def createFields(self):
fields = []
for name, dims in zip(self.names, self.dimensions):
phi = np.zeros((self.mesh.nInternalCells, dims[0]), config.precision)
fields.append(IOField(name, phi, dims, self.mesh.defaultBoundary))
self.fields = fields
for phi in self.fields:
phi.completeField()
self.firstRun = False
return fields
def run(self, checkpointData, primalData):
mesh = self.mesh
result, firstCheckpoint = checkpointData
(timeSteps,) = primalData
sensTimeSeries = []
energyTimeSeries = []
startTime = timeSteps[nSteps - firstCheckpoint*writeInterval][0]
if (firstCheckpoint > 0) or self.forceReadFields:
fields = self.readFields(startTime)
for phi in fields:
phi.field *= mesh.volumes
else:
fields = self.fields
pprint('STARTING ADJOINT')
pprint('Number of steps:', nSteps)
pprint('Write interval:', writeInterval)
pprint()
perturbations = []
for index in range(0, len(perturb)):
perturbation = perturb[index](None, mesh, 0)
if isinstance(perturbation, tuple):
perturbation = list(perturbation)
if not isinstance(perturbation, list):# or (len(parameters) == 1 and len(perturbation) > 1):
perturbation = [perturbation]
# complex parameter perturbation not supported
perturbations.append(perturbation)
totalCheckpoints = nSteps//writeInterval
nCheckpoints = min(firstCheckpoint + runCheckpoints, totalCheckpoints)
checkpoint = firstCheckpoint
while checkpoint < nCheckpoints:
pprint('PRIMAL FORWARD RUN {0}/{1}: {2} Steps\n'.format(checkpoint, totalCheckpoints, writeInterval))
primalIndex = nSteps - (checkpoint + 1)*writeInterval
t = timeSteps[primalIndex, 0]
dts = timeSteps[primalIndex:primalIndex+writeInterval+1, 1]
solutions = primal.run(startTime=t, dt=dts, nSteps=writeInterval, mode='forward', reportInterval=reportInterval)
pprint('ADJOINT BACKWARD RUN {0}/{1}: {2} Steps\n'.format(checkpoint, totalCheckpoints, writeInterval))
pprint('Time marching for', ' '.join(self.names))
if checkpoint == 0:
t, _ = timeSteps[-1]
if primal.dynamicMesh:
lastMesh, lastSolution = solutions[-1]
mesh.boundary = lastMesh.boundarydata[m:].reshape(-1,1)
else:
lastSolution = solutions[-1]
fieldsCopy = [phi.copy() for phi in fields]
for phi in fields:
phi.field /= mesh.volumes
self.writeFields(fields, t, skipProcessor=True)
fields = fieldsCopy
primal.updateSource(source(solutions[-1], mesh, 0))
pprint('Time step', writeInterval)
for phi in fields:
phi.info()
#energyTimeSeries.append(getAdjointEnergy(primal, *fields))
inputs = [phi.field for phi in fields + solutions[-1]] + mesh.getTensor() + mesh.getScalar()
energyTimeSeries.append(self.computeEnergy(*inputs))
pprint()
for step in range(0, writeInterval):
report = ((step + 1) % reportInterval) == 0
sample = ((step + 1) % sampleInterval) == 0
viscous = ((step + 1) % viscousInterval) == 0
adjointIndex = writeInterval-1 - step
t, dt = timeSteps[primalIndex + adjointIndex]
if primal.dynamicMesh:
previousMesh, previousSolution = solutions[adjointIndex]
# new mesh boundary
mesh.boundary = previousMesh.boundary
else:
previousSolution = solutions[adjointIndex]
pprint('Time step', adjointIndex)
if report:
pprint('Time marching for', ' '.join(self.names))
start = time.time()
#for index in range(0, n):
# fields[index].field *= mesh.volumes
dtca = np.zeros((1, 1)).astype(config.precision)
obja = np.ones((1, 1)).astype(config.precision)
if self.homogeneousAdjoint:
obja *= 0.
