Move medial tire drawing script into lib

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2026-06-15 16:25:33 -04:00
parent 2a56322841
commit d541aea526
8 changed files with 711 additions and 612 deletions
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"""Draw medial tire decompositions of random 5-connected triangulations.
The source graphs come from ``plantri -c5`` in graph6 format. For each sampled
30-vertex triangulation, this script chooses a random source vertex, builds the
BFS depth-component tire tree, and draws both the tire tree and the medial
tread model for each depth component.
"""
"""Compatibility wrapper for the medial tire decomposition drawing script."""
from __future__ import annotations
import argparse
import math
import os
import random
import subprocess
import sys
from collections import defaultdict
from dataclasses import dataclass
from pathlib import Path
PAPER_DIR = Path(__file__).resolve().parents[1]
REPO_ROOT = PAPER_DIR.parents[1]
os.environ.setdefault(
"MPLCONFIGDIR", str(PAPER_DIR / "experiments" / ".matplotlib-cache")
)
os.environ.setdefault("XDG_CACHE_HOME", str(PAPER_DIR / "experiments" / ".cache"))
PAPER_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
if PAPER_DIR not in sys.path:
sys.path.insert(0, PAPER_DIR)
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import networkx as nx
if str(PAPER_DIR) not in sys.path:
sys.path.insert(0, str(PAPER_DIR))
from lib.medial_tire_decomposition import (
annular_cycle_components,
ekey,
medial_tire_facemodel,
)
@dataclass(frozen=True)
class TreadNode:
idx: int
depth: int
face_indices: tuple[int, ...]
annular: frozenset
up: frozenset
down: frozenset
bites: frozenset
medial: nx.Graph
annular_cycles: tuple[tuple, ...]
@dataclass(frozen=True)
class Augmentation:
graph: nx.Graph
added_vertices: tuple[int, ...]
filled_faces: tuple[tuple[int, tuple[int, int, int], int], ...]
def sample_plantri_graphs(n: int, count: int, seed: int, scan_limit: int) -> list[nx.Graph]:
cmd = [str(REPO_ROOT / "plantri" / "plantri"), "-g", "-c5", str(n)]
rng = random.Random(seed)
sample: list[tuple[int, nx.Graph]] = []
seen = 0
with subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE) as proc:
assert proc.stdout is not None
for raw in proc.stdout:
line = raw.strip()
if not line or line.startswith(b">>"):
continue
graph = nx.from_graph6_bytes(line)
if nx.node_connectivity(graph) < 5:
continue
seen += 1
if len(sample) < count:
sample.append((seen, graph))
else:
j = rng.randrange(seen)
if j < count:
sample[j] = (seen, graph)
if seen >= scan_limit:
proc.terminate()
break
proc.wait(timeout=10)
if len(sample) < count:
raise RuntimeError(f"only found {len(sample)} graphs after scanning {seen}")
return [graph for _ordinal, graph in sample]
def triangular_faces(g: nx.Graph):
ok, emb = nx.check_planarity(g)
if not ok:
raise ValueError("not planar")
seen = set()
faces = []
for u, v in list(emb.edges()):
if (u, v) in seen:
continue
face = tuple(emb.traverse_face(u, v, mark_half_edges=seen))
faces.append(face)
return faces
def edge_face_data(faces):
face_edges = []
edge_faces: dict[tuple, list[int]] = defaultdict(list)
for i, face in enumerate(faces):
edges = {
ekey(face[0], face[1]),
ekey(face[1], face[2]),
ekey(face[2], face[0]),
}
face_edges.append(edges)
for edge in edges:
edge_faces[edge].append(i)
return face_edges, edge_faces
def augment_same_level_faces(g: nx.Graph, source: int) -> Augmentation:
"""Stack a new vertex into every facial triangle with one BFS level.
If a triangular face has all three vertices at level d, the new vertex is
adjacent to those three vertices and therefore has level d + 1. This turns
the same-level region into three adjacent-level tread faces before the tire
decomposition is extracted.
