def setUpClass(cls):
nn = 10
cls.p = Problem(model=Group())
ivc = cls.p.model.add_subsystem('ivc',
IndepVarComp(),
promotes_outputs=['*'])
ivc.add_output('r_e2b_I', val=np.ones((nn, 3)))
ivc.add_output('v_e2b_I', val=np.ones((nn, 3)))
ivc.add_output('a_pert_I', val=np.ones((nn, 3)))
cls.p.model.add_subsystem('rmag_comp',
VectorMagnitudeComp(vec_size=nn,
length=3,
in_name='r_e2b_I',
mag_name='rmag_e2b',
units='km'),
promotes_inputs=['*'],
promotes_outputs=['*'])
cls.p.model.add_subsystem('orbit_eom_comp',
OrbitEOMComp(num_nodes=nn),
promotes_inputs=['*'],
promotes_outputs=['*'])
cls.p.setup(check=True, force_alloc_complex=True)
cls.p['r_e2b_I'] = np.random.rand(nn, 3) * 1000
cls.p['v_e2b_I'] = np.random.rand(nn, 3) * 10
cls.p['a_pert_I'] = np.random.rand(nn, 3)
cls.p.run_model()
def test(self):
"""
An example demonstrating a trivial use case of MuxComp
"""
import numpy as np
from openmdao.api import Problem, Group, IndepVarComp, MuxComp, VectorMagnitudeComp
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 = Problem(model=Group())
ivc = 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=MuxComp(vec_size=n))
mux_comp.add_var('r', shape=(m, ), axis=1, units='m')
p.model.add_subsystem(name='vec_mag_comp',
subsys=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(self):
"""
A simple example to compute the magnitude of 3-vectors at at 100 points simultaneously.
"""
import numpy as np
from openmdao.api import Problem, Group, IndepVarComp, VectorMagnitudeComp
from openmdao.utils.assert_utils import assert_rel_error
n = 100
p = Problem(model=Group())
ivc = IndepVarComp()
ivc.add_output(name='pos', shape=(n, 3), units='m')
p.model.add_subsystem(name='ivc', subsys=ivc, promotes_outputs=['pos'])
dp_comp = 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'] = 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):
nn = self.options['num_nodes']
self.add_subsystem('rmag_comp',
VectorMagnitudeComp(vec_size=nn,
length=3,
in_name='r_e2b_I',
mag_name='rmag_e2b_I',
units='km'),
promotes_inputs=['r_e2b_I'],
promotes_outputs=['rmag_e2b_I'])
self.add_subsystem('grav_pert_comp',
GravityPerturbationsComp(num_nodes=nn),
promotes_inputs=['r_e2b_I', 'rmag_e2b_I'],
promotes_outputs=[('a_pert:J2', 'a_pert_I')])
self.add_subsystem('ori_comp',
ORIComp(num_nodes=nn),
promotes_inputs=['r_e2b_I', 'v_e2b_I'],
promotes_outputs=['O_RI'])
self.add_subsystem('obr_comp',
OBRComp(num_nodes=nn),
promotes_inputs=['Gamma'],
promotes_outputs=['O_BR'])
self.add_subsystem('obi_comp',
OBIComp(num_nodes=nn),
promotes_inputs=['O_BR', 'O_RI'],
promotes_outputs=['O_BI'])
self.add_subsystem(
'orbit_eom_comp',
OrbitEOMComp(num_nodes=nn),
promotes_inputs=['rmag_e2b_I', 'r_e2b_I', 'v_e2b_I', 'a_pert_I'])
def setup(self):
nn = self.options['num_nodes']
lat_gs = self.options['lat_gs']
lon_gs = self.options['lon_gs']
alt_gs = self.options['alt_gs']
self.add_subsystem('ant_quaternion_comp',
CommAntQuaternionComp(num_nodes=nn),
promotes_inputs=['antAngle'],
promotes_outputs=['q_AB'])
self.add_subsystem('ant_rotation_matrix_comp',
CommAntRotationMatrixComp(num_nodes=nn),
promotes_inputs=['q_AB'],
promotes_outputs=['O_AB'])
self.add_subsystem('comm_earth_rotation_quaternion_comp',
CommEarthRotationQuaternionComp(num_nodes=nn,
gha0=0.0),
promotes_inputs=['t'],
promotes_outputs=['q_IE'])
self.add_subsystem('comm_earth_rotation_matrix_comp',
CommEarthRotationMatrixComp(num_nodes=nn),
promotes_inputs=['q_IE'],
promotes_outputs=['O_IE'])
self.add_subsystem('comm_gs_pos_eci_comp',
CommGSPosECIComp(num_nodes=nn,
lat=lat_gs,
lon=lon_gs,
alt=alt_gs),
promotes_inputs=['O_IE'],
promotes_outputs=['r_e2g_I'])
self.add_subsystem('comm_vector_eci_comp',
CommVectorECIComp(num_nodes=nn),
promotes_inputs=['r_e2g_I', 'r_e2b_I'],
promotes_outputs=['r_b2g_I'])
self.add_subsystem('comm_vector_body_comp',
MatrixVectorProductComp(vec_size=nn,
A_name='O_BI',
x_name='r_b2g_I',
b_name='r_b2g_B',
x_units='km',
b_units='km'),
promotes_inputs=['O_BI', 'r_b2g_I'],
promotes_outputs=['r_b2g_B'])
self.add_subsystem('comm_vector_ant_comp',
MatrixVectorProductComp(vec_size=nn,
A_name='O_AB',
x_name='r_b2g_B',
b_name='r_b2g_A',
x_units='km',
b_units='km'),
promotes_inputs=['O_AB', 'r_b2g_B'],
promotes_outputs=['r_b2g_A'])
self.add_subsystem('comm_vector_spherical_comp',
CommVectorSphericalComp(num_nodes=nn),
promotes_inputs=['r_b2g_A'],
promotes_outputs=['elevationGS', 'azimuthGS'])
self.add_subsystem('comm_distance_comp',
VectorMagnitudeComp(vec_size=nn,
in_name='r_b2g_A',
mag_name='GSdist',
units='km'),
promotes_inputs=['r_b2g_A'],
promotes_outputs=['GSdist'])
self.add_subsystem('comm_gain_pattern_comp',
CommGainPatternComp(num_nodes=nn),
promotes_inputs=['elevationGS', 'azimuthGS'],
promotes_outputs=['gain'])
self.add_subsystem('comm_los_comp',
CommLOSComp(num_nodes=nn),
promotes_inputs=['r_b2g_I', 'r_e2g_I'],
promotes_outputs=['CommLOS'])
self.add_subsystem(
'data_rate_comp',
CommDataRateComp(num_nodes=nn),
promotes_inputs=['P_comm', 'gain', 'CommLOS', 'GSdist'],
promotes_outputs=['dXdt:data'])