def test_load_balanced_doe(self):
problem = Problem(impl=impl)
root = problem.root = Group()
root.add('indep_var', IndepVarComp('x', val=1.0))
root.add('const', IndepVarComp('c', val=2.0))
root.add('mult', Mult())
root.connect('indep_var.x', 'mult.x')
root.connect('const.c', 'mult.c')
num_levels = 25
problem.driver = FullFactorialDriver(num_levels=num_levels,
num_par_doe=self.N_PROCS,
load_balance=True)
problem.driver.add_desvar('indep_var.x',
lower=1.0,
upper=float(num_levels))
problem.driver.add_objective('mult.y')
problem.driver.add_recorder(InMemoryRecorder())
problem.setup(check=False)
problem.run()
for data in problem.driver.recorders[0].iters:
self.assertEqual(data['unknowns']['indep_var.x'] * 2.0,
data['unknowns']['mult.y'])
num_cases = len(problem.driver.recorders[0].iters)
if MPI:
lens = problem.comm.allgather(num_cases)
self.assertEqual(sum(lens), num_levels)
else:
self.assertEqual(num_cases, num_levels)
def test_doe(self):
problem = Problem(impl=impl)
root = problem.root = Group()
root.add('indep_var', IndepVarComp('x', val=7.0))
root.add('const', IndepVarComp('c', val=3.0))
root.add('dut', DUT())
root.connect('indep_var.x', 'dut.x')
root.connect('const.c', 'dut.c')
num_samples = 10
problem.driver = UniformDriver(num_samples=num_samples,
num_par_doe=self.N_PROCS)
problem.driver.add_desvar('indep_var.x', low=4410.0, high=4450.0)
problem.driver.add_objective('dut.y')
problem.driver.add_recorder(InMemoryRecorder())
problem.setup(check=False)
problem.run()
for data in problem.driver.recorders[0].iters:
self.assertEqual(data['unknowns']['indep_var.x'] * 3.0,
data['unknowns']['dut.y'])
num_cases = len(problem.driver.recorders[0].iters)
if MPI:
lens = problem.comm.allgather(num_cases)
self.assertEqual(sum(lens), num_samples)
else:
self.assertEqual(num_cases, num_samples)
def test_case_driver(self):
problem = Problem()
root = problem.root = Group()
root.add('indep_var', IndepVarComp('x', val=1.0))
root.add('const', IndepVarComp('c', val=2.0))
root.add('mult', ExecComp4Test("y=c*x"))
root.connect('indep_var.x', 'mult.x')
root.connect('const.c', 'mult.c')
cases = [
[('indep_var.x', 3.0), ('const.c', 1.5)],
[('indep_var.x', 4.0), ('const.c', 2.)],
[('indep_var.x', 5.5), ('const.c', 3.0)],
]
problem.driver = CaseDriver(cases)
problem.driver.add_desvar('indep_var.x')
problem.driver.add_desvar('const.c')
problem.driver.add_recorder(InMemoryRecorder())
problem.setup(check=False)
problem.run()
for i, data in enumerate(problem.driver.recorders[0].iters):
data['unknowns'] = dict(data['unknowns'])
self.assertEqual(
data['unknowns']['indep_var.x'] * data['unknowns']['const.c'],
data['unknowns']['mult.y'])
self.assertEqual(cases[i][0][1] * cases[i][1][1],
data['unknowns']['mult.y'])
self.assertEqual(len(problem.driver.recorders[0].iters), 3)
def test_load_balanced_doe_crit_fail(self):
problem = Problem(impl=impl)
root = problem.root = Group()
root.add('indep_var', IndepVarComp('x', val=1.0))
root.add('const', IndepVarComp('c', val=2.0))
if MPI:
fail_rank = 1 # raise exception from this rank
else:
fail_rank = 0
if self.comm.rank == fail_rank:
root.add('mult', ExecComp4Test("y=c*x", fails=[3], critical=True))
else:
root.add('mult', ExecComp4Test("y=c*x"))
root.connect('indep_var.x', 'mult.x')
root.connect('const.c', 'mult.c')
num_levels = 25
problem.driver = FullFactorialDriver(num_levels=num_levels,
num_par_doe=self.N_PROCS,
load_balance=True)
problem.driver.add_desvar('indep_var.x',
lower=1.0, upper=float(num_levels))
problem.driver.add_objective('mult.y')
problem.driver.add_recorder(InMemoryRecorder())
problem.setup(check=False)
if MPI:
problem.run()
else:
try:
problem.run()
except Exception as err:
self.assertEqual(str(err), "OMG, a critical error!")
