Пример #1
0
    def execute(self):
        oq = self.oqparam
        self.set_param()
        self.offset = 0
        if oq.hazard_calculation_id:  # from ruptures
            self.datastore.parent = datastore.read(oq.hazard_calculation_id)
        elif hasattr(self, 'csm'):  # from sources
            self.build_events_from_sources()
            if (oq.ground_motion_fields is False
                    and oq.hazard_curves_from_gmfs is False):
                return {}
        elif 'rupture_model' not in oq.inputs:
            logging.warning(
                'There is no rupture_model, the calculator will just '
                'import data without performing any calculation')
            fake = logictree.FullLogicTree.fake()
            self.datastore['full_lt'] = fake  # needed to expose the outputs
            self.datastore['weights'] = [1.]
            return {}
        else:  # scenario
            self._read_scenario_ruptures()
            if (oq.ground_motion_fields is False
                    and oq.hazard_curves_from_gmfs is False):
                return {}

        if oq.ground_motion_fields:
            imts = oq.get_primary_imtls()
            nrups = len(self.datastore['ruptures'])
            base.create_gmf_data(self.datastore, imts, oq.get_sec_imts())
            self.datastore.create_dset('gmf_data/sigma_epsilon',
                                       sig_eps_dt(oq.imtls))
            self.datastore.create_dset('gmf_data/time_by_rup',
                                       time_dt, (nrups, ),
                                       fillvalue=None)

        # compute_gmfs in parallel
        nr = len(self.datastore['ruptures'])
        logging.info('Reading {:_d} ruptures'.format(nr))
        allargs = [(rgetter, self.param) for rgetter in gen_rupture_getters(
            self.datastore, oq.concurrent_tasks)]
        # reading the args is fast since we are not prefiltering the ruptures,
        # nor reading the geometries; using an iterator would cause the usual
        # damned h5py error, last seen on macos
        self.datastore.swmr_on()
        smap = parallel.Starmap(self.core_task.__func__,
                                allargs,
                                h5=self.datastore.hdf5)
        smap.monitor.save('srcfilter', self.srcfilter)
        acc = smap.reduce(self.agg_dicts, self.acc0())
        if 'gmf_data' not in self.datastore:
            return acc
        if oq.ground_motion_fields:
            with self.monitor('saving avg_gmf', measuremem=True):
                self.save_avg_gmf()
        return acc
Пример #2
0
    def execute(self):
        oq = self.oqparam
        self.set_param()
        self.offset = 0
        if oq.hazard_calculation_id:  # from ruptures
            self.datastore.parent = util.read(oq.hazard_calculation_id)
        elif hasattr(self, 'csm'):  # from sources
            self.build_events_from_sources()
            if (oq.ground_motion_fields is False
                    and oq.hazard_curves_from_gmfs is False):
                return {}
        elif 'rupture_model' not in oq.inputs:  # download ShakeMap
            logging.warning(
                'There is no rupture_model, the calculator will just '
                'import data without performing any calculation')
            fake = logictree.FullLogicTree.fake()
            self.datastore['full_lt'] = fake  # needed to expose the outputs
            return {}
        else:  # scenario
            self._read_scenario_ruptures()
            if (oq.ground_motion_fields is False
                    and oq.hazard_curves_from_gmfs is False):
                return {}
        if not oq.imtls:
            raise InvalidFile('There are no intensity measure types in %s' %
                              oq.inputs['job_ini'])
        N = len(self.sitecol.complete)
        if oq.ground_motion_fields:
            M = len(oq.imtls)
            nrups = len(self.datastore['ruptures'])
            base.create_gmf_data(self.datastore, M, self.param['sec_perils'])
            self.datastore.create_dset('gmf_data/sigma_epsilon',
                                       sig_eps_dt(oq.imtls))
            self.datastore.create_dset('gmf_data/events_by_sid', U32, (N, ))
            self.datastore.create_dset('gmf_data/time_by_rup',
                                       time_dt, (nrups, ),
                                       fillvalue=None)

