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300 | gem/oq-engine | openquake/baselib/parallel.py | Result.get | def get(self):
"""
Returns the underlying value or raise the underlying exception
"""
val = self.pik.unpickle()
if self.tb_str:
etype = val.__class__
msg = '\n%s%s: %s' % (self.tb_str, etype.__name__, val)
if issubclass(etype, KeyError):
raise RuntimeError(msg) # nicer message
else:
raise etype(msg)
return val | python | def get(self):
"""
Returns the underlying value or raise the underlying exception
"""
val = self.pik.unpickle()
if self.tb_str:
etype = val.__class__
msg = '\n%s%s: %s' % (self.tb_str, etype.__name__, val)
if issubclass(etype, KeyError):
raise RuntimeError(msg) # nicer message
else:
raise etype(msg)
return val | [
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301 | gem/oq-engine | openquake/baselib/parallel.py | IterResult.sum | def sum(cls, iresults):
"""
Sum the data transfer information of a set of results
"""
res = object.__new__(cls)
res.received = []
res.sent = 0
for iresult in iresults:
res.received.extend(iresult.received)
res.sent += iresult.sent
name = iresult.name.split('#', 1)[0]
if hasattr(res, 'name'):
assert res.name.split('#', 1)[0] == name, (res.name, name)
else:
res.name = iresult.name.split('#')[0]
return res | python | def sum(cls, iresults):
"""
Sum the data transfer information of a set of results
"""
res = object.__new__(cls)
res.received = []
res.sent = 0
for iresult in iresults:
res.received.extend(iresult.received)
res.sent += iresult.sent
name = iresult.name.split('#', 1)[0]
if hasattr(res, 'name'):
assert res.name.split('#', 1)[0] == name, (res.name, name)
else:
res.name = iresult.name.split('#')[0]
return res | [
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302 | gem/oq-engine | openquake/baselib/parallel.py | Starmap.log_percent | def log_percent(self):
"""
Log the progress of the computation in percentage
"""
done = self.total - self.todo
percent = int(float(done) / self.total * 100)
if not hasattr(self, 'prev_percent'): # first time
self.prev_percent = 0
self.progress('Sent %s of data in %d %s task(s)',
humansize(self.sent.sum()), self.total, self.name)
elif percent > self.prev_percent:
self.progress('%s %3d%% [of %d tasks]',
self.name, percent, len(self.tasks))
self.prev_percent = percent
return done | python | def log_percent(self):
"""
Log the progress of the computation in percentage
"""
done = self.total - self.todo
percent = int(float(done) / self.total * 100)
if not hasattr(self, 'prev_percent'): # first time
self.prev_percent = 0
self.progress('Sent %s of data in %d %s task(s)',
humansize(self.sent.sum()), self.total, self.name)
elif percent > self.prev_percent:
self.progress('%s %3d%% [of %d tasks]',
self.name, percent, len(self.tasks))
self.prev_percent = percent
return done | [
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303 | gem/oq-engine | openquake/baselib/parallel.py | Starmap.submit | def submit(self, *args, func=None, monitor=None):
"""
Submit the given arguments to the underlying task
"""
monitor = monitor or self.monitor
func = func or self.task_func
if not hasattr(self, 'socket'): # first time
self.__class__.running_tasks = self.tasks
self.socket = Socket(self.receiver, zmq.PULL, 'bind').__enter__()
monitor.backurl = 'tcp://%s:%s' % (
config.dbserver.host, self.socket.port)
assert not isinstance(args[-1], Monitor) # sanity check
dist = 'no' if self.num_tasks == 1 else self.distribute
if dist != 'no':
args = pickle_sequence(args)
self.sent += numpy.array([len(p) for p in args])
res = submit[dist](self, func, args, monitor)
self.tasks.append(res) | python | def submit(self, *args, func=None, monitor=None):
"""
Submit the given arguments to the underlying task
"""
monitor = monitor or self.monitor
func = func or self.task_func
if not hasattr(self, 'socket'): # first time
self.__class__.running_tasks = self.tasks
self.socket = Socket(self.receiver, zmq.PULL, 'bind').__enter__()
monitor.backurl = 'tcp://%s:%s' % (
config.dbserver.host, self.socket.port)
assert not isinstance(args[-1], Monitor) # sanity check
dist = 'no' if self.num_tasks == 1 else self.distribute
if dist != 'no':
args = pickle_sequence(args)
self.sent += numpy.array([len(p) for p in args])
res = submit[dist](self, func, args, monitor)
self.tasks.append(res) | [
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304 | gem/oq-engine | openquake/baselib/parallel.py | Starmap.reduce | def reduce(self, agg=operator.add, acc=None):
"""
Submit all tasks and reduce the results
"""
return self.submit_all().reduce(agg, acc) | python | def reduce(self, agg=operator.add, acc=None):
"""
Submit all tasks and reduce the results
"""
return self.submit_all().reduce(agg, acc) | [
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305 | gem/oq-engine | openquake/hazardlib/probability_map.py | ProbabilityCurve.convert | def convert(self, imtls, idx=0):
"""
Convert a probability curve into a record of dtype `imtls.dt`.
:param imtls: DictArray instance
:param idx: extract the data corresponding to the given inner index
"""
curve = numpy.zeros(1, imtls.dt)
for imt in imtls:
curve[imt] = self.array[imtls(imt), idx]
return curve[0] | python | def convert(self, imtls, idx=0):
"""
Convert a probability curve into a record of dtype `imtls.dt`.
:param imtls: DictArray instance
:param idx: extract the data corresponding to the given inner index
"""
curve = numpy.zeros(1, imtls.dt)
for imt in imtls:
curve[imt] = self.array[imtls(imt), idx]
return curve[0] | [
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306 | gem/oq-engine | openquake/hazardlib/probability_map.py | ProbabilityMap.nbytes | def nbytes(self):
"""The size of the underlying array"""
try:
N, L, I = get_shape([self])
except AllEmptyProbabilityMaps:
return 0
return BYTES_PER_FLOAT * N * L * I | python | def nbytes(self):
"""The size of the underlying array"""
try:
N, L, I = get_shape([self])
except AllEmptyProbabilityMaps:
return 0
return BYTES_PER_FLOAT * N * L * I | [
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307 | gem/oq-engine | openquake/hazardlib/probability_map.py | ProbabilityMap.convert | def convert(self, imtls, nsites, idx=0):
"""
Convert a probability map into a composite array of length `nsites`
and dtype `imtls.dt`.
:param imtls:
DictArray instance
:param nsites:
the total number of sites
:param idx:
index on the z-axis (default 0)
"""
curves = numpy.zeros(nsites, imtls.dt)
for imt in curves.dtype.names:
curves_by_imt = curves[imt]
for sid in self:
curves_by_imt[sid] = self[sid].array[imtls(imt), idx]
return curves | python | def convert(self, imtls, nsites, idx=0):
"""
Convert a probability map into a composite array of length `nsites`
and dtype `imtls.dt`.
:param imtls:
DictArray instance
:param nsites:
the total number of sites
:param idx:
index on the z-axis (default 0)
"""
curves = numpy.zeros(nsites, imtls.dt)
for imt in curves.dtype.names:
curves_by_imt = curves[imt]
for sid in self:
curves_by_imt[sid] = self[sid].array[imtls(imt), idx]
return curves | [
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308 | gem/oq-engine | openquake/hazardlib/probability_map.py | ProbabilityMap.filter | def filter(self, sids):
"""
Extracs a submap of self for the given sids.
"""
dic = self.__class__(self.shape_y, self.shape_z)
for sid in sids:
try:
dic[sid] = self[sid]
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return dic | python | def filter(self, sids):
"""
Extracs a submap of self for the given sids.
"""
dic = self.__class__(self.shape_y, self.shape_z)
for sid in sids:
try:
dic[sid] = self[sid]
except KeyError:
pass
return dic | [
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309 | gem/oq-engine | openquake/hazardlib/probability_map.py | ProbabilityMap.extract | def extract(self, inner_idx):
"""
Extracts a component of the underlying ProbabilityCurves,
specified by the index `inner_idx`.
"""
out = self.__class__(self.shape_y, 1)
for sid in self:
curve = self[sid]
array = curve.array[:, inner_idx].reshape(-1, 1)
out[sid] = ProbabilityCurve(array)
return out | python | def extract(self, inner_idx):
"""
Extracts a component of the underlying ProbabilityCurves,
specified by the index `inner_idx`.
"""
out = self.__class__(self.shape_y, 1)
for sid in self:
curve = self[sid]
array = curve.array[:, inner_idx].reshape(-1, 1)
out[sid] = ProbabilityCurve(array)
return out | [
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310 | gem/oq-engine | openquake/commands/compare.py | compare | def compare(what, imt, calc_ids, files, samplesites=100, rtol=.1, atol=1E-4):
"""
Compare the hazard curves or maps of two or more calculations
"""
sids, imtls, poes, arrays = getdata(what, calc_ids, samplesites)
try:
levels = imtls[imt]
except KeyError:
sys.exit(
'%s not found. The available IMTs are %s' % (imt, list(imtls)))
imt2idx = {imt: i for i, imt in enumerate(imtls)}
head = ['site_id'] if files else ['site_id', 'calc_id']
if what == 'hcurves':
array_imt = arrays[:, :, imtls(imt)]
header = head + ['%.5f' % lvl for lvl in levels]
else: # hmaps
array_imt = arrays[:, :, imt2idx[imt]]
header = head + [str(poe) for poe in poes]
rows = collections.defaultdict(list)
diff_idxs = get_diff_idxs(array_imt, rtol, atol)
if len(diff_idxs) == 0:
print('There are no differences within the tolerance of %d%%' %
(rtol * 100))
return
arr = array_imt.transpose(1, 0, 2) # shape (N, C, L)
for sid, array in sorted(zip(sids[diff_idxs], arr[diff_idxs])):
for calc_id, cols in zip(calc_ids, array):
if files:
rows[calc_id].append([sid] + list(cols))
else:
rows['all'].append([sid, calc_id] + list(cols))
if files:
fdict = {calc_id: open('%s.txt' % calc_id, 'w')
for calc_id in calc_ids}
for calc_id, f in fdict.items():
f.write(views.rst_table(rows[calc_id], header))
print('Generated %s' % f.name)
else:
print(views.rst_table(rows['all'], header)) | python | def compare(what, imt, calc_ids, files, samplesites=100, rtol=.1, atol=1E-4):
"""
Compare the hazard curves or maps of two or more calculations
"""
sids, imtls, poes, arrays = getdata(what, calc_ids, samplesites)
try:
levels = imtls[imt]
except KeyError:
sys.exit(
'%s not found. The available IMTs are %s' % (imt, list(imtls)))
imt2idx = {imt: i for i, imt in enumerate(imtls)}
head = ['site_id'] if files else ['site_id', 'calc_id']
if what == 'hcurves':
array_imt = arrays[:, :, imtls(imt)]
header = head + ['%.5f' % lvl for lvl in levels]
else: # hmaps
array_imt = arrays[:, :, imt2idx[imt]]
header = head + [str(poe) for poe in poes]
rows = collections.defaultdict(list)
diff_idxs = get_diff_idxs(array_imt, rtol, atol)
if len(diff_idxs) == 0:
print('There are no differences within the tolerance of %d%%' %
(rtol * 100))
return
arr = array_imt.transpose(1, 0, 2) # shape (N, C, L)
for sid, array in sorted(zip(sids[diff_idxs], arr[diff_idxs])):
for calc_id, cols in zip(calc_ids, array):
if files:
rows[calc_id].append([sid] + list(cols))
else:
rows['all'].append([sid, calc_id] + list(cols))
if files:
fdict = {calc_id: open('%s.txt' % calc_id, 'w')
for calc_id in calc_ids}
for calc_id, f in fdict.items():
f.write(views.rst_table(rows[calc_id], header))
print('Generated %s' % f.name)
else:
print(views.rst_table(rows['all'], header)) | [
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311 | gem/oq-engine | openquake/hmtk/plotting/seismicity/catalogue_plots.py | build_filename | def build_filename(filename, filetype='png', resolution=300):
"""
Uses the input properties to create the string of the filename
:param str filename:
Name of the file
:param str filetype:
Type of file
:param int resolution:
DPI resolution of the output figure
"""
filevals = os.path.splitext(filename)
if filevals[1]:
filetype = filevals[1][1:]
if not filetype:
filetype = 'png'
filename = filevals[0] + '.' + filetype
if not resolution:
resolution = 300
return filename, filetype, resolution | python | def build_filename(filename, filetype='png', resolution=300):
"""
Uses the input properties to create the string of the filename
:param str filename:
Name of the file
:param str filetype:
Type of file
:param int resolution:
DPI resolution of the output figure
"""
filevals = os.path.splitext(filename)
if filevals[1]:
filetype = filevals[1][1:]
if not filetype:
filetype = 'png'
filename = filevals[0] + '.' + filetype
if not resolution:
resolution = 300
return filename, filetype, resolution | [
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312 | gem/oq-engine | openquake/hmtk/plotting/seismicity/catalogue_plots.py | _get_catalogue_bin_limits | def _get_catalogue_bin_limits(catalogue, dmag):
"""
Returns the magnitude bins corresponing to the catalogue
"""
mag_bins = np.arange(
float(np.floor(np.min(catalogue.data['magnitude']))) - dmag,
float(np.ceil(np.max(catalogue.data['magnitude']))) + dmag,
dmag)
counter = np.histogram(catalogue.data['magnitude'], mag_bins)[0]
idx = np.where(counter > 0)[0]
mag_bins = mag_bins[idx[0]:(idx[-1] + 2)]
return mag_bins | python | def _get_catalogue_bin_limits(catalogue, dmag):
"""
Returns the magnitude bins corresponing to the catalogue
"""
mag_bins = np.arange(
float(np.floor(np.min(catalogue.data['magnitude']))) - dmag,
float(np.ceil(np.max(catalogue.data['magnitude']))) + dmag,
dmag)
counter = np.histogram(catalogue.data['magnitude'], mag_bins)[0]
idx = np.where(counter > 0)[0]
mag_bins = mag_bins[idx[0]:(idx[-1] + 2)]
return mag_bins | [
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313 | gem/oq-engine | openquake/hmtk/plotting/seismicity/catalogue_plots.py | plot_depth_histogram | def plot_depth_histogram(
catalogue, bin_width,
normalisation=False, bootstrap=None, filename=None,
figure_size=(8, 6), filetype='png', dpi=300, ax=None):
"""
Creates a histogram of the depths in the catalogue
:param catalogue:
Earthquake catalogue as instance of :class:
openquake.hmtk.seismicity.catalogue.Catalogue
:param float bin_width:
Width of the histogram for the depth bins
:param bool normalisation:
Normalise the histogram to give output as PMF (True) or count (False)
:param int bootstrap:
To sample depth uncertainty choose number of samples
"""
if ax is None:
fig, ax = plt.subplots(figsize=figure_size)
else:
fig = ax.get_figure()
# Create depth range
if len(catalogue.data['depth']) == 0: # pylint: disable=len-as-condition
raise ValueError('No depths reported in catalogue!')
depth_bins = np.arange(0.,
np.max(catalogue.data['depth']) + bin_width,
bin_width)
depth_hist = catalogue.get_depth_distribution(depth_bins,
normalisation,
bootstrap)
ax.bar(depth_bins[:-1],
depth_hist,
width=0.95 * bin_width,
edgecolor='k')
ax.set_xlabel('Depth (km)')
if normalisation:
ax.set_ylabel('Probability Mass Function')
else:
ax.set_ylabel('Count')
ax.set_title('Depth Histogram')
_save_image(fig, filename, filetype, dpi) | python | def plot_depth_histogram(
catalogue, bin_width,
normalisation=False, bootstrap=None, filename=None,
figure_size=(8, 6), filetype='png', dpi=300, ax=None):
"""
Creates a histogram of the depths in the catalogue
:param catalogue:
Earthquake catalogue as instance of :class:
openquake.hmtk.seismicity.catalogue.Catalogue
:param float bin_width:
Width of the histogram for the depth bins
:param bool normalisation:
Normalise the histogram to give output as PMF (True) or count (False)
:param int bootstrap:
To sample depth uncertainty choose number of samples
"""
if ax is None:
fig, ax = plt.subplots(figsize=figure_size)
else:
fig = ax.get_figure()
# Create depth range
if len(catalogue.data['depth']) == 0: # pylint: disable=len-as-condition
raise ValueError('No depths reported in catalogue!')
depth_bins = np.arange(0.,
np.max(catalogue.data['depth']) + bin_width,
bin_width)
depth_hist = catalogue.get_depth_distribution(depth_bins,
normalisation,
bootstrap)
ax.bar(depth_bins[:-1],
depth_hist,
width=0.95 * bin_width,
edgecolor='k')
ax.set_xlabel('Depth (km)')
if normalisation:
ax.set_ylabel('Probability Mass Function')
else:
ax.set_ylabel('Count')
ax.set_title('Depth Histogram')
_save_image(fig, filename, filetype, dpi) | [
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Earthquake catalogue as instance of :class:
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:param float bin_width:
Width of the histogram for the depth bins
:param bool normalisation:
Normalise the histogram to give output as PMF (True) or count (False)
:param int bootstrap:
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314 | gem/oq-engine | openquake/hmtk/plotting/seismicity/catalogue_plots.py | plot_magnitude_depth_density | def plot_magnitude_depth_density(
catalogue, mag_int, depth_int,
logscale=False, normalisation=False, bootstrap=None, filename=None,
figure_size=(8, 6), filetype='png', dpi=300, ax=None):
"""
Creates a density plot of the magnitude and depth distribution
:param catalogue:
Earthquake catalogue as instance of :class:
openquake.hmtk.seismicity.catalogue.Catalogue
:param float mag_int:
Width of the histogram for the magnitude bins
:param float depth_int:
Width of the histogram for the depth bins
:param bool logscale:
Choose to scale the colours in a log-scale (True) or linear (False)
:param bool normalisation:
Normalise the histogram to give output as PMF (True) or count (False)
:param int bootstrap:
To sample magnitude and depth uncertainties choose number of samples
"""
if len(catalogue.data['depth']) == 0: # pylint: disable=len-as-condition
raise ValueError('No depths reported in catalogue!')
