def setUp(self):
self.nn = 5
ivc = om.IndepVarComp()
ivc.add_output(name='a', shape=(self.nn, 3), units='m')
ivc.add_output(name='b', shape=(2 * self.nn, 2), units='ft')
vmc = om.VectorMagnitudeComp(vec_size=self.nn, units='m')
vmc.add_magnitude('b_mag',
'b',
vec_size=2 * self.nn,
length=2,
units='ft')
model = om.Group()
model.add_subsystem('ivc', subsys=ivc, promotes_outputs=['a', 'b'])
model.add_subsystem('vmc', subsys=vmc)
model.connect('a', 'vmc.a')
model.connect('b', 'vmc.b')
p = self.p = om.Problem(model)
p.setup()
p['a'] = 1.0 + np.random.rand(self.nn, 3)
p['b'] = 1.0 + np.random.rand(2 * self.nn, 2)
p.run_model()
def test(self):
"""
An example demonstrating a trivial use case of MuxComp
"""
import numpy as np
import openmdao.api as om
from openmdao.utils.assert_utils import assert_rel_error
# The number of elements to be muxed
n = 3
# The size of each element to be muxed
m = 100
p = om.Problem()
ivc = om.IndepVarComp()
ivc.add_output(name='x', shape=(m, ), units='m')
ivc.add_output(name='y', shape=(m, ), units='m')
ivc.add_output(name='z', shape=(m, ), units='m')
p.model.add_subsystem(name='ivc',
subsys=ivc,
promotes_outputs=['x', 'y', 'z'])
mux_comp = p.model.add_subsystem(name='mux',
subsys=om.MuxComp(vec_size=n))
mux_comp.add_var('r', shape=(m, ), axis=1, units='m')
p.model.add_subsystem(name='vec_mag_comp',
subsys=om.VectorMagnitudeComp(vec_size=m,
length=n,
in_name='r',
mag_name='r_mag',
units='m'))
p.model.connect('x', 'mux.r_0')
p.model.connect('y', 'mux.r_1')
p.model.connect('z', 'mux.r_2')
p.model.connect('mux.r', 'vec_mag_comp.r')
p.setup()
p['x'] = 1 + np.random.rand(m)
p['y'] = 1 + np.random.rand(m)
p['z'] = 1 + np.random.rand(m)
p.run_model()
# Verify the results against numpy.dot in a for loop.
for i in range(n):
r_i = [p['x'][i], p['y'][i], p['z'][i]]
expected_i = np.sqrt(np.dot(r_i, r_i))
assert_rel_error(self,
p.get_val('vec_mag_comp.r_mag')[i], expected_i)
def test_input_as_output(self):
vmc = om.VectorMagnitudeComp()
with self.assertRaises(NameError) as ctx:
vmc.add_magnitude('a', 'aa')
self.assertEqual(
str(ctx.exception), "<class VectorMagnitudeComp>: 'a' specified as"
" an output, but it has already been defined as an input.")
def test_duplicate_outputs(self):
vmc = om.VectorMagnitudeComp()
with self.assertRaises(NameError) as ctx:
vmc.add_magnitude('a_mag', 'aa')
self.assertEqual(
str(ctx.exception), "<class VectorMagnitudeComp>: "
"Multiple definition of output 'a_mag'.")
def test_multiple(self):
"""
A simple example to compute the magnitude of 3-vectors at at 100 points simultaneously.
"""
import numpy as np
import openmdao.api as om
n = 100
p = om.Problem()
comp = om.VectorMagnitudeComp(vec_size=n,
length=3,
in_name='r',
mag_name='r_mag',
units='km')
comp.add_magnitude(vec_size=n,
length=3,
in_name='b',
mag_name='b_mag',
units='ft')
p.model.add_subsystem(name='vec_mag_comp',
subsys=comp,
promotes_inputs=['r', 'b'])
p.setup()
p.set_val('r', 1.0 + np.random.rand(n, 3))
p.set_val('b', 1.0 + np.random.rand(n, 3))
p.run_model()
