{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cc66df51-a48d-4abe-8477-9c1527d79293",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 程序设计与计算思维\n",
    "\n",
    "Computer Programming and Computational Thinking\n",
    "\n",
    "## 第 22 讲：二维的平流与扩散\n",
    "\n",
    "2025—2026学年度春季学期\n",
    "\n",
    "清华大学 韩文弢"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d1fbeb0-8557-4bab-bf47-4c61ccbf9f81",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 问题引入\n",
    "\n",
    "上一讲研究了**一维**空间中的平流和扩散，将温度 $T$ 视为时间 $t$ 和单一空间坐标 $x$ 的函数 $T(t, x)$，并引入了偏微分方程（PDE）的概念。\n",
    "\n",
    "但现实世界是**多维**的。海洋和大气中的温度、盐度、湿度等物理量不仅随时间变化，还在**两个甚至三个空间维度**上分布。例如，要模拟洋流如何将赤道的热量输送到极地，就必须考虑经度和纬度两个方向上的温度变化。\n",
    "\n",
    "从一维扩展到二维，核心的计算思想并没有本质改变——仍然是**离散化**和**时间步进**。但需要引入两个重要的新工具：\n",
    "\n",
    "- **模板（stencil）**：一种统一描述邻域操作的框架，将微分算子的离散化表示为一个小矩阵\n",
    "- **幽灵单元（ghost cells）**：一种优雅处理边界条件的技巧，使代码无需对边界做特殊判断\n",
    "\n",
    "本讲将首先介绍这两个工具，然后回顾上一讲的一维平流-扩散模型，最后将所有内容推广到**二维**，模拟真实的海洋洋流对热量的传输。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c6351ea-6523-4ec1-8b77-d0a0f4004894",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 准备工作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "86d1092f-5b2f-44e7-8d39-891254874ca4",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from ipywidgets import interact, FloatSlider, IntSlider\n",
    "\n",
    "import time\n",
    "from numba import njit\n",
    "\n",
    "plt.rcParams['font.family'] = ['Noto Sans', 'Noto Sans CJK SC']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fce5c90-1638-45e3-b3c3-20b32cfdb065",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 模板计算\n",
    "\n",
    "在上一讲中，一维平流和扩散的数值方法都涉及对**相邻网格点**的操作：\n",
    "\n",
    "- 平流（上游差分）：`T_new[i] = T[i] + dt * U * (T[i-1] - T[i]) / dx`\n",
    "- 扩散：`T_new[i] = T[i] + dt * D * (T[i+1] - 2*T[i] + T[i-1]) / dx**2`\n",
    "\n",
    "这些操作的共同特点是：每个网格点的新值取决于它**自身和相邻点**的旧值。在二维情况下，\"相邻\"的含义扩展为上下左右四个方向，形成一个 3×3 的**邻域**。\n",
    "\n",
    "**模板** (stencil) 就是一种将这种邻域操作**系统化**的方法：定义一个小的权重矩阵（模板），将其与每个点周围的邻域逐元素相乘再求和，就得到了该点处微分算子的近似值。\n",
    "\n",
    "下面从最基础的二维数组操作开始，逐步构建模板计算的工具箱。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "74b35afa-6418-459b-a9aa-6031ebaa2472",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "原始数组 data：\n",
      "[[7 4 8 5 7 3 7]\n",
      " [8 5 4 8 8 3 6]\n",
      " [5 2 8 6 2 5 1]\n",
      " [6 9 1 3 7 4 9]\n",
      " [3 5 3 7 5 9 7]\n",
      " [2 4 9 2 9 5 2]]\n",
      "形状: (6, 7)\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(42)\n",
    "data = np.random.randint(1, 10, size=(6, 7))\n",
    "print('原始数组 data：')\n",
    "print(data)\n",
    "print(f'形状: {data.shape}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d643625f-4a08-47d7-a10f-17e3dc58d993",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### 扩展数组与幽灵单元\n",
    "\n",
    "当模板窗口滑动到数组边缘时，朴素的做法需要进行特殊处理（回忆一维情况）。\n",
    "\n",
    "可以通过**在原始数组周围添加一圈幽灵单元**来实现相同效果。幽灵单元提供了边界值，使得模板操作无需对边界做特殊处理。\n",
    "\n",
    "下面将原始数据嵌入一个更大的数组中，四周各留一行/列作为幽灵单元："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fac1197e-99ee-4661-b8ca-de7e6c798f6e",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "扩展数组 A（四周为幽灵单元，初始值为0）：\n",
      "[[0 0 0 0 0 0 0 0 0]\n",
      " [0 7 4 8 5 7 3 7 0]\n",
      " [0 8 5 4 8 8 3 6 0]\n",
      " [0 5 2 8 6 2 5 1 0]\n",
      " [0 6 9 1 3 7 4 9 0]\n",
      " [0 3 5 3 7 5 9 7 0]\n",
      " [0 2 4 9 2 9 5 2 0]\n",
      " [0 0 0 0 0 0 0 0 0]]\n",
      "形状: (8, 9)\n",
      "\n",
      "A[1,1] = 7  (对应 data[0,0] = 7)\n",
      "A[0,0] = 0  (幽灵单元)\n"
     ]
    }
   ],
   "source": [
    "rows, cols = data.shape\n",
    "A = np.zeros((rows + 2, cols + 2), dtype=data.dtype)\n",
    "\n",
    "A[1:-1, 1:-1] = data\n",
    "\n",
    "print('扩展数组 A（四周为幽灵单元，初始值为0）：')\n",
    "print(A)\n",
    "print(f'形状: {A.shape}')\n",
    "print(f'\\nA[1,1] = {A[1,1]}  (对应 data[0,0] = {data[0,0]})')\n",
    "print(f'A[0,0] = {A[0,0]}  (幽灵单元)')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a678ceb6-bbf6-48ec-8d9f-76ab3def2b80",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### 邻域：3×3 窗口\n",
    "\n",
    "模板操作需要一个**邻域**——以当前点为中心的 3×3 窗口。对于数组中的每个位置 `(i, j)`，邻域为 `A[i-1:i+2, j-1:j+2]`。\n",
    "\n",
    "下面展示几个具有代表性的点的 3×3 邻域（注意边缘处幽灵单元的值为 0）："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8d1696f6-c5d3-47f2-b67d-db8c6cbe4cf1",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 1)（左上角）的邻域 =\n",
