def updateDataFault(cls,
feature,
m_threshold=recurrence.FAULT_BACKGROUND_MAG_THRESHOLD):
"""Update or compute moment rates for selected feature of fault source
zone layer.
Input:
feature QGis polygon feature from fault source layer
Output:
parameters dict of computed parameters
"""
provider = cls.fault_source_layer.dataProvider()
provider_fault_back = cls.fault_background_layer.dataProvider()
provider_back = cls.background_zone_layer.dataProvider()
parameters = {}
# zone ID and title
(feature_id, feature_name) = utils.getFeatureAttributes(
cls.fault_background_layer, feature,
features.FAULT_BACKGROUND_ATTRIBUTES_ID)
if feature_name.toString() != '':
zone_name_str = feature_name.toString()
else:
zone_name_str = ""
parameters['plot_title_recurrence'] = 'Zone %s, %s' % (
feature_id.toString(), zone_name_str)
# get Shapely polygon from feature geometry
polylist, vertices = utils.polygonsQGS2Shapely((feature, ))
fault_poly = polylist[0]
# fault zone polygon area in square kilometres
parameters['area_fault_sqkm'] = utils.polygonAreaFromWGS84(
fault_poly) * 1.0e-6
# get buffer zone around fault zone (convert buffer distance to degrees)
(bz_poly, parameters['area_bz_sqkm']) = utils.computeBufferZone(
fault_poly, momentrate.BUFFER_AROUND_FAULT_ZONE_KM)
# find fault background zone in which centroid of fault zone lies
# NOTE: this can yield a wrong background zone if the fault zone
# is curved and at the edge of background zone.
# TODO(fab): use GIS "within" function instead, but note that fault
# zone can overlap several BG zones
(fbz, fbz_poly, parameters['area_fbz_sqkm']) = utils.findBackgroundZone(
fault_poly.centroid, provider_fault_back)
recurrence_attributes = attributes.getAttributesFromRecurrence(
provider, feature)
if recurrence_attributes is not None:
parameters.update(recurrence_attributes)
else:
return None
# get mmax and mcdist for FBZ from background zone
(mcdist_qv, mmax_qv) = areasource.getAttributesFromBackgroundZones(
fbz_poly.centroid, provider_back, areasource.MCDIST_MMAX_ATTRIBUTES)
mmax = float(mmax_qv.toDouble()[0])
mcdist = str(mcdist_qv.toString())
parameters['mmax'] = mmax
## moment rate from EQs
# get quakes from catalog (cut with fault background polygon)
# cut catalog with min/max depth according to UI spinboxes
(mindepth, maxdepth) = eqcatalog.getMinMaxDepth(cls)
fbz_cat = QPCatalog.QPCatalog()
fbz_cat.merge(cls.catalog)
fbz_cat.cut(geometry=fbz_poly)
fbz_cat.cut(mindepth=mindepth, maxdepth=maxdepth)
bz_cat = QPCatalog.QPCatalog()
bz_cat.merge(cls.catalog)
bz_cat.cut(geometry=bz_poly)
bz_cat.cut(mindepth=mindepth, maxdepth=maxdepth)
parameters['eq_count_fbz'] = fbz_cat.size()
parameters['eq_count_bz'] = bz_cat.size()
# sum up moment from quakes (converted from Mw with Kanamori eq.)
# use quakes in buffer zone
magnitudes = []
for ev in bz_cat.eventParameters.event:
mag = ev.getPreferredMagnitude()
magnitudes.append(mag.mag.value)
moment = numpy.array(momentrate.magnitude2moment(magnitudes))
# scale moment: per year and area (in km^2)
parameters['mr_eq'] = moment.sum() / (parameters['area_bz_sqkm'] *
cls.catalog_time_span[0])
## moment rate from activity (RM)
# moment rates from activity: use a and b values from buffer zone
act_bz_arr_a = parameters['activity_bz_act_a'].strip().split()
act_bz_arr_b = parameters['activity_bz_act_b'].strip().split()
a_bz_arr = [float(x) for x in act_bz_arr_a]
b_bz_arr = [float(x) for x in act_bz_arr_b]
a_values = a_bz_arr
momentrates_arr = numpy.array(
momentrate.momentrateFromActivity(a_values, b_bz_arr,
mmax)) / cls.catalog_time_span[0]
parameters['mr_activity'] = momentrates_arr.tolist()
# moment rates from activity: use a and b values from FBZ
# (above threshold)
act_fbz_at_arr_a = parameters['activity_fbz_at_act_a'].strip().split()
act_fbz_at_arr_b = parameters['activity_fbz_at_act_b'].strip().split()
a_fbz_at_arr = [float(x) for x in act_fbz_at_arr_a]
b_fbz_at_arr = [float(x) for x in act_fbz_at_arr_b]
a_values = a_fbz_at_arr
momentrates_fbz_at_arr = numpy.array(
momentrate.momentrateFromActivity(a_values, b_fbz_at_arr,
mmax)) / cls.catalog_time_span[0]
parameters['mr_activity_fbz_at'] = momentrates_fbz_at_arr.tolist()
parameters['activity_m_threshold'] = m_threshold
# FMD from quakes in FBZ
cls.feature_data_fault_source['fmd'] = fmd.computeZoneFMD(
cls, feature, fbz_cat)
(parameters['ml_a'], parameters['ml_b'], parameters['ml_mc'],
parameters['ml_magctr']) = fmd.getFMDValues(
cls.feature_data_fault_source['fmd'])
## moment rate from slip rate
# TODO(fab): check correct scaling of moment rate from slip rate
(moment_rate_min, moment_rate_max) = \
momentrate.momentrateFromSlipRate(parameters['sliprate_min'],
parameters['sliprate_max'],
parameters['area_fault_sqkm'] * 1.0e6)
parameters['mr_slip'] = [moment_rate_min, moment_rate_max]
return parameters
def computeRecurrence(layer_fault,
layer_fault_background=None,
layer_background=None,
catalog=None,
catalog_time_span=None,
b_value=None,
mmin=atticivy.ATTICIVY_MMIN,
m_threshold=FAULT_BACKGROUND_MAG_THRESHOLD,
mindepth=eqcatalog.CUT_DEPTH_MIN,
maxdepth=eqcatalog.CUT_DEPTH_MAX,
ui_mode=True):
"""Compute recurrence parameters according to Bungum paper.
