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contributing.txt
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contributing.txt
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Shamelessly copied from scikit-image. Thanks for the great guide scikit-devs!
Development process
-------------------
Here's the long and short of it:
1. If you are a first-time contributor:
* Go to `https://github.com/scikit-beam/scikit-beam
<http://github.com/scikit-beam/scikit-beam>`_ and click the
"fork" button to create your own copy of the project.
* Clone the project to your local computer::
git clone [email protected]:your-username/scikit-beam.git
or ::
git clone https://github.com/your-username/scikit-beam.git
* Add the upstream repository::
git remote add upstream [email protected]:scikit-beam/scikit-beam.git
or ::
git remote add upstream https://github.com/scikit-beam/scikit-beam.git
* Fetch the upstream repository::
git fetch upstream
* Now, you have remote repositories named:
git remote -v
- ``upstream``, which refers to the ``scikit-beam`` repository
- ``origin``, which refers to your personal fork
2. Develop your contribution:
* Pull the latest changes from upstream::
git checkout master
git pull upstream master
* Create a branch for the feature you want to work on. Since the
branch name will appear in the merge message, use a sensible name
such as 'transform-speedups'::
git checkout -b transform-speedups
* Commit locally as you progress (``git add`` and ``git commit``)
3. Test your contribution
* at the root of the git repository, execute the following command ::
python run_tests.py
* Inspect the output to ensure that all tests passed
4. To submit your contribution:
* Push your changes back to your fork on GitHub::
git push origin transform-speedups
* **Explain your contribution.** Include a description aimed at someone
who may not be following the issue closely. If your contribution
includes new functionality or enhancements, include a link to an
IPython notebook demonstrating its use. And, as always, include tests.
* Go to GitHub. The new branch will show up with a green Pull Request
button - click it.
For a more detailed discussion, See `scikit-beam dev guide
<https://github.com/scikit-beam/scikit-beam/tree/master/doc/resource/dev_guide>`_.
Also see these scikit-image :doc:`detailed documents
<gitwash/index>` on how to use Git with ``scikit-image``
(`<http://scikit-image.org/docs/dev/gitwash/index.html>`_) and appropriately
translate scikit-image/scikit-image to scikit-beam/scikit-beam.
4. Review process:
* Reviewers (the other developers and interested community members) will
write inline and/or general comments on your Pull Request (PR) to help
you improve its implementation, documentation and style. Every single
developer working on the project has their code reviewed, and we've come
to see it as friendly conversation from which we all learn and the
overall code quality benefits. Therefore, please don't let the review
discourage you from contributing: its only aim is to improve the quality
of project, not to criticize (we are, after all, very grateful for the
time you're donating!).
* To update your pull request, make your changes on your local repository
and commit. As soon as those changes are pushed up (to the same branch as
before) the pull request will update automatically.
* `Travis-CI <http://travis-ci.org/>`__, a continuous integration service,
is triggered after each Pull Request update to build the code, run unit
tests, measure code coverage and check coding style (PEP8) of your
branch. The Travis tests must pass before your PR can be merged. If
Travis fails, you can find out why by clicking on the "failed" icon (red
cross) and inspecting the build and test log.
5. Document changes
Before merging your commits, you must add a description of your changes
to the release notes of the upcoming version in
``doc/release/release_dev.txt``.
.. note::
To reviewers: if it is not obvious, add a short explanation of what a branch
did to the merge message and, if closing a bug, also add "Closes #123"
where 123 is the issue number.
Divergence between ``upstream master`` and your feature branch
--------------------------------------------------------------
Do *not* ever merge the main branch into yours. If GitHub indicates that the
branch of your Pull Request can no longer be merged automatically, rebase
onto master::
git checkout master
git pull upstream master
git checkout transform-speedups
git rebase master
If any conflicts occur, fix the according files and continue::
git add conflict-file1 conflict-file2
git rebase --continue
However, you should only rebase your own branches and must generally not
rebase any branch which you collaborate on with someone else.
Finally, you must push your rebased branch::
git push --force origin transform-speedups
(If you are curious, here's a further discussion on the
`dangers of rebasing <http://tinyurl.com/lll385>`__.
