def test_only_unknowns_recorded(self): prob = Problem() prob.root = ConvergeDiverge() prob.driver.add_recorder(self.recorder) prob.setup(check=False) t0, t1 = run_problem(prob) prob.cleanup() # closes recorders coordinate = ["Driver", (1,)] expected_unknowns = [ ("comp1.y1", 8.0), ("comp1.y2", 6.0), ("comp2.y1", 4.0), ("comp3.y1", 21.0), ("comp4.y1", 46.0), ("comp4.y2", -93.0), ("comp5.y1", 36.8), ("comp6.y1", -46.5), ("comp7.y1", -102.7), ("p.x", 2.0), ] self.assertIterationDataRecorded(((coordinate, (t0, t1), None, expected_unknowns, None),), self.eps)
def test_only_resids_recorded(self): prob = Problem() prob.root = ConvergeDiverge() prob.driver.add_recorder(self.recorder) self.recorder.options["record_params"] = False self.recorder.options["record_unknowns"] = False self.recorder.options["record_resids"] = True prob.setup(check=False) t0, t1 = run_problem(prob) prob.cleanup() # closes recorders coordinate = ["Driver", (1,)] expected_resids = [ ("comp1.y1", 0.0), ("comp1.y2", 0.0), ("comp2.y1", 0.0), ("comp3.y1", 0.0), ("comp4.y1", 0.0), ("comp4.y2", 0.0), ("comp5.y1", 0.0), ("comp6.y1", 0.0), ("comp7.y1", 0.0), ("p.x", 0.0), ] self.assertIterationDataRecorded(((coordinate, (t0, t1), None, None, expected_resids),), self.eps)
def test_only_params_recorded(self): prob = Problem() prob.root = ConvergeDiverge() prob.driver.add_recorder(self.recorder) self.recorder.options["record_params"] = True self.recorder.options["record_resids"] = False self.recorder.options["record_unknowns"] = False prob.setup(check=False) t0, t1 = run_problem(prob) prob.cleanup() # closes recorders coordinate = ["Driver", (1,)] expected_params = [ ("comp1.x1", 2.0), ("comp2.x1", 8.0), ("comp3.x1", 6.0), ("comp4.x1", 4.0), ("comp4.x2", 21.0), ("comp5.x1", 46.0), ("comp6.x1", -93.0), ("comp7.x1", 36.8), ("comp7.x2", -46.5), ] self.assertIterationDataRecorded(((coordinate, (t0, t1), expected_params, None, None),), self.eps)
def test_unconnected_param_access_with_promotes(self): prob = Problem(root=Group()) G1 = prob.root.add('G1', Group()) G2 = G1.add('G2', Group(), promotes=['x']) C1 = G2.add('C1', ExecComp(['y=2.0*x', 'z=x*x-2.0']), promotes=['x']) C2 = G2.add('C2', ExecComp(['y=2.0*x', 'z=x*x-2.0'])) G2.connect('C1.y', 'C2.x') # ignore warning about the unconnected param with warnings.catch_warnings(record=True) as w: warnings.simplefilter("ignore") prob.setup(check=False) prob.run() # still must use absolute naming to find params even if they're # promoted. Promoted names for params can refer to more than one param. C1.params['x'] = 2. self.assertEqual(prob['G1.x'], 2.0) self.assertEqual(prob.root.G1.G2.C1.params['x'], 2.0) prob['G1.x'] = 99. self.assertEqual(C1.params['x'], 99.) prob['G1.x'] = 12. self.assertEqual(C1.params['x'], 12.) prob['G1.x'] = 17. self.assertEqual(prob.root.G1.G2.C1.params['x'], 17.0) prob.run()
def test_includes_and_excludes(self): prob = Problem() prob.root = ConvergeDiverge() prob.driver.add_recorder(self.recorder) self.recorder.options['includes'] = ['comp1.*'] self.recorder.options['excludes'] = ["*.y2"] self.recorder.options['record_params'] = True self.recorder.options['record_resids'] = True prob.setup(check=False) t0, t1 = run_problem(prob) prob.cleanup() # closes recorders coordinate = [0, 'Driver', (1,)] expected_params = [ ("comp1.x1", 2.0) ] expected_unknowns = [ ("comp1.y1", 8.0) ] expected_resids = [ ("comp1.y1", 0.0) ] self.assertIterationDataRecorded(((coordinate, (t0, t1), expected_params, expected_unknowns, expected_resids),), self.eps)
def test_2Darray_write(self): top = Problem() top.root = Group() top.root.add('my_comp', VarComponent()) top.setup(check=False) top.run() sb = Namelist(top.root.my_comp) top['my_comp.arrayvar'] = zeros([3, 2], dtype=numpy_float32) top['my_comp.arrayvar'][0, 1] = 3.7 top['my_comp.arrayvar'][2, 0] = 7.88 sb.set_filename(self.filename) sb.add_group('Test') sb.add_var("arrayvar") sb.generate() f = open(self.filename, 'r') contents = f.read() compare = "\n" + \ "&Test\n" + \ " arrayvar(1,1) = 0.0, 3.700000047683716, \n" + \ "arrayvar(1,2) = 0.0, 0.0, \n" + \ "arrayvar(1,3) = 7.880000114440918, 0.0, \n" + \ "/\n" self.assertEqual(contents, compare)
def test_multilevel_record(self): prob = Problem() prob.root = ExampleGroup() prob.root.G2.G1.nl_solver.add_recorder(self.recorder) prob.driver.add_recorder(self.recorder) self.recorder.options["record_params"] = True self.recorder.options["record_resids"] = True prob.setup(check=False) t0, t1 = run_problem(prob) prob.cleanup() # closes recorders solver_coordinate = ["Driver", (1,), "root", (1,), "G2", (1,), "G1", (1,)] g1_expected_params = [("C2.x", 5.0)] g1_expected_unknowns = [("C2.y", 10.0)] g1_expected_resids = [("C2.y", 0.0)] g1_expected = (g1_expected_params, g1_expected_unknowns, g1_expected_resids) driver_coordinate = ["Driver", (1,)] driver_expected_params = [("G3.C3.x", 10.0)] driver_expected_unknowns = [("G2.C1.x", 5.0), ("G2.G1.C2.y", 10.0), ("G3.C3.y", 20.0), ("G3.C4.y", 40.0)] driver_expected_resids = [("G2.C1.x", 0.0), ("G2.G1.C2.y", 0.0), ("G3.C3.y", 0.0), ("G3.C4.y", 0.0)] expected = [] expected.append((solver_coordinate, (t0, t1), g1_expected_params, g1_expected_unknowns, g1_expected_resids)) expected.append( (driver_coordinate, (t0, t1), driver_expected_params, driver_expected_unknowns, driver_expected_resids) ) self.assertIterationDataRecorded(expected, self.eps)
