A good layout is essential for untangling and understanding any network. We offer many different graph layouts, each designed to highlight different aspects of your data. They’ve been carefully optimized to ensure consistency, performance and clarity.
This is a force-directed layout designed specifically for your biggest datasets.
It detangles complex networks by reducing node/link overlap and minimizing white space, with multiple components laid out in a circular arrangement with larger components in the center. The organic layout uses clever adaptive behavior to accommodate network changes through small adjustments to the chart, so users don’t lose their mental map of the data. The pattern is easy to understand and helps reveal underlying structures.
‘Standard’ is an efficient, force-directed layout. This means that it constructs the graph so links are a consistent length, with nodes and edges overlapping as little as possible and distributed evenly across the chart.
Its consistency and simplicity helps make it a good catch-all for any kind of data and any size of dataset.
Standard layout also adapts intuitively to changes to the chart in a way that’s logical and simple to follow. It’s particularly useful for finding patterns and symmetries.Its consistency and simplicity helps make it a good catch-all for any kind of data and any size of dataset. Standard layout also adapts intuitively to changes to the chart in a way that’s logical and simple to follow. It’s particularly useful for finding patterns and symmetries.
This layout has been designed to push highly-connected nodes into the center, and force the less connected nodes into the periphery, so nodes are arranged in a circular shape.
This results in an attractive ‘lens’ view allowing users to find well-connected nodes more quickly. It’s a particularly efficient way to view large networks.
This layout is similar to the standard layout, except it groups nodes with similar attributes together in fans. It’s particularly useful to get an overview of the network clusters, or to identify groupings that may not be obvious.
Our sequential layout is a good way to display where there’s a clear parent-child relationship between nodes, but where the nodes also have a set tier or level that needs to be communicated.
It takes multiple components into account, minimizes link crossings and makes really efficient use of the available screen space.
Our radial layout arranges nodes in concentric circles around the original subject in a radial tree. Each generation of node becomes a new orbit extending outwards, showing a dependency chain.
Generally, this layout is the best option for networks with a large volume of child nodes to each parent.
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