Merge branch 'master' into smc_model_llk

Author: hvasbath

.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

@@ -1,6 +1,12 @@
 language: python
 sudo: false
 
+cache:
+  directories:
+    - $HOME/.theano
+    - $HOME/minicoda2
+    - $HOME/minicoda3
+
 before_install:
   - . ./scripts/install_miniconda.sh
   - sh -e /etc/init.d/xvfb start
@@ -11,14 +17,14 @@ install:
   - pip install coveralls pylint
 
 env:
-  - 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"
-  - 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"
+  - 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"
-  - 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"
+  - 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"
-  - 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"
+  - 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

@@ -1,4 +1,5 @@
-.. 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
 

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.