def test_noncontiguous_idxs(self):
# take even input indices in 0 rank and odd ones in 1 rank
size = 11
p = Problem(model=Group())
top = p.model
C1 = top.add_subsystem("C1", InOutArrayComp(size))
C2 = top.add_subsystem("C2", DistribNoncontiguousComp(size))
C3 = top.add_subsystem("C3", DistribGatherComp(size))
top.connect('C1.outvec', 'C2.invec')
top.connect('C2.outvec', 'C3.invec')
p.setup(check=False)
# Conclude setup but don't run model.
p.final_setup()
C1._inputs['invec'] = np.array(range(size), float)
p.run_model()
if MPI:
if self.comm.rank == 0:
self.assertTrue(all(C2._outputs['outvec'] ==
np.array(list(take_nth(0, 2, range(size))), 'f')*4))
else:
self.assertTrue(all(C2._outputs['outvec'] ==
np.array(list(take_nth(1, 2, range(size))), 'f')*4))
full_list = list(take_nth(0, 2, range(size))) + list(take_nth(1, 2, range(size)))
self.assertTrue(all(C3._outputs['outvec'] == np.array(full_list, 'f')*4))
else:
self.assertTrue(all(C2._outputs['outvec'] == C1._outputs['outvec']*2.))
self.assertTrue(all(C3._outputs['outvec'] == C2._outputs['outvec']))
def test_noncontiguous_idxs(self):
# take even input indices in 0 rank and odd ones in 1 rank
size = 11
p = Problem(model=Group())
top = p.model
C1 = top.add_subsystem("C1", InOutArrayComp(size))
C2 = top.add_subsystem("C2", DistribNoncontiguousComp(size))
C3 = top.add_subsystem("C3", DistribGatherComp(size))
top.connect('C1.outvec', 'C2.invec')
top.connect('C2.outvec', 'C3.invec')
p.setup(check=False)
# Conclude setup but don't run model.
p.final_setup()
C1._inputs['invec'] = np.array(range(size), float)
p.run_model()
if MPI:
if self.comm.rank == 0:
self.assertTrue(all(C2._outputs['outvec'] ==
np.array(list(take_nth(0, 2, range(size))), 'f')*4))
else:
self.assertTrue(all(C2._outputs['outvec'] ==
np.array(list(take_nth(1, 2, range(size))), 'f')*4))
full_list = list(take_nth(0, 2, range(size))) + list(take_nth(1, 2, range(size)))
self.assertTrue(all(C3._outputs['outvec'] == np.array(full_list, 'f')*4))
else:
self.assertTrue(all(C2._outputs['outvec'] == C1._outputs['outvec']*2.))
self.assertTrue(all(C3._outputs['outvec'] == C2._outputs['outvec']))
def setup(self):
comm = self.comm
rank = comm.rank
idxs = list(take_nth(rank, comm.size, range(self.arr_size)))
self.add_input('invec', np.ones(len(idxs), float), src_indices=idxs)
self.add_output('outvec', np.ones(len(idxs), float))
def setup(self):
comm = self.comm
rank = comm.rank
idxs = list(take_nth(rank, comm.size, range(self.arr_size)))
self.add_input('invec', np.ones(len(idxs), float),
src_indices=idxs)
self.add_output('outvec', np.ones(len(idxs), float))
def setup(self):
comm = self.comm
rank = comm.rank
arr_size = self.options['arr_size']
idxs = list(take_nth(rank, comm.size, range(arr_size)))
self.add_input('invec', np.ones(len(idxs), float), distributed=True,
src_indices=idxs)
self.add_output('outvec', np.ones(len(idxs), float), distributed=True)
