A python library for calculating Allan deviation and related time & frequency statistics. GPL v3+ license.
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!
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
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
- 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
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
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
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):
$ py.test -k "not (slow or fails)" --durations=10
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