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gem/oq-engine | openquake/calculators/export/hazard.py | export_ruptures_csv | def export_ruptures_csv(ekey, dstore):
"""
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object
"""
oq = dstore['oqparam']
if 'scenario' in oq.calculation_mode:
return []
dest = dstore.export_path('ruptures.csv')
header = ('rupid multiplicity mag centroid_lon centroid_lat '
'centroid_depth trt strike dip rake boundary').split()
rows = []
for rgetter in gen_rupture_getters(dstore):
rups = rgetter.get_ruptures()
rup_data = calc.RuptureData(rgetter.trt, rgetter.rlzs_by_gsim)
for r in rup_data.to_array(rups):
rows.append(
(r['rup_id'], r['multiplicity'], r['mag'],
r['lon'], r['lat'], r['depth'],
rgetter.trt, r['strike'], r['dip'], r['rake'],
r['boundary']))
rows.sort() # by rupture serial
comment = 'investigation_time=%s, ses_per_logic_tree_path=%s' % (
oq.investigation_time, oq.ses_per_logic_tree_path)
writers.write_csv(dest, rows, header=header, sep='\t', comment=comment)
return [dest] | python | def export_ruptures_csv(ekey, dstore):
oq = dstore['oqparam']
if 'scenario' in oq.calculation_mode:
return []
dest = dstore.export_path('ruptures.csv')
header = ('rupid multiplicity mag centroid_lon centroid_lat '
'centroid_depth trt strike dip rake boundary').split()
rows = []
for rgetter in gen_rupture_getters(dstore):
rups = rgetter.get_ruptures()
rup_data = calc.RuptureData(rgetter.trt, rgetter.rlzs_by_gsim)
for r in rup_data.to_array(rups):
rows.append(
(r['rup_id'], r['multiplicity'], r['mag'],
r['lon'], r['lat'], r['depth'],
rgetter.trt, r['strike'], r['dip'], r['rake'],
r['boundary']))
rows.sort()
comment = 'investigation_time=%s, ses_per_logic_tree_path=%s' % (
oq.investigation_time, oq.ses_per_logic_tree_path)
writers.write_csv(dest, rows, header=header, sep='\t', comment=comment)
return [dest] | [
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gem/oq-engine | openquake/calculators/export/hazard.py | export_hmaps_csv | def export_hmaps_csv(key, dest, sitemesh, array, comment):
"""
Export the hazard maps of the given realization into CSV.
:param key: output_type and export_type
:param dest: name of the exported file
:param sitemesh: site collection
:param array: a composite array of dtype hmap_dt
:param comment: comment to use as header of the exported CSV file
"""
curves = util.compose_arrays(sitemesh, array)
writers.write_csv(dest, curves, comment=comment)
return [dest] | python | def export_hmaps_csv(key, dest, sitemesh, array, comment):
curves = util.compose_arrays(sitemesh, array)
writers.write_csv(dest, curves, comment=comment)
return [dest] | [
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gem/oq-engine | openquake/calculators/export/hazard.py | add_imt | def add_imt(fname, imt):
"""
>>> add_imt('/path/to/hcurve_23.csv', 'SA(0.1)')
'/path/to/hcurve-SA(0.1)_23.csv'
"""
name = os.path.basename(fname)
newname = re.sub(r'(_\d+\.)', '-%s\\1' % imt, name)
return os.path.join(os.path.dirname(fname), newname) | python | def add_imt(fname, imt):
name = os.path.basename(fname)
newname = re.sub(r'(_\d+\.)', '-%s\\1' % imt, name)
return os.path.join(os.path.dirname(fname), newname) | [
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gem/oq-engine | openquake/calculators/export/hazard.py | export_hcurves_by_imt_csv | def export_hcurves_by_imt_csv(
key, kind, rlzs_assoc, fname, sitecol, array, oq, checksum):
"""
Export the curves of the given realization into CSV.
:param key: output_type and export_type
:param kind: a string with the kind of output (realization or statistics)
:param rlzs_assoc: a :class:`openquake.commonlib.source.RlzsAssoc` instance
:param fname: name of the exported file
:param sitecol: site collection
:param array: an array of shape (N, L) and dtype numpy.float32
:param oq: job.ini parameters
"""
nsites = len(sitecol)
fnames = []
for imt, imls in oq.imtls.items():
slc = oq.imtls(imt)
dest = add_imt(fname, imt)
lst = [('lon', F32), ('lat', F32), ('depth', F32)]
for iml in imls:
lst.append(('poe-%s' % iml, F32))
hcurves = numpy.zeros(nsites, lst)
for sid, lon, lat, dep in zip(
range(nsites), sitecol.lons, sitecol.lats, sitecol.depths):
hcurves[sid] = (lon, lat, dep) + tuple(array[sid, slc])
fnames.append(writers.write_csv(dest, hcurves, comment=_comment(
rlzs_assoc, kind, oq.investigation_time) + (
', imt="%s", checksum=%d' % (imt, checksum)
), header=[name for (name, dt) in lst]))
return fnames | python | def export_hcurves_by_imt_csv(
key, kind, rlzs_assoc, fname, sitecol, array, oq, checksum):
nsites = len(sitecol)
fnames = []
for imt, imls in oq.imtls.items():
slc = oq.imtls(imt)
dest = add_imt(fname, imt)
lst = [('lon', F32), ('lat', F32), ('depth', F32)]
for iml in imls:
lst.append(('poe-%s' % iml, F32))
hcurves = numpy.zeros(nsites, lst)
for sid, lon, lat, dep in zip(
range(nsites), sitecol.lons, sitecol.lats, sitecol.depths):
hcurves[sid] = (lon, lat, dep) + tuple(array[sid, slc])
fnames.append(writers.write_csv(dest, hcurves, comment=_comment(
rlzs_assoc, kind, oq.investigation_time) + (
', imt="%s", checksum=%d' % (imt, checksum)
), header=[name for (name, dt) in lst]))
return fnames | [
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:param sitecol: site collection
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gem/oq-engine | openquake/calculators/export/hazard.py | hazard_curve_name | def hazard_curve_name(dstore, ekey, kind, rlzs_assoc):
"""
:param calc_id: the calculation ID
:param ekey: the export key
:param kind: the kind of key
:param rlzs_assoc: a RlzsAssoc instance
"""
key, fmt = ekey
prefix = {'hcurves': 'hazard_curve', 'hmaps': 'hazard_map',
'uhs': 'hazard_uhs'}[key]
if kind.startswith('quantile-'): # strip the 7 characters 'hazard_'
fname = dstore.build_fname('quantile_' + prefix[7:], kind[9:], fmt)
else:
fname = dstore.build_fname(prefix, kind, fmt)
return fname | python | def hazard_curve_name(dstore, ekey, kind, rlzs_assoc):
key, fmt = ekey
prefix = {'hcurves': 'hazard_curve', 'hmaps': 'hazard_map',
'uhs': 'hazard_uhs'}[key]
if kind.startswith('quantile-'):
fname = dstore.build_fname('quantile_' + prefix[7:], kind[9:], fmt)
else:
fname = dstore.build_fname(prefix, kind, fmt)
return fname | [
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gem/oq-engine | openquake/calculators/export/hazard.py | get_kkf | def get_kkf(ekey):
"""
:param ekey: export key, for instance ('uhs/rlz-1', 'xml')
:returns: key, kind and fmt from the export key, i.e. 'uhs', 'rlz-1', 'xml'
"""
key, fmt = ekey
if '/' in key:
key, kind = key.split('/', 1)
else:
kind = ''
return key, kind, fmt | python | def get_kkf(ekey):
key, fmt = ekey
if '/' in key:
key, kind = key.split('/', 1)
else:
kind = ''
return key, kind, fmt | [
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gem/oq-engine | openquake/calculators/export/hazard.py | export_hcurves_csv | def export_hcurves_csv(ekey, dstore):
"""
Exports the hazard curves into several .csv files
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object
"""
oq = dstore['oqparam']
info = get_info(dstore)
rlzs_assoc = dstore['csm_info'].get_rlzs_assoc()
R = len(rlzs_assoc.realizations)
sitecol = dstore['sitecol']
sitemesh = get_mesh(sitecol)
key, kind, fmt = get_kkf(ekey)
fnames = []
checksum = dstore.get_attr('/', 'checksum32')
hmap_dt = oq.hmap_dt()
for kind in oq.get_kinds(kind, R):
fname = hazard_curve_name(dstore, (key, fmt), kind, rlzs_assoc)
comment = _comment(rlzs_assoc, kind, oq.investigation_time)
if (key in ('hmaps', 'uhs') and oq.uniform_hazard_spectra or
oq.hazard_maps):
hmap = extract(dstore, 'hmaps?kind=' + kind)[kind]
if key == 'uhs' and oq.poes and oq.uniform_hazard_spectra:
uhs_curves = calc.make_uhs(hmap, info)
writers.write_csv(
fname, util.compose_arrays(sitemesh, uhs_curves),
comment=comment + ', checksum=%d' % checksum)
fnames.append(fname)
elif key == 'hmaps' and oq.poes and oq.hazard_maps:
fnames.extend(
export_hmaps_csv(ekey, fname, sitemesh,
hmap.flatten().view(hmap_dt),
comment + ', checksum=%d' % checksum))
elif key == 'hcurves':
hcurves = extract(dstore, 'hcurves?kind=' + kind)[kind]
fnames.extend(
export_hcurves_by_imt_csv(
ekey, kind, rlzs_assoc, fname, sitecol, hcurves, oq,
checksum))
return sorted(fnames) | python | def export_hcurves_csv(ekey, dstore):
oq = dstore['oqparam']
info = get_info(dstore)
rlzs_assoc = dstore['csm_info'].get_rlzs_assoc()
R = len(rlzs_assoc.realizations)
sitecol = dstore['sitecol']
sitemesh = get_mesh(sitecol)
key, kind, fmt = get_kkf(ekey)
fnames = []
checksum = dstore.get_attr('/', 'checksum32')
hmap_dt = oq.hmap_dt()
for kind in oq.get_kinds(kind, R):
fname = hazard_curve_name(dstore, (key, fmt), kind, rlzs_assoc)
comment = _comment(rlzs_assoc, kind, oq.investigation_time)
if (key in ('hmaps', 'uhs') and oq.uniform_hazard_spectra or
oq.hazard_maps):
hmap = extract(dstore, 'hmaps?kind=' + kind)[kind]
if key == 'uhs' and oq.poes and oq.uniform_hazard_spectra:
uhs_curves = calc.make_uhs(hmap, info)
writers.write_csv(
fname, util.compose_arrays(sitemesh, uhs_curves),
comment=comment + ', checksum=%d' % checksum)
fnames.append(fname)
elif key == 'hmaps' and oq.poes and oq.hazard_maps:
fnames.extend(
export_hmaps_csv(ekey, fname, sitemesh,
hmap.flatten().view(hmap_dt),
comment + ', checksum=%d' % checksum))
elif key == 'hcurves':
hcurves = extract(dstore, 'hcurves?kind=' + kind)[kind]
fnames.extend(
export_hcurves_by_imt_csv(
ekey, kind, rlzs_assoc, fname, sitecol, hcurves, oq,
checksum))
return sorted(fnames) | [
