def initialize(self):
# Need to modify this dictionary when we change the SA constants
#import pdb; pdb.set_trace()
#sys.stdout = open(os.devnull, "w")
self.aoptions = aeroOptions
self.woptions = warpOptions
self.ooptions = optOptions
self.uoptions = uqOptions
self.Pr = 0.
self.P = self.uoptions['P']
self.NS0 = self.uoptions['NS0']
# Generate FFD and DVs
if rank == 0:
rank0dvg = pf.createFFD()
else:
rank0dvg = None
self.DVGeo = comm.bcast(rank0dvg, root=0)
# starting flat mesh
meshname = self.aoptions['gridFile']
gridFile = meshname
# flow characteristics
alpha = 0.0
mach = self.ooptions['mach'] #0.95
Re = self.ooptions['Re'] #50000
Re_L = 1.0
temp = 540
arearef = 2.0
chordref = 1.0
# Spalart Allmaras model constants, to be changed in UQ (4 for now)
saconstsm = [0.41, 0.1355, 0.622, 0.66666666667]
self.saconstsb = [7.1, 0.3, 2.0, 1.0, 2.0, 1.2, 0.5, 2.0]
self.saconsts = saconstsm + self.saconstsb
self.aoptions['SAConsts'] = self.saconsts
#self.gridSol = f'{meshname}_{saconstsm}_sol'
solname = self.ooptions['prob_name']
self.gridSol = f'{solname}_sol'
# Get a set of UQ sample points (LHS)
#if self.ooptions['run_once']:
# self.sample = self.uoptions['dist']
#else
# Scatter samples, multi-point parallelism
if self.uoptions['MCTimeBudget']:
self.aps = []
self.solvers = []
self.meshes = []
self.current_samples = self.NS0
if rank == 0:
rank0sam = plate_sa_lhs.genLHS(s=self.current_samples)
else:
rank0sam = None
self.sample = comm.bcast(rank0sam, root=0)
self.cases = divide_cases(self.NS0, size)
# Scatter samples on each level, multi-point parallelism
self.samplep = self.sample[self.cases[rank]]
self.nsp = len(self.cases[rank])
# Create solvers for the preliminary data
for i in range(self.nsp):
namestr = self.gridSol + "_" + str(self.cases[rank][i])
# create meshes
self.meshes.append(
USMesh(options=self.woptions, comm=MPI.COMM_SELF))
# create aeroproblems
self.aps.append(
AeroProblem(name=namestr,
alpha=alpha,
mach=mach,
reynolds=Re,
reynoldsLength=Re_L,
T=temp,
areaRef=arearef,
chordRef=chordref,
evalFuncs=['cd']))
time.sleep(0.1) # this solves a few problems for some reason
# create solvers
self.solvers.append(
ADFLOW(options=self.aoptions, comm=MPI.COMM_SELF))
saconstsm = self.samplep[i].tolist()
self.saconsts = saconstsm + self.saconstsb
self.solvers[i].setOption('SAConsts', self.saconsts)
self.solvers[i].setDVGeo(self.DVGeo)
self.solvers[i].setMesh(self.meshes[i])
print("what up %i", str(rank))
coords = self.solvers[i].getSurfaceCoordinates(
groupName=self.solvers[i].allWallsGroup)
self.solvers[i].DVGeo.addPointSet(coords, 'coords')
# start looping over mesh levels
sumt = 0.
sumtp = 0.
Et = 0.
