parameters['PC'] = 'bfgs'
parameters['memory_limit'] = np.inf
parameters['H0inv'] = 'Rinv'
if versiondolfin.split('.')[0] == '2016' and amg == 'petsc_amg':
parameters['avgPC'] = True
else:
parameters['avgPC'] = False
MPI.barrier(mpicommbarrier)
tstart = time.time()
#TODO: nbPDEs not correct (needs to be multiplied by nb sources)
waveobj.inversion(m0,
mt,
parameters,
boundsLS=[[1e-6, 1.0], [1e-3, 1.0]],
myplot=myplotf)
tend = time.time()
Dt = tend - tstart
if PRINT:
print 'Time to solve inverse problem {}'.format(Dt)
minat = at.vector().min()
maxat = at.vector().max()
minbt = bt.vector().min()
maxbt = bt.vector().max()
minct = ct.vector().min()
maxct = ct.vector().max()
mina0 = a0.vector().min()
waveobj.dd = DD
if mpirank == 0:
np.save(outputdirectory + filename + str(freq) + '/dd.npy',
np.array(DD))
waveobj.solvefwd_cost()
if mpirank == 0:
print 'noise misfit={}, regul cost={}, ratio={}'.format(waveobj.cost_misfit, \
waveobj.cost_reg, waveobj.cost_misfit/waveobj.cost_reg)
if PLOT:
plotindex = len(waveobj.solfwd) / 2
myplot.plot_timeseries(waveobj.solfwd[plotindex], 'pd', 0, skip,
dl.Function(V))
# solve inverse problem
if mpirank == 0: print 'Solve inverse problem'
waveobj.inversion(b_target_fn, b_target_fn, mpicomm, myplot=myplot)
if PLOT:
myplot.set_varname('b_MAP')
myplot.plot_vtk(waveobj.PDE.b)
# Save MAP point
fileout = dl.HDF5File(mpicomm, \
outputdirectory + filename + str(freq) + '/MAP.h5', 'w')
fileout.write(waveobj.PDE.b, 'b')
else:
# Load MAP point
fileout = dl.HDF5File(mpicomm, \
outputdirectory + filename + str(freq) + '/MAP.h5', 'r')
binit = dl.Function(Vm)
fileout.read(binit, 'b')
