5 changed files with 517 additions and 7 deletions
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// sdf_visualizer.cpp
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// ──────────────────────────────────────────────────────────────────────────────
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// 依赖：
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// prim_gen.hpp → baked_blobtree_t、aabb_t、primitive_t …
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// base/subface.hpp → internal::get_eval_sdf_ptr、surface_type
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//
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// 文件格式（output_path）：
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// 行 0 : grid_res y_slice
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// 行 1 : x0 x1 z0 z1 （世界坐标范围）
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// 行 2 : num_subfaces
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// 然后对每个 subface 重复：
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// 行 : surface_type_int
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// N 行 : N 个空格分隔的 float（iz 行，ix 列，N = grid_res+1）
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// ──────────────────────────────────────────────────────────────────────────────
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#include "sdf_visualizer.hpp" |
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#include <base/subface.hpp> // internal::get_eval_sdf_ptr, surface_type |
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#include <Eigen/Dense> |
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#include <fstream> |
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#include <functional> |
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#include <iostream> |
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#include <limits> |
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#include <vector> |
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void dump_sdf_slice(const baked_blobtree_t& tree, |
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const std::string& output_path, |
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double y_slice, |
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int grid_res, |
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double extra_margin) |
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{ |
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// ── 0. 基本校验 ────────────────────────────────────────────────────────
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if (tree.subfaces.empty()) { |
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std::cerr << "[SDF_VIZ] No subfaces — nothing to dump.\n"; |
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return; |
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} |
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// ── 1. 计算场景 AABB（含边距）──────────────────────────────────────────
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aabb_t scene_aabb{}; |
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for (const auto& prim : tree.primitives) { scene_aabb.extend(prim->fetch_aabb()); } |
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if (scene_aabb.isEmpty()) { |
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std::cerr << "[SDF_VIZ] Scene AABB is invalid.\n"; |
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return; |
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} |
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const double base_margin = scene_aabb.sizes().maxCoeff() * extra_margin + 0.05; |
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scene_aabb.min().array() -= base_margin; |
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scene_aabb.max().array() += base_margin; |
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const double x0 = scene_aabb.min().x(), x1 = scene_aabb.max().x(); |
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const double z0 = scene_aabb.min().z(), z1 = scene_aabb.max().z(); |
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const int N = grid_res + 1; // 每轴采样点数
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const uint32_t ns = static_cast<uint32_t>(tree.subfaces.size()); |
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std::cout << "[SDF_VIZ] Grid " << N << "×" << N << " | " << ns << " subface(s)" |
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<< " | Y=" << y_slice << " | X[" << x0 << ", " << x1 << "]" |
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<< " | Z[" << z0 << ", " << z1 << "]\n"; |
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// ── 2. 对每个 subface 在网格上采样 SDF ────────────────────────────────
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// grids[s][iz * N + ix] = SDF 值（float 节省内存）
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std::vector<std::vector<float>> grids(ns, std::vector<float>(N * N, 0.0f)); |
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for (uint32_t s = 0; s < ns; ++s) { |
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// 不再调用 .raw() 获取原始指针，而是直接使用包装器对象
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const auto& subface_wrapper = tree.subfaces[s]; // 使用引用，避免拷贝
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surface_type subface_type = tree.subface_types[s]; |
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auto sdf_fn = internal::get_eval_sdf_ptr(subface_type); |
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if (!sdf_fn) { |
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std::cout << "[SDF_VIZ] subface[" << s << "] type=" << static_cast<int>(subface_type) |
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<< " → null eval_sdf, skipped.\n"; |
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continue; |
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} |
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for (int iz = 0; iz < N; ++iz) { |
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const double z = z0 + (z1 - z0) * static_cast<double>(iz) / grid_res; |
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for (int ix = 0; ix < N; ++ix) { |
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const double x = x0 + (x1 - x0) * static_cast<double>(ix) / grid_res; |
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const Eigen::Vector3d pos(x, y_slice, z); |
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// 传递包装器对象，而不是原始指针
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grids[s][iz * N + ix] = static_cast<float>(sdf_fn(subface_wrapper, pos)); |
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} |
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} |
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std::cout << "[SDF_VIZ] subface[" << s << "] type=" << static_cast<int>(subface_type) << " ✓\n"; |
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} |
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// ── 3. 写文件 ──────────────────────────────────────────────────────────
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std::ofstream ofs(output_path); |
