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modesum.py
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import numpy as np
import asdf
import vmodel
import cpsfile
import subprocess, os
import copy
import matplotlib.pyplot as plt
import shutil
class modesumASDF(asdf.AsdfFile):
"""
ASDF database for mode summation computation
Note that the ASDF here is Advanced Scientific Data Format, NOT Adaptable Seismic Data Format !
"""
def __str__(self):
outstr = '==================== ASDF Database for Mode Summation Computation ====================\n'
try:
inparam = self.tree['inparam']
tempstr = ''
tempstr +='---------------------------------- Input Parameters ----------------------------------\n'
tempstr +='working directory: ' + inparam['workingdir'] + ' \n'
tempstr +='number of modes = ' + str(inparam['nmodes']) + ' \n'
tempstr +='Love wave : ' + str(inparam['love']) + ' Rayleigh wave : ' + str(inparam['rayleigh']) + ' \n'
if len(inparam['period']) !=0:
tempstr +='period = ' + str(inparam['period']) + ' \n'
if len(inparam['freq']) !=0:
tempstr +='frequency = ' + str(inparam['freq']) + ' \n'
tempstr +='hr = ' + str(inparam['hr']) + ' hr = ' + str(inparam['hs']) + ' \n'
# tempstr +='--------------------------------------------------------------------------------------\n'
outstr += tempstr
except:
outstr +='----------------------------- No input parameters in database -------------------------\n'
try:
disp = self.tree['disp']
tempstr = ''
tempstr +='----------------------------------- Dispersion Data ----------------------------------\n'
tempstr +='Love wave modes: '+ str(disp['love'].keys()) + ' \n'
if inparam['love'] and len(disp['love'].keys()) != inparam['nmodes']:
tempstr +='In compatible with input parameters\n'
tempstr +='Love wave period : '+ str(np.sort(disp['love'][0]['T'])) + ' \n'
if not np.allclose(np.sort(inparam['period']), np.sort(disp['love'][0]['T']) ) :
tempstr +='In compatible with input parameters\n'
tempstr +='Rayleigh wave modes : '+ str(disp['ray'].keys()) + ' \n'
if inparam['rayleigh'] and len(disp['ray'].keys()) != inparam['nmodes']:
tempstr +='In compatible with input parameters\n'
tempstr +='Rayleigh wave period : '+ str(np.sort(disp['ray'][0]['T'])) + ' \n'
if not np.allclose(np.sort(inparam['period']), np.sort(disp['ray'][0]['T']) ) :
tempstr +='In compatible with input parameters\n'
outstr += tempstr
except:
outstr +='----------------------------- No dispersion data in database --------------------------\n'
try:
der = self.tree['der']
tempstr = ''
tempstr +='--------------------------------- Eigenfunction Data ---------------------------------\n'
model = der['model']
if model['isotropic']: tempstr +='Isotropic model \n'
else: tempstr +='TI model \n'
tempstr +='Love wave modes : '+ str(der['egn']['love'].keys()) + ' \n'
if inparam['love'] and len(der['egn']['love'].keys()) != inparam['nmodes']:
tempstr +='In compatible with input parameters\n'
tempstr +='Love wave period : '+ str(np.sort(der['egn']['love'][0].keys())) + ' \n'
if not np.allclose(np.sort(inparam['period']), np.sort(der['egn']['love'][0].keys()) ) :
tempstr +='In compatible with input parameters\n'
tempstr +='Rayleigh wave modes : '+ str(der['egn']['ray'].keys()) + ' \n'
if inparam['rayleigh'] and len(der['egn']['ray'].keys()) != inparam['nmodes']:
tempstr +='In compatible with input parameters\n'
tempstr +='Rayleigh wave period : '+ str(np.sort(der['egn']['love'][0].keys())) + ' \n'
if not np.allclose(np.sort(inparam['period']), np.sort(der['egn']['ray'][0].keys()) ) :
tempstr +='In compatible with input parameters\n'
outstr += tempstr
except:
outstr +='----------------------------- No dispersion data in database --------------------------\n'
outstr +='======================================================================================\n'
return outstr
def __repr__(self): return self.__str__()
def getmodel(self, inmodel=None, modelindex=1, h=2., zmax=400.):
"""
Get velocity model
=====================================================================
Input parameters:
inmodel - input model
modelindex - model index (1 - ISOTROPIC, 2 - TRANSVERSE ISOTROPIC)
h - layer thickness for re-layerize
zmax - maximum depth for trim
=====================================================================
"""
if isinstance(inmodel, vmodel.Model1d):
self.model1d = inmodel
else:
self.model1d = vmodel.Model1d(modelindex=modelindex)
self.model1d.ak135()
self.model1d.trim(zmax=zmax)
self.model1d=self.model1d.relayerize(h=h)
return
def getdfile(self, distfile=None, dist0=500, dD=100, Nd=20):
"""
Get distance file
"""
if distfile==None:
self.distfile = cpsfile.DistFile()
self.distfile.addEqualDist(dist0=dist0, dD=dD, Nd=Nd)
else:
if isinstance(distfile, cpsfile.DistFile):
self.distfile = distfile
elif os.path.isfile(distfile):
self.distfile = cpsfile.DistFile(distfname=distfile)
return
def load(self, infname):
"""
Load ASDF file
"""
self.tree.update((asdf.AsdfFile.open(infname)).tree)
def run_disp(self, workingdir, outfname=None, nmodes=1, hr=0., hs=0., love=True, rayleigh=True, dt=1., N2=14,
freq=[], period=[], freqper='PER', run=True, xmin=1, xmax=100):
"""
Compute dispersion curves
=====================================================================
Input parameters:
workingdir - working directory
outfname - output file name
nmodes - number of modes (default - 1)
hr, hs - depth of receiver/source
love - compute Love wave dispersion or not
rayleigh - compute Rayleigh wave dispersion or not
dt - time interval
N2 - NPTS = 2**N2
freq, period- frequency/period list
freqper - output x axis
run - run the code or not
xmin, xmax - output xmin/xmax
=====================================================================
"""
###
# prepare for sprep96/tprep96
###
if len(freq) != 0 and len(period) != 0:
raise ValueError('Specify only one of the freq or period array!')
