def test_reports_system_mpi_basic(
self): # example taken from TestScipyOptimizeDriverMPI
setup_default_reports()
prob = om.Problem()
prob.model = SellarMDA()
prob.driver = om.ScipyOptimizeDriver(optimizer='SLSQP', tol=1e-8)
prob.model.add_design_var('x', lower=0, upper=10)
prob.model.add_design_var('z', lower=0, upper=10)
prob.model.add_objective('obj')
prob.model.add_constraint('con1', upper=0)
prob.model.add_constraint('con2', upper=0)
prob.setup()
prob.set_solver_print(level=0)
prob.run_driver()
# get the path to the problem subdirectory
problem_reports_dir = pathlib.Path(_reports_dir).joinpath(prob._name)
path = pathlib.Path(problem_reports_dir).joinpath(self.n2_filename)
self.assertTrue(path.is_file(),
f'The N2 report file, {str(path)} was not found')
path = pathlib.Path(problem_reports_dir).joinpath(
self.scaling_filename)
self.assertTrue(
path.is_file(),
f'The scaling report file, {str(path)}, was not found')
def test_xdsmjs_mdf(self):
filename = 'xdsmjs_mdf'
out_format = 'html'
prob = om.Problem(model=SellarMDA())
model = prob.model
prob.driver = om.ScipyOptimizeDriver()
model.add_design_var('z',
lower=np.array([-10.0, 0.0]),
upper=np.array([10.0, 10.0]),
indices=np.arange(2, dtype=int))
model.add_design_var('x', lower=0.0, upper=10.0)
model.add_objective('obj')
model.add_constraint('con1', equals=np.zeros(1))
model.add_constraint('con2', upper=0.0)
prob.setup()
prob.final_setup()
# Write output
om.write_xdsm(prob,
filename=filename,
out_format=out_format,
show_browser=SHOW,
include_solver=True)
# Check if file was created
self.assertTrue(os.path.isfile('.'.join([filename, out_format])))
def test_sellar_opt(self):
import openmdao.api as om
from openmdao.test_suite.components.sellar_feature import SellarMDA
prob = om.Problem()
prob.model = SellarMDA()
prob.driver = om.ScipyOptimizeDriver()
prob.driver.options['optimizer'] = 'SLSQP'
# prob.driver.options['maxiter'] = 100
prob.driver.options['tol'] = 1e-8
prob.model.add_design_var('x', lower=0, upper=10)
prob.model.add_design_var('z', lower=0, upper=10)
prob.model.add_objective('obj')
prob.model.add_constraint('con1', upper=0)
prob.model.add_constraint('con2', upper=0)
prob.setup()
prob.set_solver_print(level=0)
# Ask OpenMDAO to finite-difference across the model to compute the gradients for the optimizer
prob.model.approx_totals()
prob.run_driver()
print('minimum found at')
assert_near_equal(prob['x'][0], 0., 1e-5)
assert_near_equal(prob['z'], [1.977639, 0.], 1e-5)
print('minumum objective')
assert_near_equal(prob['obj'][0], 3.18339395045, 1e-5)
def test_pyxdsm_mda(self):
filename = 'pyxdsm_mda'
out_format = PYXDSM_OUT
p = om.Problem(model=SellarMDA())
p.setup()
p.final_setup()
# Write output
write_xdsm(p, filename=filename, out_format=out_format, quiet=QUIET, show_browser=SHOW, include_solver=True)
# Check if file was created
self.assertTrue(os.path.isfile(filename + '.' + out_format))
def test_sellar(self):
prob = om.Problem()
prob.model = SellarMDA()
prob.setup()
prob.run_model()
assert_near_equal(prob['y1'], 25.58830273, .00001)
assert_near_equal(prob['y2'], 12.05848819, .00001)
# Make sure we aren't iterating like crazy
self.assertLess(prob.model.nonlinear_solver._iter_count, 8)
def test_xdsmjs_mda(self):
filename = 'xdsmjs_mda'
out_format = 'html'
prob = Problem(model=SellarMDA())
prob.setup(check=False)
prob.final_setup()
# Write output
write_xdsm(prob, filename=filename, out_format=out_format, quiet=QUIET,
show_browser=SHOW, embed_data=True, embeddable=True, include_solver=True)
# Check if file was created
self.assertTrue(os.path.isfile('.'.join([filename, out_format])))
def test_parallel(self):
from openmdao.api import ParallelGroup, NonlinearBlockGS
class SellarMDA(Group):
"""
Group containing the Sellar MDA.
