_validate_connectivity(image_dim, connectivity, offset)

Parameters

image_dim : int

The number of dimensions of the input image.

connectivity : int, array, or None

The neighborhood connectivity. An integer is interpreted as in scipy.ndimage.generate_binary_structure , as the maximum number of orthogonal steps to reach a neighbor. An array is directly interpreted as a structuring element and its shape is validated against the input image shape. None is interpreted as a connectivity of 1.

offset : tuple of int, or None

The coordinates of the center of the structuring element.

Raises

ValueError:

If the image dimension and the connectivity or offset dimensions don't match.

Returns

c_connectivity : array of bool

The structuring element corresponding to the input :None:None:`connectivity`.

offset : array of int

The offset corresponding to the center of the structuring element.

Convert any valid connectivity to a structuring element and offset.

Examples

See :

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

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File: /skimage/morphology/_util.py#8
type: <class 'function'>
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