{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 径向网格系统\n",
    "\n",
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/bud-primordium/AtomSCF/blob/main/docs/source/tutorials/01-grid.ipynb)\n",
    "\n",
    "## 学习目标\n",
    "\n",
    "- 理解径向坐标在球对称问题中的核心地位\n",
    "- 掌握线性网格与对数网格的生成方法\n",
    "- 理解网格密度分布对计算精度的影响\n",
    "\n",
    "## 核心概念\n",
    "\n",
    "原子薛定谔方程在球对称势下可分离变量，径向部分控制主要物理行为。连续的径向坐标 r ∈ [0, ∞) 需离散化为有限网格点，才能用数值方法求解。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 理论基础：梯形积分与权重\n",
    "\n",
    "对于非均匀网格 $r_0, r_1, \\ldots, r_{N-1}$，梯形积分规则：\n",
    "\n",
    "$$\\int_{r_0}^{r_{N-1}} f(r)dr \\approx \\sum_{i=0}^{N-1} w_i f(r_i)$$\n",
    "\n",
    "权重计算公式：\n",
    "\n",
    "$$w_0 = \\frac{r_1-r_0}{2}, \\quad w_i = \\frac{r_{i+1}-r_{i-1}}{2}, \\quad w_{N-1} = \\frac{r_{N-1}-r_{N-2}}{2}$$\n",
    "\n",
    "**验证方法**：$\\sum_i w_i \\approx r_{N-1} - r_0$\n",
    "\n",
    "**代码实现**：`trapezoid_weights(r)` 函数返回积分权重数组\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-04T04:12:36.909661Z",
     "iopub.status.busy": "2025-12-04T04:12:36.909315Z",
     "iopub.status.idle": "2025-12-04T04:12:36.916018Z",
     "shell.execute_reply": "2025-12-04T04:12:36.915907Z"
    }
   },
   "outputs": [],
   "source": [
    "# Colab 环境检测\n",
    "import sys\n",
    "if \"google.colab\" in sys.modules:\n",
    "    !pip install -q git+https://github.com/bud-primordium/AtomSCF.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-04T04:12:36.920946Z",
     "iopub.status.busy": "2025-12-04T04:12:36.920830Z",
     "iopub.status.idle": "2025-12-04T04:12:54.681793Z",
     "shell.execute_reply": "2025-12-04T04:12:54.681675Z"
    }
   },
   "outputs": [],
   "source": [
    "# 配置中文字体（避免乱码）\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "\n",
    "# 跨平台中文字体配置\n",
    "matplotlib.rcParams['font.sans-serif'] = [\n",
    "    'Arial Unicode MS',      # macOS\n",
    "    'WenQuanYi Micro Hei',  # Linux\n",
    "    'SimHei',                # Windows\n",
    "    'DejaVu Sans'            # Fallback\n",
    "]\n",
    "matplotlib.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "# 清除字体缓存（重要！）\n",
    "try:\n",
    "    import matplotlib.font_manager as fm\n",
    "    fm._load_fontmanager(try_read_cache=False)\n",
    "except Exception:\n",
    "    pass\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-04T04:12:54.687373Z",
     "iopub.status.busy": "2025-12-04T04:12:54.687283Z",
     "iopub.status.idle": "2025-12-04T04:12:54.840091Z",
     "shell.execute_reply": "2025-12-04T04:12:54.839964Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from atomscf.grid import radial_grid_linear, radial_grid_log, trapezoid_weights\n",
    "\n",
    "# 设置绘图风格\n",
    "plt.rcParams['figure.figsize'] = (10, 6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 线性网格\n",
    "\n",
    "均匀采样：r[i] = rmin + i·Δr，适合氢原子等简单体系的快速基准测试。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-04T04:12:54.844773Z",
     "iopub.status.busy": "2025-12-04T04:12:54.844692Z",
     "iopub.status.idle": "2025-12-04T04:12:54.850055Z",
     "shell.execute_reply": "2025-12-04T04:12:54.849979Z"
    }
   },
   "outputs": [],
   "source": [
    "# 生成线性网格（返回两个值：r 和 w）\n",
    "r_lin, w_lin = radial_grid_linear(n=500, rmin=1e-5, rmax=20.0)\n",
    "\n",
    "# 计算局部步长\n",
    "dr_lin = np.diff(r_lin)\n",
    "\n",
    "print(\"线性网格信息:\")\n",
    "print(f\"  点数: {len(r_lin)}\")\n",
    "print(f\"  范围: [{r_lin[0]:.2e}, {r_lin[-1]:.2f}] Bohr\")\n",
    "print(f\"  步长: {dr_lin[250]:.6f} Bohr (中心点)\")\n",
    "\n",
    "print(\"\\n前 10 个网格点 (Bohr):\")\n",
    "for i in range(10):\n",
    "    print(f\"  r[{i}] = {r_lin[i]:.6f}\")\n",
    "\n",
    "print(\"\\n后 10 个网格点 (Bohr):\")\n",
    "for i in range(-10, 0):\n",
    "    print(f\"  r[{500+i}] = {r_lin[i]:.6f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 对数网格\n",
    "\n",
    "在对数坐标 x = ln(r) 上均匀采样，原子核附近密集。适合多电子原子的近核高梯度区域。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-04T04:12:54.854434Z",
