Analysis suite for 2D active nematics data, written in Python3.
This code has benefited from crucial contributions from Matthew S. E. Peterson (@mattsep) and Michael M. Norton (@wearefor).
For an example of a code used in the manuscript Data-driven discovery of active nematic hydrodynamics (arXiv version here), see this Jupyter notebook.
- Clone this repository:
git clone https://github.com/joshichaitanya3/actnempy.git
- Install via
pip
pip install wheel
cd actnempy
pip install .
Basic usage is showcased under examples/basic_example.ipynb
Analysis of an entire trajectory is shown under examples/analyze_trajectory.ipynb
Discovering the underlying PDE model from a trajectory using sparse regression methods as detailed in the manuscript Data-driven discovery of active nematic hydrodynamics (arXiv version here) is shown under examples/SINDy.ipynb
The model identification work detailed in the manuscript was supported by the Department of Energy (DOE) DE-SC0022291. Preliminary data and analysis were supported by the National Science Foundation (NSF) DMR-1855914 and the Brandeis Center for Bioinspired Soft Materials, an NSF MRSEC (DMR-2011846). Computing resources were provided by the NSF XSEDE allocation TG-MCB090163 (Stampede and Comet) and the Brandeis HPCC which is partially supported by the NSF through DMR-MRSEC 2011846 and OAC-1920147.