Parameters from Jochen's Matlab implementation:
% rParams.fBvalue : b-value
% rParams.fS : Slip rate (mm/year)
% rParams.fD : Average slip (m)
% rParams.fLength : Fault length (m)
% rParams.fWidth : Fault width (m)
% rParams.fM00 : M0(0) for Ms = 0, c in logM0=c-dM
% rParams.fMmin : Minimum magnitude
% rParams.fBinM : magnitude binnning
% rParams.fMmax : Maximum magnitude
% rParams.fDmoment : d in logM0=c-dM
% rParams.fRigid : Rgidity in Pascal
rParams.fBvalue = 1;
rParams.fS = 1e-3;
rParams.fD = 1;
rParams.fLength = 100000;
rParams.fWidth = 50000;
rParams.fM00 = 16.05;
rParams.fMmin = 5;
rParams.fBinM = 0.1;
rParams.fMmax = 8;
rParams.fDmoment = 1.5;
rParams.fRigid = 30e+6;
"""
result_values = []
provider_fault = layer_fault.dataProvider()
fts = layer_fault.selectedFeatures()
# loop over fault polygons
for zone_idx, feature in enumerate(fts):
# collect the following attribute data:
# - FBZ zone ID
# - (a, b, act_a, act_b) for FBZ
# - (a, b, act_a, act_b) for buffer zone
# - m_threshold
# - (a, b, act_a, act_b) for FBZ, below magnitude threshold
# - (a, b, act_a, act_b) for FBZ, above magnitude threshold
# - (a, b, Mc) from maximum likelihood G-R
# - Mmax from background
# - a from slip rate (min/max)
# - activity rate (min/max)
# - moment rate (min/max)
zone_data_string_min = ""
zone_data_string_max = ""
if ui_mode is False:
print "\n=== Processing FSZ feature, id %s ===" % feature.id()
# get parameters from background zones
activity_back = computeActivityFromBackground(feature,
layer_fault_background,
layer_background,
catalog,
mmin,
m_threshold,
mindepth,
maxdepth,
ui_mode=ui_mode)
if activity_back is None:
result_values.append(None)
continue
# get attribute values of zone:
# - MAXMAG, SLIPRATEMI, SLIPRATEMA
attribute_map_fault = utils.getAttributeIndex(
provider_fault,
features.FAULT_SOURCE_ATTRIBUTES_RECURRENCE,
create=True)
# get maximum magnitude (Note: it's int in feature attributes)
maxmag_name = features.FAULT_SOURCE_ATTR_MAGNITUDE_MAX['name']
maxmag = feature[attribute_map_fault[maxmag_name][0]].toDouble()[0]
# get minimum of annual slip rate
slipratemi_name = features.FAULT_SOURCE_ATTR_SLIPRATE_MIN['name']
slipratemi = \
feature[attribute_map_fault[slipratemi_name][0]].toDouble()[0]
# get maximum of annual slip rate
slipratema_name = features.FAULT_SOURCE_ATTR_SLIPRATE_MAX['name']
slipratema = \
feature[attribute_map_fault[slipratema_name][0]].toDouble()[0]
# get area of fault zone
polylist, vertices = utils.polygonsQGS2Shapely((feature, ))
fault_poly = polylist[0]
fault_area = utils.polygonAreaFromWGS84(fault_poly)
# determine b value that is used in further computations
# - use b value computed on fault background zone
if b_value is None:
b_value = activity_back['fbz']['activity'][atticivy.ATTICIVY_B_IDX]
# equidistant magnitude array on which activity rates are computed
# from global Mmin to zone-dependent Mmax
mag_arr = numpy.arange(MAGNITUDE_MIN, maxmag, MAGNITUDE_BINNING)
if len(mag_arr) == 0:
result_values.append(None)
continue
cumulative_number_min = cumulative_occurrence_model_2(
mag_arr, maxmag, slipratemi, b_value,
fault_area) / catalog_time_span
cumulative_number_max = cumulative_occurrence_model_2(
mag_arr, maxmag, slipratema, b_value,
fault_area) / catalog_time_span
# use a value computed with max of slip rate
a_value_min = computeAValueFromOccurrence(
numpy.log10(cumulative_number_min[0]), b_value, MAGNITUDE_MIN)
a_value_max = computeAValueFromOccurrence(
numpy.log10(cumulative_number_max[0]), b_value, MAGNITUDE_MIN)
