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NotesParametersReturns

Notes

Parameters

input : array_like

Array_like of values. For each region specified by labels, the median value of input over the region is computed.

labels : array_like, optional

An array_like of integers marking different regions over which the median value of input is to be computed. labels must have the same shape as input. If labels is not specified, the median over the whole array is returned.

index : array_like, optional

A list of region labels that are taken into account for computing the medians. If index is None, the median over all elements where labels is non-zero is returned.

Returns

median : float or list of floats

List of medians of input over the regions determined by labels and whose index is in index. If index or labels are not specified, a float is returned: the median value of input if labels is None, and the median value of elements where labels is greater than zero if index is None.

See Also

extrema

label

maximum

mean

minimum

standard_deviation

sum

variance

Examples

from scipy import ndimage
import numpy as np
a = np.array([[1, 2, 0, 1],
              [5, 3, 0, 4],
              [0, 0, 0, 7],
              [9, 3, 0, 0]])
labels, labels_nb = ndimage.label(a)
labels

ndimage.median(a, labels=labels, index=np.arange(1, labels_nb + 1))

ndimage.median(a)

ndimage.median(a, labels=labels)

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them