Changing the model at runtime
58 · Solver and runtime
Two boxes on a 25° ramp with μ = 0.8. At 1 s the script sets the second box's μ to 0.05 in Model.shape_material_mu. Steel keeps its own copy of the material table, so the edit takes effect only after notify_model_changed(ModelFlags.SHAPE_PROPERTIES).
What to look at
- Without notify: nothing changes.
- With notify: the edited box slides from 1 s.
Key parameter
solver.notify_model_changed(flags)Call it after editing model arrays; flags name what changed (SHAPE_PROPERTIES, JOINT_DOF_PROPERTIES, BODY_INERTIAL_PROPERTIES, ...).
Try changing
- Change a joint's armature and notify with JOINT_DOF_PROPERTIES.
- Change gravity with model.set_gravity.
The script
cd tutorials && python 58_runtime_changes.py prints each variant's final metric; --record out.json also writes the replay. Every tutorial imports replay.py from the same folder.
# SPDX-FileCopyrightText: Copyright (c) 2026 Skild AI and the Steel contributors# SPDX-License-Identifier: Apache-2.0
"""Change model properties mid-run: edit friction in place, then call notify_model_changed."""
import math
import newtonimport numpy as npimport warp as wpfrom newton.solvers import SolverSteel
from replay import Recorder
DT = 1.0 / 240.0SUBSTEPS = 8SLOPE = math.radians(25.0) # tan(25 deg) = 0.47
def build(): builder = newton.ModelBuilder() builder.add_ground_plane() tilt = wp.quat_from_axis_angle(wp.vec3(0.0, 1.0, 0.0), SLOPE) cfg = newton.ModelBuilder.ShapeConfig(mu=0.8) builder.add_shape_box( -1, xform=wp.transform((0.0, 0.0, 0.4), tilt), hx=0.9, hy=0.4, hz=0.03, cfg=cfg ) normal = np.array(wp.quat_rotate(tilt, wp.vec3(0.0, 0.0, 1.0))) uphill = np.array(wp.quat_rotate(tilt, wp.vec3(1.0, 0.0, 0.0))) for y in (-0.15, 0.15): box = builder.add_body( xform=wp.transform(np.array([0.0, y, 0.4]) + 0.55 * uphill + 0.081 * normal, tilt) ) builder.add_shape_box(box, hx=0.05, hy=0.05, hz=0.05, cfg=cfg) return builder.finalize()
def simulate(rec, label, notify): model = build() solver = SolverSteel(model) pipeline = newton.CollisionPipeline(model) contacts = pipeline.contacts() state_0, state_1, control = model.state(), model.state(), model.control() start = state_0.body_q.numpy()[:, :3].copy()
run = rec.variant(label, model) for frame in range(rec.frames(3.0)): if frame == rec.fps: # at 1 s, make the second box slippery: shapes are ground, ramp, box 0, box 1 mu = model.shape_material_mu.numpy() mu[3] = 0.05 # pair average 0.425 < tan(slope) model.shape_material_mu.assign(mu) if notify: solver.notify_model_changed(newton.ModelFlags.SHAPE_PROPERTIES) slide = np.linalg.norm(state_0.body_q.numpy()[:, :3] - start, axis=1) run.frame(state_0, unchanged_box=slide[0], edited_box=slide[1]) for _ in range(SUBSTEPS): pipeline.collide(state_0, contacts) solver.step(state_0, state_1, control, contacts, DT) state_0, state_1 = state_1, state_0 run.check(solver)
if __name__ == "__main__": rec = Recorder() simulate(rec, "edited at 1 s, no notify", False) simulate(rec, "edited at 1 s + notify_model_changed", True) rec.save()# SPDX-FileCopyrightText: Copyright (c) 2026 Skild AI and the Steel contributors# SPDX-License-Identifier: Apache-2.0
"""Record Steel tutorial runs as replay JSON for the tutorials page, or print a summary.
Every tutorial imports this module. ``python NN_name.py`` runs the variants and printsthe final metric of each; ``--record out.json`` also writes body poses, shapes and metricseries that the page replays in 3D."""
import argparseimport base64import jsonimport osimport subprocessimport sysimport time
import newtonimport numpy as npimport warp as wp
from source_hash import source_sha256
_RENDERED_TYPES = { newton.GeoType.PLANE, newton.GeoType.SPHERE, newton.GeoType.CAPSULE, newton.GeoType.ELLIPSOID, newton.GeoType.CYLINDER, newton.GeoType.BOX, newton.GeoType.MESH, newton.GeoType.CONE, newton.GeoType.CONVEX_MESH,}
class Recorder: """Collect the variants of one tutorial; ``fps`` is the replay frame rate."""
