Metadata-Version: 1.1
Name: pplot
Version: 1.1.4
Summary: UNKNOWN
Home-page: http://github.com/pmacosta/pplot/
Author: Pablo Acosta-Serafini
Author-email: pmasdev@gmail.com
License: MIT
Description: .. README.rst
        .. Copyright (c) 2013-2019 Pablo Acosta-Serafini
        .. See LICENSE for details
        
        .. image:: https://badge.fury.io/py/pplot.svg
            :target: https://pypi.org/project/pplot
            :alt: PyPI version
        
        .. image:: https://img.shields.io/pypi/l/pplot.svg
            :target: https://pypi.org/project/pplot
            :alt: License
        
        .. image:: https://img.shields.io/pypi/pyversions/pplot.svg
            :target: https://pypi.org/project/pplot
            :alt: Python versions supported
        
        .. image:: https://img.shields.io/pypi/format/pplot.svg
            :target: https://pypi.org/project/pplot
            :alt: Format
        
        |
        
        .. image::
            https://dev.azure.com/pmasdev/pplot/_apis/build/status/pmacosta.pplot?branchName=master
            :target: https://dev.azure.com/pmasdev/pplot/_build?definitionId=8&_a=summary
            :alt: Continuous integration test status
        
        .. image::
            https://img.shields.io/azure-devops/coverage/pmasdev/pplot/8.svg
            :target: https://dev.azure.com/pmasdev/pplot/_build?definitionId=8&_a=summary
            :alt: Continuous integration test coverage
        
        .. image::
            https://readthedocs.org/projects/pip/badge/?version=stable
            :target: https://pip.readthedocs.io/en/stable/?badge=stable
            :alt: Documentation status
        
        |
        
        Description
        ===========
        
        .. role:: bash(code)
        	:language: bash
        
        .. _Cog: https://nedbatchelder.com/code/cog
        .. _Coverage: https://coverage.readthedocs.io
        .. _Decorator: https://raw.githubusercontent.com/micheles/decorator/mast
           er/docs/documentation.md
        .. _Docutils: http://docutils.sourceforge.net/docs
        .. _Funcsigs: https://pypi.org/project/funcsigs
        .. _Imageio: http://imageio.github.io
        .. _Matplotlib: https://matplotlib.org
        .. _Mock: https://docs.python.org/3/library/unittest.mock.html
        .. _Numpy: http://www.numpy.org
        .. _Pcsv: https://pcsv.readthedocs.org
        .. _Peng: https://peng.readthedocs.org
        .. _Pexdoc: https://pexdoc.readthedocs.org
        .. _Pillow: https://python-pillow.org
        .. _Pmisc: http://pmisc.readthedocs.org
        .. _PyContracts: https://andreacensi.github.io/contracts
        .. _Pydocstyle: http://www.pydocstyle.org
        .. _Pylint: https://www.pylint.org
        .. _Py.test: http://pytest.org
        .. _Pytest-coverage: https://pypi.org/project/pytest-cov
        .. _Pytest-pmisc: https://pytest-pmisc.readthedocs.org
        .. _Pytest-xdist: https://pypi.org/project/pytest-xdist
        .. _Scipy: https://www.scipy.org
        .. _Six: https://pythonhosted.org/six
        .. _Sphinx: http://sphinx-doc.org
        .. _ReadTheDocs Sphinx theme: https://github.com/rtfd/sphinx_rtd_theme
        .. _Inline Syntax Highlight Sphinx Extension:
           https://bitbucket.org/klorenz/sphinxcontrib-inlinesyntaxhighlight
        .. _Shellcheck Linter Sphinx Extension:
           https://pypi.org/project/sphinxcontrib-shellcheck
        .. _Tox: https://testrun.org/tox
        .. _Virtualenv: https://docs.python-guide.org/dev/virtualenvs
        
        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
        *******
        
        .. code-block:: python
        
            # plot_example_1.py
            from __future__ import print_function
            import os, sys, numpy, pplot
        
            def main(fname, no_print):
                """Show how to use 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
        
        |
        
        Interpreter
        ===========
        
        The package has been developed and tested with Python 2.7, 3.5, 3.6 and 3.7
        under Linux (Debian, Ubuntu), Apple macOS and Microsoft Windows
        
        Installing
        ==========
        
        .. code-block:: console
        
        	$ pip install pplot
        
        Documentation
        =============
        
        Available at `Read the Docs <https://pplot.readthedocs.io>`_
        
        Contributing
        ============
        
        1. Abide by the adopted `code of conduct
           <https://www.contributor-covenant.org/version/1/4/code-of-conduct>`_
        
        2. Fork the `repository <https://github.com/pmacosta/pplot>`_ from GitHub and
           then clone personal copy [#f1]_:
        
            .. code-block:: console
        
                $ github_user=myname
                $ git clone --recurse-submodules \
                      https://github.com/"${github_user}"/pplot.git
                Cloning into 'pplot'...
                ...
                $ cd pplot || exit 1
                $ export PPLOT_DIR=${PWD}
                $
        
        3. The package uses two sub-modules: a set of custom Pylint plugins to help with
           some areas of code quality and consistency (under the ``pylint_plugins``
           directory), and a lightweight package management framework (under the
           ``pypkg`` directory). Additionally, the `pre-commit framework
           <https://pre-commit.com/>`_ is used to perform various pre-commit code
           quality and consistency checks. To enable the pre-commit hooks:
        
            .. code-block:: console
        
                $ cd "${PPLOT_DIR}" || exit 1
                $ pre-commit install
                pre-commit installed at .../pplot/.git/hooks/pre-commit
                $
        
        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/3/library/sys.html#sys.path>`_,
           etc.)
        
           .. code-block:: console
        
               $ export PYTHONPATH=${PYTHONPATH}:${PPLOT_DIR}
               $
        
        5. Install the dependencies (if needed, done automatically by pip):
        
            * `Cog`_ (2.5.1 or newer)
        
            * `Coverage`_ (4.5.3 or newer)
        
            * `Decorator`_ (4.4.0 or newer)
        
            * `Docutils`_ (0.14 or newer)
        
            * `Funcsigs`_ (Python 2.x only, 1.0.2 or newer)
        
            * `Imageio`_ (2.5.0 or newer)
        
            * `Inline Syntax Highlight Sphinx Extension`_ (0.2 or newer)
        
            * `Matplotlib`_ (Python 2.x: 2.2.4 or newer, Python 3.x: 3.0.3 or
              newer)
        
            * `Mock`_ (Python 2.x only, 2.0.0 or newer)
        
            * `Numpy`_ (1.16.2 or newer)
        
            * `Pcsv`_ (1.0.8 or newer)
        
            * `Peng`_ (1.0.9 or newer)
        
            * `Pexdoc`_ (1.1.4 or newer)
        
            * `Pillow`_ (5.4.1 or newer)
        
            * `Pmisc`_ (1.5.8 or newer)
        
            * `Py.test`_ (4.3.1 or newer)
        
            * `PyContracts`_ (1.8.2 or newer)
        
            * `Pydocstyle`_ (3.0.0 or newer)
        
            * `Pylint`_ (Python 2.x: 1.9.4 or newer, Python 3.x: 2.3.1 or newer)
        
            * `Pytest-coverage`_ (2.6.1 or newer)
        
            * `Pytest-pmisc`_ (1.0.7 or newer)
        
            * `Pytest-xdist`_ (optional, 1.26.1 or newer)
        
            * `ReadTheDocs Sphinx theme`_ (0.4.3 or newer)
        
            * `Scipy`_ (1.2.1 or newer)
        
            * `Shellcheck Linter Sphinx Extension`_ (1.0.8 or newer)
        
            * `Six`_ (1.12.0 or newer)
        
            * `Sphinx`_ (1.8.5 or newer)
        
            * `Tox`_ (3.7.0 or newer)
        
            * `Virtualenv`_ (16.4.3 or newer)
        
        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 Pytest:
        
           .. code-block:: console
        
               $ PKG_NAME=pplot tox
               GLOB sdist-make: .../pplot/setup.py
               py27-pkg create: .../pplot/.tox/py27
               py27-pkg installdeps: -r.../pplot/requirements/tests_py27.pip, -r.../pplot/requirements/docs_py27.pip
               ...
                 py27-pkg: commands succeeded
                 py35-pkg: commands succeeded
                 py36-pkg: commands succeeded
                 py37-pkg: commands succeeded
                 congratulations :)
               $
        
           `Setuptools <https://bitbucket.org/pypa/setuptools>`_ can also be used
           (Tox is configured as its virtual environment manager):
        
