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: list[numpy.ndarray], solvers: list[str])

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 np.array[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 the values for each minimizer.

Parameters

results (dict[str, dict[str, list[utils.fitbm_result.FittingResult]]]) – The sorted results grouped by row and category

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 (dict[str, dict[str, list[utils.fitbm_result.FittingResult]]]) – The sorted results grouped by row and category

• fig_dir (str) – path to directory containing the figures

Returns

path to acc and runtime profile graphs

Return type

tuple(str, str)