21758dd81de16d2bfdcf1a0d5d6d98f25a2e5868,autosklearn/metrics/util.py,,sanitize_array,#Any#,12

Before Change

    :return:
    
    a = np.ravel(array)
    maxi = np.nanmax((filter(lambda x: x != float("inf"), a))
                     )  // Max except NaN and Inf
    mini = np.nanmin((filter(lambda x: x != float("-inf"), a))
                     )  // Mini except NaN and Inf
    array[array == float("inf")] = maxi

After Change

    //mini = np.nanmin((filter(lambda x: x != float("-inf"), a))
    //                 )  // Mini except NaN and Inf
    maxi = np.nanmax(a[np.isfinite(a)])
    mini = np.nanmin(a[np.isfinite(a)])
    array[array == float("inf")] = maxi
    array[array == float("-inf")] = mini
    mid = (maxi + mini) / 2
    array[np.isnan(array)] = mid

Instances