funcs = {}
a_init = self.DVGeo.getValues()
a_init['pnts'][:] = self.ooptions['DVInit']
dvdict = {'pnts': a_init['pnts']}
for i in range(self.nsp):
saconstsm = self.samplep[i].tolist()
self.saconsts = saconstsm + self.saconstsb
self.solvers[i].setOption('SAConsts', self.saconsts)
self.solvers[i].DVGeo.setDesignVars(dvdict)
self.aps[i].setDesignVars(dvdict)
pc0 = time.process_time()
self.solvers[i](self.aps[i])
self.solvers[i].evalFunctions(self.aps[i], funcs)
pc1 = time.process_time()
astr = self.gridSol + "_" + str(self.cases[rank][i]) + "_cd"
sumtp += (pc1 - pc0)
sumt = comm.allreduce(sumtp)
Et = sumt / self.NS0
self.NS = math.ceil(self.P / Et)
self.Pr = self.NS * Et
else:
self.NS = self.uoptions['NS']
#import pdb; pdb.set_trace()
if rank == 0:
rank0sam = plate_sa_lhs.genLHS(s=self.NS)
else:
rank0sam = None
self.sample = comm.bcast(rank0sam, root=0)
self.cases = divide_cases(self.NS, size)
self.nsp = len(self.cases[rank]) #int(ns/size) # samples per processor
#import pdb; pdb.set_trace()
self.samplep = self.sample[self.cases[
rank]] #self.sample[(rank*self.nsp):(rank*self.nsp+(self.nsp))] #shouldn't really need to "scatter" per se
#import pdb; pdb.set_trace()
#assert len(self.samplep) == self.nsp
# Actually create solvers (and aeroproblems?) (and mesh?) now
self.aps = []
self.solvers = []
self.meshes = []
#self.mesh = USMesh(options=self.woptions, comm=MPI.COMM_SELF)
for i in range(self.nsp):
namestr = self.gridSol + "_" + str(self.cases[rank][i])
# create meshes
self.meshes.append(
USMesh(options=self.woptions, comm=MPI.COMM_SELF))
# create aeroproblems
self.aps.append(
AeroProblem(name=namestr,
alpha=alpha,
mach=mach,
reynolds=Re,
reynoldsLength=Re_L,
T=temp,
areaRef=arearef,
chordRef=chordref,
evalFuncs=['cd']))
time.sleep(0.1) # this solves a few problems for some reason
# create solvers
self.solvers.append(
ADFLOW(options=self.aoptions, comm=MPI.COMM_SELF))
# if not self.ooptions['run_once']:
# saconstsm = self.samplep[i].tolist()
# else:
saconstsm = self.samplep[i].tolist()
self.saconsts = saconstsm + self.saconstsb
self.solvers[i].setOption('SAConsts', self.saconsts)
self.solvers[i].setDVGeo(self.DVGeo)
self.solvers[i].setMesh(self.meshes[i])
print("what up %i", str(rank))
coords = self.solvers[i].getSurfaceCoordinates(
groupName=self.solvers[i].allWallsGroup)
self.solvers[i].DVGeo.addPointSet(coords, 'coords')
# Set constraints, should only need one of those solvers, the meshes are all the same
self.DVCon = DVConstraints()
self.DVCon2 = DVConstraints()
self.DVCon.setDVGeo(self.solvers[0].DVGeo.getFlattenedChildren()[1])
self.DVCon2.setDVGeo(self.solvers[0].DVGeo)
self.DVCon.setSurface(self.solvers[0].getTriangulatedMeshSurface(
groupName='allSurfaces'))
# set extra group for surface area condition
self.DVCon2.setSurface(self.solvers[0].getTriangulatedMeshSurface(),
name='wall')
# DV should be same into page (not doing anything right now)
#import pdb; pdb.set_trace()
lIndex = self.solvers[0].DVGeo.getFlattenedChildren()[1].getLocalIndex(
0)
indSetA = []
indSetB = []
nXc = optOptions['NX']
self.NC = math.trunc(
((1.0 - self.ooptions['DVFraction']) * self.ooptions['NX']))
ind = [
int(nXc / 2) - int(self.NC / 2),
int(nXc / 2) + int(self.NC / 2)
]
for i in range(ind[0], ind[1]):
indSetA.append(lIndex[i, 0, 1])
indSetB.append(lIndex[i, 1, 1])
# for i in range(lIndex.shape[0]):
# indSetA.append(lIndex[i, 0, 1])
# indSetB.append(lIndex[i, 1, 1])
self.DVCon.addLinearConstraintsShape(indSetA,
indSetB,
factorA=1.0,
factorB=-1.0,
lower=0,
upper=0,
name='eqs')
# Thickness constraints (one for each active DV)
#import pdb; pdb.set_trace()
# Maximum thickness of the domain, translates to minimum thickness of bump
ub = 1.0 - self.ooptions['DCMinThick']
tcf = self.ooptions['DCThickFrac']
ra = self.ooptions['bumpBounds']
lim = self.ooptions['DCMinArea']
span = numpy.linspace(0, 1, nXc)
xc = span * (ra[1] - ra[0]) + ra[0]