      "[[0 0 0]\n",
      " [0 7 4]\n",
      " [0 8 5]]\n",
      "\n",
      "(1, 3)（上边界一点）的邻域 =\n",
      "[[0 0 0]\n",
      " [4 8 5]\n",
      " [5 4 8]]\n",
      "\n",
      "(2, 3)（内部一点）的邻域 =\n",
      "[[4 8 5]\n",
      " [5 4 8]\n",
      " [2 8 6]]\n",
      "\n",
      "(2, 7)（右边界一点）的邻域 =\n",
      "[[3 7 0]\n",
      " [3 6 0]\n",
      " [5 1 0]]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for i, j, name in [\n",
    "    (1, 1, '左上角'),\n",
    "    (1, 3, '上边界一点'),\n",
    "    (2, 3, '内部一点'),\n",
    "    (2, 7, '右边界一点'),\n",
    "]:\n",
    "    neighborhood = A[i-1:i+2, j-1:j+2]\n",
    "    print(f'({i}, {j})（{name}）的邻域 =')\n",
    "    print(neighborhood)\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "768b4fa8-7798-4648-8997-ce2458b95814",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### 模板\n",
    "\n",
    "定义一个 3×3 的模板矩阵。这是**离散拉普拉斯算子**的一种形式：\n",
    "\n",
    "$$\\text{stencil} = \\begin{pmatrix} 0 & -1 & 0 \\\\ -1 & 4 & -1 \\\\ 0 & -1 & 0 \\end{pmatrix}$$\n",
    "\n",
    "将模板与邻域逐元素相乘后求和，就得到了拉普拉斯算子在该点的近似值。\n",
    "\n",
    "模板操作等价于计算：\n",
    "\n",
    "$$\\nabla^2 T_{i,j} \\approx \\frac{T_{i+1,j} + T_{i-1,j} + T_{i,j+1} + T_{i,j-1} - 4T_{i,j}}{(\\Delta x)^2}$$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d8b0bc23-f6d8-4dfd-affa-5d28b8580d92",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "模板作用结果（与原始数据同大小）：\n",
      "[[ 16  -4  19  -3  12  -5  19]\n",
      " [ 15   2 -13   9  12 -10  13]\n",
      " [  4 -19  19   3 -18  10 -16]\n",
      " [  7  22 -19  -9  14 -14  24]\n",
      " [ -1   1 -10  15 -12  15   8]\n",
      " [  1   0  27 -17  24   0  -4]]\n",
      "形状: (6, 7)  (与 data 的形状 (6, 7) 相同)\n"
     ]
    }
   ],
   "source": [
    "stencil = np.array([[ 0, -1,  0],\n",
    "                    [-1,  4, -1],\n",
    "                    [ 0, -1,  0]])\n",
    "\n",
    "result = np.zeros_like(data)\n",
    "for i in range(rows):\n",
    "    for j in range(cols):\n",
    "        neighborhood = A[i:i+3, j:j+3]\n",
    "        result[i, j] = np.sum(neighborhood * stencil)\n",
    "\n",
    "print('模板作用结果（与原始数据同大小）：')\n",
    "print(result)\n",
    "print(f'形状: {result.shape}  (与 data 的形状 {data.shape} 相同)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "006e9714-a93c-4579-9670-fd7c81905828",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### 边界条件\n",
    "\n",
    "注意结果与原始数据大小相同，模板在边缘处也\"正常工作\"了——因为幽灵单元默认值为 0。这对应了**零边界条件（Dirichlet）**：假设边界外的值为 0。\n",
    "\n",
    "但还有其他常见的边界条件：\n",
    "\n",
    "| 边界条件 | 含义 | 幽灵单元设置 | 应用场景 |\n",
    "|---|---|---|---|\n",
    "| **零值（Dirichlet）** | 边界外值为 0 | 幽灵单元 = 0 | 固定温度的边界（如恒温槽壁面） |\n",
    "| **周期性（Periodic）** | 数组左右/上下环绕 | 幽灵单元 = 对侧的值 | 环形域（如全球经度方向） |\n",
    "| **零导数（Neumann）** | 边界处导数为 0 | 幽灵单元 = 相邻内部值 | 无通量边界（如海洋-陆地交界） |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "033dbf17-1500-4688-b670-b6c3915ef0d7",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "周期性边界条件下的扩展数组：\n",
      "[[2 2 4 9 2 9 5 2 2]\n",
      " [7 7 4 8 5 7 3 7 7]\n",
      " [6 8 5 4 8 8 3 6 8]\n",
      " [1 5 2 8 6 2 5 1 5]\n",
      " [9 6 9 1 3 7 4 9 6]\n",
      " [7 3 5 3 7 5 9 7 3]\n",
      " [2 2 4 9 2 9 5 2 2]\n",
      " [7 7 4 8 5 7 3 7 7]]\n",
      "\n",
      "验证周期性：\n",
      "  B_periodic[0, 1] = 2 == data[-1, 0] = 2  (底部环绕到顶部)\n",
      "  B_periodic[1, 0] = 7 == data[0, -1] = 7  (右侧环绕到左侧)\n"
     ]
    }
   ],
   "source": [
    "B_periodic = np.zeros((rows + 2, cols + 2), dtype=int)\n",
    "B_periodic[1:-1, 1:-1] = data\n",
    "\n",
    "# 周期性边界条件\n",
    "B_periodic[0, :] = B_periodic[rows, :]  # 上幽灵行 = 底部数据行\n",
    "B_periodic[-1, :] = B_periodic[1, :]    # 下幽灵行 = 顶部数据行\n",
    "B_periodic[:, 0] = B_periodic[:, cols]  # 左幽灵列 = 右侧数据列\n",
    "B_periodic[:, -1] = B_periodic[:, 1]    # 右幽灵列 = 左侧数据列\n",
    "\n",
    "print('周期性边界条件下的扩展数组：')\n",
    "print(B_periodic)\n",
    "print(f'\\n验证周期性：')\n",
    "print(f'  B_periodic[0, 1] = {B_periodic[0, 1]} == data[-1, 0] = {data[-1, 0]}  (底部环绕到顶部)')\n",
    "print(f'  B_periodic[1, 0] = {B_periodic[1, 0]} == data[0, -1] = {data[0, -1]}  (右侧环绕到左侧)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c1c0b40d-59e3-489f-888c-31853dcdcac4",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "周期性边界条件下的模板结果：\n",
      "[[  7  -8  10  -5   3 -10  10]\n",
