def get_source_model_05(node, fname, converter=default):
converter.fname = fname
groups = [] # expect a sequence of sourceGroup nodes
for src_group in node:
if 'sourceGroup' not in src_group.tag:
raise InvalidFile(
'%s: you have an incorrect declaration '
'xmlns="http://openquake.org/xmlns/nrml/0.5"; it should be '
'xmlns="http://openquake.org/xmlns/nrml/0.4"' % fname)
groups.append(converter.convert_node(src_group))
itime = node.get('investigation_time')
if itime is not None:
itime = valid.positivefloat(itime)
stime = node.get('start_time')
if stime is not None:
stime = valid.positivefloat(stime)
return SourceModel(sorted(groups), node.get('name'), itime, stime)
def __init__(self,
src_groups,
name=None,
investigation_time=None,
start_time=None):
self.src_groups = src_groups
self.name = name
if investigation_time is not None:
investigation_time = valid.positivefloat(investigation_time)
self.investigation_time = investigation_time
self.start_time = start_time
def get_source_model_05(node, fname, converter=default):
converter.fname = fname
groups = [] # expect a sequence of sourceGroup nodes
for src_group in node:
if 'sourceGroup' not in src_group.tag:
raise InvalidFile(
'%s: you have an incorrect declaration '
'xmlns="http://openquake.org/xmlns/nrml/0.5"; it should be '
'xmlns="http://openquake.org/xmlns/nrml/0.4"' % fname)
sg = converter.convert_node(src_group)
if len(sg):
# a source group can be empty if the source_id filtering is on
groups.append(sg)
itime = node.get('investigation_time')
if itime is not None:
itime = valid.positivefloat(itime)
stime = node.get('start_time')
if stime is not None:
stime = valid.positivefloat(stime)
return SourceModel(sorted(groups), node.get('name'), itime, stime)
def _read_csv(self, csvnames, dirname):
"""
:param csvnames: names of csv files, space separated
:param dirname: the directory where the csv files are
:yields: asset nodes
"""
expected_header = self._csv_header()
fnames = [os.path.join(dirname, f) for f in csvnames.split()]
for fname in fnames:
with open(fname, encoding='utf-8') as f:
fields = next(csv.reader(f))
header = set(fields)
if len(header) < len(fields):
raise InvalidFile(
'%s: The header %s contains a duplicated field' %
(fname, header))
elif expected_header - header:
raise InvalidFile(
'Unexpected header in %s\nExpected: %s\nGot: %s' %
(fname, sorted(expected_header), sorted(header)))
occupancy_periods = self.occupancy_periods.split()
for fname in fnames:
with open(fname, encoding='utf-8') as f:
for i, dic in enumerate(csv.DictReader(f), 1):
asset = Node('asset', lineno=i)
with context(fname, asset):
asset['id'] = dic['id']
asset['number'] = valid.positivefloat(dic['number'])
asset['taxonomy'] = dic['taxonomy']
if 'area' in dic: # optional attribute
asset['area'] = dic['area']
loc = Node(
'location',
dict(lon=valid.longitude(dic['lon']),
lat=valid.latitude(dic['lat'])))
costs = Node('costs')
for cost in self.cost_types['name']:
a = dict(type=cost, value=dic[cost])
costs.append(Node('cost', a))
occupancies = Node('occupancies')
for period in occupancy_periods:
a = dict(occupants=float(dic[period]),
period=period)
occupancies.append(Node('occupancy', a))
tags = Node('tags')
for tagname in self.tagcol.tagnames:
if tagname != 'taxonomy':
tags.attrib[tagname] = dic[tagname]
asset.nodes.extend([loc, costs, occupancies, tags])
if i % 100000 == 0:
logging.info('Read %d assets', i)
yield asset
def _read_csv(self):
"""
:yields: asset nodes
"""
expected_header = self._csv_header()
for fname in self.datafiles:
with open(fname, encoding='utf-8') as f:
fields = next(csv.reader(f))
header = set(fields)
if len(header) < len(fields):
raise InvalidFile(
'%s: The header %s contains a duplicated field' %