depth_bins = np.arange(0.,
np.max(catalogue.data['depth']) + depth_int,
depth_int)
mag_bins = _get_catalogue_bin_limits(catalogue, mag_int)
mag_depth_dist = catalogue.get_magnitude_depth_distribution(mag_bins,
depth_bins,
normalisation,
bootstrap)
vmin_val = np.min(mag_depth_dist[mag_depth_dist > 0.])
if ax is None:
fig, ax = plt.subplots(figsize=figure_size)
else:
fig = ax.get_figure()
if logscale:
normaliser = LogNorm(vmin=vmin_val, vmax=np.max(mag_depth_dist))
else:
normaliser = Normalize(vmin=0, vmax=np.max(mag_depth_dist))
im = ax.pcolor(mag_bins[:-1],
depth_bins[:-1],
mag_depth_dist.T,
norm=normaliser)
ax.set_xlabel('Magnitude')
ax.set_ylabel('Depth (km)')
ax.set_xlim(mag_bins[0], mag_bins[-1])
ax.set_ylim(depth_bins[0], depth_bins[-1])
fig.colorbar(im, ax=ax)
if normalisation:
ax.set_title('Magnitude-Depth Density')
else:
ax.set_title('Magnitude-Depth Count')
_save_image(fig, filename, filetype, dpi) | python | def plot_magnitude_depth_density(
catalogue, mag_int, depth_int,
logscale=False, normalisation=False, bootstrap=None, filename=None,
figure_size=(8, 6), filetype='png', dpi=300, ax=None):
"""
Creates a density plot of the magnitude and depth distribution
:param catalogue:
Earthquake catalogue as instance of :class:
openquake.hmtk.seismicity.catalogue.Catalogue
:param float mag_int:
Width of the histogram for the magnitude bins
:param float depth_int:
Width of the histogram for the depth bins
:param bool logscale:
Choose to scale the colours in a log-scale (True) or linear (False)
:param bool normalisation:
Normalise the histogram to give output as PMF (True) or count (False)
:param int bootstrap:
To sample magnitude and depth uncertainties choose number of samples
"""
if len(catalogue.data['depth']) == 0: # pylint: disable=len-as-condition
raise ValueError('No depths reported in catalogue!')
depth_bins = np.arange(0.,
np.max(catalogue.data['depth']) + depth_int,
depth_int)
mag_bins = _get_catalogue_bin_limits(catalogue, mag_int)
mag_depth_dist = catalogue.get_magnitude_depth_distribution(mag_bins,
depth_bins,
normalisation,
bootstrap)
vmin_val = np.min(mag_depth_dist[mag_depth_dist > 0.])
if ax is None:
fig, ax = plt.subplots(figsize=figure_size)
else:
fig = ax.get_figure()
if logscale:
normaliser = LogNorm(vmin=vmin_val, vmax=np.max(mag_depth_dist))
else:
normaliser = Normalize(vmin=0, vmax=np.max(mag_depth_dist))
im = ax.pcolor(mag_bins[:-1],
depth_bins[:-1],
mag_depth_dist.T,
norm=normaliser)
ax.set_xlabel('Magnitude')
ax.set_ylabel('Depth (km)')
ax.set_xlim(mag_bins[0], mag_bins[-1])
ax.set_ylim(depth_bins[0], depth_bins[-1])
fig.colorbar(im, ax=ax)
if normalisation:
ax.set_title('Magnitude-Depth Density')
else:
ax.set_title('Magnitude-Depth Count')
_save_image(fig, filename, filetype, dpi) | [
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:param catalogue:
Earthquake catalogue as instance of :class:
openquake.hmtk.seismicity.catalogue.Catalogue
:param float mag_int:
Width of the histogram for the magnitude bins
:param float depth_int:
Width of the histogram for the depth bins
:param bool logscale:
Choose to scale the colours in a log-scale (True) or linear (False)
:param bool normalisation:
Normalise the histogram to give output as PMF (True) or count (False)
:param int bootstrap:
To sample magnitude and depth uncertainties choose number of samples | [
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] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/plotting/seismicity/catalogue_plots.py#L161-L218 |
315 | gem/oq-engine | openquake/hmtk/plotting/seismicity/catalogue_plots.py | plot_magnitude_time_scatter | def plot_magnitude_time_scatter(
catalogue, plot_error=False, fmt_string='o', filename=None,
figure_size=(8, 6), filetype='png', dpi=300, ax=None):
"""
Creates a simple scatter plot of magnitude with time
:param catalogue:
Earthquake catalogue as instance of :class:
openquake.hmtk.seismicity.catalogue.Catalogue
:param bool plot_error:
Choose to plot error bars (True) or not (False)
:param str fmt_string:
Symbology of plot
"""
if ax is None:
fig, ax = plt.subplots(figsize=figure_size)
else:
fig = ax.get_figure()
dtime = catalogue.get_decimal_time()
# pylint: disable=len-as-condition
if len(catalogue.data['sigmaMagnitude']) == 0:
print('Magnitude Error is missing - neglecting error bars!')
plot_error = False
if plot_error:
ax.errorbar(dtime,
catalogue.data['magnitude'],
xerr=None,
yerr=catalogue.data['sigmaMagnitude'],
fmt=fmt_string)
else:
ax.plot(dtime, catalogue.data['magnitude'], fmt_string)
ax.set_xlabel('Year')
ax.set_ylabel('Magnitude')
ax.set_title('Magnitude-Time Plot')
_save_image(fig, filename, filetype, dpi) | python | def plot_magnitude_time_scatter(
catalogue, plot_error=False, fmt_string='o', filename=None,
figure_size=(8, 6), filetype='png', dpi=300, ax=None):
"""
Creates a simple scatter plot of magnitude with time
:param catalogue:
Earthquake catalogue as instance of :class:
openquake.hmtk.seismicity.catalogue.Catalogue
:param bool plot_error:
Choose to plot error bars (True) or not (False)
:param str fmt_string:
Symbology of plot
"""
if ax is None:
fig, ax = plt.subplots(figsize=figure_size)
else:
fig = ax.get_figure()
dtime = catalogue.get_decimal_time()
# pylint: disable=len-as-condition
if len(catalogue.data['sigmaMagnitude']) == 0:
print('Magnitude Error is missing - neglecting error bars!')
plot_error = False
if plot_error:
ax.errorbar(dtime,
catalogue.data['magnitude'],
xerr=None,
yerr=catalogue.data['sigmaMagnitude'],
fmt=fmt_string)
else:
ax.plot(dtime, catalogue.data['magnitude'], fmt_string)
ax.set_xlabel('Year')
ax.set_ylabel('Magnitude')
ax.set_title('Magnitude-Time Plot')
_save_image(fig, filename, filetype, dpi) | [
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Earthquake catalogue as instance of :class:
openquake.hmtk.seismicity.catalogue.Catalogue
:param bool plot_error:
Choose to plot error bars (True) or not (False)
:param str fmt_string:
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316 | gem/oq-engine | openquake/hmtk/plotting/seismicity/catalogue_plots.py | plot_magnitude_time_density | def plot_magnitude_time_density(
catalogue, mag_int, time_int, completeness=None,
normalisation=False, logscale=True, bootstrap=None, xlim=[], ylim=[],
filename=None, figure_size=(8, 6), filetype='png', dpi=300, ax=None):
"""
Creates a plot of magnitude-time density
:param catalogue:
Earthquake catalogue as instance of :class:
openquake.hmtk.seismicity.catalogue.Catalogue
:param float mag_int:
Width of the histogram for the magnitude bins
:param float time_int:
Width of the histogram for the time bin (in decimal years)
:param bool normalisation:
Normalise the histogram to give output as PMF (True) or count (False)
:param int bootstrap:
To sample magnitude and depth uncertainties choose number of samples
"""
if ax is None:
fig, ax = plt.subplots(figsize=figure_size)
else:
fig = ax.get_figure()
# Create the magnitude bins
if isinstance(mag_int, (np.ndarray, list)):
mag_bins = mag_int
else:
mag_bins = np.arange(
np.min(catalogue.data['magnitude']),
np.max(catalogue.data['magnitude']) + mag_int / 2.,
mag_int)
# Creates the time bins
if isinstance(time_int, (np.ndarray, list)):
time_bins = time_int
else:
time_bins = np.arange(
float(np.min(catalogue.data['year'])),
float(np.max(catalogue.data['year'])) + 1.,
float(time_int))
# Get magnitude-time distribution
mag_time_dist = catalogue.get_magnitude_time_distribution(
mag_bins,
time_bins,
normalisation,
bootstrap)
# Get smallest non-zero value
vmin_val = np.min(mag_time_dist[mag_time_dist > 0.])
# Create plot
if logscale:
norm_data = LogNorm(vmin=vmin_val, vmax=np.max(mag_time_dist))
else:
if normalisation:
norm_data = Normalize(vmin=vmin_val, vmax=np.max(mag_time_dist))
else:
norm_data = Normalize(vmin=1.0, vmax=np.max(mag_time_dist))
im = ax.pcolor(time_bins[:-1],
mag_bins[:-1],
mag_time_dist.T,
norm=norm_data)
ax.set_xlabel('Time (year)')
ax.set_ylabel('Magnitude')
if len(xlim) == 2:
ax.set_xlim(xlim[0], xlim[1])
else:
ax.set_xlim(time_bins[0], time_bins[-1])
if len(ylim) == 2:
ax.set_ylim(ylim[0], ylim[1])
else:
ax.set_ylim(mag_bins[0], mag_bins[-1] + (mag_bins[-1] - mag_bins[-2]))
# Fix the title
if normalisation:
fig.colorbar(im, label='Event Density', shrink=0.9, ax=ax)
else:
fig.colorbar(im, label='Event Count', shrink=0.9, ax=ax)
ax.grid(True)
# Plot completeness
if completeness is not None:
_plot_completeness(ax, completeness, time_bins[0], time_bins[-1])
_save_image(fig, filename, filetype, dpi) | python | def plot_magnitude_time_density(
catalogue, mag_int, time_int, completeness=None,
normalisation=False, logscale=True, bootstrap=None, xlim=[], ylim=[],
filename=None, figure_size=(8, 6), filetype='png', dpi=300, ax=None):
"""
Creates a plot of magnitude-time density
:param catalogue:
Earthquake catalogue as instance of :class:
openquake.hmtk.seismicity.catalogue.Catalogue
:param float mag_int:
Width of the histogram for the magnitude bins
:param float time_int:
Width of the histogram for the time bin (in decimal years)
:param bool normalisation:
Normalise the histogram to give output as PMF (True) or count (False)
:param int bootstrap:
To sample magnitude and depth uncertainties choose number of samples
"""
if ax is None:
fig, ax = plt.subplots(figsize=figure_size)
else:
fig = ax.get_figure()
# Create the magnitude bins
if isinstance(mag_int, (np.ndarray, list)):
mag_bins = mag_int
else:
mag_bins = np.arange(
np.min(catalogue.data['magnitude']),
np.max(catalogue.data['magnitude']) + mag_int / 2.,
mag_int)
# Creates the time bins
if isinstance(time_int, (np.ndarray, list)):
time_bins = time_int
else:
time_bins = np.arange(
float(np.min(catalogue.data['year'])),
float(np.max(catalogue.data['year'])) + 1.,
float(time_int))
# Get magnitude-time distribution
mag_time_dist = catalogue.get_magnitude_time_distribution(
mag_bins,
time_bins,
normalisation,
bootstrap)
# Get smallest non-zero value
vmin_val = np.min(mag_time_dist[mag_time_dist > 0.])
# Create plot
if logscale:
norm_data = LogNorm(vmin=vmin_val, vmax=np.max(mag_time_dist))
else:
if normalisation:
norm_data = Normalize(vmin=vmin_val, vmax=np.max(mag_time_dist))
else:
norm_data = Normalize(vmin=1.0, vmax=np.max(mag_time_dist))
im = ax.pcolor(time_bins[:-1],
mag_bins[:-1],
mag_time_dist.T,
norm=norm_data)
ax.set_xlabel('Time (year)')
ax.set_ylabel('Magnitude')
if len(xlim) == 2:
ax.set_xlim(xlim[0], xlim[1])
else:
ax.set_xlim(time_bins[0], time_bins[-1])
if len(ylim) == 2:
ax.set_ylim(ylim[0], ylim[1])
else:
ax.set_ylim(mag_bins[0], mag_bins[-1] + (mag_bins[-1] - mag_bins[-2]))
# Fix the title
if normalisation:
fig.colorbar(im, label='Event Density', shrink=0.9, ax=ax)
else:
fig.colorbar(im, label='Event Count', shrink=0.9, ax=ax)
ax.grid(True)
# Plot completeness
if completeness is not None:
_plot_completeness(ax, completeness, time_bins[0], time_bins[-1])
_save_image(fig, filename, filetype, dpi) | [
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:param catalogue:
Earthquake catalogue as instance of :class:
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:param float mag_int:
Width of the histogram for the magnitude bins
:param float time_int:
Width of the histogram for the time bin (in decimal years)
:param bool normalisation:
Normalise the histogram to give output as PMF (True) or count (False)
:param int bootstrap:
To sample magnitude and depth uncertainties choose number of samples | [
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317 | gem/oq-engine | openquake/hmtk/plotting/seismicity/catalogue_plots.py | _plot_completeness | def _plot_completeness(ax, comw, start_time, end_time):
'''
Adds completeness intervals to a plot
'''
comw = np.array(comw)
comp = np.column_stack([np.hstack([end_time, comw[:, 0], start_time]),
np.hstack([comw[0, 1], comw[:, 1], comw[-1, 1]])])
ax.step(comp[:-1, 0], comp[1:, 1], linestyle='-',
where="post", linewidth=3, color='brown') | python | def _plot_completeness(ax, comw, start_time, end_time):
'''
Adds completeness intervals to a plot
'''
comw = np.array(comw)
comp = np.column_stack([np.hstack([end_time, comw[:, 0], start_time]),
np.hstack([comw[0, 1], comw[:, 1], comw[-1, 1]])])
ax.step(comp[:-1, 0], comp[1:, 1], linestyle='-',
where="post", linewidth=3, color='brown') | [
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318 | gem/oq-engine | openquake/hmtk/plotting/seismicity/catalogue_plots.py | get_completeness_adjusted_table | def get_completeness_adjusted_table(catalogue, completeness, dmag,
offset=1.0E-5, end_year=None, plot=False,
figure_size=(8, 6), filename=None,
filetype='png', dpi=300, ax=None):
"""
Counts the number of earthquakes in each magnitude bin and normalises
the rate to annual rates, taking into account the completeness
"""
if not end_year:
end_year = catalogue.end_year
# Find the natural bin limits
mag_bins = _get_catalogue_bin_limits(catalogue, dmag)
obs_time = end_year - completeness[:, 0] + 1.
obs_rates = np.zeros_like(mag_bins)
durations = np.zeros_like(mag_bins)
n_comp = np.shape(completeness)[0]
for iloc in range(n_comp):
low_mag = completeness[iloc, 1]
comp_year = completeness[iloc, 0]
if iloc == (n_comp - 1):
idx = np.logical_and(
catalogue.data['magnitude'] >= low_mag - offset,
catalogue.data['year'] >= comp_year)
high_mag = mag_bins[-1]
obs_idx = mag_bins >= (low_mag - offset)
else:
high_mag = completeness[iloc + 1, 1]
mag_idx = np.logical_and(
catalogue.data['magnitude'] >= low_mag - offset,
catalogue.data['magnitude'] < (high_mag - offset))
idx = np.logical_and(mag_idx,
catalogue.data['year'] >= (comp_year - offset))
obs_idx = np.logical_and(mag_bins >= (low_mag - offset),
mag_bins < (high_mag + offset))
temp_rates = np.histogram(catalogue.data['magnitude'][idx],
mag_bins[obs_idx])[0]
temp_rates = temp_rates.astype(float) / obs_time[iloc]
obs_rates[obs_idx[:-1]] = temp_rates
durations[obs_idx[:-1]] = obs_time[iloc]
selector = np.where(obs_rates > 0.)[0]
mag_bins = mag_bins[selector]
obs_rates = obs_rates[selector]
durations = durations[selector]
# Get cumulative rates
cum_rates = np.array([sum(obs_rates[iloc:])
for iloc in range(0, len(obs_rates))])
if plot:
plt.figure(figsize=figure_size)
plt.semilogy(mag_bins + dmag / 2., obs_rates, "bo",
label="Incremental")
plt.semilogy(mag_bins + dmag / 2., cum_rates, "rs",
label="Cumulative")
plt.xlabel("Magnitude (M)", fontsize=16)
plt.ylabel("Annual Rate", fontsize=16)
plt.grid(True)
plt.legend(fontsize=16)
if filename:
plt.savefig(filename, format=filetype, dpi=dpi,
bbox_inches="tight")
return np.column_stack([mag_bins, durations, obs_rates, cum_rates,
np.log10(cum_rates)]) | python | def get_completeness_adjusted_table(catalogue, completeness, dmag,
offset=1.0E-5, end_year=None, plot=False,
figure_size=(8, 6), filename=None,
filetype='png', dpi=300, ax=None):
"""
Counts the number of earthquakes in each magnitude bin and normalises
the rate to annual rates, taking into account the completeness
"""
if not end_year:
end_year = catalogue.end_year
# Find the natural bin limits
mag_bins = _get_catalogue_bin_limits(catalogue, dmag)
obs_time = end_year - completeness[:, 0] + 1.
