pplot 1.1.2
This module can be used to create high-quality, presentation-ready X-Y graphs quickly and easily
License: MIT

.. README.rst
.. Copyright (c) 2013-2018 Pablo Acosta-Serafini
.. See LICENSE for details


.. image:: https://badge.fury.io/py/pplot.svg
    :target: https://pypi.python.org/pypi/pplot
    :alt: PyPI version

.. image:: https://img.shields.io/pypi/l/pplot.svg
    :target: https://pypi.python.org/pypi/pplot
    :alt: License

.. image:: https://img.shields.io/pypi/pyversions/pplot.svg
    :target: https://pypi.python.org/pypi/pplot
    :alt: Python versions supported

.. image:: https://img.shields.io/pypi/format/pplot.svg
    :target: https://pypi.python.org/pypi/pplot
    :alt: Format

|

.. image::
   https://travis-ci.org/pmacosta/pplot.svg?branch=master

.. image::
   https://ci.appveyor.com/api/projects/status/
   7dpk342kxs8kcg5t/branch/master?svg=true
   :alt: Windows continuous integration

.. image::
   https://codecov.io/github/pmacosta/pplot/coverage.svg?branch=master
   :target: https://codecov.io/github/pmacosta/pplot?branch=master
   :alt: Continuous integration coverage

.. image::
   https://readthedocs.org/projects/pip/badge/?version=stable
   :target: http://pip.readthedocs.org/en/stable/?badge=stable
   :alt: Documentation status

|

Description
===========

.. role:: bash(code)
	:language: bash

.. [[[cog
.. import os, sys, pmisc, docs.support.requirements_to_rst
.. file_name = sys.modules['docs.support.requirements_to_rst'].__file__
.. mdir = os.path.join(os.path.realpath(
..    os.path.dirname(os.path.dirname(os.path.dirname(file_name)))), 'sbin'
.. )
.. docs.support.requirements_to_rst.def_links(cog)
.. ]]]
.. _Astroid: https://bitbucket.org/logilab/astroid
.. _Cog: http://nedbatchelder.com/code/cog
.. _Coverage: http://coverage.readthedocs.org/en/coverage-4.0a5
.. _Decorator: https://pythonhosted.org/decorator
.. _Docutils: http://docutils.sourceforge.net/docs
.. _Funcsigs: https://pypi.python.org/pypi/funcsigs
.. _Matplotlib: http://matplotlib.org
.. _Mock: http://www.voidspace.org.uk/python/mock
.. _Numpy: http://www.numpy.org
.. _Pcsv: http://pcsv.readthedocs.org
.. _Peng: http://peng.readthedocs.org
.. _Pexdoc: http://pexdoc.readthedocs.org
.. _Pillow: https://python-pillow.github.io
.. _Pmisc: http://pmisc.readthedocs.org
.. _PyContracts: https://andreacensi.github.io/contracts
.. _Pylint: http://www.pylint.org
.. _Py.test: http://pytest.org
.. _Pytest-coverage: https://pypi.python.org/pypi/pytest-cov
.. _Pytest-xdist: https://pypi.python.org/pypi/pytest-xdist
.. _Scipy: http://www.scipy.org
.. _Six: https://pythonhosted.org/six
.. _Sphinx: http://sphinx-doc.org
.. _ReadTheDocs Sphinx theme: https://github.com/snide/sphinx_rtd_theme
.. _Inline Syntax Highlight Sphinx Extension:
   https://bitbucket.org/klorenz/sphinxcontrib-inlinesyntaxhighlight
.. _Tox: https://testrun.org/tox
.. _Virtualenv: http://docs.python-guide.org/en/latest/dev/virtualenvs
.. [[[end]]]

This module can be used to create high-quality, presentation-ready X-Y graphs
quickly and easily

***************
Class hierarchy
***************

The properties of the graph (figure in Matplotlib parlance) are defined in an
object of the pplot.Figure class.

Each figure can have one or more panels, whose properties are defined by objects
of the pplot.Panel class. Panels are arranged vertically in
the figure and share the same independent axis.  The limits of the independent
axis of the figure result from the union of the limits of the independent axis
of all the panels. The independent axis is shown by default in the bottom-most
panel although it can be configured to be in any panel or panels.

