{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Leakage comparison to data\n", "\n", "This notebook compares the PSF and polarization leakage of a data set to predictions. First, we load the required modules." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[93m>>> PyXSPEC is not installed, you will no be able to use it.\u001b[0m\n" ] } ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import leakagelib\n", "\n", "SOURCE_SIZE = 41 # pixels\n", "PIXEL_SIZE = 2.5 # arcsec" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will need to bin the data to compare to the predicted leakage image. We will therefore create the source object first, and use its binning both for the leakage prediction and data binning." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "source = leakagelib.Source.delta(SOURCE_SIZE, PIXEL_SIZE)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we load data from GX 9+9, which is bright and has low polarization." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ ">>> Reading (in memory) /opt/homebrew/anaconda3/lib/python3.12/site-packages/ixpeobssim/caldb/ixpe/xrt/bcf/vign/ixpe_d3_obssim20240101_vign_v013.fits...\n", ">>> Reading (in memory) /opt/homebrew/anaconda3/lib/python3.12/site-packages/ixpeobssim/caldb/ixpe/xrt/bcf/vign/ixpe_d1_obssim20240101_vign_v013.fits...\n", ">>> Reading (in memory) /opt/homebrew/anaconda3/lib/python3.12/site-packages/ixpeobssim/caldb/ixpe/xrt/bcf/vign/ixpe_d2_obssim20240101_vign_v013.fits...\n" ] } ], "source": [ "datas = leakagelib.IXPEData.load_all_detectors(\"01002401\")\n", "data = datas[2]\n", "data.retain(data.evt_energies > 2)\n", "data.retain(data.evt_energies < 8)\n", "data.iterative_centroid_center()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We need an image of I, Q, and U from the data" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "pixel_edges = np.append(source.pixel_centers - source.pixel_size / 2, source.pixel_centers[-1] + source.pixel_size/2)\n", "i_image = np.histogram2d(data.evt_ys, data.evt_xs, (pixel_edges, pixel_edges))[0].astype(float)\n", "q_image = np.histogram2d(data.evt_ys, data.evt_xs, (pixel_edges, pixel_edges), weights=data.evt_qs)[0]\n", "u_image = np.histogram2d(data.evt_ys, data.evt_xs, (pixel_edges, pixel_edges), weights=data.evt_us)[0]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We also need a spectrum so we can compute the leakage patterns." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "spectrum = leakagelib.DataSpectrum.from_data(data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can compute leakage predictions. We can use the data set's detector index and rotation angle to specify the PSF properties. See the leakage prediction notebook for a more detailed tutorial." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "psf = leakagelib.PSF.sky_cal(data.det, source, data.rotation)\n", "combo = leakagelib.PSFSourceCombo(source, psf, use_nn=False)\n", "i_pred, q_pred, u_pred = combo.compute_leakage(spectrum, normalize=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The normalizations of the leakage patterns are arbitrary, so we need to correct the total flux to be the same as the data" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "q_pred *= np.sum(i_image) / np.sum(i_pred)\n", "u_pred *= np.sum(i_image) / np.sum(i_pred)\n", "i_pred *= np.sum(i_image) / np.sum(i_pred)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And finally we display them" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, axs = plt.subplots(ncols=3, nrows=2, sharex=True, sharey=True)\n", "vmax = 0.05 * np.max(i_image)\n", "axs[0,0].pcolormesh(source.pixel_centers, source.pixel_centers, i_image)\n", "axs[0,1].pcolormesh(source.pixel_centers, source.pixel_centers, q_image, vmin=-vmax, vmax=vmax, cmap=\"RdBu\")\n", "axs[0,2].pcolormesh(source.pixel_centers, source.pixel_centers, u_image, vmin=-vmax, vmax=vmax, cmap=\"RdBu\")\n", "axs[1,0].pcolormesh(source.pixel_centers, source.pixel_centers, i_pred)\n", "axs[1,1].pcolormesh(source.pixel_centers, source.pixel_centers, q_pred, vmin=-vmax, vmax=vmax, cmap=\"RdBu\")\n", "axs[1,2].pcolormesh(source.pixel_centers, source.pixel_centers, u_pred, vmin=-vmax, vmax=vmax, cmap=\"RdBu\")\n", "\n", "axs[0,0].set_ylabel(\"Data\")\n", "axs[1,0].set_ylabel(\"Prediction\")\n", "axs[0,0].set_title(\"I\")\n", "axs[0,1].set_title(\"Q\")\n", "axs[0,2].set_title(\"U\")\n", "\n", "for ax in axs.reshape(-1):\n", " ax.set_aspect(\"equal\")\n", " ax.set_xlim(source.pixel_centers[-1], source.pixel_centers[0])\n", " ax.set_ylim(source.pixel_centers[0], source.pixel_centers[-1])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Compute the goodness of fit between I, q, and u:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Q: 1930.3/1681 = 1.1\n", "U: 1729.8/1681 = 1.0\n" ] } ], "source": [ "chisq_q = np.sum((q_image - q_pred)**2 / (2 * i_image))\n", "chisq_u = np.sum((u_image - u_pred)**2 / (2 * i_image))\n", "dof = np.prod(i_image.shape)\n", "\n", "print(f\"Q: {chisq_q:.1f}/{dof} = {chisq_q / dof:.1f}\")\n", "print(f\"U: {chisq_u:.1f}/{dof} = {chisq_u / dof:.1f}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The leakage patters match the data rather well. To demonstrate the spatial coherence of the fit, see the significance of the residuals below." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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vPHHiBACgUaNGKXrZs2dHvXr1EBwcjJMnT8Lf3z9Zv0aNGinGHDx4EMCz40X1vkxs/H5Barbv0KFDAIAWLVq88LKq+5E7d25UrlwZe/fuxcWLF1GxYsVkfb378aK+8X5eu3ZN934aj5+9cOECWrZsiYsXL+Lx48eoWbNmpn35WfUYlChRAoUKFcLVq1fx+PHjZEkVnp6eKFasWIoxfn5+AICHDx9myvYSmeOvv/7Cf//9h2bNmiVLl+rWrRs++OADLF68GJMnT4ajo2O6bufo0aNISEhIdnx4UnFxcQD057IXzSnPS8v8cOnSJTx9+hSvvvoqvLy8UvQbNWqEyZMn4+TJk2neLr2+Oe85aZm7zWG8b3Xr1tX9PTdq1Ai//PILTp48iZ49eybr6R3+yrnOuvBwndThIt9G5ciRAzVq1MCaNWtQqFAhfPnllxg0aBD8/Pzw8OFDaJqGu3fvmr40lh7GL6RKSS3G+qNHj1L0fHx8UtTu378PANi+fTu2b98u3m5kZOQLt814m6mJiczo+/GivvF+rlq1SjnWeD/Tcl/MlZrH4Pr163j06FGyRb7e9xQAmI6vTUhIyNgNJUqH+fPnA0CKL2J6eXmhTZs2+P3337F+/Xp07NgxXbdjfI0fPXpU/CI9oD+XvWhOeZ41z3XmvOdk9nyXnsdAb77jXGddXra8e3PxUbJxuXLlQsmSJREfH2/aS2tcnFWuXBnas0OyxH+pYby+W7du6faN6Tp6GcV6f20bLzdr1izlthnTflSMk/GNGzcsfj9e1Ddez/r165X30/il1bTcF3Ol5zEgsgV37941nam2a9euKZI1fv/9dwD/+0MgPYyvkxEjRihf47t27UoxNq17Im1hrkvLe05mz3ec64i4yLcLxo8PExMTAQDu7u4oW7Yszp07hwcPHqT7+itXrgwAumd8jI+Px759+wAAVapUSdX1vfLKKwBgGpcexuvasmXLCy+ruh+PHj3CqVOnTJFvGSGt97NUqVLIlSsX/vnnH9M5C1SMSUVp2bOkegz+/fdfhIaGokiRIuKeeyJrt2TJEsTGxqJq1aro27ev7r98+fJhx44duHr16guvT/U6q1GjBhwcHDJkLnuRtMwPJUuWhJubG06fPq27p9r4R0dq5+wXMec9Jy1zN/Bsz605c93+/fsRHx+fop/RjwFZFiM0U4eLfBu3bt06XL16FY6OjsnOUvv+++8jNjYWffr00Z3kHz58aNrz/yLt27eHl5cXVqxYYTqO0mjmzJm4evUqXnvttRTH40uqVauGunXrYs2aNVi4cKHuZc6cOYM7d+688Lp69eoFDw8PzJ07F3v37k3RDw0NNf3co0cPODo6Yvbs2fj333+TXW7ChAkIDw9Hjx494OzsnKr78SLt2rVD0aJF8d1332Hz5s26lzl48CCePn0K4Nli4p133kFUVBQGDRqUIlc6NjY22fkQ8uTJAwC4fv16qrepT58+AIDJkycnu66EhASMHDkSiYmJ6Nu3b6qvj8jaGLPxv//+e/z444+6/wYOHGg6G+6LqF5n3t7e6N69O44dO4bPPvtMdxH633//peqPiRdJy/zg5OSE7t27IyIiAhMmTEixPd9++y0cHR3x1ltvpXu7jNL6npOWuRt49nsICQlJ9fYUKlQITZo0QXBwcIrvCRw+fBjLly9H7ty58frrr6f6Osl6cJGfOjwm34Yk/WLXkydPcP78edNekKlTpyJ//vymfp8+fXD8+HF8//33KFq0KJo1awZ/f388ePAAV69exd69e/H222/jhx9+eOHturu7Y+HChejUqRPq16+PTp06wd/fH8ePH8e2bdvg4+ODefPmpem+LF++HI0aNULfvn3x7bffombNmsiVKxdCQ0Pxzz//4OzZszh48GCKPPrn5c2bF8uXL0fHjh3RsGFDtGjRAhUqVEB4eDj++ecfhISEmN5gjVnY7777LqpUqYLOnTsjX7582LNnDw4ePIhSpUrhiy++SNP9UHF0dMSaNWvQrFkztGrVCrVr10alSpXg5uaGkJAQHD16FFeuXEFYWBjc3NwAABMnTsThw4exYcMGlChRAq1bt0bOnDkREhKCbdu2Yfr06abjjBs2bAgHBweMHTsWZ8+eRe7cuQEA48ePF7epdu3aGD16NL788kuUK1cOHTt2RI4cObBlyxacPXsWderUwahRozLsMSCypN27dyMoKAjly5dXfoG0b9++mDJlChYtWoRPP/00WXb78170OpszZw4uX76Mjz/+GEuXLkWdOnWQP39+3Lx5ExcuXMDRo0exYsUK3fOIpFVa5ofPP/8c+/btw5w5c3D06FE0bNjQlJMfERGBOXPmZMg2GaX1PSctczcANG7cGL/++ivatGmDKlWqwNHREfXq1UO9evXEbTKeNGzUqFHYtm0bqlWrZsrJd3BwwKJFi5AzZ84MewzIcl62xbrZMi23hzIMdKIzs2XLpvn4+Ght27bVtm3bJo7dsGGD1qpVKy1fvnyao6Ojlj9/fq169erauHHjUmTFSxGaRkeOHNHat2+v5c2bV3N0dNT8/Py0QYMG6ca5vei6NE3TwsPDtSlTpmhVqlTRcuTIobm4uGgBAQFay5YttXnz5mmRkZGpenw0TdPOnj2rvfXWW1qBAgU0R0dHzdvbW6tXr55uVOTWrVu1Jk2aaLly5dKcnJy0okWLaqNGjdKNfjNGZEpe1Ne0Z3nyY8aM0cqWLau5urpqOXLk0IoVK6Z16NBBW7p0qRYXF5fs8nFxcdrs2bO16tWrazly5NDc3Ny0YsWKaf37908RY7l06VLTeQWMzw0j1e9gxYoV2quvvqq5u7trzs7OWpkyZbTJkydrUVFRKS4rRQtq2otjPIksqVu3bhoAbdasWS+8bJMmTTQA2po1azRNUz/PVa8zTXsWWTl79mytVq1apgx6Pz8/rVGjRto333yj3bt3z3RZYxTlxIkTzbqPaZkfHj58qI0ePVorVqyY5uTkpHl6emqvvfaatnXr1hTX+6LtSu12p+U9R9NSP3ffvn1b69q1q+bt7a05ODgk2xYpJ1/TNC00NFQbNGiQ5u/vrzk6Omp58uTR2rVrpx05ciTFZY0RmosWLdK9b1DEeJJlGCM0vb29zf73MkVoGjSN56QnIiIiIusWGBiI69evp+usw/fu3YO/vz+uXLmSgVtmnXi4DhERERHZDB6ukzpc5BMRERGRzWBOfurwUSIiIiIisjPck09ERERENoOH66QOF/lEREREZDO4yE8dLvKJiIiIyGZwkZ86drvIz5UrF2JiYuDr65vVm0JENiIsLAzOzs66Z+y0ZZwPiSit7HU+fJnY7SI/JiYG0dHRuHbtGgAgR44c4mVVeavSaQRiY2PFMdmyZRN78fHxYk96IanO+hodHS32XF1dxZ5E9dexuadUkK5T9RiqzkCpIj2G7u7uZt1WXFyc2JO+3a/6/eud9j4125GYmCj2JM+fFj6pggULir3bt2/r1lULRNXzRtWTHl/V81r1u1Q9R6XXXkREhOnnmJgYcbwtM86HwcHBAGA6w7Ie1XwjPb6qx83R0VHsqeaA8PBw3Xq+fPnEMVFRUWJPNR9Kz9HMmA8lT58+FXvmbDsgv45U2+7i4iL2VPOXNB+qUlBU74fmzIeq+xUSEiL2ChUqJPbu3bunW096hvnnZfR8qHp9qdY25syHSV931jwfck9+6tjtIt/X1xfXrl0znYK8Y8eO4mXnzJkj9qRJ8syZM+IYHx8fsadaeE2aNEm3vnr1anHM/v37xZ7qdN/SQlT1ZvLkyROx5+TkJPakSf78+fPiGD8/P7Gn8uWXX+rWu3btKo5RLXj//fdfsefl5aVbV03+0gIaUN9nacGjetMtU6aM2Nu1a5fY69Chg2599+7d4hjV71+1oDx37pxu/fDhw+IY1e9Stcgz/sH/vJ9++sn089KlS5EnTx7xOmyVr68vgoODTa/vFi1aiJf99ddfxZ70+J46dUocExAQIPYuXrwo9r777jvd+sKFC8UxO3bsEHtNmzYVe9Lz19nZWRyjeq6p/rCRrF+/Xuw1a9bMrNvau3evbl217fXr1xd7YWFhYs/T01O3Ls2TAJQnIypWrJjYe/DggW5dtVNGdX3btm0Te4MHD9atr1mzRhyjet6oFuXSfHjy5ElxjGpto9pZIj32P/74o+nnX375JV0nncosBoMhXYv8tI7t3bs3lixZIvZDQ0OV64isZLeLfCIiIiKyP5bMyR84cCBee+21ZDVN0zBo0CAEBARY7QIfsPNFvo+Pj2kvuGpP488//yz2qlSpoluvVq2aOOb7778Xe++9957Yk/ZQ5cyZUxyjeqKr9hhIf8mqPt7bt2+f2AsKChJ7Q4cOFXuSli1bir3t27eLPenTENWea9WeRtXe8Pv37+vWVR8Ljx49Wuwl3YPyPOn3fOjQIXHM3bt3xZ5qT16nTp1068ZPxfSoDrtQ7f2THt/ChQuLY1SfhqheD9JzNOkneZs3bxbH27oCBQqY9harDoVYtWqV2CtXrpxuvXr16uKYH374Qey9++67Yk96buTKlUsco/rUyMPDQ+xJh3+oPinbsGGD2DMeFqVnzJgxuvXmzZuLY1Tbrjqk4vmFidGNGzfEMapDA1VzpXRYy9WrV8Ux/fv3F3uq56Hk+PHjYk/1SbT0SSkgf3Ko+sRP9YmCJedD1R5r6VO0pOuXP//8Uxz/MqlVqxZq1aqVrLZ//348ffoU3bt3z6KtSh27XuQTERERkX3J6mPyly9fDoPBgG7dumXpdrwIF/lEREREZDOycpEfFxeHlStXonbt2spPt6wBF/lEREREZDOycpG/detW3L9/3+oP1QG4yCciIiKil0hISAgCAwOT1VRpT0ktX74cjo6O6Ny5c2ZsWobiIp+IiIiIbEZW7cmPjIzE+vXr0axZM5uIW+Yin4iIiIhsgsFgSFeEpsFgQKFChVK95z6pdevW2USqjpFBy+jT9lmJwMBAhIeHY/LkyQCg/IWoTtl84MAB3Xr79u3FMaozF0oxYwBw8+ZN3brqTKOqE1WMHTtW7H388ce69fnz54tj3nrrLbGnitds3Lixbt3f318co4o7U8XT3blzR7detWpVccyePXvE3meffSb2VqxYoVtXnfxFRRUZ9/bbb6f5+q5fvy72VJFs0kmjVPGEixcvFnuqmETp5GuqE/w8fvxY7KnGSW8KSeNEK1euDAcHB7Mmf2sWGBiIiIgIfP755wCAN998U7ysKk7w2LFjunXViaZUJ+R5+PCh2JNOlqeKci1SpIjYW7BggdiTTjYl3V8AaNeundhTnbyobt26unXVmbJV7ylJT+b2vEGDBunWVSc9VM0bH374odgzvtc+T/XFRNXyQzqRFyBHg6r27qpORKk6EaH0vqw64ZV0IjcAGDVqlNiTrlM1r6leQ6pxUoxu0kjWihUrWt18GBgYiNDQUBQtWtTs6/jvv//MXuS3aNEC+/fvx+3bt5XvidaCe/KJiIiIyGZkxeE6d+/exY4dO9C1a1ebWOADgOVOGUZEREREZIN+++03xMfH28yhOgD35BMRERGRDUnPMfnmWrZsGby9vcXDxawRF/lEREREZDOy4nCdgwcPWvw204uLfCIiIiKyCRmRrvOy4DH5RERERER2xq4jNGNjY7F+/XoAz6LxJKpIPukvPlU0leqvRNW4adOm6dZbt24tjilevLjYkyKyADm6LGl81vNy5swp9v777z+xV6pUqTTf1qJFi8Se6vG4e/eubt3d3V0co4rd27Vrl9iTnlOqeLrExESx5+LiIvak55QqFk4V5amKyZN+z9u3bxfHqCI+VVOMFBuo2r4cOXKIPdXJSaTHMOnzsGTJkjAYDFYVGZcRjPPhpk2bAADly5cXL2tOJJ8q/tGceQgA1qxZo1svU6aMOKZEiRJiz5xtlGI8AaBQoUJiLzIyUuxJ0cGqmMyEhASxp3o9SPPN6dOnxTGqx1AVAe3t7a1bV83zqt+J6n7Fx8fr1sPCwsQx+fLlE3uqWGYp1tL4WtLz3nvviT3Ve4D0PFRtn6enp9hTxc3a6nwYGBiIGzduoHTp0mZfx4ULF1CwYEGrul+ZhYfrEBEREZHNeJkOuUkPLvKJiIiIyGZkRbqOLeKjRERERERkZ7JskT9lyhQYDAaUK1cuRe/AgQOoU6cO3Nzc4OPjg6FDhyqPcSQismWcD4mIUs9gMJj972WSJYfrhIaGYurUqbpfrDl16hQaN26M0qVLY8aMGQgNDcVXX32Fy5cvY8uWLVmwtUREmYfzIRFR6jFCM/WyZJE/cuRIvPLKK0hISEjxbf2PPvoIuXPnxu7du+Hh4QEACAgIQP/+/bFt2zY0bdo0KzaZiChTcD4kIkqbl2mhnh4WX+Tv3bsXq1evxsmTJ1PETIWHh2P79u0YMWKE6Q0NAHr27IkRI0Zg5cqVaXpTc3JyQpUqVQCo48lUMVOXL1/WrT969Egco4qn27Fjh9gbPXq0bv37778Xx6jiPydNmiT2du/erVv/+++/xTF6hxIYqWLX1q1bp1s/duyYOOaXX34Re6+//rrYk+I6VdFvqoi/X3/9VexJzxvVHobw8HCxd+fOHbG3detW3Xq7du3EMarYNel3AgB169bVrTs5OYljVK+vLl26iL0PPvhAt167dm1xzObNm8Ve+/btxd6oUaN061FRUaafNU2z6JuHpefDChUqAACePHkiXk4VQ3rp0iXdelxcnDgmICBA7G3cuFHsSa/zP//8Uxyjul+///672Pv333916wMGDBDHlC1bVuyp3lNOnTqlW1dFl0ZERIi9XLlyib2kz5ukVLHBgwcPFnsTJkwQe1J0sCpSWBWvmfR1+bwVK1bo1jt37iyO+eeff8Tezp07xZ4Ulaz6/cfGxoo91eM7aNAg3bpqTbFv3z6x16RJE7H38ccf69azcj6kjGfRRX5CQgLee+899OvXT/dJe+bMGcTHx6NatWrJ6k5OTqhUqRJOnjxpqU0lIspUnA+JiMzDdJ3Usegi/4cffsC1a9fEvdnGE1n4+vqm6Pn6+ir/Yg0MDEz2/yEhIfDz80vH1hIRZR7Oh0RE5uEnDKljsUX+/fv38fHHH2PChAnimeeMHxPpnWHOxcVF+fEdEZGt4HxIRGQ+LvJTx2KL/PHjx8PLy0t5umfjsXt6x+lFR0crj+17/vTEz+/JIiKyFpwPiYgos1lkkX/58mXMnz8fM2fOxM2bN0316OhoxMXFITg4GB4eHqaPpY0fUycVFhaGAgUKWGJziYgyDedDIqL04TH5qWORRf6NGzeQmJiIoUOHYujQoSn6RYoUwbBhw/Dpp58ie/bsOHbsWLJvycfGxuLUqVPKb87rSUxMNKXgfP755+LlqlevLvaKFSumW5c+YgeefRQvUaUuSHvmVCkp+fPnF3tLliwRe2fPntWtOzo6imMGDhwo9n766Sex5+XlpVtXJaioUjfWrl0r9nr27KlbVx2PrEquOHr0qNiTkjzc3d3FMarejRs3xF7Xrl1166qJrnjx4mKvefPmYk96jjZs2FAcc+TIEbHn7e0t9qpWrapbnzJlijhm3LhxYk/1eFSsWFG3nvQ5b4mPgLNqPkxISMDdu3cBAN999514uUqVKok96RMBNzc3cYwqeceYfpaW63zw4IE4RpU08/wXmJOSkm1USUMHDx4Ue7Vq1RJ7Sf+wS0qVeKP3vQyjGTNmiL06dero1vWed0ZSkheg/l1GR0fr1rNlyyaOUZEeJ0BO7NI7tM1ImmsA9fuydJ2qT8cuXrwo9lTJfFJiz/jx48UxqrnSnPeHpGlz1npITHpPamWt9yszWGSRX65cOd2F2fjx4xEREYFZs2ahaNGi8PT0xGuvvYZffvkFEyZMQM6cOQEAS5cuRWRkJDp16mSJzSUiyjScD4mI0od78lPHIov8vHnz6uZXz5w5E0DybOspU6agdu3aqF+/PgYMGIDQ0FB8/fXXaNq0qXLvIxGRLeB8SERElmB1fwpVqVIFO3bsgKurK0aMGIH58+ejb9++WL16dVZvGhGRRXE+JCJKyXjIjjn/XiYWP+NtUtJZV+vUqaM88yoRkb3hfEhElDov22LdXFm6yCciIiIiSgsek586fJSIiIiIiOyMXe/JNxgMphi2iRMnipdLTEwUe9Jfiy4uLuKYhIQEsafKtpaitc6cOSOOUX1kFRISIvbCw8N165cuXRLHqEgRdMCzNBE9UgQlANy5c0fsqSI03377bd36Rx99JI7RNE3sNWjQQOy98soruvX9+/eLY4KCgsRet27dxN66det066rnkxRp96JxhQoV0q3/+++/4pjHjx+LvTFjxog9KSaxbt264hhVjJ/qdSnFqCaNZExMTDQ78s/aOTg4wMPDAwAwduxY8XKq+VCab5ycnMzaJlXkpRSVeerUKXGM6izAhQsXFnvXr1/XrZcoUUIcExAQIPZiY2PFXpMmTXTrque1ao4aPHiw2Fu0aJFu/c8//xTHqGJ+VXPKtm3bdOv16tUTx6iea59++qnYk56/UuQ1oH5fVkVvSlGZt2/fFseo5sNZs2aJvaTxlUl17NhRHKN6DFWk+5V0HWKt8yEjNFPPrhf5RERERGRfeLhO6nCRT0REREQ242XaG58e/FOIiIiIiMjOcE8+EREREdkM7slPHS7yiYiIiMhm8Jj81OEin4iIiIhsBvfkp47dL/KNTwTVX3179uwRe1Lc2a1bt8QxqnjC+fPni70ePXro1kuWLCmOUUXX/fTTT2Lvs88+062rojDff/99sbd06VKxN378eN26Khbuyy+/FHtffPGF2JPiyVQxjseOHRN7NWvWFHtSzKMqPs/T01PsTZgwQexJ8XStW7cWx0jxlIA6Mu7ixYu69aJFi4pjdu3aJfakCFUAcHR01K2r4jpVz1FV1JwxPvJ5SSNDrTEuLiMZ50FVXKPqd9myZUvdemhoqDjG399f7C1ZskTsdenSRbderVo1ccy5c+fE3rfffiv2mjVrplv38vISx6jmw2+++UbsnT17VrcuRRoC6khZ1X3u2bOnbl31PP/ll1/EXps2bcSe9DpXxaSqYpSliGIAOHnypG7d1dVVHOPj4yP2VNt4/Phx3bq3t7c45saNG2JPivIF5Ahgaf4H1HHTqt+XFJVasGBB08/2Ph+m1YkTJ/DJJ59g//79iI6ORmBgIAYMGIChQ4dm9aaJ7H6RT0RERET2wWAwpOtwHXM+Bdi2bRvatGmDypUrY8KECXB3d8d///2n3MFhDbjIJyIiIiKbYcnDdcLDw9GzZ0+0atUKq1evtqnvA3CRT0REREQ2w5IL7eXLl+P27duYMmUKHBwc8OTJE7i6utrEYt/6t5CIiIiIKAvs2LEDHh4euHHjBkqWLAl3d3d4eHhg8ODBiI6OzurNU+KefCIiIiKyGek9XCckJCTFl92vXLmie9nLly8jPj4e7dq1Q9++fTFt2jTs3r0bs2fPxqNHj7BixYp0bUtm4iKfiIiIiGyGJY/Jj4yMxNOnTzFo0CBTStcbb7yB2NhYzJs3D5MmTULx4sUttj1pYdBUOYY2zPgXmvEvszNnzoiXVUVeShFq8fHx4pjg4GCx9/fff4u98uXL69YDAgLEMZGRkWbdVvPmzXXrqkizTZs2iT1VjJcU/9aoUSNxzGuvvSb2duzYIfYkDx48EHuq7VCNGz58uG5d9W17VTSoKgpPilGNiooSx0iRkYB6G8PCwnTr2bPL+wRKlSol9mJiYsTe06dPdeu+vr7iGFUU3qFDh8TelClTdOtJfyfVqlWDg4ODuEfHVj0/H/7zzz/iZVWRl1IErGo+vH79utjbv3+/2CtdurRuXRU1qYr8Uz0PVXGIEtVrT/VaOXHihG5dFf+oWkBIEcUAMGrUKN26KqJW9drLnTu32JPei1RzqPSeB8iPEwCUKVNGt65a+EmRkcCzL1ZKQkJCdOtS3CWgXlOoIpaluVf1+1dFFP/xxx9ib8GCBbr1sWPHmn6uXLmy1c2HgYGBuH37Nlq0aGH2dWzZsgX58+dP9f0qV64czp07hz179qBevXqm+t69e1G/fn0sWbJEjKvNajwmn4iIiIhIh/GPtvz58yerG3cOqM7dktW4yCciIiIim2AwGNL9Ly2qVq0KIOVJzm7evAkAyJcvX8bcsUzART4RERER2QxLLfABoHPnzgCAn376KVn9xx9/RPbs2dGgQYOMuEuZgl+8JSIiIiKbYckv3lauXBl9+vTBwoULER8fj/r162P37t1YtWoVxo4dq/wORlbjIp+IiIiISPDDDz/A398fixYtwtq1a1G4cGF88803YgCHtbDrdB1N00ypOv/99594WVWijJOTk25927Zt4phq1aqJPeOxXXqk5IJTp06JY44cOSL2unTpkubbUh1bpkrJUCXDVK9eXexltN9++023rnosatSoIfYeP34s9tauXatbT0xMFMckJCSIvYoVK4o96WWq+v2r0j8qV64s9h49eqRb7969uzimU6dOYm/gwIFib9CgQbp1VeKRKsln/fr1Yq9fv366dUdHR9PPtWvXRrZs2awqTSIjGOdDY6qOKm3M2dlZ7El7z1TzYdmyZcVerVq1xJ6UbHbx4kVxTFBQkNiT0nqAlF+oM/rrr7/EMarXa8GCBcXer7/+qltXJc2o5iFV2pCUXiWldQHqM4mqetJ8o5oPL1y4IPZU76NxcXG6deMx0npUaTi5cuUSe9Kc/cknn4hjpOcTALz77rtir3fv3rr1bt26iWNU79mzZ88We1LamLXPh4GBgbhz5w5at25t9nVs3LgR3t7eVnW/Mgv35BMRERGRzbDk4Tq2jIt8IiIiIrIZqk+V6H/4KBERERER2RnuySciIiIim2BuFGbS8S8LLvKJiIiIyGa8TAv19OAin4iIiIhsBhf5qWPXi/zQ0FBTzNmhQ4fEy9WvX1/sSXFnqjhBHx8fsaeKQouIiNCtSzGeAPDKK6+IvR07dog9KX7q3r174pgqVaqIvc2bN4s9c6jizt5++22xJ0VlbtiwQRzTpk2b1G9YEs2bN9et//vvv+KYDh06iL3bt2+nuaf6Havye7Nnl1/633//vW5979694pi7d++KPdVk/MMPP4g9iSr1d/fu3WJPek49ePDA9HNiYiKyZcuW5m2yBTdv3kS9evUAADt37hQvZzy7o565c+fq1lXP64CAALEXGRkp9qT4R5U8efKIPdWckiNHDt266vWlimtUvT9IUZmq+6s62c7Zs2fFXuPGjXXr8fHx4hhV9O6ECRPE3o0bN3Tr7u7u4pgBAwaIvaSvy+dJMb+qqOyGDRuKvYcPH4q9OXPm6NY///xzcYxqLlfNh8uWLdOtq9YNOXPmFHvt2rUTe9JrJelja6cJ6y8Vu17kExEREZF94Z781OEin4iIiIhsBhf5qcNFPhERERHZDC7yU4c5+UREREREdoZ78omIiIjIZnBPfupwkU9ERERENoOL/NSx60W+u7u7KVJRFQW1a9cusefs7Kxbd3R0FMeo4slUsWAhISG69QYNGohjYmNjxV7evHnFnpubm25dFdW1Zs0asRcXFyf2pEg2V1dXcUyRIkXEnhTjBwClSpXSrat+XyolS5YUexUqVNCt79mzRxzz3Xffib3ExESxJ21/4cKFxTEjRowQe82aNRN7ffv21a2rovWk+FcAuHjxotiTogtVsbFXrlwRe/369RN7Xl5euvWksZsJCQlmP1esnaurKxo1agRAPR+uWrVK7Emvc1WMn2o+VP0upXHVqlUz67ZUPem5sWXLFnGMKip5wYIFYu/NN9/UraveG0qUKCH2lixZIvbq1KmjW09ISBDHqObyjz/+WOw5OOgf/Xv48GFxzMGDB8VeWFiY2PP19dWt16hRQxyjep8vVKiQ2JMilqUYT0D9fnP16lWxt3btWt36u+++K45RPU7t27cXe9LaZuLEiaafIyIikDt3bvE6sgrPeJt6PCafiIiIiMjO2PWefCIiIiKyLy/T3vj04CKfiIiIiGwGF/mpY5HDdY4ePYohQ4agbNmyyJEjB/z9/dG5c2cEBQWluOyFCxfQvHlzuLu7w8vLC2+99Rbu3r1ric0kIsp0nA+JiNLHeFy+Of9eJhbZk//FF1/g77//RqdOnVChQgXcunULc+bMQZUqVXDo0CGUK1cOABAaGop69erB09MTU6dORWRkJL766iucOXMGR44cUX4Zj4jIFnA+JCIiS7DIIv/999/H8uXLk70pdenSBeXLl8fnn3+OX375BQAwdepUPHnyBMePH4e/vz+AZ9+Wb9KkCRYvXowBAwZYYnOJiDIN50MiovR52fbIm8sii/zatWunqBUvXhxly5bFhQsXTLXff/8drVu3Nr2hAcBrr72GEiVKYOXKlWl+U3NxcUHDhg0ByHGHABAcHCz2pL1lkZGR4hjVk6906dJi78cff9Stx8TEiGNUMZTe3t5iT4rxWrhwoTjGxcVF7Kni5KQILtX2LV26VOypIvSkuMaqVauKY1QuXbok9qTrPHPmjDgmW7ZsYs8Yb5iW7ZDi3QCgdevWZm3H6dOndetSbB2gjrz8448/xJ4U8ab6HW/YsEHsqeLejhw5olv38/Mz/WyJ+Mysmg/d3NzQqlUrAOp5SDUfSlGZquhd1WOqes5/8803unUpJhdQz1FSXCsA3Lp1S7eueizOnTsn9lTxtfPmzdOtq2JtVZGnqujNrl276tZnz54tjlFF+armgH/++Ue3XrZsWXGMKq7zxo0bYk+Kh5ZiIQH180b1np00YjepihUrimNUca3Hjh0Te4MHD9atG9cxetatWyf2VJ48eaJbTxrJqVoPZDUu8lMnyyI0NU3D7du3TS/WGzdu4M6dO7pv7jVq1MDJkyctvYlERBbB+ZCIKPV4TH7qZFm6zrJly3Djxg1MmjQJwP/+etTbU+Dr64sHDx4gJiZG/Es9MDAw2f+HhIQoTwZFRGQtLDEf5suXL4O3moiIrFmW7Mm/ePEi3n33XdSqVQu9evUC8L+zaeq9aRk/glWdcZOIyBZxPiQiSr307MV/2fbmW3xP/q1bt9CqVSt4enpi9erVpmODjceW6x1/Hh0dnewyep4/PXpgYCDfBInIqllyPjSOIyKydS/TQj09LLrIf/z4MVq0aIFHjx5h3759KFCggKln/Fg66Zc+jMLCwuDl5aX8Ug0RkS3hfEhEZB4u8lPHYov86OhotGnTBkFBQdixYwfKlCmTrF+wYEHky5dP95vnR44cQaVKldJ8m87OzqYElNGjR4uXkxJZACRLtkjq0aNH4hjVHrOnT5+meZy7u7s45t69e2IvNDRU7EmP56JFi8QxqlSA8PBwsSclEWXPLj/9AgICxJ45VMcjq35fqrSO5cuX69a9vLzEMe+//77YU5EmtD///FMco7dANNq3b5/Yk1KDVOkUP//8s9hTJWg8f+y40YkTJ8QxKqpUCymhJH/+/KafValDGSkr5kMnJydTIogq/SUkJETsFSxYULeuSn9RzZW3b98Wew8fPtSte3h4mHVbO3fuFHtSss3cuXPFMdOnTxd7KsZDsp4npasBwMCBA8Xe1KlTxd7w4cN169LvEYDyS91Dhw4Ve8WLF9etq+bQLVu2iL1ixYqJPSkZRvX7V71XPv/JV1JSApQqYU81f0nPa0B+7H/99VdxjGrOu3btmthLmiqWVKFChUw/W2o+pMxjkWPyExIS0KVLFxw8eBCrVq1CrVq1dC/XoUMHbNy4MdmbzM6dOxEUFIROnTpZYlOJiDIV50MiovTh8fipY5E9+R988AH++OMPtGnTBg8ePDCd7MWoR48eAICPPvoIq1atQsOGDTFs2DBERkZi+vTpKF++PN5++21LbCoRUabifEhElD4v22LdXBZZ5J86dQrAs5PY6J3Ixvim5ufnhz179uD999/Hhx9+CCcnJ7Rq1Qpff/01jz8lIrvA+ZCIKH0sucjfvXu3eEKygwcP4pVXXrHYtqSVRRb50hnj9JQtWxZbt27NvI0hIspCnA+JiGzP0KFDUb169WQ11XdHrEGWnQyLiIiIiCitsuJwnbp166Jjx44Wv9304CKfiIiIiGxGVh2THxERAVdXV2U6oDWxja00k4ODA3LlygUAKFKkiHg5VeShFA2XJ08ecYyTk5PYCw4OFntSXGdiYqJZt7VkyRKxJ8WdTZs2TRzTvn17sbdw4UKxJ0WUXr16VRyjioVTxfWZ88KvXbu22Bs3bpzYmzJlim59zpw54pjz58+LvedjFJPSOykSAHTp0kUco3reDBs2TOzdvHlTt54zZ05xzIABA8TeO++8I/Y+/fRTsSdRxaFGRESIvfHjx+vWn48TVc0VtizpfFizZk3xcqrIXum1p3rdGTP/9dy4cUPs+fj46NZjY2PFMap4TVXv0qVLunVVZKQq4WjFihVi7/Tp07r19957TxwjvSYB4LPPPhN7ixcv1q0bvxeiR/XeJs15AFC5cmXdeoUKFcQxCxYsEHuqOOf+/fvr1nPkyCGOUZ0cs3z58mJPep9SxUuqri9v3rxiT7rP/fr1E8eotsPb21vsSbGcY8eONf189+5dcV2SldKbkmPu2LfffhuRkZHIli0b6tati+nTp6NatWpmb4cl2PUin4iIiIgoqZCQkBTnaZHOl+Dk5IQOHTqgZcuWyJs3L86fP4+vvvoKdevWxYEDB8Q/cK0BF/lEREREZDMsebhO7dq1k33i37ZtW3Ts2BEVKlTA2LFjlSelzGpc5BMRERGRzXBwSN+5XP38/JRnOn6RYsWKoV27dlizZg0SEhKs9uzAFjnjLRERERFRRrCGM976+fkhNjYWT548ybDrzGjck09ERERENsMaznh75coVuLi4KMMKshr35BMRERER6bh7926K2unTp/HHH3+gadOm6T50KDPZ9Z78hIQE3L59GwAQEBAgXk4V/7d+/XrduouLizjm8ePHYu/5b3MnZdzW5+3fv18cI8UCAvI3xQGgRYsWunVV3F3Pnj3F3q5du8Reu3btdOuqY9ikSDtAfZ/N0a1bN7E3aNAgsaeKk5OoYjJVkaLm7LVQTTzHjh0Te9Jz1NnZWRwjRXwCwJgxY8Te82cPNHr69Kk4RnUGWFV0nTQu6Wu5aNGi4nhbp2ma6XEtXLiweDnp9QoAhw8f1q2rzvqoig2WYjIB4P79+7r1W7duiWOkeEpA/TqXIiVVz0NVRPGqVavE3ptvvqlbV71vBAUFib0HDx6IPek9oG/fvuKYo0ePpvn6ADnOOTQ0VByjeg9QRYqqfi+SESNGiD3V+560lzZ37tzimLJly4o9VSSltK5QxSEvX75c7L311ltiT3o/7927t+ln1Xolq1lyT36XLl3g6uqK2rVrw9vbG+fPn8f8+fPh5uaGzz//3GLbYQ67XuQTERERkf2wdE5++/btsWzZMsyYMQPh4eHIly8f3njjDUycOFG5g8MacJFPRERERDbDknvyhw4dqjwxnjWz3gOJiIiIiIjILNyTT0REREQ2wxrSdWwBF/lEREREZDO4yE8dHq5DRERERDbDGk6GlVp3797VTUg6fvx4pt+2Xe/Jd3BwQK5cuQAAP/zwg3g5KSYTePataj1ffPGFOEYVw3fjxg2x17JlS926KkpMFbuoinj7888/detRUVHiGFdXV7Gn0r9/f936tGnTxDG//vqr2JOiRgHzYi1Hjhwp9qQYP+BZRKse1f1SxX+qbmvcuHG6ddU3+//991+xp4p/W7x4sW7d3AmpXLlyaR6jiuts3Lix2Dt48KDYq1y5sm49NjbW9HNiYqJVZx6nlzHmcMOGDeJlVHG4EyZM0K23bt1aHDNkyBCxp5qXf/rpJ926Kv5RFaEZFxcn9qR5T/X6unnzpthTRTZLMYmTJk0Sx6iiRocNGyb2pFjLn3/+WRyjmjccHR3FnhTLq3qPUp1ESJpfAeDRo0e69WvXroljVO8bVapUEXvx8fG69aTzRlqoHkPp/Uua/wFg1KhRYk81Z0vv50mfn5qmcY95Ouzduxd9+vSBl5cX7t+/j3feeQfvv/++6TFt0aIF7ty5k6nbYL/vZkRERERkd2xhT/6AAQOwdu1aHDlyBKdOnUJwcDBq1aqFy5cvA3j2R1Rms+s9+URERERkX2zhE4aIiAjTCcVy5syJ2bNnY9OmTWjatKnyCIKMxD35RERERGQTDAYDHBwczP5nqT8QJkyYgGbNmmHz5s2mWqtWrXDgwAGsW7dOebbqjMI9+UREREREGWjQoEGoVq0azp49m6zu6+uL7du349tvv830beCefCIiIiKyGbZwTD4AVKtWDb1799bt7dixA//880+m3r5d78k3GAzInv3ZXVR9O12V5LFy5UrdetOmTcUx77//vthTJQbUrl1btx4ZGSmOUVGlWiT9+CgpVYLOmDFjxJ4qbWjBggW69Tlz5ohjVL+TH3/8UeyZQ3rcATlNBID4UdsHH3wgjpk1a5bYq1atmtjLaKokj/z58+vWVWkixteZHinJCQCOHj2qW2/QoIE4Zt++fWLv6dOnYk/axuDgYNPPCQkJdpuuYzAYTMke77zzjng51WtPSvKYO3euOEaVJnL37l2xt3DhQt16+fLlxTHLly8XexUqVBB7devW1a2rnmv+/v5ir2HDhmJv4MCBuvXHjx+LY4wpcXrq1Kkj9qRkmEKFColj7t27J/ZU70XS9ufMmVMcc/78ebE3dOhQsffdd9/p1r/88ktxzOjRo8Xe3r17xV7FihV16zly5BDHqNKL8ubNK/aio6N169988404ZuzYsWJP+v0DcqJU0m2w5nQda92utHj11VdRp04dzJs3D127ds2U27DrRT4RERER2Rd7WOSPGTMG5cqVw1tvvYXjx4/jyy+/1N3J9PDhQ2XstYp97rIiIiIiIrJirVq1