def read_hparams(job_ini):
"""
:param job_ini: path to a job.ini file
:returns: dictionary of hazard parameters
"""
jobdir = os.path.dirname(job_ini)
cp = configparser.ConfigParser()
cp.read([job_ini], encoding='utf8')
params = {}
for sect in cp.sections():
for key, val in cp.items(sect):
if key == 'intensity_measure_types_and_levels':
key = 'imtls'
val = valid.intensity_measure_types_and_levels(val)
elif key == 'maximum_distance':
val = IntegrationDistance.new(val)
elif key == 'sites':
val = valid.coordinates(val)
elif key.endswith('_file'):
val = os.path.join(jobdir, val)
else:
try:
val = ast.literal_eval(val)
except (SyntaxError, ValueError):
if val == 'true':
val = True
elif val == 'false':
val = False
params[key] = val
return params
def get_mesh(oqparam):
"""
Extract the mesh of points to compute from the sites,
the sites_csv, or the region.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
"""
global pmap, exposure, gmfs, eids
if 'exposure' in oqparam.inputs and exposure is None:
# read it only once
exposure = get_exposure(oqparam)
if oqparam.sites:
return geo.Mesh.from_coords(oqparam.sites)
elif 'sites' in oqparam.inputs:
csv_data = open(oqparam.inputs['sites'], 'U').readlines()
has_header = csv_data[0].startswith('site_id')
if has_header: # strip site_id
data = []
for i, line in enumerate(csv_data[1:]):
row = line.replace(',', ' ').split()
sid = row[0]
if sid != str(i):
raise InvalidFile('%s: expected site_id=%d, got %s' %
(oqparam.inputs['sites'], i, sid))
data.append(' '.join(row[1:]))
elif 'gmfs' in oqparam.inputs:
raise InvalidFile('Missing header in %(sites)s' % oqparam.inputs)
else:
data = [line.replace(',', ' ') for line in csv_data]
coords = valid.coordinates(','.join(data))
start, stop = oqparam.sites_slice
c = coords[start:stop] if has_header else sorted(coords[start:stop])
# TODO: sort=True below would break a lot of tests :-(
return geo.Mesh.from_coords(c, sort=False)
elif 'hazard_curves' in oqparam.inputs:
fname = oqparam.inputs['hazard_curves']
if fname.endswith('.csv'):
mesh, pmap = get_pmap_from_csv(oqparam, fname)
elif fname.endswith('.xml'):
mesh, pmap = get_pmap_from_nrml(oqparam, fname)
else:
raise NotImplementedError('Reading from %s' % fname)
return mesh
elif 'gmfs' in oqparam.inputs:
eids, gmfs = _get_gmfs(oqparam) # sets oqparam.sites
return geo.Mesh.from_coords(oqparam.sites)
elif oqparam.region and oqparam.region_grid_spacing:
poly = geo.Polygon.from_wkt(oqparam.region)
try:
mesh = poly.discretize(oqparam.region_grid_spacing)
return geo.Mesh.from_coords(zip(mesh.lons, mesh.lats))
except Exception:
raise ValueError(
'Could not discretize region %(region)s with grid spacing '
'%(region_grid_spacing)s' % vars(oqparam))
elif 'exposure' in oqparam.inputs:
return exposure.mesh
def get_mesh(oqparam):
"""
Extract the mesh of points to compute from the sites,
the sites_csv, or the region.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
"""
if oqparam.sites:
return geo.Mesh.from_coords(sorted(oqparam.sites))
elif 'sites' in oqparam.inputs:
csv_data = open(oqparam.inputs['sites'], 'U').readlines()
has_header = csv_data[0].startswith('site_id')
if has_header: # strip site_id
data = []
for i, line in enumerate(csv_data[1:]):
row = line.replace(',', ' ').split()
sid = row[0]
if sid != str(i):
raise InvalidFile('%s: expected site_id=%d, got %s' % (
oqparam.inputs['sites'], i, sid))
data.append(' '.join(row[1:]))
elif oqparam.calculation_mode == 'gmf_ebrisk':
raise InvalidFile('Missing header in %(sites)s' % oqparam.inputs)
else:
data = [line.replace(',', ' ') for line in csv_data]
coords = valid.coordinates(','.join(data))
start, stop = oqparam.sites_slice
c = coords[start:stop] if has_header else sorted(coords[start:stop])
return geo.Mesh.from_coords(c)
elif oqparam.region:
# close the linear polygon ring by appending the first
# point to the end
firstpoint = geo.Point(*oqparam.region[0])
points = [geo.Point(*xy) for xy in oqparam.region] + [firstpoint]
try:
mesh = geo.Polygon(points).discretize(oqparam.region_grid_spacing)
lons, lats = zip(*sorted(zip(mesh.lons, mesh.lats)))
return geo.Mesh(numpy.array(lons), numpy.array(lats))
except:
raise ValueError(
'Could not discretize region %(region)s with grid spacing '
'%(region_grid_spacing)s' % vars(oqparam))
elif oqparam.hazard_calculation_id:
sitecol = datastore.read(oqparam.hazard_calculation_id)['sitecol']
return geo.Mesh(sitecol.lons, sitecol.lats, sitecol.depths)
elif 'exposure' in oqparam.inputs:
# the mesh is extracted from get_sitecol_assetcol
return
elif 'site_model' in oqparam.inputs:
coords = [(param.lon, param.lat, param.depth)
for param in get_site_model(oqparam)]
mesh = geo.Mesh.from_coords(sorted(coords))
mesh.from_site_model = True
return mesh
def get_gmfs_from_txt(oqparam, fname):
"""
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
:param fname:
the full path of the CSV file
:returns:
a composite array of shape (N, R) read from a CSV file with format
`etag indices [gmv1 ... gmvN] * num_imts`
"""
with open(fname) as csvfile:
firstline = next(csvfile)
try:
coords = valid.coordinates(firstline)
except:
raise InvalidFile(
'The first line of %s is expected to contain comma separated'
'ordered coordinates, got %s instead' % (fname, firstline))
lons, lats, depths = zip(*coords)
sitecol = site.SiteCollection.from_points(lons, lats, depths, oqparam)
if not oqparam.imtls:
oqparam.set_risk_imtls(get_risk_models(oqparam))
imts = list(oqparam.imtls)
imt_dt = numpy.dtype([(imt, F32) for imt in imts])
num_gmfs = oqparam.number_of_ground_motion_fields
gmf_by_imt = numpy.zeros((num_gmfs, len(sitecol)), imt_dt)
etags = []
for lineno, line in enumerate(csvfile, 2):
row = line.split(',')
try:
indices = list(map(valid.positiveint, row[1].split()))
except:
raise InvalidFile(
'The second column in %s is expected to contain integer '
'indices, got %s' % (fname, row[1]))
r_sites = (sitecol if not indices else site.FilteredSiteCollection(
indices, sitecol))
for i in range(len(imts)):
try:
array = numpy.array(valid.positivefloats(row[i + 2]))
# NB: i + 2 because the first 2 fields are etag and indices
except:
raise InvalidFile(
'The column #%d in %s is expected to contain positive '
'floats, got %s instead' % (i + 3, fname, row[i + 2]))
gmf_by_imt[imts[i]][lineno - 2][r_sites.sids] = array
etags.append(row[0])
if lineno < num_gmfs + 1:
raise InvalidFile('%s contains %d rows, expected %d' %
(fname, lineno, num_gmfs + 1))
if etags != sorted(etags):
raise InvalidFile('The etags in %s are not ordered: %s' %
(fname, etags))
return sitecol, numpy.array([encode(e) for e in etags]), gmf_by_imt.T
def get_mesh(oqparam):
"""
Extract the mesh of points to compute from the sites,
the sites_csv, or the region.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
"""
if oqparam.sites:
return geo.Mesh.from_coords(oqparam.sites)
elif 'sites' in oqparam.inputs:
csv_data = open(oqparam.inputs['sites'], 'U').read()
coords = valid.coordinates(csv_data.strip().replace(',', ' ').replace(
'\n', ','))
start, stop = oqparam.sites_slice
return geo.Mesh.from_coords(coords[start:stop])
