(avranks, n, alpha="0.05", test="nemenyi")
return cd
Returns critical difference for Nemenyi or Bonferroni-Dunn test
    according to given alpha (either alpha="0.05" or alpha="0.1") for average
    ranks and number of tested datasets N. Test can be either "nemenyi" for
    for Nemenyi two tailed test or "bonferroni-dunn" for Bonferroni-Dunn test.
Returns critical difference for Nemenyi or Bonferroni-Dunn test
    according to given alpha (either alpha="0.05" or alpha="0.1") for average
    ranks and number of tested datasets N. Test can be either "nemenyi" for
    for Nemenyi two tailed test or "bonferroni-dunn" for Bonferroni-Dunn test.
Returns critical difference for Nemenyi or Bonferroni - Dunn test according to given alpha ( either alpha = 0 . 05 or alpha = 0 . 1 ) for average ranks and number of tested datasets N . Test can be either nemenyi for for Nemenyi two tailed test or bonferroni - dunn for Bonferroni - Dunn test .
def compute_CD(avranks, n, alpha="0.05", test="nemenyi"):
    """
    Returns critical difference for Nemenyi or Bonferroni-Dunn test
    according to given alpha (either alpha="0.05" or alpha="0.1") for average
    ranks and number of tested datasets N. Test can be either "nemenyi" for
    for Nemenyi two tailed test or "bonferroni-dunn" for Bonferroni-Dunn test.
    """
    k = len(avranks)
    d = {("nemenyi", "0.05"): [0, 0, 1.959964, 2.343701, 2.569032, 2.727774,
                               2.849705, 2.94832, 3.030879, 3.101730, 3.163684,
                               3.218654, 3.268004, 3.312739, 3.353618, 3.39123,
                               3.426041, 3.458425, 3.488685, 3.517073,
                               3.543799],
         ("nemenyi", "0.1"): [0, 0, 1.644854, 2.052293, 2.291341, 2.459516,
                              2.588521, 2.692732, 2.779884, 2.854606, 2.919889,
                              2.977768, 3.029694, 3.076733, 3.119693, 3.159199,
                              3.195743, 3.229723, 3.261461, 3.291224, 3.319233],
         ("bonferroni-dunn", "0.05"): [0, 0, 1.960, 2.241, 2.394, 2.498, 2.576,
                                       2.638, 2.690, 2.724, 2.773],
         ("bonferroni-dunn", "0.1"): [0, 0, 1.645, 1.960, 2.128, 2.241, 2.326,
                                      2.394, 2.450, 2.498, 2.539]}
    q = d[(test, alpha)]
    cd = q[k] * (k * (k + 1) / (6.0 * n)) ** 0.5
    return cd
def compute_CD ( avranks , n , alpha = "0.05" , test = "nemenyi" ) : k = len ( avranks ) d = { ( "nemenyi" , "0.05" ) : [ 0 , 0 , 1.959964 , 2.343701 , 2.569032 , 2.727774 , 2.849705 , 2.94832 , 3.030879 , 3.101730 , 3.163684 , 3.218654 , 3.268004 , 3.312739 , 3.353618 , 3.39123 , 3.426041 , 3.458425 , 3.488685 , 3.517073 , 3.543799 ] , ( "nemenyi" , "0.1" ) : [ 0 , 0 , 1.644854 , 2.052293 , 2.291341 , 2.459516 , 2.588521 , 2.692732 , 2.779884 , 2.854606 , 2.919889 , 2.977768 , 3.029694 , 3.076733 , 3.119693 , 3.159199 , 3.195743 , 3.229723 , 3.261461 , 3.291224 , 3.319233 ] , ( "bonferroni-dunn" , "0.05" ) : [ 0 , 0 , 1.960 , 2.241 , 2.394 , 2.498 , 2.576 , 2.638 , 2.690 , 2.724 , 2.773 ] , ( "bonferroni-dunn" , "0.1" ) : [ 0 , 0 , 1.645 , 1.960 , 2.128 , 2.241 , 2.326 , 2.394 , 2.450 , 2.498 , 2.539 ] } q = d [ ( test , alpha ) ] cd = q [ k ] * ( k * ( k + 1 ) / ( 6.0 * n ) ) ** 0.5 return cd