# compute contribution to total seismic moment
# TODO(fab): double-check scaling with Laurentiu!
# shear modulus: Pa = N / m^2 = kg / (m * s^2) = kg / (10^-3 km * s^2)
# 1 kg / (km * s^2) = 10^3 N
# slip rate: mm / year
# area: m^2
# moment rate unit: Nm / (year * km^2)
# kg * 10^-3 m * m^2 / (m * s^2 * 365.25*24*60*60 s)
# = 10^3 N * 10^-3 m^3 / (10^-3 * [year] s))
# = 10^3 Nm * m^2 / [year] s <- divide this by area in metres (?)
# kg m^3 / (m s^3) = kg m^2 / s^3
(seismic_moment_rate_min, seismic_moment_rate_max) = \
momentrate.momentrateFromSlipRate(slipratemi, slipratema,
fault_area)
# serialize activity rate FMD
for value_pair_idx in xrange(mag_arr.shape[0]):
zone_data_string_min = "%s %.1f %.2e" % (
zone_data_string_min, mag_arr[value_pair_idx],
cumulative_number_min[value_pair_idx])
zone_data_string_max = "%s %.1f %.2e" % (
zone_data_string_max, mag_arr[value_pair_idx],
cumulative_number_max[value_pair_idx])
attribute_list = []
if activity_back['fbz']['ID'] is None:
fbz_id = activity_back['fbz']['ID']
else:
fbz_id = str(activity_back['fbz']['ID'])
attribute_list.append(fbz_id)
attribute_list.extend(
checkAndCastActivityResult(activity_back['fbz']['activity']))
attribute_list.extend(
checkAndCastActivityResult(activity_back['bz']['activity']))
attribute_list.append(float(m_threshold))
attribute_list.extend(
checkAndCastActivityResult(activity_back['fbz_below']['activity']))
attribute_list.extend(
checkAndCastActivityResult(activity_back['fbz_above']['activity']))
attribute_list.extend([numpy.nan] * 4) # ML, Mmax
attribute_list.extend([float(a_value_min), float(a_value_max)])
attribute_list.extend([numpy.nan] * 3) # three momentrate components
attribute_list.extend([
float(seismic_moment_rate_min),
float(seismic_moment_rate_max),
zone_data_string_min.lstrip(),
zone_data_string_max.lstrip()
])
result_values.append(attribute_list)
return result_values
def computeRecurrence(layer_fault, layer_fault_background=None,
layer_background=None, catalog=None, catalog_time_span=None, b_value=None,
mmin=atticivy.ATTICIVY_MMIN,
m_threshold=FAULT_BACKGROUND_MAG_THRESHOLD,
mindepth=eqcatalog.CUT_DEPTH_MIN, maxdepth=eqcatalog.CUT_DEPTH_MAX,
ui_mode=True):
"""Compute recurrence parameters according to Bungum paper.
Parameters from Jochen's Matlab implementation:
% rParams.fBvalue : b-value
% rParams.fS : Slip rate (mm/year)
% rParams.fD : Average slip (m)
% rParams.fLength : Fault length (m)
% rParams.fWidth : Fault width (m)
% rParams.fM00 : M0(0) for Ms = 0, c in logM0=c-dM
% rParams.fMmin : Minimum magnitude
% rParams.fBinM : magnitude binnning
% rParams.fMmax : Maximum magnitude
% rParams.fDmoment : d in logM0=c-dM
% rParams.fRigid : Rgidity in Pascal
rParams.fBvalue = 1;
rParams.fS = 1e-3;
rParams.fD = 1;
rParams.fLength = 100000;
rParams.fWidth = 50000;
rParams.fM00 = 16.05;
rParams.fMmin = 5;
rParams.fBinM = 0.1;
rParams.fMmax = 8;
rParams.fDmoment = 1.5;
rParams.fRigid = 30e+6;
"""
result_values = []
provider_fault = layer_fault.dataProvider()
fts = layer_fault.selectedFeatures()
# loop over fault polygons
for zone_idx, feature in enumerate(fts):
# collect the following attribute data:
# - FBZ zone ID
# - (a, b, act_a, act_b) for FBZ
# - (a, b, act_a, act_b) for buffer zone
# - m_threshold
# - (a, b, act_a, act_b) for FBZ, below magnitude threshold
# - (a, b, act_a, act_b) for FBZ, above magnitude threshold
# - (a, b, Mc) from maximum likelihood G-R
# - Mmax from background
# - a from slip rate (min/max)
# - activity rate (min/max)
# - moment rate (min/max)
zone_data_string_min = ""
zone_data_string_max = ""
if ui_mode is False:
print "\n=== Processing FSZ feature, id %s ===" % feature.id()
# get parameters from background zones
activity_back = computeActivityFromBackground(feature,
layer_fault_background, layer_background, catalog, mmin,
m_threshold, mindepth, maxdepth, ui_mode=ui_mode)
if activity_back is None:
result_values.append(None)
continue
# get attribute values of zone:
# - MAXMAG, SLIPRATEMI, SLIPRATEMA
attribute_map_fault = utils.getAttributeIndex(provider_fault,
features.FAULT_SOURCE_ATTRIBUTES_RECURRENCE, create=True)
# get maximum magnitude (Note: it's int in feature attributes)
maxmag_name = features.FAULT_SOURCE_ATTR_MAGNITUDE_MAX['name']
maxmag = feature[attribute_map_fault[maxmag_name][0]].toDouble()[0]
# get minimum of annual slip rate
slipratemi_name = features.FAULT_SOURCE_ATTR_SLIPRATE_MIN['name']
slipratemi = \
feature[attribute_map_fault[slipratemi_name][0]].toDouble()[0]
# get maximum of annual slip rate
slipratema_name = features.FAULT_SOURCE_ATTR_SLIPRATE_MAX['name']
