def setup(self):
# Raw data to load is in 'data' directory
data_path = os.path.dirname(os.path.realpath(__file__))
data_path = os.path.join(data_path, 'data')
launch_data = np.loadtxt(data_path + '/Launch/launch1.dat')
# orbit position and velocity data for each design point
r_e2b_I0s = launch_data[1::2, 1:]
# number of days since launch for each design point
LDs = launch_data[1::2, 0] - 2451545
# Create IndepVarComp for broadcast parameters.
bp = self.add_subsystem('bp', IndepVarComp())
bp.add_output('cellInstd', np.ones((7, 12)))
bp.add_output('finAngle', np.pi/4.0, units='rad')
bp.add_output('antAngle', 0.0, units='rad')
# CADRE instances go into a Parallel Group
para = self.add_subsystem('parallel', ParallelGroup(), promotes=['*'])
# build design points
names = ['pt%s' % i for i in range(self.npts)]
for i, name in enumerate(names):
# Some initial values
inits = {
'LD': float(LDs[i]),
'r_e2b_I0': r_e2b_I0s[i]
}
para.add_subsystem(name, CADRE(n=self.n, m=self.m, initial_inputs=inits))
# Hook up broadcast inputs
self.connect('bp.cellInstd', '%s.cellInstd' % name)
self.connect('bp.finAngle', '%s.finAngle' % name)
self.connect('bp.antAngle', '%s.antAngle' % name)
self.add_subsystem('%s_con5' % name, ExecComp('val = SOCi - SOCf'))
self.connect('%s.SOC' % name, '%s_con5.SOCi' % name,
src_indices=[0], flat_src_indices=True)
self.connect('%s.SOC' % name, '%s_con5.SOCf' % name,
src_indices=[self.n-1], flat_src_indices=True)
# objective: sum of data from all design points
data_totals = ['%s_DataTot' % name for name in names]
obj = ''.join([' - %s' % data_tot for data_tot in data_totals])
meta_dicts = {}
for dt in data_totals:
meta_dicts[dt] = {'units': 'Gibyte'}
self.add_subsystem('obj', ExecComp('val='+obj, **meta_dicts))
for name in names:
self.connect('%s.Data' % name, 'obj.%s_DataTot' % name,
src_indices=[self.n-1], flat_src_indices=True)
def test_CADRE(self):
n, m, h, setd = load_validation_data(idx='0')
prob = Problem(CADRE(n=n, m=m))
prob.setup(check=verbose)
input_data = [
'CP_P_comm', 'LD', 'cellInstd', 'CP_gamma', 'finAngle', 'lon',
'CP_Isetpt', 'antAngle', 't', 'r_e2b_I0', 'lat', 'alt', 'iSOC'
]
for inp in input_data:
prob[inp] = setd[inp]
prob.run_driver()
if verbose:
inputs = prob.model.list_inputs()
outputs = prob.model.list_outputs()
else:
inputs = prob.model.list_inputs(out_stream=None)
outputs = prob.model.list_outputs(out_stream=None)
good = []
fail = []
for varpath, meta in inputs + outputs:
var = varpath.split('.')[-1]
if var in setd:
actual = setd[var]
computed = prob[var]
if isinstance(computed, np.ndarray):
rel = np.linalg.norm(actual -
computed) / np.linalg.norm(actual)
else:
rel = np.abs(actual - computed) / np.abs(actual)
if np.mean(actual) > 1e-3 or np.mean(computed) > 1e-3:
if rel > 1e-3:
fail.append(varpath)
if verbose:
print(varpath, 'failed:\n', computed, '\n---\n',
actual, '\n')
else:
good.append(varpath)
if verbose:
print(varpath, 'is good.')
elif verbose:
print(var, 'not in data.')