Each panel can have one or more data series, whose properties are defined by
objects of the pplot.Series class. A series can be associated
with either the primary or secondary dependent axis of the panel. The limits of
the primary and secondary dependent axis of the panel result from the union of
the primary and secondary dependent data points of all the series associated
with each axis. The primary axis is shown on the left of the panel and the
secondary axis is shown on the right of the panel. Axes can be linear or
logarithmic.

The data for a series is defined by a source. Two data sources are provided:
the pplot.BasicSource class provides basic data validation
and minimum/maximum independent variable range bounding. The
pplot.CsvSource class builds upon the functionality of the
pplot.BasicSource class and offers a simple way of accessing
data from a comma-separated values (CSV) file.  Other data sources can be
programmed by inheriting from the pplot.functions.DataSource
abstract base class (ABC). The custom data source needs to implement the
following methods: :code:`__str__`, :code:`_set_indep_var` and
:code:`_set_dep_var`. The latter two methods set the contents of the
independent variable (an increasing real Numpy vector) and the dependent
variable (a real Numpy vector) of the source, respectively.


***************
Axes tick marks
***************

Axes tick marks are selected so as to create the most readable graph. Two
global variables control the actual number of ticks,
pplot.constants.MIN_TICKS and
pplot.constants.SUGGESTED_MAX_TICKS.
In general the number of ticks are between these two bounds; one or two more
ticks can be present if a data series uses interpolation and the interpolated
curve goes above (below) the largest (smallest) data point. Tick spacing is
chosen so as to have the most number of data points "on grid". Engineering
notation (i.e. 1K = 1000, 1m = 0.001, etc.) is used for the axis tick marks.

*******
Example
*******

.. [[[cog
.. import pmisc
.. pmisc.incfile(
..     "plot_example_1.py",
..     cog.out,
..     "1,6-108",
..     "../docs/support"
.. )
.. ]]]
.. code-block:: python

    # plot_example_1.py
    from __future__ import print_function
    import os, sys, numpy, pplot

    def main(fname, no_print):
        """
        Example of how to use the pplot library
        to generate presentation-quality plots
        """
        ###
        # Series definition (Series class)
        ###
        # Extract data from a comma-separated (csv)
        # file using the CsvSource class
        wdir = os.path.dirname(__file__)
        csv_file = os.path.join(wdir, 'data.csv')
        series1_obj = [pplot.Series(
            data_source=pplot.CsvSource(
                fname=csv_file,
                rfilter={'value1':1},
                indep_col_label='value2',
                dep_col_label='value3',
                indep_min=None,
                indep_max=None,
                fproc=series1_proc_func,
                fproc_eargs={'xoffset':1e-3}
            ),
            label='Source 1',
            color='k',
            marker='o',
            interp='CUBIC',
            line_style='-',
            secondary_axis=False
        )]
        # Literal data can be used with the BasicSource class
        series2_obj = [pplot.Series(
            data_source=pplot.BasicSource(
                indep_var=numpy.array([0e-3, 1e-3, 2e-3]),
                dep_var=numpy.array([4, 7, 8]),
            ),
            label='Source 2',
            color='r',
            marker='s',
            interp='STRAIGHT',
            line_style='--',
            secondary_axis=False
        )]
        series3_obj = [pplot.Series(
            data_source=pplot.BasicSource(
                indep_var=numpy.array([0.5e-3, 1e-3, 1.5e-3]),
                dep_var=numpy.array([10, 9, 6]),
            ),
            label='Source 3',
            color='b',
            marker='h',
            interp='STRAIGHT',
            line_style='--',
            secondary_axis=True
        )]
        series4_obj = [pplot.Series(
            data_source=pplot.BasicSource(
                indep_var=numpy.array([0.3e-3, 1.8e-3, 2.5e-3]),
                dep_var=numpy.array([8, 8, 8]),
            ),
            label='Source 4',
            color='g',
            marker='D',
            interp='STRAIGHT',
            line_style=None,
            secondary_axis=True
        )]
        ###
        # Panels definition (Panel class)
        ###
        panel_obj = pplot.Panel(
            series=series1_obj+series2_obj+series3_obj+series4_obj,
            primary_axis_label='Primary axis label',
            primary_axis_units='-',
            secondary_axis_label='Secondary axis label',
            secondary_axis_units='W',
            legend_props={'pos':'lower right', 'cols':1}
        )
        ###
        # Figure definition (Figure class)
        ###
        dim = 2.25
        fig_obj = pplot.Figure(
            panels=panel_obj,
            indep_var_label='Indep. var.',
            indep_var_units='S',
            log_indep_axis=False,
            fig_width=4*dim,
            fig_height=3*dim,
            title='Library pplot Example'
        )
        # Save figure
        output_fname = os.path.join(wdir, fname)
        if not no_print:
            print('Saving image to file {0}'.format(output_fname))
        fig_obj.save(output_fname, compress=True)

