def test_get_available_gsims(self):
with mock.patch('os.listdir') as mock_listdir:
# returns some file names
mock_listdir.return_value = [
'__init__.py', 'base.py', 'atkinson_boore_2006.py',
'zhao_2006.py', 'README.txt']
with mock.patch('importlib.import_module', fake_import):
assert_equal(list(get_available_gsims().keys()),
['AtkinsonBoore2006', 'BooreAtkinson2008'])
assert_equal(list(get_available_gsims().values()),
[FakeModule.AtkinsonBoore2006,
FakeModule.BooreAtkinson2008])
def test_compute_gmf(self):
hc = mock.Mock()
hc.ground_motion_correlation_model = None
hc.truncation_level = None
hc.maximum_distance = 200.
gsim = get_available_gsims()['AkkarBommer2010']()
site_coll = make_site_coll(-78, 15.5, n=5)
params = dict(truncation_level=3,
correl_model=None,
maximum_distance=200)
trt = 'Subduction Interface'
rupture_ids = range(2)
ruptures = [FakeRupture(i, trt) for i in rupture_ids]
rupture_seeds = rupture_ids
gmv_dict, rup_dict = core._compute_gmf(
params, PGA(), {trt: gsim}, site_coll, ruptures, rupture_seeds)
expected_rups = {
0: rupture_ids,
1: rupture_ids,
2: rupture_ids,
3: rupture_ids,
4: rupture_ids,
}
expected_gmvs = {
0: [0.122149047040728, 0.0813899249039753],
1: [0.0541662667863476, 0.02136369236082],
2: [0.0772246502768338, 0.0226182956091826],
3: [0.166062666449449, 0.0164127269047494],
4: [0.133588538354143, 0.0529987707352876]
}
numpy.testing.assert_equal(rup_dict, expected_rups)
for i, gmvs in expected_gmvs.iteritems():
numpy.testing.assert_allclose(gmvs, expected_gmvs[i])
def info(calculators, gsims, views, exports, report, input_file=''):
"""
Give information. You can pass the name of an available calculator,
a job.ini file, or a zip archive with the input files.
"""
logging.basicConfig(level=logging.INFO)
if calculators:
for calc in sorted(base.calculators):
print(calc)
if gsims:
for gs in gsim.get_available_gsims():
print(gs)
if views:
for name in sorted(datastore.view):
print(name)
if exports:
dic = groupby(export, operator.itemgetter(0),
lambda group: [r[1] for r in group])
n = 0
for exporter, formats in dic.items():
print(exporter, formats)
n += len(formats)
print('There are %d exporters defined.' % n)
if input_file.endswith('.xml'):
print(nrml.read(input_file).to_str())
elif input_file.endswith(('.ini', '.zip')):
with Monitor('info', measuremem=True) as mon:
if report:
print('Generated', reportwriter.build_report(input_file))
else:
print_csm_info(input_file)
if mon.duration > 1:
print(mon)
elif input_file:
print("No info for '%s'" % input_file)
def check_gmpe_attributes(gmpe):
"""
Details
-------
Checks the attributes for gmpe.
Parameters
----------
gmpe : str
gmpe name for which attributes going to be checked
Returns
-------
None.
"""
from openquake.hazardlib import gsim
bgmpe = gsim.get_available_gsims()[gmpe]()
print('GMPE name: %s' % gmpe)
print('Supported tectonic region: %s' % bgmpe.DEFINED_FOR_TECTONIC_REGION_TYPE)
print(
'Supported standard deviation: %s' % ', '.join([std for std in bgmpe.DEFINED_FOR_STANDARD_DEVIATION_TYPES]))
print('Supported intensity measure: %s' % ', '.join(
[imt.__name__ for imt in bgmpe.DEFINED_FOR_INTENSITY_MEASURE_TYPES]))
print('Supported intensity measure component: %s' % bgmpe.DEFINED_FOR_INTENSITY_MEASURE_COMPONENT)
try:
sa_keys = list(bgmpe.COEFFS.sa_coeffs.keys())
print('Supported SA period range: %s' % ' - '.join([str(sa_keys[0].period), str(sa_keys[-1].period)]))
except:
pass
print('Required distance parameters: %s' % ', '.join([dist for dist in bgmpe.REQUIRES_DISTANCES]))
print('Required rupture parameters: %s' % ', '.join([rup for rup in bgmpe.REQUIRES_RUPTURE_PARAMETERS]))
print('Required site parameters: %s' % ', '.join([site for site in bgmpe.REQUIRES_SITES_PARAMETERS]))
def test_compute_gmf(self):
hc = mock.Mock()
hc.ground_motion_correlation_model = None
hc.truncation_level = None
hc.maximum_distance = 200.
gsim = get_available_gsims()['AkkarBommer2010']()
site_coll = make_site_coll(-78, 15.5, n=5)
params = dict(truncation_level=3,
correl_model=None,
maximum_distance=200)
trt = 'Subduction Interface'
rupture_ids = range(2)
ruptures = [FakeRupture(i, trt) for i in rupture_ids]
rupture_seeds = rupture_ids
gmv_dict, rup_dict = core._compute_gmf(
params, PGA(), {trt: gsim}, site_coll, ruptures, rupture_seeds)
expected_rups = {
0: rupture_ids,
1: rupture_ids,
2: rupture_ids,
3: rupture_ids,
4: rupture_ids,
}
expected_gmvs = {
0: [0.122149047040728, 0.0813899249039753],
1: [0.0541662667863476, 0.02136369236082],
2: [0.0772246502768338, 0.0226182956091826],
3: [0.166062666449449, 0.0164127269047494],
4: [0.133588538354143, 0.0529987707352876]
}
numpy.testing.assert_equal(rup_dict, expected_rups)
for i, gmvs in expected_gmvs.iteritems():
numpy.testing.assert_allclose(gmvs, expected_gmvs[i])
def _info(name, filtersources, weightsources):
if name in base.calculators:
print(textwrap.dedent(base.calculators[name].__doc__.strip()))
elif name == 'gsims':
for gs in gsim.get_available_gsims():
print(gs)
elif name.endswith('.xml'):
print(nrml.read(name).to_str())
elif name.endswith(('.ini', '.zip')):
oqparam = readinput.get_oqparam(name)
if 'exposure' in oqparam.inputs:
expo = readinput.get_exposure(oqparam)
sitecol, assets_by_site = readinput.get_sitecol_assets(
oqparam, expo)
elif filtersources or weightsources:
sitecol = readinput.get_site_collection(oqparam)
else:
sitecol = None
if 'source_model_logic_tree' in oqparam.inputs:
print('Reading the source model...')
if weightsources:
sp = source.SourceFilterWeighter
elif filtersources:
sp = source.SourceFilter
else:
sp = source.BaseSourceProcessor # do nothing
csm = readinput.get_composite_source_model(oqparam, sitecol, sp)
assoc = csm.get_rlzs_assoc()
dstore = datastore.Fake(vars(oqparam),
rlzs_assoc=assoc,
composite_source_model=csm,
sitecol=sitecol)
_print_info(dstore, filtersources, weightsources)
else:
print("No info for '%s'" % name)
def info(calculators, gsims, views, exports, report, input_file=''):
"""
Give information. You can pass the name of an available calculator,
a job.ini file, or a zip archive with the input files.
