metawards.utils.run_model¶
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metawards.utils.run_model(network: metawards._network.Network, infections: metawards._infections.Infections, rngs, s: int, output_dir: metawards._outputfiles.OutputFiles, population: metawards._population.Population = Population(initial=57104043, susceptibles=0, latent=0, total=0, recovereds=0, n_inf_wards=0, scale_uv=1.0, day=0, date=None), nsteps: int = None, profile: bool = True, profiler: metawards.utils._profiler.Profiler = None, nthreads: int = None, iterator=None, extractor=None)[source]¶ Actually run the model… Real work happens here. The model will run until completion or until ‘nsteps’ have been completed (whichever happens first)
- network: Network
- The network on which to run the model
- infections: Infections
- The space used to record the infections
- rngs: list
- The list of random number generators to use, one per thread
- population: Population
- The initial population at the start of the model outbreak. This is also used to set the date and day of the start of the model outbreak
- seed: int
- The random number seed used for this model run. If this is None then a very random random number seed will be used
- output_dir: OutputFiles
- The directory to write all of the output into
- nsteps: int
- The maximum number of steps to run in the outbreak. If None then run until the outbreak has finished
- profile: bool
- Whether or not to profile the model run and print out the results
- profiler: Profiler
- The profiler to use to profile - a new one is created if one isn’t passed
- s: int
- Index of the seeding parameter to use
- nthreads: int
- Number of threads over which to parallelise this model run
- iterator: function
- Function that will be used to dynamically get the functions that will be used at each iteration to advance the model. Any additional files or parameters needed by these functions should be included in the network.params object.
- extractor: function
- Function that will be used to dynamically get the functions that will be used at each iteration to extract data from the model run
- trajectory: Populations
- The trajectory of the population for every day of the model run