fails = len(fail)
total = fails + len(good)
self.assertEqual(
fails, 0, '%d (of %d) mismatches with validation data:\n%s' %
(fails, total, '\n'.join(sorted(fail))))
def test_RK4_issue(self):
n = 60
m = 20
LDs = [5233.5, 5294.5, 5356.5, 5417.5, 5478.5, 5537.5]
r_e2b_I0s = [np.array([4505.29362, -3402.16069, -3943.74582,
4.1923899, -1.56280012, 6.14347427]),
np.array([-1005.46693, -597.205348, -6772.86532,
-0.61047858, -7.54623146, 0.75907455]),
np.array([4401.10539, 2275.95053, -4784.13188,
-5.26605537, -1.08194926, -5.37013745]),
np.array([-4969.91222, 4624.84149, 1135.9414,
0.1874654, -1.62801666, 7.4302362]),
np.array([-235.021232, 2195.72976, 6499.79919,
-2.55956031, -6.82743519, 2.21628099]),
np.array([-690.314375, -1081.78239, -6762.90367,
7.44316722, 1.19745345, -0.96035904])]
i = 0
init = {
'LD': LDs[i],
'r_e2b_I0': r_e2b_I0s[i]
}
prob = Problem()
prob.model.add_subsystem('pt', CADRE(n=n, m=m, initial_inputs=init), promotes=['*'])
prob.setup(check=verbose)
prob.run_model()
inputs = ['CP_gamma']
outputs = ['Data']
# check partials
# partials = prob.check_partials() # out_stream=None)
# assert_check_partials(partials)
# check totals
if verbose:
J = prob.check_totals(of=outputs, wrt=inputs)
else:
J = prob.check_totals(of=outputs, wrt=inputs, out_stream=None)
for outp in outputs:
for inp in inputs:
Jn = J[outp, inp]['J_fd']
Jf = J[outp, inp]['J_fwd']
if verbose:
np.set_printoptions(threshold='nan')
print(np.nonzero(Jn))
print(np.nonzero(Jf))
diff = abs(Jf - Jn)
assert_rel_error(self, diff.max(), 0.0, 1e-4)
if key[0] == idx or not key[0].isdigit():
if not key[0].isdigit():
shortkey = key
else:
shortkey = key[2:]
# set floats correctly
if data[key].shape == (1, ) and shortkey != "iSOC":
setd[shortkey] = data[key][0]
else:
setd[shortkey] = data[key]
n = setd['P_comm'].size
m = setd['CP_P_comm'].size
t0 = time.time()
assembly = Problem(root=CADRE(n, m))
print("Instantiation: ", time.time() - t0)
t0 = time.time()
assembly.setup(check=False)
print("Setup: ", time.time() - t0)
setd['r_e2b_I0'] = np.zeros(6)
setd['r_e2b_I0'][:3] = data[idx + ":r_e2b_I0"]
setd['r_e2b_I0'][3:] = data[idx + ":v_e2b_I0"]
setd['Gamma'] = data[idx + ":gamma"]
assembly['CP_P_comm'] = setd['CP_P_comm']
assembly['LD'] = setd['LD']
assembly['cellInstd'] = setd['cellInstd']
assembly['CP_gamma'] = setd['CP_gamma']
def test_RK4_issue(self):
n = 60
m = 20
LDs = [5233.5, 5294.5, 5356.5, 5417.5, 5478.5, 5537.5]
r_e2b_I0s = [
np.array([
4505.29362, -3402.16069, -3943.74582, 4.1923899, -1.56280012,
6.14347427
]),
np.array([
-1005.46693, -597.205348, -6772.86532, -0.61047858,
-7.54623146, 0.75907455
]),
np.array([
4401.10539, 2275.95053, -4784.13188, -5.26605537, -1.08194926,
-5.37013745
]),
np.array([
-4969.91222, 4624.84149, 1135.9414, 0.1874654, -1.62801666,
7.4302362
]),
np.array([
-235.021232, 2195.72976, 6499.79919, -2.55956031, -6.82743519,
2.21628099
]),
np.array([
-690.314375, -1081.78239, -6762.90367, 7.44316722, 1.19745345,
-0.96035904
])
]
top = Problem(root=Group())
i = 0
init = {}
init["LD"] = LDs[i]
init["r_e2b_I0"] = r_e2b_I0s[i]
top.root.add('pt', CADRE(n, m, initial_params=init), promotes=['*'])
#from openmdao.solvers.ln_gauss_seidel import LinearGaussSeidel
#top.root.ln_solver = LinearGaussSeidel()
#top.root.pt.ln_solver = LinearGaussSeidel()
top.setup(check=False)
top.run()
inputs = ['CP_gamma']
outputs = ['Data']
from time import time
t0 = time()
J1 = top.calc_gradient(inputs, outputs, mode='fwd')
print('Forward', time() - t0)
t0 = time()
J2 = top.calc_gradient(inputs, outputs, mode='rev')
print('Reverse', time() - t0)
t0 = time()
Jfd = top.calc_gradient(inputs, outputs, mode='fd')
print('Fd', time() - t0)
np.set_printoptions(threshold='nan')
