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

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¶

Abide by the adopted code of conduct

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}

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 ...
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}
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 (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 (1.8.2 or newer)
- Pexdoc (1.0.0 or newer)
- Pmisc (1.0.0 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)
- Pytest-xdist (optional, 1.8.0 or newer)
- ReadTheDocs Sphinx theme (0.1.9 or newer)
- Scipy (0.13.3 or newer)
- Six (1.4.0 or newer)
- Sphinx (1.2.3 or newer)
- Tox (1.9.0 or newer)
- Virtualenv (13.1.2 or newer)
Implement a new feature or fix a bug
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
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)

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.
docs.support.term_echo.ste(command, nindent, mdir, fpointer)
Simplified terminal echo; prints STDOUT resulting from a given Bash shell command (relative to the package sbin directory) formatted in reStructuredText

Parameters:

command (string) – Bash shell command, relative to ${PUTIL_DIR}/sbin

nindent (integer) – Indentation level

mdir (string) – Module directory

fpointer (function object) – Output function pointer. Normally is cog.out but print or other functions can be used for debugging

For example:
.. This is a reStructuredText file snippet
.. [[[cog
.. import os, sys
.. from docs.support.term_echo import term_echo
.. file_name = sys.modules['docs.support.term_echo'].__file__
.. mdir = os.path.realpath(
..     os.path.dirname(
..         os.path.dirname(os.path.dirname(file_name))
..     )
.. )
.. [[[cog ste('build_docs.py -h', 0, mdir, cog.out) ]]]

.. code-block:: bash

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

.. ]]]
docs.support.term_echo.term_echo(command, nindent=0, env=None, fpointer=None, cols=60)

Terminal echo; prints STDOUT resulting from a given Bash shell command formatted in reStructuredText

Parameters:

command (string) – Bash shell command

nindent (integer) – Indentation level

env (dictionary) – Environment variable replacement dictionary. The Bash command is pre-processed and any environment variable represented in the full notation (${...}) is replaced. The dictionary key is the environment variable name and the dictionary value is the replacement value. For example, if command is '${PYTHON_CMD} -m "x=5"' and env is {'PYTHON_CMD':'python3'} the actual command issued is 'python3 -m "x=5"'

fpointer (function object) – Output function pointer. Normally is cog.out but print or other functions can be used for debugging

cols (integer) – Number of columns of output

Similarly Python files can be included in docstrings with the help of Cog and the docs.support.incfile module
docs.support.incfile.incfile(fname, fpointer, lrange='1, 6-', sdir=None)
Includes a Python source file in a docstring formatted in reStructuredText

Parameters:

fname (string) – File name, relative to environment variable ${TRACER_DIR}

fpointer (function object) – Output function pointer. Normally is cog.out but print or other functions can be used for debugging

lrange (string) – Line range to include, similar to Sphinx literalinclude directive

sdir (string) – Source file directory. If None the ${TRACER_DIR} environment variable is used if it is defined, otherwise the directory where the docs.support.incfile module is located is used

For example:
def func():
    """
    This is a docstring. This file shows how to use it:

    .. =[=cog
    .. import docs.support.incfile
    .. docs.support.incfile.incfile('func_example.py', cog.out)
    .. =]=
    .. code-block:: python

        # func_example.py
        if __name__ == '__main__':
            func()

    .. =[=end=]=
    """
    return 'This is func output'

