{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ac9729b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import ticker\n",
    "import numpy as np\n",
    "import numpy.linalg as npl\n",
    "from scipy.sparse.linalg import cg\n",
    "\n",
    "import pherosensor\n",
    "\n",
    "from pheromone_dispersion.diffusion_operator import Diffusion\n",
    "from pheromone_dispersion.diffusion_tensor import DiffusionTensor\n",
    "from pheromone_dispersion.geom import MeshRect2D\n",
    "from pheromone_dispersion.velocity import Velocity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "86bf7a70",
   "metadata": {},
   "outputs": [],
   "source": [
    "Lx = 20\n",
    "Ly = 25\n",
    "Delta_x = 0.4\n",
    "Delta_y = 0.4\n",
    "T_final = 5."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "144329c3",
   "metadata": {},
   "source": [
    "# Test of the numerical scheme of the diffusion operator\n",
    "\n",
    "This notebook aims to test the implementation of the numerical scheme of the diffusion operator.\n",
    "\n",
    "The diffusion operator is the operator $D:c\\mapsto \\nabla\\cdot(\\mathbf{K}(x,y)\\nabla c(x,y))~\\forall (x,y)\\in\\Omega$ such that $K\\nabla c\\cdot \\vec{n} = 0~\\forall(x,y)\\in\\partial\\Omega$.\n",
    "\n",
    "## Reference solution\n",
    "\n",
    "To test this operator, we consider a diffusion tensor of shape $\\mathbf{K}=diag(K_x,K_y)$.\\\n",
    "This implies that on the boundary of $\\Omega=[O;L_x]\\times[O;L_y]$, $\\mathbf{K}\\nabla c\\cdot \\vec{n} = \\pm K_x\\partial_xc$ for $x\\in\\{0,L_x\\}$ and $\\mathbf{K}\\nabla c\\cdot \\vec{n} = \\pm K_y\\partial_yc$ for $y\\in\\{0,L_y\\}$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5bdd18b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "K_x = 5./3.\n",
    "K_y = 1.\n",
    "\n",
    "def diffusion_tensor(msh): \n",
    "    \n",
    "    U_hi = np.zeros((msh.y_horizontal_interface.size,msh.x.size,2))\n",
    "    U_hi[:,:,0] = 1. \n",
    "    U_vi = np.zeros((msh.y.size,msh.x_vertical_interface.size,2))\n",
    "    U_vi[:,:,0] = 1.\n",
    "    U = Velocity(msh, U_vi, U_hi)\n",
    "    return DiffusionTensor(U, K_x, K_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "340e3b5f",
   "metadata": {},
   "source": [
    "We also consider the reference solution $c^{ref}(x,y,t) =  cos\\left(\\frac{2\\pi n_xx}{L_x}\\right)+cos\\left(\\frac{2\\pi n_yy}{L_y}\\right)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ae22f154",
   "metadata": {},
   "outputs": [],
   "source": [
    "nx = 5\n",
    "ny = 7\n",
    "lambda_x = 2 * np.pi * nx / Lx\n",
    "lambda_y = 2 * np.pi * ny / Ly\n",
    "\n",
    "def c_reference(x,y): \n",
    "    return np.cos(lambda_x * x) + np.cos(lambda_y * y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd07f184",
   "metadata": {},
   "source": [
    "Therefore, we have:\\\n",
    "$\\partial_xc^{ref}(x,y)=-\\frac{2\\pi n_x}{L_x}sin\\left(\\frac{2\\pi n_xx}{L_x}\\right)$, $\\partial_{xx}c^{ref}(x,y)=-\\frac{4\\pi^2 n_x^2}{L_x^2}cos\\left(\\frac{2\\pi n_xx}{L_x}\\right)$\\\n",
    "$\\partial_yc^{ref}(x,y)=-\\frac{2\\pi n_y}{L_y}sin\\left(\\frac{2\\pi n_yy}{L_y}\\right)$, $\\partial_{yy}c^{ref}(x,y)=-\\frac{4\\pi^2 n_y^2}{L_y^2}cos\\left(\\frac{2\\pi n_yy}{L_y}\\right)$\\\n",
    "We can note that the reference solution satisfies the boundary conditions\n",
    "\n",
