scipy.ndimage.variance#
- scipy.ndimage.variance(input, labels=None, index=None)[source]#
Calculate the variance of the values of an N-D image array, optionally at specified sub-regions.
- Parameters:
- inputarray_like
Nd-image data to process.
- labelsarray_like, optional
Labels defining sub-regions in input. If not None, must be same shape as input.
- indexint or sequence of ints, optional
labels to include in output. If None (default), all values where labels is non-zero are used.
- Returns:
- variancefloat or ndarray
Values of variance, for each sub-region if labels and index are specified.
See also
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.variance(a) 7.609375
Features to process can be specified using labels and index:
>>> lbl, nlbl = ndimage.label(a) >>> ndimage.variance(a, lbl, index=np.arange(1, nlbl+1)) array([ 2.1875, 2.25 , 9. ])
If no index is given, all non-zero labels are processed:
>>> ndimage.variance(a, lbl) 6.1875