NodePy requires Python 3.5 or later. To install with pip, do:
pip install nodepy
This will automatically fetch dependencies also. It will not fetch
optional dependencies, which include networkx, cvxpy and scipy (that are used
only in a few specialized routines and/or examples). The optional dependencies
can be installed with pip.
NodePy (Numerical ODEs in Python) is a Python package for designing, analyzing, and testing numerical methods for initial value ODEs. Its development was motivated by my own research in time integration methods for PDEs. I found that I was frequently repeating tasks that could be automated and integrated. Initially I developed a collection of MATLAB scripts, but this became unwieldy due to the large number of files that were necessary and the more limited capability for code reuse.
NodePy represents an object-oriented approach, in which the basic object is a numerical ODE solver. The idea is to design a laboratory for such methods in the same sense that MATLAB is a laboratory for matrices.
Documentation can be found online at
http://nodepy.readthedocs.org/en/latest/
To get started, you can also have a look at the examples folder,
beginning with an introduction as Jupyter notebook.
The development version can be obtained from
http://github.com/ketch/nodepy
If you use NodePy in a published work, please cite it as follows:
Ketcheson, D. I. NodePy software version <version number>,
http://github.com/ketch/nodepy/.
Please insert the version number that you used.
If you encounter an error or need help, please raise an issue.
Contributions of new features or other improvements are very welcome! Please submit a pull request or contact the authors.
NodePy is distributed under the terms of the modified Berkeley Software Distribution (BSD) license.
NodePy development has been supported by:
- A U.S. Dept. of Energy Computational Science Graduate Fellowship
- Grants from King Abdullah University of Science & Technology