`scipy.ndimage._measurements:standard_deviation`

source: build-install/usr/lib/python3.14/site-packages/scipy/ndimage/_measurements.py:866

Signature

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

Summary

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.

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)

✗

np.float64(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)

✗

np.float64(2.48746859276655)

Aliases

scipy.ndimage.standard_deviation