"""
logging.basicConfig(level=logging.INFO)
if calculators:
for calc in sorted(base.calculators):
print(calc)
if gsims:
for gs in gsim.get_available_gsims():
print(gs)
if views:
for name in sorted(datastore.view):
print(name)
if exports:
dic = groupby(export, operator.itemgetter(0),
lambda group: [r[1] for r in group])
n = 0
for exporter, formats in dic.items():
print(exporter, formats)
n += len(formats)
print('There are %d exporters defined.' % n)
if input_file.endswith('.xml'):
print(nrml.read(input_file).to_str())
elif input_file.endswith(('.ini', '.zip')):
with Monitor('info', measuremem=True) as mon:
if report:
print('Generated', reportwriter.build_report(input_file))
else:
print_csm_info(input_file)
if mon.duration > 1:
print(mon)
elif input_file:
print("No info for '%s'" % input_file)
def gsims(cls):
'''Returns a (new) dict of:
gsim_name (string) mapped to its gsim_class (class object)
defining all Ground Shaking Intensity Models defined in OpenQuake.
The dict is sorted by gsim_name
'''
return get_available_gsims() # already returns a new dict
def info(calculators, gsims, views, exports, extracts, report, input_file=''):
"""
Give information. You can pass the name of an available calculator,
a job.ini file, or a zip archive with the input files.
"""
logging.basicConfig(level=logging.INFO)
if calculators:
for calc in sorted(base.calculators):
print(calc)
if gsims:
for gs in gsim.get_available_gsims():
print(gs)
if views:
for name in sorted(view):
print(name)
if exports:
dic = groupby(export, operator.itemgetter(0),
lambda group: [r[1] for r in group])
n = 0
for exporter, formats in dic.items():
print(exporter, formats)
n += len(formats)
print('There are %d exporters defined.' % n)
if extracts:
for key in extract:
func = extract[key]
if hasattr(func, '__wrapped__'):
fm = FunctionMaker(func.__wrapped__)
else:
fm = FunctionMaker(func)
print('%s(%s)%s' % (fm.name, fm.signature, fm.doc))
if os.path.isdir(input_file) and report:
with Monitor('info', measuremem=True) as mon:
with mock.patch.object(logging.root, 'info'): # reduce logging
do_build_reports(input_file)
print(mon)
elif input_file.endswith('.xml'):
node = nrml.read(input_file)
if node[0].tag.endswith('sourceModel'):
if node['xmlns'].endswith('nrml/0.4'):
raise InvalidFile(
'%s is in NRML 0.4 format, please run the following '
'command:\noq upgrade_nrml %s' %
(input_file, os.path.dirname(input_file) or '.'))
print(source_model_info(node[0]))
else:
print(node.to_str())
elif input_file.endswith(('.ini', '.zip')):
with Monitor('info', measuremem=True) as mon:
if report:
print('Generated', reportwriter.build_report(input_file))
else:
print_csm_info(input_file)
if mon.duration > 1:
print(mon)
elif input_file:
print("No info for '%s'" % input_file)
def test_compute_gmf(self):
hc = mock.Mock()
hc.ground_motion_correlation_model = None
hc.truncation_level = None
hc.maximum_distance = 200.
trt = 'Subduction Interface'
gsim = get_available_gsims()['AkkarBommer2010']()
num_sites = 5
site_coll = make_site_coll(-78, 15.5, num_sites)
rup_id, rup_seed = 42, 44
rup = FakeRupture(rup_id, trt)
pga = PGA()
rlz = mock.Mock()
rlz.id = 1
calc = core.GmfCalculator(
[pga], [gsim], trt_model_id=1, truncation_level=3)
calc.calc_gmfs(site_coll, rup, [(rup.id, rup_seed)])
expected_rups = {
('AkkarBommer2010', 'PGA', 0): [rup_id],
('AkkarBommer2010', 'PGA', 1): [rup_id],
('AkkarBommer2010', 'PGA', 2): [rup_id],
('AkkarBommer2010', 'PGA', 3): [rup_id],
('AkkarBommer2010', 'PGA', 4): [rup_id],
}
expected_gmvs = {
('AkkarBommer2010', 'PGA', 0): [0.1027847118266612],
('AkkarBommer2010', 'PGA', 1): [0.02726361912605336],
('AkkarBommer2010', 'PGA', 2): [0.0862595971325641],
('AkkarBommer2010', 'PGA', 3): [0.04727148908077005],
('AkkarBommer2010', 'PGA', 4): [0.04750575818347277],
}
numpy.testing.assert_equal(calc.ruptures_per_site, expected_rups)
for i, gmvs in expected_gmvs.iteritems():
numpy.testing.assert_allclose(gmvs, expected_gmvs[i])
# 5 curves (one per each site) for 3 levels, 1 IMT
[(gname, [curves])] = calc.to_haz_curves(
site_coll.sids, dict(PGA=[0.03, 0.04, 0.05]),
invest_time=50., num_ses=10)
self.assertEqual(gname, 'AkkarBommer2010')
numpy.testing.assert_array_almost_equal(
curves,
[[0.09516258, 0.09516258, 0.09516258], # curve site1
[0.00000000, 0.00000000, 0.00000000], # curve site2
[0.09516258, 0.09516258, 0.09516258], # curve site3
[0.09516258, 0.09516258, 0.00000000], # curve site4
[0.09516258, 0.09516258, 0.00000000], # curve site5
])
def info(calculators, gsims, views, exports, report, input_file=''):
"""
Give information. You can pass the name of an available calculator,
a job.ini file, or a zip archive with the input files.
"""
logging.basicConfig(level=logging.INFO)
if calculators:
for calc in sorted(base.calculators):
print(calc)
if gsims:
for gs in gsim.get_available_gsims():
print(gs)
if views:
for name in sorted(view):
print(name)
if exports:
dic = groupby(export, operator.itemgetter(0),
lambda group: [r[1] for r in group])
n = 0
for exporter, formats in dic.items():
print(exporter, formats)
n += len(formats)
print('There are %d exporters defined.' % n)
if os.path.isdir(input_file) and report:
with Monitor('info', measuremem=True) as mon:
with mock.patch.object(logging.root, 'info'): # reduce logging
do_build_reports(input_file)
print(mon)
elif input_file.endswith('.xml'):
node = nrml.read(input_file)
if node[0].tag.endswith('sourceModel'):
assert node['xmlns'].endswith('nrml/0.5'), node['xmlns']
print(source_model_info(node[0]))
else:
print(node.to_str())
elif input_file.endswith(('.ini', '.zip')):
with Monitor('info', measuremem=True) as mon:
if report:
print('Generated', reportwriter.build_report(input_file))
else:
print_csm_info(input_file)
if mon.duration > 1:
print(mon)
elif input_file:
print("No info for '%s'" % input_file)
def _info(name, filtersources, weightsources):
if name in base.calculators:
print(textwrap.dedent(base.calculators[name].__doc__.strip()))
elif name == 'gsims':
for gs in gsim.get_available_gsims():
print(gs)
elif name.endswith('.xml'):
print(nrml.read(name).to_str())
elif name.endswith(('.ini', '.zip')):
oqparam = readinput.get_oqparam(name)
if 'exposure' in oqparam.inputs:
expo = readinput.get_exposure(oqparam)
sitecol, assets_by_site = readinput.get_sitecol_assets(
oqparam, expo)
elif filtersources or weightsources:
sitecol, assets_by_site = readinput.get_site_collection(
oqparam), []
else:
sitecol, assets_by_site = None, []
if 'source_model_logic_tree' in oqparam.inputs:
print('Reading the source model...')