def test_index_error_messages_con(self): prob = Problem() prob.root = Group() prob.root.fd_options['force_fd'] = True prob.root.ln_solver.options['mode'] = 'auto' prob.root.add('myparams', IndepVarComp('x', np.zeros(4))) prob.root.add('rosen', Rosenbrock(4)) prob.root.connect('myparams.x', 'rosen.x') prob.driver = MySimpleDriver() prob.driver.add_desvar('myparams.x') prob.driver.add_constraint('rosen.xxx', upper=0.0, indices=[4]) prob.setup(check=False) # Make sure we can't do this with self.assertRaises(IndexError) as cm: prob.run() msg = "Index for constraint 'rosen.xxx' is out of bounds. " msg += "Requested index: [4], " msg += "shape: (4,)." raised_error = str(cm.exception) raised_error = raised_error.replace('(4L,', '(4,') self.assertEqual(msg, raised_error)
def test_unsupported_array(self): top = Problem() top.root = Group() top.root.add('my_comp', VarComponent()) top.setup(check=False) top.run() sb = Namelist(top.root.my_comp) top['my_comp.arrayvar'] = zeros([2, 2, 2], dtype=numpy_float32) sb.set_filename(self.filename) sb.add_group('Test') sb.add_var("arrayvar") try: sb.generate() except RuntimeError as err: self.assertEqual(str(err), "Don't know how to handle array of" + \ " 3 dimensions") else: self.fail('RuntimeError expected')
def test_conflicting_connections(self): # verify we get an error if we have conflicting implicit and explicit connections root = Group() # promoting G1.x will create an implicit connection to G3.x # this is a conflict because G3.x (aka G3.C4.x) is already connected # to G3.C3.x G2 = root.add('G2', Group(), promotes=['x']) # BAD PROMOTE G2.add('C1', ParamComp('x', 5.), promotes=['x']) G1 = G2.add('G1', Group(), promotes=['x']) G1.add('C2', ExecComp('y=x*2.0'), promotes=['x']) G3 = root.add('G3', Group(), promotes=['x']) G3.add('C3', ExecComp('y=x*2.0')) G3.add('C4', ExecComp('y=x*2.0'), promotes=['x']) root.connect('G2.G1.C2.y', 'G3.C3.x') G3.connect('C3.y', 'x') prob = Problem(root) try: prob.setup(check=False) except Exception as error: msg = "Target 'G3.C4.x' is connected to multiple unknowns: ['G2.C1.x', 'G3.C3.y']" self.assertEqual(text_type(error), msg) else: self.fail("Error expected")
def test_sublevel_record(self): prob = Problem() prob.root = ExampleGroup() prob.root.G2.G1.nl_solver.add_recorder(self.recorder) self.recorder.options['record_params'] = True self.recorder.options['record_resids'] = True prob.setup(check=False) t0, t1 = run_problem(prob) prob.cleanup() # closes recorders coordinate = [0, 'Driver', (1,), "root", (1,), "G2", (1,), "G1", (1,)] expected_params = [ ("C2.x", 5.0) ] expected_unknowns = [ ("C2.y", 10.0) ] expected_resids = [ ("C2.y", 0.0) ] self.assertIterationDataRecorded(((coordinate, (t0, t1), expected_params, expected_unknowns, expected_resids),), self.eps)
def test_variable_access(self): prob = Problem(root=ExampleGroup()) # set with a different shaped array try: prob['G2.C1.x'] except Exception as err: msg = "'unknowns' has not been initialized, setup() must be called before 'G2.C1.x' can be accessed" self.assertEqual(text_type(err), msg) else: self.fail('Exception expected') prob.setup(check=False) self.assertEqual(prob['G2.C1.x'], 5.) # default output from ParamComp self.assertEqual(prob['G2.G1.C2.y'], 5.5) # output from ExecComp self.assertEqual(prob.root.G3.C3.params['x'], 0.) # initial value for a parameter self.assertEqual(prob.root.G2.G1.C2.params['x'], 0.) # initial value for a parameter prob = Problem(root=ExampleGroupWithPromotes()) prob.setup(check=False) self.assertEqual(prob.root.G2.G1.C2.params['x'], 0.) # initial value for a parameter # __setitem__ prob['G2.G1.C2.y'] = 99. self.assertEqual(prob['G2.G1.C2.y'], 99.)
def test_calc_gradient_multiple_params(self): prob = Problem() prob.root = FanIn() prob.setup(check=False) prob.run() param_list = ['p1.x1', 'p2.x2'] unknown_list = ['comp3.y'] # check that calc_gradient returns proper dict value when mode is 'fwd' J = prob.calc_gradient(param_list, unknown_list, mode='fwd', return_format='dict') np.testing.assert_almost_equal(J['comp3.y']['p2.x2'], np.array([[ 35.]])) np.testing.assert_almost_equal(J['comp3.y']['p1.x1'], np.array([[ -6.]])) # check that calc_gradient returns proper array value when mode is 'fwd' J = prob.calc_gradient(param_list, unknown_list, mode='fwd', return_format='array') np.testing.assert_almost_equal(J, np.array([[-6., 35.]])) # check that calc_gradient returns proper dict value when mode is 'rev' J = prob.calc_gradient(param_list, unknown_list, mode='rev', return_format='dict') np.testing.assert_almost_equal(J['comp3.y']['p2.x2'], np.array([[ 35.]])) np.testing.assert_almost_equal(J['comp3.y']['p1.x1'], np.array([[ -6.]])) # check that calc_gradient returns proper array value when mode is 'rev' J = prob.calc_gradient(param_list, unknown_list, mode='rev', return_format='array') np.testing.assert_almost_equal(J, np.array([[-6., 35.]])) # check that calc_gradient returns proper dict value when mode is 'fd' J = prob.calc_gradient(param_list, unknown_list, mode='fd', return_format='dict') np.testing.assert_almost_equal(J['comp3.y']['p2.x2'], np.array([[ 35.]])) np.testing.assert_almost_equal(J['comp3.y']['p1.x1'], np.array([[ -6.]])) # check that calc_gradient returns proper array value when mode is 'fd' J = prob.calc_gradient(param_list, unknown_list, mode='fd', return_format='array') np.testing.assert_almost_equal(J, np.array([[-6., 35.]]))
def test_byobj_run(self): prob = Problem(root=ExampleByObjGroup()) prob.setup(check=False) prob.run() self.assertEqual(prob['G3.C4.y'], 'fooC2C3C4')
def test_basic_run(self): prob = Problem(root=ExampleGroup()) prob.setup(check=False) prob.run() self.assertAlmostEqual(prob['G3.C4.y'], 40.)
