MemNNetSim: Memristive Nanowire Network Simulator. A proof-of-concept Python package for modelling and analyzing memristive random nanowire networks (NWNs). This package, developed by Marcus Kasdorf, was initiated from a summer research project in 2021 under the supervision of Dr. Claudia Gomes da Rocha at the University of Calgary.
MemNNetSim has been tested on Python 3.10 to 3.13. It is recommended to install MemNNetSim in a virtual environment such as with venv or conda/mamba.
For installing locally, a pip version of 21.1 or greater is required.
Install the latest release of MemNNetSim from PyPI using pip:
pip install mnnsDownload or clone the GitHub repository:
git clone https://github.com/marcus-k/MemNNetSim.git
cd ./MemNNetSimThen install the package in editable mode using pip:
pip install -e .[dev]To install for editing the documentation, add the [docs] optional dependencies:
pip install -e .[dev,docs]Uninstall MemNNetSim using pip:
pip uninstall mnnsNanowire network objects are simply NetworkX graphs with various attributes stored in the graph, edges, and nodes.
>>> import mnns
>>> NWN = mnns.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)
>>> mnns.plot_NWN(NWN)
(<Figure size 800x600 with 1 Axes>, <AxesSubplot:>)