if weightsources:
sp = source.SourceFilterWeighter
elif filtersources:
sp = source.SourceFilter
else:
sp = source.BaseSourceProcessor # do nothing
csm = readinput.get_composite_source_model(oqparam, sitecol, sp)
assoc = csm.get_rlzs_assoc()
dstore = datastore.Fake(vars(oqparam),
rlzs_assoc=assoc,
composite_source_model=csm,
sitecol=sitecol)
_print_info(dstore, filtersources, weightsources)
if len(assets_by_site):
assetcol = riskinput.build_asset_collection(assets_by_site)
dic = groupby(assetcol, operator.attrgetter('taxonomy'))
for taxo, num in dic.items():
print('taxonomy #%d, %d assets' % (taxo, num))
print('total assets = %d' % len(assetcol))
else:
print("No info for '%s'" % name)
def _info(name, filtersources, weightsources):
if name in base.calculators:
print(textwrap.dedent(base.calculators[name].__doc__.strip()))
elif name == 'gsims':
for gs in gsim.get_available_gsims():
print(gs)
elif name.endswith('.xml'):
print(nrml.read(name).to_str())
elif name.endswith(('.ini', '.zip')):
oqparam = readinput.get_oqparam(name)
if 'exposure' in oqparam.inputs:
expo = readinput.get_exposure(oqparam)
sitecol, assets_by_site = readinput.get_sitecol_assets(
oqparam, expo)
elif filtersources or weightsources:
sitecol, assets_by_site = readinput.get_site_collection(
oqparam), []
else:
sitecol, assets_by_site = None, []
if 'source_model_logic_tree' in oqparam.inputs:
print('Reading the source model...')
if weightsources:
sp = source.SourceFilterWeighter
elif filtersources:
sp = source.SourceFilter
else:
sp = source.BaseSourceProcessor # do nothing
csm = readinput.get_composite_source_model(oqparam, sitecol, sp)
assoc = csm.get_rlzs_assoc()
_print_info(
dict(rlzs_assoc=assoc, oqparam=oqparam,
composite_source_model=csm, sitecol=sitecol),
filtersources, weightsources)
if len(assets_by_site):
assetcol = riskinput.build_asset_collection(assets_by_site)
dic = groupby(assetcol, operator.attrgetter('taxonomy'))
for taxo, num in dic.items():
print('taxonomy #%d, %d assets' % (taxo, num))
print('total assets = %d' % len(assetcol))
else:
print("No info for '%s'" % name)
def test_compute_gmf(self):
hc = mock.Mock()
hc.ground_motion_correlation_model = None
hc.truncation_level = None
hc.maximum_distance = 200.
trt = 'Subduction Interface'
gsim = get_available_gsims()['AkkarBommer2010']()
num_sites = 5
site_coll = make_site_coll(-78, 15.5, num_sites)
params = dict(truncation_level=3,
correl_model=None,
maximum_distance=200,
num_sites=num_sites)
rup_id, rup_seed = 42, 44
rup = FakeRupture(rup_id, trt)
pga = PGA()
rlz = mock.Mock()
rlz.id = 1
coll = core.GmfCalculator(
params, [pga], [gsim], trt_model_id=1, task_no=0)
rdata = core.RuptureData(site_coll, rup, [(rup.id, rup_seed)])
coll.calc_gmfs([rdata])
expected_rups = {
('AkkarBommer2010', pga, 0): [rup_id],
('AkkarBommer2010', pga, 1): [rup_id],
('AkkarBommer2010', pga, 2): [rup_id],
('AkkarBommer2010', pga, 3): [rup_id],
('AkkarBommer2010', pga, 4): [rup_id],
}
expected_gmvs = {
('AkkarBommer2010', pga, 0): [0.1027847118266612],
('AkkarBommer2010', pga, 1): [0.02726361912605336],
('AkkarBommer2010', pga, 2): [0.0862595971325641],
('AkkarBommer2010', pga, 3): [0.04727148908077005],
('AkkarBommer2010', pga, 4): [0.04750575818347277],
}
numpy.testing.assert_equal(coll.ruptures_per_site, expected_rups)
for i, gmvs in expected_gmvs.iteritems():
numpy.testing.assert_allclose(gmvs, expected_gmvs[i])
def info(name, report=False):
"""
Give information. You can pass the name of an available calculator,
a job.ini file, or a zip archive with the input files.
"""
logging.basicConfig(level=logging.INFO)
if name in base.calculators:
print(textwrap.dedent(base.calculators[name].__doc__.strip()))
elif name == 'gsims':
for gs in gsim.get_available_gsims():
print(gs)
elif name.endswith('.xml'):
print(nrml.read(name).to_str())
elif name.endswith(('.ini', '.zip')):
with Monitor('info', measuremem=True) as mon:
if report:
print('Generated', reportwriter.build_report(name))
else:
print_csm_info(name)
if mon.duration > 1:
print(mon)
else:
print("No info for '%s'" % name)
def get_available_gmpes():
"""
Details
-------
Retrieves available ground motion prediction equations (gmpe) in OpenQuake.
Parameters
----------
None.
Returns
-------
gmpes : dict
Dictionary which contains available gmpes in openquake.
"""
from openquake.hazardlib import gsim
gmpes = {}
for name, gmpe in gsim.get_available_gsims().items():
gmpes[name] = gmpe
return gmpes
def info(name, report=False):
"""
Give information. You can pass the name of an available calculator,
a job.ini file, or a zip archive with the input files.
"""
logging.basicConfig(level=logging.INFO)
if name in base.calculators:
print(textwrap.dedent(base.calculators[name].__doc__.strip()))
elif name == 'gsims':
for gs in gsim.get_available_gsims():
print(gs)
elif name.endswith('.xml'):
print(nrml.read(name).to_str())
elif name.endswith(('.ini', '.zip')):
with Monitor('info', measuremem=True) as mon:
if report:
print('Generated', reportwriter.build_report(name))
else:
print_csm_info(name)
if mon.duration > 1:
print(mon)
else:
print("No info for '%s'" % name)
def _info(name, filtersources, weightsources):
if name in base.calculators:
print(textwrap.dedent(base.calculators[name].__doc__.strip()))
elif name == "gsims":
for gs in gsim.get_available_gsims():
print(gs)
elif name.endswith(".xml"):
print(nrml.read(name).to_str())
elif name.endswith((".ini", ".zip")):
oqparam = readinput.get_oqparam(name)
if "exposure" in oqparam.inputs:
expo = readinput.get_exposure(oqparam)
sitecol, assets_by_site = readinput.get_sitecol_assets(oqparam, expo)
elif filtersources or weightsources:
sitecol, assets_by_site = readinput.get_site_collection(oqparam), []
else:
sitecol, assets_by_site = None, []
if "source_model_logic_tree" in oqparam.inputs:
print("Reading the source model...")