slipratema = \
feature[attribute_map_fault[slipratema_name][0]].toDouble()[0]
# get area of fault zone
polylist, vertices = utils.polygonsQGS2Shapely((feature,))
fault_poly = polylist[0]
fault_area = utils.polygonAreaFromWGS84(fault_poly)
# determine b value that is used in further computations
# - use b value computed on fault background zone
if b_value is None:
b_value = activity_back['fbz']['activity'][atticivy.ATTICIVY_B_IDX]
# equidistant magnitude array on which activity rates are computed
# from global Mmin to zone-dependent Mmax
mag_arr = numpy.arange(MAGNITUDE_MIN, maxmag, MAGNITUDE_BINNING)
if len(mag_arr) == 0:
result_values.append(None)
continue
cumulative_number_min = cumulative_occurrence_model_2(mag_arr, maxmag,
slipratemi, b_value, fault_area) / catalog_time_span
cumulative_number_max = cumulative_occurrence_model_2(mag_arr, maxmag,
slipratema, b_value, fault_area) / catalog_time_span
# use a value computed with max of slip rate
a_value_min = computeAValueFromOccurrence(
numpy.log10(cumulative_number_min[0]), b_value, MAGNITUDE_MIN)
a_value_max = computeAValueFromOccurrence(
numpy.log10(cumulative_number_max[0]), b_value, MAGNITUDE_MIN)
# compute contribution to total seismic moment
# TODO(fab): double-check scaling with Laurentiu!
# shear modulus: Pa = N / m^2 = kg / (m * s^2) = kg / (10^-3 km * s^2)
# 1 kg / (km * s^2) = 10^3 N
# slip rate: mm / year
# area: m^2
# moment rate unit: Nm / (year * km^2)
# kg * 10^-3 m * m^2 / (m * s^2 * 365.25*24*60*60 s)
# = 10^3 N * 10^-3 m^3 / (10^-3 * [year] s))
# = 10^3 Nm * m^2 / [year] s <- divide this by area in metres (?)
# kg m^3 / (m s^3) = kg m^2 / s^3
(seismic_moment_rate_min, seismic_moment_rate_max) = \
momentrate.momentrateFromSlipRate(slipratemi, slipratema,
fault_area)
# serialize activity rate FMD
for value_pair_idx in xrange(mag_arr.shape[0]):
zone_data_string_min = "%s %.1f %.2e" % (zone_data_string_min,
mag_arr[value_pair_idx],
cumulative_number_min[value_pair_idx])
zone_data_string_max = "%s %.1f %.2e" % (zone_data_string_max,
mag_arr[value_pair_idx],
cumulative_number_max[value_pair_idx])
attribute_list = []
if activity_back['fbz']['ID'] is None:
fbz_id = activity_back['fbz']['ID']
else:
fbz_id = str(activity_back['fbz']['ID'])
attribute_list.append(fbz_id)
attribute_list.extend(checkAndCastActivityResult(
activity_back['fbz']['activity']))
attribute_list.extend(checkAndCastActivityResult(
activity_back['bz']['activity']))
attribute_list.append(float(m_threshold))
attribute_list.extend(checkAndCastActivityResult(
activity_back['fbz_below']['activity']))
attribute_list.extend(checkAndCastActivityResult(
activity_back['fbz_above']['activity']))
attribute_list.extend([numpy.nan] * 4) # ML, Mmax
attribute_list.extend([float(a_value_min), float(a_value_max)])
attribute_list.extend([numpy.nan] * 3) # three momentrate components
attribute_list.extend([
float(seismic_moment_rate_min),
float(seismic_moment_rate_max),
zone_data_string_min.lstrip(),
zone_data_string_max.lstrip()])
result_values.append(attribute_list)
return result_values
def updateDataFaultBackgr(cls, feature,
m_threshold=recurrence.FAULT_BACKGROUND_MAG_THRESHOLD):
"""Update or compute moment rates for selected feature of fault background
zone layer.
Input:
feature QGis polygon feature from fault background zone layer
Output:
parameters dict of computed parameters
"""
provider = cls.fault_background_layer.dataProvider()
provider_fault = cls.fault_source_layer.dataProvider()
provider_area = cls.area_source_layer.dataProvider()
provider_back = cls.background_zone_layer.dataProvider()
parameters = {}
# get Shapely polygon from feature geometry
polylist, vertices = utils.polygonsQGS2Shapely((feature,))
poly = polylist[0]
# get polygon area in square kilometres
parameters['area_background_sqkm'] = \
utils.polygonAreaFromWGS84(poly) * 1.0e-6
# get mmax and mcdist for FBZ from background zone
(mcdist_qv, mmax_qv) = areasource.getAttributesFromBackgroundZones(
poly.centroid, provider_back, areasource.MCDIST_MMAX_ATTRIBUTES)
mmax = float(mmax_qv.toDouble()[0])
mcdist = str(mcdist_qv.toString())
parameters['mmax'] = mmax
## moment rate from EQs
# get quakes from catalog (cut with fault background zone polygon)
poly_cat = QPCatalog.QPCatalog()
poly_cat.merge(cls.catalog)
poly_cat.cut(geometry=poly)
# cut catalog with min/max depth according to UI spinboxes
(mindepth, maxdepth) = eqcatalog.getMinMaxDepth(cls)
poly_cat.cut(mindepth=mindepth, maxdepth=maxdepth)
parameters['eq_count'] = poly_cat.size()
