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Module « scipy.ndimage »

Fonction standard_deviation - module scipy.ndimage

Signature de la fonction standard_deviation

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

Description

help(scipy.ndimage.standard_deviation)

Calculate the standard deviation of the values of an N-D image array,
optionally at specified sub-regions.

Parameters
----------
input : array_like
    N-D image data to process.
labels : array_like, optional
    Labels to identify sub-regions in `input`.
    If not None, must be same shape as `input`.
index : int or sequence of ints, optional
    `labels` to include in output. If None (default), all values where
    `labels` is non-zero are used.

Returns
-------
standard_deviation : float or ndarray
    Values of standard deviation, for each sub-region if `labels` and
    `index` are specified.

See Also
--------
label, variance, maximum, minimum, extrema

Examples
--------
>>> import numpy as np
>>> a = np.array([[1, 2, 0, 0],
...               [5, 3, 0, 4],
...               [0, 0, 0, 7],
...               [9, 3, 0, 0]])
>>> from scipy import ndimage
>>> ndimage.standard_deviation(a)
2.7585095613392387

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

>>> lbl, nlbl = ndimage.label(a)
>>> ndimage.standard_deviation(a, lbl, index=np.arange(1, nlbl+1))
array([ 1.479,  1.5  ,  3.   ])

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

>>> ndimage.standard_deviation(a, lbl)
2.4874685927665499

Vous êtes un professionnel et vous avez besoin d'une formation ? Programmation Python
Les compléments Voir le programme détaillé