#ind = range(int(nXc/2) - int(self.NC/2), int(nXc/2) + int(self.NC/2)))
ind = [
int(nXc / 2) - int(tcf * self.NC / 2),
int(nXc / 2) + int(tcf * self.NC / 2)
]
ptList = numpy.zeros([2, 3])
ptList[:, 0] = xc[ind]
ptList[:, 1] = 0.5
ptList[:, 2] = 0.5
if self.ooptions['use_area_con']:
self.DVCon2.addSurfaceAreaConstraint(lower=lim,
upper=10.,
name='sas',
surfaceName='wall')
else:
self.DVCon2.addThicknessConstraints1D(ptList,
self.NC, [0, 0, 1],
lower=0.5,
upper=ub,
name='tcs')
print("excuse me")
dummy = rank
dsum = comm.allgather(dummy)
sys.stdout = sys.__stdout__
def MFMC(self):
# Use an MFMC algorithm to determine optimal sample distribution and coefficients among mesh levels
# We do this once before optimization, then compute statistics with the same set of samples and coeffs at every iteration
# start with initial samples
# Get a set of UQ sample points (LHS), enough for each level at the start
#sys.stdout = open(os.devnull, "w")
# flow characteristics
alpha = 0.0
mach = self.ooptions['mach'] #0.95
Re = self.ooptions['Re'] #50000
Re_L = 1.0
tempR = 540
arearef = 2.0
chordref = 1.0
a_init = self.DVGeo.getValues()
a_init['pnts'][:] = self.ooptions['DVInit']
self.current_samples = self.NS0 * self.Lmax
if rank == 0:
rank0sam = plate_sa_lhs.genLHS(s=self.current_samples)
else:
rank0sam = None
self.sample = comm.bcast(rank0sam, root=0)
N1 = []
a1 = numpy.zeros(self.Lmax)
r1 = numpy.zeros(self.Lmax)
# Scatter samples on each level, multi-point parallelism
for i in range(self.Lmax):
self.cases.append(divide_cases(self.NS0, size))
for j in range(len(self.cases[i])):
for k in range(len(self.cases[i][j])):
self.cases[i][j][k] += i * self.NS0
#self.nsp.append(len(self.cases[i][rank]))#int(ns/size) # samples per processor
self.samplep.append(self.sample[self.cases[i][rank]])
#import pdb; pdb.set_trace()
#self.samplep = self.sample[self.cases[rank]]#self.sample[(rank*self.nsp):(rank*self.nsp+(self.nsp))] #shouldn't really need to "scatter" per se
#import pdb; pdb.set_trace()
# for i in range(self.Lmax):
# assert len(self.samplep[i]) == self.nsp[i]
# Create solvers for the preliminary data
nslp = []
nslt = []
for k in range(self.Lmax):
alist = []
slist = []
mlist = []
nslp.append(len(self.cases[k][rank]))
nslt.append(sum([len(self.cases[k][x]) for x in range(size)]))
for i in range(nslp[k]):
namestr = self.gridSol + "_" + str(self.cases[k][rank][i])
# create meshes
leveloptions = self.woptions
leveloptions['gridFile'] = self.meshnames[self.mord[k]]
#import pdb; pdb.set_trace()
mlist.append(USMesh(options=leveloptions, comm=MPI.COMM_SELF))
# create aeroproblems
aloptions = self.aoptions
aloptions['gridFile'] = self.meshnames[self.mord[k]]
alist.append(
AeroProblem(name=namestr,
alpha=alpha,
mach=mach,
reynolds=Re,
reynoldsLength=Re_L,
T=tempR,
areaRef=arearef,
chordRef=chordref,
evalFuncs=['cd']))
time.sleep(0.1) # this solves a few problems for some reason
# create solvers
slist.append(ADFLOW(options=aloptions, comm=MPI.COMM_SELF))
# if not self.ooptions['run_once']:
# saconstsm = self.samplep[i].tolist()
# else:
saconstsm = self.samplep[0][i].tolist()
self.saconsts = saconstsm + self.saconstsb
slist[i].setOption('SAConsts', self.saconsts)
slist[i].setDVGeo(self.DVGeo)
slist[i].setMesh(mlist[i])
coords = slist[i].getSurfaceCoordinates(
groupName=slist[i].allWallsGroup)
slist[i].DVGeo.addPointSet(coords, 'coords')
self.aps.append(alist)
self.solvers.append(slist)
self.meshes.append(mlist)
# Solve the preliminary samples
# start looping over mesh levels
sumt = []
sumtp = []
nslp = []
nslt = []
sum1 = []
mus = []
sump = []
musp = []
sumpm = []
muspm = []
summ = []
musm = []
Et = numpy.zeros(self.Lmax)
E = numpy.zeros(self.Lmax)
V = numpy.zeros(self.Lmax)
S = numpy.zeros(self.Lmax)
N1 = []
for k in range(self.Lmax):
nslp.append(len(self.cases[k][rank]))
nslt.append(sum([len(self.cases[k][x]) for x in range(size)]))
dvdict = {'pnts': a_init['pnts']}
funcs = {}
sumtp.append(0.0)
sump.append(0.)