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gem/oq-engine | openquake/calculators/export/hazard.py | get_metadata | def get_metadata(realizations, kind):
"""
:param list realizations:
realization objects
:param str kind:
kind of data, i.e. a key in the datastore
:returns:
a dictionary with smlt_path, gsimlt_path, statistics, quantile_value
"""
metadata = {}
if kind.startswith('rlz-'):
rlz = realizations[int(kind[4:])]
metadata['smlt_path'] = '_'.join(rlz.sm_lt_path)
metadata['gsimlt_path'] = rlz.gsim_rlz.uid
elif kind.startswith('quantile-'):
metadata['statistics'] = 'quantile'
metadata['quantile_value'] = float(kind[9:])
elif kind == 'mean':
metadata['statistics'] = 'mean'
elif kind == 'max':
metadata['statistics'] = 'max'
elif kind == 'std':
metadata['statistics'] = 'std'
return metadata | python | def get_metadata(realizations, kind):
metadata = {}
if kind.startswith('rlz-'):
rlz = realizations[int(kind[4:])]
metadata['smlt_path'] = '_'.join(rlz.sm_lt_path)
metadata['gsimlt_path'] = rlz.gsim_rlz.uid
elif kind.startswith('quantile-'):
metadata['statistics'] = 'quantile'
metadata['quantile_value'] = float(kind[9:])
elif kind == 'mean':
metadata['statistics'] = 'mean'
elif kind == 'max':
metadata['statistics'] = 'max'
elif kind == 'std':
metadata['statistics'] = 'std'
return metadata | [
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gem/oq-engine | openquake/calculators/export/hazard.py | export_gmf | def export_gmf(ekey, dstore):
"""
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object
"""
oq = dstore['oqparam']
if not oq.calculation_mode.startswith('scenario'):
return []
sitecol = dstore['sitecol']
investigation_time = (None if oq.calculation_mode == 'scenario'
else oq.investigation_time)
fmt = ekey[-1]
gmf_data = dstore['gmf_data']
nbytes = gmf_data.attrs['nbytes']
logging.info('Internal size of the GMFs: %s', humansize(nbytes))
if nbytes > GMF_MAX_SIZE:
logging.warning(GMF_WARNING, dstore.filename)
data = gmf_data['data'].value
ses_idx = 1 # for scenario only
events = []
for eid, gmfa in group_array(data, 'eid').items():
rup = Event(eid, ses_idx, sorted(set(gmfa['sid'])), gmfa)
events.append(rup)
fname = dstore.build_fname('gmf', 'scenario', fmt)
writer = hazard_writers.EventBasedGMFXMLWriter(
fname, sm_lt_path='', gsim_lt_path='')
writer.serialize(
GmfCollection(sitecol, oq.imtls, events, investigation_time))
return [fname] | python | def export_gmf(ekey, dstore):
oq = dstore['oqparam']
if not oq.calculation_mode.startswith('scenario'):
return []
sitecol = dstore['sitecol']
investigation_time = (None if oq.calculation_mode == 'scenario'
else oq.investigation_time)
fmt = ekey[-1]
gmf_data = dstore['gmf_data']
nbytes = gmf_data.attrs['nbytes']
logging.info('Internal size of the GMFs: %s', humansize(nbytes))
if nbytes > GMF_MAX_SIZE:
logging.warning(GMF_WARNING, dstore.filename)
data = gmf_data['data'].value
ses_idx = 1
events = []
for eid, gmfa in group_array(data, 'eid').items():
rup = Event(eid, ses_idx, sorted(set(gmfa['sid'])), gmfa)
events.append(rup)
fname = dstore.build_fname('gmf', 'scenario', fmt)
writer = hazard_writers.EventBasedGMFXMLWriter(
fname, sm_lt_path='', gsim_lt_path='')
writer.serialize(
GmfCollection(sitecol, oq.imtls, events, investigation_time))
return [fname] | [
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gem/oq-engine | openquake/calculators/export/hazard.py | save_disagg_to_csv | def save_disagg_to_csv(metadata, matrices):
"""
Save disaggregation matrices to multiple .csv files.
"""
skip_keys = ('Mag', 'Dist', 'Lon', 'Lat', 'Eps', 'TRT')
base_header = ','.join(
'%s=%s' % (key, value) for key, value in metadata.items()
if value is not None and key not in skip_keys)
for disag_tup, (poe, iml, matrix, fname) in matrices.items():
header = '%s,poe=%.7f,iml=%.7e\n' % (base_header, poe, iml)
if disag_tup == ('Mag', 'Lon', 'Lat'):
matrix = numpy.swapaxes(matrix, 0, 1)
matrix = numpy.swapaxes(matrix, 1, 2)
disag_tup = ('Lon', 'Lat', 'Mag')
axis = [metadata[v] for v in disag_tup]
header += ','.join(v for v in disag_tup)
header += ',poe'
# compute axis mid points
axis = [(ax[: -1] + ax[1:]) / 2. if ax.dtype == float
else ax for ax in axis]
values = None
if len(axis) == 1:
values = numpy.array([axis[0], matrix.flatten()]).T
else:
grids = numpy.meshgrid(*axis, indexing='ij')
values = [g.flatten() for g in grids]
values.append(matrix.flatten())
values = numpy.array(values).T
writers.write_csv(fname, values, comment=header, fmt='%.5E') | python | def save_disagg_to_csv(metadata, matrices):
skip_keys = ('Mag', 'Dist', 'Lon', 'Lat', 'Eps', 'TRT')
base_header = ','.join(
'%s=%s' % (key, value) for key, value in metadata.items()
if value is not None and key not in skip_keys)
for disag_tup, (poe, iml, matrix, fname) in matrices.items():
header = '%s,poe=%.7f,iml=%.7e\n' % (base_header, poe, iml)
if disag_tup == ('Mag', 'Lon', 'Lat'):
matrix = numpy.swapaxes(matrix, 0, 1)
matrix = numpy.swapaxes(matrix, 1, 2)
disag_tup = ('Lon', 'Lat', 'Mag')
axis = [metadata[v] for v in disag_tup]
header += ','.join(v for v in disag_tup)
header += ',poe'
axis = [(ax[: -1] + ax[1:]) / 2. if ax.dtype == float
else ax for ax in axis]
values = None
if len(axis) == 1:
values = numpy.array([axis[0], matrix.flatten()]).T
else:
grids = numpy.meshgrid(*axis, indexing='ij')
values = [g.flatten() for g in grids]
values.append(matrix.flatten())
values = numpy.array(values).T
writers.write_csv(fname, values, comment=header, fmt='%.5E') | [
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gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
for spec of input and result values.
"""
# extracting dictionary of coefficients specific to required
# intensity measure type.
C = self.COEFFS[imt]
if isinstance(imt, PGA):
imt_per = 0.0
else:
imt_per = imt.period
# Fix site parameters for consistent dS2S application.
sites.vs30 = np.array([250])
sites.z1pt0 = np.array([330])
# intensity on a reference soil is used for both mean
# and stddev calculations.
ln_y_ref = self._get_ln_y_ref(rup, dists, C)
# exp1 and exp2 are parts of eq. 7
exp1 = np.exp(C['phi3'] * (sites.vs30.clip(-np.inf, 1130) - 360))
exp2 = np.exp(C['phi3'] * (1130 - 360))
# v1 is the period dependent site term. The Vs30 above which, the
# amplification is constant
v1 = self._get_v1(imt)
# Get log-mean from regular unadjusted model
b13a_mean = self._get_mean(sites, C, ln_y_ref, exp1, exp2, v1)
# Adjust mean and standard deviation
mean = b13a_mean + self._get_dL2L(imt_per) + self._get_dS2S(imt_per)
mean += convert_to_LHC(imt)
stddevs = self._get_adjusted_stddevs(sites, rup, C, stddev_types,
ln_y_ref, exp1, exp2, imt_per)
return mean, stddevs | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
C = self.COEFFS[imt]
if isinstance(imt, PGA):
imt_per = 0.0
else:
imt_per = imt.period
sites.vs30 = np.array([250])
sites.z1pt0 = np.array([330])
ln_y_ref = self._get_ln_y_ref(rup, dists, C)
exp1 = np.exp(C['phi3'] * (sites.vs30.clip(-np.inf, 1130) - 360))
exp2 = np.exp(C['phi3'] * (1130 - 360))
v1 = self._get_v1(imt)
b13a_mean = self._get_mean(sites, C, ln_y_ref, exp1, exp2, v1)
mean = b13a_mean + self._get_dL2L(imt_per) + self._get_dS2S(imt_per)
mean += convert_to_LHC(imt)
stddevs = self._get_adjusted_stddevs(sites, rup, C, stddev_types,
ln_y_ref, exp1, exp2, imt_per)
return mean, stddevs | [
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gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._interp_function | def _interp_function(self, y_ip1, y_i, t_ip1, t_i, imt_per):
"""
Generic interpolation function used in equation 19 of 2013 report.
"""
return y_i + (y_ip1 - y_i) / (t_ip1 - t_i) * (imt_per - t_i) | python | def _interp_function(self, y_ip1, y_i, t_ip1, t_i, imt_per):
return y_i + (y_ip1 - y_i) / (t_ip1 - t_i) * (imt_per - t_i) | [
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gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._get_SRF_tau | def _get_SRF_tau(self, imt_per):
"""
Table 6 and equation 19 of 2013 report.
"""
if imt_per < 1:
srf = 0.87
elif 1 <= imt_per < 5:
srf = self._interp_function(0.58, 0.87, 5, 1, imt_per)
elif 5 <= imt_per <= 10:
srf = 0.58
else:
srf = 1
return srf | python | def _get_SRF_tau(self, imt_per):
if imt_per < 1:
srf = 0.87
elif 1 <= imt_per < 5:
srf = self._interp_function(0.58, 0.87, 5, 1, imt_per)
elif 5 <= imt_per <= 10:
srf = 0.58
else:
srf = 1
return srf | [
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gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._get_SRF_phi | def _get_SRF_phi(self, imt_per):
"""
Table 7 and equation 19 of 2013 report. NB change in notation,
2013 report calls this term 'sigma' but it is referred to here
as phi.
"""
if imt_per < 0.6:
srf = 0.8
elif 0.6 <= imt_per < 1:
srf = self._interp_function(0.7, 0.8, 1, 0.6, imt_per)
elif 1 <= imt_per <= 10:
srf = self._interp_function(0.6, 0.7, 10, 1, imt_per)
else:
srf = 1
return srf | python | def _get_SRF_phi(self, imt_per):
if imt_per < 0.6:
srf = 0.8
elif 0.6 <= imt_per < 1:
srf = self._interp_function(0.7, 0.8, 1, 0.6, imt_per)
elif 1 <= imt_per <= 10:
srf = self._interp_function(0.6, 0.7, 10, 1, imt_per)
else:
srf = 1
return srf | [
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gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._get_SRF_sigma | def _get_SRF_sigma(self, imt_per):
"""
Table 8 and equation 19 of 2013 report. NB change in notation,
2013 report calls this term 'sigma_t' but it is referred to
here as sigma. Note that Table 8 is identical to Table 7 in
the 2013 report.
