It is assumed that you have a connectivity matrix and node positions stored in Matlab files (see examples/matlab_import/data). Here you learn how to directly load these data in ConnectomeViewer and visualize the network.

The following code will do

```
import networkx as nx
import scipy.io as sio
M = sio.loadmat('data/M.mat', matlab_compatible=True)
A = M['ConMatrix']
N = sio.loadmat('data/P.mat', matlab_compatible=True)
P = N['Coordinate']
cfile.add_network_from_matrix_with_pos(name='Network', matrix = A, pos = P, directed = False)
cfile.networks[0].active = True
cfile.networks[0].select_all()
```

You can either type the code line-by-line in the Ipython console or store it as a script (Menu: File->New Text File. Ctrl-S to store it as .py file. Run it with Ctrl-R).

Alternatively, you can run the script in the ConnectomeViewer IPython shell with *run -i myscript.py*.
To get to know the current path, type *pwd*. Change paths using the *cd* command.

- Of course you have to adapt the paths to your Matlab files and the names of your arrays. You can check the loaded data with::
- print M print M.keys()

Dive into the dictionary accordingly.

If you have a directed network (asymmetric matrix, set directed = True), the edges are
still displayed without arrows. But you can change this by opening the the *Mayavi Visualization Tree*
(Menu: View->Other). Double-click on Connections (parent node is Connectivity Source).
The *Mayavi Object Editor* show the changeable attributes. Under tab Glyph, subtab Glyph Source,
you select *Arrow Source*. Below you can adjust the look of the arrows of your directed network.

See also the *Graph Layouting Tutorial* to create different graph layouts.