sgmcmc.py merge conflict fixed

Author: shkr

.github/ISSUE_TEMPLATE.md

@@ -0,0 +1,19 @@
+If you have questions about a specific use case, please post it to our discourse channel: https://discourse.pymc.io  
+If you are not sure whether this is a bug or not, please also post it on discourse.
+
+## Description of your problem
+
+**Please provide a minimal, self-contained, and reproducible example.**
+
+**Please provide the full traceback.**
+
+**Please provide any additional information below.**
+
+
+## Versions and main components
+
+* PyMC3 Version:
+* Theano Version:
+* Python Version:
+* Operating system:
+* How did you install PyMC3: (conda/pip)

.gitignore

@@ -24,3 +24,8 @@ mcmc.sqlite
 
 # Docker development
 # notebooks/
+
+# air speed velocity (asv)
+benchmarks/env/
+benchmarks/html/
+benchmarks/results/

.pylintrc

@@ -47,6 +47,7 @@ enable=import-error,
        used-before-assignment,
        cell-var-from-loop,
        global-variable-undefined,
+       dangerous-default-value,
        # redefined-builtin,
        redefine-in-handler,
        unused-import,

.travis.yml

@@ -7,14 +7,20 @@ cache:
     - $HOME/minicoda2
     - $HOME/minicoda3
 
+addons:
+  apt_packages:
+    - pandoc
+
 before_install:
   - . ./scripts/install_miniconda.sh
   - sh -e /etc/init.d/xvfb start
   - export DISPLAY=":99.0"
 
 install:
   - . ./scripts/create_testenv.sh
-  - pip install coveralls pylint
+  - pip install coveralls pylint 
+  - pip install travis-sphinx==2.0.0
+  - pip install -r requirements-dev.txt
 
 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 --ignore=pymc3/tests/test_sampling.py"
@@ -26,10 +32,13 @@ env:
   - PYTHON_VERSION=2.7 FLOATX='float64' TESTCMD="--durations=10 --cov-append pymc3/tests/test_examples.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_posteriors.py"
+  - PYTHON_VERSION=3.6 FLOATX='float64' BUILD_DOCS="true" TESTCMD="--durations=10 --cov-append pymc3/tests/test_examples.py pymc3/tests/test_posteriors.py"
   - PYTHON_VERSION=3.6 FLOATX='float64' TESTCMD="--durations=10 --cov-append pymc3/tests/test_variational_inference.py pymc3/tests/test_updates.py"
+
 script:
   - . ./scripts/test.sh $TESTCMD
+  - . ./scripts/confirm_mpl_optional.sh
 
 after_success:
+  - if [[ "$BUILD_DOCS" == "true" ]]; then travis-sphinx deploy -c "docs.pymc.io"; fi
   - coveralls

LICENSE

@@ -6,7 +6,7 @@ PyMC is distributed under the Apache License, Version 2.0
 
 Copyright (c) 2006 Christopher J. Fonnesbeck (Academic Free License)
 Copyright (c) 2007-2008 Christopher J. Fonnesbeck, Anand Prabhakar Patil, David Huard (Academic Free License)
-Copyright (c) 2009-2013 The PyMC developers (see contributors to pymc-devs on GitHub)
+Copyright (c) 2009-2017 The PyMC developers (see contributors to pymc-devs on GitHub)
 All rights reserved.
 
                                  Apache License

README.rst

@@ -10,8 +10,8 @@ which focuses on advanced Markov chain Monte Carlo and variational fitting
 algorithms. Its flexibility and extensibility make it applicable to a
 large suite of problems.
 
