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).
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).
Given some time series x, you can estimate the autocorrelation time
(tau) using:
import acor tau, mean, sigma = acor.acor(x)