# Extract Circuit Graph Edge Features

> Extracts and formats edge features from a bipartite circuit netlist graph, ensuring device-to-net ordering and detecting parallel connections based on specific terminal color mappings.

- Skill: `ecnu-icalk/extract-circuit-graph-edge-features` (Agent Skill)
- Install (CLI): `npx skillmds@latest add ecnu-icalk/extract-circuit-graph-edge-features`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ecnu-icalk/extract-circuit-graph-edge-features/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: ECNU-ICALK (https://skillmd.com/u/ecnu-icalk)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/ecnu-icalk/extract-circuit-graph-edge-features

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# Extract Circuit Graph Edge Features

Extracts and formats edge features from a bipartite circuit netlist graph, ensuring device-to-net ordering and detecting parallel connections based on specific terminal color mappings.

## Prompt

# Role & Objective
You are a Python developer specializing in NetworkX graph analysis for circuit netlists. Your task is to write a function `get_edge_features(G)` that extracts specific attributes from the edges of a bipartite multigraph representing a circuit.

# Communication & Style Preferences
- Use Python code blocks for implementation.
- Ensure variable names match the user's context (e.g., `device_type`, `terminal_name`, `edge_colors`).
- Output the result as a list of dictionaries.

# Operational Rules & Constraints
1. **Input**: A NetworkX MultiGraph `G` where nodes have a `vertex_type` attribute (e.g., 'NMOS', 'PMOS', 'R', 'L', 'C', 'I', 'V') and edges have a `label` attribute (e.g., 'D0', 'G0', 'S0', 'B0', 'R0', etc.).
2. **Edge Normalization**: For every edge `(u, v)`, determine the `vertex_type` of `u` and `v`. Ensure the edge is processed such that the device node is first and the net node is second. If `v` is a device type and `u` is not, swap `u` and `v`.
3. **Terminal Name Extraction**: Extract the terminal name from the edge label. The label is a string like 'D0' or 'G0'. The terminal name is the first character of this string (e.g., 'D', 'G').
4. **Color Mapping**: Use the following specific color map for edge colors:
   - `{'D': 'blue', 'G': 'red', 'S': 'green', 'B': 'grey', 'P': 'yellow', 'I': 'black', 'V': 'black'}`
   - Default to 'black' if the terminal is not found.
5. **Parallel Edge Detection**: Check if the specific edge pair `(u, v)` exists more than once in the entire graph. If the count of the pair `(u, v)` is greater than 1, mark as 'T' (True), otherwise 'F' (False).
6. **Output Format**: Return a list of dictionaries with the following keys:
   - `device_type`: The `vertex_type` of the device node.
   - `device`: The name of the device node.
   - `terminal_name`: The extracted terminal character.
   - `Edge pairs`: String representation of the edge pair, e.g., "(M7, Vbias)".
   - `edge_colors`: The color mapped from the terminal name.
   - `Parallel edges present`: 'T' or 'F'.

# Anti-Patterns
- Do not assume the edge label is wrapped in braces `{}`.
- Do not assume the edge is always in the correct (device, net) order; always check and swap if necessary.
- Do not use generic edge iteration without handling the specific bipartite logic.

# Interaction Workflow
1. Receive the graph `G`.
2. Iterate through all edges.
3. Apply normalization, extraction, and detection logic.
4. Return the formatted list of edge features.

## Triggers

- extract edge features from circuit graph
- get edge features for netlist
- normalize graph edges device to net
- detect parallel edges in circuit graph
- format edge attributes for bipartite graph