def save(self, dict, path, parameters=['vp','vs','rho'],
prefix='', suffix=''):
"""
Saves SPECFEM2D/3D models or kernels
:input dict :: model stored as a dictionary or Container
:input path :: directory to which model is written
:input parameters :: list of material parameters to be written
:input prefix :: optional filename prefix
:input suffix :: optional filename suffix, eg '_kernel'
"""
unix.mkdir(path)
# fill in any missing parameters
missing_keys = diff(parameters, dict.keys())
for iproc in range(self.mesh_properties.nproc):
for key in missing_keys:
dict[key] += self.io.read_slice(
PATH.MODEL_INIT, prefix+key+suffix, iproc)
# write slices to disk
for iproc in range(self.mesh_properties.nproc):
for key in parameters:
self.io.write_slice(
dict[key][iproc], path, prefix+key+suffix, iproc)
def setup(self):
""" Sets up nonlinear optimization machinery
"""
unix.mkdir(PATH.OPTIMIZE)
# prepare output writers
self.writer = Writer(
path=PATH.OUTPUT)
self.stepwriter = StepWriter(
path=PATH.SUBMIT)
# prepare algorithm machinery
if PAR.SCHEME in ['NLCG']:
self.NLCG = NLCG(
path=PATH.OPTIMIZE,
maxiter=PAR.NLCGMAX,
thresh=PAR.NLCGTHRESH,
precond=self.precond())
elif PAR.SCHEME in ['LBFGS']:
self.LBFGS = LBFGS(
path=PATH.OPTIMIZE,
memory=PAR.LBFGSMEM,
maxiter=PAR.LBFGSMAX,
thresh=PAR.LBFGSTHRESH,
precond=self.precond())
# write initial model
if exists(PATH.MODEL_INIT):
import solver
src = PATH.MODEL_INIT
dst = join(PATH.OPTIMIZE, 'm_new')
savenpy(dst, solver.merge(solver.load(src)))
def smooth(self, path='', parameters=[], span=0.):
""" Smooths kernels by convolving them with a Gaussian. Wrapper over
xsmooth_sem utility.
"""
assert exists(path)
assert len(parameters) > 0
# apply smoothing operator
unix.cd(self.cwd)
for name in parameters or self.parameters:
print ' smoothing', name
call_solver(
system.mpiexec(),
PATH.SPECFEM_BIN +'/'+ 'xsmooth_sem '
+ str(span) + ' '
+ str(span) + ' '
+ name + '_kernel' + ' '
+ path + '/ '
+ path + '/ ',
output='/dev/null')
print ''
# move input files
src = path
dst = path + '_nosmooth'
unix.mkdir(dst)
for name in parameters or self.parameters:
unix.mv(glob(src+'/*'+name+'_kernel.bin'), dst)
# rename output files
unix.rename('_smooth', '', glob(src+'/*'))
def _launch(self, classname, funcname, hosts='all'):
unix.mkdir(PATH.SYSTEM)
# prepare sbatch arguments
if hosts == 'all':
args = ('--array=%d-%d ' % (0, PAR.NTASK - 1) + '--output %s ' %
(PATH.SUBMIT + '/' + 'output.slurm/' + '%A_%a'))
elif hosts == 'head':
args = ('--array=%d-%d ' % (0, 0) + '--output=%s ' %
(PATH.SUBMIT + '/' + 'output.slurm/' + '%j'))
#+('--export=SEISFLOWS_TASK_ID=%s ' % 0
# submit job
with open(PATH.SYSTEM + '/' + 'job_id', 'w') as f:
subprocess.call(
'sbatch ' + '--job-name=%s ' % PAR.TITLE +
'--nodes=%d ' % math.ceil(PAR.NPROC / float(PAR.NODESIZE)) +
'--ntasks-per-node=%d ' % PAR.NODESIZE +
'--time=%d ' % PAR.STEPTIME + args + findpath('system') + '/' +
'slurm/wrapper_srun ' + PATH.OUTPUT + ' ' + classname + ' ' +
funcname + ' ',
shell=1,
stdout=f)
# retrieve job ids
with open(PATH.SYSTEM + '/' + 'job_id', 'r') as f:
line = f.readline()
job = line.split()[-1].strip()
if hosts == 'all' and PAR.NTASK > 1:
nn = range(PAR.NTASK)
return [job + '_' + str(ii) for ii in nn]
else:
return [job]
def smooth(self, input_path='', output_path='', parameters=[], span=0.):
""" Smooths kernels by convolving them with a Gaussian. Wrapper over
xsmooth_sem utility.
"""
if not exists(input_path):
raise Exception
if not exists(output_path):
unix.mkdir(output_path)
# apply smoothing operator
unix.cd(self.cwd)
for name in parameters or self.parameters:
print ' smoothing', name
call_solver(
system.mpiexec(),
PATH.SPECFEM_BIN +'/'+ 'xsmooth_sem '
+ str(span) + ' '
+ str(span) + ' '
+ name + '_kernel' + ' '
+ input_path + '/ '
+ output_path + '/ ',
output='/dev/null')
print ''
# rename output files
files = glob(output_path+'/*')
unix.rename('_smooth', '', files)
def initialize_io_machinery(self):
""" Writes mesh files expected by input/output methods
"""
if system.getnode() == 0:
model_set = set(self.model_parameters)
inversion_set = set(self.inversion_parameters)
parts = self.load(PATH.MODEL_INIT)
try:
path = PATH.GLOBAL + '/' + 'mesh'
except:
raise Exception
if not exists(path):
for key in list(setdiff(model_set,
inversion_set)) + ['x', 'z']:
unix.mkdir(path + '/' + key)
for proc in range(PAR.NPROC):
with open(path + '/' + key + '/' + '%06d' % proc,
'w') as file:
np.save(file, parts[key][proc])
try:
path = PATH.OPTIMIZE + '/' + 'm_new'
except:
return
if not exists(path):
savenpy(path, self.merge(parts))
def smooth(self, input_path='', output_path='', parameters=[], span=0.):
""" Smooths kernels by convolving them with a Gaussian. Wrapper over
xsmooth_sem utility.
"""
if not exists(input_path):
raise Exception
if not exists(output_path):
unix.mkdir(output_path)
# apply smoothing operator
unix.cd(self.cwd)
files = []
files += glob(PATH.MODEL_INIT + '/proc??????_x.bin')
files += glob(PATH.MODEL_INIT + '/proc??????_z.bin')
files += glob(PATH.MODEL_INIT + '/proc??????_NSPEC_ibool.bin')
files += glob(PATH.MODEL_INIT + '/proc??????_jacobian.bin')
for file in files:
unix.cp(file, input_path)
for name in parameters or self.parameters:
print(' smoothing', name)
call_solver(system.mpiexec(),
PATH.SPECFEM_BIN + '/' + 'xsmooth_sem ' + str(span) +
' ' + str(span) + ' ' + name + '_kernel' + ' ' +
input_path + '/ ' + output_path + '/ F',
output=output_path + '/smooth_' + name + '.log')
print('')
# rename output files
files = glob(output_path + '/*')
unix.rename('_smooth', '', files)
def clip(self, path='', parameters=[], minval=-np.inf, maxval=np.inf):
""" Clips kernels by convolving them with a Gaussian. Wrapper over
xclip_sem utility.
"""
assert exists(path)
assert len(parameters) > 0
unix.cd(self.getpath)
for name in parameters or self.parameters:
call_solver(
system.mpiexec,
PATH.SPECFEM_BIN +'/'+ 'xclip_sem '
+ str(minval) + ' '
+ str(maxval) + ' '
+ name + '_kernel' + ' '
+ path + '/ '
+ path + '/ ')
# move input files
src = path
dst = path + '_noclip'
unix.mkdir(dst)
for name in parameters or self.parameters:
unix.mv(glob(src+'/*'+name+'.bin'), dst)
# rename output files
unix.rename('_clip', '', glob(src+'/*'))
def apply_hessian(self, m, dm, h):
""" Computes the action of the Hessian on a given vector through
solver calls
"""
system = sys.modules['seisflows_system']
solver = sys.modules['seisflows_solver']
postprocess = sys.modules['seisflows_postprocess']
self.save('m_lcg', m + h * dm)
solver.save(solver.split(m + h * dm), PATH.HESS + '/' + 'model')
system.run('optimize', 'apply_hess', path=PATH.HESS)
postprocess.write_gradient(path=PATH.HESS)
self.save(
'g_lcg',
solver.merge(
solver.load(PATH.HESS + '/' + 'gradient', suffix='_kernel')))
# uncomment for debugging
#if True:
# unix.rm(PATH.HESS+'_debug')
# unix.mv(PATH.HESS, PATH.HESS+'_debug')
# unix.mkdir(PATH.HESS)
unix.rm(PATH.HESS)
unix.mkdir(PATH.HESS)
return self.hessian_product(h)
def submit(self, *args, **kwargs):
""" Submits job
"""
# create scratch directories
if not exists(PATH.SCRATCH):
path = '/scratch/gpfs' + '/' + getuser(
) + '/' + 'seisflows' + '/' + str(uuid4())
unix.mkdir(path)
unix.ln(path, PATH.SCRATCH)
unix.mkdir(PATH.SYSTEM)
# create output directories
unix.mkdir(PATH.OUTPUT)
unix.mkdir(PATH.WORKDIR + '/' + 'output.slurm')
self.checkpoint()
if not exists(PATH.SCRATCH):
path = '/scratch/gpfs' + '/' + getuser(
) + '/' + 'seisflows' + '/' + str(uuid4())
unix.mkdir(path)
unix.ln(path, PATH.SCRATCH)
call('sbatch ' + '%s ' % PAR.SLURMARGS + '--job-name=%s ' % PAR.TITLE +
'--output=%s ' % (PATH.WORKDIR + '/' + 'output.log') +
'--ntasks-per-node=%d ' % 28 + '--gres=gpu:%d ' % 4 +
'--nodes=%d ' % 1 + '--time=%d ' % PAR.WALLTIME +
pkgpath('seisflows') + '/' + 'system/wrappers/submit ' +
PATH.OUTPUT)
def launch(self, classname, funcname, hosts='all'):
unix.mkdir(PATH.SYSTEM)
# submit job
with open(PATH.SYSTEM+'/'+'job_id', 'w') as f:
subprocess.call('bsub '
+ '%s ' % PAR.LSFARGS
+ '-n %d ' % PAR.NPROC
+ '-R "span[ptile=%d]" ' % PAR.NODESIZE
+ '-W %d:00 ' % PAR.STEPTIME
+ '-J "%s' %PAR.TITLE
+ self.launch_args(hosts)
+ findpath('seisflows.system') +'/'+ 'wrapper/run '
+ PATH.OUTPUT + ' '
+ classname + ' '
+ funcname + ' ',
shell=True,
stdout=f)
# retrieve job ids
with open(PATH.SYSTEM+'/'+'job_id', 'r') as f:
# reads one entire line from the file
line = f.readline()
job_buf = line.split()[1].strip()
job = job_buf[1:-1]
if hosts == 'all' and PAR.NSRC > 1:
nn = range(1,PAR.NSRC+1)
#return [job+'_'+str(ii) for ii in nn]
return [job+'['+str(ii)+']' for ii in nn]
else:
return [job]
def export_traces(self, path, prefix='traces/obs'):
unix.mkdir(join(path))
src = join(self.cwd, prefix)
dst = join(path, self.source_name)
print self.source_name
unix.cp(src, dst)
def combine(self, path=''):
