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FetchOpenSHA.py
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FetchOpenSHA.py
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# -*- coding: utf-8 -*-
#
# Copyright (c) 2018 Leland Stanford Junior University
# Copyright (c) 2018 The Regents of the University of California
#
# This file is part of the SimCenter Backend Applications
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its contributors
# may be used to endorse or promote products derived from this software without
# specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
# You should have received a copy of the BSD 3-Clause License along with
# this file. If not, see <http://www.opensource.org/licenses/>.
#
# Contributors:
# Kuanshi Zhong
#
import json
import numpy as np
import pandas as pd
from tqdm import tqdm
from java.io import *
from java.lang import *
from java.lang.reflect import *
from java.util import *
from org.opensha.commons.data import *
from org.opensha.commons.data.siteData import *
from org.opensha.commons.data.function import *
from org.opensha.commons.exceptions import ParameterException
from org.opensha.commons.geo import *
from org.opensha.commons.param import *
from org.opensha.commons.param.event import *
from org.opensha.commons.param.constraint import *
from org.opensha.commons.util import ServerPrefUtils
from org.opensha.sha.earthquake import *
from org.opensha.sha.earthquake.param import *
from org.opensha.sha.earthquake.rupForecastImpl.Frankel02 import Frankel02_AdjustableEqkRupForecast
from org.opensha.sha.earthquake.rupForecastImpl.WGCEP_UCERF1 import WGCEP_UCERF1_EqkRupForecast
from org.opensha.sha.earthquake.rupForecastImpl.WGCEP_UCERF_2_Final import UCERF2
from org.opensha.sha.earthquake.rupForecastImpl.WGCEP_UCERF_2_Final.MeanUCERF2 import MeanUCERF2
from org.opensha.sha.faultSurface import *
from org.opensha.sha.imr import *
from org.opensha.sha.imr.attenRelImpl import *
from org.opensha.sha.imr.attenRelImpl.ngaw2 import *
from org.opensha.sha.imr.attenRelImpl.ngaw2.NGAW2_Wrappers import *
from org.opensha.sha.imr.param.IntensityMeasureParams import *
from org.opensha.sha.imr.param.OtherParams import *
from org.opensha.sha.imr.param.SiteParams import Vs30_Param
from org.opensha.sha.calc import *
from org.opensha.sha.util import *
try:
from scratch.UCERF3.erf.mean import MeanUCERF3
except ModuleNotFoundError:
MeanUCERF3 = jpype.JClass("scratch.UCERF3.erf.mean.MeanUCERF3")
from org.opensha.sha.gcim.imr.attenRelImpl import *
from org.opensha.sha.gcim.imr.param.IntensityMeasureParams import *
from org.opensha.sha.gcim.imr.param.EqkRuptureParams import *
from org.opensha.sha.gcim.calc import *
def getERF(erf_name, update_flag):
# Initialization
erf = None
# ERF model options
if erf_name == 'WGCEP (2007) UCERF2 - Single Branch':
erf = MeanUCERF2()
elif erf_name == 'USGS/CGS 2002 Adj. Cal. ERF':
erf = Frankel02_AdjustableEqkRupForecast()
elif erf_name == 'WGCEP UCERF 1.0 (2005)':
erf = WGCEP_UCERF1_EqkRupForecast()
elif erf_name == 'Mean UCERF3':
tmp = MeanUCERF3()
tmp.setPreset(MeanUCERF3.Presets.BOTH_FM_BRANCH_AVG)
erf = tmp
del tmp
elif erf_name == 'Mean UCERF3 FM3.1':
tmp = MeanUCERF3()
tmp.setPreset(MeanUCERF3.Presets.FM3_1_BRANCH_AVG)
erf = tmp
del tmp
elif erf_name == 'Mean UCERF3 FM3.2':
tmp = MeanUCERF3()
tmp.setPreset(MeanUCERF3.Presets.FM3_2_BRANCH_AVG)
erf = tmp
del tmp
elif erf_name == 'WGCEP Eqk Rate Model 2 ERF':
erf = UCERF2()
else:
print('Please check the ERF model name.')
