Estimate the autocorrelation time of a time series quickly.

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Project description

This is an updated, maintained fork of the original acor package. Below is the original README with the appropriate changes to the name and source locations.

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 encor

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/davecwright3/acor.git

Then run

cd acor
python -m pip 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)

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