def _getSmartIndenter(indenterName, qpart, indenter):
    """Get indenter by name.
    Available indenters are none, normal, cstyle, haskell, lilypond, lisp, python, ruby, xml
    Indenter name is not case sensitive
    Raise KeyError if not found
    indentText is indentation, which shall be used. i.e. '\t' for tabs, '    ' for 4 space symbols
    """
    indenterName = indenterName.lower()

    if indenterName in ('haskell', 'lilypond'):  # not supported yet
        logger.warning('Smart indentation for %s not supported yet. But you could be a hero who implemented it' % indenterName)
        from qutepart.indenter.base import IndentAlgNormal as indenterClass
    elif 'none' == indenterName:
        from qutepart.indenter.base import IndentAlgBase as indenterClass
    elif 'normal' == indenterName:
        from qutepart.indenter.base import IndentAlgNormal as indenterClass
    elif 'cstyle' == indenterName:
        from qutepart.indenter.cstyle import IndentAlgCStyle as indenterClass
    elif 'python' == indenterName:
        from qutepart.indenter.python import IndentAlgPython as indenterClass
    elif 'ruby' == indenterName:
        from qutepart.indenter.ruby import IndentAlgRuby as indenterClass
    elif 'xml' == indenterName:
        from qutepart.indenter.xmlindent import IndentAlgXml as indenterClass
    elif 'haskell' == indenterName:
        from qutepart.indenter.haskell import IndenterHaskell as indenterClass
    elif 'lilypond' == indenterName:
        from qutepart.indenter.lilypond import IndenterLilypond as indenterClass
    elif 'lisp' == indenterName:
        from qutepart.indenter.lisp import IndentAlgLisp as indenterClass
    elif 'scheme' == indenterName:
        from qutepart.indenter.scheme import IndentAlgScheme as indenterClass
    else:
        raise KeyError("Indenter %s not found" % indenterName)

    return indenterClass(qpart, indenter)
def apply_ktst(K, y, iterations=10000, subjects=False, verbose=True):
    """
    Compute MMD^2_u, its null distribution and the p-value of the
    kernel two-sample test.

    Parameters:
    ----------
    K: array-like
        Kernel matrix
    y: array_like
        class labels
    verbose: bool
        Verbosity

    Returns:
    -------
    mmd2u: float
        MMD^2_u value.
    acc_null: array
        Null distribution of the MMD^2_u
    p_value: float
         p-value
    """
    assert len(np.unique(y)) == 2, 'KTST only works on binary problems'

    # Assuming that the first m rows of the kernel matrix are from one
    # class and the other n rows from the second class.
    m = len(y[y == 0])
    n = len(y[y == 1])
    mmd2u = MMD2u(K, m, n)
    if verbose:
        print("MMD^2_u = %s" % mmd2u)
        print("Computing the null distribution.")
    if subjects:
        perms = [permutation_subjects_ktst(y) for i in range(iterations)]
        mmd2u_null = compute_null_distribution_given_permutations(K, m, n,
                                                                  perms,
                                                                  iterations)
    else:
        mmd2u_null = compute_null_distribution(K, m, n, iterations,
                                               verbose=verbose)

    p_value = max(1.0/iterations, (mmd2u_null > mmd2u).sum()
                  / float(iterations))
    if verbose:
        print("p-value ~= %s \t (resolution : %s)" % (p_value, 1.0/iterations))

    return mmd2u, mmd2u_null, p_value