ElsevierSoftwareX / SOFTX-D-24-00145

Uniformly distributed Pareto-front representation

What is pymcma?

PyMCMA is a Python package for generation of uniformly distributed Pareto-efficient representation for the provided core-model.

You can read more about the project in the online documentation.

Installation

Below you can find a short description of how to install pymcma software. For extended information see the documentation available under the link.

1. Creating and/or activating the Conda environment

   In order to avoid possible conflicts with already installed packages, we recommend to install and use the pyMCMA within a dedicated and regularly updated conda environment created for Python version 3.11.

   To be sure that everything will work as intended we highly recommend to use the following .condarc configuration file:

       ssl_verify: true
       channels:
         - conda-forge
         - defauklts
       channel_priority: flexible
       auto_activate_base: false

   1. Update of the conda version.

       $ conda update -n base -c conda-forge conda

   2. Create a dedicated conda environment for pyMCMA.

       $ conda create --name pymcma -c conda-forge python=3.11

   The dedicated conda environment should be activated whenever the pymcma is executed by the command-line.

2. Installation of the pymcma

   The installation shall be done by executing at the terminal prompt the following two commands (the first one should be skipped, if the conda pymcma environment is active in the currently used terminal window):

       $ conda activate pymcma
       $ conda install pymcma

   Installation shall be tested by running:

       $ pymcma -h

   which displays the command-line options.

3. Copying the examples and templates

   The following command copies to the current directory the files organized into three directories:

       $ pymcma --install

   The copied files are needed for running the example analysis on the model shipped with the package using; this can be done by the following command:

       $ pymcma --anaDir anaTst

   More details about the pymcma installation and testing is available documentation.

Basic usage

To make your own analysis with the our example model you need to change the configuration in the anaTst/cfg.yml in your work directory. Then, you need to run the following command to start analysis:

    $ pymcma --anaDir anaTst

To make analysis for your own model you need to create a core model in Pyomo and export it in the dill format, as well as adapt the pymcma configuration file for your desired analysis. Please refer to the User Guide section in the documentation for comprehensive guidelines.