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Deep Learning avec Python
et Keras et Tensorflow
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Module « scipy.signal »
Signature de la fonction order_filter
def order_filter(a, domain, rank)
Description
help(scipy.signal.order_filter)
Perform an order filter on an N-D array.
Perform an order filter on the array in. The domain argument acts as a
mask centered over each pixel. The non-zero elements of domain are
used to select elements surrounding each input pixel which are placed
in a list. The list is sorted, and the output for that pixel is the
element corresponding to rank in the sorted list.
Parameters
----------
a : ndarray
The N-dimensional input array.
domain : array_like
A mask array with the same number of dimensions as `a`.
Each dimension should have an odd number of elements.
rank : int
A non-negative integer which selects the element from the
sorted list (0 corresponds to the smallest element, 1 is the
next smallest element, etc.).
Returns
-------
out : ndarray
The results of the order filter in an array with the same
shape as `a`.
Examples
--------
>>> import numpy as np
>>> from scipy import signal
>>> x = np.arange(25).reshape(5, 5)
>>> domain = np.identity(3)
>>> x
array([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19],
[20, 21, 22, 23, 24]])
>>> signal.order_filter(x, domain, 0)
array([[ 0, 0, 0, 0, 0],
[ 0, 0, 1, 2, 0],
[ 0, 5, 6, 7, 0],
[ 0, 10, 11, 12, 0],
[ 0, 0, 0, 0, 0]])
>>> signal.order_filter(x, domain, 2)
array([[ 6, 7, 8, 9, 4],
[ 11, 12, 13, 14, 9],
[ 16, 17, 18, 19, 14],
[ 21, 22, 23, 24, 19],
[ 20, 21, 22, 23, 24]])
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Les fondamentaux
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