Nonlinear measures for dynamical systems (based on one-dimensional time series)
Nolds is a small numpy-based library that provides an implementation and a learning resource for nonlinear measures for dynamical systems based on one-dimensional time series. Currently the following measures are implemented:
import nolds import numpy as np rwalk = np.cumsum(np.random.random(1000)) h = nolds.dfa(rwalk)
Nolds supports Python 2 (>= 2.7) and 3 (>= 3.4) from one code source. It requires the package numpy.
If you want to use the RANSAC algorithm for line fitting, you will also need the package sklearn.
Nolds is available through PyPI and can be installed using pip:
pip install nolds
You can test your installation by running some sample code with:
python -m nolds.examples all
Nolds is designed as a learning resource for the measures mentioned above. Therefore the corresponding functions feature extensive documentation that not only explains the interface but also the algorithm used and points the user to additional reference code and papers. The documentation can be found in the code, but it is also available as HTML-Version.
All relevant code can be found in the file nolds/measures.py.