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Project Description

This is a direct port of a C++ routine by Jonathan Goodman (NYU) called ACOR that estimates the autocorrelation time of time series data very quickly.

Dan Foreman-Mackey (NYU) made a few surface changes to the interface in order to write a Python wrapper (with the permission of the original author).

Installation

Just run

pip install acor

with sudo if you really need it.

Otherwise, download the source code as a tarball or clone the git repository from GitHub:

git clone https://github.com/dfm/acor.git

Then run

cd acor
python setup.py install

to compile and install the module acor in your Python path. The only dependency is NumPy (including the python-dev and python-numpy-dev packages which you might have to install separately on some systems).

Usage

Given some time series x, you can estimate the autocorrelation time (tau) using:

import acor
tau, mean, sigma = acor.acor(x)
Release History

Release History

1.1.1

This version

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1.1.0

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1.0.2

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1.0.1

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1.0.0

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TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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Download Files

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
acor-1.1.1.tar.gz (6.1 kB) Copy SHA256 Checksum SHA256 Source Aug 5, 2014

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