"""
if imt_per < 0.6:
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elif 0.6 <= imt_per < 1:
srf = self._interp_function(0.7, 0.8, 1, 0.6, imt_per)
elif 1 <= imt_per <= 10:
srf = self._interp_function(0.6, 0.7, 10, 1, imt_per)
else:
srf = 1
return srf | python | def _get_SRF_sigma(self, imt_per):
if imt_per < 0.6:
srf = 0.8
elif 0.6 <= imt_per < 1:
srf = self._interp_function(0.7, 0.8, 1, 0.6, imt_per)
elif 1 <= imt_per <= 10:
srf = self._interp_function(0.6, 0.7, 10, 1, imt_per)
else:
srf = 1
return srf | [
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gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._get_dL2L | def _get_dL2L(self, imt_per):
"""
Table 3 and equation 19 of 2013 report.
"""
if imt_per < 0.18:
dL2L = -0.06
elif 0.18 <= imt_per < 0.35:
dL2L = self._interp_function(0.12, -0.06, 0.35, 0.18, imt_per)
elif 0.35 <= imt_per <= 10:
dL2L = self._interp_function(0.65, 0.12, 10, 0.35, imt_per)
else:
dL2L = 0
return dL2L | python | def _get_dL2L(self, imt_per):
if imt_per < 0.18:
dL2L = -0.06
elif 0.18 <= imt_per < 0.35:
dL2L = self._interp_function(0.12, -0.06, 0.35, 0.18, imt_per)
elif 0.35 <= imt_per <= 10:
dL2L = self._interp_function(0.65, 0.12, 10, 0.35, imt_per)
else:
dL2L = 0
return dL2L | [
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gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._get_dS2S | def _get_dS2S(self, imt_per):
"""
Table 4 of 2013 report
"""
if imt_per == 0:
dS2S = 0.05
elif 0 < imt_per < 0.15:
dS2S = self._interp_function(-0.15, 0.05, 0.15, 0, imt_per)
elif 0.15 <= imt_per < 0.45:
dS2S = self._interp_function(0.4, -0.15, 0.45, 0.15, imt_per)
elif 0.45 <= imt_per < 3.2:
dS2S = 0.4
elif 3.2 <= imt_per < 5:
dS2S = self._interp_function(0.08, 0.4, 5, 3.2, imt_per)
elif 5 <= imt_per <= 10:
dS2S = 0.08
else:
dS2S = 0
return dS2S | python | def _get_dS2S(self, imt_per):
if imt_per == 0:
dS2S = 0.05
elif 0 < imt_per < 0.15:
dS2S = self._interp_function(-0.15, 0.05, 0.15, 0, imt_per)
elif 0.15 <= imt_per < 0.45:
dS2S = self._interp_function(0.4, -0.15, 0.45, 0.15, imt_per)
elif 0.45 <= imt_per < 3.2:
dS2S = 0.4
elif 3.2 <= imt_per < 5:
dS2S = self._interp_function(0.08, 0.4, 5, 3.2, imt_per)
elif 5 <= imt_per <= 10:
dS2S = 0.08
else:
dS2S = 0
return dS2S | [
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gem/oq-engine | openquake/hazardlib/calc/filters.py | context | def context(src):
"""
Used to add the source_id to the error message. To be used as
with context(src):
operation_with(src)
Typically the operation is filtering a source, that can fail for
tricky geometries.
"""
try:
yield
except Exception:
etype, err, tb = sys.exc_info()
msg = 'An error occurred with source id=%s. Error: %s'
msg %= (src.source_id, err)
raise_(etype, msg, tb) | python | def context(src):
try:
yield
except Exception:
etype, err, tb = sys.exc_info()
msg = 'An error occurred with source id=%s. Error: %s'
msg %= (src.source_id, err)
raise_(etype, msg, tb) | [
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Typically the operation is filtering a source, that can fail for
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gem/oq-engine | openquake/hazardlib/calc/filters.py | split_sources | def split_sources(srcs):
"""
:param srcs: sources
:returns: a pair (split sources, split time) or just the split_sources
"""
from openquake.hazardlib.source import splittable
sources = []
split_time = {} # src.id -> time
for src in srcs:
t0 = time.time()
mag_a, mag_b = src.get_min_max_mag()
min_mag = src.min_mag
if mag_b < min_mag: # discard the source completely
continue
has_serial = hasattr(src, 'serial')
if has_serial:
src.serial = numpy.arange(
src.serial, src.serial + src.num_ruptures)
if not splittable(src):
sources.append(src)
split_time[src.id] = time.time() - t0
continue
if min_mag:
splits = []
for s in src:
s.min_mag = min_mag
mag_a, mag_b = s.get_min_max_mag()
if mag_b < min_mag:
continue
s.num_ruptures = s.count_ruptures()
if s.num_ruptures:
splits.append(s)
else:
splits = list(src)
split_time[src.id] = time.time() - t0
sources.extend(splits)
has_samples = hasattr(src, 'samples')
if len(splits) > 1:
start = 0
for i, split in enumerate(splits):
split.source_id = '%s:%s' % (src.source_id, i)
split.src_group_id = src.src_group_id
split.id = src.id
if has_serial:
nr = split.num_ruptures
split.serial = src.serial[start:start + nr]
start += nr
if has_samples:
split.samples = src.samples
elif splits: # single source
splits[0].id = src.id
if has_serial:
splits[0].serial = src.serial
if has_samples:
splits[0].samples = src.samples
return sources, split_time | python | def split_sources(srcs):
from openquake.hazardlib.source import splittable
sources = []
split_time = {}
for src in srcs:
t0 = time.time()
mag_a, mag_b = src.get_min_max_mag()
min_mag = src.min_mag
if mag_b < min_mag:
continue
has_serial = hasattr(src, 'serial')
if has_serial:
src.serial = numpy.arange(
src.serial, src.serial + src.num_ruptures)
if not splittable(src):
sources.append(src)
split_time[src.id] = time.time() - t0
continue
if min_mag:
splits = []
for s in src:
s.min_mag = min_mag
mag_a, mag_b = s.get_min_max_mag()
if mag_b < min_mag:
continue
s.num_ruptures = s.count_ruptures()
if s.num_ruptures:
splits.append(s)
else:
splits = list(src)
split_time[src.id] = time.time() - t0
sources.extend(splits)
has_samples = hasattr(src, 'samples')
if len(splits) > 1:
start = 0
for i, split in enumerate(splits):
split.source_id = '%s:%s' % (src.source_id, i)
split.src_group_id = src.src_group_id
split.id = src.id
if has_serial:
nr = split.num_ruptures
split.serial = src.serial[start:start + nr]
start += nr
if has_samples:
split.samples = src.samples
elif splits:
splits[0].id = src.id
if has_serial:
splits[0].serial = src.serial
if has_samples:
splits[0].samples = src.samples
return sources, split_time | [
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gem/oq-engine | openquake/hazardlib/calc/filters.py | IntegrationDistance.get_bounding_box | def get_bounding_box(self, lon, lat, trt=None, mag=None):
"""
Build a bounding box around the given lon, lat by computing the
maximum_distance at the given tectonic region type and magnitude.
:param lon: longitude
:param lat: latitude
:param trt: tectonic region type, possibly None
:param mag: magnitude, possibly None
:returns: min_lon, min_lat, max_lon, max_lat
"""
if trt is None: # take the greatest integration distance
maxdist = max(self(trt, mag) for trt in self.dic)
else: # get the integration distance for the given TRT
maxdist = self(trt, mag)
a1 = min(maxdist * KM_TO_DEGREES, 90)
a2 = min(angular_distance(maxdist, lat), 180)
return lon - a2, lat - a1, lon + a2, lat + a1 | python | def get_bounding_box(self, lon, lat, trt=None, mag=None):
if trt is None:
maxdist = max(self(trt, mag) for trt in self.dic)
else:
maxdist = self(trt, mag)
a1 = min(maxdist * KM_TO_DEGREES, 90)
a2 = min(angular_distance(maxdist, lat), 180)
return lon - a2, lat - a1, lon + a2, lat + a1 | [
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gem/oq-engine | openquake/hazardlib/calc/filters.py | IntegrationDistance.get_affected_box | def get_affected_box(self, src):
"""
Get the enlarged bounding box of a source.
:param src: a source object
:returns: a bounding box (min_lon, min_lat, max_lon, max_lat)
"""
mag = src.get_min_max_mag()[1]
maxdist = self(src.tectonic_region_type, mag)
bbox = get_bounding_box(src, maxdist)
return (fix_lon(bbox[0]), bbox[1], fix_lon(bbox[2]), bbox[3]) | python | def get_affected_box(self, src):
mag = src.get_min_max_mag()[1]
maxdist = self(src.tectonic_region_type, mag)
bbox = get_bounding_box(src, maxdist)
return (fix_lon(bbox[0]), bbox[1], fix_lon(bbox[2]), bbox[3]) | [
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gem/oq-engine | openquake/hazardlib/calc/filters.py | SourceFilter.sitecol | def sitecol(self):
"""
Read the site collection from .filename and cache it
"""
if 'sitecol' in vars(self):
return self.__dict__['sitecol']
if self.filename is None or not os.path.exists(self.filename):
# case of nofilter/None sitecol
return
with hdf5.File(self.filename, 'r') as h5:
self.__dict__['sitecol'] = sc = h5.get('sitecol')
return sc | python | def sitecol(self):
if 'sitecol' in vars(self):
return self.__dict__['sitecol']
if self.filename is None or not os.path.exists(self.filename):
return
with hdf5.File(self.filename, 'r') as h5:
self.__dict__['sitecol'] = sc = h5.get('sitecol')
return sc | [
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gem/oq-engine | openquake/hazardlib/calc/filters.py | SourceFilter.get_rectangle | def get_rectangle(self, src):
"""
:param src: a source object
:returns: ((min_lon, min_lat), width, height), useful for plotting
"""
min_lon, min_lat, max_lon, max_lat = (
self.integration_distance.get_affected_box(src))
return (min_lon, min_lat), (max_lon - min_lon) % 360, max_lat - min_lat | python | def get_rectangle(self, src):
min_lon, min_lat, max_lon, max_lat = (
self.integration_distance.get_affected_box(src))
return (min_lon, min_lat), (max_lon - min_lon) % 360, max_lat - min_lat | [
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gem/oq-engine | openquake/hazardlib/calc/filters.py | SourceFilter.get_bounding_boxes | def get_bounding_boxes(self, trt=None, mag=None):
"""
:param trt: a tectonic region type (used for the integration distance)
:param mag: a magnitude (used for the integration distance)
:returns: a list of bounding boxes, one per site
"""
bbs = []
for site in self.sitecol:
bb = self.integration_distance.get_bounding_box(
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bbs.append(bb)
return bbs | python | def get_bounding_boxes(self, trt=None, mag=None):
bbs = []
for site in self.sitecol:
bb = self.integration_distance.get_bounding_box(
site.location.longitude, site.location.latitude, trt, mag)
bbs.append(bb)
return bbs | [
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gem/oq-engine | openquake/hazardlib/calc/filters.py | SourceFilter.close_sids | def close_sids(self, rec, trt, mag):
"""
:param rec:
a record with fields minlon, minlat, maxlon, maxlat
:param trt:
tectonic region type string
:param mag:
magnitude
:returns:
the site indices within the bounding box enlarged by the integration
distance for the given TRT and magnitude
"""
if self.sitecol is None:
return []
elif not self.integration_distance: # do not filter
return self.sitecol.sids
if hasattr(rec, 'dtype'):
bbox = rec['minlon'], rec['minlat'], rec['maxlon'], rec['maxlat']
else:
bbox = rec # assume it is a 4-tuple
maxdist = self.integration_distance(trt, mag)
a1 = min(maxdist * KM_TO_DEGREES, 90)
a2 = min(angular_distance(maxdist, bbox[1], bbox[3]), 180)
bb = bbox[0] - a2, bbox[1] - a1, bbox[2] + a2, bbox[3] + a1
if hasattr(self, 'index'): # RtreeFilter
return within(bb, self.index)
return self.sitecol.within_bbox(bb) | python | def close_sids(self, rec, trt, mag):
if self.sitecol is None:
return []
elif not self.integration_distance:
return self.sitecol.sids
if hasattr(rec, 'dtype'):
bbox = rec['minlon'], rec['minlat'], rec['maxlon'], rec['maxlat']
else:
bbox = rec
maxdist = self.integration_distance(trt, mag)
a1 = min(maxdist * KM_TO_DEGREES, 90)
a2 = min(angular_distance(maxdist, bbox[1], bbox[3]), 180)
bb = bbox[0] - a2, bbox[1] - a1, bbox[2] + a2, bbox[3] + a1
if hasattr(self, 'index'):
return within(bb, self.index)
return self.sitecol.within_bbox(bb) | [
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a record with fields minlon, minlat, maxlon, maxlat
:param trt:
tectonic region type string
:param mag:
magnitude
:returns:
the site indices within the bounding box enlarged by the integration
distance for the given TRT and magnitude | [
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gem/oq-engine | openquake/hazardlib/calc/filters.py | SourceFilter.filter | def filter(self, sources):
"""
:param sources: a sequence of sources
:yields: sources with .indices
"""
for src in sources:
if hasattr(src, 'indices'): # already filtered
yield src
continue
box = self.integration_distance.get_affected_box(src)
indices = self.sitecol.within_bbox(box)
if len(indices):
src.indices = indices
yield src | python | def filter(self, sources):
for src in sources:
if hasattr(src, 'indices'):
yield src
continue
box = self.integration_distance.get_affected_box(src)
indices = self.sitecol.within_bbox(box)
if len(indices):
src.indices = indices
yield src | [
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gem/oq-engine | openquake/hazardlib/calc/filters.py | RtreeFilter.filter | def filter(self, sources):
"""
:param sources: a sequence of sources
:yields: rtree-filtered sources
"""
if self.sitecol is None: # do not filter
yield from sources
return
for src in sources:
box = self.integration_distance.get_affected_box(src)
indices = within(box, self.index)
if len(indices):
src.indices = indices
yield src | python | def filter(self, sources):
if self.sitecol is None:
yield from sources
return
for src in sources:
box = self.integration_distance.get_affected_box(src)
indices = within(box, self.index)
if len(indices):
src.indices = indices
yield src | [
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gem/oq-engine | openquake/commands/to_shapefile.py | to_shapefile | def to_shapefile(output, input_nrml_file, validate):
"""
Convert a NRML source model file to ESRI Shapefile(s).
