def nrml_from_shapefile(shapefile,
shapefile_faultname_attribute,
shapefile_dip_attribute,
shapefile_sliprate_attribute,
source_model_name,
simple_fault_tectonic_region,
magnitude_scaling_relation,
rupture_aspect_ratio,
upper_depth,
lower_depth,
a_value,
b_value,
min_mag,
max_mag,
rake,
output_dir,
incremental_mfd,
shapefile_uplift_attribute=None,
quiet=True):
"""Driver routine to convert nrml to shapefile
"""
# Get geometry
fault_traces, faultnames, dips, \
sliprate, fault_lengths = parse_line_shapefile(shapefile,
shapefile_faultname_attribute,
shapefile_dip_attribute,
shapefile_sliprate_attribute,
shapefile_uplift_attribute)
# Output is written line-by-line to this list
output_xml = []
append_xml_header(output_xml, source_model_name)
# If b-value is not given, take from Leonard 2008 model
region_shapefile = '../zones/Leonard2008/shapefiles/LEONARD08_NSHA18_MFD.shp'
if b_value is None:
b_value = b_value_from_region(fault_traces, region_shapefile)
# If tectonic region type is not given, take from domains model
domains_shapefile = '../zones/Domains/shapefiles/DOMAINS_NSHA18.shp'
if simple_fault_tectonic_region is None:
simple_fault_tectonic_region = trt_from_domains(fault_traces, domains_shapefile)
# Loop through each fault and add source specific info
for i in range(len(fault_traces)):
# Skip faults with zero or null sliprate
if sliprate[i] == "" or sliprate[i] == 0:
continue
simple_fault_id = i
A = fault_lengths[i]*(float(lower_depth)-float(upper_depth))
# Calculate M_max from scaling relations
scalrel = Leonard2014_SCR()
bin_width = 0.1
max_mag = scalrel.get_median_mag(A, float(rake))
char_mag = max_mag - 0.25 #characteristic magnitude for OQ def
# print A
# Calculate characteristic incremental occurrence rates from slip rate
if sliprate[i] != '""':
print sliprate[i]
# just to calculate the moment rate, need to fix this function
a_value, moment_rate = fault_slip_rate_GR_conversion.slip2GR(sliprate[i], A,
float(b_value[i]),
float(max_mag),
M_min=0.0)
a_value=None # We aren't using the a value
# mfd = YoungsCoppersmith1985MFD.from_total_moment_rate(min_mag=min_mag,
# b_val=float(b_value),
# char_mag=float(max_mag),
# total_moment_rate=moment_rate,
# bin_width=0.1)
# mags,rates=zip(*mfd.get_annual_occurrence_rates())
append_rupture_geometry(output_xml, fault_traces[i],
dips[i], simple_fault_id,
faultnames[i], upper_depth,
lower_depth, simple_fault_tectonic_region[i])
if incremental_mfd:
append_earthquake_information_inc(output_xml,
magnitude_scaling_relation,
rupture_aspect_ratio, char_mag, b_value[i],
min_mag, max_mag, rake, moment_rate, bin_width)
else:
append_earthquake_information_YC(output_xml,
magnitude_scaling_relation,
rupture_aspect_ratio, char_mag, b_value[i],
min_mag, max_mag, rake, moment_rate, bin_width)
# Close xml
output_xml.append(' </sourceModel>')
output_xml.append('</nrml>')
# Add newlines
output_xml = [oxml + '\n' for oxml in output_xml]
return output_xml
def run_smoothing(grid_lims,
smoothing_config,
catalogue,
completeness_table,
map_config,
run,
overwrite=True):
"""Run all the smoothing
"""
ystart = completeness_table[-1][0]
yend = catalogue.end_year
catalogue_comp = deepcopy(catalogue)
# Ensuring that catalogue is cleaned of earthquakes outside of
# completeness period
index = catalogue_comp.data['year'] >= ystart
catalogue_comp.purge_catalogue(index)
completeness_string = 'comp'
for ym in completeness_table:
completeness_string += '_%i_%.1f' % (ym[0], ym[1])
smoother_filename = 'Australia_Fixed_%i_%i_b%.3f_mmin_%.1f_0.1%s.csv' % (
smoothing_config["BandWidth"], smoothing_config["Length_Limit"],
bvalue, completeness_table[0][1], completeness_string)
filename = smoother_filename[:-4] + '.xml'
if os.path.exists(filename) and not overwrite:
print '%s already created, not overwriting!' % filename
return
smoother = SmoothedSeismicity(
[105., 160., 0.1, -47., -5, 0.1, 0., 20., 20.],