obs_rates = np.zeros_like(mag_bins)
durations = np.zeros_like(mag_bins)
n_comp = np.shape(completeness)[0]
for iloc in range(n_comp):
low_mag = completeness[iloc, 1]
comp_year = completeness[iloc, 0]
if iloc == (n_comp - 1):
idx = np.logical_and(
catalogue.data['magnitude'] >= low_mag - offset,
catalogue.data['year'] >= comp_year)
high_mag = mag_bins[-1]
obs_idx = mag_bins >= (low_mag - offset)
else:
high_mag = completeness[iloc + 1, 1]
mag_idx = np.logical_and(
catalogue.data['magnitude'] >= low_mag - offset,
catalogue.data['magnitude'] < (high_mag - offset))
idx = np.logical_and(mag_idx,
catalogue.data['year'] >= (comp_year - offset))
obs_idx = np.logical_and(mag_bins >= (low_mag - offset),
mag_bins < (high_mag + offset))
temp_rates = np.histogram(catalogue.data['magnitude'][idx],
mag_bins[obs_idx])[0]
temp_rates = temp_rates.astype(float) / obs_time[iloc]
obs_rates[obs_idx[:-1]] = temp_rates
durations[obs_idx[:-1]] = obs_time[iloc]
selector = np.where(obs_rates > 0.)[0]
mag_bins = mag_bins[selector]
obs_rates = obs_rates[selector]
durations = durations[selector]
# Get cumulative rates
cum_rates = np.array([sum(obs_rates[iloc:])
for iloc in range(0, len(obs_rates))])
if plot:
plt.figure(figsize=figure_size)
plt.semilogy(mag_bins + dmag / 2., obs_rates, "bo",
label="Incremental")
plt.semilogy(mag_bins + dmag / 2., cum_rates, "rs",
label="Cumulative")
plt.xlabel("Magnitude (M)", fontsize=16)
plt.ylabel("Annual Rate", fontsize=16)
plt.grid(True)
plt.legend(fontsize=16)
if filename:
plt.savefig(filename, format=filetype, dpi=dpi,
bbox_inches="tight")
return np.column_stack([mag_bins, durations, obs_rates, cum_rates,
np.log10(cum_rates)]) | [
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the rate to annual rates, taking into account the completeness | [
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319 | gem/oq-engine | openquake/hmtk/plotting/seismicity/catalogue_plots.py | plot_observed_recurrence | def plot_observed_recurrence(
catalogue, completeness, dmag, end_year=None, filename=None,
figure_size=(8, 6), filetype='png', dpi=300, ax=None):
"""
Plots the observed recurrence taking into account the completeness
"""
# Get completeness adjusted recurrence table
if isinstance(completeness, float):
# Unique completeness
completeness = np.array([[np.min(catalogue.data['year']),
completeness]])
if not end_year:
end_year = catalogue.update_end_year()
catalogue.data["dtime"] = catalogue.get_decimal_time()
cent_mag, t_per, n_obs = get_completeness_counts(catalogue,
completeness,
dmag)
obs_rates = n_obs / t_per
cum_obs_rates = np.array([np.sum(obs_rates[i:])
for i in range(len(obs_rates))])
if ax is None:
fig, ax = plt.subplots(figsize=figure_size)
else:
fig = ax.get_figure()
ax.semilogy(cent_mag, obs_rates, 'bo', label="Incremental")
ax.semilogy(cent_mag, cum_obs_rates, 'rs', label="Cumulative")
ax.set_xlim([cent_mag[0] - 0.1, cent_mag[-1] + 0.1])
ax.set_xlabel('Magnitude')
ax.set_ylabel('Annual Rate')
ax.legend()
_save_image(fig, filename, filetype, dpi) | python | def plot_observed_recurrence(
catalogue, completeness, dmag, end_year=None, filename=None,
figure_size=(8, 6), filetype='png', dpi=300, ax=None):
"""
Plots the observed recurrence taking into account the completeness
"""
# Get completeness adjusted recurrence table
if isinstance(completeness, float):
# Unique completeness
completeness = np.array([[np.min(catalogue.data['year']),
completeness]])
if not end_year:
end_year = catalogue.update_end_year()
catalogue.data["dtime"] = catalogue.get_decimal_time()
cent_mag, t_per, n_obs = get_completeness_counts(catalogue,
completeness,
dmag)
obs_rates = n_obs / t_per
cum_obs_rates = np.array([np.sum(obs_rates[i:])
for i in range(len(obs_rates))])
if ax is None:
fig, ax = plt.subplots(figsize=figure_size)
else:
fig = ax.get_figure()
ax.semilogy(cent_mag, obs_rates, 'bo', label="Incremental")
ax.semilogy(cent_mag, cum_obs_rates, 'rs', label="Cumulative")
ax.set_xlim([cent_mag[0] - 0.1, cent_mag[-1] + 0.1])
ax.set_xlabel('Magnitude')
ax.set_ylabel('Annual Rate')
ax.legend()
_save_image(fig, filename, filetype, dpi) | [
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] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/plotting/seismicity/catalogue_plots.py#L420-L452 |
320 | gem/oq-engine | openquake/hmtk/strain/geodetic_strain.py | GeodeticStrain.get_number_observations | def get_number_observations(self):
'''
Returns the number of observations in the data file
'''
if isinstance(self.data, dict) and ('exx' in self.data.keys()):
return len(self.data['exx'])
else:
return 0 | python | def get_number_observations(self):
'''
Returns the number of observations in the data file
'''
if isinstance(self.data, dict) and ('exx' in self.data.keys()):
return len(self.data['exx'])
else:
return 0 | [
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321 | gem/oq-engine | openquake/commands/plot_lc.py | plot_lc | def plot_lc(calc_id, aid=None):
"""
Plot loss curves given a calculation id and an asset ordinal.
"""
# read the hazard data
dstore = util.read(calc_id)
dset = dstore['agg_curves-rlzs']
if aid is None: # plot the global curves
plt = make_figure(dset.attrs['return_periods'], dset.value)
else:
sys.exit('Not implemented yet')
plt.show() | python | def plot_lc(calc_id, aid=None):
"""
Plot loss curves given a calculation id and an asset ordinal.
"""
# read the hazard data
dstore = util.read(calc_id)
dset = dstore['agg_curves-rlzs']
if aid is None: # plot the global curves
plt = make_figure(dset.attrs['return_periods'], dset.value)
else:
sys.exit('Not implemented yet')
plt.show() | [
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322 | gem/oq-engine | openquake/hazardlib/gsim/nshmp_2014.py | get_weighted_poes | def get_weighted_poes(gsim, sctx, rctx, dctx, imt, imls, truncation_level,
weighting=DEFAULT_WEIGHTING):
"""
This function implements the NGA West 2 GMPE epistemic uncertainty
adjustment factor without re-calculating the actual GMPE each time.
:param gsim:
Instance of the GMPE
:param list weighting:
Weightings as a list of tuples of (weight, number standard deviations
of the epistemic uncertainty adjustment)
"""
if truncation_level is not None and truncation_level < 0:
raise ValueError('truncation level must be zero, positive number '
'or None')
gsim._check_imt(imt)
adjustment = nga_west2_epistemic_adjustment(rctx.mag, dctx.rrup)
adjustment = adjustment.reshape(adjustment.shape + (1, ))
if truncation_level == 0:
# zero truncation mode, just compare imls to mean
imls = gsim.to_distribution_values(imls)
mean, _ = gsim.get_mean_and_stddevs(sctx, rctx, dctx, imt, [])
mean = mean.reshape(mean.shape + (1, ))
output = np.zeros([mean.shape[0], imls.shape[0]])
for (wgt, fct) in weighting:
output += (wgt *
(imls <= (mean + (fct * adjustment))).astype(float))
return output
else:
# use real normal distribution
assert (const.StdDev.TOTAL
in gsim.DEFINED_FOR_STANDARD_DEVIATION_TYPES)
imls = gsim.to_distribution_values(imls)
mean, [stddev] = gsim.get_mean_and_stddevs(sctx, rctx, dctx, imt,
[const.StdDev.TOTAL])
mean = mean.reshape(mean.shape + (1, ))
stddev = stddev.reshape(stddev.shape + (1, ))
output = np.zeros([mean.shape[0], imls.shape[0]])
for (wgt, fct) in weighting:
values = (imls - (mean + (fct * adjustment))) / stddev
if truncation_level is None:
output += (wgt * _norm_sf(values))
else:
output += (wgt * _truncnorm_sf(truncation_level, values))
return output | python | def get_weighted_poes(gsim, sctx, rctx, dctx, imt, imls, truncation_level,
weighting=DEFAULT_WEIGHTING):
"""
This function implements the NGA West 2 GMPE epistemic uncertainty
adjustment factor without re-calculating the actual GMPE each time.
:param gsim:
Instance of the GMPE
:param list weighting:
Weightings as a list of tuples of (weight, number standard deviations
of the epistemic uncertainty adjustment)
"""
if truncation_level is not None and truncation_level < 0:
raise ValueError('truncation level must be zero, positive number '
'or None')
gsim._check_imt(imt)
adjustment = nga_west2_epistemic_adjustment(rctx.mag, dctx.rrup)
adjustment = adjustment.reshape(adjustment.shape + (1, ))
if truncation_level == 0:
# zero truncation mode, just compare imls to mean
imls = gsim.to_distribution_values(imls)
mean, _ = gsim.get_mean_and_stddevs(sctx, rctx, dctx, imt, [])
mean = mean.reshape(mean.shape + (1, ))
output = np.zeros([mean.shape[0], imls.shape[0]])
for (wgt, fct) in weighting:
output += (wgt *
(imls <= (mean + (fct * adjustment))).astype(float))
return output
else:
# use real normal distribution
assert (const.StdDev.TOTAL
in gsim.DEFINED_FOR_STANDARD_DEVIATION_TYPES)
imls = gsim.to_distribution_values(imls)
mean, [stddev] = gsim.get_mean_and_stddevs(sctx, rctx, dctx, imt,
[const.StdDev.TOTAL])
mean = mean.reshape(mean.shape + (1, ))
stddev = stddev.reshape(stddev.shape + (1, ))
output = np.zeros([mean.shape[0], imls.shape[0]])
for (wgt, fct) in weighting:
values = (imls - (mean + (fct * adjustment))) / stddev
if truncation_level is None:
output += (wgt * _norm_sf(values))
else:
output += (wgt * _truncnorm_sf(truncation_level, values))
return output | [
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Instance of the GMPE
:param list weighting:
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323 | gem/oq-engine | openquake/commonlib/shapefileparser.py | register_fields | def register_fields(w):
"""
Register shapefile fields.
"""
PARAMS_LIST = [BASE_PARAMS, GEOMETRY_PARAMS, MFD_PARAMS]
for PARAMS in PARAMS_LIST:
for _, param, dtype in PARAMS:
w.field(param, fieldType=dtype, size=FIELD_SIZE)
PARAMS_LIST = [
RATE_PARAMS, STRIKE_PARAMS, DIP_PARAMS, RAKE_PARAMS, NPW_PARAMS,
HDEPTH_PARAMS, HDW_PARAMS, PLANES_STRIKES_PARAM, PLANES_DIPS_PARAM]
for PARAMS in PARAMS_LIST:
for param, dtype in PARAMS:
w.field(param, fieldType=dtype, size=FIELD_SIZE)
# source typology
w.field('sourcetype', 'C') | python | def register_fields(w):
"""
Register shapefile fields.
"""
PARAMS_LIST = [BASE_PARAMS, GEOMETRY_PARAMS, MFD_PARAMS]
for PARAMS in PARAMS_LIST:
for _, param, dtype in PARAMS:
w.field(param, fieldType=dtype, size=FIELD_SIZE)
PARAMS_LIST = [
RATE_PARAMS, STRIKE_PARAMS, DIP_PARAMS, RAKE_PARAMS, NPW_PARAMS,
HDEPTH_PARAMS, HDW_PARAMS, PLANES_STRIKES_PARAM, PLANES_DIPS_PARAM]
for PARAMS in PARAMS_LIST:
for param, dtype in PARAMS:
w.field(param, fieldType=dtype, size=FIELD_SIZE)
# source typology
w.field('sourcetype', 'C') | [
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324 | gem/oq-engine | openquake/commonlib/shapefileparser.py | extract_source_params | def extract_source_params(src):
"""
Extract params from source object.
"""
tags = get_taglist(src)
data = []
for key, param, vtype in BASE_PARAMS:
if key in src.attrib:
if vtype == "c":
data.append((param, src.attrib[key]))
elif vtype == "f":
data.append((param, float(src.attrib[key])))
else:
data.append((param, None))
elif key in tags:
if vtype == "c":
data.append((param, src.nodes[tags.index(key)].text))
elif vtype == "f":
data.append((param, float(src.nodes[tags.index(key)].text)))
else:
data.append((param, None))
else:
data.append((param, None))
return dict(data) | python | def extract_source_params(src):
"""
Extract params from source object.
"""
tags = get_taglist(src)
data = []
for key, param, vtype in BASE_PARAMS:
if key in src.attrib:
if vtype == "c":
data.append((param, src.attrib[key]))
elif vtype == "f":
data.append((param, float(src.attrib[key])))
else:
data.append((param, None))
elif key in tags:
if vtype == "c":
data.append((param, src.nodes[tags.index(key)].text))
elif vtype == "f":
data.append((param, float(src.nodes[tags.index(key)].text)))
else:
data.append((param, None))
else:
data.append((param, None))
return dict(data) | [
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325 | gem/oq-engine | openquake/commonlib/shapefileparser.py | parse_complex_fault_geometry | def parse_complex_fault_geometry(node):
"""
Parses a complex fault geometry node returning both the attributes and
parameters in a dictionary
"""
assert "complexFaultGeometry" in node.tag
# Get general attributes
geometry = {"intermediateEdges": []}
for subnode in node:
crds = subnode.nodes[0].nodes[0].text
if "faultTopEdge" in subnode.tag:
geometry["faultTopEdge"] = numpy.array(
[[crds[i], crds[i + 1], crds[i + 2]]
for i in range(0, len(crds), 3)])
geometry["upperSeismoDepth"] = numpy.min(
geometry["faultTopEdge"][:, 2])
elif "faultBottomEdge" in subnode.tag:
geometry["faultBottomEdge"] = numpy.array(
[[crds[i], crds[i + 1], crds[i + 2]]
for i in range(0, len(crds), 3)])
geometry["lowerSeismoDepth"] = numpy.max(
geometry["faultBottomEdge"][:, 2])
elif "intermediateEdge" in subnode.tag:
geometry["intermediateEdges"].append(
numpy.array([[crds[i], crds[i + 1], crds[i + 2]]
for i in range(0, len(crds), 3)]))
else:
pass
geometry["dip"] = None
return geometry | python | def parse_complex_fault_geometry(node):
"""
Parses a complex fault geometry node returning both the attributes and
parameters in a dictionary
"""
assert "complexFaultGeometry" in node.tag
# Get general attributes
geometry = {"intermediateEdges": []}
for subnode in node:
crds = subnode.nodes[0].nodes[0].text
if "faultTopEdge" in subnode.tag:
geometry["faultTopEdge"] = numpy.array(
[[crds[i], crds[i + 1], crds[i + 2]]
for i in range(0, len(crds), 3)])
geometry["upperSeismoDepth"] = numpy.min(
geometry["faultTopEdge"][:, 2])
elif "faultBottomEdge" in subnode.tag:
geometry["faultBottomEdge"] = numpy.array(
[[crds[i], crds[i + 1], crds[i + 2]]
for i in range(0, len(crds), 3)])
geometry["lowerSeismoDepth"] = numpy.max(
geometry["faultBottomEdge"][:, 2])
elif "intermediateEdge" in subnode.tag:
geometry["intermediateEdges"].append(
numpy.array([[crds[i], crds[i + 1], crds[i + 2]]
for i in range(0, len(crds), 3)]))
else:
pass
geometry["dip"] = None
return geometry | [
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326 | gem/oq-engine | openquake/commonlib/shapefileparser.py | parse_planar_fault_geometry | def parse_planar_fault_geometry(node):
"""
Parses a planar fault geometry node returning both the attributes and
parameters in a dictionary
"""
assert "planarSurface" in node.tag
geometry = {"strike": node.attrib["strike"],
"dip": node.attrib["dip"]}
upper_depth = numpy.inf
lower_depth = 0.0
tags = get_taglist(node)
corner_points = []
for locn in ["topLeft", "topRight", "bottomRight", "bottomLeft"]:
plane = node.nodes[tags.index(locn)]
upper_depth = plane["depth"] if plane["depth"] < upper_depth else\
upper_depth
lower_depth = plane["depth"] if plane["depth"] > lower_depth else\
lower_depth
corner_points.append([plane["lon"], plane["lat"], plane["depth"]])
geometry["upperSeismoDepth"] = upper_depth
geometry["lowerSeismoDepth"] = lower_depth
geometry["corners"] = numpy.array(corner_points)
return geometry | python | def parse_planar_fault_geometry(node):
"""
Parses a planar fault geometry node returning both the attributes and
parameters in a dictionary
"""
assert "planarSurface" in node.tag
geometry = {"strike": node.attrib["strike"],
"dip": node.attrib["dip"]}
upper_depth = numpy.inf
lower_depth = 0.0
tags = get_taglist(node)
corner_points = []
for locn in ["topLeft", "topRight", "bottomRight", "bottomLeft"]:
plane = node.nodes[tags.index(locn)]
upper_depth = plane["depth"] if plane["depth"] < upper_depth else\
upper_depth
lower_depth = plane["depth"] if plane["depth"] > lower_depth else\
lower_depth
corner_points.append([plane["lon"], plane["lat"], plane["depth"]])
geometry["upperSeismoDepth"] = upper_depth
geometry["lowerSeismoDepth"] = lower_depth
geometry["corners"] = numpy.array(corner_points)
return geometry | [
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327 | gem/oq-engine | openquake/commonlib/shapefileparser.py | extract_mfd_params | def extract_mfd_params(src):
"""
Extracts the MFD parameters from an object
"""
tags = get_taglist(src)
if "incrementalMFD" in tags:
mfd_node = src.nodes[tags.index("incrementalMFD")]
elif "truncGutenbergRichterMFD" in tags:
mfd_node = src.nodes[tags.index("truncGutenbergRichterMFD")]
elif "arbitraryMFD" in tags:
mfd_node = src.nodes[tags.index("arbitraryMFD")]
elif "YoungsCoppersmithMFD" in tags:
mfd_node = src.nodes[tags.index("YoungsCoppersmithMFD")]
else:
raise ValueError("Source %s contains no supported MFD type!" % src.tag)
data = []
rates = []
for key, param, vtype in MFD_PARAMS:
if key in mfd_node.attrib and mfd_node.attrib[key] is not None:
data.append((param, mfd_node.attrib[key]))
else:
data.append((param, None))
if ("incrementalMFD" or "arbitraryMFD") in mfd_node.tag:
# Extract Rates
rates = ~mfd_node.occurRates
n_r = len(rates)
if n_r > MAX_RATES:
raise ValueError("Number of rates in source %s too large "
"to be placed into shapefile" % src.tag)
rate_dict = dict([(key, rates[i] if i < n_r else None)
for i, (key, _) in enumerate(RATE_PARAMS)])
elif "YoungsCoppersmithMFD" in mfd_node.tag:
rate_dict = dict([(key, mfd_node.attrib['characteristicRate'])
for i, (key, _) in enumerate(RATE_PARAMS)])
else:
rate_dict = dict([(key, None)
for i, (key, _) in enumerate(RATE_PARAMS)])
return dict(data), rate_dict | python | def extract_mfd_params(src):
"""
Extracts the MFD parameters from an object
"""
tags = get_taglist(src)
if "incrementalMFD" in tags:
mfd_node = src.nodes[tags.index("incrementalMFD")]
elif "truncGutenbergRichterMFD" in tags:
mfd_node = src.nodes[tags.index("truncGutenbergRichterMFD")]
elif "arbitraryMFD" in tags:
mfd_node = src.nodes[tags.index("arbitraryMFD")]
elif "YoungsCoppersmithMFD" in tags:
mfd_node = src.nodes[tags.index("YoungsCoppersmithMFD")]
else:
raise ValueError("Source %s contains no supported MFD type!" % src.tag)
data = []
rates = []
for key, param, vtype in MFD_PARAMS:
if key in mfd_node.attrib and mfd_node.attrib[key] is not None:
data.append((param, mfd_node.attrib[key]))
else:
data.append((param, None))
if ("incrementalMFD" or "arbitraryMFD") in mfd_node.tag:
# Extract Rates
rates = ~mfd_node.occurRates
n_r = len(rates)
if n_r > MAX_RATES:
raise ValueError("Number of rates in source %s too large "
"to be placed into shapefile" % src.tag)
rate_dict = dict([(key, rates[i] if i < n_r else None)
for i, (key, _) in enumerate(RATE_PARAMS)])
elif "YoungsCoppersmithMFD" in mfd_node.tag:
rate_dict = dict([(key, mfd_node.attrib['characteristicRate'])
for i, (key, _) in enumerate(RATE_PARAMS)])
else:
rate_dict = dict([(key, None)
for i, (key, _) in enumerate(RATE_PARAMS)])
return dict(data), rate_dict | [
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328 | gem/oq-engine | openquake/commonlib/shapefileparser.py | extract_source_hypocentral_depths | def extract_source_hypocentral_depths(src):
"""
Extract source hypocentral depths.