For each type of source geometry defined in the NRML file (point, area,
simple fault, complex fault, planar) a separate shapefile is created. Each
shapefile is differentiated by a specific ending('_point', '_area',
'_simple', '_complex', '_planar').
NB: nonparametric sources are not supported.
"""
input_parser = shapefileparser.SourceModelParser()
source_model = input_parser.read(input_nrml_file, validate)
if not output:
output = os.path.splitext(input_nrml_file)[0]
print('Extracting %s_ files' % output)
shapefileparser.ShapefileParser().write(output, source_model) | python | def to_shapefile(output, input_nrml_file, validate):
input_parser = shapefileparser.SourceModelParser()
source_model = input_parser.read(input_nrml_file, validate)
if not output:
output = os.path.splitext(input_nrml_file)[0]
print('Extracting %s_ files' % output)
shapefileparser.ShapefileParser().write(output, source_model) | [
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gem/oq-engine | openquake/hazardlib/geo/surface/simple_fault.py | simple_fault_node | def simple_fault_node(fault_trace, dip, upper_depth, lower_depth):
"""
:param fault_trace: an object with an attribute .points
:param dip: dip parameter
:param upper_depth: upper seismogenic depth
:param lower_depth: lower seismogenic depth
:returns: a Node of kind simpleFaultGeometry
"""
node = Node('simpleFaultGeometry')
line = []
for p in fault_trace.points:
line.append(p.longitude)
line.append(p.latitude)
node.append(Node('gml:LineString', nodes=[Node('gml:posList', {}, line)]))
node.append(Node('dip', {}, dip))
node.append(Node('upperSeismoDepth', {}, upper_depth))
node.append(Node('lowerSeismoDepth', {}, lower_depth))
return node | python | def simple_fault_node(fault_trace, dip, upper_depth, lower_depth):
node = Node('simpleFaultGeometry')
line = []
for p in fault_trace.points:
line.append(p.longitude)
line.append(p.latitude)
node.append(Node('gml:LineString', nodes=[Node('gml:posList', {}, line)]))
node.append(Node('dip', {}, dip))
node.append(Node('upperSeismoDepth', {}, upper_depth))
node.append(Node('lowerSeismoDepth', {}, lower_depth))
return node | [
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gem/oq-engine | openquake/hazardlib/geo/surface/simple_fault.py | SimpleFaultSurface.check_fault_data | def check_fault_data(cls, fault_trace, upper_seismogenic_depth,
lower_seismogenic_depth, dip, mesh_spacing):
"""
Verify the fault data and raise ``ValueError`` if anything is wrong.
This method doesn't have to be called by hands before creating the
surface object, because it is called from :meth:`from_fault_data`.
"""
if not len(fault_trace) >= 2:
raise ValueError("the fault trace must have at least two points")
if not fault_trace.horizontal():
raise ValueError("the fault trace must be horizontal")
tlats = [point.latitude for point in fault_trace.points]
tlons = [point.longitude for point in fault_trace.points]
if geo_utils.line_intersects_itself(tlons, tlats):
raise ValueError("fault trace intersects itself")
if not 0.0 < dip <= 90.0:
raise ValueError("dip must be between 0.0 and 90.0")
if not lower_seismogenic_depth > upper_seismogenic_depth:
raise ValueError("lower seismogenic depth must be greater than "
"upper seismogenic depth")
if not upper_seismogenic_depth >= fault_trace[0].depth:
raise ValueError("upper seismogenic depth must be greater than "
"or equal to depth of fault trace")
if not mesh_spacing > 0.0:
raise ValueError("mesh spacing must be positive") | python | def check_fault_data(cls, fault_trace, upper_seismogenic_depth,
lower_seismogenic_depth, dip, mesh_spacing):
if not len(fault_trace) >= 2:
raise ValueError("the fault trace must have at least two points")
if not fault_trace.horizontal():
raise ValueError("the fault trace must be horizontal")
tlats = [point.latitude for point in fault_trace.points]
tlons = [point.longitude for point in fault_trace.points]
if geo_utils.line_intersects_itself(tlons, tlats):
raise ValueError("fault trace intersects itself")
if not 0.0 < dip <= 90.0:
raise ValueError("dip must be between 0.0 and 90.0")
if not lower_seismogenic_depth > upper_seismogenic_depth:
raise ValueError("lower seismogenic depth must be greater than "
"upper seismogenic depth")
if not upper_seismogenic_depth >= fault_trace[0].depth:
raise ValueError("upper seismogenic depth must be greater than "
"or equal to depth of fault trace")
if not mesh_spacing > 0.0:
raise ValueError("mesh spacing must be positive") | [
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gem/oq-engine | openquake/hazardlib/geo/surface/simple_fault.py | SimpleFaultSurface.from_fault_data | def from_fault_data(cls, fault_trace, upper_seismogenic_depth,
lower_seismogenic_depth, dip, mesh_spacing):
"""
Create and return a fault surface using fault source data.
:param openquake.hazardlib.geo.line.Line fault_trace:
Geographical line representing the intersection between the fault
surface and the earth surface. The line must be horizontal (i.e.
all depth values must be equal). If the depths are not given, they
are assumed to be zero, meaning the trace intersects the surface at
sea level, e.g. fault_trace = Line([Point(1, 1), Point(1, 2)]).
:param upper_seismo_depth:
Minimum depth ruptures can reach, in km (i.e. depth
to fault's top edge).
:param lower_seismo_depth:
Maximum depth ruptures can reach, in km (i.e. depth
to fault's bottom edge).
:param dip:
Dip angle (i.e. angle between fault surface
and earth surface), in degrees.
:param mesh_spacing:
Distance between two subsequent points in a mesh, in km.
:returns:
An instance of :class:`SimpleFaultSurface` created using that data.
Uses :meth:`check_fault_data` for checking parameters.
"""
cls.check_fault_data(fault_trace, upper_seismogenic_depth,
lower_seismogenic_depth, dip, mesh_spacing)
# Loops over points in the top edge, for each point
# on the top edge compute corresponding point on the bottom edge, then
# computes equally spaced points between top and bottom points.
vdist_top = upper_seismogenic_depth - fault_trace[0].depth
vdist_bottom = lower_seismogenic_depth - fault_trace[0].depth
hdist_top = vdist_top / math.tan(math.radians(dip))
hdist_bottom = vdist_bottom / math.tan(math.radians(dip))
strike = fault_trace[0].azimuth(fault_trace[-1])
azimuth = (strike + 90.0) % 360
mesh = []
for point in fault_trace.resample(mesh_spacing):
top = point.point_at(hdist_top, vdist_top, azimuth)
bottom = point.point_at(hdist_bottom, vdist_bottom, azimuth)
mesh.append(top.equally_spaced_points(bottom, mesh_spacing))
# number of rows corresponds to number of points along dip
# number of columns corresponds to number of points along strike
surface_points = numpy.array(mesh).transpose().tolist()
mesh = RectangularMesh.from_points_list(surface_points)
assert 1 not in mesh.shape, (
"Mesh must have at least 2 nodes along both length and width."
" Possible cause: Mesh spacing could be too large with respect to"
" the fault length and width."
)
self = cls(mesh)
self.surface_nodes = [simple_fault_node(
fault_trace, dip,
upper_seismogenic_depth, lower_seismogenic_depth)]
return self | python | def from_fault_data(cls, fault_trace, upper_seismogenic_depth,
lower_seismogenic_depth, dip, mesh_spacing):
cls.check_fault_data(fault_trace, upper_seismogenic_depth,
lower_seismogenic_depth, dip, mesh_spacing)
vdist_top = upper_seismogenic_depth - fault_trace[0].depth
vdist_bottom = lower_seismogenic_depth - fault_trace[0].depth
hdist_top = vdist_top / math.tan(math.radians(dip))
hdist_bottom = vdist_bottom / math.tan(math.radians(dip))
strike = fault_trace[0].azimuth(fault_trace[-1])
azimuth = (strike + 90.0) % 360
mesh = []
for point in fault_trace.resample(mesh_spacing):
top = point.point_at(hdist_top, vdist_top, azimuth)
bottom = point.point_at(hdist_bottom, vdist_bottom, azimuth)
mesh.append(top.equally_spaced_points(bottom, mesh_spacing))
surface_points = numpy.array(mesh).transpose().tolist()
mesh = RectangularMesh.from_points_list(surface_points)
assert 1 not in mesh.shape, (
"Mesh must have at least 2 nodes along both length and width."
" Possible cause: Mesh spacing could be too large with respect to"
" the fault length and width."
