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importcocoex# experimentation moduleimportscipy.optimize# to define the solver to be benchmarked### inputsuite_name="bbob"fmin=scipy.optimize.fmin# optimizer to be benchmarked### preparesuite=cocoex.Suite(suite_name, "", "")
observer=cocoex.Observer(suite_name, "")
### goforprobleminsuite: # this loop may take several minutes or moreproblem.observe_with(observer) # generates the data for cocoppfmin(problem, problem.initial_solution, disp=False)
Missing functionalities are (in order of supposed importance)
restarts until enough successes are observed (like here)
meaningful output folder name
batch distribution (and accepting the batch number as argument)
MKL bug fix?
timing printout
saving of solver output and termination flags for later investigation
saving of setting when called with parameters (in particular budget_multiplier)
We may have several "examples" with increasing functionality (and complexity). How many seems a good number? Currently we have two, example_experiment_for_beginners and example_experiment2 (and also example_experiment_non_anytime for benchmarking non-anytime algorithms).
The text was updated successfully, but these errors were encountered:
I have the following examples now, the next generally includes the functionality of the previous.
Starting from the script with 35 lines without the file docstring and
restarts until enough successes are observed or the budget is exhausted (like here)
meaningful output folder name
65 lines (+30)
batch distribution and reading the batch number as script argument
saving of setting when called with parameters (in particular budget_multiplier)
77 lines (+12)
timings printout
84 lines (+7)
saving of solver output like the termination flags for later investigation
122 lines (+38)
code for multiple solvers and space to implement calling code for another solver
The suggestion by @brockho and @ttusar is to have a separate file for the MKL bug fix and two scripts, one with 35 lines and one with full functionality.
Name suggestion: example_experiment_simple.py, example_experiment_complete.py.
A most minimalistic example experiment looks like this
Missing functionalities are (in order of supposed importance)
We may have several "examples" with increasing functionality (and complexity). How many seems a good number? Currently we have two,
example_experiment_for_beginners
andexample_experiment2
(and alsoexample_experiment_non_anytime
for benchmarking non-anytime algorithms).The text was updated successfully, but these errors were encountered: