Simulation Modelling Integration Framework
smif is a framework for handling the creation, management and running of system-of-systems models.
A system-of-systems model is a collection of system simulation models that are coupled through dependencies on data produced by each other.
smif provides a user with the ability to
- create system-of-systems models
- add simulation models to a system-of-systems model
- create dependencies between models by linking model inputs and outputs
- pick from a library of data adapters which perform common data conversions across dependencies
- create user-defined data adapters for more special cases
- add scenario data sources and link those to model inputs within a system-of-systems
- add a simulation model to a library of models
- write a simulation model wrapper which allows smif to run the model
- define multi-dimensional model inputs, outputs and parameters and appropriate metadata
- run system-of-systems models
- link concrete scenario data sets to a system-of-systems model
- define one or more decision modules that operate across the system-of-systems
- define a narrative to parameterise the contained models
- persist intermediate data for each model output, and write results to a data store for subsequent analysis
In summary, the framework facilitates the hard coupling of complex systems models into a system-of-systems.
There are number of practical limits imposed by the implementation of smif. These are a result of a conscious design decision that stems from the requirements of coupling the infrastructure system models to create the next generation National Infrastructure System Model (NISMOD2).
The discussion below may help you determine whether smif is an appropriate tool for you.
- smif is not a scheduler, but has been designed to make performing system-of-systems analyses with a scheduler easier
- Geographical extent is expected to be defined explicitly by a vector geometry
- smif is not optimised for models which simulate on a grid, though they can be accomodated
- smif is designed for models that read and write spatial data defined over irregular grids or polygons using any spatial format readable by fiona
- Inputs and outputs are exchanged at the ‘planning timestep’ resolution
- smif makes a distinction between simulation of operation, which happens at a model-defined timestep resolution, and application of planning decisions which happens at a timestep which is synchronised between all models
- smif is not focussed on tight coupling between models which need to exchange data at every simulation timestep (running in lockstep)
- smif does accomodate individual models with different spatial and temporal (and other dimensional) resolutions, by providing data adaptors to convert from one resolution to another
- smif has been designed to support the coupling of bottom-up, engineering
simulation models built to simulate the operation of a given infrastructure system
- smif provides a mechanism for passing information from the system-of-systems level (at planning timesteps scale) to the contained models
- smif is appropriate for coupling large complex models that exchange resources and information at relatively course timesteps
- smif is not appropriate for
- discrete event system simulation models (e.g. queuing systems)
- dynamical system models (e.g. predator/prey)
- equilibrium models without explicit timesteps (e.g. Land-Use Transport Interaction)
- for simulating 100s of small actor-scale entities within a system-level environment
smif is written in Python (Python>=3.5) and has a number of dependencies. See requirements.txt for a full list.
The recommended installation method is to use conda, which handles packages and virtual environments, along with the conda-forge channel which has a host of pre-built libraries and packages.
Create a conda environment:
conda create --name smif_env python=3.6
Activate it (run each time you switch projects):
conda activate smif_env
Add the conda-forge channel, which has smif available:
conda config --add channels conda-forge
Finally install smif
:
conda install smif
Once the dependencies are installed on your system, a normal installation of smif can be achieved using pip on the command line:
pip install smif
Versions under development can be installed from github using pip too:
pip install git+https://github.com/nismod/smif
To install from the source code in development mode:
git clone https://github.com/nismod/smif cd smif python setup.py develop
smif
optionally depends on fiona and shapely, which depend on the GDAL and GEOS libraries. These
add support for reading and writing common spatial file formats and for spatial data
conversions.
If not using conda, on Mac or Linux these can be installed with your OS package manager:
# On debian/Ubuntu: apt-get install gdal-bin libspatialindex-dev libgeos-dev # or on Mac brew install gdal brew install spatialindex brew install geos
Then to install the python packages, run:
pip install smif[spatial]
Follow the getting started guide to help set up the necessary configuration.
To set up an sample project in the current directory, run:
$ smif setup
To list available model runs:
$ smif list demo_model_run ...
To start the smif app, a user-interface that helps to display, create and edit a configuration, run:
$ smif app
To run a system-of-systems model run:
$ smif run demo_model_run ... Model run complete
By default, results will be stored in a results directory, grouped by model run and simulation model.
To see all options and flags:
$ smif --help usage: smif [-h] [-V] {setup,list,run} ... Command line tools for smif positional arguments: {setup,list,app,run} available commands setup Setup the project folder list List available model runs app Open smif app run Run a model optional arguments: -h, --help show this help message and exit -V, --version show the current version of smif
If you use smif for research, please cite the software directly:
- Will Usher, Tom Russell, Roald Schoenmakers, Craig Robson, Fergus Cooper, Thibault Lestang & Rose Dickinson. (2019). nismod/smif vX.Y.Z (Version vX.Y.Z). Zenodo. http://doi.org/10.5281/zenodo.1309336
Here's an example BibTeX entry:
@misc{smif_software, author = {Will Usher and Tom Russell and Roald Schoenmakers and Craig Robson and Fergus Cooper and Thibault Lestang and Rose Dickinson}, title = {nismod/smif vX.Y.Z}, month = Aug, year = 2018, doi = {10.5281/zenodo.1309336}, url = {https://doi.org/10.5281/zenodo.1309336} }
Please also cite the software description paper:
- Will Usher and Tom Russell. (2019) A Software Framework for the Integration of Infrastructure Simulation Models. Journal of Open Research Software, 7: 16 DOI: https://doi.org/10.5334/jors.265
Here's an example BibTeX entry:
@misc{smif_paper, author = {Will Usher and Tom Russell}, title = {A Software Framework for the Integration of Infrastructure Simulation Models}, journal = {Journal of Open Research Software}, volume = {7}, number = {16}, pages = {1--5}, month = May, year = {2019}, doi = {10.5334/jors.265}, url = {https://doi.org/10.5334/jors.265} }
smif was written and developed at the Environmental Change Institute, University of Oxford within the EPSRC sponsored MISTRAL programme, as part of the Infrastructure Transition Research Consortium.