)
self = cls(mesh)
self.surface_nodes = [simple_fault_node(
fault_trace, dip,
upper_seismogenic_depth, lower_seismogenic_depth)]
return self | [
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:param openquake.hazardlib.geo.line.Line fault_trace:
Geographical line representing the intersection between the fault
surface and the earth surface. The line must be horizontal (i.e.
all depth values must be equal). If the depths are not given, they
are assumed to be zero, meaning the trace intersects the surface at
sea level, e.g. fault_trace = Line([Point(1, 1), Point(1, 2)]).
:param upper_seismo_depth:
Minimum depth ruptures can reach, in km (i.e. depth
to fault's top edge).
:param lower_seismo_depth:
Maximum depth ruptures can reach, in km (i.e. depth
to fault's bottom edge).
:param dip:
Dip angle (i.e. angle between fault surface
and earth surface), in degrees.
:param mesh_spacing:
Distance between two subsequent points in a mesh, in km.
:returns:
An instance of :class:`SimpleFaultSurface` created using that data.
Uses :meth:`check_fault_data` for checking parameters. | [
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gem/oq-engine | openquake/hazardlib/geo/surface/simple_fault.py | SimpleFaultSurface.get_fault_patch_vertices | def get_fault_patch_vertices(cls, rupture_top_edge,
upper_seismogenic_depth,
lower_seismogenic_depth, dip, index_patch=1):
"""
Get surface main vertices.
Parameters are the same as for :meth:`from_fault_data`, excluding
fault_trace, and mesh spacing.
:param rupture_top_edge:
A instances of :class:`openquake.hazardlib.geo.line.Line`
representing the rupture surface's top edge.
:param index_patch:
Indicate the patch of the fault in order to output the vertices.
The fault patch numbering follows the same logic of the right-hand
rule i.e. patch with index 1 is the first patch along the trace.
:returns:
Four :class:~openquake.hazardlib.geo.point.Point objects
representing the four vertices of the target patch.
"""
# Similar to :meth:`from_fault_data`, we just don't resample edges
dip_tan = math.tan(math.radians(dip))
hdist_bottom = (
lower_seismogenic_depth - upper_seismogenic_depth) / dip_tan
strike = rupture_top_edge[0].azimuth(rupture_top_edge[-1])
azimuth = (strike + 90.0) % 360
# Collect coordinates of vertices on the top and bottom edge
lons = []
lats = []
deps = []
t_lon = []
t_lat = []
t_dep = []
for point in rupture_top_edge.points:
top_edge_point = point
bottom_edge_point = point.point_at(hdist_bottom, 0, azimuth)
lons.append(top_edge_point.longitude)
lats.append(top_edge_point.latitude)
deps.append(upper_seismogenic_depth)
t_lon.append(bottom_edge_point.longitude)
t_lat.append(bottom_edge_point.latitude)
t_dep.append(lower_seismogenic_depth)
all_lons = numpy.array(lons + list(reversed(t_lon)), float)
all_lats = numpy.array(lats + list(reversed(t_lat)), float)
all_deps = numpy.array(deps + list(reversed(t_dep)), float)
index1 = int(index_patch - 1)
index2 = int(index_patch)
index3 = int(2 * len(rupture_top_edge) - (index_patch + 1))
index4 = int(2 * len(rupture_top_edge) - index_patch)
p0 = Point(all_lons[index1], all_lats[index1], all_deps[index1])
p1 = Point(all_lons[index2], all_lats[index2], all_deps[index2])
p2 = Point(all_lons[index3], all_lats[index3], all_deps[index3])
p3 = Point(all_lons[index4], all_lats[index4], all_deps[index4])
return p0, p1, p2, p3 | python | def get_fault_patch_vertices(cls, rupture_top_edge,
upper_seismogenic_depth,
lower_seismogenic_depth, dip, index_patch=1):
dip_tan = math.tan(math.radians(dip))
hdist_bottom = (
lower_seismogenic_depth - upper_seismogenic_depth) / dip_tan
strike = rupture_top_edge[0].azimuth(rupture_top_edge[-1])
azimuth = (strike + 90.0) % 360
lons = []
lats = []
deps = []
t_lon = []
t_lat = []
t_dep = []
for point in rupture_top_edge.points:
top_edge_point = point
bottom_edge_point = point.point_at(hdist_bottom, 0, azimuth)
lons.append(top_edge_point.longitude)
lats.append(top_edge_point.latitude)
deps.append(upper_seismogenic_depth)
t_lon.append(bottom_edge_point.longitude)
t_lat.append(bottom_edge_point.latitude)
t_dep.append(lower_seismogenic_depth)
all_lons = numpy.array(lons + list(reversed(t_lon)), float)
all_lats = numpy.array(lats + list(reversed(t_lat)), float)
all_deps = numpy.array(deps + list(reversed(t_dep)), float)
index1 = int(index_patch - 1)
index2 = int(index_patch)
index3 = int(2 * len(rupture_top_edge) - (index_patch + 1))
index4 = int(2 * len(rupture_top_edge) - index_patch)
p0 = Point(all_lons[index1], all_lats[index1], all_deps[index1])
p1 = Point(all_lons[index2], all_lats[index2], all_deps[index2])
p2 = Point(all_lons[index3], all_lats[index3], all_deps[index3])
p3 = Point(all_lons[index4], all_lats[index4], all_deps[index4])
return p0, p1, p2, p3 | [
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Parameters are the same as for :meth:`from_fault_data`, excluding
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:param rupture_top_edge:
A instances of :class:`openquake.hazardlib.geo.line.Line`
representing the rupture surface's top edge.
:param index_patch:
Indicate the patch of the fault in order to output the vertices.
The fault patch numbering follows the same logic of the right-hand
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:returns:
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gem/oq-engine | openquake/hazardlib/geo/surface/simple_fault.py | SimpleFaultSurface.hypocentre_patch_index | def hypocentre_patch_index(cls, hypocentre, rupture_top_edge,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
"""
This methods finds the index of the fault patch including
the hypocentre.
:param hypocentre:
:class:`~openquake.hazardlib.geo.point.Point` object
representing the location of hypocentre.
:param rupture_top_edge:
A instances of :class:`openquake.hazardlib.geo.line.Line`
representing the rupture surface's top edge.
:param upper_seismo_depth:
Minimum depth ruptures can reach, in km (i.e. depth
to fault's top edge).
:param lower_seismo_depth:
Maximum depth ruptures can reach, in km (i.e. depth
to fault's bottom edge).
:param dip:
Dip angle (i.e. angle between fault surface
and earth surface), in degrees.
:return:
An integer corresponding to the index of the fault patch which
contains the hypocentre.
"""
totaln_patch = len(rupture_top_edge)
indexlist = []
dist_list = []
for i, index in enumerate(range(1, totaln_patch)):
p0, p1, p2, p3 = cls.get_fault_patch_vertices(
rupture_top_edge, upper_seismogenic_depth,
lower_seismogenic_depth, dip, index_patch=index)
[normal, dist_to_plane] = get_plane_equation(p0, p1, p2,
hypocentre)
indexlist.append(index)
dist_list.append(dist_to_plane)
if numpy.allclose(dist_to_plane, 0., atol=25., rtol=0.):
return index
break
index = indexlist[numpy.argmin(dist_list)]
return index | python | def hypocentre_patch_index(cls, hypocentre, rupture_top_edge,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
totaln_patch = len(rupture_top_edge)
indexlist = []
dist_list = []
for i, index in enumerate(range(1, totaln_patch)):
p0, p1, p2, p3 = cls.get_fault_patch_vertices(
rupture_top_edge, upper_seismogenic_depth,
lower_seismogenic_depth, dip, index_patch=index)
[normal, dist_to_plane] = get_plane_equation(p0, p1, p2,
hypocentre)
indexlist.append(index)
dist_list.append(dist_to_plane)
if numpy.allclose(dist_to_plane, 0., atol=25., rtol=0.):
return index
break
index = indexlist[numpy.argmin(dist_list)]
return index | [
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:param rupture_top_edge:
A instances of :class:`openquake.hazardlib.geo.line.Line`
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Minimum depth ruptures can reach, in km (i.e. depth
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Maximum depth ruptures can reach, in km (i.e. depth
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gem/oq-engine | openquake/hazardlib/geo/surface/simple_fault.py | SimpleFaultSurface.get_surface_vertexes | def get_surface_vertexes(cls, fault_trace,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
"""
Get surface main vertexes.
Parameters are the same as for :meth:`from_fault_data`, excluding
mesh spacing.
:returns:
Instance of :class:`~openquake.hazardlib.geo.polygon.Polygon`
describing the surface projection of the simple fault with
specified parameters.
"""
# Similar to :meth:`from_fault_data`, we just don't resample edges
dip_tan = math.tan(math.radians(dip))
hdist_top = upper_seismogenic_depth / dip_tan
hdist_bottom = lower_seismogenic_depth / dip_tan
strike = fault_trace[0].azimuth(fault_trace[-1])
azimuth = (strike + 90.0) % 360
# Collect coordinates of vertices on the top and bottom edge
lons = []
lats = []
for point in fault_trace.points:
top_edge_point = point.point_at(hdist_top, 0, azimuth)
bottom_edge_point = point.point_at(hdist_bottom, 0, azimuth)
lons.append(top_edge_point.longitude)
lats.append(top_edge_point.latitude)
lons.append(bottom_edge_point.longitude)
lats.append(bottom_edge_point.latitude)
lons = numpy.array(lons, float)
lats = numpy.array(lats, float)
return lons, lats | python | def get_surface_vertexes(cls, fault_trace,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
dip_tan = math.tan(math.radians(dip))
hdist_top = upper_seismogenic_depth / dip_tan
hdist_bottom = lower_seismogenic_depth / dip_tan
strike = fault_trace[0].azimuth(fault_trace[-1])
azimuth = (strike + 90.0) % 360
lons = []
lats = []
for point in fault_trace.points:
top_edge_point = point.point_at(hdist_top, 0, azimuth)
bottom_edge_point = point.point_at(hdist_bottom, 0, azimuth)
lons.append(top_edge_point.longitude)
lats.append(top_edge_point.latitude)
lons.append(bottom_edge_point.longitude)
lats.append(bottom_edge_point.latitude)
lons = numpy.array(lons, float)
lats = numpy.array(lats, float)
return lons, lats | [
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Parameters are the same as for :meth:`from_fault_data`, excluding
mesh spacing.
:returns:
Instance of :class:`~openquake.hazardlib.geo.polygon.Polygon`
describing the surface projection of the simple fault with
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gem/oq-engine | openquake/hazardlib/geo/surface/simple_fault.py | SimpleFaultSurface.surface_projection_from_fault_data | def surface_projection_from_fault_data(cls, fault_trace,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
"""
Get a surface projection of the simple fault surface.
Parameters are the same as for :meth:`from_fault_data`, excluding
mesh spacing.
:returns:
Instance of :class:`~openquake.hazardlib.geo.polygon.Polygon`
describing the surface projection of the simple fault with
specified parameters.
"""
lons, lats = cls.get_surface_vertexes(fault_trace,
upper_seismogenic_depth,
lower_seismogenic_depth, dip)
return Mesh(lons, lats, depths=None).get_convex_hull() | python | def surface_projection_from_fault_data(cls, fault_trace,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
lons, lats = cls.get_surface_vertexes(fault_trace,
upper_seismogenic_depth,
lower_seismogenic_depth, dip)
return Mesh(lons, lats, depths=None).get_convex_hull() | [
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gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006Asc.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
for spec of input and result values.