def test_mode_auto(self): # Make sure mode=auto chooses correctly for all prob sizes as well # as for abs/rel/etc paths prob = Problem() root = prob.root = Group() root.add('p1', ParamComp('a', 1.0), promotes=['*']) root.add('p2', ParamComp('b', 1.0), promotes=['*']) root.add('comp', ExecComp(['x = 2.0*a + 3.0*b', 'y=4.0*a - 1.0*b']), promotes=['*']) root.ln_solver.options['mode'] = 'auto' prob.setup(check=False) prob.run() mode = prob._mode('auto', ['a'], ['x']) self.assertEqual(mode, 'fwd') mode = prob._mode('auto', ['a', 'b'], ['x']) self.assertEqual(mode, 'rev') # make sure _check function does it too #try: #mode = prob._check_for_matrix_matrix(['a'], ['x']) #except Exception as err: #msg = "Group '' must have the same mode as root to use Matrix Matrix." #self.assertEqual(text_type(err), msg) #else: #self.fail('Exception expected') root.ln_solver.options['mode'] = 'fwd' mode = prob._check_for_matrix_matrix(['a', 'b'], ['x']) self.assertEqual(mode, 'fwd')
def test_fd_skip_keys(self): prob = Problem() root = prob.root = Group() comp = Component() comp.add_param('x', 0.) comp.add_param('y', 0.) comp.add_output('z', 0.) comp.solve_nonlinear = lambda p, u, r: u.__setitem__('z', 1.) comp._get_fd_params = lambda: ['x'] comp.jacobian = lambda a,b,c: {('z', 'x'): 0.} root.add('comp', comp, promotes=['x', 'y']) root.add('px', ParamComp('x', 0.), promotes=['*']) root.add('py', ParamComp('y', 0.), promotes=['*']) prob.setup(check=False) prob.run() try: prob.check_partial_derivatives() except KeyError as err: self.fail('KeyError raised: {0}'.format(str(err)))
def test_conflicting_promotions(self): # verify we get an error if we have conflicting promotions root = Group() # promoting G1.x will create an implicit connection to G3.x # this is a conflict because G3.x (aka G3.C4.x) is already connected # to G3.C3.x G2 = root.add('G2', Group()) G2.add('C1', ParamComp('x', 5.), promotes=['x']) G1 = G2.add('G1', Group(), promotes=['x']) G1.add('C2', ExecComp('y=x*2.0'), promotes=['x']) G3 = root.add('G3', Group(), promotes=['x']) G3.add('C3', ExecComp('y=x*2.0'), promotes=['y']) # promoting y G3.add('C4', ExecComp('y=x*2.0'), promotes=['x', 'y']) # promoting y again.. BAD prob = Problem(root) try: prob.setup(check=False) except Exception as error: msg = "Promoted name 'G3.y' matches multiple unknowns: ['G3.C3.y', 'G3.C4.y']" self.assertEqual(text_type(error), msg) else: self.fail("Error expected")
def test_driver_records_metadata(self): size = 3 prob = Problem(Group(), impl=impl) G1 = prob.root.add('G1', ParallelGroup()) G1.add('P1', IndepVarComp('x', np.ones(size, float) * 1.0)) G1.add('P2', IndepVarComp('x', np.ones(size, float) * 2.0)) prob.root.add('C1', ABCDArrayComp(size)) prob.root.connect('G1.P1.x', 'C1.a') prob.root.connect('G1.P2.x', 'C1.b') prob.driver.add_recorder(self.recorder) self.recorder.options['record_metadata'] = True prob.setup(check=False) prob.cleanup() expected = ( list(prob.root.params.iteritems()), list(prob.root.unknowns.iteritems()), list(prob.root.resids.iteritems()), ) self.assertMetadataRecorded(expected)
def test_splitterW(self): g = Group() p = Problem(root=g) comp = g.add('comp', SplitterW()) p.setup(check=False) comp.params['W1_des'] = 1.08 comp.params['MNexit1_des'] = 1.0 comp.params['MNexit2_des'] = 1.0 comp.params['design'] = True comp.params['flow_in:in:W'] = 3.48771299 comp.params['flow_in:in:Tt'] = 630.74523 comp.params['flow_in:in:Pt'] = 0.0271945 comp.params['flow_in:in:Mach'] = 1.0 p.run() self.check(comp) comp.params['design'] = False comp.params['flow_out_1:in:is_super'] = True comp.params['flow_out_2:in:is_super'] = True p.run() self.check(comp) comp.params['flow_in:in:W'] *= 0.95 comp.params['flow_out_1:in:is_super'] = False comp.params['flow_out_2:in:is_super'] = False p.run() TOL = 0.001 assert_rel_error(self, comp.unknowns['flow_out_1:out:Mach'], 0.76922, TOL) assert_rel_error(self, comp.unknowns['flow_out_2:out:Mach'], 0.76922, TOL)
def test_2Darray_read(self): namelist1 = "Testing\n" + \ "$GROUP\n" + \ " arrayvartwod(1,1) = 12, 24, 36\n" + \ " arrayvartwod(1,2) = 33, 66, 99\n" + \ "$END\n" outfile = open(self.filename, 'w') outfile.write(namelist1) outfile.close() top = Problem() top.root = Group() top.root.add('my_comp', VarComponent()) top.setup(check=False) top.run() sb = Namelist(top.root.my_comp) sb.set_filename(self.filename) sb.parse_file() sb.load_model() # Unchanged self.assertEqual(top['my_comp.arrayvartwod'][0][0], 12) self.assertEqual(top['my_comp.arrayvartwod'][1][2], 99)
def test_noncontiguous_idxs(self): # take even input indices in 0 rank and odd ones in 1 rank size = 11 p = Problem(root=Group(), impl=impl) top = p.root top.add("C1", InOutArrayComp(size)) top.add("C2", DistribNoncontiguousComp(size)) top.add("C3", DistribGatherComp(size)) top.connect('C1.outvec', 'C2.invec') top.connect('C2.outvec', 'C3.invec') p.setup(check=False) top.C1.params['invec'] = np.array(range(size), float) p.run() if MPI: if self.comm.rank == 0: self.assertTrue(all(top.C2.unknowns['outvec'] == np.array(list(take_nth(0, 2, range(size))), 'f')*4)) else: self.assertTrue(all(top.C2.unknowns['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(top.C3.unknowns['outvec'] == np.array(full_list, 'f')*4)) else: self.assertTrue(all(top.C2.unknowns['outvec']==top.C1.unknowns['outvec']*2.)) self.assertTrue(all(top.C3.unknowns['outvec']==top.C2.unknowns['outvec']))