if len(freq) != 0: outdata = np.asarray(freq)
else: outdata = np.asarray(period)
input_parameters = {'inparam':{'workingdir': workingdir, 'nmodes': nmodes, 'hr': hr, 'hs': hs, 'love': love,
'rayleigh': rayleigh, 'dt': dt, 'N2': N2, 'freq': freq, 'period': period, 'freqper': freqper, 'xmin': xmin, 'xmax': xmax,
'redo': False}}
try: self.model1d
except:
print 'WARNING: No input model! Use ak135 as default!'
self.getmodel()
if not os.path.isdir(workingdir): os.makedirs(workingdir)
if self.model1d.modeltype == 'ISOTROPIC': command = ['sprep96', '-M', 'out.mod']
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC': command = ['tprep96', '-M', 'out.mod']
self.model1d.write(outfname=workingdir+'/out.mod')
try:
self.distfile.write(distfname=workingdir+'/dfile')
command.append('-d'); command.append('dfile')
except:
command.append('-DT'); command.append('%g' %dt)
npts = 2**N2
command.append('-NPTS'); command.append('%g' %npts)
command.append('-NMOD'); command.append('%g' %nmodes)
command.append('-HS'); command.append('%g' %hs)
command.append('-HR'); command.append('%g' %hr)
if love: command.append('-L')
if rayleigh: command.append('-R')
if len(freq) == 1: command.append('-FREQ'); command.append('%g' %freq[0])
elif len(freq) > 1:
command.append('-FARR'); command.append('freq_lst')
np.savetxt(workingdir+'/freq_lst', freq, fmt='%g')
if len(period) == 1: command.append('-PER'); command.append('%g' %period[0])
elif len(period) > 1:
command.append('-PARR'); command.append('per_lst')
np.savetxt(workingdir+'/per_lst', period, fmt='%g')
command_prep = copy.deepcopy(command)
###
# prepare for sdisp96/tdisp96
###
if self.model1d.modeltype == 'ISOTROPIC': command_disp = ['sdisp96']
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC': command_disp = ['tdisp96']
command.append('\n'+command_disp[0])
###
# prepare for sdpsrf96/tdpsrf96
###
if self.model1d.modeltype == 'ISOTROPIC': command_dpsrf=['sdpsrf96', '-U', '-C', '-G']
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC': command_dpsrf=['tdpsrf96', '-U', '-C', '-G']
command_dpsrf.append('-'+freqper)
command_dpsrf.append('-XMIN'); command_dpsrf.append('%g' %xmin)
command_dpsrf.append('-XMAX'); command_dpsrf.append('%g' %xmax)
command_dpsrf.append('-TXT')
###
# saving input parameters
###
self.tree.update(input_parameters)
disptree = {'ray':{}, 'love': {}}
if run:
cdir = os.getcwd()
os.chdir(workingdir)
subprocess.call(command_prep)
subprocess.call(command_disp)
if love:
command_dpsrf_love = copy.deepcopy(command_dpsrf)
command_dpsrf_love.append('-L')
subprocess.call(command_dpsrf_love)
if self.model1d.modeltype == 'ISOTROPIC':
dispfile = cpsfile.DispFile(workingdir+'/SDISPL.TXT')
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC':
dispfile = cpsfile.DispFile(workingdir+'/TDISPL.TXT')
disptree.update(dispfile.get_tree(intree=disptree))
if rayleigh:
command_dpsrf_ray = copy.deepcopy(command_dpsrf)
command_dpsrf_ray.append('-R')
subprocess.call(command_dpsrf_ray)
if self.model1d.modeltype == 'ISOTROPIC':
dispfile = cpsfile.DispFile(workingdir+'/SDISPR.TXT')
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC':
dispfile = cpsfile.DispFile(workingdir+'/TDISPR.TXT')
disptree.update(dispfile.get_tree(intree=disptree))
###
# Save dispersion curves
###
self.tree.update({'disp': disptree})
if outfname!=None: self.write_to(outfname)
os.chdir(cdir)
return True
else:
if love:
command_dpsrf_love = copy.deepcopy(command_dpsrf)
command_dpsrf_love.append('-L')
command.append('\n'+command_dpsrf_love[0])
command += command_dpsrf_love[1:]
if rayleigh:
command_dpsrf_ray = copy.deepcopy(command_dpsrf)
command_dpsrf_ray.append('-R')
command.append('\n'+command_dpsrf_ray[0])
command += command_dpsrf_ray[1:]
outstr = ' '.join(command)
print outstr
return outstr
return
def run_eigen(self, workingdir=None, infname=None, outfname=None, love=True, rayleigh=True, runtype='ALL', noq=True, hr=None, hs=None, freqper='PER',
xmin=1, xmax=100, verbose=True, redo=False, run=True):
"""
Compute eigenfunctions
================================================================================
Input parameters:
workingdir - working directory
infname - input file name
outfname - output file name
love - compute Love wave dispersion or not
rayleigh - compute Rayleigh wave dispersion or not
runtype - type of run (ALL, SYN, DER, DE, DR, DH, DA, DB)
noq - computation with attenuation or not
hr, hs - depth of receiver/source
freqper - output x axis
xmin, xmax - output xmin/xmax
redo - redo the run with scomb96/tcomb96 or not (not implemented yet)
run - run the code or not
================================================================================
"""
if runtype != 'ALL' and runtype != 'SYN' and runtype != 'DER' and runtype != 'DE' and runtype != 'DR' and runtype != 'DH'\
and runtype != 'DA' and runtype != 'DB':
raise ValueError('Unrecognized runtype (should be ALL, SYN, DER, DE, DR, DH, DA, DB)!')
if infname != None: self.load(infname=infname)
try:
inparam = copy.deepcopy(self.tree['inparam'])
if workingdir == None: workingdir = inparam['workingdir']
if hr==None: hr = inparam['hr']
if hs==None: hs = inparam['hs']
if not redo: redo = inparam['redo']
except:
inparam = {}
print 'WARNING: No input parameters for run_disp'
if workingdir == None: raise ValueError('Working directory is not specified!')
if hr==None: hr = 0.
if hs==None: hs = 0.
###
# Update input parameters
###
inparam.update({'workingdir': workingdir, 'hr': hr, 'hs': hs, 'love': love, 'rayleigh': rayleigh, 'freqper': freqper, 'xmin': xmin, 'xmax': xmax,
'redo': False})
command_love = []
command_ray = []
command_dpegn = []
command_dpegn_love = []
command_dpegn_ray = []
command_dpder = []
command_dpder_love = []
command_dpder_ray = []
command = []
###############
# Love command
###############
if love:
if self.model1d.modeltype == 'ISOTROPIC':
command_love = ['slegn96']
if redo:
if not os.path.isfile(workingdir+'/tsdisp96.lov'): raise ValueError('No tsdisp96.lov file!')
command_love.append('-T')
else:
if not os.path.isfile(workingdir+'/sdisp96.lov'): raise ValueError('No sdisp96.lov file!')
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC':
command_love = ['tlegn96']
if redo:
if not os.path.isfile(workingdir+'/ttdisp96.lov'): raise ValueError('No ttdisp96.lov file!')
command_love.append('-T')
else:
if not os.path.isfile(workingdir+'/tdisp96.lov'): raise ValueError('No tdisp96.lov file!')
command_love.append('-HS'); command_love.append('%g' %hs)
command_love.append('-HR'); command_love.append('%g' %hr)
if noq: command_love.append('-NOQ')
command += command_love
###############
# Rayleigh command
###############
if rayleigh:
if self.model1d.modeltype == 'ISOTROPIC':
command_ray = ['sregn96']
if redo:
if not os.path.isfile(workingdir+'/tsdisp96.ray'): raise ValueError('No tsdisp96.ray file!')
command_ray.append('-T')
else:
if not os.path.isfile(workingdir+'/sdisp96.ray'): raise ValueError('No sdisp96.ray file!')
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC':
command_ray = ['tregn96']
if redo:
if not os.path.isfile(workingdir+'/ttdisp96.ray'): raise ValueError('No ttdisp96.ray file!')
command_ray.append('-T')
else:
if not os.path.isfile(workingdir+'/tdisp96.ray'): raise ValueError('No tdisp96.ray file!')
command_ray.append('-HS'); command_ray.append('%g' %hs)
command_ray.append('-HR'); command_ray.append('%g' %hr)
if noq: command_ray.append('-NOQ')
if love and rayleigh:
command.append('\n'+command_ray[0])
command += command_ray[1:]
else: command += command_ray
###############
# convert dispersion data to TXT
###############
if runtype != 'SYN':
if self.model1d.modeltype == 'ISOTROPIC': command_dpegn = ['sdpegn96', '-TXT', '-C', '-U', '-G']
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC': command_dpegn = ['tdpegn96', '-TXT', '-C', '-U', '-G']
command_dpegn.append('-'+freqper)
command_dpegn.append('-XMIN'); command_dpegn.append('%g' %xmin)
command_dpegn.append('-XMAX'); command_dpegn.append('%g' %xmax)
if love:
command_dpegn_love = copy.deepcopy(command_dpegn)
command_dpegn_love.append('-L')
if rayleigh:
command_dpegn_ray = copy.deepcopy(command_dpegn)
command_dpegn_ray.append('-R')
###############
# convert eigenfunction data to TXT
###############
if runtype != 'SYN':
try:
if len(self.tree['inparam']['period'])==0:
raise ValueError ('period array needs to be specified for eigenfunction extraction!')
except:
raise ValueError ('period array needs to be specified for eigenfunction extraction!')
if self.model1d.modeltype == 'ISOTROPIC': command_dpder = ['sdpder96', '-TXT']
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC': command_dpder = ['tdpder96', '-TXT']
if love:
command_dpder_love = copy.deepcopy(command_dpder)
command_dpder_love.append('-L')
if rayleigh:
command_dpder_ray = copy.deepcopy(command_dpder)
command_dpder_ray.append('-R')
###############
# run command
###############
try:
disptree = copy.deepcopy(self.tree['disp'])
except:
self.tree.update( {'disp':{'ray':{}, 'love': {}}} )
disptree = {'ray':{}, 'love': {}}
dertree={'model': {}, 'egn': {'ray':{}, 'love': {} } }
if run:
cdir = os.getcwd()
os.chdir(workingdir)
if runtype == 'ALL':
subprocess.call(command_love)
subprocess.call(command_ray)
command_love.append('-DER')
command_ray.append('-DER')
subprocess.call(command_love)
subprocess.call(command_ray)
elif runtype == 'DER' or runtype == 'DH' or runtype == 'DA' or runtype == 'DB' or runtype == 'DR':
command_love.append('-'+runtype)
command_ray.append('-'+runtype)
subprocess.call(command_love)
subprocess.call(command_ray)
else:
subprocess.call(command_love)
subprocess.call(command_ray)
###
# Read/Upate dispersion data
###
if len(command_dpegn_love) !=0:
subprocess.call(command_dpegn_love)
if self.model1d.modeltype == 'ISOTROPIC':
dispfile = cpsfile.DispFile(workingdir+'/SLEGN.TXT')
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC':
dispfile = cpsfile.DispFile(workingdir+'/TLEGN.TXT')
disptree.update( dispfile.get_tree(intree=disptree) )
if len(command_dpegn_ray) !=0:
subprocess.call(command_dpegn_ray)
if self.model1d.modeltype == 'ISOTROPIC':
dispfile = cpsfile.DispFile(workingdir+'/SREGN.TXT')
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC':
dispfile = cpsfile.DispFile(workingdir+'/TREGN.TXT')
disptree.update( dispfile.get_tree(intree=disptree) )
self.tree['disp'].update(disptree)
###
# Read eigenfunction data
###
if len(command_dpder_love) !=0:
subprocess.call(command_dpder_love)
if self.model1d.modeltype == 'ISOTROPIC':
derfile = cpsfile.derFile(workingdir+'/SLDER.TXT')
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC':
derfile = cpsfile.derFile(workingdir+'/TLDER.TXT')
dertree = derfile.get_tree(intree=dertree)
if len(command_dpder_ray) !=0:
subprocess.call(command_dpder_ray)
if self.model1d.modeltype == 'ISOTROPIC':
derfile = cpsfile.derFile(workingdir+'/SRDER.TXT')
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC':
derfile = cpsfile.derFile(workingdir+'/TRDER.TXT')
dertree = derfile.get_tree(intree=dertree)
self.tree.update({'der': dertree})
###
# Update input parameters
###
self.tree.update({'inparam': inparam})
if outfname!=None: self.write_to(outfname)
os.chdir(cdir)
return True
if runtype == 'ALL':
command_love.append('-DER')
command_ray.append('-DER')
command.append('\n'+command_ray[0])
command += command_ray[1:]
command.append('\n'+command_love[0])
command += command_love[1:]
elif runtype == '-DER' or runtype == '-DH' or runtype == '-DA' or runtype == '-DB' or runtype == '-DR':
command_love.append('-'+runtype)
command_ray.append('-'+runtype)
command = []
command += command_love
command.append('\n'+command_ray[0])
command += command_ray[1:]
if len(command_dpegn_love) !=0:
command.append('\n'+command_dpegn_love[0])
command += command_dpegn_love[1:]
if len(command_dpegn_ray) !=0:
command.append('\n'+command_dpegn_ray[0])
command += command_dpegn_ray[1:]
if len(command_dpder_love) !=0:
command.append('\n'+command_dpder_love[0])
command += command_dpder_love[1:]
if len(command_dpder_ray) !=0:
command.append('\n'+command_dpder_ray[0])
command += command_dpder_ray[1:]
outstr = ' '.join(command)
print outstr
return outstr
def run_pulse(self, distfile=None, dist0=500, dD=100, Nd=10, workingdir=None, infname=None, outfname=None, stftype='-i',
duraparam=2, sourcetype='-ALL', outtype='-D', fund=True, verbose=False, run=True):
"""
Compute synthetics seismograms given eigenfunction data
================================================================================
Input parameters:
distfile - distance file, object or file path
dist0 - distance for origin point
dD - distance interval
Nd - number of distance point
workingdir - working directory
infname - input file name
outfname - output file name
stftype - type of source time function (-i, -o, -t, -p)
duraparam - duration controle parameters for source pulse
sourcetype - type of source (-EX, -EQ, -ALL)
outtype - output type (-D, -V, -A), displacement, velocity, acceleration
fund - only include fundamental mode or not
run - run the code or not
================================================================================
"""
if infname != None: self.load(infname=infname)
inparam = copy.deepcopy(self.tree['inparam'])
if workingdir == None: workingdir = inparam['workingdir']
if outtype!='-D' and outtype!='-V' and outtype!='-A':
raise ValueError('Unrecognized type of output seismogram '+ outtype +' should be -D, -V or -A')
if sourcetype!='-EX' and sourcetype!='-EQ' and sourcetype!='-ALL':
raise ValueError('Unrecognized type of souce '+ sourcetype +' should be -EX, -EQ or -ALL')
if stftype!='-i' and stftype!='-t' and stftype!='-p' and stftype!='-o':
raise ValueError('Unrecognized type of souce '+ stftype +' should be -i, -t, -p or -o')
###
# distance file
###
self.getdfile(distfile=distfile, dist0=dist0, dD=dD, Nd=Nd)
try: self.distfile
except: raise ValueError('Distance file not specified!')