# sum up moment from quakes (converted from Mw with Kanamori eq.)
magnitudes = []
for ev in poly_cat.eventParameters.event:
mag = ev.getPreferredMagnitude()
magnitudes.append(mag.mag.value)
moment = numpy.array(momentrate.magnitude2moment(magnitudes))
# scale moment: per year and area (in km^2)
parameters['mr_eq'] = moment.sum() / (
parameters['area_background_sqkm'] * cls.catalog_time_span[0])
## moment rate from activity (RM)
parameters['activity_mmin'] = atticivy.ATTICIVY_MMIN
activity = atticivy.computeActivityAtticIvy(
(poly, ), (mmax, ), (mcdist, ), cls.catalog,
mmin=parameters['activity_mmin'])
# get RM (a, b) values from feature attribute
activity_str_a = activity[0][3]
activity_arr_a = activity_str_a.strip().split()
activity_str_b = activity[0][4]
activity_arr_b = activity_str_b.strip().split()
# ignore weights
activity_a = [float(x) for x in activity_arr_a]
activity_b = [float(x) for x in activity_arr_b]
parameters['activity_a'] = activity_a
parameters['activity_b'] = activity_b
a_values = activity_a
momentrates_arr = numpy.array(momentrate.momentrateFromActivity(
a_values, activity_b, mmax)) / cls.catalog_time_span[0]
parameters['mr_activity'] = momentrates_arr.tolist()
# get separate catalogs below and above magnitude threshold
cat_below_threshold = QPCatalog.QPCatalog()
cat_below_threshold.merge(poly_cat)
cat_below_threshold.cut(maxmag=m_threshold, maxmag_excl=True)
parameters['eq_count_below'] = cat_below_threshold.size()
cat_above_threshold = QPCatalog.QPCatalog()
cat_above_threshold.merge(poly_cat)
cat_above_threshold.cut(minmag=m_threshold, maxmag_excl=False)
parameters['eq_count_above'] = cat_above_threshold.size()
activity_below_threshold = atticivy.computeActivityAtticIvy(
(poly,), (mmax,), (mcdist,), cat_below_threshold,
mmin=parameters['activity_mmin'])
activity_above_threshold = atticivy.computeActivityAtticIvy(
(poly,), (mmax,), (mcdist,), cat_above_threshold,
mmin=parameters['activity_mmin'])
# get RM (weight, a, b) values from feature attribute
activity_below_str_a = activity_below_threshold[0][3]
activity_below_arr_a = activity_below_str_a.strip().split()
activity_below_str_b = activity_below_threshold[0][4]
activity_below_arr_b = activity_below_str_b.strip().split()
activity_above_str_a = activity_above_threshold[0][3]
activity_above_arr_a = activity_above_str_a.strip().split()
activity_above_str_b = activity_above_threshold[0][4]
activity_above_arr_b = activity_above_str_b.strip().split()
# ignore weights
activity_below_a = [float(x) for x in activity_below_arr_a]
activity_below_b = [float(x) for x in activity_below_arr_b]
activity_above_a = [float(x) for x in activity_above_arr_a]
activity_above_b = [float(x) for x in activity_above_arr_b]
a_values_below = activity_below_a
momentrates_below_arr = numpy.array(momentrate.momentrateFromActivity(
a_values_below, activity_below_b, mmax)) / cls.catalog_time_span[0]
a_values_above = activity_above_a
momentrates_above_arr = numpy.array(momentrate.momentrateFromActivity(
a_values_above, activity_above_b, mmax)) / cls.catalog_time_span[0]
parameters['activity_below_a'] = activity_below_a
parameters['activity_below_b'] = activity_below_b
parameters['activity_above_a'] = activity_above_a
parameters['activity_above_b'] = activity_above_b
parameters['mr_activity_below'] = momentrates_below_arr.tolist()
parameters['mr_activity_above'] = momentrates_above_arr.tolist()
parameters['activity_m_threshold'] = m_threshold
# FMD from quakes in FBZ
cls.feature_data_fault_background['fmd'] = fmd.computeZoneFMD(cls,
feature, poly_cat)
(parameters['ml_a'], parameters['ml_b'], parameters['ml_mc'],
parameters['ml_magctr']) = fmd.getFMDValues(
cls.feature_data_fault_background['fmd'])
## moment rate from slip rate
sliprate_min_name = features.FAULT_SOURCE_ATTR_SLIPRATE_MIN['name']
sliprate_max_name = features.FAULT_SOURCE_ATTR_SLIPRATE_MAX['name']
attribute_map = utils.getAttributeIndex(provider_fault,
(features.FAULT_SOURCE_ATTR_SLIPRATE_MIN,
features.FAULT_SOURCE_ATTR_SLIPRATE_MAX), create=False)
moment_rate_min = 0.0
moment_rate_max = 0.0
parameters['area_fault_sqkm'] = 0.0
parameters['fault_count'] = 0
provider_fault.rewind()
for fault in provider_fault:
