MetaWards.extractors API Detail

Functions

extract_custom(custom_function, stage, **kwargs)

This returns the default list of 'output_XXX' functions that are called in sequence for each iteration of the model run.

extract_default(stage, **kwargs)

This returns the default list of 'output_XXX' functions that are called in sequence for each iteration of the model run.

extract_large(**kwargs)

This extractor extracts the default files, plus the "large" files, e.g.

extract_none(**kwargs)

This extractor extracts nothing - meaning that no output will be written

extract_small(**kwargs)

This extractor only extracts the 'small' default files, e.g.

output_basic([nthreads])

This will write basic trajectory data to the output files.

output_core(network, population, workspace, ...)

This is the core output function that must be called every iteration as it is responsible for accumulating the core data each day, which is used to report a summary to the main output file.

output_core_omp(network, population, ...)

This is the core output function that must be called every iteration as it is responsible for accumulating the core data each day, which is used to report a summary to the main output file.

output_core_serial(network, population, ...)

This is the core output function that must be called every iteration as it is responsible for accumulating the core data each day, which is used to report a summary to the main output file.

output_incidence([nthreads])

This will incidence of infection for each ward for each timestep.

output_dispersal(nthreads, **kwargs)

This will calculate and output the geographic dispersal of the outbreak

output_prevalence([nthreads])

This will output the number of infections per ward per timestep as a (large) 2D matrix

output_trajectory(network, output_dir, ...)

Call in the "finalise" stage to output the population trajectory to the 'trajectory.csv' file

output_wards_trajectory([nthreads])

This will output the complete trajectory for S, E, I and R for each of the wards in the model.

setup_core([nthreads])

This is the setup function that corresponds with output_core().