Runs python script in specified argument combinations and produces a pandas dataframe of all results.
Project description
args_to_db - Data Generation Tool for Argument Optimisation
pip install args_to_db
You want to analyze a (python) script for different arguments/settings? - Argument optimization is becoming more and more important in many application areas. args_to_db is an attempt to generalize and simplify the process of running a programm in different modes or configurations and combining the resulting datasets to allow for further analysis.
When should I use args_to_db?
You have a programm which is highly dependent on parameters and arguments, for example a solver framework for linear system of equations. Different inputs vary performance of solving methods dramatically. So we want to optimize the solver and preonditioner used for a specific linear system of equations.
This is performed once and results in preferences which are then to be used automatically by the programm. args_to_db simplifies the process of argument variation and dataset generation.
How to use args_to_db?
commands = arg('python3') + arg('solver.py') + \
option('--solver', ['cg', 'jacobi']) + \
option('--preconditioner', ['gs', 'spai']) + \
flag('--log', vary=False)
run(commands, threads=4)
How to report results?
The parameters on which we want to optimize need to be logged and combined later on. args_to_db makes this very easy.
add_result('solver_time', 20.3)
add_result('solver_state', 'converged')
write_results(__file__, args)
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