fault_poly, vertices = utils.polygonsQGS2Shapely((fault,))
if fault_poly[0].intersects(poly):
parameters['fault_count'] += 1
sliprate_min = \
fault[attribute_map[sliprate_min_name][0]].toDouble()[0]
sliprate_max = \
fault[attribute_map[sliprate_max_name][0]].toDouble()[0]
area_fault = utils.polygonAreaFromWGS84(fault_poly[0])
# TODO(fab): correct scaling of moment rate from slip rate
(rate_min, rate_max) = momentrate.momentrateFromSlipRate(
sliprate_min, sliprate_max, area_fault)
moment_rate_min += rate_min
moment_rate_max += rate_max
parameters['area_fault_sqkm'] += area_fault
moment_rate_min /= cls.catalog_time_span[0]
moment_rate_max /= cls.catalog_time_span[0]
parameters['mr_slip'] = [moment_rate_min, moment_rate_max]
parameters['area_fault_sqkm'] *= 1.0e-6
## moment rate from geodesy (strain)
momentrate_strain_barba = momentrate.momentrateFromStrainRateBarba(
poly, cls.data.strain_rate_barba,
cls.data.deformation_regimes_bird)
parameters['mr_strain_barba'] = momentrate_strain_barba / (
cls.catalog_time_span[0])
momentrate_strain_bird = momentrate.momentrateFromStrainRateBird(poly,
cls.data.strain_rate_bird, cls.data.deformation_regimes_bird)
parameters['mr_strain_bird'] = momentrate_strain_bird / (
cls.catalog_time_span[0])
return parameters
def updateDataFaultBackgr(cls,
feature,
m_threshold=recurrence.FAULT_BACKGROUND_MAG_THRESHOLD
):
"""Update or compute moment rates for selected feature of fault background
zone layer.
Input:
feature QGis polygon feature from fault background zone layer
Output:
parameters dict of computed parameters
"""
provider = cls.fault_background_layer.dataProvider()
provider_fault = cls.fault_source_layer.dataProvider()
provider_area = cls.area_source_layer.dataProvider()
provider_back = cls.background_zone_layer.dataProvider()
parameters = {}
# get Shapely polygon from feature geometry
polylist, vertices = utils.polygonsQGS2Shapely((feature, ))
poly = polylist[0]
# get polygon area in square kilometres
parameters['area_background_sqkm'] = \
utils.polygonAreaFromWGS84(poly) * 1.0e-6
# get mmax and mcdist for FBZ from background zone
(mcdist_qv, mmax_qv) = areasource.getAttributesFromBackgroundZones(
poly.centroid, provider_back, areasource.MCDIST_MMAX_ATTRIBUTES)
mmax = float(mmax_qv.toDouble()[0])
mcdist = str(mcdist_qv.toString())
parameters['mmax'] = mmax
## moment rate from EQs
# get quakes from catalog (cut with fault background zone polygon)
poly_cat = QPCatalog.QPCatalog()
poly_cat.merge(cls.catalog)
poly_cat.cut(geometry=poly)
# cut catalog with min/max depth according to UI spinboxes
(mindepth, maxdepth) = eqcatalog.getMinMaxDepth(cls)
poly_cat.cut(mindepth=mindepth, maxdepth=maxdepth)
parameters['eq_count'] = poly_cat.size()
# sum up moment from quakes (converted from Mw with Kanamori eq.)
magnitudes = []
for ev in poly_cat.eventParameters.event:
mag = ev.getPreferredMagnitude()
magnitudes.append(mag.mag.value)
moment = numpy.array(momentrate.magnitude2moment(magnitudes))
# scale moment: per year and area (in km^2)
parameters['mr_eq'] = moment.sum() / (parameters['area_background_sqkm'] *
cls.catalog_time_span[0])
## moment rate from activity (RM)
parameters['activity_mmin'] = atticivy.ATTICIVY_MMIN
activity = atticivy.computeActivityAtticIvy(
(poly, ), (mmax, ), (mcdist, ),
cls.catalog,
mmin=parameters['activity_mmin'])
# get RM (a, b) values from feature attribute
activity_str_a = activity[0][3]
activity_arr_a = activity_str_a.strip().split()
activity_str_b = activity[0][4]
activity_arr_b = activity_str_b.strip().split()
# ignore weights
activity_a = [float(x) for x in activity_arr_a]
activity_b = [float(x) for x in activity_arr_b]
parameters['activity_a'] = activity_a
parameters['activity_b'] = activity_b
a_values = activity_a
momentrates_arr = numpy.array(
momentrate.momentrateFromActivity(a_values, activity_b,
mmax)) / cls.catalog_time_span[0]
parameters['mr_activity'] = momentrates_arr.tolist()
# get separate catalogs below and above magnitude threshold
cat_below_threshold = QPCatalog.QPCatalog()
cat_below_threshold.merge(poly_cat)
cat_below_threshold.cut(maxmag=m_threshold, maxmag_excl=True)
parameters['eq_count_below'] = cat_below_threshold.size()
