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    "# Adaptive PDE discretizations on Cartesian grids\n",
    "## Volume : Algorithmic tools\n",
    "## Part : Tensor decomposition techniques\n",
    "## Chapter : Selling's algorithm, in dimension 2 and 3\n",
    "\n",
    "$\n",
    "\\newcommand\\bZ{\\mathbb{Z}}\n",
    "\\newcommand\\cE{\\mathcal{E}}\n",
    "\\newcommand\\cO{\\mathcal{O}}\n",
    "\\newcommand\\<{\\langle} \\newcommand\\>{\\rangle}\n",
    "$\n"
   ]
  },
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   "source": [
    "This notebook presents some tensor decomposition techniques that are at the foundation of our anisotropic PDE discretizations on Cartesian grids. The general objective is to write a given symmetric positive definite matrix $D$ under the form\n",
    "$$\n",
    "    D = \\sum_{0 \\leq i < I} \\lambda_i e_i e_i^T. \n",
    "$$\n",
    "From this point, various numerical schemes can be designed, for both first order and second order, and both linear and non-linear PDEs.\n",
    "\n",
    "The techniques used for constructing the above decomposition are non-trivial, and are related to classical yet subtle tools of discrete geometry. This notebook is meant to illustrate some of their properties.\n",
    "\n",
    "This notebook is limited to dimensions $d\\in \\{2,3\\}$. Tensor decomposition in dimension $d \\in \\{4,5\\}$ requires another set of techniques (and in practice the call to a c++ library), which are discussed in [II Tensor decomposition, dimensions 4 and 5](TensorVoronoi.ipynb)\n",
    "\n",
    "**References**\n",
    "\n",
    "The tensor decomposition presented in this notebook is a central ingredient of the following paper:\n",
    "\n",
    "Fehrenbach, J., & Mirebeau, J.-M. (2014). Sparse non-negative stencils for anisotropic diffusion. Journal of Mathematical Imaging and Vision, 49(1), 123–147. http://doi.org/http://dx.doi.org/10.1007/s10851-013-0446-3"
   ]
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   "cell_type": "markdown",
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   "source": [
    "[**Summary**](Summary.ipynb) of volume Algorithmic tools, this series of notebooks.\n",
    "\n",
    "[**Main summary**](../Summary.ipynb) of the Adaptive Grid Discretizations \n",
    "\tbook of notebooks, including the other volumes.\n",
    "\n",
    "# Table of contents\n",
    "  * [1. Decomposing a tensor, or a tensor field](#1.-Decomposing-a-tensor,-or-a-tensor-field)\n",
    "    * [1.1 Case of a $2\\times 2$ matrix](#1.1-Case-of-a-$2\\times-2$-matrix)\n",
    "    * [1.2 Case of a $3 \\times 3$ matrix.](#1.2-Case-of-a-$3-\\times-3$-matrix.)\n",
    "    * [1.3 Case of (extremely) strong anisotropy](#1.3-Case-of-(extremely)-strong-anisotropy)\n",
    "    * [1.4 Decomposition a field of symmetric tensors](#1.4-Decomposition-a-field-of-symmetric-tensors)\n",
    "  * [2. Under the hood : obtuse superbases](#2.-Under-the-hood-:-obtuse-superbases)\n",
    "    * [2.1 Two dimensions](#2.1-Two-dimensions)\n",
    "    * [2.2 Three dimensions](#2.2-Three-dimensions)\n",
    "  * [3. Properties of the decomposition](#3.-Properties-of-the-decomposition)\n",
    "    * [3.1 Offsets smallness](#3.1-Offsets-smallness)\n",
    "    * [3.2 Stability](#3.2-Stability)\n",
    "    * [3.3 Spanning property (no chessboard artifacts)](#3.3-Spanning-property-(no-chessboard-artifacts))\n",
    "    * [3.4 Piecewise linearity](#3.4-Piecewise-linearity)\n",
    "  * [4. Smooth two-dimensional decomposition](#4.-Smooth-two-dimensional-decomposition)\n",
    "    * [4.1 Construction](#4.1-Construction)\n",
    "    * [4.2 Display of coefficients](#4.2-Display-of-coefficients)\n",
    "    * [4.3 Linear decomposition](#4.3-Linear-decomposition)\n",
    "    * [4.4 Automatic differentiation](#4.4-Automatic-differentiation)\n",
    "  * [5. Convolved decomposition](#5.-Convolved-decomposition)\n",
    "  * [6. Smooth three-dimensional decomposition](#6.-Smooth-three-dimensional-decomposition)\n",
    "    * [6.1 Python implementation](#6.1-Python-implementation)\n",
    "    * [6.2 Comparison with the C++ implementation](#6.2-Comparison-with-the-C++-implementation)\n",
    "\n",
    "\n",
    "\n",
    "**Acknowledgement.** Some of the experiments presented in these notebooks are part of \n",
    "ongoing research with Ludovic Métivier and Da Chen.\n",
    "\n",
    "Copyright Jean-Marie Mirebeau, Centre Borelli, ENS Paris-Saclay, CNRS, University Paris-Saclay"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "## 0. Importing the required libraries"
   ]
  },
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   "source": [
    "import sys; sys.path.insert(0,\"..\") # Allow import of agd from parent directory (useless if conda package installed)\n",
    "#from Miscellaneous import TocTools; print(TocTools.displayTOC('TensorSelling','Algo'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "from agd import LinearParallel as lp\n",
    "from agd import FiniteDifferences as fd\n",
    "from agd import Selling\n",
    "from agd.Plotting import savefig; #savefig.dirName = 'Figures/TensorSelling'\n",
    "from agd import AutomaticDifferentiation as ad\n",
    "from agd import Interpolation\n",
    "from agd.Metrics import Riemann"
   ]
  },
  {
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   "metadata": {
    "editable": true,
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   "source": [
    "The library imported as **lp** is a set of routines meant to facilitate the manipulation of *numerous small vectors and matrices* simultaneously. It is based on numpy and implements  only a small number of linear algebra tools."
   ]
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     "ExportCode"
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   "source": [
    "import numpy as np; xp = np; allclose = np.allclose; π = np.pi\n",
    "import matplotlib.pyplot as plt\n",
    "np.set_printoptions(linewidth=2000)"
   ]
  },
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   "source": [
    "### 0.1 Additional configuration\n",
    "\n",
    "Uncomment the following line to run the notebook on the GPU. (This only for compatibility testing, since no intensive computation is involved in this specific notebook.)"
   ]
  },
  {
   "cell_type": "code",
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     "GPU_config"
    ]
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   "source": [
    "#xp,plt,allclose=map(ad.cupy_friendly,(xp,plt,allclose))"
   ]
  },
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   "cell_type": "markdown",
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    "editable": true,
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   "source": [
    "## 1. Decomposing a tensor, or a tensor field\n",
    "\n",
    "In order to illustrate our tensor decomposition facilities, we will rely on randomly generated *symmetric positive definite* tensors. They are built as \n",
    "$$\n",
    "    M = A^T A + \\varepsilon \\mathrm{Id}\n",
    "$$\n",
    "where $A$ has normalized random Gaussian entries."
   ]
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   "metadata": {
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   "source": [
    "def MakeRandomTensor(dim,shape = tuple(),relax=0.01):\n",
    "    identity = fd.as_field(np.eye(dim),shape,depth=2)\n",
    "    A = np.random.standard_normal( (dim,dim) + shape ) \n",
    "    M = lp.dot_AA(lp.transpose(A),A) + relax*identity\n",
    "    return xp.asarray(M) # Convert to GPU array if needed"
   ]
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   "cell_type": "code",
   "execution_count": 6,
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    "execution": {
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   "source": [
    "# For reproducibility, we fix the random seed\n",
    "np.random.seed(42) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1 Case of a $2\\times 2$ matrix \n"
   ]
  },
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   "source": [
    "# Generate a 2x2 random psd tensor\n",
    "D2 = MakeRandomTensor(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The **Selling.Decomposition** routine, applies to a symmetric positive definite matrix $D$ of size $d \\times d$, with $d\\leq 3$. It returns coefficients $\\lambda_i \\geq 0$ and offsets $e_i \\in Z^d$.\n",
    "\n",
    "A discussion on the inner workings of this decomposition is presented in the next section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
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   "source": [
    "coefs,offsets = Selling.Decomposition(D2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The matrix can be reconstructed by the formula\n",
    "$$\n",
    "    D = \\sum_{0 \\leq i < I} \\lambda_i e_i e_i^T. \n",
    "$$\n",
    "\n",
    "<!---ExoFR\n",
    "Définissez une fonction qui reconstruit le tenseur D à partir de coefficients $(\\lambda_i)_{0\\leq i <I}$ et offsets $(e_i)_{0 \\leq i < I}$.\n",
    "--->\n",
    "\n",
    "<!---ExoCode\n",
    "def Reconstruct(coefs,offsets):\n",
    "    \"\"\"\n",
    "    Input.\n",
    "     - coefs :   array of shape   (I,n1,...,nk)\n",
    "     - offsets : array of shape (d,I,n1,...,nk)\n",
    "    Output. \n",
    "     - D :       array of shape (d,d,n1,...,nk)\n",
    "    \"\"\"\n",
    "    return # TODO.\n",
    "--->"
   ]
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   "source": [
    "def Reconstruct(coefs,offsets):\n",
    "     return (coefs*lp.outer_self(offsets)).sum(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
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   "source": [
    "assert allclose(D2,Reconstruct(coefs,offsets))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are $I = d(d+1)/2$ coefficients and offsets (a.k.a $I=3$ if $d=2$, and $I=6$ if $d=3$). Note that this is more than the similar-looking eigen-decomposition of a matrix, which uses only $d$ coefficients and unit vectors. However, Selling's offsets have integer entries, hence are suitable for the construction of finite difference schemes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selling decomposition of matrix : \n",
      " [[0.67622539 0.91777115]\n",
      " [0.91777115 2.34873696]]\n",
      "Coefficients :  [0.43467964 0.94787431 0.24154575]\n",
      "Offsets : \n",
      " [[-1  0  1]\n",
      " [-1 -1  2]]\n"
     ]
    }
   ],
   "source": [
    "print(\"Selling decomposition of matrix : \\n\", D2)\n",
    "print(\"Coefficients : \", coefs)\n",
    "print(\"Offsets : \\n\", offsets)"
   ]
  },
  {
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    {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.axis('equal'); plt.title(\"Decomposition offsets for the matrix D2\")\n",
    "plt.quiver(*np.zeros(offsets.shape),*offsets,angles='xy',scale_units='xy',scale=1);\n",
    "plt.scatter(*offsets); plt.scatter(*(-offsets));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2 Case of a $3 \\times 3$ matrix.\n",
    "\n",
    "As previously, we generate a 3x3 random psd tensor, decompose it and validate the absence of reconstruction error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.382511Z",
     "iopub.status.busy": "2024-04-30T09:12:20.382413Z",
     "iopub.status.idle": "2024-04-30T09:12:20.384102Z",
     "shell.execute_reply": "2024-04-30T09:12:20.383866Z"
    }
   },
   "outputs": [],
   "source": [
    "D3 = MakeRandomTensor(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.385460Z",
     "iopub.status.busy": "2024-04-30T09:12:20.385381Z",
     "iopub.status.idle": "2024-04-30T09:12:20.387333Z",
     "shell.execute_reply": "2024-04-30T09:12:20.387101Z"
    }
   },
   "outputs": [],
   "source": [
    "coefs,offsets = Selling.Decomposition(D3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.388710Z",
     "iopub.status.busy": "2024-04-30T09:12:20.388606Z",
     "iopub.status.idle": "2024-04-30T09:12:20.390206Z",
     "shell.execute_reply": "2024-04-30T09:12:20.389958Z"
    }
   },
   "outputs": [],
   "source": [
    "assert allclose(D3,Reconstruct(coefs,offsets))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.391487Z",
     "iopub.status.busy": "2024-04-30T09:12:20.391414Z",
     "iopub.status.idle": "2024-04-30T09:12:20.393503Z",
     "shell.execute_reply": "2024-04-30T09:12:20.393247Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selling decomposition of matrix : \n",
      " [[ 0.86853982 -0.08963958 -0.06552819]\n",
      " [-0.08963958  0.50213052 -0.73715916]\n",
      " [-0.06552819 -0.73715916  2.85683026]]\n",
      "Coefficients :  [0.15516777 0.08963958 0.62373247 0.23502864 1.49444606 0.1774623 ]\n",
      "Offsets : \n",
      " [[-1  1 -1  0  0  0]\n",
      " [ 0 -1  0  1  0 -1]\n",
      " [ 1  1  0 -2  1  1]]\n"
     ]
    }
   ],
   "source": [
    "print(\"Selling decomposition of matrix : \\n\", D3)\n",
    "print(\"Coefficients : \", coefs)\n",
    "print(\"Offsets : \\n\", offsets)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3 Case of (extremely) strong anisotropy\n",
    "\n",
    "Selling's tensor decomposition algorithm requires the matrix to be positive definite. It involves a loop, whose number of iterations grows to infinity as the matrix degenerates.\n",
    "\n",
    "A maximum number of iterations is set by default, to a reasonably large value, so that non-convergence is typically due to an error on the user's side - namely a non-positive matrix. \n",
    "\n",
    "In the following cell, we define the following matrix, which is positive definite but strongly anisotropic:\n",
    "$$\n",
    "    \\begin{pmatrix}\n",
    "    1 & \\varepsilon\\\\\n",
    "    \\varepsilon & 2 \\varepsilon^2\n",
    "    \\end{pmatrix}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.394835Z",
     "iopub.status.busy": "2024-04-30T09:12:20.394756Z",
     "iopub.status.idle": "2024-04-30T09:12:20.396493Z",
     "shell.execute_reply": "2024-04-30T09:12:20.396269Z"
    }
   },
   "outputs": [],
   "source": [
    "# Construct some matrix with extremely large condition number\n",
    "eps = 1/200.\n",
    "D2_bad = np.array([[1,eps],[eps,2*eps**2]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition, the anisotropy direction of this matrix is *almost but not exactly* aligned with the coordinate axes, which is a worst case scenario for Selling's algorithm. As a result, Selling's algorithm fails to converge within the prescribed iteration limit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.397829Z",
     "iopub.status.busy": "2024-04-30T09:12:20.397746Z",
     "iopub.status.idle": "2024-04-30T09:12:20.401389Z",
     "shell.execute_reply": "2024-04-30T09:12:20.401154Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(\"Selling's algorithm did not terminate in iterMax2=100 iterations\",)\n"
     ]
    }
   ],
   "source": [
    "#Selling's decomposition does not terminate within the iteration limit\n",
    "try:\n",
    "    coefs,offsets = Selling.Decomposition(D2_bad)\n",
    "except ValueError as e:\n",
    "    print(e.args)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The iteration limit of Selling's algorithm may be increased, so as to ensure correct termination."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.402756Z",
     "iopub.status.busy": "2024-04-30T09:12:20.402672Z",
     "iopub.status.idle": "2024-04-30T09:12:20.404304Z",
     "shell.execute_reply": "2024-04-30T09:12:20.404091Z"
    }
   },
   "outputs": [],
   "source": [
    "Selling.iterMax2 *= 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.405554Z",
     "iopub.status.busy": "2024-04-30T09:12:20.405476Z",
     "iopub.status.idle": "2024-04-30T09:12:20.409451Z",
     "shell.execute_reply": "2024-04-30T09:12:20.409229Z"
    }
   },
   "outputs": [],
   "source": [
    "coefs,offsets = Selling.Decomposition(D2_bad)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, the resulting offsets are unlikely to be of use for any PDE discretization, since they are way too large. \n",
    "\n",
    "Note also that basis reduction techniques more efficient than Selling's algorithm are available for tensors with extremely large condition numbers. (E.g. Lagrange's algorithm.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.410828Z",
     "iopub.status.busy": "2024-04-30T09:12:20.410752Z",
     "iopub.status.idle": "2024-04-30T09:12:20.412465Z",
     "shell.execute_reply": "2024-04-30T09:12:20.412241Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "offsets : \n",
      " [[-99 100  -1]\n",
      " [ -1   1   0]]\n"
     ]
    }
   ],
   "source": [
    "print(\"offsets : \\n\", offsets)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.4 Decomposition a field of symmetric tensors\n",
    "\n",
    "Our implementation of Selling's algorithm automatically threads over dimensions deeper than two."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.413812Z",
     "iopub.status.busy": "2024-04-30T09:12:20.413740Z",
     "iopub.status.idle": "2024-04-30T09:12:20.415343Z",
     "shell.execute_reply": "2024-04-30T09:12:20.415099Z"
    }
   },
   "outputs": [],
   "source": [
    "# Generate a 10x10 field of random 2x2 spd tensors\n",
    "D2_field = MakeRandomTensor(2,(10,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.416660Z",
     "iopub.status.busy": "2024-04-30T09:12:20.416582Z",
     "iopub.status.idle": "2024-04-30T09:12:20.418648Z",
     "shell.execute_reply": "2024-04-30T09:12:20.418419Z"
    }
   },
   "outputs": [],
   "source": [
    "coefs, offsets = Selling.Decomposition(D2_field)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The shape of the matrix field is $(d,d, n_1,\\cdots,n_k)$, whereas the coefficients are $(I,n_1,\\cdots,n_k)$ and the offsets $(d,I,n_1,\\cdots,n_k)$ where $I = d (d+1)/2$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.419950Z",
     "iopub.status.busy": "2024-04-30T09:12:20.419860Z",
     "iopub.status.idle": "2024-04-30T09:12:20.421436Z",
     "shell.execute_reply": "2024-04-30T09:12:20.421209Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2, 2, 10, 10), (3, 10, 10), (2, 3, 10, 10)\n"
     ]
    }
   ],
   "source": [
    "print(f\"{D2_field.shape}, {coefs.shape}, {offsets.shape}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.422729Z",
     "iopub.status.busy": "2024-04-30T09:12:20.422631Z",
     "iopub.status.idle": "2024-04-30T09:12:20.424193Z",
     "shell.execute_reply": "2024-04-30T09:12:20.423966Z"
    }
   },
   "outputs": [],
   "source": [
    "assert allclose(D2_field,Reconstruct(coefs,offsets))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Under the hood : obtuse superbases\n",
    "\n",
    "This section illustrates the main mathematical concept underlying Selling's decomposition, known as *obtuse superbases* of the lattice $Z^d$.\n",
    "\n",
    "A superbase of $Z^d$ is a special kind of coordinate system $(b_0,\\cdots,b_d)$, spanning the lattice of integer points and with some redundancy. More precisely, one requires\n",
    "$$\n",
    "\\begin{aligned}\n",
    "    b_0+\\cdots+b_d &= 0,\\\\\n",
    "    \\det(b_1,\\cdots,b_d) &= \\pm 1.\n",
    "\\end{aligned}\n",
    "$$\n",
    "Such a superbase is said $D$-obtuse, where $D$ is a given $d\\times d$ symmetric positive definite matrix, if \n",
    "$$\n",
    "    <b_i,D b_j> \\leq 0\n",
    "$$\n",
    "for all distinct $i,j\\in \\{0,\\cdots,d\\}$.\n",
    "\n",