     "iopub.status.busy": "2025-12-04T04:12:54.854357Z",
     "iopub.status.idle": "2025-12-04T04:12:54.861278Z",
     "shell.execute_reply": "2025-12-04T04:12:54.861208Z"
    }
   },
   "outputs": [],
   "source": [
    "# 生成对数网格\n",
    "r_log, w_log = radial_grid_log(n=500, rmin=1e-6, rmax=20.0)\n",
    "\n",
    "# 计算局部步长\n",
    "dr_log = np.diff(r_log)\n",
    "\n",
    "print(\"对数网格信息:\")\n",
    "print(f\"  点数: {len(r_log)}\")\n",
    "print(f\"  范围: [{r_log[0]:.2e}, {r_log[-1]:.2f}] Bohr\")\n",
    "\n",
    "# 找最接近 r=0.01 和 r=10.0 的点\n",
    "idx_001 = np.argmin(np.abs(r_log - 0.01))\n",
    "idx_10 = np.argmin(np.abs(r_log - 10.0))\n",
    "\n",
    "print(f\"  步长 (r≈0.01): {dr_log[idx_001]:.6e} Bohr\")\n",
    "print(f\"  步长 (r≈10.0): {dr_log[idx_10]:.6f} Bohr\")\n",
    "\n",
    "print(\"\\n前 10 个网格点 (Bohr):\")\n",
    "for i in range(10):\n",
    "    print(f\"  r[{i}] = {r_log[i]:.6e}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 网格密度可视化\n",
    "\n",
    "对比线性与对数网格的点分布和局部步长 dr(r)："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-04T04:12:54.866115Z",
     "iopub.status.busy": "2025-12-04T04:12:54.866020Z",
     "iopub.status.idle": "2025-12-04T04:12:55.467354Z",
     "shell.execute_reply": "2025-12-04T04:12:55.467265Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "# 左图：r 分布\n",
    "ax1.plot(np.arange(len(r_lin)), r_lin, 'b-', label='线性网格', linewidth=2)\n",
    "ax1.plot(np.arange(len(r_log)), r_log, 'r--', label='对数网格', linewidth=2)\n",
    "ax1.set_xlabel('网格点索引', fontsize=12)\n",
    "ax1.set_ylabel('径向坐标 r (Bohr)', fontsize=12)\n",
    "ax1.set_title('网格点分布比较', fontsize=14)\n",
    "ax1.legend(fontsize=11)\n",
    "ax1.grid(alpha=0.3)\n",
    "\n",
    "# 右图：dr 分布（对数刻度）\n",
    "ax2.semilogy(r_lin[:-1], dr_lin, 'b-', label='线性网格', linewidth=2)\n",
    "ax2.semilogy(r_log[:-1], dr_log, 'r--', label='对数网格', linewidth=2)\n",
    "ax2.set_xlabel('径向坐标 r (Bohr)', fontsize=12)\n",
    "ax2.set_ylabel('局部步长 dr (Bohr)', fontsize=12)\n",
    "ax2.set_title('网格密度分布', fontsize=14)\n",
    "ax2.legend(fontsize=11)\n",
    "ax2.grid(alpha=0.3, which='both')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"关键观察:\")\n",
    "print(\"  • 线性网格: dr 恒定，远区浪费点\")\n",
    "print(\"  • 对数网格: dr ∝ r，近核密集，远区稀疏\")\n",
    "print(\"  • 核附近波函数变化剧烈，需要高分辨率\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 积分权重\n",
    "\n",
    "梯形积分权重 w[i] 用于计算波函数归一化和期望值积分：\n",
    "\n",
    "$$\\int_0^\\infty f(r) dr \\approx \\sum_i f(r_i) w_i$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-04T04:12:55.499496Z",
     "iopub.status.busy": "2025-12-04T04:12:55.499370Z",
     "iopub.status.idle": "2025-12-04T04:12:55.505293Z",
     "shell.execute_reply": "2025-12-04T04:12:55.505212Z"
    }
   },
   "outputs": [],
   "source": [
    "# 验证积分权重：计算 ∫₀²⁰ r² dr = 20³/3\n",
    "integrand_lin = r_lin**2\n",
    "integrand_log = r_log**2\n",
    "\n",
    "integral_lin = np.sum(integrand_lin * w_lin)\n",
    "integral_log = np.sum(integrand_log * w_log)\n",
    "exact = 20.0**3 / 3\n",
    "\n",
    "print(\"积分测试: ∫₀²⁰ r² dr\")\n",
    "print(f\"  线性网格: {integral_lin:.6f}\")\n",
    "print(f\"  对数网格: {integral_log:.6f}\")\n",
    "print(f\"  精确值:   {exact:.6f}\")\n",
    "print(f\"  线性误差: {abs(integral_lin - exact)/exact * 100:.4f}%\")\n",
    "print(f\"  对数误差: {abs(integral_log - exact)/exact * 100:.4f}%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 网格选择建议\n",
    "\n",
    "| 网格类型 | 适用场景 | 典型点数 |\n",
    "|---------|---------|----------|\n",
    "| 线性 | 氢原子、基准测试 | 500-1000 |\n",
    "| 对数 | 多电子原子、高精度 | 1000-2000 |\n",
    "\n",
    "**关键参数**：\n",
    "- `rmin`：避免奇点，通常 10⁻⁵ ~ 10⁻⁶ Bohr\n",
    "- `rmax`：覆盖波函数衰减区，通常 20-50 Bohr\n",
    "- `n`：精度与效率平衡，500 点足够教学\n",
    "\n",
    "## 下一步\n",
    "\n",
    "在 **[02-solver.ipynb](02-solver.ipynb)** 中，将使用这些网格求解径向薛定谔方程。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}