def test_model_viewer_has_correct_data_from_problem(self): """ Verify that the correct model structure data exists when stored as compared to the expected structure, using the SellarStateConnection model. """ p = Problem(model=SellarStateConnection()) p.setup(check=False) model_viewer_data = _get_viewer_data(p) # check expected model tree self.assertDictEqual(model_viewer_data['tree'], self.expected_tree) # check expected system pathnames pathnames = model_viewer_data['sys_pathnames_list'] self.assertListEqual(sorted(pathnames), self.expected_pathnames) # check expected connections, after mapping cycle_arrows indices back to pathnames connections = model_viewer_data['connections_list'] for conn in connections: if 'cycle_arrows' in conn: cycle_arrows = [] for src, tgt in conn['cycle_arrows']: cycle_arrows.append(' '.join([pathnames[src], pathnames[tgt]])) conn['cycle_arrows'] = sorted(cycle_arrows) self.assertListEqual(connections, self.expected_conns) # check expected abs2prom map self.assertDictEqual(model_viewer_data['abs2prom'], self.expected_abs2prom)
def test_metadata_recorded(self): prob = Problem(impl=impl) prob.root = FanInGrouped() rec = DumpRecorder(out=self.filename) rec.options["record_metadata"] = True rec.options["includes"] = ["p1.x1", "p2.x2", "comp3.y"] prob.driver.add_recorder(rec) prob.setup(check=False) prob.cleanup() with open(self.expected_filename, "r") as dumpfile: params = iteritems(prob.root.params) unknowns = iteritems(prob.root.unknowns) self.assertEqual("Metadata:\n", dumpfile.readline()) self.assertEqual("Params:\n", dumpfile.readline()) for name, metadata in params: fmat = " {0}: {1}\n".format(name, metadata) self.assertEqual(fmat, dumpfile.readline()) self.assertEqual("Unknowns:\n", dumpfile.readline()) for name, metadata in unknowns: fmat = " {0}: {1}\n".format(name, metadata) self.assertEqual(fmat, dumpfile.readline())
def test_src_indices_error(self): size = 3 group = Group() group.add('P', IndepVarComp('x', numpy.ones(size))) group.add('C1', DistribExecComp(['y=2.0*x'], arr_size=size, x=numpy.zeros(size), y=numpy.zeros(size))) group.add('C2', ExecComp(['z=3.0*y'], y=numpy.zeros(size), z=numpy.zeros(size))) prob = Problem(impl=impl) prob.root = group prob.root.ln_solver = LinearGaussSeidel() prob.root.connect('P.x', 'C1.x') prob.root.connect('C1.y', 'C2.y') prob.driver.add_desvar('P.x') prob.driver.add_objective('C1.y') try: prob.setup(check=False) except Exception as err: self.assertEqual(str(err), "'C1.y' is a distributed variable and may not be used as a " "design var, objective, or constraint.") else: if MPI: # pragma: no cover self.fail("Exception expected")
def test_array2D_index_connection(self): group = Group() group.add('x_param', IndepVarComp('x', np.ones((2, 2))), promotes=['*']) sub = group.add('sub', Group(), promotes=['*']) sub.add('mycomp', ArrayComp2D(), promotes=['x', 'y']) group.add('obj', ExecComp('b = a')) group.connect('y', 'obj.a', src_indices=[3]) prob = Problem() prob.root = group prob.root.ln_solver = LinearGaussSeidel() prob.setup(check=False) prob.run() J = prob.calc_gradient(['x'], ['obj.b'], mode='fwd', return_format='dict') Jbase = prob.root.sub.mycomp._jacobian_cache assert_rel_error(self, Jbase[('y', 'x')][3][0], J['obj.b']['x'][0][0], 1e-8) assert_rel_error(self, Jbase[('y', 'x')][3][1], J['obj.b']['x'][0][1], 1e-8) assert_rel_error(self, Jbase[('y', 'x')][3][2], J['obj.b']['x'][0][2], 1e-8) assert_rel_error(self, Jbase[('y', 'x')][3][3], J['obj.b']['x'][0][3], 1e-8) J = prob.calc_gradient(['x'], ['obj.b'], mode='rev', return_format='dict') Jbase = prob.root.sub.mycomp._jacobian_cache assert_rel_error(self, Jbase[('y', 'x')][3][0], J['obj.b']['x'][0][0], 1e-8) assert_rel_error(self, Jbase[('y', 'x')][3][1], J['obj.b']['x'][0][1], 1e-8) assert_rel_error(self, Jbase[('y', 'x')][3][2], J['obj.b']['x'][0][2], 1e-8) assert_rel_error(self, Jbase[('y', 'x')][3][3], J['obj.b']['x'][0][3], 1e-8)
def test_too_few_procs(self): size = 3 group = Group() group.add('P', IndepVarComp('x', numpy.ones(size))) group.add('C1', DistribExecComp(['y=2.0*x'], arr_size=size, x=numpy.zeros(size), y=numpy.zeros(size))) group.add('C2', ExecComp(['z=3.0*y'], y=numpy.zeros(size), z=numpy.zeros(size))) prob = Problem(impl=impl) prob.root = group prob.root.ln_solver = LinearGaussSeidel() prob.root.connect('P.x', 'C1.x') prob.root.connect('C1.y', 'C2.y') try: prob.setup(check=False) except Exception as err: self.assertEqual(str(err), "This problem was given 1 MPI processes, " "but it requires between 2 and 2.") else: if MPI: # pragma: no cover self.fail("Exception expected")
def test_driver_param_indices_slsqp_force_fd(self): """ Test driver param indices with ScipyOptimizer SLSQP and force_fd=True """ prob = Problem() prob.root = SellarStateConnection() prob.root.fd_options['force_fd'] = True prob.driver = ScipyOptimizer() prob.driver.options['optimizer'] = 'SLSQP' prob.driver.options['tol'] = 1.0e-8 prob.driver.add_desvar('z', low=np.array([-10.0]), high=np.array([10.0]),indices=[0]) prob.driver.add_desvar('x', low=0.0, high=10.0) prob.driver.add_objective('obj') prob.driver.add_constraint('con1', upper=0.0) prob.driver.add_constraint('con2', upper=0.0) #prob.driver.options['disp'] = False prob.setup(check=False) prob['z'][1] = 0.0 prob.run() assert_rel_error(self, prob['z'][0], 1.9776, 1e-3) assert_rel_error(self, prob['z'][1], 0.0, 1e-3) assert_rel_error(self, prob['x'], 0.0, 1e-3)
def test_Sellar_state_SLSQP(self): """ Baseline Sellar test case without specifying indices. """ prob = Problem() prob.root = SellarStateConnection() prob.driver = ScipyOptimizer() prob.driver.options['optimizer'] = 'SLSQP' prob.driver.options['tol'] = 1.0e-8 prob.driver.add_desvar('z', low=np.array([-10.0, 0.0]), high=np.array([10.0, 10.0])) prob.driver.add_desvar('x', low=0.0, high=10.0) prob.driver.add_objective('obj') prob.driver.add_constraint('con1', upper=0.0) prob.driver.add_constraint('con2', upper=0.0) prob.driver.options['disp'] = False prob.setup(check=False) prob.run() assert_rel_error(self, prob['z'][0], 1.9776, 1e-3) assert_rel_error(self, prob['z'][1], 0.0, 1e-3) assert_rel_error(self, prob['x'], 0.0, 1e-3)
