Сохраняемся

2026-07-24 09:45:32 +03:00
parent 6cfc16e53c
commit 0614ea384a
14 changed files with 1592 additions and 142 deletions
@@ -81,42 +81,103 @@ def _height_at(
 def build_seafloor_params(
    seed: int = 42,
    *,
-    size_x: float = 40.0,
-    size_y: float = 60.0,
+    size_x: float | None = None,
+    size_y: float | None = None,
+    relief_scale_pct: float = 20.0,
+    corridor: dict[str, Any] | None = None,
 ) -> dict[str, Any]:
+    """Build seafloor heightfield params.
+
+    When ``corridor`` is provided (AUV survey swath), random unevenness is placed
+    only inside that yellow echosounder strip. Feature size scales with
+    ``relief_scale_pct`` percent of the strip width.
+    """
    rng = random.Random(int(seed))
-    size_x = max(4.0, float(size_x))
-    size_y = max(4.0, float(size_y))
+    relief_scale_pct = max(1.0, min(100.0, float(relief_scale_pct)))
+
+    corr = corridor if isinstance(corridor, dict) else {}
+    corr = {k: v for k, v in corr.items() if v is not None}
+    auv_x = float(corr.get("auvX", 0.0))
+    auv_y = float(corr.get("auvY", 0.0))
+    heading_deg = float(corr.get("headingDeg", 0.0))
+    survey_length = max(1.0, float(corr.get("surveyLength", 40.0)))
+    auv_depth = max(0.3, float(corr.get("auvDepth", 2.5)))
+    swath_deg = max(5.0, min(170.0, float(corr.get("swathAngleDeg", 90.0))))
+
+    half_swath = auv_depth * math.tan(math.radians(swath_deg) * 0.5)
+    strip_width = max(4.0, 2.0 * half_swath)
+    half_w = strip_width * 0.5
+    heading = math.radians(heading_deg)
+    hx, hy = math.cos(heading), math.sin(heading)
+    nx, ny = -math.sin(heading), math.cos(heading)
+
+    # AABB of the survey strip (+ padding) → terrain extent around origin.
+    pad = strip_width * 0.6 + 8.0
+    xs: list[float] = []
+    ys: list[float] = []
+    for t in (0.0, survey_length):
+        for lat in (-half_w, half_w):
+            xs.append(auv_x + hx * t + nx * lat)
+            ys.append(auv_y + hy * t + ny * lat)
+    reach = max(
+        max(abs(v) for v in xs) + pad,
+        max(abs(v) for v in ys) + pad,
+        strip_width + 12.0,
+        survey_length * 0.35 + 12.0,
+    )
+    auto_size = max(24.0, reach * 2.0)
+    size_x = max(4.0, float(size_x) if size_x is not None else auto_size)
+    size_y = max(4.0, float(size_y) if size_y is not None else auto_size)
+
+    # Mild background undulation (not the main corridor features).
    base_z = rng.uniform(-8.0, -3.0)
-    amplitude = rng.uniform(0.15, 0.6)
-    frequency = rng.uniform(0.15, 0.55)
-    hills = [
-        (
-            rng.uniform(-size_x * 0.4, size_x * 0.4),
-            rng.uniform(-size_y * 0.4, size_y * 0.4),
-            rng.uniform(0.3, 1.4),
-            rng.uniform(2.0, 8.0),
+    amplitude = rng.uniform(0.05, 0.18)
+    frequency = rng.uniform(0.08, 0.25)
+
+    # Characteristic feature size = pct of yellow strip width.
+    feature_scale = strip_width * (relief_scale_pct / 100.0)
+    feature_scale = max(0.15, feature_scale)
+
+    def point_in_strip(t: float, lat: float) -> tuple[float, float]:
+        return (
+            auv_x + hx * t + nx * lat,
+            auv_y + hy * t + ny * lat,
        )
-        for _ in range(rng.randint(2, 5))
-    ]
-    valleys = [
-        (
-            rng.uniform(-size_x * 0.4, size_x * 0.4),
-            rng.uniform(-size_y * 0.4, size_y * 0.4),
-            rng.uniform(0.2, 0.9),
-            rng.uniform(2.0, 7.0),
-        )
-        for _ in range(rng.randint(1, 4))
-    ]
-    bumps = [
-        (
-            rng.uniform(-size_x * 0.45, size_x * 0.45),
-            rng.uniform(-size_y * 0.45, size_y * 0.45),
-            rng.uniform(0.05, 0.4),
-            rng.uniform(0.4, 2.0),
-        )
-        for _ in range(rng.randint(8, 20))
-    ]
+
+    n_hills = rng.randint(2, 4)
+    n_valleys = rng.randint(1, 3)
+    # More bumps when features are smaller so the strip stays filled.
+    density = max(0.35, min(1.6, 20.0 / max(relief_scale_pct, 1.0)))
+    n_bumps = int(round(rng.uniform(10, 18) * density))
+    n_bumps = max(6, min(36, n_bumps))
+
+    hills = []
+    for _ in range(n_hills):
+        t = rng.uniform(0.0, survey_length)
+        lat = rng.uniform(-half_w * 0.85, half_w * 0.85)
+        x, y = point_in_strip(t, lat)
+        rad = feature_scale * rng.uniform(0.9, 1.8)
+        amp = feature_scale * rng.uniform(0.25, 0.7)
+        hills.append((x, y, amp, rad))
+
+    valleys = []
+    for _ in range(n_valleys):
+        t = rng.uniform(0.0, survey_length)
+        lat = rng.uniform(-half_w * 0.85, half_w * 0.85)
+        x, y = point_in_strip(t, lat)
+        rad = feature_scale * rng.uniform(0.8, 1.6)
+        amp = feature_scale * rng.uniform(0.18, 0.5)
+        valleys.append((x, y, amp, rad))
+
+    bumps = []
+    for _ in range(n_bumps):
+        t = rng.uniform(0.0, survey_length)
+        lat = rng.uniform(-half_w * 0.98, half_w * 0.98)
+        x, y = point_in_strip(t, lat)
+        rad = feature_scale * rng.uniform(0.35, 1.15)
+        amp = feature_scale * rng.uniform(0.1, 0.4)
+        bumps.append((x, y, amp, rad))
+
    return {
        "seed": int(seed),
        "sizeX": size_x,
@@ -127,6 +188,17 @@ def build_seafloor_params(
        "hills": hills,
        "valleys": valleys,
        "bumps": bumps,
+        "reliefScalePct": relief_scale_pct,
+        "stripWidth": strip_width,
+        "corridor": {
+            "auvX": auv_x,
+            "auvY": auv_y,
+            "headingDeg": heading_deg,
+            "surveyLength": survey_length,
+            "auvDepth": auv_depth,
+            "swathAngleDeg": swath_deg,
+            "stripWidth": strip_width,
+        },
    }


