def get_site_model(oqparam, req_site_params):
"""
Convert the NRML file into an array of site parameters.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
:param req_site_params:
required site parameters
:returns:
an array with fields lon, lat, vs30, measured, z1pt0, z2pt5, backarc
"""
nodes = nrml.read(oqparam.inputs['site_model']).siteModel
params = [valid.site_param(node.attrib) for node in nodes]
missing = req_site_params - set(params[0])
if missing == set(['backarc']): # use a default of False
for param in params:
param['backarc'] = False
elif missing:
raise InvalidFile('%s: missing parameter %s' %
(oqparam.inputs['site_model'], ', '.join(missing)))
# NB: the sorted in sorted(params[0]) is essential, otherwise there is
# an heisenbug in scenario/test_case_4
site_model_dt = numpy.dtype([(p, site.site_param_dt[p])
for p in sorted(params[0])])
tuples = [
tuple(param[name] for name in site_model_dt.names) for param in params
]
return numpy.array(tuples, site_model_dt)
def get_site_model(oqparam):
"""
Convert the NRML file into an array of site parameters.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
:returns:
an array with fields lon, lat, vs30, ...
"""
req_site_params = get_gsim_lt(oqparam).req_site_params
arrays = []
for fname in oqparam.inputs['site_model']:
if isinstance(fname, str) and fname.endswith('.csv'):
sm = hdf5.read_csv(fname, {
None: float,
'vs30measured': numpy.uint8
}).array
if 'site_id' in sm.dtype.names:
raise InvalidFile('%s: you passed a sites.csv file instead of '
'a site_model.csv file!' % fname)
z = numpy.zeros(len(sm), sorted(sm.dtype.descr))
for name in z.dtype.names: # reorder the fields
z[name] = sm[name]
arrays.append(z)
continue
nodes = nrml.read(fname).siteModel
params = [valid.site_param(node.attrib) for node in nodes]
missing = req_site_params - set(params[0])
if 'vs30measured' in missing: # use a default of False
missing -= {'vs30measured'}
for param in params:
param['vs30measured'] = False
if 'backarc' in missing: # use a default of False
missing -= {'backarc'}
for param in params:
param['backarc'] = False
if missing:
raise InvalidFile(
'%s: missing parameter %s' %
(oqparam.inputs['site_model'], ', '.join(missing)))
# NB: the sorted in sorted(params[0]) is essential, otherwise there is
# an heisenbug in scenario/test_case_4
site_model_dt = numpy.dtype([(p, site.site_param_dt[p])
for p in sorted(params[0])])
sm = numpy.array([
tuple(param[name] for name in site_model_dt.names)
for param in params
], site_model_dt)
dupl = "\n".join('%s %s' % loc
for loc, n in countby(sm, 'lon', 'lat').items()
if n > 1)
if dupl:
raise InvalidFile('There are duplicated sites in %s:\n%s' %
(fname, dupl))
arrays.append(sm)
return numpy.concatenate(arrays)
def get_site_model(oqparam):
"""
Convert the NRML file into an iterator over 6-tuple of the form
(z1pt0, z2pt5, measured, vs30, lon, lat)
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
"""
for node in nrml.read(oqparam.inputs['site_model']).siteModel:
yield valid.site_param(**node.attrib)
def get_site_model(oqparam):
"""
Convert the NRML file into an array of site parameters.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
:returns:
an array with fields lon, lat, vs30, ...
