def test_basic_dense_jac(self):
"""Test that output values and total derivatives are correct."""
prob = om.Problem(model=UnitConvGroup(assembled_jac_type='dense'))
prob.model.linear_solver = om.DirectSolver(assemble_jac=True)
# Check the outputs after running to test the unit conversions
prob.setup(check=False, mode='fwd')
prob.run_model()
assert_near_equal(prob['src.x2'], 100.0, 1e-6)
assert_near_equal(prob['tgtF.x3'], 212.0, 1e-6)
assert_near_equal(prob['tgtC.x3'], 100.0, 1e-6)
assert_near_equal(prob['tgtK.x3'], 373.15, 1e-6)
# Check the total derivatives in forward mode
wrt = ['px1.x1']
of = ['tgtF.x3', 'tgtC.x3', 'tgtK.x3']
J = prob.compute_totals(of=of, wrt=wrt, return_format='flat_dict')
assert_near_equal(J['tgtF.x3', 'px1.x1'][0][0], 1.8, 1e-6)
assert_near_equal(J['tgtC.x3', 'px1.x1'][0][0], 1.0, 1e-6)
assert_near_equal(J['tgtK.x3', 'px1.x1'][0][0], 1.0, 1e-6)
# Check the total derivatives in reverse mode
prob.setup(check=False, mode='rev')
prob.run_model()
J = prob.compute_totals(of=of, wrt=wrt, return_format='flat_dict')
assert_near_equal(J['tgtF.x3', 'px1.x1'][0][0], 1.8, 1e-6)
assert_near_equal(J['tgtC.x3', 'px1.x1'][0][0], 1.0, 1e-6)
assert_near_equal(J['tgtK.x3', 'px1.x1'][0][0], 1.0, 1e-6)
def test_basic(self):
"""Test that output values and total derivatives are correct."""
prob = Problem(model=UnitConvGroup())
# Check the outputs after running to test the unit conversions
prob.setup(check=False, mode='fwd')
prob.run_model()
assert_rel_error(self, prob['src.x2'], 100.0, 1e-6)
assert_rel_error(self, prob['tgtF.x3'], 212.0, 1e-6)
assert_rel_error(self, prob['tgtC.x3'], 100.0, 1e-6)
assert_rel_error(self, prob['tgtK.x3'], 373.15, 1e-6)
# Check the total derivatives in forward mode
wrt = ['px1.x1']
of = ['tgtF.x3', 'tgtC.x3', 'tgtK.x3']
J = prob.compute_totals(of=of, wrt=wrt, return_format='flat_dict')
assert_rel_error(self, J['tgtF.x3', 'px1.x1'][0][0], 1.8, 1e-6)
assert_rel_error(self, J['tgtC.x3', 'px1.x1'][0][0], 1.0, 1e-6)
assert_rel_error(self, J['tgtK.x3', 'px1.x1'][0][0], 1.0, 1e-6)
# Check the total derivatives in reverse mode
prob.setup(check=False, mode='rev')
prob.run_model()
J = prob.compute_totals(of=of, wrt=wrt, return_format='flat_dict')
assert_rel_error(self, J['tgtF.x3', 'px1.x1'][0][0], 1.8, 1e-6)
assert_rel_error(self, J['tgtC.x3', 'px1.x1'][0][0], 1.0, 1e-6)
assert_rel_error(self, J['tgtK.x3', 'px1.x1'][0][0], 1.0, 1e-6)
# Make sure check partials handles conversion
data = prob.check_partials()
for key1, val1 in iteritems(data):
for key2, val2 in iteritems(val1):
assert_rel_error(self, val2['abs error'][0], 0.0, 1e-6)
assert_rel_error(self, val2['abs error'][1], 0.0, 1e-6)
assert_rel_error(self, val2['abs error'][2], 0.0, 1e-6)
assert_rel_error(self, val2['rel error'][0], 0.0, 1e-6)
assert_rel_error(self, val2['rel error'][1], 0.0, 1e-6)
assert_rel_error(self, val2['rel error'][2], 0.0, 1e-6)