        # compute_gmfs in parallel
        nr = len(self.datastore['ruptures'])
        self.datastore.swmr_on()
        logging.info('Reading {:_d} ruptures'.format(nr))
        iterargs = ((rgetter, self.param) for rgetter in gen_rupture_getters(
            self.datastore, oq.concurrent_tasks))
        smap = parallel.Starmap(self.core_task.__func__,
                                iterargs,
                                h5=self.datastore.hdf5)
        smap.monitor.save('srcfilter', self.srcfilter)
        acc = smap.reduce(self.agg_dicts, self.acc0())
        if 'gmf_data' not in self.datastore:
            return acc
        if oq.ground_motion_fields:
            eids = self.datastore['gmf_data/eid'][:]
            rel_events = numpy.unique(eids)
            e = len(rel_events)
            if e == 0:
                raise RuntimeError('No GMFs were generated, perhaps they were '
                                   'all below the minimum_intensity threshold')
            elif e < len(self.datastore['events']):
                self.datastore['relevant_events'] = rel_events
                logging.info('Stored %d relevant event IDs', e)
        return acc
Пример #3
0
    def execute(self):
        oq = self.oqparam
        dstore = self.datastore
        if oq.ground_motion_fields and oq.min_iml.sum() == 0:
            logging.warning('The GMFs are not filtered: '
                            'you may want to set a minimum_intensity')
        else:
            logging.info('minimum_intensity=%s', oq.minimum_intensity)
        self.offset = 0
        if oq.hazard_calculation_id:  # from ruptures
            dstore.parent = datastore.read(oq.hazard_calculation_id)
        elif hasattr(self, 'csm'):  # from sources
            self.build_events_from_sources()
            if (oq.ground_motion_fields is False
                    and oq.hazard_curves_from_gmfs is False):
                return {}
        elif 'rupture_model' not in oq.inputs:
            logging.warning(
                'There is no rupture_model, the calculator will just '
                'import data without performing any calculation')
            fake = logictree.FullLogicTree.fake()
            dstore['full_lt'] = fake  # needed to expose the outputs
            dstore['weights'] = [1.]
            return {}
        else:  # scenario
            self._read_scenario_ruptures()
            if (oq.ground_motion_fields is False
                    and oq.hazard_curves_from_gmfs is False):
                return {}

        if oq.ground_motion_fields:
            imts = oq.get_primary_imtls()
            nrups = len(dstore['ruptures'])
            base.create_gmf_data(dstore, imts, oq.get_sec_imts())
            dstore.create_dset('gmf_data/sigma_epsilon', sig_eps_dt(oq.imtls))
            dstore.create_dset('gmf_data/time_by_rup',
                               time_dt, (nrups, ),
                               fillvalue=None)

        # event_based in parallel
        nr = len(dstore['ruptures'])
        logging.info('Reading {:_d} ruptures'.format(nr))
        scenario = 'scenario' in oq.calculation_mode
        proxies = [
            RuptureProxy(rec, scenario) for rec in dstore['ruptures'][:]
        ]
        full_lt = self.datastore['full_lt']
        dstore.swmr_on()  # must come before the Starmap
        smap = parallel.Starmap.apply_split(
            self.core_task.__func__, (proxies, full_lt, oq, self.datastore),
            key=operator.itemgetter('trt_smr'),
            weight=operator.itemgetter('n_occ'),
            h5=dstore.hdf5,
            concurrent_tasks=oq.concurrent_tasks or 1,
            duration=oq.time_per_task,
            split_level=oq.split_level)
        acc = smap.reduce(self.agg_dicts, self.acc0())
        if 'gmf_data' not in dstore:
            return acc
        if oq.ground_motion_fields:
            with self.monitor('saving avg_gmf', measuremem=True):
                self.save_avg_gmf()
        return acc
Пример #4
0
    def execute(self):
        oq = self.oqparam
        self.set_param()
        self.offset = 0
        if oq.hazard_calculation_id:  # from ruptures
            self.datastore.parent = util.read(oq.hazard_calculation_id)
        elif hasattr(self, 'csm'):  # from sources
            self.build_events_from_sources()
            if (oq.ground_motion_fields is False
                    and oq.hazard_curves_from_gmfs is False):
                return {}
        elif 'rupture_model' not in oq.inputs:  # download ShakeMap
            logging.warning(
                'There is no rupture_model, the calculator will just '
                'import data without performing any calculation')
            fake = logictree.FullLogicTree.fake()
            self.datastore['full_lt'] = fake  # needed to expose the outputs
            return {}
        else:  # scenario
            self._read_scenario_ruptures()
            if (oq.ground_motion_fields is False
                    and oq.hazard_curves_from_gmfs is False):
                return {}
        N = len(self.sitecol.complete)
        if oq.ground_motion_fields:
            M = len(oq.get_primary_imtls())
            nrups = len(self.datastore['ruptures'])
            base.create_gmf_data(self.datastore, M, oq.get_sec_imts())
            self.datastore.create_dset('gmf_data/sigma_epsilon',
                                       sig_eps_dt(oq.imtls))
            self.datastore.create_dset('gmf_data/events_by_sid', U32, (N, ))
            self.datastore.create_dset('gmf_data/time_by_rup',
                                       time_dt, (nrups, ),
                                       fillvalue=None)