"""
if "pointSource" not in src.tag and "areaSource" not in src.tag:
hds = dict([(key, None) for key, _ in HDEPTH_PARAMS])
hdsw = dict([(key, None) for key, _ in HDW_PARAMS])
return hds, hdsw
tags = get_taglist(src)
hdd_nodeset = src.nodes[tags.index("hypoDepthDist")]
if len(hdd_nodeset) > MAX_HYPO_DEPTHS:
raise ValueError("Number of hypocentral depths %s exceeds stated "
"maximum of %s" % (str(len(hdd_nodeset)),
str(MAX_HYPO_DEPTHS)))
if len(hdd_nodeset):
hds = []
hdws = []
for hdd_node in hdd_nodeset:
hds.append(float(hdd_node.attrib["depth"]))
hdws.append(float(hdd_node.attrib["probability"]))
hds = expand_src_param(hds, HDEPTH_PARAMS)
hdsw = expand_src_param(hdws, HDW_PARAMS)
else:
hds = dict([(key, None) for key, _ in HDEPTH_PARAMS])
hdsw = dict([(key, None) for key, _ in HDW_PARAMS])
return hds, hdsw | python | def extract_source_hypocentral_depths(src):
"""
Extract source hypocentral depths.
"""
if "pointSource" not in src.tag and "areaSource" not in src.tag:
hds = dict([(key, None) for key, _ in HDEPTH_PARAMS])
hdsw = dict([(key, None) for key, _ in HDW_PARAMS])
return hds, hdsw
tags = get_taglist(src)
hdd_nodeset = src.nodes[tags.index("hypoDepthDist")]
if len(hdd_nodeset) > MAX_HYPO_DEPTHS:
raise ValueError("Number of hypocentral depths %s exceeds stated "
"maximum of %s" % (str(len(hdd_nodeset)),
str(MAX_HYPO_DEPTHS)))
if len(hdd_nodeset):
hds = []
hdws = []
for hdd_node in hdd_nodeset:
hds.append(float(hdd_node.attrib["depth"]))
hdws.append(float(hdd_node.attrib["probability"]))
hds = expand_src_param(hds, HDEPTH_PARAMS)
hdsw = expand_src_param(hdws, HDW_PARAMS)
else:
hds = dict([(key, None) for key, _ in HDEPTH_PARAMS])
hdsw = dict([(key, None) for key, _ in HDW_PARAMS])
return hds, hdsw | [
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] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/commonlib/shapefileparser.py#L397-L425 |
329 | gem/oq-engine | openquake/commonlib/shapefileparser.py | extract_source_planes_strikes_dips | def extract_source_planes_strikes_dips(src):
"""
Extract strike and dip angles for source defined by multiple planes.
"""
if "characteristicFaultSource" not in src.tag:
strikes = dict([(key, None) for key, _ in PLANES_STRIKES_PARAM])
dips = dict([(key, None) for key, _ in PLANES_DIPS_PARAM])
return strikes, dips
tags = get_taglist(src)
surface_set = src.nodes[tags.index("surface")]
strikes = []
dips = []
num_planes = 0
for surface in surface_set:
if "planarSurface" in surface.tag:
strikes.append(float(surface.attrib["strike"]))
dips.append(float(surface.attrib["dip"]))
num_planes += 1
if num_planes > MAX_PLANES:
raise ValueError("Number of planes in sourcs %s exceededs maximum "
"of %s" % (str(num_planes), str(MAX_PLANES)))
if num_planes:
strikes = expand_src_param(strikes, PLANES_STRIKES_PARAM)
dips = expand_src_param(dips, PLANES_DIPS_PARAM)
else:
strikes = dict([(key, None) for key, _ in PLANES_STRIKES_PARAM])
dips = dict([(key, None) for key, _ in PLANES_DIPS_PARAM])
return strikes, dips | python | def extract_source_planes_strikes_dips(src):
"""
Extract strike and dip angles for source defined by multiple planes.
"""
if "characteristicFaultSource" not in src.tag:
strikes = dict([(key, None) for key, _ in PLANES_STRIKES_PARAM])
dips = dict([(key, None) for key, _ in PLANES_DIPS_PARAM])
return strikes, dips
tags = get_taglist(src)
surface_set = src.nodes[tags.index("surface")]
strikes = []
dips = []
num_planes = 0
for surface in surface_set:
if "planarSurface" in surface.tag:
strikes.append(float(surface.attrib["strike"]))
dips.append(float(surface.attrib["dip"]))
num_planes += 1
if num_planes > MAX_PLANES:
raise ValueError("Number of planes in sourcs %s exceededs maximum "
"of %s" % (str(num_planes), str(MAX_PLANES)))
if num_planes:
strikes = expand_src_param(strikes, PLANES_STRIKES_PARAM)
dips = expand_src_param(dips, PLANES_DIPS_PARAM)
else:
strikes = dict([(key, None) for key, _ in PLANES_STRIKES_PARAM])
dips = dict([(key, None) for key, _ in PLANES_DIPS_PARAM])
return strikes, dips | [
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330 | gem/oq-engine | openquake/commonlib/shapefileparser.py | set_params | def set_params(w, src):
"""
Set source parameters.
"""
params = extract_source_params(src)
# this is done because for characteristic sources geometry is in
# 'surface' attribute
params.update(extract_geometry_params(src))
mfd_pars, rate_pars = extract_mfd_params(src)
params.update(mfd_pars)
params.update(rate_pars)
strikes, dips, rakes, np_weights = extract_source_nodal_planes(src)
params.update(strikes)
params.update(dips)
params.update(rakes)
params.update(np_weights)
hds, hdsw = extract_source_hypocentral_depths(src)
params.update(hds)
params.update(hdsw)
pstrikes, pdips = extract_source_planes_strikes_dips(src)
params.update(pstrikes)
params.update(pdips)
params['sourcetype'] = striptag(src.tag)
w.record(**params) | python | def set_params(w, src):
"""
Set source parameters.
"""
params = extract_source_params(src)
# this is done because for characteristic sources geometry is in
# 'surface' attribute
params.update(extract_geometry_params(src))
mfd_pars, rate_pars = extract_mfd_params(src)
params.update(mfd_pars)
params.update(rate_pars)
strikes, dips, rakes, np_weights = extract_source_nodal_planes(src)
params.update(strikes)
params.update(dips)
params.update(rakes)
params.update(np_weights)
hds, hdsw = extract_source_hypocentral_depths(src)
params.update(hds)
params.update(hdsw)
pstrikes, pdips = extract_source_planes_strikes_dips(src)
params.update(pstrikes)
params.update(pdips)
params['sourcetype'] = striptag(src.tag)
w.record(**params) | [
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331 | gem/oq-engine | openquake/commonlib/shapefileparser.py | set_area_geometry | def set_area_geometry(w, src):
"""
Set area polygon as shapefile geometry
"""
assert "areaSource" in src.tag
geometry_node = src.nodes[get_taglist(src).index("areaGeometry")]
area_attrs = parse_area_geometry(geometry_node)
w.poly(parts=[area_attrs["polygon"].tolist()]) | python | def set_area_geometry(w, src):
"""
Set area polygon as shapefile geometry
"""
assert "areaSource" in src.tag
geometry_node = src.nodes[get_taglist(src).index("areaGeometry")]
area_attrs = parse_area_geometry(geometry_node)
w.poly(parts=[area_attrs["polygon"].tolist()]) | [
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332 | gem/oq-engine | openquake/commonlib/shapefileparser.py | set_point_geometry | def set_point_geometry(w, src):
"""
Set point location as shapefile geometry.
"""
assert "pointSource" in src.tag
geometry_node = src.nodes[get_taglist(src).index("pointGeometry")]
point_attrs = parse_point_geometry(geometry_node)
w.point(point_attrs["point"][0], point_attrs["point"][1]) | python | def set_point_geometry(w, src):
"""
Set point location as shapefile geometry.
"""
assert "pointSource" in src.tag
geometry_node = src.nodes[get_taglist(src).index("pointGeometry")]
point_attrs = parse_point_geometry(geometry_node)
w.point(point_attrs["point"][0], point_attrs["point"][1]) | [
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333 | gem/oq-engine | openquake/commonlib/shapefileparser.py | set_simple_fault_geometry | def set_simple_fault_geometry(w, src):
"""
Set simple fault trace coordinates as shapefile geometry.
:parameter w:
Writer
:parameter src:
source
"""
assert "simpleFaultSource" in src.tag
geometry_node = src.nodes[get_taglist(src).index("simpleFaultGeometry")]
fault_attrs = parse_simple_fault_geometry(geometry_node)
w.line(parts=[fault_attrs["trace"].tolist()]) | python | def set_simple_fault_geometry(w, src):
"""
Set simple fault trace coordinates as shapefile geometry.
:parameter w:
Writer
:parameter src:
source
"""
assert "simpleFaultSource" in src.tag
geometry_node = src.nodes[get_taglist(src).index("simpleFaultGeometry")]
fault_attrs = parse_simple_fault_geometry(geometry_node)
w.line(parts=[fault_attrs["trace"].tolist()]) | [
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334 | gem/oq-engine | openquake/commonlib/shapefileparser.py | set_simple_fault_geometry_3D | def set_simple_fault_geometry_3D(w, src):
"""
Builds a 3D polygon from a node instance
"""
assert "simpleFaultSource" in src.tag
geometry_node = src.nodes[get_taglist(src).index("simpleFaultGeometry")]
fault_attrs = parse_simple_fault_geometry(geometry_node)
build_polygon_from_fault_attrs(w, fault_attrs) | python | def set_simple_fault_geometry_3D(w, src):
"""
Builds a 3D polygon from a node instance
"""
assert "simpleFaultSource" in src.tag
geometry_node = src.nodes[get_taglist(src).index("simpleFaultGeometry")]
fault_attrs = parse_simple_fault_geometry(geometry_node)
build_polygon_from_fault_attrs(w, fault_attrs) | [
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335 | gem/oq-engine | openquake/commonlib/shapefileparser.py | SourceModel.appraise_source_model | def appraise_source_model(self):
"""
Identify parameters defined in NRML source model file, so that
shapefile contains only source model specific fields.
"""
for src in self.sources:
# source params
src_taglist = get_taglist(src)
if "areaSource" in src.tag:
self.has_area_source = True
npd_node = src.nodes[src_taglist.index("nodalPlaneDist")]
npd_size = len(npd_node)
hdd_node = src.nodes[src_taglist.index("hypoDepthDist")]
hdd_size = len(hdd_node)
self.num_np = (npd_size if npd_size > self.num_np
else self.num_np)
self.num_hd = (hdd_size if hdd_size > self.num_hd
else self.num_hd)
elif "pointSource" in src.tag:
self.has_point_source = True
npd_node = src.nodes[src_taglist.index("nodalPlaneDist")]
npd_size = len(npd_node)
hdd_node = src.nodes[src_taglist.index("hypoDepthDist")]
hdd_size = len(hdd_node)
self.num_np = (npd_size if npd_size > self.num_np
else self.num_np)
self.num_hd = (hdd_size if hdd_size > self.num_hd
else self.num_hd)
elif "simpleFaultSource" in src.tag:
self.has_simple_fault_geometry = True
elif "complexFaultSource" in src.tag:
self.has_complex_fault_geometry = True
elif "characteristicFaultSource" in src.tag:
# Get the surface node
surface_node = src.nodes[src_taglist.index("surface")]
p_size = 0
for surface in surface_node.nodes:
if "simpleFaultGeometry" in surface.tag:
self.has_simple_fault_geometry = True
elif "complexFaultGeometry" in surface.tag:
self.has_complex_fault_geometry = True
elif "planarSurface" in surface.tag:
self.has_planar_geometry = True
p_size += 1
self.num_p = p_size if p_size > self.num_p else self.num_p
else:
pass
# MFD params
if "truncGutenbergRichterMFD" in src_taglist:
self.has_mfd_gr = True
elif "incrementalMFD" in src_taglist:
self.has_mfd_incremental = True
# Get rate size
mfd_node = src.nodes[src_taglist.index("incrementalMFD")]
r_size = len(mfd_node.nodes[0].text)
self.num_r = r_size if r_size > self.num_r else self.num_r
else:
pass | python | def appraise_source_model(self):
"""
Identify parameters defined in NRML source model file, so that
shapefile contains only source model specific fields.
"""
for src in self.sources:
# source params
src_taglist = get_taglist(src)
if "areaSource" in src.tag:
self.has_area_source = True
npd_node = src.nodes[src_taglist.index("nodalPlaneDist")]
npd_size = len(npd_node)
hdd_node = src.nodes[src_taglist.index("hypoDepthDist")]
hdd_size = len(hdd_node)
self.num_np = (npd_size if npd_size > self.num_np
else self.num_np)
self.num_hd = (hdd_size if hdd_size > self.num_hd
else self.num_hd)
elif "pointSource" in src.tag:
self.has_point_source = True
npd_node = src.nodes[src_taglist.index("nodalPlaneDist")]
npd_size = len(npd_node)
hdd_node = src.nodes[src_taglist.index("hypoDepthDist")]
hdd_size = len(hdd_node)
self.num_np = (npd_size if npd_size > self.num_np
else self.num_np)
self.num_hd = (hdd_size if hdd_size > self.num_hd
else self.num_hd)
elif "simpleFaultSource" in src.tag:
self.has_simple_fault_geometry = True
elif "complexFaultSource" in src.tag:
self.has_complex_fault_geometry = True
elif "characteristicFaultSource" in src.tag:
# Get the surface node
surface_node = src.nodes[src_taglist.index("surface")]
p_size = 0
for surface in surface_node.nodes:
if "simpleFaultGeometry" in surface.tag:
self.has_simple_fault_geometry = True
elif "complexFaultGeometry" in surface.tag:
self.has_complex_fault_geometry = True
elif "planarSurface" in surface.tag:
self.has_planar_geometry = True
p_size += 1
self.num_p = p_size if p_size > self.num_p else self.num_p
else:
pass
# MFD params
if "truncGutenbergRichterMFD" in src_taglist:
self.has_mfd_gr = True
elif "incrementalMFD" in src_taglist:
self.has_mfd_incremental = True
# Get rate size
mfd_node = src.nodes[src_taglist.index("incrementalMFD")]
r_size = len(mfd_node.nodes[0].text)
self.num_r = r_size if r_size > self.num_r else self.num_r
else:
pass | [
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shapefile contains only source model specific fields. | [
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336 | gem/oq-engine | openquake/commonlib/shapefileparser.py | SourceModelParser.write | def write(self, destination, source_model, name=None):
"""
Exports to NRML
"""
if os.path.exists(destination):
os.remove(destination)
self.destination = destination
if name:
source_model.name = name
output_source_model = Node("sourceModel", {"name": name})
dic = groupby(source_model.sources,
operator.itemgetter('tectonicRegion'))
for i, (trt, srcs) in enumerate(dic.items(), 1):
output_source_model.append(
Node('sourceGroup',
{'tectonicRegion': trt, 'name': 'group %d' % i},
nodes=srcs))
print("Exporting Source Model to %s" % self.destination)
with open(self.destination, "wb") as f:
nrml.write([output_source_model], f, "%s") | python | def write(self, destination, source_model, name=None):
"""
Exports to NRML
"""
if os.path.exists(destination):
os.remove(destination)
self.destination = destination
if name:
source_model.name = name
output_source_model = Node("sourceModel", {"name": name})
dic = groupby(source_model.sources,
operator.itemgetter('tectonicRegion'))
for i, (trt, srcs) in enumerate(dic.items(), 1):
output_source_model.append(
Node('sourceGroup',
{'tectonicRegion': trt, 'name': 'group %d' % i},
nodes=srcs))
print("Exporting Source Model to %s" % self.destination)
with open(self.destination, "wb") as f:
nrml.write([output_source_model], f, "%s") | [
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337 | gem/oq-engine | openquake/commonlib/shapefileparser.py | ShapefileParser.filter_params | def filter_params(self, src_mod):
"""
Remove params uneeded by source_model
"""
# point and area related params
STRIKE_PARAMS[src_mod.num_np:] = []
DIP_PARAMS[src_mod.num_np:] = []
RAKE_PARAMS[src_mod.num_np:] = []
NPW_PARAMS[src_mod.num_np:] = []
HDEPTH_PARAMS[src_mod.num_hd:] = []
HDW_PARAMS[src_mod.num_hd:] = []
# planar rupture related params
PLANES_STRIKES_PARAM[src_mod.num_p:] = []
PLANES_DIPS_PARAM[src_mod.num_p:] = []
# rate params
RATE_PARAMS[src_mod.num_r:] = []
if src_mod.has_simple_fault_geometry is False:
GEOMETRY_PARAMS.remove(('dip', 'dip', 'f'))
if (src_mod.has_simple_fault_geometry is False and
src_mod.has_complex_fault_geometry is False and
src_mod.has_planar_geometry is False):
BASE_PARAMS.remove(('rake', 'rake', 'f'))
if (src_mod.has_simple_fault_geometry is False and
src_mod.has_complex_fault_geometry is False and
src_mod.has_area_source is False and
src_mod.has_point_source is False):
GEOMETRY_PARAMS[:] = []
if src_mod.has_mfd_incremental is False:
MFD_PARAMS.remove(('binWidth', 'bin_width', 'f')) | python | def filter_params(self, src_mod):
"""
Remove params uneeded by source_model
"""
# point and area related params
STRIKE_PARAMS[src_mod.num_np:] = []
DIP_PARAMS[src_mod.num_np:] = []
RAKE_PARAMS[src_mod.num_np:] = []
NPW_PARAMS[src_mod.num_np:] = []
HDEPTH_PARAMS[src_mod.num_hd:] = []
HDW_PARAMS[src_mod.num_hd:] = []
# planar rupture related params
PLANES_STRIKES_PARAM[src_mod.num_p:] = []
PLANES_DIPS_PARAM[src_mod.num_p:] = []
# rate params
RATE_PARAMS[src_mod.num_r:] = []
if src_mod.has_simple_fault_geometry is False:
GEOMETRY_PARAMS.remove(('dip', 'dip', 'f'))
if (src_mod.has_simple_fault_geometry is False and
src_mod.has_complex_fault_geometry is False and
src_mod.has_planar_geometry is False):
BASE_PARAMS.remove(('rake', 'rake', 'f'))
if (src_mod.has_simple_fault_geometry is False and
src_mod.has_complex_fault_geometry is False and
src_mod.has_area_source is False and
src_mod.has_point_source is False):
GEOMETRY_PARAMS[:] = []
if src_mod.has_mfd_incremental is False:
MFD_PARAMS.remove(('binWidth', 'bin_width', 'f')) | [
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338 | gem/oq-engine | openquake/baselib/node.py | tostring | def tostring(node, indent=4, nsmap=None):
"""
Convert a node into an XML string by using the StreamingXMLWriter.