def __init__(self, fps: int = 30): parser = argparse.ArgumentParser() parser.add_argument( "--record", metavar="OUT.json", help="write a replay file for the tutorials page" ) parser.add_argument("--device", default=None, help="Warp device, for example cuda:0") self.args = parser.parse_args() if self.args.device: wp.set_device(self.args.device) self.fps = fps self.script = os.path.abspath(sys.argv[0]) self.variants: list[Variant] = []
def frames(self, seconds: float) -> int: """Number of replay frames in ``seconds``, including the first.""" return int(round(seconds * self.fps)) + 1
def variant( self, label: str, model: newton.Model, *, ghost: bool = False, slot: int | None = None, scene: str | None = None, ) -> "Variant": """Start one run; ``ghost`` overlays run ``slot``, ``scene`` groups runs for charts.""" variant = Variant(label, model, self.fps, ghost, slot, scene) self.variants.append(variant) return variant
def save(self) -> None: """Print a summary and, with ``--record``, write the replay file.""" for variant in self.variants: last = variant.metrics[-1] if variant.metrics else {} flag = " (rows dropped)" if variant.overflow else "" print(f"{variant.label:<48} {json.dumps(last)} {variant.wall:.2f} s{flag}") if not self.args.record: return source_sha = source_sha256(self.script) doc = { "script": os.path.basename(self.script), "script_sha256": source_sha, "newton_commit": _newton_commit(), "newton_version": newton.__version__, "warp_version": wp.config.version, "gpu": wp.get_device().name, "fps": self.fps, "variants": [v.to_json() for v in self.variants], } with open(self.args.record, "w") as f: json.dump(doc, f, separators=(",", ":")) print(f"wrote {self.args.record}")
class Variant: """One recorded run: a pose per frame for every body, plus named metric values."""
def __init__(self, label, model, fps, ghost, slot, scene): self.label, self.model, self.fps, self.ghost, self.slot = label, model, fps, ghost, slot self.scene = scene self.poses: list[np.ndarray] = [] self.metrics: list[dict] = [] self.awake: list[list[int]] = [] self.particles: list[np.ndarray] = [] self.overflow = False self.start = time.perf_counter() self.wall = 0.0
def frame(self, state: newton.State, awake=None, particles=None, **metrics) -> None: """Record ``state.body_q``, optional awake flags, particle positions and metric values.""" self.poses.append(state.body_q.numpy().astype(np.float32).copy()) if particles is not None: self.particles.append(particles.numpy().astype(np.float32).copy()) self.metrics.append({k: _round(v) for k, v in metrics.items()}) if awake is not None: self.awake.append([int(x) for x in awake.numpy()]) self.wall = time.perf_counter() - self.start
def check(self, solver) -> None: """Note whether the solver dropped rows; call once after the run.""" try: solver.check_constraint_capacity() except RuntimeError: self.overflow = True
def to_json(self) -> dict: poses = ( np.stack(self.poses) if self.poses else np.zeros((0, self.model.body_count, 7), np.float32) ) return { "label": self.label, "fps": self.fps, "ghost": self.ghost, "slot": self.slot, "scene": self.scene, "bodies": int(self.model.body_count), "frames": int(poses.shape[0]), "poses": base64.b64encode(poses.astype(np.float32).tobytes()).decode(), "shapes": _shape_table(self.model), "metric": self.metrics, "awake": self.awake or None, "particles": self._particles_json(), "wall_s": round(self.wall, 3), "overflow": self.overflow, }
def _particles_json(self): if not self.particles: return None frames = np.stack(self.particles) tris = self.model.tri_indices radius = self.model.particle_radius.numpy() return { "count": int(frames.shape[1]), "frames": base64.b64encode(frames.astype(np.float32).tobytes()).decode(), "radius": round(float(radius.mean()), 5) if radius.size else 0.0, "tris": [int(v) for v in tris.numpy().reshape(-1)] if tris is not None and tris.shape[0] else None, }
def _shape_table(model): types = model.shape_type.numpy() scales = model.shape_scale.numpy() xforms = model.shape_transform.numpy() bodies = model.shape_body.numpy() flags = model.shape_flags.numpy() shapes = [] for i, t in enumerate(types): if int(t) not in _RENDERED_TYPES or not flags[i] & int(newton.ShapeFlags.VISIBLE): continue shape = { "b": int(bodies[i]), "t": int(t), "s": [round(float(v), 5) for v in scales[i]], "x": [round(float(v), 6) for v in xforms[i]], } if int(t) in (newton.GeoType.MESH, newton.GeoType.CONVEX_MESH): mesh = model.shape_source[i] shape["v"] = [round(float(v), 5) for v in np.asarray(mesh.vertices).reshape(-1)] shape["i"] = [int(v) for v in np.asarray(mesh.indices).reshape(-1)] shapes.append(shape) return shapes
def _round(value): value = float(value) return round(value, 5) if np.isfinite(value) else None
def _newton_commit(): if os.environ.get("NEWTON_COMMIT"): return os.environ["NEWTON_COMMIT"] try: root = os.path.dirname(os.path.dirname(newton.__file__)) return subprocess.check_output(["git", "-C", root, "rev-parse", "HEAD"], text=True).strip() except (OSError, subprocess.CalledProcessError): return NoneRecorded with SolverSteel on Newton 1.9.0.dev0, Warp 1.19.0, NVIDIA RTX PRO 6000 Blackwell Server Edition. Replays read the state back every frame, so they are not a speed benchmark. Script · page text
Steel docs and tutorials are licensed under Apache-2.0. Third-party notices. "Skild", "Skild AI" and the Skild logo are trademarks of Skild AI and are not licensed under Apache-2.0.