test.py

        def lambda_apriori_ratio_from_interval(value: float, interval: Interval) -> float:
            """
            Returns 1 for a value at the center of the interval
            Return 1.3 for a value at the border of the interval
            i.e the values at the border are multiplied by 1.3
            (and are thus less likely to be a minimum)
            """
            # x is between -0.5 and 0.5 (0 is the interval center)
            x = math_utils.unlerp(interval.Min, interval.Max, value) - 0.5
            border_increase_ratio = 0.3
            anti_hat = 1. - math_utils.hat_width_1(x)
            k =  1. + anti_hat * border_increase_ratio
            return k
            
      
 for v in src_values:
     patch_comparison_result = lambda_patch_comparison_result_for_value(v)
     diff_value_with_apriori = patch_comparison_result.mDiffValue * lambda_apriori_ratio_from_interval(v, value_search_interval)
     diff_values.append(diff_value_with_apriori)