def test_read3(self): # Parse a single group in a deck with non-unique group names namelist1 = "Testing\n" + \ "$GROUP\n" + \ " intvar = 99\n" + \ "$END\n" + \ "$GROUP\n" + \ " floatvar = 3.5e-23\n" + \ "$END\n" outfile = open(self.filename, 'w') outfile.write(namelist1) outfile.close() top = Problem() top.root = Group() top.root.add('my_comp', VarComponent()) top.setup(check=False) top.run() sb = Namelist(top.root.my_comp) sb.set_filename(self.filename) sb.parse_file() sb.load_model(single_group=1) # Unchanged self.assertEqual(top['my_comp.intvar'], 333) # Changed self.assertEqual(top['my_comp.floatvar'], 3.5e-23)
def test_simplest_run(self): prob = Problem(root=Group()) root = prob.root root.add('x_param', ParamComp('x', 7.0)) root.add('mycomp', ExecComp('y=x*2.0')) root.connect('x_param.x', 'mycomp.x') prob.setup(check=False) prob.run() result = root.unknowns['mycomp.y'] self.assertAlmostEqual(14.0, result, 3)
def test_fd_params(self): # tests retrieval of a list of any internal params whose source is either # a ParamComp or is outside of the Group prob = Problem(root=ExampleGroup()) prob.setup(check=False) root = prob.root self.assertEqual(root._get_fd_params(), ['G2.G1.C2.x']) self.assertEqual(root.G2._get_fd_params(), ['G1.C2.x']) self.assertEqual(root.G2.G1._get_fd_params(), ['C2.x']) self.assertEqual(root.G3._get_fd_params(), ['C3.x']) self.assertEqual(root.G3.C3._get_fd_params(), ['x']) self.assertEqual(root.G2.G1.C2._get_fd_params(), ['x'])
def test_sellar_state_connection(self): prob = Problem() prob.root = SellarStateConnection() prob.root.nl_solver = Newton() prob.setup(check=False) prob.run() assert_rel_error(self, prob['y1'], 25.58830273, .00001) assert_rel_error(self, prob['state_eq.y2_command'], 12.05848819, .00001) # Make sure we aren't iterating like crazy self.assertLess(prob.root.nl_solver.iter_count, 8)
def test_explicit_connection_errors(self): class A(Component): def __init__(self): super(A, self).__init__() self.add_state('x', 0) class B(Component): def __init__(self): super(B, self).__init__() self.add_param('x', 0) prob = Problem() prob.root = Group() prob.root.add('A', A()) prob.root.add('B', B()) prob.root.connect('A.x', 'B.x') prob.setup(check=False) expected_error_message = ( "Source 'A.y' cannot be connected to target 'B.x': " "'A.y' does not exist.") prob = Problem() prob.root = Group() prob.root.add('A', A()) prob.root.add('B', B()) prob.root.connect('A.y', 'B.x') with self.assertRaises(ConnectError) as cm: prob.setup(check=False) self.assertEqual(str(cm.exception), expected_error_message) expected_error_message = ( "Source 'A.x' cannot be connected to target 'B.y': " "'B.y' does not exist.") prob = Problem() prob.root = Group() prob.root.add('A', A()) prob.root.add('B', B()) prob.root.connect('A.x', 'B.y') with self.assertRaises(ConnectError) as cm: prob.setup(check=False) self.assertEqual(str(cm.exception), expected_error_message) expected_error_message = ( "Source 'A.x' cannot be connected to target 'A.x': " "Target must be a parameter but 'A.x' is an unknown.") prob = Problem() prob.root = Group() prob.root.add('A', A()) prob.root.add('B', B()) prob.root.connect('A.x', 'A.x') with self.assertRaises(ConnectError) as cm: prob.setup(check=False) self.assertEqual(str(cm.exception), expected_error_message)
def test_sellar_derivs(self): prob = Problem() prob.root = SellarDerivatives() prob.root.nl_solver = Newton() prob.setup(check=False) prob.run() assert_rel_error(self, prob['y1'], 25.58830273, .00001) assert_rel_error(self, prob['y2'], 12.05848819, .00001) # Make sure we aren't iterating like crazy self.assertLess(prob.root.nl_solver.iter_count, 8)
def test_subsolver_records_metadata(self): prob = Problem() prob.root = ExampleGroup() prob.root.G2.G1.nl_solver.add_recorder(self.recorder) self.recorder.options['record_metadata'] = True prob.setup(check=False) prob.cleanup() # closes recorders expected_params = list(iteritems(prob.root.params)) expected_unknowns = list(iteritems(prob.root.unknowns)) expected_resids = list(iteritems(prob.root.resids)) self.assertMetadataRecorded( (expected_params, expected_unknowns, expected_resids))
def test_solver_record(self): prob = Problem() prob.root = ConvergeDiverge() prob.root.nl_solver.add_recorder(self.recorder) self.recorder.options['record_params'] = True self.recorder.options['record_resids'] = True prob.setup(check=False) t0, t1 = run_problem(prob) prob.cleanup() # closes recorders coordinate = [0, 'Driver', (1,), "root", (1,)] expected_params = [ ("comp1.x1", 2.0), ("comp2.x1", 8.0), ("comp3.x1", 6.0), ("comp4.x1", 4.0), ("comp4.x2", 21.0), ("comp5.x1", 46.0), ("comp6.x1", -93.0), ("comp7.x1", 36.8), ("comp7.x2", -46.5) ] expected_unknowns = [ ("comp1.y1", 8.0), ("comp1.y2", 6.0), ("comp2.y1", 4.0), ("comp3.y1", 21.0), ("comp4.y1", 46.0), ("comp4.y2", -93.0), ("comp5.y1", 36.8), ("comp6.y1", -46.5), ("comp7.y1", -102.7), ("p.x", 2.0) ] expected_resids = [ ("comp1.y1", 0.0), ("comp1.y2", 0.0), ("comp2.y1", 0.0), ("comp3.y1", 0.0), ("comp4.y1", 0.0), ("comp4.y2", 0.0), ("comp5.y1", 0.0), ("comp6.y1", 0.0), ("comp7.y1", 0.0), ("p.x", 0.0) ] self.assertIterationDataRecorded(((coordinate, (t0, t1), expected_params, expected_unknowns, expected_resids),), self.eps)
