Modelling and analyzing random nanowire networks in Python.
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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.
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Installation
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.
Installation from PyPI
Install the latest release of MemNNetSim using pip:
pip install mnns
Installation for development
Download or clone the GitHub repository:
git clone https://github.com/marcus-k/MemNNetSim.git
cd ./MemNNetSim
Then 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 .[docs]
Uninstallation
Uninstall MemNNetSim using pip:
pip uninstall mnns
Usage
Nanowire 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:>)
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