else:
self.fail("expected exception")
for data in problem.driver.recorders[0].iters:
self.assertEqual(data['unknowns']['indep_var.x']*2.0,
data['unknowns']['mult.y'])
num_cases = len(problem.driver.recorders[0].iters)
if MPI:
# in load balanced mode, we can't really predict how many cases
# will actually run before we terminate, so just check to see if
# we at least have less than the full set we'd have if nothing
# went wrong.
lens = problem.comm.allgather(num_cases)
self.assertTrue(sum(lens) < num_levels,
"Cases run (%d) should be less than total cases (%d)" %
(sum(lens), num_levels))
else:
self.assertEqual(num_cases, 3)
def test_doe_fail_critical(self):
problem = Problem(impl=impl)
root = problem.root = Group()
root.add('indep_var', IndepVarComp('x', val=1.0))
root.add('const', IndepVarComp('c', val=2.0))
if MPI:
fail_rank = 1 # raise exception from this rank
else:
fail_rank = 0
if self.comm.rank == fail_rank:
root.add('mult', ExecComp4Test("y=c*x", fails=[3], critical=True))
else:
root.add('mult', ExecComp4Test("y=c*x"))
root.connect('indep_var.x', 'mult.x')
root.connect('const.c', 'mult.c')
num_levels = 25
problem.driver = FullFactorialDriver(num_levels=num_levels,
num_par_doe=self.N_PROCS)
problem.driver.add_desvar('indep_var.x',
lower=1.0,
upper=float(num_levels))
problem.driver.add_objective('mult.y')
problem.driver.add_recorder(InMemoryRecorder())
problem.setup(check=False)
try:
problem.run()
except Exception as err:
with MultiProcFailCheck(self.comm):
if self.comm.rank == fail_rank:
self.assertEqual(str(err), "OMG, a critical error!")
else:
self.assertEqual(
str(err),
"an exception was raised by another MPI process.")
for data in problem.driver.recorders[0].iters:
self.assertEqual(data['unknowns']['indep_var.x'] * 2.0,
data['unknowns']['mult.y'])
num_cases = len(problem.driver.recorders[0].iters)
if MPI:
lens = problem.comm.allgather(num_cases)
self.assertEqual(sum(lens), 12)
else:
self.assertEqual(num_cases, 3)
def test_doe_fail_analysis_error(self):
problem = Problem(impl=impl)
root = problem.root = Group()
root.add('indep_var', IndepVarComp('x', val=1.0))
root.add('const', IndepVarComp('c', val=2.0))
fail_rank = 1 # raise exception from this rank
if self.comm.rank == fail_rank:
root.add('mult', ExecComp4Test("y=c*x", fails=[3, 4]))
else:
root.add('mult', ExecComp4Test("y=c*x"))
root.connect('indep_var.x', 'mult.x')
root.connect('const.c', 'mult.c')
num_levels = 25
problem.driver = FullFactorialDriver(num_levels=num_levels,
num_par_doe=self.N_PROCS)
problem.driver.add_desvar('indep_var.x',
lower=1.0,
upper=float(num_levels))
problem.driver.add_objective('mult.y')
problem.driver.add_recorder(InMemoryRecorder())
problem.setup(check=False)
problem.run()
for data in problem.driver.recorders[0].iters:
self.assertEqual(data['unknowns']['indep_var.x'] * 2.0,
data['unknowns']['mult.y'])
num_cases = len(problem.driver.recorders[0].iters)
if MPI:
lens = problem.comm.allgather(num_cases)
self.assertEqual(sum(lens), 25)
else:
self.assertEqual(num_cases, 25)
nfails = 0
for data in problem.driver.recorders[0].iters:
if not data['success']:
nfails += 1
if self.comm.rank == fail_rank:
self.assertEqual(nfails, 2)
else:
self.assertEqual(nfails, 0)
def run_list(driver, inputs):
if driver.TestMotor: # test the motor design instead of an external model
outputs = []
for i in inputs:
outputs.append(motorDesign.motor(i, len(driver.outputNames)))
elif driver.UseParametersCSV:
outputs = []
with open('parameters.csv', 'r') as f: # read log file of inputs and outputs
f.readline() # skip past the line specifying the names of inputs and outputs
for line in f:
output = []
for num in line.split(',')[-len(driver.outputNames):]: # get list of outputs from line (in string form)
output.append(float(num))
outputs.append(output)
f.close()
else:
recorder = InMemoryRecorder()
recorder.startup(driver.root)
driver.recorders.append(recorder)
driver.runlist = [zip(driver.inputNames, input) for input in inputs]
if UseParallel:
driver.sequential = False
if UseCluster:
print 'Using remote cluster.'
