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Converge netx-topology MCP to dual-unit drain + orbit/polish mainline.
Trim public tools to 14, expose only kept layout actions/recipes, merge Fabric queries, drop createTopologyView/listTopologyViews, and align skill/docs with the live catalog. Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
parent
9bcb8ee0e3
commit
79f929de0c
86 changed files with 31578 additions and 240 deletions
791
packages/netx-topology-mcp/src/netx_topology_mcp/layout_tool.py
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packages/netx-topology-mcp/src/netx_topology_mcp/layout_tool.py
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"""MCP-facing layout runner: full layout + local fix/relax (no temp scripts)."""
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from __future__ import annotations
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from dataclasses import replace
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from typing import Any
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from netx_topology_mcp.layout_ops import (
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LayoutParams,
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build_state_from_nodes_edges,
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positions_for_api,
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run_recipe,
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score_state,
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)
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from netx_topology_mcp.layout_ops.hotspots import (
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fix_overlaps_local,
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hotspot_scopes,
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overlapping_nodes,
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)
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from netx_topology_mcp.layout_ops.recipe import RECIPES
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from netx_topology_mcp.layout_ops.state import LayoutState
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from netx_topology_mcp.layout_ops.transforms import normalize_origin
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from netx_topology_mcp.layout_ops.channels import (
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straighten_channels_greedy,
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straighten_params_from_overrides,
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)
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from netx_topology_mcp.layout_ops.dual_units import (
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dual_unit_params_from_overrides,
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layout_dual_unit,
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)
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from netx_topology_mcp.layout_ops.rigid_units import groups_from_membership
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from netx_topology_mcp.layout_ops.untangle import (
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untangle_crossings,
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untangle_params_from_overrides,
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)
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from netx_topology_mcp.layout_ops.press_crossings import (
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park_phantom_nodes,
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polish_crossings,
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press_params_from_overrides,
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)
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from netx_topology_mcp.layout_ops.clear_edge_hits import (
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clear_edge_hits,
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clear_edge_params_from_overrides,
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)
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from netx_topology_mcp.layout_ops.orbit_sweep import (
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apply_orbit_pick,
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orbit_params_from_overrides,
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orbit_sweep_node,
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orbit_sweep_round,
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)
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# Public recipe names → internal multipass ids
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RECIPE_ALIASES: dict[str, str] = {
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"rings": "agg_rings_v1",
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"corridor": "smd_corridor_v1",
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"compact": "smd_corridor_compact_v1",
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"unstick": "smd_corridor_unstick_v1",
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"agg_rings_v1": "agg_rings_v1",
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"smd_corridor_v1": "smd_corridor_v1",
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"smd_corridor_compact_v1": "smd_corridor_compact_v1",
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"smd_corridor_unstick_v1": "smd_corridor_unstick_v1",
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}
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PRESETS: dict[str, dict[str, float]] = {
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"loose": {
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"target_nn": 170.0,
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"scale_cap": 2.8,
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"target_util": 0.12,
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"pack_min_scale": 0.35,
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"pack_iters": 6,
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"island_pad_x": 200.0,
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"island_pad_y": 180.0,
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"lane": 300.0,
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"x_gain": 1.8,
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"pitch": 220.0,
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"side": 200.0,
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"an_gap": 560.0,
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"width_mul": 2.4,
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"height_mul": 1.5,
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},
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"balanced": {
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"target_nn": 155.0,
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"scale_cap": 2.2,
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"target_util": 0.18,
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"pack_min_scale": 0.28,
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"pack_iters": 6,
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"island_pad_x": 180.0,
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"island_pad_y": 160.0,
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"lane": 260.0,
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"x_gain": 1.8,
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"width_mul": 2.0,
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"height_mul": 1.35,
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},
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"dense": {
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"target_nn": 145.0,
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"scale_cap": 2.0,
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"target_util": 0.28,
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"pack_min_scale": 0.22,
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"pack_iters": 8,
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"island_pad_x": 160.0,
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"island_pad_y": 160.0,
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"lane": 240.0,
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"x_gain": 1.8,
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"width_mul": 1.7,
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"height_mul": 1.2,
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},
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}
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_PARAM_KEYS = (
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"target_nn",
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"scale_cap",
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"target_util",
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"pack_min_scale",
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"pack_iters",
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"pack_nn_floor",
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"island_pad_x",
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"island_pad_y",
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"cluster_gap",
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"cluster_thr",
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"x_gain",
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"lane",
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"overlap_iters",
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"overlap_step",
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"width_mul",
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"height_mul",
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"pitch",
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"side",
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"an_gap",
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)
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ACTIONS = (
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"layout",
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"fix_overlaps",
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"resolve_overlaps", # alias of fix_overlaps
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"untangle",
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"straighten_channels",
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"layout_dual_unit",
