Simulation Modelling Integration Framework
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 simple models that simulate the operation of a system. smif will eventually implement optimisation routines which will allow, for example, the solution of capacity expansion problems.
smif is written in Python (Python>=3.5) and has a number of dependencies. See requirements.txt for a full list.
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 orbrew 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 yourPATH
.
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 pip install -r requirements.txt
On Windows, the simplest approach seems to be using 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 python=3.5 numpy scipy
Activate it (run each time you switch projects):
activate smif
Note that you source activate smif
on OSX and Linux.
Add the conda-forge channel, which has shapely and fiona available:
conda config --add channels conda-forge
Install python packages, along with GDAL and dependencies:
conda install fiona shapely rtree pip install -r requirements.txt
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#egg=v0.2
The suffix #egg=v0.2
refers to a specific version of the source code.
Omitting the suffix installs the latest version of the library.
To install from the source code in development mode:
git clone http://github.com/nismod/smif cd smif python setup.py develop
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.