"""
def setup(self):
indeps = self.add_subsystem('indeps', IndepVarComp(), promotes=['*'])
indeps.add_output('x', 1.0)
indeps.add_output('z', np.array([5.0, 2.0]))
cycle = self.add_subsystem('cycle', ParallelGroup(), promotes=['*'])
cycle.add_subsystem('d1', SellarDis1(), promotes_inputs=['x', 'z', 'y2'],
promotes_outputs=['y1'])
cycle.add_subsystem('d2', SellarDis2(), promotes_inputs=['z', 'y1'],
promotes_outputs=['y2'])
# Nonlinear Block Gauss Seidel is a gradient free solver
cycle.nonlinear_solver = NonlinearBlockGS()
self.add_subsystem('obj_cmp', ExecComp('obj = x**2 + z[1] + y1 + exp(-y2)',
z=np.array([0.0, 0.0]), x=0.0),
promotes=['x', 'z', 'y1', 'y2', 'obj'])
self.add_subsystem('con_cmp1', ExecComp('con1 = 3.16 - y1'),
promotes=['con1', 'y1'])
self.add_subsystem('con_cmp2', ExecComp('con2 = y2 - 24.0'),
promotes=['con2', 'y2'])
filename = 'xdsmjs_parallel'
out_format = 'html'
prob = Problem(model=SellarMDA())
model = prob.model
prob.driver = ScipyOptimizeDriver()
model.add_design_var('z', lower=np.array([-10.0, 0.0]),
upper=np.array([10.0, 10.0]), indices=np.arange(2, dtype=int))
model.add_design_var('x', lower=0.0, upper=10.0)
model.add_objective('obj')
model.add_constraint('con1', equals=np.zeros(1))
model.add_constraint('con2', upper=0.0)
prob.setup(check=False)
prob.final_setup()
# Write output
write_xdsm(prob, filename=filename, out_format=out_format, quiet=QUIET, show_browser=SHOW,
show_parallel=True)
# Check if file was created
self.assertTrue(os.path.isfile('.'.join([filename, out_format])))
def test_sellar(self):
# Just tests Newton on Sellar with FD derivs.
prob = Problem()
prob.model = SellarMDA()
prob.setup(check=False)
prob.run_model()
assert_rel_error(self, prob['y1'], 25.58830273, .00001)
assert_rel_error(self, prob['y2'], 12.05848819, .00001)
# Make sure we aren't iterating like crazy
self.assertLess(prob.model.nonlinear_solver._iter_count, 8)
def test_pyxdsm_mda(self):
filename = 'pyxdsm_mda'
out_format = PYXDSM_OUT
prob = Problem(model=SellarMDA())
prob.setup(check=False)
prob.final_setup()
# Write output
write_xdsm(prob,
filename=filename,
out_format=out_format,
quiet=QUIET,
show_browser=False,
include_solver=True)
# Check if file was created
self.assertTrue(os.path.isfile('.'.join([filename, out_format])))
def test_mpi_bug_solver(self):
# This test verifies that mpi doesn't hang due to collective calls in the solver.
prob = om.Problem()
prob.model = SellarMDA()
prob.model.add_design_var('x', lower=0, upper=10)
prob.model.add_design_var('z', lower=0, upper=10)
prob.model.add_objective('obj')
prob.driver = om.DifferentialEvolutionDriver(run_parallel=True)