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"polish_crossings",
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"clear_edge_hits",
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"orbit_sweep",
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)
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def resolve_recipe(name: str | None) -> str:
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key = str(name or "rings").strip().lower() or "rings"
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if key not in RECIPE_ALIASES:
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raise ValueError(f"unknown_recipe:{key}")
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internal = RECIPE_ALIASES[key]
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if internal not in RECIPES:
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raise ValueError(f"recipe_not_registered:{internal}")
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return internal
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def build_params(
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*,
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preset: str = "balanced",
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overrides: dict[str, Any] | None = None,
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) -> LayoutParams:
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preset_key = str(preset or "balanced").strip().lower() or "balanced"
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if preset_key not in PRESETS:
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raise ValueError(f"unknown_preset:{preset_key}")
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base = LayoutParams()
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merged = {**PRESETS[preset_key]}
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for k, v in (overrides or {}).items():
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if k not in _PARAM_KEYS or v is None:
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continue
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try:
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merged[k] = float(v) if k not in {"pack_iters", "overlap_iters"} else int(v)
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except (TypeError, ValueError):
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continue
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return replace(base, **merged)
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def _rank_key(fin: dict[str, Any]) -> tuple:
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rk = (fin.get("score") or {}).get("rank_key")
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if isinstance(rk, list) and rk:
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return tuple(rk)
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ov = int(fin.get("footprint_overlap_pairs") or 0) + int(
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fin.get("label_overlap_pairs") or 0
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)
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total = float((fin.get("score") or {}).get("total") or 0.0)
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cross = int(fin.get("edge_crossings") or 0)
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return (ov, -total, cross)
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def _tune_grid(base: LayoutParams) -> list[LayoutParams]:
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"""Sweep knobs that actually move util/nn/crossings (incl. skeleton scale)."""
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out: list[LayoutParams] = []
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for tu, pms in (
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(0.08, base.pack_min_scale),
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(0.14, max(0.45, base.pack_min_scale - 0.05)),
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(0.20, max(0.40, base.pack_min_scale - 0.10)),
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(0.12, min(0.70, base.pack_min_scale + 0.05)),
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):
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for wm, hm in ((2.2, 1.4), (2.8, 1.7), (3.5, 2.0)):
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for tnn in (base.target_nn, 160.0, 140.0):
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out.append(
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replace(
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base,
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target_util=tu,
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pack_min_scale=pms,
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target_nn=tnn,
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width_mul=wm,
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height_mul=hm,
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)
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)
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seen: set[tuple] = set()
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uniq: list[LayoutParams] = []
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for p in out:
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key = (
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p.target_util,
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p.pack_min_scale,
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p.target_nn,
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p.width_mul,
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p.height_mul,
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)
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if key in seen:
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continue
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seen.add(key)
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uniq.append(p)
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return uniq[:12]
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def _pack_result(
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st: LayoutState,
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fin: dict[str, Any],
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*,
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action: str,
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recipe: str | None,
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recipe_id: str | None,
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preset: str,
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params: LayoutParams,
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tune: bool,
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tried: list[dict[str, Any]] | None,
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local: dict[str, Any] | None = None,
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) -> dict[str, Any]:
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report = dict(fin.get("report") or {})
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meta = st.meta or {}
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return {
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"ok": True,
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"action": action,
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"recipe": recipe,
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"recipe_id": recipe_id,
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"preset": preset,
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"tune": bool(tune),
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"tried": tried,
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"local": local,
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"rings_mode": meta.get("rings_mode"),
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"min_rings": meta.get("min_rings"),
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"params_used": {
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k: getattr(params, k)
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for k in (
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"target_nn",
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"scale_cap",
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"target_util",
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"pack_min_scale",
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"island_pad_x",
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"island_pad_y",
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"cluster_gap",
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"x_gain",
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"lane",
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)
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},
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"node_count": len(st.positions),
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"positions": positions_for_api(st),
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"verdict": report.get("verdict"),
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"size": report.get("size"),
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"overlap": report.get("overlap"),
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"crossing": report.get("crossing"),
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"spacing": report.get("spacing"),
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"sparsity": report.get("sparsity"),
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"edges": report.get("edges"),
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"chains": report.get("chains"),
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"rings": report.get("rings"),
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"score": report.get("score"),
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"summary": fin.get("summary") or {},
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"guide": report.get("guide"),
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}
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def _ensure_zero_overlap(st: LayoutState, params: LayoutParams) -> tuple[LayoutState, dict[str, Any]]:
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"""If any overlap remains, surgical local pull-apart (not global scale)."""
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before = len(overlapping_nodes(st))
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if before == 0:
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return st, {"ran": False, "overlaps_before": 0, "overlaps_after": 0}
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op = fix_overlaps_local(st, params)
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after = len(overlapping_nodes(op.state))
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return op.state, {
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"ran": True,
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"overlaps_before": before,
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"overlaps_after": after,
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"moved_n": len(op.moved),
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"note": op.note,
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}
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def run_layout_on_graph(
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nodes: list[dict[str, Any]],
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edges: list[dict[str, Any]],
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*,
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action: str = "layout",
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recipe: str = "rings",
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preset: str = "balanced",
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params: dict[str, Any] | None = None,
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tune: bool = False,
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) -> dict[str, Any]:
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"""Compute layout or local polish on existing positions. Does not PATCH."""
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action_key = str(action or "layout").strip().lower() or "layout"
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if action_key not in ACTIONS:
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raise ValueError(
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f"unknown_action:{action_key}; "
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f"allowed={','.join(ACTIONS)}"
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)
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if action_key == "resolve_overlaps":
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action_key = "fix_overlaps"
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base_params = build_params(preset=preset, overrides=params)
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st0 = build_state_from_nodes_edges(nodes, edges)
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park_phantom_nodes(st0)
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# Inject rigid/portal groups from staging membership when provided.
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if params:
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raw = params.get("_rigid_membership") or params.get("rigid_membership")
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if isinstance(raw, list):
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groups: list[dict[str, Any]] = []
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pairs: list[tuple[str, list[str]]] = []
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any_pivots = False
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for row in raw:
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if not isinstance(row, dict):
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continue
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key = str(row.get("key") or "").strip()
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ids = [str(x) for x in (row.get("node_ids") or []) if str(x)]
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pivots = [str(x) for x in (row.get("pivots") or []) if str(x)]
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if not key or len(ids) < 2:
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continue
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if pivots:
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any_pivots = True
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groups.append({"key": key, "node_ids": ids, "pivots": pivots})
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pairs.append((key, ids))
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if groups:
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if not any_pivots:
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groups = groups_from_membership(pairs)
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st0 = st0.copy()
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st0.meta = dict(st0.meta or {})
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st0.meta["compose_views"] = {
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**(st0.meta.get("compose_views") or {}),
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"rigid_groups": groups,
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}
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# --- local actions: keep current coordinates, do not rebuild skeleton ---
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if action_key == "fix_overlaps":
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op = fix_overlaps_local(st0, base_params)
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st, fix_meta = _ensure_zero_overlap(op.state, base_params)
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fin = score_state(st)
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return _pack_result(
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st,
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fin,
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action=action_key,
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recipe=None,
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recipe_id=None,
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preset=preset,
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params=base_params,
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tune=False,
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tried=None,
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local={"op": op.params, "ensure": fix_meta, "hotspots": len(hotspot_scopes(st0))},
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)
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if action_key == "untangle":
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knobs = untangle_params_from_overrides(params)
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op = untangle_crossings(st0, base_params, **knobs)
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# Origin shift only — soft_nn_scale can inflate an already-good human
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# layout; local jumps are capped inside untangle_crossings.
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st = normalize_origin(op.state, base_params).state
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# Overlap crush must not erase untangle gains.
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from netx_topology_mcp.layout_metrics import count_edge_crossings as _cx
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x_before_fix = _cx(st.positions, st.links)
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st2, fix_meta = _ensure_zero_overlap(st, base_params)
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x_after_fix = _cx(st2.positions, st2.links)
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if x_after_fix <= x_before_fix + 2:
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st = st2
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else:
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fix_meta = {
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**fix_meta,
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"reverted": True,
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"crossings_before": x_before_fix,
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"crossings_after": x_after_fix,
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"reason": "overlap_fix_raised_crossings",
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}
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fin = score_state(st)
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return _pack_result(
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st,
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fin,
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action=action_key,
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recipe=None,
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recipe_id=None,
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preset=preset,
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params=base_params,
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tune=False,
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tried=None,
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local={"op": op.params, "note": op.note, "meta": st.meta.get("untangle"), "ensure": fix_meta},
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)
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if action_key == "straighten_channels":
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knobs = straighten_params_from_overrides(params)
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op = straighten_channels_greedy(st0, base_params, **knobs)
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st, fix_meta = _ensure_zero_overlap(op.state, base_params)
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fin = score_state(st)
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return _pack_result(
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st,
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fin,
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action=action_key,
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recipe=None,
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recipe_id=None,
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preset=preset,
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params=base_params,
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tune=False,
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tried=None,
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local={
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"op": op.params,
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"note": op.note,
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"meta": st.meta.get("straighten_channels"),
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"ensure": fix_meta,
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},
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)
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if action_key == "layout_dual_unit":
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knobs = dual_unit_params_from_overrides(params)
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op = layout_dual_unit(
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st0,
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base_params,
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unit_id=knobs.get("unit_id"),
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portal_a=knobs.get("portal_a"),
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portal_b=knobs.get("portal_b"),
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)
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accepted = bool(op.params.get("accepted", False))
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# Always return best-effort dual geometry (even if accepted=False).
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# Do NOT run global overlap crush — it reintroduces crossings.
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st = op.state
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fin = score_state(st)
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return _pack_result(
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st,
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fin,
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action=action_key,
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recipe=None,
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recipe_id=None,
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preset=preset,
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params=base_params,
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tune=False,
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tried=None,
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local={
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"op": op.params,
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"note": op.note,
|
||||
"accepted": accepted,
|
||||
"meta": st.meta.get("layout_dual_unit"),
|
||||
"ensure": {"ran": False, "reason": "dual_unit_preserves_zero_cross"},
|
||||
},
|
||||
)
|
||||
|
||||
if action_key == "orbit_sweep":
|
||||
knobs = orbit_params_from_overrides(params)
|
||||
do_round = bool(knobs.get("round"))
|
||||
node_id = str(knobs.get("node_id") or "").strip()
|
||||
frozen = knobs.get("frozen_ids")
|
||||
protect = knobs.get("protect_rigid", "off")
|
||||
if do_round:
|
||||
op = orbit_sweep_round(
|
||||
st0,
|
||||
params=base_params,
|
||||
top_n=int(knobs.get("top_n") or 12),
|
||||
max_degree=int(knobs.get("max_degree") or 9),
|
||||
max_jump=knobs.get("max_jump"),
|
||||
angle_step=knobs.get("angle_step"),
|
||||
nn_floor=float(knobs.get("nn_floor") or 36.0),
|
||||
min_angle_sep=float(knobs.get("min_angle_sep") or 35.0),
|
||||
protect_rigid=protect,
|
||||
frozen_ids=frozen,
|
||||
focus_ids=knobs.get("focus_ids"),
|
||||
)
|
||||
st = normalize_origin(op.state, base_params).state
|
||||
fin = score_state(st)
|
||||
return _pack_result(
|
||||
st,
|
||||
fin,
|
||||
action=action_key,
|
||||
recipe=None,
|
||||
recipe_id=None,
|
||||
preset=preset,
|
||||
params=base_params,
|
||||
tune=False,
|
||||
tried=None,
|
||||
local={
|
||||
"op": op.params,
|
||||
"note": op.note,
|
||||
"meta": st.meta.get("orbit_sweep"),
|
||||
"round": True,
|
||||
},
|
||||
)
|
||||
if not node_id:
|
||||
raise ValueError(
|
||||
"orbit_sweep_requires_node_id_or_round:"
|
||||
"params.node_id=… or params.round=true"
|
||||
)
|
||||
sweep = orbit_sweep_node(
|
||||
st0,
|
||||
node_id,
|
||||
params=base_params,
|
||||
max_jump=knobs.get("max_jump"),
|
||||
angle_step=knobs.get("angle_step"),
|
||||
nn_floor=float(knobs.get("nn_floor") or 36.0),
|
||||
min_angle_sep=float(knobs.get("min_angle_sep") or 35.0),
|
||||
cand_cap=int(knobs.get("cand_cap") or 280),
|
||||
protect_rigid=protect,
|
||||
frozen_ids=frozen,
|
||||
top_k=int(knobs.get("top_k") or 3),
|
||||
)
|
||||
if not sweep.get("ok"):
|
||||
fin = score_state(st0)
|
||||
return _pack_result(
|
||||
st0,
|
||||
fin,
|
||||
action=action_key,
|
||||
recipe=None,
|
||||
recipe_id=None,
|
||||
preset=preset,
|
||||
params=base_params,
|
||||
tune=False,
|
||||
tried=None,
|
||||
local={"op": sweep, "note": f"orbit_sweep:{sweep.get('error')}"},
|
||||
)
|
||||
# Suggest-only keeps coords. Apply path sets params.pick (HTTP injects
|
||||
# pick=1 on mode=apply) so the chosen candidate is in positions.
|
||||
apply_pick = knobs.get("pick")
|
||||
if apply_pick is not None:
|
||||
op = apply_orbit_pick(st0, sweep, pick=int(apply_pick or 1))
|
||||
st = normalize_origin(op.state, base_params).state
|
||||
fin = score_state(st)
|
||||
return _pack_result(
|
||||
st,
|
||||
fin,
|
||||
action=action_key,
|
||||
recipe=None,
|
||||
recipe_id=None,
|
||||
preset=preset,
|
||||
params=base_params,
|
||||
tune=False,
|
||||
tried=None,
|
||||
local={
|
||||
"op": op.params,
|
||||
"note": op.note,
|
||||
"sweep": sweep,
|
||||
"pick": int(apply_pick or 1),
|
||||
},
|
||||
)
|
||||
fin = score_state(st0)
|
||||
return _pack_result(
|
||||
st0,
|
||||
fin,
|
||||
action=action_key,
|
||||
recipe=None,
|
||||
recipe_id=None,
|
||||
preset=preset,
|
||||
params=base_params,
|
||||
tune=False,
|
||||
tried=None,
|
||||
local={
|
||||
"op": {
|
||||
"node_id": sweep.get("node_id"),
|
||||
"crossings_before": sweep.get("crossings_before"),
|
||||
"candidates": sweep.get("candidates"),
|
||||
"sampled": sweep.get("sampled"),
|
||||
"improving_n": sweep.get("improving_n"),
|
||||
},
|
||||
"note": (
|
||||
f"orbit_sweep top3 improving={sweep.get('improving_n')} "
|
||||
f"sampled={sweep.get('sampled')}"
|
||||
),
|
||||
"sweep": sweep,
|
||||
"hint": sweep.get("hint"),
|
||||
},
|
||||
)
|
||||
|
||||
if action_key == "clear_edge_hits":
|
||||
knobs = clear_edge_params_from_overrides(params)
|
||||
preserve = bool(knobs.get("preserve_axis"))
|
||||
op = clear_edge_hits(
|
||||
st0,
|
||||
base_params,
|
||||
top_n=int(knobs.get("top_n") or 12),
|
||||
thr=float(knobs.get("thr") or 40.0),
|
||||
margin=float(knobs.get("margin") or 20.0),
|
||||
max_moves=int(knobs.get("max_moves") or 24),
|
||||
preserve_axis=preserve,
|
||||
pitch=knobs.get("pitch"),
|
||||
side=knobs.get("side"),
|
||||
rounds=int(knobs.get("rounds") or (6 if preserve else 1)),
|
||||
)
|
||||
st = normalize_origin(op.state, base_params).state
|
||||
from netx_topology_mcp.layout_metrics import count_edge_crossings as _cx
|
||||
|
||||
x0 = _cx(st.positions, st.links)
|
||||
st2, fix_meta = _ensure_zero_overlap(st, base_params)
|
||||
x1 = _cx(st2.positions, st2.links)
|
||||
if x1 <= x0 + 2:
|
||||
st = st2
|
||||
else:
|
||||
fix_meta = {"ran": False, "reason": "overlap_fix_would_raise_crossings"}
|
||||
fin = score_state(st)
|
||||
return _pack_result(
|
||||
st,
|
||||
fin,
|
||||
action=action_key,
|
||||
recipe=None,
|
||||
recipe_id=None,
|
||||
preset=preset,
|
||||
params=base_params,
|
||||
tune=False,
|
||||
tried=None,
|
||||
local={
|
||||
"op": op.params,
|
||||
"note": op.note,
|
||||
"meta": st.meta.get("clear_edge_hits"),
|
||||
"ensure": fix_meta,
|
||||
},
|
||||
)
|
||||
|
||||
if action_key == "polish_crossings":
|
||||
knobs = press_params_from_overrides(params)
|
||||
# Omit knobs so polish can auto-scale budgets on large E (MCP timeout).
|
||||
# Internal polish still calls straighten / press_hot_edges /
|
||||
# press_crossers / untangle.
|
||||
op = polish_crossings(
|
||||
st0,
|
||||
base_params,
|
||||
portal_ids=knobs.get("portal_ids"),
|
||||
straighten=knobs.get("straighten"),
|
||||
max_degree=int(knobs.get("max_degree") or 9),
|
||||
untangle_rounds=knobs.get("untangle_rounds"),
|
||||
top_n=knobs.get("top_n"),
|
||||
max_moves=knobs.get("max_moves"),
|
||||
max_sweeps=knobs.get("max_sweeps"),
|
||||
)
|
||||
st = normalize_origin(op.state, base_params).state
|
||||
# Overlap crush must not erase crossing gains.
|
||||
from netx_topology_mcp.layout_metrics import count_edge_crossings as _cx
|
||||
|
||||
x0 = _cx(st.positions, st.links)
|
||||
st2, fix_meta = _ensure_zero_overlap(st, base_params)
|
||||
x1 = _cx(st2.positions, st2.links)
|
||||
if x1 <= x0 + 2:
|
||||
st = st2
|
||||
else:
|
||||
fix_meta = {
|
||||
**fix_meta,
|
||||
"reverted": True,
|
||||
"reason": "overlap_fix_raised_crossings",
|
||||
}
|
||||
fin = score_state(st)
|
||||
return _pack_result(
|
||||
st,
|
||||
fin,
|
||||
action=action_key,
|
||||
recipe=None,
|
||||
recipe_id=None,
|
||||
preset=preset,
|
||||
params=base_params,
|
||||
tune=False,
|
||||
tried=None,
|
||||
local={
|
||||
"op": op.params,
|
||||
"note": op.note,
|
||||
"meta": st.meta.get(action_key),
|
||||
"ensure": fix_meta,
|
||||
},
|
||||
)
|
||||
|
||||
# --- full layout recipe ---
|
||||
recipe_id = resolve_recipe(recipe)
|
||||
tried: list[dict[str, Any]] = []
|
||||
best_st = None
|
||||
best_fin: dict[str, Any] | None = None
|
||||
best_params = base_params
|
||||
combos = _tune_grid(base_params) if tune else [base_params]
|
||||
|
||||
for i, p in enumerate(combos):
|
||||
st, _trace, fin = run_recipe(st0, recipe_id, p)
|
||||
st, fix_meta = _ensure_zero_overlap(st, p)
|
||||
fin = score_state(st)
|
||||
row = {
|
||||
"i": i,
|
||||
"total": (fin.get("score") or {}).get("total"),
|
||||
"overlaps": fin.get("footprint_overlap_pairs"),
|
||||
"crossings": fin.get("edge_crossings"),
|
||||
"nn_p50": fin.get("nn_p50"),
|
||||
"util": fin.get("space_utilization"),
|
||||
"fix": fix_meta,
|
||||
"headline": ((fin.get("report") or {}).get("verdict") or {}).get("headline"),
|
||||
}
|
||||
tried.append(row)
|
||||
if best_fin is None or _rank_key(fin) < _rank_key(best_fin):
|
||||
best_st, best_fin, best_params = st, fin, p
|
||||
|
||||
assert best_st is not None and best_fin is not None
|
||||
return _pack_result(
|
||||
best_st,
|
||||
best_fin,
|
||||
action=action_key,
|
||||
recipe=recipe if recipe in RECIPE_ALIASES else recipe_id,
|
