fitbenchmarking.results_processing.performance_profiler module

Set up performance profiles for both accuracy and runtime tables

fitbenchmarking.results_processing.performance_profiler.create_plot(ax, step_values, solvers)

Function to draw the profile on a matplotlib axis

Parameters:
  • ax (an .axes.SubplotBase subclass of ~.axes.Axes (or a subclass of ~.axes.Axes)) – A matplotlib axis to be filled
  • step_values (list of float) – a sorted list of the values of the metric being profiled
  • solvers (list of strings) – A list of the labels for the different solvers
fitbenchmarking.results_processing.performance_profiler.plot(acc, runtime, fig_dir)

Function that generates profiler plots

Parameters:
  • acc (dict) – acc dictionary containing number of occurrences
  • runtime (dict) – runtime dictionary containing number of occurrences
  • fig_dir (str) – path to directory containing the figures
Returns:

path to acc and runtime profile graphs
Return type:

tuple(str, str)
fitbenchmarking.results_processing.performance_profiler.prepare_profile_data(results)

Helper function which generates acc and runtime dictionaries which contain number of occurrences that the minimizer produces a normalised result which is less than the bounds in PROFILER_BOUNDS

Parameters:results (list of list of fitbenchmarking.utils.fitbm_result.FittingResult) – results nested array of objects
Returns:dictionary containing number of occurrences
Return type:tuple(dict, dict)
fitbenchmarking.results_processing.performance_profiler.profile(results, fig_dir)

Function that generates profiler plots

Parameters:
  • results (list of list of fitbenchmarking.utils.fitbm_result.FittingResult) – results nested array of objects
  • fig_dir (str) – path to directory containing the figures
Returns:

path to acc and runtime profile graphs
Return type:

tuple(str, str)