"""
levels = nx.single_source_shortest_path_length(g, source)
faces = triangular_faces(g)
augmented = g.copy()
next_vertex = max(augmented.nodes()) + 1
added = []
filled = []
for face in faces:
face_levels = {levels[v] for v in face}
if len(face_levels) != 1:
continue
new_vertex = next_vertex
next_vertex += 1
augmented.add_node(new_vertex)
augmented.add_edges_from((new_vertex, v) for v in face)
added.append(new_vertex)
filled.append((new_vertex, tuple(face), next(iter(face_levels))))
return Augmentation(
graph=augmented,
added_vertices=tuple(added),
filled_faces=tuple(filled),
)
def depth_components(faces, face_edges, edge_faces, levels):
depths = [min(levels[v] for v in face) for face in faces]
dual_adj: dict[int, set[int]] = defaultdict(set)
for incident in edge_faces.values():
for a in range(len(incident)):
for b in range(a + 1, len(incident)):
dual_adj[incident[a]].add(incident[b])
dual_adj[incident[b]].add(incident[a])
comps = []
seen = [False] * len(faces)
for start in range(len(faces)):
if seen[start]:
continue
depth = depths[start]
stack = [start]
comp = []
seen[start] = True
while stack:
face = stack.pop()
comp.append(face)
for other in dual_adj[face]:
if not seen[other] and depths[other] == depth:
seen[other] = True
stack.append(other)
comps.append((depth, tuple(sorted(comp))))
return comps, depths, dual_adj
def tread_from_component(faces, levels, face_indices):
tread_faces = [faces[i] for i in face_indices]
if not tread_faces:
return None
depth = min(min(levels[v] for v in face) for face in tread_faces)
annular, up, down = set(), set(), set()
face_of_down = defaultdict(int)
for face in tread_faces:
for x, y in ((face[0], face[1]), (face[1], face[2]), (face[2], face[0])):
e = ekey(x, y)
lx, ly = levels[x], levels[y]
if {lx, ly} == {depth, depth + 1}:
annular.add(e)
elif lx == ly == depth:
up.add(e)
elif lx == ly == depth + 1:
down.add(e)
face_of_down[e] += 1
if len(annular) < 3:
return None
return {
"tread_faces": tread_faces,
"annular": annular,
"up": up,
"down": down,
"bites": {e for e in down if face_of_down[e] == 2},
}
def build_tire_tree(g: nx.Graph, source: int, augment: bool = True):
augmentation = augment_same_level_faces(g, source) if augment else Augmentation(g, (), ())
work_graph = augmentation.graph
faces = triangular_faces(work_graph)
face_edges, edge_faces = edge_face_data(faces)
levels = nx.single_source_shortest_path_length(work_graph, source)
comps, depths, dual_adj = depth_components(faces, face_edges, edge_faces, levels)
comp_of_face = {}
for comp_idx, (_depth, face_indices) in enumerate(comps):
for face in face_indices:
comp_of_face[face] = comp_idx
nodes: list[TreadNode] = []
comp_to_node = {}
for comp_idx, (depth, face_indices) in enumerate(comps):
tread = tread_from_component(faces, levels, face_indices)
if tread is None or len(tread["up"]) < 3:
continue
mt = medial_tire_facemodel(tread["tread_faces"])
annular_cycles = tuple(annular_cycle_components(mt, tread["annular"]))
if not annular_cycles:
continue
node = TreadNode(
idx=len(nodes),
depth=depth,
face_indices=face_indices,
annular=frozenset(tread["annular"]),
up=frozenset(tread["up"]),
down=frozenset(tread["down"]),
bites=frozenset(tread["bites"]),
medial=mt,
annular_cycles=annular_cycles,
)
comp_to_node[comp_idx] = node.idx
nodes.append(node)
tree_edges = set()
for comp_idx, (depth, face_indices) in enumerate(comps):
if comp_idx not in comp_to_node:
continue
child = comp_to_node[comp_idx]
parent_candidates = set()
for face in face_indices:
for other in dual_adj[face]:
other_comp = comp_of_face[other]
if depths[other] == depth - 1 and other_comp in comp_to_node:
parent_candidates.add(comp_to_node[other_comp])
for parent in parent_candidates:
tree_edges.add((parent, child))
return augmentation, faces, levels, nodes, sorted(tree_edges)
def graph_layout(g: nx.Graph):
try:
return nx.planar_layout(g)
except nx.NetworkXException:
return nx.spring_layout(g, seed=0)
def draw_base_graph(ax, g, levels, source, added_vertices=()):
pos = graph_layout(g)
max_level = max(levels.values())
cmap = plt.get_cmap("viridis", max_level + 1)
node_colors = [cmap(levels[v]) for v in g.nodes()]
nx.draw_networkx_edges(g, pos, ax=ax, edge_color="#cbd5e1", width=0.8)
added_set = set(added_vertices)
nx.draw_networkx_nodes(
g,
pos,
ax=ax,
node_color=node_colors,
node_size=[
150 if v == source else 96 if v in added_set else 72
for v in g.nodes()
],
edgecolors=[
"#dc2626" if v == source else "#7c3aed" if v in added_set else "#111827"
for v in g.nodes()
],
linewidths=[
1.8 if v == source else 1.2 if v in added_set else 0.45
for v in g.nodes()
],
)
labels = {v: str(v) for v in g.nodes()}
nx.draw_networkx_labels(g, pos, labels=labels, ax=ax, font_size=5)
ax.set_title(
f"Augmented G, source {source}; vertex levels 0..{max_level}",
fontsize=10,
)
ax.set_aspect("equal")
ax.axis("off")
def tree_positions(nodes: list[TreadNode], tree_edges):
children: dict[int, list[int]] = defaultdict(list)
has_parent = set()
for parent, child in tree_edges:
children[parent].append(child)
has_parent.add(child)
roots = [node.idx for node in nodes if node.idx not in has_parent]
for child_list in children.values():
child_list.sort(key=lambda idx: (nodes[idx].depth, idx))
x_counter = 0
pos = {}
