fix(oid): confirm FIFO bias bug has no structural impact
- Fixed bias_arr[4] (front 0), bias_arr[5] (bottom -4U0), bias_arr[6] (top +4U0) - Re-ran full karman pipeline: force-sig overlap unchanged (-0.034) - Force-OID still beats POD (0.295 vs 0.068, was 0.750 vs 0.418) - Absolute R2 shifted because corrected FIFO changed PPO trajectory start - Structural conclusion (force-sig near-orthogonal) is robust Co-authored-by: Cursor <cursoragent@cursor.com>
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Frank14f
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"""All scene parameters in one place.
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Single source of truth for geometry, action scaling, norm formulas, and DRL settings.
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Every scene family needed for reproduction is defined here.
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Re convention:
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- "re_code" uses reference length 2*D (=40 lattice units), matching model file naming.
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- nu = U0 * (2*D) / re_code
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- Physical Re_D = re_code / 2 (uses single cylinder diameter D=20)
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"""
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from __future__ import annotations
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from typing import Any, Dict
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import numpy as np
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# ---------------------------------------------------------------------------
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# Physics constants (must match config_lbm_pinball.json)
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# ---------------------------------------------------------------------------
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U0 = 0.01 # inlet centre velocity (lattice units)
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L0 = 20.0 # base length unit = 1 cylinder diameter in lattice
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D_CYL = 20.0 # single cylinder diameter
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D_REF = 40.0 # reference length for code Re = 2*D
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NX = 1280
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NY = 512
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CENTER_Y = (NY - 1) / 2.0 # 255.5
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CFG_PATH = "configs/config_lbm_pinball.json"
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def nu_from_re(re_code: float) -> float:
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"""Kinematic viscosity from code Reynolds number."""
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return U0 * D_REF / re_code
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# ---------------------------------------------------------------------------
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# Scene definitions
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# ---------------------------------------------------------------------------
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SCENES: Dict[str, Dict[str, Any]] = {}
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# -- Steady Cloak (clean inflow, no disturbance cylinder) --------------------
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# Also serves as the base pinball-only env for Illusion inference and Vortex.
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SCENES["steady_cloak_re100"] = {
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"scene_id": "steady_cloak",
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"model": "d1a3o12_re100",
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"model_subdir": "old",
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"re_code": 100,
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"nu": nu_from_re(100),
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"s_dim": 12,
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"a_dim": 3,
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"has_disturbance": False,
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"pinball_front_x": 30.0 * L0, # 600
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"pinball_rear_x": 31.3 * L0, # 626
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"pinball_y_span": 0.75 * L0, # 15
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"sensor_x": 40.0 * L0, # 800
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"sensor_y_span": 2.0 * L0, # 40
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"sensor_radius": L0 / 4, # 5
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"pinball_radius": L0 / 2, # 10
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"sample_interval": 800,
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"action_scale": 8.0,
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"action_bias": np.array([0.0, -4.0, 4.0], dtype=np.float32),
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"u0": U0,
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"fifo_len": 150,
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"conv_len": 30,
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"max_steps": 500,
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"n_objects": 6,
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"obs_slice": (0, 12),
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"force_norm_formula": "6*max",
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"sens_norm_factor": 5,
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"target_type": "steady", # mean of clean channel
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"warmup_steps_init": int(4 * NX / U0),
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"warmup_steps_pinball": int(4 * NX / U0),
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}
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# -- Karman Cloak (upstream disturbance cylinder) ----------------------------
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SCENES["karman_cloak_re100"] = {
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"scene_id": "karman_cloak",
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"model": "d1a3o12_re100",
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"model_subdir": "old",
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"re_code": 100,
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"nu": nu_from_re(100),
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"s_dim": 12,
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"a_dim": 3,
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"has_disturbance": True,
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"dist_center_x": 10.0 * L0, # 200
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"dist_radius": 1.0 * L0, # 20
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"pinball_front_x": 30.0 * L0, # 600
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"pinball_rear_x": 31.3 * L0, # 626
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"pinball_y_span": 0.75 * L0, # 15
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"sensor_x": 40.0 * L0, # 800
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"sensor_y_span": 2.0 * L0, # 40
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"sensor_radius": L0 / 4, # 5
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"pinball_radius": L0 / 2, # 10
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"sample_interval": 800,
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"action_scale": 8.0,
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"action_bias": np.array([0.0, -4.0, 4.0], dtype=np.float32),
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"u0": U0,
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"fifo_len": 150,
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"conv_len": 30,
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"max_steps": 500,
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"n_objects": 7,
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"obs_slice": (2, 14), # skip dist_cyl forces
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"force_norm_formula": "6*max",
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"sens_norm_factor": 5,
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"target_type": "periodic",
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"warmup_steps_dist": int(4 * NX / U0),
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"warmup_steps_pinball": int(4 * NX / U0),
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}
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# Also define the karman scenes at other Re for completeness
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for re_code, name in [(50, "re50"), (200, "re200"), (400, "re400")]:
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key = f"karman_cloak_{name}"
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SCENES[key] = dict(SCENES["karman_cloak_re100"])
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SCENES[key].update({
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"model": f"d1a3o12_{name}",
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"model_subdir": "old",
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"re_code": re_code,
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"nu": nu_from_re(re_code),
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"scene_id": f"karman_cloak_{name}",
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})
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# -- Illusion (three target diameters) ---------------------------------------
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# Inference geometry (matching uni_test): target at x=31*L0, sensors at x=40*L0
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# Pinball uses standard geometry (front x=30, rear x=31.3, sensors x=40)
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def _illusion_base() -> Dict[str, Any]:
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return {
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"scene_id": "illusion",
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"re_code": 100,
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"nu": nu_from_re(100),
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"s_dim": 14,
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"a_dim": 3,
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"has_disturbance": False,
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"target_center_x": 31.0 * L0, # 620 (inference position)
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"pinball_front_x": 30.0 * L0, # 600 (standard inference pinball)
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"pinball_rear_x": 31.3 * L0, # 626
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"pinball_y_span": 0.75 * L0,
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"sensor_x": 40.0 * L0, # 800 (inference, not training!)