musp.append(numpy.zeros(nslp[k]))
sumpm.append(0.)
muspm.append(numpy.zeros(nslp[k]))
for i in range(nslp[k]):
# just do this again in case
saconstsm = self.samplep[0][i].tolist()
self.saconsts = saconstsm + self.saconstsb
self.solvers[k][i].setOption('SAConsts', self.saconsts)
self.solvers[k][i].DVGeo.setDesignVars(dvdict)
self.aps[k][i].setDesignVars(dvdict)
pc0 = time.process_time()
self.solvers[k][i](self.aps[k][i])
self.solvers[k][i].evalFunctions(self.aps[k][i], funcs)
pc1 = time.process_time()
astr = self.gridSol + "_" + str(self.cases[k][rank][i]) + "_cd"
musp[k][i] = funcs[astr]
sump[k] += funcs[astr]
sumtp[k] += (pc1 - pc0)
# compute mean and variance estimate from start up samples
for k in range(self.Lmax):
sumt.append(comm.allreduce(sumtp[k]))
sum1.append(comm.allreduce(sump[k]))
mus.append(comm.allgather(musp[k]))
summ.append(comm.allreduce(sumpm[k]))
musm.append(comm.allgather(muspm[k]))
mus[k] = numpy.concatenate(mus[k][:])
musm[k] = numpy.concatenate(musm[k][:])
#import pdb; pdb.set_trace()
# mean at each level
Et[k] = sumt[k] / nslt[k]
E[k] = (sum1[k]) / nslt[k] #+summ[k]
sum2 = 0.
for i in range(len(mus[k])): #loop over processors
sum2 += (mus[k][i] - E[k])**2
V[k] = sum2 / nslt[k]
S[k] = math.sqrt(V[k])
# compute correlation matrix and rearrange models if necessary
ordered = False
while not ordered:
rho = numpy.corrcoef(mus)
ordered = True # check if contradicted
#tarr = rho[0,1:]
for k in range(self.Lmax - 2):
test = rho[0, 1 + k]**2 - rho[0, 2 + k]**2
if test < 0:
ordered = False
tarr = -rho[0, :]**2
if not ordered:
sind = numpy.argsort(tarr)
#import pdb; pdb.set_trace()
self.mord[:] = [self.mord[i] for i in sind]
E[:] = [E[i] for i in sind]
Et[:] = [Et[i] for i in sind]
V[:] = [V[i] for i in sind]
S[:] = [S[i] for i in sind]
mus[:] = [mus[i] for i in sind]
# now compute N1 and a1 using sigma, rho, w, and p
for k in range(self.Lmax):
a1[k] = S[0] * rho[0, k] / S[k]
if k == 0:
r1[k] = 1
elif k == self.Lmax - 1:
work = Et[0] * (rho[0, k]**2)
work /= Et[k] * (1 - rho[0, 1]**2)
r1[k] = math.sqrt(work)
else:
work = Et[0] * (rho[0, k - 1]**2 - rho[0, k]**2)
work /= Et[k] * (1 - rho[0, 1]**2)
r1[k] = math.sqrt(work)
for k in range(self.Lmax):
N1.append(0)
nsf = self.P / numpy.dot(Et, r1)
N1[0] = math.ceil(nsf)
for k in range(self.Lmax):
nsf = N1[0] * r1[k]
N1[k] = math.ceil(nsf)
# limit the number of samples on the last one to pass the sanity check, for debug
sanity = numpy.dot(N1, Et)
if sanity > 1.2 * self.P:
N1n = (self.P - numpy.dot(N1[0:self.Lmax - 2],
Et[0:self.Lmax - 2])) / Et[self.Lmax - 1]
N1[self.Lmax - 1] = math.ceil(N1n)
self.Pr = numpy.dot(N1, Et)
self.N1 = N1
self.a1 = a1
#import pdb; pdb.set_trace()
if rank == 0:
print("MFMC Completed, Samples per level: ", N1)
def dist_samples(self):
# If we already have the number of samples, just create as many solvers as needed at each level
# Just do this after running MLMC() anyway
# flow characteristics
alpha = 0.0
mach = self.ooptions['mach'] #0.95
Re = self.ooptions['Re'] #50000
Re_L = 1.0
tempR = 540
arearef = 2.0
chordref = 1.0
a_init = self.DVGeo.getValues()
a_init['pnts'][:] = self.ooptions['DVInit']
self.current_samples = sum(self.N1)