# Set these low because we don't need to run long.
prob.driver.options['max_gen'] = 2
prob.driver.options['pop_size'] = 5
prob.setup()
prob.set_solver_print(level=0)
prob.run_driver()
def test_sellar(self):
self.pb = pb = Problem(SellarMDA())
pb.model.add_design_var("x", lower=0, upper=10)
pb.model.add_design_var("z", lower=0, upper=10)
pb.model.add_objective("obj")
pb.model.add_constraint("con1", upper=0)
pb.model.add_constraint("con2", upper=0)
pb.driver = OneraSegoDriver(optimizer="SEGOMOE")
pb.driver.opt_settings["maxiter"] = 10
self.case_recorder_filename = "test_segomoe_driver_sellar.sqlite"
recorder = SqliteRecorder(self.case_recorder_filename)
pb.model.add_recorder(recorder)
pb.setup()
self.pb.run_driver()
self.assertTrue(os.path.exists(self.case_recorder_filename))
reader = CaseReader(self.case_recorder_filename)
for case_id in reader.list_cases():
case = reader.get_case(case_id)
print(case.outputs["obj"])
def test_setup_memleak(self):
# Record the memory still in use after each run
mem_used = []
# Setup of the Sellar poblem
prob = om.Problem()
tracemalloc.start()
for memtest in ITERS:
prob.model = SellarMDA()
snapshots = []
for i in range(memtest):
prob.setup(check=False) # called here causes memory leak
prob.run_driver()
totals = prob.compute_totals("z", "x")
del totals
# Force garbage collection now instead of waiting for an
# optimal/arbitrary point since we're tracking memory usage
gc.collect()
snapshots.append(tracemalloc.take_snapshot())
top_stats = snapshots[memtest - 1].compare_to(
snapshots[0], 'lineno')
total_mem = 0
for stat in top_stats:
tb_str = str(stat.traceback)
# Ignore memory allocations by tracemalloc itself, which throw things off:
if "/tracemalloc.py:" not in tb_str:
total_mem += stat.size
mem_used.append(total_mem)
tracemalloc.stop()
mem_diff = (mem_used[1] - mem_used[0]) / 1024
self.assertLess(
mem_diff, MAX_MEM_DIFF_KB,
"Memory leak in setup(): %.1f KiB difference between %d and %d iter runs"
% (mem_diff, ITERS[0], ITERS[1]))
def test_pyxdsm_mdf(self):
filename = 'pyxdsm_mdf'
out_format = PYXDSM_OUT
p = om.Problem(model=SellarMDA())
model = p.model
p.driver = om.ScipyOptimizeDriver()
model.add_design_var('z', lower=np.array([-10.0, 0.0]),
upper=np.array([10.0, 10.0]), indices=np.arange(2, dtype=int))
model.add_design_var('x', lower=0.0, upper=10.0)
model.add_objective('obj')
model.add_constraint('con1', equals=np.zeros(1))
model.add_constraint('con2', upper=0.0)
p.setup()
p.final_setup()
# Write output
write_xdsm(p, filename=filename, out_format=out_format, quiet=QUIET, show_browser=SHOW, include_solver=True)
# Check if file was created
self.assertTrue(os.path.isfile(filename + '.' + out_format))
import openmdao.api as om
from openmdao.test_suite.components.sellar_feature import SellarMDA
prob = om.Problem()
prob.model = SellarMDA()
prob.driver = om.ScipyOptimizeDriver()
prob.driver.options['optimizer'] = 'SLSQP'
# prob.driver.options['maxiter'] = 100
prob.driver.options['tol'] = 1e-8
prob.model.add_design_var('x', lower=0, upper=10)
prob.model.add_design_var('z', lower=0, upper=10)
prob.model.add_objective('obj')
prob.model.add_constraint('con1', upper=0)
prob.model.add_constraint('con2', upper=0)
prob.setup()
prob.set_solver_print(level=0)
# Ask OpenMDAO to finite-difference across the model to compute the gradients for the optimizer
prob.model.approx_totals()
prob.run_driver()
print('minimum found at')
print(prob['x'][0])
print(prob['z'])
print('minumum objective')
print(prob['obj'][0])
def test_pyxdsm_tikz_content(self):