if erf_name and update_flag:
erf.updateForecast()
# return
return erf
def export_to_json(erf, site_loc, outfile = None, EqName = None, minMag = 0.0, maxMag = 10.0, maxDistance = 1000.0, maxSources = 500):
# Initializing
erf_data = {"type": "FeatureCollection"}
site_loc = Location(site_loc[0], site_loc[1])
# Total source number
num_sources = erf.getNumSources()
source_tag = []
source_dist = []
for i in range(num_sources):
rupSource = erf.getSource(i)
sourceSurface = rupSource.getSourceSurface()
distanceToSource = sourceSurface.getDistanceRup(site_loc)
source_tag.append(i)
source_dist.append(distanceToSource)
df = pd.DataFrame.from_dict({
'sourceID': source_tag,
'sourceDist': source_dist
})
# Sorting sources
source_collection = df.sort_values(['sourceDist'], ascending = (True))
# Collecting source features
maxSources = min(maxSources, num_sources)
feature_collection = []
for i in tqdm(range(maxSources), desc='Sources'):
source_index = source_collection.iloc[i, 0]
distanceToSource = source_collection.iloc[i, 1]
# Checking maximum distance
if (distanceToSource > maxDistance):
break
# Getting rupture distances
rupSource = erf.getSource(source_index)
try:
rupList = rupSource.getRuptureList()
except:
continue
rup_tag = []
rup_dist = []
for j in range(rupList.size()):
rupture = rupList.get(j)
cur_dist = rupture.getRuptureSurface().getDistanceRup(site_loc)
rup_tag.append(j)
rup_dist.append(cur_dist)
df = pd.DataFrame.from_dict({
'rupID': rup_tag,
'rupDist': rup_dist
})
# Sorting
rup_collection = df.sort_values(['rupDist'], ascending = (True))
# Preparing the dict of ruptures
for j in range(rupList.size()):
cur_dict = dict()
cur_dict.update({'type': 'Feature'})
rup_index = rup_collection.iloc[j, 0]
cur_dist = rup_collection.iloc[j, 1]
rupture = rupList.get(rup_index)
maf = rupture.getMeanAnnualRate(erf.getTimeSpan().getDuration())
if maf <= 0.:
continue
ruptureSurface = rupture.getRuptureSurface()
# Properties
cur_dict['properties'] = dict()
name = str(rupSource.getName())
if (EqName is not None):
if (EqName not in name):
continue
cur_dict['properties'].update({'Name': name})
Mag = float(rupture.getMag())
if (Mag < minMag) or (Mag > maxMag):
continue
cur_dict['properties'].update({'Magnitude': Mag})
cur_dict['properties'].update({'Rupture': int(rup_index)})
cur_dict['properties'].update({'Source': int(source_index)})
if outfile is not None:
# these calls are time-consuming, so only run them if one needs
# detailed outputs of the sources
cur_dict['properties'].update({'Distance': float(cur_dist)})
distanceRup = rupture.getRuptureSurface().getDistanceRup(site_loc)
cur_dict['properties'].update({'DistanceRup': float(distanceRup)})
distanceSeis = rupture.getRuptureSurface().getDistanceSeis(site_loc)
cur_dict['properties'].update({'DistanceSeis': float(distanceSeis)})
distanceJB = rupture.getRuptureSurface().getDistanceJB(site_loc)
cur_dict['properties'].update({'DistanceJB': float(distanceJB)})
distanceX = rupture.getRuptureSurface().getDistanceX(site_loc)
cur_dict['properties'].update({'DistanceX': float(distanceX)})
Prob = rupture.getProbability()
cur_dict['properties'].update({'Probability': float(Prob)})
maf = rupture.getMeanAnnualRate(erf.getTimeSpan().getDuration())
cur_dict['properties'].update({'MeanAnnualRate': abs(float(maf))})
# Geometry
cur_dict['geometry'] = dict()
if (ruptureSurface.isPointSurface()):
# Point source
pointSurface = ruptureSurface
