Merge remote-tracking branches 'origin/sub_laptop_3' and 'origin/sub_laptop_8' into main_laptop_1

common_util/common_util_surface_sampler.py

@@ -24,25 +24,16 @@ from typing import Literal, Protocol, get_args
 import numpy as np
 from scipy.interpolate import RegularGridInterpolator
 
-#: 지면 필터 · 지표면 표현 허용 목록 — 파일 이름에 들어감(B04 `_FILTERS` · `MODEL_METHODS`)
+#: 지면 필터 · 지표면 표현 허용 목록 — 파일 이름에 들어감(B04 `_FILTERS` · `BUILDERS`)
 #: `sheet_*` = 수치지형도 등고선 서피스(B04 `SHEET_METHOD_LABELS` 키 앞에 `sheet_`)
 SurfaceFilter = Literal[
     "classification",
-    "grid_min_z",
-    "csf",
-    "pmf",
     "ptd",
-    "ransac",
     "classification_refine",
     "ptd_refine",
-    "sheet_tin_sheet",
-    "sheet_tin",
-    "sheet_biharmonic",
-    "sheet_anudem",
-    "sheet_multires",
     "sheet_laplace",
 ]
-SurfaceMethod = Literal["dtm", "tin", "nurbs", "implicit", "meshfree"]
+SurfaceMethod = Literal["dtm", "implicit"]
 
 
 def check_surface_keys(filter_key: str, method: str = "dtm") -> None:
@@ -243,31 +234,12 @@ class CallableSurfaceSampler:
         return values, valid
 
 
-@dataclass
-class InterpolatedSurfaceSampler:
-    """불규칙/곡면 모델 보간기와 DTM footprint 유효성을 결합한다."""
-
-    interpolator: Callable[[np.ndarray], np.ndarray]
-    footprint: SurfaceElevationSampler | None = None
-
-    def sample_xy(self, xy: np.ndarray) -> tuple[np.ndarray, np.ndarray]:
-        xy = np.asarray(xy, dtype=np.float64)
-        values = np.asarray(self.interpolator(xy), dtype=np.float64).reshape(-1)
-        valid = np.isfinite(values)
-        if self.footprint is not None:
-            _, footprint_valid = self.footprint.sample_xy(xy)
-            valid &= footprint_valid
-        values[~valid] = np.nan
-        return values, valid
-
-
 def build_surface_sampler(
     models_dir: Path | str, source_filter: str, method: str, smooth: bool
 ) -> SurfaceElevationSampler:
     """1단계 확정 모델을 종·횡단용 일괄 XY 표고 sampler로 연다."""
     check_surface_keys(source_filter, method)
     models_dir = Path(models_dir)
-    smooth_suffix = "_smooth" if smooth and method in {"dtm", "tin"} else ""
     dtm_smooth = models_dir / f"dtm_{source_filter}_smooth.npz"
     dtm_original = models_dir / f"dtm_{source_filter}.npz"
     dtm_path = dtm_smooth if smooth and dtm_smooth.exists() else dtm_original
@@ -277,46 +249,8 @@ def build_surface_sampler(
     if method == "dtm":
         return footprint
 
-    if method == "tin":
-        from scipy.interpolate import LinearNDInterpolator
-
-        path = models_dir / f"tin_{source_filter}{smooth_suffix}.npz"
-        if not path.exists() and smooth_suffix:
-            path = models_dir / f"tin_{source_filter}.npz"
-        with np.load(path, allow_pickle=False) as data:
-            vertices = np.asarray(data["vertices"], dtype=np.float64)
-        interpolator = LinearNDInterpolator(vertices[:, :2], vertices[:, 2], fill_value=np.nan)
-        return InterpolatedSurfaceSampler(lambda xy: interpolator(xy), footprint)
-
-    if method == "nurbs":
-        from scipy.interpolate import RectBivariateSpline
-
-        path = models_dir / f"nurbs_{source_filter}.npz"
-        with np.load(path, allow_pickle=False) as data:
-            control_x = np.asarray(data["control_x"], dtype=np.float64)
-            control_y = np.asarray(data["control_y"], dtype=np.float64)
-            control_z = np.asarray(data["control_z"], dtype=np.float64)
-            degree = int(data["degree"][0]) if "degree" in data else 3
-        spline = RectBivariateSpline(
-            control_y,
-            control_x,
-            control_z,
-            kx=min(degree, len(control_y) - 1),
-            ky=min(degree, len(control_x) - 1),
-        )
-        return InterpolatedSurfaceSampler(lambda xy: spline.ev(xy[:, 1], xy[:, 0]), footprint)
-
     if method == "implicit":
         # 굳힌 격자(641-1) — 브라우저 · Node 측점 · B06 이 같은 파일을 읽음(`source` 가 붙음)
         return DtmGridSampler.open_cached(implicit_grid_npz(models_dir, source_filter))
 
-    if method == "meshfree":
-        from scipy.interpolate import LinearNDInterpolator
-
-        path = models_dir / f"meshfree_{source_filter}.npz"
-        with np.load(path, allow_pickle=False) as data:
-            points = np.asarray(data["points"], dtype=np.float64)
-        interpolator = LinearNDInterpolator(points[:, :2], points[:, 2], fill_value=np.nan)
-        return InterpolatedSurfaceSampler(lambda xy: interpolator(xy), footprint)
-
     raise ValueError(f"지원하지 않는 지표면 모델입니다: {method}")