elif oqparam.region:
# close the linear polygon ring by appending the first
# point to the end
firstpoint = geo.Point(*oqparam.region[0])
points = [geo.Point(*xy) for xy in oqparam.region] + [firstpoint]
try:
mesh = geo.Polygon(points).discretize(oqparam.region_grid_spacing)
lons, lats = zip(*sorted(zip(mesh.lons, mesh.lats)))
return geo.Mesh(numpy.array(lons), numpy.array(lats))
except:
raise ValueError(
'Could not discretize region %(region)s with grid spacing '
'%(region_grid_spacing)s' % vars(oqparam))
elif 'gmfs' in oqparam.inputs:
return get_gmfs(oqparam)[0].mesh
elif oqparam.hazard_calculation_id:
sitecol = datastore.read(oqparam.hazard_calculation_id)['sitecol']
return geo.Mesh(sitecol.lons, sitecol.lats, sitecol.depths)
elif 'exposure' in oqparam.inputs:
# the mesh is extracted from get_sitecol_assetcol
return
elif 'site_model' in oqparam.inputs:
coords = [(param.lon, param.lat, param.depth)
for param in get_site_model(oqparam)]
mesh = geo.Mesh.from_coords(coords)
mesh.from_site_model = True
return mesh
def get_mesh(oqparam, h5=None):
"""
Extract the mesh of points to compute from the sites,
the sites_csv, the region, the site model, the exposure in this order.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
"""
global pmap, exposure, gmfs, eids
if 'exposure' in oqparam.inputs and exposure is None:
# read it only once
exposure = get_exposure(oqparam)
if oqparam.sites:
return geo.Mesh.from_coords(oqparam.sites)
elif 'sites' in oqparam.inputs:
fname = oqparam.inputs['sites']
header = get_csv_header(fname)
if 'lon' in header:
data = []
for i, row in enumerate(
csv.DictReader(open(fname, encoding='utf-8-sig'))):
if header[0] == 'site_id' and row['site_id'] != str(i):
raise InvalidFile('%s: expected site_id=%d, got %s' % (
fname, i, row['site_id']))
data.append(' '.join([row['lon'], row['lat']]))
elif 'gmfs' in oqparam.inputs:
raise InvalidFile('Missing header in %(sites)s' % oqparam.inputs)
else:
data = [line.replace(',', ' ')
for line in open(fname, encoding='utf-8-sig')]
coords = valid.coordinates(','.join(data))
start, stop = oqparam.sites_slice
c = (coords[start:stop] if header[0] == 'site_id'
else sorted(coords[start:stop]))
# NB: Notice the sort=False below
# Calculations starting from ground motion fields input by the user
# require at least two input files related to the gmf data:
# 1. A sites.csv file, listing {site_id, lon, lat} tuples
# 2. A gmfs.csv file, listing {event_id, site_id, gmv[IMT1],
# gmv[IMT2], ...} tuples
# The site coordinates defined in the sites file do not need to be in
# sorted order.
# We must only ensure uniqueness of the provided site_ids and
# coordinates.
# When creating the site mesh from the site coordinates read from
# the csv file, the sort=False flag maintains the user-specified
# site_ids instead of reassigning them after sorting.
return geo.Mesh.from_coords(c, sort=False)
elif 'hazard_curves' in oqparam.inputs:
fname = oqparam.inputs['hazard_curves']
if isinstance(fname, list): # for csv
mesh, pmap = get_pmap_from_csv(oqparam, fname)
else:
raise NotImplementedError('Reading from %s' % fname)
return mesh
elif oqparam.region_grid_spacing:
if oqparam.region:
poly = geo.Polygon.from_wkt(oqparam.region)
elif exposure:
# in case of implicit grid the exposure takes precedence over
# the site model
poly = exposure.mesh.get_convex_hull()
elif 'site_model' in oqparam.inputs:
# this happens in event_based/case_19, where there is an implicit
# grid over the site model
sm = get_site_model(oqparam) # do not store in h5!
