Simulation Modelling Integration Framework
Project description
Simulation Modelling Integration Framework
Description
smif is a framework for handling the creation of system-of-systems models. The framework handles inputs and outputs, dependencies between models, persistence of data and the communication of state across years.
This early version of the framework handles simulation models that simulate the operation of a system within a year. smif exposes an interface to a planning module which will allows different algorithms to be used against a common API.
Setup and Configuration
smif is written in Python (Python>=3.5) and has a number of dependencies. See requirements.txt for a full list.
Using conda
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):
activate smif_env
Note that you source activate smif_env on OSX and Linux (or e.g. Git Bash on Windows).
Add the conda-forge channel, which has smif available:
conda config --add channels conda-forge
Finally install smif:
conda install smif
GLPK
The optimisation routines currently use GLPK - the GNU Linear Programming Kit. To install the glpk solver:
on Linux or Mac OSX, you can likely use a package manager, e.g. apt install python-glpk glpk-utils for Ubuntu or brew install glpk for OSX.
on Windows, GLPK for Windows provide executables. For 64bit Windows, download and unzip the distribution files then add the w64 folder to your PATH.
fiona, GDAL and GEOS
We use fiona, which depends on GDAL and GEOS libraries.
On Mac or Linux these can be installed with your OS package manager, then install the python packages as usual using:
# On debian/Ubuntu: apt-get install gdal-bin libspatialindex-dev libgeos-dev # or on Mac brew install gdal brew install spatialindex brew install geos
Installing smif with other methods
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+http://github.com/nismod/smif
To install from the source code in development mode:
git clone http://github.com/nismod/smif cd smif python setup.py develop
Running smif from the command line
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] [-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 -v, --verbose show messages: -v to see messages reporting on progress, -vv to see debug messages.
Citation
If you use smif for research, please cite the software directly:
Usher, W., Russell, T. and Schoenmakers, R. (2018). smif: simulation modelling integration framework (v0.7.6) [Software]. Available online: https://github.com/nismod/smif
Here’s an example BibTeX entry:
@Misc{, author = {Will Usher and Tom Russell and Roald Schoenmakers}, title = {{smif}: simulation modelling integration framework (v0.7.6)}, year = {2018}, url = "https://github.com/nismod/smif", note = {[Online; accessed <today>]} }
A word from our sponsors
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.
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