Also see this `LWN article <http://tinyurl.com/nqcbkj>`__.)
Guidelines
----------
* All code should have tests (see `test coverage`_ below for more details).
* All code should be documented, to the same
`standard <http://projects.scipy.org/numpy/wiki/CodingStyleGuidelines>`_
as NumPy and SciPy.
* For new functionality, always add an example to the
gallery.
* **Never merge your own pull request.**
* Examples in the gallery should have a maximum figure width of 8 inches.
* When documenting APIs and/or source code, don’t make assumptions or make
implications about race, gender, religion, political orientation or anything
else that isn’t relevant to the project.
Stylistic Guidelines
--------------------
* Set up your editor to remove trailing whitespace. Follow `PEP08
<www.python.org/dev/peps/pep-0008/>`__. Check code with pyflakes / flake8.
* Use numpy data types instead of strings (``np.uint8`` instead of
``"uint8"``).
* Use the following import conventions::
import numpy as np
import matplotlib.pyplot as plt
cimport numpy as cnp # in Cython code
* When documenting array parameters, use ``image : (M, N) ndarray``
and then refer to ``M`` and ``N`` in the docstring, if necessary.
* Functions should support all input image dtypes. Use utility functions such
as ``img_as_float`` to help convert to an appropriate type. The output
format can be whatever is most efficient. This allows us to string together
several functions into a pipeline, e.g.::
hough(canny(my_image))
* Use ``Py_ssize_t`` as data type for all indexing, shape and size variables
in C/C++ and Cython code.
Test coverage
-------------
Tests for a module should ideally cover all code in that module,
i.e., statement coverage should be at 100%.
To measure the test coverage, install
`coverage.py <http://nedbatchelder.com/code/coverage/>`__
(using ``easy_install coverage``) and then run::
$ python run_tests.py
This will print a report with one line for each file in `skbeam`,
detailing the test coverage::
Name Stmts Miss Cover Missing
------------------------------------------------------------------
skbeam.calibration 48 0 100%
skbeam.constants 153 2 99% 783, 836
skbeam.core 306 113 63% 63-64, 101-105,
108, 113-146, 149-162, 167-172, 176, 179, 186-191, 237-240, 245-262,
266-270, 273-277, 280, 283, 289-294, 298-300, 304-334, 476, 658, 804,
894-903, 911, 915, 942, 960,
963, 1158
skbeam.feature 58 4 93% 133-136, 177, 216
skbeam.fitting 15 1 93% 77
skbeam.fitting.api 11 0 100%
skbeam.fitting.background 51 4 92% 127, 133, 141, 163
skbeam.fitting.base 4 0 100%
skbeam.fitting.base.parameter_data 9 0 100%
skbeam.fitting.lineshapes 56 1 98% 137
skbeam.fitting.models 40 2 95% 126, 156
skbeam.image 14 0 100%
skbeam.io 2 0 100%
skbeam.io.net_cdf_io 15 10 33% 81-105
skbeam.recip 35 4 89% 57-58, 142, 147
skbeam.spectroscopy 69 2 97% 133, 267
------------------------------------------------------------------
TOTAL 886 143 84%
----------------------------------------------------------------------
Ran 102 tests in 2.221s
(clearly we need to improve our own tests!)
Activate Travis-CI for your fork (optional)
-------------------------------------------
Travis-CI checks all unittests in the project to prevent breakage.
Before sending a pull request, you may want to check that Travis-CI
successfully passes all tests. To do so,
* Go to `Travis-CI <http://travis-ci.org/>`__ and follow the Sign In link at the top
* Go to your `profile page <https://travis-ci.org/profile>`__ and switch on your
scikit-beam fork
It corresponds to steps one and two in
`Travis-CI documentation <http://about.travis-ci.org/docs/user/getting-started/>`__
(Step three is already done in scikit-beam).
Thus, as soon as you push your code to your fork, it will trigger Travis-CI,
and you will receive an email notification when the process is done.
Every time Travis is triggered, it also calls on `Coveralls
<http://coveralls.io>`_ to inspect the current test overage.
Bugs
----
Please `report bugs on GitHub <https://github.com/scikit-beam/scikit-beam/issues>`_.