||||
recipe_id=recipe_id,
|
||||
preset=preset,
|
||||
params=best_params,
|
||||
tune=bool(tune),
|
||||
tried=tried if tune else None,
|
||||
local={"auto_fix_overlaps": True},
|
||||
)
|
||||
|
||||
|
||||
def list_layout_catalog() -> dict[str, Any]:
|
||||
from netx_topology_mcp import NETX_MCP_REV, __version__
|
||||
|
||||
return {
|
||||
"version": __version__,
|
||||
"rev": NETX_MCP_REV,
|
||||
"actions": {
|
||||
"layout": "全图配方（骨架）；块内 pack，结束时局部解叠",
|
||||
"fix_overlaps": "只拉开当前重叠点（+1 跳邻居），不重排全图",
|
||||
"resolve_overlaps": "fix_overlaps 别名",
|
||||
"straighten_channels": (
|
||||
"拉直 deg≤2 通道（弦/横/纵）；仅全局交叉下降才接受该通道"
|
||||
"（params: step/min_len）"
|
||||
),
|
||||
"layout_dual_unit": (
|
||||
"双门户单元美化（多走廊→平行 H/V 道；链→拉直）；"
|
||||
"单元内交叉必须为 0 才接受（params: unit_id）"
|
||||
),
|
||||
"untangle": (
|
||||
"贪心挪低度数点降交叉；默认 protect_rigid=portals "
|
||||
"只冻共享门户，走廊/触手可动（all=全冻，off=不冻）；"
|
||||
"可用 focus_ids / source_view_ids"
|
||||
),
|
||||
"polish_crossings": (
|
||||
"一键压交叉：straighten→press_hot_edges→press_crossers→"
|
||||
"untangle(portals)；优先用 source_view_ids 冻门户 "
|
||||
"（勿写临时 py）"
|
||||
),
|
||||
"clear_edge_hits": (
|
||||
"把贴在非关联边上的网元沿垂直方向弹开（直角偏好 H/V）；"
|
||||
"门控：不增交叉、不增重叠。"
|
||||
"params: top_n/thr/margin/max_moves"
|
||||
),
|
||||
"orbit_sweep": (
|
||||
"压交叉（默认可动门户）：以网元为圆心不定长扫角 top-3；"
|
||||
"preview+node_id / apply+pick / round=true；"
|
||||
"protect_rigid 默认 off（portals/all 可恢复刚体冻）"
|
||||
),
|
||||
"job_status": (
|
||||
"轮询后台 job：params.job_id；返回 progress.phase/pct、elapsed_ms、"
|
||||
"heartbeat_age_ms、stale（软警告，不改状态）"
|
||||
),
|
||||
"job_cancel": (
|
||||
"协作式取消后台 job：params.job_id；下一检查点退出；"
|
||||
"若已 PATCH 则保留写入并回报 applied"
|
||||
),
|
||||
"move_nodes": (
|
||||
"成员迁移（双向）：params.fabric_node_ids 从 source_view_id→view_id；"
|
||||
"默认 remove_from_source；对调两 view 即回迁；"
|
||||
"copy_positions|park；mode=preview|apply"
|
||||
),
|
||||
"sink_nodes": "move_nodes 别名",
|
||||
},
|
||||
"recipes": {
|
||||
"rings": "环+链花瓣；core_bar 时梁优先（多 CN 不塞进 AN 列）",
|
||||
"corridor": "Tutte 走廊骨架，交叉常更少，易偏空——稳基线",
|
||||
"compact": "走廊 + 分块 pack（禁止全局压扁）——稳基线",
|
||||
"unstick": "corridor 后再强解重叠",
|
||||
},
|
||||
"presets": {
|
||||
"loose": "偏疏、交叉友好",
|
||||
"balanced": "默认折中",
|
||||
"dense": "偏紧、抬 util",
|
||||
},
|
||||
"modes": {
|
||||
"preview": "只算分+坐标，不写库",
|
||||
"apply": "PATCH 到 view_id（有残留重叠则拒绝落笔）",
|
||||
},
|
||||
"workflow": (
|
||||
"主路径：analyze(structure) → layout_dual_unit（或小图 layout "
|
||||
"compact|corridor|rings）→ sinkTopologyDualUnits / move_nodes(park) → "
|
||||
"orbit_sweep(round) → polish_crossings → clear_edge_hits → "
|
||||
"手拖微调。禁止临时 py 算坐标。"
|
||||
),
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue