#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
dd_voxel 离线验证 / 渲染基准：把两条交叉剖面(剖面原数据1+2)三维空间插值(IDW + maxDist 裁剪)
成体素,切片可视化。用于:
  1) 提前验证 IDW + 包络裁剪算法(与 Phase 1 core/algo/IdwInterpolator 同逻辑);
  2) 把"可信体"问题看实——两条 1D 测线只在其所在竖直面附近有约束,体内大部分靠插值/留空;
  3) 产出 VTK 体绘制/切片的地面真值对照图。

每个测点三维坐标 = (projX, projY, z=ylist[高程]),值 = vlist。
运行: python tools/validate_voxel.py   输出: docs/_validate/voxel_*.png
依赖: numpy, scipy, matplotlib
"""
import json
import os
import sys

import numpy as np
from scipy.spatial import cKDTree
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt

DATA = os.path.join(os.path.dirname(__file__), "..", "docs", "剖面网格数据的色阶数据2等文件")
OUT = os.path.join(os.path.dirname(__file__), "..", "docs", "_validate")

POWER = 2.0          # IDW 幂
K = 8                # 取最近 K 个点
MAX_DIST = 4.0       # 超过此距离(米)→ 留空(NaN),约束插值域(设计 §10)
DXY = 1.0            # 水平网格步长(米)
DZ = 0.5             # 垂向步长(米)


def load_points(name):
    d = json.load(open(os.path.join(DATA, name), encoding="utf-8"))["data"]
    px = np.asarray(d["projectXList"], float)
    py = np.asarray(d["projectYList"], float)
    z = np.asarray(d["ylist"], float)          # 高程
    v = np.asarray(d["vlist"], float)
    return np.column_stack([px, py, z]), v


def idw_voxel(pts, vals, spec):
    ox, oy, oz, nx, ny, nz, dx, dy, dz = spec
    tree = cKDTree(pts)
    # 网格中心点
    gx = ox + (np.arange(nx) + 0.5) * dx
    gy = oy + (np.arange(ny) + 0.5) * dy
    gz = oz + (np.arange(nz) + 0.5) * dz
    GX, GY, GZ = np.meshgrid(gx, gy, gz, indexing="ij")
    Q = np.column_stack([GX.ravel(), GY.ravel(), GZ.ravel()])
    dist, idx = tree.query(Q, k=K)
    dist = np.maximum(dist, 1e-9)
    w = 1.0 / dist ** POWER
    vol = (w * vals[idx]).sum(1) / w.sum(1)
    vol[dist[:, 0] > MAX_DIST] = np.nan          # 最近点都超距 → 留空
    return vol.reshape(nx, ny, nz), (gx, gy, gz)


def main():
    os.makedirs(OUT, exist_ok=True)
    p1, v1 = load_points("剖面原数据1.txt")
    p2, v2 = load_points("剖面原数据2.txt")
    pts = np.vstack([p1, p2])
    vals = np.concatenate([v1, v2])

    # 局部化（减最小，规避大坐标；同 LocalFrame 思路）
    origin = pts.min(0)
    ptsL = pts - origin
    ext = ptsL.max(0)
    nx = int(ext[0] / DXY) + 1
    ny = int(ext[1] / DXY) + 1
    nz = int(ext[2] / DZ) + 1
    spec = (0, 0, 0, nx, ny, nz, DXY, DXY, DZ)
    print(f"points={len(vals)} grid={nx}x{ny}x{nz}={nx*ny*nz} cells "
          f"horiz_extent={ext[0]:.1f}x{ext[1]:.1f}m depth={ext[2]:.1f}m")

    vol, (gx, gy, gz) = idw_voxel(ptsL, vals, spec)
    filled = np.isfinite(vol).sum()
    print(f"filled cells={filled} ({100*filled/vol.size:.1f}%) "
          f"-> 其余为留空(两测线包络外无约束) | v[{np.nanmin(vol):.0f},{np.nanmax(vol):.0f}]")

    vmin, vmax = np.nanpercentile(vol, [2, 98])

    # 1) 中深度水平切片：应显示两条交叉的带(十字支撑)
    kz = nz // 2
    plt.figure(figsize=(6, 5))
    plt.imshow(vol[:, :, kz].T, origin="lower", extent=[0, ext[0], 0, ext[1]],
               cmap="turbo", vmin=vmin, vmax=vmax)
    plt.scatter(ptsL[:, 0], ptsL[:, 1], s=1, c="k", alpha=0.15)
    plt.title(f"voxel 水平切片 z={gz[kz]:.1f} (应见交叉十字支撑)")
    plt.xlabel("E(m)"); plt.ylabel("N(m)"); plt.colorbar(shrink=.8)
    plt.tight_layout(); plt.savefig(f"{OUT}/voxel_hslice.png", dpi=90); plt.close()

    # 2) 沿 E 的垂直切片（取 profile1 附近 N）：应重现剖面竖直结构
    jy = ny // 2
    plt.figure(figsize=(8, 3))
    plt.imshow(vol[:, jy, :].T, origin="lower", extent=[0, ext[0], 0, ext[2]],
               cmap="turbo", vmin=vmin, vmax=vmax, aspect="auto")
    plt.title(f"voxel 垂直切片 N={gy[jy]:.1f}")
    plt.xlabel("E(m)"); plt.ylabel("elev(m)"); plt.colorbar(shrink=.8)
    plt.tight_layout(); plt.savefig(f"{OUT}/voxel_vslice.png", dpi=90); plt.close()

    # 3) 非留空区的三维散点（直观看"十字片"支撑）
    xi, yi, zi = np.where(np.isfinite(vol))
    sub = slice(None, None, max(1, len(xi) // 6000))
    fig = plt.figure(figsize=(7, 5)); ax = fig.add_subplot(111, projection="3d")
    sc = ax.scatter(gx[xi[sub]], gy[yi[sub]], gz[zi[sub]],
                    c=vol[xi[sub], yi[sub], zi[sub]], cmap="turbo",
                    vmin=vmin, vmax=vmax, s=3)
    ax.set_title("voxel 非留空区(两测线竖直面附近=十字片)")
    ax.set_xlabel("E"); ax.set_ylabel("N"); ax.set_zlabel("elev")
    fig.colorbar(sc, shrink=.6)
    plt.tight_layout(); plt.savefig(f"{OUT}/voxel_support.png", dpi=90); plt.close()

    print("written:", sorted(f for f in os.listdir(OUT) if f.startswith("voxel")))


if __name__ == "__main__":
    sys.stdout.reconfigure(encoding="utf-8")
    main()