self.distfile.write(distfname=workingdir+'/dfile')
###
#
###
if self.model1d.modeltype == 'ISOTROPIC':
command = ['spulse96']
elif self.model1d.modeltype == 'TRANSVERSE ISOTROPIC':
command = ['tpulse96']
command.append('-d'); command.append('dfile')
command.append(sourcetype); command.append(outtype)
if verbose: command.append('-v')
command.append(stftype)
if stftype == '-t' or stftype == '-p':
command.append('-l'); command.append('%d' %duraparam)
if fund==True: command.append('-FUND')
###
# Update input parameters
###
inparam.update({'workingdir': workingdir, 'stf': stftype, 'sourcetype': sourcetype, 'outtype': outtype, 'fund': fund})
self.tree.update({'inparam': inparam})
command2sac=['f96tosac', '-B', 'tempf96']
if outfname!=None: self.write_to(outfname)
if run:
cdir = os.getcwd()
os.chdir(workingdir)
with open('tempf96', 'w') as f:
subprocess.call(command, stdout=f)
subprocess.call(command2sac)
os.remove(workingdir+'/tempf96')
os.chdir(cdir)
else:
command.append('>'); command.append('tempf96')
command.append('\n'+command2sac[0])
command+=command2sac[1:]
outstr = ' '.join(command)
print outstr
return outstr
def write_disp(self, outfname, wavetype='ray', mode=0, dtype='ph'):
"""
Write dispersion curve to txt file
================================================================================
Input parameters:
outfname - output file name
wavetype - type of wave (Love or Rayleigh)
mode - mode id (0: fundamental mode, 1, 2,... overtones)
dtype - data type
================================================================================
"""
wavetype = wavetype.lower()
if wavetype == 'rayleigh': wavetype = 'ray'
if wavetype != 'ray' and wavetype != 'love':
raise ValueError('wavetype can only be ray or love')
try:
disptree= self.tree['disp'][wavetype][mode]
if dtype == 'ph' or dtype == 'C': dtype = 'ph'
elif dtype == 'gr' or dtype == 'U': dtype = 'gr'
else: raise ValueError('Unrecognized data type!')
vel = disptree['V'+dtype]
periods = disptree['T']
except:
egntree = self.tree['der']['egn'][wavetype][mode]
periods = np.sort(egntree.keys())
vel = []
if dtype == 'ph' or dtype == 'C': dtype = 'C'
elif dtype == 'gr' or dtype == 'U': dtype = 'U'
else: raise ValueError('Unrecognized data type!')
for per in periods:
vel.append( egntree[per][dtype] )
vel = np.asarray(vel)
outArr = np.append(periods, vel)
outArr = (outArr.reshape(2, periods.size)).T
np.savetxt(outfname, outArr, fmt='%g')
return
def del_dir(self, workingdir=None):
"""
Delete working directory
"""
try:
inparam = copy.deepcopy(self.tree['inparam'])
if workingdir == None: workingdir = inparam['workingdir']
except:
pass
if workingdir == None: raise ValueError('Working directory is not specified!')
shutil.rmtree(workingdir)
return
def plot_eigen(self, wavetype, period, dtype, style=None, mode=0, zmax=9999., newfig=True, showfig=True):
"""
Plot eigenfunction/sensitivity kernels
================================================================================
Input parameters:
wavetype - type of wave (Love or Rayleigh)
dtype - data type
------------------------- eigenfunctions ---------------------------
ur, tr, uz, tz - Rayleigh wave eigenfunctions
ut, tt - Love wave eigenfunctions
----------------------- sensitivity kernels ------------------------
dcdh - layer thickness
dcda, dcdb - P/S wave velocity
dcdr - density
dcdav/dcdah - PV/PH wave velocity
dcdbv/dcdbh - SV/SH wave velocity
dcdn - eta (eta = F/(A-2L); A, L, F are Love parameters)
style - line style for plot
mode - mode id (0: fundamental mode, 1, 2,... overtones)
zmax - maximum depth for trim
================================================================================
"""
###
# Check input
###
wavetype = wavetype.lower(); #dtype = dtype.lower()
if wavetype == 'rayleigh': wavetype = 'ray'
if wavetype != 'ray' and wavetype != 'love':
raise ValueError('wavetype can only be ray or love')
if dtype !='ur' and dtype !='tr' and dtype !='uz' and dtype !='tz' and dtype !='ut' and dtype !='tt' and dtype !='dcdh' and dtype !='dcda' \
and dtype !='dcdb' and dtype !='dcdr' and dtype !='dcdav' and dtype !='dcdah' and dtype !='dcdbv' and dtype !='dcdbh' and dtype !='dcdn'\
and dtype !='dcdA' and dtype !='dcdC' and dtype !='dcdL' and dtype !='dcdF' and dtype !='dcdN':
raise ValueError('dtype should be one of Ur, Tr, Uz, Tz, Ut, Tt, DCDH, DCDA, DCDB, DCDR, DCDAV, DCDAH, DCDBV, DCDBH, DCDN')
if self.tree['der']['model']['isotropic']:
if dtype == 'dcdav' or dtype == 'dcdah' or dtype == 'dcdbv' or dtype == 'dcdbh' or dtype == 'dcdn':
raise ValueError('For isotropic model, dtype should NOT be one of DCDAV, DCDAH, DCDBV, DCDBH, DCDN')
else:
if dtype == 'dcda' or dtype == 'dcdb':
raise ValueError('For TI model, dtype should NOT be one of DCDA, DCDB')