if weightsources:
sp = source.SourceFilterWeighter
elif filtersources:
sp = source.SourceFilter
else:
sp = source.BaseSourceProcessor # do nothing
csm = readinput.get_composite_source_model(oqparam, sitecol, sp)
assoc = csm.get_rlzs_assoc()
dstore = datastore.Fake(vars(oqparam), rlzs_assoc=assoc, composite_source_model=csm, sitecol=sitecol)
_print_info(dstore, filtersources, weightsources)
if len(assets_by_site):
assetcol = riskinput.build_asset_collection(assets_by_site)
dic = groupby(assetcol, operator.attrgetter("taxonomy"))
for taxo, num in dic.items():
print("taxonomy #%d, %d assets" % (taxo, num))
print("total assets = %d" % len(assetcol))
else:
print("No info for '%s'" % name)
def _info(name, filtersources, weightsources):
if name in base.calculators:
print(textwrap.dedent(base.calculators[name].__doc__.strip()))
elif name == 'gsims':
for gs in gsim.get_available_gsims():
print(gs)
elif name.endswith('.xml'):
print(nrml.read(name).to_str())
elif name.endswith(('.ini', '.zip')):
oqparam = readinput.get_oqparam(name)
if 'exposure' in oqparam.inputs:
expo = readinput.get_exposure(oqparam)
sitecol, assets_by_site = readinput.get_sitecol_assets(
oqparam, expo)
elif filtersources or weightsources:
sitecol, assets_by_site = readinput.get_site_collection(
oqparam), []
else:
sitecol, assets_by_site = None, []
if 'source_model_logic_tree' in oqparam.inputs:
print('Reading the source model...')
if weightsources:
sp = source.SourceFilterWeighter
elif filtersources:
sp = source.SourceFilter
else:
sp = source.BaseSourceProcessor # do nothing
csm = readinput.get_composite_source_model(oqparam, sitecol, sp)
assoc = csm.get_rlzs_assoc()
_print_info(assoc, oqparam, csm, sitecol,
filtersources, weightsources)
if len(assets_by_site):
print('assets = %d' %
sum(len(assets) for assets in assets_by_site))
else:
print("No info for '%s'" % name)
from shapely import wkt
from openquake.hazardlib.geo.point import Point
from openquake.hazardlib.geo.surface import PlanarSurface
from openquake.hazardlib.geo.geodetic import geodetic_distance
from openquake.hazardlib.correlation import JB2009CorrelationModel
from openquake.hazardlib.site import Site, SiteCollection
from openquake.hazardlib.imt import from_string
from openquake.hazardlib.gsim import get_available_gsims
from openquake.hazardlib.gsim.base import ContextMaker
from openquake.hazardlib.sourceconverter import RuptureConverter
from openquake.hazardlib import nrml
from smtk.residuals.gmpe_residuals import Residuals
DEFAULT_CORRELATION = JB2009CorrelationModel(False)
GSIM_LIST = get_available_gsims()
def build_planar_surface(geometry):
"""
Builds the planar rupture surface from the openquake.nrmllib.models
instance
"""
# Read geometry from wkt
geom = wkt.loads(geometry.wkt)
top_left = Point(geom.xy[0][0],
geom.xy[1][0],
geometry.upper_seismo_depth)
top_right = Point(geom.xy[0][1],
geom.xy[1][1],
geometry.upper_seismo_depth)
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# OpenQuake is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>.
from openquake.hazardlib.gsim import get_available_gsims
from openquake.commonlib import valid
GSIMS = get_available_gsims()
GROUND_MOTION_CORRELATION_MODELS = ['JB2009', 'Jayaram-Baker 2009']
HAZARD_CALCULATORS = ['classical', 'disaggregation', 'event_based', 'scenario']
RISK_CALCULATORS = [
'classical_risk', 'event_based_risk', 'scenario_risk', 'classical_bcr',
'event_based_bcr', 'scenario_damage'
]
EXPERIMENTAL_CALCULATORS = ['event_based_fr']
CALCULATORS = HAZARD_CALCULATORS + RISK_CALCULATORS + EXPERIMENTAL_CALCULATORS
def main(what, report=False):
"""
Give information about the passed keyword or filename
"""
if os.environ.get('OQ_DISTRIBUTE') not in ('no', 'processpool'):
os.environ['OQ_DISTRIBUTE'] = 'processpool'
if what == 'calculators':
for calc in sorted(base.calculators):
print(calc)
elif what == 'gsims':
for gs in gsim.get_available_gsims():
print(gs)
elif what == 'portable_gsims':
for gs in gsim.get_portable_gsims():
print(gs)
elif what == 'imts':
for im in vars(imt).values():
if inspect.isfunction(im) and is_upper(im):
print(im.__name__)
elif what == 'views':
for name in sorted(view):
print(name)
elif what == 'exports':
dic = groupby(export, operator.itemgetter(0),
lambda group: [r[1] for r in group])
items = [(DISPLAY_NAME.get(exporter, '?'), exporter, formats)
for exporter, formats in dic.items()]
n = 0
for dispname, exporter, formats in sorted(items):
print(dispname, '"%s"' % exporter, formats)
n += len(formats)
print('There are %d exporters defined.' % n)
elif what == 'extracts':
for key in extract:
func = extract[key]
if hasattr(func, '__wrapped__'):
fm = FunctionMaker(func.__wrapped__)
elif hasattr(func, 'func'): # for partial objects
fm = FunctionMaker(func.func)
else:
fm = FunctionMaker(func)
print('%s(%s)%s' % (fm.name, fm.signature, fm.doc))
elif what == 'parameters':
docs = OqParam.docs()
names = set()
for val in vars(OqParam).values():
if hasattr(val, 'name'):
names.add(val.name)
params = sorted(names)
for param in params:
print(param)
print(docs[param])
elif what == 'mfds':
for cls in gen_subclasses(BaseMFD):
print(cls.__name__)
elif what == 'venv':
print(sys.prefix)
elif what == 'sources':
for cls in gen_subclasses(BaseSeismicSource):
print(cls.__name__)
elif what == 'consequences':
known = scientific.KNOWN_CONSEQUENCES
print('The following %d consequences are implemented:' % len(known))
for cons in known:
print(cons)
elif os.path.isdir(what) and report:
with Monitor('info', measuremem=True) as mon:
with mock.patch.object(logging.root, 'info'): # reduce logging
do_build_reports(what)
print(mon)
elif what.endswith('.xml'):
node = nrml.read(what)
if node[0].tag.endswith('sourceModel'):
print(source_model_info([node]))
elif node[0].tag.endswith('logicTree'):
bset = node[0][0]
if bset.tag.endswith("logicTreeBranchingLevel"):
bset = bset[0]
if bset.attrib['uncertaintyType'] == 'sourceModel':
sm_nodes = []
for smpath in logictree.collect_info(what).smpaths:
sm_nodes.append(nrml.read(smpath))
print(source_model_info(sm_nodes))
elif bset.attrib['uncertaintyType'] == 'gmpeModel':
print(logictree.GsimLogicTree(what))
else:
print(node.to_str())
elif what.endswith(('.ini', '.zip')):
with Monitor('info', measuremem=True) as mon:
if report:
print('Generated', reportwriter.build_report(what))
else:
print(readinput.get_oqparam(what).json())
if mon.duration > 1:
print(mon)
elif what:
print("No info for '%s'" % what)
import sys
import numpy as np
import multiprocessing
from collections import OrderedDict
#from openquake.hazardlib.calc.hazard_curve import hazard_curves
from openquake.hazardlib.calc import hazard_curve
from openquake.hazardlib.site import Site, SiteCollection
from openquake.hazardlib.gsim import get_available_gsims
from openquake.hazardlib.gsim.base import ContextMaker
from openquake.hazardlib.calc import filters
from openquake.hazardlib import imt
from openquake.hazardlib.geo.point import Point
from hmtk.sources.source_model import mtkSourceModel
DEFAULT_WORKERS = multiprocessing.cpu_count()
GSIM_MAP = get_available_gsims()
def _check_supported_imts(imts):
"""
Checks that all of the IMTs in the list are supported
"""
output_imts = []
for imtx in imts:
if imtx in imt.__all__:
output_imts.append(imt.__dict__[imtx]())
elif 'SA' in imtx:
output_imts.append(imt.from_string(imtx))
else:
raise ValueError('IMT %s not supported in OpenQuake!' % imtx)
return output_imts
import ast
import logging
import textwrap
import collections
from decimal import Decimal
import numpy
from openquake.baselib.python3compat import with_metaclass
from openquake.baselib import hdf5
from openquake.hazardlib import imt, scalerel, gsim
from openquake.baselib.general import distinct
SCALEREL = scalerel.get_available_magnitude_scalerel()
GSIM = gsim.get_available_gsims()
# more tests are in tests/valid_test.py
def gsim(value, **kwargs):
"""
Make sure the given value is the name of an available GSIM class.