""" combines SPECFEM3D kernels
"""
unix.cd(self.getpath)
# create temporary files and directories
dirs = unix.ls(path)
with open('kernels_list.txt', 'w') as file:
file.write('\n'.join(dirs) + '\n')
unix.mkdir('INPUT_KERNELS')
unix.mkdir('OUTPUT_SUM')
for dir in dirs:
src = path + '/' + dir
dst = 'INPUT_KERNELS' + '/' + dir
unix.ln(src, dst)
# sum kernels
self.mpirun(PATH.SOLVER_BINARIES + '/' + 'xsum_kernels')
unix.mv('OUTPUT_SUM', path + '/' + 'sum')
# remove temporary files and directories
unix.rm('INPUT_KERNELS')
unix.rm('kernels_list.txt')
unix.cd(path)
def smooth(self, path='', tag='gradient', span=0.):
""" smooths SPECFEM3D kernels
"""
unix.cd(self.getpath)
# list kernels
kernels = []
for name in self.model_parameters:
if name in self.inversion_parameters:
flag = True
else:
flag = False
kernels = kernels + [[name, flag]]
# smooth kernels
for name, flag in kernels:
if flag:
print ' smoothing', name
self.mpirun(PATH.SOLVER_BINARIES + '/' + 'xsmooth_sem ' +
str(span) + ' ' + str(span) + ' ' + name + ' ' +
path + '/' + tag + '/ ' + path + '/' + tag + '/ ')
# move kernels
src = path + '/' + tag
dst = path + '/' + tag + '_nosmooth'
unix.mkdir(dst)
for name, flag in kernels:
if flag:
unix.mv(glob(src + '/*' + name + '.bin'), dst)
else:
unix.cp(glob(src + '/*' + name + '.bin'), dst)
unix.rename('_smooth', '', glob(src + '/*'))
print ''
unix.cd(path)
def run(self, classname, funcname, hosts='all', **kwargs):
""" Runs tasks in serial or parallel on specified hosts
"""
name = task.__name__
if PAR.VERBOSE >= 2:
print 'running', name
# save current state
save_objects(join(PATH.OUTPUT, 'SeisflowsObjects'))
# save keyword arguments
kwargspath = join(PATH.OUTPUT, 'SeisflowsObjects',
classname + '_kwargs')
kwargsfile = join(kwargspath, funcname + '.p')
unix.mkdir(kwargspath)
saveobj(kwargsfile, kwargs)
if hosts == 'all':
# run on all available nodes
args = ('pbsdsh ' + findpath('system') + '/' +
'pbs/wrapper_pbsdsh ' + PATH.OUTPUT + ' ' + classname +
' ' + funcname)
elif hosts == 'head':
# run on head node
args = ('pbsdsh ' + findpath('system') + '/' +
'slurm/wrapper_pbsdsh ' + PATH.OUTPUT + ' ' + classname +
' ' + funcname)
else:
raise Exception
subprocess.call(args, shell=1)
def submit(self, workflow):
"""Submits job
"""
unix.mkdir(PATH.OUTPUT)
unix.cd(PATH.OUTPUT)
# save current state
save_objects('SeisflowsObjects')
save_parameters('SeisflowsParameters.json')
save_paths('SeisflowsPaths.json')
nodes = PAR.NTASK / 16
cores = PAR.NTASK % 16
hours = PAR.WALLTIME / 60
minutes = PAR.WALLTIME % 60
# construct resource list
resources = 'walltime=%02d:%02d:00 ' % (hours, minutes)
if nodes == 0:
resources += ',nodes=1:ppn=%d' % cores
elif cores == 0:
resources += ',nodes=%d:ppn=16' % nodes
else:
resources += ',nodes=%d:ppn=16+1:ppn=%d' % (nodes, cores)
args = ('qsub ' + '-N %s ' % PAR.TITLE + '-o %s ' %
(PATH.SUBMIT + '/' + 'output.log') + '-l %s ' % resources +
'-j %s ' % 'oe' + findpath('system') + '/' +
'pbs/wrapper_qsub ' + PATH.OUTPUT)
print args # DEBUG
subprocess.call(args, shell=1)
def combine(self, input_path='', output_path='', parameters=[]):
""" Sums individual source contributions. Wrapper over xcombine_sem
utility.
"""
if not exists(input_path):
raise Exception
if not exists(output_path):
unix.mkdir(output_path)
unix.cd(self.cwd)
names = self.check_source_names()
subset = [names[isrc] for isrc in self._source_subset]
with open('kernel_paths', 'w') as f:
f.writelines([join(input_path, dir) + '\n' for dir in subset])
# SAGA component - include contributions from reference gradient
remainder = list(set(self._source_names) - set(subset))
with open('kernel_paths', 'a') as f:
f.writelines(
[join(PATH.GRAD_AGG, dir) + '\n' for dir in remainder])
for name in parameters or self.parameters:
call_solver(
system.mpiexec(), PATH.SPECFEM_BIN + '/' + 'xcombine_sem ' +
name + '_kernel' + ' ' + 'kernel_paths' + ' ' + output_path)
def combine(self, input_path='', output_path='', parameters=[]):
""" Sums individual source contributions. Wrapper over xcombine_sem
utility.