# Check if TiKZ file was created.
# Compare the content of the sample below and the newly created TiKZ file.
# The texts are cleaned up before comparison from whitespaces, line ends and comments
# Despite this different versions of pyxdsm *might* produce different outputs. If the test fails for you,
# it might be that the program still produces the correct output.
# The ordering of some lines might be different at different runs, but the test should work regardless
# of these changes.
# The sample text should be replaced if changes in the formatting or in the test problem are made.
sample_tikz_txt = r"""
%%% Preamble Requirements %%%
% \usepackage{geometry}
% \usepackage{amsfonts}
% \usepackage{amsmath}
% \usepackage{amssymb}
% \usepackage{tikz}
% Optional packages such as sfmath set through python interface
% \usepackage{sfmath}
% \usetikzlibrary{arrows,chains,positioning,scopes,shapes.geometric,shapes.misc,shadows}
%%% End Preamble Requirements %%%
\input{"path/to/diagram_styles"}
\begin{tikzpicture}
\matrix[MatrixSetup]{
%Row 0
\node [Optimization] (Driver) {$\text{\text{0, 10 $ \rightarrow $ 1: Driver}}$};&
&
&
&
&
&
&
\\
%Row 1
&
\node [Function] (indeps) {$\begin{array}{c}\text{1: indeps} \\ \text{\textit{IndepVarComp}}\end{array}$};&
&
\node [DataInter] (indeps-cycle@d1) {$\begin{array}{c}x, z\end{array}$};&
\node [DataInter] (indeps-cycle@d2) {$\begin{array}{c}z\end{array}$};&
\node [DataInter] (indeps-obj@cmp) {$\begin{array}{c}x, z\end{array}$};&
&
\\
%Row 2
&
&
\node [MDA] (cycle@solver) {$\text{\text{2, 5 $ \rightarrow $ 3: NL: NLBGS}}$};&
\node [DataInter] (cycle@solver-cycle@d1) {$\begin{array}{c}y2^{t}\end{array}$};&
\node [DataInter] (cycle@solver-cycle@d2) {$\begin{array}{c}y1^{t}\end{array}$};&
&
&
\\
%Row 3
&
&
\node [DataInter] (cycle@d1-cycle@solver) {$\begin{array}{c}y1\end{array}$};&
\node [Function] (cycle@d1) {$\begin{array}{c}\text{3: d1} \\ \text{\textit{SellarDis1}}\end{array}$};&
\node [DataInter] (cycle@d1-cycle@d2) {$\begin{array}{c}y1\end{array}$};&
\node [DataInter] (cycle@d1-obj@cmp) {$\begin{array}{c}y1\end{array}$};&
\node [DataInter] (cycle@d1-con@cmp1) {$\begin{array}{c}y1\end{array}$};&
\\
%Row 4
&
&
\node [DataInter] (cycle@d2-cycle@solver) {$\begin{array}{c}y2\end{array}$};&
\node [DataInter] (cycle@d2-cycle@d1) {$\begin{array}{c}y2\end{array}$};&
\node [Function] (cycle@d2) {$\begin{array}{c}\text{4: d2} \\ \text{\textit{SellarDis2}}\end{array}$};&
\node [DataInter] (cycle@d2-obj@cmp) {$\begin{array}{c}y2\end{array}$};&
&
\node [DataInter] (cycle@d2-con@cmp2) {$\begin{array}{c}y2\end{array}$};\\
%Row 5
&
&
&
&
&
\node [Function] (obj@cmp) {$\begin{array}{c}\text{6: obj\_cmp} \\ \text{\textit{ExecComp}}\end{array}$};&
&
\\
%Row 6
&
&
&
&
&
&
\node [Function] (con@cmp1) {$\begin{array}{c}\text{7: con\_cmp1} \\ \text{\textit{ExecComp}}\end{array}$};&
\\
%Row 7
&
&
&
&
&
&
&
\node [Function] (con@cmp2) {$\begin{array}{c}\text{8: con\_cmp2} \\ \text{\textit{ExecComp}}\end{array}$};\\
};
% XDSM process chains
{ [start chain=process]
\begin{pgfonlayer}{process}
\chainin (Driver);
\chainin (indeps) [join=by ProcessHV];
\chainin (cycle@solver) [join=by ProcessHV];
\chainin (obj@cmp) [join=by ProcessHV];