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

Changelog¶

0.9.11 [2016-04-15]:
- Created new APIs in the exh module to simplify adding and conditionally raising exceptions that can be auto-documented with the exdoc module
- Homogenized API arguments in several pcsv module functions
- Bug fixes
- Documentation updates
0.9.10 [2016-03-10]: Final release of 0.9.10 branch
0.9.10rc1 [2016-03-09]: Apple OS X compatibility changes. Reduced memory consumption during exception auto-documentation process. Bug fixes
0.9.9 [2016-01-27]: Fixed documentation bugs that were causing errors with Sphinx 1.3.5+
0.9.8 [2016-01-22]: Bug fixes
0.9.7 [2016-01-22]: Enhanced control of exceptions automatic documentation output
0.9.6 [2016-01-20]: Bug fixes
0.9.5 [2016-01-08]: Bug fixes
0.9.4 [2015-12-18]: Minor documentation update regarding continuous integration setup
0.9.3 [2015-12-17]: Fixed critical bug in plot module that prevented figures without any axis labels from being generated
0.9.2 [2015-12-15]: Speed improvements in plot module
0.9.1 [2015-12-01]: Final release of 0.9.1 branch
0.9.1rc5 [2015-12-01]: Fixed documentation URL in top-level README.rst
0.9.1rc4 [2015-12-01]: Fixed bug in top-level README.rst verification
0.9.1rc3 [2015-12-01]:
- Documentation updates
- Package verification improvements
0.9.1rc2 [2015-12-01]: Fixed top-level README.rst file
0.9.1rc1 [2015-11-30]: Initial public release

License¶

The MIT License (MIT)

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.

Contents¶

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¶

Abide by the adopted code of conduct

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}

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 ...
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}
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 (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 (1.8.2 or newer)
- Pexdoc (1.0.0 or newer)
- Pmisc (1.0.0 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)
- Pytest-xdist (optional, 1.8.0 or newer)
- ReadTheDocs Sphinx theme (0.1.9 or newer)
- Scipy (0.13.3 or newer)
- Six (1.4.0 or newer)
- Sphinx (1.2.3 or newer)
- Tox (1.9.0 or newer)
- Virtualenv (13.1.2 or newer)
Implement a new feature or fix a bug
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
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)

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.
docs.support.term_echo.ste(command, nindent, mdir, fpointer)
Simplified terminal echo; prints STDOUT resulting from a given Bash shell command (relative to the package sbin directory) formatted in reStructuredText

Parameters:

command (string) – Bash shell command, relative to ${PUTIL_DIR}/sbin

nindent (integer) – Indentation level

mdir (string) – Module directory

fpointer (function object) – Output function pointer. Normally is cog.out but print or other functions can be used for debugging

For example:
.. This is a reStructuredText file snippet
.. [[[cog
.. import os, sys
.. from docs.support.term_echo import term_echo
.. file_name = sys.modules['docs.support.term_echo'].__file__
.. mdir = os.path.realpath(
..     os.path.dirname(
..         os.path.dirname(os.path.dirname(file_name))
..     )
.. )
.. [[[cog ste('build_docs.py -h', 0, mdir, cog.out) ]]]

.. code-block:: bash

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

.. ]]]
docs.support.term_echo.term_echo(command, nindent=0, env=None, fpointer=None, cols=60)

Terminal echo; prints STDOUT resulting from a given Bash shell command formatted in reStructuredText

Parameters:

command (string) – Bash shell command

nindent (integer) – Indentation level

env (dictionary) – Environment variable replacement dictionary. The Bash command is pre-processed and any environment variable represented in the full notation (${...}) is replaced. The dictionary key is the environment variable name and the dictionary value is the replacement value. For example, if command is '${PYTHON_CMD} -m "x=5"' and env is {'PYTHON_CMD':'python3'} the actual command issued is 'python3 -m "x=5"'

fpointer (function object) – Output function pointer. Normally is cog.out but print or other functions can be used for debugging

cols (integer) – Number of columns of output

Similarly Python files can be included in docstrings with the help of Cog and the docs.support.incfile module
docs.support.incfile.incfile(fname, fpointer, lrange='1, 6-', sdir=None)
Includes a Python source file in a docstring formatted in reStructuredText

Parameters:

fname (string) – File name, relative to environment variable ${TRACER_DIR}

fpointer (function object) – Output function pointer. Normally is cog.out but print or other functions can be used for debugging

lrange (string) – Line range to include, similar to Sphinx literalinclude directive

sdir (string) – Source file directory. If None the ${TRACER_DIR} environment variable is used if it is defined, otherwise the directory where the docs.support.incfile module is located is used