"""
if not exists(input_path):
raise Exception
if not exists(output_path):
unix.mkdir(output_path)
unix.cd(self.cwd)
names = self.check_source_names()
subset = [names[isrc] for isrc in self._source_subset]
with open('kernel_paths', 'w') as f:
f.writelines([join(input_path, dir)+'\n' for dir in subset])
# SAGA component - include contributions from reference gradient
remainder = list(set(self._source_names) - set(subset))
with open('kernel_paths', 'a') as f:
f.writelines([join(PATH.GRAD_AGG, dir)+'\n' for dir in remainder])
for name in parameters or self.parameters:
call_solver(
system.mpiexec(),
PATH.SPECFEM_BIN +'/'+ 'xcombine_sem '
+ name + '_kernel' + ' '
+ 'kernel_paths' + ' '
+ output_path)
def save(self,
path,
model,
prefix='',
suffix='',
solver_parameters=['vp', 'vs']):
""" writes SPECFEM model or kernels
"""
unix.mkdir(path)
for iproc in range(self.mesh_properties.nproc):
# write parameters required to update model
for key in self.parameters:
sem.write(model[key][iproc], path, prefix + key + suffix,
iproc)
# kernels not required for model updates need not be written
if suffix == '_kernel':
continue
# write any parameters not required for model updates but still
# expected by solver
for key in solver_parameters:
if key not in self.parameters:
src = PATH.OUTPUT + '/' + 'model_init'
dst = path
sem.copy(src, dst, iproc, prefix + key + suffix)
# density is treated as a special case
if self.density_scaling:
rho = self.density_scaling(*model[iproc].items())
sem.write(rho, path, prefix + 'rho' + suffix, iproc)
def save(self, path):
""" Save objects to disk for later reference
"""
fullpath = self.fullpath(path)
unix.mkdir(fullpath)
for key in self.objects:
saveobj(fullpath +'/'+ key+'.p', sys.modules[key])
def submit(self, workflow):
"""Submits job
"""
unix.mkdir(PATH.OUTPUT)
unix.cd(PATH.OUTPUT)
# save current state
self.checkpoint()
# construct resource list
nodes = PAR.NTASK/PAR.NODESIZE
cores = PAR.NTASK%PAR.NODESIZE
hours = PAR.WALLTIME/60
minutes = PAR.WALLTIME%60
resources = 'walltime=%02d:%02d:00 '%(hours, minutes)
if nodes == 0:
resources += ',nodes=1:ppn=%d'%cores
elif cores == 0:
resources += ',nodes=%d:ppn=16'%nodes
else:
resources += ',nodes=%d:ppn=16+1:ppn=%d'%(nodes, cores)
# construct arguments list
unix.run('qsub '
+ '-N %s '%PAR.TITLE
+ '-o %s '%(PATH.SUBMIT +'/'+ 'output.log')
+ '-l %s '%resources
+ '-j %s '%'oe'
+ findpath('system') +'/'+ 'pbs/wrapper_qsub '
+ PATH.OUTPUT,
shell=True)
def _launch(self, classname, funcname, hosts='all'):
unix.mkdir(PATH.SYSTEM)
# submit job
with open(PATH.SYSTEM+'/'+'job_id', 'w') as f:
hours = PAR.WALLTIME/60
minutes = PAR.WALLTIME%60
resources = 'walltime=%02d:%02d:00 '%(hours, minutes)
args = ('/opt/pbs/12.1.1.131502/bin/qsub '
+ '-l select=1:ncpus=32:mpiprocs=32 '
+ '-l %s '%resources
+ '-q standard '
+ '-A ERDCH38424KSC '
+ '-J 0-%s ' % PAR.NTASK
+ '-N %s ' % PAR.TITLE
+ ' -- ' + findpath('system') +'/'+ 'wrappers/runpbsdsh '
+ PATH.OUTPUT + ' '
+ classname + ' '
+ funcname + ' ')
subprocess.call(args, shell=1, stdout=f)
# retrieve job ids
with open(PATH.SYSTEM+'/'+'job_id', 'r') as f:
line = f.readline()
job = line.split()[-1].strip()
if hosts == 'all' and PAR.NTASK > 1:
nn = range(PAR.NTASK)
return [job+'_'+str(ii) for ii in nn]
else:
return [job]
def submit(self, workflow):
"""Submits job
"""
unix.mkdir(PATH.OUTPUT)
unix.cd(PATH.OUTPUT)
# save current state
self.checkpoint()
# construct resource list
nodes = int(PAR.NTASK / PAR.NODESIZE)
cores = PAR.NTASK % PAR.NODESIZE
hours = int(PAR.WALLTIME / 60)
minutes = PAR.WALLTIME % 60
resources = 'walltime=%02d:%02d:00' % (hours, minutes)
if nodes == 0:
resources += ',mem=%dgb,nodes=1:ppn=%d' % (PAR.MEMORY, cores)
elif cores == 0:
resources += ',mem=%dgb,nodes=%d:ppn=%d' % (PAR.MEMORY, nodes,
PAR.NODESIZE)
else:
resources += ',mem=%dgb,nodes=%d:ppn=%d+1:ppn=%d' % (
PAR.MEMORY, nodes, PAR.NODESIZE, cores)
# construct arguments list
call('qsub ' + '%s ' % PAR.PBSARGS + '-N %s ' % PAR.TITLE + '-o %s ' %
(PATH.SUBMIT + '/' + 'output.log') + '-l %s ' % resources +
'-j %s ' % 'oe' + findpath('seisflows.system') + '/' +
'wrappers/submit ' + '-F %s ' % PATH.OUTPUT)
def save(self,
dict,
path,
parameters=['vp', 'vs', 'rho'],
prefix='',
suffix=''):
"""
Saves SPECFEM2D/3D models or kernels
:input dict :: model stored as a dictionary or Container
:input path :: directory from which model is read
:input parameters :: list of material parameters to be read,
:input prefix :: optional filename prefix
:input suffix :: optional filename suffix, eg '_kernel'
"""
unix.mkdir(path)
# fill in any missing parameters
missing_keys = diff(parameters, dict.keys())
for iproc in range(self.mesh_properties.nproc):
for key in missing_keys:
dict[key] += self.io.read_slice(PATH.MODEL_INIT,
prefix + key + suffix, iproc)
# write slices to disk
for iproc in range(self.mesh_properties.nproc):
for key in parameters:
self.io.write_slice(dict[key][iproc], path,
prefix + key + suffix, iproc)
def smooth(self, path='', parameters=[], span=0.):
""" Smooths kernels by convolving them with a Gaussian. Wrapper over
xsmooth_sem utility.
