MetaWards.extractors API Detail¶
Functions¶
extract_core(nthreads[, setup, auto_output_core]) |
This returns the default list of ‘output_XXX’ functions that are called in sequence at the end of each iteration of the model run. |
extract_custom(custom_function[, setup]) |
This returns the default list of ‘output_XXX’ functions that are called in sequence to extract data after each iteration of the model run. |
extract_default([setup]) |
This returns the default list of ‘output_XXX’ functions that are called in sequence for each iteration of the model run. |
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. |
extractor_needs_setup(extractor) |
Return whether or not the passed extractor function has a “setup” argument, and thus needs to be setup before it can be used |
output_basic(network, population, …) |
This will write basic trajectory data to the output files. |
output_core(nthreads, **kwargs) |
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(population, output_dir, …) |
This will incidence of infection for each ward for each timestep. |
output_dispersal(network, population, …) |
This will calculate and output the geographic dispersal of the outbreak |
output_prevalence(population, output_dir, …) |
This will output the number of infections per ward per timestep as a (large) 2D matrix |
setup_core(network, nthreads, **kwargs) |
This is the setup function that corresponds with output_core(). |