def place(idx, depth):
nonlocal x_counter
if not children[idx]:
pos[idx] = (x_counter, -depth)
x_counter += 1
return pos[idx][0]
xs = [place(child, depth + 1) for child in children[idx]]
x = sum(xs) / len(xs)
pos[idx] = (x, -depth)
return x
for root in sorted(roots, key=lambda idx: (nodes[idx].depth, idx)):
place(root, 0)
x_counter += 1
return pos
def draw_tire_tree(ax, nodes: list[TreadNode], tree_edges):
pos = tree_positions(nodes, tree_edges)
for parent, child in tree_edges:
x0, y0 = pos[parent]
x1, y1 = pos[child]
ax.plot([x0, x1], [y0, y1], color="#374151", lw=1.0, zorder=1)
for node in nodes:
x, y = pos[node.idx]
ax.text(
x,
y,
f"T{node.idx}\nd={node.depth}\n{len(node.annular_cycles)} cycle(s)",
ha="center",
va="center",
fontsize=8,
bbox={
"boxstyle": "round,pad=0.32",
"facecolor": "#fef3c7",
"edgecolor": "#111827",
"linewidth": 0.9,
},
zorder=3,
)
ax.set_title("Depth-component tire tree", fontsize=10)
if pos:
xs = [p[0] for p in pos.values()]
ys = [p[1] for p in pos.values()]
ax.set_xlim(min(xs) - 1.0, max(xs) + 1.0)
ax.set_ylim(min(ys) - 0.7, max(ys) + 0.7)
ax.axis("off")
def vertex_xy(k: int, n: int, radius: float) -> tuple[float, float]:
angle = math.pi / 2 - 2 * math.pi * k / n
return radius * math.cos(angle), radius * math.sin(angle)
def edge_midpoint_angle(i: int, n: int) -> float:
return math.pi / 2 - 2 * math.pi * (i + 0.5) / n
def draw_tread_model(ax, node: TreadNode):
cycle_count = len(node.annular_cycles)
offsets = [3.25 * (i - (cycle_count - 1) / 2) for i in range(cycle_count)]
apex_positions: dict[tuple, tuple[float, float]] = {}
apex_corners: dict[tuple, list[tuple[float, float]]] = defaultdict(list)
ann_positions: dict[tuple, tuple[float, float]] = {}
for cycle_idx, order in enumerate(node.annular_cycles):
n = len(order)
dx = offsets[cycle_idx]
ann = {
vertex: (dx + x, y)
for vertex, (x, y) in zip(order, [vertex_xy(k, n, 1.0) for k in range(n)])
}
ann_positions.update(ann)
cyc_x = [ann[v][0] for v in order] + [ann[order[0]][0]]
cyc_y = [ann[v][1] for v in order] + [ann[order[0]][1]]
ax.plot(cyc_x, cyc_y, color="black", lw=1.3, zorder=2)
for i, a in enumerate(order):
b = order[(i + 1) % n]
apexes = [
w for w in set(node.medial.neighbors(a)) & set(node.medial.neighbors(b))
if w not in node.annular
]
for apex in apexes:
apex_corners[apex].extend([ann[a], ann[b]])
if apex in apex_positions:
continue
angle = edge_midpoint_angle(i, n)
if apex in node.up:
radius = 1.42
else:
radius = 0.58
apex_positions[apex] = (
dx + radius * math.cos(angle),
radius * math.sin(angle),
)
for apex, corners in apex_corners.items():
if apex in node.bites and corners:
cx = sum(p[0] for p in corners) / len(corners)
cy = sum(p[1] for p in corners) / len(corners)
center_x = sum(offsets) / len(offsets) if offsets else 0.0
apex_positions[apex] = (
center_x + 0.82 * (cx - center_x),
0.82 * cy,
)
pos = apex_positions[apex]
for corner in corners:
ax.plot([pos[0], corner[0]], [pos[1], corner[1]], color="#9ca3af", lw=0.5)
for apex, pos in apex_positions.items():
if apex in node.up:
color, size, edgecolor = "#2563eb", 13, "none"
elif apex in node.bites:
color, size, edgecolor = "#7f1d1d", 24, "black"
else:
color, size, edgecolor = "#dc2626", 13, "none"
ax.scatter(
[pos[0]],
[pos[1]],
s=size,
color=color,
edgecolors=edgecolor,
linewidths=0.4,
zorder=3,
)
if ann_positions:
ax.scatter(
[p[0] for p in ann_positions.values()],
[p[1] for p in ann_positions.values()],
s=9,
color="black",
zorder=4,
)
singleton_down = set(node.down) - set(node.bites)
ax.set_title(
f"T{node.idx} d={node.depth}: {len(node.annular_cycles)} annular cycle(s)\n"
f"ann={len(node.annular)} up={len(node.up)} down={len(singleton_down)} "
f"bite={len(node.bites)}",
fontsize=6.4,
pad=1.5,
)
pad = 1.7
ax.set_xlim(min(offsets, default=0.0) - pad, max(offsets, default=0.0) + pad)
ax.set_ylim(-1.65, 1.65)
ax.set_aspect("equal")
ax.axis("off")
def draw_medial_tire_grid(fig, outer_spec, nodes):
if not nodes:
ax = fig.add_subplot(outer_spec)
ax.text(0.5, 0.5, "No medial treads extracted", ha="center")
ax.axis("off")
return
cols = min(3, max(1, math.ceil(math.sqrt(len(nodes)))))
rows = math.ceil(len(nodes) / cols)
sub = outer_spec.subgridspec(rows, cols, wspace=0.08, hspace=0.35)
for i in range(rows * cols):
ax = fig.add_subplot(sub[i // cols, i % cols])
if i < len(nodes):
draw_tread_model(ax, nodes[i])
else:
ax.axis("off")
def write_index(
path: Path,
graph_idx: int,
source: int,
original_graph: nx.Graph,
augmentation: Augmentation,
nodes,
tree_edges,
):
g = augmentation.graph
lines = [
f"# Random medial tire decomposition {graph_idx}",
"",
f"- original vertices: {original_graph.number_of_nodes()}",
f"- original edges: {original_graph.number_of_edges()}",
f"- original node connectivity: {nx.node_connectivity(original_graph)}",
f"- augmented vertices: {g.number_of_nodes()}",
f"- augmented edges: {g.number_of_edges()}",
f"- same-level faces filled: {len(augmentation.added_vertices)}",
f"- source vertex: {source}",
f"- tire-tree nodes: {len(nodes)}",
f"- tire-tree edges: {len(tree_edges)}",
"",
"| node | depth | faces | annular cycles | annular | up | singleton down | bite apexes |",
"|--:|--:|--:|--:|--:|--:|--:|--:|",
]
for node in nodes:
singleton_down = set(node.down) - set(node.bites)