"""
req_site_params = get_gsim_lt(oqparam).req_site_params
arrays = []
for fname in oqparam.inputs['site_model']:
if isinstance(fname, str) and fname.endswith('.csv'):
sm = hdf5.read_csv(
fname, {None: float, 'vs30measured': bool}).array
if 'site_id' in sm.dtype.names:
raise InvalidFile('%s: you passed a sites.csv file instead of '
'a site_model.csv file!' % fname)
z = numpy.zeros(len(sm), sorted(sm.dtype.descr))
for name in z.dtype.names: # reorder the fields
z[name] = sm[name]
arrays.append(z)
continue
nodes = nrml.read(fname).siteModel
params = [valid.site_param(node.attrib) for node in nodes]
missing = req_site_params - set(params[0])
if 'vs30measured' in missing: # use a default of False
missing -= {'vs30measured'}
for param in params:
param['vs30measured'] = False
if 'backarc' in missing: # use a default of False
missing -= {'backarc'}
for param in params:
param['backarc'] = False
if missing:
raise InvalidFile('%s: missing parameter %s' %
(oqparam.inputs['site_model'],
', '.join(missing)))
# NB: the sorted in sorted(params[0]) is essential, otherwise there is
# an heisenbug in scenario/test_case_4
site_model_dt = numpy.dtype([(p, site.site_param_dt[p])
for p in sorted(params[0])])
sm = numpy.array([tuple(param[name] for name in site_model_dt.names)
for param in params], site_model_dt)
arrays.append(sm)
return numpy.concatenate(arrays)
def get_site_model(oqparam):
"""
Convert the NRML file into an array of site parameters.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
:returns:
an array with fields lon, lat, vs30, measured, z1pt0, z2pt5, backarc
"""
nodes = nrml.read(oqparam.inputs['site_model']).siteModel
params = sorted(valid.site_param(**node.attrib) for node in nodes)
array = numpy.zeros(len(params), site_model_dt)
for i, param in enumerate(params):
rec = array[i]
for name in site_model_dt.names:
rec[name] = getattr(param, name)
return array
def get_site_model(oqparam):
"""
Convert the NRML file into an array of site parameters.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
:returns:
an array with fields lon, lat, vs30, ...
"""
req_site_params = get_gsim_lt(oqparam).req_site_params
if 'amplification' in oqparam.inputs:
req_site_params.add('ampcode')
arrays = []
for fname in oqparam.inputs['site_model']:
if isinstance(fname, str) and fname.endswith('.csv'):
sm = hdf5.read_csv(fname, site.site_param_dt).array
sm['lon'] = numpy.round(sm['lon'], 5)
sm['lat'] = numpy.round(sm['lat'], 5)
dupl = get_duplicates(sm, 'lon', 'lat')
if dupl:
raise InvalidFile(
'Found duplicate sites %s in %s' % (dupl, fname))
if 'site_id' in sm.dtype.names:
raise InvalidFile('%s: you passed a sites.csv file instead of '
'a site_model.csv file!' % fname)
params = sorted(set(sm.dtype.names) | req_site_params)
z = numpy.zeros(
len(sm), [(p, site.site_param_dt[p]) for p in params])
for name in z.dtype.names:
try:
z[name] = sm[name]
except ValueError: # missing, use the global parameter
# exercised in the test classical/case_28
value = getattr(oqparam, site.param[name])
if name == 'vs30measured': # special case
value = value == 'measured'
z[name] = value
arrays.append(z)
continue
nodes = nrml.read(fname).siteModel
params = [valid.site_param(node.attrib) for node in nodes]
missing = req_site_params - set(params[0])
if 'vs30measured' in missing: # use a default of False
missing -= {'vs30measured'}
for param in params:
param['vs30measured'] = False
if 'backarc' in missing: # use a default of False
missing -= {'backarc'}
for param in params:
param['backarc'] = False
if 'ampcode' in missing: # use a default of b''
missing -= {'ampcode'}
for param in params:
param['ampcode'] = b''
if missing:
raise InvalidFile('%s: missing parameter %s' %
(oqparam.inputs['site_model'],
', '.join(missing)))
# NB: the sorted in sorted(params[0]) is essential, otherwise there is
# an heisenbug in scenario/test_case_4
site_model_dt = numpy.dtype([(p, site.site_param_dt[p])
for p in sorted(params[0])])
sm = numpy.array([tuple(param[name] for name in site_model_dt.names)
for param in params], site_model_dt)
dupl = "\n".join(
'%s %s' % loc for loc, n in countby(sm, 'lon', 'lat').items()
if n > 1)
if dupl:
raise InvalidFile('There are duplicated sites in %s:\n%s' %
(fname, dupl))
arrays.append(sm)
return numpy.concatenate(arrays)