def execute(self):
"""Loop over realizations (logic tree samples), split the geometry of
interest into blocks of sites, and distribute Celery tasks to carry out
the UHS computation.
"""
job_ctxt = self.job_ctxt
all_sites = job_ctxt.sites_to_compute()
site_block_size = config.hazard_block_size()
job_profile = job_ctxt.oq_job_profile
src_model_rnd = random.Random(job_profile.source_model_lt_random_seed)
gmpe_rnd = random.Random(job_profile.gmpe_lt_random_seed)
for rlz in xrange(job_ctxt.oq_job_profile.realizations):
# Sample the gmpe and source models:
general.store_source_model(
job_ctxt.job_id, src_model_rnd.getrandbits(32),
job_ctxt.params, self.lt_processor)
general.store_gmpe_map(
job_ctxt.job_id, gmpe_rnd.getrandbits(32), self.lt_processor)
for site_block in block_splitter(all_sites, site_block_size):
tf_args = dict(job_id=job_ctxt.job_id, realization=rlz)
num_tasks_completed = completed_task_count(job_ctxt.job_id)
ath_args = dict(job_id=job_ctxt.job_id,
num_tasks=len(site_block),
start_count=num_tasks_completed)
utils_tasks.distribute(
compute_uhs_task, ('site', site_block), tf_args=tf_args,
ath=uhs_task_handler, ath_args=ath_args)
def execute(self, kvs_keys_purged=None): # pylint: disable=W0221
"""
Trigger the calculation and serialization of hazard curves, mean hazard
curves/maps and quantile curves.
:param kvs_keys_purged: a list only passed by tests who check the
kvs keys used/purged in the course of the job.
:returns: the keys used in the course of the calculation (for the sake
of testability).
"""
sites = self.job_ctxt.sites_to_compute()
realizations = self.job_ctxt["NUMBER_OF_LOGIC_TREE_SAMPLES"]
LOG.info("Going to run classical PSHA hazard for %s realizations "
"and %s sites" % (realizations, len(sites)))
stats.pk_set(self.job_ctxt.job_id, "hcls_sites", len(sites))
stats.pk_set(self.job_ctxt.job_id, "hcls_realizations", realizations)
block_size = config.hazard_block_size()
stats.pk_set(self.job_ctxt.job_id, "block_size", block_size)
blocks = range(0, len(sites), block_size)
stats.pk_set(self.job_ctxt.job_id, "blocks", len(blocks))
stats.pk_set(self.job_ctxt.job_id, "cblock", 0)
for start in blocks:
stats.pk_inc(self.job_ctxt.job_id, "cblock")
end = start + block_size
data = sites[start:end]
LOG.debug("> curves!")
self.do_curves(
data,
realizations,
serializer=self.serialize_hazard_curve_of_realization)
LOG.debug("> means!")
# mean curves
self.do_means(data,
realizations,
curve_serializer=self.serialize_mean_hazard_curves,
map_func=general.compute_mean_hazard_maps,
map_serializer=self.serialize_mean_hazard_map)
LOG.debug("> quantiles!")
# quantile curves
quantiles = self.quantile_levels
self.do_quantiles(
data,
realizations,
quantiles,
curve_serializer=self.serialize_quantile_hazard_curves,
map_func=general.compute_quantile_hazard_maps,
map_serializer=self.serialize_quantile_hazard_map)
# Done with this block, purge intermediate results from kvs.
release_data_from_kvs(self.job_ctxt.job_id, data, realizations,
quantiles, self.poes_hazard_maps,
kvs_keys_purged)
def test_not_configured_default_overriden(self):
"""
The hazard block size was not set in openquake.cfg, the default
is specified by the caller is returned.
"""
with patch("openquake.utils.config.get") as mget:
mget.return_value = None
self.assertEqual(333, config.hazard_block_size(333))
def test_not_configured(self):
"""
The hazard block size was not set in openquake.cfg, the default
is returned.
"""
with patch("openquake.utils.config.get") as mget:
mget.return_value = None
self.assertEqual(8192, config.hazard_block_size())
def test_not_configured_default_overriden(self):
"""
The hazard block size was not set in openquake.cfg, the default
is specified by the caller is returned.
"""
with patch("openquake.utils.config.get") as mget:
mget.return_value = None
self.assertEqual(333, config.hazard_block_size(333))
def test_not_configured(self):
"""
The hazard block size was not set in openquake.cfg, the default
is returned.
"""
with patch("openquake.utils.config.get") as mget:
mget.return_value = None
self.assertEqual(8192, config.hazard_block_size())
def execute(self, kvs_keys_purged=None): # pylint: disable=W0221
"""
Trigger the calculation and serialization of hazard curves, mean hazard
curves/maps and quantile curves.
:param kvs_keys_purged: a list only passed by tests who check the
kvs keys used/purged in the course of the job.
:returns: the keys used in the course of the calculation (for the sake
of testability).
"""
sites = self.job_ctxt.sites_to_compute()
realizations = self.job_ctxt["NUMBER_OF_LOGIC_TREE_SAMPLES"]
LOG.info("Going to run classical PSHA hazard for %s realizations "
"and %s sites" % (realizations, len(sites)))
stats.pk_set(self.job_ctxt.job_id, "hcls_sites", len(sites))
stats.pk_set(self.job_ctxt.job_id, "hcls_realizations",
realizations)
block_size = config.hazard_block_size()
stats.pk_set(self.job_ctxt.job_id, "block_size", block_size)
blocks = range(0, len(sites), block_size)
stats.pk_set(self.job_ctxt.job_id, "blocks", len(blocks))
stats.pk_set(self.job_ctxt.job_id, "cblock", 0)
for start in blocks:
stats.pk_inc(self.job_ctxt.job_id, "cblock")
end = start + block_size
data = sites[start:end]
LOG.debug("> curves!")
self.do_curves(
data, realizations,
serializer=self.serialize_hazard_curve_of_realization)
LOG.debug("> means!")