lines.append(
f"| T{node.idx} | {node.depth} | {len(node.face_indices)} | "
f"{len(node.annular_cycles)} | {len(node.annular)} | {len(node.up)} | "
f"{len(singleton_down)} | {len(node.bites)} |"
)
path.write_text("\n".join(lines) + "\n")
def draw_case(out_dir: Path, graph_idx: int, g: nx.Graph, source: int, augment: bool = True):
augmentation, _faces, levels, nodes, tree_edges = build_tire_tree(g, source, augment=augment)
work_graph = augmentation.graph
fig = plt.figure(figsize=(17, 10))
spec = fig.add_gridspec(2, 2, width_ratios=[1.15, 1.0], height_ratios=[1.0, 1.25])
ax_graph = fig.add_subplot(spec[0, 0])
ax_tree = fig.add_subplot(spec[1, 0])
draw_base_graph(ax_graph, work_graph, levels, source, augmentation.added_vertices)
draw_tire_tree(ax_tree, nodes, tree_edges)
draw_medial_tire_grid(fig, spec[:, 1], nodes)
fig.suptitle(
f"Random 5-connected maximal planar graph {graph_idx}: "
f"n={g.number_of_nodes()} (+{len(augmentation.added_vertices)}), "
f"source={source}",
fontsize=13,
)
legend = [
Line2D([0], [0], marker="o", color="w", label="source",
markerfacecolor="#fde68a", markeredgecolor="#dc2626", markersize=8),
Line2D([0], [0], marker="o", color="w", label="inserted vertex",
markerfacecolor="#fde68a", markeredgecolor="#7c3aed", markersize=8),
Line2D([0], [0], color="black", lw=1.3, label="annular cycle A(T)"),
Line2D([0], [0], marker="o", color="w", label="up tooth",
markerfacecolor="#2563eb", markersize=6),
Line2D([0], [0], marker="o", color="w", label="down tooth",
markerfacecolor="#dc2626", markersize=6),
Line2D([0], [0], marker="o", color="w", label="bite apex",
markerfacecolor="#7f1d1d", markeredgecolor="black", markersize=6),
]
fig.legend(handles=legend, loc="lower center", ncol=5, fontsize=9)
fig.subplots_adjust(left=0.03, right=0.99, top=0.92, bottom=0.08, wspace=0.08, hspace=0.16)
png = out_dir / f"random_c5_n30_medial_tire_decomposition_{graph_idx}.png"
pdf = out_dir / f"random_c5_n30_medial_tire_decomposition_{graph_idx}.pdf"
fig.savefig(png, dpi=180)
fig.savefig(pdf)
plt.close(fig)
write_index(
out_dir / f"random_c5_n30_medial_tire_decomposition_{graph_idx}.md",
graph_idx,
source,
g,
augmentation,
nodes,
tree_edges,
)
return png, pdf, len(nodes), sum(len(node.annular_cycles) for node in nodes)
def run(args: argparse.Namespace):
out_dir = Path(args.out_dir)
out_dir.mkdir(parents=True, exist_ok=True)
if args.graph6:
graphs = [nx.from_graph6_bytes(args.graph6.encode())]
if args.source is None:
raise ValueError("--source is required with --graph6")
sources = [args.source]
else:
graphs = sample_plantri_graphs(args.n, args.count, args.seed, args.scan_limit)
rng = random.Random(args.seed + 101)
sources = [rng.choice(list(graph.nodes())) for graph in graphs]
for i, (graph, source) in enumerate(zip(graphs, sources), start=1):
png, pdf, node_count, annular_cycle_count = draw_case(
out_dir, i, graph, source, augment=not args.no_augment_same_level_faces
)
print(
f"case {i}: source={source}, connectivity={nx.node_connectivity(graph)}, "
f"tire nodes={node_count}, annular cycles={annular_cycle_count}"
)
print(f" wrote {png}")
print(f" wrote {pdf}")
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--n", type=int, default=30)
parser.add_argument("--count", type=int, default=2)
parser.add_argument("--seed", type=int, default=20260615)
parser.add_argument("--scan-limit", type=int, default=500)
parser.add_argument("--graph6", help="draw this graph6 graph instead of sampling")
parser.add_argument("--source", type=int, help="source vertex for --graph6")
parser.add_argument(
"--no-augment-same-level-faces",
action="store_true",
help="skip the same-level-face vertex insertion step",
)
parser.add_argument(
"--out-dir",
default=str(PAPER_DIR / "experiments" / "random_medial_tire_decompositions"),
)
run(parser.parse_args())
from lib.draw_random_medial_tire_decompositions import main
if __name__ == "__main__":
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"""Draw medial tire decompositions of random 5-connected triangulations.
The source graphs come from ``plantri -c5`` in graph6 format. For each sampled
30-vertex triangulation, this script chooses a random source vertex, builds the
BFS depth-component tire tree, and draws both the tire tree and the medial
tread model for each depth component.
"""
from __future__ import annotations
import argparse
import math
import os
import random
import subprocess
import sys
from collections import defaultdict
from dataclasses import dataclass
from pathlib import Path
PAPER_DIR = Path(__file__).resolve().parents[1]
REPO_ROOT = PAPER_DIR.parents[1]
os.environ.setdefault(
"MPLCONFIGDIR", str(PAPER_DIR / "experiments" / ".matplotlib-cache")
)
os.environ.setdefault("XDG_CACHE_HOME", str(PAPER_DIR / "experiments" / ".cache"))
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import networkx as nx
if str(PAPER_DIR) not in sys.path:
sys.path.insert(0, str(PAPER_DIR))
from lib.medial_tire_decomposition import (
annular_cycle_components,
ekey,
medial_tire_facemodel,
)
@dataclass(frozen=True)
class TreadNode:
idx: int
depth: int
face_indices: tuple[int, ...]
annular: frozenset
up: frozenset
down: frozenset
bites: frozenset
medial: nx.Graph
annular_cycles: tuple[tuple, ...]