(fname, header))
elif expected_header - header - {'exposure', 'country'}:
raise InvalidFile(
'Unexpected header in %s\nExpected: %s\nGot: %s' %
(fname, sorted(expected_header), sorted(header)))
occupancy_periods = self.occupancy_periods.split()
for fname in self.datafiles:
with open(fname, encoding='utf-8') as f:
for i, dic in enumerate(csv.DictReader(f), 1):
asset = Node('asset', lineno=i)
with context(fname, asset):
asset['id'] = dic['id']
asset['number'] = valid.positivefloat(dic['number'])
asset['taxonomy'] = dic['taxonomy']
if 'area' in dic: # optional attribute
asset['area'] = dic['area']
loc = Node(
'location',
dict(lon=valid.longitude(dic['lon']),
lat=valid.latitude(dic['lat'])))
costs = Node('costs')
for cost in self.cost_types['name']:
a = dict(type=cost, value=dic[cost])
if 'retrofitted' in dic:
a['retrofitted'] = dic['retrofitted']
costs.append(Node('cost', a))
occupancies = Node('occupancies')
for period in occupancy_periods:
a = dict(occupants=float(dic[period]),
period=period)
occupancies.append(Node('occupancy', a))
tags = Node('tags')
for tagname in self.tagcol.tagnames:
if tagname not in ('taxonomy', 'exposure',
'country'):
tags.attrib[tagname] = dic[tagname]
asset.nodes.extend([loc, costs, occupancies, tags])
yield asset
def _read_csv(self):
"""
:yields: asset nodes
"""
expected_header = self._csv_header()
for fname in self.datafiles:
with open(fname, encoding='utf-8') as f:
fields = next(csv.reader(f))
header = set(fields)
if len(header) < len(fields):
raise InvalidFile(
'%s: The header %s contains a duplicated field' %
(fname, header))
elif expected_header - header - {'exposure', 'country'}:
raise InvalidFile(
'Unexpected header in %s\nExpected: %s\nGot: %s' %
(fname, sorted(expected_header), sorted(header)))
occupancy_periods = self.occupancy_periods.split()
for fname in self.datafiles:
with open(fname, encoding='utf-8') as f:
for i, dic in enumerate(csv.DictReader(f), 1):
asset = Node('asset', lineno=i)
with context(fname, asset):
asset['id'] = dic['id']
asset['number'] = valid.positivefloat(dic['number'])
asset['taxonomy'] = dic['taxonomy']
if 'area' in dic: # optional attribute
asset['area'] = dic['area']
loc = Node('location',
dict(lon=valid.longitude(dic['lon']),
lat=valid.latitude(dic['lat'])))
costs = Node('costs')
for cost in self.cost_types['name']:
a = dict(type=cost, value=dic[cost])
if 'retrofitted' in dic:
a['retrofitted'] = dic['retrofitted']
costs.append(Node('cost', a))
occupancies = Node('occupancies')
for period in occupancy_periods:
a = dict(occupants=float(dic[period]),
period=period)
occupancies.append(Node('occupancy', a))
tags = Node('tags')
for tagname in self.tagcol.tagnames:
if tagname not in (
'taxonomy', 'exposure', 'country'):
tags.attrib[tagname] = dic[tagname]
asset.nodes.extend([loc, costs, occupancies, tags])
yield asset
def test_positivefloat(self):
self.assertEqual(valid.positiveint('1'), 1)
with self.assertRaises(ValueError):
valid.positivefloat('-1')
self.assertEqual(valid.positivefloat('1.1'), 1.1)
def damage_triple(value, ds, mean, stddev):
return ds, valid.positivefloat(mean), valid.positivefloat(stddev)
def asset_mean_stddev(value, assetRef, mean, stdDev):
return assetRef, valid.positivefloat(mean), valid.positivefloat(stdDev)
def test_positivefloat(self):
self.assertEqual(valid.positiveint('1'), 1)
with self.assertRaises(ValueError):
valid.positivefloat('-1')
self.assertEqual(valid.positivefloat('1.1'), 1.1)
def damage_triple(value, ds, mean, stddev):
return ds, valid.positivefloat(mean), valid.positivefloat(stddev)
def asset_mean_stddev(value, assetRef, mean, stdDev):
return assetRef, valid.positivefloat(mean), valid.positivefloat(stdDev)