def test_solver_debug_print(self, name, solver): p = Problem() model = p.model model.add_subsystem('ground', IndepVarComp('V', 0., units='V')) model.add_subsystem('source', IndepVarComp('I', 0.1, units='A')) model.add_subsystem('circuit', Circuit()) model.connect('source.I', 'circuit.I_in') model.connect('ground.V', 'circuit.Vg') p.setup() nl = model.circuit.nonlinear_solver = solver() nl.options['debug_print'] = True # suppress solver output for test nl.options['iprint'] = model.circuit.linear_solver.options['iprint'] = -1 # For Broydensolver, don't calc Jacobian try: nl.options['compute_jacobian'] = False except KeyError: pass # set some poor initial guesses so that we don't converge p['circuit.n1.V'] = 10. p['circuit.n2.V'] = 1e-3 opts = {} # formatting has changed in numpy 1.14 and beyond. if LooseVersion(np.__version__) >= LooseVersion("1.14"): opts["legacy"] = '1.13' with printoptions(**opts): # run the model and check for expected output file output = run_model(p) expected_output = '\n'.join([ self.expected_data, "Inputs and outputs at start of iteration " "have been saved to '%s'.\n" % self.filename ]) self.assertEqual(output, expected_output) with open(self.filename, 'r') as f: self.assertEqual(f.read(), self.expected_data)
def test_fd_unknowns(self): # tests retrieval of a list of any internal unknowns with ParamComp # variables filtered out. prob = Problem(root=ExampleGroup()) prob.setup(check=False) root = prob.root self.assertEqual(root._get_fd_unknowns(), ['G2.G1.C2.y', 'G3.C3.y', 'G3.C4.y']) self.assertEqual(root.G2._get_fd_unknowns(), ['G1.C2.y']) self.assertEqual(root.G2.G1._get_fd_unknowns(), ['C2.y']) self.assertEqual(root.G3._get_fd_unknowns(), ['C3.y', 'C4.y']) self.assertEqual(root.G3.C3._get_fd_unknowns(), ['y']) self.assertEqual(root.G2.G1.C2._get_fd_unknowns(), ['y'])
def test_sellar_group(self): prob = Problem() prob.root = SellarDerivativesGrouped() prob.root.nl_solver = NLGaussSeidel() prob.root.nl_solver.options['atol'] = 1e-9 prob.root.mda.nl_solver.options['atol'] = 1e-3 prob.root.nl_solver.options[ 'iprint'] = 1 # so that print_norm is in coverage prob.setup(check=False) prob.run() assert_rel_error(self, prob['y1'], 25.58830273, .00001) assert_rel_error(self, prob['y2'], 12.05848819, .00001)
def test_invalid_unit(self): prob = Problem() prob.root = Group() prob.root.add( 'uc', UnitComp(shape=1, param_name='in', out_name='out', units='junk')) prob.root.add('pc', ParamComp('x', 0., units='ft')) prob.root.connect('pc.x', 'uc.in') with self.assertRaises(ValueError) as cm: prob.setup(check=False) expected_msg = "no unit named 'junk' is defined" self.assertEqual(expected_msg, str(cm.exception))
def test_incompatible_units(self): prob = Problem() prob.root = Group() prob.root.add( 'uc', UnitComp(shape=1, param_name='in', out_name='out', units='degC')) prob.root.add('pc', ParamComp('x', 0., units='ft')) prob.root.connect('pc.x', 'uc.in') with self.assertRaises(TypeError) as cm: prob.setup(check=False) expected_msg = "Unit 'ft' in source 'pc.x' is incompatible with unit 'degC' in target 'uc.in'." self.assertEqual(expected_msg, str(cm.exception))
def test_model_viewer_has_correct_data_from_problem(self): """ Verify that the correct model structure data exists when stored as compared to the expected structure, using the SellarStateConnection model. """ p = Problem() p.model = SellarStateConnection() p.setup(check=False) model_viewer_data = _get_viewer_data(p) self.assertDictEqual(model_viewer_data['tree'], self.expected_tree) self.assertListEqual(model_viewer_data['connections_list'], self.expected_conns) self.assertDictEqual(model_viewer_data['abs2prom'], self.expected_abs2prom)
def test_input_input_explicit_conns_no_conn(self): prob = Problem(root=Group()) root = prob.root root.add('p1', ParamComp('x', 1.0)) root.add('c1', ExecComp('y = x*2.0')) root.add('c2', ExecComp('y = x*3.0')) root.connect('c1.x', 'c2.x') # ignore warning about the unconnected params with warnings.catch_warnings(record=True) as w: warnings.simplefilter("ignore") prob.setup(check=False) prob.run() self.assertEqual(root.connections, {})
def test_auto_order2(self): # this tests the auto ordering when we have a cycle that is the full graph. p = Problem(root=Group()) root = p.root C1 = root.add("C1", ExecComp('y=x*2.0')) C2 = root.add("C2", ExecComp('y=x*2.0')) C3 = root.add("C3", ExecComp('y=x*2.0')) root.connect('C1.y', 'C3.x') root.connect('C3.y', 'C2.x') root.connect('C2.y', 'C1.x') p.setup(check=False) self.assertEqual(p.root.list_auto_order(), ['C1', 'C3', 'C2'])
def test_direct_solver_comp(self): """ Test the direct solver on a component. """ for jac in ['dict', 'coo', 'csr', 'csc', 'dense']: prob = Problem(model=ImplComp4Test()) prob.model.nonlinear_solver = NewtonSolver() prob.model.linear_solver = DirectSolver() prob.set_solver_print(level=0) if jac == 'dict': pass elif jac == 'csr': prob.model.jacobian = CSRJacobian() elif jac == 'csc': prob.model.jacobian = CSCJacobian() elif jac == 'coo': prob.model.jacobian = COOJacobian() elif jac == 'dense': prob.model.jacobian = DenseJacobian() prob.setup(check=False) if jac == 'coo': with self.assertRaises(Exception) as context: prob.run_model() self.assertEqual( str(context.exception), "Direct solver is not compatible with matrix type COOMatrix in system ''." ) continue prob.run_model() assert_rel_error(self, prob['y'], [-1., 1.]) d_inputs, d_outputs, d_residuals = prob.model.get_linear_vectors() d_residuals.set_const(2.0) d_outputs.set_const(0.0) prob.model.run_solve_linear(['linear'], 'fwd') result = d_outputs.get_data() assert_rel_error(self, result, [-2., 2.]) d_outputs.set_const(2.0) d_residuals.set_const(0.0) prob.model.run_solve_linear(['linear'], 'rev') result = d_residuals.get_data() assert_rel_error(self, result, [2., -2.])
