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Module « scipy.ndimage »

Fonction maximum_position - module scipy.ndimage

Signature de la fonction maximum_position

def maximum_position(input, labels=None, index=None) 

Description

help(scipy.ndimage.maximum_position)

Find the positions of the maximums of the values of an array at labels.

For each region specified by `labels`, the position of the maximum
value of `input` within the region is returned.

Parameters
----------
input : array_like
    Array_like of values.
labels : array_like, optional
    An array of integers marking different regions over which the
    position of the maximum value of `input` is to be computed.
    `labels` must have the same shape as `input`. If `labels` is not
    specified, the location of the first maximum over the whole
    array is returned.

    The `labels` argument only works when `index` is specified.
index : array_like, optional
    A list of region labels that are taken into account for finding the
    location of the maxima. If `index` is None, the first maximum
    over all elements where `labels` is non-zero is returned.

    The `index` argument only works when `labels` is specified.

Returns
-------
output : list of tuples of ints
    List of tuples of ints that specify the location of maxima of
    `input` over the regions determined by `labels` and whose index
    is in `index`.

    If `index` or `labels` are not specified, a tuple of ints is
    returned specifying the location of the ``first`` maximal value
    of `input`.

See Also
--------
label, minimum, median, maximum_position, extrema, sum, mean, variance,
standard_deviation

Examples
--------
>>> from scipy import ndimage
>>> import numpy as np
>>> a = np.array([[1, 2, 0, 0],
...               [5, 3, 0, 4],
...               [0, 0, 0, 7],
...               [9, 3, 0, 0]])
>>> ndimage.maximum_position(a)
(3, 0)

Features to process can be specified using `labels` and `index`:

>>> lbl = np.array([[0, 1, 2, 3],
...                 [0, 1, 2, 3],
...                 [0, 1, 2, 3],
...                 [0, 1, 2, 3]])
>>> ndimage.maximum_position(a, lbl, 1)
(1, 1)

If no index is given, non-zero `labels` are processed:

>>> ndimage.maximum_position(a, lbl)
(2, 3)

If there are no maxima, the position of the first element is returned:

>>> ndimage.maximum_position(a, lbl, 2)
(0, 2)

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