      " [  9   2 -13   9  12 -10   5]\n",
      " [  3 -19  19   3 -18  10 -21]\n",
      " [ -2  22 -19  -9  14 -14  18]\n",
      " [ -8   1 -10  15 -12  15   5]\n",
      " [ -8  -4  19 -22  17  -3 -13]]\n"
     ]
    }
   ],
   "source": [
    "result_periodic = np.zeros_like(data)\n",
    "for i in range(rows):\n",
    "    for j in range(cols):\n",
    "        neighborhood = B_periodic[i:i+3, j:j+3]\n",
    "        result_periodic[i, j] = np.sum(neighborhood * stencil)\n",
    "\n",
    "print('周期性边界条件下的模板结果：')\n",
    "print(result_periodic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "39af6f77-9a43-4d56-bac3-97c63cb821bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "零导数边界条件下的模板结果：\n",
      "[[  2  -8  11  -8   5  -8   5]\n",
      " [  7   2 -13   9  12 -10   7]\n",
      " [ -1 -19  19   3 -18  10 -17]\n",
      " [  1  22 -19  -9  14 -14  15]\n",
      " [ -4   1 -10  15 -12  15   1]\n",
      " [ -3  -4  18 -19  15  -5  -8]]\n"
     ]
    }
   ],
   "source": [
    "B_neumann = np.zeros((rows + 2, cols + 2), dtype=int)\n",
    "B_neumann[1:-1, 1:-1] = data\n",
    "\n",
    "B_neumann[0, :] = B_neumann[1, :]\n",
    "B_neumann[-1, :] = B_neumann[-2, :]\n",
    "B_neumann[:, 0] = B_neumann[:, 1]\n",
    "B_neumann[:, -1] = B_neumann[:, -2]\n",
    "\n",
    "result_neumann = np.zeros_like(data)\n",
    "for i in range(rows):\n",
    "    for j in range(cols):\n",
    "        neighborhood = B_neumann[i:i+3, j:j+3]\n",
    "        result_neumann[i, j] = np.sum(neighborhood * stencil)\n",
    "\n",
    "print('零导数边界条件下的模板结果：')\n",
    "print(result_neumann)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5b87c644-fcf1-43c4-b8ab-c8673a57e25f",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x1000 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(12, 10))\n",
    "\n",
    "ax = axes[0, 0]\n",
    "im = ax.imshow(data, cmap='RdBu_r', vmax=10, vmin=-30)\n",
    "ax.set_title('原始数据')\n",
    "plt.colorbar(im, ax=ax)\n",
    "\n",
    "ax = axes[0, 1]\n",
    "im = ax.imshow(result, cmap='RdBu_r', vmax=10, vmin=-30)\n",
    "ax.set_title('零值边界（Dirichlet）')\n",
    "plt.colorbar(im, ax=ax)\n",
    "\n",
    "ax = axes[1, 0]\n",
    "im = ax.imshow(result_periodic, cmap='RdBu_r', vmax=10, vmin=-30)\n",
    "ax.set_title('周期性边界（Periodic）')\n",
    "plt.colorbar(im, ax=ax)\n",
    "\n",
    "ax = axes[1, 1]\n",
    "im = ax.imshow(result_neumann, cmap='RdBu_r', vmax=10, vmin=-30)\n",
    "ax.set_title('零导数边界（Neumann）')\n",
    "plt.colorbar(im, ax=ax)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed04faa9-0f52-41ab-95a8-deffeb7a6010",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 一维平流-扩散问题回顾\n",
    "\n",
    "在将平流-扩散方程推广到二维之前，先回顾上一讲的核心结果。\n",
    "\n",
    "上一讲考虑了定义在区间 $[0, L_x]$ 上的温度场 $T(t, x)$，满足以下 PDE：\n",
    "\n",
    "$$\\frac{\\partial T}{\\partial t} = -U \\frac{\\partial T}{\\partial x} + \\kappa \\frac{\\partial^2 T}{\\partial x^2}$$\n",
    "\n",
    "其中 $U$ 是均匀流速（平流），$\\kappa$ 是热扩散率（扩散）。\n",
    "\n",
    "数值方法的关键步骤：\n",
    "\n",
    "1. **空间离散化**：将区间等分为 $N_x$ 个单元，在每个单元中心存储温度值，得到向量 $\\mathbf{T}^n = (T^n_1, \\ldots, T^n_{N_x})$\n",
    "2. **空间导数的近似**：\n",
    "   - 一阶导数（平流项）：中心差分 $\\frac{\\partial T}{\\partial x} \\approx \\frac{T_{i+1} - T_{i-1}}{2\\delta x}$\n",
    "   - 二阶导数（扩散项）：$\\frac{\\partial^2 T}{\\partial x^2} \\approx \\frac{T_{i+1} - 2T_i + T_{i-1}}{\\delta x^2}$\n",
    "3. **时间步进**：前向欧拉法 $T^{n+1}_i = T^n_i + \\delta t \\cdot (\\text{平流} + \\text{扩散})$\n",
    "4. **边界条件**：周期性边界条件（$T_0 = T_{N_x}$，$T_{N_x+1} = T_1$）\n",
    "\n",
    "在二维情况下，温度场变为 $T(t, x, y)$，需要在**两个方向**上分别近似空间导数。每个方向的操作与一维完全相同——这正是**模板**方法的优势所在：只需定义好二维模板，就可以统一处理任意方向的导数。\n",
    "\n",
    "下面将看到，二维扩散项就是将 $x$ 方向和 $y$ 方向的二阶导数模板**叠加**，得到的就是前面介绍的离散拉普拉斯算子模板。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c488081b-9753-4300-9995-ad9731b9f89e",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 二维平流-扩散方程\n",
    "\n",
    "二维平流-扩散方程描述温度场 $T = T(x, y, t)$ 在速度场 $\\vec{u}(x,y) = (u, v)$ 中的演变：\n",
    "\n",
    "$$\\frac{\\partial T(x,y,t)}{\\partial t} = -u(x,y) \\frac{\\partial T}{\\partial x} - v(x,y) \\frac{\\partial T}{\\partial y} + \\kappa \\left( \\frac{\\partial^{2} T}{\\partial x^{2}} + \\frac{\\partial^{2} T}{\\partial y^{2}} \\right),$$\n",
    "\n",
    "其中 $\\kappa$ 是热扩散率。$x$ 为经度方向（西→东为正），$y$ 为纬度方向（南→北为正）。\n",