>>> gsim('BooreAtkinson2011')
'BooreAtkinson2011()'
"""
if value == 'FromFile':
return 'FromFile'
elif value.endswith('()'):
value = value[:-2] # strip parenthesis
try:
def gsims(cls):
'''Returns a (new) dict of:
gsim_name (string) mapped to its gsim_class (class object)
defining all Ground Shaking Intensity Models defined in OpenQuake.
'''
return dict(get_available_gsims())
Sets up a simple rupture-site configuration to allow for physical comparison
of GMPEs
'''
import numpy as np
from collections import Iterable, OrderedDict
from math import floor, ceil
from sets import Set
import matplotlib
import matplotlib.pyplot as plt
from openquake.hazardlib import gsim, imt
from openquake.hazardlib.scalerel.wc1994 import WC1994
from smtk.sm_utils import _save_image, _save_image_tight
import smtk.trellis.trellis_utils as utils
from smtk.trellis.configure import GSIMRupture
AVAILABLE_GSIMS = gsim.get_available_gsims()
PARAM_DICT = {'magnitudes': [],
'distances': [],
'distance_type': 'rjb',
'vs30': [],
'strike': None,
'dip': None,
'rake': None,
'ztor': None,
'hypocentre_location': (0.5, 0.5),
'hypo_loc': (0.5, 0.5),
'msr': WC1994()}
PLOT_UNITS = {'PGA': 'g',
'PGV': 'cm/s',
def get_gsims(trts, imts):
'''Writes all Gsims from OpenQuake to the db'''
entity_type = ENTITIES[0][0]
trts_d = {_.oq_name: _ for _ in trts}
imts_d = {_.key: _ for _ in imts}
create_err = Error.objects.create # pylint: disable=no-member
create_gsim = Gsim.objects.create # pylint: disable=no-member
gsims = []
with warnings.catch_warnings():
# Catch warnings as if they were exceptions, and skip deprecation w.
# https://stackoverflow.com/a/30368735
warnings.filterwarnings('error') # raises every time, not only 1st
for key, gsim in get_available_gsims().items():
if inspect.isabstract(gsim):
continue
warning = ''
needs_args = False
try:
gsim_inst = gsim()
except TypeError:
gsim_inst = gsim
needs_args = True
except (OSError, NotImplementedError) as exc:
create_err(type=exc.__class__.__name__,
message=str(exc),
entity_type=entity_type,
entity_key=key)
continue
except OQDeprecationWarning as warn:
# the builtin DeprecationWarning is silenced, OQ uses it's own
create_err(type=warn.__class__.__name__,
message=str(warn),
entity_type=entity_type,
entity_key=key)
continue
# except NotVerifiedWarning as warn:
# warning = str(warn)
except Warning as warn:
warning = str(warn)
try:
gsim_imts = gsim_inst.DEFINED_FOR_INTENSITY_MEASURE_TYPES
except AttributeError as exc:
create_err(type=exc.__class__.__name__,
message=str(exc),
entity_type=entity_type,
entity_key=key)
continue
if not gsim_imts and hasattr(gsim_imts, '__iter__'):
create_err(type=Exception.__name__,
message='No IMT defined',
entity_type=entity_type,
entity_key=key)
continue
try:
trt = trts_d[gsim_inst.DEFINED_FOR_TECTONIC_REGION_TYPE]
except KeyError:
create_err(type=Exception.__name__,
message='%s is not a valid TRT' %
str(gsim_inst.DEFINED_FOR_TECTONIC_REGION_TYPE),
entity_type=entity_type,
entity_key=key)
continue
except AttributeError:
create_err(type=Exception.__name__,
message='No TRT defined',
entity_type=entity_type,
entity_key=key)
continue
# convert gsim imts (classes) into strings:
gsim_imts = [_.__name__ for _ in gsim_imts]
# and not convert to Imt model instances:
gsim_imts = [imts_d[_] for _ in gsim_imts if _ in imts_d]
if not gsim_imts:
create_err(type=Exception.__name__,
message='No IMT in %s' % str([_.key for _ in imts]),
entity_type=entity_type,
entity_key=key)
continue
gsim = create_gsim(key=key,
trt=trt,
warning=warning,
needs_args=needs_args)
gsim.imts.set(gsim_imts)
gsims.append(gsim)
return gsims
import numpy as np from copy import deepcopy from openquake.hazardlib.imt import PGA, PGV, SA from openquake.hazardlib.site import Site, SiteCollection from openquake.hazardlib.geo.point import Point from openquake.hazardlib import gsim from openquake.hazardlib.pmf import PMF from openquake.hazardlib.geo.nodalplane import NodalPlane from openquake.hazardlib.scalerel.wc1994 import WC1994 from openquake.hazardlib.mfd.truncated_gr import TruncatedGRMFD from openquake.hazardlib.tom import PoissonTOM from openquake.hazardlib.source.point import PointSource from openquake.hazardlib.calc.hazard_curve import calc_hazard_curves import hmtk.hazard as haz SUPPORTED_GSIMS = gsim.get_available_gsims() #class TestCheckSupportedIMTs(unittest.TestCase): # """ # Checks the pre-processor for ensuring IMT input is correctly formatted # """ # def setUp(self): # """ # # """ # self.imt_list = None # # def test_correct_input(self): # """ # Checks the output when a correctly formatted list of IMTs is passed # """
}
}
TAB_STYLE = {'height': '100vh', 'width': '100vw'}
IMC_MAPPINGS = {
'rotd50.0': 'ROTD50.0',
'arithmetic_mean': 'Arithmetic Mean',
'geometric_mean': 'Geometric Mean',
'quadratic_mean': 'Quadratic Mean'
}
MAPBOX_ACCESS_TOKEN = ('pk.eyJ1IjoianJla29za2UiLCJhIjoiY2p5amJ3ZnJpMDIzbjNlbjd'
'jdXJ5bTQ5MSJ9.QjIZKHgkxz21YOKkxLBOVQ')
IMT_REGEX = re.compile(r'PGA|PGV|SA\(*|FAS\(*|ARIAS|DURATION')
DIST_REGEX = re.compile(r'.*Distance$')
MODELS_DICT = {}
for item in get_available_gsims().items():
with warnings.catch_warnings(record=True) as caught_warnings:
try:
item[1]()
except Exception:
continue
if not caught_warnings:
MODELS_DICT[item[0]] = item[1]
ALL_PARAMS = [
param for param_type in DEFAULT_PARAMS.keys()
for param in DEFAULT_PARAMS[param_type]
]
AZIMUTH = 0
DIST_DICT = {
'EpicentralDistance': ('repi', 'Epicentral distance (km)'),