poly = geo.Mesh(sm['lon'], sm['lat']).get_convex_hull()
else:
raise InvalidFile('There is a grid spacing but not a region, '
'nor a site model, nor an exposure in %s' %
oqparam.inputs['job_ini'])
try:
logging.info('Inferring the hazard grid')
mesh = poly.dilate(oqparam.region_grid_spacing).discretize(
oqparam.region_grid_spacing)
return geo.Mesh.from_coords(zip(mesh.lons, mesh.lats))
except Exception:
raise ValueError(
'Could not discretize region with grid spacing '
'%(region_grid_spacing)s' % vars(oqparam))
# the site model has the precedence over the exposure, see the
# discussion in https://github.com/gem/oq-engine/pull/5217
elif 'site_model' in oqparam.inputs:
logging.info('Extracting the hazard sites from the site model')
sm = get_site_model(oqparam)
if h5:
h5['site_model'] = sm
mesh = geo.Mesh(sm['lon'], sm['lat'])
return mesh
elif 'exposure' in oqparam.inputs:
return exposure.mesh
def __init__(self, **names_vals):
if '_job_id' in names_vals:
# assume most attributes already validated
vars(self).update(names_vals)
if 'hazard_calculation_id' in names_vals:
self.hazard_calculation_id = int(
names_vals['hazard_calculation_id'])
if 'maximum_distance' in names_vals:
self.maximum_distance = valid.MagDepDistance.new(
str(names_vals['maximum_distance']))
if 'pointsource_distance' in names_vals:
self.pointsource_distance = valid.MagDepDistance.new(
str(names_vals['pointsource_distance']))
if 'region_constraint' in names_vals:
self.region = valid.wkt_polygon(
names_vals['region_constraint'])
if 'minimum_magnitude' in names_vals:
self.minimum_magnitude = valid.floatdict(
str(names_vals['minimum_magnitude']))
if 'minimum_intensity' in names_vals:
self.minimum_intensity = valid.floatdict(
str(names_vals['minimum_intensity']))
if 'sites' in names_vals:
self.sites = valid.coordinates(names_vals['sites'])
return
# support legacy names
for name in list(names_vals):
if name == 'quantile_hazard_curves':
names_vals['quantiles'] = names_vals.pop(name)
elif name == 'mean_hazard_curves':
names_vals['mean'] = names_vals.pop(name)
elif name == 'max':
names_vals['max'] = names_vals.pop(name)
super().__init__(**names_vals)
if 'job_ini' not in self.inputs:
self.inputs['job_ini'] = '<in-memory>'
job_ini = self.inputs['job_ini']
if 'calculation_mode' not in names_vals:
raise InvalidFile('Missing calculation_mode in %s' % job_ini)
if 'region_constraint' in names_vals:
if 'region' in names_vals:
raise InvalidFile('You cannot have both region and '
'region_constraint in %s' % job_ini)
logging.warning(
'region_constraint is obsolete, use region instead')
self.region = valid.wkt_polygon(
names_vals.pop('region_constraint'))
self.risk_investigation_time = (self.risk_investigation_time
or self.investigation_time)
self.collapse_level = int(self.collapse_level)
if ('intensity_measure_types_and_levels' in names_vals
and 'intensity_measure_types' in names_vals):
logging.warning('Ignoring intensity_measure_types since '
'intensity_measure_types_and_levels is set')
if 'iml_disagg' in names_vals:
self.iml_disagg.pop('default')
# normalize things like SA(0.10) -> SA(0.1)
self.iml_disagg = {
str(from_string(imt)): val
for imt, val in self.iml_disagg.items()
}
self.hazard_imtls = self.iml_disagg
if 'intensity_measure_types_and_levels' in names_vals:
raise InvalidFile(
'Please remove the intensity_measure_types_and_levels '
'from %s: they will be inferred from the iml_disagg '
'dictionary' % job_ini)
elif 'intensity_measure_types_and_levels' in names_vals:
self.hazard_imtls = self.intensity_measure_types_and_levels
delattr(self, 'intensity_measure_types_and_levels')
lens = set(map(len, self.hazard_imtls.values()))
if len(lens) > 1:
dic = {imt: len(ls) for imt, ls in self.hazard_imtls.items()}
raise ValueError(
'Each IMT must have the same number of levels, instead '
'you have %s' % dic)
elif 'intensity_measure_types' in names_vals:
self.hazard_imtls = dict.fromkeys(self.intensity_measure_types)
if 'maximum_intensity' in names_vals:
