def _run(self):
classical_psha.compute_mean_hazard_maps(self.engine)
def _run(self):
classical_psha.compute_mean_hazard_maps(self.engine)
def _run(self, poes, sites=None):
if sites is None:
sites = [self.site]
classical_psha.compute_mean_hazard_maps(self.job.job_id, sites,
self.imls, poes)
def execute(self):
results = []
source_model_generator = random.Random()
source_model_generator.seed(
self.params.get('SOURCE_MODEL_LT_RANDOM_SEED', None))
gmpe_generator = random.Random()
gmpe_generator.seed(self.params.get('GMPE_LT_RANDOM_SEED', None))
realizations = int(self.params['NUMBER_OF_LOGIC_TREE_SAMPLES'])
site_list = self.sites_for_region()
LOG.info('Going to run classical PSHA hazard for %s realizations '\
'and %s sites' % (realizations, len(site_list)))
for realization in xrange(0, realizations):
LOG.info('Calculating hazard curves for realization %s'
% realization)
pending_tasks = []
results_per_realization = []
self.store_source_model(source_model_generator.getrandbits(32))
self.store_gmpe_map(source_model_generator.getrandbits(32))
pending_tasks.append(
tasks.compute_hazard_curve.delay(self.id, site_list,
realization))
for task in pending_tasks:
task.wait()
if task.status != 'SUCCESS':
raise Exception(task.result)
results_per_realization.extend(task.result)
self.write_hazardcurve_file(results_per_realization)
results.extend(results_per_realization)
del results_per_realization
# compute and serialize mean and quantile hazard curves
pending_tasks_mean = []
results_mean = []
pending_tasks_quantile = []
results_quantile = []
LOG.info('Computing mean and quantile hazard curves')
pending_tasks_quantile.append(
tasks.compute_quantile_curves.delay(self.id, site_list))
if self.params['COMPUTE_MEAN_HAZARD_CURVE'].lower() == 'true':
pending_tasks_mean.append(
tasks.compute_mean_curves.delay(self.id, site_list))
for task in pending_tasks_mean:
task.wait()
if task.status != 'SUCCESS':
raise Exception(task.result)
results_mean.extend(task.result)
for task in pending_tasks_quantile:
task.wait()
if task.status != 'SUCCESS':
raise Exception(task.result)
results_quantile.extend(task.result)
if self.params['COMPUTE_MEAN_HAZARD_CURVE'].lower() == 'true':
LOG.info('Serializing mean hazard curves')
self.write_hazardcurve_file(results_mean)
del results_mean
if self.params[classical_psha.POES_PARAM_NAME] != '':
LOG.info('Computing/serializing mean hazard maps')
results_mean_maps = classical_psha.compute_mean_hazard_maps(
self)
self.write_hazardmap_file(results_mean_maps)
del results_mean_maps
# collect hazard curve keys per quantile value
quantile_values = _collect_curve_keys_per_quantile(results_quantile)
LOG.info('Serializing quantile hazard curves for %s quantile values' \
% len(quantile_values))
for key_list in quantile_values.values():
self.write_hazardcurve_file(key_list)
# compute quantile hazard maps
if (self.params[classical_psha.POES_PARAM_NAME] != '' and
len(quantile_values) > 0):
LOG.info('Computing quantile hazard maps')
results_quantile_maps = \
classical_psha.compute_quantile_hazard_maps(self)
quantile_values = _collect_map_keys_per_quantile(
results_quantile_maps)
LOG.info(
"Serializing quantile hazard maps for %s quantile values"
% len(quantile_values))
for key_list in quantile_values.values():
self.write_hazardmap_file(key_list)
return results
def execute(self):
results = []
source_model_generator = random.Random()
source_model_generator.seed(
self.params.get('SOURCE_MODEL_LT_RANDOM_SEED', None))
gmpe_generator = random.Random()
gmpe_generator.seed(self.params.get('GMPE_LT_RANDOM_SEED', None))
realizations = int(self.params['NUMBER_OF_LOGIC_TREE_SAMPLES'])
site_list = self.sites_for_region()
LOG.info('Going to run classical PSHA hazard for %s realizations '\
'and %s sites' % (realizations, len(site_list)))
for realization in xrange(0, realizations):
LOG.info('Calculating hazard curves for realization %s' %
realization)
pending_tasks = []
results_per_realization = []
self.store_source_model(source_model_generator.getrandbits(32))
self.store_gmpe_map(source_model_generator.getrandbits(32))
pending_tasks.append(
tasks.compute_hazard_curve.delay(self.id, site_list,
realization))
for task in pending_tasks:
task.wait()
if task.status != 'SUCCESS':
raise Exception(task.result)
results_per_realization.extend(task.result)
self.write_hazardcurve_file(results_per_realization)
results.extend(results_per_realization)
del results_per_realization
# compute and serialize mean and quantile hazard curves
pending_tasks_mean = []
results_mean = []
pending_tasks_quantile = []
results_quantile = []
LOG.info('Computing mean and quantile hazard curves')
pending_tasks_quantile.append(
tasks.compute_quantile_curves.delay(self.id, site_list))
if self.params['COMPUTE_MEAN_HAZARD_CURVE'].lower() == 'true':
pending_tasks_mean.append(
tasks.compute_mean_curves.delay(self.id, site_list))
for task in pending_tasks_mean:
task.wait()
if task.status != 'SUCCESS':
raise Exception(task.result)
results_mean.extend(task.result)
for task in pending_tasks_quantile:
task.wait()
if task.status != 'SUCCESS':
raise Exception(task.result)
results_quantile.extend(task.result)
if self.params['COMPUTE_MEAN_HAZARD_CURVE'].lower() == 'true':
LOG.info('Serializing mean hazard curves')
self.write_hazardcurve_file(results_mean)
del results_mean
if self.params[classical_psha.POES_PARAM_NAME] != '':
LOG.info('Computing/serializing mean hazard maps')
results_mean_maps = classical_psha.compute_mean_hazard_maps(
self)
self.write_hazardmap_file(results_mean_maps)
del results_mean_maps
# collect hazard curve keys per quantile value
quantile_values = _collect_curve_keys_per_quantile(results_quantile)
LOG.info('Serializing quantile hazard curves for %s quantile values' \
% len(quantile_values))
for key_list in quantile_values.values():
self.write_hazardcurve_file(key_list)
# compute quantile hazard maps
if (self.params[classical_psha.POES_PARAM_NAME] != ''
and len(quantile_values) > 0):
LOG.info('Computing quantile hazard maps')
results_quantile_maps = \
classical_psha.compute_quantile_hazard_maps(self)
quantile_values = _collect_map_keys_per_quantile(
results_quantile_maps)
LOG.info(
"Serializing quantile hazard maps for %s quantile values" %
len(quantile_values))
for key_list in quantile_values.values():
self.write_hazardmap_file(key_list)
return results