@@ -251,12 +323,14 @@ def save_survey_surface(
 def prepare_mle_scene(
    *,
    seed: int = 42,
-    size_x: float = 40.0,
-    size_y: float = 60.0,
+    size_x: float | None = None,
+    size_y: float | None = None,
    res_x: int = 80,
    res_y: int = 120,
    output_dir: str | Path = "mle_runs",
    settings: dict[str, Any] | None = None,
+    relief_scale_pct: float = 20.0,
+    corridor: dict[str, Any] | None = None,
 ) -> dict[str, Any]:
    """Generate seafloor for simulation; create run folder with empty survey OBJ."""
    base = resolve_mle_dir(output_dir)
@@ -269,7 +343,33 @@ def prepare_mle_scene(
        n += 1
    run_dir.mkdir(parents=True, exist_ok=False)

-    params = build_seafloor_params(seed, size_x=size_x, size_y=size_y)
+    # Prefer explicit corridor fields; fill gaps from settings snapshot.
+    corr: dict[str, Any] = {}
+    if isinstance(corridor, dict):
+        corr.update({k: v for k, v in corridor.items() if v is not None})
+    if isinstance(settings, dict):
+        auv = settings.get("auv") if isinstance(settings.get("auv"), dict) else {}
+        beams = settings.get("beams") if isinstance(settings.get("beams"), dict) else {}
+        motion = settings.get("motion") if isinstance(settings.get("motion"), dict) else {}
+        defaults_from_settings = {
+            "auvX": auv.get("x", settings.get("auvX")),
+            "auvY": auv.get("y", settings.get("auvY")),
+            "headingDeg": auv.get("headingDeg", settings.get("auvHeadingDeg")),
+            "surveyLength": motion.get("surveyLength", settings.get("surveyLength")),
+            "auvDepth": auv.get("depth", settings.get("auvDepth")),
+            "swathAngleDeg": beams.get("swathAngleDeg", settings.get("swathAngleDeg")),
+        }
+        for key, value in defaults_from_settings.items():
+            if corr.get(key) is None and value is not None:
+                corr[key] = value
+
+    params = build_seafloor_params(
+        seed,
+        size_x=size_x,
+        size_y=size_y,
+        relief_scale_pct=relief_scale_pct,
+        corridor=corr,
+    )
    mesh = sample_seafloor_grid(params, res_x=res_x, res_y=res_y)
    # Survey OBJ starts empty and is filled from multibeam hits during motion.
    obj_path = run_dir / "seafloor.obj"