###
# Get data for plot
###
dataArr = self.tree['der']['egn'][wavetype][mode][period][dtype]
HArr = self.tree['der']['model']['H']
zArr = np.cumsum(HArr) - HArr
dataArr = dataArr[zArr<zmax]
zArr = zArr[zArr<zmax]
###
# Plot data
###
if newfig: fig, ax=plt.subplots()
plt.title('')
if style !=None:
plt.plot(dataArr, zArr, style, lw=3, label='mode: '+str(mode)+', T = '+str(period))
else:
plt.plot(dataArr, zArr, lw=3, label='mode: '+str(mode)+', T = '+str(period))
if newfig:
ax.tick_params(axis='x', labelsize=20)
ax.tick_params(axis='y', labelsize=20)
plt.gca().invert_yaxis()
plt.xlabel(dtype.upper(), fontsize=30)
plt.ylabel('Depth (km)', fontsize=30)
if showfig:
plt.legend(numpoints=1, fontsize=20, loc=0)
plt.show()
def compute_love_kernel(self, outfname=None, modelst=None, perlst=None):
refmodel = self.tree['der']['model']
if refmodel['isotropic']: raise ValueError('Sensitivity kernels for Love parameters can not be computed for isotropic model')
if modelst == None: modelst = self.tree['der']['egn']['ray'].keys()
if perlst == None: perlst = self.tree['der']['egn']['ray'][modelst[0]].keys()
###
# model parameters
###
A = refmodel['A']
L = refmodel['L']
C = refmodel['C']
F = refmodel['F']
N = refmodel['N']
eta = F/(A-2.*L)
rho = refmodel['rho']
for mode in modelst:
for period in perlst:
VphR = self.tree['der']['egn']['ray'][mode][period]['C']
VgrR = self.tree['der']['egn']['ray'][mode][period]['U']
kR = 2.*np.pi/VphR/period
VphL = self.tree['der']['egn']['love'][mode][period]['C']
VgrL = self.tree['der']['egn']['love'][mode][period]['U']
kL = 2.*np.pi/VphL/period
# eigenfuntions
Ur = self.tree['der']['egn']['ray'][mode][period]['ur']
Uz = self.tree['der']['egn']['ray'][mode][period]['uz']
Tr = self.tree['der']['egn']['ray'][mode][period]['tr']
Tz = self.tree['der']['egn']['ray'][mode][period]['tz']
Ut = self.tree['der']['egn']['love'][mode][period]['ut']
Tt = self.tree['der']['egn']['love'][mode][period]['tt']
# derivative of eigenfunctions, $5.8 of R.Herrmann
durdz = 1./L*Tr - kR*Uz
duzdz = kR*F/C*Ur + Tz/C
dutdz = Tt/L
# Rayleigh wave sensitivity kernel
dcRdav = self.tree['der']['egn']['ray'][mode][period]['dcdav']
dcRdah = self.tree['der']['egn']['ray'][mode][period]['dcdah']
dcRdbv = self.tree['der']['egn']['ray'][mode][period]['dcdbv']
dcRdbh = self.tree['der']['egn']['ray'][mode][period]['dcdbh']
dcRdeta = self.tree['der']['egn']['ray'][mode][period]['dcdn']
dcRdr = self.tree['der']['egn']['ray'][mode][period]['dcdr']
# Love wave sensitivity kernel
dcLdbv = self.tree['der']['egn']['love'][mode][period]['dcdbv']
dcLdbh = self.tree['der']['egn']['love'][mode][period]['dcdbh']
dcLdr = self.tree['der']['egn']['love'][mode][period]['dcdr']
# get trees for update
rayTree = self.tree['der']['egn']['ray'][mode][period]
loveTree= self.tree['der']['egn']['love'][mode][period]
# compute partial derivatives using chain rule
# Rayleigh wave
dcRdA = -dcRdeta * F/((A-2.*L)**2) + dcRdah *0.5 /np.sqrt(rho*A)
dcRdC = dcRdav *0.5 /np.sqrt(rho*C)
dcRdF = dcRdeta /(A-2.*L)
dcRdL = dcRdeta * 2.*F/((A-2.*L)**2) + dcRdbv *0.5 /np.sqrt(rho*L)
dcRdN = dcRdbh *0.5 /np.sqrt(rho*N)
# Love wave
dcLdA = np.array([])
dcLdC = np.array([])
dcLdF = np.array([])
dcLdL = dcLdbv *0.5 /np.sqrt(rho*L)
dcLdN = dcLdbh *0.5 /np.sqrt(rho*N)
# Update trees
addRtree= {'dcdA': dcRdA, 'dcdC': dcRdC, 'dcdF': dcRdF, 'dcdL': dcRdL, 'dcdN': dcRdN}
addLtree= {'dcdA': dcLdA, 'dcdC': dcLdC, 'dcdF': dcLdF, 'dcdL': dcLdL, 'dcdN': dcLdN}
rayTree.update(addRtree)
loveTree.update(addLtree)
if outfname!=None: self.write_to(outfname)
return
def compute_love_kernel_montagner(self, outfname=None, modelst=None, perlst=None):
refmodel = self.tree['der']['model']
if refmodel['isotropic']: raise ValueError('Sensitivity kernels for Love parameters can not be computed for isotropic model')
if modelst == None: modelst = self.tree['der']['egn']['ray'].keys()
if perlst == None: perlst = self.tree['der']['egn']['ray'][modelst[0]].keys()
###
# model parameters
###
A = refmodel['A']
L = refmodel['L']
C = refmodel['C']
F = refmodel['F']
N = refmodel['N']
eta = F/(A-2.*L)
rho = refmodel['rho']
for mode in modelst:
for period in perlst:
VphR = self.tree['der']['egn']['ray'][mode][period]['C']
VgrR = self.tree['der']['egn']['ray'][mode][period]['U']
kR = 2.*np.pi/VphR/period
VphL = self.tree['der']['egn']['love'][mode][period]['C']
VgrL = self.tree['der']['egn']['love'][mode][period]['U']
kL = 2.*np.pi/VphL/period
# eigenfuntions
Ur = self.tree['der']['egn']['ray'][mode][period]['ur']
Uz = self.tree['der']['egn']['ray'][mode][period]['uz']
Tr = self.tree['der']['egn']['ray'][mode][period]['tr']
Tz = self.tree['der']['egn']['ray'][mode][period]['tz']
Ut = self.tree['der']['egn']['love'][mode][period]['ut']