cat_above_threshold = QPCatalog.QPCatalog()
cat_above_threshold.merge(poly_cat)
cat_above_threshold.cut(minmag=m_threshold, maxmag_excl=False)
parameters['eq_count_above'] = cat_above_threshold.size()
activity_below_threshold = atticivy.computeActivityAtticIvy(
(poly, ), (mmax, ), (mcdist, ),
cat_below_threshold,
mmin=parameters['activity_mmin'])
activity_above_threshold = atticivy.computeActivityAtticIvy(
(poly, ), (mmax, ), (mcdist, ),
cat_above_threshold,
mmin=parameters['activity_mmin'])
# get RM (weight, a, b) values from feature attribute
activity_below_str_a = activity_below_threshold[0][3]
activity_below_arr_a = activity_below_str_a.strip().split()
activity_below_str_b = activity_below_threshold[0][4]
activity_below_arr_b = activity_below_str_b.strip().split()
activity_above_str_a = activity_above_threshold[0][3]
activity_above_arr_a = activity_above_str_a.strip().split()
activity_above_str_b = activity_above_threshold[0][4]
activity_above_arr_b = activity_above_str_b.strip().split()
# ignore weights
activity_below_a = [float(x) for x in activity_below_arr_a]
activity_below_b = [float(x) for x in activity_below_arr_b]
activity_above_a = [float(x) for x in activity_above_arr_a]
activity_above_b = [float(x) for x in activity_above_arr_b]
a_values_below = activity_below_a
momentrates_below_arr = numpy.array(
momentrate.momentrateFromActivity(a_values_below, activity_below_b,
mmax)) / cls.catalog_time_span[0]
a_values_above = activity_above_a
momentrates_above_arr = numpy.array(
momentrate.momentrateFromActivity(a_values_above, activity_above_b,
mmax)) / cls.catalog_time_span[0]
parameters['activity_below_a'] = activity_below_a
parameters['activity_below_b'] = activity_below_b
parameters['activity_above_a'] = activity_above_a
parameters['activity_above_b'] = activity_above_b
parameters['mr_activity_below'] = momentrates_below_arr.tolist()
parameters['mr_activity_above'] = momentrates_above_arr.tolist()
parameters['activity_m_threshold'] = m_threshold
# FMD from quakes in FBZ
cls.feature_data_fault_background['fmd'] = fmd.computeZoneFMD(
cls, feature, poly_cat)
(parameters['ml_a'], parameters['ml_b'], parameters['ml_mc'],
parameters['ml_magctr']) = fmd.getFMDValues(
cls.feature_data_fault_background['fmd'])
## moment rate from slip rate
sliprate_min_name = features.FAULT_SOURCE_ATTR_SLIPRATE_MIN['name']
sliprate_max_name = features.FAULT_SOURCE_ATTR_SLIPRATE_MAX['name']
attribute_map = utils.getAttributeIndex(
provider_fault, (features.FAULT_SOURCE_ATTR_SLIPRATE_MIN,
features.FAULT_SOURCE_ATTR_SLIPRATE_MAX),
create=False)
moment_rate_min = 0.0
moment_rate_max = 0.0
parameters['area_fault_sqkm'] = 0.0
parameters['fault_count'] = 0
provider_fault.rewind()
for fault in provider_fault:
fault_poly, vertices = utils.polygonsQGS2Shapely((fault, ))
if fault_poly[0].intersects(poly):
parameters['fault_count'] += 1
sliprate_min = \
fault[attribute_map[sliprate_min_name][0]].toDouble()[0]
sliprate_max = \
fault[attribute_map[sliprate_max_name][0]].toDouble()[0]
area_fault = utils.polygonAreaFromWGS84(fault_poly[0])
# TODO(fab): correct scaling of moment rate from slip rate
(rate_min, rate_max) = momentrate.momentrateFromSlipRate(
sliprate_min, sliprate_max, area_fault)
moment_rate_min += rate_min
moment_rate_max += rate_max
parameters['area_fault_sqkm'] += area_fault
moment_rate_min /= cls.catalog_time_span[0]
moment_rate_max /= cls.catalog_time_span[0]
parameters['mr_slip'] = [moment_rate_min, moment_rate_max]
parameters['area_fault_sqkm'] *= 1.0e-6
## moment rate from geodesy (strain)
momentrate_strain_barba = momentrate.momentrateFromStrainRateBarba(
poly, cls.data.strain_rate_barba, cls.data.deformation_regimes_bird)
parameters['mr_strain_barba'] = momentrate_strain_barba / (
cls.catalog_time_span[0])
momentrate_strain_bird = momentrate.momentrateFromStrainRateBird(
poly, cls.data.strain_rate_bird, cls.data.deformation_regimes_bird)
parameters['mr_strain_bird'] = momentrate_strain_bird / (
cls.catalog_time_span[0])
return parameters
def updateDataFault(cls, feature,
m_threshold=recurrence.FAULT_BACKGROUND_MAG_THRESHOLD):
"""Update or compute moment rates for selected feature of fault source
zone layer.
