The model needs the configurations file to run (described in previous sections). These configs become lengthy and sometimes difficult to type manually. The config writer helps to generate configs provided the relevant files are present.

Print Functions:

These functions are used to print specific sections of the configuration files.

print_header

Used to generate the global header. For more information on global headers click .

print_spatial_setup

Used to generate the spatial setup section of the configuration. For more information on spatial setup click .

print_compartments

Used to generate the compartment list for each way a population can be divided.

Parts of the configuration files that are printed but not needed for FlepiMop runs (need to be mentioned for US or COVID-19 specific runs??)

Spatial Setup:

• census year: year of geodata files

• modeled states (sim_states): This has US state abbreviations. Do we include the names of the sub-populations in the geodata file? Eg: small_province, large_province

• state_level: Specifies if the runs are run for US states

We provide helper scripts to aid users in understanding model outputs and diagnosing simulations and iterations. These scripts may be set to run automatically after a model run, and are dependent on the model defined in the user's defined config file ;

The script postprocess_snapshot.R requires the following command line inputs:

• a user-defined config, $CONFIG_PATH

• a run index, $FLEPI_RUN_INDEX

• a path to the model output results, $FS_RESULTS_PATH

• a path to the flepiMoP repository, $FLEPI_PATH; an ;

• a list of outputs to plot, $OUTPUTS, by default the script provides diagnostics for the following model output file ;

Plots of hosp output files show confidence intervals of model runs, against the provided ground truth data for inference runs, for each metapopulation node. hnpi and snpi plots provide violin plots of parameter values for each slot ;

Other scripts are included as more specific examples of post-processing, used for diagnostic tools. processing_diagnostics.R scripts provides a detailed diagnosis of inference model runs and fits ;

Some information to consider if you'd like your script to be run automatically after an inference run ;

• Most R/python packages are installed already installed. Try to run your script on the conda environment defined on the submission page (or easier if you are not set up on MARCC, ask me)

• There will be some variables set in the environment. These variables are:

  • $CONFIG_PATH the path to the configuration fil ;

  • $FLEPI_RUN_INDEX the run id for this run (e.g `CH_R3_highVE_pesImm_2022_Jan29`

  • $JOB_NAME this job name (e.g USA-20230130T163847_inference_med)

  • $FS_RESULTS_PATH the path where lies the model results. It's a folder that contains the model_ouput/ as a subfolder

  • $FLEPI_PATH path of the flepiMoP repository.

  • $PROJECT_PATH path of the Data directory (e.g Flu_USA or COVID19_USA).

  • Anything you ask can theoretically be provided here.

• The script must run without any user intervention.

• The script is run from $PROJECT_PATH.

• Your script lies in the flepiMoP directory (preferably) or it's ok if it is in a data directory if it makes sense ;

• It is run on a 64Gb of RAM multicore machine. All scripts combined must complete under 4 hours, and you can use multiprocessing (48 cores)

• Outputs (pdf, csv, html, txt, png ...) must be saved in a directory named pplot/ (you can assume that it exists) in order to be sent to slack by FlepiBot 🤖 after the run.

• an example postprocessing script (in python) is .

• You can test your script on MARCC on a run that is already saved in /data/struelo1/flepimop-runs or I can do it for you.

• Once your script works, add (or ask to add) the command line to run in file batch/postprocessing_scripts.sh between the START and END lines, with a little comment about what your script does.