bvalue=smoothing_config['bvalue'])
print 'Running smoothing'
smoothed_grid = smoother.run_analysis(
catalogue_comp,
smoothing_config,
completeness_table=completeness_table)
smoother.write_to_csv(smoother_filename)
from openquake.hazardlib.nrml import SourceModelParser, write, NAMESPACE
from openquake.baselib.node import Node
from openquake.hazardlib import nrml
from openquake.hazardlib.sourcewriter import obj_to_node
# Build nrml input file of point sources
source_list = []
#i=0
min_mag = 4.5
max_mag = 7.8
bval = bvalue # just define as 1 for time being
# Read in data again to solve number fomatting issue in smoother.data
# For some reason it just returns 0 for all a values
try:
data = np.genfromtxt(smoother_filename, delimiter=',', skip_header=1)
except ValueError:
print 'Something wrong with file %s' % smoother_filename
sys.exit()
tom = PoissonTOM(
50) # Dummy temporal occurence model for building pt sources
msr = Leonard2014_SCR()
for j in range(len(data[:, 4])):
# print smoother.data[j,:]
identifier = 'FSS' + str(j) + '_' + str(run)
name = 'Frankel' + str(j) + '_' + str(run)
point = Point(data[j, 0], data[j, 1], data[j, 2])
annual_rate = data[j, 4] / (yend - ystart + 1)
aval = np.log10(annual_rate) + smoothing_config[
'bvalue'] * completeness_table[0][1]
mfd = TruncatedGRMFD(min_mag, max_mag, 0.1, aval, bval)
hypo_depth_dist = PMF([(0.5, 10.0), (0.25, 5.0), (0.25, 15.0)])
nodal_plane_dist = PMF([(0.3, NodalPlane(0, 30, 90)),
(0.2, NodalPlane(90, 30, 90)),
(0.3, NodalPlane(180, 30, 90)),
(0.2, NodalPlane(270, 30, 90))])
point_source = PointSource(identifier, name, 'Non_cratonic', mfd, 2,
msr, 2.0, tom, 0.1, 20.0, point,
nodal_plane_dist, hypo_depth_dist)
source_list.append(point_source)
nodes = list(map(obj_to_node, sorted(source_list)))
source_model = Node("sourceModel", {"name": name}, nodes=nodes)
with open(filename, 'wb') as f:
nrml.write([source_model], f, '%s', xmlns=NAMESPACE)
# Creating a basemap - input a cconfiguration and (if desired) a title
title = 'Smoothed seismicity rate for learning \nperiod %i 2017, Mmin = %.1f' % (
completeness_table[0][0], completeness_table[0][1])
basemap1 = HMTKBaseMap(map_config, 'Smoothed seismicity rate')
# Adding the smoothed grip to the basemap
sym = (2., 3., 'cx')
x, y = basemap1.m(smoother.data[:, 0], smoother.data[:, 1])
basemap1.m.scatter(x,
y,
marker='s',
c=np.log10(smoother.data[:, 4]),
cmap=plt.cm.coolwarm,
zorder=10,
lw=0,
vmin=-6.5,
vmax=1.5)
basemap1.m.drawcoastlines(linewidth=1, zorder=50) # Add coastline on top
basemap1.m.drawmeridians(
np.arange(map_config['min_lat'], map_config['max_lat'], 5))
basemap1.m.drawparallels(
np.arange(map_config['min_lon'], map_config['max_lon'], 5))
plt.colorbar(label='log10(Smoothed rate per cell)')
plt.legend()
figname = smoother_filename[:-4] + '_smoothed_rates_map.png'
plt.savefig(figname)
from openquake.hazardlib import nrml
from openquake.hazardlib.sourcewriter import obj_to_node
# Build nrml input file of point sources
source_list = []
#i=0
min_mag = 4.5
max_mag = 7.8
bval = bvalue # just define as 1 for time being
# Read in data again to solve number fomatting issue in smoother.data
# For some reason it just returns 0 for all a values
data = np.genfromtxt(smoother_filename, delimiter=',', skip_header=1)
#print max(data[:,4])
#print data[:,4]
#print len(data[:,4])
tom = PoissonTOM(50) # Dummy temporal occurence model for building pt sources
msr = Leonard2014_SCR()
for j in range(len(data[:, 4])):
# print smoother.data[j,:]
identifier = 'FSS' + str(j)
name = 'Frankel' + str(j)
point = Point(data[j, 0], data[j, 1], data[j, 2])
rate = data[j, 4]
aval = np.log10(rate)
# aval = rate # trying this based on some testing
# aval = np.log10(rate) #+ bval*completeness_table_a[0][1]
# print aval
mfd = TruncatedGRMFD(min_mag, max_mag, 0.1, aval, bval)
hypo_depth_dist = PMF([(0.5, 10.0), (0.25, 5.0), (0.25, 15.0)])
nodal_plane_dist = PMF([(0.3, NodalPlane(0, 30, 90)),