    "\n",
    "### 矢量形式\n",
    "\n",
    "利用梯度 $\\nabla$ 和拉普拉斯 $\\nabla^2$ 算子，方程可简写为：\n",
    "\n",
    "$$\\frac{\\partial T}{\\partial t} = -\\vec{u} \\cdot \\nabla T + \\kappa \\nabla^{2} T$$\n",
    "\n",
    "由于海水近似**不可压缩**（$\\nabla \\cdot \\vec{u} = 0$），利用乘积法则可以改写为**通量形式**：\n",
    "\n",
    "$$\\frac{\\partial T}{\\partial t} = -\\nabla \\cdot (\\vec{u}T) + \\kappa \\nabla^{2} T$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f449816-6841-4851-b50e-88128d2e49f7",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 二维平流-扩散的模板\n",
    "\n",
    "### 离散化一阶偏导数\n",
    "\n",
    "$x$ 方向的一阶偏导数使用中心差分：\n",
    "\n",
    "$$\\frac{\\partial T(x_i, y_j, t_n)}{\\partial x} \\approx \\frac{T_{i+1,\\,j}^{n} - T_{i-1,\\,j}^{n}}{2 \\Delta x}$$\n",
    "\n",
    "对应的 $x$-梯度模板和 $y$-梯度模板如下：\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3813ee26-1bd7-4bbb-b4f8-b91d5c3bf44c",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(10, 8))\n",
    "\n",
    "xgrad = np.array([[0, 0, 0], [-1, 0, 1], [0, 0, 0]]) / 2.0\n",
    "ygrad = np.array([[0, -1, 0], [0, 0, 0], [0, 1, 0]]) / 2.0\n",
    "xdiff = np.array([[0, 0, 0], [1, -2, 1], [0, 0, 0]])\n",
    "ydiff = np.array([[0, 1, 0], [0, -2, 0], [0, 1, 0]])\n",
    "\n",
    "for ax, kernel, title in [\n",
    "    (axes[0, 0], xgrad, 'x-梯度模板 ∂T/∂x'),\n",
    "    (axes[0, 1], ygrad, 'y-梯度模板 ∂T/∂y'),\n",
    "    (axes[1, 0], xdiff, 'x-二阶导数模板 ∂²T/∂x²'),\n",
    "    (axes[1, 1], ydiff, 'y-二阶导数模板 ∂²T/∂y²'),\n",
    "]:\n",
    "    vmax = max(abs(kernel.min()), abs(kernel.max()))\n",
    "    im = ax.imshow(kernel, cmap='RdBu_r', vmin=-vmax, vmax=vmax)\n",
    "    ax.set_title(title)\n",
    "    ax.set_xticks([])\n",
    "    ax.set_yticks([])\n",
    "    for ii in range(3):\n",
    "        for jj in range(3):\n",
    "            ax.text(jj, ii, f'{kernel[ii, jj]:.1f}', ha='center', va='center',\n",
    "                    color='black' if abs(kernel[ii, jj]) < vmax * 0.5 else 'white')\n",
    "    plt.colorbar(im, ax=ax, fraction=0.046)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ae88fbc-1fb0-48ef-8dfd-4814e06ecb9b",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### 离散化扩散项\n",
    "\n",
    "扩散项的离散化是两个方向二阶导数的叠加——将上面两个二阶导数模板相加，就得到了前面介绍的离散拉普拉斯算子：\n",
    "\n",
    "$$\\kappa \\left( \\frac{\\partial^{2} T}{\\partial x^{2}} + \\frac{\\partial^{2} T}{\\partial y^{2}} \\right) \\approx \\kappa \\left( \\frac{T_{i+1,j} - 2T_{i,j} + T_{i-1,j}}{(\\Delta x)^2} + \\frac{T_{i,j+1} - 2T_{i,j} + T_{i,j-1}}{(\\Delta y)^2} \\right)$$\n",
    "\n",
    "### 无通量边界条件\n",
    "\n",
    "在 $x$ 和 $y$ 边界上施加无通量条件（即上面介绍的 **Neumann 边界条件**）：$u\\frac{\\partial T}{\\partial x} = \\kappa \\frac{\\partial T}{\\partial x} = 0$。\n",
    "\n",
    "通过**幽灵单元**实现：$T_{1,j} = T_{2,j}$，$T_{N_x,j} = T_{N_x-1,j}$（$y$ 方向类似）。这正是前面零导数边界条件的做法。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e039a1d5-4736-4512-bd25-aaa9f55815de",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "class Grid:\n",
    "    \"\"\"网格对象\"\"\"\n",
    "    \n",
    "    def __init__(self, N, L):\n",
    "        \"\"\"\n",
    "        N: 一个维度上的网格数量\n",
    "        L: 一个维度的长度\n",
    "        \"\"\"\n",
    "        self.N = N\n",
    "        self.L = L\n",
    "        self.dx = L / N\n",
    "        self.dy = L / N\n",
    "        \n",
    "        self.x = np.arange(-self.dx/2, L + self.dx, self.dx)\n",
    "        self.y = np.arange(-L - self.dy/2, L + self.dy, self.dy)\n",
    "        self.Nx = len(self.x)\n",
    "        self.Ny = len(self.y)\n",
    "        \n",
    "        self.X, self.Y = np.meshgrid(self.x, self.y)\n",
    "\n",
    "\n",
    "class OceanModel:\n",
    "    \"\"\"海洋模式\"\"\"\n",
    "    \n",
    "    def __init__(self, grid, kappa=1e4, u=None, v=None):\n",
    "        self.G = grid\n",
    "        self.kappa = kappa\n",
    "        if u is None:\n",
    "            self.u = np.zeros((grid.Ny, grid.Nx))\n",
    "        else:\n",
    "            self.u = u\n",
    "        if v is None:\n",
    "            self.v = np.zeros((grid.Ny, grid.Nx))\n",
    "        else:\n",
    "            self.v = v\n",
    "\n",
    "\n",
    "def update_ghost_cells(T):\n",
    "    T[0, :] = T[1, :]\n",
    "    T[-1, :] = T[-2, :]\n",
    "    T[:, 0] = T[:, 1]\n",
    "    T[:, -1] = T[:, -2]\n",
    "\n",
    "\n",
    "def advect(T, u, v, dx, dy):\n",
    "    Ny, Nx = T.shape\n",
    "    tendency = np.zeros((Ny, Nx))\n",
    "    tendency[1:-1, 1:-1] = -(\n",
    "        u[1:-1, 1:-1] * (T[1:-1, 2:] - T[1:-1, :-2]) / (2 * dx) +\n",
    "        v[1:-1, 1:-1] * (T[2:, 1:-1] - T[:-2, 1:-1]) / (2 * dy)\n",
    "    )\n",
    "    return tendency\n",
    "\n",
    "\n",
    "def diffuse(T, kappa, dx, dy):\n",
    "    Ny, Nx = T.shape\n",
    "    tendency = np.zeros((Ny, Nx))\n",
    "    tendency[1:-1, 1:-1] = kappa * (\n",
    "        (T[1:-1, 2:] - 2*T[1:-1, 1:-1] + T[1:-1, :-2]) / dx**2 +\n",
    "        (T[2:, 1:-1] - 2*T[1:-1, 1:-1] + T[:-2, 1:-1]) / dy**2\n",
    "    )\n",
    "    return tendency\n",
    "\n",
    "\n",
    "def timestep(T, model):\n",
    "    update_ghost_cells(T)\n",
    "    adv = advect(T, model.u, model.v, model.G.dx, model.G.dy)\n",
    "    diff = diffuse(T, model.kappa, model.G.dx, model.G.dy)\n",
    "    T[1:-1, 1:-1] += model.dt * (adv[1:-1, 1:-1] + diff[1:-1, 1:-1])\n",
    "    return T"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa4bf294-d93b-4fa4-8aff-037cd431e640",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### 双环流海洋速度场\n",
    "\n",
    "速度场采用经典的风驱动环流解析解。该解通过边界层渐近方法求解四阶 PDE 得到：\n",
    "\n",
    "$$- \\epsilon_{M} \\hat{\\nabla}^{4} \\hat{\\Psi} + \\frac{\\partial \\hat{\\Psi}}{\\partial \\hat{x}} = \\nabla \\times \\hat{\\tau} \\mathbf{z}$$\n",
    "\n",
    "其中 $\\epsilon_M = \\nu / (\\beta L^3)$ 是无量纲参数。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "60739a94-d3ea-49a0-8138-c051cc01b2e0",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "def double_gyre(G, beta=2e-11, tau0=0.1, rho0=1e3, nu=1e5, H=1000.):\n",
    "    epsM = nu / (beta * G.L**3)\n",
    "    eps = epsM**(1/3)\n",
    "    \n",
    "    x = G.X / G.L\n",
    "    y = G.Y / G.L\n",
    "    \n",
    "    psi = np.pi * np.sin(np.pi * y) * (\n",
    "        1 - x - np.exp(-x/(2*eps)) * (\n",
    "            np.cos(np.sqrt(3)*x/(2*eps)) +\n",
    "            (1/np.sqrt(3)) * np.sin(np.sqrt(3)*x/(2*eps))\n",
    "        ) + eps * np.exp((x - 1)/eps)\n",
    "    )\n",
    "    \n",
    "    dpsi_dy, dpsi_dx = np.gradient(psi, G.dy, G.dx)\n",
    "    u = dpsi_dy\n",
    "    v = -dpsi_dx\n",
    "    \n",
    "    scale = (tau0/rho0) / (beta * G.L * H)\n",
    "    u = scale * u\n",
    "    v = scale * v\n",
    "    \n",
    "    u[0, :] = 0; v[0, :] = 0\n",
    "    u[-1, :] = 0; v[-1, :] = 0\n",
    "    u[:, 0] = 0; v[:, 0] = 0\n",
    "    u[:, -1] = 0; v[:, -1] = 0\n",
    "    \n",
    "    return u, v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c8d0d00e-3ed2-4a88-8f75-b4f54c5c6a11",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "N_grid = 30\n",
    "L_domain = 6e6\n",
    "G = Grid(N_grid, L_domain)\n",
    "u_dg, v_dg = double_gyre(G)\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "speed = np.sqrt(u_dg**2 + v_dg**2)\n",
    "im1 = ax1.pcolormesh(G.X * 1e-3, G.Y * 1e-3, speed, cmap='viridis', shading='auto')\n",
    "plt.colorbar(im1, ax=ax1, label='流速 [m/s]')\n",
    "ax1.set_xlabel('经度距离 [km]')\n",
    "ax1.set_ylabel('纬度距离 [km]')\n",
    "ax1.set_title('双环流速度场大小')\n",
    "\n",
    "skip = 3\n",
    "ax2.quiver(G.X[::skip, ::skip] * 1e-3, G.Y[::skip, ::skip] * 1e-3,\n",
    "           u_dg[::skip, ::skip], v_dg[::skip, ::skip],\n",
    "           speed[::skip, ::skip], cmap='viridis', alpha=0.8)\n",
    "ax2.set_xlabel('经度距离 [km]')\n",
    "ax2.set_ylabel('纬度距离 [km]')\n",
    "ax2.set_title('双环流速度矢量场')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fcb7c64-b104-4bb0-b512-b3147311b12d",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 初始条件\n",
    "\n",
    "### 纬度线性温度\n",
    "\n",
    "模拟从赤道到极地的线性温度分布：\n",
    "\n",
    "$$T_0(x, y) = 0.5 \\left(1 - \\frac{y}{L}\\right)$$\n",
    "\n",
    "### 热点初始条件\n",
    "\n",
    "在中纬度放置一个温度为 1°C 的热点区域。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "59d45070-106d-42c3-adc7-bd91138bb414",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def linear_temperature(G):\n",
    "    return 0.5 * (1 - G.Y / G.L)\n",
    "\n",
    "\n",
    "def init_box(G, value=1.0, nx=2, ny=2, xspan=False, yspan=False):\n",
    "    T = np.zeros((G.Ny, G.Nx))\n",
    "    cy, cx = G.Ny // 2, G.Nx // 2\n",
    "    T[cy-ny:cy+ny, cx-nx:cx+nx] = value\n",
    "    if xspan:\n",