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if (!ofs) { |
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std::cerr << "[SDF_VIZ] Cannot open: " << output_path << "\n"; |
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return; |
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} |
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// 文件头
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ofs << grid_res << ' ' << y_slice << '\n'; |
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ofs << x0 << ' ' << x1 << ' ' << z0 << ' ' << z1 << '\n'; |
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ofs << ns << '\n'; |
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// 每个 subface 的数据块
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for (uint32_t s = 0; s < ns; ++s) { |
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ofs << static_cast<int>(tree.subface_types[s]) << '\n'; |
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for (int iz = 0; iz < N; ++iz) { |
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for (int ix = 0; ix < N; ++ix) { |
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if (ix) ofs << ' '; |
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ofs << grids[s][iz * N + ix]; |
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} |
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ofs << '\n'; |
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} |
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} |
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std::cout << "[SDF_VIZ] Written → " << output_path << '\n'; |
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} |
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#pragma once |
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// sdf_visualizer.hpp
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// ──────────────────────────────────────────────────────────────────────────────
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// 将 baked_blobtree 在指定二维截面上的 SDF 分布写入文本文件，
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// 供 visualize_sdf.py 读取并渲染热力图。
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//
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// 使用方法（在 main.cpp 中）：
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// #include "sdf_visualizer.hpp"
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// // bake 完成后、solve 之前：
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// dump_sdf_slice(baked_blobtree, "sdf_slice.txt");
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// // 然后命令行运行：python visualize_sdf.py sdf_slice.txt
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// ──────────────────────────────────────────────────────────────────────────────
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#include <string> |
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#include "../../network_process/include/prim_gen.hpp" // baked_blobtree_t, aabb_t … |
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// 在世界坐标 XZ 平面（y = y_slice）按 grid_res×grid_res 网格
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// 对每个 subface 采样 SDF，结果写入 output_path。
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void dump_sdf_slice(const baked_blobtree_t& tree, |
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const std::string& output_path = "sdf_slice.txt", |
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double y_slice = 0.0, |
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int grid_res = 256, |
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double extra_margin = 0.2); |
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#!/usr/bin/env python3 |
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""" |
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visualize_sdf.py |
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──────────────────────────────────────────────────────────────────────── |
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读取 dump_sdf_slice() 生成的文本文件，绘制： |
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· 各 subface 的 SDF 热力图（蓝=负/内部，红=正/外部，白=零面） |
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· 零等值线（石灰绿，代表算法"认定"的模型表面） |
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· 合成 SDF（max 合并，即 CSG 求交结果） |
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用法： |
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pip install numpy matplotlib scipy |
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python visualize_sdf.py sdf_slice.txt [y_slice_for_xy_view] |
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──────────────────────────────────────────────────────────────────────── |
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""" |
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import sys |
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import numpy as np |
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import matplotlib.pyplot as plt |
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import matplotlib.colors as mcolors |
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import matplotlib.ticker as mticker |
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from pathlib import Path |
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from scipy.ndimage import gaussian_filter |
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from matplotlib.gridspec import GridSpec |
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# ── surface_type 枚举（与 C++ 侧对齐）──────────────────────────────── |
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SURFACE_NAMES = { |
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0: "Plane (cap)", |
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1: "Sphere", |
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2: "Cylinder", |
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3: "Cone", |
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4: "ExtrudePolyline\nSide Face", |
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5: "ExtrudeHelixline\nSide Face", |
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} |
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# 设置全局样式 |
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plt.rcParams.update({ |
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'font.size': 9, |
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'axes.titlesize': 10, |
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'axes.labelsize': 9, |
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'xtick.labelsize': 8, |
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'ytick.labelsize': 8, |
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'legend.fontsize': 8, |
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'figure.titlesize': 12, |
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'figure.autolayout': False, |
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'savefig.bbox': 'tight', |
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'savefig.pad_inches': 0.1, |
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}) |