(0.2, NodalPlane(90, 30, 90)),
(0.3, NodalPlane(180, 30, 90)),
def nrml_from_shapefile(shapefile,
shapefile_faultname_attribute,
shapefile_dip_attribute,
shapefile_sliprate_attribute,
source_model_name,
simple_fault_tectonic_region,
magnitude_scaling_relation,
rupture_aspect_ratio,
upper_depth,
lower_depth,
a_value,
b_value,
min_mag,
max_mag,
rake,
output_dir,
shapefile_uplift_attribute=None,
quiet=True):
"""Driver routine to convert nrml to shapefile
"""
# Get geometry
fault_traces, faultnames, dips, \
sliprate, fault_lengths = parse_line_shapefile(shapefile,
shapefile_faultname_attribute,
shapefile_dip_attribute,
shapefile_sliprate_attribute,
shapefile_uplift_attribute)
# Output is written line-by-line to this list
output_xml = []
append_xml_header(output_xml, source_model_name)
# If b-value is not given, take from Leonard 2008 model
region_shapefile = '../zones/Leonard2008/shapefiles/LEONARD08_NSHA18_MFD.shp'
if b_value is None:
b_value = b_value_from_region(fault_traces, region_shapefile)
# If tectonic region type is not given, take from domains model
domains_shapefile = '../zones/Domains/shapefiles/DOMAINS_NSHA18.shp'
if simple_fault_tectonic_region is None:
simple_fault_tectonic_region = trt_from_domains(
fault_traces, domains_shapefile)
# Loop through each fault and add source specific info
for i in range(len(fault_traces)):
# Skip faults with zero or null sliprate
if sliprate[i] == "" or sliprate[i] == 0:
continue
simple_fault_id = i
A = fault_lengths[i] * (float(lower_depth) - float(upper_depth))
# Calculate M_max from scaling relations
scalrel = Leonard2014_SCR()
max_mag = scalrel.get_median_mag(A, float(rake))
# print A
# Calculate GR a values from slip rate
if sliprate[i] != '""':
# print sliprate[i]
a_value, moment_rate = fault_slip_rate_GR_conversion.slip2GR(
sliprate[i], A, float(b_value[i]), float(max_mag), M_min=0.0)
append_rupture_geometry(output_xml, fault_traces[i], dips[i],
simple_fault_id, faultnames[i], upper_depth,
lower_depth, simple_fault_tectonic_region[i])
append_earthquake_information(output_xml, magnitude_scaling_relation,
rupture_aspect_ratio, a_value,
b_value[i], min_mag, max_mag, rake)
# Close xml
output_xml.append(' </sourceModel>')
output_xml.append('</nrml>')
# Add newlines
output_xml = [oxml + '\n' for oxml in output_xml]
return output_xml
def run_smoothing(grid_lims, config, catalogue, completeness_table, map_config,
run):
"""Run all the smoothing
:params config:
Dictionary of configuration parameters.
For more info see helmstetter_werner_2012 code
and docs.
"""
completeness_string = 'comp'
for ym in completeness_table:
completeness_string += '_%i_%.1f' % (ym[0], ym[1])
smoother_filename = "Australia_Adaptive_K%i_b%.3f_mmin%.1f_%s.csv" % (
config['k'], config['bvalue'], config['mmin'], completeness_string)
filename = smoother_filename[:-4] + '.xml'
if os.path.exists(filename) and not overwrite:
print '%s already created, not overwriting!' % filename
return
smoother = h_w.HelmstetterEtAl2007(grid_lims,
config,
catalogue,
storage_file=("Aus1_tmp2%.3f_%s.hdf5" %
(config['bvalue'], run)))
smoother._get_catalogue_completeness_weights(completeness_table)
smoother.build_distance_arrays()
smoother.build_catalogue_2_grid_array()
# Exhaustive smoothing
exhaustive = False
if exhaustive == True:
params, poiss_llh = smoother.exhaustive_smoothing(
np.arange(2, 10, 1), np.arange(1.0e-6, 1.0e-5, 2.0e-6))
print params, poiss_llh
smoother.config["k"] = params[0]
smoother.config["r_min"] = params[1]
#print 'Exiting now, re-run using optimised parameters'
#sys.exit()
d_i = smoother.optimise_bandwidths()
smoother.run_smoothing(config["r_min"], d_i)
data = np.column_stack([smoother.grid, smoother.rates])
np.savetxt(
smoother_filename,
data,
# np.column_stack([smoother.grid, smoother.rates]),
delimiter=",",
fmt=["%.4f", "%.4f", "%.8e"],
header="longitude,latitude,rate")