    "Hence, we have $Dc^{ref}(x,y) = \\nabla\\cdot(\\mathbf{K}\\nabla c^{ref}) = -K_x\\frac{4\\pi^2 n_x^2}{L_x^2}cos\\left(\\frac{2\\pi n_xx}{L_x}\\right)-K_y\\frac{4\\pi^2 n_y^2}{L_y^2}cos\\left(\\frac{2\\pi n_yy}{L_y}\\right)$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6d41485f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def Dc_reference(x,y): \n",
    "    return - K_x * lambda_x**2 * np.cos(lambda_x * x) - K_y * lambda_y**2 * np.cos(lambda_y * y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f2f1910",
   "metadata": {},
   "source": [
    "## Numerical scheme\n",
    "\n",
    "The numerical scheme used is a finite volume scheme. The average of the diffusion operator over a control volume $\\Omega_{i,j}$ is : \n",
    "$\\frac{1}{|\\Omega_{i,j}|} \\int_{\\Omega_{i,j}} \\nabla\\cdot(\\mathbf{K}(x,y) \\nabla c(x,y))dx dy = \\frac{1}{|\\Omega_{i,j}|} \\int_{\\partial \\Omega_{i,j}}\\mathbf{K}(x,y) \\nabla c(x,y)\\cdot \\vec{n} dx dy$. \\\n",
    "In the present case, we use uniform cartesian meshes with the same space step along the two axis. We will denote by the indexes $i+\\frac{1}{2},j$ the vertical interface between the control volumes $i,j$ and $i+1,j$, and similarly for the horizontal interfaces. Moreover, let us note that on the vertical interfaces $\\vec{n}=(\\pm1,0)$ and on the horizontal interfaces $\\vec{n}=(0,\\pm1)$.\\\n",
    "Therefore, we have: $\\frac{1}{|\\Omega_{i,j}|} \\int_{\\partial \\Omega_{i,j}}\\mathbf{K}(x,y)\\nabla c(x,y)\\cdot \\vec{n} dx dy \\approx D^{solver}c(x_i,y_j) = \\frac{1}{|\\Omega_{i,j}|}\\left(\\Delta y\\left(\\mathbf{K}_{i+\\frac{1}{2},j}\\nabla c_{i+\\frac{1}{2},j}-\\mathbf{K}_{i-\\frac{1}{2},j}\\nabla c_{i-\\frac{1}{2},j}\\right)+\\Delta x\\left(\\mathbf{K}_{i,j+\\frac{1}{2}}\\nabla c_{i,j+\\frac{1}{2}}-\\mathbf{K}_{i,j-\\frac{1}{2}}\\nabla c_{i,j-\\frac{1}{2}}\\right)\\right)$\\\n",
    "The gradient at the interfaces are computed using a centered finite difference approximation:\\\n",
    "$\\nabla c_{i+1/2,j} = \\left(  \\frac{c_{i+1,j}-c_{i,j}}{\\Delta x}; \\frac{c_{i+1/2,j+1/2}-c_{i+1/2,j-1/2}}{\\Delta y}  \\right)$ and $\\nabla c_{i,j+1/2} = \\left(\\frac{c_{i+1/2,j+1/2}-c_{i-1/2,j+1/2}}{\\Delta x}; \\frac{c_{i,j+1}-c_{i,j}}{\\Delta y}\\right)$\\\n",
    "with the values at the angles computed by averaging the value of the cell sharing the angle, for instance: $c_{i+1/2,j+1/2} = \\frac{c_{i,j}+c_{i+1,j}+c_{i,j+1}+c_{i+1,j+1}}{4}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "23a94e9f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "dx =  0.002\n",
      "\n",
      "dx =  0.004\n",
      "\n",
      "dx =  0.04000000000000001\n",
      "\n",
      "dx =  0.4\n"
     ]
    }
   ],
   "source": [
    "space_factor_a = [0.005, 0.01, 0.1, 1.]\n",
    "dx_a = np.zeros(len(space_factor_a))\n",
    "\n",
    "MAE = np.zeros(len(space_factor_a))\n",
    "RMSE = np.zeros(len(space_factor_a))\n",
    "\n",
    "for i, space_factor in enumerate(space_factor_a):\n",
    "    \n",
    "    msh = MeshRect2D(Lx, Ly, Delta_x*space_factor, Delta_y*space_factor, T_final)\n",
    "    dx_a[i] = Delta_x*space_factor    \n",
    "    x, y = np.meshgrid(msh.x, msh.y)\n",
    "    \n",
    "    c_ref = c_reference(x,y)\n",
    "    Dc_ref = Dc_reference(x,y)\n",
    "    \n",
    "    K = diffusion_tensor(msh)\n",
    "    D = Diffusion(K, msh)\n",
    "    Dc_solver = D.matvec(c_ref.reshape((msh.y.size * msh.x.size,)))\n",
    "    Dc_solver = Dc_solver.reshape((msh.y.size, msh.x.size))\n",
    "    \n",