location = pointSurface.getLocation()
cur_dict['geometry'].update({'type': 'Point'})
cur_dict['geometry'].update({'coordinates': [float(location.getLongitude()), float(location.getLatitude())]})
else:
# Line source
try:
trace = ruptureSurface.getUpperEdge()
except:
trace = ruptureSurface.getEvenlyDiscritizedUpperEdge()
coordinates = []
for k in trace:
coordinates.append([float(k.getLongitude()), float(k.getLatitude())])
cur_dict['geometry'].update({'type': 'LineString'})
cur_dict['geometry'].update({'coordinates': coordinates})
# Appending
feature_collection.append(cur_dict)
# end for j
# end for i
erf_data.update({'features': feature_collection})
# Output
if outfile is not None:
with open(outfile, 'w') as f:
json.dump(erf_data, f, indent=2)
# return
return erf_data
def CreateIMRInstance(gmpe_name):
# GMPE name map
gmpe_map = {str(ASK_2014.NAME): ASK_2014_Wrapper.class_.getName(),
str(BSSA_2014.NAME): BSSA_2014_Wrapper.class_.getName(),
str(CB_2014.NAME): CB_2014_Wrapper.class_.getName(),
str(CY_2014.NAME): CY_2014_Wrapper.class_.getName(),
str(KS_2006_AttenRel.NAME): KS_2006_AttenRel.class_.getName(),
str(BommerEtAl_2009_AttenRel.NAME): BommerEtAl_2009_AttenRel.class_.getName(),
str(AfshariStewart_2016_AttenRel.NAME): AfshariStewart_2016_AttenRel.class_.getName()}
# Mapping GMPE name
imrClassName = gmpe_map.get(gmpe_name, None)
if imrClassName is None:
return imrClassName
# Getting the java class
imrClass = Class.forName(imrClassName)
ctor = imrClass.getConstructor()
imr = ctor.newInstance()
# Setting default parameters
imr.setParamDefaults()
# return
return imr
def get_DataSource(paramName, siteData):
typeMap = SiteTranslator.DATA_TYPE_PARAM_NAME_MAP
for dataType in typeMap.getTypesForParameterName(paramName):
if dataType == SiteData.TYPE_VS30:
for dataValue in siteData:
if dataValue.getDataType() != dataType:
continue
vs30 = Double(dataValue.getValue())
if (not vs30.isNaN()) and (vs30 > 0.0):
return dataValue.getSourceName()
elif (dataType == SiteData.TYPE_DEPTH_TO_1_0) or (dataType == SiteData.TYPE_DEPTH_TO_2_5):
for dataValue in siteData:
if dataValue.getDataType() != dataType:
continue
depth = Double(dataValue.getValue())
if (not depth.isNaN()) and (depth > 0.0):
return dataValue.getSourceName()
return 1
def get_site_prop(gmpe_name, siteSpec):
# GMPE
try:
imr = CreateIMRInstance(gmpe_name)
except:
print('Please check GMPE name.')
return 1
# Site data
sites = ArrayList()
for cur_site in siteSpec:
cur_loc = Location(cur_site['Location']['Latitude'], cur_site['Location']['Longitude'])
sites.add(Site(cur_loc))
siteDataProviders = OrderedSiteDataProviderList.createSiteDataProviderDefaults()
try:
availableSiteData = siteDataProviders.getAllAvailableData(sites)
except:
print('Error in getAllAvailableData')
return 1
siteTrans = SiteTranslator()
# Looping over all sites
site_prop = []
for i in range(len(siteSpec)):
site_tmp = dict()
# Current site
site = sites.get(i)
# Location
cur_site = siteSpec[i]
locResults = {'Latitude': cur_site['Location']['Latitude'],
'Longitude': cur_site['Location']['Longitude']}
cur_loc = Location(cur_site['Location']['Latitude'], cur_site['Location']['Longitude'])
siteDataValues = ArrayList()
for j in range(len(availableSiteData)):
siteDataValues.add(availableSiteData.get(j).getValue(i))
imrSiteParams = imr.getSiteParams()
siteDataResults = []
# Setting site parameters
for j in range(imrSiteParams.size()):
siteParam = imrSiteParams.getByIndex(j)
