peng 1.0.6

This package provides engineering-related classes and functions

Description

This package provides engineering-related classes and functions, including:

• A waveform class that is a first-class object. For example:

  >>> import copy, numpy, peng
  >>> obj_a=peng.Waveform(
  ...     indep_vector=numpy.array([1, 2, 3]),
  ...     dep_vector=numpy.array([10, 20, 30]),
  ...     dep_name='obj_a'
  ... )
  >>> obj_b = obj_a*2
  >>> print(obj_b)
  Waveform: obj_a*2
  Independent variable: [ 1, 2, 3 ]
  Dependent variable: [ 20, 40, 60 ]
  Independent variable scale: LINEAR
  Dependent variable scale: LINEAR
  Independent variable units: (None)
  Dependent variable units: (None)
  Interpolating function: CONTINUOUS
  >>> obj_c = copy.copy(obj_b)
  >>> obj_a == obj_b
  False
  >>> obj_b == obj_c
  True

  Numerous functions are provided (trigonometric, calculus, transforms, etc.) and creating new functions that operate on waveforms is simple since all of their relevant information can be accessed through properties

• Handling numbers represented in engineering notation, obtaining their constituent components and converting to and from regular floats. For example:

  >>> import peng
  >>> x = peng.peng(1346, 2, True)
  >>> x
  '   1.35k'
  >>> peng.peng_float(x)
  1350.0
  >>> peng.peng_int(x)
  1
  >>> peng.peng_frac(x)
  35
  >>> str(peng.peng_mant(x))
  '1.35'
  >>> peng.peng_power(x)
  EngPower(suffix='k', exp=1000.0)
  >>> peng.peng_suffix(x)
  'k'

• Pretty printing Numpy vectors. For example:

  >>> from __future__ import print_function
  >>> import peng
  >>> header = 'Vector: '
  >>> data = [1e-3, 20e-6, 30e+6, 4e-12, 5.25e3, -6e-9, 70, 8, 9]
  >>> print(
  ...     header+peng.pprint_vector(
  ...         data,
  ...         width=30,
  ...         eng=True,
  ...         frac_length=1,
  ...         limit=True,
  ...         indent=len(header)
  ...     )
  ... )
  Vector: [    1.0m,   20.0u,   30.0M,
                       ...
              70.0 ,    8.0 ,    9.0  ]

• Formatting numbers represented in scientific notation with a greater degree of control and options than standard Python string formatting. For example:

  >>> import peng
  >>> peng.to_scientific_string(
  ...     number=99.999,
  ...     frac_length=1,
  ...     exp_length=2,
  ...     sign_always=True
  ... )
  '+1.0E+02'

Interpreter

The package has been developed and tested with Python 2.6, 2.7, 3.3, 3.4 and 3.5 under Linux (Debian, Ubuntu), Apple OS X and Microsoft Windows

Installing

$ pip install peng

Documentation

Available at Read the Docs

Contributing

1. Abide by the adopted code of conduct

2. Fork the repository from GitHub and then clone personal copy [1]:

   $ git clone \
         https://github.com/[github-user-name]/peng.git
   Cloning into 'peng'...
   ...
   $ cd peng
   $ export PENG_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 compliance via Pylint. Assuming the directory to which the repository was cloned is in the $PENG_DIR shell environment variable:

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

4. Ensure that the Python interpreter can find the package modules (update the $PYTHONPATH environment variable, or use sys.paths(), etc.)

   $ export PYTHONPATH=${PYTHONPATH}:${PENG_DIR}

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

   • Astroid (Python 2.6: older than 1.4, Python 2.7 or newer: 1.3.8 or newer)

   • Cog (2.4 or newer)

   • Coverage (3.7.1 or newer)

   • Decorator (3.4.2 or newer)

   • Docutils (Python 2.6: 0.12 or newer and older than 0.13, Python 2.7: 0.12 or newer, Python 3.3: 0.12 or newer and older than 0.13, Python 3.4: 0.12 or newer, Python 3.5: 0.12 or newer, Python 3.6: 0.12 or newer)

   • Funcsigs (Python 2.x only, 0.4 or newer)

   • Inline Syntax Highlight Sphinx Extension (0.2 or newer)

   • Mock (Python 2.x only, 1.0.1 or newer)

   • Nose (Python 2.6: 1.0.0 or newer)

   • Numpy (Python 2.6: 1.8.2 or newer and older than 1.12, Python 2.7: 1.8.2 or newer, Python 3.3: 1.8.2 or newer and older than 1.12, Python 3.4: 1.8.2 or newer, Python 3.5: 1.8.2 or newer, Python 3.6: 1.8.2 or newer)

   • Pexdoc (1.0.9 or newer)

   • Pmisc (1.2.2 or newer)

   • Py.test (2.7.0 or newer)

   • PyParsing (2.0.7 or newer)

   • Pylint (Python 2.6: 1.3 or newer and older than 1.4, Python 2.7 or newer: 1.3.1 or newer)

   • Pytest-coverage (1.8.0 or newer except 2.3.0)

   • Pytest-xdist (optional, 1.8.0 or newer)