-Check out the `getting started
-guide <http://pymc-devs.github.io/pymc3/notebooks/getting_started.html>`__!
+Check out the `getting started guide <http://docs.pymc.io/notebooks/getting_started>`__!
+
 
 Features
 ========
@@ -38,10 +38,12 @@ Getting started
 If you already know about Bayesian statistics:
 ----------------------------------------------
 
--  `API quickstart guide <http://pymc-devs.github.io/pymc3/notebooks/api_quickstart.html>`__
--  The `PyMC3 tutorial <http://pymc-devs.github.io/pymc3/notebooks/getting_started.html>`__
--  `PyMC3 examples <http://pymc-devs.github.io/pymc3/examples.html>`__
-   and the `API reference <http://pymc-devs.github.io/pymc3/api.html>`__
+
+-  `API quickstart guide <http://docs.pymc.io/notebooks/api_quickstart>`__
+-  The `PyMC3 tutorial <http://docs.pymc.io/notebooks/getting_started>`__
+-  `PyMC3 examples <http://docs.pymc.io/examples>`__ and the `API reference <http://docs.pymc.io/api>`__
+
+
 
 Learn Bayesian statistics with a book together with PyMC3:
 ----------------------------------------------------------
@@ -117,9 +119,9 @@ enables sparse scaling matrices which are useful for large problems.
 Citing PyMC3
 ============
 
-Salvatier J, Wiecki TV, Fonnesbeck C. (2016) Probabilistic programming
+Salvatier J., Wiecki T.V., Fonnesbeck C. (2016) Probabilistic programming
 in Python using PyMC3. PeerJ Computer Science 2:e55
-https://doi.org/10.7717/peerj-cs.55
+`DOI: 10.7717/peerj-cs.55 <https://doi.org/10.7717/peerj-cs.55>`__.
 
 Contact
 =======

RELEASE-NOTES.md

@@ -1,5 +1,80 @@
 # Release Notes
 
+
+## PyMC 3.3. (Unreleased) 
+ 
+### New features 
+ 
+- Improve NUTS initialization `advi+adapt_diag_grad` and add `jitter+adapt_diag_grad` (#2643) 
+- Update loo, new improved algorithm (#2730)
+
+### Fixes 
+- Fixed `compareplot` to use `loo` output. 
+- Add test for `model.logp_array` and `model.bijection` (#2724) 
+- Fixed `sample_ppc` and `sample_ppc_w` to iterate all chains(#2633)
+- Add Bayesian R2 score (for GLMs) `stats.r2_score` (#2696) and test (#2729).
+
+
+
+## PyMC3 3.2 (October 10, 2017)
+
+### New features
+
+This version includes two major contributions from our Google Summer of Code 2017 students:
+
+* Maxim Kochurov extended and refactored the variational inference module. This primarily adds two important classes, representing operator variational inference (`OPVI`) objects and `Approximation` objects. These make it easier to extend existing `variational` classes, and to derive inference from `variational` optimizations, respectively. The `variational` module now also includes normalizing flows (`NFVI`).
+* Bill Engels added an extensive new Gaussian processes (`gp`) module. Standard GPs can be specified using either `Latent` or `Marginal` classes, depending on the nature of the underlying function. A Student-T process `TP` has been added. In order to accomodate larger datasets, approximate marginal Gaussian processes (`MarginalSparse`) have been added. 
+
+Documentation has been improved as the result of the project's monthly "docathons".
+
+An experimental stochastic gradient Fisher scoring (`SGFS`) sampling step method has been added.
+
+The API for `find_MAP` was enhanced.
+
+SMC now estimates the marginal likelihood.
+
+Added `Logistic` and `HalfFlat` distributions to set of continuous distributions.
+
+Bayesian fraction of missing information (`bfmi`) function added to `stats`.
+
+Enhancements to `compareplot` added.
+
+QuadPotential adaptation has been implemented.
+
+Script added to build and deploy documentation.
+
+MAP estimates now available for transformed and non-transformed variables.
+
+The `Constant` variable class has been deprecated, and will be removed in 3.3.
+
+DIC and BPIC calculations have been sped up.
+
+Arrays are now accepted as arguments for the `Bound` class.
+
+`random` method was added to the `Wishart` and `LKJCorr` distributions.
+
+Progress bars have been added to LOO and WAIC calculations.
+
+All example notebooks updated to reflect changes in API since 3.1.
+
+Parts of the test suite have been refactored.
+
+### Fixes
+
+Fixed sampler stats error in NUTS for non-RAM backends
+
+Matplotlib is  no longer a hard dependency, making it easier to use in settings where installing Matplotlib is problematic. PyMC will only complain if plotting is attempted.
+
+Several bugs in the Gaussian process covariance were fixed.
+
+All chains are now used to calculate WAIC and LOO.
+
+AR(1) log-likelihood function has been fixed.
+
+Slice sampler fixed to sample from 1D conditionals.
+
+Several docstring fixes.
+
 ## PyMC3 3.1 (June 23, 2017)
 
