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)
References
1 maintainer
Release files for acor 1.1.1
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Source distribution (sdist)
| File | Size | Uploaded | |
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| acor-1.1.1.tar.gz | 6.1 kB | Details |
Release files / acor-1.1.1.tar.gz
| Download URL | acor-1.1.1.tar.gz |
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| Size | 6.1 kB |
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