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#!/usr/bin/env python
# -*- coding: utf-8 -*-
u"""
This package provides a multiple-τ algorithm for Python 2.7 and
Python 3.x and requires the package :py:mod:`numpy`.
Multipe-τ correlation is computed on a logarithmic scale (less
data points are computed) and is thus much faster than conventional
correlation on a linear scale such as :py:func:`numpy.correlate`.
Recommended literature
----------------------
- Klaus Schaetzel and Rainer Peters; *Noise on multiple-tau photon
correlation data*. Proc. SPIE 1430, Photon Correlation
Spectroscopy: Multicomponent Systems, 109 (June 1, 1991);
http://doi.org/10.1117/12.44160
- Thorsten Wohland, Rudolf Rigler, and Horst Vogel; *The Standard
Deviation in Fluorescence Correlation Spectroscopy*. Biophysical
Journal, 80 (June 1, 2001);
http://dx.doi.org/10.1016/S0006-3495(01)76264-9
Obtaining multipletau
---------------------
If you have Python and :py:mod:`numpy` installed, simply run
pip install multipletau
The source code of multipletau is available at
https://github.com/FCS-analysis/multipletau.
Citing multipletau
------------------
The multipletau package should be cited like this (replace "x.x.x"
with the actual version of multipletau used and "DD Month YYYY"
with a matching date).
.. topic:: cite
Paul Müller (2012) *Python multiple-tau algorithm* (Version x.x.x)
[Computer program].
Available at https://pypi.python.org/pypi/multipletau/
(Accessed DD Month YYYY)
You can find out what version you are using by typing
(in a Python console):
>>> import multipletau
>>> multipletau.__version__
'0.1.4'
Usage
-----
The package is straightforward to use. Here is a quick example:
>>> import numpy as np
>>> import multipletau
>>> a = np.linspace(2,5,42)
>>> v = np.linspace(1,6,42)
>>> multipletau.correlate(a, v, m=2)
array([[ 0. , 569.56097561],
[ 1. , 549.87804878],
[ 2. , 530.37477692],
[ 4. , 491.85812017],
[ 8. , 386.39500297]])
"""
from ._multipletau import *
from ._version import version as __version__
__author__ = u"Paul Müller"
__license__ = "BSD (3 clause)"
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