- Code Refactoring: Model Output Valuation
- Team members: Sameer Ali, Ana Pereda
- Format: Refactoring a piece of existing code (Option 2)
To create an R script that simulates a population, disease incidence, mortality data and vaccine coverage and then automates validation of model valuation
30/11/22 Submit proposal/ discuss structure
3/12/22 Data Simulation
8/12/22 Code Refactoring
~ Time permitting ~ CLI / Graph output / Final validation report output
12/12/22 Present
14/12/22 Submit
If running a simulation, run the Simulation.R script which will autopopulate the test_files
If including preprocessed data, add the following files:
- mu.csv = Mortality Rate
- coverage.csv = Vaccine Coverage
- incidence.csv = Incidence
- population.csv = Population
- model_out.csv = Model Output
Within the "Data" file there is a simulation.R script that will create the necessary .csv for data validation.
With the simulation data prepared and correctly named, the validation can be executed by running the refact_script_validation.R script. This script will create a gui for inputting the model parameters, and calls functions.R for data reshapping. refact_script_validation.R will output a dataframe of the comparison between the expected and calculated models. This dataframe can be used for making plots, or can be otherwise outputted (not implemented).