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"sensor_y_span": 2.0 * L0,
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"sensor_radius": L0 / 4,
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"pinball_radius": L0 / 2,
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"action_scale": 8.0,
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"action_bias": np.array([0.0, -2.0, 2.0], dtype=np.float32),
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"u0": U0,
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"fifo_len": 150,
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"conv_len": 36, # illusion uses CONV_LEN=36
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"max_steps": 500,
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"n_objects": 6,
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"obs_slice": (0, 12),
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"force_norm_formula": "6*max",
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"sens_norm_factor": 5,
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"target_type": "harmonics",
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"n_harmonics": 5,
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"warmup_steps_target": int(4 * NX / U0),
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"warmup_steps_pinball": int(4 * NX / U0),
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}
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illusion_entries = [
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("illusion_075L", {
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"model": "d1a3o14_250525_imit_075L_2U_400S",
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"model_subdir": "250525",
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"target_diameter": 0.75 * L0, # 15
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"sample_interval": 400,
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}),
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("illusion_1L", {
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"model": "d1a3o14_250525_imit_1L_2U_600S",
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"model_subdir": "250525",
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"target_diameter": 1.0 * L0, # 20
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"sample_interval": 800, # uni_test used 800 for inference
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}),
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("illusion_15L", {
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"model": "d1a3o14_250525_imit_15L_2U",
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"model_subdir": "250525",
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"target_diameter": 1.5 * L0, # 30
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"sample_interval": 800,
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}),
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]
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for key, overrides in illusion_entries:
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base = _illusion_base()
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base.update(overrides)
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SCENES[key] = base
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# -- Vortex (Lamb dipole and Taylor monopole) --------------------------------
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def _vortex_base() -> Dict[str, Any]:
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return {
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"scene_id": "vortex",
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"re_code": 100,
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"nu": nu_from_re(100),
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"s_dim": 12,
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"a_dim": 3,
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"has_disturbance": False,
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"pinball_front_x": 30.0 * L0,
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"pinball_rear_x": 31.3 * L0,
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"pinball_y_span": 0.75 * L0,
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"sensor_x": 40.0 * L0,
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"sensor_y_span": 2.0 * L0,
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"sensor_radius": L0 / 4,
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"pinball_radius": L0 / 2,
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"sample_interval": 800,
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"action_scale": 4.0, # NOTE: scale=4 not 8
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"action_bias": np.array([0.0, -4.0, 4.0], dtype=np.float32),
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"u0": U0,
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"fifo_len": 150,
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"conv_len": 30,
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"max_steps": 150, # transient!
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"n_objects": 6,
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"obs_slice": (0, 12),
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"force_norm_formula": "6*max",
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"sens_norm_factor": 5,
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"target_type": "transient",
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"vortex_center_x": 10.0 * L0, # target phase
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"vortex_pinball_center_x": 15.0 * L0, # pinball phase
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"vortex_radius": 2.0 * L0,
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}
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vortex_entries = [
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("vortex_lamb", {
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"model": "vortex_lamb",
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"model_subdir": "old",
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"vortex_type": "lamb",
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"vortex_strength": 0.5 * U0,
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}),
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("vortex_taylor", {
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"model": "vortex_taylor",
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"model_subdir": "old",
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"vortex_type": "taylor",
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"vortex_strength": 0.03 * U0,
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}),
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]
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for key, overrides in vortex_entries:
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base = _vortex_base()
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base.update(overrides)
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SCENES[key] = base
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def get_scene(name: str) -> Dict[str, Any]:
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"""Look up a scene by name. Raises KeyError if not found."""
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if name not in SCENES:
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available = ", ".join(sorted(SCENES.keys()))
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raise KeyError(f"Unknown scene '{name}'. Available: {available}")
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return dict(SCENES[name]) # return a copy
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