    def series1_proc_func(indep_var, dep_var, xoffset):
        """ Process data 1 series """
        return (indep_var*1e-3)-xoffset, dep_var

.. [[[end]]]

|


Interpreter
===========

The package has been developed and tested with Python 2.7, 3.5 and 3.6 under
Linux (Debian, Ubuntu), Apple OS X and Microsoft Windows

Installing
==========

.. code-block:: bash

	$ pip install pplot

Documentation
=============

Available at `Read the Docs <https://pplot.readthedocs.org>`_

Contributing
============

1. Abide by the adopted `code of conduct
   <http://contributor-covenant.org/version/1/3/0>`_

2. Fork the `repository <https://github.com/pmacosta/pplot>`_ from
   GitHub and then clone personal copy [#f1]_:

	.. code-block:: bash

		$ git clone \
		      https://github.com/[github-user-name]/pplot.git
                Cloning into 'pplot'...
                ...
		$ cd pplot
		$ export PPLOT_DIR=${PWD}

3. Install the project's Git hooks and build the documentation. The pre-commit
   hook does some minor consistency checks, namely trailing whitespace and
   `PEP8 <https://www.python.org/dev/peps/pep-0008/>`_ compliance via
   Pylint. Assuming the directory to which the repository was cloned is
   in the :bash:`$PPLOT_DIR` shell environment variable:

	.. code-block:: bash

		$ ${PPLOT_DIR}/sbin/complete-cloning.sh
                Installing Git hooks
                Building pplot package documentation
                ...

4. Ensure that the Python interpreter can find the package modules
   (update the :bash:`$PYTHONPATH` environment variable, or use
   `sys.paths() <https://docs.python.org/2/library/sys.html#sys.path>`_,
   etc.)

	.. code-block:: bash

		$ export PYTHONPATH=${PYTHONPATH}:${PPLOT_DIR}

5. Install the dependencies (if needed, done automatically by pip):

    .. [[[cog
    .. docs.support.requirements_to_rst.proc_requirements(cog)
    .. ]]]


    * `Astroid`_ (1.5.3 or newer)

    * `Cog`_ (2.5.1 or newer)

    * `Coverage`_ (4.4.1 or newer)

    * `Decorator`_ (4.0.11 or newer)

    * `Docutils`_ (0.13.1 or newer)

    * `Funcsigs`_ (Python 2.x only, 1.0.2 or newer)

    * `Inline Syntax Highlight Sphinx Extension`_ (0.2 or newer)

    * `Matplotlib`_ (2.0.0 or newer)

    * `Mock`_ (Python 2.x only, 2.0.0 or newer)

    * `Numpy`_ (1.13.1 or newer)

    * `Pcsv`_ (1.0.6 or newer)

    * `Peng`_ (1.0.6 or newer)

    * `Pexdoc`_ (1.0.9 or newer)

    * `Pillow`_ (4.0.0 or newer)

    * `Pmisc`_ (1.2.2 or newer)

    * `Py.test`_ (3.1.2 or newer)

    * `PyContracts`_ (1.7.15 or newer)

    * `Pylint`_ (1.7.1 or newer)

    * `Pytest-coverage`_ (2.5.1 or newer)

    * `Pytest-xdist`_ (optional, 1.21.0 or newer)

    * `ReadTheDocs Sphinx theme`_ (0.2.4 or newer)

    * `Scipy`_ (1.0.0 or newer)

    * `Six`_ (1.11.0 or newer)

    * `Sphinx`_ (1.6.5 or newer)

    * `Tox`_ (2.9.1 or newer)

    * `Virtualenv`_ (15.1.0 or newer)

    .. [[[end]]]

6. Implement a new feature or fix a bug

7. Write a unit test which shows that the contributed code works as expected.
   Run the package tests to ensure that the bug fix or new feature does not
   have adverse side effects. If possible achieve 100% code and branch
   coverage of the contribution. Thorough package validation
   can be done via Tox and Py.test:

	.. code-block:: bash

            $ tox
            GLOB sdist-make: .../pplot/setup.py
            py26-pkg inst-nodeps: .../pplot/.tox/dist/pplot-...zip

   `Setuptools <https://bitbucket.org/pypa/setuptools>`_ can also be used
   (Tox is configured as its virtual environment manager) [#f2]_:

	.. code-block:: bash

	    $ python setup.py tests
            running tests
            running egg_info
            writing requirements to pplot.egg-info/requires.txt
            writing pplot.egg-info/PKG-INFO
            ...

   Tox (or Setuptools via Tox) runs with the following default environments:
   ``py27-pkg``, ``py35-pkg`` and ``py36-pkg`` [#f3]_. These use the 2.7, 3.5
   and 3.6 interpreters, respectively, to test all code in the documentation
   (both in Sphinx ``*.rst`` source files and in docstrings), run all unit
   tests, measure test coverage and re-build the exceptions documentation. To
   pass arguments to Py.test (the test runner) use a double dash (``--``) after
   all the Tox arguments, for example:

	.. code-block:: bash

	    $ tox -e py27-pkg -- -n 4
            GLOB sdist-make: .../pplot/setup.py
            py27-pkg inst-nodeps: .../pplot/.tox/dist/pplot-...zip
            ...

   Or use the :code:`-a` Setuptools optional argument followed by a quoted
   string with the arguments for Py.test. For example:

	.. code-block:: bash

	    $ python setup.py tests -a "-e py27-pkg -- -n 4"
            running tests
            ...

   There are other convenience environments defined for Tox [#f4]_:

    * ``py27-repl``, ``py35-repl`` and ``py36-repl`` run the 2.7, 3.6 or 3.6
      REPL, respectively, in the appropriate virtual environment. The ``pplot``
      package is pip-installed by Tox when the environments are created.
      Arguments to the interpreter can be passed in the command line after a
      double dash (``--``)

    * ``py27-test``, ``py35-test`` and ``py36-test`` run py.test using the
      Python 2.7, 3.5 or Python 3.6 interpreter, respectively, in the
      appropriate virtual environment. Arguments to py.test can be passed in the
      command line after a double dash (``--``) , for example:

	.. code-block:: bash

	    $ tox -e py36-test -- -x test_pplot.py
            GLOB sdist-make: [...]/pplot/setup.py
            py36-test inst-nodeps: [...]/pplot/.tox/dist/pplot-1.1rc1.zip
            py36-test installed: -f file:[...]
            py36-test runtests: PYTHONHASHSEED='1264622266'
            py36-test runtests: commands[0] | [...]py.test -x test_pplot.py
            ===================== test session starts =====================
            platform linux -- Python 3.6.4, pytest-3.3.1, py-1.5.2, pluggy-0.6.0
            rootdir: [...]/pplot/.tox/py36/share/pplot/tests, inifile: pytest.ini
            plugins: xdist-1.21.0, forked-0.2, cov-2.5.1
            collected 414 items
            ...

    * ``py27-cov``, ``py35-cov`` and ``py36-cov`` test code and branch coverage
      using the 2.7, 3.5 or 3.6 interpreter, respectively, in the appropriate
      virtual environment. Arguments to py.test can be passed in the command
      line after a double dash (``--``). The report can be found in
      :bash:`${PPLOT_DIR}/.tox/py[PV]/usr/share/pplot/tests/htmlcov/index.html`
      where ``[PV]`` stands for ``27``, ``35`` or ``36`` depending on the
      interpreter used

8. Verify that continuous integration tests pass. The package has continuous
   integration configured for Linux (via `Travis <http://www.travis-ci.org>`_)
   and for Microsoft Windows (via `Appveyor <http://www.appveyor.com>`_).
   Aggregation/cloud code coverage is configured via
   `Codecov <https://codecov.io>`_. It is assumed that the Codecov repository
   upload token in the Travis build is stored in the :bash:`${CODECOV_TOKEN}`
   environment variable (securely defined in the Travis repository settings
   page). Travis build artifacts can be transferred to Dropbox using the
   `Dropbox Uploader <https://github.com/andreafabrizi/Dropbox-Uploader>`_
   script (included for convenience in the :bash:`${PPLOT_DIR}/sbin` directory).
   For an automatic transfer that does not require manual entering of
   authentication credentials place the APPKEY, APPSECRET, ACCESS_LEVEL,
   OAUTH_ACCESS_TOKEN and OAUTH_ACCESS_TOKEN_SECRET values required by
   Dropbox Uploader in the in the :bash:`${DBU_APPKEY}`,
   :bash:`${DBU_APPSECRET}`, :bash:`${DBU_ACCESS_LEVEL}`,
   :bash:`${DBU_OAUTH_ACCESS_TOKEN}` and
   :bash:`${DBU_OAUTH_ACCESS_TOKEN_SECRET}` environment variables,
   respectively (also securely defined in Travis repository settings page)


9. Document the new feature or bug fix (if needed). The script
   :bash:`${PPLOT_DIR}/sbin/build_docs.py` re-builds the whole package
   documentation (re-generates images, cogs source files, etc.):

	.. [[[cog pmisc.ste('build_docs.py -h', 0, mdir, cog.out) ]]]

	.. code-block:: bash

	    $ ${PKG_BIN_DIR}/build_docs.py -h
	    usage: build_docs.py [-h] [-d DIRECTORY] [-r]
	                         [-n NUM_CPUS] [-t]

	    Build pplot package documentation

	    optional arguments:
	      -h, --help            show this help message and exit
	      -d DIRECTORY, --directory DIRECTORY
	                            specify source file directory
	                            (default ../pplot)
	      -r, --rebuild         rebuild exceptions documentation.
	                            If no module name is given all
	                            modules with auto-generated
	                            exceptions documentation are
	                            rebuilt
	      -n NUM_CPUS, --num-cpus NUM_CPUS
	                            number of CPUs to use (default: 1)
	      -t, --test            diff original and rebuilt file(s)
	                            (exit code 0 indicates file(s) are
	                            identical, exit code 1 indicates
	                            file(s) are different)


	.. [[[end]]]

.. rubric:: Footnotes

.. [#f1] All examples are for the `bash <https://www.gnu.org/software/bash/>`_
   shell

.. [#f2] It appears that Scipy dependencies do not include Numpy (as they
   should) so running the tests via Setuptools will typically result in an
   error. The pplot requirement file specifies Numpy before Scipy and this
   installation order is honored by Tox so running the tests via Tox sidesteps
   Scipy's broken dependency problem but requires Tox to be installed before
   running the tests (Setuptools installs Tox if needed)

.. [#f3] It is assumed that all the Python interpreters are in the executables
   path. Source code for the interpreters can be downloaded from Python's main
   `site <http://www.python.org/downloads>`_

.. [#f4] Tox configuration largely inspired by
   `Ionel's codelog <http://blog.ionelmc.ro/2015/04/14/
   tox-tricks-and-patterns/>`_


License
=======

The MIT License (MIT)

Copyright (c) 2013-2018 Pablo Acosta-Serafini

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
.. CHANGELOG.rst
.. Copyright (c) 2013-2018 Pablo Acosta-Serafini
.. See LICENSE for details

Changelog
=========

* 1.1.2 [2018-01-16]: Hosted documentation build fixes

* 1.1.1 [2018-01-16]: Corrected PyPI Python interpreter version

* 1.1.0 [2018-01-16]: Added support for specifying independent axis tick labels
  (ignored for figures with logarithmic independent axis). Improved minimum
  image size computation.  Removed all padding around the exterior of the image.
  Dropped support for Python interpreter versions 2.6, 3.3 and 3.4. Updated
  dependencies versions to their current versions

* 1.0.4 [2017-02-25]: Fixed tick marks labels in the [0, 1] range. Closed image
  tests escapes

* 1.0.3 [2017-02-16]: Python 3.6 support

* 1.0.2 [2016-05-16]: PyPI front page fixes

* 1.0.1 [2016-05-16]: Documentation build fixes to display README information
  correctly in repositories and PyPI

* 1.0.0 [2016-05-16]: Final release of 1.0.0 branch

* 1.0.0rc1 [2016-05-12]: Initial commit, forked a subset from putil PyPI
  package