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# ───────────────────────────────────────────────────────────────────── |
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# 1. 读取数据 |
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# ───────────────────────────────────────────────────────────────────── |
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def load_sdf_data(path: str) -> dict: |
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"""解析 dump_sdf_slice 输出文件，返回结构化字典。""" |
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lines = Path(path).read_text().splitlines() |
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idx = 0 |
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# 行 0: grid_res y_slice |
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tok = lines[idx].split(); idx += 1 |
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grid_res = int(tok[0]) |
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y_slice = float(tok[1]) |
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# 行 1: x0 x1 z0 z1 |
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tok = lines[idx].split(); idx += 1 |
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x0, x1, z0, z1 = float(tok[0]), float(tok[1]), float(tok[2]), float(tok[3]) |
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# 行 2: num_subfaces |
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ns = int(lines[idx]); idx += 1 |
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N = grid_res + 1 |
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subfaces = [] |
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for _ in range(ns): |
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stype = int(lines[idx]); idx += 1 |
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rows = [] |
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for _ in range(N): |
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rows.append(list(map(float, lines[idx].split()))) |
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idx += 1 |
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subfaces.append({"type": stype, "grid": np.array(rows, dtype=np.float64)}) |
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return dict(grid_res=grid_res, y_slice=y_slice, |
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x0=x0, x1=x1, z0=z0, z1=z1, subfaces=subfaces) |
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# ───────────────────────────────────────────────────────────────────── |
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# 2. 绘制单个面板 |
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# ───────────────────────────────────────────────────────────────────── |
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def draw_panel(ax, XX, ZZ, grid: np.ndarray, title: str, y_slice: float, |
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cmap=None, show_neg_region=True, highlight_sign_flip=False): |
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""" |
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在 ax 上绘制： |
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· 连续色带热力图（双斜率归一化，保证零值白色） |
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· 石灰绿零等值线（模型表面位置） |
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· 负值区边界（蓝色虚线，"算法认为的内部"边界） |
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""" |
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if cmap is None: |
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cmap = plt.cm.RdBu_r # 改为 RdBu_r，红色为正，蓝色为负，更直观 |
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finite = grid[np.isfinite(grid)] |
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if finite.size == 0: |
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ax.set_title(title + "\n[no finite data]") |
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return |
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# 以 98 分位数作为色域上限，避免极值压缩色彩 |
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vmax = float(np.percentile(np.abs(finite), 98)) |
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vmax = max(vmax, 1e-6) |
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norm = mcolors.TwoSlopeNorm(vmin=-vmax, vcenter=0.0, vmax=vmax) |
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# 应用轻微高斯平滑，使热力图更清晰 |
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if grid.shape[0] > 10 and grid.shape[1] > 10: |
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grid_smoothed = gaussian_filter(grid, sigma=0.7, mode='nearest') |
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else: |
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grid_smoothed = grid |
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# ── 填充等高线热力图 ── |
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cf = ax.contourf(XX, ZZ, grid_smoothed, levels=50, cmap=cmap, norm=norm, |
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alpha=0.85, extend='both') |
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# 添加颜色条，但位置更紧凑 |
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cbar = plt.colorbar(cf, ax=ax, pad=0.01, fraction=0.045, shrink=0.9) |
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cbar.set_label("SDF", fontsize=7, labelpad=2) |
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cbar.ax.tick_params(labelsize=6, pad=1) |
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# ── 零等值线（模型表面） ── |
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try: |
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cs0 = ax.contour(XX, ZZ, grid_smoothed, levels=[0.0], |
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colors=["lime"], linewidths=1.8, zorder=5, alpha=0.9) |
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if len(cs0.collections) > 0: |
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# 只在有零等值线的地方添加标签 |
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ax.clabel(cs0, fmt=" SDF=0 ", fontsize=7, inline=True, |
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colors="lime", zorder=6, inline_spacing=5) |
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except Exception: |
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pass |
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# 高亮显示符号突变区域（如果启用） |
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if highlight_sign_flip and finite.size > 4: |
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from scipy.ndimage import generic_filter |
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def local_range(vals): |
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return vals.max() - vals.min() if vals.size > 0 else 0 |
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# 检测局部范围内的剧烈符号变化 |
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local_range_grid = generic_filter(grid, local_range, size=3) |
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mean_range = float(np.percentile(local_range_grid, 85)) |
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sign_flip_mask = (local_range_grid > mean_range * 2.5) & np.isfinite(grid) |
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if sign_flip_mask.any(): |