if rank == 0:
rank0sam = plate_sa_lhs.genLHS(s=self.current_samples)
else:
rank0sam = None
self.sample = comm.bcast(rank0sam, root=0)
#import pdb; pdb.set_trace()
# Scatter samples on each level, multi-point parallelism
self.cases = []
self.samplep = []
for i in range(self.Lmax):
self.cases.append(divide_cases(self.N1[i], size))
for j in range(len(self.cases[i])):
for k in range(len(self.cases[i][j])):
self.cases[i][j][k] += sum(self.N1[0:i])
#self.nsp.append(len(self.cases[i][rank]))#int(ns/size) # samples per processor
self.samplep.append(self.sample[self.cases[i][rank]])
# Actually create solvers (and aeroproblems?) (and mesh?) now
self.aps = []
self.solvers = []
self.meshes = []
nslp = []
nslt = []
for k in range(self.Lmax):
alist = []
slist = []
mlist = []
nslp.append(len(self.cases[k][rank]))
nslt.append(sum([len(self.cases[k][x]) for x in range(size)]))
for i in range(nslp[k]):
namestr = self.gridSol + "_" + str(self.cases[k][rank][i])
# create meshes
leveloptions = self.woptions
leveloptions['gridFile'] = self.meshnames[self.mord[k]]
mlist.append(USMesh(options=leveloptions, comm=MPI.COMM_SELF))
# create aeroproblems
aloptions = self.aoptions
aloptions['gridFile'] = self.meshnames[self.mord[k]]
alist.append(
AeroProblem(name=namestr,
alpha=alpha,
mach=mach,
reynolds=Re,
reynoldsLength=Re_L,
T=tempR,
areaRef=arearef,
chordRef=chordref,
evalFuncs=['cd']))
time.sleep(0.1) # this solves a few problems for some reason
# create solvers
slist.append(ADFLOW(options=aloptions, comm=MPI.COMM_SELF))
saconstsm = self.samplep[self.Lmax - 1][i].tolist()
self.saconsts = saconstsm + self.saconstsb
slist[i].setOption('SAConsts', self.saconsts)
slist[i].setDVGeo(self.DVGeo)
slist[i].setMesh(mlist[i])
coords = slist[i].getSurfaceCoordinates(
groupName=slist[i].allWallsGroup)
slist[i].DVGeo.addPointSet(coords, 'coords')
self.aps.append(alist)
self.solvers.append(slist)
self.meshes.append(mlist)
def MLMC(self):
# Use an MLMC algorithm to determine an optimal sample distribution between existing mesh levels
# We do this once before optimization, then compute statistics with the same set of samples at every iteration
# start with initial samples
# Get a set of UQ sample points (LHS), enough for each level at the start
#sys.stdout = open(os.devnull, "w")
# flow characteristics
alpha = 0.0
mach = self.ooptions['mach'] #0.95
Re = self.ooptions['Re'] #50000
Re_L = 1.0
tempR = 540
arearef = 2.0
chordref = 1.0
a_init = self.DVGeo.getValues()
a_init['pnts'][:] = self.ooptions['DVInit']
self.current_samples = self.NS0 * self.Lmax
if rank == 0:
rank0sam = plate_sa_lhs.genLHS(s=self.current_samples)
else:
rank0sam = None
self.sample = comm.bcast(rank0sam, root=0)
# Scatter samples on each level, multi-point parallelism
for i in range(self.Lmax):
self.cases.append(divide_cases(self.NS0, size))
for j in range(len(self.cases[i])):
for k in range(len(self.cases[i][j])):
self.cases[i][j][k] += i * self.NS0
#self.nsp.append(len(self.cases[i][rank]))#int(ns/size) # samples per processor
self.samplep.append(self.sample[self.cases[i][rank]])
#import pdb; pdb.set_trace()