    "Sellings decomposition of a matrix $D \\in S_d^{++}$ is based Selling's formula applied to a $D$-obtuse superbase, which itself is produced by Selling's algorithm."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1 Two dimensions\n",
    "\n",
    "The following method applies Selling's algorithm to a given positive definite tensor $D \\in S_2^{++}$, producing a suitable superbase of $Z^2$.\n",
    "\n",
    "<!---ExoFR\n",
    "Implémenter l'algorithme de Selling, pour construire une superbase $D$-obtuse pour toute matrice symétrique définie positive $D$ donnée de taille $2 \\times 2$.\n",
    "\n",
    "On rappelle que si $(v_0,v_1,v_2)$ est une superbase qui n'est pas obtuse, donc satisfaisant $<v_i,D v_j> > 0$ où $\\{i,j,k\\}$ est une permutation de $\\{0,1,2\\}$, alors la règle de mise à jour Selling est \n",
    "$$\n",
    "    (v_0,v_1,v_2) \\gets (-v_i,v_j,v_i-v_j).\n",
    "$$\n",
    "--->\n",
    "\n",
    "<!---ExoCode\n",
    "def ObtuseSuperbase2(D,niter=100):\n",
    "    \"\"\"\n",
    "    Input.\n",
    "     - D :  array of shape (2,2)\n",
    "    Output : \n",
    "     - sb : array of shape (2,3)\n",
    "    \"\"\"\n",
    "    sb = np.array([[-1,-1],[1,0],[0,1]]) # here of shape (3,2), transposed in the end\n",
    "    for _ in range(niter):\n",
    "        for i,j,k in [(0,1,2),(0,2,1),(1,2,0)]:\n",
    "            # TODO : check if <sb_i, D sb_j> > 0\n",
    "            # in that case, apply the Selling update rule and break\n",
    "        else: \n",
    "            # All superbase angles are obtuse\n",
    "            return sb.T\n",
    "    raise ValueError(f\"Selling algorithm failed to converge in {niter} iterations\")\n",
    "\n",
    "# Try your code\n",
    "sb = ObtuseSuperbase2(D2)\n",
    "--->\n",
    "\n",
    "<!---\n",
    "def ObtuseSuperbase2(D,niter=100):\n",
    "    sb = np.array([[-1,-1],[1,0],[0,1]])\n",
    "    for _ in range(niter):\n",
    "        for i,j,k in [(0,1,2),(0,2,1),(1,2,0)]:\n",
    "            if lp.dot_VAV(sb[i],D,sb[j]) > 0:\n",
    "                sb[k] = sb[i]-sb[j]\n",
    "                sb[i] = -sb[i]\n",
    "                break\n",
    "        else: \n",
    "            return sb.T\n",
    "    raise ValueError(f\"Selling algorithm failed to converge in {niter} iterations\")\n",
    "--->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.425493Z",
     "iopub.status.busy": "2024-04-30T09:12:20.425419Z",
     "iopub.status.idle": "2024-04-30T09:12:20.426979Z",
     "shell.execute_reply": "2024-04-30T09:12:20.426757Z"
    }
   },
   "outputs": [],
   "source": [
    "sb = Selling.ObtuseSuperbase(D2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.428247Z",
     "iopub.status.busy": "2024-04-30T09:12:20.428170Z",
     "iopub.status.idle": "2024-04-30T09:12:20.430331Z",
     "shell.execute_reply": "2024-04-30T09:12:20.430091Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1., -1.,  2.],\n",
       "       [ 1., -0., -1.]])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The generated superbase $(b_0,\\cdots,b_d)$ is designed to be $D$-obtuse. In other words to obey \n",
    "$$\n",
    "    <b_i,D b_j> \\leq 0\n",
    "$$\n",
    "for all distinct $i,j\\in \\{0,\\cdots,d\\}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.432340Z",
     "iopub.status.busy": "2024-04-30T09:12:20.432232Z",
     "iopub.status.idle": "2024-04-30T09:12:20.434585Z",
     "shell.execute_reply": "2024-04-30T09:12:20.434346Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-0.2415457537440081, -0.4346796384446704, -0.9478743070679034]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[lp.dot_VAV(sb[:,i],D2,sb[:,np.mod(i+1,3)]) for i in range(3)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Selling's formula yields the desired decomposition of the given symmetric positive definite matrix $D$\n",
    "$$\n",
    "    D = -\\sum_{0\\leq i<j \\leq d} <b_i,D b_j> v_{ij} v_{ij}^T,\n",
    "$$\n",
    "where one defines $v_{ij} = \\pm b_k^\\perp$ whenever $\\{i,j,k\\} = \\{0,1,2\\}$. \n",
    "\n",
    "Note that, \n",
    "* the weight of the decomposition are the negated scalar products, hence are non-negative.\n",
    "* the offsets of the decomposition are the superbase elements rotated by $\\pi/2$, hence have integer coordinates.\n",
    "\n",
    "<!---ExoFR\n",
    "Implémentez la formule de reconstruction de Selling, en dimension 2.\n",
    "--->\n",
    "\n",
    "<!---ExoCode\n",
    "def Decomposition2(D):\n",
    "    coefs = []\n",
    "    offsets = []\n",
    "    for i,j,k in [(0,1,2),(0,2,1),(1,2,0)]:\n",
    "        coefs.append(   # TODO. Append coefficient\n",
    "        offsets.append( # TODO. Append offset\n",
    "    return np.array(coefs),np.array(offsets).T\n",
    "--->\n",
    "\n",
    "<!---\n",
    "def Decomposition2(D):\n",
    "    sb = ObtuseSuperbase2(D)\n",
    "    coefs = []\n",
    "    offsets = []\n",
    "    for i,j,k in [(0,1,2),(0,2,1),(1,2,0)]:\n",
    "        coefs.append(-lp.dot_VAV(sb[:,i],D,sb[:,j]))\n",
    "        offsets.append([sb[1,k],-sb[0,k]])\n",
    "    return np.array(coefs),np.array(offsets).T\n",
    "--->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.436064Z",
     "iopub.status.busy": "2024-04-30T09:12:20.435957Z",
     "iopub.status.idle": "2024-04-30T09:12:20.437789Z",
     "shell.execute_reply": "2024-04-30T09:12:20.437522Z"
    }
   },
   "outputs": [],
   "source": [
    "coefs,offsets = Selling.Decomposition(D2,sb=sb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.439173Z",
     "iopub.status.busy": "2024-04-30T09:12:20.439069Z",
     "iopub.status.idle": "2024-04-30T09:12:20.440861Z",
     "shell.execute_reply": "2024-04-30T09:12:20.440642Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients :  [0.43467964 0.94787431 0.24154575]\n",
      "Offsets : \n",
      " [[-1  0  1]\n",
      " [-1 -1  2]]\n"
     ]
    }
   ],
   "source": [
    "print(\"Coefficients : \", coefs)\n",
    "print(\"Offsets : \\n\", offsets)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is possible to produce a tensor decomposition from an arbitrary superbase, but the coefficients are positive only if the superbase is obtuse."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.442204Z",
     "iopub.status.busy": "2024-04-30T09:12:20.442108Z",
     "iopub.status.idle": "2024-04-30T09:12:20.444069Z",
     "shell.execute_reply": "2024-04-30T09:12:20.443830Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients :  [-0.91777115  3.26650811  1.59399654]\n",
      "Offsets : \n",
      " [[ 1  0 -1]\n",
      " [-1  1  0]]\n"
     ]
    }
   ],
   "source": [
    "sb = Selling.CanonicalSuperbase(D2) # Only takes the dimension an array type from the argument\n",
    "coefs,offsets = Selling.Decomposition(D2,sb=sb)\n",
    "print(\"Coefficients : \", coefs)\n",
    "print(\"Offsets : \\n\", offsets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.445398Z",
     "iopub.status.busy": "2024-04-30T09:12:20.445299Z",
     "iopub.status.idle": "2024-04-30T09:12:20.446972Z",
     "shell.execute_reply": "2024-04-30T09:12:20.446742Z"
    }
   },
   "outputs": [],
   "source": [
    "assert np.allclose(D2,Reconstruct(coefs,offsets))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Three dimensions\n",
    "\n",
    "We follow similar steps in dimension $d=3$. Selling's algorithm, applied to the given matrix $D$, yields a specific superbase of $Z^3$.\n",
    "\n",
    "<!---ExoFR\n",
    "Implémenter l'algorithme de Selling, pour construire une superbase $D$-obtuse pour toute matrice symétrique définie positive $D$ donnée de taille $3 \\times 3$.\n",
    "\n",
    "On rappelle que si $(v_0,v_1,v_2,v_3)$ est une superbase qui n'est pas obtuse, donc satisfaisant $<v_i,D v_j> > 0$ où $\\{i,j,k,l\\}$ est une permutation de $\\{0,1,2,3\\}$, alors la règle de mise à jour Selling est \n",
    "$$\n",
    "    (v_0,v_1,v_2,v_3) \\gets (-v_i,v_j,v_k+v_i,v_l+v_i).\n",
    "$$\n",
    "--->\n",
    "\n",
    "<!---ExoCode\n",
    "def ObtuseSuperbase3(D,niter=100):\n",
    "    \"\"\"\n",
    "    Input.\n",
    "     - D :  array of shape (3,3)\n",
    "    Output : \n",
    "     - sb : array of shape (3,6)\n",
    "    \"\"\"\n",
    "    # TODO : reprendre et adapter ObtuseSuperbase2\n",
    "    raise ValueError(f\"Selling algorithm failed to converge in {niter} iterations\")\n",
    "\n",
    "# Try your code\n",
    "sb = ObtuseSuperbase3(D3)\n",
    "--->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.448363Z",
     "iopub.status.busy": "2024-04-30T09:12:20.448285Z",
     "iopub.status.idle": "2024-04-30T09:12:20.450024Z",
     "shell.execute_reply": "2024-04-30T09:12:20.449802Z"
    }
   },
   "outputs": [],
   "source": [
    "sb = Selling.ObtuseSuperbase(D3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.451310Z",
     "iopub.status.busy": "2024-04-30T09:12:20.451232Z",
     "iopub.status.idle": "2024-04-30T09:12:20.453260Z",
     "shell.execute_reply": "2024-04-30T09:12:20.453040Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1., -0.,  0., -1.],\n",
       "       [ 0.,  1.,  1., -2.],\n",
       "       [ 0.,  1.,  0., -1.]])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The superbase produced by Selling's algorithm is $D$-obtuse, similarly to the two dimensional case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.454691Z",
     "iopub.status.busy": "2024-04-30T09:12:20.454616Z",
     "iopub.status.idle": "2024-04-30T09:12:20.456967Z",
     "shell.execute_reply": "2024-04-30T09:12:20.456742Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-0.1551677694190755,\n",
       " -0.08963958172347006,\n",
       " -0.2350286383841237,\n",
       " -0.6237324732734056,\n",
       " -1.4944460568297004,\n",
       " -0.1774622969114411]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[lp.dot_VAV(sb[:,i],D3,sb[:,j]) for i in range(4) for j in range(i)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Selling's formula yields the desired decomposition of the given positive definite matrix $D \\in S_3^{++}$:\n",
    "$$\n",
    "    D = -\\sum_{0\\leq i<j \\leq d} <b_i,D b_j> v_{ij} v_{ij}^T,\n",
    "$$\n",
    "where one defines $v_{ij} = \\pm b_k \\wedge b_l$ whenever $\\{i,j,k,l\\} = \\{0,1,2,3\\}$. \n",
    "\n",
    "Note that:\n",
    "* the weight of the decomposition are the negated scalar products, hence are non-negative.\n",
    "* the offsets of the decomposition are the cross-products of superbase elements (or their opposites), hence have integer entries.\n",
    "\n",
    "<!---ExoFR\n",
    "Implémenter la formule de décomposition de Selling en dimension $d=3$.\n",
    "--->\n",
    "\n",
    "<!---ExoCode\n",
    "def Decomposition3(D):\n",
    "    \"\"\"\n",
    "    Input.\n",
    "     - D :       array of shape (3,3)\n",
    "    Output.\n",
    "     - coefs :   array of shape (6,)\n",
    "     - offsets : array of shape (3,6)\n",
    "    \"\"\"\n",
    "    coefs = []\n",
    "    offsets = []\n",
    "    # TODO : Reprendre et adapter Decomposition2\n",
    "    return np.array(coefs),np.array(offsets).T\n",
    "--->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.458300Z",
     "iopub.status.busy": "2024-04-30T09:12:20.458224Z",
     "iopub.status.idle": "2024-04-30T09:12:20.460255Z",
     "shell.execute_reply": "2024-04-30T09:12:20.460008Z"
    }
   },
   "outputs": [],
   "source": [
    "coefs,offsets = Selling.Decomposition(D3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.461590Z",
     "iopub.status.busy": "2024-04-30T09:12:20.461518Z",
     "iopub.status.idle": "2024-04-30T09:12:20.463408Z",
     "shell.execute_reply": "2024-04-30T09:12:20.463171Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients :  [0.15516777 0.08963958 0.62373247 0.23502864 1.49444606 0.1774623 ]\n",
      "Offsets : \n",
      " [[-1  1 -1  0  0  0]\n",
      " [ 0 -1  0  1  0 -1]\n",
      " [ 1  1  0 -2  1  1]]\n"
     ]
    }
   ],
   "source": [
    "print(\"Coefficients : \", coefs)\n",
    "print(\"Offsets : \\n\", offsets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.464710Z",
     "iopub.status.busy": "2024-04-30T09:12:20.464629Z",
     "iopub.status.idle": "2024-04-30T09:12:20.467214Z",
     "shell.execute_reply": "2024-04-30T09:12:20.466981Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  0,  1,  0, -1,  1],\n",
       "       [ 1,  0,  0, -1,  1,  0],\n",
       "       [-1, -1,  0,  2, -1, -1]])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Comparing with the cross products of the superbase elements.\n",
    "ad.array(\n",
    "    [lp.cross(sb[:,i],sb[:,j]) for i in range(4) for j in range(i)]\n",
    ").astype(int).T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Properties of the decomposition\n",
    "\n",
    "Selling's decomposition of tensors, presented in this notebook, has a qualities that make it particularly suitable for PDE discretizations. More precisely, it is:\n",
    "* *Local*: The offsets appearing in the decomposition are typically small, and in any case bounded in terms of the anisotropy ratio of the matrix, see below.\n",
    "* *Stable*: The decomposition is unique, up to trivial transformations (reordering the offsets, and replacing some with their opposites). It is also stable, more precisely the coefficients are locally Lipschitz w.r.t. the decomposed matrix.  \n",
    "* *Spanning*: The offsets of the decomposition span $Z^d$ by linear relations with integer coordinates. In practice, this means that anisotropic PDE discretizations using this method should not produce chessboard artifacts. \n",
    "\n",
    "We denote the *anisotropy ratio* of a symmetric positive definite matrix $D$ by \n",
    "$$\n",
    "    \\mu(D) := \\sqrt{\\|D\\| \\|D^{-1}\\|}.\n",
    "$$\n",
    "In other words, this is the square root of the condition number of $D$.\n",
    "\n",
    "We illustrate these properties in dimension $d=2$, by considering the following family of matrices $D(\\theta,\\mu) \\in S_2^{++}$:\n",
    "$$\n",
    "    D(\\theta,\\mu) := \\mu^2 e(\\theta) e(\\theta)^T + e(\\theta)^\\perp (e(\\theta)^\\perp)^T,\n",
    "$$\n",
    "whose condition number is equal to $\\mu\\geq 1$, and whose anisotropy direction is aligned with the vector $e(\\theta):=(\\cos \\theta,\\sin \\theta)$, $\\theta \\in R$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.468571Z",
     "iopub.status.busy": "2024-04-30T09:12:20.468494Z",
     "iopub.status.idle": "2024-04-30T09:12:20.470597Z",
     "shell.execute_reply": "2024-04-30T09:12:20.470372Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "θ = xp.linspace(0,π/2,100)\n",
    "μ = 10\n",
    "D2_rotating = (\n",
    "    μ**2 * lp.outer_self(xp.array([np.cos(θ),np.sin(θ)])) \n",
    "    + lp.outer_self(xp.array([-np.sin(θ),np.cos(θ)])) \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.471915Z",
     "iopub.status.busy": "2024-04-30T09:12:20.471835Z",
     "iopub.status.idle": "2024-04-30T09:12:20.473852Z",
     "shell.execute_reply": "2024-04-30T09:12:20.473614Z"
    }
   },
   "outputs": [],
   "source": [
    "coefs,offsets = Selling.Decomposition(D2_rotating)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 Offsets smallness \n",
    "\n",
    "The offsets $(e_i)_{1 \\leq i \\leq I}$ involved in Selling's decomposition of a tensor $D$ obey\n",
    "$$\n",
    "    \\|e_i\\| \\leq C \\mu(D),\n",
    "$$\n",
    "where $C$ is an absolute constant. \n",
    "\n",
    "<!---\n",
    "np.sqrt(np.sum(offsets**2,axis=0))\n",
    "--->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.475316Z",
     "iopub.status.busy": "2024-04-30T09:12:20.475240Z",
     "iopub.status.idle": "2024-04-30T09:12:20.476940Z",
     "shell.execute_reply": "2024-04-30T09:12:20.476678Z"
    }
   },
   "outputs": [],
   "source": [
    "offsets_norms = xp.linalg.norm(offsets,axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.478271Z",
     "iopub.status.busy": "2024-04-30T09:12:20.478190Z",
     "iopub.status.idle": "2024-04-30T09:12:20.479895Z",
     "shell.execute_reply": "2024-04-30T09:12:20.479664Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sqrt of condition number :  10\n",
      "Largest offset norm :  5.0990195135927845\n"
     ]
    }
   ],
   "source": [
    "print(\"Sqrt of condition number : \", μ)\n",
    "print(\"Largest offset norm : \", np.max(offsets_norms))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.481244Z",
     "iopub.status.busy": "2024-04-30T09:12:20.481163Z",
     "iopub.status.idle": "2024-04-30T09:12:20.535888Z",
     "shell.execute_reply": "2024-04-30T09:12:20.535650Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(θ,np.max(offsets_norms,axis=0));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Stability\n",
    "\n",
    "We can rewrite Selling's decomposition in a manner independent of the a specific ordering of the offsets, as follows\n",
    "$$\n",
    "    D = \\sum_{e \\in Z^d} \\lambda^e(D) e e^T.\n",
    "$$\n",
    "One can then prove that the coefficient $\\lambda^e(D)$ of Selling's tensor decomposition, for a given offset $e \\in Z^d$, depends continuously on the parameter $D$, as illustrated below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.537376Z",
     "iopub.status.busy": "2024-04-30T09:12:20.537291Z",
     "iopub.status.idle": "2024-04-30T09:12:20.540076Z",
     "shell.execute_reply": "2024-04-30T09:12:20.539850Z"
    }
   },
   "outputs": [],
   "source": [
    "decomp = Selling.GatherByOffset(θ,coefs,offsets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.541362Z",
     "iopub.status.busy": "2024-04-30T09:12:20.541285Z",
     "iopub.status.idle": "2024-04-30T09:12:20.670947Z",
     "shell.execute_reply": "2024-04-30T09:12:20.670645Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,4))\n",
    "for offset,(angle,coef) in decomp.items():\n",
    "    plt.plot(angle,coef)\n",
    "plt.legend(decomp.keys(),ncol=3);\n",
    "savefig(fig,\"Coefs_Sel2_rot.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 Spanning property (no chessboard artifacts)\n",
    "\n",
    "The lattice $Z^d$ is spanned, by integer combinations, by the offsets $(e_i)_{1 \\leq i \\leq I}$ appearing in the decomposition of an arbitrary p.s.d. tensor $D$. In other words, for all $x \\in Z^d$, there exists coefficients $k_1,\\cdots, k_I \\in Z$ such that \n",
    "$$\n",
    "    x = k_1 e_1 + \\cdots+ k_d e_d.\n",
    "$$\n",
    "In addition, one may select this decomposition so that the weight $\\lambda_i$ of $e_i$ is positive whenever $k_i \\neq 0$.\n",
    "\n",
    "This property guarantees that the graph underlying e.g. the discretization of an anisotropic laplacian is locally connected, hence that spurious modes such as chessboard artifacts will not appear. \n",
    "\n",
    "From a mathematical standpoint, the spanning property can be deduced from the construction of the decomposition in terms of obtuse superbases. Numerically, we can check it by finding a subset of the offsets whose determinant equals $\\pm 1$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.672474Z",
     "iopub.status.busy": "2024-04-30T09:12:20.672361Z",
     "iopub.status.idle": "2024-04-30T09:12:20.674678Z",
