Examples of chap evaluate commands

The following are examples of running various chap-integrated models on various datasets:

  • minimalist_example_r: chap evaluate --model-name https://github.com/dhis2-chap/minimalist_example_r --dataset-name ISIMIP_dengue_harmonized --dataset-country vietnam --report-filename report.pdf --debug --n-splits=2

  • minimalist_multiregion_r: chap evaluate --model-name https://github.com/dhis2-chap/minimalist_multiregion_r --dataset-name ISIMIP_dengue_harmonized --dataset-country vietnam --report-filename report.pdf --debug --n-splits=2

  • minimalist_example_lag_r: chap evaluate --model-name https://github.com/dhis2-chap/minimalist_example_lag_r --dataset-name ISIMIP_dengue_harmonized --dataset-country vietnam --report-filename report.pdf --debug --n-splits=2

  • Madagascar_ARIMA: chap evaluate --model-name https://github.com/dhis2-chap/Madagascar_ARIMA --dataset-name ISIMIP_dengue_harmonized --dataset-country vietnam --report-filename report.pdf --debug --n-splits=2

  • Epidemiar: chap evaluate --model-name https://github.com/dhis2-chap/epidemiar_example_model --dataset-csv ../epidemiar_example_data/input/laos_test_data.csv --report-filename report.pdf --debug --n-splits=2

  • chap_auto_ewars_weekly: chap evaluate --model-name https://github.com/dhis2-chap/chap_auto_ewars_weekly --dataset-name ISIMIP_dengue_harmonized --dataset-country vietnam --report-filename report.pdf --debug --n-splits=1

  • chap_auto_ewars: chap evaluate --model-name https://github.com/dhis2-chap/chap_auto_ewars --dataset-name ISIMIP_dengue_harmonized --dataset-country vietnam --report-filename report.pdf --debug --n-splits=1

Note that the Epidemiar command uses a local file path for the supplied dataset as it requires weekly data, which is not currently available in CHAP’s internal datasets. The command above works when cloning the epidemiar_example_model locally and if the command is run from the folder chap-core, then it assumes that the cloned repository is in the same folder as chap-core, and we use the relative file path. You can also simply dowload the csv file laos_test_data.csv from the github folder and reference the path to the local file.

chap_auto_ewars only accepts mothly data while chap_auto_ewars_weekly can use both weekly and monthly data, should be combined together soon. Additionaly there is a version of chap_auto_ewars which uses spatial smoothing and a geojson file which can be ran as

  • chap evaluate --model-name https://github.com/Halvardgithub/chap_auto_ewars --dataset-csv ../chap_auto_ewars/example_data_Viet/historic_data.csv --polygons-json ../chap_auto_ewars/example_data_Viet/vietnam.json --report-filename report.pdf --debug --n-splits=1 --polygons-id-field VARNAME_1 The above uses local files and their relative paths, the files are available at the github url.

For Windows users

Windows users might have issues with the commands above. The solution is to clone the repositories for the external models and add the optional command --run-directory-type use_existing. An example is shown below.

  • minimalist_example_r: chap evaluate --model-name /mnt/c/Users/NAME/Documents/GitHub/minimalist_example_r/ --dataset-name ISIMIP_dengue_harmonized --dataset-country vietnam --report-filename report.pdf --debug --n-splits=2 --run-directory-type use_existing

Note that you need to use your own local file path, and if you are using WSL and ubuntu this might be with mnt from linux, even on a Windows system.

Warnings

When running the command with a local file path for the model folder you can in theory run the command from any folder, not just from chap-core. However, running chap evaluate with --run-directory-type use_existing from the same folder as you are using as the --model-name will cause an inifnite copying loop. Sometimes, if a command fails, it might be neccessary to exit and open the folder again, for example run cd ../chap-core to go one folder up and then back to chap-core. Additionaly, having an active VPN can aslo confuse CHAP and cause the commands to fail.