#self.samplep = self.sample[self.cases[rank]]#self.sample[(rank*self.nsp):(rank*self.nsp+(self.nsp))] #shouldn't really need to "scatter" per se
#import pdb; pdb.set_trace()
# for i in range(self.Lmax):
# assert len(self.samplep[i]) == self.nsp[i]
# Actually create solvers (and aeroproblems?) (and mesh?) now
nslp = []
nslt = []
for k in range(self.Lmax):
alist = []
slist = []
mlist = []
alist2 = []
slist2 = []
mlist2 = []
nslp.append(len(self.cases[k][rank]))
nslt.append(sum([len(self.cases[k][x]) for x in range(size)]))
for i in range(nslp[k]):
namestr = self.gridSol + "_" + str(self.cases[k][rank][i])
# create meshes
leveloptions = self.woptions
leveloptions['gridFile'] = self.meshnames[k]
mlist.append(USMesh(options=leveloptions, comm=MPI.COMM_SELF))
# create aeroproblems
aloptions = self.aoptions
aloptions['gridFile'] = self.meshnames[k]
alist.append(
AeroProblem(name=namestr,
alpha=alpha,
mach=mach,
reynolds=Re,
reynoldsLength=Re_L,
T=tempR,
areaRef=arearef,
chordRef=chordref,
evalFuncs=['cd']))
time.sleep(0.1) # this solves a few problems for some reason
# create solvers
slist.append(ADFLOW(options=aloptions, comm=MPI.COMM_SELF))
# if not self.ooptions['run_once']:
# saconstsm = self.samplep[i].tolist()
# else:
saconstsm = self.samplep[k][i].tolist()
self.saconsts = saconstsm + self.saconstsb
slist[i].setOption('SAConsts', self.saconsts)
slist[i].setDVGeo(self.DVGeo)
slist[i].setMesh(mlist[i])
coords = slist[i].getSurfaceCoordinates(
groupName=slist[i].allWallsGroup)
slist[i].DVGeo.addPointSet(coords, 'coords')
if k > 0: #create additional solvers at higher levels for the estimators
# create meshes
namestr = self.gridSol + "_" + str(
self.cases[k][rank][i]) + "_m"
leveloptions = self.woptions
leveloptions['gridFile'] = self.meshnames[k - 1]
mlist2.append(
USMesh(options=leveloptions, comm=MPI.COMM_SELF))
# create aeroproblems
aloptions = self.aoptions
aloptions['gridFile'] = self.meshnames[k - 1]
alist2.append(
AeroProblem(name=namestr,
alpha=alpha,
mach=mach,
reynolds=Re,
reynoldsLength=Re_L,
T=tempR,
areaRef=arearef,
chordRef=chordref,
evalFuncs=['cd']))
time.sleep(
0.1) # this solves a few problems for some reason
# create solvers
slist2.append(ADFLOW(options=aloptions,
comm=MPI.COMM_SELF))
slist2[i].setOption('SAConsts', self.saconsts)
slist2[i].setDVGeo(self.DVGeo)
slist2[i].setMesh(mlist2[i])
coords = slist[i].getSurfaceCoordinates(
groupName=slist2[i].allWallsGroup)
slist2[i].DVGeo.addPointSet(coords, 'coords')
self.aps.append(alist)
self.solvers.append(slist)
self.meshes.append(mlist)
if k > 0:
self.aps[k] += alist2
self.solvers[k] += slist2
self.meshes[k] += mlist2
#import pdb; pdb.set_trace()
# start looping over mesh levels
L = 0
M = 4.0 #0.5 #refinement factor?
converged = 0
eps = self.uoptions['vartol']
sum1 = []
mus = []
sump = []
musp = []
sumpm = []
muspm = []
summ = []
musm = []
E = []
V = []
N1 = []
while ~converged & L < self.Lmax:
# compute start up samples to estimate variance
dvdict = {'pnts': a_init['pnts']}
funcs = {}
nslp = []
nslt = []
for k in range(self.Lmax):
nslp.append(len(self.cases[k][rank]))
nslt.append(sum([len(self.cases[k][x]) for x in range(size)]))
sump.append(0.)
musp.append(numpy.zeros(nslp[L]))
sumpm.append(0.)
