Merge remote-tracking branch 'upstream/master'

Author: fonnesbeck

.github/workflows/pre-commit.yml

@@ -0,0 +1,14 @@
+name: pre-commit
+
+on:
+  pull_request:
+  push:
+    branches: [master]
+
+jobs:
+  pre-commit:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v2
+    - uses: actions/setup-python@v2
+    - uses: pre-commit/[email protected]

.gitignore

@@ -41,4 +41,3 @@ benchmarks/results/
 pytestdebug.log
 .dir-locals.el
 .pycheckers
-

.pre-commit-config.yaml

@@ -0,0 +1,28 @@
+repos:
+- repo: https://github.com/pre-commit/pre-commit-hooks
+  rev: v3.2.0
+  hooks:
+    -   id: end-of-file-fixer
+    -   id: check-toml
+- repo: https://github.com/nbQA-dev/nbQA
+  rev: 0.3.2
+  hooks:
+    - id: nbqa-black
+    - id: nbqa-isort
+    - id: nbqa-pyupgrade
+- repo: https://github.com/asottile/pyupgrade
+  rev: v2.7.2
+  hooks:
+    - id: pyupgrade
+      args: [--py36-plus]
+- repo: https://github.com/psf/black
+  rev: 20.8b1
+  hooks:
+    - id: black
+- repo: local
+  hooks:
+    - id: watermark
+      name: Check notebooks have watermark
+      types: [jupyter]
+      entry: python scripts/check_watermark.py
+      language: python

README.rst

@@ -13,6 +13,7 @@ large suite of problems.
 Check out the `getting started guide <http://docs.pymc.io/notebooks/getting_started>`__,  or
 `interact with live examples <https://mybinder.org/v2/gh/pymc-devs/pymc3/master?filepath=%2Fdocs%2Fsource%2Fnotebooks>`__
 using Binder!
+For questions on PyMC3, head on over to our `PyMC Discourse <https://discourse.pymc.io/>`__ forum.
 
 Features
 ========
@@ -78,12 +79,7 @@ Or via conda-forge:
 
     conda install -c conda-forge pymc3
 
-Plotting is done using `ArviZ <https://arviz-devs.github.io/arviz/>`__
-which may be installed separately, or along with PyMC3:
-
-::
-
-    pip install pymc3[plots]
+Plotting is done using `ArviZ <https://arviz-devs.github.io/arviz/>`__ - if you follow the installation instructions above, then it will be installed alongside ``PyMC3``.
 
 The current development branch of PyMC3 can be installed from GitHub, also using ``pip``:
 
@@ -172,7 +168,7 @@ Contributors
 ============
 
 See the `GitHub contributor
-page <https://github.com/pymc-devs/pymc3/graphs/contributors>`__
+page <https://github.com/pymc-devs/pymc3/graphs/contributors>`__. Also read our `Code of Conduct <https://github.com/pymc-devs/pymc3/blob/master/CODE_OF_CONDUCT.md>`__ guidelines for a better contributing experience.
 
 Support
 =======

RELEASE-NOTES.md

@@ -3,14 +3,22 @@
 ## PyMC3 3.9.x (on deck)
 
 ### Maintenance
+- Switch the dependency of Theano to our own fork, [Theano-PyMC](https://github.com/pymc-devs/Theano-PyMC).
 - Mentioned the way to do any random walk with `theano.tensor.cumsum()` in `GaussianRandomWalk` docstrings (see [#4048](https://github.com/pymc-devs/pymc3/pull/4048)).
 - Fixed numerical instability in ExGaussian's logp by preventing `logpow` from returning `-inf` (see [#4050](https://github.com/pymc-devs/pymc3/pull/4050)).
 - Use dill to serialize user defined logp functions in `DensityDist`. The previous serialization code fails if it is used in notebooks on Windows and Mac. `dill` is now a required dependency. (see [#3844](https://github.com/pymc-devs/pymc3/issues/3844)).
+- Numerically improved stickbreaking transformation - e.g. for the `Dirichlet` distribution. [#4129](https://github.com/pymc-devs/pymc3/pull/4129)
+- Enabled the `Multinomial` distribution to handle batch sizes that have more than 2 dimensions. [#4169](https://github.com/pymc-devs/pymc3/pull/4169)
 
 ### Documentation
 
 ### New features
 - `sample_posterior_predictive_w` can now feed on `xarray.Dataset` - e.g. from `InferenceData.posterior`. (see [#4042](https://github.com/pymc-devs/pymc3/pull/4042))
+- Added `pymc3.gp.cov.Circular` kernel for Gaussian Processes on circular domains, e.g. the unit circle (see [#4082](https://github.com/pymc-devs/pymc3/pull/4082)).
+- Add MLDA, a new stepper for multilevel sampling. MLDA can be used when a hierarchy of approximate posteriors of varying accuracy is available, offering improved sampling efficiency especially in high-dimensional problems and/or where gradients are not available (see [#3926](https://github.com/pymc-devs/pymc3/pull/3926))
+- Change SMC metropolis kernel to independent metropolis kernel [#4115](https://github.com/pymc-devs/pymc3/pull/3926))
+- Add alternative parametrization to NegativeBinomial distribution in terms of n and p (see [#4126](https://github.com/pymc-devs/pymc3/issues/4126))
+- Added a new `MixtureSameFamily` distribution to handle mixtures of arbitrary dimensions in vectorized form (see [#4185](https://github.com/pymc-devs/pymc3/issues/4185)).
 
 
 ## PyMC3 3.9.3 (11 August 2020)

benchmarks/benchmarks/__init__.py

@@ -11,5 +11,3 @@
 #   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #   See the License for the specific language governing permissions and
 #   limitations under the License.
-
-