# Verify the results against numpy.dot in a for loop.
expected_r = []
expected_b = []
for i in range(n):
a_i = p.get_val('r')[i, :]
expected_r.append(np.sqrt(np.dot(a_i, a_i)))
actual_i = p.get_val('vec_mag_comp.r_mag')[i]
rel_error = np.abs(expected_r[i] - actual_i) / actual_i
assert rel_error < 1e-9, f"Relative error: {rel_error}"
b_i = p.get_val('b')[i, :]
expected_b.append(np.sqrt(np.dot(b_i, b_i)))
actual_i = p.get_val('vec_mag_comp.b_mag')[i]
rel_error = np.abs(expected_b[i] - actual_i) / actual_i
assert rel_error < 1e-9, f"Relative error: {rel_error}"
assert_near_equal(p.get_val('vec_mag_comp.r_mag'),
np.array(expected_r))
assert_near_equal(p.get_val('vec_mag_comp.b_mag'),
np.array(expected_b))
def test_units_mismatch(self):
vmc = om.VectorMagnitudeComp()
with self.assertRaises(ValueError) as ctx:
vmc.add_magnitude('a_mag2', 'a', units='ft')
self.assertEqual(
str(ctx.exception), "<class VectorMagnitudeComp>: "
"Conflicting units 'ft' specified for input 'a', "
"which has already been defined with units 'None'.")
def test_length_mismatch(self):
vmc = om.VectorMagnitudeComp()
with self.assertRaises(ValueError) as ctx:
vmc.add_magnitude('a_mag2', 'a', length=5)
self.assertEqual(
str(ctx.exception), "<class VectorMagnitudeComp>: "
"Conflicting length=5 specified for input 'a', "
"which has already been defined with length=1.")
def test_vec_size_mismatch(self):
vmc = om.VectorMagnitudeComp()
with self.assertRaises(ValueError) as ctx:
vmc.add_magnitude('a_mag2', 'a', vec_size=10)
self.assertEqual(
str(ctx.exception), "VectorMagnitudeComp: "
"Conflicting vec_size=10 specified for input 'a', "
"which has already been defined with vec_size=1.")
def test(self):
"""
An example demonstrating a trivial use case of MuxComp
"""
import numpy as np
import openmdao.api as om
# The number of elements to be muxed
n = 3
# The size of each element to be muxed
m = 100
p = om.Problem()
mux_comp = p.model.add_subsystem(name='mux',
subsys=om.MuxComp(vec_size=n))
mux_comp.add_var('r', shape=(m, ), axis=1, units='m')
p.model.add_subsystem(name='vec_mag_comp',
subsys=om.VectorMagnitudeComp(vec_size=m,
length=n,
in_name='r',
mag_name='r_mag',
units='m'))
p.model.connect('mux.r', 'vec_mag_comp.r')
p.setup()
p.set_val('mux.r_0', 1 + np.random.rand(m))
p.set_val('mux.r_1', 1 + np.random.rand(m))
p.set_val('mux.r_2', 1 + np.random.rand(m))
p.run_model()
# Verify the results against numpy.dot in a for loop.
for i in range(n):
r_i = [
p.get_val('mux.r_0')[i],
p.get_val('mux.r_1')[i],
p.get_val('mux.r_2')[i]
]
expected_i = np.sqrt(np.dot(r_i, r_i))
assert_near_equal(p.get_val('vec_mag_comp.r_mag')[i], expected_i)
def test(self):
"""
A simple example to compute the magnitude of 3-vectors at at 100 points simultaneously.
"""
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='pos', shape=(n, 3), units='m')
p.model.add_subsystem(name='ivc', subsys=ivc, promotes_outputs=['pos'])
dp_comp = om.VectorMagnitudeComp(vec_size=n,
length=3,
in_name='r',
mag_name='r_mag',
units='km')
p.model.add_subsystem(name='vec_mag_comp', subsys=dp_comp)
p.model.connect('pos', 'vec_mag_comp.r')
p.setup()
p['pos'] = 1.0 + np.random.rand(n, 3)
p.run_model()
# Verify the results against numpy.dot in a for loop.
for i in range(n):
a_i = p['pos'][i, :]
expected_i = np.sqrt(np.dot(a_i, a_i)) / 1000.0
assert_rel_error(self,
p.get_val('vec_mag_comp.r_mag')[i], expected_i)
def setUp(self):
self.nn = 5
self.p = om.Problem()
ivc = om.IndepVarComp()
ivc.add_output(name='a', shape=(self.nn, 3), units='m')
self.p.model.add_subsystem(name='ivc',
subsys=ivc,
promotes_outputs=['a'])
self.p.model.add_subsystem(name='vec_mag_comp',
subsys=om.VectorMagnitudeComp(vec_size=self.nn, units='m'))
self.p.model.connect('a', 'vec_mag_comp.a')
self.p.setup()
self.p['a'] = 1.0 + np.random.rand(self.nn, 3)
self.p.run_model()
def setup(self):
self.add_subsystem(
'ivc', om.IndepVarComp('a', shape=(5, 3), units='m'))
self.add_subsystem(
'vmc', om.VectorMagnitudeComp(vec_size=5, units='m'))
self.connect('ivc.a', 'vmc.a')