"""
# extracting dictionary of coefficients specific to required
# intensity measure type.
C = self.COEFFS_ASC[imt]
# mean value as given by equation 1, p. 901, without considering the
# interface and intraslab terms (that is SI, SS, SSL = 0) and the
# inter and intra event terms, plus the magnitude-squared term
# correction factor (equation 5 p. 909).
mean = self._compute_magnitude_term(C, rup.mag) +\
self._compute_distance_term(C, rup.mag, dists.rrup) +\
self._compute_focal_depth_term(C, rup.hypo_depth) +\
self._compute_faulting_style_term(C, rup.rake) +\
self._compute_site_class_term(C, sites.vs30) +\
self._compute_magnitude_squared_term(P=0.0, M=6.3, Q=C['QC'],
W=C['WC'], mag=rup.mag)
# convert from cm/s**2 to g
mean = np.log(np.exp(mean) * 1e-2 / g)
stddevs = self._get_stddevs(C['sigma'], C['tauC'], stddev_types,
num_sites=len(sites.vs30))
return mean, stddevs | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
C = self.COEFFS_ASC[imt]
mean = self._compute_magnitude_term(C, rup.mag) +\
self._compute_distance_term(C, rup.mag, dists.rrup) +\
self._compute_focal_depth_term(C, rup.hypo_depth) +\
self._compute_faulting_style_term(C, rup.rake) +\
self._compute_site_class_term(C, sites.vs30) +\
self._compute_magnitude_squared_term(P=0.0, M=6.3, Q=C['QC'],
W=C['WC'], mag=rup.mag)
mean = np.log(np.exp(mean) * 1e-2 / g)
stddevs = self._get_stddevs(C['sigma'], C['tauC'], stddev_types,
num_sites=len(sites.vs30))
return mean, stddevs | [
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gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006Asc._compute_distance_term | def _compute_distance_term(self, C, mag, rrup):
"""
Compute second and third terms in equation 1, p. 901.
"""
term1 = C['b'] * rrup
term2 = - np.log(rrup + C['c'] * np.exp(C['d'] * mag))
return term1 + term2 | python | def _compute_distance_term(self, C, mag, rrup):
term1 = C['b'] * rrup
term2 = - np.log(rrup + C['c'] * np.exp(C['d'] * mag))
return term1 + term2 | [
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gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006Asc._compute_focal_depth_term | def _compute_focal_depth_term(self, C, hypo_depth):
"""
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"""
# p. 901. "(i.e, depth is capped at 125 km)".
focal_depth = hypo_depth
if focal_depth > 125.0:
focal_depth = 125.0
# p. 902. "We used the value of 15 km for the
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hc = 15.0
# p. 901. "When h is larger than hc, the depth terms takes
# effect ...". The next sentence specifies h>=hc.
return float(focal_depth >= hc) * C['e'] * (focal_depth - hc) | python | def _compute_focal_depth_term(self, C, hypo_depth):
focal_depth = hypo_depth
if focal_depth > 125.0:
focal_depth = 125.0
hc = 15.0
return float(focal_depth >= hc) * C['e'] * (focal_depth - hc) | [
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gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006Asc._compute_site_class_term | def _compute_site_class_term(self, C, vs30):
"""
Compute nine-th term in equation 1, p. 901.
"""
# map vs30 value to site class, see table 2, p. 901.
site_term = np.zeros(len(vs30))
# hard rock
site_term[vs30 > 1100.0] = C['CH']
# rock
site_term[(vs30 > 600) & (vs30 <= 1100)] = C['C1']
# hard soil
site_term[(vs30 > 300) & (vs30 <= 600)] = C['C2']
# medium soil
site_term[(vs30 > 200) & (vs30 <= 300)] = C['C3']
# soft soil
site_term[vs30 <= 200] = C['C4']
return site_term | python | def _compute_site_class_term(self, C, vs30):
site_term = np.zeros(len(vs30))
site_term[vs30 > 1100.0] = C['CH']
site_term[(vs30 > 600) & (vs30 <= 1100)] = C['C1']
site_term[(vs30 > 300) & (vs30 <= 600)] = C['C2']
site_term[(vs30 > 200) & (vs30 <= 300)] = C['C3']
site_term[vs30 <= 200] = C['C4']
return site_term | [
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gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006Asc._compute_magnitude_squared_term | def _compute_magnitude_squared_term(self, P, M, Q, W, mag):
"""
Compute magnitude squared term, equation 5, p. 909.
"""
return P * (mag - M) + Q * (mag - M) ** 2 + W | python | def _compute_magnitude_squared_term(self, P, M, Q, W, mag):
return P * (mag - M) + Q * (mag - M) ** 2 + W | [
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gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006SSlab._compute_slab_correction_term | def _compute_slab_correction_term(self, C, rrup):
"""
Compute path modification term for slab events, that is
the 8-th term in equation 1, p. 901.
"""
slab_term = C['SSL'] * np.log(rrup)
return slab_term | python | def _compute_slab_correction_term(self, C, rrup):
slab_term = C['SSL'] * np.log(rrup)
return slab_term | [
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gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006AscSGS.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
Using a minimum distance of 5km for the calculation.
"""
dists_mod = copy.deepcopy(dists)
dists_mod.rrup[dists.rrup <= 5.] = 5.
return super().get_mean_and_stddevs(
sites, rup, dists_mod, imt, stddev_types) | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
dists_mod = copy.deepcopy(dists)
dists_mod.rrup[dists.rrup <= 5.] = 5.
return super().get_mean_and_stddevs(
sites, rup, dists_mod, imt, stddev_types) | [
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gem/oq-engine | openquake/engine/utils/__init__.py | confirm | def confirm(prompt):
"""
Ask for confirmation, given a ``prompt`` and return a boolean value.
"""
while True:
try:
answer = input(prompt)
except KeyboardInterrupt:
# the user presses ctrl+c, just say 'no'
return False
answer = answer.strip().lower()
if answer not in ('y', 'n'):
print('Please enter y or n')
continue
return answer == 'y' | python | def confirm(prompt):
while True:
try:
answer = input(prompt)
except KeyboardInterrupt:
return False
answer = answer.strip().lower()
if answer not in ('y', 'n'):
print('Please enter y or n')
continue
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gem/oq-engine | openquake/risklib/asset.py | build_asset_array | def build_asset_array(assets_by_site, tagnames=(), time_event=None):
"""
:param assets_by_site: a list of lists of assets
:param tagnames: a list of tag names
:returns: an array `assetcol`
"""
for assets in assets_by_site:
if len(assets):
first_asset = assets[0]
break
else: # no break
raise ValueError('There are no assets!')
loss_types = []
occupancy_periods = []
for name in sorted(first_asset.values):
if name.startswith('occupants_'):
period = name.split('_', 1)[1]
if period != 'None':
# see scenario_risk test_case_2d
occupancy_periods.append(period)
loss_types.append(name)
# discard occupants for different time periods
else:
loss_types.append('value-' + name)
# loss_types can be ['value-business_interruption', 'value-contents',
# 'value-nonstructural', 'occupants_None', 'occupants_day',
# 'occupants_night', 'occupants_transit']
deductible_d = first_asset.deductibles or {}
limit_d = first_asset.insurance_limits or {}
if deductible_d or limit_d:
logging.warning('Exposures with insuranceLimit/deductible fields are '
'deprecated and may be removed in the future')
retro = ['retrofitted'] if first_asset._retrofitted else []
float_fields = loss_types + retro
int_fields = [(str(name), U16) for name in tagnames]
tagi = {str(name): i for i, name in enumerate(tagnames)}
asset_dt = numpy.dtype(
[('ordinal', U32), ('lon', F32), ('lat', F32), ('site_id', U32),
('number', F32), ('area', F32)] + [
(str(name), float) for name in float_fields] + int_fields)
num_assets = sum(len(assets) for assets in assets_by_site)
assetcol = numpy.zeros(num_assets, asset_dt)
asset_ordinal = 0
fields = set(asset_dt.fields)
for sid, assets_ in enumerate(assets_by_site):
for asset in assets_:
asset.ordinal = asset_ordinal
record = assetcol[asset_ordinal]
asset_ordinal += 1
for field in fields:
if field == 'ordinal':
value = asset.ordinal
elif field == 'number':
value = asset.number
elif field == 'area':
value = asset.area
elif field == 'site_id':
value = sid
elif field == 'lon':
value = asset.location[0]
elif field == 'lat':
value = asset.location[1]
elif field.startswith('occupants_'):
value = asset.values[field]
elif field == 'retrofitted':
value = asset.retrofitted()
elif field in tagnames:
value = asset.tagidxs[tagi[field]]
else:
name, lt = field.split('-')
value = asset.value(lt, time_event)
record[field] = value
return assetcol, ' '.join(occupancy_periods) | python | def build_asset_array(assets_by_site, tagnames=(), time_event=None):
for assets in assets_by_site:
if len(assets):
first_asset = assets[0]
break
else:
raise ValueError('There are no assets!')
loss_types = []
occupancy_periods = []
for name in sorted(first_asset.values):
if name.startswith('occupants_'):
period = name.split('_', 1)[1]
if period != 'None':
occupancy_periods.append(period)
loss_types.append(name)
else:
loss_types.append('value-' + name)
deductible_d = first_asset.deductibles or {}
limit_d = first_asset.insurance_limits or {}
if deductible_d or limit_d:
logging.warning('Exposures with insuranceLimit/deductible fields are '
'deprecated and may be removed in the future')
retro = ['retrofitted'] if first_asset._retrofitted else []
float_fields = loss_types + retro
int_fields = [(str(name), U16) for name in tagnames]
tagi = {str(name): i for i, name in enumerate(tagnames)}
asset_dt = numpy.dtype(
[('ordinal', U32), ('lon', F32), ('lat', F32), ('site_id', U32),
('number', F32), ('area', F32)] + [
(str(name), float) for name in float_fields] + int_fields)
num_assets = sum(len(assets) for assets in assets_by_site)
assetcol = numpy.zeros(num_assets, asset_dt)
asset_ordinal = 0
fields = set(asset_dt.fields)
for sid, assets_ in enumerate(assets_by_site):
for asset in assets_:
asset.ordinal = asset_ordinal
record = assetcol[asset_ordinal]
asset_ordinal += 1
for field in fields:
if field == 'ordinal':
value = asset.ordinal
elif field == 'number':
value = asset.number
elif field == 'area':
value = asset.area
elif field == 'site_id':
value = sid
elif field == 'lon':
value = asset.location[0]
elif field == 'lat':
value = asset.location[1]
elif field.startswith('occupants_'):
value = asset.values[field]
elif field == 'retrofitted':
value = asset.retrofitted()
elif field in tagnames:
value = asset.tagidxs[tagi[field]]
else:
name, lt = field.split('-')
value = asset.value(lt, time_event)
record[field] = value
return assetcol, ' '.join(occupancy_periods) | [
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] | :param assets_by_site: a list of lists of assets
:param tagnames: a list of tag names
:returns: an array `assetcol` | [
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gem/oq-engine | openquake/risklib/asset.py | _get_exposure | def _get_exposure(fname, stop=None):
"""
:param fname:
path of the XML file containing the exposure
:param stop:
node at which to stop parsing (or None)
:returns:
a pair (Exposure instance, list of asset nodes)
"""
[exposure] = nrml.read(fname, stop=stop)
if not exposure.tag.endswith('exposureModel'):
raise InvalidFile('%s: expected exposureModel, got %s' %
(fname, exposure.tag))
description = exposure.description
try:
conversions = exposure.conversions
except AttributeError:
conversions = Node('conversions', nodes=[Node('costTypes', [])])
try:
inslimit = conversions.insuranceLimit
except AttributeError:
inslimit = Node('insuranceLimit', text=True)
try:
deductible = conversions.deductible
except AttributeError:
deductible = Node('deductible', text=True)
try:
area = conversions.area
except AttributeError:
# NB: the area type cannot be an empty string because when sending
# around the CostCalculator object we would run into this numpy bug
# about pickling dictionaries with empty strings:
# https://github.com/numpy/numpy/pull/5475
area = Node('area', dict(type='?'))