'HypocentralDistance': ('rhypo', 'Hypocentral distance (km)'),
import subprocess
import h5py
import numpy as np
import pandas as pd
from openquake.hazardlib.geo import Point, PlanarSurface, MultiSurface, Mesh
from openquake.hazardlib.gsim import get_available_gsims
from openquake.hazardlib.imt import PGA, PGV, SA, from_string
from openquake.hazardlib.contexts import (ContextMaker, get_distances,
SitesContext, DistancesContext)
from openquake.hazardlib.source.rupture import ParametricProbabilisticRupture
from openquake.hazardlib.site import Site, SiteCollection
from openquake.hazardlib.scalerel.wc1994 import WC1994
from openquake.hazardlib import const
import synthetic_rupture_generator as srg
GSIM_SET = get_available_gsims()
def create_planar_surface(top_centroid, strike, dip, area, aspect):
"""
Given a central location, create a simple planar rupture
:param top_centroid:
Centroid of trace of the rupture, as instance of :class:
openquake.hazardlib.geo.point.Point
:param float strike:
Strike of rupture(Degrees)
:param float dip:
Dip of rupture (degrees)
:param float area:
Area of rupture (km^2)
:param float aspect:
def compute_cs(t_cs, bgmpe, sctx, rctx, dctx, im_type, t_star, rrup, mag,
avg_periods, corr_type, im_star, gmpe_input):
"""
Compute the conditional spectrum according to the procedure outlined
in Baker JW, Lee C. An Improved Algorithm for Selecting Ground Motions
to Match a Conditional Spectrum. J Earthq Eng 2018;22:708-23.
https://doi.org/10.1080/13632469.2016.1264334.
When the IM and the GMM are defined for the maximum of the two horizontal
components, the The Boore and Kishida (2017) relationship is applied to
convert the maximum of the two horizontal components into `RotD50`. This is
done only for `PGA` and `SA`.
"""
import numpy as np
import sys
from openquake.hazardlib import imt, const, gsim
from .compute_avgSA import compute_rho_avgsa
from .modified_akkar_correlation_model import ModifiedAkkarCorrelationModel
# Use the same periods as the available spectra to construct the
# conditional spectrum
p = []
s = [const.StdDev.TOTAL]
if im_type == 'AvgSA':
_ = gsim.get_available_gsims()
p = imt.AvgSA()
mgmpe = gsim.mgmpe.generic_gmpe_avgsa.GenericGmpeAvgSA \
(gmpe_name=gmpe_input, avg_periods=avg_periods, corr_func=corr_type)
mu_im_cond, sigma_im_cond = mgmpe.get_mean_and_stddevs(
sctx, rctx, dctx, p, s)
else:
if im_type == 'PGA':
p = imt.PGA()
else:
p = imt.SA(t_star)
s = [const.StdDev.TOTAL]
mu_im_cond, sigma_im_cond = bgmpe().get_mean_and_stddevs(
sctx, rctx, dctx, p, s)
sigma_im_cond = sigma_im_cond[0]
if (bgmpe.DEFINED_FOR_INTENSITY_MEASURE_COMPONENT ==
'Greater of two horizontal'):
if im_type == 'PGA' or im_type == 'SA':
from shakelib.conversions.imc.boore_kishida_2017 import \
BooreKishida2017
bk17 = BooreKishida2017(const.IMC.GREATER_OF_TWO_HORIZONTAL,
const.IMC.RotD50)
mu_im_cond = bk17.convertAmps(p, mu_im_cond, rrup, float(mag))
sigma_im_cond = bk17.convertSigmas(p, sigma_im_cond[0])
else:
sys.exit('Error: conversion between intensity measures is not '
'possible for AvgSA')
# Compute how many standard deviations the PSHA differs from
# the GMPE value
epsilon = (np.log(im_star) - mu_im_cond) / sigma_im_cond
mu_im = np.zeros(len(t_cs))
sigma_im = np.zeros(len(t_cs))
rho_t_tstar = np.zeros(len(t_cs))
mu_im_im_cond = np.zeros(len(t_cs))
for i in range(len(t_cs)):
# Get the GMPE ouput for a rupture scenario
if t_cs[i] == 0.:
p = imt.PGA()
else:
p = imt.SA(t_cs[i])
s = [const.StdDev.TOTAL]
mu0, sigma0 = bgmpe().get_mean_and_stddevs(sctx, rctx, dctx, p, s)
if (bgmpe.DEFINED_FOR_INTENSITY_MEASURE_COMPONENT ==
'Greater of two horizontal'):
if im_type == 'PGA' or im_type == 'SA':
from shakelib.conversions.imc.boore_kishida_2017 \
import BooreKishida2017
bk17 = BooreKishida2017(const.IMC.GREATER_OF_TWO_HORIZONTAL,
const.IMC.RotD50)
mu0 = bk17.convertAmps(p, mu0, rrup, float(mag))
sigma0 = bk17.convertSigmas(p, sigma0[0])
mu_im[i] = mu0[0]
sigma_im[i] = sigma0[0][0]
rho = None
if im_type == 'AvgSA':
rho = compute_rho_avgsa(t_cs[i], avg_periods, sctx, rctx, dctx,
sigma_im_cond, bgmpe, corr_type)
rho = rho[0]
else:
if corr_type == 'baker_jayaram':
rho = gsim.mgmpe.generic_gmpe_avgsa. \
BakerJayaramCorrelationModel([t_cs[i], t_star])(0, 1)
if corr_type == 'akkar':
rho = ModifiedAkkarCorrelationModel([t_cs[i], t_star])(0, 1)
rho_t_tstar[i] = rho
# Get the value of the CMS
mu_im_im_cond[i] = \
mu_im[i] + rho_t_tstar[i] * epsilon[0] * sigma_im[i]
# Compute covariances and correlations at all periods
cov = np.zeros((len(t_cs), len(t_cs)))
for i in np.arange(len(t_cs)):
for j in np.arange(len(t_cs)):
var1 = sigma_im[i]**2
var2 = sigma_im[j]**2
var_tstar = sigma_im_cond**2
sigma_corr = []
if corr_type == 'baker_jayaram':
sigma_corr = gsim.mgmpe.generic_gmpe_avgsa. \
BakerJayaramCorrelationModel([t_cs[i], t_cs[j]])(0, 1) * \
np.sqrt(var1 * var2)
if corr_type == 'akkar':
sigma_corr = ModifiedAkkarCorrelationModel([t_cs[i], t_cs[j]])(0, 1) * \
np.sqrt(var1 * var2)
sigma11 = np.matrix([[var1, sigma_corr], [sigma_corr, var2]])
sigma22 = np.array(var_tstar)
sigma12 = np.array([
rho_t_tstar[i] * np.sqrt(var1 * var_tstar),
rho_t_tstar[j] * np.sqrt(var_tstar * var2)
])
sigma_cond = sigma11 - sigma12 * 1. / (sigma22) * sigma12.T
cov[i, j] = sigma_cond[0, 1]
# find covariance values of zero and set them to a small number
# so that random number generation can be performed
cov[np.absolute(cov) < 1e-10] = 1e-10
stdevs = np.sqrt(np.diagonal(cov))