def test_multilevel_record(self): prob = Problem() prob.root = ExampleGroup() prob.root.G2.G1.nl_solver.add_recorder(self.recorder) prob.driver.add_recorder(self.recorder) self.recorder.options['record_params'] = True self.recorder.options['record_resids'] = True prob.setup(check=False) t0, t1 = run_problem(prob) self.recorder.close() solver_coordinate = ['Driver', (1,), "root", (1,), "G2", (1,), "G1", (1,)] g1_expected_params = [ ("C2.x", 5.0) ] g1_expected_unknowns = [ ("C2.y", 10.0) ] g1_expected_resids = [ ("C2.y", 0.0) ] driver_coordinate = ['Driver', (1,)] driver_expected_params = [ ("G3.C3.x", 10.0) ] driver_expected_unknowns = [ ("G2.C1.x", 5.0), ("G2.G1.C2.y", 10.0), ("G3.C3.y", 20.0), ("G3.C4.y", 40.0), ] driver_expected_resids = [ ("G2.C1.x", 0.0), ("G2.G1.C2.y", 0.0), ("G3.C3.y", 0.0), ("G3.C4.y", 0.0), ] expected = [] expected.append((solver_coordinate, (t0, t1), g1_expected_params, g1_expected_unknowns, g1_expected_resids)) expected.append((driver_coordinate, (t0, t1), driver_expected_params, driver_expected_unknowns, driver_expected_resids)) self.assertIterationDataRecorded(expected, self.eps)
def test_implicit_component(self, m): self.setup_endpoints(m) from openmdao.core.tests.test_impl_comp import QuadraticLinearize, QuadraticJacVec group = Group() group.add_subsystem('comp1', IndepVarComp([('a', 1.0), ('b', 1.0), ('c', 1.0)])) group.add_subsystem('comp2', QuadraticLinearize()) group.add_subsystem('comp3', QuadraticJacVec()) group.connect('comp1.a', 'comp2.a') group.connect('comp1.b', 'comp2.b') group.connect('comp1.c', 'comp2.c') group.connect('comp1.a', 'comp3.a') group.connect('comp1.b', 'comp3.b') group.connect('comp1.c', 'comp3.c') prob = Problem(model=group) prob.setup(check=False) prob['comp1.a'] = 1. prob['comp1.b'] = -4. prob['comp1.c'] = 3. comp2 = prob.model.comp2 # ImplicitComponent comp2.recording_options['record_metadata'] = False comp2.add_recorder(self.recorder) t0, t1 = run_driver(prob) prob.cleanup() upload(self.filename, self._accepted_token) expected_inputs = [ {'name': 'comp2.a', 'values': [1.0]}, {'name': 'comp2.b', 'values': [-4.0]}, {'name': 'comp2.c', 'values': [3.0]} ] expected_outputs = [{'name': 'comp2.x', 'values': [3.0]}] expected_residuals = [{'name': 'comp2.x', 'values': [0.0]}] system_iteration = json.loads(self.system_iterations) for i in expected_inputs: self.assert_array_close(i, system_iteration['inputs']) for r in expected_residuals: self.assert_array_close(r, system_iteration['residuals']) for o in expected_outputs: self.assert_array_close(o, system_iteration['outputs'])
def test_view_model_from_sqlite(self): """ Test that an n2 html file is generated from a sqlite file. """ p = Problem() p.model = SellarStateConnection() r = SqliteRecorder(self.sqlite_db_filename2) p.driver.add_recorder(r) p.setup(check=False) p.final_setup() r.shutdown() view_model(self.sqlite_db_filename2, outfile=self.sqlite_filename, show_browser=False) # Check that the html file has been created and has something in it. self.assertTrue(os.path.isfile(self.sqlite_html_filename), (self.problem_html_filename + " is not a valid file.")) self.assertGreater(os.path.getsize(self.sqlite_html_filename), 100)
def test_inp_inp_promoted_no_src(self): p = Problem(root=Group()) root = p.root G1 = root.add("G1", Group()) G2 = G1.add("G2", Group()) C1 = G2.add("C1", ExecComp('y=x*2.0')) C2 = G2.add("C2", ExecComp('y=x*2.0')) G3 = root.add("G3", Group()) G4 = G3.add("G4", Group()) C3 = G4.add("C3", ExecComp('y=x*2.0'), promotes=['x']) C4 = G4.add("C4", ExecComp('y=x*2.0'), promotes=['x']) stream = cStringIO() checks = p.setup(out_stream=stream) self.assertEqual(checks['dangling_params'], ['G1.G2.C1.x', 'G1.G2.C2.x', 'G3.G4.x']) self.assertEqual(checks['no_connect_comps'], ['G1.G2.C1', 'G1.G2.C2', 'G3.G4.C3', 'G3.G4.C4']) self.assertEqual(p._dangling['G3.G4.x'], set(['G3.G4.C3.x', 'G3.G4.C4.x'])) # setting promoted name should set both params mapped to that name since the # params are dangling. p['G3.G4.x'] = 999. self.assertEqual(p.root.G3.G4.C3.params['x'], 999.) self.assertEqual(p.root.G3.G4.C4.params['x'], 999.)
def test_simple_matvec(self): group = Group() group.add('x_param', ParamComp('x', 1.0), promotes=['*']) group.add('mycomp', SimpleCompDerivMatVec(), promotes=['x', 'y']) prob = Problem() prob.root = group prob.root.ln_solver = LinearGaussSeidel() prob.setup(check=False) prob.run() J = prob.calc_gradient(['x'], ['y'], mode='fwd', return_format='dict') assert_rel_error(self, J['y']['x'][0][0], 2.0, 1e-6) J = prob.calc_gradient(['x'], ['y'], mode='rev', return_format='dict') assert_rel_error(self, J['y']['x'][0][0], 2.0, 1e-6)
def test_simple_jac(self): group = Group() group.add('x_param', ParamComp('x', 1.0), promotes=['*']) group.add('mycomp', ExecComp(['y=2.0*x']), promotes=['x', 'y']) prob = Problem() prob.root = group prob.root.ln_solver = ScipyGMRES() prob.setup(check=False) prob.run() J = prob.calc_gradient(['x'], ['y'], mode='fwd', return_format='dict') assert_rel_error(self, J['y']['x'][0][0], 2.0, 1e-6) J = prob.calc_gradient(['x'], ['y'], mode='rev', return_format='dict') assert_rel_error(self, J['y']['x'][0][0], 2.0, 1e-6)
def test_too_many_procs(self): prob = Problem(Group(), impl=impl) size = 5 A1 = prob.root.add('A1', ParamComp('a', np.zeros(size, float))) C1 = prob.root.add('C1', ABCDArrayComp(size)) try: prob.setup(check=False) except Exception as err: self.assertEqual( str(err), "This problem was given 2 MPI processes, " "but it requires between 1 and 1.") else: if MPI: self.fail("Exception expected")
