Python package for modelling and analyzing random nanowire networks. This package was a summer research project lasting from May 2021 to August 2021 under the supervision of Dr. Claudia Gomes da Rocha.
This repository is discontinued, to be replaced its successor with: https://github.com/marcus-k/MemNNetSim
Random NWNs can be installed from PyPI for quick use or installed manually for development.
The latest version of randomnwn can be installed from PyPI:
pip install randomnwn
An Anaconda environment file is also provided to create a new virtual environment with the minimum required dependencies required to run the package.
conda env create -n randomnwn -f environment.yml
Be sure you activate the environment before using the package!
conda activate randomnwn
One can use the dev-environment.yml file with Anaconda to create a new
virtual environment with all the required dependencies for development.
conda env create -n randomnwn -f dev-environment.yml
This will also install the randomnwn package in editable mode (i.e. as if
running pip install -e . in the base folder).
Nanowire network objects are simply NetworkX graphs with various attributes stored in the graph, edges, and nodes.
>>> import randomnwn as rnwn
>>> NWN = rnwn.create_NWN(seed=123)
>>> NWN
Type: JDA
Wires: 750
Electrodes: 0
Inner-wire junctions: None
Wire junctions: 3238
Length: 50.00 um (7.143 l0)
Width: 50.00 um (7.143 l0)
Wire Density: 0.3000 um^-2 (14.70 l0^-2)
>>> rnwn.plot_NWN(NWN)
(<Figure size 800x600 with 1 Axes>, <AxesSubplot:>)
See the wiki pages for more detail on usage.
To uninstall the package, use:
pip uninstall randomnwn