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# 用半透明黄色填充显示符号突变区域 |
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ax.contourf(XX, ZZ, sign_flip_mask.astype(float), |
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levels=[0.5, 1.5], colors=["yellow"], |
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alpha=0.25, zorder=4) |
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ax.contour(XX, ZZ, sign_flip_mask.astype(float), levels=[0.5], |
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colors=["yellow"], linewidths=1.0, linestyles="dotted", |
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zorder=5, alpha=0.7) |
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# 添加图例说明 |
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sign_flip_pct = sign_flip_mask.sum() / sign_flip_mask.size * 100 |
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if sign_flip_pct > 0.5: # 仅在显著区域添加标注 |
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ax.text(0.02, 0.98, f"⚠ {sign_flip_pct:.1f}% sign-flip", |
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transform=ax.transAxes, fontsize=6, color="black", |
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bbox=dict(boxstyle="round,pad=0.2", fc="yellow", |
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alpha=0.7, ec="black", lw=0.5), |
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zorder=10, verticalalignment='top') |
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# ── 统计信息标注 ── |
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neg_pct = np.sum(grid < 0) / grid.size * 100 |
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pos_pct = 100 - neg_pct |
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min_val, max_val = np.min(grid), np.max(grid) |
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# 更简洁的统计信息 |
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info = f"Neg: {neg_pct:.1f}%\nPos: {pos_pct:.1f}%\nMin: {min_val:.2e}\nMax: {max_val:.2e}" |
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ax.text(0.02, 0.02, info, transform=ax.transAxes, |
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fontsize=6, color="white", zorder=7, |
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bbox=dict(boxstyle="round,pad=0.2", fc="black", alpha=0.6, |
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ec="gray", lw=0.5), |
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verticalalignment='bottom') |
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# ── 坐标轴 ── |
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ax.set_xlabel("X", fontsize=8, labelpad=2) |
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ax.set_ylabel("Z", fontsize=8, labelpad=2) |
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ax.set_title(title, fontsize=9, pad=6, fontweight='medium') |
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ax.set_aspect("equal", adjustable="box") |
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ax.tick_params(labelsize=7, pad=2) |
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ax.xaxis.set_minor_locator(mticker.AutoMinorLocator(2)) |
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ax.yaxis.set_minor_locator(mticker.AutoMinorLocator(2)) |
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# 更精细的网格 |
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ax.grid(True, which="major", color="gray", alpha=0.2, lw=0.3, linestyle='-') |
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ax.grid(True, which="minor", color="gray", alpha=0.1, lw=0.1, linestyle=':') |
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# ───────────────────────────────────────────────────────────────────── |
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# 3. 主绘图入口 - 重新设计布局 |
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# ───────────────────────────────────────────────────────────────────── |
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def plot_sdf_heatmap(data: dict, out_path: str): |
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subfaces = data["subfaces"] |
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ns = len(subfaces) |
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y_slice = data["y_slice"] |
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x0, x1, z0, z1 = data["x0"], data["x1"], data["z0"], data["z1"] |
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N = data["grid_res"] + 1 |
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X = np.linspace(x0, x1, N) |
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Z = np.linspace(z0, z1, N) |
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XX, ZZ = np.meshgrid(X, Z) |
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# 计算合成SDF |
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if ns > 0: |
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combined = subfaces[0]["grid"].copy() |
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for sf in subfaces[1:]: |
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combined = np.maximum(combined, sf["grid"]) |
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# 智能布局计算 |
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if ns <= 1: |
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# 只有1个子面：一行两列 |
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fig = plt.figure(figsize=(12, 5.5)) |
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gs = GridSpec(1, 3, width_ratios=[1, 0.05, 1.2], wspace=0.15, hspace=0.1) |
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axes = [fig.add_subplot(gs[0, 0]), fig.add_subplot(gs[0, 2])] |
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elif ns == 2: |
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# 2个子面：一行三列 |
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fig = plt.figure(figsize=(15, 5)) |
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gs = GridSpec(1, 4, width_ratios=[1, 1, 0.05, 1.2], wspace=0.15, hspace=0.1) |
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axes = [fig.add_subplot(gs[0, 0]), fig.add_subplot(gs[0, 1]), fig.add_subplot(gs[0, 3])] |
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elif ns == 3: |
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# 3个子面：两行两列 |
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fig = plt.figure(figsize=(12, 9)) |
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gs = GridSpec(2, 3, width_ratios=[1, 1, 0.05], height_ratios=[1, 1], wspace=0.15, hspace=0.2) |
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axes = [ |
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fig.add_subplot(gs[0, 0]), fig.add_subplot(gs[0, 1]), |
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fig.add_subplot(gs[1, 0]), fig.add_subplot(gs[1, 1]), |
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fig.add_subplot(gs[0:2, 2]) # 合成图占两行 |
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] |
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else: |
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# 更多子面：计算最优布局 |
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ncols = min(3, int(np.ceil(np.sqrt(ns + 1)))) |