Input:
feature QGis polygon feature from fault source layer
Output:
parameters dict of computed parameters
"""
provider = cls.fault_source_layer.dataProvider()
provider_fault_back = cls.fault_background_layer.dataProvider()
provider_back = cls.background_zone_layer.dataProvider()
parameters = {}
# zone ID and title
(feature_id, feature_name) = utils.getFeatureAttributes(
cls.fault_background_layer, feature,
features.FAULT_BACKGROUND_ATTRIBUTES_ID)
if feature_name.toString() != '':
zone_name_str = feature_name.toString()
else:
zone_name_str = ""
parameters['plot_title_recurrence'] = 'Zone %s, %s' % (
feature_id.toString(), zone_name_str)
# get Shapely polygon from feature geometry
polylist, vertices = utils.polygonsQGS2Shapely((feature,))
fault_poly = polylist[0]
# fault zone polygon area in square kilometres
parameters['area_fault_sqkm'] = utils.polygonAreaFromWGS84(
fault_poly) * 1.0e-6
# get buffer zone around fault zone (convert buffer distance to degrees)
(bz_poly, parameters['area_bz_sqkm']) = utils.computeBufferZone(
fault_poly, momentrate.BUFFER_AROUND_FAULT_ZONE_KM)
# find fault background zone in which centroid of fault zone lies
# NOTE: this can yield a wrong background zone if the fault zone
# is curved and at the edge of background zone.
# TODO(fab): use GIS "within" function instead, but note that fault
# zone can overlap several BG zones
(fbz, fbz_poly, parameters['area_fbz_sqkm']) = utils.findBackgroundZone(
fault_poly.centroid, provider_fault_back)
recurrence_attributes = attributes.getAttributesFromRecurrence(provider,
feature)
if recurrence_attributes is not None:
parameters.update(recurrence_attributes)
else:
return None
# get mmax and mcdist for FBZ from background zone
(mcdist_qv, mmax_qv) = areasource.getAttributesFromBackgroundZones(
fbz_poly.centroid, provider_back, areasource.MCDIST_MMAX_ATTRIBUTES)
mmax = float(mmax_qv.toDouble()[0])
mcdist = str(mcdist_qv.toString())
parameters['mmax'] = mmax
## moment rate from EQs
# get quakes from catalog (cut with fault background polygon)
# cut catalog with min/max depth according to UI spinboxes
(mindepth, maxdepth) = eqcatalog.getMinMaxDepth(cls)
fbz_cat = QPCatalog.QPCatalog()
fbz_cat.merge(cls.catalog)
fbz_cat.cut(geometry=fbz_poly)
fbz_cat.cut(mindepth=mindepth, maxdepth=maxdepth)
bz_cat = QPCatalog.QPCatalog()
bz_cat.merge(cls.catalog)
bz_cat.cut(geometry=bz_poly)
bz_cat.cut(mindepth=mindepth, maxdepth=maxdepth)
parameters['eq_count_fbz'] = fbz_cat.size()
parameters['eq_count_bz'] = bz_cat.size()
# sum up moment from quakes (converted from Mw with Kanamori eq.)
# use quakes in buffer zone
magnitudes = []
for ev in bz_cat.eventParameters.event:
mag = ev.getPreferredMagnitude()
magnitudes.append(mag.mag.value)
moment = numpy.array(momentrate.magnitude2moment(magnitudes))
# scale moment: per year and area (in km^2)
parameters['mr_eq'] = moment.sum() / (
parameters['area_bz_sqkm'] * cls.catalog_time_span[0])
## moment rate from activity (RM)
# moment rates from activity: use a and b values from buffer zone
act_bz_arr_a = parameters['activity_bz_act_a'].strip().split()
act_bz_arr_b = parameters['activity_bz_act_b'].strip().split()
a_bz_arr = [float(x) for x in act_bz_arr_a]
b_bz_arr = [float(x) for x in act_bz_arr_b]
a_values = a_bz_arr
momentrates_arr = numpy.array(momentrate.momentrateFromActivity(
a_values, b_bz_arr, mmax)) / cls.catalog_time_span[0]
parameters['mr_activity'] = momentrates_arr.tolist()
# moment rates from activity: use a and b values from FBZ
# (above threshold)
act_fbz_at_arr_a = parameters['activity_fbz_at_act_a'].strip().split()
act_fbz_at_arr_b = parameters['activity_fbz_at_act_b'].strip().split()
a_fbz_at_arr = [float(x) for x in act_fbz_at_arr_a]
b_fbz_at_arr = [float(x) for x in act_fbz_at_arr_b]
a_values = a_fbz_at_arr
momentrates_fbz_at_arr = numpy.array(momentrate.momentrateFromActivity(
a_values, b_fbz_at_arr, mmax)) / cls.catalog_time_span[0]
parameters['mr_activity_fbz_at'] = momentrates_fbz_at_arr.tolist()
parameters['activity_m_threshold'] = m_threshold
# FMD from quakes in FBZ
cls.feature_data_fault_source['fmd'] = fmd.computeZoneFMD(cls, feature,
fbz_cat)
(parameters['ml_a'], parameters['ml_b'], parameters['ml_mc'],
parameters['ml_magctr']) = fmd.getFMDValues(
cls.feature_data_fault_source['fmd'])
## moment rate from slip rate
# TODO(fab): check correct scaling of moment rate from slip rate
(moment_rate_min, moment_rate_max) = \
momentrate.momentrateFromSlipRate(parameters['sliprate_min'],
parameters['sliprate_max'],
parameters['area_fault_sqkm'] * 1.0e6)
parameters['mr_slip'] = [moment_rate_min, moment_rate_max]
return parameters