#print np.nonzero(J1)
#print np.nonzero(J2)
#print np.nonzero(Jfd)
#print J1
#print J2
#print Jfd
print np.max(abs(J1 - Jfd))
print np.max(abs(J2 - Jfd))
print np.max(abs(J1 - J2))
self.assertTrue(np.max(abs(J1 - J2)) < 1.0e-6)
self.assertTrue(np.max(abs(J1 - Jfd)) < 1.0e-4)
self.assertTrue(np.max(abs(J2 - Jfd)) < 1.0e-4)
from __future__ import print_function
import time
import numpy as np
from openmdao.api import Problem, DirectSolver
from CADRE.CADRE_group import CADRE
from CADRE.test.util import load_validation_data
n, m, h, setd = load_validation_data(idx='0')
# instantiate Problem with CADRE model
t0 = time.time()
model = CADRE(n=n, m=m)
#model = CADRE(n=n, m=m, assembled_jac_type='csc')
prob = Problem(model)
#model.linear_solver = DirectSolver(assemble_jac=True)
print("Instantiation: ", time.time() - t0, 's')
# do problem setup
t0 = time.time()
prob.setup(check=False)
print("Problem Setup: ", time.time() - t0, 's')
# set initial values from validation data
input_data = [
'CP_P_comm', 'LD', 'cellInstd', 'CP_gamma', 'finAngle', 'lon', 'CP_Isetpt',
def __init__(self, n=1500, m=300, npts=6):
super(CADRE_MDP_Group, self).__init__()
# Raw data to load
fpath = os.path.dirname(os.path.realpath(__file__))
fpath = os.path.join(fpath, 'data')
solar_raw1 = np.genfromtxt(fpath + '/Solar/Area10.txt')
solar_raw2 = np.loadtxt(fpath + '/Solar/Area_all.txt')
comm_rawGdata = np.genfromtxt(fpath + '/Comm/Gain.txt')
comm_raw = (10**(comm_rawGdata / 10.0)).reshape((361, 361), order='F')
power_raw = np.genfromtxt(fpath + '/Power/curve.dat')
# Load launch data
launch_data = np.loadtxt(fpath + '/Launch/launch1.dat')
# orbit position and velocity data for each design point
r_e2b_I0s = launch_data[1::2, 1:]
# number of days since launch for each design point
LDs = launch_data[1::2, 0] - 2451545
# Create ParmComps for broadcast parameters.
self.add('bp1', IndepVarComp('cellInstd', np.ones((7, 12))))
self.add('bp2', IndepVarComp('finAngle', np.pi / 4.0))
self.add('bp3', IndepVarComp('antAngle', 0.0))
# CADRE instances go into a Parallel Group
para = self.add('parallel', ParallelGroup(), promotes=['*'])
# build design points
names = ['pt%s' % i for i in range(npts)]
for i, name in enumerate(names):
# Some initial values
inits = {}
inits['LD'] = float(LDs[i])
inits['r_e2b_I0'] = r_e2b_I0s[i]
comp = para.add(
name,
CADRE(n,
m,
solar_raw1,
solar_raw2,
comm_raw,
power_raw,
initial_params=inits))
# Hook up broadcast params
self.connect('bp1.cellInstd', "%s.cellInstd" % name)
self.connect('bp2.finAngle', "%s.finAngle" % name)
self.connect('bp3.antAngle', "%s.antAngle" % name)
self.add('%s_con5' % name, ExecComp("val = SOCi - SOCf"))
self.connect("%s.SOC" % name,
'%s_con5.SOCi' % name,
src_indices=[0])
self.connect("%s.SOC" % name,
'%s_con5.SOCf' % name,
src_indices=[n - 1])
obj = ''.join([" - %s_DataTot" % name for name in names])
self.add('obj', ExecComp('val=' + obj))
for name in names:
self.connect("%s.Data" % name,
"obj.%s_DataTot" % name,
src_indices=[n - 1])
# Set our groups to auto
self.ln_solver.options['mode'] = 'auto'
para.ln_solver.options['mode'] = 'auto'
"""
from __future__ import print_function
import time
from openmdao.api import Problem
from CADRE.CADRE_group import CADRE
from CADRE.test.util import load_validation_data
n, m, h, setd = load_validation_data(idx='0')
# instantiate Problem with CADRE model
t0 = time.time()
model = CADRE(n=n, m=m)
prob = Problem(model)
print("Instantiation: ", time.time() - t0, 's')
# do problem setup
t0 = time.time()
prob.setup(check=False)
print("Problem Setup: ", time.time() - t0, 's')
# set initial values from validation data
input_data = [
'CP_P_comm',
'LD',
'cellInstd',
'CP_gamma',
'finAngle',