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spec: add network-weighted specification (#3292)
## New Specification: `network-weighted` Related to #3290 --- ### specification.md # network-weighted: Weighted Network Graph with Edge Thickness ## Description A weighted network graph displays relationships between entities using edge thickness to represent connection strength or weight. Unlike basic network graphs where edges are uniform, the varying line widths immediately communicate the relative importance of each relationship. This visualization makes it easy to identify strong vs weak connections, central hubs with many heavy links, and structural patterns in weighted relational data. ## Applications - Analyzing trade flows between countries where thicker edges represent higher export/import volumes - Visualizing communication patterns in organizations where edge weight shows message frequency between teams - Mapping collaboration networks in research where thickness indicates number of co-authored papers - Displaying transportation networks where edge weight represents passenger volume or freight capacity ## Data - `nodes` (list of dicts) - entities with unique IDs and optional labels or group attributes - `edges` (list of dicts/tuples) - connections as (source_id, target_id, weight) where weight is a positive numeric value - `weight` (numeric) - connection strength/intensity mapped to edge thickness - Size: 10-50 nodes for clear visualization of weighted edges without clutter - Example: Trade network with 15 countries where edge weights represent billions of USD in annual trade volume ## Notes - Edge thickness should scale proportionally but remain visually distinguishable (avoid too thin or too thick extremes) - Consider a legend or annotation explaining the weight scale - Nodes can optionally be sized by weighted degree (sum of connected edge weights) - Use force-directed or spring layout to position nodes, allowing edge weights to influence attraction - Avoid edge overlap where possible to keep individual weights readable --- **Next:** Add `approved` label to the issue to merge this PR. --- :robot: *[spec-create workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20822531517)* Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
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# network-weighted: Weighted Network Graph with Edge Thickness
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## Description
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A weighted network graph displays relationships between entities using edge thickness to represent connection strength or weight. Unlike basic network graphs where edges are uniform, the varying line widths immediately communicate the relative importance of each relationship. This visualization makes it easy to identify strong vs weak connections, central hubs with many heavy links, and structural patterns in weighted relational data.
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## Applications
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- Analyzing trade flows between countries where thicker edges represent higher export/import volumes
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- Visualizing communication patterns in organizations where edge weight shows message frequency between teams
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- Mapping collaboration networks in research where thickness indicates number of co-authored papers
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- Displaying transportation networks where edge weight represents passenger volume or freight capacity
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## Data
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- `nodes` (list of dicts) - entities with unique IDs and optional labels or group attributes
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- `edges` (list of dicts/tuples) - connections as (source_id, target_id, weight) where weight is a positive numeric value
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- `weight` (numeric) - connection strength/intensity mapped to edge thickness
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- Size: 10-50 nodes for clear visualization of weighted edges without clutter
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- Example: Trade network with 15 countries where edge weights represent billions of USD in annual trade volume
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## Notes
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- Edge thickness should scale proportionally but remain visually distinguishable (avoid too thin or too thick extremes)
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- Consider a legend or annotation explaining the weight scale
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- Nodes can optionally be sized by weighted degree (sum of connected edge weights)
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- Use force-directed or spring layout to position nodes, allowing edge weights to influence attraction
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- Avoid edge overlap where possible to keep individual weights readable
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# Specification-level metadata for network-weighted
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# Auto-synced to PostgreSQL on push to main
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spec_id: network-weighted
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title: Weighted Network Graph with Edge Thickness
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# Specification tracking
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created: 2026-01-08T15:44:42Z
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updated: null
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issue: 3290
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suggested: MarkusNeusinger
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# Classification tags (applies to all library implementations)
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# See docs/reference/tagging-system.md for detailed guidelines
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tags:
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plot_type:
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- network
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data_type:
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- network
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- relational
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- numeric
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domain:
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- general
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- business
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features:
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- weighted
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- proportional

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