def test_profile_with_history():
objective = rosen_for_sensi(max_sensi_order=2, integrated=False)['obj']
with warnings.catch_warnings():
warnings.simplefilter("ignore")
(problem, result, optimizer) = create_optimization_results(objective,
dim_full=5)
profile_options = profile.ProfileOptions(
min_step_size=0.0005,
delta_ratio_max=0.05,
default_step_size=0.005,
ratio_min=0.03,
)
problem.fix_parameters(
[0, 3],
[
result.optimize_result.list[0].x[0],
result.optimize_result.list[0].x[3],
],
)
problem.objective.history = pypesto.MemoryHistory({'trace_record': True})
profile.parameter_profile(
problem=problem,
result=result,
optimizer=optimizer,
profile_index=np.array([0, 2, 4]),
result_index=0,
profile_options=profile_options,
filename=None,
)
def test_selected_profiling(self):
# create options in order to ensure a short computation time
options = profile.ProfileOptions(
default_step_size=0.02,
min_step_size=0.005,
max_step_size=1.0,
step_size_factor=1.5,
delta_ratio_max=0.2,
ratio_min=0.3,
reg_points=5,
reg_order=2,
)
# 1st run of profiling, computing just one out of two profiles
result = profile.parameter_profile(
problem=self.problem,
result=self.result,
optimizer=self.optimizer,
profile_index=np.array([1]),
next_guess_method='fixed_step',
result_index=1,
profile_options=options,
filename=None,
)
self.assertIsInstance(result.profile_result.list[0][1],
pypesto.ProfilerResult)
self.assertIsNone(result.profile_result.list[0][0])
# 2nd run of profiling, appending to an existing list of profiles
# using another algorithm and another optimum
result = profile.parameter_profile(
problem=self.problem,
result=result,
optimizer=self.optimizer,
profile_index=np.array([0]),
result_index=2,
profile_list=0,
profile_options=options,
filename=None,
)
self.assertIsInstance(result.profile_result.list[0][0],
pypesto.ProfilerResult)
# 3rd run of profiling, opening a new list, using the default algorithm
result = profile.parameter_profile(
problem=self.problem,
result=result,
optimizer=self.optimizer,
next_guess_method='fixed_step',
profile_index=np.array([0]),
profile_options=options,
filename=None,
)
# check result
self.assertIsInstance(result.profile_result.list[1][0],
pypesto.ProfilerResult)
self.assertIsNone(result.profile_result.list[1][1])
def test_profile_with_history():
objective = test_objective.rosen_for_sensi(max_sensi_order=2,
integrated=False)['obj']
with warnings.catch_warnings():
warnings.simplefilter("ignore")
(problem, result, optimizer) = \
create_optimization_results(objective)
profile_options = profile.ProfileOptions(min_step_size=0.0005,
delta_ratio_max=0.05,
default_step_size=0.005,
ratio_min=0.03)
problem.objective.history = pypesto.MemoryHistory({'trace_record': True})
profile.parameter_profile(problem=problem,
result=result,
optimizer=optimizer,
profile_index=np.array(
[1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0]),
result_index=0,
profile_options=profile_options)