For example:
def func():
    """
    This is a docstring. This file shows how to use it:

    .. =[=cog
    .. import docs.support.incfile
    .. docs.support.incfile.incfile('func_example.py', cog.out)
    .. =]=
    .. code-block:: python

        # func_example.py
        if __name__ == '__main__':
            func()

    .. =[=end=]=
    """
    return 'This is func output'

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

Changelog¶

0.9.11 [2016-04-15]:
- Created new APIs in the exh module to simplify adding and conditionally raising exceptions that can be auto-documented with the exdoc module
- Homogenized API arguments in several pcsv module functions
- Bug fixes
- Documentation updates
0.9.10 [2016-03-10]: Final release of 0.9.10 branch
0.9.10rc1 [2016-03-09]: Apple OS X compatibility changes. Reduced memory consumption during exception auto-documentation process. Bug fixes
0.9.9 [2016-01-27]: Fixed documentation bugs that were causing errors with Sphinx 1.3.5+
0.9.8 [2016-01-22]: Bug fixes
0.9.7 [2016-01-22]: Enhanced control of exceptions automatic documentation output
0.9.6 [2016-01-20]: Bug fixes
0.9.5 [2016-01-08]: Bug fixes
0.9.4 [2015-12-18]: Minor documentation update regarding continuous integration setup
0.9.3 [2015-12-17]: Fixed critical bug in plot module that prevented figures without any axis labels from being generated
0.9.2 [2015-12-15]: Speed improvements in plot module
0.9.1 [2015-12-01]: Final release of 0.9.1 branch
0.9.1rc5 [2015-12-01]: Fixed documentation URL in top-level README.rst
0.9.1rc4 [2015-12-01]: Fixed bug in top-level README.rst verification
0.9.1rc3 [2015-12-01]:
- Documentation updates
- Package verification improvements
0.9.1rc2 [2015-12-01]: Fixed top-level README.rst file
0.9.1rc1 [2015-11-30]: Initial public release

License¶

The MIT License (MIT)

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.

API¶

Global variables¶

Named tuples¶

Functions¶

Waveform pseudo-type¶

Class¶

Functions¶

Contracts pseudo-types¶

Introduction¶

The pseudo-types defined below can be used in contracts of the PyContracts or Pexdoc libraries. As an example, with the latter:

>>> from __future__ import print_function
>>> import pexdoc
>>> from peng.ptypes import engineering_notation_suffix
>>> @pexdoc.pcontracts.contract(suffix='engineering_notation_suffix')
... def myfunc(suffix):
...     print('Suffix received: '+str(suffix))
...
>>> myfunc('m')
Suffix received: m
>>> myfunc(35)
Traceback (most recent call last):
    ...
RuntimeError: Argument `suffix` is not valid

Alternatively each pseudo-type has a checker function associated with it that can be used to verify membership. For example:

>>> import peng.ptypes
>>> # None is returned if object belongs to pseudo-type
>>> peng.ptypes.engineering_notation_suffix('m')
>>> # ValueError is raised if object does not belong to pseudo-type
>>> peng.ptypes.engineering_notation_suffix(3.5) 
Traceback (most recent call last):
    ...
ValueError: [START CONTRACT MSG: engineering_notation_suffix]...

Description¶

EngineeringNotationNumber¶

Import as engineering_notation_number. String with a number represented in engineering notation. Optional leading whitespace can precede the mantissa; optional whitespace can also follow the engineering suffix. An optional sign (+ or -) can precede the mantissa after the leading whitespace. The suffix must be one of 'y', 'z', 'a', 'f', 'p', 'n', 'u', 'm', ' ' (space), 'k', 'M', 'G', 'T', 'P', 'E', 'Z' or 'Y'. The correspondence between suffix and floating point exponent is:

Exponent	Name	Suffix
1E-24	yocto	y
1E-21	zepto	z
1E-18	atto	a
1E-15	femto	f
1E-12	pico	p
1E-9	nano	n
1E-6	micro	u
1E-3	milli	m
1E+0
1E+3	kilo	k
1E+6	mega	M
1E+9	giga	G
1E+12	tera	T
1E+15	peta	P
1E+18	exa	E
1E+21	zetta	Z
1E+24	yotta	Y

EngineeringNotationSuffix¶

Import as engineering_notation_suffix. A single character string, one of 'y', 'z', 'a', 'f', 'p', 'n', 'u', 'm', ' ' (space), 'k', 'M', 'G', 'T', 'P', 'E', 'Z' or 'Y'. EngineeringNotationNumber lists the correspondence between suffix and floating point exponent

IncreasingRealNumpyVector¶

Import as increasing_real_numpy_vector. Numpy vector in which all elements are real (integers and/or floats) and monotonically increasing (each element is strictly greater than the preceding one)

NumberNumpyVector¶

Import as number_numpy_vector. Numpy vector in which all elements are integers and/or floats and/or complex

RealNumpyVector¶

Import as real_numpy_vector. Numpy vector in which all elements are real (integers and/or floats)

TouchstoneData¶

Import as touchstone_data. A dictionary with the following structure:

points (integer) – Number of data points
freq (IncreasingRealNumpyVector) – Frequency vector
pars (NumberNumpyVector) – Parameter data, its size is equal to nports x nports x points where nports represents the number of ports in the file

The dictionary keys are case sensitive

TouchstoneNoiseData¶

Import as touchstone_noise_data. A dictionary with the following structure:

points (integer) – Number of data points
freq (IncreasingRealNumpyVector) – Frequency vector
nf (RealNumpyVector) – Minimum noise figure vector in decibels
rc (NumberNumpyVector) – Source source reflection coefficient to realize minimum noise figure
res (RealNumpyVector) – Normalized effective noise resistance

The dictionary keys are case sensitive

TouchstoneOptions¶

Import as touchstone_options. A dictionary with the following structure:

units (string) – Frequency units, one of 'GHz', 'MHz', 'KHz' or 'Hz' (case insensitive, default 'GHz')
ptype (string) – Parameter type, one of 'S', 'Y', 'Z', 'H' or 'G' (case insensitive, default 'S')
pformat (string) – Data point format type, one of 'DB' (decibels), 'MA' (magnitude and angle), or 'RI' (real and imaginary) (case insensitive, default 'MA')
z0 (float) – Reference resistance in Ohms, default 50 Ohms

The dictionary keys are case sensitive

WaveInterpOption¶

Import as wave_interp_option. String representing a waveform interpolation type, one of 'CONTINUOUS' or 'STAIRCASE' (case insensitive)

WaveScaleOption¶

Import as wave_scale_option. String representing a waveform scale type, one of 'LINEAR' or 'LOG' (case insensitive)

WaveVectors¶

Import as wave_vectors. Non-empty list of tuples in which each tuple is a waveform point. The first item of a point tuple is its independent variable and the second item of a point tuple is its dependent variable. The vector formed by the first item of the point tuples is of IncreasingRealNumpyVector pseudo-type; the vector formed by the second item of the point tuples is of RealNumpyVector pseudo-type

Description¶

Interpreter¶

Installing¶

Documentation¶

Contributing¶

Changelog¶

License¶

Contents¶

Description¶

Interpreter¶

Installing¶

Documentation¶

Contributing¶

Changelog¶

License¶

API¶

Global variables¶

Named tuples¶

Functions¶

Waveform pseudo-type¶

Class¶

Functions¶

Contracts pseudo-types¶

Introduction¶

Description¶

EngineeringNotationNumber¶

EngineeringNotationSuffix¶

IncreasingRealNumpyVector¶

NumberNumpyVector¶

RealNumpyVector¶

TouchstoneData¶

TouchstoneNoiseData¶

TouchstoneOptions¶

WaveInterpOption¶

WaveScaleOption¶

WaveVectors¶

Checker functions¶

Indices and tables¶