        # compute_gmfs in parallel
        nr = len(self.datastore['ruptures'])
        logging.info('Reading {:_d} ruptures'.format(nr))
        allargs = [(rgetter, self.param) for rgetter in gen_rupture_getters(
            self.datastore, oq.concurrent_tasks)]
        # reading the args is fast since we are not prefiltering the ruptures,
        # nor reading the geometries; using an iterator would cause the usual
        # damned h5py error, last seen on macos
        self.datastore.swmr_on()
        smap = parallel.Starmap(self.core_task.__func__,
                                allargs,
                                h5=self.datastore.hdf5)
        smap.monitor.save('srcfilter', self.srcfilter)
        acc = smap.reduce(self.agg_dicts, self.acc0())
        if 'gmf_data' not in self.datastore:
            return acc
        if oq.ground_motion_fields:
            with self.monitor('saving avg_gmf', measuremem=True):
                self.weights = self.datastore['weights'][:]
                self.rlzs = self.datastore['events']['rlz_id']
                self.num_events = numpy.bincount(self.rlzs)  # events by rlz
                avg_gmf = {
                    imt: numpy.zeros(self.N, F32)
                    for imt in oq.all_imts()
                }
                rel_events = self.save_avg_gmf(avg_gmf)
                self.datastore.create_dframe('avg_gmf', avg_gmf.items())
            e = len(rel_events)
            if e == 0:
                raise RuntimeError('No GMFs were generated, perhaps they were '
                                   'all below the minimum_intensity threshold')
            elif e < len(self.datastore['events']):
                self.datastore['relevant_events'] = rel_events
                logging.info('Stored %d relevant event IDs', e)
        return acc
    def run_calc(self):
        """
        Run a calculation and return results (reinvented from openquake.calculators.base)
        """

        with self.calculator._monitor:
            self.calculator._monitor.username = ''
            try:
                # Pre-execute setups
                self.calculator.pre_execute()

                #self.calculator.datastore.swmr_on()
                oq = self.calculator.oqparam
                dstore = self.calculator.datastore
                self.calculator.set_param()
                self.calculator.offset = 0

                # Source model
                print('self.__dict__ = ')
                print(self.calculator.__dict__)
                if oq.hazard_calculation_id:  # from ruptures
                    dstore.parent = self.calculator.datastore.read(
                        oq.hazard_calculation_id)
                elif hasattr(self.calculator, 'csm'):  # from sources
                    self.calculator_build_events_from_sources()
                    #self.calculator.build_events_from_sources()
                    if (oq.ground_motion_fields is False
                            and oq.hazard_curves_from_gmfs is False):
                        return {}
                elif 'rupture_model' not in oq.inputs:
                    logging.warning(
                        'There is no rupture_model, the calculator will just '
                        'import data without performing any calculation')
                    fake = logictree.FullLogicTree.fake()
                    dstore['full_lt'] = fake  # needed to expose the outputs
                    dstore['weights'] = [1.]
                    return {}
                else:  # scenario
                    self.calculator._read_scenario_ruptures()
                    if (oq.ground_motion_fields is False
                            and oq.hazard_curves_from_gmfs is False):
                        return {}

                # Intensity measure models
                if oq.ground_motion_fields:
                    imts = oq.get_primary_imtls()
                    nrups = len(dstore['ruptures'])
                    base.create_gmf_data(dstore, imts, oq.get_sec_imts())
                    dstore.create_dset('gmf_data/sigma_epsilon',
                                       getters.sig_eps_dt(oq.imtls))
                    dstore.create_dset('gmf_data/time_by_rup',
                                       getters.time_dt, (nrups, ),
                                       fillvalue=None)

                # Prepare inputs for GmfGetter
                nr = len(dstore['ruptures'])
                logging.info('Reading {:_d} ruptures'.format(nr))
                rgetters = getters.get_rupture_getters(
                    dstore,
                    oq.concurrent_tasks * 1.25,
                    srcfilter=self.calculator.srcfilter)
                args = [(rgetter, self.calculator.param)
                        for rgetter in rgetters]
                mon = performance.Monitor()
                mon.version = version
                mon.config = config
                rcvr = 'tcp://%s:%s' % (config.dbserver.listen,
                                        config.dbserver.receiver_ports)
                skt = zeromq.Socket(rcvr, zeromq.zmq.PULL, 'bind').__enter__()
                mon.backurl = 'tcp://%s:%s' % (config.dbserver.host, skt.port)
                mon = mon.new(operation='total ' +
                              self.calculator.core_task.__func__.__name__,
                              measuremem=True)
                mon.weight = getattr(args[0], 'weight',
                                     1.)  # used in task_info
                mon.task_no = 1  # initialize the task number
                args += (mon, )

                self.args = args
                self.mon = mon
                self.dstore = dstore

            finally:
                print('FetchOpenQuake: OpenQuake Hazard Calculator defined.')