API Reference

Classes

Core classes

CapacitySchedule: Apply a repeating availability schedule to one resource pool.
WarmUpAuditor: Warm-up auditor - records cumulative mean results at intervals.
SimConfig: Configuration for a simulation run.
Dispatcher: Allocate ambulances and permits to waiting patients.
EmpiricalRunner: Run replications using empirical process time distributions.
FitDist: Fit distributions using sim-tools and compare samples to real data.
Model: Discrete-event simulation model for ambulance responses.
Patient: Represents a patient who has called 999.
Results: Simulation output for a single model run.
UtilisationCalculator: Compute time-weighted ambulance utilisation from an event log.
Runner: Run the simulation for one or more replications.

Methods for the CapacitySchedule class

CapacitySchedule.validate_schedule(): Validate the capacity schedule.
CapacitySchedule.run(): Apply the capacity schedule repeatedly.
CapacitySchedule.apply_target(): Try to reach capacity target until the specified deadline.
CapacitySchedule.return_units(): Return units to the resource pool.
CapacitySchedule.remove_units(): Remove available units until the target or deadline is reached.
CapacitySchedule.record_change(): Record a single change in capacity.
CapacitySchedule.assert_resource_invariants(): Check that resource counting is consistent.

Data-holding classes

Public functions

plot_warm_up(): Plot warm-up trajectories for one metric and response category.
run_warm_up_audit(): Run warm-up audit for one or more replications (can run in parallel).
convert_keys_to_int(): Convert dictionary keys to int.
convert_resource_hours_to_ambulances(): Convert resource hours per week to a fixed number of ambulances.
resolve_dict(): Return a dictionary unchanged, or load one from a JSON file path.
build_empirical_config(): Build registry configuration for empirical time distributions.
build_arrival_config(): Determine arrival parameters and create config dict.
fit_config(): Fit distributions for each metric and category from raw time data.
get_dist_params(): Compute sim-tools parameter dict for a given distribution.
plot_metric_kde(): Plot KDE curve by category (C1-C4).
plot_observed_fitted(): Plot overlaid comparison of observed vs fitted data.
plot_capacity_vs_util(): Plot capacity v.s., utilisation during the model run.

Module-level constants and data