[Feature] Graph decluttering & focus visualization for large networks

[oxy86]

Overview

Large graphs in SocNetV (100+ nodes) quickly become visually cluttered, making meaningful analysis difficult. Users report dense edge crossings and lack of tools to isolate and inspect substructures.

This feature introduces focus-based visualization tools that allow users to reduce visual noise and explore meaningful subsets of the graph without modifying the underlying data.

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Goals

• Improve usability for medium and large networks
• Enable users to focus on relevant parts of the graph
• Reduce edge crossing and visual clutter
• Provide intuitive exploration workflows

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Key Concept

Introduce non-destructive visibility control:

• Nodes and edges can be temporarily hidden
• The underlying graph data remains unchanged
• Works as a foundation for future filtering/subgraph features

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Phase Plan

Phase 1 — Immediate UX Improvements (short-term) ✔

• Focus on selected nodes
• Show only neighbors of selected nodes (ego network, k=1)
• Hide non-selected nodes
• Hide non-neighbor edges
• Edge visibility threshold (e.g. by weight)

Phase 2 — Layout Improvements (mid-term) ✔

• Improve force-directed layout defaults for large graphs
• Add radial layout (ego-centered)
• Add circular layout (group-friendly)

Phase 3 — Advanced Visualization (long-term)

• Community-based layouts
• Edge bundling (optional)

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Implementation Notes

• Reuse existing APIs:
  • setNodeVisibility(...)
  • setEdgeVisibility(...)
• Integrates with GraphicsWidget rendering layer
• Should remain independent of Graph data model

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Subtasks

Phase 1 — Immediate UX

• [Subtask] Focus view: show only selected nodes and their edges #210 Focus view
• [Subtask] Ego network view (k=1): show neighbors of selected nodes #211 Ego network
• [Subtask] Visibility mode: hide non-selected nodes and incident edges #212 Hide non-selected nodes
• [Subtask] Edge visibility filtering by weight threshold #213 Edge weight filtering

Phase 2 — Layout

• [Subtask] Improve layouts for large graphs (force-directed tuning + radial layout) #214 Layout improvements

Related enhancements

• Enhance edge rendering (Bezier curves) for improved graph readability #149 Bezier edges
• Visualize node metrics using color mapping (e.g. clustering coefficient) #37 Node metric color mapping

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Motivation

This feature directly addresses real-world usage challenges and is a prerequisite for scalable graph exploration in SocNetV.****