inputs = [phi.field for phi in previousSolution] + \
[np.array([[dt]], config.precision)] + \
mesh.getTensor() + mesh.getScalar() + \
[x[1] for x in primal.sourceTerms] + \
primal.getBoundaryTensor(1) + \
[x[1] for x in primal.extraArgs] + \
[phi.field for phi in fields] + \
[dtca, obja] + \
[np.array([[self.scaling]], config.precision)]
options = {'return_static': sample,
'zero_static': sample,
'return_reusable': report,
'replace_reusable': False,
}
start10 = time.time()
if self.viscosityType and not matop_python and viscous:
outputs = self.viscousMap(*inputs, **options)
else:
outputs = self.map(*inputs, **options)
pprint(time.time()-start10)
#print(sum([(1e-3*phi).sum() for phi in gradient]))
#inp1 = inputs[:3] + inputs[-3:-1]
#inp2 = [phi + 1e-3 for phi in inputs[:3]] + inputs[-3:-1]
#x1 = primal.map(*inp1)[-2]
#x2 = primal.map(*inp2)[-2]
#print(x1, x2, x1-x2)
#import pdb;pdb.set_trace()
# gradients
n = len(fields)
gradient = outputs[:n]
for index in range(0, n):
fields[index].field = gradient[index]
#fields[index].field = gradient[index]/mesh.volumes
if matop_python:
stackedFields = np.concatenate([phi.field/mesh.volumes for phi in fields], axis=1)
stackedFields = np.ascontiguousarray(stackedFields)
inputs = previousSolution + [self.scaling]
kwargs = {'visc': self.viscosityType, 'scale': self.viscosityScaler, 'report':report}
weight = interp.centralOld(getAdjointViscosity(*inputs, **kwargs), mesh)
stackedPhi = Field('a', stackedFields, (5,))
stackedPhi.old = stackedFields
newStackedFields = (matop_petsc.ddt(stackedPhi, dt) - matop_petsc.laplacian(stackedPhi, weight, correction=False)).solve()
#newStackedFields = stackedFields/(1 + weight*dt)
newFields = [newStackedFields[:,[0]],
newStackedFields[:,[1,2,3]],
newStackedFields[:,[4]]
]
fields = self.getFields(newFields, IOField)
for phi in fields:
phi.field = np.ascontiguousarray(phi.field)*mesh.volumes
#print([type(x) for x in outputs])
if sample:
paramGradient = list(outputs[n:n + self.nParams])
# compute sensitivity using adjoint solution
sensitivities = []
for index, perturbation in enumerate(perturbations):
# make efficient cpu implementation
#sensitivity = 0.
#for derivative, delphi in zip(paramGradient, perturbation):
# sensitivity += np.sum(derivative * delphi)
sensitivity = cmesh.computeSensitivity(paramGradient, perturbation)
sensitivities.append(sensitivity)
sensitivities = parallel.sum(sensitivities, allreduce=False)
if (nSteps - (primalIndex + adjointIndex)) > avgStart:
for index in range(0, len(perturb)):
result[index] += sensitivities[index]
sensitivities = [sens/sampleInterval for sens in sensitivities]
for i in range(0, sampleInterval):
sensTimeSeries.append(sensitivities)
if report:
for phi in fields:
phi.info()
#energyTimeSeries.append(getAdjointEnergy(primal, *fields))
inputs = [phi.field for phi in fields + previousSolution] + mesh.getTensor() + mesh.getScalar()
energyTimeSeries.append(self.computeEnergy(*inputs))
#print(self.computeEnergy(*inputs), getSymmetrizedAdjointEnergy(primal, *inputs[:6]))
end = time.time()
pprint('Time for adjoint iteration: {0}'.format(end-start))
pprint('Time since beginning:', end-config.runtime)
pprint('Simulation Time and step: {0}, {1}'.format(*timeSteps[primalIndex + adjointIndex + 1]))
pprint()
#parallel.mpi.Barrier()
self.writeStatusFile([checkpoint + 1, result])
#energyTimeSeries = mpi.gather(timeSeries, root=0)
if parallel.rank == 0:
with open(self.sensTimeSeriesFile, 'ab') as f:
np.savetxt(f, sensTimeSeries)
with open(self.energyTimeSeriesFile, 'ab') as f:
np.savetxt(f, energyTimeSeries)
sensTimeSeries = []
energyTimeSeries = []
checkpoint += 1
#exit(1)
#print(fields[0].field.max())
fieldsCopy = [phi.copy() for phi in fields]
for phi in fields:
phi.field /= mesh.volumes
self.writeFields(fields, t, skipProcessor=True)
fields = fieldsCopy
# write M_2norm
if write_M_2norm:
with IOField.handle(t):
IOField('M_2norm', outputs[-1], (1,)).write()
#for phi in fields:
# phi.field /= mesh.volumes
#self.writeFields(fields, t, skipProcessor=True)
#for phi in fields:
# phi.field *= mesh.volumes
#print(fields[0].field.max())
#pprint(checkpoint, totalCheckpoints)
if checkpoint >= totalCheckpoints:
writeResult('adjoint', result, str(self.scaling), self.sensTimeSeriesFile)
#for index in range(0, nPerturb):
# writeResult('adjoint', result[index], '{} {}'.format(index, self.scaling))
self.removeStatusFile()
return
def test_field_io(case, hdf5):
config.hdf5 = hdf5
mesh = Mesh.create(case)
Field.setMesh(mesh)
time = 1.0
field = np.random.rand(mesh.nInternalCells, 3)
boundary = copy.deepcopy(mesh.defaultBoundary)
nFaces = mesh.getPatchFaceRange('inlet')[2]
boundary['inlet'] = {
'type':'CBC_TOTAL_PT',
'pt': 'uniform 20',
'value': np.random.rand(nFaces, 3)
}
U = IOField('U', field, (3,), boundary)
U.partialComplete()
field = np.random.rand(mesh.nInternalCells, 1)
boundary = copy.deepcopy(mesh.defaultBoundary)
T = IOField('T', field, (1,), boundary)
boundary['outlet'] = {
'type':'fixedValue',
'value': 'uniform 10'
}
with IOField.handle(time):
U.write()
T.write()
with IOField.handle(time):
#!/usr/bin/python2
import sys, os
import numpy as np
from adFVM import config
from adFVM.field import Field, IOField
from adFVM.mesh import Mesh
case = sys.argv[1]
time1, time2 = sys.argv[2:4]
mesh = Mesh.create(case)
Field.setMesh(mesh)
fields = ['p', 'T', 'U']
fieldsRef = [2e5, 300, 100]
for name, ref in zip(fields, fieldsRef):
with IOField.handle(float(time1)):
phi = IOField.read(name)
phi.partialComplete()
with IOField.handle(float(time2)):
mid = np.array([-0.02, 0.01, 0.005])
G = 1e0 * np.exp(-3e3 * np.linalg.norm(
mid - mesh.cellCentres[:mesh.nInternalCells], axis=1, keepdims=1)**
2)
phi.field[:mesh.nInternalCells] = G * ref
phi = IOField(name, phi.field, phi.dimensions, phi.boundary)
phi.write()
for patchID in mesh1.boundary:
startFace, endFace, indices1 = getPatchInfo(mesh1, patchID)
centres1 = mesh1.faceCentres[startFace:endFace]
startFace, endFace, indices2 = getPatchInfo(mesh2, patchID)
centres2 = mesh2.faceCentres[startFace:endFace]
patchIndices[patchID] = mapNearest(centres1, centres2)
#for field in mesh1.getFields(time1):
for field in ['U', 'T', 'p', 'rho', 'rhoU', 'rhoE']:
print 'interpolating', field
Field.setMesh(mesh1)
with IOField.handle(time1):
phi1 = IOField.read(field)
phi1.partialComplete()
dims = phi1.dimensions
phi2 = np.zeros((mesh2.nCells, ) + dims)
phi2 = IOField(field, phi2, dims)
phi2.field[:mesh2.nInternalCells] = phi1.field[internalIndices]
for patchID in phi1.boundary:
startFace, endFace, indices1 = getPatchInfo(mesh1, patchID)
startFace, endFace, indices2 = getPatchInfo(mesh2, patchID)
phi2.field[indices2] = phi1.field[indices1][patchIndices[patchID]]
phi2.boundary = copy.deepcopy(phi1.boundary)
Field.setMesh(mesh2)
with IOField.handle(time2):
phi2.write()
print