual environment say `conda install python.app` and then use 
 `pythonw` instead of `python`.
-- Note that ELFI currently supports Python 3.5 only, although 3.x may work as well, 
+- Note that ELFI currently supports Python 3.5-3.6 only, although 3.x may work as well, 
 so try `pip3 install elfi`.