import os
from soil import simulation

NUM_AGENTS = int(os.environ.get('NUM_AGENTS', 100))
NUM_ITERS = int(os.environ.get('NUM_ITERS', 10))
MAX_STEPS = int(os.environ.get('MAX_STEPS', 500))


def run_sim(model, **kwargs):
    from soil import Simulation
    opts = dict(model=model,
                dump=False,
                num_processes=1,
                parameters={'num_nodes': NUM_AGENTS,
                            "avg_node_degree": 3,
                            "initial_outbreak_size": 5,
                            "virus_spread_chance": 0.25,
                            "virus_check_frequency": 0.25,
                            "recovery_chance": 0.3,
                            "gain_resistance_chance": 0.1,
                            },
                max_steps=MAX_STEPS,
                iterations=NUM_ITERS)
    opts.update(kwargs)
    its = Simulation(**opts).run()
    assert len(its) == NUM_ITERS

    if not simulation._AVOID_RUNNING:
        ratios = list(it.resistant_susceptible_ratio for it in its)
        print("Max - Avg - Min ratio:", max(ratios), sum(ratios)/len(ratios), min(ratios))
        infected = list(it.number_infected for it in its)
        print("Max - Avg - Min infected:", max(infected), sum(infected)/len(infected), min(infected))

        assert all((it.schedule.steps == MAX_STEPS or it.number_infected == 0) for it in its)
        assert all(sum([it.number_susceptible,
                        it.number_infected,
                        it.number_resistant]) == NUM_AGENTS for it in its)
    return its