mnns 1.0.5

Modelling and analyzing random nanowire networks in Python.

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 and continued to be developed under the supervision of Dr. Claudia Gomes da Rocha at the University of Calgary.

Table of Contents

• Installation
  • PyPi
  • Development
  • Uninstallation
• Usage

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 from PyPI 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 .[dev,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:>)