Merge branch 'master' into sample_ppc_ma

Author: aloctavodia

.readthedocs.yml

@@ -0,0 +1,14 @@
+# Build ePub (pdf is currently failing)
+formats:
+  - epub
+
+# pip requirements file for building sphinx docs (e.g. nbsphinx)
+requirements_file: docs/requirements-docs.txt
+
+# can also specify a conda env file if pip isn't enough, for example:
+# conda:
+#   file: environment.yml
+
+# Use python 3 for building
+python:
+  version: 3.5

.travis.yml

@@ -1,23 +1,31 @@
 language: python
+sudo: false
+
+cache:
+  directories:
+    - $HOME/.theano
+    - $HOME/minicoda2
+    - $HOME/minicoda3
 
 before_install:
   - . ./scripts/install_miniconda.sh
-  - "export DISPLAY=:99.0"
-  - "sh -e /etc/init.d/xvfb start"
-  - if [ ${MATPLOTLIB} = "1.2" ]; then mkdir $HOME/.matplotlib; fi
-  - if [ ${MATPLOTLIB} = "1.2" ]; then cp ${SRCDIR}/tools/matplotlibrc $HOME/.matplotlib/matplotlibrc; fi
+  - sh -e /etc/init.d/xvfb start
+  - export DISPLAY=":99.0"
 
 install:
   - . ./scripts/create_testenv.sh
   - pip install coveralls pylint
 
 env:
-  - PYTHON_VERSION=2.7 TESTCMD="--durations=10 --ignore=pymc3/tests/test_examples.py --cov-append --ignore=pymc3/tests/test_distributions_random.py --ignore=pymc3/tests/test_variational_inference.py --ignore=pymc3/tests/test_shared.py --ignore=pymc3/tests/test_smc.py --ignore=pymc3/tests/test_updates.py"
-  - PYTHON_VERSION=2.7 RUN_PYLINT="true" TESTCMD="--durations=10 --cov-append pymc3/tests/test_distributions_random.py pymc3/tests/test_shared.py pymc3/tests/test_smc.py"
-  - PYTHON_VERSION=2.7 TESTCMD="--durations=10 --cov-append pymc3/tests/test_examples.py pymc3/tests/test_variational_inference.py pymc3/tests/test_updates.py"
-  - PYTHON_VERSION=3.6 TESTCMD="--durations=10 --cov-append --ignore=pymc3/tests/test_examples.py --ignore=pymc3/tests/test_distributions_random.py --ignore=pymc3/tests/test_variational_inference.py --ignore=pymc3/tests/test_shared.py --ignore=pymc3/tests/test_smc.py --ignore=pymc3/tests/test_updates.py"
-  - PYTHON_VERSION=3.6 TESTCMD="--durations=10 --cov-append pymc3/tests/test_distributions_random.py pymc3/tests/test_shared.py pymc3/tests/test_smc.py"
-  - PYTHON_VERSION=3.6 TESTCMD="--durations=10 --cov-append pymc3/tests/test_examples.py pymc3/tests/test_variational_inference.py pymc3/tests/test_updates.py"
+  - PYTHON_VERSION=2.7 FLOATX='float32' TESTCMD="--durations=10 --ignore=pymc3/tests/test_examples.py --cov-append --ignore=pymc3/tests/test_distributions_random.py --ignore=pymc3/tests/test_variational_inference.py --ignore=pymc3/tests/test_shared.py --ignore=pymc3/tests/test_smc.py --ignore=pymc3/tests/test_updates.py --ignore=pymc3/tests/test_posteriors.py --ignore=pymc3/tests/test_sampling.py"
+  - PYTHON_VERSION=2.7 FLOATX='float32' RUN_PYLINT="true" TESTCMD="--durations=10 --cov-append pymc3/tests/test_distributions_random.py pymc3/tests/test_shared.py pymc3/tests/test_smc.py pymc3/tests/test_sampling.py"
+  - PYTHON_VERSION=2.7 FLOATX='float32' TESTCMD="--durations=10 --cov-append pymc3/tests/test_examples.py pymc3/tests/test_variational_inference.py pymc3/tests/test_updates.py pymc3/tests/test_posteriors.py"
+  - PYTHON_VERSION=2.7 FLOATX='float64' TESTCMD="--durations=10 --ignore=pymc3/tests/test_examples.py --cov-append --ignore=pymc3/tests/test_distributions_random.py --ignore=pymc3/tests/test_variational_inference.py --ignore=pymc3/tests/test_shared.py --ignore=pymc3/tests/test_smc.py --ignore=pymc3/tests/test_updates.py --ignore=pymc3/tests/test_posteriors.py --ignore=pymc3/tests/test_sampling.py"
+  - PYTHON_VERSION=2.7 FLOATX='float64' RUN_PYLINT="true" TESTCMD="--durations=10 --cov-append pymc3/tests/test_distributions_random.py pymc3/tests/test_shared.py pymc3/tests/test_smc.py pymc3/tests/test_sampling.py"
+  - PYTHON_VERSION=2.7 FLOATX='float64' TESTCMD="--durations=10 --cov-append pymc3/tests/test_examples.py pymc3/tests/test_variational_inference.py pymc3/tests/test_updates.py pymc3/tests/test_posteriors.py"
+  - PYTHON_VERSION=3.6 FLOATX='float64' TESTCMD="--durations=10 --cov-append --ignore=pymc3/tests/test_examples.py --ignore=pymc3/tests/test_distributions_random.py --ignore=pymc3/tests/test_variational_inference.py --ignore=pymc3/tests/test_shared.py --ignore=pymc3/tests/test_smc.py --ignore=pymc3/tests/test_updates.py --ignore=pymc3/tests/test_posteriors.py --ignore=pymc3/tests/test_sampling.py"
+  - PYTHON_VERSION=3.6 FLOATX='float64' TESTCMD="--durations=10 --cov-append pymc3/tests/test_distributions_random.py pymc3/tests/test_shared.py pymc3/tests/test_smc.py pymc3/tests/test_sampling.py"
+  - PYTHON_VERSION=3.6 FLOATX='float64' TESTCMD="--durations=10 --cov-append pymc3/tests/test_examples.py pymc3/tests/test_variational_inference.py pymc3/tests/test_updates.py pymc3/tests/test_posteriors.py"
 script:
   - . ./scripts/test.sh $TESTCMD
 