"""
assert exists(path)
assert len(parameters) > 0
# apply smoothing operator
unix.cd(self.getpath)
for name in parameters:
print ' smoothing', name
self.call(PATH.SPECFEM_BIN + '/' + 'xsmooth_sem ' + str(span) +
' ' + str(span) + ' ' + name + '_kernel' + ' ' + path +
'/ ' + path + '/ ',
output=self.getpath + '/' +
'OUTPUT_FILES/output_smooth_sem.txt')
print ''
# move input files
src = path
dst = path + '_nosmooth'
unix.mkdir(dst)
for name in self.parameters:
unix.mv(glob(src + '/*' + name + '.bin'), dst)
# rename output files
unix.rename('_smooth', '', glob(src + '/*'))
def export_residuals(self, path):
# hack deals with problems on parallel filesystem
unix.mkdir(join(path, 'residuals'), noexit=True)
src = join(self.getpath, 'residuals')
dst = join(path, 'residuals', basename(self.getpath))
unix.mv(src, dst)
def export_traces(self, path, prefix='traces/obs'):
# hack deals with problems on parallel filesystem
unix.mkdir(join(path, 'traces'), noexit=True)
src = join(self.getpath, prefix)
dst = join(path, 'traces', basename(self.getpath))
unix.cp(src, dst)
def submit(self, workflow):
""" Submits workflow
"""
unix.mkdir(PATH.OUTPUT)
unix.cd(PATH.OUTPUT)
unix.mkdir(PATH.SUBMIT+'/'+'output.pbs')
self.checkpoint()
hours = PAR.WALLTIME/60
minutes = PAR.WALLTIME%60
walltime = 'walltime=%02d:%02d:00 ' % (hours, minutes)
ncpus = PAR.NODESIZE
mpiprocs = PAR.NODESIZE
# prepare qsub arguments
unix.run( 'qsub '
+ '%s ' % PAR.PBSARGS
+ '-l select=1:ncpus=%d:mpiprocs=%d ' % (ncpus, mpiprocs)
+ '-l %s ' % walltime
+ '-N %s ' % PAR.TITLE
+ '-j %s '%'oe'
+ '-o %s ' % (PATH.SUBMIT+'/'+'output.log')
+ '-V '
+ ' -- ' + findpath('seisflows.system') +'/'+ 'wrappers/submit '
+ PATH.OUTPUT)
def export_kernels(self, path):
unix.cd(self.kernel_databases)
# work around conflicting name conventions
files = []
files += glob('*proc??????_alpha_kernel.bin')
files += glob('*proc??????_alpha[hv]_kernel.bin')
files += glob('*proc??????_reg1_alpha_kernel.bin')
files += glob('*proc??????_reg1_alpha[hv]_kernel.bin')
unix.rename('alpha', 'vp', files)
files = []
files += glob('*proc??????_beta_kernel.bin')
files += glob('*proc??????_beta[hv]_kernel.bin')
files += glob('*proc??????_reg1_beta_kernel.bin')
files += glob('*proc??????_reg1_beta[hv]_kernel.bin')
unix.rename('beta', 'vs', files)
# hack to deal with problems on parallel filesystem
unix.mkdir(join(path, 'kernels'), noexit=True)
unix.mkdir(join(path, 'kernels', basename(self.getpath)))
src = join(glob('*_kernel.bin'))
dst = join(path, 'kernels', basename(self.getpath))
unix.mv(src, dst)
def export_residuals(self, path):
# hack deals with problems on parallel filesystem
unix.mkdir(join(path, 'residuals'), noexit=True)
src = join(self.getpath, 'residuals')
dst = join(path, 'residuals', basename(self.getpath))
unix.mv(src, dst)
def clip(self, path='', parameters=[], minval=-np.inf, maxval=np.inf):
""" Clips kernels by convolving them with a Gaussian. Wrapper over
xclip_sem utility.
"""
assert exists(path)
assert len(parameters) > 0
unix.cd(self.getpath)
for name in self.parameters:
self.mpirun(
PATH.SPECFEM_BIN +'/'+ 'xclip_sem '
+ str(minval) + ' '
+ str(maxval) + ' '
+ name + '_kernel' + ' '
+ path + '/ '
+ path + '/ ')
# move input files
src = path
dst = path + '_noclip'
unix.mkdir(dst)
for name in self.parameters:
unix.mv(glob(src+'/*'+name+'.bin'), dst)
# rename output files
unix.rename('_clip', '', glob(src+'/*'))
def smooth(self, path='', parameters=[], span=0.):
""" Smooths kernels by convolving them with a Gaussian. Wrapper over
xsmooth_sem utility.
