That directory contains examples how to prepare input data, run the model and process results using Python.

Please keep in mind, it is an examples only and some important details, like error handling, intentionally omitted. It is highly recommended to use try ... except in production code.

For more information visit our wiki or e-mail to: openmpp dot org at gmail dot com.

Python scripts are using openM++ web-service in order to run the model, modify parameters and read output values. No installation required, just download latest release of openM++, unpack it into any directory and start oms.exe:

Windows: double click on C:\my-openmpp-release\bin\ompp_ui.bat

Linux: open in terminal (or double click on): ~/my-openmpp-release/bin/ompp_ui_linux.sh

MacOS: double click on: ~/my-openmpp-release/bin/ompp_ui_mac.command

Linux / MacOS command line:

cd ~/my-openmpp-release
bin/start_oms.sh

As result oms web-service will start to listen incoming requests on http://localhost:4040 and Python script will do all actions using oms web-service API.

NewCaseBased model: loop over MortalityHazard parameter to analyze DurationOfLife output value.

RiskPaths model: analyze contribution of delayed union formations versus decreased fertility on childlessness.

License: MIT.