Metadata-Version: 1.1
Name: AllanTools
Version: 2018.3
Summary: Allan deviation and related time/frequency statistics
Home-page: https://github.com/aewallin/allantools
Author: Anders E. E. Wallin
Author-email: anders.e.e.wallin@gmail.com
License: LGPLv3+
Description: AllanTools
        ==========
        
        .. image:: https://badge.fury.io/py/AllanTools.svg
            :target: https://badge.fury.io/py/AllanTools
        .. image:: https://travis-ci.org/aewallin/allantools.svg?branch=master
            :target: https://travis-ci.org/aewallin/allantools
        .. image:: http://readthedocs.org/projects/allantools/badge/?version=latest
            :target: http://allantools.readthedocs.io/en/latest/?badge=latest
            :alt: Documentation Status
        .. image:: https://coveralls.io/repos/github/aewallin/allantools/badge.svg?branch=master 
            :target: https://coveralls.io/github/aewallin/allantools?branch=master 
        
        A python library for calculating Allan deviation and related 
        time & frequency statistics. `LGPL v3+ license <https://www.gnu.org/licenses/lgpl.html>`_.
        
        Developed at https://github.com/aewallin/allantools and also available 
        on PyPi at https://pypi.python.org/pypi/AllanTools
        Discussion group at https://groups.google.com/d/forum/allantools
        
        Input data should be evenly spaced observations of either fractional frequency,
        or phase in seconds. Deviations are calculated for given tau values in seconds.
        
        These statistics are currently included:
        
        * adev()    Allan deviation
        * oadev()   overlapping Allan deviation,
        * mdev()    modified Allan deviation,
        * tdev()    Time deviation
        * hdev()    Hadamard deviation
        * ohdev()   overlapping Hadamard deviation
        * totdev()  total Allan deviation
        * mtie()    Maximum time interval error
        * tierms()  Time interval error RMS
        * mtotdev() Modified total deviation
        * ttotdev() Time total deviation
        * htotdev() Hadamard total deviation
        * theo1()   Thêo1 deviation
        
        Noise generators for creating synthetic datasets are also included:
        
        * violet noise with f^2 PSD
        * white noise with f^0 PSD
        * pink noise with f^-1 PSD
        * Brownian or random walk noise with f^-2 PSD 
        
        
        see /tests for tests that compare allantools output to other 
        (e.g. Stable32) programs. More test data, benchmarks, ipython notebooks, 
        and comparisons to known-good algorithms are welcome!
        
        Documentation
        =============
        See /docs for documentation in sphinx format. On Ubuntu this requires 
        the **python-sphinx** and **python-numpydoc** packages.
        html/pdf documentation using sphinx can be built locally with::
        
            /docs$ make html
            /docs$ make latexpdf
        
        this generates html documentation in docs/_build/html and pdf 
        documentation in docs/_build/latex.
        
        The sphinx documentation is also auto-generated online
        
        * http://allantools.readthedocs.org
        
        IPython notebooks with examples 
        =============================== 
        See /examples for some examples in IPython notebook format.
        
        
        github formats the notebooks into nice web-pages, for example 
        
        * https://github.com/aewallin/allantools/blob/master/examples/noise-color-demo.ipynb
        * https://github.com/aewallin/allantools/blob/master/examples/three-cornered-hat-demo.ipynb
        
        todo: add here a very short guide on how to get started with ipython
        
        Authors 
        ======= 
        * Anders E.E. Wallin, anders.e.e.wallin "at" gmail.com 
        * Danny Price, https://github.com/telegraphic 
        * Cantwell G. Carson, carsonc "at" gmail.com 
        * Frédéric Meynadier, https://github.com/fmeynadier
        
        Installation 
        ============
        
        
        clone from github, then install with::  
        
            sudo python setup.py install    
        
        (see `python setup.py --help install` for install options)
        
        or download from pypi::
            
            sudo pip install allantools
        
        
        Usage 
        =====
        
        New in 2016.11 : simple top-level API, using dedicated classes for data handling and plotting.
        
        ::
        
            import allantools # https://github.com/aewallin/allantools/
            import numpy as np
        
            # Compute a deviation using the Dataset class
            a = allantools.Dataset(data=np.random.rand(1000))
            a.compute("mdev")
        
            # Plot it using the Plot class
            b = allantools.Plot()
            b.plot(a, errorbars=True, grid=True)
            # You can override defaults before "show" if needed
            b.ax.set_xlabel("Tau (s)")
            b.show()
        
        Lower-level access to the algorithms is still possible :
        
        ::
        
            import allantools # https://github.com/aewallin/allantools/ 
            rate = 1/float(data_interval_in_s) # data rate in Hz 
            taus = [1,2,4,8,16] #  tau-values in seconds
            # fractional frequency data
            (taus_used, adev, adeverror, adev_n) = allantools.adev(fract_freqdata, data_type='freq', rate=rate, taus=taus)
            # phase data
            (taus_used, adev, adeverror, adev_n) = allantools.adev(phasedata, data_type='phase', rate=rate, taus=taus)
        
            # notes:
            #  - taus_used may differ from taus, if taus has a non-integer multiples 
            #  of data_interval - adeverror assumes 1/sqrt(adev_n) errors
        
        Tests
        =====
        
        The tests compare the output of allantools to other programs such
        as Stable32. Tests may be run using py.test (http://pytest.org).
        Slow tests are marked 'slow' and tests failing because of a known
        reason are marked 'fails'. To run all tests::
            
            $ py.test
        
        To exclude known failing tests::
        
            $ py.test -m "not fails" --durations=10
        
        To exclude tests that run slowly::
        
            $ py.test -m "not slow" --durations=10
        
        To exclude both (note option change) and also check docstrings is ReST files ::
        
            $ py.test -k "not (slow or fails)" --durations=10 --doctest-glob='*.rst'
        
        To run the above command without installing the package::
        
            $ python setup.py test --addopts "-k 'not (fails or slow)'"
        
        Test coverage may be obtained with the 
        (https://pypi.python.org/pypi/coverage) module::
        
            coverage run --source allantools setup.py test --addopts "-k 'not (fails or slow)'"
            coverage report # Reports on standard output 
            coverage html # Writes annotated source code as html in ./htmlcov/
        
        On Ubuntu this requires packages **python-pytest** and 
        **python-coverage**.
        
        Testing on multiple python versions can be done with tox (https://testrun.org/tox)
        
            $ tox
        
        Tests run continuously on Travis-CI at https://travis-ci.org/aewallin/allantools
        
        
        
        
Platform: UNKNOWN
Requires: numpy
Requires: scipy