try:
occupancy_periods = exposure.occupancyPeriods.text or ''
except AttributeError:
occupancy_periods = ''
try:
tagNames = exposure.tagNames
except AttributeError:
tagNames = Node('tagNames', text='')
tagnames = ~tagNames or []
if set(tagnames) & {'taxonomy', 'exposure', 'country'}:
raise InvalidFile('taxonomy, exposure and country are reserved names '
'you cannot use it in <tagNames>: %s' % fname)
tagnames.insert(0, 'taxonomy')
# read the cost types and make some check
cost_types = []
retrofitted = False
for ct in conversions.costTypes:
with context(fname, ct):
ctname = ct['name']
if ctname == 'structural' and 'retrofittedType' in ct.attrib:
if ct['retrofittedType'] != ct['type']:
raise ValueError(
'The retrofittedType %s is different from the type'
'%s' % (ct['retrofittedType'], ct['type']))
if ct['retrofittedUnit'] != ct['unit']:
raise ValueError(
'The retrofittedUnit %s is different from the unit'
'%s' % (ct['retrofittedUnit'], ct['unit']))
retrofitted = True
cost_types.append(
(ctname, valid.cost_type_type(ct['type']), ct['unit']))
if 'occupants' in cost_types:
cost_types.append(('occupants', 'per_area', 'people'))
cost_types.sort(key=operator.itemgetter(0))
cost_types = numpy.array(cost_types, cost_type_dt)
insurance_limit_is_absolute = il = inslimit.get('isAbsolute')
deductible_is_absolute = de = deductible.get('isAbsolute')
cc = CostCalculator(
{}, {}, {},
True if de is None else de,
True if il is None else il,
{name: i for i, name in enumerate(tagnames)},
)
for ct in cost_types:
name = ct['name'] # structural, nonstructural, ...
cc.cost_types[name] = ct['type'] # aggregated, per_asset, per_area
cc.area_types[name] = area['type']
cc.units[name] = ct['unit']
assets = []
asset_refs = []
exp = Exposure(
exposure['id'], exposure['category'],
description.text, cost_types, occupancy_periods,
insurance_limit_is_absolute, deductible_is_absolute, retrofitted,
area.attrib, assets, asset_refs, cc, TagCollection(tagnames))
assets_text = exposure.assets.text.strip()
if assets_text:
# the <assets> tag contains a list of file names
dirname = os.path.dirname(fname)
exp.datafiles = [os.path.join(dirname, f) for f in assets_text.split()]
else:
exp.datafiles = []
return exp, exposure.assets | python | def _get_exposure(fname, stop=None):
[exposure] = nrml.read(fname, stop=stop)
if not exposure.tag.endswith('exposureModel'):
raise InvalidFile('%s: expected exposureModel, got %s' %
(fname, exposure.tag))
description = exposure.description
try:
conversions = exposure.conversions
except AttributeError:
conversions = Node('conversions', nodes=[Node('costTypes', [])])
try:
inslimit = conversions.insuranceLimit
except AttributeError:
inslimit = Node('insuranceLimit', text=True)
try:
deductible = conversions.deductible
except AttributeError:
deductible = Node('deductible', text=True)
try:
area = conversions.area
except AttributeError:
area = Node('area', dict(type='?'))
try:
occupancy_periods = exposure.occupancyPeriods.text or ''
except AttributeError:
occupancy_periods = ''
try:
tagNames = exposure.tagNames
except AttributeError:
tagNames = Node('tagNames', text='')
tagnames = ~tagNames or []
if set(tagnames) & {'taxonomy', 'exposure', 'country'}:
raise InvalidFile('taxonomy, exposure and country are reserved names '
'you cannot use it in <tagNames>: %s' % fname)
tagnames.insert(0, 'taxonomy')
cost_types = []
retrofitted = False
for ct in conversions.costTypes:
with context(fname, ct):
ctname = ct['name']
if ctname == 'structural' and 'retrofittedType' in ct.attrib:
if ct['retrofittedType'] != ct['type']:
raise ValueError(
'The retrofittedType %s is different from the type'
'%s' % (ct['retrofittedType'], ct['type']))
if ct['retrofittedUnit'] != ct['unit']:
raise ValueError(
'The retrofittedUnit %s is different from the unit'
'%s' % (ct['retrofittedUnit'], ct['unit']))
retrofitted = True
cost_types.append(
(ctname, valid.cost_type_type(ct['type']), ct['unit']))
if 'occupants' in cost_types:
cost_types.append(('occupants', 'per_area', 'people'))
cost_types.sort(key=operator.itemgetter(0))
cost_types = numpy.array(cost_types, cost_type_dt)
insurance_limit_is_absolute = il = inslimit.get('isAbsolute')
deductible_is_absolute = de = deductible.get('isAbsolute')
cc = CostCalculator(
{}, {}, {},
True if de is None else de,
True if il is None else il,
{name: i for i, name in enumerate(tagnames)},
)
for ct in cost_types:
name = ct['name']
cc.cost_types[name] = ct['type']
cc.area_types[name] = area['type']
cc.units[name] = ct['unit']
assets = []
asset_refs = []
exp = Exposure(
exposure['id'], exposure['category'],
description.text, cost_types, occupancy_periods,
insurance_limit_is_absolute, deductible_is_absolute, retrofitted,
area.attrib, assets, asset_refs, cc, TagCollection(tagnames))
assets_text = exposure.assets.text.strip()
if assets_text:
dirname = os.path.dirname(fname)
exp.datafiles = [os.path.join(dirname, f) for f in assets_text.split()]
else:
exp.datafiles = []
return exp, exposure.assets | [
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gem/oq-engine | openquake/risklib/asset.py | CostCalculator.get_units | def get_units(self, loss_types):
"""
:param: a list of loss types
:returns: an array of units as byte strings, suitable for HDF5
"""
lst = []
for lt in loss_types:
if lt.endswith('_ins'):
lt = lt[:-4]
if lt == 'occupants':
unit = 'people'
else:
unit = self.units[lt]
lst.append(encode(unit))
return numpy.array(lst) | python | def get_units(self, loss_types):
lst = []
for lt in loss_types:
if lt.endswith('_ins'):
lt = lt[:-4]
if lt == 'occupants':
unit = 'people'
else:
unit = self.units[lt]
lst.append(encode(unit))
return numpy.array(lst) | [
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gem/oq-engine | openquake/risklib/asset.py | Asset.value | def value(self, loss_type, time_event=None):
"""
:returns: the total asset value for `loss_type`
"""
if loss_type == 'occupants':
return self.values['occupants_' + str(time_event)]
try: # extract from the cache
val = self._cost[loss_type]
except KeyError: # compute
val = self.calc(loss_type, self.values, self.area, self.number)
self._cost[loss_type] = val
return val | python | def value(self, loss_type, time_event=None):
if loss_type == 'occupants':
return self.values['occupants_' + str(time_event)]
try:
val = self._cost[loss_type]
except KeyError:
val = self.calc(loss_type, self.values, self.area, self.number)
self._cost[loss_type] = val
return val | [
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gem/oq-engine | openquake/risklib/asset.py | Asset.deductible | def deductible(self, loss_type, dummy=None):
"""
:returns: the deductible fraction of the asset cost for `loss_type`
"""
val = self.calc(loss_type, self.deductibles, self.area, self.number)
if self.calc.deduct_abs: # convert to relative value
return val / self.calc(loss_type, self.values,
self.area, self.number)
else:
return val | python | def deductible(self, loss_type, dummy=None):
val = self.calc(loss_type, self.deductibles, self.area, self.number)
if self.calc.deduct_abs:
return val / self.calc(loss_type, self.values,
self.area, self.number)
else:
return val | [
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gem/oq-engine | openquake/risklib/asset.py | Asset.insurance_limit | def insurance_limit(self, loss_type, dummy=None):
"""
:returns: the limit fraction of the asset cost for `loss_type`
"""
val = self.calc(loss_type, self.insurance_limits, self.area,
self.number)
if self.calc.limit_abs: # convert to relative value
return val / self.calc(loss_type, self.values,
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else:
return val | python | def insurance_limit(self, loss_type, dummy=None):
val = self.calc(loss_type, self.insurance_limits, self.area,
self.number)
if self.calc.limit_abs:
return val / self.calc(loss_type, self.values,
self.area, self.number)
else:
return val | [
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gem/oq-engine | openquake/risklib/asset.py | Asset.retrofitted | def retrofitted(self):
"""
:returns: the asset retrofitted value
"""
return self.calc('structural', {'structural': self._retrofitted},
self.area, self.number) | python | def retrofitted(self):
return self.calc('structural', {'structural': self._retrofitted},
self.area, self.number) | [
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gem/oq-engine | openquake/risklib/asset.py | Asset.tagmask | def tagmask(self, tags):
"""
:returns: a boolean array with True where the assets has tags
"""
mask = numpy.zeros(len(tags), bool)
for t, tag in enumerate(tags):
tagname, tagvalue = tag.split('=')
mask[t] = self.tagvalue(tagname) == tagvalue
return mask | python | def tagmask(self, tags):
mask = numpy.zeros(len(tags), bool)
for t, tag in enumerate(tags):
tagname, tagvalue = tag.split('=')
mask[t] = self.tagvalue(tagname) == tagvalue
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gem/oq-engine | openquake/risklib/asset.py | TagCollection.add | def add(self, tagname, tagvalue):
"""
:returns: numeric index associated to the tag
"""
dic = getattr(self, tagname + '_idx')
try:
return dic[tagvalue]
except KeyError:
dic[tagvalue] = idx = len(dic)
getattr(self, tagname).append(tagvalue)
if idx > TWO16:
raise InvalidFile('contains more then %d tags' % TWO16)
return idx | python | def add(self, tagname, tagvalue):
dic = getattr(self, tagname + '_idx')
try:
return dic[tagvalue]
except KeyError:
dic[tagvalue] = idx = len(dic)
getattr(self, tagname).append(tagvalue)
if idx > TWO16:
raise InvalidFile('contains more then %d tags' % TWO16)
return idx | [
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gem/oq-engine | openquake/risklib/asset.py | TagCollection.add_tags | def add_tags(self, dic, prefix):
"""
:param dic: a dictionary tagname -> tagvalue
:returns: a list of tag indices, one per tagname
"""
# fill missing tagvalues with "?", raise an error for unknown tagnames
idxs = []
for tagname in self.tagnames:
if tagname in ('exposure', 'country'):
idxs.append(self.add(tagname, prefix))
continue
try:
tagvalue = dic.pop(tagname)
except KeyError:
tagvalue = '?'