     "shell.execute_reply": "2024-04-30T09:12:20.674435Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  1, -1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1,  1,  1,  1,  1,  1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1,  1,  1,  1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,  1, -1, -1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,  1,  1,  1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1,  1,  1,  1,  1,  1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1,  1, -1,  1, -1])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lp.det(offsets[:,0:2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.676084Z",
     "iopub.status.busy": "2024-04-30T09:12:20.675978Z",
     "iopub.status.idle": "2024-04-30T09:12:20.677938Z",
     "shell.execute_reply": "2024-04-30T09:12:20.677717Z"
    }
   },
   "outputs": [],
   "source": [
    "coefs,offsets = Selling.Decomposition(D3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.679336Z",
     "iopub.status.busy": "2024-04-30T09:12:20.679238Z",
     "iopub.status.idle": "2024-04-30T09:12:20.681346Z",
     "shell.execute_reply": "2024-04-30T09:12:20.681068Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lp.det(offsets[:,0:3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.4 Piecewise linearity\n",
    "\n",
    "Selling's coefficients depend in a piecewise linear manner on the decomposed tensor, since by Selling's formula they read $ - <b_i,D b_j>$ where $b_i,b_j$ are elements of a $D$-obtuse superbase $(b_0,\\cdots,b_d)$. This property is exploited, in some (somewhat sophisticated) numerical schemes, e.g. for the [Pucci](../Notebooks_NonDiv/NonlinearMonotoneSecond2D.ipynb) and [Monge Ampere](../Notebooks_NonDiv/MongeAmpere.ipynb) PDEs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.682784Z",
     "iopub.status.busy": "2024-04-30T09:12:20.682687Z",
     "iopub.status.idle": "2024-04-30T09:12:20.684652Z",
     "shell.execute_reply": "2024-04-30T09:12:20.684422Z"
    }
   },
   "outputs": [],
   "source": [
    "def Interpolate(a,b,T=np.linspace(0,1,100)):\n",
    "    return T, np.moveaxis(ad.array([(1-t)*a + t*b for t in T]),0,-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.686011Z",
     "iopub.status.busy": "2024-04-30T09:12:20.685917Z",
     "iopub.status.idle": "2024-04-30T09:12:20.689360Z",
     "shell.execute_reply": "2024-04-30T09:12:20.689122Z"
    }
   },
   "outputs": [],
   "source": [
    "np.random.seed(42)\n",
    "t,D2t = Interpolate(MakeRandomTensor(2),MakeRandomTensor(2))\n",
    "decomp = Selling.GatherByOffset(t,*Selling.Decomposition(D2t))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.690683Z",
     "iopub.status.busy": "2024-04-30T09:12:20.690607Z",
     "iopub.status.idle": "2024-04-30T09:12:20.756364Z",
     "shell.execute_reply": "2024-04-30T09:12:20.756105Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,4))\n",
    "for offset,(time,coef) in decomp.items(): plt.plot(time,coef)\n",
    "plt.legend(decomp.keys());"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.757733Z",
     "iopub.status.busy": "2024-04-30T09:12:20.757652Z",
     "iopub.status.idle": "2024-04-30T09:12:20.762220Z",
     "shell.execute_reply": "2024-04-30T09:12:20.761990Z"
    }
   },
   "outputs": [],
   "source": [
    "np.random.seed(1)\n",
    "t,D3t = Interpolate(MakeRandomTensor(3),MakeRandomTensor(3))\n",
    "decomp = Selling.GatherByOffset(t,*Selling.Decomposition(D3t))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.763615Z",
     "iopub.status.busy": "2024-04-30T09:12:20.763533Z",
     "iopub.status.idle": "2024-04-30T09:12:20.874529Z",
     "shell.execute_reply": "2024-04-30T09:12:20.874262Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,4)); plt.title(\"Coefficients of Selling's decomposition (d=3)\")\n",
    "for offset,(time,coef) in decomp.items(): plt.plot(time,coef)\n",
    "plt.legend(decomp.keys(),ncol=3)\n",
    "savefig(fig,\"Coefs_Sel3.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## 4. Smooth two-dimensional decomposition\n",
    "\n",
    "The coefficients of Selling's decomposition are piecewise linear, hence have Lipschitz regularity, but not better. In some applications it is preferable, at least from the theoretical standpoint, to define a decomposition whose coefficients have a *Lipschitz gradient*, or whose *square root is Lipschitz*. We describe such a construction in the following."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "### 4.1 Construction\n",
    "\n",
    "Two auxiliary functions are needed for our smooth variant of Selling's decomposition. The first one is a regularized substitude for the absolute value, smoothed within the interval $[-1,1]$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.876121Z",
     "iopub.status.busy": "2024-04-30T09:12:20.876019Z",
     "iopub.status.idle": "2024-04-30T09:12:20.878741Z",
     "shell.execute_reply": "2024-04-30T09:12:20.878502Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "ExportCode"
    ]
   },
   "outputs": [],
   "source": [
    "def sabs(x,order):\n",
    "    \"\"\"\n",
    "    Regularized absolute value. Guarantee : 0 <= result-|x| <= 1/2.\n",
    "    - order (0, 1, 2 or 3) : order of the last continuous derivative. \n",
    "    \"\"\"\n",
    "    x = np.abs(x) # Actually useless for this specific application\n",
    "    if order==0: return x # Continuous value\n",
    "    elif order==1: return np.where(x<=1, 0.5*(1+x**2), x) # Continuous derivative\n",
    "    elif order==2: return np.where(x<=1, (3+6*x**2-x**4)/8,x) # Continuous second order derivative\n",
    "    elif order==3: return np.where(x<=1, (5+15*x**2-5*x**4+x**6)/16,x) # Continuous second order derivative\n",
    "    else: raise ValueError(f\"Unsupported {order=} in sabs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.880195Z",
     "iopub.status.busy": "2024-04-30T09:12:20.880094Z",
     "iopub.status.idle": "2024-04-30T09:12:20.962872Z",
     "shell.execute_reply": "2024-04-30T09:12:20.962605Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=np.linspace(-2,2,100)\n",
    "plt.plot(x,sabs(x,order=0),label=\"abs\")\n",
    "plt.plot(x,sabs(x,order=1),label=\"sabs\")\n",
    "plt.plot(x,sabs(x,order=2),label=\"sabs2\")\n",
    "plt.plot(x,sabs(x,order=3),label=\"sabs3\")\n",
    "plt.title(\"Smoothed absolute value\")\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "The second auxiliary function is a regularized substitute for the median of three positive reals $\\rho_0,\\rho_1,\\rho_2$. In addition, the result is also defined in terms of two quantities denoted $s$ and $q$, that are chosen for their invariance under Selling's superbase operations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.964444Z",
     "iopub.status.busy": "2024-04-30T09:12:20.964338Z",
     "iopub.status.idle": "2024-04-30T09:12:20.966378Z",
     "shell.execute_reply": "2024-04-30T09:12:20.966105Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "ExportCode"
    ]
   },
   "outputs": [],
   "source": [
    "def smed(ρ0,ρ1,ρ2):\n",
    "    \"\"\"Regularized median (a.k.a. ρ1) assuming ρ0<=ρ1<=ρ2.\n",
    "    Guarantee : ρ1/(2*sqrt(2)) <= result < ρ1\"\"\"\n",
    "    s,q = ρ0*ρ1+ρ1*ρ2+ρ2*ρ0, (ρ2-ρ1)**2 # Invariant quantities under Selling superbase flip \n",
    "    return 0.5*s/np.sqrt(q+2*s) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:20.967743Z",
     "iopub.status.busy": "2024-04-30T09:12:20.967647Z",
     "iopub.status.idle": "2024-04-30T09:12:21.047654Z",
     "shell.execute_reply": "2024-04-30T09:12:21.047389Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = np.linspace(0,2*π,200)\n",
    "ρ0,ρ1,ρ2 = np.sort([1.5+np.cos(t),0.5*np.sin(t)**2,np.cos(3*t)+2],axis=0)\n",
    "plt.plot(t,ρ0, t,ρ1, t,ρ2, t,smed(ρ0,ρ1,ρ2))\n",
    "plt.title(\"Smoothed median\")\n",
    "plt.legend(['ρ0','ρ1','ρ2', 'smed']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Consider a positive definite matrix $D$, and a $D$-obtuse superbase $(v_0,v_1,v_2)$.\n",
    "Define the Selling weights $\\rho_i = -<e_{i-1},D e_{i+1}>$, with periodic indices, and offsets $e_i = v_i^\\perp$. Assume that $\\rho_0\\leq \\rho_1\\leq \\rho_2$, up to permuting the basis elements.\n",
    "\n",
    "Our regularized Selling decomposition takes the following form, with $m = \\mathrm{smed}(\\rho_0,\\rho_1,\\rho_2)$.\n",
    "$$\n",
    "    D = \\sum_{0 \\leq i \\leq 2} \\rho_i e_i e_i^\\top + \\frac 1 2 (m\\, \\mathrm{sabs}(\\rho_0/m)-\\rho_0)(e_0 e_0^\\top - 2 e_1 e_1^\\top - 2 e_2 e_2^\\top + (e_1-e_2)(e_1-e_2)^\\top).\n",
    "$$\n",
    "Note that the first term $\\sum_{0 \\leq i \\leq 2} \\rho_i e_i e_i^\\top$ is Selling's standard decomposition of $D$. The second term amounts to zero, since $e_0 e_0^\\top - 2 e_1 e_1^\\top - 2 e_2 e_2^\\top + (e_1-e_2)(e_1-e_2)^\\top = 0$, but it introduces the additional offset $e_1-e_2$ and modifies the weights in a smooth manner."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.049215Z",
     "iopub.status.busy": "2024-04-30T09:12:21.049107Z",
     "iopub.status.idle": "2024-04-30T09:12:21.052181Z",
     "shell.execute_reply": "2024-04-30T09:12:21.051940Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "ExportCode"
    ]
   },
   "outputs": [],
   "source": [
    "def smooth_decomp(D,order=3):\n",
    "    \"\"\"Smooth variant of Selling's two dimensional decomposition\"\"\"\n",
    "    v = np.moveaxis(Selling.ObtuseSuperbase(D),1,0)\n",
    "    ρ = np.array([-lp.dot_VAV(v[1],D,v[2]),-lp.dot_VAV(v[0],D,v[2]),-lp.dot_VAV(v[0],D,v[1])])\n",
    "    ord = np.argsort(ρ,axis=0) \n",
    "    v = np.take_along_axis(v,ord[:,None],axis=0); ρ=np.take_along_axis(ρ,ord,axis=0)\n",
    "\n",
    "    m = smed(*ρ)\n",
    "    w = np.maximum(0,m*sabs(ρ[0]/m,order)-ρ[0]) # Positive up to roundoff error (max for safety)\n",
    "    \n",
    "    return (ad.array([ρ[0]+w/2, ρ[1]-w, ρ[2]-w, w/2]),\n",
    "         lp.perp(np.moveaxis(ad.array([v[0],v[1],v[2],v[1]-v[2]]),0,1)).astype(int) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "### 4.2 Display of coefficients\n",
    "\n",
    "Recall that Selling's decomposition has piecewise linear coefficients."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.053574Z",
     "iopub.status.busy": "2024-04-30T09:12:21.053495Z",
     "iopub.status.idle": "2024-04-30T09:12:21.055655Z",
     "shell.execute_reply": "2024-04-30T09:12:21.055395Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "np.random.seed(42)\n",
    "t,D2t = Interpolate(MakeRandomTensor(2),MakeRandomTensor(2))\n",
    "if xp is not np: D2t = D2t.get() # Bug with cupy 9.0 and np.zeros_like below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.057067Z",
     "iopub.status.busy": "2024-04-30T09:12:21.056987Z",
     "iopub.status.idle": "2024-04-30T09:12:21.132357Z",
     "shell.execute_reply": "2024-04-30T09:12:21.132078Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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YWFiwfPlyhg0bRkxMDH379sXR0ZHIyEguX75MZGRkgZPFp3nllVcYMmQI8+fPJyIigq5du2JsbMylS5cwMzPjzTffzPO4gQMHsnHjRjp37szkyZNp3LgxGo2GBw8e8Mcff9CjRw969epVoFhq1aoFwA8//IClpSUmJiZ4e3tz5swZVqxYQc+ePfHx8UGSJHbs2MHjx49p167dU89nY2PDrFmz+OCDDxg6dCiDBg0iOjqaefPmYWJiwpw5cwoUX5YOHTrg5uZGt27dqF69OjqdDj8/P5YsWYKFhUV2EX8vLy8++ugjZs6cSUBAAB07dsTW1paIiAjOnTuHubk58+bNK1QMBVWzZk0GDRrEkiVLUKlUvPbaa/j7+7NkyRKsra3zLBGVZd++fYW6/ra2tkyfPp358+czevRo+vXrR0hICHPnzs3VTT1lyhS2b9/Oq6++ytSpU6lTpw46nY7g4GAOHz7M22+/TZMmTfL1fs3v56wo7dixA7VaTbt27fD392fWrFnUrVs3e4xtfmMq7LWuVKkSpqambNy4EV9fXywsLHBxcckxZjWLHNdHEIqcbFOdBKEE8fPzk4YNGyZ5eHhIRkZG2aVWZs+eLT169Ch7P61WK3366adS1apVJY1GI9nb20tvvPFGdlmUJx0/flzq0qWLZGdnJ2k0GsnV1VXq0qVLjpntLzrbPSumL774QqpVq5ZkZGQkWVtbS82aNZP27t2bvU9eM68zMjKkzz//XKpbt65kYmIiWVhYSNWrV5fGjRsn3blzJ3s/T09PqUuXLrleX17nXLZsmeTt7S2pVKrs2bs3b96UBg0aJFWqVEkyNTWVrK2tpcaNG0vr1q3Ldc68rFq1SqpTp072a+vRo0eOMkfPul552bx5szR48GCpSpUqkoWFhaTRaCQPDw9pyJAheZYe2rVrl9S6dWvJyspKMjY2ljw9PaW+fftml8ySpBef7f7fuLPeF09WDkhNTZWmTZsmOTo6SiYmJlLTpk2lM2fOSNbW1rlmaz/pRa6/TqeTFi1aJLm7u0tGRkZSnTp1pL179+b52hITE6UPP/xQqlatWvbPqnbt2tLUqVOl8PDw7P3y837N7+esZcuWUs2aNXPF/bT3LCBNmjQp+3nWz+3ChQtSt27dJAsLC8nS0lIaNGiQFBERkePY/MSU32v939nukqSvXFC9enVJo9HkeJ/k9d560euT1+8RQShOCkmSJHnSXkEQBOFFnD59mhYtWrBx40YGDx4sdzilzty5c5k3bx6RkZFirKQgFCPR7S4IglAKHDlyhDNnztCwYUNMTU25fPkyn3zyCVWqVKF3795yhycIgpBvIvkUBEEoBaysrDh8+DDLli0jISEBe3t7OnXqxKJFizAxMZE7PEEQhHwT3e6CIAiCIAhCsRGllgRBEARBEIRiI5JPQRAEQRAEodiI5FMQBEEQBEEoNqViwpFOpyMsLAxLS0sUCoXc4QiCIAiCIAj/IUkSCQkJuLi4PHPxiwIXmT9+/LjUtWtXqWLFihIg7dy585n7b9++XWrbtq1kb28vWVpaSk2bNpUOHjxYoDZDQkIkQDzEQzzEQzzEQzzEQzxK+COvhVeeVOA7n0lJSdStW5cRI0bQp0+f5+5/4sQJ2rVrx8KFC7GxsWHt2rV069aNs2fPUr9+/Xy1aWlpCUBISAhWVlYFDVkQBEEQBEEwsPj4eNzd3bPztqd5oVJLCoWCnTt30rNnzwIdV7NmTQYMGMDs2bPztX98fDzW1tbExcWJ5FMQBEEQBKEEym++VuwTjnQ6HQkJCdjZ2RV304IgCIIgCILMin3C0ZIlS0hKSqJ///5P3SctLY20tLTs5/Hx8cURmiAIgiAIgmBgxXrnc9OmTcydO5fNmzfj6Oj41P0WLVqEtbV19sPd3b0YoxQEQRAEQRAMpdjufG7evJlRo0axdetW2rZt+8x9Z8yYwbRp07KfZw1gFQRBEARByC+dTkd6errcYZQZGo0GlUr1wucpluRz06ZNjBw5kk2bNtGlS5fn7m9sbIyxsXExRCYIgiAIQlmUnp5OYGAgOp1O7lDKFBsbG5ydnV+o7nqBk8/ExETu3r2b/TwwMBA/Pz/s7Ozw8PBgxowZhIaGsn79ekCfeA4dOpQvv/ySpk2bEh4eDoCpqSnW1taFDlwQBEEQBCEvkiTx8OFDVCoV7u7uzy54LuSLJEkkJyfz6NEjACpWrFjocxU4+Tx//jytW7fOfp7VPT5s2DDWrVvHw4cPCQ4Ozv7377//nszMTCZNmsSkSZOyt2ftLwiCIAiCUJQyMzNJTk7GxcUFMzMzucMpM0xNTQF49OgRjo6Ohe6CL3Dy2apVK55VGvS/CeWxY8cK2oQgCIIgCEKhabVaAIyMjGSOpOzJSuYzMjIKnXyK+9CCIAiCIJRJLzIuUchbUVxTkXwKgiAIgiAIxabYi8wLgiAIQmmh00mEPk4hMCqJgMhEAqOSCIpOprG3HRNbVRJ31oQiFx0dja+vL+fOncPLy6tY2+7bty/NmzfPUe7SEETyKQiCIJR7sUnpBDyRYOqTzSSCopNIy8xdquf47UjSM3VMbVdVhmiFsmzRokV069YtR+I5efJkTp06xbVr1/D19cXPz6/A5/X392f27NlcuHCB+/fv88UXXzBlypQc+8yePZvWrVszevToZ67N/qJE8ikIgiCUC6kZWu5HJxMQmUhAdoKpTzZjkzOeepxGpcCzgjk+9uZ4O5iTqZVYfSqQL3+7g6WJmtGv+BTjqxDKspSUFFavXs3+/ftzbJckiZEjR3L27FmuXLlSqHMnJyfj4+NDv379mDp1ap771KlTBy8vLzZu3MiECRMK1U5+iORTEARBKDN0OomwuJTsO5eBUUnc+yfBDH2cwjOKtVDR2gQfB3O87c3xsbfA28GcSvYWuNiYoFblnCJha6bh88O3mf/rDSxN1Ax4ycPAr0woDw4cOIBaraZZs2Y5tn/11VcAREZGFjr5fOmll3jppZcAeP/995+6X/fu3dm0aZNIPgVBEAThSY+Ts7rJkwiMSsyRbObVTZ7F0liNj4M5Pg4W+iTzn2TT294cM6P8/0mc1LoyCamZfH8igPd3XMXcWE3XOi5F8dIEA5AkiZQMrSxtm2pU+R4bfOLECRo1amTgiJ6tcePGLFq0iLS0NIOtNimST0EQBKFESs3QEhzzbzd5VnIZGJVETNLT1+vWqBS425nhY29Bpaw7mf8km/YWRkUySUihUPB+p+okpGXy89lgpm72w9xYTetqji98bqHopWRoqTH7kCxtX/+oQ76/2AQFBeHiIu+XGFdXV9LS0ggPD8fT09MgbYjkUxAEQZCNTifxMD41e+xlQGRS9sSf53WTO1uZZN+99HGw0I/JtDfHzdY0Vze5ISgUCj7uUYvE1Ez2XA5j/E8X+HlMExp62hm8baFsSklJwcTERNYYslYxSk5ONlgbIvkUBEEQDC4uOYN7UYkERiYRUIhucn3XuEWObnJzY/n/hKmUCpb0r0tSWia/3XzE21suc3DKq5hoCrfyi2AYphoV1z/qIFvb+WVvb09sbKwBo3m+mJgYABwcHAzWhvyfXEEQBKFMSMvMmk2ecyZ5QD66yT3szPB+ops8q6u8qLrJDUmjUrJsYD3aLj1OUHQyK/64y7T21eQOS3iCQqEo0JheudSvX58NGzbIGsO1a9dwc3PD3t7eYG2U/J+EIAiCUGLodBLh8anZyeW9rEQzKpHQ2BR0+ewmz+4ut7cotm5yQ7I00TC3W00mbLzIt8fv0b2eC5UdLeUOSyhlOnTowIwZM4iNjcXW1jZ7+927d0lMTCQ8PJyUlJTsOp81atTI9/r16enpXL9+Pfv/Q0ND8fPzw8LCgsqVK2fvd/LkSdq3b190LyoPCkl61oiakiE+Ph5ra2vi4uIMWvRUEARB0ItLychVcD0gKomgqKRnzhq2MFbnSCy9Hcyzx2KWhG5yQ5IkiVE/nuf3m49o4m3HL2Oblvi7tmVVamoqgYGBeHt7yz6GsqCaNWvG8OHDGTduXPa2Vq1acfz48Vz7BgYGZhejVygUrF27luHDh+d53qCgILy9vXNtb9myJceOHQP0183JyYlDhw7RtGnTPM/zrGub33ytbP8mEARBEJ4qLVNLSEwy9yJzlyyKfkY3uVqpwKOCfjb5v3Ux9QXYHSyMy23CpVAomNe9JqfvRXE2MIZtFx7Qr5G73GEJpcysWbOYPn06Y8aMQanU9whkJYdPExQUhFqtpkWLFk/dx8vLi+fdb1y9ejVNmjR5auJZVETyKQiCUIZJkr6bPOvO5ZMTfkJikp/ZTe5kZZzj7qU+0bTAvQx0kxuKu50ZU9pW5ZMDN1m4/wZtfJ2wM89ft6ggAHTu3Jk7d+4QGhqKu3v+vrwcPHiQsWPHUqVKlRdqW6PRsHz58hc6R36IbndBEIQyID41I/vu5ZOJZmABusmzJvmUl25yQ8nQ6ui2/BQ3wxPo19CNz/rVlTukcqc0d7uXdKLbXSgdMtPBfwfc+wNMrMDCSf+wdAYLR7CrBMYWckcpCCVeeqYuu+j6k6WKAqISiUp8Tje5ndkTSabFP2MyzXGwLL/d5IaiUSlZ0Ks2fb87zdYLD+jT0I2mPhXkDksQSgyRfAqGkxQN59fA3yshMeLp+xlbQ781ULlt8cUmCCXUi3STO1oa/5tc2v87o9zdzgyN6CYvVg09bRnU2IOfzwYzc+dV9k9+BWO1qP0pCCCST8EQHt2Ev1bAlc2QmarfZuEM9V/X/39CBCSG6xPSuFBIiYGN/aH7V1D/DfniFoRiFJ+akd0t/t/lI5/VTW5upPpnDOa/k30qOVjgZW+OhegmL1He61Cdw/7h3ItM4ofjAbzZ5sXG4wlCWSF+UwlFQ5Lg7m/w1zdw7/d/t1esB80mQY2eoM5j0H1mOuyeBFe36P/7OARavQ+iG1AoA/7bTf5kyaKoxLSnHqd6spv8iXXJKzmIbvLSxNpMw6yuNZj8ix/L/7hLt7oueNmbyx2WIMhOJJ/Ci8lIgcu/wF/fQtStfzYqoHoXfdLp0ezZiaTaCHr/ADbucHIJHP8E4h5At2Wg0hTHKxCEFyJJEhHxadl3L59c2SckNgXtM/rJHSyNs2eR+9jrE0xvB3M8RDd5mdG9rgtbzz/g1N0oZu2+xvqRjcWXB6HcE8mnUDjxD/VjOc+v1XebAxhZQoMh0Hgs2OUuZPtUCgW0mQ3W7vDrNPDbAAlh0O9H/QQlQSgBElIzcty5fPJuZnL687vJve3/vXuZtXykpYn4glXWKRQK5vesRftlJzh5J4o9l8PoUc9V7rAEQVYi+RQKJuwSnFmhn72uy9Rvs/GEJuP14zVfJFlsNAKsXGDrcH3X/drO8PpWsKpYJKELwvNkdZPrk8rEJxLNgnWTez8xFtNRdJOXe1725rzZujJLjtzm4303aFXVEWsz8cVDKL9E8ik8n04LN3/Vd60Hn/53u0dzaDYRqnUGZRHN4qzaAYb/Cj/3h4irsKotvLENHH2L5vxCuSdJEo8S0rj333JFkYnP7Sa3tzDOLlHk88TdTA87M4zUoptceLqxLX3Y5RfKvcgkPj10k4W9assdklBCRUdH4+vry7lz57KXziwuffv2pXnz5kybNs2g7Ygi88LTpcbDpZ/g7HfwOFi/TamGWn2g6QRwqW+4tmMCYWNfiL6rL8U0cCN4v2K49oQyJ6ubPDAqiXv/JJiBUYkERiaR9IxucjMjFV4V/hmH+U/BdR8Hc7zszbES3eTCC/grIJqBP/wFwPYJzWnoaStzRGVXaS4yP336dGJjY1m9enX2tuDgYCZNmsTvv/+OqakpgwcP5vPPP8fIKP+rZ/n7+zN79mwuXLjA/fv3+eKLL5gyZUqOfa5cuULr1q0JDAx8ar4liswLhhEbBGe/h4s/QXqCfpupLTQaCS+NKZ5ucDtvGHUENg2CkL9gQ2/o+S3U7mv4toVSI0OrIyQmOUex9ayu8siE53eTe1Uw0yeY2euTW+BkJbrJBcNo6lOBvg3d2HbhATN3XmXvmy+LiWVCDikpKaxevZr9+/dnb9NqtXTp0gUHBwdOnTpFdHQ0w4YNQ5KkAi2FmZycjI+PD/369WPq1Kl57lOnTh28vLzYuHEjEyZMeOHX8zQi+RT0JAmCz8CZb+DWfpB0+u321fR3OesMACOz4o3JzA6G7oKd4+D6btg+CuJCoMUUUYqpHMnqJn+ye1yfaCYRHJNc4G5yHwdz3G1FN7kgjw86+/LbjQhuhiew5lQg41pWkjskoQQ5cOAAarWaZs2aZW87fPgw169fJyQkBBcXFwCWLFnC8OHDWbBgQb57hF966SVeeuklAN5///2n7te9e3c2bdokkk/BgDLTwX+nvij8Q79/t1dqA00nQqXXQCnjH2mNKfRdB4c/1NcQPTpXXwu082dFN85UKBES0zKzV/PJXt0nn93kWbPHsyb7+Nhb4O0gusmFksfO3IgZnX15d9sVlh29Q+faFXG3K+Yv9uWRJEFGsjxta8zyfcPkxIkTNGrUKMe2M2fOUKtWrezEE6BDhw6kpaVx4cIFWrduXaThNm7cmEWLFpGWloaxsXGRnjuLSD7Lq+QY/dKX51bqVxsCUJtA3YH6meslaYKPUgkdF+prgR6cAedXQ3wY9F0NRqJgc2mSu5v83zuZj57RTa5UgLud2T9LRlo8cTdTdJMLpU+/f7rezwXGMGePP6uHNRLvYUPLSIaFLs/fzxA+CMv336qgoKAcSSZAeHg4Tk5OObbZ2tpiZGREeHh4kYWZxdXVlbS0NMLDw/H09Czy84NIPsufyFv6u5yXf8m59GXj0dBwJJhXkDe+Z2k6QV+KacdYuH0A1nWFwVvAwkHuyIQnSJJEZELaE8tFJmYnm8ExyWQ+o5u8grnRvwXXn+gu97AzF93kQpmhUChY2KsWnb48ye83H3HwWjidaouScoJ+zGdeE6Ty+nIiSZJBvrSYmpoC+jGihiKSz/JAkuDeb/r6nPd++3d7xbrQdBLU7JX30pclUY0e+mR500AIuwir28Lr28G+styRlTuJaZkE/efuZVaSmZiW+dTjTDTK/9y9/LdkkbWp6CYXyofKjpaMb1mJ5b/fZe5ef16uYi8WHTAkjZn+DqRcbeeTvb09sbGxObY5Oztz9uzZHNtiY2PJyMjIdUe0KMTE6BeOcXAw3I0dkXyWZRkpcGWzvj5n5M1/Nv6z9GXTieDZvHRO3PFoop8Jv7GPfmb+6nYw6Bf9dqFIZWp1hMSm/Kfguj7RjIh/dje5m+0/RdefKFnkbW+Os5UJSmUpfN8JQhGb1Loyey6HcT86mSWHbzO3e025Qyq7FIpSMUyrfv36bNiwIce2Zs2asWDBAh4+fEjFivo75IcPH8bY2JiGDRsWeQzXrl3Dzc0Ne3v7Ij93FpF8lkUJ4fqxnOfXPLH0pQXUHwJNxhVs6cuSyr4yjDqqL0YfdhHWd4c+q8C3m9yRlTqSJBGZmPbPZJ9/Z5QHRCURHP3sbnJ7C6PsEkVe/ySalRzMcbczw1gtJoQJwrOYaFTM71mLIavPsf5MEH0auFHbzVrusAQZdejQgRkzZhAbG4utrb4ObPv27alRowZDhgzhs88+IyYmhunTpzNmzJgC1T5PT0/n+vXr2f8fGhqKn58fFhYWVK78b+/hyZMnad++fdG+sP8QRebLkjA//XjOaztAl6HfZuPxxNKXZfCXWnoSbBulHwOKAjp+Ak3Hyx1ViZSUlpk9ySdrVnngP/+fkJ9u8uwucv2dTO8K5mKJQEEoAm9tusSey2HUdrVm16QWqETPwAsrzUXmmzVrxvDhwxk3blz2tuDgYCZOnJiryPyTs9EVCgVr165l+PDheZ43KCgIb+/cN59atmzJsWPHAP11c3Jy4tChQzRt2jTP84gi84J+6ctbB/RJ5/0//93u0UzftV6tM6jK8I/ZyBwGbIAD7+pnwR98T18LtN3H8paIkkle3eRZiWaBusmzEkzRTS4IBvdhV1/+uPWIq6FxrD8TxIgWZaB3Sii0WbNmZd/ZVP7zd8zDw4N9+/Y99ZigoCDUajUtWrR46j5eXl48737j6tWradKkyVMTz6JShrOSMi41Hvw26pe+jA3Sb1Oq9ZOHmk4E1wayhlesVGrosgSs3eC3eXDma4h7AL2+B03p+sabHy/STW5nbpSr4LqPvTkeFUQ3uSDIxdHShPc6VufDXddYcvg2HWs5U9HaVO6wBJl07tyZO3fuEBoairu7e76OOXjwIGPHjqVKlSov1LZGoynQqkmFJbrdS5vY+/qlLy/9BGnx+m2mttBwBDQeoy9FVJ5d2Qq7JuiHHXg0g4E/61dKKoVepJs8e23yf2aRZ/2/6CYXhJJJp5Po891pLgU/pmNNZ74bUvQTScqT0tztXtKJbvfyQpIg+C/9Cj83f31i6cuq/yx9ObD4l74sqer0A0sn+OUN/XKhq9vDG9vA1kvuyPKUqdXxIDYl56o+/5QrCo9PfepxCgW42ZrmSi69HcypKLrJBaHUUSoVLOxVm67LT3HQP5zfbkTQxrfoy+gIQklQ4OTzxIkTfPbZZ1y4cIGHDx+yc+dOevbs+cxjjh8/zrRp0/D398fFxYV3332X8ePFpJDnykyH67v04znDLv27vdJr/yx92aZcjmt8Lu9XYdQh2NAXou/AqnYweLNsQxEkSSIqMT3HuuT3/im+HhyTTIb2+d3k3k8sG6kvum6GiUZ0kwtCWeJb0YrRL3vz/YkAZu/2p1mlCpgZiXtEQtlT4Hd1UlISdevWZcSIEfTp