   • ReadTheDocs Sphinx theme (0.1.9 or newer)

   • Scipy (Python 2.6: 0.13.3 or newer and older than 0.18, Python 2.7: 0.13.3 or newer, Python 3.3: 0.13.3 or newer and older than 0.18, Python 3.4: 0.13.3 or newer, Python 3.5: 0.13.3 or newer, Python 3.6: 0.13.3 or newer)

   • Six (1.4.0 or newer)

   • Sphinx (Python 2.6: 1.2.3 or newer and 1.4.9 or older, Python 2.7: 1.5 or newer, Python 3.3: 1.2.3 or newer and 1.4.9 or older, Python 3.4: 1.5 or newer, Python 3.5: 1.5 or newer, Python 3.6: 1.5 or newer)

   • Tox (1.9.0 or newer)

   • Virtualenv (13.1.2 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 Py.test:

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

   Setuptools can also be used (Tox is configured as its virtual environment manager) [2]:

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

   Tox (or Setuptools via Tox) runs with the following default environments: py26-pkg, py27-pkg, py33-pkg, py34-pkg and py35-pkg [3]. These use the Python 2.6, 2.7, 3.3, 3.4 and 3.5 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:

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

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

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

   There are other convenience environments defined for Tox [4]:

   • py26-repl, py27-repl, py33-repl, py34-repl and py35-repl run the Python 2.6, 2.7, 3.3, 3.4 or 3.5 REPL, respectively, in the appropriate virtual environment. The peng 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 (--)

   • py26-test, py27-test, py33-test, py34-test and py35-test run py.test using the Python 2.6, 2.7, 3.3, 3.4 or Python 3.5 interpreter, respectively, in the appropriate virtual environment. Arguments to py.test can be passed in the command line after a double dash (--) , for example:

     $ tox -e py34-test -- -x test_eng.py
     GLOB sdist-make: [...]/peng/setup.py
     py34-test inst-nodeps: [...]/peng/.tox/dist/peng-[...].zip
     py34-test runtests: PYTHONHASHSEED='680528711'
     py34-test runtests: commands[0] | [...]py.test -x test_eng.py
     ==================== test session starts ====================
     platform linux -- Python 3.4.2 -- py-1.4.30 -- [...]
     ...

   • py26-cov, py27-cov, py33-cov, py34-cov and py35-cov test code and branch coverage using the Python 2.6, 2.7, 3.3, 3.4 or 3.5 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 ${PENG_DIR}/.tox/py[PV]/usr/share/peng/tests/htmlcov/index.html where [PV] stands for 26, 27, 33, 34 or 35 depending on the interpreter used

8. Verify that continuous integration tests pass. The package has continuous integration configured for Linux (via Travis) and for Microsoft Windows (via Appveyor). Aggregation/cloud code coverage is configured via Codecov. It is assumed that the Codecov repository upload token in the Travis build is stored in the ${CODECOV_TOKEN} environment variable (securely defined in the Travis repository settings page). Travis build artifacts can be transferred to Dropbox using the Dropbox Uploader script (included for convenience in the ${PENG_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 ${DBU_APPKEY}, ${DBU_APPSECRET}, ${DBU_ACCESS_LEVEL}, ${DBU_OAUTH_ACCESS_TOKEN} and ${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 ${PENG_DIR}/sbin/build_docs.py re-builds the whole package documentation (re-generates images, cogs source files, etc.):

   $ ${PUTIL_DIR}/sbin/build_docs.py -h
   usage: build_docs.py [-h] [-d DIRECTORY] [-r]
                        [-n NUM_CPUS] [-t]
   
   Build peng package documentation
   
   optional arguments:
     -h, --help            show this help message and exit
     -d DIRECTORY, --directory DIRECTORY
                           specify source file directory
                           (default ../peng)
     -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)

   Output of shell commands can be automatically included in reStructuredText source files with the help of Cog and the docs.support.term_echo module.

   Similarly Python files can be included in docstrings with the help of Cog and the docs.support.incfile module

Footnotes

[1]

All examples are for the bash shell

[2]

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 peng 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)

[3]

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

[4]

Tox configuration largely inspired by Ionel’s codelog

License

The MIT License (MIT)

Copyright (c) 2013-2017 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) 2013-2017 Pablo Acosta-Serafini .. See LICENSE for details

Changelog

• 1.0.6 [2016-02-11]: Package build enhancements and fixes

• 1.0.5 [2016-02-09]: Python 3.6 support

• 1.0.4 [2016-09-19]: Fixed Touchstone read function for “MA” and “DB” formats where the angles were incorrectly treated as being in radians

• 1.0.3 [2016-07-29]: Fixed resolution loss when writing Touchstone files

• 1.0.2 [2016-07-25]:

  • Frequency vector is now always in Hertz regardless of unit used in Touchstone file

  • Minor documentation bug fixes

• 1.0.1 [2016-06-11]: Minor documentation build bug fix

• 1.0.0 [2016-05-12]: Final release of 1.0.0 branch

• 1.0.0rc1 [2016-05-11]: Initial commit, forked a subset from putil PyPI package