"""
assert exists(path)
assert len(parameters) > 0
# apply smoothing operator
unix.cd(self.getpath)
for name in parameters:
print ' smoothing', name
self.mpirun(
PATH.SPECFEM_BIN +'/'+ 'xsmooth_sem '
+ str(span) + ' '
+ str(span) + ' '
+ name + '_kernel' + ' '
+ path + '/ '
+ path + '/ ',
output=self.getpath+'/'+'OUTPUT_FILES/output_smooth_sem.txt')
print ''
# move input files
src = path
dst = path + '_nosmooth'
unix.mkdir(dst)
for name in self.parameters:
unix.mv(glob(src+'/*'+name+'.bin'), dst)
# rename output files
unix.rename('_smooth', '', glob(src+'/*'))
def save(self,
dict,
path,
parameters=['vp', 'vs', 'rho'],
prefix='',
suffix=''):
""" Writes SPECFEM model or kernels
INPUT
DICT - ModelDict object containing model
PATH - the directory to which model is saved
PARAMETERS - list of material parameters to be loaded
PREFIX - optional filename prefix
SUFFIX - optional filename suffix, eg '_kernel'
"""
unix.mkdir(path)
# fill in any missing parameters
missing_keys = diff(parameters, dict.keys())
for iproc in range(self.mesh_properties.nproc):
for key in missing_keys:
dict[key] += self.io.read_slice(PATH.MODEL_INIT,
prefix + key + suffix, iproc)
# write slices to disk
for iproc in range(self.mesh_properties.nproc):
for key in parameters:
self.io.write_slice(dict[key][iproc], path,
prefix + key + suffix, iproc)
def submit(self, workflow):
"""Submits job
"""
unix.mkdir(PATH.OUTPUT)
unix.cd(PATH.OUTPUT)
# save current state
self.checkpoint()
# construct resource list
nodes = PAR.NTASK / PAR.NODESIZE
cores = PAR.NTASK % PAR.NODESIZE
hours = PAR.WALLTIME / 60
minutes = PAR.WALLTIME % 60
resources = 'walltime=%02d:%02d:00 ' % (hours, minutes)
if nodes == 0:
resources += ',nodes=1:ppn=%d' % cores
elif cores == 0:
resources += ',nodes=%d:ppn=16' % nodes
else:
resources += ',nodes=%d:ppn=16+1:ppn=%d' % (nodes, cores)
# construct arguments list
unix.run('qsub ' + '-N %s ' % PAR.TITLE + '-o %s ' %
(PATH.SUBMIT + '/' + 'output.log') + '-l %s ' % resources +
'-j %s ' % 'oe' + findpath('system') + '/' +
'pbs/wrapper_qsub ' + PATH.OUTPUT,
shell=True)
def setup(self):
""" Sets up nonlinear optimization machinery
"""
unix.mkdir(PATH.OPTIMIZE)
# prepare output writers
self.writer = Writer(path=PATH.OUTPUT)
self.stepwriter = StepWriter(path=PATH.SUBMIT)
# prepare algorithm machinery
if PAR.SCHEME in ["NLCG"]:
self.NLCG = NLCG(path=PATH.OPTIMIZE, maxiter=PAR.NLCGMAX, thresh=PAR.NLCGTHRESH, precond=self.precond)
elif PAR.SCHEME in ["LBFGS"]:
self.LBFGS = LBFGS(
path=PATH.OPTIMIZE,
memory=PAR.LBFGSMEM,
maxiter=PAR.LBFGSMAX,
thresh=PAR.LBFGSTHRESH,
precond=self.precond,
)
# write initial model
if exists(PATH.MODEL_INIT):
src = PATH.MODEL_INIT
dst = join(PATH.OPTIMIZE, "m_new")
savenpy(dst, solver.merge(solver.load(src)))
def _launch(self, classname, funcname, hosts='all'):
unix.mkdir(PATH.SYSTEM)
with open(PATH.SYSTEM+'/'+'job_id', 'w') as f:
subprocess.call('sbatch '
+ '%s ' % PAR.SLURMARGS
+ '--job-name=%s ' % PAR.TITLE
+ '--nodes=%d ' % math.ceil(PAR.NPROC/float(PAR.NODESIZE))
+ '--ntasks-per-node=%d ' % PAR.NODESIZE
+ '--ntasks=%d ' % PAR.NPROC
+ '--time=%d ' % PAR.STEPTIME
+ self._launch_args(hosts)
+ findpath('seisflows.system') +'/'+ 'wrappers/run '
+ PATH.OUTPUT + ' '
+ classname + ' '
+ funcname + ' ',
shell=1,
stdout=f)
# retrieve job ids
with open(PATH.SYSTEM+'/'+'job_id', 'r') as f:
line = f.readline()
job = line.split()[-1].strip()
if hosts == 'all' and PAR.NTASK > 1:
return [job+'_'+str(ii) for ii in range(PAR.NTASK)]
else:
return [job]
def apply_hessian(self, m, dm, h):
""" Computes the action of the Hessian on a given vector through
solver calls
"""
system = sys.modules['seisflows_system']
solver = sys.modules['seisflows_solver']
postprocess = sys.modules['seisflows_postprocess']
self.save('m_lcg', m + h*dm)
solver.save(solver.split(m + h*dm),
PATH.HESS+'/'+'model')
system.run('optimize', 'apply_hess',
path=PATH.HESS)
postprocess.write_gradient(
path=PATH.HESS)
self.save('g_lcg', solver.merge(solver.load(
PATH.HESS+'/'+'gradient', suffix='_kernel')))
# uncomment for debugging
#if True:
# unix.rm(PATH.HESS+'_debug')
# unix.mv(PATH.HESS, PATH.HESS+'_debug')
# unix.mkdir(PATH.HESS)
unix.rm(PATH.HESS)
unix.mkdir(PATH.HESS)
return self.hessian_product(h)
def save(self, path):
""" Save objects to disk for later reference
"""
unix.mkdir(_full(path))
for name in self.names:
fullfile = join(_full(path), name + '.p')
saveobj(fullfile, sys.modules[name])
def save(self, path, model, prefix='reg1_', suffix=''):
""" writes SPECFEM3D_GLOBE transerverly isotropic model
"""
unix.mkdir(path)
for iproc in range(self.mesh_properties.nproc):
for key in ['vpv', 'vph', 'vsv', 'vsh', 'eta']:
if key in self.parameters:
savebin(model[key][iproc], path, iproc,
prefix + key + suffix)
elif 'kernel' in suffix:
pass
else:
src = PATH.OUTPUT + '/' + 'model_init'
dst = path
copybin(src, dst, iproc, prefix + key + suffix)
if 'rho' in self.parameters:
savebin(model['rho'][iproc], path, iproc,
prefix + 'rho' + suffix)
elif 'kernel' in suffix:
pass
else:
src = PATH.OUTPUT + '/' + 'model_init'
dst = path
copybin(src, dst, iproc, prefix + 'rho' + suffix)
def export_kernels(self, path):
unix.cd(self.kernel_databases)
# work around conflicting name conventions
files = []
files += glob('*proc??????_alpha_kernel.bin')
files += glob('*proc??????_alpha[hv]_kernel.bin')
files += glob('*proc??????_reg1_alpha_kernel.bin')
files += glob('*proc??????_reg1_alpha[hv]_kernel.bin')
unix.rename('alpha', 'vp', files)
files = []
files += glob('*proc??????_beta_kernel.bin')
files += glob('*proc??????_beta[hv]_kernel.bin')
files += glob('*proc??????_reg1_beta_kernel.bin')
files += glob('*proc??????_reg1_beta[hv]_kernel.bin')
unix.rename('beta', 'vs', files)
# hack to deal with problems on parallel filesystem
unix.mkdir(join(path, 'kernels'), noexit=True)
unix.mkdir(join(path, 'kernels', basename(self.getpath)))
src = join(glob('*_kernel.bin'))
dst = join(path, 'kernels', basename(self.getpath))
unix.mv(src, dst)
def save(self, path):
""" Save objects to disk for later reference
"""
unix.mkdir(_full(path))
for name in self.names:
fullfile = join(_full(path), name+'.p')
saveobj(fullfile, sys.modules[name])
def export_traces(self, path, prefix='traces/obs'):
# hack deals with problems on parallel filesystem
unix.mkdir(join(path, 'traces'), noexit=True)
src = join(self.getpath, prefix)
dst = join(path, 'traces', basename(self.getpath))
unix.cp(src, dst)
def export_model(self, path):
if system.getnode() == 0:
for name in self.model_parameters:
src = glob(join(self.databases, '*_' + name + '.bin'))
dst = path
unix.mkdir(dst)
unix.cp(src, dst)
def smooth(self, input_path='', output_path='', parameters=[], span=0.):
""" Smooths kernels by convolving them with a Gaussian. Wrapper over
xsmooth_sem utility.
"""
if not exists(input_path):
raise Exception
if not exists(output_path):
unix.mkdir(output_path)
# apply smoothing operator
unix.cd(self.cwd)
for name in parameters or self.parameters:
print ' smoothing', name
call_solver(system.mpiexec(),
PATH.SPECFEM_BIN + '/' + 'xsmooth_sem ' + str(span) +
' ' + str(span) + ' ' + name + '_kernel' + ' ' +
input_path + '/ ' + output_path + '/ ',
output='/dev/null')
print ''
# rename output files
files = glob(output_path + '/*')
unix.rename('_smooth', '', files)
def _launch(self, classname, funcname, hosts='all'):
unix.mkdir(PATH.SYSTEM)
nodes = math.ceil(PAR.NTASK / float(PAR.NODESIZE))
ncpus = PAR.NPROC
mpiprocs = PAR.NPROC
hours = PAR.STEPTIME / 60
minutes = PAR.STEPTIME % 60
walltime = 'walltime=%02d:%02d:00 ' % (hours, minutes)
# submit job
with open(PATH.SYSTEM + '/' + 'job_id', 'w') as f:
call(
'qsub ' + '%s ' % PAR.PBSARGS +
'-l select=%d:ncpus=%d:mpiprocs=%d ' (nodes, ncpus, mpiprocs) +
'-l %s ' % walltime + '-J 0-%s ' % (PAR.NTASK - 1) +
'-N %s ' % PAR.TITLE + '-o %s ' %
(PATH.SUBMIT + '/' + 'output.pbs/' + '$PBS_ARRAYID') +
'-r y ' + '-j oe ' + '-V ' + self.launch_args(hosts) +
PATH.OUTPUT + ' ' + classname + ' ' + funcname + ' ' +
findpath('seisflows.system'),
stdout=f)
# retrieve job ids
with open(PATH.SYSTEM + '/' + 'job_id', 'r') as f:
line = f.readline()
job = line.split()[-1].strip()
if hosts == 'all' and PAR.NTASK > 1:
nn = range(PAR.NTASK)
job0 = job.strip('[].sdb')
return [job0 + '[' + str(ii) + '].sdb' for ii in nn]
else:
return [job]
def submit(self, workflow):
"""Submits job
"""
unix.mkdir(PATH.OUTPUT)
unix.cd(PATH.OUTPUT)
# save current state
self.checkpoint()
# construct resource list
nodes = int(PAR.NTASK / PAR.NODESIZE)
cores = PAR.NTASK % PAR.NODESIZE
hours = int(PAR.WALLTIME / 60)
minutes = PAR.WALLTIME % 60
resources = 'walltime=%02d:%02d:00'%(hours, minutes)
if nodes == 0:
resources += ',mem=%dgb,nodes=1:ppn=%d'%(PAR.MEMORY, cores)
elif cores == 0:
resources += ',mem=%dgb,nodes=%d:ppn=%d'%(PAR.MEMORY, nodes, PAR.NODESIZE)
else:
resources += ',mem=%dgb,nodes=%d:ppn=%d+1:ppn=%d'%(PAR.MEMORY, nodes, PAR.NODESIZE, cores)
# construct arguments list
unix.run('qsub '
+ '-N %s '%PAR.TITLE
+ '-o %s '%(PATH.SUBMIT +'/'+ 'output.log')
+ '-l %s '%resources
+ '-j %s '%'oe'
+ findpath('system') +'/'+ 'wrappers/submit '
+ '-F %s '%PATH.OUTPUT)
def _launch(self, classname, funcname, hosts='all'):
unix.mkdir(PATH.SYSTEM)
with open(PATH.SYSTEM+'/'+'job_id', 'w') as f:
call('sbatch '
+ '%s ' % PAR.SLURMARGS
+ '--job-name=%s ' % PAR.TITLE
+ '--nodes=%d ' % math.ceil(PAR.NPROC/float(PAR.NODESIZE))
+ '--ntasks-per-node=%d ' % PAR.NODESIZE
+ '--ntasks=%d ' % PAR.NPROC
+ '--time=%d ' % PAR.STEPTIME
+ self._launch_args(hosts)
+ findpath('seisflows.system') +'/'+ 'wrappers/run '
+ PATH.OUTPUT + ' '
+ classname + ' '
+ funcname + ' ',
stdout=f)
# retrieve job ids
with open(PATH.SYSTEM+'/'+'job_id', 'r') as f:
line = f.readline()
job = line.split()[-1].strip()
if hosts == 'all' and PAR.NTASK > 1:
return [job+'_'+str(ii) for ii in range(PAR.NTASK)]
else:
return [job]
def write_gradient(self, path):
""" Reads kernels and writes gradient of objective function
"""
if not exists(path):
unix.mkdir(path)
self.combine_kernels(path, solver.parameters)
self.process_kernels(path, solver.parameters)
def checkpoint(self, path, classname, method, args, kwargs):
""" Writes information to disk so tasks can be executed remotely
"""
argspath = join(path, 'kwargs')
argsfile = join(argspath, classname+'_'+method+'.p')
unix.mkdir(argspath)
saveobj(argsfile, kwargs)
save()
def submit(self, workflow):
""" Submits job
"""
unix.mkdir(PATH.OUTPUT)
unix.cd(PATH.OUTPUT)
self.checkpoint()
workflow.main()
def write_model(self, path='', suffix=''):
""" Writes model in format used by solver
"""
unix.mkdir(path)
src = PATH.OPTIMIZE +'/'+ 'm_' + suffix
dst = path +'/'+ 'model'
parts = solver.split(loadnpy(src))
solver.save(dst, parts)
def clean(self):
""" Cleans directories in which function and gradient evaluations were
carried out
"""
unix.rm(PATH.GRAD)
unix.rm(PATH.FUNC)
unix.mkdir(PATH.GRAD)
unix.mkdir(PATH.FUNC)
def clean_directory(self, path):
""" If dir exists clean otherwise make
"""
if not exists(path):
unix.mkdir(path)
else:
unix.rm(path)
unix.mkdir(path)
def submit(self, *args, **kwargs):
""" Submits job
"""
if not exists(PATH.SCRATCH):
path = '/scratch/gpfs'+'/'+getuser()+'/'+'seisflows'+'/'+str(uuid4())
unix.mkdir(path)
unix.ln(path, PATH.SCRATCH)
super(tiger_lg, self).submit(*args, **kwargs)
def write_model(self, path='', suffix=''):
""" Writes model in format used by solver
"""
unix.mkdir(path)
src = PATH.OPTIMIZE +'/'+ 'm_' + suffix
dst = path +'/'+ 'model'
unix.mkdir(dst)
unix.cp(glob(join(PATH.MODEL, '*.bin')), dst)
solver.split(src, dst, '.bin')
def export_kernels(self, path):
unix.cd(self.kernel_databases)
# work around conflicting name conventions
self.rename_kernels()
src = glob('*_kernel.bin')
dst = join(path, 'kernels', self.source_name)
unix.mkdir(dst)
unix.mv(src, dst)
def clean(self):
isready = self.solver_status()
if isready:
unix.rm(PATH.GRAD)
unix.mv(PATH.FUNC, PATH.GRAD)
unix.mkdir(PATH.FUNC)
unix.rm(PATH.SOLVER)
unix.mv(PATH.SOLVER+'_best', PATH.SOLVER)
else:
super(thrifty_inversion, self).clean()
def clean(self):
# can forward simulations from line search be carried over?
self.update_status()
if self.status==1:
unix.rm(PATH.GRAD)
unix.mv(PATH.FUNC, PATH.GRAD)
unix.mkdir(PATH.FUNC)
else:
super(thrifty_inversion, self).clean()
def setup(cls):
unix.mkdir(cls.path)
unix.cd(cls.path)
optimize.check()
optimize.setup()
unix.cd(cls.path)
m = problem.model_init()
savenpy('m_new',m)