return mu_im_im_cond, cov, stdevs
import numpy as np from copy import deepcopy from openquake.hazardlib.imt import PGA, PGV, SA from openquake.hazardlib.site import Site, SiteCollection from openquake.hazardlib.geo.point import Point from openquake.hazardlib import gsim from openquake.hazardlib.pmf import PMF from openquake.hazardlib.geo.nodalplane import NodalPlane from openquake.hazardlib.scalerel.wc1994 import WC1994 from openquake.hazardlib.mfd.truncated_gr import TruncatedGRMFD from openquake.hazardlib.tom import PoissonTOM from openquake.hazardlib.source.point import PointSource from openquake.hazardlib.calc.hazard_curve import calc_hazard_curves import hmtk.hazard as haz SUPPORTED_GSIMS = gsim.get_available_gsims() #class TestCheckSupportedIMTs(unittest.TestCase): # """ # Checks the pre-processor for ensuring IMT input is correctly formatted # """ # def setUp(self): # """ # # """ # self.imt_list = None # # def test_correct_input(self): # """ # Checks the output when a correctly formatted list of IMTs is passed # """
from openquake.hazardlib.scalerel.wc1994 import WC1994
from smtk.sm_utils import _save_image, _save_image_tight
import smtk.trellis.trellis_utils as utils
from smtk.trellis.configure import GSIMRupture
# Default - defines a 21 color and line-type cycle
matplotlib.rcParams["axes.prop_cycle"] = \
cycler(u'color', [u'b', u'g', u'r', u'c', u'm', u'y', u'k',
u'b', u'g', u'r', u'c', u'm', u'y', u'k',
u'b', u'g', u'r', u'c', u'm', u'y', u'k']) +\
cycler(u'linestyle', ["-", "-", "-", "-", "-", "-", "-",
"--", "--", "--", "--", "--", "--", "--",
"-.", "-.", "-.", "-.", "-.", "-.", "-."])
# Get a list of the available GSIMs
AVAILABLE_GSIMS = gsim.get_available_gsims()
# Generic dictionary of parameters needed for a trellis calculation
PARAM_DICT = {
'magnitudes': [],
'distances': [],
'distance_type': 'rjb',
'vs30': [],
'strike': None,
'dip': None,
'rake': None,
'ztor': None,
'hypocentre_location': (0.5, 0.5),
'hypo_loc': (0.5, 0.5),
'msr': WC1994()
}
def main(what, report=False):
"""
Give information about the passed keyword or filename
"""
if os.environ.get('OQ_DISTRIBUTE') not in ('no', 'processpool'):
os.environ['OQ_DISTRIBUTE'] = 'processpool'
if what == 'calculators':
for calc in sorted(base.calculators):
print(calc)
elif what == 'gsims':
for gs in gsim.get_available_gsims():
print(gs)
elif what == 'imts':
for im in gen_subclasses(imt.IMT):
print(im.__name__)
elif what == 'views':
for name in sorted(view):
print(name)
elif what == 'exports':
dic = groupby(export, operator.itemgetter(0),
lambda group: [r[1] for r in group])
n = 0
for exporter, formats in dic.items():
print(exporter, formats)
n += len(formats)
print('There are %d exporters defined.' % n)
elif what == 'extracts':
for key in extract:
func = extract[key]
if hasattr(func, '__wrapped__'):
fm = FunctionMaker(func.__wrapped__)
elif hasattr(func, 'func'): # for partial objects
fm = FunctionMaker(func.func)
else:
fm = FunctionMaker(func)
print('%s(%s)%s' % (fm.name, fm.signature, fm.doc))
elif what == 'parameters':
params = []
for val in vars(OqParam).values():
if hasattr(val, 'name'):
params.append(val)
params.sort(key=lambda x: x.name)
for param in params:
print(param.name)
elif what == 'mfds':
for cls in gen_subclasses(BaseMFD):
print(cls.__name__)
elif what == 'sources':
for cls in gen_subclasses(BaseSeismicSource):
print(cls.__name__)
elif os.path.isdir(what) and report:
with Monitor('info', measuremem=True) as mon:
with mock.patch.object(logging.root, 'info'): # reduce logging
do_build_reports(what)
print(mon)
elif what.endswith('.xml'):
node = nrml.read(what)
if node[0].tag.endswith('sourceModel'):
print(source_model_info([node]))
elif node[0].tag.endswith('logicTree'):
sm_nodes = []
for smpath in logictree.collect_info(what).smpaths:
sm_nodes.append(nrml.read(smpath))
print(source_model_info(sm_nodes))
else:
print(node.to_str())
elif what.endswith(('.ini', '.zip')):
with Monitor('info', measuremem=True) as mon:
if report:
print('Generated', reportwriter.build_report(what))
else:
print(readinput.get_oqparam(what).json())
if mon.duration > 1:
print(mon)
elif what:
print("No info for '%s'" % what)
def get_available_gsims(request):
"""
Return a list of strings with the available GSIMs
"""
gsims = list(gsim.get_available_gsims())
return HttpResponse(content=json.dumps(gsims), content_type=JSON)
import h5py
import numpy as np
from math import sqrt, ceil
from scipy.special import erf
from scipy.stats import scoreatpercentile, norm
from copy import deepcopy
from collections import OrderedDict
from openquake.hazardlib.gsim import get_available_gsims
from openquake.hazardlib.gsim.gsim_table import GMPETable
import smtk.intensity_measures as ims
from openquake.hazardlib import imt
from smtk.strong_motion_selector import SMRecordSelector
from smtk.trellis.trellis_plots import _get_gmpe_name, _check_gsim_list
GSIM_LIST = get_available_gsims()
GSIM_KEYS = set(GSIM_LIST.keys())
#SCALAR_IMTS = ["PGA", "PGV", "PGD", "CAV", "Ia"]
SCALAR_IMTS = ["PGA", "PGV"]
STDDEV_KEYS = ["Mean", "Total", "Inter event", "Intra event"]
def _check_gsim_list(gsim_list):
"""
Checks the list of GSIM models and returns an instance of the
openquake.hazardlib.gsim class. Raises error if GSIM is not supported in
OpenQuake
:param list gsim_list:
List of GSIM names (str)
:returns:
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# OpenQuake is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>.
