Neworder
A dynamic microsimulation framework for python
Install / Use
/learn @virgesmith/NeworderREADME
neworder
neworder is a microsimulation framework inspired by openm++, MODGEN and, to a lesser extent, the python-based LIAM2 tool, and can be thought of as a powerful best-of-both-worlds hybrid of MODGEN and LIAM2. Modellers can define their models in a simple, well-known language, yet benefit from the efficiency of compiled code and parallel execution:
- python module: easy to install and integrate, available on all common platforms
- low barriers to entry: users need only write standard python code, little or no new coding skills required.
- flexibility: models are specified in python code, so can be arbitrarily complex
- data agnosticism: the framework does not impose any constraints on data formats for either sources or outputs.
- reusability: leverage python modules like numpy, pandas and matplotlib.
- reproducibility: built-in, customisable random generator seeding strategies
- speed: the module is predominantly written in optimised C++ and provides fast Monte-Carlo, statistical and data manipulation functions.
- compatibility: operate directly on numpy arrays and pandas DataFrames
- scalability: can be run on a desktop or a HPC cluster, supporting parallel execution using MPI.
System Requirements
neworder requires python 3.12 or above and runs on 64-bit linux, OSX and Windows platforms. To take advantage of the optional parallel execution functionality, you may also need to install an MPI implementation, such as open-mpi or ms-mpi. (As of Nov 2025, mpich has noted to cause mpi4py to incorrect report rank/size).
For example, to install opemmpi on debian-based linux:
sudo apt install -y build-essential openmpi-bin
Or open-mpi on OSX,
brew install open-mpi
Installation
The package can be installed from pypi.
For a basic (serial only) installation,
pip install neworder
or to enable parallel execution using MPI:
pip install neworder[parallel]
or enable the (geo)spatial graph functionality:
pip install neworder[geospatial]
or both:
pip install neworder[parallel,geospatial]
Docker
The docker image contains all the examples, and should be run interactively. Some of the examples require permission to connect to the host's graphical display.
docker pull virgesmith/neworder
xhost +local:
docker run --net=host -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=$DISPLAY -it virgesmith/neworder
NB The above works on ubuntu but may require modification on other OSs.
Then in the container, e.g.
python examples/mortality/model.py
Documentation
To get started first see the detailed documentation here. Then, check out "Hello World" and the other examples.
Related Skills
node-connect
339.1kDiagnose OpenClaw node connection and pairing failures for Android, iOS, and macOS companion apps
frontend-design
83.8kCreate distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
openai-whisper-api
339.1kTranscribe audio via OpenAI Audio Transcriptions API (Whisper).
commit-push-pr
83.8kCommit, push, and open a PR