muspm.append(numpy.zeros(nslp[L]))
for i in range(nslp[L]):
# just do this again in case
saconstsm = self.samplep[L][i].tolist()
self.saconsts = saconstsm + self.saconstsb
self.solvers[L][i].setOption('SAConsts', self.saconsts)
self.solvers[L][i].DVGeo.setDesignVars(dvdict)
self.aps[L][i].setDesignVars(dvdict)
self.solvers[L][i](self.aps[L][i])
self.solvers[L][i].evalFunctions(self.aps[L][i], funcs)
astr = self.gridSol + "_" + str(self.cases[L][rank][i]) + "_cd"
musp[L][i] = funcs[astr]
sump[L] += funcs[astr]
#import pdb; pdb.set_trace()
if L > 0:
self.solvers[L][i + nslp[L]].setOption(
'SAConsts', self.saconsts)
self.solvers[L][i + nslp[L]].DVGeo.setDesignVars(dvdict)
self.aps[L][i + nslp[L]].setDesignVars(dvdict)
self.solvers[L][i + nslp[L]](self.aps[L][i + nslp[L]])
self.solvers[L][i + nslp[L]].evalFunctions(
self.aps[L][i + nslp[L]], funcs)
astr = self.gridSol + "_" + str(
self.cases[L][rank][i]) + "_m_cd"
muspm[L][i] = -funcs[astr]
sumpm[L] += -funcs[astr]
# compute mean and variance estimate from start up samples
sum1.append(comm.allreduce(sump[L]))
mus.append(comm.allgather(musp[L]))
summ.append(comm.allreduce(sumpm[L]))
musm.append(comm.allgather(muspm[L]))
#import pdb; pdb.set_trace()
# mean at each level
E = numpy.zeros(L + 1)
for l in range(L + 1):
E[l] = (sum1[l] + summ[l]) / nslt[l]
# variance at each level
V = numpy.zeros(L + 1)
for l in range(L + 1):
sum2 = 0.
for i in range(len(mus[l])): #range(size):
for j in range(len(mus[l][i])): #range(self.nsp):
if l > 0:
sum2 += ((mus[l][i][j] + musm[l][i][j]) - E[l])**2
else:
sum2 += (mus[l][i][j] - E[l])**2
V[l] = sum2 / nslt[l]
#import pdb; pdb.set_trace()
# now determine the optimal number of samples at each level
N1.append(0.)
worksum = 0
for l in range(L + 1):
worksum += numpy.sqrt(V[l] * (M**l))
for l in range(L + 1):
nlf = 2 * numpy.sqrt(V[l] / (M**l)) * worksum / (eps * eps)
nlfm = max(nslt[l], math.ceil(nlf))
N1[l] = nlfm
# now compute and generate additional samples at each level
# first partition samples NEVERMIND (just do it once at each level, no need to repeat)
# create the extra number of solvers at each (the current) level
# need to loop everything from here on
for l in range(L + 1):
alist = self.aps[l][0:nslp[l]]
slist = self.solvers[l][0:nslp[l]]
mlist = self.meshes[l][0:nslp[l]]
if l > 0:
alist2 = self.aps[l][nslp[l]:]
slist2 = self.solvers[l][nslp[l]:]
mlist2 = self.meshes[l][nslp[l]:]
self.naddedtot[l] = N1[l] - nslt[l]
self.current_samples += self.naddedtot[l]
#import pdb; pdb.set_trace()
if rank == 0:
rank0sam = plate_sa_lhs.genLHS(s=self.current_samples)
else:
rank0sam = None
self.sample = comm.bcast(rank0sam, root=0)
if self.naddedtot[l] > 0:
temp = divide_cases(self.naddedtot[l], size)
for i in range(len(temp)):
for j in range(len(temp[i])):
temp[i][j] += self.current_samples - self.naddedtot[
l] #self.Lmax*self.NS0 + sum(self.naddedtot[0:L])
else:
temp = []
if len(temp):
for ns in range(size):
self.cases[l][ns] += temp[ns] #append
nslpnew = len(self.cases[l][rank])
nsltnew = sum([len(self.cases[l][x]) for x in range(size)])
#self.nsp[L] = len(self.cases[L][rank]) #int(ns/size) # samples per processor
self.samplep[l] = self.sample[self.cases[l][rank]]
for i in range(nslp[l],
nslpnew): #need it to be just the extra cases
#import pdb; pdb.set_trace()
namestr = self.gridSol + "_" + str(self.cases[l][rank][i])
# create meshes
leveloptions = self.woptions
leveloptions['gridFile'] = self.meshnames[l]
mlist.append(
USMesh(options=leveloptions, comm=MPI.COMM_SELF))
# create aeroproblems
aloptions = self.aoptions
