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graph_utils

Source: Distributed_Design_Optimizer/postprocess/utils/graph_utils.py

Graph layout and color utility functions for topology analysis.

Functions

hierarchical_layout(graph: nx.Graph, subsystem_details: dict) → dict[str, dict]

Compute hierarchical positions from subsystem level data.

Args:

graph: The NetworkX graph whose nodes will be positioned.
subsystem_details: Mapping of node id to detail dicts containing a Level key.

Returns:

A dict mapping node id to {"x": float, "y": float} position dicts.

green_yellow_red(normalized: float) → str

Map 0..1 to a green-yellow-red hex color.

Args:

normalized: A value in [0, 1] where 0 is green and 1 is red.

Returns:

A CSS hex color string interpolated along the green-yellow-red gradient.

safe_edge_iter(graph: nx.Graph) → list

Iterate edges safely for both multi and non-multi graphs.

Args:

graph: A NetworkX graph (regular or multigraph).

Returns:

A list of edge tuples, each containing (u, v, key) or
(u, v, key, data) depending on the data flag.

build_edges(graph: nx.Graph, positions: dict[str, dict], default_color: str | None) → list[dict]

Build an edge list with source/target coordinates for GraphWidget.

Args:

graph: The NetworkX graph to extract edges from.
positions: Mapping of node id to {"x": float, "y": float} dicts.
default_color: Optional fallback CSS color for edges without a type.

Returns:

A list of dicts, each containing source/target coordinates, color,
width, and tooltip for one edge.