def finalized_canonical_averages_dtype(spanning_cluster=True):
    """
    The NumPy Structured Array type for finalized canonical averages over
    several runs

    Helper function

    Parameters
    ----------
    spanning_cluster : bool, optional
        Whether to detect a spanning cluster or not.
        Defaults to ``True``.

    Returns
    -------
    ret : list of pairs of str
        A list of tuples of field names and data types to be used as ``dtype``
        argument in numpy ndarray constructors

    See Also
    --------
    http://docs.scipy.org/doc/numpy/user/basics.rec.html
    canonical_averages_dtype
    """
    fields = list()
    fields.extend([
        ('number_of_runs', 'uint32'),
        ('p', 'float64'),
        ('alpha', 'float64'),
    ])
    if spanning_cluster:
        fields.extend([
            ('percolation_probability_mean', 'float64'),
            ('percolation_probability_std', 'float64'),
            ('percolation_probability_ci', '(2,)float64'),
        ])
    fields.extend([
        ('percolation_strength_mean', 'float64'),
        ('percolation_strength_std', 'float64'),
        ('percolation_strength_ci', '(2,)float64'),
        ('moments_mean', '(5,)float64'),
        ('moments_std', '(5,)float64'),
        ('moments_ci', '(5,2)float64'),
    ])
    return _ndarray_dtype(fields)
def finalized_canonical_averages_dtype(spanning_cluster=True):
    """
    The NumPy Structured Array type for finalized canonical averages over
    several runs

    Helper function

    Parameters
    ----------
    spanning_cluster : bool, optional
        Whether to detect a spanning cluster or not.
        Defaults to ``True``.

    Returns
    -------
    ret : list of pairs of str
        A list of tuples of field names and data types to be used as ``dtype``
        argument in numpy ndarray constructors

    See Also
    --------
    http://docs.scipy.org/doc/numpy/user/basics.rec.html
    canonical_averages_dtype
    """
    fields = list()
    fields.extend([
        ('number_of_runs', 'uint32'),
        ('p', 'float64'),
        ('alpha', 'float64'),
    ])
    if spanning_cluster:
        fields.extend([
            ('percolation_probability_mean', 'float64'),
            ('percolation_probability_std', 'float64'),
            ('percolation_probability_ci', '(2,)float64'),
        ])
    fields.extend([
        ('percolation_strength_mean', 'float64'),
        ('percolation_strength_std', 'float64'),
        ('percolation_strength_ci', '(2,)float64'),
        ('moments_mean', '(5,)float64'),
        ('moments_std', '(5,)float64'),
        ('moments_ci', '(5,2)float64'),
    ])
    return _ndarray_dtype(fields)
def finalized_canonical_averages_dtype ( spanning_cluster = True ) : fields = list ( ) fields . extend ( [ ( 'number_of_runs' , 'uint32' ) , ( 'p' , 'float64' ) , ( 'alpha' , 'float64' ) , ] ) if spanning_cluster : fields . extend ( [ ( 'percolation_probability_mean' , 'float64' ) , ( 'percolation_probability_std' , 'float64' ) , ( 'percolation_probability_ci' , '(2,)float64' ) , ] ) fields . extend ( [ ( 'percolation_strength_mean' , 'float64' ) , ( 'percolation_strength_std' , 'float64' ) , ( 'percolation_strength_ci' , '(2,)float64' ) , ( 'moments_mean' , '(5,)float64' ) , ( 'moments_std' , '(5,)float64' ) , ( 'moments_ci' , '(5,2)float64' ) , ] ) return _ndarray_dtype ( fields )
The NumPy Structured Array type for finalized canonical averages over
    several runs

    Helper function

    Parameters
    ----------
    spanning_cluster : bool, optional
        Whether to detect a spanning cluster or not.
        Defaults to ``True``.

    Returns
    -------
    ret : list of pairs of str
        A list of tuples of field names and data types to be used as ``dtype``
        argument in numpy ndarray constructors

    See Also
    --------
    http://docs.scipy.org/doc/numpy/user/basics.rec.html
    canonical_averages_dtype
The NumPy Structured Array type for finalized canonical averages over several runs