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nrows = int(np.ceil((ns + 1) / ncols)) |
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fig_width = min(6 * ncols, 18) |
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fig_height = 5 * nrows |
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fig, axes = plt.subplots(nrows, ncols, |
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figsize=(fig_width, fig_height), |
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squeeze=False) |
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axes = axes.flatten() |
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cmap = plt.cm.RdBu_r |
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# 绘制每个子面 |
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for s, sf in enumerate(subfaces): |
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if s < len(axes) - 1: # 最后一个位置留给合成图 |
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stype = sf["type"] |
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name = SURFACE_NAMES.get(stype, f"Type {stype}") |
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title = f"Subface {s}: {name}" |
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# 对于第4种类型（ExtrudePolyline Side Face），启用符号突变检测 |
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highlight = (stype == 4) |
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draw_panel(axes[s], XX, ZZ, sf["grid"], title, y_slice, |
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cmap, highlight_sign_flip=highlight) |
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# 绘制合成面板 |
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if ns > 0 and ns < len(axes): |
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title_comb = "Combined SDF\nmax(subfaces) ≈ CSG Intersection" |
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draw_panel(axes[ns], XX, ZZ, combined, title_comb, y_slice, cmap, |
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highlight_sign_flip=True) |
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# 标记隐藏多余子图 |
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for i in range(ns + 1, len(axes)): |
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axes[i].set_visible(False) |
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elif ns == 0: |
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axes[0].text(0.5, 0.5, "No subface data", |
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ha='center', va='center', transform=axes[0].transAxes) |
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axes[0].set_title("Empty Data") |
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for i in range(1, len(axes)): |
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axes[i].set_visible(False) |
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|
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# 添加全局标题 |
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fig.suptitle( |
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f"SDF Cross-Section Analysis - Y = {y_slice:.6f}\n" |
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"Blue = Inside Model (SDF < 0) | Red = Outside Model (SDF > 0) | " |
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"Lime Green = Model Surface (SDF = 0)", |
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fontsize=11, y=0.98, fontweight='bold' |
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) |
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|
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# 添加图例说明 |
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fig.text(0.02, 0.02, |
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f"Data: {Path(out_path).stem}.txt | Grid: {data['grid_res']}×{data['grid_res']} | " |
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f"Subfaces: {ns} | X: [{x0:.3f}, {x1:.3f}] | Z: [{z0:.3f}, {z1:.3f}]", |
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fontsize=7, style='italic', alpha=0.7) |
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|
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# 保存图形 |
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fig.savefig(out_path, dpi=200, bbox_inches="tight", facecolor='white') |
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print(f"[SDF_VIZ] Heatmap saved → {out_path}") |
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|
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# 显示图形 |
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plt.tight_layout(rect=[0, 0.03, 1, 0.95]) # 为标题留出空间 |
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plt.show() |
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|
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|
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# ───────────────────────────────────────────────────────────────────── |
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# 4. CLI 入口 |
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# ───────────────────────────────────────────────────────────────────── |
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if __name__ == "__main__": |
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if len(sys.argv) < 2: |
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print("Usage: python visualize_sdf.py <sdf_data_file.txt>") |
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print("Example: python visualize_sdf.py sdf_slice.txt") |
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sys.exit(1) |
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|
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data_path = sys.argv[1] |
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|
|||
if not Path(data_path).exists(): |
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print(f"[ERROR] File not found: {data_path}") |
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sys.exit(1) |
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|
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print(f"[SDF_VIZ] Loading {data_path} ...") |
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try: |
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data = load_sdf_data(data_path) |
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print(f"[SDF_VIZ] Grid: {data['grid_res']}×{data['grid_res']} | " |
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f"Y-slice: {data['y_slice']:.6f} | " |
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f"Subfaces: {len(data['subfaces'])}") |
|||
|
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# 生成输出路径 |
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stem = Path(data_path).stem |
|||
out_dir = Path(data_path).parent |
|||
out_path = str(out_dir / f"{stem}_heatmap.png") |
|||
|
|||
# 绘制热力图 |
|||
plot_sdf_heatmap(data, out_path) |
|||
|
|||
# 打印文件信息 |
|||
if Path(out_path).exists(): |
|||
file_size = Path(out_path).stat().st_size |
|||
print(f"[SDF_VIZ] Output: {out_path} ({file_size/1024:.1f} KB)") |
|||
|
|||
except Exception as e: |
|||
print(f"[ERROR] Failed to process {data_path}: {e}") |
|||
import traceback |
|||
traceback.print_exc() |
|||
sys.exit(1) |
|||
Loading…
Reference in new issue