from openquake.hazardlib.gsim import get_available_gsims
from openquake.commonlib import valid
GSIMS = get_available_gsims()
GROUND_MOTION_CORRELATION_MODELS = [
'JB2009', 'Jayaram-Baker 2009']
HAZARD_CALCULATORS = [
'classical', 'disaggregation', 'event_based', 'scenario']
RISK_CALCULATORS = [
'classical_risk', 'event_based_risk', 'scenario_risk',
'classical_bcr', 'event_based_bcr', 'scenario_damage']
EXPERIMENTAL_CALCULATORS = [
'event_based_fr']
CALCULATORS = HAZARD_CALCULATORS + RISK_CALCULATORS + EXPERIMENTAL_CALCULATORS
def get_available_gsims(request):
"""
Return a list of strings with the available GSIMs
"""
gsims = list(gsim.get_available_gsims())
return HttpResponse(content=json.dumps(gsims), content_type=JSON)
def inizialize_gmm(index, gmpe_input, rjb, mag, z_hyp_input, dip_input, rake,
upper_sd_input, lower_sd_input, azimuth_input, fhw,
vs30type, vs30_input, z2pt5_input, z1pt0_input, site_code):
"""
Defines all the parameters for the computation of a Ground Motion Model. If
not defined by the user as input parameters, most parameters (dip,
hypocentral depth, fault width, ztor, azimuth, source-to-site distances
based on extended sources, z2pt5, z1pt0) are defined according to the
relationships included in:
Kaklamanos J, Baise LG, Boore DM. (2011) Estimating unknown input parameters
when implementing the NGA ground-motion prediction equations in engineering
practice. Earthquake Spectra 27: 1219-1235.
https://doi.org/10.1193/1.3650372.
"""
import sys
from openquake.hazardlib import gsim
import numpy as np
bgmpe = None
for name_gmpe, gmpes in gsim.get_available_gsims().items():
if name_gmpe == gmpe_input:
bgmpe = gmpes
if bgmpe is None:
sys.exit('The GMM is not found')
sctx = gsim.base.SitesContext()
rctx = gsim.base.RuptureContext()
dctx = gsim.base.DistancesContext()
# -----------------------------------------------------------------------------
# Initialise contexts
if (bgmpe() == '[Ambraseys1996]'):
mw = np.exp(1.421 + 0.108 * mag) - 1.863
else:
mw = mag
dip, z_hyp, width, ztor, azimuth = compute_source_params(
mw, z_hyp_input, dip_input, rake, upper_sd_input, lower_sd_input,
azimuth_input, fhw)
[rx, rrup,
ry] = compute_dists(rjb, mw, z_hyp_input, dip_input, rake, upper_sd_input,
lower_sd_input, azimuth_input, fhw)
[vs30, vs30measured, z1pt0,
z2pt5] = compute_soil_params(vs30_input, z2pt5_input, z1pt0_input,
gmpe_input, vs30type, index)
setattr(rctx, 'width', width)
setattr(rctx, 'ztor', ztor)
setattr(rctx, 'dip', dip)
setattr(dctx, 'rx', rx)
setattr(dctx, 'rrup', rrup)
setattr(dctx, 'ry0', ry)
z1pt0 = z1pt0 + np.zeros(rjb.shape)
setattr(sctx, 'z1pt0', z1pt0)
z2pt5 = z2pt5 + np.zeros(rjb.shape)
setattr(sctx, 'z2pt5', z2pt5)
setattr(sctx, 'vs30measured', vs30measured)
setattr(rctx, 'mag', mag)
setattr(rctx, 'hypo_depth', z_hyp)
setattr(rctx, 'rake', rake)
setattr(rctx, 'occurrence_rate', 0.)
setattr(dctx, 'rjb', rjb)
vs30 = vs30 + np.zeros(rjb.shape)
setattr(sctx, 'vs30', vs30)
sc = site_code[index] + np.zeros(rjb.shape)
setattr(sctx, 'sids', sc)
return bgmpe, sctx, rctx, dctx, vs30, rrup
import logging
import textwrap
import collections
from decimal import Decimal
import numpy
from openquake.baselib.python3compat import with_metaclass
from openquake.baselib.general import distinct
from openquake.baselib import hdf5
from openquake.hazardlib import imt, scalerel, gsim
from openquake.hazardlib.calc import disagg
from openquake.hazardlib.calc.filters import IntegrationDistance
SCALEREL = scalerel.get_available_magnitude_scalerel()
GSIM = gsim.get_available_gsims()
disagg_outs = ['_'.join(tup) for tup in sorted(disagg.pmf_map)]
def disagg_outputs(value):
"""
Validate disaggregation outputs. For instance
>>> disagg_outputs('TRT Mag_Dist')
['TRT', 'Mag_Dist']
"""
values = value.split()
for val in values:
if val not in disagg_outs:
raise ValueError('Invalid disagg output: %s' % val)
def info(calculators, gsims, views, exports, extracts, parameters,
report, input_file=''):
"""
Give information. You can pass the name of an available calculator,
a job.ini file, or a zip archive with the input files.
"""
if calculators:
for calc in sorted(base.calculators):
print(calc)
if gsims:
for gs in gsim.get_available_gsims():
print(gs)
if views:
for name in sorted(view):
print(name)
if exports:
dic = groupby(export, operator.itemgetter(0),
lambda group: [r[1] for r in group])
n = 0
for exporter, formats in dic.items():
print(exporter, formats)
n += len(formats)
print('There are %d exporters defined.' % n)
if extracts:
for key in extract:
func = extract[key]
if hasattr(func, '__wrapped__'):
fm = FunctionMaker(func.__wrapped__)
else:
fm = FunctionMaker(func)
print('%s(%s)%s' % (fm.name, fm.signature, fm.doc))
if parameters:
params = []
for val in vars(OqParam).values():
if hasattr(val, 'name'):
params.append(val)
params.sort(key=lambda x: x.name)
for param in params:
print(param.name)
if os.path.isdir(input_file) and report:
with Monitor('info', measuremem=True) as mon:
with mock.patch.object(logging.root, 'info'): # reduce logging
do_build_reports(input_file)
print(mon)
elif input_file.endswith('.xml'):
node = nrml.read(input_file)
if node[0].tag.endswith('sourceModel'):
if node['xmlns'].endswith('nrml/0.4'):
raise InvalidFile(
'%s is in NRML 0.4 format, please run the following '
'command:\noq upgrade_nrml %s' % (
input_file, os.path.dirname(input_file) or '.'))
print(source_model_info([node[0]]))
elif node[0].tag.endswith('logicTree'):
nodes = [nrml.read(sm_path)[0]
for sm_path in logictree.collect_info(input_file).smpaths]
print(source_model_info(nodes))
else:
print(node.to_str())
elif input_file.endswith(('.ini', '.zip')):
with Monitor('info', measuremem=True) as mon:
if report:
print('Generated', reportwriter.build_report(input_file))
else:
print_csm_info(input_file)
if mon.duration > 1:
print(mon)
elif input_file:
print("No info for '%s'" % input_file)