This is useful for testing purposes.
:param node: a node object (typically an ElementTree object)
:param indent: the indentation to use in the XML (default 4 spaces)
"""
out = io.BytesIO()
writer = StreamingXMLWriter(out, indent, nsmap=nsmap)
writer.serialize(node)
return out.getvalue() | python | def tostring(node, indent=4, nsmap=None):
"""
Convert a node into an XML string by using the StreamingXMLWriter.
This is useful for testing purposes.
:param node: a node object (typically an ElementTree object)
:param indent: the indentation to use in the XML (default 4 spaces)
"""
out = io.BytesIO()
writer = StreamingXMLWriter(out, indent, nsmap=nsmap)
writer.serialize(node)
return out.getvalue() | [
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339 | gem/oq-engine | openquake/baselib/node.py | parse | def parse(source, remove_comments=True, **kw):
"""Thin wrapper around ElementTree.parse"""
return ElementTree.parse(source, SourceLineParser(), **kw) | python | def parse(source, remove_comments=True, **kw):
"""Thin wrapper around ElementTree.parse"""
return ElementTree.parse(source, SourceLineParser(), **kw) | [
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340 | gem/oq-engine | openquake/baselib/node.py | iterparse | def iterparse(source, events=('end',), remove_comments=True, **kw):
"""Thin wrapper around ElementTree.iterparse"""
return ElementTree.iterparse(source, events, SourceLineParser(), **kw) | python | def iterparse(source, events=('end',), remove_comments=True, **kw):
"""Thin wrapper around ElementTree.iterparse"""
return ElementTree.iterparse(source, events, SourceLineParser(), **kw) | [
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341 | gem/oq-engine | openquake/baselib/node.py | _displayattrs | def _displayattrs(attrib, expandattrs):
"""
Helper function to display the attributes of a Node object in lexicographic
order.
:param attrib: dictionary with the attributes
:param expandattrs: if True also displays the value of the attributes
"""
if not attrib:
return ''
if expandattrs:
alist = ['%s=%r' % item for item in sorted(attrib.items())]
else:
alist = list(attrib)
return '{%s}' % ', '.join(alist) | python | def _displayattrs(attrib, expandattrs):
"""
Helper function to display the attributes of a Node object in lexicographic
order.
:param attrib: dictionary with the attributes
:param expandattrs: if True also displays the value of the attributes
"""
if not attrib:
return ''
if expandattrs:
alist = ['%s=%r' % item for item in sorted(attrib.items())]
else:
alist = list(attrib)
return '{%s}' % ', '.join(alist) | [
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342 | gem/oq-engine | openquake/baselib/node.py | _display | def _display(node, indent, expandattrs, expandvals, output):
"""Core function to display a Node object"""
attrs = _displayattrs(node.attrib, expandattrs)
if node.text is None or not expandvals:
val = ''
elif isinstance(node.text, str):
val = ' %s' % repr(node.text.strip())
else:
val = ' %s' % repr(node.text) # node.text can be a tuple
output.write(encode(indent + striptag(node.tag) + attrs + val + '\n'))
for sub_node in node:
_display(sub_node, indent + ' ', expandattrs, expandvals, output) | python | def _display(node, indent, expandattrs, expandvals, output):
"""Core function to display a Node object"""
attrs = _displayattrs(node.attrib, expandattrs)
if node.text is None or not expandvals:
val = ''
elif isinstance(node.text, str):
val = ' %s' % repr(node.text.strip())
else:
val = ' %s' % repr(node.text) # node.text can be a tuple
output.write(encode(indent + striptag(node.tag) + attrs + val + '\n'))
for sub_node in node:
_display(sub_node, indent + ' ', expandattrs, expandvals, output) | [
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343 | gem/oq-engine | openquake/baselib/node.py | to_literal | def to_literal(self):
"""
Convert the node into a literal Python object
"""
if not self.nodes:
return (self.tag, self.attrib, self.text, [])
else:
return (self.tag, self.attrib, self.text,
list(map(to_literal, self.nodes))) | python | def to_literal(self):
"""
Convert the node into a literal Python object
"""
if not self.nodes:
return (self.tag, self.attrib, self.text, [])
else:
return (self.tag, self.attrib, self.text,
list(map(to_literal, self.nodes))) | [
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344 | gem/oq-engine | openquake/baselib/node.py | pprint | def pprint(self, stream=None, indent=1, width=80, depth=None):
"""
Pretty print the underlying literal Python object
"""
pp.pprint(to_literal(self), stream, indent, width, depth) | python | def pprint(self, stream=None, indent=1, width=80, depth=None):
"""
Pretty print the underlying literal Python object
"""
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345 | gem/oq-engine | openquake/baselib/node.py | read_nodes | def read_nodes(fname, filter_elem, nodefactory=Node, remove_comments=True):
"""
Convert an XML file into a lazy iterator over Node objects
satifying the given specification, i.e. a function element -> boolean.
:param fname: file name of file object
:param filter_elem: element specification
In case of errors, add the file name to the error message.
"""
try:
for _, el in iterparse(fname, remove_comments=remove_comments):
if filter_elem(el):
yield node_from_elem(el, nodefactory)
el.clear() # save memory
except Exception:
etype, exc, tb = sys.exc_info()
msg = str(exc)
if not str(fname) in msg:
msg = '%s in %s' % (msg, fname)
raise_(etype, msg, tb) | python | def read_nodes(fname, filter_elem, nodefactory=Node, remove_comments=True):
"""
Convert an XML file into a lazy iterator over Node objects
satifying the given specification, i.e. a function element -> boolean.
:param fname: file name of file object
:param filter_elem: element specification
In case of errors, add the file name to the error message.
"""
try:
for _, el in iterparse(fname, remove_comments=remove_comments):
if filter_elem(el):
yield node_from_elem(el, nodefactory)
el.clear() # save memory
except Exception:
etype, exc, tb = sys.exc_info()
msg = str(exc)
if not str(fname) in msg:
msg = '%s in %s' % (msg, fname)
raise_(etype, msg, tb) | [
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346 | gem/oq-engine | openquake/baselib/node.py | node_from_xml | def node_from_xml(xmlfile, nodefactory=Node):
"""
Convert a .xml file into a Node object.
:param xmlfile: a file name or file object open for reading
"""
root = parse(xmlfile).getroot()
return node_from_elem(root, nodefactory) | python | def node_from_xml(xmlfile, nodefactory=Node):
"""
Convert a .xml file into a Node object.
:param xmlfile: a file name or file object open for reading
"""
root = parse(xmlfile).getroot()
return node_from_elem(root, nodefactory) | [
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347 | gem/oq-engine | openquake/baselib/node.py | node_from_ini | def node_from_ini(ini_file, nodefactory=Node, root_name='ini'):
"""
Convert a .ini file into a Node object.
:param ini_file: a filename or a file like object in read mode
"""
fileobj = open(ini_file) if isinstance(ini_file, str) else ini_file
cfp = configparser.RawConfigParser()
cfp.read_file(fileobj)
root = nodefactory(root_name)
sections = cfp.sections()
for section in sections:
params = dict(cfp.items(section))
root.append(Node(section, params))
return root | python | def node_from_ini(ini_file, nodefactory=Node, root_name='ini'):
"""
Convert a .ini file into a Node object.
:param ini_file: a filename or a file like object in read mode
"""
fileobj = open(ini_file) if isinstance(ini_file, str) else ini_file
cfp = configparser.RawConfigParser()
cfp.read_file(fileobj)
root = nodefactory(root_name)
sections = cfp.sections()
for section in sections:
params = dict(cfp.items(section))
root.append(Node(section, params))
return root | [
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348 | gem/oq-engine | openquake/baselib/node.py | node_to_ini | def node_to_ini(node, output=sys.stdout):
"""
Convert a Node object with the right structure into a .ini file.
:params node: a Node object
:params output: a file-like object opened in write mode
"""
for subnode in node:
output.write(u'\n[%s]\n' % subnode.tag)
for name, value in sorted(subnode.attrib.items()):
output.write(u'%s=%s\n' % (name, value))
output.flush() | python | def node_to_ini(node, output=sys.stdout):
"""
Convert a Node object with the right structure into a .ini file.
:params node: a Node object
:params output: a file-like object opened in write mode
"""
for subnode in node:
output.write(u'\n[%s]\n' % subnode.tag)
for name, value in sorted(subnode.attrib.items()):
output.write(u'%s=%s\n' % (name, value))
output.flush() | [
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349 | gem/oq-engine | openquake/baselib/node.py | node_copy | def node_copy(node, nodefactory=Node):
"""Make a deep copy of the node"""
return nodefactory(node.tag, node.attrib.copy(), node.text,
[node_copy(n, nodefactory) for n in node]) | python | def node_copy(node, nodefactory=Node):
"""Make a deep copy of the node"""
return nodefactory(node.tag, node.attrib.copy(), node.text,
[node_copy(n, nodefactory) for n in node]) | [
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350 | gem/oq-engine | openquake/baselib/node.py | context | def context(fname, node):
"""
Context manager managing exceptions and adding line number of the
current node and name of the current file to the error message.
:param fname: the current file being processed
:param node: the current node being processed
"""
try:
yield node
except Exception:
etype, exc, tb = sys.exc_info()
msg = 'node %s: %s, line %s of %s' % (
striptag(node.tag), exc, getattr(node, 'lineno', '?'), fname)
raise_(etype, msg, tb) | python | def context(fname, node):
"""
Context manager managing exceptions and adding line number of the
current node and name of the current file to the error message.
:param fname: the current file being processed
:param node: the current node being processed
"""
try:
yield node
except Exception:
etype, exc, tb = sys.exc_info()
msg = 'node %s: %s, line %s of %s' % (
striptag(node.tag), exc, getattr(node, 'lineno', '?'), fname)
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351 | gem/oq-engine | openquake/baselib/node.py | StreamingXMLWriter.shorten | def shorten(self, tag):
"""
Get the short representation of a fully qualified tag
:param str tag: a (fully qualified or not) XML tag
"""
if tag.startswith('{'):
ns, _tag = tag.rsplit('}')
tag = self.nsmap.get(ns[1:], '') + _tag
return tag | python | def shorten(self, tag):
"""
Get the short representation of a fully qualified tag
:param str tag: a (fully qualified or not) XML tag
"""
if tag.startswith('{'):
ns, _tag = tag.rsplit('}')
tag = self.nsmap.get(ns[1:], '') + _tag
return tag | [
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352 | gem/oq-engine | openquake/baselib/node.py | StreamingXMLWriter._write | def _write(self, text):
"""Write text by respecting the current indentlevel"""
spaces = ' ' * (self.indent * self.indentlevel)
t = spaces + text.strip() + '\n'
if hasattr(t, 'encode'):
t = t.encode(self.encoding, 'xmlcharrefreplace')
self.stream.write(t) | python | def _write(self, text):
"""Write text by respecting the current indentlevel"""
spaces = ' ' * (self.indent * self.indentlevel)
t = spaces + text.strip() + '\n'
if hasattr(t, 'encode'):
t = t.encode(self.encoding, 'xmlcharrefreplace')
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353 | gem/oq-engine | openquake/baselib/node.py | StreamingXMLWriter.start_tag | def start_tag(self, name, attrs=None):
"""Open an XML tag"""
if not attrs:
self._write('<%s>' % name)
else:
self._write('<' + name)
for (name, value) in sorted(attrs.items()):
self._write(
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self._write('>')
self.indentlevel += 1 | python | def start_tag(self, name, attrs=None):
"""Open an XML tag"""
if not attrs:
self._write('<%s>' % name)
else:
self._write('<' + name)
for (name, value) in sorted(attrs.items()):
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self._write('>')
self.indentlevel += 1 | [
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354 | gem/oq-engine | openquake/baselib/node.py | Node.getnodes | def getnodes(self, name):
"Return the direct subnodes with name 'name'"
for node in self.nodes:
if striptag(node.tag) == name:
yield node | python | def getnodes(self, name):
"Return the direct subnodes with name 'name'"
for node in self.nodes:
if striptag(node.tag) == name:
yield node | [
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355 | gem/oq-engine | openquake/baselib/node.py | Node.append | def append(self, node):
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if not isinstance(node, self.__class__):
raise TypeError('Expected Node instance, got %r' % node)
self.nodes.append(node) | python | def append(self, node):
"Append a new subnode"
if not isinstance(node, self.__class__):
raise TypeError('Expected Node instance, got %r' % node)
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356 | gem/oq-engine | openquake/baselib/node.py | ValidatingXmlParser.parse_bytes | def parse_bytes(self, bytestr, isfinal=True):
"""
Parse a byte string. If the string is very large, split it in chuncks
and parse each chunk with isfinal=False, then parse an empty chunk
with isfinal=True.