 ### New features

benchmarks/asv.conf.json

@@ -0,0 +1,83 @@
+{
+    // The version of the config file format.  Do not change, unless
+    // you know what you are doing.
+    "version": 1,
+
+    // The name of the project being benchmarked
+    "project": "pymc3",
+
+    // The project's homepage
+    "project_url": "https://pymc-devs.github.io/pymc3/",
+
+    // The URL or local path of the source code repository for the
+    // project being benchmarked
+    "repo": "..",
+
+    // List of branches to benchmark. If not provided, defaults to "master"
+    // (for git) or "tip" (for mercurial).
+    "branches": ["master"],
+
+    // The DVCS being used.  If not set, it will be automatically
+    // determined from "repo" by looking at the protocol in the URL
+    // (if remote), or by looking for special directories, such as
+    // ".git" (if local).
+    "dvcs": "git",
+
+    // The tool to use to create environments.  May be "conda",
+    // "virtualenv" or other value depending on the plugins in use.
+    // If missing or the empty string, the tool will be automatically
+    // determined by looking for tools on the PATH environment
+    // variable.
+    "environment_type": "conda",
+
+    // the base URL to show a commit for the project.
+    "show_commit_url": "https://github.com/pymc-devs/pymc3/commit/",
+
+    // The Pythons you'd like to test against.  If not provided, defaults
+    // to the current version of Python used to run `asv`.
+    "pythons": ["3.6"],
+
+    // The matrix of dependencies to test.  Each key is the name of a
+    // package (in PyPI) and the values are version numbers.  An empty
+    // list indicates to just test against the default (latest)
+    // version.
+    "matrix": {
+    },
+
+    // The directory (relative to the current directory) that benchmarks are
+    // stored in.  If not provided, defaults to "benchmarks"
+    "benchmark_dir": "benchmarks",
+
+    // The directory (relative to the current directory) to cache the Python
+    // environments in.  If not provided, defaults to "env"
+    "env_dir": "env",
+
+    // The directory (relative to the current directory) that raw benchmark
+    // results are stored in.  If not provided, defaults to "results".
+    "results_dir": "results",
+
+    // The directory (relative to the current directory) that the html tree
+    // should be written to.  If not provided, defaults to "html".
+    "html_dir": "html",
+
+    // The number of characters to retain in the commit hashes.
+    // "hash_length": 8,
+
+    // `asv` will cache wheels of the recent builds in each
+    // environment, making them faster to install next time.  This is
+    // number of builds to keep, per environment.
+    "wheel_cache_size": 2,
+
+    // The commits after which the regression search in `asv publish`
+    // should start looking for regressions. Dictionary whose keys are
+    // regexps matching to benchmark names, and values corresponding to
+    // the commit (exclusive) after which to start looking for
+    // regressions.  The default is to start from the first commit
+    // with results. If the commit is `null`, regression detection is
+    // skipped for the matching benchmark.
+    //
+    // "regressions_first_commits": {
+    //    "some_benchmark": "352cdf",  // Consider regressions only after this commit
+    //    "another_benchmark": null,   // Skip regression detection altogether
+    // }
+}

benchmarks/benchmarks/__init__.py

@@ -0,0 +1 @@
+