    "    MAE[i] = np.mean(np.abs(Dc_solver - Dc_ref))\n",
    "    RMSE[i] = npl.norm(Dc_solver - Dc_ref) / np.sqrt(Dc_ref.size)\n",
    "    \n",
    "    print(\"\")\n",
    "    print(\"dx = \", msh.dx)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6e9ebc5",
   "metadata": {},
   "source": [
    "## Analysis of the truncation error\n",
    "In the present case, since the diffusion tensor is diagonal and the mesh is uniform and cartesian (with $\\Delta x = \\Delta y$), the finite volume scheme is equivalent to a standard centered finite difference scheme.\\\n",
    "Hence, we have the truncation error $R(x,y) = |D^{solver}c(x,y) - Dc(x,y)|=\\mathcal{O}(\\Delta x^2)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8a466d5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x758460554a90>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "slope_MAE = (np.log(MAE[0]) - np.log(MAE[-1])) / (np.log(dx_a[0]) - np.log(dx_a[-1])) \n",
    "slope_RMSE = (np.log(RMSE[0]) - np.log(RMSE[-1]) ) / ( np.log(dx_a[0]) - np.log(dx_a[-1])) \n",
    "\n",
    "fontsize = 25\n",
    "fig, ax1 = plt.subplots(figsize=(20, 10))\n",
    "\n",
    "ax1.plot(dx_a,RMSE,'-ob',label=r'$\\frac{1}{\\sqrt{|\\Omega|}}||Rc^{ref}||_{L^2(\\Omega)}$'+f', slope = {\"{:.5f}\".format(slope_RMSE)}')\n",
    "ax1.plot(dx_a,MAE,'-or',label=r'$\\frac{1}{|\\Omega|}||Rc^{ref}||_{L^1(\\Omega)}$'+f', slope = {\"{:.5f}\".format(slope_MAE)}')\n",
    "ax1.tick_params(axis='both',labelsize=fontsize-5)\n",
    "ax1.set_ylabel(r'error', fontsize=fontsize)\n",
    "ax1.set_xlabel('$\\Delta x$ ($m$)', fontsize=fontsize)\n",
    "ax1.set_xscale('log')\n",
    "ax1.set_yscale('log')\n",
    "ax1.legend(loc='upper left',prop={'size': fontsize})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ad8884d",
   "metadata": {},
   "source": [
    "# Scalar product test for the adjoint of the diffusion operator\n",
    "\n",
    "Let us note that the diffusion operator is auto-adjoint: $D^*=D$, for a symmetric diffusion tensor $\\mathbf{K}=\\mathbf{K}^T$.\n",
    "\n",
    "This section aims at performing the scalar product test for the diffusion operator. It also enables to check that the scheme of the diffusion operator is also auto-adjoint. \n",
    "\n",
    "The test of the scalar product consists in checking that $<Dc_1,c_2>\\approx<c_1,D^*c_2>$ for any $c_1$ and $c_2$ (here picked randomly)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "75dce07a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<Dc_1,c_2> =  1902.906719677645\n",
      "<c_1,D*c_2> =  1902.9067196776446\n",
      "|<Dc_1,c_2>-<c_1,D*c_2>| =  4.547473508864641e-13\n"
     ]
    }
   ],
   "source": [
    "msh = MeshRect2D(Lx, Ly, Delta_x, Delta_y, T_final)\n",
    "K = diffusion_tensor(msh)\n",
    "\n",
    "D = Diffusion(K, msh)\n",
    "\n",
    "np.random.seed(0)\n",
    "c1 = np.random.normal(0, 1, size=msh.x.size*msh.y.size)\n",
    "c2 = np.random.normal(0, 1, size=msh.x.size*msh.y.size)\n",
    "\n",
    "prod_scal_D = np.dot(c2,D.matvec(c1))\n",
    "prod_scal_DT = np.dot(c1,D.matvec(c2))\n",
    "\n",
    "print(\"<Dc_1,c_2> = \",prod_scal_D)\n",
    "print(\"<c_1,D*c_2> = \",prod_scal_DT)\n",
    "print(\"|<Dc_1,c_2>-<c_1,D*c_2>| = \", np.abs(prod_scal_D-prod_scal_DT))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pherosensor-new",
   "language": "python",
   "name": "pherosensor-new"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}