# mean curves
self.do_means(
data, realizations,
curve_serializer=self.serialize_mean_hazard_curves,
map_func=general.compute_mean_hazard_maps,
map_serializer=self.serialize_mean_hazard_map)
LOG.debug("> quantiles!")
# quantile curves
quantiles = self.quantile_levels
self.do_quantiles(
data, realizations, quantiles,
curve_serializer=self.serialize_quantile_hazard_curves,
map_func=general.compute_quantile_hazard_maps,
map_serializer=self.serialize_quantile_hazard_map)
# Done with this block, purge intermediate results from kvs.
release_data_from_kvs(self.job_ctxt.job_id, data, realizations,
quantiles, self.poes_hazard_maps,
kvs_keys_purged)
def test_configured(self):
"""The hazard block size *was* configured in openquake.cfg"""
content = '''
[hazard]
block_size=33'''
local_path = self.touch(content=textwrap.dedent(content))
os.environ["OQ_LOCAL_CFG_PATH"] = local_path
config.Config().cfg.clear()
config.Config()._load_from_file()
self.assertEqual(33, config.hazard_block_size())
def execute(self, kvs_keys_purged=None):
"""
Trigger the calculation and serialization of hazard curves, mean hazard
curves/maps and quantile curves.
:param kvs_keys_purged: a list only passed by tests who check the
kvs keys used/purged in the course of the calculation.
:returns: the keys used in the course of the calculation (for the sake
of testability).
"""
sites = self.sites_to_compute()
realizations = self["NUMBER_OF_LOGIC_TREE_SAMPLES"]
LOG.info("Going to run classical PSHA hazard for %s realizations " "and %s sites" % (realizations, len(sites)))
stats.set_total(self.job_id, "classical:execute:sites", len(sites))
stats.set_total(self.job_id, "classical:execute:realizations", realizations)
block_size = config.hazard_block_size()
for start in xrange(0, len(sites), block_size):
end = start + block_size
data = sites[start:end]
self.do_curves(data, realizations, serializer=self.serialize_hazard_curve_of_realization)
# mean curves
self.do_means(
data,
realizations,
curve_serializer=self.serialize_mean_hazard_curves,
map_func=classical_psha.compute_mean_hazard_maps,
map_serializer=self.serialize_mean_hazard_map,
)
# quantile curves
quantiles = self.quantile_levels
self.do_quantiles(
data,
realizations,
quantiles,
curve_serializer=self.serialize_quantile_hazard_curves,
map_func=classical_psha.compute_quantile_hazard_maps,
map_serializer=self.serialize_quantile_hazard_map,
)
# Done with this chunk, purge intermediate results from kvs.
release_data_from_kvs(self.job_id, data, realizations, quantiles, self.poes_hazard_maps, kvs_keys_purged)
def execute(self):
"""Loop over realizations (logic tree samples), split the geometry of
interest into blocks of sites, and distribute Celery tasks to carry out
the UHS computation.
"""
job_ctxt = self.job_ctxt
all_sites = job_ctxt.sites_to_compute()
site_block_size = config.hazard_block_size()
job_profile = job_ctxt.oq_job_profile
self.initialize_pr_data(
sites=all_sites, realizations=job_ctxt.oq_job_profile.realizations)
src_model_rnd = random.Random(job_profile.source_model_lt_random_seed)
gmpe_rnd = random.Random(job_profile.gmpe_lt_random_seed)
for rlz in xrange(job_ctxt.oq_job_profile.realizations):
# Sample the gmpe and source models:
general.store_source_model(
job_ctxt.job_id, src_model_rnd.getrandbits(32),
job_ctxt.params, self.lt_processor)
general.store_gmpe_map(
job_ctxt.job_id, gmpe_rnd.getrandbits(32), self.lt_processor)
for site_block in block_splitter(all_sites, site_block_size):
tf_args = dict(job_id=job_ctxt.job_id, realization=rlz)
num_tasks_completed = completed_task_count(job_ctxt.job_id)
ath_args = dict(job_id=job_ctxt.job_id,
num_tasks=len(site_block),
start_count=num_tasks_completed)
utils_tasks.distribute(
compute_uhs_task, ('site', site_block), tf_args=tf_args,
ath=uhs_task_handler, ath_args=ath_args)
def test_configured(self):
"""The hazard block size *was* configured in openquake.cfg"""
with patch("openquake.utils.config.get") as mget:
mget.return_value = "33"
self.assertEqual(33, config.hazard_block_size())
def test_configured(self):
"""The hazard block size *was* configured in openquake.cfg"""
with patch("openquake.utils.config.get") as mget:
mget.return_value = "33"
self.assertEqual(33, config.hazard_block_size())
def test_not_configured_default_overriden(self):
"""
The hazard block size was not set in openquake.cfg, the default
is specified by the caller is returned.
"""
self.assertEqual(333, config.hazard_block_size(333))
def test_not_configured(self):
"""
The hazard block size was not set in openquake.cfg, the default
is returned.
"""
self.assertEqual(8192, config.hazard_block_size())
