Пример #1
0
    def _run(self, points, resample_step):
        """
        This run method is for running simulations, which is the in-common part of resampling.
        :param points: The points to run simulations at.
        :return: The Experiment object for these simulations
        """
        # create a sweep where each point is a separate sim
        if not self.calib_manager:
            raise Exception(
                'calibration manager has not set for resampler. Cannot generate simulations.'
            )

        point_dicts = [point.to_value_dict() for point in points]

        # ck4, the number of replicates must be 1 for HIV for now; the general solution should allow a user-selected
        # replicate count, so long as their likelihood analyzer can handle > 1 replicates.
        exp_builder = self.calib_manager.exp_builder_func(point_dicts,
                                                          n_replicates=1)

        # Create an experiment manager
        manager = ExperimentManagerFactory.from_cb(
            self.calib_manager.config_builder)
        exp_name = self.calib_manager.name + '_resample_step_%d' % resample_step

        manager.run_simulations(exp_name=exp_name,
                                blocking=True,
                                exp_builder=exp_builder)

        return manager
    def test_verify_asset_collection_id_and_tags_added_to_experiment(self):
        """
        Makes sure the individual asset collection ids are stored as tags on an experiment and that
        the 'master' asset collection id (id for all asset files together in one collection) is stored properly
        on the simulations as well.
        """
        expected_asset_collection = 'e05d3535-dab8-e711-80c3-f0921c167860'  # master collection

        run_sim_args = {'exp_name': 'AssetCollectionTestSim'}
        exp_manager = ExperimentManagerFactory.from_cb(
            config_builder=self.config_builder)
        exp_manager.run_simulations(**run_sim_args)

        # now query COMPS for this experiment and retrieve/verify tags
        sim = exp_manager.comps_experiment.get_simulations(
            query_criteria=COMPSQueryCriteria().select_children(
                children=['tags', 'configuration']))[0]
        tags = sim.tags
        for asset_type in SimulationAssets.COLLECTION_TYPES:
            if asset_type == SimulationAssets.PYTHON: continue
            tag = "%s_collection_id" % asset_type
            self.assertTrue(
                exp_manager.assets.collections.get(asset_type, None)
                is not None)
            self.assertTrue(tags.get(tag, None) is not None)

        # verify the asset_collection_id was added properly
        asset_collection_id = sim.configuration.asset_collection_id
        self.assertEqual(str(asset_collection_id), expected_asset_collection)
            else:
                values = [
                    0.4 + 0.59 * math.sqrt(random.uniform(0, 1)),
                    0.4 + 0.59 * math.sqrt(random.uniform(0, 1)), SIACov[ind],
                    random.randint(1, 1e6), Migration[ind],
                    RuralMultiplier[ind], UrbanMultiplier[ind], MCV1Days[ind],
                    mAbProfile[ind], Dropout[ind], MCV2Days[ind],
                    BirthRateScale[ind], basePop, 3.0
                ]
            mod_fns.append(ModFn(sample_point_fn, names, values))

        builder = ModBuilder.from_combos(mod_fns)

        # Name the experiment
        exp_name = 'Measles RI targets'
        exp_manager = ExperimentManagerFactory.from_cb(cb)
        # suite_id = exp_manager.create_suite("My experiment - Iteration 0")

        run_sim_args = {
            'config_builder': cb,
            'exp_name': exp_name,
            'exp_builder': builder
        }

        exp_manager.experiment_tags = {}
        for name, value in zip(names, values):
            if name not in [
                    'META_Vaccination_Threshold', 'META_Fraction_Meeting',
                    'Run_Number'
            ]:
                exp_manager.experiment_tags[name] = value
########################
# other configurations
########################

# If the base collection containing CMS exists, use it
# If not, use the local
if SetupParser.default_block == "HPC":
    try:
        cb.set_collection_id('CMS 0.82 Pre-release')
    except SimulationAssets.InvalidCollection:
        cb.set_experiment_executable('inputs/compartments/compartments.exe')
        cb.set_dll_root('inputs/compartments')
else:
    cb.set_experiment_executable('inputs/compartments/compartments.exe')
    cb.set_dll_root('inputs/compartments')

run_sim_args = {"config_builder": cb, "exp_name": "First Default CMS run"}

if __name__ == "__main__":
    SetupParser.init()
    em = ExperimentManagerFactory.from_cb(run_sim_args["config_builder"])
    em.run_simulations(exp_name=run_sim_args["exp_name"])

    # Wait for the simulation to complete
    em.wait_for_finished(verbose=True)

    # Analyze
    am = AnalyzeManager(exp_list='latest')
    am.add_analyzer(SimpleCMSAnalyzer())
    am.analyze()
Пример #5
0
from dtk.utils.core.DTKConfigBuilder import DTKConfigBuilder
from dtk.vector.study_sites import configure_site
from simtools.ExperimentManager.ExperimentManagerFactory import ExperimentManagerFactory
from simtools.SetupParser import SetupParser
from dtk.interventions.outbreakindividualdengue import add_OutbreakIndividualDengue

# This block will be used unless overridden on the command-line
SetupParser.default_block = 'HPC'

cb = DTKConfigBuilder.from_defaults('DENGUE_SIM')
configure_site(cb, 'Puerto_Rico')
cb.campaign["Campaign_Name"] = "Campaign - Outbreak"
add_OutbreakIndividualDengue(cb, 100, {'max': 1.725, 'min': 0}, 'Strain_1', [])
add_OutbreakIndividualDengue(cb, 5000, {}, 'Strain_2', [])
add_OutbreakIndividualDengue(cb, 5000, {}, 'Strain_3', [])
add_OutbreakIndividualDengue(cb, 5000, {}, 'Strain_4', [])

# cb.set_param('Simulation_Duration', 30*365)

run_sim_args = {
    'exp_name': 'ExampleSim',
    'config_builder': cb
}


if __name__ == "__main__":
    SetupParser.init()
    exp_manager = ExperimentManagerFactory.from_cb(config_builder=cb)
    exp_manager.run_simulations(**run_sim_args)
                ModFn(
                    DTKConfigBuilder.update_params, {
                        "Run_Number": run_num,
                        "x_Temporary_Larval_Habitat": 10**hab_exp
                    }),
            ] for run_num in range(10)
             for hab_exp in np.concatenate((np.arange(-3.75, -2, 0.25),
                                            np.arange(-2, 2.25, 0.1)))])

    run_sim_args = {
        "config_builder": cb,
        "exp_name": sweep_name,
        "exp_builder": builder
    }

    em = ExperimentManagerFactory.from_cb(cb)
    em.run_simulations(**run_sim_args)

    em.wait_for_finished(verbose=True)
    assert (em.succeeded())

    analyzer = PfPRAnalyzer(expt_name=sweep_name,
                            report_names=sites["name"].tolist(),
                            sweep_variables=[
                                "Run_Number", "x_Temporary_Larval_Habitat",
                                "intervention", "intervention_coverage"
                            ])

    am = AnalyzeManager(em.experiment, analyzers=analyzer)
    am.analyze()