Tt = self.tree['der']['egn']['love'][mode][period]['tt']
# derivative of eigenfunctions, $5.8 of R.Herrmann
durdz = 1./L*Tr - kR*Uz
duzdz = kR*F/C*Ur + Tz/C
dutdz = Tt/L
R0 = np.sum(rho*(Ur**2+Uz**2))
L0 = np.sum(rho*(Ut**2))
# Rayleigh wave sensitivity kernel
dcRdav = self.tree['der']['egn']['ray'][mode][period]['dcdav']
dcRdah = self.tree['der']['egn']['ray'][mode][period]['dcdah']
dcRdbv = self.tree['der']['egn']['ray'][mode][period]['dcdbv']
dcRdbh = self.tree['der']['egn']['ray'][mode][period]['dcdbh']
dcRdeta = self.tree['der']['egn']['ray'][mode][period]['dcdn']
dcRdr = self.tree['der']['egn']['ray'][mode][period]['dcdr']
# Love wave sensitivity kernel
dcLdbv = self.tree['der']['egn']['love'][mode][period]['dcdbv']
dcLdbh = self.tree['der']['egn']['love'][mode][period]['dcdbh']
dcLdr = self.tree['der']['egn']['love'][mode][period]['dcdr']
# get trees for update
rayTree = self.tree['der']['egn']['ray'][mode][period]
loveTree= self.tree['der']['egn']['love'][mode][period]
# compute partial derivatives using chain rule
# Rayleigh wave
dcRdA = (Uz**2)/2./VgrR/R0
dcRdC = ((durdz/kR)**2)/2./VgrR/R0
dcRdF = (2.*durdz*Uz/kR)/2./VgrR/R0
dcRdL = ((duzdz/kR-Ur)**2)/2./VgrR/R0
dcRdN = dcRdbh *0.5 /np.sqrt(rho*N)
# Love wave
dcLdA = np.array([])
dcLdC = np.array([])
dcLdF = np.array([])
dcLdL = ((dutdz/kL)**2)/2./VgrL/L0
dcLdN = (Ut**2)/2./VgrL/L0
# Update trees
addRtree= {'dcdA': dcRdA, 'dcdC': dcRdC, 'dcdF': dcRdF, 'dcdL': dcRdL, 'dcdN': dcRdN}
addLtree= {'dcdA': dcLdA, 'dcdC': dcLdC, 'dcdF': dcLdF, 'dcdL': dcLdL, 'dcdN': dcLdN}
rayTree.update(addRtree)
loveTree.update(addLtree)
if outfname!=None: self.write_to(outfname)
return
def perturb(self, inmodel, wavetype, mode=0, perlst=[10.]):
"""
Compute phase velocity dispersion curve given a perturbed model
================================================================================
Input parameters:
inmodel - input perturbed model
wavetype - type of wave (Love or Rayleigh)
mode - mode id (0: fundamental mode, 1, 2,... overtones)
perlst - period list
================================================================================
"""
wavetype = wavetype.lower()
if wavetype == 'rayleigh': wavetype = 'ray'
refmodel = self.tree['der']['model']
if (refmodel['isotropic'] and inmodel.modeltype != 'ISOTROPIC') or ((not refmodel['isotropic']) and inmodel.modeltype == 'ISOTROPIC'):
raise ValueError('Model need to be the same type!')
if not np.allclose(refmodel['H'], inmodel.HArr):
raise ValueError('Model layers are not the same!')
HArr = inmodel.HArr
c0Arr = []
cArr = []
if refmodel['isotropic']:
dvs = inmodel.VsArr - refmodel['vs']
dvp = inmodel.VpArr - refmodel['vp']
drho= inmodel.rhoArr - refmodel['rho']
for period in perlst:
dcda = self.tree['der']['egn'][wavetype][mode][period]['dcda']
dcdb = self.tree['der']['egn'][wavetype][mode][period]['dcdb']
dcdr = self.tree['der']['egn'][wavetype][mode][period]['dcdr']
# # # dc = np.sum(dcda*dvp*HArr) + np.sum(dcdb*dvs*HArr) + np.sum(dcdr*drho*HArr)
if wavetype=='ray':
dc = np.sum(dcda*dvp) + np.sum(dcdb*dvs) + np.sum(dcdr*drho)
else:
dc = np.sum(dcdb*dvs) + np.sum(dcdr*drho)
c0 = self.tree['der']['egn'][wavetype][mode][period]['C']
c = c0+dc
c0Arr.append(c0)
cArr.append(c)
else:
rho = refmodel['rho']
vsv0 = np.sqrt(refmodel['L'] / rho)
vsh0 = np.sqrt(refmodel['N'] / rho)
vpv0 = np.sqrt(refmodel['C'] / rho)
vph0 = np.sqrt(refmodel['A'] / rho)
eta0 = refmodel['F'] / (refmodel['A'] - 2.* refmodel['L'])
eta = (inmodel.VpfArr**2)/(inmodel.VphArr**2 - 2.*(inmodel.VsvArr**2))
drho = inmodel.rhoArr - rho
dvsv = inmodel.VsvArr - vsv0
dvsh = inmodel.VshArr - vsh0
dvpv = inmodel.VpvArr - vpv0
dvph = inmodel.VphArr - vph0
deta = eta - eta0
# print 'HERE:', drho.min(), dvsv.max()
for period in perlst:
dcdav = self.tree['der']['egn'][wavetype][mode][period]['dcdav']
dcdah = self.tree['der']['egn'][wavetype][mode][period]['dcdah']
dcdbv = self.tree['der']['egn'][wavetype][mode][period]['dcdbv']
dcdbh = self.tree['der']['egn'][wavetype][mode][period]['dcdbh']
dcdeta = self.tree['der']['egn'][wavetype][mode][period]['dcdn']
dcdr = self.tree['der']['egn'][wavetype][mode][period]['dcdr']
# # # dc = np.sum(dcda*dvp*HArr) + np.sum(dcdb*dvs*HArr) + np.sum(dcdr*drho*HArr)
if wavetype=='ray':
dc = np.sum(dcdav*dvpv) + np.sum(dcdah*dvph) + np.sum(dcdbv*dvsv) + np.sum(dcdbh*dvsh) \
+ np.sum(dcdr*drho) + np.sum(dcdeta*deta)
else:
dc = np.sum(dcdbv*dvsv) + np.sum(dcdbh*dvsh) + np.sum(dcdr*drho)
c0 = self.tree['der']['egn'][wavetype][mode][period]['C']
c = c0+dc
c0Arr.append(c0)
cArr.append(c)
return c0Arr, cArr
def perturb_love(self, inmodel, wavetype, mode=0, perlst=[10.]):
"""
Compute phase velocity dispersion curve given a perturbed model,
using partial derivatives for Love parameters.
