Package: pplot
DescriptionThis module can be used to create high-quality, presentation-ready X-Y graphs
quickly and easilyClass hierarchyThe 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:__str__,_set_indep_varand_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 marksAxes 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# plot_example_1.pyfrom__future__importprint_functionimportos,sys,numpy,pplotdefmain(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 classwdir=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 classseries2_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=2.25fig_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 figureoutput_fname=os.path.join(wdir,fname)ifnotno_print:print("Saving image to file{0}".format(output_fname))fig_obj.save(output_fname,compress=True)defseries1_proc_func(indep_var,dep_var,xoffset):"""Process data 1 series."""return(indep_var*1e-3)-xoffset,dep_varInterpreterThe 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 WindowsInstalling$pipinstallpplotDocumentationAvailable atRead the DocsContributingAbide by the adoptedcode of conductFork therepositoryfrom GitHub and
then clone personal copy[1]:$github_user=myname$gitclone--recurse-submodules\https://github.com/"${github_user}"/pplot.gitCloning into 'pplot'...
...$cdpplot||exit1$exportPPLOT_DIR=${PWD}$The package uses two sub-modules: a set of custom Pylint plugins to help with
some areas of code quality and consistency (under thepylint_pluginsdirectory), and a lightweight package management framework (under thepypkgdirectory). Additionally, thepre-commit frameworkis used to perform various pre-commit code
quality and consistency checks. To enable the pre-commit hooks:$cd"${PPLOT_DIR}"||exit1$pre-commitinstallpre-commit installed at .../pplot/.git/hooks/pre-commit$Ensure that the Python interpreter can find the package modules
(update the$PYTHONPATHenvironment variable, or usesys.paths(),
etc.)$exportPYTHONPATH=${PYTHONPATH}:${PPLOT_DIR}$Install the dependencies (if needed, done automatically by pip):Cog(2.5.1 or newer)Coverage(4.5.3 or newer)Decorator(4.4.0 or newer)Docutils(0.14 or newer)Funcsigs(Python 2.x only, 1.0.2 or newer)Imageio(2.5.0 or newer)Inline Syntax Highlight Sphinx Extension(0.2 or newer)Matplotlib(Python 2.x: 2.2.4 or newer, Python 3.x: 3.0.3 or
newer)Mock(Python 2.x only, 2.0.0 or newer)Numpy(1.16.2 or newer)Pcsv(1.0.8 or newer)Peng(1.0.9 or newer)Pexdoc(1.1.4 or newer)Pillow(5.4.1 or newer)Pmisc(1.5.8 or newer)Py.test(4.3.1 or newer)PyContracts(1.8.2 or newer)Pydocstyle(3.0.0 or newer)Pylint(Python 2.x: 1.9.4 or newer, Python 3.x: 2.3.1 or newer)Pytest-coverage(2.6.1 or newer)Pytest-pmisc(1.0.7 or newer)Pytest-xdist(optional, 1.26.1 or newer)ReadTheDocs Sphinx theme(0.4.3 or newer)Scipy(1.2.1 or newer)Shellcheck Linter Sphinx Extension(1.0.8 or newer)Six(1.12.0 or newer)Sphinx(1.8.5 or newer)Tox(3.7.0 or newer)Virtualenv(16.4.3 or newer)Implement a new feature or fix a bugWrite a unit test which shows that the contributed code works as expected.
