def create_bonus_plots()

in src/minmaxML.py [0:0]

• 11 lines of code
• 3 McCabe index (conditional complexity)

def create_bonus_plots(extra_error_types, numgroups, specific_errors, index, groupsize, total_steps):
    """
    :return: List of bonus plots which is defined by a tuple of (err_type, group_errs, pop_errs, pop_err_type)
    """
    bonus_plots = []
    for err_type in extra_error_types:
        # Determine pop error type
        if err_type in ['FP', 'FN', 'FP-Log-Loss', 'FN-Log-Loss']:
            pop_err_type = '0/1 Loss'
        else:
            pop_err_type = err_type

        grp_errs = compute_mixture_group_errors(numgroups, specific_errors[err_type], index, groupsize, total_steps)
        pop_errs = compute_mixture_pop_errors(specific_errors[pop_err_type], total_steps)
        bonus_plots.append((err_type, grp_errs, pop_errs, pop_err_type))
    return bonus_plots