CHANGELOG.md

@@ -1,8 +1,9 @@
-.. image:: https://github.com/pymc-devs/pymc3/blob/master/docs/pymc3_logo.jpg?raw=true
+.. image:: https://cdn.rawgit.com/pymc-devs/pymc3/master/docs/logos/svg/PyMC3_banner.svg
+    :height: 100px
     :alt: PyMC3 logo
     :align: center
 
-|Gitter| |Build Status| |Coverage|
+|Build Status| |Coverage|
 
 PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning
 which focuses on advanced Markov chain Monte Carlo and variational fitting
@@ -123,13 +124,13 @@ https://doi.org/10.7717/peerj-cs.55
 Contact
 =======
 
-To report an issue with PyMC3 or to suggest a feature please use the `issue tracker <https://github.com/pymc-devs/pymc3/issues>`__.
+We are using `discourse.pymc.io <https://discourse.pymc.io/>`__ as our main communication channel. You can also follow us on `Twitter @pymc_devs <https://twitter.com/pymc_devs>`__ for updates and other announcements. 
 
-To ask a question regarding modeling or usage of PyMC3 we encourage posting to `StackOverflow using the "pymc" tag <http://stackoverflow.com/questions/tagged/pymc>`__.
+To ask a question regarding modeling or usage of PyMC3 we encourage posting to our Discourse forum under the `“Questions” Category <https://discourse.pymc.io/c/questions>`__. You can also suggest feature in the `“Development” Category <https://discourse.pymc.io/c/development>`__.
 
-To interact with PyMC3 developers, visit the `pymc Gitter channel <https://gitter.im/pymc-devs/pymc>`__.
+To report an issue with PyMC3 please use the `issue tracker <https://github.com/pymc-devs/pymc3/issues>`__.
 
-Finally, if you need to get in touch for non-technical information about the project, `send us an e-mail <fonnesbeck+[email protected]>`__.
+Finally, if you need to get in touch for non-technical information about the project, `send us an e-mail <pymc.devs@gmail.com>`__.
 
