**Visualize**

- Draw a network manually
- Draw a network as a graph, as a traditional tree or as radial tree
- Import network data as a list of edges, as an adjacency list, or as an adjacency matrix
- Import x,y-coordinates of the vertices (f.ex. vertices that represent locations on a map can be set to their latitude and longitude coordinates)
- Open a network file made in DiscretePath (.gdp extension)
- Categories can be assigned to vertices.
- Vertices can be organized in sub and super categories
- Vertices can be organized in groups (improves graph layout, visualization and analysis)
- Many options to modify the layout of a network, of the vertices and edges
- The option is available to display grid lines in the canvas

**Analyze**

- Shortest path
- Longest path
- Maximum flow through the edges
- Maximum flow through both the edges and vertices
- Minimum s-t cut
- Global minimum cut
- Minimum spanning tree
- Degree centrality
- Betweenness centrality (vertex and edge betweenness)
- Closeness centrality
- Clustering (based on ‘nearest neighbor’, ‘hitting time’ and ‘random walk’)
- Ability to perform sequential clustering to reduce the number of clusters and gain deeper insight into network structure
- Crossing of edges (only suitable for smaller graphs)
- Random graphs can be created (for example, these can be used as an analysis tool)
- Random walk
- ‘Maximum clique’ and ‘All cliques
**‘**: The maximum clique is used in many applications to identify the most connected and interactive parts in biological, collaboration, interaction, technological, social, ….. networks. The identification of all cliques allows to identify also the smaller interactive parts of a network.

*Networks up to 20,000 edges (the number of vertices has less impact) can be imported and visualized within a reasonable amount of time. It is possible to work with larger networks (f.ex. 40,000 edges and about 10,000 vertices), but the visualization of these very large networks takes some time. Most analyses can be performed on larger graphs, except when non-polynomial algorithms are used (for example, clustering using random walks).*

**Artificial intelligence**

- Decision trees (for categorical and numerical data)
- Categorical trees
- Regression trees

- Built into most of the ‘analysis functions’.

**General**

- Export a network as a ‘.txt’ or as a ‘.csv’ file
- Layout preferences: user and network specific
- Backups are made before calculations or when changes in the overall layout are made
- Full featured undo/redo
- Zoom function
- Search function
- DiscretePath is available for MacOS and Windows
- and ………. much more

To explore the features of DiscretePath consult the user guide (User guide)

Example graphs and other resources can be downloaded: Resources

Go to Welcome page