fitbenchmarking.results_processing.acc_table module

Accuracy table

class fitbenchmarking.results_processing.acc_table.AccTable(results, best_results, options, group_dir, pp_locations, table_name)

Bases: Table

The accuracy results are calculated by evaluating the cost function with the fitted parameters.

For Bayesian fitting, accuracy results represent the reciporcal of the confidence that the fitted parameter values are within \(2 \sigma\) of the expected parameter values (calculated using scipy.optimize.curve_fit).

cbar_title = 'Problem-Specific Cell Shading: Relative Accuracy'

get_value(result)

Gets the main value to be reported in the tables for a given result

Note that the first value (relative accuracy) will be used in the default colour handling.

Parameters:

result (FittingResult) – The result to generate the values for.

Returns:

The normalised chi sq with respect to the smallest accuracy value and absolute accuracy for the result.

Return type:

tuple(float, float)

name = 'acc'