Run the package tests to ensure that the bug fix or new feature does not
have adverse side effects. If possible achieve 100% code and branch
coverage of the contribution. Thorough package validation
can be done via Tox and Pytest:$PKG_NAME=pplottoxGLOB 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 :)$Setuptoolscan also be used
(Tox is configured as its virtual environment manager):$PKG_NAME=pplotpythonsetup.pytestsrunning 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 :)$Tox (or Setuptools via Tox) runs with the following default environments:py27-pkg,py35-pkg,py36-pkgandpy37-pkg[3]. These use
the 2.7, 3.5, 3.6 and 3.7 interpreters, respectively, to test all code in
the documentation (both in Sphinx*.rstsource files and in
docstrings), run all unit tests, measure test coverage and re-build the
exceptions documentation. To pass arguments to Pytest (the test runner) use
a double dash (--) after all the Tox arguments, for example:$PKG_NAME=pplottox-epy27-pkg---n4GLOB sdist-make: .../pplot/setup.py
py27-pkg inst-nodeps: .../pplot/.tox/.tmp/package/1/pplot-1.1.4.zip
...
  py27-pkg: commands succeeded
  congratulations :)$Or use the-aSetuptools optional argument followed by a quoted
string with the arguments for Pytest. For example:$PKG_NAME=pplotpythonsetup.pytests-a"-e py27-pkg -- -n 4"running tests
...
  py27-pkg: commands succeeded
  congratulations :)$There are other convenience environments defined for Tox[3]:py27-repl,py35-repl,py36-replandpy37-replrun the
Python 2.7, 3.5, 3.6 and 3.7 REPL, respectively, in the appropriate
virtual environment. Thepplotpackage is pip-installed by Tox when
the environments are created.  Arguments to the interpreter can be
passed in the command line after a double dash (--).py27-test,py35-test,py36-testandpy37-testrun Pytest
using the Python 2.7, 3.5, 3.6 and 3.7 interpreter, respectively, in the
appropriate virtual environment. Arguments to pytest can be passed in
the command line after a double dash (--) , for example:$PKG_NAME=pplottox-epy27-test---xtest_pplot.pyGLOB sdist-make: .../pplot/setup.py
py27-pkg inst-nodeps: .../pplot/.tox/.tmp/package/1/pplot-1.1.4.zip
...
  py27-pkg: commands succeeded
  congratulations :)$py27-test,py35-test,py36-testandpy37-testtest code
and branch coverage using the 2.7, 3.5, 3.6 and 3.7 interpreter,
respectively, in the appropriate virtual environment. Arguments to
pytest can be passed in the command line after a double dash (--).
The report can be found in${PPLOT_DIR}/.tox/py[PV]/usr/share/pplot/tests/htmlcov/index.htmlwhere[PV]stands for2.7,3.5,3.6or3.7depending on the interpreter used.Verify that continuous integration tests pass. The package has continuous
integration configured for Linux, Apple macOS and Microsoft Windows (all viaAzure DevOps).Document the new feature or bug fix (if needed). The script${PPLOT_DIR}/pypkg/build_docs.pyre-builds the whole package
documentation (re-generates images, cogs source files, etc.):$"${PPLOT_DIR}"/pypkg/build_docs.py-husage: 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)Footnotes[1]All examples are for thebashshell[2]It is assumed that all the Python interpreters are in the executables
path. Source code for the interpreters can be downloaded from Python’s mainsite[3](1,2)Tox configuration largely inspired byIonel’s codelogLicenseThe MIT License (MIT)Copyright (c) 2013-2019 Pablo Acosta-SerafiniPermission 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 detailsChangelog1.1.4 [2019-03-22]: Documentation and dependencies update1.1.3 [2019-03-16]: Adopted lightweight package management framework1.1.2 [2018-01-16]: Hosted documentation build fixes1.1.1 [2018-01-16]: Corrected PyPI Python interpreter version1.1.0 [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 versions1.0.4 [2017-02-25]: Fixed tick marks labels in the [0, 1] range. Closed image
tests escapes1.0.3 [2017-02-16]: Python 3.6 support1.0.2 [2016-05-16]: PyPI front page fixes1.0.1 [2016-05-16]: Documentation build fixes to display README information
correctly in repositories and PyPI1.0.0 [2016-05-16]: Final release of 1.0.0 branch1.0.0rc1 [2016-05-12]: Initial commit, forked a subset from putil PyPI
package