driver.sequential = False
# This is necessary more often than it should be.
driver.ignore_egg_requirements = True
# Force use of only cluster hosts by adding this requirement.
driver.extra_resources = dict(allocator='PCCCluster')
super(driver.__class__, driver).run(driver)
outputs = []
for c in recorder.iters:
unknowns = c['unknowns']
output = []
missing = object()
for name in driver.outputNames:
unknown = unknowns.get(name, missing)
if unknown is missing:
raise Exception('No outputs from simulator matching requested output \'{0}\'. Available outputs: {1}'.format(name, unknowns.keys()))
if unknown is None:
# FIXME upgrade OpenMDAO, and the testbench should throw AnalysisException
raise Exception('No value from simulator matching requested output \'{0}\'. Perhaps the testbench failed')
if not isinstance(unknown, float):
# FIXME should really be a float. TODO fix post_processing_class.py update_metrics_in_report_json in all models everywhere...
# warnings.warn('Unknown \'{0}\' produced from a TestBench is not a float'.format(name))
unknown = float(unknown)
output.append(unknown)
outputs.append(output)
driver.recorders._recorders.remove(recorder)
if not driver.UseParametersCSV:
with open('parameters.csv', 'w') as f: # write log file of inputs and outputs
f.write(','.join(driver.inputNames)+','+','.join(driver.outputNames)+'\n')
for x, i in enumerate(inputs):
f.write(','.join(str(y) for y in inputs[x]))
if x < len(outputs):
f.write(','+','.join(str(y) for y in outputs[x]))
f.write('\n')
f.close()
if len(outputs) != len(inputs):
raise Exception('Simulator returned only {0} results of a requested {1}. See parameters.csv for details.'.format(len(outputs), len(inputs)))
return asarray(outputs)
def run_list(problem, driver, inputs):
if driver.TestMotor: # test the motor design instead of an external model
outputs = []
for i in inputs:
outputs.append(motorDesign.motor(i, len(driver.outputNames)))
elif driver.UseParametersCSV:
outputs = []
with open('parameters.csv',
'r') as f: # read log file of inputs and outputs
f.readline(
) # skip past the line specifying the names of inputs and outputs
for line in f:
output = []
for num in line.split(
','
)[-len(driver.outputNames
):]: # get list of outputs from line (in string form)
output.append(float(num))
outputs.append(output)
f.close()
else:
recorder = InMemoryRecorder()
recorder.startup(driver.root)
driver.recorders.append(recorder)
problem.setup()
driver.runlist = [zip(driver.inputNames, input) for input in inputs]
if UseParallel:
driver.sequential = False
if UseCluster:
print 'Using remote cluster.'
driver.sequential = False
# This is necessary more often than it should be.
driver.ignore_egg_requirements = True
# Force use of only cluster hosts by adding this requirement.
driver.extra_resources = dict(allocator='PCCCluster')
super(driver.__class__, driver).run(problem)
outputs = []
for c in recorder.iters:
unknowns = c['unknowns']
output = []
missing = object()
for name in driver.outputNames:
path = name.split(".")
