FAQ: The Lens Layout

A couple of blog posts ago, we introduced our network clustering algorithm – to help uncover community structures in your data. At the time, we skipped over the cool new layout featured in the screengrab. Let’s take a closer look at…

The Lens Layout

Lens layout is another example of a force-directed layout, meaning it aims to produce a network layout with consistent link lengths and minimal overlaps. Specifically, the lens layout uses a combination of the repulsion/spring system in our standard layout, and an isometric approach to uniformly spread nodes within the circular drawing space.

The result is a layout algorithm that is computationally efficient and allows us to get a good ‘close up’ view of the nodes:

the standard (force-directed) layout
The standard layout, using a force model to layout nodes to detangle the network
The lens layout, which is also force-directed
The same data in the same drawing space with the Lens layout applied. We can view node detail more closely.

Data taken from this research paper.

How does the lens layout work?

The Lens layout is inspired by the Binary Stress (bStress) model, created by Yehuda Koren and Ali Civril. We have made a number of modifications and optimizations, but the overall approach is similar:

  • The nodes are uniformly arranged into a circular grid
  • The algorithm clusters connected nodes in varying degrees of tightness
  • The most efficient equilibrium between clustering and uniform spread is reached

As a consequence of this, we see that places densely connected nodes move towards the center, while less densely connected nodes are pushed to the periphery.

Why should I use it?

There are two scenarios in which this layout is particularly useful:

Large networks

The lens layout is relatively computationally cheap. That means it can be more easily scaled up to very large networks.

Disconnected networks or networks with singletons

Singletons and disconnected networks are treated the same way as connected networks. That means no packing algorithm is needed to retrieve and re-position far-flung nodes.

the standard layout stacks singleton nodes to the side of the graph
A dataset shown using the standard layout. Note the singleton nodes on the right hand side.
The new lens layout, which handles singleton nodes the same as connected nodes
With the lens layout, singleton nodes are treated the same as connected nodes.

Find the right layout for the job

Analyzing and visualizing networks can be a case of trial and error. The more views you can have of your network topologies and dynamics, the more likely you are to understand what’s happening.

Why not try our graph visualization products on your own data? Request a free trial to get started.

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