Installation

Chama requires Python (tested on 3.7, 3.8, and 3.9) along with several Python package dependencies. Information on installing and using Python can be found at https://www.python.org/. Python distributions, such as Anaconda, are recommended to manage the Python interface.

To install the latest stable version of Chama using pip:

pip install chama

To install the development branch of Chama from source using git:

git clone https://github.com/sandialabs/chama
cd chama
python setup.py install

Developers should build Chama using the setup.py ‘develop’ option.

Dependencies

Required Python package dependencies include:

• Pyomo [HLWW12]: Used to formulate optimization problems and call solvers, https://github.com/pyomo.

• Pandas [Mcki13]: Used to analyze and store dataframes, http://pandas.pydata.org.

• Numpy [VaCV11]: Used to analyze large, multi-dimensional arrays and matrices, http://www.numpy.org.

• Scipy [VaCV11]: Used to support efficient routines for numerical analysis, http://www.scipy.org.

Optional Python package dependencies include:

• Matplotlib [Hunt07]: Used to produce graphics, http://matplotlib.org.

• nose: Used to run software tests, http://nose.readthedocs.io.

Required Pyomo supported MIP solver:

• In addition to the Python package dependencies, a Pyomo supported MIP solver is required to solve the optimization problems formulated in Chama. Examples of solvers that meet this requirement include GLPK [Makh10], Gurobi [GUROBI], and CPLEX [CPLEX].

• GLPK can be installed through conda-forge, conda install -c conda-forge glpk