def setUp(self):
self.n = 5
self.p = om.Problem()
ivc = om.IndepVarComp()
ivc.add_output(name='a', shape=(self.n, 3))
ivc.add_output(name='b', shape=(self.n, 3))
self.p.model.add_subsystem(name='ivc',
subsys=ivc,
promotes_outputs=['a', 'b'])
self.p.model.add_subsystem(name='cross_prod_comp',
subsys=om.CrossProductComp(vec_size=self.n))
self.p.model.connect('a', 'cross_prod_comp.a')
self.p.model.connect('b', 'cross_prod_comp.b')
self.p.setup(force_alloc_complex=True)
self.p['a'] = np.random.rand(self.n, 3)
self.p['b'] = np.random.rand(self.n, 3)
self.p['a'][:, 0] = 2.0
self.p['a'][:, 1] = 3.0
self.p['a'][:, 2] = 4.0
self.p['b'][:, 0] = 5.0
self.p['b'][:, 1] = 6.0
self.p['b'][:, 2] = 7.0
self.p.run_model()
def setUp(self):
self.nn = 5
self.p = om.Problem()
ivc = om.IndepVarComp()
ivc.add_output(name='a', shape=(self.nn, 3), units='ft')
ivc.add_output(name='b', shape=(self.nn, 3), units='lbf')
self.p.model.add_subsystem(name='ivc',
subsys=ivc,
promotes_outputs=['a', 'b'])
self.p.model.add_subsystem(name='cross_prod_comp',
subsys=om.CrossProductComp(vec_size=self.nn,
a_units='m',
b_units='N',
c_units='N*m'))
self.p.model.connect('a', 'cross_prod_comp.a')
self.p.model.connect('b', 'cross_prod_comp.b')
self.p.setup()
self.p['a'] = np.random.rand(self.nn, 3)
self.p['b'] = np.random.rand(self.nn, 3)
self.p.run_model()
def test_multiple(self):
n = 24
p = om.Problem()
cpc = om.CrossProductComp(vec_size=n,
a_name='r',
b_name='F',
c_name='torque',
a_units='m',
b_units='N',
c_units='N*m')
cpc.add_product(vec_size=n,
a_name='r',
b_name='p',
c_name='L',
a_units='m',
b_units='kg*m/s',
c_units='kg*m**2/s')
p.model.add_subsystem(name='cross_prod_comp',
subsys=cpc,
promotes_inputs=['r', 'F', 'p'])
p.setup()
p.set_val('r', np.random.rand(n, 3))
p.set_val('F', np.random.rand(n, 3))
p.set_val('p', np.random.rand(n, 3))
p.run_model()
# Check the output.
expected_T = []
expected_L = []
for i in range(n):
a_i = p.get_val('r')[i, :]
b_i = p.get_val('F')[i, :]
expected_T.append(np.cross(a_i, b_i))
actual_i = p.get_val('cross_prod_comp.torque')[i]
rel_error = np.abs(expected_T[i] - actual_i) / actual_i
assert np.all(rel_error < 1e-8), f"Relative error: {rel_error}"
b_i = p.get_val('p')[i, :]
expected_L.append(np.cross(a_i, b_i))
actual_i = p.get_val('cross_prod_comp.L')[i]
rel_error = np.abs(expected_L[i] - actual_i) / actual_i
assert np.all(rel_error < 1e-8), f"Relative error: {rel_error}"
assert_near_equal(p.get_val('cross_prod_comp.torque'),
np.array(expected_T),
tolerance=1e-8)
assert_near_equal(p.get_val('cross_prod_comp.L'),
np.array(expected_L),
tolerance=1e-8)
def test_output_as_input_b(self):
cpc = om.CrossProductComp()
with self.assertRaises(NameError) as ctx:
cpc.add_product('z', 'a', 'c')
self.assertEqual(
str(ctx.exception), "CrossProductComp: 'c' specified as "
"an input, but it has already been defined as an output.")
def test_duplicate_outputs(self):
cpc = om.CrossProductComp()
with self.assertRaises(NameError) as ctx:
cpc.add_product('c')
self.assertEqual(
str(ctx.exception), "CrossProductComp: "
"Multiple definition of output 'c'.")
def test_b_units_mismatch(self):
cpc = om.CrossProductComp()
with self.assertRaises(ValueError) as ctx:
cpc.add_product('z', 'a', 'b', b_units='ft')
self.assertEqual(
str(ctx.exception), "CrossProductComp: "
"Conflicting units 'ft' specified for input 'b', "
"which has already been defined with units 'None'.")
def test_b_vec_size_mismatch(self):
cpc = om.CrossProductComp()
with self.assertRaises(ValueError) as ctx:
cpc.add_product('z', 'x', 'b', vec_size=10)
self.assertEqual(
str(ctx.exception), "CrossProductComp: "
"Conflicting vec_size=10 specified for input 'b', "
"which has already been defined with vec_size=1.")