0+e5+wcGBtK5c2fGjBnDhg0b+PPPP5k4cSIODg75Or5cSo6BC2v15ZISHuq3qYyh7gB90lmSlr4sqRx9YfRR2NgPIq7Cui7Q70eoarjyEcnp+m7yJ4utZ43FTEh9eje5sVqZfffS+z/LR9qYlZLi/4IgFInJbauw78pDQh+n8OXRO8zoLH7fC2VPgZPPTp060alTp3zv/9133+Hh4cGyZcsA8PX15fz583z++eci+fyvyNtPLH2Zot9m4QQvjYFGI8DccAVfyySrijBiP2wZCgF/6FdF6roUGg4v9CkztTpCH6fkuXTkw7hnd5O72pjmKLaelXC6WJuKbnJBEAAwM1LzUY+ajPrxPKtOBdKzviu+Fcv5XAehzDH4/fwzZ87kKlbaoUMHVq9eTUZGBhpN7gkQaWlppKX9WxYmPj7e0GHKR5L0idGZFXD3yL/bnetAs6ylL42ffrzwbCZW8PpW2DtZXx1g72R4HAKvffjU1Z0kSSI6KT1Hcpk1qzw4Opl0re6pzdmZG+VILLNKFoluckEQ8quNrxMdazpz0D+cD3ZeZfv45uILqlCmGDz5DA8Pz7X2qJOTE5mZmURFRWUvFfWkRYsWMW/ePEOHJq+nLX1ZrTM0mwieLUrn0pclkUoDPb4Ba3c4/gmc/BziHpDc6QsCYzOyZ5AHPLFO+fO6ybNnkzuIbnJBEIrenO41OHknkkvBj9n0dzCvN/GUOyRBKDLFMpJZ8Z8kKqu603+3Z5kxYwbTpk3Lfh4fH5/vWlclXkI4/L1Kv/RlcrR+m5GFfgWiJuPAzkfe+MoYrU4iNDaFe1GJBGoGYusO3UMWo7ryCxcvXWVCxlQSyF0pIKubXL905L8F10U3uSAIxaGitSlvt6/GR/uu8+mBm7Sv4YyDpegFE8oGgyefzs7OhIeH59j26NEj1Go1FSpUyPMYY2PjHEtGlQkPL+u71q9t/3fpS2sPfcLZYEjZXPqymEiSRExSenaZontRidnliu7n6iavwy7lO3yj+ZKXVf5sV33EZxXmY+3shbe9fl1yb3sLPCuIbnJBEOQ1rLkXOy494FpoPPN/vc6XA+vLHZJQDKKjo/H19eXcuXN4eXkVa9t9+/alefPmOW4AGoLBk89mzZqxd+/eHNsOHz5Mo0aN8hzvWaY8belL9yb6WevVu5btpS+LWEq6lqDopFxjMQMiE4l/Rje5kVqJdwXzJ2aU1yFY+QrVfxtJ1aRgVqa/D69sBefKxfhqBEEQnk2lVLCoVx16fHOK3X5h9G3oxitVHOQOSzCwRYsW0a1btxyJ5+TJkzl16hTXrl3D19cXPz+/Ap935cqVrF+/nmvXrgHQsGFDFi5cSOPGjbP3mT17Nq1bt2b06NEGXdSnwJlPYmIid+/ezX4eGBiIn58fdnZ2eHh4MGPGDEJDQ1m/fj0A48eP5+uvv2batGmMGTOGM2fOsHr1ajZt2lR0r6KkSUuASxvh7Lc5l76s0VM/ntNVrFzxNFnd5AFPzCIP+OdOZthzZpO7WJtmj73U18XUzyx3sTFFlaub3B18ftPXAo26BWs7wYCfwKeVQV+fIAhCQdR2s2ZoMy/WnQ5i1q5rHJzyquiVKcNSUlJYvXo1+/fvz7FdkiRGjhzJ2bNnuXLlSqHOfezYMQYNGkTz5s0xMTFh8eLFtG/fHn9/f1xdXQGoU6cOXl5ebNy4kQkTJrzw63maAief58+fp3Xr1tnPs27NDhs2jHXr1vHw4UOCg4Oz/93b25v9+/czdepUvvnmG1xcXPjqq6/KZpml2Ptw7ge4uP7fpS9NbPRlkl4aA9ausoZXEvmFPObgtfDsO5m5u8lzsjbVZK/mk1UX08fBHK8K5gX/hWzjoS9G/8vr+jvTG/roJybVHfiCr0oQBKHovN2+KgeuPSQoOplv/rjL2+2ryR2SYCAHDhxArVbTrFmzHNu/+uorACIjIwudfG7cuDHH85UrV7Jt2zZ+++03hg4dmr29e/fubNq0qWQln61ateJZy8GvW7cu17aWLVty8eLFgjZVOkgShJyFM9/AzX3/Ln1ZoQo0HQ91B4GRubwxllB7LocxbbMfmbqc7ycjlRLPCmb/zCa3yDEW0868iGeTm9rCkJ2wczz474Cd4yAuBF6ZLqoNCIJQIliaaJjbrSYTNl7ku+P36FHPhcqOlnKHVapIkkRKVv3sYmaqNn3qBOv/OnHiBI0aNTJwRHrJyclkZGRgZ2eXY3vjxo1ZtGgRaWlpBpt/IwYcFpY2A/x36ddbf3LpS5/W+vqcYunLZ9p49j4f7rqGJEHLqg60qubwT5Jp8ZRucgNSG0Of1WDtBqe/gt/n62uBdlkqxuQKglAidKzlzGvVHfn95iNm7rzGL2Ob5juhESAlM4UmPzeRpe2zg89ipsldVSUvQUFBuLi4GDgivffffx9XV1fatm2bY7urqytpaWmEh4fj6WmYEl/iL2tBPW3pyzr99ZOInGrIG18psOLYXRYfvAXAG009+Kh7LflLFymV0P5jfVf8gXfh4o/6n2/ftWBsIW9sgiCUewqFgnnda3LmXjRnA2PYduEB/RqVkRKEQraUlBRMTEwM3s7ixYvZtGkTx44dy9WeqakpoL8zaigi+cyvyNv6CUR+m/5d+tLcERqPgUYjxdKX+SBJEp8cvMn3xwMAmNS6EtPbVytZ394bjwErF9g2Cu4c1q8JP3gLWDo9/1hBEAQDcrczY0rbKiw6cJOF+2/Qxtep6IcilVGmalPODj4rW9v5ZW9vT2xsrAGjgc8//5yFCxdy9OhR6tSpk+vfY2JiAHBwMFxlBZF8PstTl76sDU0nQa3eYunLfNLqJD7cdY1N5/ST0T7oXJ2xr1aSOaqnqN4Fhu+Dn/vDQz9Y3RZe3w4OVeWOTBCEcm7ky97svBTKzfAEFu2/wWf96sodUqmgUCjy3fUtp/r167NhwwaDnf+zzz5j/vz5HDp06KljS69du4abmxv29oa7qSYGJeYlIwUu/AgrmsFPvf5JPBVQrQsM2wfjTkK9QSLxLICF+2+w6VwwSgV80rt2yU08s7g1glFH9CtOPQ6G1e3g/mm5oxIEoZzTqJQs6FUbhQK2XnjAXwHRcockFKEOHTrg7++f6+7n3bt38fPzIzw8nJSUFPz8/PDz8yM9PT3f5168eDEffvgha9aswcvLi/DwcMLDw0lMTMyx38mTJ2nfvn2RvJ6nEcnnf0XdgS9qwt63IPKGfunLJuPhzQsw6GfwfkXMgi6g0/eiWH0qEIBlA+szsLGHzBHlU4VK+gTU7SVIfQzre4L/TrmjEgShnGvoacugf36Pztx5lbRMrcwRCUWldu3aNGrUiC1btuTYPnr0aOrXr8/333/P7du3qV+/PvXr1ycsLCx7H4VCkWfFoSwrVqwgPT2dvn37UrFixezH559/nr1PamoqO3fuZMyYMUX+2p4kks//svMBY0uwdof282GqP3T6VJ+ICAWWkJrBO1v1NckGN/Gge93imcVXZMztYege/V1vbRpsHQ6nv9YPyRAEQZDJex2qY29hzL3IJH74Zxy9UDbMmjWLL7/8Ep3u35rXx44dQ5KkXI+sVZCCgoJQq9W0aNHiqecNCgrK8xxz587N3mf16tU0adKEpk2bGurlASL5zE2p0td9fMsPmr8JpjZyR1SqLfj1BqGPU3C3M+WDzr5yh1M4Rmb61Y8aj9U/PzwTDr6vXz5VEARBBtZmGmZ11f9OXf7HXYKikmSOSCgqnTt3Zty4cYSGhub7mIMHDzJ27FiqVKnyQm1rNBqWL1/+QufID4X0rIrxJUR8fDzW1tbExcUZdK1RoWj9fjOCkevOo1DApjFNaepTQe6QXowkwZmv4fCH+ufVu0KfVaDJ/0xGQRCEoiJJEkPXnOPknSheqWLP+pGNS1b1EBmlpqYSGBiIt7d3sZQuKk+edW3zm6+JO5+CQcQmpfPe9qsAjGzhXfoTT9CP9W3+JvRdAyoj/YpWP3aDJDHgXxCE4qdQKPi4Ry2M1EpO3oliz+Ww5x8kCCWASD4Fg5izx5/IhDQqOZjzTocytg5xrT4wZBeYWMODv/Uz4WPEmCtBEIqfl705b7auDMDH+64Tl5whc0SC8Hwi+RSK3K9XHrLnchgqpYIl/etholHJHVLR82qhnwlv7QEx92BVO3hwQe6oBEEoh8a29KGSgzlRiel8euim3OEIwnOJ5FMoUpEJaXy4S9/dPrFVJeq528gbkCE5VIPRR6BiXUiO0q+GdHO/3FEJglDOGKtVLOhVG4CfzwZz4b5hV8gRhBclkk+hyEiSxIwdV4lNzsC3ohVvvvZis+5KBUtnGL4fKrfVL7u6+XU4t1LuqARBKGea+lSgb0M3QF/7M0Ore84RgiAfkXwKRWbHxVCO3ohAo1KwtH9djNTl5O1lbAGDfoEGQ0HSwf7pcGQO6MQvf0EQis8HnX2xNdNwMzyBNf8s7CEIJVE5yQ4EQwt7nMLcPf4ATGlbFd+K5awklkoD3b6C1v+UYfpzGewYA5lpsoYlCEL5YWdulF1PednROzyITZY5IkHIm0g+hRcmSRLvbrtCQlom9T1sGPeqj9whyUOhgJbvQM/vQKmGa9tgQx9IeSx3ZIIglBN9G7rRxNuOlAwts3f7UwpKeQv/ER0djaOjI0FBQcXedt++fVm6dKnB2xHJp/DCNpwN5tTdKEw0Spb0q4taVc7fVvUGwetbwcgSgk7Cmg7wOETuqARBKAcUCgULetVGo1Lw+81HHLwWLndIQgEtWrSIbt26ZS+dCTB58mQaNmyIsbEx9erVK/S5t2/fTo0aNTA2NqZGjRrs3Lkzx7/Pnj2bBQsWEB8fX+g28qOcZwnCi7ofncTCX28A8F7H6vg4WMgcUQlR6TUYeQAsK0LkTVjVFh5ekTsqQRDKgcqOFoxvWQmAuXv9SUgVtT9Li5SUFFavXs3o0aNzbJckiZEjRzJgwIBCn/vMmTMMGDCAIUOGcPnyZYYMGUL//v05e/Zs9j516tTBy8uLjRs3Frqd/BDJp1BoWp3E9K2XScnQ0tTHjmHNvOQOqWRxrg2jj4JjDUgMh7Wd4O5vckclCEI5MKl1ZTwrmBERn8aSw7flDkfIpwMHDqBWq2nWrFmO7V999RWTJk3Cx6fww9qWLVtGu3btmDFjBtWrV2fGjBm0adOGZcuW5dive/fubNq0qdDt5IdIPoVCW3MqkL+DYjE3UvFZ37oolWJN4Vys3WDEAfB6BdIT4ef+cMmw3ygFQRBMNCrm96wFwPozQVx9ECdzRPKSJAldcrIsj4KMuz1x4gSNGjUyyDU4c+YM7du3z7GtQ4cOnD59Ose2xo0bc+7cOdLSDDdhVm2wMwtl2p2IBD47fAuAWV1r4G5nJnNEJZipDbyxA3ZPgqtbYPdEiAuBlu/pJykJgiAYwCtVHOhe14U9l8OYsfMKuya2KLdj8qWUFG41aChL29UuXkBhlr+/kUFBQbi4uBgkjvDwcJycnHJsc3JyIjw857hgV1dX0tLSCA8Px9PT0yCxlM93ofBCMrQ6pm25THqmjlbVHBjwkrvcIZV8aiPo/QO8PE3//Ngi2PM/0IqxWIIgGM6HXX2xMlFzLTSe9Wfuyx2O8BwpKSmYmJgY7PyK/9zwkCQp1zZTU1MAkpMNV6pL3PkUCmzFH/e4GhqHtamGT/vUyfXGFZ5CoYC2c8DGHX59Gy5tgPiH0P9HMLaUOzpBEMogR0sT3utUnZk7r7Hk8C061XamorWp3GEVO4WpKdUuXpCt7fyyt7cnNtYwy6M6Ozvnusv56NGjXHdDY2JiAHBwcDBIHCDufAoFdC00juW/3wHgox41cbIy3De0MqvRSBi4CTRmcO83/USk+IdyRyUIQhk16CUPGnjYkJSuZd6e63KHIwuFQoHSzEyWR0Fu0NSvX5/r1w3zM2rWrBlHjhzJse3w4cM0b948x7Zr167h5uaGvb29QeIAkXwKBZCWqWXaFj8ydRKdazvTva5hxqWUC9U6wvB9YO4A4VdhdTt4dEPuqARBKIOUSn3tT5VSwUH/cH67ESF3SMJTdOjQAX9//1x3P+/evYufnx/h4eGkpKTg5+eHn58f6enp+T735MmTOXz4MJ9++ik3b97k008/5ejRo0yZMiXHfidPnsw1MamoieRTyLcvjtzhdkQi9hZGfNyjluhuf1GuDWHUEahQWT8BaXUHCDwpd1SCIJRBvhWtGP2yNwCzd/uTnJ4pc0RCXmrXrk2jRo3YsmVLju2jR4+mfv36fP/999y+fZv69etTv359wsLCsvdRKBSsW7fuqedu3rw5v/zyC2vXrqVOnTqsW7eOzZs306RJk+x9UlNT2blzJ2PGjCny1/YkkXwK+XLhfgw/nLgHwMJetalgYSxzRGWEnbc+AXVvCmlxsKE3XN0md1SCIJRBk9tWwdXGlNDHKXx59I7c4QhPMWvWLL788kt0Ol32tmPHjiFJUq5H1ipIQUFBqNVqWrRo8cxz9+3bl5s3b5Kens6NGzfo3bt3jn9fvXo1TZo0oWnTpkX+up4kkk/huZLTM3l7y2V0EvRp4Eb7ms5yh1S2mNnB0F3g2x206bB9FJxaBmJNZkEQipCZkZqPetQEYNWpQK6HGXYJRaFwOnfuzLhx4wgNDc33MQcPHmTs2LFUqVLlhdrWaDQsX778hc6RHwqpINVPZRIfH4+1tTVxcXFYWVnJHU65M2f3NX48c5+K1iYcnPIq1qYauUMqm3Q6ODwT/lqhf95oFHT+DJQqeeMSBKFMmbDhAgeuhVPfw4bt45uXyQVCUlNTCQwMxNvb26Cli8qjZ13b/OZr4s6n8Ex/3o3ix39qw33ap45IPA1JqYSOi6DDIkAB51fD5jcg3XC11gRBKH/mdKuJhbGaS8GP+flcsNzhCOWQSD6Fp4pPzeCdrZcBeKOpB69WNVzNL+EJzSbqa3+qjOHWfvixKyRGyh2VIAhlhLO1CW+3rwrApwdv8ighVeaIhPJGJJ/CU3289zphcal42Jkxo5Ov3OGULzV6wLA9YGoLoRdgdVuIvid3VIIglBFDm3lR29WahNRM5u8TZd6E4iWSTyFPR69HsPXCAxQKWNK/LubGYjGsYufRVD8T3sYTYoNgVVsIOSd3VIIglAEqpYJFvWujVMCey2GcuC16V4TiI5JPIZfYpHTe33EVgDGv+PCSl53MEZVj9lVg9FFwqQ8pMfBjN7ixV+6oBKHcSr19m+CxYwn7YCYZT9RYLI1quVozrLkXALN2XyM1QytvQEK5IZJPIZdZu68RlZhGZUcLprWrKnc4goUjDP8VqnaEzFTYPATOfi93VIJQrkgZGUR9+y2BffqSdOIkcTt2cK9jJx4tWYo2IUHu8Art7fbVcLYy4X50Ml//flfucIRyQiSfQg57L4ex78pDVEoFS/vXxUQjyvyUCEbmMGCjfl14JDjwLhyaqS/PJAiCQaXeuEFg/wFEfvkVZGRg0aoVZi+9hJSeTvTKldxr34GYDRuRMjLkDrXALIzVzO1eA4DvT9zj7qPSm0gLpUehks8VK1Zk13dq2LAhJ08+e0nAjRs3UrduXczMzKhYsSIjRowgOjq6UAELhvMoPpVZu68BMKl1Zeq42cgbkJCTSg1dlkKbOfrnZ76GbSMgQ8xUFQRDkNLTifxqOYH9+pN24wYqa2tcPvsMt29X4LH+R9xWrMDI2xttbCwR8+cT0K07KVeuyB12gXWo6Uyb6o5kaCU+2HmNUlD+u0yLjo7G0dGRoKCgYm+7b9++LF261ODtFDj53Lx5M1OmTGHmzJlcunSJV155hU6dOhEcnHetsFOnTjF06FBGjRqFv78/W7du5e+//2b06NEvHLxQdCRJYsaOqzxOzqCmixVvvlZZ7pCEvCgU8Mo06L0KlBq4vgt+6gnJMXJHJghlSsrVawT26UvUihWQmYll+/b4/LoP625dUSgUKBQKLF9rjc+e3TjPmY3Kzo70oCCCx4wl7U7pWrpSoVAwr0dNTDUqzgXGsPXCA7lDKtcWLVpEt27dspfOvHz5MoMGDcLd3R1TU1N8fX358ssvC3xef39/+vTpg5eXFwqFgmXLluXaZ/bs2SxYsID4eMOuflXg5HPp0qWMGjWK0aNH4+vry7Jly3B3d+fbb7/Nc/+//voLLy8v3nrrLby9vXn55ZcZN24c58+ff+HghaKz9cIDfrv5CCOVkqX966FRiREZJVqdfjBkBxhbQ/AZWNMBYu/LHZUglHq6tDQeLVlK0MCBpN25g8rODtdlX+D21Zeo7e1z7a/QaLAdNIhKhw5iWrcuurg4gkePKXWTkdxszZjaTr8048L9N4hOTJM5ovIpJSWF1atX57hBd+HCBRwcHNiwYQP+/v7MnDmTGTNm8PXXXxfo3MnJyfj4+PDJJ5/g7Jz3Mtl16tTBy8uLjRs3vtDreJ4CZRjp6elcuHCB9u3b59jevn17Tp8+necxzZs358GDB+zfvx9JkoiIiGDbtm106dKl8FELRepBbDIf7b0OwLT2VanmbClzREK+eL8KIw+ClRtE3daXYgq7JHdUglBqpfj5Edi7D9ErV4JWi1Xnzvjs24tVx47PPVZlaYnbd99iVKkSmRERBI8eQ2ZsbDFEXXRGtPCmurMlj5MzWLj/ptzhlEsHDhxArVbTrFmz7G0jR47kq6++omXLlvj4+PDGG28wYsQIduzYUaBzv/TSS3z22WcMHDgQY2Pjp+7XvXt3Nm3aVOjXkB8FSj6joqLQarU4OTnl2O7k5ER4eHiexzRv3pyNGzcyYMAAjIyMcHZ2xsbG5pkL16elpREfH5/jIRiGTifx7rYrJKZl0sDDhjGv+MgdklAQTjVg9BFwqgVJj2BtZ7h9WO6oBKFU0aWmEvHpYoIGv076vXuo7O1x+3o5rkuXoLbLf6k5ta0tHqtWonZ2Jj0ggJDx49Ell57lcTUqJQt710ahgO0XH3DmXtmZmyFJEhlpWlkeBRlDe+LECRo1avTc/eLi4rArwHuzIBo3bsy5c+dISzPc3e9CVQ5XKBQ5nkuSlGtbluvXr/PWW28xe/ZsOnTowMOHD3nnnXcYP348q1evzvOYRYsWMW/evMKEJhTQT3/d5/S9aEw0Spb0r4dKmffPUSjBrFxgxAHYMhQC/oBNA6HrUmg4XO7IBKHESz5/nrCZM8m4r5+3YN2jO04zZqCysSnU+TQVK+KxehX3B79O6uUrPJg8BfcV36DQaIowasNp4GHL4MYebDwbzMxdVzkw+RWM1aW/6klmuo4fJh+Xpe2xX7ZEY5y/axgUFISLi8sz9zlz5gxbtmzh119/LYrwcnF1dSUtLY3w8HA8PT0N0kaB7nza29ujUqly3eV89OhRrruhWRYtWkSLFi145513qFOnDh06dGDFihWsWbOGhw8f5nnMjBkziIuLy36EhIQUJEwhnwKjklh0QL+s2oxOvnjbm8sckVBoJlbw+laoOxgkLeydDL99DGLWqiDkSZecTPj8BdwfMpSM+8GonZxw++5bXD79tNCJZxbjSpVw//47FKamJJ08SdgHM5FKUVm0dztWx97CmIDIJL4/HiB3OOVKSkoKJiYmT/13f39/evTowezZs2nXrp1BYjA1NQX0Y0QNpUB3Po2MjGjYsCFHjhyhV69e2duPHDlCjx498jwmOTkZtTpnMyqV/hvA025FGxsbP3M8gvDitDqJt7f4kZqho0XlCgxpaphvN0IxUmmg5wqwcYfjn8LJzyHuAXRfDmojuaMThBIj6a+zPPzwQzIe6Gd1W/ftg9N776GyLLrx7qb16uH25TJCJk4ifu9e1HZ2OL7/3lN7CUsSa1MNs7r6MvkXP77+4y7d6rqU+psTaiMlY79sKVvb+WVvb0/sU8YKX79+nddee40xY8bw4YcfFlV4ucTE6KunODg4GKyNAk9pnjZtGqtWrWLNmjXcuHGDqVOnEhwczPjx4wH9XcuhQ4dm79+tWzd27NjBt99+S0BAAH/++SdvvfUWjRs3fu6tZcFwVp4M4GLwYyyM1SzuWxel6G4vGxQKaP2BPuFUqODKL7CxL6TGyR2ZIMhOm5jEw7lzCR4+nIwHD1C7VMR91Spc5s8v0sQzi8Wrr+KycAEAMT/+SPSqVUXehqF0r+vCK1XsSc/UMWtX6a/9qVAo0BirZHkU5AtH/fr1uX79eq7t/v7+tG7dmmHDhrFgwYKivDS5XLt2DTc3N+zzqO5QVAqcfA4YMIBly5bx0UcfUa9ePU6cOMH+/fuzxwU8fPgwR83P4cOHs3TpUr7++mtq1apFv379qFatWoFnaQlF52Z4PEsP3wZgdrcauNqYyhyRUOQaDIXBm0FjDoHHYU0niAuVOypBkE3iqT8J6N6Nx79sBsBm0EB89uzF4uUWBm3Xunt3HN97D4DIJUt5vL10/O1TKBTM71kLY7WSU3ej2HO5dJWOKq06dOiAv79/jrufWYlnu3btmDZtGuHh4YSHhxMZGVmgc6enp+Pn54efnx/p6emEhobi5+fH3bs5l1U9efJkrqpGRU0hlYKvM/Hx8VhbWxMXF4eVlZXc4ZRq6Zk6eq34E/+weNpUd2TVsEalohtIKKQwP/i5PyRGgKWLflyocy25oxKEYqONjydi8WLitm0HQOPmRsX58zFv2qRY43j0+edEr1oNKhVuy5dj+VrrYm2/sL7+/Q6fH76NvYURv01rhbVZ6Zg4lZqaSmBgYPZqjKVJs2bNGD58OOPGjQNg7ty5eU7C9vT0zLEKkkKhYO3atQwfPjzP8wYFBeHt7Z1re8uWLTl27Bigv25OTk4cOnSIpk2b5nmeZ13b/OZropJ4OfP1H3fxD4vHxkzDot61ReJZ1rnUg1FHwL4aJITB2k4QcEzuqAShWCQeP05At+76xFOhwHbIEHz27C72xBPA4e23se7VC7RaQqdOJfnChWKPoTDGvlqJyo4WRCWm88lBUfuzOMyaNYsvv/wS3T+T1ObOnYskSbkeTyaeQUFBqNVqWrR4+p18Ly+vPM+TlXgCrF69miZNmjw18SwqIvksR648eMw3f+hvr3/coxaOVqXr26BQSLaeMOoQeLaAtHjY0Acu/yJ3VIJgMNrHjwl77z1Cxo0nMyICI09PPDf8hPPMD1CamckSk0KhoOLHH2HRqhVSWhohEyaSeuu2LLEUhJFayYKe+t6STeeCuXBfLOVraJ07d2bcuHGEhuZ/qNTBgwcZO3YsVapUeaG2NRrNM+uwFxXR7V5OpGZo6br8FHcfJdK1TkW+HtxA7pCE4paRCrvGg/9O/fPXPoRXpusnKQlCGZFw9CgP581DGxkFSiV2w4bh8NabKE1Lxth2XUoKwaNGk3LxImpHR7w2/YzG1VXusJ7rna2X2XrhAdWcLNn31sslfgnm0tztXtKJbnch35YcvsXdR4nYWxjzcQ8x5q9c0phAnzXQ/C3989/n6+uBajPljUsQikBmbCyh097mwf/eRBsZhZGPD14/b8TpvXdLTOIJoDQ1xf3bFRhXqUzmo0cEjxpNZkzJv5s4o7MvtmYabkUksPpUoNzhCKWcSD7LgXOBMaz655fFJ71rY2suaj6WW0oltP8YOn8OKODij/DLIEhLlDsyQSi0+IMHCejSlfj9+0GppMKYMXjv3IFpvXpyh5YnlbU17qtWoXapSHpQECHjxqNLSpI7rGeyMzfig86+ACw7epuQmNKzbKhQ8ojks4xLSstk+tbLSBL0a+hG2xp5r0QllDONx8CADaA2gTuHYV0XSIiQOypBKJDMqCgevDWZ0ClT0cbEYFylCl6bN+P49jSUJXyhEo2TEx6rVqGysSH16lUevPkWUnq63GE9U9+GbjTxtiM1Q8ecPf6lovZnaYixtCmKayqSzzJu0YEbBMck42pjyuxuNeQORyhJfLvCsH1gVgEe+sHqthBZ8idACIIkScTt3UtAl64kHD4MajX2EyfivX0bprVLz7AiYx8f3H/4Xr8M5+nThM34oEQvw6lQKFjQqzYalYLfbz7i4LXw5x8kk6yVFNNLeEJfGmUtu6nRFL7slphwVIaduB3J0DXnANg4ugktKhtutQKhFIu+p58BHxsIJjYw6BfwbCZ3VIKQp4yIR4TPm0fi778DYOzri8vCBZj4+socWeElnjxFyIQJkJmJ7ZAhOH0wo0SXwVt6+BZf/X4XJytjjk5riaVJyav9KUkSwcHBZGRk4OLiglIp7rW9KEmSSE5O5tGjR9jY2FCxYsVc++Q3XxPJZxkVl5JBhy9OEB6fyrBmnswTk4yEZ0mKgp8HQOh5UBlD7++hZi+5oxKEbJIkEbdzFxGffIIuPh40GhwmTqDC6NEoXuAOTEkRt3cvYe+8C4DDlCnYjx8nc0RPl5qhpeOyEwRFJzO8uRdzu9eUO6Q8paenExgYmF0vUygaNjY2ODs75/kFSSSf5dy0LX7suBiKt705+996BVMjldwhCSVdejJsHw23fgUU0GEBNJskd1SCQMbDhzycPYekkycBMKlVi4oLF2BStarMkRWtmB9/JGLRJwA4f/wRtv36yRzR0526E8Ubq8+iUMDuSS2o42Yjd0h50ul0ouu9CGk0muwhDXkRyWc5dsg/nHE/XUCpgK3jm9HQ007ukITSQqeFg+/DuR/0z5tM0CehSvHlRSh+kiTxeMtWHi1ejC4pCYWREfZv/o8KI0agUKvlDs8gHi1ZSvTKlaBU4vbVl1i2bSt3SE81+ZdL7PYLo5arFbsmtkBdwmt/CoYn6nyWU9GJaczceRXQL4smEk+hQJQq6LQY2n2sf372W9g6DDJS5I1LKHfSH4QSPHIk4XPmoEtKwrRePbx37cR+zJgym3gCOEybinWf3qDTETrtbZL//lvukJ7qwy41sDJRcy00nvVn7ssdjlCKiOSzDJEkiVm7rxGVmE41J0umtnuxZbaEckqhgBZvQd81oDKCG3vhx+6QFC13ZEI5IOl0xGzcSED37iSf+QuFiQmO77+H58YNGPv4yB2ewSkUCirOm4fFa68hpacTMnESqbduyR1WnhwsjXm/k36i15LDt3gYJ76kCvkjks8yZM/lMPZfDUetVLCkf12M1aKrVHgBtfrAkF1gYg0PzsHqdhATIHdUQhmWfv8+wcOGE/HxfKTkZMwaNcJn9y4qDB+O4hnjzMoahVqN69IlmDZsiC4hgeDRo0l/8EDusPI08CV3GnrakpSuZd6e63KHI5QSIvksIyLiU5m16xoAb7WpQi1Xa5kjEsoErxYw8jBYu0PMPVjVDh6clzsqoYyRtFpifvyRgB49Sf77bxRmZjh9+CEe63/EyNNT7vBkoTQxwX3FNxhXqYI2MorgUaPIjC55vQ9KpYIFvWqhVio46B/O0etisQrh+UTyWQZIksR7268Qn5pJHTdrJrSqJHdIQlniWB1GHQHnOpAcBeu6ws39ckcllBFpAYHcf2MIEYs+QUpNxaxpU3z27MbujddRlPPajFnLcGpcXMi4H0zI2HFoE0veMpzVna0Y9Yo3AHP2+JOcnilzREJJV74/2WXE5r9DOHYrEiO1kiX96qIRMw6FomZVEUbsh8ptITMFNr8O51bKHZVQiklaLdGrVxPYqxcply6hNDfHed48PNauwcjNTe7wSgyNkyPuq1ehsrUl1d+fB2/+D10JLB00uU0VXG1MCX2cwrKjd+QORyjhRJZSyoXEJPPxPv04m3c7VKOKk6XMEQlllrGlfvWj+kNA0sH+6XBkDogCzkIBpd29S9CgwTz67HOktDTMW7TAZ+8ebAf0L9Er+8jF2NtbvwynmRnJZ/7i4fvvl7hlOM2M1MzvqV/MZPWpQK6HxcsckVCSieSzFNPpJN7ZdpmkdC0vedkyooW33CEJZZ1KA92XQ6sP9M//XAY7xkBmmqxhCaWDlJFB1HffE9irN6lXrqC0tKTigvm4r1qJxsVF7vBKNNPatXFb/hVoNMTvP0DEgoWUtDLdras70rm2M1qdxMxdV9HpSlZ8Qskhks9S7MczQfwVEIOZkYrP+9VFpRR3DIRioFBAq/egxwpQquHaNv3a8CmP5Y5MKMFSb90iaMBAIpctQ8rIwKJlS3z27cWmTx9xtzOfLFq0wOWTRaBQELtxI9HffSd3SLnM6VYTC2M1l4If8/O5YLnDEUookXyWUvciE/nkwE0APujsi2cFc5kjEsqd+q/D4C1gZAlBJ2FNB3gcIndUQgkjpacTufxrAvv0JfX6dZTW1rgs/hS3775F4+Qkd3iljnWXLjh9oO95iPzyK2I3b5E5opycrEyY3l6/7OmnB2/yKCFV5oiEkkgkn6VQplbH21suk5ap45Uq9rzexEPukITyqnIbGHkALCtC5E1Y1RYeXpE7KqGESLnmT2C//kR98w1kZmLZri2V9u3Funt3cbfzBdgNeYMK48cBED5vHvGHD8scUU5DmnlRx82ahNRM5u+7IXc4Qgkkks9S6PsTAfiFPMbSRM2nfeqIX+KCvJxrw+ij4OALieGwthPc/U3uqAQZ6dLTebT0C4IGDCDt1i1Utra4Ll2C61dfoXZwkDu8MsFh8mRs+vUDnY6w6e+QdO6c3CFlUykVLOxVG6VCv/jJiduRcocklDAi+SxlbjyMZ9nR2wDM7VYTFxtTmSMSBMDaDUYeBK9XID0Rfu4PlzbKHZUgg5TLlwns1ZvoH34ArRarzp3w+XUfVp07iy/KRUihUOA8ZzYWbdsgpafzYOIkUm/elDusbLVcrRnW3AuAD3ddIzVDK29AQokiks9SJD1Tx7Qtl8nQSrT1daJ3A1e5QxKEf5nawBvboXZ/0GXC7olw7BMoYTNyBcPQpaYSsfgzggYNJv3ePVT29rgu/wrXpUtR29nJHV6ZpFCrcV2yBLNGjdAlJhI8ZgzpISVn3PXb7avhbGVCcEwyX/9+V+5whBJEJJ+lyPLf73DjYTy2ZhoW9a4t7iIIJY/aGHr/AC9P0z8/tgj2/A+0GfLGJRhU8sWLBPbsRcyaNaDTYdWtGz5792DVrp3coZV5SmNj3FZ8g3G1avplOEePLjHLcFoYq5nbvSYA35+4x91HCTJHJJQUIvksJfxCHrPi2D0AFvSqjYOlscwRCcJTKBTQdg50/QIUSri0AX4eAGniD09Zo0tOJnzhQu6//gbpQUGoHR1xW7EC188Wo7a1lTu8ckNlZYX7yh/QuLnpl+EcMxZtYqLcYQHQoaYTbX0dydBKfLDzWomrTSrIQySfpUBqhpZpW/zQ6iS613Whc+2KcockCM/XaCQM3AQaM7j3G6ztDAnhckclFJGkc+cI6NGT2PU/gSRh3bs3Pvv2Yvlaa7lDK5c0jo54rFqJys6O1OvXefC/N0vEMpwKhYK53WtiqlFxLjCGrRceyB2SUAKI5LMU+OzQLQIik3C0NOajHjXlDkcQ8q9aRxi+D8wdIPyKvhTTo5IzKUIoOG1iEuEffUTw0GFkhISgdnbGfeUPuCxcgMrKSu7wyjUjLy/cf/gBpZkZyX/9Rdi77yFp5Z/o42ZrxtR2VQBYtP8GMUnyJ8WCvETyWcL9FRDNmj8DAfi0Tx1szIxkjkgQCsi1IYw6AhUqQ1wIrGkPQafkjkoohKTTpwns3p3YnzcBYNO/Pz779mLxyisyRyZkMa1VE7evl4NGQ8LBg0QsWFAiurpHtPCmurMlsckZLNwvan+WdyL5LMES0zKZvvUykgQDX3KndXVHuUMShMKx89YnoO5NITUOfuoFV7fJHZWQT9qEBB7OmkXwyFFkhIWhcXXFY+0aKn40D5WFhdzhCf9h3rw5ros/1S/D+fMmolaskDskNColC3vXRqGAbRcecOZeyZgUJchDJJ8l2IJfb/AgNgVXG1NmdvGVOxxBeDFmdjB0F9ToAdp02D4KTi0TpZhKuMQTJwjo1p3HW/VfFmwHD8Znz27MmzWTOTLhWaw6dcLpw5kARC3/mthffpE5ImjgYZu9It/MXVdJy5R/SIAgD5F8llDHbj1i07lgAD7rVwdLE43MEQlCEdCYQt910HSS/vnRObB/OujEH6GSRhsXR9j7MwgZO47M8HA0Hh54rP8R59mzUJqbyx2ekA92r7+O/cQJAITP+4j4Q/Ivw/lOh+o4WBoTEJnE98cD5A5HkIlIPkuguOQM3tuuXx97RAsvmleylzkiQShCSiV0XAgdFgEK+HsVbB4C6clyRyb8I+H33wno2o24XbtAocBu2DB8du3EvHFjuUMTCsj+zTex6d8fJImw6dNJ+uusrPFYm2qY1bUGAF//cZfAqCRZ4xHkIZLPEmjOnmtExKfhY2/Oux2qyx2OIBhGs4nQ/0dQGcOtX+HHrpAo1oCWU2ZsLKHT3+HBxElkRkZi5O2N58aNOM14H6WZmdzhCYWQtQynZbt2SBkZPJg0idTr12WNqVudirxSxZ70TB2zdonan+WRSD5LmANXH7LLLwylAj7vXxdTI5XcIQmC4dToAcP2gKkthF6A1e0g+p7cUZVL8YcOE9C1G/H79oFSSYXRo/DeuQOzBvXlDk14QQqVCpfPP8OscWN0SUkEjx1HenCwfPEoFMzvWQtjtZJTd6PY7RcmWyyCPETyWYJEJaYxc9c1AMa3rEQDD7FCiFAOeDTVz4S38YTYQH0CGvK33FGVG5nR0TyYPIXQyZPRRkdjVLkSXr9swnH6dJQmJnKHJxQRpbExbt98jXH16mijoggeNZrMSPl6GjwrmPPma5UBmP/rdeKSxRK85YlIPksISZL4YMdVYpLSqe5syeS2VeQOSRCKj30VGH0UXOpDcrS+C/7GPrmjKtMkSSJu368EdOlKwqFDoFJRYcJ4vHfswLROHbnDEwxAZWmJx8of0Li7kxESQvDYcWgT5Fv2duyrlajiaEFUYjqfHBSLTxhCUlxaiRzWUKjkc8WKFXh7e2NiYkLDhg05efLkM/dPS0tj5syZeHp6YmxsTKVKlVizZk2hAi6rdvmFcvh6BBqVgqX962GsFt3tQjlj4QjDf4UqHSAzFTa/AWd/kDuqMinj0SMe/O9NwqZPR/v4McbVq+O9dQuOkyejNBILWZRlagcHPFavQlWhAmk3bvBg0v/QpaXJEouRWl/7E2DTuWAu3I+RJY6y6uHdx2z66CwXD92XO5RcCpx8bt68mSlTpjBz5kwuXbrEK6+8QqdOnQh+xviR/v3789tvv7F69Wpu3brFpk2bqF5dTKTJ8jAuhdm7/QGY3KYKNVzEEnVCOWVkDgN/hoYjAAkOvAOHPwSdTu7IygRJkni8axcB3bqT+NtvoNFg/+b/8N6yGZMaNeQOTygmRh4eeKz8AaW5OcnnzhE2/R3ZluF8ycuO/o3cAPhgxzUytOKzXhTuXnjE7mV+pCVlEnQlCm0Ju64KqYD3Y5s0aUKDBg349ttvs7f5+vrSs2dPFi1alGv/gwcPMnDgQAICArCzsytUkPHx8VhbWxMXF4dVGVs7WJIkhq39mxO3I6nrZs32Cc1Rq8RoCKGckyQ49QX8Nk//vGZv6PktaMQYxMLKCA/n4Zw5JB0/AYBJzZpUXLgQk2pVZY5MkEvSX38RMmYsUkYGNgMG4Dx3DgqFotjjiE1Kp83S48QkpfNex+pMaFWp2GMoS/yOBvPn9rsggXdde9qNqommmCYv5zdfK1CWk56ezoULF2jfvn2O7e3bt+f06dN5HrNnzx4aNWrE4sWLcXV1pWrVqkyfPp2UlJSntpOWlkZ8fHyOR1n187lgTtyOxFitZEn/eiLxFAQAhQJemQa9V4JSA/47YENvSBbdcgUlSRKxW7cS0LUbScdPoNBocJg6Fa/Nv4jEs5wzb9oUl88+A4WCx5s3E7X8a1nisDU34oPO+lX8vvztNiExouZvYeh0Eie33ObPbfrEs3YrNzqOq11siWdBFCjTiYqKQqvV4uTklGO7k5MT4eHheR4TEBDAqVOnuHbtGjt37mTZsmVs27aNSZMmPbWdRYsWYW1tnf1wd3cvSJilRnB0Mgt+vQHAux2rU9lRrJEsCDnU6Q9vbAdjK7j/J6zpALElb/xSSZURGkrIqNGEz5qNLjERk7p18N65A/txY1Go1XKHJ5QAVh074Dx7FgBRK1YQ8/PPssTRp4ErTX3sSM3QMXu3qP1ZUJnpWg6tvMaV3x8A0Lx3ZV4ZUAWlsvjvZOdHoW6z/fe2vCRJT71Vr9PpUCgUbNy4kcaNG9O5c2eWLl3KunXrnnr3c8aMGcTFxWU/QkJCChNmiabTSUzfepnkdC1NvO0Y0dxL7pAEoWTyaQkjD4GVK0Td1pdiCvOTO6oSTdLpiN20iYBu3Uk6fRqFsTGO776L188/Y1y5stzhCSWM7aBB2P9zQyji4/nEHzxY7DHoa3/WRqNS8MetSA5cy/uGlpBbSmI6u5f5EXApEqVaQfvRNanf3kOWIRT5VaDk097eHpVKlesu56NHj3LdDc1SsWJFXF1dsba2zt7m6+uLJEk8ePAgz2OMjY2xsrLK8Shr1vwZyLmgGMyNVHzer26J/XYiCCWCUw19KSanWpAYAWs7w50jckdVIqWHhBA8YiTh8z5Cl5yMacOGeO/aSYWRI1CoSl73m1Ay2P9vEjYDB+iX4XznXZL++qvYY6jsaMGEVvovR3P3+BOfKmp/Pk9cZDLbF18gPCAOYzM1PSbXo0qjvPOxkqRAyaeRkRENGzbkyJGcv/SPHDlC8+bN8zymRYsWhIWFkZiYmL3t9u3bKJVK3NzcChFy6Xf3UQKLD90C4MOuNXC3E8vWCcJzWbnAiAPg0woykuDnAXDhR7mjKjEknY6Y9T8R0L0HyWfPojA1xemDGXj+tB5jb2+5wxNKOIVCgfOsWVh26KBfhnPiJFL8/Ys9jomtKuFtb86jhDSW/PN3UshbRGA82xdfIO5RChZ2xvSe3hCXKqVjcZoCd7tPmzaNVatWsWbNGm7cuMHUqVMJDg5m/PjxgL7LfOjQodn7Dx48mAoVKjBixAiuX7/OiRMneOeddxg5ciSmpqZF90pKiUytjre3XCY9U0fLqg4MfKlsjmcVBIMwsYLBW6HuYJC0sPct+H2BfnZ8OZYWGMj9IUOJWLgQKSUFs8aN8dm9C7uhQ1EoxSRGIX8UKhUuny3GrEkTdMnJhIwdR/r94h1jbaJR8XGPWgCs/+s+l0MeF2v7pUXglSh2Lb1ISkIG9u4W9H2vEXYu5nKHlW8F/q00YMAAli1bxkcffUS9evU4ceIE+/fvx9PTE4CHDx/mqPlpYWHBkSNHePz4MY0aNeL111+nW7dufPXVV0X3KkqRb4/d4/KDOKxM1Hzap06JHpMhCCWS2gh6roCW7+mfn1gMuyZAZrq8cclA0mqJXr2GwJ69SLlwAaWZGc5zZuOxbi1GHh5yhyeUQkojI/0ynDV80UZHEzxqNBmPHhVrDC9XsadnPRckCT7YeZXMElajUm7Xjj/gwLdXyMzQ4VHTjl5vN8Dc2ljusAqkwHU+5VBW6nz6h8XR4+s/ydRJLBtQj571XeUOSRBKt4vrYe8U/V1Qn1bQfz2YWD/vqDIh7e5dwmbOJPXyFQDMmzen4scfoXEVv1eEF5cZFUXQ4NfJCA7GuHp1PH9aj8rSstjaj0xIo82SY8SnZjKraw1GvSyGjkg6ib923+PiIf0NPt8WFWk5uBqqElSi0SB1PoXCS8vUMm3zZTJ1Ep1qOdOjnovcIQlC6ddgKAzeDBpzCDimn4gUFyp3VAYlZWYS9f0PBPbqTerlKygtLKg4/2PcV68SiadQZNT29vplOO3tSbt5kwcTJxXrMpwOlsa830lf+3PJ4VuEPX56bfDyQJuh48ja69mJZ+Nu3rR+o3qJSjwLonRGXQotO3qHWxEJVDA3Yn7PWqK7XRCKSpV2MGI/WDhBxDVY1RYiin+iRHFIvXWboAEDifziC6SMDMxbvorPvr3Y9O0rfqcIRc7I3V2/DKeFBcl//03Y9OnFugznwJfcaehpS3K6lnl7y+ZnOj/SkjPYu9yPO39HoFQqaDPMl5e6eJfqz7xIPovBhfuxfH/8HgALe9emgkXpGpshCCWeSz0YdQTsq0FCGKzpqL8TWkZIGRlEfvMNgX37kurvj9LKioqfLML9u+/QODvLHZ5Qhpn4+uL2zTcojIxIOHKU8Lnziq0AvFKpYEGvWqiVCg75R3DkekSxtFuSJMSksv2zi4TefozGREXX/9WlerOKcof1wkTyaWAp6Vqmb72MToLe9V3pUFP8oRAEg7D1hFGHwLMFpMXDhr5w+Re5o3phqdevE9ivv37pw4wMLNq00d/t7NmzVN/5EEoP8yaNcfn8M1Aqebx1K5HFOGG4urMVo1/xAWDO7mskpWUWW9tyiwxJYNun54l9mIS5tRG9pzfAvYad3GEVCZF8GtinB28SGJWEs5UJc7rVlDscQSjbTG3hjR1QszfoMmDnODjxeaksxaRLT+fRsmUE9utP2s2bqGxscFnyOW5fL0fj6Ch3eEI5Y9W+Pc5z5gAQ/e13xPy0odjantymCm62poTFpbLs6O1ia1dOwdej2fn5RZLj0rFzMafPe42wdyu+CV+GJpJPAzp9N4p1p4MA+LRvHazNNPIGJAjlgcYE+qyG5m/pn//+MeybAtrSc8ck5epVgvr0Ifq770GrxbJjR3x+3Yd1ly7ibqcgG9sB/XGYrP9cRSxcSPz+/cXSrqnRv7U/1/wZxPWw+GJpVy43Tj/k16+vkJGmxbWaDb2nN8DSzkTusIqUSD4NJCE1g3e26UugvN7Eg5ZVHWSOSBDKEaUS2n8MnT8HFHBhHfwyGNISn3ekrHRpaTz6/HOCBgwk7c5dVBUq4Prll7gt+wJ1hQpyhycIVBg/HtvBg0GSCH3vfRL//LNY2m1d3ZHOtZ3R6iQ+2HkVra709WY8jyRJnNsXyO/rb6DTSVRt7ES3/9XDuAzeuBLJp4HM33eD0McpuNuZ8kFnX7nDEYTyqfEYGLgR1KZw5xCs6wKJxVswO7+SL14isFdvoletBp0Oq65d8dm3F6sO7eUOTRCyKRQKnGZ+gGWnjpCRwYM33yLl6rViaXtOt5pYGKvxC3nMz+eCn39AKaLV6vjjp5v8vS8QgAYdPWk7ogYqTdlM08rmq5LZ7zcj2Hw+BIUCPu9bF3NjtdwhCUL5Vb0LDNsLZhXgoZ++FFPUHbmjyqZLSSFi0Sfcf/110gMCUDnY4/bN17h+/hlq29KxTrNQvihUKlw+/RSzZk2RkpMJGTuWtMBAg7frZGXC9PZVAVh88CaPElIN3mZxSE/NZP83V7hx+iEKBbQcXI1mPSuV6SE2IvksYo+T03l/+1UARrXwpomP6CoTBNm5v6QvxWTnA4/vw+p2cP+M3FGRdO4cAT16EvPjjyBJWPfsSaV9+7Bs00bu0AThmZRGRrgt/xqTmjXRxsYSMmo0GRGG71UY0syLOm7WJKRm8vG+GwZvz9CSHqexc8lFgq/HoDZS0nlCHWq9WvYXixDJZxGbtdufRwlpVHIwZ3qHanKHIwhClgqV9Amo20uQEgvre4D/TllC0SUlEf7RxwQPHUZGcDBqJyfcv/8Ol08WobIuH8uDCqWfysIc9x++R+PpQUZYGCFjxqCNN+xkIJVSwcJetVEqYO/lME7cjjRoe4YUHZbItsXniQpJxNRSQ89pDfCqYy93WMVCJJ9FaN+VMPZeDkOlVLC0fz1MNCq5QxIE4Unm9jB0D1TrAto02DoCznxTrCEknTlDQPcexP78MwDWffvgs28vFi1bFmscglAU1BUq4LF6NSoHe9Ju3yZkwkR0qYbtDq/las3w5vq13j/cdY3UjOJbdamohN6KZcdnF0mMScPGyYw+7zbCyevpa6GXNSL5LCKPElKZtUs/6HpSq0rUdbeRNyBBEPJmZAYDfoLGYwEJDn0AB94HnWH/gGkTE3k4ew7BI0aSERqK2qUi7qtX4TJ/PirLslO/Tyh/jNzc8Fi5EqWFBSkXLhA67W2kTMOWNpvWvioVrU0Ijklm+e8lZwx3ftz5O4I9y/1IT8mkYiVr+rzTEGsHU7nDKlYi+SwCkiTxwY5rxCZnUKOiFf97rYrcIQmC8CxKFXRaDO0+1j8/+y1sHQYZKQZpLvHkKQK6defxli0A2A4ehM+evVi0aGGQ9gShuJlUr477tytQGBmR+PvvPJw716DLcFoYq7MXbvnhRAB3IhIM1lZRkSSJi4fuc3i1P7pMiUr1Heg+uR4mFmWvlNLziOSzCGy/GMrRGxFoVAqWDqiLkVpcVkEo8RQKaPEW9F0DKiO4sVc/DjQpusia0MbHE/bBTELGjCHz4UM07u54/PgjzrNno7IwL7J2BKEkMHvpJVyXLgGlkrht24lc9qVB2+tQ04m2vo5kaCVm7ryGrgTX/tTpJE78cpszO+8BULeNOx3G1EJtVD6H54ks6QWFPk5h3h5/AKa0rUp15/IzZkMQyoRafWDILjCxhpCz+pnwMS9eNibhjz8I6NqNuB07QKHAdugQfHbvwrxJ4xePWRBKKMu2bXGeNxeA6O+/J2b9eoO1pVAomNu9JqYaFeeCYth24YHB2noRGelaDnx3lWvHQ0EBL/erwsv9qqBQlt1SSs8jks8XoNNJvLftCglpmdT3sGHcqz5yhyQIQmF4tYCRh8HaHWLu6WuBhl4o1Km0jx8T+u67PJgwkcxHjzDy8sJz4wacP/gApZlZEQcuCCWPbb9+OEyZAkDEwkXE7fvVYG252ZoxtZ1+qNvCAzeITkwzWFuFkRyfzq6llwi6EoVKraTD6FrUbeMud1iyE8nnC9h49j6n7kZholGypF9d1CpxOQWh1HKsDqOPgnMdSI6CdV3h1sECnSL+yBHude1G/J69oFRiN3Ik3rt2YtaggYGCFoSSqcK4sdgOGQJA2IwZJJ4y3DKcI1p441vRisfJGSzcf9Ng7RTU44hkti8+z6OgeIzN1fSYUo/KDR3lDqtEENlSIQVFJWW/yd/vWB0fBwuZIxIE4YVZOsOI/VC5LWQkwy+D4O/Vzz0sMyaGB1OnEvrmW2ijojCqXAmvTT/j9O47KE1MiiFwQShZFAoFTjPex6pLF/0ynG+9RcqVKwZpS6NSsrBXLRQK2H7xAWfuFd247cIKD4hj++ILxEelYmVvQp93GlKxso3cYZUYIvksBK1OYvrWy6RkaGnmU4GhzbzkDkkQhKJibAmDfoH6Q0DSwa/T4Ohc0Oly7SpJEvH79xPQpSsJBw6CSkWFcePw3rED07p1iz92QShBFEolLosWYt6ixT/LcI4jLcAwy3DW97Dl9SYeAMzcdZW0TPlqfwb4RbLri0ukJmXg6GlJn3cbYessJhg+SSSfhbDqZADn78diYazms351UJbjQcOCUCapNNB9ObT6QP/81BewcxxkpmfvkhkZSehbbxE67W20sbEYV6uG15bNOE6dgtLISKbABaFkURgZ4fbVl5jUro328WOCR48iIyLCIG2906E6DpbGBEQm8d2xAIO08TxX/gjhwPdX0Wbo8KpdgZ7TGmBmJX4f/JdIPgvodkQCSw7fBmB21xq42YoJBIJQJikU0Oo96LEClGq4ugU29EZKjiVuzx7ude1GwpGjoFZj/7//4b11C6Y1a8odtSCUOEpzc9y//w4jLy8ywx4SMnoM2ri4Im/H2lTDrK41APjm2F0Co5KKvI2nkXQSf267w8nNd0CCmq+60ml8bTTG5bOU0vOI5LMAMrQ6pm3xI12r47XqjvRr5CZ3SIIgGFr912HwFjCyJOP6nzzo/Sph776HLi4O4xq+eG/bisP/JqEQdzsF4anUdna4r1qF2tGRtDt39MtwphT9og7d6lTklSr2pGfq+HDXVYMWus+SmaHl8Gp//I6GANC0pw8tB1VFKSYhP5W4MgXwzR93uRYaj7Wphk9610ahEN3tglAeSJVe47HzOwQcdCIxKBOFUsJh1EC8N2/GpHp1ucMThFLByM0V95UrUVpZkXLxIqFTpxX5MpwKhYL5PWthrFby591odvuFFen5/ys1KYM9X/px98IjlCoFbUfUoGFHL5EfPIdIPvPp6oM4vv79LgAf96yFo5WYwSoI5UFGWBghY8bycPF36NIVmDip8O4QiX3GShT3T8gdniCUKibVquqX4TQ2JvHYMR7OnlPkdyc9K5jzVht97c/5v14nLjmjSM+fJT4qhR2fXeDh3TiMTNV0e6se1Zo4G6StskYkn/mQmqFl2hY/MnUSXWpXpFudinKHJAiCgUmSROwvmwno1p2kU6dQGBnh+M50vPYdw7huM0hPgJ/7w6UNcocqCKWKWcOGuH6xFFQq4nbsIHLp0iJvY8wrPlRxtCAqMZ1PDhZ97c9H9+PZtvgCseHJWNga03t6A9yq2RZ5O2WVSD7z4Ysjt7nzKBF7C2M+7llL3E4XhDIu/cEDgkeOJHzuXHRJSZjWr4/3rl1UGDUKhaU9vLEdavcHXSbsngTHPoFiGFsmCGWF5WuvUfGjeQBEr1xF9Lp1RXp+I7WSBb1qA7DpXDDng2KK7NxBV6PYufQSKfHpVHC1oM+7jajgKmp9F4RIPp/jfFAMP5zUl2xY1Ls2duZiUoEglFWSTkfMho0EdO9B8pm/UJiY4DTjfTw3/ISxj/e/O6qNodf38PI0/fNji2DP/0BrmO49QSiLbPr0wWGa/jP06JNPiduzp0jP39jbjv7/TAyeufMaGdrctXoLyv9kKPu/vUpmmhZ3X1t6T2+Aha3xC5+3vBHJ5zMkp2fy9tbLSBL0behGuxpOcockCIKBpN+/T/DQYUTMn4+UnIxZo0b47N6F3bBhKFR5lEtRKqHtHOj6BSiU+u73nwdAWkLxBy8IpVSFMaOxGzYUgLAPZpJ4omjHUc/o5IuduRG3IhJYdbLwBe4lSeLsngCObbyFpJOo3tSZLv+ri5GpugijLT9E8vkMnxy4yf3oZFysTZjdrYbc4QiCYACSVkv0unUE9OhJ8vnzKMzMcJr1IR7rf8TI0/P5J2g0EgZuAo0Z3PsN1naGhHDDBy4IZYBCocDxvfew6toVMjN5MHkKKZcvF9n5bc2NmNnZF4Avf7tNSExygc+hzdTx2483OL8/CIBGXbx4bZgvKlFKqdDElXuKU3eiWH/mPgCL+9bFykQjc0SCIBS1tIAA7r/+Bo8++RQpNRWzZk3x2bMbu9dfR6EswK/Hah1h+D4wd4DwK7CqLTwq+kkOglAWKZRKXBYuwPzll5FSUvTLcN67V2Tn793AlWY+FUjN0DF797UCza5PS8lk39eXufVXOAqlgtZDqtOkm4+Y+/GCRPKZh/jUDN7dpv/mNaSpJy9XsZc5IkEQipKUmUnUypUE9uxFip8fSnNznOfNw2PNGozcCrl4hGtDGHUEKlSGuBBY0x6CThVt4IJQRimMjHD7chkmdeqgjYsjePQYMh4+LJpzKxTM71ULI5WSP25Fsv9q/nomEmNT2fn5BR7cjEVtrKLLxDrUaOFSJDGVdyL5zMNHe68TFpeKZwUz3u8kCkgLQlmSevs2QYMGE7lkKVJ6OuYvv4zP3j3YDuj/4ncz7Lz1Cah7E0iNg596wdVtRRO4IJRx2ctwenuT+fAhwWPGoH38uEjOXcnBgvGtKgEwb68/8anPnhwYHZrItk8vEB2ahJmVEb3fboBnrQpFEosgks9croXGse3CAxQKWNKvLubGYjCxIJQFUkYGUd9+S2CfvqRevYrS0pKKCxbgvvIHNC5FeDfDzA6G7gbf7qBNh+2j4M8vRSkmQcgHta0tHqtXoXZyIv3uPULGTyiyZTgntqqEt705jxLSWHLo1lP3C7kZw47PLpD0OA1bZzP6vNsQBw/LIolB0BPJ53/UcrVm1dBGTG9fjUZednKHIwhCEUi9cYPAAQOI/PIryMjAolUrfPbtxaZPb8OM3dKYQr910HSi/vmR2bD/HdBpi74tQShjNC4ueKxaidLamhQ/Px5MmYKU8eJlzEw0Kj7uUQuA9X/d53LI41z73Dobzr7ll0lP1eJSxYbe7zTEyt70hdsWclJIRb2ulQHEx8djbW1NXFwcVlZWcocjCEIpIaWnE/Xdd0T9sBIyM1FZW+P04UysunYtvgkDZ76BQzMBCap1gT6rwMiseNoWhFIs+eIlgkeOREpNxbpHDyouWliwiYBPMeWXS+zyC6OmixW7J7VArVIiSRIXDt7n7G59Xe/KDR1pM9wXtSaPMmvCU+U3XxN3PgVBKJNSrl4jsE9folZ8C5mZWLZrh8++vVh361a8M1WbTdLfBVUZw61f4ceukBhZfO0LQill1qA+rsu+0C/DuXs3jz5fUiTn/bBrDaxNNfiHxbPudBA6rY5jP9/KTjzrt/Og/aiaIvE0oEIlnytWrMDb2xsTExMaNmzIyZMn83Xcn3/+iVqtpl69eoVpVhAE4bl0aWk8WrKUoIEDSbtzB5WtLa5fLMX1qy9ROzjIE1TNnvpxoKa2EHoBVreD6KIrJSMIZZVlq1ZUnD8fgJg1a4heveaFz2lvYZw9mXj5odvs+MqP6yfDQAGvDqxK8z6VUShFKSVDKnDyuXnzZqZMmcLMmTO5dOkSr7zyCp06dSI4OPiZx8XFxTF06FDatGlT6GAFQRCeJcXPj8DefYheuRK0Wqw6d8Ln131Ydeokf10+z2b6mfA2HhAbqE9AQ/6WNyZBKAVsevXE8Z3pADz67DMe79r1wucc0Mid5i42dI9VE3HrMSqNkk7jalO7VSFLrQkFUuAxn02aNKFBgwZ8++232dt8fX3p2bMnixYteupxAwcOpEqVKqhUKnbt2oWfn1++2xRjPgVBeBZdaiqRX35FzI8/gk6Hyt4e5zmzsWrXTu7Qckt8BD/3h7BLoDaBPqvBt6vcUQlCiRfx6WJi1q4FlQq3b77GslWrQp8rNjyJHcsukfo4nWSFRLW+PnRv4110wZZTBhnzmZ6ezoULF2jfvn2O7e3bt+f06dNPPW7t2rXcu3ePOXPmFKQ5QRCE50q+cIHAHj31f5R0Oqx7dKfSvr0lM/EEsHCE4b9ClQ6QmQqb34CzP8gdlSCUeI7vTMeqezfQagmdMpXkS5cKdZ6wu4/ZvvgCqY/T0Zmr2GiRxifnAkhKyyziiIWnKVDyGRUVhVarxcnJKcd2JycnwsPzXjHgzp07vP/++2zcuBG1On81M9PS0oiPj8/xEARBeJIuOZnwBQu5/8YQ0u/fR+3oiNu3K3D59FNUNjZyh/dsRuYw8GdoOAKQ4MA7cPhD0OnkjkwQSiyFUonLggWYv/oKUmoqIeMnkHbnToHOcffCI/Ys8yMtORMnbyte/6AxFvYmhMWlsuzobQNFLvxXoSYc/XfslCRJeY6n0mq1DB48mHnz5lG1atV8n3/RokVYW1tnP9zd3QsTpiAIZVTSX2cJ6NGT2J9+AknCum8ffPbtxbJ1a7lDyz+VGrp+AW1m65+fXq4vSJ+RKm9cglCCKTQa3JYtw7RuXXRZy3CGheXrWL+jwRxadQ1tpg7vuvb0mFofuwqmfNxTX/tzzZ9B+IfFGTJ84R8FGvOZnp6OmZkZW7dupVevXtnbJ0+ejJ+fH8ePH8+x/+PHj7G1tUWl+rdcgU6nQ5IkVCoVhw8f5rXXXsvVTlpaGmlpadnP4+PjcXd3F2M+BaGc0yYm8ejzz3j8y2YA1C4VqfjRx1i83ELmyF7Q5c2wexLoMsCjOQzcqF8pSRCEPGXGxup7Pe7dw8jHB8+NG1Db2ua5r04n8ee2O1z5/QEAtVu58XL/KiifmNE+aeNFfr36kLruNuyY0ByVmO1eKAYZ82lkZETDhg05cuRIju1HjhyhefPmufa3srLi6tWr+Pn5ZT/Gjx9PtWrV8PPzo0mTJnm2Y2xsjJWVVY6HIAjlW+KpPwno3i078bQZOACfPXtKf+IJUHcAvLEdjK0g+DSs6QCx9+WOShBKLLWtLR6rVqJ2diY9IICQ8ePRJSfn2i8zXcuhldeyE8/mvSvzyoCciSfA7G41sDRWcznkMT+fFZ89Qytwt/u0adNYtWoVa9as4caNG0ydOpXg4GDGjx8PwIwZMxg6dKj+5EoltWrVyvFwdHTExMSEWrVqYW5uXrSvRhCEMkcbH0/Yhx8SMno0mWEP0bi54bFuLRXnzkVlYSF3eEXHpyWMPARWrhB1W1+KKaxwEyoEoTzQVKyIx6qVqKytSb18hQeTcy7DmZKYzu5lfgRcikSpVtB+dE3qt/fIc5igk5UJ0ztUA2DxwVs8ihfDXwypwMnngAEDWLZsGR999BH16tXjxIkT7N+/H09PTwAePnz43JqfgiAI+ZFw7BgB3boTt207ALZvvIHP7l2YN20qc2QG4lQDRh8Fp1qQGAFru8Dtw3JHJQgllnHlyrh99y0KExOSTp4k7IOZSDodcZHJbF98gfCAOIzN1PSYXI8qjZyeea43mnpS192GhLRMPtp3vZheQfkk1nYXBKHE0T5+TMSiRcTt3gOAxtMDlwULMGvUSObIiklqPGwZAgHHQKGCrkuh4XC5oxKEEivx+HFCJk4CrRYGTuRMYj1SEjOwtDOh65t1sauYv55W/7A4ui0/hU6CH0c2pmVVmVZFK6XE2u6CIJRKCb/9xr1u3fSJp0KB3fDh+OzaVX4STwATKxi8FeoOAkkLeyfD7/Oh5N8rEARZWLRsicvCBURVqMWx0CqkJGbg4GFJn/ca5jvxBKjpYs2IFvpi87N2XSM1Q2uokMs1kXwKglAiZMbGEjrtbR5M+h/ayCj9DNafN+L0/nsoTU3lDq/4qY2g57fw6rv65yc+g10TIDNd3rgEoYQKsWnI1drj0amMsIv2p3XlB5hbGxf4PNPaVaWitQnBMcks/71gdUSF/BHJpyAIsos/eJCALl2J378flEoqjBmN984dmNWvL3do8lIo4LWZ0O0rfff75U3wcz9IFbUIBSGLpJM4s/MexzfdRkKBl2UUda59R9S8WST8/keBz2durGZu95oA/HAigNsRCUUdcrknkk9BEGSTGRXFg7cmEzplKtqYGIyrVMFr8y84vv02SuOC37EosxoOg8GbQWOuHwe6tjPE56+wtiCUZdoMHUfWXufiIX15pMbdvOn0aV9se3TXL8M5dSrJFy8W+LwdajrT1teJDK3EzJ1X0enEkJeiJJJPQRCKnSRJxO3dR0DXbiQcPgxqNfYTJ+C1fRumtWvLHV7JVKUdjNgPFk4QcQ1WtYUIf7mjEgTZpCVnsHe5H3f+jkCpVNBmmC8vdfFGqVRS8eOPsGjZEiktrVDLcALM61ETMyMVfwfFsvVCiAFeQfklkk9BEIpVxqNHPJj0P8LeeQft48cY+/rivWUzDm+9hdLISO7wSjaXejDqCNhXg/hQWNMRAo4/9zBBKGsSYlLZ8flFQm8/RmOiouv/6lK9WcXsf1doNLgu+wLT+vXRxcfrl+EMDS1QG642pkxrp18afNGBm0Qnpj3nCCG/RPIpCEKxkCSJxzt3EdC1G4m//w4aDfZvvYn3ls2Y1Kghd3ilh60njDoEni0gLR429NEvzykI5URkSALbPj1PTFgS5tZG9J7eAPcauZejVZqa4v7tCowqVyIzIoLg0WPIjI0tUFvDm3tRo6IVj5MzWLD/RlG9hHJPJJ+CIBhcRng4IePG8XDGDHTx8ZjUrIn3tm04TJyIQqORO7zSx9QW3tgBNXvp14PfORZOLhGlmIQyL/h6NDs/v0hyXDp2Lub0ea8R9m6WT91fZWODx6pVqCtWJD0wkJBx49ElJeW7PbVKycLetVEoYMfFUE7fiyqKl1HuieRTEASDkSSJ2C1bCOjajaQTJ1FoNDhMm4bX5l8wqVZV7vBKN40J9FkDzd/SP//tI9g3FbSZ8sYlCAZy4/RDfv36ChlpWlyr2dB7egMs7Uyee5zG2RmP1atQ2diQeuWfZTjT81+yrJ67DW800a/i+OHOa6RlitqfL0okn4IgGET6g1BCRo0ifPYcdImJmNati/eundiPHYNCrZY7vLJBqYT2H0PnzwEFXFgLvwyGtES5IxOEIiNJEuf2BfL7+hvodBJVGzvR7X/1MDbLf6+JsY8P7t9/h8LUlKRTp7KX4cyvdzpWw8HSmICoJL47FlCYlyE8QSSfgiAUKUmnI2bjRgK6dyfp9BkUxsY4vvcenj9vxLhSJbnDK5saj4EBG0BtAncOwboukPhI7qgE4YVptTp+/+kmf+8LBKBBR0/aDq+BSlPw9MW0bl3cvvoK1Gri9+0j4pNPyO8K41YmGmZ31Y9N/+aPuwREii94L0Ikn4IgFJn04GCChw0n4uP5SMnJmDZqiM/uXVQYMRyFSiV3eGWbb1cYtg/MKsBDP30ppiixOotQeqWnZrL/myvcPP0QhQJaDq5Gs56VUCgVhT6nxSsv47JoIQCx638ieuWqfB/btU5FXq3qQLpWx4e7ruU7cRVyE8mnIAgvTNJqiVm/noAePUn++28UpqY4zZyJ5/r1GHl5yR1e+eH+kr4Uk603PL4Pq9tB8F9yRyUIBZb0OI2dSy4SfD0GtZGSzhPqUOtV1yI5t3W3bjjNeB+AyKVLebx9e76OUygUzO9RC2O1ktP3otnlV7DSTcK/RPIpCMILSQsI5P4bQ4hYuAgpJQWzJk3w2bMbuyFvoFCKXzHFrkIlGH0UXBtBSiz82B38d8kdlSDkW3RYItsWnycqJBFTSw09pzXAq459kbZhN2wYFcaMAeDhrNkk/P57vo7zqGDG5LZVAJi/7waPk/M/cUn4l/jLIAhCoUhaLdGrVxPYqxcply6hNDPDee4cPNauwcjdXe7wyjdzexi2F6p1AW0abB0OZ76ROypBeK7QW7Hs+OwiiTFp2DiZ0efdRjh5WRmkLYdpU7Hu0xt0OkKnTiP5/Pl8HTf6ZR+qOlkQnZTOpwdvGiS2sk4kn4IgFFja3bsEDRrMo88+R0pLw7xFC3z27cV24EBxt7OkMDKDAT9B47GABIc+gAPvg06UiRFKpjt/R7BnuR/pKZk4+1jT552GWDuYGqw9hUJBxXnzsHjtNf0ynBMmknrr1nOPM1IrWdBLvwzwpnMhnA+KMViMZZX4KyEIQr5JmZlEffc9gb16k3rlCkpLSyrO/xj3VSvRuLjIHZ7wX0oVdFoM7T7WPz/7LWwdBhkp8sYlCE+QJImLh+5zeLU/ukyJSvUd6DGlHiYWhl+AQqFW47p0CaYNG6JLSCBk9BjSHzx47nEvedkxoJG+h+eDnVdJz8x/2SZBJJ+CIORT6q1bBPUfQOSyZUgZGVi0bInPvr3Y9O2LQlH42aeCgSkU0OIt6LsGVEZwYy+s7wFJ0XJHJgjodBInfrnNmZ33AKj7mjvtx9RCbVR81TGUJia4r/gG4ypVyIyMJGTUaDKjn//5eL9TdezMjbgdkciqU6L2Z0GI5FMQhGeS0tOJ/PobAvv0JfX6dZRWVlT8ZBFu332LxslJ7vCE/KrVB4bsAhNrCDmrnwkfEyh3VEI5lpGu5eD3V7l2PBQU0KJvZV7uXwXlC5RSKiyVtXV2D076/fuEjBuPNvHZy3Damhsxs7MvAF/9doeQmOTiCLVMEMmnIAhPleLvT2C//kR9/TVkZmLRpo3+bmfPnuJuZ2nk1QJGHgZr9/+3d9/hTVb//8efWZ10QxctpZU9ZBSZIuqHvZcgIAjiQHEAggooQwRUQESWoID4Ye+96gAREKWU2TILlNFSWkp3mzS5f3/kJ98PUpAycif0/biuXF65c9K86iHpO+e+zzlw/ay1AL0crXYqUQzlZhpZPzWGc4dT0Om1tHi1GjWbllE1kyEggNDvv0fn40PesWNcfvedf92Gs3Pt0jSI8CPPZOGT9bL2572S4lMIcRuL0Ujy119zvlt38k+eROftTfCUyYTMmI7B31/teOJB+FeyLsUU+CRkX4Mf2sLJbWqnEsXIjas5rPoymqvnMnB219N+UE3KRdrH54pzRDihc+egcXMje+8+rnw0/K7bcGo0Gj7rVA0nnZadJ6+x5WiSDdM6Lik+hRC3yD1yhPNdupD67Rwwm/Fo2ZKIzZvwatNGRjsfFx6B0G8LlGsKphxY1gP+mqd2KlEMJMWns3pSNBnXcvEs6UKXYZEEl/NWO9YtXKtXt27DaTCQsWWLdQ3ju4xoPlGqBG8+a906eOzG42TkmWwV1WFJ8SmEAMCSl8fVSZM4/2IP8k+fQefnR+mvvybk66no/fzUjiceNmcP6LEMavUGxQKbh8BPY+AuozxCPIj4Q9dYNzWGvCwT/mEedPmgDj6B7mrHKlSJpxsRPHEiAGmLFpE6Z85d27/57BOEl3QnOTOfKdv/fbmm4k6KTyEEOQdjONepM9fnzQeLBc927YjYtBHPli3UjiYeJZ0B2k+HZ0dY7/8+Fda+DgX56uYSj50jv15k65yjmE0Wwqr70XFIbdw8ndSOdVdebdsQMML63rj29TTSVq68Y1sXg47xHasB8OMfFzh08YYtIjosKT6FKMYsublcnTiRC716YTx3Dn2pUoTMmknpSV+i9/FRO56wBY0Gnv0QOswCrR6OroRFXSD3htrJxGNAsSjsWXWa3ctPgwJVGwfTekB1DM62W0rpQfj26Y3fG28AkDR6DJk//XTHtg3LlaRTrdIoCoxYc5QCs5xFuBMpPoUoprL//JP4Dh25vvBHUBS8OnUiYtNGPJ5/Xu1oQg21ekHPFeDkAed3w/yWcOOi2qmEAyswmdkx7ziHfrL+O6rfMYImPSui1TlW6VFq0Ht4v9DVug3nkPfJ+euvO7Yd2aYyXq4GYhMz+GHveduFdDCO9S9ACPHALNnZJH06joQ+L2NKSEAfGEjo3DkET5yAzstL7XhCTeX+A69sBY8guBZnXYop8YjaqYQDyss2sWHaIc5EJ6PVaWjarwqRLcs65KRFjUZD4OjRlGj6HxSjkYtvDbzjNpwlSzjzUatKAHwVdYorN2Q3scJI8SlEMZK9bx/x7TuQtmQJAN4vvEDExg2UeOYZlZMJuxFYHfpHQanKkJkIC1rD2V/UTiUcSEZKLmsmRZN4Jh0nFx3t3qlBxXqBasd6IBq9ntKTJ+Nax7oNZ8Krr95xG87udUKpE+ZDjtHMmA3HbZzUMUjxKUQxYM7KInHUaBL6vYLp8mUMwcGUmT+PoHGfovPwUDuesDfeofDKNijbGIyZsPgFiFmsdirhAK4lZLL6y2jSknIo4eNM52GRhFTyVTvWQ2HdhnMWzhUrYr6WQkL//oVuw6nVapjQuTp6rYYdsVfZcVzW/vwnKT6FeMxl7d5NfNt23FixAgCfnj0J37AB94YNVU4m7JqrN7y0Gqq/AJYCWP8W7PwCZAcXcQcXjqWyZspBcjKM+JUuQZcP6uBXuoTasR4qnacnod/NxVC6NKYLCVx8/Y1Ct+GsEODBa89EADBmw3Gy8wtsHdWuSfFZiGxTtmyRJRyeOT2dK8NHcPG11ylISsIQGkqZHxcSOOoTdCXsc209YWf0ztBpLjw92Hp/5wTY8DaYZRFtcavY36+wedYRCvLNhFTyofPQ2pTwcVY71iNh8PenzLzv0fn6knf8OJfeeRtLIdtwvvt8eUJ9XbmSnsfUqFMqJLVfUnz+g6IovPfrewz8eSBJ2TJULhxT5i+/Et+2Helr14JGg+/LfYhYvw73unXVjiYcjVYLTcdAm69Ao4WYRbD0RcjPVDuZsAOKorB/Qzy/LjqBYlGoWD+Qtm/XwMlVr3a0R8qpbFlC585F6+ZGzr4/uPLBhyhm8y1tXJ10fNrBuvbngr3nOX4lXY2odkmKz384lXaKg1cPsvvybjqt78Sa02tkFFQ4jIK0NC4P+4BLb71FwbVrOJUtS9jiRQQMH47WzU3teMKRPdUfXlwCBjc485N1IlKmfEEvzswFFn5eGMeBLecBqNO6LP95uTI6ffEoLVyrVSVkxnQwGMjcto2r48ffVi88V9GfNtWDMFsURqw9htki9QRI8Xmbir4VWdluJU+WfJIsUxaj945mwE8DSMxKVDuaEHeVsX0H8W3bkbFxI2i1+PZ/hfB1a3GrXVvtaOJxUbEV9N0EbiUh6Qh83wyST6idSqggP7eATTMOc/KPJDRaDc+9VIl67SMccimlB+HesCGlv/wCNBrSliwlZdas29qMalcFD2c9hy/eYMn+CyqktD9SfBbiCe8n+LHVj7wf+T7OOmf2XtlLx/UdWXFyBRZFdiwQ9qUgNZVLgwZz+b33MKem4lTuCcouXULAsGFoXVzUjiceN6Uj4dWfwK8cpCfA/OZw/ne1UwkbykrLZ+3kg1w6kYbeWUebt56kytPBasdSjWerVgSMHAlAyvQZpC1bdsvjAZ4uDG1REYAvt50kOSPP5hntjRSfd6DT6uhbrS+r2q2iln8tcgpyGPfHOF7b8RoXM2XXD6E+RVFI37yZ+LbtyNy2DXQ6/N54g/A1a3CtUUPteOJx5htuXQs0tB7kpcN/O8HRVWqnEjaQejmL1V8eIPVyFq6eTnQaUouwan5qx1Kd70u98HtzAABJYz8lY/uOWx5/qX4YNUK8yMwvYOymWDUi2hUpPv9FWa+yLGixgA+f+hAXnQt/Jv1Jlw1dWBy3WEZBhWoKrl3j0jvvcOX9oZjT0nCuWJGyK5bjP3gQWicnteOJ4sDNF/qsh8rtwWyE1f1hzzRZiukxdunEddZMiiYrLR+fQDe6fhCJf5in2rHsRql338W7WzdQFK4MHUr2H/tvPqbTahjfqTpaDWw+ksjOk8kqJlWfFJ/3QKfV8VKVl1jTfg11AuqQW5DL539+Tr9t/biQIddvCNtRFIX09es527YdWT/9DHo9Jd9+m/CVK3CtWlXteKK4MbjCCz9A/bes96NGwZZhYDHf9WnC8Zz8I5GN0w9jzDMTVM6LzsMi8SzpqnYsu2LdhnMUHs2aophMXBo4kLzY/xvlrFbai36NwgH4ZP0xco3F931yX8XnrFmzCA8Px8XFhcjISHbv3n3HtmvWrKFZs2aUKlUKT09PGjRowPbt2+87sJpCPUOZ12IeI+uNxFXvysHkg3TZ0IWFxxdilg9b8YiZrl7l0oA3ufLhR1jS03GpUoXw1aso9fZANDLaKdSi1UHLidBiAqCBv76D5b3BmKN2MvEQKIrCga3n+emHOCxmhXKR/rR/ryYu7ga1o9kljU5H8OTJuD31FJbsbBJefwNjQsLNx4c0q0CQlwsXr+cy/ZfTKiZVV5GLz+XLlzNo0CBGjhxJTEwMjRs3plWrViT8z//c//Xbb7/RrFkztmzZQnR0NM899xzt2rUjJibmgcOrQavR8mKlF1nbYS0NghqQb85n8oHJ9NnWh/gb8WrHE48hRVG4sWoV8W3akrVrFxqDgVKDB1N2xXJcKlZUO54QVg0GWkdBdc5wcjMsbAfZKWqnEg/AYrawc8lJ9q+3/m2r2awMzftXRW/QqZzMvmmdnQmZNRPnSpUwp6SQ8OprFKRY3wvuznrGtLeepZr7WzynrhbP9XI1ShEXsaxXrx61a9dm9uzZN49VrlyZjh07MnHixHv6GVWrVqV79+6MGjXqntpnZGTg5eVFeno6np72c32JoiisOb2GyQcmk2XKwknrxJs136Rv1b7otY/3ArvCNkxXrpD4ySiy9+wBwOXJJwmeMB7ncuVUTibEHVzYB8t6QG4a+IRbt+j0e0LtVKKIjHkF7Jh3nAtHU0EDjbtV4MnnQtSO5VBMyclc6NkL06VLOFepTNiPP6IrYd1u9NWFB/gp7ipPlfVh+esN0GofjyWq7rVeK9LIp9FoJDo6mubNm99yvHnz5uzdu/eefobFYiEzMxNfX987tsnPzycjI+OWmz3SaDR0qdCFtR3W0rh0Y4wWI9MOTqPXll6cSpOttMT9UywW0pYtI75tO7L37EHj7Iz/sGGUXbpECk9h38IaWGfCe5eBtHMwrxlc/EvtVKIIcjKMrJ8aw4WjqegMWlq9Xl0Kz/twcxtOPz/yY+O4NPBtLPn5AIztUBU3Jx1/nU9jxYHit4JOkYrPlJQUzGYzAQEBtxwPCAggKenedrqYMmUK2dnZdOvW7Y5tJk6ciJeX181baGhoUWLaXKB7IDP/M5PxT4/Hw8mD2NRYum/qzuzDszFZZA9kUTTGixdJ6PcKSWPGYsnJwbV2bcLXrcWv/ytodHK6SziAkuWh/08QVBNyUmFhW4jbpHYqcQ/SkrJZ/eUBki9k4uJuoOPgWkTUKqV2LIflFBZG6Nw5aN3dydm/nyvDPkAxmynt7cqQZhUAmLj1BClZ+Sonta37mnD0zx0MFEW5p10Nli5dypgxY1i+fDn+/v53bDd8+HDS09Nv3i5etP9vBRqNhvZPtGd9h/U8F/ocBZYCZh2aRY9NPYhLjVM7nnAAisXC9f8uIr59B3L270fj6krAiBGE/fdHnMPD1Y4nRNF4BEDfzVC+ORTkwfKXYP9ctVOJu0g8c4PVk6LJSMnDs5QrXT6IJDDCS+1YDs+1alVCZs5AYzCQuWMHSePGoSgKfRuWpUqQJ+m5JiZsLl51QpGKz5IlS6LT6W4b5UxOTr5tNPSfli9fTv/+/VmxYgVNmza9a1tnZ2c8PT1vuTmKUm6lmPbcNL5o/AXezt6cTDtJz809mR4zHaPZqHY8YaeM589zoU8f697Aubm4PfUUEevX4dunt4x2CsflXAJeXAqRfQEFtg6DHR+DRdZItjdnopNZ//Uh8rML8C/rSZdhkXgHuKkd67HhXr8+wZMmgUbDjWXLSZkxE71Oy4TO1dFoYE3MZfaeKT4T9IpUfDo5OREZGUlUVNQtx6OiomjYsOEdn7d06VL69u3LkiVLaNOmzf0ldSAajYbWEa1Z22EtzcKaUaAUMPfIXLpv6s6xlGNqxxN2RDGbSV3wA/EdOpJ7IBqNmxsBoz6hzMIfcCpTRu14Qjw4nR7afg3Pf2K9v3c6rH4FTLLFoL049FMC278/hrnAQniNknQcUgs3T1m+7WHzbNmCwFHW90HKzJmkLV1KzVBvXqoXBsDH646RX1A8lm0s8mn3IUOG8P333zN//nzi4uIYPHgwCQkJDBhg3VZq+PDh9OnT52b7pUuX0qdPH6ZMmUL9+vVJSkoiKSmJ9PT0h/db2KmSriX56tmvmNJkCr4uvpy5cYZeW3oxNXoq+ebidX2HuF3+2bNc6NmL5C++QMnPx61BfSI2bMC3Z080Wtn/QTxGNBp4Zih0mgtaAxxfa92SM+e62smKNYtF4fcVp9mz6gwoUL1JaVq+UR2Dk5xteVR8evSg5MCBACR9Oo6MbdsY1rIipTyciU/JZvbOsyontI0iL7UE1kXmv/zySxITE6lWrRpTp07lmWeeAaBv376cP3+enTt3AvDss8+ya9eu237Gyy+/zA8//HBPr2evSy0VRVpeGhP/nMjWc1sBCPcK59OGn1LTv6a6wYTNKQUFpM5fQMqMGShGI1p3d/w//ADvF164p2unhXBo8bus13/mZ0DJCtBrFfiEqZ2q2CkwmolaEEt8zDUAGnR+glrNyshnkA0oikLS2LHcWLYcjcFA6Hdz+cW1DO8sjcFJp2XboMZElCqhdsz7cq/12n0Vn7b2OBSff/sl4RfG/TGOlNwUNGjoXaU3b9d6G1e9bFNWHOSdOkXiiJHkHbNefuH+TGOCxo7FEBSkcjIhbOjqcVj8AmRcBnd/6LUSgmuqnarYyM0ysmXWUZLi09HqNTR9uQrln7r7vA3xcClmM5eHvE/m9u1o3dwo8+OPDPgzm12nrtEgwo8lr9VzyC8CUnzasfT8dL7860s2nN0AQBmPMoxtOJY6gXVUTiYeFcVkImXuXFK+nQMmE1pPTwKGD8erYweH/IAR4oGlX4Yl3eDqMTC4Q7eFUL6Z2qkee+nXctk4/RDpybk4u+lpNaA6pSv4qB2rWLIYjVx87XVy9u9H5+uL06x5tFh1jvwCC191q0Hn2o63tqoUnw7gt0u/MXbfWJJzkgHoUakHg2oPws0gMwwfJ3mxsVwZMZL8EycAKPH88wSOHo0h4M7LjQlRLORlwIreEL8TNDpoOxUiX1Y71WPr6vkMNs88TG6miRK+zrR7uya+we5qxyrWzFlZXOjTh/zYOAwhIfz69njG/3ENP3cnfn6/Cd5ujjXx65HscCQermdCnmFdh3V0Kd8FgKUnltJ5Q2f2J+5XOZl4GCxGI8nTpnGuW3fyT5xA5+1N8OTJhMycIYWnEAAuntBzJdToAYoZNr4Lv4wH+x8TcTjnj6Sw7quD5GaaKBlagq4f1pHC0w7oSpSgzJw5GEJDMV26xPMLJlDdW0dqtpHPt55QO94jIyOfdmLvlb2M2TuGxOxEAF6o8AJDIodQwskxLzou7nKPHiVxxAjyT58BwKNFCwI/+Rh9yZIqJxPCDikK/DoBfvvSer9GT2g3DfSONepjr479dpnflp5EUaBMVV9avFYNJxe92rHE/zAmJHC+Zy/MKSmYq9eiU9lumHQGVg5owFNl77wdub2R0+4OKNuUzdToqSw/uRywbts5psEYGpVupHIyca8s+fmkzJhB6rz5YLGg8/UlcNQoPFu2UDuaEPYveiFsGmwdBY14Frr9CC6yw879UiwKf6yP5+D2CwBUbhhEk14V0enkpKc9youN5ULvPliyszlfpS4Dy3elXKAnm95pjJPeMfpMik8H9mfin4zaO4rLWZcB6FSuE0OfGoqn0+P/uzuynJgYEkd+jDE+HgDPNm0I+Hgkeh+5mF+Ie3Y6Cla8DKZsCKhmnQnvGax2KodjNln4+cc4Tv91FYC67cKp07qsTHC0c9l/7Ofia6+hmEz8Uq4hk6p2YljLSgx8rpza0e6JFJ8OLseUwzcx37AkbgkKCv6u/oxqMIomoU3Ujib+wZKby7Vp33B94UJQFHSlShI0ejQe/7KNrBDiDq4css6Ez7oKnqWtBWhAVbVTOYz8HBNbvz3K5VM30Go1PNe7EpUayHJujiJj+w4uDxoEisKSik1ZUb01UYObUMbP/icjS/H5mDh49SCj9o7iQob1tEnbiLZ8VPcjvJzlVJQ9yPnrL658/DGmCwkAeHXoQMDwj9B5e6sbTAhHl3bBuhZoyklw9oTuiyBCvnz/m8zreWyacZjrV7IxuOho9Xp1Qqs4zjWDwipt2XKSxowBYNaTHclo2Ykf+j1l9yPXMtv9MVE7oDar2q2ib9W+aDVaNsVvosO6Dvx84We1oxVrlpwckj4bz4XefTBdSEAfEEDIt7MJ/uJzKTyFeBh8wqD/dghrZN0NaVEXOLxc7VR27drFTFZ/cYDrV7Jx83Ki0/u1pfB0UD4vdqfkO28DMODIeiy/RrH5aKLKqR4eKT4dgIvehffrvM9/W/2XCK8IUvNSGbRzEMN2DeN6nuyNbGvZf+wnvn0H0hYtAsD7ha5EbNqIx7PPqhtMiMeNqw+8tAaqdgKLCda+DrunyFJMhbgYe521Uw6SnW7EN9idrh/WoVSoh9qxxAMo+dZb+PTsiRaFYQeWsmruGjLyTGrHeijktLuDyTfn8+3hb1lwbAFmxYyviy/D6w2nRVgLux+Od3TmrCySJ0/mxjLr6Is+OIigceMo0UhWIxDikbJY4KdRsHe69X5kP2g9GXSyXBBA3N5Edi46gcWiULqCN60GVMfZzaB2LPEQKGYzFwe/T/aO7eTonfltwFgGv91B7Vh3JNd8PuaOpx7nkz2fcDrtNABNyzRlZP2RlHSVdSQfhazdv5M4ahQFidbTHt49XsT//aHoSsgizULYzP65sPUDQIEKLaHrfHAqvu9BRVE4sOU8f248B0CFugE837syOoOc1HycWIxGjvV+BcPhaG44ueM2ZwE1GlRXO1ahpPgsBkxmE3OPzuX7I99ToBTg5ezFR3U/ok14GxkFfUjMGRlc/eIL0levAcAQGkrQuHG416+ncjIhiqm4jbD6VSjIg+Ba0HMFlCh+O4aZzRZ2LTlJ3B7rF+LaLcOo3z4CjVY++x9H5qxs9rR7gVKJ50j18KPOhlW4BAWqHes2UnwWIyevn+STPZ8Qdz0OgGdDnuWTBp/g71b8PpAfpsxffyVp9BgKkpNBo8Gn90v4DxqE1s3+l7sQ4rF28U9Y0h1yr4N3GLy0GkqWVzuVzRjzCtj+3TESjl9Ho4FnelSk2jOl1Y4lHrHkhESOde5GUFYK2aXLUmvtcnR2VhNJ8VnMmCwmFhxbwOzDsymwFOBh8GDYU8PoWK6jjIIWkfnGDZImTCBjw0YAnMLCCJowHrfISJWTCSFuSj1rnQGfds46ManHMihTX+1Uj1x2ej6bZhwm5WIWeictzV+tRviTcrlVcbFm858EjHgb3/xMdDVrUe6H+WhdXNSOdZMstVTMGLQGXn/ydVa2XUk1v2pkmjIZtXcUb/78JknZSWrHcxgZUVGcbdvOWnhqtfi+8grh69dJ4SmEvfF7AvpHQelIyE2Dhe3h+Dq1Uz1S169ks+qLA6RczMLVw0DHIbWl8CxmOrZ6iqVd3idb74L5UAyX3x+KUlCgdqwik5HPx1CBpYAfY39kZsxMjBYj7gZ33q/zPl3Ld5VR0DsouH6dpHHjyNy6DQCnJ54geMJ4XGvUUDmZEOKujDmwuj+c3AJooMV4aDBQ7VQP3eVTaWz99ij5OQV4B7jR9u0aeJVyVTuWUMGpq5kM++QHPv19Lk6WAry6diFo3Di7+PsuI5/FmF6r55Vqr7Cy/UpqlKpBtimbT/d9ymtRr93cL15YKYpCxtatxLdpay08dTr8XnuN8DWrpfAUwhE4uVl3P3rqVUCB7SNg23Dr8kyPidN/XWXDN4fIzykgMMKLLsMipfAsxioEeNCoczM+r/MSFo2G9FWruTZtmtqxikRGPh9zZouZxXGLmR4znTxzHq56VwZHDqZ7xe5oNcX7u0dBSgpJYz8lMyoKAOfy5QmaMAHX6tVUTiaEKDJFgT3T4KfR1vuV20PnuWBw3CJNURRiohLYt+YsAE/UKkXTflXQO+lUTibUlms00/zrXVQ5uJNBh1YCEDBiBL59equaSyYciVskZCQwau8ooq9GA1AnoA5jG46ljGcZlZPZnqIoZGzaxNXPxmNOTwe9npKvv07JAW+gcXJSO54Q4kEcXQXr3gSzEULrWSciuTneFpMWi8Lvy09xdJf1bNWTz4fQqGt5tLKUkvj/dp5Mpu+Cv+hx6if6xG4DjYbgyZPwatNGtUxSfIrbWBQLy04s4+uDX5NbkIuLzoV3a79Lz0o90WmLxzdp09VkksaMIevXXwFwrlyZ4AnjcalcWeVkQoiH5vzvsKwn5KWDXznotQp8w9VOdc9MRjNR845z7nAKaKBRl3LUbFr8BgrEvxu45CCbD1/h43NbaXTkFzAYCP12tmo770nxKe7oUuYlxuwdw/6k/QDULFWTTxt9SriX43w4F5WiKKSvXcfVzz/HkpEBBgOl3noTv1dfRWOQbeiEeOwkx8HiFyD9IriXgp7LrTPj7VxuppHNs45w9VwGOr2Wpv2qUC5S1mwWhUvOyOM/U3aRlWfkv0mb8du/C42bG2ELf8C1uu13QZLiU9yVoiisOr2KKQemkG3KxknrxMBaA+lTpQ967eO1X7IpMZHEUaPJ3r0bAJfq1QmeMB7n8sVnUWohiqWMRFjyAiQdBYMbdF0AFVuqneqOblzNYeOMw2Rcy8XZXU/rN58kuJy32rGEnftx33lGrT+Otx5WXlxFwf4/0Pn4ELZ4Mc4Rth1Uktnu4q40Gg0vVHiBte3X0ii4EUaLkanRU+m9pTdn0s6oHe+hUBSFtOUriG/bjuzdu9E4OeE/9H3KLl0ihacQxYFnEPTbCk/8B0w5sKwH/DVP7VSFSopPZ/WkaDKu5eLh50KXYZFSeIp70qteGDVCvblRADOffRWXatUwp6Vx8dVXMV1NVjteoWTkU6AoCuvOrGPSX5PINGVi0BoYUGMA/ar1w6B1zFPSxkuXSfzkY3L2/QGAa82aBE0Yj3NEhMrJhBA2ZzbBpkEQs8h6/+nB8Pwo0NrH+Ev8oWvsmHccs8lCqTIetBn4JO5ezmrHEg7k2OV02s/4HYsCP3QuT+io9zCeP49z+fKELfovOi8vm+SQkU9xzzQaDZ3Kd2Jth7U0CWmCyWJiesx0em3uxcnrJ9WOVySKxcL1xYuJb9+enH1/oHFxwf+jDwlbvEgKTyGKK50B2s+AZ0dY7/8+Fda+AQVGdXMBR369xNY5RzGbLIRV86PjkFpSeIoiq1bai1caWU+xf/zrJUrNnoPe35/806e5+OZbKCaTyglvJcWnuCnAPYDpz09nwtMT8HTyJO56HC9uepGZh2ZiMtvXP9zCGC9cIOHlvlwd9xlKTg5udeoQsX4dfn37otEVj9n8Qog70Gjg2Q+hwyzQ6uHoCljUGXJvqBJHsSjsWX2G3ctPgQJVGgfT+s3qOLk8XtfcC9sZ3KwCwV4uXErLZfbJHEK/+w6tlxceTZva3cRaOe0uCpWSm8Jnf3zGzwk/A1DepzzjGo2jql9VlZPdTjGbSVu0iOSpX6Pk5aFxc8N/yBB8evZAYyen1YQQduTMz7DiZTBmQqnK8NIq8Aqx2csXmMz8vDCOMwes1+PV6xBBZMswu9geUTi2HceTeP2/0ei1Gja/25gnnAvQ+/jY7PVltrt4YIqisP3Cdib8MYG0/DR0Gh39qvVjQI0BOOvs47RQfvw5EkeOJDcmBgC3+vUJ+mwcTiG2+0MihHBAiUesSzFlJYFHEPRaCYGPfmmavGwTW2YfIfFMOlqdhuf7VKZivcBH/rqi+HjtxwNExV6lTpgPK95oYNONCeSaT/HANBoNLcu2ZF3HdbQs2xKzYub7o9/TbWM3jlw7omo2paCA1O+/51zHjuTGxKB1dydw7FjKLJgvhacQ4t8FPQmv/mQd+cxMhPmt4Owvj/QlM1JzWTMpmsQz6Ti56Gj7Tg0pPMVDN7Z9VdycdBy4kMaKAxfVjlMoKT7Fv/J18WVSk0l8/ezX+Ln4EZ8eT++tvZn812TyCvJsnif/9GnO9+hJ8uQpKEYj7k8/TcTGDfh07yanrYQQ9847FF7ZBmUbW0/BL34BYhY/kpe6lpDJ6i+iSUvKoYSPM52HRRJayfG2/RT2L9jblSHNKgAwcesJUrLyVU50Oyk+xT37T9h/WNdhHW0j2mJRLCyMXUjXjV05ePWgTV5fMZlI+fZbznXuQt7Ro2g9PAiaMIHQ7+ZiCA62SQYhxGPG1RteWg3Vu4GlANa/BTu/gId4RdqF46msmXKQnAwjfqVL0OWDSPxKl3hoP1+If+rbsCxVgjxJzzUxfnOc2nFuI8WnKBJvF28mNp7IjOdn4O/qz4WMC/Td1pfP//ycHFPOI3vdvBMnONe9O9e+noZiMlHiueeI2LQJ786dZLRTCPFg9M7QaQ48PcR6f+cE2PCOdX3QBxS75wqbZx6hIN9MSCUfOg2tTQkflwf+uULcjV6nZULn6mg1oNNqMFvsa3qPTDgS9y3DmMGkvyax7sw6AEJKhPBpo095KvCph/YaitFIypy5pMyZAwUF6Ly8CBg5As927aToFEI8fH/Ngy1DQbFYd0bqthCcPYr8YxRF4c+N5ziw5TwAFesH8txLldDpZcxH2M6F1GzC/Nxt9noy213YzJ7LexizbwxJ2UkAdK/YncGRg3E3PNg/+Nxjx0kcOZL8k9aF7j2aNSNw1CfoS5V64MxCCHFHJ7fCyn5QkGudAd9zpXWrzntkLrCwc9EJTvxh/Uys07osdduFyxdm8diT4lPYVJYxi6+iv2LlqZUABLsHM7rhaBoGNyzyz7Lk55Mycxap8+aB2YzOx4fAUZ/g0bKlfHgLIWzjUjQs6QY5KeAVCr1WgX+lf32aMbeArXOOculEGhqthmd7VqTK03JNuigepPgUqtifuJ/Re0dzOesyAF3Kd+H9Ou/j4XRvp61yDx/myoiRGM+eBcCzdSsCPv4Yva/MChVC2Nj1eFjUFa6fBRcveHEJlH36js2z0vLZNOMwqZez0DvraPlaNcKq+dkwsBDqeqTrfM6aNYvw8HBcXFyIjIxk9+7dd22/a9cuIiMjcXFxISIigm+//fZ+XlY4gHpB9VjTfg09K/UEYPXp1XRc35HfLv121+dZ8vK4+sWXnO/RE+PZs+hKlqT09G8o/dVXUngKIdThGwH9oyCkLuSlw387wdFVhTZNvZzF6i8PkHo5C1dPJzoNqSWFpxB3UOTic/ny5QwaNIiRI0cSExND48aNadWqFQkJCYW2P3fuHK1bt6Zx48bExMQwYsQI3n33XVavXv3A4YV9cjO4MbzecBa0WECoRyjJOckM/HkgI38fSXp++m3tc6KjOdehI9cXLACLBc/27YjYuAHPZs1USC+EEP/D3Q9e3gCV24HZCKv7w55pty3FFLMjgay0fHwC3ej6QST+YXKWTog7KfJp93r16lG7dm1mz55981jlypXp2LEjEydOvK39hx9+yIYNG4iL+791pgYMGMDhw4fZt2/fPb2mnHZ3XLkFuUyPmc6i2EUoKLSJaMPnjT8HwJKTQ/LUr0lbtAgUBb2/P4Fjx+Dx3HMqpxZCiH+wmGH7SNj////2PfUatPoCtDoATEYz+9aepW7bcFzcDSoGFUI9j+S0u9FoJDo6mubNm99yvHnz5uzdu7fQ5+zbt++29i1atODAgQOYTA++hpqwb656Vz546gN+bPUj1fyq8V6t924+ZsnPJ2PLFlAUvDp3JmLTRik8hRD2SauDVp9DiwnW+7HrIOvqzYcNTjqe6V5BCk8h7oG+KI1TUlIwm80EBATccjwgIICkpKRCn5OUlFRo+4KCAlJSUggKun35ivz8fPLz/287qIyMjKLEFHaopn9NlrRZcstsdb2PD8ETxoNWS4nGjVVMJ4QQ96jBQPAMBu8w63+FEEVWpOLzb/9c7kZRlLsugVNY+8KO/23ixImMHTv2fqIJO1ZYf5do0kSFJEII8QCqdlI7gRAOrUin3UuWLIlOp7ttlDM5Ofm20c2/BQYGFtper9fj51f4TMDhw4eTnp5+83bx4sWixBRCCCGEEHaqSMWnk5MTkZGRREVF3XI8KiqKhg0LX0y8QYMGt7XfsWMHderUwWAo/NoYZ2dnPD09b7kJIYQQQgjHV+SlloYMGcL333/P/PnziYuLY/DgwSQkJDBgwADAOmrZp0+fm+0HDBjAhQsXGDJkCHFxccyfP5958+YxdOjQh/dbCCGEEEIIh1Dkaz67d+9Oamoqn376KYmJiVSrVo0tW7YQFhYGQGJi4i1rfoaHh7NlyxYGDx7MzJkzCQ4O5ptvvqFLly4P77cQQgghhBAOQbbXFEIIIYQQD+yRbq8phBBCCCHE/ZDiUwghhBBC2IwUn0IIIYQQwmak+BRCCCGEEDYjxacQQgghhLCZ+9pe09b+npAve7wLIYQQQtinv+u0f1tIySGKz8zMTABCQ0NVTiKEEEIIIe4mMzMTLy+vOz7uEOt8WiwWrly5goeHBxqN5pG/XkZGBqGhoVy8eFHWFXVQ0oeOTfrP8UkfOj7pQ8dn6z5UFIXMzEyCg4PRau98ZadDjHxqtVpCQkJs/rqyr7zjkz50bNJ/jk/60PFJHzo+W/bh3UY8/yYTjoQQQgghhM1I8SmEEEIIIWxGis9CODs7M3r0aJydndWOIu6T9KFjk/5zfNKHjk/60PHZax86xIQjIYQQQgjxeJCRTyGEEEIIYTNSfAohhBBCCJuR4lMIIYQQQtiMFJ9CCCGEEMJmim3xOWvWLMLDw3FxcSEyMpLdu3fftf2uXbuIjIzExcWFiIgIvv32WxslFXdSlD5cs2YNzZo1o1SpUnh6etKgQQO2b99uw7Tin4r6Hvzbnj170Ov11KxZ89EGFP+qqH2Yn5/PyJEjCQsLw9nZmSeeeIL58+fbKK0oTFH7cPHixdSoUQM3NzeCgoLo168fqampNkor/tdvv/1Gu3btCA4ORqPRsG7dun99jt3UMkoxtGzZMsVgMCjfffedEhsbq7z33nuKu7u7cuHChULbx8fHK25ubsp7772nxMbGKt99951iMBiUVatW2Ti5+FtR+/C9995TvvjiC+XPP/9UTp06pQwfPlwxGAzKwYMHbZxcKErR++9vN27cUCIiIpTmzZsrNWrUsE1YUaj76cP27dsr9erVU6KiopRz584p+/fvV/bs2WPD1OJ/FbUPd+/erWi1WmXatGlKfHy8snv3bqVq1apKx44dbZxcKIqibNmyRRk5cqSyevVqBVDWrl171/b2VMsUy+Kzbt26yoABA245VqlSJeWjjz4qtP0HH3ygVKpU6ZZjb7zxhlK/fv1HllHcXVH7sDBVqlRRxo4d+7CjiXtwv/3XvXt35eOPP1ZGjx4txafKitqHW7duVby8vJTU1FRbxBP3oKh9OGnSJCUiIuKWY998840SEhLyyDKKe3Mvxac91TLF7rS70WgkOjqa5s2b33K8efPm7N27t9Dn7Nu377b2LVq04MCBA5hMpkeWVRTufvrwnywWC5mZmfj6+j6KiOIu7rf/FixYwNmzZxk9evSjjij+xf304YYNG6hTpw5ffvklpUuXpkKFCgwdOpTc3FxbRBb/cD992LBhQy5dusSWLVtQFIWrV6+yatUq2rRpY4vI4gHZUy2jt+mr2YGUlBTMZjMBAQG3HA8ICCApKanQ5yQlJRXavqCggJSUFIKCgh5ZXnG7++nDf5oyZQrZ2dl069btUUQUd3E//Xf69Gk++ugjdu/ejV5f7D627M799GF8fDy///47Li4urF27lpSUFN566y2uX78u132q4H76sGHDhixevJju3buTl5dHQUEB7du3Z/r06baILB6QPdUyxW7k828ajeaW+4qi3Hbs39oXdlzYTlH78G9Lly5lzJgxLF++HH9//0cVT/yLe+0/s9lMz549GTt2LBUqVLBVPHEPivIetFgsaDQaFi9eTN26dWndujVfffUVP/zwg4x+qqgofRgbG8u7777LqFGjiI6OZtu2bZw7d44BAwbYIqp4COyllil2QwglS5ZEp9Pd9s0uOTn5tm8EfwsMDCy0vV6vx8/P75FlFYW7nz782/Lly+nfvz8rV66kadOmjzKmuIOi9l9mZiYHDhwgJiaGt99+G7AWMoqioNfr2bFjB88//7xNsgur+3kPBgUFUbp0aby8vG4eq1y5MoqicOnSJcqXL/9IM4tb3U8fTpw4kUaNGjFs2DAAnnzySdzd3WncuDGfffaZnAW0c/ZUyxS7kU8nJyciIyOJioq65XhUVBQNGzYs9DkNGjS4rf2OHTuoU6cOBoPhkWUVhbufPgTriGffvn1ZsmSJXKOkoqL2n6enJ0ePHuXQoUM3bwMGDKBixYocOnSIevXq2Sq6+P/u5z3YqFEjrly5QlZW1s1jp06dQqvVEhIS8kjzitvdTx/m5OSg1d5aNuh0OuD/RtCE/bKrWsbmU5zswN/LS8ybN0+JjY1VBg0apLi7uyvnz59XFEVRPvroI6V379432/+9PMHgwYOV2NhYZd68ebLUksqK2odLlixR9Hq9MnPmTCUxMfHm7caNG2r9CsVaUfvvn2S2u/qK2oeZmZlKSEiI0rVrV+X48ePKrl27lPLlyyuvvvqqWr9CsVfUPlywYIGi1+uVWbNmKWfPnlV+//13pU6dOkrdunXV+hWKtczMTCUmJkaJiYlRAOWrr75SYmJibi6VZc+1TLEsPhVFUWbOnKmEhYUpTk5OSu3atZVdu3bdfOzll19WmjRpckv7nTt3KrVq1VKcnJyUsmXLKrNnz7ZxYvFPRenDJk2aKMBtt5dfftn2wYWiKEV/D/4vKT7tQ1H7MC4uTmnatKni6uqqhISEKEOGDFFycnJsnFr8r6L24TfffKNUqVJFcXV1VYKCgpRevXoply5dsnFqoSiK8uuvv97175o91zIaRZGxciGEEEIIYRvF7ppPIYQQQgihHik+hRBCCCGEzUjxKYQQQgghbEaKTyGEEEIIYTNSfAohhBBCCJuR4lMIIYQQQtiMFJ9CCCGEEMJmpPgUQgghhBA2I8WnEEIIIYSwGSk+hRBCCCGEzUjxKYQQQgghbEaKTyGEEEIIYTP/DxwYpyIuKTx9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,4)); plt.title(\"Coefficients of Selling's decomposition\")\n",
    "decomp = Selling.GatherByOffset(t,*Selling.Decomposition(D2t))\n",
    "for offset,(time,coef) in decomp.items(): plt.plot(time,coef)\n",
    "plt.legend(decomp.keys()); savefig(fig,\"Coefs_Sel2.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "In this section, we constructed a matrix decomposition whose coefficients have a bounded second order derivative."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.133880Z",
     "iopub.status.busy": "2024-04-30T09:12:21.133775Z",
     "iopub.status.idle": "2024-04-30T09:12:21.220496Z",
     "shell.execute_reply": "2024-04-30T09:12:21.220240Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,4)); plt.title(\"Coefficients of the smooth decomposition\")\n",
    "decomp = Selling.GatherByOffset(t,*smooth_decomp(D2t,order=1))\n",
    "for offset,(time,coef) in decomp.items(): plt.plot(time,coef)\n",
    "plt.legend(decomp.keys()); savefig(fig,\"Coefs_Smooth.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "In particular, their square root is Lipschitz, a property used in some convergence analyses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.222023Z",
     "iopub.status.busy": "2024-04-30T09:12:21.221918Z",
     "iopub.status.idle": "2024-04-30T09:12:21.297496Z",
     "shell.execute_reply": "2024-04-30T09:12:21.297230Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,4)); plt.title(\"Sqrt of coefficients, smooth decomposition\")\n",
    "for offset,(time,coef) in decomp.items(): plt.plot(time,np.sqrt(coef))\n",
    "plt.legend(decomp.keys(),loc=\"upper right\"); savefig(fig,\"SqCoefs_Smooth.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Choosing `order=3` in the absolute value regularization, we obtain coefficients wanishing like $\\cO(x^4)$, hence their square root vanishes like $\\cO(x^2)$, differentiably."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.298945Z",
     "iopub.status.busy": "2024-04-30T09:12:21.298847Z",
     "iopub.status.idle": "2024-04-30T09:12:21.376945Z",
     "shell.execute_reply": "2024-04-30T09:12:21.376673Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "decomp = Selling.GatherByOffset(t,*smooth_decomp(D2t,order=3))\n",
    "fig = plt.figure(figsize=(8,4)); plt.title(\"Sqrt of coefficients, smooth decomposition\")\n",
    "for offset,(time,coef) in decomp.items(): plt.plot(time,np.sqrt(coef))\n",
    "plt.legend(decomp.keys(),loc=\"upper right\"); savefig(fig,\"SqCoefs_Smooth3.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "### 4.3 Linear decomposition\n",
    "\n",
    "Selling's decomposition is piecewise linear, and is non-differentiable close to the identity matrix.\n",
    "In contrast, it can be useful in some applications to have a positive matrix decomposition that is smooth (as the previous one) or even better linear in a neighborhood of the identity matrix. We provide the following routine, which provides such a linear and non-negative decomposition for all positive definite matrices $D$ such that \n",
    "$$\n",
    "    \\kappa \\lambda_{\\max}(D) \\leq \\lambda_{min}(D), \\quad \\kappa:= \\frac {d-1}{d+1},\n",
    "$$\n",
    "using a fixed stencil of $d^2$ points.\n",
    "It appears that no decomposition with a fixed stencil and linear weights applies to a larger neighborhood of the identity matrix, defined by a smaller constant $\\kappa$ (unless there is an error in my calculations)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.378489Z",
     "iopub.status.busy": "2024-04-30T09:12:21.378375Z",
     "iopub.status.idle": "2024-04-30T09:12:21.381904Z",
     "shell.execute_reply": "2024-04-30T09:12:21.381666Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "ExportCode"
    ]
   },
   "outputs": [],
   "source": [
    "def linear_decomp_offsets(d):\n",
    "    \"\"\"The stencil for this linear decomposition is fixed and has $d^2$ elements\"\"\"\n",
    "    e = xp.eye(d).astype(int)\n",
    "    return np.concatenate(\n",
    "        (e,xp.array([e[i]+s*e[j] for i in range(d) for j in range(i) for s in (-1,1)])),axis=0).T\n",
    "\n",
    "def linear_decomp_coefs(D):\n",
    "    \"\"\"These weights depend linearly on the matrix $D$\"\"\"\n",
    "    d=len(D)\n",
    "    α=(d+1)/(2*d); β=-1/(2*d); γ=1/(4*d); δ=1/4; # ε=(d-1)/(d+1)\n",
    "    t = sum(D[i,i] for i in range(d))\n",
    "    return np.concatenate((ad.array([(α-β)*D[i,i]+β*t for i in range(d)]),\n",
    "        ad.array([γ*(D[i,i]+D[j,j])+s*δ*(D[i,j]+D[j,i]) for i in range(d) \n",
    "        for j in range(i) for s in (-1,1)]) ),axis=0)\n",
    "\n",
    "def linear_decomp(D): return linear_decomp_coefs(D),linear_decomp_offsets(len(D))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.383295Z",
     "iopub.status.busy": "2024-04-30T09:12:21.383210Z",
     "iopub.status.idle": "2024-04-30T09:12:21.385211Z",
     "shell.execute_reply": "2024-04-30T09:12:21.384959Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Two dimensional stencil:\n",
      " [[ 1  0 -1  1]\n",
      " [ 0  1  1  1]]\n",
      "Three dimensional stencil:\n",
      " [[ 1  0  0 -1  1 -1  1  0  0]\n",
      " [ 0  1  0  1  1  0  0 -1  1]\n",
      " [ 0  0  1  0  0  1  1  1  1]]\n"
     ]
    }
   ],
   "source": [
    "print(\"Two dimensional stencil:\\n\",linear_decomp_offsets(2))\n",
    "print(\"Three dimensional stencil:\\n\",linear_decomp_offsets(3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "We numerically check the announced properties of this linear decomposition, in dimensions $2$ and $3$, on a hundred matrices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.386555Z",
     "iopub.status.busy": "2024-04-30T09:12:21.386481Z",
     "iopub.status.idle": "2024-04-30T09:12:21.389144Z",
     "shell.execute_reply": "2024-04-30T09:12:21.388908Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "d=2; D = MakeRandomTensor(d,(100,),relax=0.5) \n",
    "coefs,offsets = linear_decomp_coefs(D),linear_decomp_offsets(d)\n",
    "\n",
    "# Check reconstruction\n",
    "assert allclose(Reconstruct(coefs,offsets[...,None]),D)\n",
    "\n",
    "# Check positivity for sufficiently well conditioned matrices\n",
    "poscoef = np.min(coefs,axis=0)>=0\n",
    "λmin,λmax = np.linalg.eigvalsh(np.moveaxis(D,-1,0)).T\n",
    "illcond = λmin < (d-1)/(d+1)*λmax\n",
    "assert np.all(poscoef | illcond)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.390473Z",
     "iopub.status.busy": "2024-04-30T09:12:21.390393Z",
     "iopub.status.idle": "2024-04-30T09:12:21.396575Z",
     "shell.execute_reply": "2024-04-30T09:12:21.396314Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "d=3; D = MakeRandomTensor(d,(100,),relax=0.5)\n",
    "coefs,offsets = linear_decomp_coefs(D),linear_decomp_offsets(d)\n",
    "\n",
    "# Check reconstruction\n",
    "assert np.allclose(Reconstruct(coefs,offsets[...,None]),D)\n",
    "\n",
    "# Check positivity for sufficiently well conditioned matrices\n",
    "poscoef = np.min(coefs,axis=0)>=0\n",
    "λmin,_,λmax = np.linalg.eigvalsh(np.moveaxis(D,-1,0)).T\n",
    "illcond = λmin < (d-1)/(d+1)*λmax\n",
    "assert np.all(poscoef | illcond)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "### 4.4 Automatic differentiation\n",
    "\n",
    "**Selling's decomposition** This decomposition is piecewise linear. The code is compatible with automatic differentiation, but the AD part is unstable at points of non-differentiability, which include the identity matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.397957Z",
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   "source": [
    "np.random.seed(42)\n",
    "D0 = ad.Dense.identity(constant=xp.eye(2)) # identity matrix + symbolic first order perturbation\n",
    "D0 = (D0+D0.T)/2 # Symmetrize the first order part\n",
    "D1 = D0 + 1e-4*xp.asarray(np.random.rand(2,2)-0.5) # A perturbation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "The matrices $D_0$ and $D_1$ are close, and so are their Selling decompositions.\n",
    "(Note that the stencil for $D_0$, the identity matrix, is not uniquely determined, but the Selling weight associated to the modified stencil elements is zero anyway.)\n",
    "However, the first order AD parts are different.\n",
    "\n",
    "<!---\n",
    "λ0,e0 = Selling.Decomposition(D0)\n",
    "λ1,e1 = Selling.Decomposition(D1)\n",
    "print(λ0-λ1)\n",
    "--->"
   ]
  },
  {
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    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 69,
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   ],
   "source": [
    "λ0,e0 = Selling.Decomposition(D0)\n",
    "λ1,e1 = Selling.Decomposition(D1)\n",
    "# In other cases, λ1 may need to be permuted, to account for arbitrary ordering of e0,e1\n",
    "λdiff = λ0-λ1\n",
    "assert np.max(np.abs(λdiff.value)) < 1e-4 # The coefficients values are close\n",
    "np.max(np.abs(λdiff.coef)) # The coefficient derivatives are different"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "**Smoothed variant of Selling's decomposition.** The previous instability phenomenon is avoided with the smooth variant of the decomposition.\n",
    "\n",
    "Note that the *ordering* of the stencil elements, is not uniquely determined. But this can be dealt with easily by putting them into some canonical ordering."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "editable": true,
    "execution": {
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   "source": [
    "λ0,e0 = smooth_decomp(D0)\n",
    "λ1,e1 = smooth_decomp(D1)\n",
    "# λ1 is reversed here to account for reversed ordering of the offsets e0 and e1 \n",
    "# (An arbitrary permutation is possible in general)\n",
    "λdiff = λ0-λ1[::-1] \n",
    "assert np.max(np.abs(λdiff.value))<1e-4 # The coefficients are close\n",
    "assert np.max(np.abs(λdiff.coef))<2e-4 # The coefficient derivatives are close"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "**Linear variant.**\n",
    "The linear decomposition presented above only applies to positive definite matrices whose condition number is sufficiently small. Since it linear, however, not only the coefficients are close, but their derivatives are identical. The offsets are also, of course, identical."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.410088Z",
     "iopub.status.busy": "2024-04-30T09:12:21.410005Z",
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   "source": [