newParam = Parameter.clone(siteParam)
siteDataFound = siteTrans.setParameterValue(newParam, siteDataValues)
if (str(newParam.getName())=='Vs30' and bool(cur_site.get('Vs30', None))):
newParam.setValue(Double(cur_site['Vs30']))
siteDataResults.append({'Type': 'Vs30',
'Value': float(newParam.getValue()),
'Source': 'User Defined'})
elif (str(newParam.getName())=='Vs30 Type' and bool(cur_site.get('Vs30', None))):
newParam.setValue("Measured")
siteDataResults.append({'Type': 'Vs30 Type',
'Value': 'Measured',
'Source': 'User Defined'})
elif siteDataFound:
provider = "Unknown"
provider = get_DataSource(newParam.getName(), siteDataValues)
if 'String' in str(type(newParam.getValue())):
tmp_value = str(newParam.getValue())
elif 'Double' in str(type(newParam.getValue())):
tmp_value = float(newParam.getValue())
if str(newParam.getName())=='Vs30':
cur_site.update({'Vs30': tmp_value})
else:
tmp_value = str(newParam.getValue())
siteDataResults.append({'Type': str(newParam.getName()),
'Value': tmp_value,
'Source': str(provider)})
else:
newParam.setValue(siteParam.getDefaultValue())
siteDataResults.append({'Type': str(siteParam.getName()),
'Value': float(siteParam.getDefaultValue()),
'Source': 'Default'})
site.addParameter(newParam)
# End for j
# Updating site specifications
siteSpec[i] = cur_site
site_tmp.update({'Location': locResults,
'SiteData': siteDataResults})
site_prop.append(site_tmp)
# Return
return siteSpec, sites, site_prop
def get_IM(gmpe_info, erf, sites, siteSpec, site_prop, source_info, station_info, im_info):
# GMPE name
gmpe_name = gmpe_info['Type']
# Creating intensity measure relationship instance
try:
imr = CreateIMRInstance(gmpe_name)
except:
print('Please check GMPE name.')
return 1, station_info
# Getting supported intensity measure types
ims = imr.getSupportedIntensityMeasures()
saParam = ims.getParameter(SA_Param.NAME)
supportedPeriods = saParam.getPeriodParam().getPeriods()
Arrays.sort(supportedPeriods)
# Rupture
eqRup = EqkRupture()
if source_info['Type'] == 'PointSource':
eqRup.setMag(source_info['Magnitude'])
eqRupLocation = Location(source_info['Location']['Latitude'],
source_info['Location']['Longitude'],
source_info['Location']['Depth'])
eqRup.setPointSurface(eqRupLocation, source_info['AverageDip'])
eqRup.setAveRake(source_info['AverageRake'])
magnitude = source_info['Magnitude']
meanAnnualRate = None
elif source_info['Type'] == 'ERF':
timeSpan = TimeSpan(TimeSpan.NONE, TimeSpan.YEARS)
erfParams = source_info.get('Parameters', None)
# Additional parameters (if any)
if erfParams is not None:
for k in erfParams.keys:
erf.setParameter(k, erfParams[k])
# Time span
timeSpan = erf.getTimeSpan()
# Source
eqSource = erf.getSource(source_info['SourceIndex'])
eqSource.getName()
# Rupture
eqRup = eqSource.getRupture(source_info['RuptureIndex'])
# Properties
magnitude = eqRup.getMag()
averageDip = eqRup.getRuptureSurface().getAveDip()
averageRake = eqRup.getAveRake()
# Probability
probEqRup = eqRup
probability = probEqRup.getProbability()
# MAF
meanAnnualRate = probEqRup.getMeanAnnualRate(timeSpan.getDuration())
# Rupture surface
surface = eqRup.getRuptureSurface()
# Setting up imr
imr.setEqkRupture(eqRup)
imrParams = gmpe_info['Parameters']
if bool(imrParams):
for k in imrParams.keys():
imr.getParameter(k).setValue(imrParams[k])
# Station
if station_info['Type'] == 'SiteList':
siteSpec = station_info['SiteList']
# Intensity measure
periods = im_info.get('Periods', None)