@dataclass(frozen=True)
class Augmentation:
graph: nx.Graph
added_vertices: tuple[int, ...]
filled_faces: tuple[tuple[int, tuple[int, int, int], int], ...]
def sample_plantri_graphs(n: int, count: int, seed: int, scan_limit: int) -> list[nx.Graph]:
cmd = [str(REPO_ROOT / "plantri" / "plantri"), "-g", "-c5", str(n)]
rng = random.Random(seed)
sample: list[tuple[int, nx.Graph]] = []
seen = 0
with subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE) as proc:
assert proc.stdout is not None
for raw in proc.stdout:
line = raw.strip()
if not line or line.startswith(b">>"):
continue
graph = nx.from_graph6_bytes(line)
if nx.node_connectivity(graph) < 5:
continue
seen += 1
if len(sample) < count:
sample.append((seen, graph))
else:
j = rng.randrange(seen)
if j < count:
sample[j] = (seen, graph)
if seen >= scan_limit:
proc.terminate()
break
proc.wait(timeout=10)
if len(sample) < count:
raise RuntimeError(f"only found {len(sample)} graphs after scanning {seen}")
return [graph for _ordinal, graph in sample]
def triangular_faces(g: nx.Graph):
ok, emb = nx.check_planarity(g)
if not ok:
raise ValueError("not planar")
seen = set()
faces = []
for u, v in list(emb.edges()):
if (u, v) in seen:
continue
face = tuple(emb.traverse_face(u, v, mark_half_edges=seen))
faces.append(face)
return faces
def edge_face_data(faces):
face_edges = []
edge_faces: dict[tuple, list[int]] = defaultdict(list)
for i, face in enumerate(faces):
edges = {
ekey(face[0], face[1]),
ekey(face[1], face[2]),
ekey(face[2], face[0]),
}
face_edges.append(edges)
for edge in edges:
edge_faces[edge].append(i)
return face_edges, edge_faces
def augment_same_level_faces(g: nx.Graph, source: int) -> Augmentation:
"""Stack a new vertex into every facial triangle with one BFS level.
If a triangular face has all three vertices at level d, the new vertex is
adjacent to those three vertices and therefore has level d + 1. This turns
the same-level region into three adjacent-level tread faces before the tire
decomposition is extracted.
"""
levels = nx.single_source_shortest_path_length(g, source)
faces = triangular_faces(g)
augmented = g.copy()
next_vertex = max(augmented.nodes()) + 1
added = []
filled = []
for face in faces:
face_levels = {levels[v] for v in face}
if len(face_levels) != 1:
continue
new_vertex = next_vertex
next_vertex += 1
augmented.add_node(new_vertex)
augmented.add_edges_from((new_vertex, v) for v in face)
added.append(new_vertex)
filled.append((new_vertex, tuple(face), next(iter(face_levels))))
return Augmentation(
graph=augmented,
added_vertices=tuple(added),
filled_faces=tuple(filled),
)
def depth_components(faces, face_edges, edge_faces, levels):
depths = [min(levels[v] for v in face) for face in faces]
dual_adj: dict[int, set[int]] = defaultdict(set)
for incident in edge_faces.values():
for a in range(len(incident)):
for b in range(a + 1, len(incident)):
dual_adj[incident[a]].add(incident[b])
dual_adj[incident[b]].add(incident[a])
comps = []
seen = [False] * len(faces)
for start in range(len(faces)):
if seen[start]:
continue
depth = depths[start]
stack = [start]
comp = []
seen[start] = True
while stack:
face = stack.pop()
comp.append(face)
for other in dual_adj[face]:
if not seen[other] and depths[other] == depth:
seen[other] = True
stack.append(other)
comps.append((depth, tuple(sorted(comp))))
return comps, depths, dual_adj
def tread_from_component(faces, levels, face_indices):
tread_faces = [faces[i] for i in face_indices]
if not tread_faces:
return None
depth = min(min(levels[v] for v in face) for face in tread_faces)
annular, up, down = set(), set(), set()
face_of_down = defaultdict(int)
for face in tread_faces:
for x, y in ((face[0], face[1]), (face[1], face[2]), (face[2], face[0])):
e = ekey(x, y)
lx, ly = levels[x], levels[y]
if {lx, ly} == {depth, depth + 1}:
annular.add(e)
elif lx == ly == depth:
up.add(e)
elif lx == ly == depth + 1:
down.add(e)
face_of_down[e] += 1
if len(annular) < 3:
return None
return {
"tread_faces": tread_faces,
"annular": annular,
"up": up,
"down": down,
"bites": {e for e in down if face_of_down[e] == 2},
}
def build_tire_tree(g: nx.Graph, source: int, augment: bool = True):
augmentation = augment_same_level_faces(g, source) if augment else Augmentation(g, (), ())
work_graph = augmentation.graph
faces = triangular_faces(work_graph)
face_edges, edge_faces = edge_face_data(faces)
levels = nx.single_source_shortest_path_length(work_graph, source)
comps, depths, dual_adj = depth_components(faces, face_edges, edge_faces, levels)