\chainin (con@cmp1) [join=by ProcessHV];
\chainin (con@cmp2) [join=by ProcessHV];
\chainin (Driver) [join=by ProcessHV];
\end{pgfonlayer}
}{ [start chain=process]
\begin{pgfonlayer}{process}
\chainin (cycle@solver);
\chainin (cycle@d1) [join=by ProcessHV];
\chainin (cycle@d2) [join=by ProcessHV];
\chainin (cycle@solver) [join=by ProcessHV];
\end{pgfonlayer}
}
\begin{pgfonlayer}{data}
\path
% Horizontal edges
(cycle@solver) edge [DataLine] (cycle@solver-cycle@d2)
(cycle@d1) edge [DataLine] (cycle@d1-cycle@solver)
(cycle@solver) edge [DataLine] (cycle@solver-cycle@d1)
(cycle@d2) edge [DataLine] (cycle@d2-cycle@solver)
(cycle@d1) edge [DataLine] (cycle@d1-obj@cmp)
(cycle@d1) edge [DataLine] (cycle@d1-con@cmp1)
(cycle@d1) edge [DataLine] (cycle@d1-cycle@d2)
(cycle@d2) edge [DataLine] (cycle@d2-obj@cmp)
(cycle@d2) edge [DataLine] (cycle@d2-con@cmp2)
(cycle@d2) edge [DataLine] (cycle@d2-cycle@d1)
(indeps) edge [DataLine] (indeps-cycle@d1)
(indeps) edge [DataLine] (indeps-obj@cmp)
(indeps) edge [DataLine] (indeps-cycle@d2)
% Vertical edges
(cycle@solver-cycle@d2) edge [DataLine] (cycle@d2)
(cycle@d1-cycle@solver) edge [DataLine] (cycle@solver)
(cycle@solver-cycle@d1) edge [DataLine] (cycle@d1)
(cycle@d2-cycle@solver) edge [DataLine] (cycle@solver)
(cycle@d1-obj@cmp) edge [DataLine] (obj@cmp)
(cycle@d1-con@cmp1) edge [DataLine] (con@cmp1)
(cycle@d1-cycle@d2) edge [DataLine] (cycle@d2)
(cycle@d2-obj@cmp) edge [DataLine] (obj@cmp)
(cycle@d2-con@cmp2) edge [DataLine] (con@cmp2)
(cycle@d2-cycle@d1) edge [DataLine] (cycle@d1)
(indeps-cycle@d1) edge [DataLine] (cycle@d1)
(indeps-obj@cmp) edge [DataLine] (obj@cmp)
(indeps-cycle@d2) edge [DataLine] (cycle@d2);
\end{pgfonlayer}
\end{tikzpicture}"""
def filter_lines(lns):
# Empty lines are excluded.
# Leading and trailing whitespaces are removed
# Comments are removed.
return [ln.strip() for ln in lns if ln.strip() and not ln.strip().startswith('%')]
filename = 'pyxdsm_mda_tikz'
out_format = PYXDSM_OUT
p = om.Problem(model=SellarMDA())
p.setup()
p.final_setup()
# Write output
write_xdsm(p, filename=filename, out_format=out_format, quiet=QUIET, show_browser=SHOW, include_solver=True)
# Check if file was created
tikz_file = filename + '.tikz'
self.assertTrue(os.path.isfile(tikz_file))
sample_lines = sample_tikz_txt.split('\n')
sample_lines = filter_lines(sample_lines)
with open(tikz_file, "r") as f:
new_lines = filter_lines(f.readlines())
no_match_sample = [] # Sample text
no_match_new = [] # New text
for new_line, sample_line in zip(new_lines, sample_lines):
if new_line.startswith(r"\input{"):
continue
if new_line != sample_line: # else everything is okay
# This can be because of the different ordering of lines or because of an error.
no_match_sample.append(new_line)
no_match_new.append(sample_line)
# Sort both sets of suspicious lines
no_match_sample.sort()
no_match_new.sort()
for sample_line, new_line in zip(no_match_sample, no_match_new):
# Now the lines should match, if only the ordering was different
self.assertEqual(sample_line, new_line)
# To be sure, check the length, otherwise a missing last line could get unnoticed because of using zip
self.assertEqual(len(new_lines), len(sample_lines))