# Creating a basemap - input a cconfiguration and (if desired) a title
title = 'Smoothed seismicity rate for learning \nperiod %i %i, K=%i, Mmin=%.1f' % (
config['learning_start'], config['learning_end'], smoother.config['k'],
smoother.config['mmin'])
basemap1 = HMTKBaseMap(map_config, title)
basemap1.m.drawmeridians(
np.arange(map_config['min_lat'], map_config['max_lat'], 5))
basemap1.m.drawparallels(
np.arange(map_config['min_lon'], map_config['max_lon'], 5))
# Adding the smoothed grip to the basemap
sym = (2., 3., 'cx')
x, y = basemap1.m(smoother.grid[:, 0], smoother.grid[:, 1])
if smoother.config['mmin'] == 3.5:
vmax = -1.0
elif smoother.config['mmin'] == 4.0:
vmax = -2.5
else:
vmax = -1.0
basemap1.m.scatter(x,
y,
marker='s',
c=np.log10(smoother.rates),
cmap=plt.cm.coolwarm,
zorder=10,
lw=0,
vmin=-7.0,
vmax=vmax)
basemap1.m.drawcoastlines(linewidth=1, zorder=50) # Add coastline on top
#basemap1.m.drawmeridians(np.arange(llat, ulat, 5))
#basemap1.m.drawparallels(np.arange(llon, ulon, 5))
plt.colorbar(label='Log10(Smoothed rate per cell)')
#plt.colorbar()#label='log10(Smoothed rate per cell)')
plt.legend()
#basemap1.m.scatter(x, y, marker = 's', c = smoother.data[:,4], cmap = plt.cm.coolwarm, zorder=10)
#basemap1.m.scatter([150],[22], marker='o')
#basemap1.fig.show()
#(smoother.data[0], smoother.data[1])
#basemap1.add_catalogue(catalogue_depth_clean, erlay=False)
figname = smoother_filename[:-4] + '_smoothed_rates_map.png'
plt.savefig(figname)
source_list = []
#i=0
min_mag = 4.5
max_mag = 7.2
# Read in data again to solve number fomatting issue in smoother.data
# For some reason it just returns 0 for all a values
#data = np.genfromtxt(smoother_filename, delimiter = ',', skip_header = 1)
tom = PoissonTOM(
50) # Dummy temporal occurence model for building pt sources
msr = Leonard2014_SCR()
for j in range(len(data[:, 2])):
identifier = 'ASS' + str(j) + '_' + str(run)
name = 'Helmstetter' + str(j) + '_' + str(run)
point = Point(data[j, 0], data[j, 1], 10)
rate = data[j, 2]
# Convert rate to a value
aval = np.log10(rate) + config['bvalue'] * config["mmin"]
mfd = TruncatedGRMFD(min_mag, max_mag, 0.1, aval, config['bvalue'])
hypo_depth_dist = PMF([(0.5, 10.0), (0.25, 5.0), (0.25, 15.0)])
nodal_plane_dist = PMF([(0.3, NodalPlane(0, 30, 90)),
(0.2, NodalPlane(90, 30, 90)),
(0.3, NodalPlane(180, 30, 90)),
(0.2, NodalPlane(270, 30, 90))])
point_source = PointSource(identifier, name, 'Non_cratonic', mfd, 2,
msr, 2.0, tom, 0.1, 20.0, point,
nodal_plane_dist, hypo_depth_dist)
source_list.append(point_source)
mod_name = "Australia_Adaptive_K%i_b%.3f" % (smoother.config['k'],
smoother.config['bvalue'])
nodes = list(map(obj_to_node, sorted(source_list)))
source_model = Node("sourceModel", {"name": name}, nodes=nodes)
with open(filename, 'wb') as f:
nrml.write([source_model], f, '%s', xmlns=NAMESPACE)
shp2nrml.append_xml_header(output_xml_geom,
('%s_geom_filtered' % source_model_name))
shp2nrml.append_xml_header(output_xml_all_methods,
('%s_all_methods_collapsed' % source_model_name))
for i, fault_trace in enumerate(fault_traces):
# Get basic parameters
fault_area = fault_lengths[i] * (float(lower_depth) - float(upper_depth))
sliprate = sliprates[i]
trt = trts[i]
faultname = faultnames[i]
b_value = b_values[i]
dip = dips[i]
print 'Calculating rates for %s in domain %s' % (faultname, trt)
# Calculate M_max from scaling relations
scalrel = Leonard2014_SCR()
max_mag = scalrel.get_median_mag(fault_area, float(rake))
# Round to nearest 0.05 mag unit
max_mag = np.round((max_mag - 0.05), 1) + 0.05
print 'Maximum magnitude is %.3f' % max_mag
# Append geometry information
for output_xml in output_xmls:
shp2nrml.append_rupture_geometry(output_xml, fault_trace, dip, i,
faultname, upper_depth, lower_depth,
trt)
# Get truncated Gutenberg-Richter rates
gr_mags, gr_rates, moment_rate = \
shp2nrml.sliprate2GR_incremental(sliprate, fault_area,
b_value, max_mag,