else:
if tagvalue in '?*':
raise ValueError(
'Invalid tagvalue="%s"' % tagvalue)
idxs.append(self.add(tagname, tagvalue))
if dic:
raise ValueError(
'Unknown tagname %s or <tagNames> not '
'specified in the exposure' % ', '.join(dic))
return idxs | python | def add_tags(self, dic, prefix):
idxs = []
for tagname in self.tagnames:
if tagname in ('exposure', 'country'):
idxs.append(self.add(tagname, prefix))
continue
try:
tagvalue = dic.pop(tagname)
except KeyError:
tagvalue = '?'
else:
if tagvalue in '?*':
raise ValueError(
'Invalid tagvalue="%s"' % tagvalue)
idxs.append(self.add(tagname, tagvalue))
if dic:
raise ValueError(
'Unknown tagname %s or <tagNames> not '
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return idxs | [
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gem/oq-engine | openquake/risklib/asset.py | TagCollection.get_tag | def get_tag(self, tagname, tagidx):
"""
:returns: the tag associated to the given tagname and tag index
"""
return '%s=%s' % (tagname, decode(getattr(self, tagname)[tagidx])) | python | def get_tag(self, tagname, tagidx):
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gem/oq-engine | openquake/risklib/asset.py | TagCollection.get_tagvalues | def get_tagvalues(self, tagnames, tagidxs):
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"""
values = tuple(getattr(self, tagname)[tagidx + 1]
for tagidx, tagname in zip(tagidxs, tagnames))
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values = tuple(getattr(self, tagname)[tagidx + 1]
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gem/oq-engine | openquake/risklib/asset.py | TagCollection.gen_tags | def gen_tags(self, tagname):
"""
:yields: the tags associated to the given tagname
"""
for tagvalue in getattr(self, tagname):
yield '%s=%s' % (tagname, decode(tagvalue)) | python | def gen_tags(self, tagname):
for tagvalue in getattr(self, tagname):
yield '%s=%s' % (tagname, decode(tagvalue)) | [
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gem/oq-engine | openquake/risklib/asset.py | TagCollection.agg_shape | def agg_shape(self, shp, aggregate_by):
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"""
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"""
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num_taxonomies = numpy.zeros(self.tot_sites, U32)
for sid, arr in dic.items():
num_taxonomies[sid] = len(numpy.unique(arr['taxonomy']))
return num_taxonomies | python | def num_taxonomies_by_site(self):
dic = general.group_array(self.array, 'site_id')
num_taxonomies = numpy.zeros(self.tot_sites, U32)
for sid, arr in dic.items():
num_taxonomies[sid] = len(numpy.unique(arr['taxonomy']))
return num_taxonomies | [
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gem/oq-engine | openquake/risklib/asset.py | AssetCollection.get_aids_by_tag | def get_aids_by_tag(self):
"""
:returns: dict tag -> asset ordinals
"""
aids_by_tag = general.AccumDict(accum=set())
for aid, ass in enumerate(self):
for tagname in self.tagnames:
tag = self.tagcol.get_tag(tagname, ass[tagname])
aids_by_tag[tag].add(aid)
return aids_by_tag | python | def get_aids_by_tag(self):
aids_by_tag = general.AccumDict(accum=set())
for aid, ass in enumerate(self):
for tagname in self.tagnames:
tag = self.tagcol.get_tag(tagname, ass[tagname])
aids_by_tag[tag].add(aid)
return aids_by_tag | [
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gem/oq-engine | openquake/risklib/asset.py | AssetCollection.assets_by_site | def assets_by_site(self):
"""
:returns: numpy array of lists with the assets by each site
"""
assets_by_site = [[] for sid in range(self.tot_sites)]
for i, ass in enumerate(self.array):
assets_by_site[ass['site_id']].append(self[i])
return numpy.array(assets_by_site) | python | def assets_by_site(self):
assets_by_site = [[] for sid in range(self.tot_sites)]
for i, ass in enumerate(self.array):
assets_by_site[ass['site_id']].append(self[i])
return numpy.array(assets_by_site) | [
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gem/oq-engine | openquake/risklib/asset.py | AssetCollection.aggregate_by | def aggregate_by(self, tagnames, array):
"""
:param tagnames: a list of valid tag names
:param array: an array with the same length as the asset collection
:returns: an array of aggregate values with the proper shape
"""
missing = set(tagnames) - set(self.tagcol.tagnames)
if missing:
raise ValueError('Unknown tagname(s) %s' % missing)
A, *shp = array.shape
if A != len(self):
raise ValueError('The array must have length %d, got %d' %
(len(self), A))
if not tagnames:
return array.sum(axis=0)
shape = [len(getattr(self.tagcol, tagname))-1 for tagname in tagnames]
acc = numpy.zeros(shape, (F32, shp) if shp else F32)
for asset, row in zip(self.array, array):
acc[tuple(idx - 1 for idx in asset[tagnames])] += row
return acc | python | def aggregate_by(self, tagnames, array):
missing = set(tagnames) - set(self.tagcol.tagnames)
if missing:
raise ValueError('Unknown tagname(s) %s' % missing)
A, *shp = array.shape
if A != len(self):
raise ValueError('The array must have length %d, got %d' %
(len(self), A))
if not tagnames:
return array.sum(axis=0)
shape = [len(getattr(self.tagcol, tagname))-1 for tagname in tagnames]
acc = numpy.zeros(shape, (F32, shp) if shp else F32)
for asset, row in zip(self.array, array):
acc[tuple(idx - 1 for idx in asset[tagnames])] += row
return acc | [
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gem/oq-engine | openquake/risklib/asset.py | AssetCollection.agg_value | def agg_value(self, *tagnames):
"""
:param tagnames:
tagnames of lengths T1, T2, ... respectively
:returns:
the values of the exposure aggregated by tagnames as an array
of shape (T1, T2, ..., L)
"""
aval = numpy.zeros((len(self), len(self.loss_types)), F32) # (A, L)
for asset in self:
for lti, lt in enumerate(self.loss_types):
if lt == 'occupants':
aval[asset['ordinal'], lti] = asset[lt + '_None']
else:
aval[asset['ordinal'], lti] = asset['value-' + lt]
return self.aggregate_by(list(tagnames), aval) | python | def agg_value(self, *tagnames):
aval = numpy.zeros((len(self), len(self.loss_types)), F32)
for asset in self:
for lti, lt in enumerate(self.loss_types):
if lt == 'occupants':
aval[asset['ordinal'], lti] = asset[lt + '_None']
else:
aval[asset['ordinal'], lti] = asset['value-' + lt]
return self.aggregate_by(list(tagnames), aval) | [
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gem/oq-engine | openquake/risklib/asset.py | AssetCollection.reduce | def reduce(self, sitecol):
"""
:returns: a reduced AssetCollection on the given sitecol
"""
ok_indices = numpy.sum(
[self.array['site_id'] == sid for sid in sitecol.sids],
axis=0, dtype=bool)
new = object.__new__(self.__class__)
vars(new).update(vars(self))
new.array = self.array[ok_indices]
new.array['ordinal'] = numpy.arange(len(new.array))
new.asset_refs = self.asset_refs[ok_indices]
return new | python | def reduce(self, sitecol):
ok_indices = numpy.sum(
[self.array['site_id'] == sid for sid in sitecol.sids],
axis=0, dtype=bool)
new = object.__new__(self.__class__)
vars(new).update(vars(self))
new.array = self.array[ok_indices]
new.array['ordinal'] = numpy.arange(len(new.array))
new.asset_refs = self.asset_refs[ok_indices]
return new | [
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gem/oq-engine | openquake/risklib/asset.py | AssetCollection.reduce_also | def reduce_also(self, sitecol):
"""
:returns: a reduced AssetCollection on the given sitecol
NB: diffently from .reduce, also the SiteCollection is reduced
and turned into a complete site collection.
"""
array = []
asset_refs = []
for idx, sid in enumerate(sitecol.sids):
mask = self.array['site_id'] == sid
arr = self.array[mask]
arr['site_id'] = idx
array.append(arr)
asset_refs.append(self.asset_refs[mask])
new = object.__new__(self.__class__)
vars(new).update(vars(self))
new.tot_sites = len(sitecol)
new.array = numpy.concatenate(array)
new.array['ordinal'] = numpy.arange(len(new.array))
new.asset_refs = numpy.concatenate(asset_refs)
sitecol.make_complete()
return new | python | def reduce_also(self, sitecol):
array = []
asset_refs = []
for idx, sid in enumerate(sitecol.sids):
mask = self.array['site_id'] == sid
arr = self.array[mask]
arr['site_id'] = idx
array.append(arr)
asset_refs.append(self.asset_refs[mask])
new = object.__new__(self.__class__)
vars(new).update(vars(self))
new.tot_sites = len(sitecol)
new.array = numpy.concatenate(array)
new.array['ordinal'] = numpy.arange(len(new.array))
new.asset_refs = numpy.concatenate(asset_refs)
sitecol.make_complete()
return new | [
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empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
Cleaning
Unlike the original dataset, the func_code_string column was updated to remove any comments and keep just the code.
The original version can still be found in the whole_func_string.
import re
def remove_comments_docstrings(code, language):
if language == 'python':
# Remove docstrings
code = re.sub(r'"""(.*?)"""', '', code, flags=re.DOTALL)
code = re.sub(r"'''(.*?)'''", '', code, flags=re.DOTALL)
# Remove comments
code = re.sub(r'#.*', '', code)
elif language == 'java' or language == 'javascript':
# Remove multiline comments
code = re.sub(r'/\*.*?\*/', '', code, flags=re.DOTALL)
# Remove single line comments
code = re.sub(r'//.*', '', code)
elif language == 'go':
# Similar to Java/Javascript
code = re.sub(r'/\*.*?\*/', '', code, flags=re.DOTALL)
code = re.sub(r'//.*', '', code)
elif language == 'ruby':
# Remove multiline comments
code = re.sub(r'=begin.*?=end', '', code, flags=re.DOTALL)
# Remove single line comments
code = re.sub(r'#.*', '', code)
elif language == 'php':
# Remove multiline comments
code = re.sub(r'/\*.*?\*/', '', code, flags=re.DOTALL)
# Remove single line and hash comments
code = re.sub(r'//.*', '', code)
code = re.sub(r'#.*', '', code)
return code.strip()
The validity of that snippet can be tested with the following example:
# Example DataFrame
import pandas as pd
example = {
'language': ['python', 'java', 'javascript', 'go', 'ruby', 'php'],
'func_code_string': [
'"""Example docstring""" def foo(): # This is a comment\n return 1',
'/** Java doc */ public class Test { // Comment\n public void method() {} }',
'/* JS doc */ function test() { // Comment\n return true; }',
'/* Go doc */ package main // Import comment\nimport "fmt"',
'=begin Ruby doc =end def foo # Comment\n 1 + 1 end',
'<?php /* PHP doc */ // Comment\necho "Hello"; # Another comment ?>'
]}
example_df = pd.DataFrame(example)
example_df['cleaned_code'] = example_df.apply(lambda x: remove_comments_docstrings(x['func_code_string'], x['language']), axis=1)
print(example_df[['language', 'cleaned_code']])
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