minint = self.minimum_intensity or {'default': 1E-2}
for imt in self.hazard_imtls:
i1 = calc.filters.getdefault(minint, imt)
i2 = calc.filters.getdefault(self.maximum_intensity, imt)
self.hazard_imtls[imt] = list(valid.logscale(i1, i2, 20))
delattr(self, 'intensity_measure_types')
self._risk_files = get_risk_files(self.inputs)
if self.hazard_precomputed() and self.job_type == 'risk':
self.check_missing('site_model', 'debug')
self.check_missing('gsim_logic_tree', 'debug')
self.check_missing('source_model_logic_tree', 'debug')
# check investigation_time
if (self.investigation_time
and self.calculation_mode.startswith('scenario')):
raise ValueError('%s: there cannot be investigation_time in %s' %
(self.inputs['job_ini'], self.calculation_mode))
# check the gsim_logic_tree
if self.inputs.get('gsim_logic_tree'):
if self.gsim != '[FromFile]':
raise InvalidFile('%s: if `gsim_logic_tree_file` is set, there'
' must be no `gsim` key' % job_ini)
path = os.path.join(self.base_path, self.inputs['gsim_logic_tree'])
gsim_lt = logictree.GsimLogicTree(path, ['*'])
# check the IMTs vs the GSIMs
self._trts = set(gsim_lt.values)
for gsims in gsim_lt.values.values():
self.check_gsims(gsims)
elif self.gsim is not None:
self.check_gsims([valid.gsim(self.gsim, self.base_path)])
# check inputs
unknown = set(self.inputs) - self.KNOWN_INPUTS
if unknown:
raise ValueError('Unknown key %s_file in %s' %
(unknown.pop(), self.inputs['job_ini']))
# checks for disaggregation
if self.calculation_mode == 'disaggregation':
if not self.poes_disagg and self.poes:
self.poes_disagg = self.poes
elif not self.poes and self.poes_disagg:
self.poes = self.poes_disagg
elif self.poes != self.poes_disagg:
raise InvalidFile(
'poes_disagg != poes: %s!=%s in %s' %
(self.poes_disagg, self.poes, self.inputs['job_ini']))
if not self.poes_disagg and not self.iml_disagg:
raise InvalidFile('poes_disagg or iml_disagg must be set '
'in %(job_ini)s' % self.inputs)
elif self.poes_disagg and self.iml_disagg:
raise InvalidFile(
'%s: iml_disagg and poes_disagg cannot be set '
'at the same time' % job_ini)
for k in ('mag_bin_width', 'distance_bin_width',
'coordinate_bin_width', 'num_epsilon_bins'):
if k not in vars(self):
raise InvalidFile('%s must be set in %s' % (k, job_ini))
if self.disagg_outputs and not any('Eps' in out
for out in self.disagg_outputs):
self.num_epsilon_bins = 1
if (self.rlz_index is not None
and self.num_rlzs_disagg is not None):
raise InvalidFile('%s: you cannot set rlzs_index and '
'num_rlzs_disagg at the same time' % job_ini)
# checks for classical_damage
if self.calculation_mode == 'classical_damage':
if self.conditional_loss_poes:
raise InvalidFile('%s: conditional_loss_poes are not defined '
'for classical_damage calculations' %
job_ini)
# checks for event_based_risk
if (self.calculation_mode == 'event_based_risk'
and self.asset_correlation not in (0, 1)):
raise ValueError('asset_correlation != {0, 1} is no longer'
' supported')
# checks for ebrisk
if self.calculation_mode == 'ebrisk':
if self.risk_investigation_time is None:
raise InvalidFile('Please set the risk_investigation_time in'
' %s' % job_ini)
# check for GMFs from file
if (self.inputs.get('gmfs', '').endswith('.csv')
and 'sites' not in self.inputs and self.sites is None):
raise InvalidFile('%s: You forgot sites|sites_csv' % job_ini)
elif self.inputs.get('gmfs', '').endswith('.xml'):
raise InvalidFile('%s: GMFs in XML are not supported anymore' %
job_ini)
# checks for event_based
if 'event_based' in self.calculation_mode:
if self.ses_per_logic_tree_path >= TWO32:
raise ValueError('ses_per_logic_tree_path too big: %d' %
self.ses_per_logic_tree_path)
if self.number_of_logic_tree_samples >= TWO16:
raise ValueError('number_of_logic_tree_samples too big: %d' %
self.number_of_logic_tree_samples)
# check grid + sites
if self.region_grid_spacing and ('sites' in self.inputs or self.sites):
raise ValueError('You are specifying grid and sites at the same '
'time: which one do you want?')
