CelerisLab/tests/postproc/run_stealth_steady_sweep.py
Frank14f 6e3756c587 fix(esopull): correct init layout and pre-streaming semantics (v0.5.1)
EsoPull curved boundaries and wall BCs now use consistent backing-layout
reads; InitEsoPull writes equilibrium in t=0 EsoPull layout. Cache N_OBJS
after compile and atomic config header writes to avoid parallel races.
Adds config screening tools, flume configs, and FP16S/EsoPull diagnosis doc.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-27 22:32:01 +08:00

239 lines
8.0 KiB
Python

# CelerisLab/tests/postproc/run_stealth_steady_sweep.py
"""Steady stealth rotation sweep: vorticity + final-step streakline per speed.
Grid nx=1500 (see config_lbm_three_cylinder_triangle.json). Steady means
constant surface-speed means only (no harmonic components).
"""
from __future__ import annotations
import argparse
import json
import sys
from pathlib import Path
from typing import List, Tuple
_REPO = Path(__file__).resolve().parents[2]
sys.path.insert(0, str(_REPO / "src"))
sys.path.insert(0, str(_REPO / "tests" / "postproc"))
import run_exp_ctrl_matrix_vorticity as vort_mod
import run_exp_ctrl_matrix_streakline as streak
from CelerisLab import Simulation
from CelerisLab.common.preprocess import build_triangle_release_points, cylinders_from_triangle_layout
from CelerisLab.common.render import compute_vorticity, render_vorticity_field
from CelerisLab.common.streakline import Streakline, IntegratorConfig, ReleaseConfig
STEALTH_REF_M_S = 0.01806
# Fractions of reference stealth surface speed (action2 negative, action3 positive).
SPEED_FRACTIONS: List[Tuple[str, float]] = [
("s050", 0.50),
("s075", 0.75),
("s100", 1.00),
("s125", 1.25),
("s150", 1.50),
]
DEFAULT_OUT = _REPO / "tests" / "output" / "stealth_steady_sweep_nx1500"
def _stealth_features(omega_m_s: float) -> dict:
return {
"action1": {"mean": 0.0, "components": []},
"action2": {"mean": -float(omega_m_s), "components": []},
"action3": {"mean": float(omega_m_s), "components": []},
}
def run_one(
tag: str,
omega_m_s: float,
*,
out_dir: Path,
total_steps: int,
streak_window: int,
sample_every: int,
report_every: int,
device_id: int,
) -> dict:
features = _stealth_features(omega_m_s)
slug = f"stealth_{tag}_w{omega_m_s:.5f}"
compat = vort_mod._ensure_compat_config(vort_mod.CONFIG_PATH)
sim = Simulation(compat, device_id=device_id)
layout = vort_mod._add_triangle_cylinders(sim)
sim.initialize()
u_lb = float(sim.lbm_cfg.velocity)
nx = int(sim.lbm_cfg.nx)
ny = int(sim.lbm_cfg.ny)
dt_phys = (vort_mod.CYLINDER_DIAMETER_M / vort_mod.DIAMETER_CELLS) * (
u_lb / vort_mod.INLET_U_PHYS_M_S
)
cylinders = cylinders_from_triangle_layout(layout)
base_release = build_triangle_release_points(
layout, nx=nx, ny=ny, diameter_cells=vort_mod.DIAMETER_CELLS
)
release_cfg = ReleaseConfig(
mode="strip",
line_count=1,
line_span=0.0,
downstream_count=5,
downstream_spacing=1.0,
inject_per_seed=1,
)
integrator_cfg = IntegratorConfig(alpha_t=0.25, alpha_x=0.40, max_particle_age=None)
streak_obj = Streakline(
release_points=base_release,
release_cfg=release_cfg,
integrator_cfg=integrator_cfg,
nx=nx,
ny=ny,
cylinders=cylinders,
)
streak_start = max(0, int(total_steps) - int(streak_window))
print(
f"--- {slug} omega={omega_m_s:.5f} m/s steps={total_steps} "
f"grid={nx}x{ny} streak_from={streak_start} ---"
)
print(
f" layout x_apex={layout['x_apex']:.1f} x_rear={layout['x_rear']:.1f} "
f"release_x={base_release[0, 0]:.1f}"
)
for step in range(total_steps):
t_phys = step * dt_phys
a1, a2, a3 = vort_mod._actions_at_time(t_phys, features)
w1 = vort_mod._action_to_omega_lb(a1, u_lb)
w2 = vort_mod._action_to_omega_lb(a2, u_lb)
w3 = vort_mod._action_to_omega_lb(a3, u_lb)
if vort_mod.SWAP_ACTION23_BODIES:
vort_mod._set_body_omegas(sim, w1, w3, w2)
else:
vort_mod._set_body_omegas(sim, w1, w2, w3)
sim.run(1)
if report_every > 0 and (step + 1) % report_every == 0:
print(
f" step {step + 1}/{total_steps} a=({a1:+.5f},{a2:+.5f},{a3:+.5f}) "
f"omega_lb=({w1:+.6f},{w2:+.6f},{w3:+.6f}) "
f"particles={streak_obj.n_particles}"
)
if step >= streak_start and (step + 1) % sample_every == 0:
macro = sim.get_macroscopic()
streak_obj.observe(ux=macro["ux"], uy=macro["uy"], step=int(step + 1))
if streak_obj.n_particles == 0:
raise RuntimeError(f"{slug}: no particles in streak window.")