"""
with self._context():
self.filename = None
self.p.Parse(bytestr, isfinal)
return self._root | python | def parse_bytes(self, bytestr, isfinal=True):
"""
Parse a byte string. If the string is very large, split it in chuncks
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357 | gem/oq-engine | openquake/baselib/node.py | ValidatingXmlParser.parse_file | def parse_file(self, file_or_fname):
"""
Parse a file or a filename
"""
with self._context():
if hasattr(file_or_fname, 'read'):
self.filename = getattr(
file_or_fname, 'name', file_or_fname.__class__.__name__)
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self.filename = file_or_fname
with open(file_or_fname, 'rb') as f:
self.p.ParseFile(f)
return self._root | python | def parse_file(self, file_or_fname):
"""
Parse a file or a filename
"""
with self._context():
if hasattr(file_or_fname, 'read'):
self.filename = getattr(
file_or_fname, 'name', file_or_fname.__class__.__name__)
self.p.ParseFile(file_or_fname)
else:
self.filename = file_or_fname
with open(file_or_fname, 'rb') as f:
self.p.ParseFile(f)
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358 | gem/oq-engine | openquake/hmtk/plotting/seismicity/completeness/cumulative_rate_analysis.py | SimpleCumulativeRate._get_magnitudes_from_spacing | def _get_magnitudes_from_spacing(self, magnitudes, delta_m):
'''If a single magnitude spacing is input then create the bins
:param numpy.ndarray magnitudes:
Vector of earthquake magnitudes
:param float delta_m:
Magnitude bin width
:returns: Vector of magnitude bin edges (numpy.ndarray)
'''
min_mag = np.min(magnitudes)
max_mag = np.max(magnitudes)
if (max_mag - min_mag) < delta_m:
raise ValueError('Bin width greater than magnitude range!')
mag_bins = np.arange(np.floor(min_mag), np.ceil(max_mag), delta_m)
# Check to see if there are magnitudes in lower and upper bins
is_mag = np.logical_and(mag_bins - max_mag < delta_m,
min_mag - mag_bins < delta_m)
mag_bins = mag_bins[is_mag]
return mag_bins | python | def _get_magnitudes_from_spacing(self, magnitudes, delta_m):
'''If a single magnitude spacing is input then create the bins
:param numpy.ndarray magnitudes:
Vector of earthquake magnitudes
:param float delta_m:
Magnitude bin width
:returns: Vector of magnitude bin edges (numpy.ndarray)
'''
min_mag = np.min(magnitudes)
max_mag = np.max(magnitudes)
if (max_mag - min_mag) < delta_m:
raise ValueError('Bin width greater than magnitude range!')
mag_bins = np.arange(np.floor(min_mag), np.ceil(max_mag), delta_m)
# Check to see if there are magnitudes in lower and upper bins
is_mag = np.logical_and(mag_bins - max_mag < delta_m,
min_mag - mag_bins < delta_m)
mag_bins = mag_bins[is_mag]
return mag_bins | [
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359 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | _merge_data | def _merge_data(dat1, dat2):
"""
Merge two data dictionaries containing catalogue data
:parameter dictionary dat1:
Catalogue data dictionary
:parameter dictionary dat2:
Catalogue data dictionary
:returns:
A catalogue data dictionary containing the information originally
included in dat1 and dat2
"""
cnt = 0
for key in dat1:
flg1 = len(dat1[key]) > 0
flg2 = len(dat2[key]) > 0
if flg1 != flg2:
cnt += 1
if cnt:
raise Warning('Cannot merge catalogues with different' +
' attributes')
return None
else:
for key in dat1:
if isinstance(dat1[key], np.ndarray):
dat1[key] = np.concatenate((dat1[key], dat2[key]), axis=0)
elif isinstance(dat1[key], list):
dat1[key] += dat2[key]
else:
raise ValueError('Unknown type')
return dat1 | python | def _merge_data(dat1, dat2):
"""
Merge two data dictionaries containing catalogue data
:parameter dictionary dat1:
Catalogue data dictionary
:parameter dictionary dat2:
Catalogue data dictionary
:returns:
A catalogue data dictionary containing the information originally
included in dat1 and dat2
"""
cnt = 0
for key in dat1:
flg1 = len(dat1[key]) > 0
flg2 = len(dat2[key]) > 0
if flg1 != flg2:
cnt += 1
if cnt:
raise Warning('Cannot merge catalogues with different' +
' attributes')
return None
else:
for key in dat1:
if isinstance(dat1[key], np.ndarray):
dat1[key] = np.concatenate((dat1[key], dat2[key]), axis=0)
elif isinstance(dat1[key], list):
dat1[key] += dat2[key]
else:
raise ValueError('Unknown type')
return dat1 | [
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360 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue._get_row_str | def _get_row_str(self, i):
"""
Returns a string representation of the key information in a row
"""
row_data = ["{:s}".format(self.data['eventID'][i]),
"{:g}".format(self.data['year'][i]),
"{:g}".format(self.data['month'][i]),
"{:g}".format(self.data['day'][i]),
"{:g}".format(self.data['hour'][i]),
"{:g}".format(self.data['minute'][i]),
"{:.1f}".format(self.data['second'][i]),
"{:.3f}".format(self.data['longitude'][i]),
"{:.3f}".format(self.data['latitude'][i]),
"{:.1f}".format(self.data['depth'][i]),
"{:.1f}".format(self.data['magnitude'][i])]
return " ".join(row_data) | python | def _get_row_str(self, i):
"""
Returns a string representation of the key information in a row
"""
row_data = ["{:s}".format(self.data['eventID'][i]),
"{:g}".format(self.data['year'][i]),
"{:g}".format(self.data['month'][i]),
"{:g}".format(self.data['day'][i]),
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"{:.3f}".format(self.data['latitude'][i]),
"{:.1f}".format(self.data['depth'][i]),
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return " ".join(row_data) | [
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361 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.load_to_array | def load_to_array(self, keys):
"""
This loads the data contained in the catalogue into a numpy array. The
method works only for float data
:param keys:
A list of keys to be uploaded into the array
:type list:
"""
# Preallocate the numpy array
data = np.empty((len(self.data[keys[0]]), len(keys)))
for i in range(0, len(self.data[keys[0]])):
for j, key in enumerate(keys):
data[i, j] = self.data[key][i]
return data | python | def load_to_array(self, keys):
"""
This loads the data contained in the catalogue into a numpy array. The
method works only for float data
:param keys:
A list of keys to be uploaded into the array
:type list:
"""
# Preallocate the numpy array
data = np.empty((len(self.data[keys[0]]), len(keys)))
for i in range(0, len(self.data[keys[0]])):
for j, key in enumerate(keys):
data[i, j] = self.data[key][i]
return data | [
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362 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.load_from_array | def load_from_array(self, keys, data_array):
"""
This loads the data contained in an array into the catalogue object
:param keys:
A list of keys explaining the content of the columns in the array
:type list:
"""
if len(keys) != np.shape(data_array)[1]:
raise ValueError('Key list does not match shape of array!')
for i, key in enumerate(keys):
if key in self.INT_ATTRIBUTE_LIST:
self.data[key] = data_array[:, i].astype(int)
else:
self.data[key] = data_array[:, i]
if key not in self.TOTAL_ATTRIBUTE_LIST:
print('Key %s not a recognised catalogue attribute' % key)
self.update_end_year() | python | def load_from_array(self, keys, data_array):
"""
This loads the data contained in an array into the catalogue object
:param keys:
A list of keys explaining the content of the columns in the array
:type list:
"""
if len(keys) != np.shape(data_array)[1]:
raise ValueError('Key list does not match shape of array!')
for i, key in enumerate(keys):
if key in self.INT_ATTRIBUTE_LIST:
self.data[key] = data_array[:, i].astype(int)
else:
self.data[key] = data_array[:, i]
if key not in self.TOTAL_ATTRIBUTE_LIST:
print('Key %s not a recognised catalogue attribute' % key)
self.update_end_year() | [
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363 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.catalogue_mt_filter | def catalogue_mt_filter(self, mt_table, flag=None):
"""
Filter the catalogue using a magnitude-time table. The table has
two columns and n-rows.
:param nump.ndarray mt_table:
Magnitude time table with n-rows where column 1 is year and column
2 is magnitude
"""
if flag is None:
# No flag defined, therefore all events are initially valid
flag = np.ones(self.get_number_events(), dtype=bool)
for comp_val in mt_table:
id0 = np.logical_and(self.data['year'].astype(float) < comp_val[0],
self.data['magnitude'] < comp_val[1])
print(id0)
flag[id0] = False
if not np.all(flag):
self.purge_catalogue(flag) | python | def catalogue_mt_filter(self, mt_table, flag=None):
"""
Filter the catalogue using a magnitude-time table. The table has
two columns and n-rows.
:param nump.ndarray mt_table:
Magnitude time table with n-rows where column 1 is year and column
2 is magnitude
"""
if flag is None:
# No flag defined, therefore all events are initially valid
flag = np.ones(self.get_number_events(), dtype=bool)
for comp_val in mt_table:
id0 = np.logical_and(self.data['year'].astype(float) < comp_val[0],
self.data['magnitude'] < comp_val[1])
print(id0)
flag[id0] = False
if not np.all(flag):
self.purge_catalogue(flag) | [
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364 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.get_bounding_box | def get_bounding_box(self):
"""
Returns the bounding box of the catalogue
:returns: (West, East, South, North)
"""
return (np.min(self.data["longitude"]),
np.max(self.data["longitude"]),
np.min(self.data["latitude"]),
np.max(self.data["latitude"])) | python | def get_bounding_box(self):
"""
Returns the bounding box of the catalogue
:returns: (West, East, South, North)
"""
return (np.min(self.data["longitude"]),
np.max(self.data["longitude"]),
np.min(self.data["latitude"]),
np.max(self.data["latitude"])) | [
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365 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.get_decimal_time | def get_decimal_time(self):
'''
Returns the time of the catalogue as a decimal
'''
return decimal_time(self.data['year'],
self.data['month'],
self.data['day'],
self.data['hour'],
self.data['minute'],
self.data['second']) | python | def get_decimal_time(self):
'''
Returns the time of the catalogue as a decimal
'''
return decimal_time(self.data['year'],
self.data['month'],
self.data['day'],
self.data['hour'],
self.data['minute'],
self.data['second']) | [
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366 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.sort_catalogue_chronologically | def sort_catalogue_chronologically(self):
'''
Sorts the catalogue into chronological order
'''
dec_time = self.get_decimal_time()
idx = np.argsort(dec_time)
if np.all((idx[1:] - idx[:-1]) > 0.):
# Catalogue was already in chronological order
return
self.select_catalogue_events(idx) | python | def sort_catalogue_chronologically(self):
'''
Sorts the catalogue into chronological order
'''
dec_time = self.get_decimal_time()
idx = np.argsort(dec_time)
if np.all((idx[1:] - idx[:-1]) > 0.):
# Catalogue was already in chronological order
return
self.select_catalogue_events(idx) | [
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367 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.purge_catalogue | def purge_catalogue(self, flag_vector):
'''
Purges present catalogue with invalid events defined by flag_vector
:param numpy.ndarray flag_vector:
Boolean vector showing if events are selected (True) or not (False)
'''
id0 = np.where(flag_vector)[0]
self.select_catalogue_events(id0)
self.get_number_events() | python | def purge_catalogue(self, flag_vector):
'''
Purges present catalogue with invalid events defined by flag_vector
:param numpy.ndarray flag_vector:
Boolean vector showing if events are selected (True) or not (False)
'''
id0 = np.where(flag_vector)[0]
self.select_catalogue_events(id0)
self.get_number_events() | [
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368 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.select_catalogue_events | def select_catalogue_events(self, id0):
'''
Orders the events in the catalogue according to an indexing vector.
:param np.ndarray id0:
Pointer array indicating the locations of selected events
'''
for key in self.data:
if isinstance(
self.data[key], np.ndarray) and len(self.data[key]) > 0:
# Dictionary element is numpy array - use logical indexing
self.data[key] = self.data[key][id0]
elif isinstance(
self.data[key], list) and len(self.data[key]) > 0:
# Dictionary element is list
self.data[key] = [self.data[key][iloc] for iloc in id0]
else:
continue | python | def select_catalogue_events(self, id0):
'''
Orders the events in the catalogue according to an indexing vector.
:param np.ndarray id0:
Pointer array indicating the locations of selected events
'''
for key in self.data:
if isinstance(
self.data[key], np.ndarray) and len(self.data[key]) > 0:
# Dictionary element is numpy array - use logical indexing
self.data[key] = self.data[key][id0]
elif isinstance(
self.data[key], list) and len(self.data[key]) > 0:
# Dictionary element is list
self.data[key] = [self.data[key][iloc] for iloc in id0]
else:
continue | [
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369 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.get_depth_distribution | def get_depth_distribution(self, depth_bins, normalisation=False,
bootstrap=None):
'''
Gets the depth distribution of the earthquake catalogue to return a
single histogram. Depths may be normalised. If uncertainties are found
in the catalogue the distrbution may be bootstrap sampled
:param numpy.ndarray depth_bins:
getBin edges for the depths
:param bool normalisation:
Choose to normalise the results such that the total contributions
sum to 1.0 (True) or not (False)
:param int bootstrap:
Number of bootstrap samples
:returns:
Histogram of depth values
'''
if len(self.data['depth']) == 0:
# If depth information is missing
raise ValueError('Depths missing in catalogue')
if len(self.data['depthError']) == 0:
self.data['depthError'] = np.zeros(self.get_number_events(),
dtype=float)
return bootstrap_histogram_1D(self.data['depth'],
depth_bins,
self.data['depthError'],
normalisation=normalisation,
number_bootstraps=bootstrap,
boundaries=(0., None)) | python | def get_depth_distribution(self, depth_bins, normalisation=False,
bootstrap=None):
'''
Gets the depth distribution of the earthquake catalogue to return a
single histogram. Depths may be normalised. If uncertainties are found
in the catalogue the distrbution may be bootstrap sampled
:param numpy.ndarray depth_bins:
getBin edges for the depths
:param bool normalisation:
Choose to normalise the results such that the total contributions
sum to 1.0 (True) or not (False)
:param int bootstrap:
Number of bootstrap samples
:returns:
Histogram of depth values
'''
if len(self.data['depth']) == 0:
# If depth information is missing
raise ValueError('Depths missing in catalogue')
if len(self.data['depthError']) == 0:
self.data['depthError'] = np.zeros(self.get_number_events(),
dtype=float)
return bootstrap_histogram_1D(self.data['depth'],
depth_bins,
self.data['depthError'],
normalisation=normalisation,
number_bootstraps=bootstrap,
boundaries=(0., None)) | [
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370 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.get_depth_pmf | def get_depth_pmf(self, depth_bins, default_depth=5.0, bootstrap=None):
"""
Returns the depth distribution of the catalogue as a probability mass
function
"""
if len(self.data['depth']) == 0:
# If depth information is missing
return PMF([(1.0, default_depth)])
# Get the depth distribution
depth_hist = self.get_depth_distribution(depth_bins,
normalisation=True,
bootstrap=bootstrap)
# If the histogram does not sum to 1.0 then remove the difference
# from the lowest bin
depth_hist = np.around(depth_hist, 3)
while depth_hist.sum() - 1.0:
depth_hist[-1] -= depth_hist.sum() - 1.0
depth_hist = np.around(depth_hist, 3)
pmf_list = []
for iloc, prob in enumerate(depth_hist):
pmf_list.append((prob,
(depth_bins[iloc] + depth_bins[iloc + 1]) / 2.0))
return PMF(pmf_list) | python | def get_depth_pmf(self, depth_bins, default_depth=5.0, bootstrap=None):
"""
Returns the depth distribution of the catalogue as a probability mass
function
"""
if len(self.data['depth']) == 0:
# If depth information is missing
return PMF([(1.0, default_depth)])
# Get the depth distribution
depth_hist = self.get_depth_distribution(depth_bins,
normalisation=True,
bootstrap=bootstrap)
# If the histogram does not sum to 1.0 then remove the difference
# from the lowest bin
depth_hist = np.around(depth_hist, 3)
while depth_hist.sum() - 1.0:
depth_hist[-1] -= depth_hist.sum() - 1.0
depth_hist = np.around(depth_hist, 3)
pmf_list = []
for iloc, prob in enumerate(depth_hist):
pmf_list.append((prob,
(depth_bins[iloc] + depth_bins[iloc + 1]) / 2.0))
return PMF(pmf_list) | [
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371 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.get_magnitude_depth_distribution | def get_magnitude_depth_distribution(self, magnitude_bins, depth_bins,
normalisation=False, bootstrap=None):
'''
Returns a 2-D magnitude-depth histogram for the catalogue
:param numpy.ndarray magnitude_bins:
Bin edges for the magnitudes
:param numpy.ndarray depth_bins:
Bin edges for the depths
:param bool normalisation:
Choose to normalise the results such that the total contributions
sum to 1.0 (True) or not (False)
:param int bootstrap:
Number of bootstrap samples
:returns:
2D histogram of events in magnitude-depth bins
'''
if len(self.data['depth']) == 0:
# If depth information is missing
raise ValueError('Depths missing in catalogue')
if len(self.data['depthError']) == 0:
self.data['depthError'] = np.zeros(self.get_number_events(),
dtype=float)
if len(self.data['sigmaMagnitude']) == 0:
self.data['sigmaMagnitude'] = np.zeros(self.get_number_events(),
dtype=float)
return bootstrap_histogram_2D(self.data['magnitude'],
self.data['depth'],
magnitude_bins,
depth_bins,
boundaries=[(0., None), (None, None)],
xsigma=self.data['sigmaMagnitude'],
ysigma=self.data['depthError'],
normalisation=normalisation,
number_bootstraps=bootstrap) | python | def get_magnitude_depth_distribution(self, magnitude_bins, depth_bins,
normalisation=False, bootstrap=None):
'''
Returns a 2-D magnitude-depth histogram for the catalogue
:param numpy.ndarray magnitude_bins:
Bin edges for the magnitudes
:param numpy.ndarray depth_bins:
Bin edges for the depths
:param bool normalisation:
Choose to normalise the results such that the total contributions
sum to 1.0 (True) or not (False)
:param int bootstrap:
Number of bootstrap samples
:returns:
2D histogram of events in magnitude-depth bins
'''
if len(self.data['depth']) == 0:
# If depth information is missing
raise ValueError('Depths missing in catalogue')
if len(self.data['depthError']) == 0:
self.data['depthError'] = np.zeros(self.get_number_events(),
dtype=float)
if len(self.data['sigmaMagnitude']) == 0:
self.data['sigmaMagnitude'] = np.zeros(self.get_number_events(),
dtype=float)
return bootstrap_histogram_2D(self.data['magnitude'],
self.data['depth'],
magnitude_bins,
depth_bins,
boundaries=[(0., None), (None, None)],
xsigma=self.data['sigmaMagnitude'],
ysigma=self.data['depthError'],
normalisation=normalisation,
number_bootstraps=bootstrap) | [
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Bin edges for the depths
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Choose to normalise the results such that the total contributions
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Number of bootstrap samples
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372 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.get_magnitude_time_distribution | def get_magnitude_time_distribution(self, magnitude_bins, time_bins,
normalisation=False, bootstrap=None):
'''
Returns a 2-D histogram indicating the number of earthquakes in a
set of time-magnitude bins. Time is in decimal years!
:param numpy.ndarray magnitude_bins:
Bin edges for the magnitudes
:param numpy.ndarray time_bins:
Bin edges for the times
:param bool normalisation:
Choose to normalise the results such that the total contributions
sum to 1.0 (True) or not (False)
:param int bootstrap:
Number of bootstrap samples
:returns:
2D histogram of events in magnitude-year bins
'''
return bootstrap_histogram_2D(
self.get_decimal_time(),
self.data['magnitude'],
time_bins,
magnitude_bins,
xsigma=np.zeros(self.get_number_events()),
ysigma=self.data['sigmaMagnitude'],
normalisation=normalisation,
number_bootstraps=bootstrap) | python | def get_magnitude_time_distribution(self, magnitude_bins, time_bins,
normalisation=False, bootstrap=None):
'''
Returns a 2-D histogram indicating the number of earthquakes in a
set of time-magnitude bins. Time is in decimal years!