# check for amplification
if ('amplification' in self.inputs and self.imtls
and self.calculation_mode
in ['classical', 'classical_risk', 'disaggregation']):
check_same_levels(self.imtls)
def get_mesh(oqparam):
"""
Extract the mesh of points to compute from the sites,
the sites_csv, or the region.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
"""
global pmap, exposure, gmfs, eids
if 'exposure' in oqparam.inputs and exposure is None:
# read it only once
exposure = get_exposure(oqparam)
if oqparam.sites:
return geo.Mesh.from_coords(oqparam.sites)
elif 'sites' in oqparam.inputs:
fname = oqparam.inputs['sites']
header = get_csv_header(fname)
if 'lon' in header:
data = []
for i, row in enumerate(
csv.DictReader(open(fname, encoding='utf-8-sig'))):
if header[0] == 'site_id' and row['site_id'] != str(i):
raise InvalidFile('%s: expected site_id=%d, got %s' % (
fname, i, row['site_id']))
data.append(' '.join([row['lon'], row['lat']]))
elif 'gmfs' in oqparam.inputs:
raise InvalidFile('Missing header in %(sites)s' % oqparam.inputs)
else:
data = [line.replace(',', ' ')
for line in open(fname, encoding='utf-8-sig')]
coords = valid.coordinates(','.join(data))
start, stop = oqparam.sites_slice
c = (coords[start:stop] if header[0] == 'site_id'
else sorted(coords[start:stop]))
return geo.Mesh.from_coords(c)
elif 'hazard_curves' in oqparam.inputs:
fname = oqparam.inputs['hazard_curves']
if isinstance(fname, list): # for csv
mesh, pmap = get_pmap_from_csv(oqparam, fname)
else:
raise NotImplementedError('Reading from %s' % fname)
return mesh
elif oqparam.region_grid_spacing:
if oqparam.region:
poly = geo.Polygon.from_wkt(oqparam.region)
elif 'site_model' in oqparam.inputs:
sm = get_site_model(oqparam)
poly = geo.Mesh(sm['lon'], sm['lat']).get_convex_hull()
elif exposure:
poly = exposure.mesh.get_convex_hull()
else:
raise InvalidFile('There is a grid spacing but not a region, '
'nor a site model, nor an exposure in %s' %
oqparam.inputs['job_ini'])
try:
mesh = poly.dilate(oqparam.region_grid_spacing).discretize(
oqparam.region_grid_spacing)
return geo.Mesh.from_coords(zip(mesh.lons, mesh.lats))
except Exception:
raise ValueError(
'Could not discretize region with grid spacing '
'%(region_grid_spacing)s' % vars(oqparam))
elif 'exposure' in oqparam.inputs:
return exposure.mesh
def get_mesh(oqparam):
"""
Extract the mesh of points to compute from the sites,
the sites_csv, or the region.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
"""
global pmap, exposure, gmfs, eids
if 'exposure' in oqparam.inputs and exposure is None:
# read it only once
exposure = get_exposure(oqparam)
if oqparam.sites:
return geo.Mesh.from_coords(oqparam.sites)
elif 'sites' in oqparam.inputs:
fname = oqparam.inputs['sites']
header = get_csv_header(fname)
if 'lon' in header:
data = []
for i, row in enumerate(
csv.DictReader(open(fname, encoding='utf-8-sig'))):
if header[0] == 'site_id' and row['site_id'] != str(i):
raise InvalidFile('%s: expected site_id=%d, got %s' %
(fname, i, row['site_id']))
data.append(' '.join([row['lon'], row['lat']]))
elif 'gmfs' in oqparam.inputs:
raise InvalidFile('Missing header in %(sites)s' % oqparam.inputs)
else:
data = [
line.replace(',', ' ')
for line in open(fname, encoding='utf-8-sig')
]
coords = valid.coordinates(','.join(data))
start, stop = oqparam.sites_slice
c = (coords[start:stop]
if header[0] == 'site_id' else sorted(coords[start:stop]))
return geo.Mesh.from_coords(c)
elif 'hazard_curves' in oqparam.inputs:
fname = oqparam.inputs['hazard_curves']
if isinstance(fname, list): # for csv
mesh, pmap = get_pmap_from_csv(oqparam, fname)
else:
raise NotImplementedError('Reading from %s' % fname)
return mesh
elif oqparam.region_grid_spacing:
if oqparam.region:
poly = geo.Polygon.from_wkt(oqparam.region)
elif 'site_model' in oqparam.inputs:
sm = get_site_model(oqparam)
poly = geo.Mesh(sm['lon'], sm['lat']).get_convex_hull()
elif exposure:
poly = exposure.mesh.get_convex_hull()
else:
raise InvalidFile('There is a grid spacing but not a region, '
'nor a site model, nor an exposure in %s' %
oqparam.inputs['job_ini'])
try:
mesh = poly.dilate(oqparam.region_grid_spacing).discretize(
oqparam.region_grid_spacing)
return geo.Mesh.from_coords(zip(mesh.lons, mesh.lats))
except Exception:
raise ValueError('Could not discretize region with grid spacing '
'%(region_grid_spacing)s' % vars(oqparam))
elif 'exposure' in oqparam.inputs:
return exposure.mesh
