def METHOD_NAME():
    from copy import deepcopy
    from muse import examples
    from muse.sectors.subsector import Subsector, aggregate_enduses
    model_list = ["default", "medium"]
    sector_list = ["residential", "power", "gas"]
    for model in model_list:
        mca = examples.model(model)
        for sname in sector_list:
            agents = list(examples.sector(sname, model).agents)
            sector = next((sector for sector in mca.sectors if sector.name == sname))
            technologies = sector.technologies
            commodities = aggregate_enduses(
                (agent.assets for agent in agents), technologies
            )
            market = mca.market.sel(
                commodity=technologies.commodity, region=technologies.region
            ).interp(year=[2020, 2025])
            subsector = Subsector(agents, commodities)
            initial_agents = deepcopy(agents)
            assert {agent.year for agent in agents} == {int(market.year.min())}
            assert subsector.aggregate_lp(technologies, market) is None
            assert {agent.year for agent in agents} == {int(market.year.min() + 5)}
            for initial, final in zip(initial_agents, agents):
                assert initial.assets.sum() != final.assets.sum()