accepts_stage(func, None]) |
Return whether the passed function accepts the “stage” argument, meaning that it can do different things for different day stages |
add_lookup(network, nthreads) |
Add in metadata about the network that can be used to look up wards by name of location or region etc. |
add_wards_network_distance(network, nthreads) |
Reads the location data in network.parameters.input_files.position and adds those locations to all of the nodes in the passed network. |
aggregate_networks(network, profiler, nthreads) |
Aggregate all of the Susceptibles data from the demographic sub-networks into an overall total set of data that is stored in the overall network |
allocate_vaccination(network, output_dir) |
Allocate memory and open files needed to track vaccination |
assert_sane_network(network, profiler) |
This function runs through and checks that the passed network is sane. |
build_play_matrix(network, max_nodes, …) |
Build the play matrix for the passed network |
build_wards_network(params, profiler, …) |
Creates a network of wards using the information provided in the file specified in parameters.input_files.work. |
call_function_on_network(network, …) |
Call either ‘func’ or ‘parallel’ (depending on the number of threads, nthreads) on the passed Network, or on all demographic subnetworks |
clear_all_infections(infections, …) |
Clears all infections associated with a model run |
Console |
This is a singleton class that provides access to printing and logging functions to the console. |
create_int_array(size, default) |
Create a new array.array of the specified size. |
create_double_array(size, default) |
Create a new array.array of the specified size. |
create_string_array(size, unicode default) |
Create an array of python strings of size ‘size’, optionally initialised with ‘default’ |
create_thread_generators(rng, nthreads) |
Return a set of random number generators, one for each thread - these are seeded using the next ‘nthreads’ random numbers drawn from the passed generator |
delete_ran_binomial(rng) |
Delete the passed random number generator. |
fill_in_gaps(network, max_nodes) |
Fills in gaps in the network |
get_available_num_threads() |
Return the maximum number of threads that are recommended for this computer (the OMP_NUM_THREADS value) |
get_functions(stage, network, …[, results]) |
Return the functions that must be called for the specified stage of the day; |
get_initialise_functions(**kwargs) |
Convenience function that returns all of the functions that should be called during the initialisation step of the model (e.g. |
get_finalise_functions(trajectory, **kwargs) |
Convenience function that returns all of the functions that should be called during the finalisation step of the model (e.g. |
get_model_loop_functions(**kwargs) |
Convenience function that returns all of the functions that should be called during the model loop (i.e. |
get_min_max_distances(network, nthreads, …) |
Return the minimum and maximum distances recorded in the network |
get_number_of_processes(parallel_scheme, nprocs) |
This function works out how many processes have been set by the paralellisation system called ‘parallel_scheme’ |
how_many_vaccinated(vac) |
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initialise_infections(network) |
Initialise the data structure used to store the infections |
initialise_play_infections(network) |
Initialise the space used to store the play infections |
move_population_from_work_to_play(network, …) |
This function is not used or implemented, but is implied by the naming scheme… |
move_population_from_play_to_work(network, …) |
And Vice Versa From Work to Play The relevant parameters are network.params.play_to_work and network.params.work_to_play |
prepare_worker(params, demographics, …) |
Prepare a worker to receive work to run a model using the passed parameters. |
ran_binomial(rng, double p, n) |
Return a random number drawn from the binomial distribution [p,n] (see gsl_ran_binomial for documentation) |
ran_int(rng[, lower, upper]) |
Draw a random integer from [0,upper] inclusive |
ran_uniform(rng) |
Return a random double drawn from a uniform distribution between zero and one |
read_done_file(filename) |
This function reads the ‘done_file’ from ‘filename’ returning the list of seeded nodes |
recalculate_work_denominator_day(network, …) |
Recalculate the denominator_d for the wards (nodes) in the network for the normal links |
recalculate_play_denominator_day(network, …) |
Recalculate the denominator_d for the wards (nodes) in the network for the play links |
rescale_play_matrix(network, nthreads, profiler) |
Static Play At Home rescaling. |
resize_array(a, size, default) |
Resize the passed array to size ‘size’, adding ‘default’ if this will grow the array |
reset_everything(network, profiler, nthreads) |
Reset everything in the passed network so that it can be used for a new model run |
reset_play_matrix(network, nthreads) |
Resets the play entries in the passed Network. |
reset_play_susceptibles(network, nthreads) |
Resets the ward entries in the passed Network. |
reset_work_matrix(network[, nthreads]) |
Resets the work entries in the passed Network. |
run_model(network, …[, susceptibles, …]) |
Actually run the model… |
run_models(network, …[, debug_seeds]) |
Run all of the models on the passed Network that are described by the passed VariableSets |
run_worker(arguments) |
Ask the worker to run a model using the passed variables and options. |
safe_eval_number(s, int, str]) |
Convert ‘s’ to a number. |
scale_link_susceptibles(links, ratio) |
Scale the number of susceptibles in the passed Links by the passed scale ratio. |
scale_node_susceptibles(nodes, ratio, …) |
Scale the number of susceptibles in the passed Nodes by the passed scale ratios. |
seed_ran_binomial(seed) |
Seed and return the random binomial generator. |
string_to_ints(string, strings) |
Convert the passed string (or strings) containing integers (or ranges of integers) into a single sorted list of integers where no value is repeated |
vaccinate_same_id(network, risk_ra, sort_ra, …) |
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zero_workspace(workspace) |
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