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efeed27 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 | """
Fold execution engine.
Applies fold operations (valley / mountain) to a Paper object using
Rodrigues' rotation formula, face splitting, and layer tracking.
"""
from __future__ import annotations
import math
from typing import Callable
import numpy as np
from .paper import Paper
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Rodrigues' rotation
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def _rodrigues_rotate(
points: np.ndarray,
axis_point: np.ndarray,
axis_dir: np.ndarray,
angle_rad: float,
) -> np.ndarray:
"""Rotate *points* (N, 3) around an axis defined by a point and direction
using Rodrigues' rotation formula. Returns rotated points (N, 3)."""
k = axis_dir / (np.linalg.norm(axis_dir) + 1e-30)
translated = points - axis_point
cos_a = math.cos(angle_rad)
sin_a = math.sin(angle_rad)
dot_term = np.dot(translated, k).reshape(-1, 1) * k # (N,1)*(3,) broadcast
rotated = (
translated * cos_a
+ np.cross(k, translated) * sin_a
+ dot_term * (1.0 - cos_a)
)
return rotated + axis_point
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Single fold
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def apply_fold(
paper: Paper,
fold_dict: dict,
) -> tuple[Paper, str | None]:
"""Apply a single fold to *paper* and return ``(new_paper, error_or_None)``.
*fold_dict* has the form::
{
"type": "valley" | "mountain",
"line": {"start": [x, y], "end": [x, y]},
"angle": 0-180,
}
Steps:
1. Validate inputs.
2. Split faces along the fold line.
3. Determine vertices to rotate (one side of fold line).
4. Rodrigues' rotation of those vertices.
5. Update edge assignments for new fold-line edges.
6. Update fold angles.
7. Update layer tracking.
"""
# ββ 0. parse & validate βββββββββββββββββββββββββββββββββββββββββ
fold_type = fold_dict.get("type", "valley")
line = fold_dict.get("line", {})
angle_deg = fold_dict.get("angle", 180)
if fold_type not in ("valley", "mountain"):
return paper, f"Unknown fold type: {fold_type}"
try:
start_2d = np.array(line["start"], dtype=np.float64)[:2]
end_2d = np.array(line["end"], dtype=np.float64)[:2]
except (KeyError, TypeError, IndexError) as exc:
return paper, f"Invalid fold line: {exc}"
if np.linalg.norm(end_2d - start_2d) < 1e-12:
return paper, "Fold line has zero length"
if not (0 < angle_deg <= 180):
return paper, f"Angle must be in (0, 180], got {angle_deg}"
# ββ 1. deep copy so the original is untouched βββββββββββββββββββ
new_paper = paper.copy()
# ββ 2. split faces along fold line ββββββββββββββββββββββββββββββ
try:
fold_edge_ids = new_paper.split_faces_along_line(start_2d, end_2d)
except Exception as exc:
return paper, f"Face split failed: {exc}"
# ββ 3. determine vertices to rotate βββββββββββββββββββββββββββββ
rotate_ids = new_paper.get_vertices_on_side(start_2d, end_2d, "positive")
if not rotate_ids:
# Try the other side β maybe the fold line is at the boundary
rotate_ids = new_paper.get_vertices_on_side(start_2d, end_2d, "negative")
if not rotate_ids:
return paper, "No vertices to rotate β fold line may not intersect paper"
# ββ 4. Rodrigues' rotation ββββββββββββββββββββββββββββββββββββββ
sign = 1.0 if fold_type == "valley" else -1.0
angle_rad = sign * math.radians(angle_deg)
axis_point = np.array([start_2d[0], start_2d[1], 0.0])
axis_dir = np.array([end_2d[0] - start_2d[0], end_2d[1] - start_2d[1], 0.0])
pts = new_paper.vertices[rotate_ids]
rotated = _rodrigues_rotate(pts, axis_point, axis_dir, angle_rad)
new_paper.vertices[rotate_ids] = rotated
# ββ 5. update edge assignments ββββββββββββββββββββββββββββββββββ
assignment = "V" if fold_type == "valley" else "M"
for eidx in fold_edge_ids:
if eidx < len(new_paper.assignments):
new_paper.assignments[eidx] = assignment
# ββ 6. update fold angles βββββββββββββββββββββββββββββββββββββββ
for eidx in fold_edge_ids:
if eidx < len(new_paper.fold_angles):
new_paper.fold_angles[eidx] = angle_deg * sign
# ββ 7. update layer tracking ββββββββββββββββββββββββββββββββββββ
# For each pair of faces on opposite sides of the fold line, record
# layer ordering. Simple heuristic: faces that were rotated are now
# on top (sign +1) of faces that stayed put.
rotated_set = set(rotate_ids)
def _face_side(face_verts: list[int]) -> str:
"""Classify a face as 'rotated', 'fixed', or 'mixed'."""
r_count = sum(1 for v in face_verts if v in rotated_set)
if r_count == len(face_verts):
return "rotated"
if r_count == 0:
return "fixed"
return "mixed"
face_sides = [_face_side(f) for f in new_paper.faces]
for i in range(len(new_paper.faces)):
for j in range(i + 1, len(new_paper.faces)):
if face_sides[i] == "rotated" and face_sides[j] == "fixed":
new_paper.face_orders.append((i, j, 1))
elif face_sides[i] == "fixed" and face_sides[j] == "rotated":
new_paper.face_orders.append((j, i, 1))
return new_paper, None
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Strategy executor (matches mock_env.execute_fold_strategy signature)
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def execute_fold_strategy(
strategy_fn: Callable,
paper: Paper,
max_folds: int = 20,
) -> tuple[Paper, list[dict], str | None]:
"""Execute a ``fold_strategy`` function against the real physics engine.
Signature matches ``mock_env.execute_fold_strategy`` so the trainer
reward functions can swap engines transparently.
Parameters
----------
strategy_fn : callable
``strategy_fn(paper_state_dict) -> list[dict]``
paper : Paper
The initial paper state.
max_folds : int
Maximum number of folds to apply.
Returns
-------
(final_paper, applied_folds, error_or_None)
"""
state_dict = paper.to_dict()
try:
folds = strategy_fn(state_dict)
except Exception as exc:
return paper, [], f"Strategy function raised: {exc}"
if not isinstance(folds, list):
return paper, [], "Strategy must return a list of fold dicts"
applied: list[dict] = []
current = paper
for i, fold in enumerate(folds):
if i >= max_folds:
break
if not isinstance(fold, dict):
return current, applied, f"Fold {i} is not a dict"
current, error = apply_fold(current, fold)
if error:
return current, applied, f"Fold {i} failed: {error}"
applied.append(fold)
return current, applied, None
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