aloptions['gridFile'] = self.meshnames[l]
alist.append(
AeroProblem(name=namestr,
alpha=alpha,
mach=mach,
reynolds=Re,
reynoldsLength=Re_L,
T=tempR,
areaRef=arearef,
chordRef=chordref,
evalFuncs=['cd']))
time.sleep(
0.1) # this solves a few problems for some reason
# create solvers
slist.append(ADFLOW(options=aloptions, comm=MPI.COMM_SELF))
saconstsm = self.samplep[l][i].tolist()
self.saconsts = saconstsm + self.saconstsb
slist[i].setOption('SAConsts', self.saconsts)
slist[i].setDVGeo(self.DVGeo)
slist[i].setMesh(mlist[i])
coords = slist[i].getSurfaceCoordinates(
groupName=slist[i].allWallsGroup)
slist[i].DVGeo.addPointSet(coords, 'coords')
time.sleep(0.1)
if l > 0: #create additional solvers at higher levels for the estimators
# create meshes
#import pdb; pdb.set_trace()
namestr = self.gridSol + "_" + str(
self.cases[l][rank][i]) + "_m"
leveloptions = self.woptions
leveloptions['gridFile'] = self.meshnames[l - 1]
mlist2.append(
USMesh(options=leveloptions, comm=MPI.COMM_SELF))
# create aeroproblems
aloptions = self.aoptions
aloptions['gridFile'] = self.meshnames[l - 1]
alist2.append(
AeroProblem(name=namestr,
alpha=alpha,
mach=mach,
reynolds=Re,
reynoldsLength=Re_L,
T=tempR,
areaRef=arearef,
chordRef=chordref,
evalFuncs=['cd']))
time.sleep(
0.1) # this solves a few problems for some reason
# create solvers
slist2.append(
ADFLOW(options=aloptions, comm=MPI.COMM_SELF))
slist2[i].setOption('SAConsts', self.saconsts)
slist2[i].setDVGeo(self.DVGeo)
slist2[i].setMesh(mlist2[i])
coords = slist[i].getSurfaceCoordinates(
groupName=slist2[i].allWallsGroup)
slist2[i].DVGeo.addPointSet(coords, 'coords')
nslp[l] = nslpnew
nslt[l] = nsltnew
self.aps[l] = alist
self.solvers[l] = slist
self.meshes[l] = mlist
if l > 0:
self.aps[l] += alist2
self.solvers[l] += slist2
self.meshes[l] += mlist2
# compute remaining samples
sump[l] = 0
sumpm[l] = 0
musp[l] = numpy.zeros(nslp[l])
muspm[l] = numpy.zeros(nslp[l])
for i in range(nslp[l]):
# just do this again in case
saconstsm = self.samplep[l][i].tolist()
self.saconsts = saconstsm + self.saconstsb
self.solvers[l][i].setOption('SAConsts', self.saconsts)
self.solvers[l][i].DVGeo.setDesignVars(dvdict)
self.aps[l][i].setDesignVars(dvdict)
self.solvers[l][i](self.aps[l][i])
self.solvers[l][i].evalFunctions(self.aps[l][i], funcs)
astr = self.gridSol + "_" + str(
self.cases[l][rank][i]) + "_cd"
musp[l][i] = funcs[astr]
sump[l] += funcs[astr]
#import pdb; pdb.set_trace()
if l > 0:
self.solvers[l][i + nslp[l]].setOption(
'SAConsts', self.saconsts)
self.solvers[l][i +
nslp[l]].DVGeo.setDesignVars(dvdict)
self.aps[l][i + nslp[l]].setDesignVars(dvdict)
self.solvers[l][i + nslp[l]](self.aps[l][i + nslp[l]])
self.solvers[l][i + nslp[l]].evalFunctions(
self.aps[l][i + nslp[l]], funcs)
astr = self.gridSol + "_" + str(
self.cases[l][rank][i]) + "_m_cd"
muspm[l][i] = -funcs[astr]
sumpm[l] += -funcs[astr]
# compute mean and variance estimate from all samples
sum1[l] = comm.allreduce(sump[l])
mus[l] = comm.allgather(musp[l])
summ[l] = comm.allreduce(sumpm[l])
musm[l] = comm.allgather(muspm[l])
# mean at each level
E[l] = (sum1[l] + summ[l]) / nslt[l]
# variance at each level
sum2 = 0.
for i in range(len(mus[l])): #range(size):
for j in range(len(mus[l][i])): #range(self.nsp):
if l > 0:
sum2 += ((mus[l][i][j] + musm[l][i][j]) - E[l])**2
else:
sum2 += (mus[l][i][j] - E[l])**2
V[l] = sum2 / nslt[l]
# if L == 1:
# import pdb; pdb.set_trace()
L += 1
#import pdb; pdb.set_trace()
#sys.stdout = sys.__stdout__
if rank == 0:
print("MLMC Completed, Samples per level: ", N1)
self.N1 = N1