def test_a_vec_size_mismatch(self):
cpc = om.CrossProductComp(vec_size=7)
with self.assertRaises(ValueError) as ctx:
cpc.add_product('z', 'a', 'y', vec_size=42)
self.assertEqual(
str(ctx.exception), "<class CrossProductComp>: "
"Conflicting vec_size=42 specified for input 'a', "
"which has already been defined with vec_size=7.")
def setup(self):
ivc = om.IndepVarComp()
ivc.add_output(name='a', shape=(5, 3), units='ft')
ivc.add_output(name='b', shape=(5, 3), units='lbf')
cpc = om.CrossProductComp(vec_size=5,
a_units='m',
b_units='N',
c_units='N*m')
self.add_subsystem('ivc', ivc, promotes_outputs=['*'])
self.add_subsystem('cpc', cpc)
self.connect('a', 'cpc.a')
self.connect('b', 'cpc.b')
def test(self):
import numpy as np
import openmdao.api as om
from openmdao.utils.assert_utils import assert_rel_error
n = 100
p = om.Problem()
ivc = om.IndepVarComp()
ivc.add_output(name='r', shape=(n, 3))
ivc.add_output(name='F', shape=(n, 3))
p.model.add_subsystem(name='ivc',
subsys=ivc,
promotes_outputs=['r', 'F'])
p.model.add_subsystem(name='cross_prod_comp',
subsys=om.CrossProductComp(vec_size=n,
a_name='r',
b_name='F',
c_name='torque',
a_units='m',
b_units='N',
c_units='N*m'))
p.model.connect('r', 'cross_prod_comp.r')
p.model.connect('F', 'cross_prod_comp.F')
p.setup()
p['r'] = np.random.rand(n, 3)
p['F'] = np.random.rand(n, 3)
p.run_model()
# Check the output in units of ft*lbf to ensure that our units work as expected.
for i in range(n):
a_i = p['r'][i, :]
b_i = p['F'][i, :]
expected_i = np.cross(a_i, b_i) * 0.73756215
assert_rel_error(self,
p.get_val('cross_prod_comp.torque',
units='ft*lbf')[i, :],
expected_i,
tolerance=1.0E-8)
def setUp(self):
self.nn = 5
ivc = om.IndepVarComp()
ivc.add_output(name='a', shape=(self.nn, 3), units='ft')
ivc.add_output(name='b', shape=(self.nn, 3), units='lbf')
ivc.add_output(name='x', shape=(self.nn, 3), units='ft')
ivc.add_output(name='y', shape=(self.nn, 3), units='lbf')
cpc = om.CrossProductComp(vec_size=self.nn,
a_units='m',
b_units='N',
c_units='N*m')
cpc.add_product('z',
a_name='x',
b_name='y',
vec_size=self.nn,
a_units='m',
b_units='N',
c_units='N*m')
model = om.Group()
model.add_subsystem('ivc',
subsys=ivc,
promotes_outputs=['a', 'b', 'x', 'y'])
model.add_subsystem('cross_prod_comp', subsys=cpc)
model.connect('a', 'cross_prod_comp.a')
model.connect('b', 'cross_prod_comp.b')
model.connect('x', 'cross_prod_comp.x')
model.connect('y', 'cross_prod_comp.y')
p = self.p = om.Problem(model)
p.setup()
p['a'] = np.random.rand(self.nn, 3)
p['b'] = np.random.rand(self.nn, 3)
p.run_model()
def test(self):
import numpy as np
import openmdao.api as om
n = 24
p = om.Problem()
p.model.add_subsystem(name='cross_prod_comp',
subsys=om.CrossProductComp(vec_size=n,
a_name='r',
b_name='F',
c_name='torque',
a_units='m',
b_units='N',
c_units='N*m'),
promotes_inputs=['r', 'F'])
p.setup()
p.set_val('r', np.random.rand(n, 3))
p.set_val('F', np.random.rand(n, 3))
p.run_model()
# Check the output in units of ft*lbf to ensure that our units work as expected.
expected = []
for i in range(n):
a_i = p.get_val('r')[i, :]
b_i = p.get_val('F')[i, :]
expected.append(np.cross(a_i, b_i) * 0.73756215)
actual_i = p.get_val('cross_prod_comp.torque', units='ft*lbf')[i]
rel_error = np.abs(expected[i] - actual_i) / actual_i
assert np.all(rel_error < 1e-8), f"Relative error: {rel_error}"
assert_near_equal(p.get_val('cross_prod_comp.torque', units='ft*lbf'),
np.array(expected),
tolerance=1e-8)