:param numpy.ndarray magnitude_bins:
Bin edges for the magnitudes
:param numpy.ndarray time_bins:
Bin edges for the times
:param bool normalisation:
Choose to normalise the results such that the total contributions
sum to 1.0 (True) or not (False)
:param int bootstrap:
Number of bootstrap samples
:returns:
2D histogram of events in magnitude-year bins
'''
return bootstrap_histogram_2D(
self.get_decimal_time(),
self.data['magnitude'],
time_bins,
magnitude_bins,
xsigma=np.zeros(self.get_number_events()),
ysigma=self.data['sigmaMagnitude'],
normalisation=normalisation,
number_bootstraps=bootstrap) | [
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Bin edges for the times
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373 | gem/oq-engine | openquake/hmtk/seismicity/catalogue.py | Catalogue.concatenate | def concatenate(self, catalogue):
"""
This method attaches one catalogue to the current one
:parameter catalogue:
An instance of :class:`htmk.seismicity.catalogue.Catalogue`
"""
atts = getattr(self, 'data')
attn = getattr(catalogue, 'data')
data = _merge_data(atts, attn)
if data is not None:
setattr(self, 'data', data)
for attrib in vars(self):
atts = getattr(self, attrib)
attn = getattr(catalogue, attrib)
if attrib is 'end_year':
setattr(self, attrib, max(atts, attn))
elif attrib is 'start_year':
setattr(self, attrib, min(atts, attn))
elif attrib is 'data':
pass
elif attrib is 'number_earthquakes':
setattr(self, attrib, atts + attn)
elif attrib is 'processes':
if atts != attn:
raise ValueError('The catalogues cannot be merged' +
' since the they have' +
' a different processing history')
else:
raise ValueError('unknown attribute: %s' % attrib)
self.sort_catalogue_chronologically() | python | def concatenate(self, catalogue):
"""
This method attaches one catalogue to the current one
:parameter catalogue:
An instance of :class:`htmk.seismicity.catalogue.Catalogue`
"""
atts = getattr(self, 'data')
attn = getattr(catalogue, 'data')
data = _merge_data(atts, attn)
if data is not None:
setattr(self, 'data', data)
for attrib in vars(self):
atts = getattr(self, attrib)
attn = getattr(catalogue, attrib)
if attrib is 'end_year':
setattr(self, attrib, max(atts, attn))
elif attrib is 'start_year':
setattr(self, attrib, min(atts, attn))
elif attrib is 'data':
pass
elif attrib is 'number_earthquakes':
setattr(self, attrib, atts + attn)
elif attrib is 'processes':
if atts != attn:
raise ValueError('The catalogues cannot be merged' +
' since the they have' +
' a different processing history')
else:
raise ValueError('unknown attribute: %s' % attrib)
self.sort_catalogue_chronologically() | [
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374 | gem/oq-engine | openquake/engine/engine.py | expose_outputs | def expose_outputs(dstore, owner=getpass.getuser(), status='complete'):
"""
Build a correspondence between the outputs in the datastore and the
ones in the database.
:param dstore: datastore
"""
oq = dstore['oqparam']
exportable = set(ekey[0] for ekey in export.export)
calcmode = oq.calculation_mode
dskeys = set(dstore) & exportable # exportable datastore keys
dskeys.add('fullreport')
rlzs = dstore['csm_info'].rlzs
if len(rlzs) > 1:
dskeys.add('realizations')
if len(dstore['csm_info/sg_data']) > 1: # export sourcegroups.csv
dskeys.add('sourcegroups')
hdf5 = dstore.hdf5
if 'hcurves-stats' in hdf5 or 'hcurves-rlzs' in hdf5:
if oq.hazard_stats() or oq.individual_curves or len(rlzs) == 1:
dskeys.add('hcurves')
if oq.uniform_hazard_spectra:
dskeys.add('uhs') # export them
if oq.hazard_maps:
dskeys.add('hmaps') # export them
if 'avg_losses-stats' in dstore or (
'avg_losses-rlzs' in dstore and len(rlzs)):
dskeys.add('avg_losses-stats')
if 'curves-rlzs' in dstore and len(rlzs) == 1:
dskeys.add('loss_curves-rlzs')
if 'curves-stats' in dstore and len(rlzs) > 1:
dskeys.add('loss_curves-stats')
if oq.conditional_loss_poes: # expose loss_maps outputs
if 'loss_curves-stats' in dstore:
dskeys.add('loss_maps-stats')
if 'all_loss_ratios' in dskeys:
dskeys.remove('all_loss_ratios') # export only specific IDs
if 'ruptures' in dskeys and 'scenario' in calcmode:
exportable.remove('ruptures') # do not export, as requested by Vitor
if 'rup_loss_table' in dskeys: # keep it hidden for the moment
dskeys.remove('rup_loss_table')
if 'hmaps' in dskeys and not oq.hazard_maps:
dskeys.remove('hmaps') # do not export the hazard maps
if logs.dbcmd('get_job', dstore.calc_id) is None:
# the calculation has not been imported in the db yet
logs.dbcmd('import_job', dstore.calc_id, oq.calculation_mode,
oq.description + ' [parent]', owner, status,
oq.hazard_calculation_id, dstore.datadir)
keysize = []
for key in sorted(dskeys & exportable):
try:
size_mb = dstore.get_attr(key, 'nbytes') / MB
except (KeyError, AttributeError):
size_mb = None
keysize.append((key, size_mb))
ds_size = os.path.getsize(dstore.filename) / MB
logs.dbcmd('create_outputs', dstore.calc_id, keysize, ds_size) | python | def expose_outputs(dstore, owner=getpass.getuser(), status='complete'):
"""
Build a correspondence between the outputs in the datastore and the
ones in the database.
:param dstore: datastore
"""
oq = dstore['oqparam']
exportable = set(ekey[0] for ekey in export.export)
calcmode = oq.calculation_mode
dskeys = set(dstore) & exportable # exportable datastore keys
dskeys.add('fullreport')
rlzs = dstore['csm_info'].rlzs
if len(rlzs) > 1:
dskeys.add('realizations')
if len(dstore['csm_info/sg_data']) > 1: # export sourcegroups.csv
dskeys.add('sourcegroups')
hdf5 = dstore.hdf5
if 'hcurves-stats' in hdf5 or 'hcurves-rlzs' in hdf5:
if oq.hazard_stats() or oq.individual_curves or len(rlzs) == 1:
dskeys.add('hcurves')
if oq.uniform_hazard_spectra:
dskeys.add('uhs') # export them
if oq.hazard_maps:
dskeys.add('hmaps') # export them
if 'avg_losses-stats' in dstore or (
'avg_losses-rlzs' in dstore and len(rlzs)):
dskeys.add('avg_losses-stats')
if 'curves-rlzs' in dstore and len(rlzs) == 1:
dskeys.add('loss_curves-rlzs')
if 'curves-stats' in dstore and len(rlzs) > 1:
dskeys.add('loss_curves-stats')
if oq.conditional_loss_poes: # expose loss_maps outputs
if 'loss_curves-stats' in dstore:
dskeys.add('loss_maps-stats')
if 'all_loss_ratios' in dskeys:
dskeys.remove('all_loss_ratios') # export only specific IDs
if 'ruptures' in dskeys and 'scenario' in calcmode:
exportable.remove('ruptures') # do not export, as requested by Vitor
if 'rup_loss_table' in dskeys: # keep it hidden for the moment
dskeys.remove('rup_loss_table')
if 'hmaps' in dskeys and not oq.hazard_maps:
dskeys.remove('hmaps') # do not export the hazard maps
if logs.dbcmd('get_job', dstore.calc_id) is None:
# the calculation has not been imported in the db yet
logs.dbcmd('import_job', dstore.calc_id, oq.calculation_mode,
oq.description + ' [parent]', owner, status,
oq.hazard_calculation_id, dstore.datadir)
keysize = []
for key in sorted(dskeys & exportable):
try:
size_mb = dstore.get_attr(key, 'nbytes') / MB
except (KeyError, AttributeError):
size_mb = None
keysize.append((key, size_mb))
ds_size = os.path.getsize(dstore.filename) / MB
logs.dbcmd('create_outputs', dstore.calc_id, keysize, ds_size) | [
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375 | gem/oq-engine | openquake/engine/engine.py | raiseMasterKilled | def raiseMasterKilled(signum, _stack):
"""
When a SIGTERM is received, raise the MasterKilled
exception with an appropriate error message.
:param int signum: the number of the received signal
:param _stack: the current frame object, ignored
"""
# Disable further CTRL-C to allow tasks revocation when Celery is used
if OQ_DISTRIBUTE.startswith('celery'):
signal.signal(signal.SIGINT, inhibitSigInt)
msg = 'Received a signal %d' % signum
if signum in (signal.SIGTERM, signal.SIGINT):
msg = 'The openquake master process was killed manually'
# kill the calculation only if os.getppid() != _PPID, i.e. the controlling
# terminal died; in the workers, do nothing
# NB: there is no SIGHUP on Windows
if hasattr(signal, 'SIGHUP'):
if signum == signal.SIGHUP:
if os.getppid() == _PPID:
return
else:
msg = 'The openquake master lost its controlling terminal'
raise MasterKilled(msg) | python | def raiseMasterKilled(signum, _stack):
"""
When a SIGTERM is received, raise the MasterKilled
exception with an appropriate error message.
:param int signum: the number of the received signal
:param _stack: the current frame object, ignored
"""
# Disable further CTRL-C to allow tasks revocation when Celery is used
if OQ_DISTRIBUTE.startswith('celery'):
signal.signal(signal.SIGINT, inhibitSigInt)
msg = 'Received a signal %d' % signum
if signum in (signal.SIGTERM, signal.SIGINT):
msg = 'The openquake master process was killed manually'
# kill the calculation only if os.getppid() != _PPID, i.e. the controlling
# terminal died; in the workers, do nothing
# NB: there is no SIGHUP on Windows
if hasattr(signal, 'SIGHUP'):
if signum == signal.SIGHUP:
if os.getppid() == _PPID:
return
else:
msg = 'The openquake master lost its controlling terminal'
raise MasterKilled(msg) | [
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376 | gem/oq-engine | openquake/engine/engine.py | job_from_file | def job_from_file(job_ini, job_id, username, **kw):
"""
Create a full job profile from a job config file.
:param job_ini:
Path to a job.ini file
:param job_id:
ID of the created job
:param username:
The user who will own this job profile and all results
:param kw:
Extra parameters including `calculation_mode` and `exposure_file`
:returns:
an oqparam instance
"""
hc_id = kw.get('hazard_calculation_id')
try:
oq = readinput.get_oqparam(job_ini, hc_id=hc_id)
except Exception:
logs.dbcmd('finish', job_id, 'failed')
raise
if 'calculation_mode' in kw:
oq.calculation_mode = kw.pop('calculation_mode')
if 'description' in kw:
oq.description = kw.pop('description')
if 'exposure_file' in kw: # hack used in commands.engine
fnames = kw.pop('exposure_file').split()
if fnames:
oq.inputs['exposure'] = fnames
elif 'exposure' in oq.inputs:
del oq.inputs['exposure']
logs.dbcmd('update_job', job_id,
dict(calculation_mode=oq.calculation_mode,
description=oq.description,
user_name=username,
hazard_calculation_id=hc_id))
return oq | python | def job_from_file(job_ini, job_id, username, **kw):
"""
Create a full job profile from a job config file.
:param job_ini:
Path to a job.ini file
:param job_id:
ID of the created job
:param username:
The user who will own this job profile and all results
:param kw:
Extra parameters including `calculation_mode` and `exposure_file`
:returns:
an oqparam instance
"""
hc_id = kw.get('hazard_calculation_id')
try:
oq = readinput.get_oqparam(job_ini, hc_id=hc_id)
except Exception:
logs.dbcmd('finish', job_id, 'failed')
raise
if 'calculation_mode' in kw:
oq.calculation_mode = kw.pop('calculation_mode')
if 'description' in kw:
oq.description = kw.pop('description')
if 'exposure_file' in kw: # hack used in commands.engine
fnames = kw.pop('exposure_file').split()
if fnames:
oq.inputs['exposure'] = fnames
elif 'exposure' in oq.inputs:
del oq.inputs['exposure']
logs.dbcmd('update_job', job_id,
dict(calculation_mode=oq.calculation_mode,
description=oq.description,
user_name=username,
hazard_calculation_id=hc_id))
return oq | [
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The user who will own this job profile and all results
:param kw:
Extra parameters including `calculation_mode` and `exposure_file`
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377 | gem/oq-engine | openquake/engine/engine.py | check_obsolete_version | def check_obsolete_version(calculation_mode='WebUI'):
"""
Check if there is a newer version of the engine.
:param calculation_mode:
- the calculation mode when called from the engine
- an empty string when called from the WebUI
:returns:
- a message if the running version of the engine is obsolete
- the empty string if the engine is updated
- None if the check could not be performed (i.e. github is down)
"""
if os.environ.get('JENKINS_URL') or os.environ.get('TRAVIS'):
# avoid flooding our API server with requests from CI systems
return
headers = {'User-Agent': 'OpenQuake Engine %s;%s;%s;%s' %
(__version__, calculation_mode, platform.platform(),
config.distribution.oq_distribute)}
try:
req = Request(OQ_API + '/engine/latest', headers=headers)
# NB: a timeout < 1 does not work
data = urlopen(req, timeout=1).read() # bytes
tag_name = json.loads(decode(data))['tag_name']
current = version_triple(__version__)
latest = version_triple(tag_name)
except Exception: # page not available or wrong version tag
return
if current < latest:
return ('Version %s of the engine is available, but you are '
'still using version %s' % (tag_name, __version__))
else:
return '' | python | def check_obsolete_version(calculation_mode='WebUI'):
"""
Check if there is a newer version of the engine.
:param calculation_mode:
- the calculation mode when called from the engine
- an empty string when called from the WebUI
:returns:
- a message if the running version of the engine is obsolete
- the empty string if the engine is updated
- None if the check could not be performed (i.e. github is down)
"""
if os.environ.get('JENKINS_URL') or os.environ.get('TRAVIS'):
# avoid flooding our API server with requests from CI systems
return
headers = {'User-Agent': 'OpenQuake Engine %s;%s;%s;%s' %
(__version__, calculation_mode, platform.platform(),
config.distribution.oq_distribute)}
try:
req = Request(OQ_API + '/engine/latest', headers=headers)
# NB: a timeout < 1 does not work
data = urlopen(req, timeout=1).read() # bytes
tag_name = json.loads(decode(data))['tag_name']
current = version_triple(__version__)
latest = version_triple(tag_name)
except Exception: # page not available or wrong version tag
return
if current < latest:
return ('Version %s of the engine is available, but you are '
'still using version %s' % (tag_name, __version__))
else:
return '' | [
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378 | gem/oq-engine | openquake/baselib/python3compat.py | encode | def encode(val):
"""
Encode a string assuming the encoding is UTF-8.
:param: a unicode or bytes object
:returns: bytes
"""
if isinstance(val, (list, tuple)): # encode a list or tuple of strings
return [encode(v) for v in val]
elif isinstance(val, str):
return val.encode('utf-8')
else:
# assume it was an already encoded object
return val | python | def encode(val):
"""
Encode a string assuming the encoding is UTF-8.
:param: a unicode or bytes object
:returns: bytes
"""
if isinstance(val, (list, tuple)): # encode a list or tuple of strings
return [encode(v) for v in val]
elif isinstance(val, str):
return val.encode('utf-8')
else:
# assume it was an already encoded object
return val | [
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379 | gem/oq-engine | openquake/baselib/python3compat.py | raise_ | def raise_(tp, value=None, tb=None):
"""
A function that matches the Python 2.x ``raise`` statement. This
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Python 2 and 3.
"""
if value is not None and isinstance(tp, Exception):
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if value is not None:
exc = tp(value)
else:
exc = tp
if exc.__traceback__ is not tb:
raise exc.with_traceback(tb)
raise exc | python | def raise_(tp, value=None, tb=None):
"""
A function that matches the Python 2.x ``raise`` statement. This
allows re-raising exceptions with the cls value and traceback on
Python 2 and 3.
"""
if value is not None and isinstance(tp, Exception):
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exc = tp(value)
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exc = tp
if exc.__traceback__ is not tb:
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raise exc | [
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380 | gem/oq-engine | openquake/commands/plot_pyro.py | plot_pyro | def plot_pyro(calc_id=-1):
"""
Plot the pyroclastic cloud and the assets
"""
# NB: matplotlib is imported inside since it is a costly import
import matplotlib.pyplot as p
dstore = util.read(calc_id)
sitecol = dstore['sitecol']
asset_risk = dstore['asset_risk'].value
pyro, = numpy.where(dstore['multi_peril']['PYRO'] == 1)
lons = sitecol.lons[pyro]
lats = sitecol.lats[pyro]
p.scatter(lons, lats, marker='o', color='red')
building_pyro, = numpy.where(asset_risk['building-PYRO'] == 1)
lons = sitecol.lons[building_pyro]
lats = sitecol.lats[building_pyro]
p.scatter(lons, lats, marker='.', color='green')
p.show() | python | def plot_pyro(calc_id=-1):
"""
Plot the pyroclastic cloud and the assets
"""
# NB: matplotlib is imported inside since it is a costly import
import matplotlib.pyplot as p
dstore = util.read(calc_id)
sitecol = dstore['sitecol']
asset_risk = dstore['asset_risk'].value
pyro, = numpy.where(dstore['multi_peril']['PYRO'] == 1)
lons = sitecol.lons[pyro]
lats = sitecol.lats[pyro]
p.scatter(lons, lats, marker='o', color='red')
building_pyro, = numpy.where(asset_risk['building-PYRO'] == 1)
lons = sitecol.lons[building_pyro]
lats = sitecol.lats[building_pyro]
p.scatter(lons, lats, marker='.', color='green')
p.show() | [
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381 | gem/oq-engine | openquake/hazardlib/geo/polygon.py | get_resampled_coordinates | def get_resampled_coordinates(lons, lats):
"""
Resample polygon line segments and return the coordinates of the new
vertices. This limits distortions when projecting a polygon onto a
spherical surface.
Parameters define longitudes and latitudes of a point collection in the
form of lists or numpy arrays.
:return:
A tuple of two numpy arrays: longitudes and latitudes
of resampled vertices.