    "        T[cy-ny:cy+ny, :] = value\n",
    "    if yspan:\n",
    "        T[:, cx-nx:cx+nx] = value\n",
    "    return T\n",
    "\n",
    "\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(16, 4))\n",
    "\n",
    "G_test = Grid(30, 6e6)\n",
    "im1 = ax1.pcolormesh(G_test.X*1e-3, G_test.Y*1e-3, linear_temperature(G_test),\n",
    "                      cmap='RdBu_r', vmin=-1, vmax=1, shading='auto')\n",
    "ax1.set_title('线性温度')\n",
    "ax1.set_ylabel('纬度 [km]')\n",
    "plt.colorbar(im1, ax=ax1, label='T [°C]')\n",
    "\n",
    "im2 = ax2.pcolormesh(G_test.X*1e-3, G_test.Y*1e-3, init_box(G_test),\n",
    "                      cmap='RdBu_r', vmin=-1, vmax=1, shading='auto')\n",
    "ax2.set_title('中心热点')\n",
    "plt.colorbar(im2, ax=ax2, label='T [°C]')\n",
    "\n",
    "im3 = ax3.pcolormesh(G_test.X*1e-3, G_test.Y*1e-3, init_box(G_test, xspan=True),\n",
    "                      cmap='RdBu_r', vmin=-1, vmax=1, shading='auto')\n",
    "ax3.set_title('纬向热点')\n",
    "plt.colorbar(im3, ax=ax3, label='T [°C]')\n",
    "\n",
    "for ax in [ax1, ax2, ax3]:\n",
    "    ax.set_xlabel('经度 [km]')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba14ab21-9b25-4eea-99ff-25917a5107ac",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 模拟洋流的热量传输\n",
    "\n",
    "使用双环流速度场运行二维平流-扩散模拟。调整参数观察不同的物理效果：\n",
    "\n",
    "- **U 倍数**：放大/缩小洋流速度\n",
    "- **扩散率 $\\kappa$**：控制热量扩散的速率\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9938d06c-64ce-4887-9f0a-e07900d48fd3",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CFL = 0.000\n",
      "模拟天数: 250 天\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x1000 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def run_simulation(G, kappa, U_mult, IC, dt=12*3600, n_steps=500):\n",
    "    u, v = double_gyre(G)\n",
    "    model = OceanModel(G, kappa=kappa, u=u * U_mult, v=v * U_mult)\n",
    "    model.dt = dt\n",
    "    \n",
    "    T = IC.copy()\n",
    "    snapshots = [T.copy()]\n",
    "    times = [0]\n",
    "    \n",
    "    cfl = np.max(np.sqrt(model.u**2 + model.v**2)) * dt / G.dx\n",
    "    \n",
    "    for step in range(n_steps):\n",
    "        T = timestep(T, model)\n",
    "        if (step + 1) % (n_steps // 10) == 0:\n",
    "            snapshots.append(T.copy())\n",
    "            times.append((step + 1) * dt / (3600 * 24))\n",
    "    \n",
    "    return T, snapshots, times, cfl\n",
    "\n",
    "\n",
    "G_sim = Grid(30, 6e6)\n",
    "IC_sim = init_box(G_sim, xspan=True)\n",
    "\n",
    "T_final, snapshots, times, cfl = run_simulation(\n",
    "    G_sim, kappa=1e4, U_mult=1.0, IC=IC_sim, n_steps=500\n",
    ")\n",
    "\n",
    "print(f'CFL = {cfl:.3f}')\n",
    "print(f'模拟天数: {times[-1]:.0f} 天')\n",
    "\n",
    "n_panels = min(len(snapshots), 6)\n",
    "indices = np.linspace(0, len(snapshots)-1, n_panels, dtype=int)\n",
    "\n",
    "fig, axes = plt.subplots(2, 3, figsize=(16, 10))\n",
    "for idx, ax in zip(indices, axes.flat):\n",
    "    im = ax.pcolormesh(G_sim.X*1e-3, G_sim.Y*1e-3, snapshots[idx],\n",
    "                        cmap='RdBu_r', vmin=-0.5, vmax=1.0, shading='auto')\n",
    "    ax.set_title(f't = {times[idx]:.0f} 天')\n",
    "    ax.set_xlabel('经度 [km]')\n",
    "    ax.set_ylabel('纬度 [km]')\n",
    "    plt.colorbar(im, ax=ax, label='T [°C]')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4315bf64-6cb2-4d70-baf6-e66ad4705159",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ea6de494e9cb4f2784c0019808b48d0d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=1.0, description='U 倍数', max=8.0, step=0.5), FloatSlider(value=10000.0…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_simulation_interactive(U_mult=1.0, kappa=1e4, n_steps=300):\n",
    "    G = Grid(30, 6e6)\n",
    "    IC = init_box(G, xspan=True)\n",
    "    T_final, snaps, day_list, cfl = run_simulation(\n",
    "        G, kappa=kappa, U_mult=U_mult, IC=IC, n_steps=n_steps\n",
    "    )\n",
    "    \n",
    "    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 5))\n",
    "    \n",
    "    im1 = ax1.pcolormesh(G.X*1e-3, G.Y*1e-3, snaps[-1],\n",
    "                          cmap='RdBu_r', vmin=-0.5, vmax=1.0, shading='auto')\n",
    "    ax1.set_xlabel('经度 [km]')\n",
    "    ax1.set_ylabel('纬度 [km]')\n",
    "    ax1.set_title(f'温度场 (t = {day_list[-1]:.0f} 天)')\n",