comp_of_face = {}
for comp_idx, (_depth, face_indices) in enumerate(comps):
for face in face_indices:
comp_of_face[face] = comp_idx
nodes: list[TreadNode] = []
comp_to_node = {}
for comp_idx, (depth, face_indices) in enumerate(comps):
tread = tread_from_component(faces, levels, face_indices)
if tread is None or len(tread["up"]) < 3:
continue
mt = medial_tire_facemodel(tread["tread_faces"])
annular_cycles = tuple(annular_cycle_components(mt, tread["annular"]))
if not annular_cycles:
continue
node = TreadNode(
idx=len(nodes),
depth=depth,
face_indices=face_indices,
annular=frozenset(tread["annular"]),
up=frozenset(tread["up"]),
down=frozenset(tread["down"]),
bites=frozenset(tread["bites"]),
medial=mt,
annular_cycles=annular_cycles,
)
comp_to_node[comp_idx] = node.idx
nodes.append(node)
tree_edges = set()
for comp_idx, (depth, face_indices) in enumerate(comps):
if comp_idx not in comp_to_node:
continue
child = comp_to_node[comp_idx]
parent_candidates = set()
for face in face_indices:
for other in dual_adj[face]:
other_comp = comp_of_face[other]
if depths[other] == depth - 1 and other_comp in comp_to_node:
parent_candidates.add(comp_to_node[other_comp])
for parent in parent_candidates:
tree_edges.add((parent, child))
return augmentation, faces, levels, nodes, sorted(tree_edges)
def graph_layout(g: nx.Graph):
try:
return nx.planar_layout(g)
except nx.NetworkXException:
return nx.spring_layout(g, seed=0)
def draw_base_graph(ax, g, levels, source, added_vertices=()):
pos = graph_layout(g)
max_level = max(levels.values())
cmap = plt.get_cmap("viridis", max_level + 1)
node_colors = [cmap(levels[v]) for v in g.nodes()]
nx.draw_networkx_edges(g, pos, ax=ax, edge_color="#cbd5e1", width=0.8)
added_set = set(added_vertices)
nx.draw_networkx_nodes(
g,
pos,
ax=ax,
node_color=node_colors,
node_size=[
150 if v == source else 96 if v in added_set else 72
for v in g.nodes()
],
edgecolors=[
"#dc2626" if v == source else "#7c3aed" if v in added_set else "#111827"
for v in g.nodes()
],
linewidths=[
1.8 if v == source else 1.2 if v in added_set else 0.45
for v in g.nodes()
],
)
labels = {v: str(v) for v in g.nodes()}
nx.draw_networkx_labels(g, pos, labels=labels, ax=ax, font_size=5)
ax.set_title(
f"Augmented G, source {source}; vertex levels 0..{max_level}",
fontsize=10,
)
ax.set_aspect("equal")
ax.axis("off")
def tree_positions(nodes: list[TreadNode], tree_edges):
children: dict[int, list[int]] = defaultdict(list)
has_parent = set()
for parent, child in tree_edges:
children[parent].append(child)
has_parent.add(child)
roots = [node.idx for node in nodes if node.idx not in has_parent]
for child_list in children.values():
child_list.sort(key=lambda idx: (nodes[idx].depth, idx))
x_counter = 0
pos = {}
def place(idx, depth):
nonlocal x_counter
if not children[idx]:
pos[idx] = (x_counter, -depth)
x_counter += 1
return pos[idx][0]
xs = [place(child, depth + 1) for child in children[idx]]
x = sum(xs) / len(xs)
pos[idx] = (x, -depth)
return x
for root in sorted(roots, key=lambda idx: (nodes[idx].depth, idx)):
place(root, 0)
x_counter += 1
return pos
def draw_tire_tree(ax, nodes: list[TreadNode], tree_edges):
pos = tree_positions(nodes, tree_edges)
for parent, child in tree_edges:
x0, y0 = pos[parent]
x1, y1 = pos[child]
ax.plot([x0, x1], [y0, y1], color="#374151", lw=1.0, zorder=1)
for node in nodes:
x, y = pos[node.idx]
ax.text(
x,
y,
f"T{node.idx}\nd={node.depth}\n{len(node.annular_cycles)} cycle(s)",
ha="center",
va="center",
fontsize=8,
bbox={
"boxstyle": "round,pad=0.32",
"facecolor": "#fef3c7",
"edgecolor": "#111827",
"linewidth": 0.9,
},
zorder=3,
)
ax.set_title("Depth-component tire tree", fontsize=10)
if pos:
xs = [p[0] for p in pos.values()]
ys = [p[1] for p in pos.values()]
ax.set_xlim(min(xs) - 1.0, max(xs) + 1.0)
ax.set_ylim(min(ys) - 0.7, max(ys) + 0.7)
ax.axis("off")
def vertex_xy(k: int, n: int, radius: float) -> tuple[float, float]:
angle = math.pi / 2 - 2 * math.pi * k / n
return radius * math.cos(angle), radius * math.sin(angle)
def edge_midpoint_angle(i: int, n: int) -> float:
return math.pi / 2 - 2 * math.pi * (i + 0.5) / n
def annular_cycle_edges(node: TreadNode) -> set[tuple]:
edges = set()
for order in node.annular_cycles:
for i, a in enumerate(order):
b = order[(i + 1) % len(order)]
edges.add(tuple(sorted((a, b))))
return edges
def draw_compound_tread_model(ax, node: TreadNode):
"""Draw a compound tread using a planar layout of its actual medial graph."""