macro = sim.get_macroscopic()
vort_field = compute_vorticity(macro["ux"], macro["uy"])
vort_png = out_dir / f"vorticity_{slug}.png"
streak_png = out_dir / f"streakline_{slug}.png"
ckpt = out_dir / f"state_{slug}.h5"
sim.save_checkpoint(str(ckpt))
vort_info = render_vorticity_field(
vort_field,
nx=nx,
ny=ny,
out_path=str(vort_png),
cylinders=cylinders,
vmin=vort_mod.VORT_VMIN,
vmax=vort_mod.VORT_VMAX,
minimal_axes=True,
)
streak_info = streak_obj.render(
str(streak_png),
age_decay_steps=streak.STREAK_AGE_DECAY,
blur_sigma=streak.STREAK_BLUR_SIGMA,
background_color=(1.0, 1.0, 1.0),
streak_color=streak.STREAK_COLOR,
)
sim.close()
summary = {
"tag": tag,
"slug": slug,
"omega_m_s": float(omega_m_s),
"fraction_of_ref": float(omega_m_s / STEALTH_REF_M_S),
"total_steps": int(total_steps),
"streak_window_steps": int(streak_window),
"streak_start_step": int(streak_start),
"sample_every": int(sample_every),
"layout": {k: float(layout[k]) for k in layout},
"release_points": base_release.tolist(),
"particle_count_final": int(streak_obj.n_particles),
"vort_png": str(vort_png),
"streak_png": str(streak_png),
"checkpoint": str(ckpt),
"vorticity": vort_info,
"streakline": streak_info,
}
with (out_dir / f"summary_{slug}.json").open("w", encoding="utf-8") as f:
json.dump(summary, f, indent=2)
print(f" saved {vort_png.name} {streak_png.name} particles={streak_obj.n_particles}")
return summary
def main() -> int:
ap = argparse.ArgumentParser(description="steady stealth rotation sweep")
ap.add_argument("--out-dir", type=str, default=str(DEFAULT_OUT))
ap.add_argument("--steps", type=int, default=vort_mod.FIXED_STEPS)
ap.add_argument("--streak-window", type=int, default=streak.STREAK_WINDOW_STEPS)
ap.add_argument("--sample-every", type=int, default=streak.STREAK_SAMPLE_EVERY)
ap.add_argument("--report-every", type=int, default=20000)
ap.add_argument("--device-id", type=int, default=0)
ap.add_argument("--tags", type=str, default="", help="Comma tags e.g. s050,s100 or empty=all")
args = ap.parse_args()
out_dir = Path(args.out_dir)
out_dir.mkdir(parents=True, exist_ok=True)
selected = {t.strip() for t in args.tags.split(",") if t.strip()} if args.tags else None
with vort_mod.CONFIG_PATH.open("r", encoding="utf-8") as f:
grid = json.load(f)["grid"]
print(
f"Output: {out_dir} | grid={grid['nx']}x{grid['ny']} | steps={args.steps} | "
f"ref_omega={STEALTH_REF_M_S} m/s"
)
summaries = []
for tag, frac in SPEED_FRACTIONS:
if selected and tag not in selected:
continue
omega = STEALTH_REF_M_S * frac
summaries.append(
run_one(
tag,
omega,
out_dir=out_dir,
total_steps=int(args.steps),
streak_window=int(args.streak_window),
sample_every=int(args.sample_every),
report_every=int(args.report_every),
device_id=int(args.device_id),
)
)
manifest = {
"grid": grid,
"steps": int(args.steps),
"stealth_ref_m_s": STEALTH_REF_M_S,
"speed_fractions": SPEED_FRACTIONS,
"streak_color": list(streak.STREAK_COLOR),
"cases": summaries,
}
with (out_dir / "manifest.json").open("w", encoding="utf-8") as f:
json.dump(manifest, f, indent=2)
print(f"Manifest: {out_dir / 'manifest.json'}")
return 0
if __name__ == "__main__":
raise SystemExit(main())