    "λ0 = linear_decomp_coefs(D0)\n",
    "λ1 = linear_decomp_coefs(D1)\n",
    "λdiff = λ0-λ1 # Always the same ordering here\n",
    "assert np.max(np.abs(λdiff.value))<1e-4 # The coefficients are close\n",
    "assert np.max(np.abs(λdiff.coef))==0 # Their derivatives are identical"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "## 5. Convolved decomposition\n",
    "\n",
    "Another approach to obtain smooth Selling-like coefficients and decomposition is to convolve them. However, this raises the issue of the consistency of the matrix decomposition. \n",
    "\n",
    "If the matrix field is initially given as a convolution,\n",
    "$$\n",
    "    D = D_0 \\star G_\\sigma,\n",
    "$$\n",
    "where $G_\\sigma$ is e.g. a Gaussian kernel, one simply needs to decompose $D_0$ \n",
    "$$\n",
    "    D_0(x) = \\sum_{e \\in \\bZ^d} \\lambda_0^e (x) e e^\\top\n",
    "$$\n",
    "and convolve the obtained coefficients \n",
    "$$\n",
    "    D(x) = \\sum_{e \\in \\bZ^d} \\lambda^e(x) e e^\\top, \\text{ where } \\lambda^e = \\lambda^e_0 \\star G_\\sigma.\n",
    "$$\n",
    "\n",
    "**Possible applications.**\n",
    "In some cases, the matrix field $D$ may be directly given in a convolution form. For instance, in seismic tomography, the model coefficients are obtained from gradient backpropagation, which undergoes Gaussian smoothing. \n",
    "In general, however, the matrix field $D(x)$ has no reason to be of this form. If it is sufficiently smooth, however, then one may de-convolve $D$ to obtain $D_0$. \n",
    "We choose deconvolve using the routines developed for spline coefficients, which have a small stencil of $k$ pixels for order $k$ splines."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Deconvolution is easily computed using the Fourier transform. More precisely, consider the optimization problem\n",
    "$$\n",
    "    \\min_u \\|G \\star u - v\\|^2 + \\epsilon^2 \\|u\\|^2,\n",
    "$$\n",
    "where $G$ is some convolution kernel, and $\\epsilon>0$ is a relaxation parameter.\n",
    "Assuming periodic boundary conditions, the solution is obtained explicitly as \n",
    "$$\n",
    "    \\hat u := \\frac {\\overline {\\hat G} v}{\\epsilon^2 + |\\hat G|^2}.\n",
    "$$\n",
    "\n",
    "\n",
    "**Notes of caution.**\n",
    "- (Unstability) De-convolution is in unstable, in the limit as $\\epsilon\\to 0$. One of the consequences of this unstability is that the deconvolved tensors may not be positive definite.\n",
    "- (Number of coefficients and complexity.) The number of positive coefficients $\\#\\{e \\mid \\lambda^e(x)>0\\}$ after convolution exceeds the original number $\\#\\{e \\mid \\lambda^e_0(x)>0\\}$, possibly substantially. Very small coefficients are eventually pruned, but the convolution computation may hold large intermediate results. In addition, one cannot bound a priori the number of positive decomposition coefficients. \n",
    "\n",
    "**Alternatives** If the dimension is $d=2$, or if the condition number is sufficiently small, the one can use then the previously introduced smooth and linear decompositions. In dimension $d=3$, we also present below a smooth decomposition, albeit more experimental and costly.\n",
    "\n",
    "<!---\n",
    "def conv_circulant(circ,val):\n",
    "    from numpy.fft import fft,ifft\n",
    "    \"\"\"Product of a circulant matrix with an array of values, computed using the FFT.\"\"\"\n",
    "    return np.moveaxis(ifft(fft(np.moveaxis(val,0,-1)) * fft(circ)).real,-1,0)\n",
    "\n",
    "def conv_decomp(D,order=5,periodic=True,rtol=1e-10):\n",
    "    \"\"\"Deconvolve the matrix field D, apply Selling's decomposition, then convolve the coefficients.\n",
    "    - D : positive definite matrix field, of shape (d,d,n1,...,nk). Convolution is applied to axes n1,...,nk.\n",
    "    - order (either 3, 5 or 7): spline interpolation order\n",
    "    - periodic : choose between periodic and reflected boundary conditions\n",
    "    - rtol : relative tolerance for eliminating small coefficients.\n",
    "    \"\"\"\n",
    "    D = Interpolation.spline_coefs(D,depth=2,order=order,periodic=periodic) # Deconvolution\n",
    "    tol = rtol * lp.trace(D) # Compute absolute tolerance\n",
    "    λ,e = Selling.Decomposition(D) # Selling decomposition\n",
    "    vdim = len(e)\n",
    "    shape = λ[0].shape\n",
    "    pos = np.argmax(e!=0,axis=0) # position of the first non-zero coefficient\n",
    "    e *= np.sign(np.take_along_axis(e,pos[None],0)) # Normalized offset, starts > 0\n",
    "    emax = np.max(np.abs(e))\n",
    "    r = 2*emax+1 # Base exponent for conversion to integer\n",
    "    ie = sum(e[i] * r**(vdim-i-1) for i in range(vdim)) # Convert offsets to integers\n",
    "    Λ = ad.Sparse.spAD(np.zeros_like(λ[0]),np.moveaxis(λ,0,-1),np.moveaxis(ie,0,-1))\n",
    "    Λ = Λ.tangent_operator().todense() # Possible improvement : optimization opportunities here\n",
    "    Λ = np.moveaxis(np.asarray(Λ).reshape((*shape,-1)),-1,0)\n",
    "    Λ = Interpolation.spline_coefs(Λ,depth=1,solver=conv_circulant,order=order,periodic=periodic)\n",
    "    Λ = np.roll(Λ,order-1,axis=tuple(range(1,Λ.ndim)))\n",
    "    Λ[np.abs(Λ)<=tol]=0 # Remove almost zero coefficients\n",
    "    index = fd.as_field(np.arange(len(Λ)),shape,depth=1)\n",
    "    x = ad.Sparse.spAD(np.zeros_like(λ[0]),np.moveaxis(Λ,0,-1),np.moveaxis(index,0,-1))\n",
    "    x.simplify_ad() # Remove null coefficients.\n",
    "    λ = np.moveaxis(x.coef,-1,0) # The new coefficients\n",
    "    ie = np.moveaxis(x.index,-1,0) # The new offsets, for now as integers\n",
    "    e = []\n",
    "    for i in range(vdim):\n",
    "        mod = ie%r\n",
    "        pos = mod>emax\n",
    "        ie = (ie//r)+pos\n",
    "        e.append(np.where(pos,mod-r,mod))\n",
    "    return λ,np.array(e[::-1])\n",
    "--->"
   ]
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   "source": [
    "def deconv(arr,σ=5.,ϵ=0.05,periodic=True,depth=0,real=True):\n",
    "    \"\"\"\n",
    "    Input : \n",
    "    - σ : standard deviation of Gaussian kernel in pixels. Alternatively, provide an exact kernel. (Same for all axes.)\n",
    "    - ϵ : stability parameter for the deconvolution\n",
    "    - periodic : choose between periodic and reflected boundary conditions\n",
    "    - depth : initial dimensions, not touched by the convolution\n",
    "    - real : extract the real part after convolutions, deconvolutions\n",
    "\n",
    "    Returns : \n",
    "    - deconvolved array\n",
    "    - function to convolve back\n",
    "    \"\"\"\n",
    "    from numpy.fft import fft,ifft\n",
    "    fkernels = []\n",
    "    def reflect(arr,axis): return np.concatenate((arr,arr[(slice(None),)*axis+(slice(None,None,-1),)]),axis)\n",
    "    def half(arr,axis): return arr[(slice(None),)*axis+(slice(0,arr.shape[axis]//2),)]\n",
    "    for i,s in enumerate(arr.shape[depth:]):\n",
    "        s2 = s if periodic else 2*s # Size of kernel\n",
    "        if np.ndim(σ)==0: # Use Gaussian convolution kernel\n",
    "            x = np.arange(s2)\n",
    "            x[x>=x.size/2]-=x.size # Periodic boundary conditions\n",
    "            kernel = np.exp(-x**2/(2*σ**2)) / (np.sqrt(2*π)*σ)\n",
    "        elif np.ndim(σ)==1: # Use provided kernel\n",
    "            kernel = np.roll(np.pad(σ,(0,s2-len(σ))),-(len(σ)//2))\n",
    "        fkernel = fft(kernel)\n",
    "        fkernels.append(fkernel)\n",
    "        ikernel = np.conj(fkernel)/(ϵ**2+np.abs(fkernel)**2) # Deconvolution kernel\n",
    "        if not periodic: arr = reflect(arr,depth+i)\n",
    "        arr = ifft(fft(arr,axis=depth+i)*np.expand_dims(ikernel,tuple(range(depth+1+i-arr.ndim,0))),axis=depth+i)\n",
    "        if not periodic: arr = half(arr,depth+i)\n",
    "        if real: arr = arr.real\n",
    "\n",
    "    def conv(arr,depth=depth):\n",
    "        for i,fkernel in enumerate(fkernels):\n",
    "            if not periodic: arr = reflect(arr,depth+i)\n",
    "            arr = ifft(fft(arr,axis=depth+i)*np.expand_dims(fkernel,tuple(range(depth+1+i-arr.ndim,0))),axis=depth+i)\n",
    "            if not periodic: arr = half(arr,depth+i)\n",
    "            if real: arr = arr.real\n",
    "        return arr\n",
    "    \n",
    "    return arr,conv"
   ]
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(42)\n",
    "D0 = MakeRandomTensor(2)\n",
    "D1 = MakeRandomTensor(2)\n",
    "t,dt = np.linspace(0,π,20,endpoint=False,retstep=True) # True periodicity with endpoint=False only\n",
    "t+=dt/2\n",
    "D = D0[:,:,None]*np.cos(t)**2 + D1[:,:,None]*np.sin(t)**2\n",
    "deconvD,reconv = deconv(D,σ=3.,depth=2,ϵ=0.05,periodic=False)\n",
    "reconvD = reconv(2*deconvD)/2\n",
    "plt.plot(D[0,0],label='D')\n",
    "plt.plot(deconvD[0,0],label='deconvD')\n",
    "plt.plot(reconvD[0,0],label='reconvD') \n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.483942Z",
     "iopub.status.busy": "2024-04-30T09:12:21.483838Z",
     "iopub.status.idle": "2024-04-30T09:12:21.488173Z",
     "shell.execute_reply": "2024-04-30T09:12:21.487922Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "ExportCode"
    ]
   },
   "outputs": [],
   "source": [
    "def conv_decomp(deconvD,conv,rtol=1e-6):\n",
    "    \"\"\"Apply Selling's decomposition, then convolve the coefficients, and finally prune the small ones.\n",
    "    - deconvD : deconvolved positive definite matrix field. \n",
    "    - conv : convolution operator\n",
    "    - rtol : relative tolerance for eliminating small coefficients.\n",
    "    \"\"\"\n",
    "    tol = rtol * lp.trace(deconvD) # Compute absolute tolerance\n",
    "    λ,e = Selling.Decomposition(deconvD) # Selling decomposition\n",
    "    vdim = len(e)\n",
    "    shape = λ[0].shape\n",
    "    pos = np.argmax(e!=0,axis=0) # position of the first non-zero coefficient\n",
    "    e *= np.sign(np.take_along_axis(e,pos[None],0)) # Normalized offset, starts > 0\n",
    "    emax = np.max(np.abs(e))\n",
    "    r = 2*emax+1 # Base exponent for conversion to integer\n",
    "    ie = sum(e[i] * r**(vdim-i-1) for i in range(vdim)) # Convert offsets to integers\n",
    "    Λ = ad.Sparse.spAD(np.zeros_like(λ[0]),np.moveaxis(λ,0,-1),np.moveaxis(ie,0,-1))\n",
    "    Λ = Λ.tangent_operator().todense() # Possible improvement : optimization opportunities here\n",
    "    Λ = np.moveaxis(np.asarray(Λ).reshape((*shape,-1)),-1,0)\n",
    "    Λ = conv(Λ,depth=1)\n",
    "    Λ[np.abs(Λ)<=tol]=0 # Remove almost zero coefficients\n",
    "    index = fd.as_field(np.arange(len(Λ)),shape,depth=1)\n",
    "    x = ad.Sparse.spAD(np.zeros_like(λ[0]),np.moveaxis(Λ,0,-1),np.moveaxis(index,0,-1))\n",
    "    x.simplify_ad() # Remove null coefficients.\n",
    "    λ = np.moveaxis(x.coef,-1,0) # The new coefficients\n",
    "    ie = np.moveaxis(x.index,-1,0) # The new offsets, for now as integers\n",
    "    e = []\n",
    "    for i in range(vdim): # Expand the offsets, as vectors\n",
    "        mod = ie%r\n",
    "        pos = mod>emax\n",
    "        ie = (ie//r)+pos\n",
    "        e.append(np.where(pos,mod-r,mod))\n",
    "    return λ,np.array(e[::-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to check the correctness of the code, we remove the relaxation parameter $\\epsilon=0$, and check for machine precision equality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.489606Z",
     "iopub.status.busy": "2024-04-30T09:12:21.489526Z",
     "iopub.status.idle": "2024-04-30T09:12:21.494461Z",
     "shell.execute_reply": "2024-04-30T09:12:21.494202Z"
    }
   },
   "outputs": [],
   "source": [
    "D0,D1,D2 = (np.eye(2),[[1,-0.1],[-0.1,1]],[[1,0.1],[0.1,1]])\n",
    "D = np.stack((D0,D1,D2,D0,D2,D0,D1),axis=-1)\n",
    "for order in (3,5,7):\n",
    "    σ = Interpolation.spline_base(0,3)[1:] # Using a convolution kernel corresponding to spline interpolation\n",
    "    deconvD,reconv = deconv(D,σ,ϵ=0,depth=2) # No relaxation (ϵ=0)\n",
    "    assert np.allclose(reconv(deconvD),D) # Reconvolution of D is exact\n",
    "    λ,e = conv_decomp(deconvD,reconv,rtol=1e-10)\n",
    "    rec = np.sum(λ*lp.outer_self(e),axis=2)\n",
    "    assert np.allclose(rec,D) # Reconstruction of D from convolved coefficients is exact"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.495875Z",
     "iopub.status.busy": "2024-04-30T09:12:21.495792Z",
     "iopub.status.idle": "2024-04-30T09:12:21.497870Z",
     "shell.execute_reply": "2024-04-30T09:12:21.497634Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "np.random.seed(42)\n",
    "D0 = MakeRandomTensor(2)\n",
    "D1 = MakeRandomTensor(2)\n",
    "t = np.linspace(0,π,100,endpoint=False)\n",
    "D2t = D0[:,:,None]*np.cos(t)**2 + D1[:,:,None]*np.sin(t)**2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tuning the convolution kernel width $\\sigma$ (measured in pixels) requires some attention : \n",
    "- if $\\sigma$ is too small, then the obtained coefficients are not very smooth.\n",
    "- if $\\sigma$ is too large, then the deconvolved matrices may be highly anisotropic or non-positive. As a result, Selling's decomposition may involve large offsets or fail.\n",
    "\n",
    "In the example below, $\\sigma = 3$ is the good choice."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "editable": true,
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.499338Z",
     "iopub.status.busy": "2024-04-30T09:12:21.499250Z",
     "iopub.status.idle": "2024-04-30T09:12:21.730920Z",
     "shell.execute_reply": "2024-04-30T09:12:21.730625Z"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x1200 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[8,12])\n",
    "for i,σ in enumerate((1.5,3,4)):\n",
    "    λ,e = conv_decomp(*deconv(D2t,σ,depth=2))\n",
    "    rec = np.sum(λ*lp.outer_self(e),axis=2)\n",
    "\n",
    "    decomp = Selling.GatherByOffset(t,λ,e)\n",
    "    plt.subplot(3,1,1+i)\n",
    "    plt.title(f\"Sqrt of coefficients, convolved decomposition, {σ=}\")\n",
    "    for offset,(time,coef) in decomp.items(): plt.plot(time,np.sqrt(coef))\n",
    "    plt.legend(decomp.keys(),loc=\"upper right\"); savefig(fig,f\"SqCoefs_Conv{order}.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## 6. Smooth three-dimensional decomposition\n",
    "\n",
    "As a proof of concept, we present a smooth variant of Selling's three dimensional decomposition. \n",
    "\n",
    "**Superbases and Selling's transformation.** In order to describe our matrix decomposition, we recall that a superbase of $\\bZ^3$ is a tuple $(b_0,b_1,b_2,b_3)\\in (\\bZ^3)^4$ such that \n",
    "\\begin{align*}\n",
    "    b_0+b_1+b_2+b_3 &=0, & |\\det(b_1,b_2,b_3)| &=1.\n",
    "\\end{align*}\n",
    "In our application, superbases are considered up to a re-ordering of their elements, and to a global change of sign $(-b_0,-b_1,-b_2,-b_3)$. Given a matrix $D \\in S_3^{++}$, the energy of a superbase reads\n",
    "$$\n",
    "    \\cE_D(b_0,b_1,b_2,b_3) = \\frac 1 2 \\sum_{0 \\leq i \\leq 3} \\|b_i\\|_D^2.\n",
    "$$ \n",
    "Selling's transformation of a superbase takes the form $(-b_i,b_j,b_i+b_k,b_i+b_l)$\n",
    "where $(i,j,k,l)$ is any permutation of $(0,1,2,3)$. It satisfies\n",
    "$$\n",
    "    \\cE_D(-b_i,b_j,b_i+b_k,b_i+b_l) = \\cE_D(b_0,b_1,b_2,b_3) - \\<b_i,D b_j\\>. \n",
    "$$\n",
    "\n",
    "Selling's algorithm starts from an arbitrary superbase, and iteratively applies Selling's transformations whenever a pair of indices $(i,j)$ satisfies $\\<b_i,D b_j\\> > 0$. It can be shown that this procedure terminates, thus produces an $D$-obtuse superbase (i.e. $\\<b_i,D b_j\\> \\leq 0$, for any pair of indices), which globally minimizes the energy $\\cE_D$ among all superbases.\n",
    "\n",
    "Eventually, Selling's decomposition reads denoting $v_{ij} := b_i \\times b_j$\n",
    "$$\n",
    "    D = \\sum_{0\\leq i<j\\leq 3} (-\\<b_i,D b_j\\>) v_{ij} \\otimes v_{ij}.\n",
    "$$\n",
    "It can be shown that this decomposition, whose coefficients can be denoted $\\lambda : \\bZ^3 \\to [0,\\infty[$, is a global minimizer to the linear program defined by maximizing \n",
    "\\begin{align*}\n",
    "    & \\sum_{e \\in \\bZ^3\\setminus\\{0\\}} \\lambda(e) & \\text{s.t.}\\quad D &= \\sum_{e \\in \\bZ^3} \\lambda(e) e e^\\top.\n",
    "\\end{align*}\n",
    "\n",
    "\n",
    "**Variant of the decomposition.**\n",
    "The idea is to solve a modified optimization problem, featuring penalty terms depending on the matrix $D$ and providing some control over the  decomposition coefficients $\\lambda$ : a logarithmic barrier enforces their positivity, and a quadratic penalization ensures their smallness. The penalty terms must depend smoothly on $D$, and be carefully tuned to ensure that the solution exists and depends smoothly on $D$.  \n",
    "\n",
    "I slightly more detail, the steps of the modified decomposition are as follows : \n",
    "1. Attribute weights $\\rho_D(B)$ to all superbases of $\\bZ^3$ (considered up to a permutation and a change of sign). The weights must be (i) non-negative, (ii) finitely supported, (iii) positive for all superbases minimizing $\\cE_D(B)$, (iv) depend smoothly on $D \\in S_3^{++}$.\n",
    "2. Attribute weights $\\mu_D(e)$ to all vectors $e \\in \\bZ^3/\\pm$ (considered up to a change of sign). We define $\\mu_D(e)$ as the sum of $\\rho_D(B)$ among all superbases $B = (b_0,b_1,b_2,b_3)$ such that $e = b_i \\times b_j$ for some $0 \\leq i \\leq j \\leq 3$. \n",
    "3. Define the decomposition $\\lambda : \\bZ^3/\\pm \\to [0,\\infty[$ as the one minimizing the energy\n",
    "\\begin{align*}\n",
    "    &\\sum_{e \\in \\bZ^3/\\pm,\\, \\rho_D(e)>0} \\Big(- \\lambda(e)/\\epsilon - \\mu_D(e) \\ln \\lambda(e) + \\frac {\\lambda(e)^2}{2 \\mu_D(e)}\\Big) &\n",
    "  \\text{s.t.}\\quad D = \\sum_{e \\in \\bZ^3/\\pm} \\lambda(e) e e^\\top,\n",
    "\\end{align*}\n",
    "where $\\epsilon>0$ is a relaxation parameter. The usual Selling decomposition is recovered in the limit as $\\epsilon\\to 0$.\n",
    "\n",
    "**Magic numbers.**\n",
    "For any $D \\in S_3^{++}$, there are at most $16$ superbases $B$ for which $\\cE_D(B)$ is minimal, and $36$ superbases $B$ for which $\\cE_D(B)$ is second to minimal. Furthermore all these $16+36 = 52$ superbases can be obtained by applying at most $5$ Selling transformations to an arbitrary $D$-obtuse superbase. These bounds are attained for $D=\\mathrm{Id}$, have no published proof but seem very likely, and are implicitely used in the construction of the weights $\\rho_D(B)$ coded below. \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.1 Python implementation\n",
    "\n",
    "**Caution.** The code below is not backed by a full theoretical analysis, is very slow, and can likely be improved in many ways (e.g. by tuning the parameters)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.733410Z",
     "iopub.status.busy": "2024-04-30T09:12:21.733305Z",
     "iopub.status.idle": "2024-04-30T09:12:21.758330Z",
     "shell.execute_reply": "2024-04-30T09:12:21.758050Z"
    }
   },
   "outputs": [],
   "source": [
    "from agd.ExportedCode.Notebooks_Div import WaveExamples as we\n",
    "from agd.Metrics import misc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.760098Z",
     "iopub.status.busy": "2024-04-30T09:12:21.760006Z",
     "iopub.status.idle": "2024-04-30T09:12:21.987481Z",
     "shell.execute_reply": "2024-04-30T09:12:21.987200Z"
    }
   },
   "outputs": [],
   "source": [
    "# Neighbors up to distance 5 on Selling's graph of superbases (Ryskov's 3D polyhedron)\n",
    "_neigh_energy = 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1,1,1,6,4,10],[3,4,2,13,10,15],[3,2,1,11,5,11],[3,3,1,13,7,15],[1,1,1,5,5,9],[2,4,3,10,11,13],[1,2,3,5,7,7],[1,3,3,6,10,10],[5,9,5,15,16,13],[3,4,3,7,9,7],[3,7,5,10,14,10],[7,8,3,17,11,11],[9,13,5,23,17,15],[6,8,3,16,11,11],[7,11,5,20,17,15],[5,9,5,13,13,9],[7,8,3,13,9,7],[9,13,5,21,16,13],[7,11,5,16,14,10],[7,3,1,12,4,6],[9,5,1,15,5,7],[6,4,1,12,5,7],[7,6,2,15,8,9],[3,2,2,5,6,5],[5,1,1,5,3,3],[5,6,2,15,10,13],[3,3,1,7,5,7],[3,3,1,10,6,10],[7,9,3,17,11,11],[9,10,3,23,13,15],[7,9,3,20,13,15],[9,8,2,21,10,13],[7,5,1,16,6,10],[3,1,1,5,4,5],[3,-1,1,1,3,3],[1,-1,3,-1,9,7],[1,-1,3,0,8,6],[1,1,3,3,10,9],[1,1,3,2,9,7],[3,7,5,11,16,13],[3,5,3,7,9,7],[1,3,5,5,16,13],[1,3,5,4,14,10],[1,3,3,6,11,11],[2,6,5,10,17,15],[1,3,3,5,11,11],[1,4,5,7,17,15],[3,4,2,11,10,13],[3,2,1,7,5,7],[1,0,1,1,5,7],[1,2,2,5,10,13],[1,1,1,4,6,10],[2,4,3,10,13,15],[1,2,3,5,11,11],[1,3,3,7,13,15],[5,9,5,16,15,13],[3,4,3,9,7,7],[3,8,7,11,17,11],[5,13,9,17,23,15],[3,8,6,11,16,11],[5,11,7,17,20,15],[3,8,7,9,13,7],[5,13,9,16,21,13],[5,11,7,14,16,10],[2,2,3,6,5,5],[1,1,5,3,5,3],[1,4,6,5,12,7],[2,6,7,8,15,9],[1,3,7,4,12,6],[1,5,9,5,15,7],[2,6,5,10,15,13],[1,3,3,5,7,7],[3,9,7,11,17,11],[3,10,9,13,23,15],[3,9,7,13,20,15],[2,8,9,10,21,13],[1,5,7,6,16,10]],dtype=np.int8)\n",
    "_neigh_uoffset = np.array([[2,1,0],[2,0,1],[1,1,-1],[1,0,1],[1,0,0],[0,1,-1],[1,1,0],[0,0,1],[2,2,-1],[1,-1,1],[0,1,0],[1,1,1],[1,0,2],[0,1,-2],[1,2,-2],[1,-1,2],[1,1,-2],[1,0,-1],[1,2,-1],[2,1,-1],[2,1,1],[2,1,-2],[0,1,1],[1,2,0],[1,0,-2],[1,-1,-1],[1,-1,0],[2,0,-1],[1,3,-1],[1,3,-2],[2,3,-2],[2,3,-1],[0,2,-1],[1,-2,1],[1,-2,0],[1,-2,2],[2,-2,1],[2,-1,0],[2,-1,1],[2,-1,-1],[1,-2,-1],[2,-1,-2],[1,-1,-2],[2,-2,-1],[2,1,-3],[2,0,-3],[2,2,-3],[2,1,-4],[1,0,-3],[1,1,-3],[2,3,-4],[1,3,-3],[2,3,-3],[1,2,-3],[0,1,-3],[1,2,-4],[0,2,-3],[3,2,-3],[3,2,-4],[3,1,-3],[3,1,-2],[3,0,-2],[3,-1,-1],[3,0,-1],[1,-3,1],[0,3,-2],[0,3,-1],[3,2,-1],[3,2,-2],[3,1,-1],[1,2,1],[0,1,2],[0,2,1],[2,-1,2],[1,-1,3],[1,-2,3],[2,-2,3],[2,-1,3],[2,-3,1],[2,-3,0],[2,-3,2],[2,-4,1],[1,-3,0],[2,-4,3],[1,-3,3],[2,-3,3],[1,-3,2],[1,-4,2],[3,-3,2],[3,-4,2],[3,-3,1],[3,-2,1],[3,-2,0],[3,-1,0],[3,-1,2],[3,-2,2],[3,-1,1],[1,1,2],[1,-2,-2],[3,-1,-2],[3,-2,-2],[3,-2,-1],[2,-3,-1],[2,-3,-2],[2,-4,-1],[1,-3,-1],[1,1,-4],[3,-1,-4],[3,-2,-3],[3,-1,-3],[2,-1,-3],[2,-1,-4],[2,-2,-3],[1,-1,-3],[1,-4,1],[3,-4,-1],[3,-3,-2],[3,-3,-1],[1,-2,-3],[4,-1,-2],[4,-3,-2],[4,-2,-1],[4,-2,-3],[1,-3,-2],[4,-2,1],[1,-3,4],[1,-2,4],[4,-1,-1],[4,-3,1],[4,1,-2],[1,4,-3],[1,4,-2],[4,1,-3]],dtype=np.int8)\n",
    "_neigh_ioffset = 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  {
   "cell_type": "code",
   "execution_count": 80,
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    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.989268Z",
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   "source": [
    "def tADA(A,D): return lp.dot_AA(np.moveaxis(A,0,1),lp.dot_AA(D,A))\n",
    "\n",
    "def _smooth3_decomp(D,e,μ):\n",
    "    \"\"\"Decompose D over the offsets e, with weights μ for the modified optimization problem\"\"\"\n",
    "    sdetD = np.linalg.det(D)**(1/3) # normalize D for unit determinant (unless weights are homogeneous w.r.t D)\n",
    "    D/=sdetD\n",
    "    # The equality constraint D = sum λ(e) e e^T is used to eliminate 6 variables\n",
    "    A = misc.flatten_symmetric_matrix(lp.outer_self(e))\n",
    "    iA = np.linalg.inv(A[:,:6])\n",
    "    rA = A[:,6:]\n",
    "    Dflat = misc.flatten_symmetric_matrix(D)\n",
    "    def complement(λ): return np.concatenate( (lp.dot_AV(iA, Dflat-lp.dot_AV(rA,λ)), λ) )\n",
    "    # The logarithmic barrier and squared penalty in the optimization problem control the coefficients range\n",
    "    ϵ = 0.1 # Recover Selling as ϵ->O\n",
    "    def objective(λ): λ = complement(λ); return np.sum(-λ/ϵ - μ*np.log(λ) + 0.5*λ**2/μ)\n",
    "    # Build the initial guess\n",
    "    D0 = misc.expand_symmetric_matrix(A@μ)\n",
    "    r = np.linalg.norm(D0 @ np.linalg.inv(D))\n",
    "    x0 = (μ/r)[6:]\n",
    "    while np.any(complement(x0)<0): x0/=1.3\n",
    "    x = ad.Optimization.newton_minimize(objective,x0,f_value_gradient_direction='Dense2',maxiter=20,verbosity=-1)\n",
    "    return complement(x)*sdetD\n",
    "\n",
    "def _smooth3_energies(e,order=4):\n",
    "    \"\"\"Get approximately the 0th and 16th energy, in a smooth way\"\"\"\n",
    "    r = 2 # transition stiffness, should be >=2. Obtain e[0],e[16] as r->infty\n",
    "    def objective(ext):\n",
    "        emin,emax=ext; eδ = (emax-emin)/r\n",
    "        return ad.array([we.heaviside((emin-e)/eδ,order).sum()-0.5, we.heaviside((emax-e)/eδ,order).sum()-16.5])\n",
    "    return ad.Optimization.newton_root(objective,e[[0,16]],ad='Dense',stop={'verbosity':0})\n",
    "        \n",
    "def _smooth3_cutoff(energy,emin,emax,order=4):\n",
    "    r = 2 # Cutoff parameter, should be >=1. Large values yield fewer positive offsets, but possibly less smoothness.\n",
    "    eδ = (emax-emin)/r \n",
    "    x = np.maximum(0,emin+eδ-energy)/eδ # 1 at minimum energy, 0 at cutoff and after\n",
    "    return we.heaviside(2*x-1,order) # Needs smooth extrema to get expected smoothness\n",
    "\n",
    "def smooth3_decomp(D,smoothness_order=6):\n",
    "    \"\"\"Smooth variant of Selling's decomposition\"\"\"\n",
    "    sb = Selling.ObtuseSuperbase(D)\n",
    "    D = tADA(sb[:,:3],D) # Unimodular change of coordinates, so that the canonical superbase becomes optimal\n",
    "    energies = _neigh_energy@misc.flatten_symmetric_matrix(D) # Should include all minimal energies, and all next level too\n",
    "    # Fit the table, compute the superbase weights. \n",
    "    ord = np.argsort(energies,axis=-1) # Only need the 17 first elements (at most 16 attain the minimum energy)\n",
    "    energies = energies[ord]\n",
    "    emin,emax = _smooth3_energies(energies,smoothness_order)\n",
    "    ρ = _smooth3_cutoff(energies,emin,emax,smoothness_order)\n",
    "    pos = ρ>0\n",
    "    ord = ord[pos]\n",
    "    ρ = ρ[pos]\n",
    "    ρ /= ρ.sum()\n",
    "    \n",
    "    # Get the stencil, and associated weights\n",
    "    moffset = _neigh_ioffset[ord] # Offsets associated to all candidate superbases\n",
    "    ioffset = np.unique(moffset.reshape(-1))\n",
    "    ioffset = np.concatenate((moffset[0],np.setdiff1d(ioffset,moffset[0])))\n",
    "    offsets = np.moveaxis(_neigh_uoffset[ioffset],1,0)\n",
    "    μ = np.sum([ρ*np.any(moffset==i,axis=1) for i in ioffset],axis=1)\n",
    "    # Solve an optimization problem. We want to guarantee that the weights are non-negative\n",
    "    sol = _smooth3_decomp(D,offsets,μ)\n",
    "    # Map back the offsets using A\n",
    "    A = np.linalg.inv(sb[:,:3]).T.round().astype(int)\n",
    "    offsets = lp.dot_AV(A[:,:,None],offsets)\n",
    "    return sol,offsets #,λ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:21.996980Z",
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     "shell.execute_reply": "2024-04-30T09:12:22.005642Z"
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   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jean-mariemirebeau/Dropbox/Programmes/GithubM1/AdaptiveGridDiscretizations/agd/AutomaticDifferentiation/Base.py:46: RuntimeWarning: invalid value encountered in log\n",
      "  def log(x):\ty=1./x; return (np.log(x),y,-y**2)\n",
      "/var/folders/pr/ywmc0vdj1_q45y494__w0nsr0000gn/T/ipykernel_72775/2393254036.py:15: RuntimeWarning: invalid value encountered in log\n",
      "  def objective(λ): λ = complement(λ); return np.sum(-λ/ϵ - μ*np.log(λ) + 0.5*λ**2/μ)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([1.14291728, 4.33762813, 0.79610349, 0.48048527, 2.28577442, 2.08181777, 0.04544158, 0.10191819, 0.00456276]),\n",
       " array([[ 1,  1,  0,  1,  1,  0,  2,  0,  0],\n",
       "        [ 1,  0,  1,  0, -1,  1,  0,  2,  0],\n",
       "        [-1,  0,  0, -1,  0, -1, -1, -1,  1]]))"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D = Riemann.needle((1,2,3.),1,3).m\n",
    "#D = np.eye(3)\n",
    "#D = misc.expand_symmetric_matrix([ 3., -1.,  1., -1.,  0.,  1.])\n",
    "#D = misc.expand_symmetric_matrix([2,-1,1,0,0,1.])\n",
    "#np.sum(smooth_decomp3(D)<=4.01)\n",
    "λ,e = smooth3_decomp(D)[:2]\n",
    "rec = np.sum(λ*lp.outer_self(e),axis=2)\n",
    "assert np.allclose(rec,D)\n",
    "λ,e"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The coefficients are smooth as desired. They also vanish smoothly, and as a result their square root is also smooth, which is needed in some applications."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:22.007450Z",
     "iopub.status.busy": "2024-04-30T09:12:22.007362Z",
     "iopub.status.idle": "2024-04-30T09:12:23.127183Z",
     "shell.execute_reply": "2024-04-30T09:12:23.126893Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/pr/ywmc0vdj1_q45y494__w0nsr0000gn/T/ipykernel_72775/2393254036.py:15: RuntimeWarning: invalid value encountered in log\n",
      "  def objective(λ): λ = complement(λ); return np.sum(-λ/ϵ - μ*np.log(λ) + 0.5*λ**2/μ)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Random matrices\n",
    "np.random.seed(38)\n",
    "relax = 0.5\n",
    "D0,D1 = np.random.randn(2,3,3)\n",
    "D0,D1 = [lp.dot_AA(D.T,D)+relax*np.eye(3) for D in (D0,D1)]\n",
    "\n",
    "tmin,tmax = 0,1\n",
    "T = np.linspace(tmin,tmax,200)\n",
    "D = (1-T)*D0[:,:,None]+T*D1[:,:,None]\n",
    "decomps = [smooth3_decomp(Di)[:2] for Di in np.moveaxis(D,-1,0)]\n",
    "nmax = np.max([len(λ) for (λ,_) in decomps])\n",
    "λ = np.zeros((nmax,len(decomps)))\n",
    "e = np.zeros((3,nmax,len(decomps)),dtype=int)\n",
    "for i,(λi,ei) in enumerate(decomps):\n",
    "    ni = len(λi)\n",
    "    λ[:ni,i]=λi\n",
    "    e[:,:ni,i]=ei\n",
    "\n",
    "rec = np.sum(λ*lp.outer_self(e),axis=2)\n",
    "assert np.allclose(rec,D)\n",
    "\n",
    "decomp = Selling.GatherByOffset(T,λ,e)\n",
    "fig = plt.figure(figsize=(16,8)); plt.title(f\"Sqrt of coefficients\")\n",
    "for offset,(time,coef) in decomp.items(): plt.plot(time,np.sqrt(coef))\n",
    "#plt.ylim(0,0.3)\n",
    "plt.legend(decomp.keys(),loc=\"upper right\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The decomposition uses more offsets than the usual Selling decomposition, as expected. A preliminary analysis suggests that a smooth decomposition exists that uses at most 13 offsets, which should achievable with the above method (possibly suitably tuned)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:23.129090Z",
     "iopub.status.busy": "2024-04-30T09:12:23.128972Z",
     "iopub.status.idle": "2024-04-30T09:12:23.131488Z",
     "shell.execute_reply": "2024-04-30T09:12:23.131257Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 8,  9, 10]), array([ 31, 120,  49]))"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique([len(w) for w,_ in decomps],return_counts=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In any case, at least 13 offsets are required in the neighborhood of the identity matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:23.132958Z",
     "iopub.status.busy": "2024-04-30T09:12:23.132852Z",
     "iopub.status.idle": "2024-04-30T09:12:23.142297Z",
     "shell.execute_reply": "2024-04-30T09:12:23.142028Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of weights and offsets for the identity matrix decomposition : 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/pr/ywmc0vdj1_q45y494__w0nsr0000gn/T/ipykernel_72775/2393254036.py:15: RuntimeWarning: invalid value encountered in log\n",
      "  def objective(λ): λ = complement(λ); return np.sum(-λ/ϵ - μ*np.log(λ) + 0.5*λ**2/μ)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([0.00884536, 0.03453354, 0.03453354, 0.82648441, 0.82648441, 0.82648441, 0.00884536, 0.03453354, 0.03453354, 0.00884536, 0.03453354, 0.00884536, 0.03453354]),\n",
       " array([[-1, -1, -1,  0,  0, -1,  1,  1,  0, -1,  1, -1,  0],\n",
       "        [-1,  0, -1,  0, -1,  0, -1, -1,  1,  1,  0, -1, -1],\n",
       "        [-1, -1,  0, -1,  0,  0, -1,  0, -1, -1, -1,  1, -1]]))"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "λ,e = smooth3_decomp(np.eye(3))\n",
    "print(f\"Number of weights and offsets for the identity matrix decomposition : {len(λ)}\")\n",
    "λ,e"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.2 Comparison with the C++ implementation\n",
    "\n",
    "A slightly more usable C++ implementation, still slow and experimental, is provided. We check below that it matches the Python implementation. \n",
    "\n",
    "**Availability.** This final subsection assumes that the [FileVDQ](https://github.com/Mirebeau/HamiltonFastMarching/tree/master/Interfaces/FileVDQ) library is compiled, with the SmoothDecomp flag. No GPU support yet, although this should be trivial to add when needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:23.143772Z",
     "iopub.status.busy": "2024-04-30T09:12:23.143685Z",
     "iopub.status.idle": "2024-04-30T09:12:23.145304Z",
     "shell.execute_reply": "2024-04-30T09:12:23.145079Z"
    }
   },
   "outputs": [],
   "source": [
    "from agd.Eikonal import VoronoiDecomposition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:23.146718Z",
     "iopub.status.busy": "2024-04-30T09:12:23.146636Z",
     "iopub.status.idle": "2024-04-30T09:12:23.148878Z",
     "shell.execute_reply": "2024-04-30T09:12:23.148636Z"
    }
   },
   "outputs": [],
   "source": [
    "def normalize_decomp(λ,e,tol=1e-12):\n",
    "    pos = λ>tol; λ = λ[pos]; e = e[:,pos] # eliminate zero weights\n",
    "    ord = np.argsort(np.abs(sum(100**i*ei for i,ei in enumerate(e))))\n",
    "    λ = λ[ord]; e = e[:,ord]\n",
    "    return λ,e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:23.150246Z",
     "iopub.status.busy": "2024-04-30T09:12:23.150169Z",
     "iopub.status.idle": "2024-04-30T09:12:33.821094Z",
     "shell.execute_reply": "2024-04-30T09:12:33.820654Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/pr/ywmc0vdj1_q45y494__w0nsr0000gn/T/ipykernel_72775/2393254036.py:15: RuntimeWarning: invalid value encountered in log\n",
      "  def objective(λ): λ = complement(λ); return np.sum(-λ/ϵ - μ*np.log(λ) + 0.5*λ**2/μ)\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(42)\n",
    "ntest = 1000\n",
    "relax = 0.5\n",
    "D = np.random.randn(3,3,ntest)\n",
    "D = lp.dot_AA(lp.transpose(D),D)+relax*np.eye(3)[:,:,None]\n",
    "for i,Di in enumerate(np.moveaxis(D,-1,0)):\n",
    "    λP,eP = normalize_decomp(*smooth3_decomp(Di)[:2])\n",
    "    λC,eC = normalize_decomp(*VoronoiDecomposition(Di,smooth=True))\n",
    "    if len(λC)!=len(λP): print(i,\"Unequal stencil size\")\n",
    "    elif not np.allclose(λC,λP): print(i,np.max(np.abs(λC-λP)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sometimes a different stencil is obtained, but this is only due to roundoff error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:33.823021Z",
     "iopub.status.busy": "2024-04-30T09:12:33.822900Z",
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     "shell.execute_reply": "2024-04-30T09:12:33.838568Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1.79966517e+00, 2.82945906e-01, 1.97789446e-01, 2.35956346e+00, 6.66807093e+00, 9.52499584e-02, 9.21649353e-01, 6.03618479e-02, 1.55966725e-02, 5.65366515e-03]),\n",
       " array([1.79966517e+00, 2.82945906e-01, 1.97789446e-01, 9.59518122e-19, 2.35956346e+00, 6.66807093e+00, 9.52499584e-02, 9.21649353e-01, 6.03618479e-02, 1.55966725e-02, 5.65366515e-03]))"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Di=D[:,:,157] # Assumes seed 42, ntest = 1000\n",
    "λP,eP = normalize_decomp(*smooth3_decomp(Di)[:2],tol=0)\n",
    "λC,eC = normalize_decomp(*VoronoiDecomposition(Di,smooth=True),tol=0)\n",
    "λP,λC # Not the same length, due to almost zero coefficient in 5th position"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The C implementation is obviously much faster than the Python one. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:33.840513Z",
     "iopub.status.busy": "2024-04-30T09:12:33.840398Z",
     "iopub.status.idle": "2024-04-30T09:12:33.887722Z",
     "shell.execute_reply": "2024-04-30T09:12:33.887369Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 707 µs, sys: 3.27 ms, total: 3.98 ms\n",
      "Wall time: 43.2 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([[3.52041362e+00, 3.35051667e+00, 4.51050651e-01, ..., 9.20535412e-01, 1.36756739e+00, 2.24773471e-01],\n",
       "        [3.92909809e-01, 1.09185929e-01, 1.87170234e-01, ..., 4.45705538e+00, 6.19884062e-01, 2.46481247e-01],\n",
       "        [1.57546841e+00, 5.72829228e-01, 3.04706575e-01, ..., 4.93940444e+00, 1.57386327e+00, 2.54528785e+00],\n",
       "        ...,\n",
       "        [1.75853242e-03, 0.00000000e+00, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "        [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "        [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00]]),\n",
       " array([[[ 1,  0, -1, ...,  1, -1,  0],\n",
       "         [ 1,  0, -1, ...,  0,  0, -1],\n",
       "         [ 1, -1,  0, ...,  0, -1,  0],\n",
       "         ...,\n",
       "         [ 2,  0,  0, ...,  0,  0,  0],\n",
       "         [ 0,  0,  0, ...,  0,  0,  0],\n",
       "         [ 0,  0,  0, ...,  0,  0,  0]],\n",
       " \n",
       "        [[ 0,  1,  1, ..., -1,  0, -2],\n",
       "         [ 0,  1,  1, ...,  1, -1, -1],\n",
       "         [ 1,  0,  1, ..., -1, -1, -1],\n",
       "         ...,\n",
       "         [ 0,  0,  0, ...,  0,  0,  0],\n",
       "         [ 0,  0,  0, ...,  0,  0,  0],\n",
       "         [ 0,  0,  0, ...,  0,  0,  0]],\n",
       " \n",
       "        [[ 0,  0,  0, ..., -1,  0, -1],\n",
       "         [ 1,  1, -1, ..., -1,  1,  0],\n",
       "         [ 0,  0,  0, ...,  0,  0,  0],\n",
       "         ...,\n",
       "         [ 1,  0,  0, ...,  0,  0,  0],\n",
       "         [ 0,  0,  0, ...,  0,  0,  0],\n",
       "         [ 0,  0,  0, ...,  0,  0,  0]]]))"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "VoronoiDecomposition(D,smooth=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The two dimensional decomposition is also implemented in C. The speedup is also significant, although in that case the Python performance is less catastrophic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T09:12:33.889268Z",
     "iopub.status.busy": "2024-04-30T09:12:33.889165Z",
     "iopub.status.idle": "2024-04-30T09:12:38.574738Z",
     "shell.execute_reply": "2024-04-30T09:12:38.574284Z"
    }
   },
   "outputs": [],
   "source": [
    "np.random.seed(42)\n",
    "ntest = 1000\n",
    "relax = 0.5\n",
    "D = np.random.randn(2,2,ntest)\n",
    "D = lp.dot_AA(lp.transpose(D),D)+relax*np.eye(2)[:,:,None]\n",
    "for i,Di in enumerate(np.moveaxis(D,-1,0)):\n",
    "    λP,eP = normalize_decomp(*smooth_decomp(Di)[:2])\n",
    "    λC,eC = normalize_decomp(*VoronoiDecomposition(Di,smooth=True))\n",
    "    if len(λC)!=len(λP): print(i,\"Unequal stencil size\")\n",
    "    elif not np.allclose(λC,λP): print(i,np.max(np.abs(λC-λP)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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