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Module « scipy.cluster.hierarchy »

Fonction inconsistent - module scipy.cluster.hierarchy

Signature de la fonction inconsistent

def inconsistent(Z, d=2) 

Description

help(scipy.cluster.hierarchy.inconsistent)

Calculate inconsistency statistics on a linkage matrix.

Parameters
----------
Z : ndarray
    The :math:`(n-1)` by 4 matrix encoding the linkage (hierarchical
    clustering).  See `linkage` documentation for more information on its
    form.
d : int, optional
    The number of links up to `d` levels below each non-singleton cluster.

Returns
-------
R : ndarray
    A :math:`(n-1)` by 4 matrix where the ``i``'th row contains the link
    statistics for the non-singleton cluster ``i``. The link statistics are
    computed over the link heights for links :math:`d` levels below the
    cluster ``i``. ``R[i,0]`` and ``R[i,1]`` are the mean and standard
    deviation of the link heights, respectively; ``R[i,2]`` is the number
    of links included in the calculation; and ``R[i,3]`` is the
    inconsistency coefficient,

    .. math:: \frac{\mathtt{Z[i,2]} - \mathtt{R[i,0]}} {R[i,1]}

Notes
-----
This function behaves similarly to the MATLAB(TM) ``inconsistent``
function.

Examples
--------
>>> from scipy.cluster.hierarchy import inconsistent, linkage
>>> from matplotlib import pyplot as plt
>>> X = [[i] for i in [2, 8, 0, 4, 1, 9, 9, 0]]
>>> Z = linkage(X, 'ward')
>>> print(Z)
[[ 5.          6.          0.          2.        ]
 [ 2.          7.          0.          2.        ]
 [ 0.          4.          1.          2.        ]
 [ 1.          8.          1.15470054  3.        ]
 [ 9.         10.          2.12132034  4.        ]
 [ 3.         12.          4.11096096  5.        ]
 [11.         13.         14.07183949  8.        ]]
>>> inconsistent(Z)
array([[ 0.        ,  0.        ,  1.        ,  0.        ],
       [ 0.        ,  0.        ,  1.        ,  0.        ],
       [ 1.        ,  0.        ,  1.        ,  0.        ],
       [ 0.57735027,  0.81649658,  2.        ,  0.70710678],
       [ 1.04044011,  1.06123822,  3.        ,  1.01850858],
       [ 3.11614065,  1.40688837,  2.        ,  0.70710678],
       [ 6.44583366,  6.76770586,  3.        ,  1.12682288]])

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