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Multiple-tau 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 numpy.correlate.

Installation

The only requirement for multipletau is Python 3.x and NumPy. Install multipletau from the Python package index:

pip install multipletau

Documentation

The documentation, including the reference and examples, is available on readthedocs.io.

Usage

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]])

Citing

The multipletau package should be cited like this (replace “x.x.x” with the actual version of multipletau that you used and “DD Month YYYY” with a matching date).

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__
'0.4.0'

Metadata

Release files for multipletau 0.4.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for multipletau 0.4.1
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multipletau-0.4.1.tar.gz 94.8 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for multipletau 0.4.1
File Interpreter ABI Platform
multipletau-0.4.1-py2.py3-none-any.whl Python 2, Python 3 none any Details

Total release size: 105.3 kB

Release files / multipletau-0.4.1.tar.gz

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Size 94.8 kB
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Release files / multipletau-0.4.1-py2.py3-none-any.whl

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