try:
pos = nx.planar_layout(node.medial)
except nx.NetworkXException:
pos = nx.spring_layout(node.medial, seed=node.idx)
cycle_edges = annular_cycle_edges(node)
non_cycle_edges = [
edge for edge in node.medial.edges()
if tuple(sorted(edge)) not in cycle_edges
]
nx.draw_networkx_edges(
node.medial,
pos,
edgelist=non_cycle_edges,
ax=ax,
edge_color="#cbd5e1",
width=0.7,
)
nx.draw_networkx_edges(
node.medial,
pos,
edgelist=list(cycle_edges),
ax=ax,
edge_color="black",
width=1.4,
)
annular = set(node.annular)
singleton_down = set(node.down) - set(node.bites)
categories = [
(annular, "black", 13, "none"),
(set(node.up) - annular, "#2563eb", 18, "none"),
(singleton_down - annular, "#dc2626", 18, "none"),
(set(node.bites) - annular, "#7f1d1d", 28, "black"),
]
for vertices, color, size, edgecolor in categories:
drawn = [v for v in vertices if v in pos]
if not drawn:
continue
ax.scatter(
[pos[v][0] for v in drawn],
[pos[v][1] for v in drawn],
s=size,
color=color,
edgecolors=edgecolor,
linewidths=0.4,
zorder=3,
)
xs = [p[0] for p in pos.values()]
ys = [p[1] for p in pos.values()]
xpad = max(0.05, (max(xs) - min(xs)) * 0.12)
ypad = max(0.05, (max(ys) - min(ys)) * 0.12)
ax.set_xlim(min(xs) - xpad, max(xs) + xpad)
ax.set_ylim(min(ys) - ypad, max(ys) + ypad)
ax.set_aspect("equal")
ax.axis("off")
def draw_tread_model(ax, node: TreadNode):
if len(node.annular_cycles) > 1:
draw_compound_tread_model(ax, node)
singleton_down = set(node.down) - set(node.bites)
ax.set_title(
f"T{node.idx} d={node.depth}: {len(node.annular_cycles)} annular cycle(s)\n"
f"ann={len(node.annular)} up={len(node.up)} down={len(singleton_down)} "
f"bite={len(node.bites)}",
fontsize=6.4,
pad=1.5,
)
return
cycle_count = len(node.annular_cycles)
offsets = [3.25 * (i - (cycle_count - 1) / 2) for i in range(cycle_count)]
apex_positions: dict[tuple, tuple[float, float]] = {}
apex_corners: dict[tuple, list[tuple[float, float]]] = defaultdict(list)
ann_positions: dict[tuple, tuple[float, float]] = {}
for cycle_idx, order in enumerate(node.annular_cycles):
n = len(order)
dx = offsets[cycle_idx]
ann = {
vertex: (dx + x, y)
for vertex, (x, y) in zip(order, [vertex_xy(k, n, 1.0) for k in range(n)])
}
ann_positions.update(ann)
cyc_x = [ann[v][0] for v in order] + [ann[order[0]][0]]
cyc_y = [ann[v][1] for v in order] + [ann[order[0]][1]]
ax.plot(cyc_x, cyc_y, color="black", lw=1.3, zorder=2)
for i, a in enumerate(order):
b = order[(i + 1) % n]
apexes = [
w for w in set(node.medial.neighbors(a)) & set(node.medial.neighbors(b))
if w not in node.annular
]
for apex in apexes:
apex_corners[apex].extend([ann[a], ann[b]])
if apex in apex_positions:
continue
angle = edge_midpoint_angle(i, n)
if apex in node.up:
radius = 1.42
else:
radius = 0.58
apex_positions[apex] = (
dx + radius * math.cos(angle),
radius * math.sin(angle),
)
for apex, corners in apex_corners.items():
if apex in node.bites and corners:
cx = sum(p[0] for p in corners) / len(corners)
cy = sum(p[1] for p in corners) / len(corners)
center_x = sum(offsets) / len(offsets) if offsets else 0.0
apex_positions[apex] = (
center_x + 0.82 * (cx - center_x),
0.82 * cy,
)
pos = apex_positions[apex]
for corner in corners:
ax.plot([pos[0], corner[0]], [pos[1], corner[1]], color="#9ca3af", lw=0.5)
for apex, pos in apex_positions.items():
if apex in node.up:
color, size, edgecolor = "#2563eb", 13, "none"
elif apex in node.bites:
color, size, edgecolor = "#7f1d1d", 24, "black"
else:
color, size, edgecolor = "#dc2626", 13, "none"
ax.scatter(
[pos[0]],
[pos[1]],
s=size,
color=color,
edgecolors=edgecolor,
linewidths=0.4,
zorder=3,
)
if ann_positions:
ax.scatter(
[p[0] for p in ann_positions.values()],
[p[1] for p in ann_positions.values()],
s=9,
color="black",
zorder=4,
)
singleton_down = set(node.down) - set(node.bites)
ax.set_title(
f"T{node.idx} d={node.depth}: {len(node.annular_cycles)} annular cycle(s)\n"
f"ann={len(node.annular)} up={len(node.up)} down={len(singleton_down)} "
f"bite={len(node.bites)}",
fontsize=6.4,
pad=1.5,
)
pad = 1.7
ax.set_xlim(min(offsets, default=0.0) - pad, max(offsets, default=0.0) + pad)
ax.set_ylim(-1.65, 1.65)
ax.set_aspect("equal")
ax.axis("off")
def draw_medial_tire_grid(fig, outer_spec, nodes):
if not nodes:
ax = fig.add_subplot(outer_spec)
ax.text(0.5, 0.5, "No medial treads extracted", ha="center")
ax.axis("off")
return
cols = min(3, max(1, math.ceil(math.sqrt(len(nodes)))))
rows = math.ceil(len(nodes) / cols)
sub = outer_spec.subgridspec(rows, cols, wspace=0.08, hspace=0.35)
for i in range(rows * cols):
ax = fig.add_subplot(sub[i // cols, i % cols])
if i < len(nodes):
draw_tread_model(ax, nodes[i])
else:
ax.axis("off")
def write_index(
path: Path,
graph_idx: int,
