# Skeleton Network

build net work from nd skeleton image

### graph = sknw.build_sknw(ske， multi=False)

ske:should be a nd skeleton image

multi:if True，a multigraph is retured, which allows more than one edge between two nodes and self-self edge. default is False.

return:is a networkx Graph object

### graph detail:

graph.node[id]['pts'] :Numpy(x, n), coordinates of nodes points

graph.node[id]['o']:Numpy(n), centried of the node

graph.edge(id1, id2)['pts']:Numpy(x, n), sequence of the edge point

graph.edge(id1, id2)['weight']:float, length of this edge

if it's a multigraph, you must add a index after two node id to get the edge, like: graph.edge(id1, id2)[0].

### Build Graph:

build Graph by Skeleton, then plot as a vector Graph in matplotlib.

```
from skimage.morphology import skeletonize
from skimage import data
import sknw
# open and skeletonize
img = data.horse()
ske = skeletonize(~img).astype(np.uint16)
# build graph from skeleton
graph = sknw.build_sknw(ske)
# draw image
plt.imshow(img, cmap='gray')
# draw edges by pts
for (s,e) in graph.edges():
ps = graph[s][e]['pts']
plt.plot(ps[:,1], ps[:,0], 'green')
# draw node by o
node, nodes = graph.node, graph.nodes()
ps = np.array([node[i]['o'] for i in nodes])
plt.plot(ps[:,1], ps[:,0], 'r.')
# title and show
plt.title('Build Graph')
plt.show()
```

### Find Path

then you can use networkx do what you want

### 3D Skeleton

sknw can works on nd image, this is a 3d demo by mayavi

### About ImagePy

https://github.com/Image-Py/imagepy

ImagePy is my opensource image processihng framework. It is the ImageJ of Python, you can wrap any numpy based function esaily. And sknw is a sub module of ImagePy. You can use sknw without any code.