def test_read_non_distributed_non_scattered_txt(self):
cls = self.__class__
rank = cls.comm.getRank()
nproc = cls.comm.getSize()
if nproc > 1:
mvector_filename = 'in_mvector_read_test_' + str(nproc)
else:
mvector_filename = 'in_mvector_read_test'
file_dir = os.path.dirname(__file__)
filename = 'input.yaml'
problem = Utils.createAlbanyProblem(file_dir + '/' + filename,
cls.parallelEnv)
n_cols = 4
parameter_map = problem.getParameterMap(0)
mvector = Utils.loadMVector(file_dir + '/' + mvector_filename,
n_cols,
parameter_map,
distributedFile=False,
useBinary=False,
readOnRankZero=False)
tol = 1e-8
mvector_target = np.array([1., -1, 3.26, -3.1]) * (rank + 1)
for i in range(0, n_cols):
self.assertTrue(np.abs(mvector[i, 0] - mvector_target[i]) < tol)
def test_all(self):
cls = self.__class__
rank = cls.comm.getRank()
file_dir = os.path.dirname(__file__)
# Create an Albany problem:
filename = 'input_conductivity_dist_paramT.yaml'
problem = Utils.createAlbanyProblem(file_dir+'/'+filename, cls.parallelEnv)
parameter_map = problem.getParameterMap(0)
parameter = Tpetra.MultiVector(parameter_map, 1, dtype="d")
num_elems = parameter_map.getNodeNumElements()
parameter[0, :] = 2.0*np.ones(num_elems)
problem.performSolve()
state_map = problem.getStateMap()
state = Tpetra.MultiVector(state_map, 1, dtype="d")
state[0, :] = problem.getState()
state_ref = Utils.loadMVector('state_ref', 1, state_map, distributedFile=False, useBinary=False, readOnRankZero=True)
stackedTimer = problem.getStackedTimer()
setup_time = stackedTimer.accumulatedTime("PyAlbany: Setup Time")
print("setup_time = " + str(setup_time))
tol = 1.e-8
self.assertTrue(np.linalg.norm(state_ref[0, :] - state[0,:]) < tol)
def test_read_non_distributed_npy(self):
comm = Teuchos.DefaultComm.getComm()
rank = comm.getRank()
nproc = comm.getSize()
if nproc > 1:
mvector_filename = 'in_mvector_read_test_' + str(nproc)
else:
mvector_filename ='in_mvector_read_test'
file_dir = os.path.dirname(__file__)
filename = 'input.yaml'
problem = Utils.createAlbanyProblem(file_dir+'/'+filename)
n_cols = 4
parameter_map = problem.getParameterMap(0)
mvector = Utils.loadMVector(file_dir+'/'+mvector_filename, n_cols, parameter_map, distributedFile = False)
tol = 1e-8
mvector_target = np.array([1., -1, 3.26, -3.1])*(rank+1)
for i in range(0, n_cols):
self.assertTrue(np.abs(mvector[i,0]-mvector_target[i]) < tol)
"PyAlbany: Read multivector directions",
"PyAlbany: Set directions",
"PyAlbany: Perform Solve",
"PyAlbany: Get Reduced Hessian",
"PyAlbany: Write Reduced Hessian",
"PyAlbany: Total"])
timers[6].start()
timers[0].start()
problem = Utils.createAlbanyProblem(filename)
timers[0].stop()
timers[1].start()
n_directions=4
parameter_map = problem.getParameterMap(0)
directions = Utils.loadMVector('random_directions', n_directions, parameter_map, distributedFile = False, useBinary = True)
timers[1].stop()
timers[2].start()
problem.setDirections(parameter_index, directions)
timers[2].stop()
timers[3].start()
problem.performSolve()
timers[3].stop()
timers[4].start()
hessian = problem.getReducedHessian(response_index, parameter_index)
timers[4].stop()
timers[5].start()
def main(parallelEnv):
# This example illustrates how PyAlbany can be used to compute
# reduced Hessian-vector products w.r.t to the basal friction.
comm = parallelEnv.comm
rank = comm.getRank()
nprocs = comm.getSize()
file_dir = os.path.dirname(__file__)
filename = 'input_fo_gis_analysis_beta_smbT.yaml'
parameter_index = 0
response_index = 0
timers = Utils.createTimers([
"PyAlbany: Create Albany Problem",
"PyAlbany: Read multivector directions", "PyAlbany: Set directions",
"PyAlbany: Perform Solve", "PyAlbany: Get Reduced Hessian",
"PyAlbany: Write Reduced Hessian", "PyAlbany: Total"
])
timers[6].start()
timers[0].start()
problem = Utils.createAlbanyProblem(filename, parallelEnv)
timers[0].stop()
timers[1].start()
n_directions = 4
parameter_map = problem.getParameterMap(0)
directions = Utils.loadMVector('random_directions',
n_directions,
parameter_map,
distributedFile=False,
useBinary=True)
timers[1].stop()
timers[2].start()
problem.setDirections(parameter_index, directions)
timers[2].stop()
timers[3].start()
problem.performSolve()
timers[3].stop()
timers[4].start()
hessian = problem.getReducedHessian(response_index, parameter_index)
timers[4].stop()
timers[5].start()
Utils.writeMVector("hessian_nprocs_" + str(nprocs),
hessian,
distributedFile=True,
useBinary=False)
Utils.writeMVector("hessian_all_nprocs_" + str(nprocs),
hessian,
distributedFile=False,
useBinary=False)
timers[5].stop()
print(hessian[0, 0])
print(hessian[1, 0])
print(hessian[2, 0])
print(hessian[3, 0])
timers[6].stop()
Utils.printTimers(timers, "timers_nprocs_" + str(nprocs) + ".txt")