def test_solver_record(self): size = 3 prob = Problem(Group(), impl=impl) G1 = prob.root.add('G1', ParallelGroup()) G1.add('P1', IndepVarComp('x', np.ones(size, float) * 1.0)) G1.add('P2', IndepVarComp('x', np.ones(size, float) * 2.0)) prob.root.add('C1', ABCDArrayComp(size)) prob.root.connect('G1.P1.x', 'C1.a') prob.root.connect('G1.P2.x', 'C1.b') prob.root.nl_solver.add_recorder(self.recorder) self.recorder.options['record_params'] = True self.recorder.options['record_resids'] = True prob.setup(check=False) t0, t1 = run(prob) prob.cleanup() if MPI: coord = [MPI.COMM_WORLD.rank, 'Driver', (1, ), "root", (1,)] else: coord = [0, 'Driver', (1, ), "root", (1,)] expected_params = [ ("C1.a", [1.0, 1.0, 1.0]), ("C1.b", [2.0, 2.0, 2.0]), ] expected_unknowns = [ ("G1.P1.x", np.array([1.0, 1.0, 1.0])), ("G1.P2.x", np.array([2.0, 2.0, 2.0])), ("C1.c", np.array([3.0, 3.0, 3.0])), ("C1.d", np.array([-1.0, -1.0, -1.0])), ("C1.out_string", "_C1"), ("C1.out_list", [1.5]), ] expected_resids = [ ("G1.P1.x", np.array([0.0, 0.0, 0.0])), ("G1.P2.x", np.array([0.0, 0.0, 0.0])), ("C1.c", np.array([0.0, 0.0, 0.0])), ("C1.d", np.array([0.0, 0.0, 0.0])), ("C1.out_string", ""), ("C1.out_list", []), ] self.assertIterationDataRecorded(((coord, (t0, t1), expected_params, expected_unknowns, expected_resids),), self.eps, prob.root)
def test_sellar_derivs_grouped(self): prob = Problem() prob.root = SellarDerivativesGrouped() prob.root.ln_solver = LinearGaussSeidel() prob.root.ln_solver.options['maxiter'] = 15 prob.root.mda.nl_solver.options['atol'] = 1e-12 prob.setup(check=False) prob.run() # Just make sure we are at the right answer assert_rel_error(self, prob['y1'], 25.58830273, .00001) assert_rel_error(self, prob['y2'], 12.05848819, .00001) param_list = ['x', 'z'] unknown_list = ['obj', 'con1', 'con2'] Jbase = {} Jbase['con1'] = {} Jbase['con1']['x'] = -0.98061433 Jbase['con1']['z'] = np.array([-9.61002285, -0.78449158]) Jbase['con2'] = {} Jbase['con2']['x'] = 0.09692762 Jbase['con2']['z'] = np.array([1.94989079, 1.0775421 ]) Jbase['obj'] = {} Jbase['obj']['x'] = 2.98061392 Jbase['obj']['z'] = np.array([9.61001155, 1.78448534]) J = prob.calc_gradient(param_list, unknown_list, mode='fwd', return_format='dict') print(J) #for key1, val1 in Jbase.items(): #for key2, val2 in val1.items(): #assert_rel_error(self, J[key1][key2], val2, .00001) J = prob.calc_gradient(param_list, unknown_list, mode='rev', return_format='dict') print(J) #for key1, val1 in Jbase.items(): #for key2, val2 in val1.items(): #assert_rel_error(self, J[key1][key2], val2, .00001) prob.root.fd_options['form'] = 'central' J = prob.calc_gradient(param_list, unknown_list, mode='fd', return_format='dict') print(J) for key1, val1 in Jbase.items(): for key2, val2 in val1.items(): assert_rel_error(self, J[key1][key2], val2, .00001)
def test_record_derivs_lists(self): prob = Problem() prob.root = SellarDerivativesGrouped() prob.driver = ScipyOptimizer() prob.driver.options['optimizer'] = 'SLSQP' prob.driver.options['tol'] = 1.0e-8 prob.driver.options['disp'] = False prob.driver.add_desvar('z', lower=np.array([-10.0, 0.0]), upper=np.array([10.0, 10.0])) prob.driver.add_desvar('x', lower=0.0, upper=10.0) prob.driver.add_objective('obj') prob.driver.add_constraint('con1', upper=0.0) prob.driver.add_constraint('con2', upper=0.0) prob.driver.add_recorder(self.recorder) self.recorder.options['record_metadata'] = False self.recorder.options['record_derivs'] = True prob.setup(check=False) prob.run() prob.cleanup() hdf = h5py.File(self.filename, 'r') deriv_group = hdf['rank0:SLSQP|1']['Derivs'] self.assertEqual(deriv_group.attrs['success'], 1) self.assertEqual(deriv_group.attrs['msg'], '') J1 = deriv_group['Derivatives'] assert_rel_error(self, J1[0][0], 9.61001155, .00001) assert_rel_error(self, J1[0][1], 1.78448534, .00001) assert_rel_error(self, J1[0][2], 2.98061392, .00001) assert_rel_error(self, J1[1][0], -9.61002285, .00001) assert_rel_error(self, J1[1][1], -0.78449158, .00001) assert_rel_error(self, J1[1][2], -0.98061433, .00001) assert_rel_error(self, J1[2][0], 1.94989079, .00001) assert_rel_error(self, J1[2][1], 1.0775421, .00001) assert_rel_error(self, J1[2][2], 0.09692762, .00001) hdf.close()
def test_view_model_set_title(self): """ Test that an n2 html file is generated from a Problem. """ p = Problem() p.model = SellarStateConnection() p.setup() view_model(p, outfile=self.problem_html_filename, show_browser=DEBUG, title="Sellar State Connection") # Check that the html file has been created and has something in it. self.assertTrue(os.path.isfile(self.problem_html_filename), (self.problem_html_filename + " is not a valid file.")) self.assertTrue( 'OpenMDAO Model Hierarchy and N2 diagram: Sellar State Connection' \ in open(self.problem_html_filename).read() )
def test_distrib_idx_in_full_out(self): size = 11 p = Problem(root=Group(), impl=impl) top = p.root top.add("C1", InOutArrayComp(size)) top.add("C2", DistribInputComp(size)) top.connect('C1.outvec', 'C2.invec') p.setup(check=False) top.C1.params['invec'] = np.array(range(size, 0, -1), float) p.run() self.assertTrue( all(top.C2.unknowns['outvec'] == np.array(range(size, 0, -1), float) * 4))
def test_double_diamond_model(self): prob = Problem() prob.root = ConvergeDivergeGroups() prob.setup(check=False) prob.run() data = prob.check_total_derivatives(out_stream=None) for key, val in iteritems(data): assert_rel_error(self, val['abs error'][0], 0.0, 1e-5) assert_rel_error(self, val['abs error'][1], 0.0, 1e-5) assert_rel_error(self, val['abs error'][2], 0.0, 1e-5) assert_rel_error(self, val['rel error'][0], 0.0, 1e-5) assert_rel_error(self, val['rel error'][1], 0.0, 1e-5) assert_rel_error(self, val['rel error'][2], 0.0, 1e-5)
def test_distrib_full_in_out(self): size = 11 p = Problem(root=Group(), impl=impl) top = p.root top.add("C1", InOutArrayComp(size)) top.add("C2", DistribCompSimple(size)) top.connect('C1.outvec', 'C2.invec') p.setup(check=False) top.C1.params['invec'] = np.ones(size, float) * 5.0 p.run() self.assertTrue( all(top.C2.unknowns['outvec'] == np.ones(size, float) * 7.5))