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Population pyramid

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 will also need an MPI implementation, such as open-mpi or mpich. Note that MPI packages are not currently available for Windows via pip - Windows users must install an MPI runtime separately (e.g. MS-MPI) and use the parallel-native extra.

Installation

The package can be installed from pypi.

For a basic (serial only) installation,

pip install neworder

or to enable parallel execution using MPI use one of the following:

pip install neworder[parallel-openmpi]  # install the openmpi runtime in the virtual environment
pip install neworder[parallel-mpich]  # install the mpich runtime in the virtual environment
pip install neworder[parallel-native]  # use the system's mpi runtime

and to enable the (geo)spatial graph functionality:

pip install neworder[geospatial]

or a combination of the two:

pip install neworder[parallel-openmpi,geospatial]

Examples

Download the examples zipfile/archive can from the releases page, or pull the docker image.

The docker image should be run interactively. Some of the examples require permission to connect to the host's graphical display, e.g.

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

Developer

See Contributing for installation steps.