Pull request checklist#

We recommend that your contribution complies with the following guidelines before you submit a pull request:

If your pull request addresses an issue, please use the pull request title to describe the issue and mention the issue number in the pull request description. This will make sure a link back to the original issue is created.
All public methods must have informative docstrings with sample usage when appropriate.
Please prefix the title of incomplete contributions with [WIP] (to indicate a work in progress). WIPs may be useful to (1) indicate you are working on something to avoid duplicated work, (2) request a broad review of functionality or API, or (3) seek collaborators.
All other tests pass when everything is rebuilt from scratch. See Developing in Docker for information on running the test suite locally.
When adding additional plotting functionality, provide at least one example script in the arviz/examples/ folder. Have a look at other examples for reference. Examples should demonstrate why the new functionality is useful in practice and, if possible, compare it to other methods available in ArviZ.
Added tests follow the pytest fixture pattern.
Documentation and high-coverage tests are necessary for enhancements to be accepted.
Documentation follows Numpy style guide.
Run any of the pre-existing examples in docs/source/notebooks that contain analyses that would be affected by your changes to ensure that nothing breaks. This is a useful opportunity to not only check your work for bugs that might not be revealed by unit test, but also to show how your contribution improves ArviZ for end users.
If modifying a plot, render your plot to inspect for changes and copy image in the pull request message on Github.

You can also check for common programming errors with the following tools:

Save plots as part of tests. Plots will be saved to a directory named test_images by default.
```
$ pytest arviz/tests/base_tests/<name of test>.py --save
```
Optionally save plots to a user named directory. This is useful for comparing changes across branches.
```
$ pytest arviz/tests/base_tests/<name of test>.py --save user_defined_directory
```

Code coverage cannot decrease. Coverage can be checked with pytest-cov package:

$ pip install pytest pytest-cov coverage
$ pytest --cov=arviz --cov-report=html arviz/tests/

Your code has been formatted with black with a line length of 100 characters.
```
$ pip install black
$ black arviz/ examples/ asv_benchmarks/
```
Your code passes pylint
```
$ pip install pylint
$ pylint arviz/
```
No code style warnings, check with:
```
$ ./scripts/lint.sh
```