source: int,
original_graph: nx.Graph,
augmentation: Augmentation,
nodes,
tree_edges,
):
g = augmentation.graph
lines = [
f"# Random medial tire decomposition {graph_idx}",
"",
f"- original vertices: {original_graph.number_of_nodes()}",
f"- original edges: {original_graph.number_of_edges()}",
f"- original node connectivity: {nx.node_connectivity(original_graph)}",
f"- augmented vertices: {g.number_of_nodes()}",
f"- augmented edges: {g.number_of_edges()}",
f"- same-level faces filled: {len(augmentation.added_vertices)}",
f"- source vertex: {source}",
f"- tire-tree nodes: {len(nodes)}",
f"- tire-tree edges: {len(tree_edges)}",
"",
"| node | depth | faces | annular cycles | annular | up | singleton down | bite apexes |",
"|--:|--:|--:|--:|--:|--:|--:|--:|",
]
for node in nodes:
singleton_down = set(node.down) - set(node.bites)
lines.append(
f"| T{node.idx} | {node.depth} | {len(node.face_indices)} | "
f"{len(node.annular_cycles)} | {len(node.annular)} | {len(node.up)} | "
f"{len(singleton_down)} | {len(node.bites)} |"
)
path.write_text("\n".join(lines) + "\n")
def draw_case(out_dir: Path, graph_idx: int, g: nx.Graph, source: int, augment: bool = True):
augmentation, _faces, levels, nodes, tree_edges = build_tire_tree(g, source, augment=augment)
work_graph = augmentation.graph
fig = plt.figure(figsize=(17, 10))
spec = fig.add_gridspec(2, 2, width_ratios=[1.15, 1.0], height_ratios=[1.0, 1.25])
ax_graph = fig.add_subplot(spec[0, 0])
ax_tree = fig.add_subplot(spec[1, 0])
draw_base_graph(ax_graph, work_graph, levels, source, augmentation.added_vertices)
draw_tire_tree(ax_tree, nodes, tree_edges)
draw_medial_tire_grid(fig, spec[:, 1], nodes)
fig.suptitle(
f"Random 5-connected maximal planar graph {graph_idx}: "
f"n={g.number_of_nodes()} (+{len(augmentation.added_vertices)}), "
f"source={source}",
fontsize=13,
)
legend = [
Line2D([0], [0], marker="o", color="w", label="source",
markerfacecolor="#fde68a", markeredgecolor="#dc2626", markersize=8),
Line2D([0], [0], marker="o", color="w", label="inserted vertex",
markerfacecolor="#fde68a", markeredgecolor="#7c3aed", markersize=8),
Line2D([0], [0], color="black", lw=1.3, label="annular cycle A(T)"),
Line2D([0], [0], marker="o", color="w", label="up tooth",
markerfacecolor="#2563eb", markersize=6),
Line2D([0], [0], marker="o", color="w", label="down tooth",
markerfacecolor="#dc2626", markersize=6),
Line2D([0], [0], marker="o", color="w", label="bite apex",
markerfacecolor="#7f1d1d", markeredgecolor="black", markersize=6),
]
fig.legend(handles=legend, loc="lower center", ncol=5, fontsize=9)
fig.subplots_adjust(left=0.03, right=0.99, top=0.92, bottom=0.08, wspace=0.08, hspace=0.16)
png = out_dir / f"random_c5_n30_medial_tire_decomposition_{graph_idx}.png"
pdf = out_dir / f"random_c5_n30_medial_tire_decomposition_{graph_idx}.pdf"
fig.savefig(png, dpi=180)
fig.savefig(pdf)
plt.close(fig)
write_index(
out_dir / f"random_c5_n30_medial_tire_decomposition_{graph_idx}.md",
graph_idx,
source,
g,
augmentation,
nodes,
tree_edges,
)
return png, pdf, len(nodes), sum(len(node.annular_cycles) for node in nodes)
def run(args: argparse.Namespace):
out_dir = Path(args.out_dir)
out_dir.mkdir(parents=True, exist_ok=True)
if args.graph6:
graphs = [nx.from_graph6_bytes(args.graph6.encode())]
if args.source is None:
raise ValueError("--source is required with --graph6")
sources = [args.source]
else:
graphs = sample_plantri_graphs(args.n, args.count, args.seed, args.scan_limit)
rng = random.Random(args.seed + 101)
sources = [rng.choice(list(graph.nodes())) for graph in graphs]
for i, (graph, source) in enumerate(zip(graphs, sources), start=1):
png, pdf, node_count, annular_cycle_count = draw_case(
out_dir, i, graph, source, augment=not args.no_augment_same_level_faces
)
print(
f"case {i}: source={source}, connectivity={nx.node_connectivity(graph)}, "
f"tire nodes={node_count}, annular cycles={annular_cycle_count}"
)
print(f" wrote {png}")
print(f" wrote {pdf}")
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--n", type=int, default=30)
parser.add_argument("--count", type=int, default=2)
parser.add_argument("--seed", type=int, default=20260615)
parser.add_argument("--scan-limit", type=int, default=500)
parser.add_argument("--graph6", help="draw this graph6 graph instead of sampling")
parser.add_argument("--source", type=int, help="source vertex for --graph6")
parser.add_argument(
"--no-augment-same-level-faces",
action="store_true",
help="skip the same-level-face vertex insertion step",
)
parser.add_argument(
"--out-dir",
default=str(PAPER_DIR / "experiments" / "random_medial_tire_decompositions"),
)
run(parser.parse_args())
if __name__ == "__main__":
main()