           .. code-block:: console
        
               $ PKG_NAME=pplot python setup.py tests
               running tests
               running egg_info
               writing pplot.egg-info/PKG-INFO
               writing dependency_links to pplot.egg-info/dependency_links.txt
               writing requirements to pplot.egg-info/requires.txt
               ...
                 py27-pkg: commands succeeded
                 py35-pkg: commands succeeded
                 py36-pkg: commands succeeded
                 py37-pkg: commands succeeded
                 congratulations :)
               $
        
           Tox (or Setuptools via Tox) runs with the following default environments:
           ``py27-pkg``, ``py35-pkg``, ``py36-pkg`` and ``py37-pkg`` [#f3]_. These use
           the 2.7, 3.5, 3.6 and 3.7 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 Pytest (the test runner) use
           a double dash (``--``) after all the Tox arguments, for example:
        
           .. code-block:: console
        
               $ PKG_NAME=pplot tox -e py27-pkg -- -n 4
               GLOB sdist-make: .../pplot/setup.py
               py27-pkg inst-nodeps: .../pplot/.tox/.tmp/package/1/pplot-1.1.4.zip
               ...
                 py27-pkg: commands succeeded
                 congratulations :)
               $
        
           Or use the :code:`-a` Setuptools optional argument followed by a quoted
           string with the arguments for Pytest. For example:
        
           .. code-block:: console
        
               $ PKG_NAME=pplot python setup.py tests -a "-e py27-pkg -- -n 4"
               running tests
               ...
                 py27-pkg: commands succeeded
                 congratulations :)
               $
        
           There are other convenience environments defined for Tox [#f3]_:
        
            * ``py27-repl``, ``py35-repl``, ``py36-repl`` and ``py37-repl`` run the
              Python 2.7, 3.5, 3.6 and 3.7 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``, ``py36-test`` and ``py37-test`` run Pytest
              using the Python 2.7, 3.5, 3.6 and 3.7 interpreter, respectively, in the
              appropriate virtual environment. Arguments to pytest can be passed in
              the command line after a double dash (``--``) , for example:
        
              .. code-block:: console
        
               $ PKG_NAME=pplot tox -e py27-test -- -x test_pplot.py
               GLOB sdist-make: .../pplot/setup.py
               py27-pkg inst-nodeps: .../pplot/.tox/.tmp/package/1/pplot-1.1.4.zip
               ...
                 py27-pkg: commands succeeded
                 congratulations :)
               $
            * ``py27-test``, ``py35-test``, ``py36-test`` and ``py37-test`` test code
              and branch coverage using the 2.7, 3.5, 3.6 and 3.7 interpreter,
              respectively, in the appropriate virtual environment. Arguments to
              pytest 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/ppl
              ot/tests/htmlcov/index.html` where ``[PV]`` stands for ``2.7``, ``3.5``,
              ``3.6`` or ``3.7`` depending on the interpreter used.
        
        8. Verify that continuous integration tests pass. The package has continuous
           integration configured for Linux, Apple macOS and Microsoft Windows (all via
           `Azure DevOps <https://dev.azure.com/pmasdev>`_).
        
        9. Document the new feature or bug fix (if needed). The script
           :bash:`${PPLOT_DIR}/pypkg/build_docs.py` re-builds the whole package
           documentation (re-generates images, cogs source files, etc.):
        
           .. code-block:: console
        
               $ "${PPLOT_DIR}"/pypkg/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)
        
        .. rubric:: Footnotes
        
        .. [#f1] All examples are for the `bash <https://www.gnu.org/software/bash/>`_
           shell
        
        .. [#f2] 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 <https://www.python.org/downloads/>`_
        
        .. [#f3] Tox configuration largely inspired by
           `Ionel's codelog <https://blog.ionelmc.ro/2015/04/14/
           tox-tricks-and-patterns/>`_
        
        License
        =======
        
        The MIT License (MIT)
        
        Copyright (c) 2013-2019 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) 2013-2019 Pablo Acosta-Serafini
        .. See LICENSE for details
        
        Changelog
        =========
        
        * 1.1.4 [2019-03-22]: Documentation and dependencies update
        
        * 1.1.3 [2019-03-16]: Adopted lightweight package management framework
        
        * 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
        
Platform: any
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Development Status :: 5 - Production/Stable
Classifier: Natural Language :: English
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries :: Python Modules
