scientific parameter sweeper, with easy debugging capabilities and an interface for most scientific queuing systems.
scisweeper is a utility for parameter sweeps in a scientific environment. By defining the writeinput and collectoutput function, as well as a link to the executable the users can link scisweeper to their own code. Afterwards scisweeper can execute the parameter sweep either locally using a given number of parallel threads or submit the individual calculations to a queuing system like LFS, MOAB, SGE, SLURM, or TORQUE using the built-in interface to pysqa. After the calculations are finished the results are summarized in a pandas.DataFrame, which makes them easily accessible for machine learning tools like tensorflow or pytorch. Coming from a scientific environment scisweeper was develop with a focus on debugging. Broken jobs can be identified, executed again manually or deleted and in case you need to update the collect_output function there is no need to execute the calculations again, the output can be parsed separatly to update the results in the pandas.DataFrame.
