Contribution start guide
========================

The preferred way to start contributing for the project is creating a virtualenv (you can do by using virtualenv,
virtualenvwrapper, pyenv or whatever tool you'd like). Only **Python 3.x** are supported


Preparing the eviroment
#######################

Create the virtualenv:

.. code-block:: bash

    mkvirtualenv hrv

Install all dependencies:

.. code-block:: bash

    pip install -r requirements.txt

Install development dependencies:

.. code-block:: bash

    pip install -r dev-requirements.txt

Running the tests
#################

In order to run the tests, activate the virtualenv and execute pytest:

.. code-block:: bash

    workon <virtualenv>
    pytest -v
    # or
    make test


Coding and Docstring styles
##########################


Generally, we try to use Python common styles conventions as described
in `PEP 8`_ and `PEP 257`_, which are also followed by the `numpy`_ project.

.. _PEP 8: https://www.python.org/dev/peps/pep-0008/ 
.. _PEP 257: https://www.python.org/dev/peps/pep-0257/
.. _numpy: https://numpydoc.readthedocs.io/en/latest/format.html

Example
********
.. code-block:: python

    def moving_average(rri, order=3):
        """
        Low-pass filter. Replace each RRi value by the average of its ⌊N/2⌋
        neighbors. The first and the last ⌊N/2⌋ RRi values are not filtered

        Parameters
        ----------
        rri : array_like
        sequence containing the RRi series
        order : int, optional
        Strength of the filter. Number of adjacent RRi values used to calculate
        the average value to replace the current RRi. Defaults to 3.

        .. math::
        considering movinge average of order equal to 3:
        RRi[j] = sum(RRi[j-2] + RRi[j-1] + RRi[j+1] + RRi[j+2]) / 3

        Returns
        -------
        results : RRi array
        instance of the RRi class containing the filtered RRi values

        See Also
        -------
        moving_median, threshold_filter, quotient

        Examples
        --------
        >>> from hrv.filters import moving_average
        >>> from hrv.sampledata import load_noisy_rri
        >>> noisy_rri = load_noisy_rri()
        >>> moving_average(noisy_rri)
        RRi array([904., 918., 941.66666667, ..., 732.66666667, 772.33333, 808.])
        """

We also encourage the  use of code linters, such `isort`_ , `black`_ and `autoflake`_.

.. _isort: https://github.com/timothycrosley/isort
.. _black: https://github.com/psf/black
.. _autoflake: https://github.com/myint/autoflake


.. code-block:: bash

    autoflake --in-place --recursive --remove-unused-variables --remove-all-unused-imports .
    sort -rc .
    black .