This suite of codes predicts Ae. aegypti abundance in a given location, using time series for temperature, precipitation, and relative humidity as input. It is provided here as a Python library.
- Main program: MoLS
Arguments:- weather_pathname (string): directory where input file is located
- weatherfile (string): name of weather data file in csv format, without the .csv extension
- Format of input file (weatherfile.csv):
9 columns showing (1) year; (2) month; (3) day; (4) maximum temperature; (5) minimum temperature; (6) precipitation in mm; (7) average temperature; (8) precipitation in cm; (9) relative humidity.
Note: only columns 7-9 are used.
Template: see example in Weather subdirectory - Output: Excel file called weatherfile.xlsx, placed in the weather_pathname directory, containing the same information as the input file plus an additional column corresponding to predictions for the number of gravid female mosquitoes.
- Example: Run_Model.py reads Test_Data.csv and creates an Excel file called Test_Data.xlsx in the Weather directory.