size = 5
value = self.comm.rank + 1
values = np.ones(size)*value
A1 = prob.root.add('A1', IndepVarComp('x', values))
C1 = prob.root.add('C1', ABCDArrayComp(size))
prob.root.connect('A1.x', 'C1.a')
prob.root.connect('A1.x', 'C1.b')
prob.setup(check=False)
prob.run()
# check the first output array and store in result
self.assertTrue(all(prob['C1.c'] == np.ones(size)*(value*2)))
result = prob['C1.c']
# gather the results from the separate processes/problems and check
# for expected values
results = self.comm.allgather(result)
self.assertEqual(len(results), self.comm.size)
for n in range(self.comm.size):
expected = np.ones(size)*2*(n+1)
self.assertTrue(all(results[n] == expected))
if __name__ == '__main__':
from openmdao.test.mpi_util import mpirun_tests
mpirun_tests()
def test_parallel_array_comps_fwd(self):
prob = self.prob
prob.root.ln_solver.options['mode'] = 'fwd'
prob.root.par.ln_solver.options['mode'] = 'fwd'
prob.root.par.ser1.ln_solver.options['mode'] = 'fwd'
prob.root.par.ser2.ln_solver.options['mode'] = 'fwd'
prob.setup(check=False)
prob.run()
assert_rel_error(self, prob['total.obj'], 50.0, 1e-6)
def test_parallel_derivs_fwd(self):
prob = self.prob
prob.root.ln_solver.options['mode'] = 'fwd'
prob.root.par.ln_solver.options['mode'] = 'fwd'
prob.root.par.ser1.ln_solver.options['mode'] = 'fwd'
prob.root.par.ser2.ln_solver.options['mode'] = 'fwd'
prob.driver.parallel_derivs(['par.ser1.p1.x', 'par.ser2.p1.x'])
prob.setup(check=False)
prob.run()
assert_rel_error(self, prob['total.obj'], 50.0, 1e-6)
if __name__ == '__main__':
from openmdao.test.mpi_util import mpirun_tests
mpirun_tests()