if len(path) > 1 and path[0] in driver.subproblem_output_meta:
real_name = driver.subproblem_output_meta[path[0]][path[1]]
real_path = "{}.{}".format(path[0], real_name)
else:
real_path = name
unknown = unknowns.get(real_path, missing)
if unknown is missing:
raise Exception(
'No outputs from simulator matching requested output \'{0}\'. Available outputs: {1}'
.format(real_path, unknowns.keys()))
if unknown is None:
# FIXME upgrade OpenMDAO, and the testbench should throw AnalysisException
raise Exception(
'No value from simulator matching requested output \'{0}\'. Perhaps the testbench failed'
)
if not isinstance(unknown, float):
# FIXME should really be a float. TODO fix post_processing_class.py update_metrics_in_report_json in all models everywhere...
# warnings.warn('Unknown \'{0}\' produced from a TestBench is not a float'.format(name))
unknown = float(unknown)
output.append(unknown)
outputs.append(output)
driver.recorders._recorders.remove(recorder)
if not driver.UseParametersCSV:
with open('parameters.csv',
'w') as f: # write log file of inputs and outputs
f.write(','.join(driver.inputNames) + ',' +
','.join(driver.outputNames) + '\n')
for x, i in enumerate(inputs):
f.write(','.join(str(y) for y in inputs[x]))
if x < len(outputs):
f.write(',' + ','.join(str(y) for y in outputs[x]))
f.write('\n')
f.close()
if len(outputs) != len(inputs):
raise Exception(
'Simulator returned only {0} results of a requested {1}. See parameters.csv for details.'
.format(len(outputs), len(inputs)))
return asarray(outputs)
def setUp(self):
self.recorder = InMemoryRecorder()
def test_load_balanced_doe_soft_fail(self):
problem = Problem(impl=impl)
root = problem.root = Group()
root.add('indep_var', IndepVarComp('x', val=1.0))
root.add('const', IndepVarComp('c', val=2.0))
if MPI:
fail_rank = 1 # raise exception from this rank
else:
fail_rank = 0
fail_idxs = [3, 4, 5]
if self.comm.rank == fail_rank:
root.add('mult', ExecComp4Test("y=c*x", fails=fail_idxs))
else:
root.add('mult', ExecComp4Test("y=c*x"))
root.connect('indep_var.x', 'mult.x')
root.connect('const.c', 'mult.c')
num_levels = 25
problem.driver = FullFactorialDriver(num_levels=num_levels,
num_par_doe=self.N_PROCS,
load_balance=True)
problem.driver.add_desvar('indep_var.x',
lower=1.0,
upper=float(num_levels))
problem.driver.add_objective('mult.y')
problem.driver.add_recorder(InMemoryRecorder())
problem.setup(check=False)
problem.run()
for data in problem.driver.recorders[0].iters:
self.assertEqual(data['unknowns']['indep_var.x'] * 2.0,
data['unknowns']['mult.y'])
num_cases = len(problem.driver.recorders[0].iters)
if MPI and self.comm.rank > 0:
self.assertEqual(num_cases, 0)
else:
self.assertEqual(num_cases, num_levels)
nfails = 0
cases_in_fail_rank = 0
for data in problem.driver.recorders[0].iters:
if not data['success']:
nfails += 1
if data['unknowns']['mult.case_rank'] == fail_rank:
cases_in_fail_rank += 1
if self.comm.rank == 0:
# FIXME: for now, all cases get sent back to the master process (0),
# even when recorders are parallel.
# there's a chance that the fail rank didn't get enough
# cases to actually fail 3 times, so we need to check
# how many cases it actually got.
if cases_in_fail_rank > 5:
self.assertEqual(nfails, 3)
elif cases_in_fail_rank > 4:
self.assertEqual(nfails, 2)
elif cases_in_fail_rank > 3:
self.assertEqual(nfails, 1)
else:
self.assertEqual(nfails, 0)
else:
self.assertEqual(nfails, 0)