if periods is not None:
periods = supportedPeriods
tag_SA = False
tag_PGA = False
tag_PGV = False
tag_Ds575 = False
tag_Ds595 = False
if 'SA' in im_info['Type']:
tag_SA = True
if 'PGA' in im_info['Type']:
tag_PGA = True
if 'PGV' in im_info['Type']:
tag_PGV = True
if 'Ds575' in im_info['Type']:
tag_Ds575 = True
if 'Ds595' in im_info['Type']:
tag_Ds595 = True
# Looping over sites
gm_collector = []
for i in range(len(siteSpec)):
gmResults = site_prop[i]
# Current site
site = sites.get(i)
# Location
cur_site = siteSpec[i]
# Set up the site in the imr
imr.setSite(site)
try:
stdDevParam = imr.getParameter(StdDevTypeParam.NAME)
hasIEStats = stdDevParam.isAllowed(StdDevTypeParam.STD_DEV_TYPE_INTER) and \
stdDevParam.isAllowed(StdDevTypeParam.STD_DEV_TYPE_INTRA)
except:
stdDevParaam = None
hasIEStats = False
cur_T = im_info.get('Periods', None)
if tag_SA:
saResult = {'Mean': [],
'TotalStdDev': []}
if hasIEStats:
saResult.update({'InterEvStdDev': []})
saResult.update({'IntraEvStdDev': []})
imr.setIntensityMeasure("SA")
imtParam = imr.getIntensityMeasure()
for Tj in cur_T:
imtParam.getIndependentParameter(PeriodParam.NAME).setValue(float(Tj))
mean = imr.getMean()
saResult['Mean'].append(float(mean))
if stdDevParam is not None:
stdDevParam.setValue(StdDevTypeParam.STD_DEV_TYPE_TOTAL)
stdDev = imr.getStdDev()
saResult['TotalStdDev'].append(float(stdDev))
if hasIEStats:
stdDevParam.setValue(StdDevTypeParam.STD_DEV_TYPE_INTER)
interEvStdDev = imr.getStdDev()
stdDevParam.setValue(StdDevTypeParam.STD_DEV_TYPE_INTRA)
intraEvStdDev = imr.getStdDev()
saResult['InterEvStdDev'].append(float(interEvStdDev))
saResult['IntraEvStdDev'].append(float(intraEvStdDev))
gmResults.update({'lnSA': saResult})
if tag_PGA:
# for PGA current T = 0
cur_T = [0.00]
pgaResult = {'Mean': [],
'TotalStdDev': []}
if hasIEStats:
pgaResult.update({'InterEvStdDev': []})
pgaResult.update({'IntraEvStdDev': []})
imr.setIntensityMeasure("PGA")
mean = imr.getMean()
pgaResult['Mean'].append(float(mean))
stdDev = imr.getStdDev()
pgaResult['TotalStdDev'].append(float(stdDev))
if hasIEStats:
stdDevParam.setValue(StdDevTypeParam.STD_DEV_TYPE_INTER)
interEvStdDev = imr.getStdDev()
stdDevParam.setValue(StdDevTypeParam.STD_DEV_TYPE_INTRA)
intraEvStdDev = imr.getStdDev()
pgaResult['InterEvStdDev'].append(float(interEvStdDev))
pgaResult['IntraEvStdDev'].append(float(intraEvStdDev))
gmResults.update({'lnPGA': pgaResult})
if tag_PGV:
# for PGV current T = 0
cur_T = [0.00]
pgvResult = {'Mean': [],
'TotalStdDev': []}
if hasIEStats:
pgaResult.update({'InterEvStdDev': []})
pgaResult.update({'IntraEvStdDev': []})
imr.setIntensityMeasure("PGV")
mean = imr.getMean()
pgvResult['Mean'].append(float(mean))
stdDev = imr.getStdDev()
pgvResult['TotalStdDev'].append(float(stdDev))
if hasIEStats:
stdDevParam.setValue(StdDevTypeParam.STD_DEV_TYPE_INTER)
interEvStdDev = imr.getStdDev()
stdDevParam.setValue(StdDevTypeParam.STD_DEV_TYPE_INTRA)
intraEvStdDev = imr.getStdDev()
pgvResult['InterEvStdDev'].append(float(interEvStdDev))
pgvResult['IntraEvStdDev'].append(float(intraEvStdDev))
gmResults.update({'lnPGV': pgvResult})
gm_collector.append(gmResults)
# Updating station information
if station_info['Type'] == 'SiteList':
station_info.update({'SiteList': siteSpec})
# Final results
res = {'Magnitude': magnitude,
'MeanAnnualRate': meanAnnualRate,
'Periods': cur_T,
'GroundMotions': gm_collector}
# return
return res, station_info