    "    plt.colorbar(im1, ax=ax1, label='T [°C]')\n",
    "    \n",
    "    anomaly = snaps[-1] - IC\n",
    "    im2 = ax2.pcolormesh(G.X*1e-3, G.Y*1e-3, anomaly,\n",
    "                          cmap='RdBu_r', vmin=-1.0, vmax=1.0, shading='auto')\n",
    "    ax2.set_xlabel('经度 [km]')\n",
    "    ax2.set_ylabel('纬度 [km]')\n",
    "    ax2.set_title('温度异常')\n",
    "    plt.colorbar(im2, ax=ax2, label='ΔT [°C]')\n",
    "    \n",
    "    plt.suptitle(f'U 倍数 = {U_mult:.1f}, κ = {kappa:.0f} m²/s, CFL = {cfl:.2f}')\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "interact(plot_simulation_interactive,\n",
    "         U_mult=FloatSlider(min=0.0, max=8.0, step=0.5, value=1.0,\n",
    "                            description='U 倍数'),\n",
    "         kappa=FloatSlider(min=0, max=1e5, step=1e3, value=1e4,\n",
    "                           description='κ [m²/s]'),\n",
    "         n_steps=IntSlider(min=100, max=1000, step=100, value=300,\n",
    "                          description='时间步数'));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2d23bf4a-4c84-4274-9f42-2e815b617489",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G_check = Grid(30, 6e6)\n",
    "IC_check = init_box(G_check, xspan=True)\n",
    "\n",
    "T_end, snaps_check, days_check, cfl_check = run_simulation(\n",
    "    G_check, kappa=1e4, U_mult=1.0, IC=IC_check, n_steps=500\n",
    ")\n",
    "\n",
    "heat_capacity = 51.0\n",
    "dx_dy = G_check.dx * G_check.dy\n",
    "\n",
    "heat_content = [heat_capacity * np.sum(s) * dx_dy * 1e-15 for s in snaps_check]\n",
    "mean_temps = [np.mean(s) for s in snaps_check]\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 4))\n",
    "\n",
    "ax1.plot(days_check, heat_content, lw=2)\n",
    "ax1.set_xlabel('时间 [天]')\n",
    "ax1.set_ylabel('总热量 [Peta-Joules]')\n",
    "ax1.set_title(f'总热量守恒 (变化 < {abs(heat_content[-1]-heat_content[0])/heat_content[0]*100:.3f}%)')\n",
    "\n",
    "ax2.plot(days_check, mean_temps, lw=2, color='orange')\n",
    "ax2.set_xlabel('时间 [天]')\n",
    "ax2.set_ylabel('平均温度 [°C]')\n",
    "ax2.set_title(f'平均温度 (初始={mean_temps[0]:.4f}, 最终={mean_temps[-1]:.4f})')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7859d30-2704-4e7d-99a6-dc87c2ca80d5",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 计算性能\n",
    "\n",
    "模拟的计算量与网格点数的平方成正比（二维网格）。下面测试不同网格分辨率下每个时间步的耗时。\n",
    "\n",
    "同时使用 [Numba](https://numba.pydata.org/) 的 `@njit` 装饰器对核心计算函数进行**即时编译**（JIT）加速，与纯 Python/NumPy 实现进行对比。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d9202496-ea2d-4b29-b419-d13228e3c410",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Numba JIT 编译完成\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最大加速比: 5.6x (N = 136)\n"
     ]
    }
   ],
   "source": [
    "@njit\n",
    "def update_ghost_cells_jit(T):\n",
    "    T[0, :] = T[1, :]\n",
    "    T[-1, :] = T[-2, :]\n",
    "    T[:, 0] = T[:, 1]\n",
    "    T[:, -1] = T[:, -2]\n",
    "\n",
    "\n",
    "@njit\n",
    "def advect_jit(T, u, v, dx, dy):\n",
    "    Ny, Nx = T.shape\n",
    "    tendency = np.zeros((Ny, Nx))\n",
    "    for i in range(1, Ny - 1):\n",
    "        for j in range(1, Nx - 1):\n",
    "            tendency[i, j] = -(\n",
    "                u[i, j] * (T[i, j+1] - T[i, j-1]) / (2 * dx) +\n",
    "                v[i, j] * (T[i+1, j] - T[i-1, j]) / (2 * dy)\n",
    "            )\n",
    "    return tendency\n",
    "\n",
    "\n",
    "@njit\n",
    "def diffuse_jit(T, kappa, dx, dy):\n",
    "    Ny, Nx = T.shape\n",
    "    tendency = np.zeros((Ny, Nx))\n",
    "    for i in range(1, Ny - 1):\n",
    "        for j in range(1, Nx - 1):\n",
    "            tendency[i, j] = kappa * (\n",
    "                (T[i, j+1] - 2*T[i, j] + T[i, j-1]) / dx**2 +\n",
    "                (T[i+1, j] - 2*T[i, j] + T[i-1, j]) / dy**2\n",
    "            )\n",
    "    return tendency\n",
    "\n",
    "\n",
    "# 预热 JIT 编译\n",
    "_G_warmup = Grid(8, 6e6)\n",
    "_T_warmup = init_box(_G_warmup)\n",
    "_u_warmup, _v_warmup = double_gyre(_G_warmup)\n",
    "update_ghost_cells_jit(_T_warmup.copy())\n",
    "_ = advect_jit(_T_warmup.copy(), _u_warmup, _v_warmup, _G_warmup.dx, _G_warmup.dy)\n",
    "_ = diffuse_jit(_T_warmup.copy(), 1e4, _G_warmup.dx, _G_warmup.dy)\n",
    "print('Numba JIT 编译完成')\n",
    "\n",
    "\n",
    "Nvec = range(1, 20)\n",
    "tvec = []\n",
    "tvec_jit = []\n",
    "\n",
    "for Npower in Nvec:\n",
    "    G_scale = Grid(8 * Npower, 6e6)\n",
    "    IC_scale = init_box(G_scale)\n",
    "    u_s, v_s = double_gyre(G_scale)\n",
    "    model = OceanModel(G_scale, kappa=1e4, u=u_s, v=v_s)\n",
    "    model.dt = 6 * 3600\n",
    "\n",
    "    T_test = IC_scale.copy()\n",
    "    T_test_jit = IC_scale.copy()\n",
    "\n",
    "    # 纯 NumPy\n",
    "    t0 = time.time()\n",
    "    update_ghost_cells(T_test)\n",
    "    adv = advect(T_test, model.u, model.v, model.G.dx, model.G.dy)\n",
    "    diff = diffuse(T_test, model.kappa, model.G.dx, model.G.dy)\n",
    "    elapsed = time.time() - t0\n",
    "    tvec.append(elapsed)\n",
    "\n",
    "    # Numba JIT\n",
    "    t0 = time.time()\n",
    "    update_ghost_cells_jit(T_test_jit)\n",
    "    adv_jit = advect_jit(T_test_jit, model.u, model.v, model.G.dx, model.G.dy)\n",
    "    diff_jit = diffuse_jit(T_test_jit, model.kappa, model.G.dx, model.G.dy)\n",
    "    elapsed_jit = time.time() - t0\n",
    "    tvec_jit.append(elapsed_jit)\n",
    "\n",
    "# 绘图\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "N_vals = [8 * n for n in Nvec]\n",
    "\n",
    "ax.plot(N_vals, tvec, 'o-', lw=2, label='NumPy（纯 Python）')\n",
    "ax.plot(N_vals, tvec_jit, 's-', lw=2, color='green', label='Numba JIT')\n",
    "\n",
    "ax.set_xlabel('x 方向网格点数')\n",
    "ax.set_ylabel('每步耗时 [秒]')\n",
    "ax.set_title('计算时间 vs 网格分辨率：NumPy vs Numba')\n",
    "ax.grid(True, alpha=0.3)\n",
    "ax.legend()\n",
    "\n",
    "if len(tvec) > 2:\n",
    "    coeffs = np.polyfit(np.log(N_vals[3:]), np.log(tvec[3:]), 1)\n",
    "    ax.plot(N_vals, np.exp(coeffs[1]) * np.array(N_vals)**coeffs[0],\n",
    "            '--', color='blue', alpha=0.5, label=f'NumPy 拟合: O(N^{coeffs[0]:.1f})')\n",
    "\n",
    "if len(tvec_jit) > 2:\n",
    "    coeffs_jit = np.polyfit(np.log(N_vals[3:]), np.log(tvec_jit[3:]), 1)\n",
    "    ax.plot(N_vals, np.exp(coeffs_jit[1]) * np.array(N_vals)**coeffs_jit[0],\n",
    "            '--', color='green', alpha=0.5, label=f'Numba 拟合: O(N^{coeffs_jit[0]:.1f})')\n",
    "\n",
    "ax.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# 打印最大加速比\n",
    "if len(tvec) > 0 and len(tvec_jit) > 0:\n",
    "    max_speedup = max(t / j for t, j in zip(tvec, tvec_jit) if j > 0)\n",
    "    max_idx = max(range(len(tvec)), key=lambda k: tvec[k] / tvec_jit[k] if tvec_jit[k] > 0 else 0)\n",
    "    print(f'最大加速比: {max_speedup:.1f}x (N = {N_vals[max_idx]})')"
   ]
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   "source": [
    "## 现实世界中的气候模型\n",
    "\n",
    "模板操作是气候建模的核心计算工具。本节从基础的模板概念出发，逐步构建了完整的二维海洋热量传输模拟。\n",
    "\n",
    "在前面的一维纬度能量平衡模型中，扩散项\n",
    "\n",
    "$$D \\frac{\\partial}{\\partial x}\\left[(1-x^2)\\frac{\\partial T}{\\partial x}\\right]$$\n",
    "\n",
    "正是通过模板来离散化的。在更复杂的三维气候模型中，同样的原理应用于全球网格：\n",
    "\n",
    "- **大气环流模型（GCM）**：在经度、纬度、高度三维网格上求解流体力学方程\n",
    "- **海洋环流模型**：在海量网格点上计算温度、盐度、流速的演变\n",
    "- **每个网格点的更新**都需要模板操作——将邻域信息与微分算子的离散近似相结合\n",
    "\n",
    "边界条件的选择同样关键：\n",
    "\n",
    "- 极地通常使用周期性或对称边界条件\n",
    "- 海洋-陆地交界处使用特殊的通量条件\n",
    "- 大气顶部和地表使用辐射边界条件"
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    "<video width=\"960\" controls>\n",
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   "source": [
    "## 本讲小结\n",
    "\n",
    "本讲从一维 PDE 推广到二维 PDE，引入了模板计算的核心工具。从**计算思维**的角度：\n",
    "\n",
    "**1. 抽象：模板作为统一的算子表示**\n",
    "\n",
    "上一讲中，平流和扩散的数值方法分别用不同的代码实现。本讲引入**模板**这一抽象：任何线性微分算子的离散化都可以表示为一个小矩阵（3×3），与邻域逐元素相乘再求和。同一个框架统一处理了梯度、拉普拉斯等不同算子，这是计算思维中\"抽象\"的典型体现。\n",
    "\n",
    "**2. 维度的扩展**\n",
    "\n",
    "从一维到二维，温度场从向量 $T_i$ 变为矩阵 $T_{i,j}$，空间导数的近似从一维切片变为二维切片。代码结构几乎不变——`advect()` 和 `diffuse()` 函数中的 NumPy 切片语法从一维推广到二维，核心逻辑相同。\n",
    "\n",
    "**3. 幽灵单元：边界条件的优雅处理**\n",
    "\n",
    "边界条件是数值计算中的经典难题。本讲引入的**幽灵单元**技巧，通过在数据周围添加一圈额外单元来统一处理边界：\n",
    "- 零值边界（Dirichlet）：幽灵单元 = 0\n",
    "- 周期性边界（Periodic）：幽灵单元 = 对侧值\n",
    "- 零导数边界（Neumann）：幽灵单元 = 相邻值\n",
    "\n",
    "这使得核心计算代码无需任何边界判断，体现了\"分离关注点\"的设计思想。\n",
    "\n",
    "**4. 建模：从工具到物理**\n",
    "\n",
    "将模板、幽灵单元和时间步进组合在一起，成功模拟了二维海洋洋流对热量的传输。速度场来自风驱动环流的解析解（双环流），温度场的演变同时受平流和扩散的影响——这与第 19 讲的气候模型和第 21 讲的一维模型形成了完整的知识链条。"
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