 License
 =======
@@ -173,8 +174,6 @@ Sponsors
 
 |Quantopian|
 
-.. |Gitter| image:: https://badges.gitter.im/Join%20Chat.svg
-   :target: https://gitter.im/pymc-devs/pymc?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
 .. |Build Status| image:: https://travis-ci.org/pymc-devs/pymc3.png?branch=master
    :target: https://travis-ci.org/pymc-devs/pymc3
 .. |Coverage| image:: https://coveralls.io/repos/github/pymc-devs/pymc3/badge.svg?branch=master

README.rst

@@ -1,13 +1,29 @@
 # Release Notes
 
-## PyMC3 3.1 (TBA)
+## PyMC3 3.1 (June 23, 2017)
 
 ### New features
 
-* [Add Gaussian Process submodule](http://pymc-devs.github.io/pymc3/notebooks/GP-introduction.html)
+* New user forum at http://discourse.pymc.io
+
+* [Gaussian Process submodule](http://pymc-devs.github.io/pymc3/notebooks/GP-introduction.html)
+
+* Much improved variational inference support:
+
+  - [Add Operator Variational Inference (experimental).](http://pymc-devs.github.io/pymc3/notebooks/bayesian_neural_network_opvi-advi.html)
+
+  - [Add Stein-Variational Gradient Descent as well as Amortized SVGD (experimental).](https://github.com/pymc-devs/pymc3/pull/2183)
+
+  - [Add pm.Minibatch() to easily specify mini-batches.](http://pymc-devs.github.io/pymc3/notebooks/bayesian_neural_network_opvi-advi.html#Minibatch-ADVI)
+
+  - Added various optimizers including ADAM.
+  
+  - Stopping criterion implemented via callbacks.
 
 * sample() defaults changed: tuning is enabled for the first 500 samples which are then discarded from the trace as burn-in.
 
+* MvNormal supports Cholesky Decomposition now for increased speed and numerical stability.
+
 * Many optimizations and speed-ups.
 
 * NUTS implementation now matches current Stan implementation.
@@ -28,24 +44,32 @@
 
 * Much improved variational inference support:
 
-  - [Add Operator Variational Inference (experimental).](http://pymc-devs.github.io/pymc3/notebooks/bayesian_neural_network_opvi-advi.html)
+  - [Added Operator Variational Inference (experimental).](http://pymc-devs.github.io/pymc3/notebooks/variational_api_quickstart.html)
 
-  - [Add Stein-Variational Gradient Descent as well as Amortized SVGD (experimental).](https://github.com/pymc-devs/pymc3/pull/2183)
+  - [Added Stein-Variational Gradient Descent as well as Amortized SVGD (experimental).](https://github.com/pymc-devs/pymc3/pull/2183)
 
-  - [Add pm.generator() to easily specify mini-batches.](http://pymc-devs.github.io/pymc3/notebooks/bayesian_neural_network_opvi-advi.html#Minibatch-ADVI)
+  - [Added `Minibatch` to easily specify mini-batches.](http://pymc-devs.github.io/pymc3/notebooks/bayesian_neural_network_opvi-advi.html#Minibatch-ADVI)
+  
+  - Added full-rank ADVI
 
   - Added various optimizers including ADAM.
+  
+  - Deprecated old ADVI interface
+  
+  - implemented `fit` function as the primary interface to approximation algorithms
+
+* Added support for multidimensional minibatches
 
 * [Sampled posteriors can now be turned into priors for Bayesian updating with a new interpolated distribution.](https://github.com/pymc-devs/pymc3/pull/2163)
 
+* Added `Approximation` class and the ability to convert a sampled trace into an approximation via its `Empirical` subclass.
+
 * `Model` can now be inherited from and act as a base class for user specified models (see pymc3.models.linear).
 
 * Add MvGaussianRandomWalk and MvStudentTRandomWalk distributions.
 
 * GLM models do not need a left-hand variable anymore.
 
-* Add support for cholesky parametrizations for cov/corr matrices.
-
 * Refactored HMC and NUTS for better readability.
 
 * Add support for Python 3.6.