================================================================================
Input parameters:
inmodel - input perturbed model
wavetype - type of wave (Love or Rayleigh)
mode - mode id (0: fundamental mode, 1, 2,... overtones)
perlst - period list
================================================================================
"""
wavetype = wavetype.lower()
if wavetype == 'rayleigh': wavetype = 'ray'
refmodel = self.tree['der']['model']
if refmodel['isotropic']:
raise ValueError('This function only works for TI model')
if not np.allclose(refmodel['H'], inmodel.HArr):
raise ValueError('Model layers are not the same!')
HArr = inmodel.HArr
c0Arr = []
cArr = []
A = refmodel['A']
L = refmodel['L']
C = refmodel['C']
F = refmodel['F']
N = refmodel['N']
rho0 = refmodel['rho']
rho = inmodel.rhoArr
A1 = (inmodel.VphArr**2)*rho
L1 = (inmodel.VsvArr**2)*rho
C1 = (inmodel.VpvArr**2)*rho
F1 = (inmodel.VpfArr**2)*rho
N1 = (inmodel.VshArr**2)*rho
drho = inmodel.rhoArr - rho0
dA = A1 - A
dC = C1 - C
dF = F1 - F
dL = L1 - L
dN = N1 - N
for period in perlst:
dcdA = self.tree['der']['egn'][wavetype][mode][period]['dcdA']
dcdC = self.tree['der']['egn'][wavetype][mode][period]['dcdC']
dcdF = self.tree['der']['egn'][wavetype][mode][period]['dcdF']
dcdL = self.tree['der']['egn'][wavetype][mode][period]['dcdL']
dcdN = self.tree['der']['egn'][wavetype][mode][period]['dcdN']
dcdr = self.tree['der']['egn'][wavetype][mode][period]['dcdr']
# # # dc = np.sum(dcda*dvp*HArr) + np.sum(dcdb*dvs*HArr) + np.sum(dcdr*drho*HArr)
if wavetype=='ray':
dc = np.sum(dcdA*dA) + np.sum(dcdC*dC) + np.sum(dcdF*dF) + np.sum(dcdL*dL) \
+ np.sum(dcdr*drho) + np.sum(dcdN*dN)
else:
dc = np.sum(dcdL*dL) + np.sum(dcdr*drho) + np.sum(dcdN*dN)
c0 = self.tree['der']['egn'][wavetype][mode][period]['C']
c = c0+dc
c0Arr.append(c0)
cArr.append(c)
return c0Arr, cArr
def compare_disp(self, inmodel, indbase, wavetype, mode=0, perlst=[10.]):
"""
Compare dispersion curve from sensitivity kernel based computation with input database
=======================================================================================
Input parameters:
inmodel - input perturbed model
indbase - input database
wavetype - type of wave (Love or Rayleigh)
mode - mode id (0: fundamental mode, 1, 2,... overtones)
perlst - period list
=======================================================================================
"""
wavetype = wavetype.lower()
if wavetype == 'rayleigh': wavetype = 'ray'
c0Arr, cpreArr = self.perturb(inmodel=inmodel, wavetype=wavetype, mode=mode, perlst=perlst)
cArr = []
for period in perlst:
c = indbase.tree['der']['egn'][wavetype][mode][period]['C']
cArr.append(c)
return c0Arr, cpreArr, cArr
def test_derivative(self, zmax, period, mode=0):
refmodel = self.tree['der']['model']
###
# Get data for plot
###
HArr = self.tree['der']['model']['H']
A = refmodel['A']
L = refmodel['L']
C = refmodel['C']
F = refmodel['F']
eta = refmodel['F'] / (refmodel['A'] - 2.* refmodel['L'])
rho = refmodel['rho']
VphR = self.tree['der']['egn']['ray'][mode][period]['C']
VgrR = self.tree['der']['egn']['ray'][mode][period]['U']
kR = 2.*np.pi/VphR/period
VphL = self.tree['der']['egn']['love'][mode][period]['C']
kL = 2.*np.pi/VphL/period
Ur = self.tree['der']['egn']['ray'][mode][period]['ur']
Uz = self.tree['der']['egn']['ray'][mode][period]['uz']
Tr = self.tree['der']['egn']['ray'][mode][period]['tr']
Tz = self.tree['der']['egn']['ray'][mode][period]['tz']
Ut = self.tree['der']['egn']['love'][mode][period]['ut']
Tt = self.tree['der']['egn']['love'][mode][period]['tt']
diffur1 = (Ur[1:] - Ur[:-1]) /1./HArr[1:]
diffur2 = 1./L*Tr - kR*Uz
diffuz1 = (Uz[1:] - Uz[:-1]) /1./HArr[1:]
diffuz2 = kR*F/C*Ur + Tz/C
diffut1 = (Ut[1:] - Ut[:-1]) /1./HArr[1:]
diffut2 = Tt/L
R0 = np.sum(rho*(Ur**2+Uz**2))
dcdA1 = (Uz**2)/R0