"""
num_coords = len(lons)
assert num_coords == len(lats)
lons1 = numpy.array(lons)
lats1 = numpy.array(lats)
lons2 = numpy.concatenate((lons1[1:], lons1[:1]))
lats2 = numpy.concatenate((lats1[1:], lats1[:1]))
distances = geodetic.geodetic_distance(lons1, lats1, lons2, lats2)
resampled_lons = [lons[0]]
resampled_lats = [lats[0]]
for i in range(num_coords):
next_point = (i + 1) % num_coords
lon1, lat1 = lons[i], lats[i]
lon2, lat2 = lons[next_point], lats[next_point]
distance = distances[i]
num_points = int(distance / UPSAMPLING_STEP_KM) + 1
if num_points >= 2:
# We need to increase the resolution of this arc by adding new
# points.
new_lons, new_lats, _ = geodetic.npoints_between(
lon1, lat1, 0, lon2, lat2, 0, num_points)
resampled_lons.extend(new_lons[1:])
resampled_lats.extend(new_lats[1:])
else:
resampled_lons.append(lon2)
resampled_lats.append(lat2)
# NB: we cut off the last point because it repeats the first one
return numpy.array(resampled_lons[:-1]), numpy.array(resampled_lats[:-1]) | python | def get_resampled_coordinates(lons, lats):
"""
Resample polygon line segments and return the coordinates of the new
vertices. This limits distortions when projecting a polygon onto a
spherical surface.
Parameters define longitudes and latitudes of a point collection in the
form of lists or numpy arrays.
:return:
A tuple of two numpy arrays: longitudes and latitudes
of resampled vertices.
"""
num_coords = len(lons)
assert num_coords == len(lats)
lons1 = numpy.array(lons)
lats1 = numpy.array(lats)
lons2 = numpy.concatenate((lons1[1:], lons1[:1]))
lats2 = numpy.concatenate((lats1[1:], lats1[:1]))
distances = geodetic.geodetic_distance(lons1, lats1, lons2, lats2)
resampled_lons = [lons[0]]
resampled_lats = [lats[0]]
for i in range(num_coords):
next_point = (i + 1) % num_coords
lon1, lat1 = lons[i], lats[i]
lon2, lat2 = lons[next_point], lats[next_point]
distance = distances[i]
num_points = int(distance / UPSAMPLING_STEP_KM) + 1
if num_points >= 2:
# We need to increase the resolution of this arc by adding new
# points.
new_lons, new_lats, _ = geodetic.npoints_between(
lon1, lat1, 0, lon2, lat2, 0, num_points)
resampled_lons.extend(new_lons[1:])
resampled_lats.extend(new_lats[1:])
else:
resampled_lons.append(lon2)
resampled_lats.append(lat2)
# NB: we cut off the last point because it repeats the first one
return numpy.array(resampled_lons[:-1]), numpy.array(resampled_lats[:-1]) | [
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382 | gem/oq-engine | openquake/hazardlib/geo/surface/gridded.py | GriddedSurface.get_middle_point | def get_middle_point(self):
"""
Compute coordinates of surface middle point.
The actual definition of ``middle point`` depends on the type of
surface geometry.
:return:
instance of :class:`openquake.hazardlib.geo.point.Point`
representing surface middle point.
"""
lons = self.mesh.lons.squeeze()
lats = self.mesh.lats.squeeze()
depths = self.mesh.depths.squeeze()
lon_bar = lons.mean()
lat_bar = lats.mean()
idx = np.argmin((lons - lon_bar)**2 + (lats - lat_bar)**2)
return Point(lons[idx], lats[idx], depths[idx]) | python | def get_middle_point(self):
"""
Compute coordinates of surface middle point.
The actual definition of ``middle point`` depends on the type of
surface geometry.
:return:
instance of :class:`openquake.hazardlib.geo.point.Point`
representing surface middle point.
"""
lons = self.mesh.lons.squeeze()
lats = self.mesh.lats.squeeze()
depths = self.mesh.depths.squeeze()
lon_bar = lons.mean()
lat_bar = lats.mean()
idx = np.argmin((lons - lon_bar)**2 + (lats - lat_bar)**2)
return Point(lons[idx], lats[idx], depths[idx]) | [
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383 | gem/oq-engine | openquake/hazardlib/mfd/base.py | BaseMFD.modify | def modify(self, modification, parameters):
"""
Apply a single modification to an MFD parameters.
Reflects the modification method and calls it passing ``parameters``
as keyword arguments. See also :attr:`MODIFICATIONS`.
Modifications can be applied one on top of another. The logic
of stacking modifications is up to a specific MFD implementation.
:param modification:
String name representing the type of modification.
:param parameters:
Dictionary of parameters needed for modification.
:raises ValueError:
If ``modification`` is missing from :attr:`MODIFICATIONS`.
"""
if modification not in self.MODIFICATIONS:
raise ValueError('Modification %s is not supported by %s' %
(modification, type(self).__name__))
meth = getattr(self, 'modify_%s' % modification)
meth(**parameters)
self.check_constraints() | python | def modify(self, modification, parameters):
"""
Apply a single modification to an MFD parameters.
Reflects the modification method and calls it passing ``parameters``
as keyword arguments. See also :attr:`MODIFICATIONS`.
Modifications can be applied one on top of another. The logic
of stacking modifications is up to a specific MFD implementation.
:param modification:
String name representing the type of modification.
:param parameters:
Dictionary of parameters needed for modification.
:raises ValueError:
If ``modification`` is missing from :attr:`MODIFICATIONS`.
"""
if modification not in self.MODIFICATIONS:
raise ValueError('Modification %s is not supported by %s' %
(modification, type(self).__name__))
meth = getattr(self, 'modify_%s' % modification)
meth(**parameters)
self.check_constraints() | [
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384 | gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003._get_stddevs | def _get_stddevs(self, rup, arias, stddev_types, sites):
"""
Return standard deviations as defined in table 1, p. 200.
"""
stddevs = []
# Magnitude dependent inter-event term (Eq. 13)
if rup.mag < 4.7:
tau = 0.611
elif rup.mag > 7.6:
tau = 0.475
else:
tau = 0.611 - 0.047 * (rup.mag - 4.7)
# Retrieve site-class dependent sigma
sigma1, sigma2 = self._get_intra_event_sigmas(sites)
sigma = np.copy(sigma1)
# Implements the nonlinear intra-event sigma (Eq. 14)
idx = arias >= 0.125
sigma[idx] = sigma2[idx]
idx = np.logical_and(arias > 0.013, arias < 0.125)
sigma[idx] = sigma1[idx] - 0.106 * (np.log(arias[idx]) -
np.log(0.0132))
sigma_total = np.sqrt(tau ** 2. + sigma ** 2.)
for stddev_type in stddev_types:
assert stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES
if stddev_type == const.StdDev.TOTAL:
stddevs.append(sigma_total)
elif stddev_type == const.StdDev.INTRA_EVENT:
stddevs.append(sigma)
elif stddev_type == const.StdDev.INTER_EVENT:
stddevs.append(tau * np.ones_like(sites.vs30))
return stddevs | python | def _get_stddevs(self, rup, arias, stddev_types, sites):
"""
Return standard deviations as defined in table 1, p. 200.
"""
stddevs = []
# Magnitude dependent inter-event term (Eq. 13)
if rup.mag < 4.7:
tau = 0.611
elif rup.mag > 7.6:
tau = 0.475
else:
tau = 0.611 - 0.047 * (rup.mag - 4.7)
# Retrieve site-class dependent sigma
sigma1, sigma2 = self._get_intra_event_sigmas(sites)
sigma = np.copy(sigma1)
# Implements the nonlinear intra-event sigma (Eq. 14)
idx = arias >= 0.125
sigma[idx] = sigma2[idx]
idx = np.logical_and(arias > 0.013, arias < 0.125)
sigma[idx] = sigma1[idx] - 0.106 * (np.log(arias[idx]) -
np.log(0.0132))
sigma_total = np.sqrt(tau ** 2. + sigma ** 2.)
for stddev_type in stddev_types:
assert stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES
if stddev_type == const.StdDev.TOTAL:
stddevs.append(sigma_total)
elif stddev_type == const.StdDev.INTRA_EVENT:
stddevs.append(sigma)
elif stddev_type == const.StdDev.INTER_EVENT:
stddevs.append(tau * np.ones_like(sites.vs30))
return stddevs | [
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385 | gem/oq-engine | openquake/hazardlib/gsim/travasarou_2003.py | TravasarouEtAl2003._get_intra_event_sigmas | def _get_intra_event_sigmas(self, sites):
"""
The intra-event term nonlinear and dependent on both the site class
and the expected ground motion. In this case the sigma coefficients
are determined from the site class as described below Eq. 14
"""
sigma1 = 1.18 * np.ones_like(sites.vs30)
sigma2 = 0.94 * np.ones_like(sites.vs30)
idx1 = np.logical_and(sites.vs30 >= 360.0, sites.vs30 < 760.0)
idx2 = sites.vs30 < 360.0
sigma1[idx1] = 1.17
sigma2[idx1] = 0.93
sigma1[idx2] = 0.96
sigma2[idx2] = 0.73
return sigma1, sigma2 | python | def _get_intra_event_sigmas(self, sites):
"""
The intra-event term nonlinear and dependent on both the site class
and the expected ground motion. In this case the sigma coefficients
are determined from the site class as described below Eq. 14
"""
sigma1 = 1.18 * np.ones_like(sites.vs30)
sigma2 = 0.94 * np.ones_like(sites.vs30)
idx1 = np.logical_and(sites.vs30 >= 360.0, sites.vs30 < 760.0)
idx2 = sites.vs30 < 360.0
sigma1[idx1] = 1.17
sigma2[idx1] = 0.93
sigma1[idx2] = 0.96
sigma2[idx2] = 0.73
return sigma1, sigma2 | [
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386 | gem/oq-engine | openquake/hazardlib/gsim/boore_2014.py | BooreEtAl2014._get_pga_on_rock | def _get_pga_on_rock(self, C, rup, dists):
"""
Returns the median PGA on rock, which is a sum of the
magnitude and distance scaling
"""
return np.exp(self._get_magnitude_scaling_term(C, rup) +
self._get_path_scaling(C, dists, rup.mag)) | python | def _get_pga_on_rock(self, C, rup, dists):
"""
Returns the median PGA on rock, which is a sum of the
magnitude and distance scaling
"""
return np.exp(self._get_magnitude_scaling_term(C, rup) +
self._get_path_scaling(C, dists, rup.mag)) | [
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387 | gem/oq-engine | openquake/hazardlib/mfd/multi_mfd.py | MultiMFD.modify | def modify(self, modification, parameters):
"""
Apply a modification to the underlying point sources, with the
same parameters for all sources
"""
for src in self:
src.modify(modification, parameters) | python | def modify(self, modification, parameters):
"""
Apply a modification to the underlying point sources, with the
same parameters for all sources
"""
for src in self:
src.modify(modification, parameters) | [
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388 | gem/oq-engine | openquake/hazardlib/gsim/geomatrix_1993.py | Geomatrix1993SSlabNSHMP2008._compute_mean | def _compute_mean(self, C, mag, ztor, rrup):
"""
Compute mean value as in ``subroutine getGeom`` in ``hazgridXnga2.f``
"""
gc0 = 0.2418
ci = 0.3846
gch = 0.00607
g4 = 1.7818
ge = 0.554
gm = 1.414
mean = (
gc0 + ci + ztor * gch + C['gc1'] +
gm * mag + C['gc2'] * (10 - mag) ** 3 +
C['gc3'] * np.log(rrup + g4 * np.exp(ge * mag))
)
return mean | python | def _compute_mean(self, C, mag, ztor, rrup):
"""
Compute mean value as in ``subroutine getGeom`` in ``hazgridXnga2.f``
"""
gc0 = 0.2418
ci = 0.3846
gch = 0.00607
g4 = 1.7818
ge = 0.554
gm = 1.414
mean = (
gc0 + ci + ztor * gch + C['gc1'] +
gm * mag + C['gc2'] * (10 - mag) ** 3 +
C['gc3'] * np.log(rrup + g4 * np.exp(ge * mag))
)
return mean | [
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389 | gem/oq-engine | openquake/commands/abort.py | abort | def abort(job_id):
"""
Abort the given job
"""
job = logs.dbcmd('get_job', job_id) # job_id can be negative
if job is None:
print('There is no job %d' % job_id)
return
elif job.status not in ('executing', 'running'):
print('Job %d is %s' % (job.id, job.status))
return
name = 'oq-job-%d' % job.id
for p in psutil.process_iter():
if p.name() == name:
try:
os.kill(p.pid, signal.SIGTERM)
logs.dbcmd('set_status', job.id, 'aborted')
print('Job %d aborted' % job.id)
except Exception as exc:
print(exc)
break
else: # no break
# set job as failed if it is set as 'executing' or 'running' in the db
# but the corresponding process is not running anymore
logs.dbcmd('set_status', job.id, 'failed')
print('Unable to find a process for job %d,'
' setting it as failed' % job.id) | python | def abort(job_id):
"""
Abort the given job
"""
job = logs.dbcmd('get_job', job_id) # job_id can be negative
if job is None:
print('There is no job %d' % job_id)
return
elif job.status not in ('executing', 'running'):
print('Job %d is %s' % (job.id, job.status))
return
name = 'oq-job-%d' % job.id
for p in psutil.process_iter():
if p.name() == name:
try:
os.kill(p.pid, signal.SIGTERM)
logs.dbcmd('set_status', job.id, 'aborted')
print('Job %d aborted' % job.id)
except Exception as exc:
print(exc)
break
else: # no break
# set job as failed if it is set as 'executing' or 'running' in the db
# but the corresponding process is not running anymore
logs.dbcmd('set_status', job.id, 'failed')
print('Unable to find a process for job %d,'
' setting it as failed' % job.id) | [
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390 | gem/oq-engine | openquake/baselib/sap.py | compose | def compose(scripts, name='main', description=None, prog=None,
version=None):
"""
Collects together different scripts and builds a single
script dispatching to the subparsers depending on
the first argument, i.e. the name of the subparser to invoke.
:param scripts: a list of script instances
:param name: the name of the composed parser
:param description: description of the composed parser
:param prog: name of the script printed in the usage message
:param version: version of the script printed with --version
"""
assert len(scripts) >= 1, scripts
parentparser = argparse.ArgumentParser(
description=description, add_help=False)
parentparser.add_argument(
'--version', '-v', action='version', version=version)
subparsers = parentparser.add_subparsers(
help='available subcommands; use %s help <subcmd>' % prog,
prog=prog)
def gethelp(cmd=None):
if cmd is None:
print(parentparser.format_help())
return
subp = subparsers._name_parser_map.get(cmd)
if subp is None:
print('No help for unknown command %r' % cmd)
else:
print(subp.format_help())
help_script = Script(gethelp, 'help', help=False)
progname = '%s ' % prog if prog else ''
help_script.arg('cmd', progname + 'subcommand')
for s in list(scripts) + [help_script]:
subp = subparsers.add_parser(s.name, description=s.description)
for args, kw in s.all_arguments:
subp.add_argument(*args, **kw)
subp.set_defaults(_func=s.func)
def main(**kw):
try:
func = kw.pop('_func')
except KeyError:
parentparser.print_usage()
else:
return func(**kw)
main.__name__ = name
return Script(main, name, parentparser) | python | def compose(scripts, name='main', description=None, prog=None,
version=None):
"""
Collects together different scripts and builds a single
script dispatching to the subparsers depending on
the first argument, i.e. the name of the subparser to invoke.
:param scripts: a list of script instances
:param name: the name of the composed parser
:param description: description of the composed parser
:param prog: name of the script printed in the usage message
:param version: version of the script printed with --version
"""
assert len(scripts) >= 1, scripts
parentparser = argparse.ArgumentParser(
description=description, add_help=False)
parentparser.add_argument(
'--version', '-v', action='version', version=version)
subparsers = parentparser.add_subparsers(
help='available subcommands; use %s help <subcmd>' % prog,
prog=prog)
def gethelp(cmd=None):
if cmd is None:
print(parentparser.format_help())
return
subp = subparsers._name_parser_map.get(cmd)
if subp is None:
print('No help for unknown command %r' % cmd)
else:
print(subp.format_help())
help_script = Script(gethelp, 'help', help=False)
progname = '%s ' % prog if prog else ''
help_script.arg('cmd', progname + 'subcommand')
for s in list(scripts) + [help_script]:
subp = subparsers.add_parser(s.name, description=s.description)
for args, kw in s.all_arguments:
subp.add_argument(*args, **kw)
subp.set_defaults(_func=s.func)
def main(**kw):
try:
func = kw.pop('_func')
except KeyError:
parentparser.print_usage()
else:
return func(**kw)
main.__name__ = name
return Script(main, name, parentparser) | [
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391 | gem/oq-engine | openquake/baselib/sap.py | Script._add | def _add(self, name, *args, **kw):
"""
Add an argument to the underlying parser and grow the list
.all_arguments and the set .names
"""
argname = list(self.argdict)[self._argno]
if argname != name:
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397 | gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type1RecurrenceModel.incremental_value | def incremental_value(self, slip_moment, mmax, mag_value, bbar, dbar):
"""
Returns the incremental rate of earthquakes with M = mag_value
"""
delta_m = mmax - mag_value
dirac_term = np.zeros_like(mag_value)
dirac_term[np.fabs(delta_m) < 1.0E-12] = 1.0
a_1 = self._get_a1(bbar, dbar, slip_moment, mmax)
return a_1 * (bbar * np.exp(bbar * delta_m) * (delta_m > 0.0)) +\
a_1 * dirac_term | python | def incremental_value(self, slip_moment, mmax, mag_value, bbar, dbar):
"""
Returns the incremental rate of earthquakes with M = mag_value
"""
delta_m = mmax - mag_value
dirac_term = np.zeros_like(mag_value)
dirac_term[np.fabs(delta_m) < 1.0E-12] = 1.0
a_1 = self._get_a1(bbar, dbar, slip_moment, mmax)
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398 | gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type2RecurrenceModel._get_a2 | def _get_a2(bbar, dbar, slip_moment, mmax):
"""
Returns the A2 value defined in II.4 of Table 2
"""
return ((dbar - bbar) / bbar) * (slip_moment / _scale_moment(mmax)) | python | def _get_a2(bbar, dbar, slip_moment, mmax):
"""
Returns the A2 value defined in II.4 of Table 2
"""
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399 | gem/oq-engine | openquake/hmtk/faults/mfd/anderson_luco_arbitrary.py | Type3RecurrenceModel.incremental_value | def incremental_value(self, slip_moment, mmax, mag_value, bbar, dbar):
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"""
delta_m = mmax - mag_value
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"""
delta_m = mmax - mag_value
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Subsets and Splits