wpEjR7B161Y0a9YMDx8+TNYPDQ1F9erVxU+9X4R78omIiIjIZtjDnvzr169j7ty5CAoKQq5cubBz506UL18edevWRe7cuXH37l1s27YNERERCAkJQfXq1dN8G1zkExEREZHNsIdFfrNmzRAUFIRmzZqhYcOGqFWrFq5evYpVq1bB29sbzZo1Q//+/dGsWTM0adLErNvgIp+IiIiIbIY9LPJbtGiB3r17pwg12bJlC3r06AF3d3d88cUXyJYtm9m3wUU+EREREZEFzZgxA3FxcSnqLVq0wNGjR/HGG2+gSZMmWLVqFfLkyWPWbdj1Ij8xMdEUE6WK8UpMTBR7MTExunVVFOa1a9fEniqucfXq1br1evXqiWMePXok9lSxa2vXrtWtlyxZUhyjislUxYJJcWdTp04Vx1SqVEnsVa5cWey99tprunXVl1bu378v9lTjpMdqy5Yt4piTJ0+KPVWs3U8//aRbf+utt8Qxr776qthTxZD6+fnp1lXxdIcPHxZ7qsmpXLlyunVVjKOKKgI2X758uvUrV66YflZFgdq6hIQE03Nd9XpVzW1ST7VX7datW2JPFSkrvVYmTpwojlHFtUrzEACULVtWt+7r6yuOUb1eVY+hFB18+/Ztccx///0n9lTzl/S+p3q9hoeHiz3pcQLk55Qq1vbSpUtiTxUpKD1vVPNrbGys2Js5c6bYk37PqojqKVOmiD1VrKW0x/aNN94Qx9y4cUPsqe7ztGnTdOtJX1/Wurc8vXn31nS/pIjhwMBAHDx4EH379kXlypWxefNm8f1Shek6RERERGQzbOVkWOnh6uqK5cuXY8SIETh48KBZ12G/u62IiIiIyO7Y0mI9vUaMGKH8dFCFe/KJiIiIiKyUuV++5Z58IiIiIrIZemeGpZS4yCciIiIim/EyHa6THlzkExEREZHN4CI/dex+kW+Mq5KiMAF1XF+PHj106wMHDnzhbeqRYquAZ5FJev79919xjOo4LdV2SHFtBQsWFMeMGzdO7Kkiw1555RXdepcuXcQxKqpIvjfffDNNdQAoXbq02FPFUJpDFQ2q0rdv3zTVX0SK7QKA5s2b69ZV8YQ1a9YUe61atRJ7/fr10617eHiIY1atWiX2VBP/3r17deuhoaGmn+Pj45WPjS0zGAxwcnICoI41dHNzE3uvv/66bv2jjz4Sx6hiEtu1a5fm7VBt37Zt28RegQIFxJ4Ulevv7y+OefjwodhTvVakM1cuWrRIHFO1alWxp4pQdHFx0a2r4j8jIiLE3qZNm8ReixYtdOvXr18Xx9SvX1/s9e7dW+xJUYLVqlUTx6hiQzdv3iz2pMjmUaNGiWOio6PFnhRRDMjz8m+//SaO+eCDD8Rer169xF7Pnj116+Z+wZNkqteAimr+SS27X+QTERERkf2wpT35AQEBZm1vRvzBxUU+EREREdkEWzsZ1sKFC7PsjxIu8omIiIjIZtjSnnzVoWeZzSoziGJiYjBmzBgUKFAArq6uqFmzJrZv357Vm0VEZHGcD4mIrMeUKVNgMBjE74ZYE6vck9+7d2+sXr0aw4cPR/HixbF48WK0bNkSu3btQp06dbJ684iILIbzIRFRclm1Jz80NBRTp05Fjhw50nU90dHR+P3333HixAk8fvwYiYmJyfoGgwE//fRTum4DsMJF/pEjR/Drr79i+vTpGDlyJIBn3wIvV64cRo8ejQMHDmTxFhIRWQbnQyKilLJqkT9y5Ei88sorSEhIwL1798y6jmvXrqFhw4YIDg5Grly58PjxY3h5eeHRo0dISEhA3rx54e7uniHba3WL/NWrVyNbtmwYMGCAqebi4oK+ffvio48+QkhIiDKCKqmoqCjTx9pSbBmgjn+cMWOGbl0V45grVy6xp4pCK1GihG5dFV05evRosTdv3jyx17VrV936P//8I45RRdD99ddfYq9w4cJizxx79uwRe66urrr1d955RxyjildVkZ4b77//vjjm1KlTZt1W3rx5devmTjIqqvg/cyxdulTseXl56dbDw8PFMZ06dRJ7w4cPF3tSfGlcXJzpZ3NPHZ5ZMno+NP5umzZtKl5u/PjxYm/BggW6dSmeFFDH1yaNL33exYsXdeuff/65OGb58uVir23btmJPit6U5pMX9bp16yb2pOeYao564403xJ7q0K0jR47o1lVzctmyZcWe6vFN+jpKqnz58uKY5/deJjVo0CCxJz2G0nMGAGrUqCH2Zs6cKfa+/PJL3brqvVd6LADgzp07Yk96Dqjiprt37y72vv32W7GXJ08e3bq574eWlhWL/L1792L16tU4efIk3nvvPbOvZ9SoUXj8+DEOHTqEwMBAeHt747fffsOrr76Kb7/9FnPmzMHWrVszZJut7pj8kydPokSJEilyso0vUHMXSUREtobzIRFR1ktISMB7772Hfv36Kf9wTY2//voL77zzDmrUqAEHh2fLcE3T4OzsjFGjRqFx48bKHVZpYXV78sPCwuDr65uibqzdvHlTd9zzJ5IKCQkR9xISEdkCzodERCmld09+SEhIinnyypUr4uV/+OEHXLt2DTt27EjX7QLPTkYYEBAA4NmJHw0GAx4/fmzq16pVy3R4ZnpZ3Z78qKgo3TPQGs/cFxUVZelNIiLKEpwPiYhScnBwMPtfWt2/fx8ff/wxJkyYgHz58qV72/39/U2HKmbPnh0FCxbEoUOHTP3z58+LZ6tOK6vbk+/q6qp7TJjxNNHScZDP/wUWGBiIJ0+eZPwGEhFZCOdDIqLkMuJkWH5+fso990mNHz8eXl5e6ToOP6lGjRph/fr1mDhxIoBnCWrTpk3Dw4cPkZiYiKVLl6Jnz54ZcltWt8j39fXFjRs3UtTDwsIAqL/8SURkTzgfEhFlncuXL2P+/PmYOXNmssMjo6OjERcXh+DgYHh4eKTpcMgPP/wQR48eRUxMDJydnfHRRx/h5s2bpqCFbt26icEeaWV1i/xKlSph165dCA8PT/Zls8OHD5v6qRUeHo7vvvsOgPpYK1UaSqNGjXTr+/btE8cEBweLPVUKxblz53TrhQoVEsesXLlS7PXo0UPsDRw4UOxZO1WqhZSiJKXTAEDu3LnFXseOHcXerFmzxJ5k48aNYq9169ZiT0rRKV68uDjm8uXLYk+VeHPy5Endeps2bcQxquSKo0ePir0NGzbo1letWiWOGTJkiNhT/S6l5I2kiVfmfJSbmTJyPoyIiMDChQsByMfyA+p0ncWLF+vWK1SoII5R7XHT+76B0dq1a3Xrqud1+/btxZ6jo6PYa9mypW49NjZWHKP6ZOT27dtiLyEhQbeu+nheNW+o3oukQwtUc6gqhUhKZQPkOVaVoKT6nZQsWVLsffbZZ7p1455RPVKaDAA8ePBA7E2dOlW3XrBgQXGMKqWuVKlSYm/UqFG69ddee00co3rfkNKVADkFMOlzXtM0qz2zrKW268aNG0hMTMTQoUMxdOjQFP0iRYpg2LBhyoSm5/n7+8Pf39/0/y4uLvjxxx/x448/ZsQmJ2Nd72h4tqhKSEjA/PnzTbWYmBgsWrQINWvWTHVcHBGRreN8SESUkvGQHXP+pUW5cuWwdu3aFP/Kli0Lf39/rF27Fn379k3TdcbHxytjosPDwxEfH5+m65RY3Z78mjVrolOnThg7dizu3LmDYsWKYcmSJQgODs6Qs38REdkKzodERClZ6lPXvHnz6n5CaNxzr/r0UDJ06FDs3bsXZ8+e1e2/+uqraNSokVlHCzzP6vbkA8DPP/+M4cOHY+nSpRg6dCji4uKwceNG1KtXL6s3jYjIojgfEhHZjz///FN5KHDHjh2xefPmDLktq9uTDzw7Pmn69OmYPn16Vm8KEVGW4nxIRJRcVn9XYPfu3WaPvXnzpvI7HQUKFNANXDCHVS7yiYiIiIj0ZPUiPz3y5MmDS5cuif0LFy6kOMu5uazycB0iIiIiouel50u36c3YzwjNmzfHvHnzdJPsTpw4gfnz56NFixYZclsGTdO0DLkmKxMYGIjQ0FBTDJcqSurOnTtiT/pIRRX9pYoMbNq0qdiTotVU38K2V6rIuBMnToi9509TbaSKE5ViywAoD5H466+/dOtS7CoAnDp1Suypnhuq56g5VDGvX3/9tW5dlcnerFkzsbds2TKxJ93n2rVri2MaNGgg9lSxe40bN9atJz32ccuWLcifP3+qT5JiKwIDAxEcHIycOXMCAO7evSte9unTp2JPipTMnz+/OEYVT2g8qZce47Y+z3iOAD0lSpQQe1evXhV7UjRoq1atxDGq2NjIyEixJ21/9uzyB+vSewMAZXTfN998o1uX4mSBZ5GAEm9vb7G3a9cu3XrNmjXFMaq5vGjRomJPiuUMCAgQx+zfv1/sJT3b6PMGDRqkW1+3bp045u233xZ70pctATleU5W08sYbb4g9Kf4TAHLkyKFbTxqvPHfuXHh5eVnVfBgYGIjIyEh8+eWXZl/H6NGj4e7unmX36+bNm6hevTru3LmDtm3bomzZsgCePTc2bNgAb29vHD58WBmfnlo8XIeIiIiIbEZW741PjwIFCuDYsWP48MMPsX79etM5QTw8PNC9e3dMnTo1w050yEU+EREREdkMaztxYVr5+vpiyZIl0DTN9Mlqvnz5MvyPFy7yiYiIiMhm2PKe/KSePHmC+/fvAwDc3Nzg7u6eoddv238KERERERHZkKNHj6Jhw4bInTs3ypUrh3LlyiF37txo1KgRjh07lmG3wz35RERERGQzbHlP/uHDh9GgQQM4OTmhX79+KF26NIBn0ZkrVqxAvXr1sHv3buWX+1OLi3wiIiIishm2vMgfN24cChYsiP3798PHxydZ75NPPsGrr76KcePGYfv27em+LbuO0IyPj8fevXsBAIULFxYvq4pr3LJli249V65c4pihQ4eKvQEDBoi9DRs2iD1r98cff4g9Z2dn3fqFCxfEMeXLlxd7+fLlE3sVKlQQe+aIiooSe1Ic5q1bt8QxqqjJhw8fij3V2fHMMXfuXLEnxY3eu3dPHLNgwQKx16lTJ7FXsWJF3boqMvDcuXNiL1u2bGLv+++/161/++23pp+NEYzWFBmXEQIDA5GQkGCKClRFIapiDaXHV/WGW7lyZbFnPBZVjzT3quZXKcYRkJ9rAJCYmKhbj4mJEceoPlKvW7eu2JNiQ1W3pYpRlqIQAcDJyUm3fu3aNXGMan69fv262JNeM6p4VVVcp5eXl9iTHkMpdhV4duZoifT7V/VUz13V9amWXHny5NGtq96HVNGrqrOmSs/fbt26mX42RlJb03wYGBiIJ0+eYNasWWZfx7Bhw5AjR44su185c+bExx9/LMZ3f/nll/jss88QERGR7tviMflERERERBbg4OCgPPdBQkJChqUHcZFPRERERDbDVs92Czw72eN3332n+4na9evX8f333+PVV1/NkNviMflEREREZDOsYbFurqlTp6JevXooVaoUXn/9ddNhopcuXcL69euRPXt2TJs2LUNui4t8IiIiIrIZtrzIr1y5Mg4fPoxx48bhjz/+wNOnTwE8y8lv3rw5Jk+ejDJlymTIbXGRT0RERERkIWXKlMHatWuRmJiY7Iy3Dg4OePLkCW7evIkCBQqk+3Z4TD4RERER2QxbPiY/KQcHB+TPnx/58+c3fdl25syZ8PPzy5Drt+s9+Y8ePTId19SuXTvxcsa/ovRIkVyqKMTLly+LvfXr14u9H3/8Ubeuit0cNmyY2Bs4cKDY8/f3162rTqncuHFjsdeqVSuxJz0ejx49Muu2jhw5Ivak+zxv3jxxjMoHH3wg9qTfy82bN8UxkydPFnuqKLRVq1bp1hs0aCCOUUXhzZgxQ+w1b95ctx4ZGSmOUf2+jMcb6qlUqZJuXRWT2KdPH7Gnek598sknuvW4uDjTz5qmWd2bQEZ5/Pgxvv76awDquUEVARsQEKBbL1SokDhGFb2qihp88803desHDhwQx5QrV07sqeIEx4wZo1tXvdEWK1ZM7NWsWVPsXbp0SbeuiowsWrSo2Fu5cqXYk+Zl48l39KhiaFVzQMmSJXXrf/31lzhGlQPepk0bsSfNldI8Cahjg1X3S3pPVMVoq96jqlevLvZ++eUX3XqdOnXEMarnqOo9QHrvePLkielna54PMyp9xt7Z9SKfiIiIiOxHevfIW+sfLpmBfwoREREREdkZ7sknIiIiIpvxMu2NTw8u8omIiIjIZtjaIv/EiROpvqzqe31pxUU+EREREdkMW/vibbVq1VL9h0lGfuHZoGmaliHXZGUCAwMB/C/JQHU3nZ2dxd6dO3d067lz5xbHdOnSReypEhTmzJmjW1elHahSY1QpFMuXL9etq9Ipzp49K/b27dsn9qR0lfz584tjVEaNGiX2pASVHDlymHVbKlIig+r5FBUVJfbeeecdsXf+/Hndet68ecUx27ZtE3sq0uPbqVMns66vVKlSYk96DNu3by+O+eqrr8Se9LwGgJCQEN26k5OT6eetW7cif/78uHLling9tigwMBCapuHixYsA1PNhy5YtxZ4qDUUiPe6AnF4GyK9Z44lj9Kheex06dBB7UkKNq6urOObff/8Ve8b3Hz2HDh3SrasS4B4/fiz2kqZDPe/06dO69fDwcHHMt99+K/bGjx8v9sqXL69bT/r6et7169fFniqVSXq/UT2vCxcuLPak9w0AmDVrlm5dlZKjokpRk6h+J6r59erVq2LPOBc87/79+6afN23aBG9vb6uaDwMDA/H06VMsWLDA7Ovo378/3NzcLHq/lixZkuYxvXr1Svftck8+EREREdkMWztcJyMW7ObgIp+IiIiIbIatLfKzChf5RERERGQzuMhPHdv65gIREREREb0Q9+QTERERkU3gGW9Tj3vyiYiIiMhmODg4mP0vrc6dO4dOnTohMDAQbm5uyJs3L+rVq4cNGzZkwj3LWHa9J//JkydYv349AHUsnCqCLDY2Vreu+kvwjTfeEHuqmMQffvhBt37q1ClxTMmSJcVe06ZNxZ4U5Xn48GFxTExMjNhr1aqV2Nu6datu/fLly+KY4sWLi73p06eLvWrVqom9jFa2bFndeuXKlcUxwcHBYu/nn38We9JzVBV5qjr5RpkyZcSe9DwsVqyYOEYV8ffjjz+KvTfffFO3ropkVd3WkCFDxJ6Hh4du3dvb2/SzKo7O1sXGxuLkyZMA1L/Lv/76S+zFx8fr1lXzoSq+VpobAKBRo0a6dVUMsaOjo9j7/fffxZ4U5aqKvFXFKN+9e1fsSXOUam5QRXmqxknxxdJrHFDHMufLl0/sSYuno0ePimNu374t9lT3uUGDBrp1aU4G1O/zbdu2FXu//fabbt3cqGRVtHXSuSipQYMGiWNUcahVqlQRe2FhYbr1pFGo1jwfWnJv/LVr1xAREYFevXqhQIECePr0KX7//Xe0bdsW8+bNw4ABAyy2LWll14t8IiIiIiJztWzZMsWO4iFDhqBq1aqYMWOGVS/yebgOEREREdkM43H55vzLCNmyZYOfnx8ePXqUIdeXWbgnn4iIiIhsRlZ8efbJkyeIiorC48eP8ccff2DLli3o0qWLxbcjLbjIJyIiIiKbYDAYzPoCbdLx5vjggw9M31lxcHDAG2+8gTlz5pi9HZbART4RERERvTRCQkIQGBiYrHblyhXlmOHDh6Njx464efMmVq5ciYSEBDGcxVpwkU9ERERENiMrDtcpVaqUKXGoZ8+eaNq0Kdq0aYPDhw9bbfa+XS/y3dzc0Lp1awDqyDApSgqQ48Ru3boljnFychJ7xgg7PVIUWsOGDcUxe/fuFXurV68We9JHTKr4PNV9XrRokdg7ffq0bl0V76WK7rp48aLYs+TxcdeuXdOtG59zevz8/MSeKjKudOnSuvWRI0eKYwICAsRe1apVxZ6Li4tuXfW8njp1qthTfZwp7QVRReudP39e7DVp0kTsSXPA4MGDTT9b60SdEZycnEzxrn///bd4ufv374u9X3/9Vbe+cuVKcYzqd9muXTuxt2DBAt36iBEjxDGquGFVbKyPj49u/cmTJ+IYNzc3sRcdHS32EhISdOuqSM6goCCxlzNnTrEXERGhWx82bJg45syZM2JPFYc6bdo03brqfei9994Te6rHXooGHTp0qDhGimQF1HO2FOesiuRURWWrIoU1TdOtq2Iyd+3aJfa6d+8u9qTfS9IIaHueD/38/F645/5FOnbsiIEDByIoKEgZZ56V7HqRT0RERET2xRr+ADGeD0F17pasxghNIiIiIrIZlozQvHPnTopaXFwcfv75Z7i6uio/Jcxq3JNPRERERKRj4MCBCA8PR7169VCwYEHcunULy5Ytw8WLF/H111/D3d09qzdRZJE9+Tt37kSfPn1QokQJuLm5ITAwEP369ROPhT9w4ADq1KkDNzc3+Pj4YOjQoeJpx4mIbAnnQyKi9LHknvwuXbrAwcEBc+fOxeDBgzFjxgwUKlQI69evx/vvv58J9y7jWGRP/pgxY/DgwQN06tQJxYsXx5UrVzBnzhxs3LgRp06dSvalp1OnTqFx48YoXbo0ZsyYgdDQUHz11Ve4fPkytmzZYonNJSLKNJwPiYjSx5LH5L/55pt48803LXZ7Gckii/wZM2agTp06yU5e0Lx5c9SvXx9z5szB5MmTTfWPPvoIuXPnxu7du+Hh4QHgWUpI//79sW3bNjRt2tQSm0xElCk4HxIRpY81fPHWFhg0KbPJAvLkyYMGDRrg999/B/AsJipPnjwYMWIEvvzyS9PlYmNjkSdPHnTp0kUZP5VUYGAgoqKisGTJEgBAjRo1xMuq4s6keDJVpFmFChXEXrZs2cTeF198kebbWrhwodjr1KmT2JPizj788ENxzPTp08Xehg0bxF6dOnV06z/99JM45rvvvhN73t7eYk/vCzIvoposMvrloYqTVMVaPn/SDqN8+fKJY/Lnzy/27t69K/auXr2qWy9SpIg4RpUuoIr4kx571e9RFTWqeq1IsXtJYwGLFSsG4MUnRckMmT0fhoeHm/6A6N27t3jZmJgYsSfFq6ridQsXLiz2VCeSmTFjhm5dFZNarVo1sXf58mWx5+npqVtXPZ9Ut7Vs2TKxp5qXJcYUDz2q44GliN13331XHHP06FGxd/bsWbEnzcvx8fHiGFUEcGJiotiT3kdVc3n16tXFnip6VbrP5cqVE8c8evRI7KnmQ+ksrqGhoeKYPHnyiL2DBw+KPen9JunzyRgfmhXzoSQwMBDR0dHK2N4X6dy5M1xcXKzqfmWWLPvibWRkJCIjI5E3b15T7cyZM4iPj08xeTo5OaFSpUrKjHkiIlvF+ZCIKPW4Jz91smyRP3PmTMTGxiY7eZHxi2e+vr4pLu/r64t9+/aJ1/f8ns6QkJBkb5hERNbKEvOhtLeaiMiWmPsF2qTjXxZpXuQnJiYqP2JNytnZWffB3Lt3Lz799FN07tw52VnojB9JOjs7pxjj4uKi/MiSiMjSOB8SEZG1SvMif+/evWjYsGGqLnvhwgWUKlUqWe3ixYt4/fXXUa5cuRTHkxqPtdU7JjQ6Olp5LO7zx1YZj8knIsostjQfhoeHp2o7iYjIPqR5kV+qVCksWrQoVZd9/mPmkJAQNG3aFJ6enti8eXOKL6AYL6+XFx0WFoYCBQqkdXOJiDIN50MiIst7mQ65SY80L/J9fHyUyQyS+/fvo2nTpoiJicHOnTt1jzMtV64csmfPjmPHjqFz586memxsLE6dOpWslhrZsmUzffNclZLw119/ib3+/fvr1itXriyOUaU46H30biSl8qhSbWbNmiX2SpcuLfb0Hv8X3ZbqsISkCSXPMyaWPG/Hjh3iGBVzEnTmzp0r9gYPHiz2+vTpI/akZKNu3bqJY4YMGSL2VAkPUlLO+fPnxTFHjhwRe1u3bhV7UpLDsGHDxDFubm5ir1evXmJv9uzZuvWnT5+KY1TPNdVJopycnHTrSRMooqOjxQQZPbY0H7q6uqJu3boAgNOnT4uX27Nnj9gbOHCgbt3f318cs2nTJrFXu3btNN+WavukZCgA+Oyzz8Te/PnzdeuqBBXVc1RKwwLk5++ZM2fEMfXr1xd7GzduFHvt27dP0zYAUP7x2LNnT7G3d+9e3bqUkgQAb731ltj79ddfxZ4xTvZ5qhSa7du3iz1p2wHg2rVruvUpU6aIY1SJR6r3lG+//Va3HhcXJ45RLXZVRzNIc3bS11da50NL4iI/dSxyxtsnT56gZcuWuHHjBjZv3myKZXqep6cnXnvtNfzyyy+IiIgw1ZcuXYrIyEizoseIiKwJ50MiovSx5BlvbZlF0nW6d++OI0eOoE+fPrhw4QIuXLhg6rm7uyfb2zBlyhTUrl0b9evXx4ABAxAaGoqvv/4aTZs2RfPmzS2xuUREmYbzIRERWYJFFvnGwxAWLlyY4hCHwoULJ3tTq1KlCnbs2IExY8ZgxIgRyJkzJ/r27SuevImIyJZwPiQiSp+XbY+8uSyyyA8ODk7T5evUqYO///47czaGiCgLcT4kIkofLvJTJ8tOhkVERERElFZc5KeORb54S0RERERElmPQNE3L6o3IDIGBgUhISMCBAwcAAI6OjuJlkyZXPG/VqlW6dVUUoip2TRVdd/fuXd26FEEJqCPDChUqJPaaNGmiW5ei5AB1TF50dLTY279/v27dwUH+G7N8+fJir1+/fmJPipPr0qWLOEZ1UqHvv/9e7EkxdKovRNarV0/sqe6z9PvKli2bOEb1+KoiRUNCQnTr77//vjhGFRl38+ZNsefn56dbV0XN7t69W+zlzZtX7BUsWFC3/vDhQ9PPDRo0QPbs2VOcTMrWGedDY1youfOhFIepivN88803xd6cOXPEnre3t249d+7c4hhVrOXz5yFIauTIkbr1Dh06iGNq1aol9m7cuCH2pNesp6enOCZ7dvlDd73zKBitWbNGt66aD1Wv5XPnzom9XLly6dal1x2gf6I3I9V7m/QckKI1X9Tbtm2b2JPmw65du4pjVPPy/fv3xZ70nFfFWO7atUvsqeJQpdtKetK8unXrWt18GBgYiNjYWKxfv97s62jXrh2cnJys6n5lFu7JJyIiIiKyMzwmn4iIiIhsBo/JTx3uySciIiIisjPck09ERERENoN78lOHi3wiIiIishlc5KcOF/lEREREZDO4yE8du17kP3r0CF999RUAoGPHjuLlAgICxF6+fPl063fu3BHHqOK4VNFaUuTlypUrxTGdOnUSe0ePHhV78+bN060XKVJEHJOYmCj2PvvsM7E3efJk3fqyZcvEMQ8ePBB7qsdj/PjxuvUJEyaIY6RYQAAYM2aM2JN8++23Yq9///5iz8fHR+xJEaX37t0Tx/j6+oq9bt26iT3pOteuXSuOUUX8qaJBpW2Mj48XxxQvXlzsqWLynJycdOuq55o9efz4MWbPng0AaNq0qXg5VQSwFIfq5uYmjlG9XlVxmNJzSorJBYDWrVuLvZMnT4q9Dz74QLeuiiCMi4sTe0eOHBF7r7/+um798uXL4pgyZcqIvZ9++knsSZG9qthgKRoYUD8eUpRjr169xDGqmN9KlSqJvaSxt0mp4j9V7701a9YUe4ULF9atf/jhh+IY1evhrbfeEntSBLBqjlK9XlVRxNJzIOnaxk4T1l8qdr3IJyIiIiL7wj35qcNFPhERERHZDC7yU4eLfCIiIiKyGVzkpw5z8omIiIiI7Az35BMRERGRTTAYDOnak/8yfQrAPflERERERHbGoNlpRlJgYCASExNNsWmxsbHiZVV/1bm4uOjWVRFZ//33n9grVqyY2Lt+/Xqab6tVq1Zi7/fffxd7kZGRunXV00EVn/bPP/+IPSkmTxULp4pQvH37ttjLnz+/bj1PnjzimEePHok9VQTZG2+8oVtfunSpOMbR0VHsBQUFiT0pJu3+/fvimCZNmoi9vXv3ir2EhIQ035Yqdk/1u/Ty8tKtqx73zZs3i72qVauKPSmiMGm0XqdOneDs7IwrV66I12OLjPOh8XUaHh4uXtbT01PsSfOo6vWlinlVzW1SZK8qCrF79+5i75tvvhF70nM7JiZGHKOKG7506ZLYk2IeVVGzqvco1eMhWb16tdhr27at2CtRooTYkyJKVXOeKpZZ9TyUojefPHkijhk7dqzYM0Zt65Ge89I8Cah/X2FhYWLP399ft656DA8cOCD2pPhPQH6OJp3LrXE+DAwMRFxcHLZu3Wr2dTRr1gyOjo5Wdb8yC/fkExERERHpOHr0KIYMGYKyZcsiR44c8Pf3R+fOnZU75qwFj8knIiIiIpthyePqv/jiC/z999/o1KkTKlSogFu3bmHOnDmoUqUKDh06pDwhWVbjIp+IiIiIbIYlF/nvv/8+li9fnuys6V26dEH58uXx+eef45dffrHYtqQVF/lEREREZDMsucivXbt2ilrx4sVRtmxZXLhwwWLbYQ4ek09ERERElEqapuH27dvImzdvVm+Kkl3vyY+Pj8fVq1cBAAsWLBAvV6VKFbHXqVMn3fq+ffvEMcbb1KNKZAgODtatq5JratasKfY8PDzEnvQt/n///VccI20fADRs2FDsSYkHf/75pzhGSskBgBo1aoi96dOn69Z3796d5jGA+vGQHsPs2eWXlSrVRpU2NGHCBN26KpHj+PHjYk+VaiIlr+TLl08cI6VdAOrEi507d+rW69atK45p1qyZ2Hv8+LHYk54327dvN/2sSsywdQkJCQgNDQWgng9VSTkffPCBbl1KLgLU80atWrXSPE6VDKNKAFOltUiv5ZCQEHHM2bNnxZ4q2Up6faneN1SpZ4UKFRJ7cXFxunVVgo4qbUxKgAOA6OjoNG0DIKfXAeo9tdJ7our9VfU+qpqzb9y4oVtXvU5Uvy8fHx+xd/r0ad26KtVI9X6omnvr1aunW0+aXmbN82F69+SHhIQgMDAwWS0taTvLli3DjRs3MGnSpHRtR2az60U+EREREdmXrDyh1cWLF/Huu++iVq1a6NWrV5ZtR2pwkU9ERERELw0/Pz+zcvJv3bqFVq1awdPTE6tXrzbrPBWWxEU+EREREZHC48eP0aJFCzx69Aj79u1THh5oLbjIJyIiIiKbYenDdaKjo9GmTRsEBQVhx44dyu/QWRMu8omIiIjIJhgMhnQt8tM6NiEhAV26dMHBgwexfv16ZWCAteEin4iIiIhIxwcffIA//vgDbdq0wYMHD1Kc/KpHjx5ZtGUvZtBUWU82LDAwEJGRkZgxYwYAoEOHDuJlY2NjxZ4UraWKjCtWrJjYc3V1FXtS1Jgqgs7Z2dms28qdO7duXfVYHDhwQOy9+uqrYu/OnTu6ddUXVlTxZKooNGk7oqKixDEqt27dEnve3t66dSlyDQA2btwo9lSP/ciRI3XrUmwdACxZskTsffLJJ2Jvz549unVVPGWFChXE3s2bN8VewYIFdeuqx0J18pHnI9GSkqa6nj17mn7et28ffHx8zPpCljUzzofffPMNAKB169biZZOe1fF5UlTq7du3xTGq17IqyjUyMlK3rop4lOIpAXUErJeXl279/v374ph169aJvS5duog96bFSPRaqOOTExESx165dO936X3/9JY5RxS6qnhvS+41q+1QRxTly5BB70tyrinxUxRerYnn/+++/NN+WKq5V9XhI78vx8fHiGNX6wJzY41atWpl+Pn36NAoUKGBV82FgYCDi4+Oxa9cus6+jYcOGyJ49e6rvV4MGDcT3RUAdmZrVuCefiIiIiGyGJY/JV51nx9pxkU9ERERENiMrc/JtCRf5RERERGQzuMhPHflc9EREREREZJO4yCciIiIisjM8XIeIiIiIbAYP10kdu17kOzk5oVy5cqafJar4o7t37+rWpfgpADhx4oTYq1y5stibNWuWbr1v377iGFWEoipec8eOHbr14sWLi2NUMYlS1CgA+Pj46NZV26eKrpSuD5DjGlVxoqpIs5w5c4q9DRs26NY3b94sjqlYsaLYUz32UoSaKtb0lVdeEXtSLBwgPx5SvBugfj1s3bpV7HXr1k23LkUaAurfl2ril8b9+uuvpp9Vr09b5+zsjCpVqgBQP69VUanSYxgRESGOCQsLE3uqOWXMmDG6dVX8q4uLi1m9bdu26dalqEYgedTg81SRl1I8rCruUBXZLG07IEdlzpkzRxwzePBgsad6fUnxpQcPHhTHODo6ij3Vc1SimhtUzzVVVKq0jaoo11y5cok91fuDNGf7+vqKY1RRnqrfl7Tu2bRpk+nnatWqieOzGhf5qcPDdYiIiIiI7AwX+UREREREdsauD9chIiIiIvvCw3VSJ0v25Pfv3x8Gg0E8tfoff/yBKlWqwMXFBf7+/pg4caLytM5ERLaK8yERUeoZDIZ0/3tZWHyRf+zYMSxevFj8EtSWLVvQvn175MqVC7Nnz0b79u0xefJkvPfeexbeUiKizMX5kIiIMotFD9fRNA1Dhw5Fz549sXPnTt3LjBw5EhUqVMC2bdtMiS0eHh6YOnUqhg0bhlKlSllyk4mIMgXnQyIi87xMe+PTw6KL/KVLl+Ls2bNYs2aN7pva+fPncf78eXz33XfJIhnfeecdTJkyBatXr8b48eNTfXuOjo4oXbo0AHVkoOrJkj9/ft26KpLz33//FXvHjh0Te126dNGtq6ILY2JixN65c+fEXtGiRXXrFy5cEMeoIhlnzJgh9rp3765bv3fvnjhGFaF4+vRpsdeiRQvdelBQkDhGRRWT1rRpU936a6+9Jo5RxcKdPXtW7P3zzz+69YYNG4pjVL/Lp0+fij13d3fduiri78aNG2JP9VqRojdVkYxSrC0A7N69W+x17NhRt540MjIxMVEZB5qRsmI+LFasGAB1JKMqblZ6buTJk0ccc+fOHbEnPa8BYNSoUbp1T09PcYwqJlM1BxQuXFi3LkXyAjA9lnqWL18u9oyxzs978OCBOEb1GpKe14D83jZkyBBxzJMnT8SeijS3NW7cWByjev9SvQ5/+ukn3XrPnj3FMaq5XPX4SgoWLCj2rl+/LvbOnz8v9po3b65bl+JJAeD27dtiTxVf2r59e9160t+/JedDyhwWW+RHRERgzJgx+Oijj8Sc85MnTwJImc1aoEABFCpUyNQnIrJlnA+JiMzHPfmpY7FF/qRJk+Dq6ooRI0aIlzGeNEXvxA++vr7KvSqBgYHJ/j8kJASFChUyc2uJiDJPVsyHfn5+Zm4tERHZojQv8hMTE8Uz9j3P2dkZBoMBQUFBmDVrFlasWKE8y2lUVJRp3PNcXFyUH1kREVka50MiIsvjnvzUSfMif+/evcrjgJO6cOECSpUqhWHDhqF27dro0KGD8vLGY0H1jtOLjo5WHit65cqVZP8fGBgonraZiCgj2NJ8SERkL7jIT500L/JLlSqFRYsWpeqyvr6++Ouvv/Dnn39izZo1CA4ONvXi4+MRFRWF4OBgeHl5wcPDw/SxdFhYWIqPlsPCwlCjRo20bi4RUabhfEhERNYqzYt8Hx8f9O7dO9WXN37L/I033kjRu3HjBooUKYJvvvkGw4cPR6VKlQA8S6BJ+gZ28+ZNhIaGYsCAAWna1qioKGzZsgWAnAoBAJUrVxZ7cXFxuvWVK1eKY1TbqVoQSN/wd3R0FMdIKQMAMG7cOLEn0Tv+1+jhw4diz/g465GSfDp37iyOSboAep4qvUZKhlCl2hw6dEjs1axZU+wdOXJEty49ZwAoP12qX7++2JOSN1QpNKr0Dzc3N7FXpEgR3fpXX30ljmnZsqXYUyVeSCk/qtQNVcpPaGio2JPShpLWY2JikiXZvIgtzYeRkZH49ddfAagTdKSED+B/hxA9b9WqVeKYvn37ij3VPCrtqVO9hpYtWyb2pLQeFVWCiupwqc8//1zsffPNN7r1Jk2aiGNUKSnS6xWQH0NV8pbqPqveR6W5SLXHVdVT3Zbx+yrPU6WGqd7bVHOKtB3ffvutOKZVq1ZiT/U8jI6O1q0nJCSIY6QEQED9Pnrx4kXdetL0n7TOh2R9Mv2316hRI6xduzZFfcCAAShcuDDGjRuH8uXLAwDKli2LUqVKYf78+Rg4cCCyZcsGAJg7dy4MBoMyKoyIyNpxPiQiSj8erpM6mb7I9/f3h7+/f4r68OHDkT9//hRZrdOnT0fbtm3RtGlTvPnmmzh79izmzJmDfv36mTLviYhsEedDIqL04yI/dazuLAetW7fGmjVr8ODBA7z33ntYs2YNPvroI3z33XdZvWlERBbF+ZCIiMyVZQdbqY4Va9++vXg2NiIie8P5kIiIMhq/UUFERERENoOH66QOF/lEREREZBMMBkO6Fvkv0x8Idr3Id3FxMZ2oRhVruH79erHXoEED3XqFChXEMY8ePRJ7qkhGKQpt7ty54phOnTqJvYEDB4q9HDly6NYDAgLEMRs2bBB7W7duFXt79uzRraui8FSRYR4eHmLv6tWrunVVzNgrr7wi9hITE8We9ByQolCBZ/GHkrt374o9Y/Ti81RfvvTx8RF7qvslRa+qIv5Uk6b0OwGAkiVL6ta///57cczbb78t9nr16iX2cuXKpVtP+vtS/e5sXY4cOfD6668DeBanKVm4cKHYa9OmjW69atWq4hjVbRljQvUULlxYt656buhFkxoNGTJE7ElnHpa24UXbERQUJPZOnDihW1e9JqXoUuDZl7YlCxYs0K17eXmJY3Lnzi32VNsoxbKqIqBV90sVURoSEqJbV8UG582bV+zdv39f7H388ce69caNG4tjVO9t//33n9iT5sPZs2eLY/r06SP2evToIfby5MmjW7eV+fBlWqinh9V98ZaIiIiIiNKHi3wiIiIiIjtj14frEBEREZF94eE6qcM9+URERERkM4xfvjXnX1pFRkZi4sSJaN68Oby8vGAwGLB48eKMv1OZgIt8IiIiIiId9+7dw6RJk3DhwgVUrFgxqzcnTXi4DhERERGRDl9fX4SFhcHHxwfHjh1D9erVs3qTUs2uF/nx8fGm6MGCBQuKl+vbt6/YW7ZsmW69Xbt24hhVfNZff/0l9rp06aJb//fff8Ux8fHxYm/y5MliT4onU8V/fvDBB2LvwYMHYk+KGtu0aVOax7yIt7e3bv38+fPiGDc3N7FXtGhRsSfFi8XGxopjVFGuixYtEntSTN6TJ0/EMaq4TlVk3Pjx43Xr77//vjimfPnyYm/QoEFiz8FB/8PEpk2bimNUMXmq14NqG18G8fHxCA0NBaCOExw2bJjYk6IXVWfkVc2He/fuFXsdOnTQrasiCGNiYsTeJ598Ivak+fDhw4fiGNXrISwsTOxJC4Tt27eLY1SRzbt37xZ70qEJjx8/FsdcvnxZ7FWrVk3subi46NZV7ynS6x8AvvvuO7E3atQo3boqdvPWrVti7+nTp2Lvo48+0q2roktV0bCDBw8We9Lj0apVK3FMYGCg2FM9HrVr19atJ33OWPNx75bcNmdnZ2UktTWz60U+EREREdkXa/4DxJpwkU9EREREL42QkJAUn4JcuXIli7Ym8/CLt0REREREdoZ78omIiIjIZqT3cB0/Pz+73HP/PO7JJyIiIiKyM9yTT0REREQ2wdyTWiUd/7Kw60W+o6MjihQpAgBITEwUL/fuu++KPSlmSopPBIAFCxaIvbfeekvsSVGOqiixbNmyiT1VvGKBAgV066qIR1U8oaOjo9iTXlCqk0oMGTJE7AUHB4u9lStX6tabN28ujvH09BR7qog36bH6+eefxTE9evQQez179hR70uOreq6potpUEYrffvutbv3zzz8Xx6gmTVVc5/Hjx3Xr+fPnF8dMmjRJ7M2aNUvsJSQk6NaTvoayZ7ffKTF79uzw8/MDoI55HT16tNirV6+ebt3Z2Vkco3qOSjGZAODu7q5bnzNnjjhGNR+qYhKleDzpOQOo50PV4yEpXLiw2KtZs6bY27hxo9iTHqtu3bqJY6pWrSr2VPdLikpVnRm0f//+Yk81V0qv0zVr1ohjOnbsKPZy584t9pYuXapb//rrr8UxqvWGaj48ceKEbj1fvnzimKlTp4q9GTNmiD3p/Svpe43q9US2wX7f0YiIiIiI0mnOnDl49OiR6fwzGzZsMJ135L333lPuLMxKBk11phIb5urqivj4eBQqVAiA+oQsqhOeSL841R4/1QkocuTIIfakvaHmfrSkus/SHmpznw7m3JZqT5jqd6La6xIdHa1bd3V1Fceo9tarHnvpPkdERIhjcubMKfZUe3+kPSqqk9p4eHiIPdX9kp6/0p7VF1E9N1Kzd/15qudGnjx5Ur9hOkJDQ5E9e3ZERUWl63qsTVrmQ9XJi6TnFOfD5Mx5Las+RVWdXEv1qZf0PFa9llWvPXMee3PnKNWnKNLzTTX3qp5rqveAyMhI3brqJIoqnA/TJzAwEJqm4cyZM2ZfR/ny5WEwGNL0xduAgABcu3ZNt3f16lUEBASYvT2ZyW4X+cYXrbU+8JYUEhICAKaP6l92fDz+h49FcsZDwVSLNFvE+fB/+JxPjo/H//CxSM4a58OsWuTbKrs9XMf4ZvYy/BJfxHjCBz4Wz/Dx+B8+FsmpThFvyzgf/g+f88nx8fgfPhbJ2et8+DKx20U+EREREdmflykhJz2Yk09EREREZGe4J5+IiIiIbAb35KeO3X7xloiIiIjsh/GLt+fOnTP7OsqWLfvSfPGWh+sQEREREdkZHq5DRERERDaDh+ukDvfkExERERHZGS7yiYiIiIjsDA/XISIiIiKbwcN1Uscm9+Tv3r0bBoNB99+hQ4eSXfbAgQOoU6cO3Nzc4OPjg6FDhyIyMjKLtjxzHD16FEOGDEHZsmWRI0cO+Pv7o3PnzggKCkp2ud69e+s+ZqVKlcqiLbesmJgYjBkzBgUKFICrqytq1qyJ7du3Z/VmZYmdO3eiT58+KFGiBNzc3BAYGIh+/fohLCwsxWUbNGig+7xp3rx5Fmx55li8eLE4p9y6dSvF5f/44w9UqVIFLi4u8Pf3x8SJExEfH58FW8758HmcD1OH8+H/cD5MzpbnQ0rOpvfkDx06FNWrV09WK1asmOnnU6dOoXHjxihdujRmzJiB0NBQfPXVV7h8+TK2bNli6c3NNF988QX+/vtvdOrUCRUqVMCtW7cwZ84cVKlSBYcOHUK5cuVMl3V2dsaPP/6YbLynp6elNzlL9O7dG6tXr8bw4cNRvHhxLF68GC1btsSuXbtQp06drN48ixozZgwePHiATp06oXjx4rhy5QrmzJmDjRs34tSpU/Dx8Ul2+UKFCmHatGnJagUKFLDkJlvEpEmTUKRIkWS1XLlyJfv/LVu2oH379mjQoAFmz56NM2fOYPLkybhz5w7mzp1rwa1NjvPhM5wPU4fz4f9wPtRny/Mh/T/NBu3atUsDoK1atUp5uRYtWmi+vr7a48ePTbUFCxZoALStW7dm9mZazN9//63FxMQkqwUFBWnOzs5a9+7dTbVevXppOXLksPTmWYXDhw9rALTp06ebalFRUVrRokW1WrVqZeGWZY09e/ZoCQkJKWoAtHHjxiWr169fXytbtqwlN8/iFi1apAHQjh49+sLLlilTRqtYsaIWFxdnqo0bN04zGAzahQsXMnMzdXE+TI7z4YtxPkyO82Fy1jwfFilSRAsICNCioqLM/hcQEKAVKVIkw7fNGtnk4TpJRURE6H4sFB4eju3bt6NHjx7w8PAw1Xv27Al3d3esXLnSkpuZqWrXrg0nJ6dkteLFi6Ns2bK4cOFCissnJCQgPDzcUptnFVavXo1s2bJhwIABppqLiwv69u2LgwcPIiQkJAu3zvLq1asHBweHFDUvLy/d5wwAxMfH292hHXoiIiKQkJCg2zt//jzOnz+PAQMGIHv2/30Q+s4770DTNKxevdpSm6mL8yHnw9TgfJgc50OZtc6H0uFEqfn3MrHpRf7bb78NDw8PuLi4oGHDhjh27Jipd+bMGcTHx6NatWrJxjg5OaFSpUo4efKkpTfXojRNw+3bt5E3b95k9adPn8LDwwOenp7w8vLCu++++1JMVCdPnkSJEiWSLXAAoEaNGgCeHcrwsouMjERkZGSK5wwABAUFIUeOHMiZMyd8fHwwYcIExMXFZcFWZq6GDRvCw8MDbm5uaNu2LS5fvpysb5w3np9XChQogEKFCmXpvML5UMb5MDnOhy/G+dC250N6xiaPyXdyckKHDh3QsmVL5M2bF+fPn8dXX32FunXr4sCBA6hcubLpCzO+vr4pxvv6+mLfvn2W3myLWrZsGW7cuIFJkyaZar6+vhg9ejSqVKmCxMRE/Pnnn/j+++9x+vRp7N69O9lf4vYmLCxMfC4AwM2bNy29SVZn5syZiI2NRZcuXZLVixYtioYNG6J8+fJ48uQJVq9ejcmTJyMoKAi//fZbFm1txnJzc0Pv3r1Nb2rHjx/HjBkzULt2bZw4cQJ+fn4A8MJ5JSueR5wPX4zzYXKcD1+M86F1z4cv2x55s2Xt0UIZ5/Lly5qrq6vWrFkzTdM07eeff9YAaIcPH05x2bfeekvz9PS08BZazoULFzQPDw+tVq1aWnx8vPKyU6ZM0QBoK1assNDWZY3AwECtRYsWKer//fefBkD75ptvLL9RGSQhISHVxyImJibqXseePXu07Nmza507d07Vbfbv318DoB08eDAj70qGyIjHQ9M0bd++fZrBYNAGDhxoqk2aNEkDoN2+fTvF5evWratVrFgxM+5SmnE+/B/OhylxPuR8aKvzofGY/JiYGLP/8Zh8G1SsWDG0a9cOu3btQkJCAlxdXQE8iwl7XnR0tKlvb27duoVWrVrB09PTdNylyogRI+Dg4IAdO3ZYaAuzhqurq/hcMPZt1d69e+Hq6pqqf5cuXUox/uLFi3j99ddRrly5FEkjkg8++AAArPJ5k97Hw6hOnTqoWbNmsvtoK/MK58NnOB/q43zI+fBlmg9fZnb1eaSfnx9iY2Px5MkT08dHejm3YWFhdhl39fjxY7Ro0QKPHj3Cvn37UnUfXV1dkSdPHjx48MACW5h1fH19cePGjRR14/PDlp8PpUqVwqJFi1J12ec/Vg0JCUHTpk3h6emJzZs3I2fOnKm6HuPHtdb4vEnP4/E8Pz+/ZG98SecV42NgFBYWZjqm2RpwPuR8KOF8+Aznw+RsZT5M7xdoX6ZDfexqkX/lyhW4uLjA3d0d5cqVQ/bs2XHs2DF07tzZdJnY2FicOnUqWc0eREdHo02bNggKCsKOHTtQpkyZVI2LiIjAvXv3kC9fvkzewqxVqVIl7Nq1C+Hh4cm+bHb48GFT31b5+Pigd+/eaR53//59NG3aFDExMdi5c+cLJ/ikrly5AgBW+bwx9/HQc+XKlWT30fg8OXbsWLI3sJs3byI0NDRZWklW43zI+VDC+TAlzocvZsvz4Usrq48XMsedO3dS1E6dOqU5Ojpqbdu2NdWaN2+u+fr6auHh4abajz/+qAHQtmzZYpFttYT4+Hitbdu2Wvbs2bVNmzbpXiYqKirZ42A0atQoDYC2Zs2azN7MLHXo0KEUudDR0dFasWLFtJo1a2bhlmWNyMhIrUaNGlrOnDm1Y8eOiZd7/PixFh0dnayWmJiodenSRQOgHT9+PLM31SL05pRNmzZpALShQ4cmq5cqVUqrWLFisuO7x48frxkMBu38+fOZvq3P43yYHOfDF+N8mBznw+SseT4sUqSIVqRIES02Ntbsf8breBkYNE3TsuoPDHM1atQIrq6uqF27Nry9vXH+/HnMnz8fjo6OOHjwIEqXLg0AOHHiBGrXro0yZcpgwIABCA0Nxddff4169eph69atWXwvMs7w4cMxa9YstGnTRnePXI8ePRAcHIzKlSuja9euptO2b926FZs3b0bz5s2xadOmFDnB9qZz585Yu3YtRowYgWLFimHJkiU4cuQIdu7ciXr16mX15llU+/btsX79evTp0wcNGzZM1nN3d0f79u0BALt370bXrl3RtWtXFCtWDFFRUVi7di3+/vtvDBgwAPPmzcuCrc94xYsXR+XKlVGtWjV4enrixIkTWLhwIXx9fXH06FHkz5/fdNmNGzeibdu2aNiwId58802cPXsWc+bMQd++fTF//nyLbzvnw+Q4H6YO58P/4XyYnDXPh4GBgQCexZiaq0SJEgD+9wmMXcvqvzLMMWvWLK1GjRqal5eXlj17ds3X11fr0aOHdvny5RSX3bdvn1a7dm3NxcVFy5cvn/buu+/q7sGxZfXr19cAiP80TdMePnyo9ejRQytWrJjm5uamOTs7a2XLltWmTp2qxcbGZvE9sIyoqCht5MiRmo+Pj+bs7KxVr15d+/PPP7N6s7JE4cKFxedL4cKFTZe7cuWK1qlTJy0gIEBzcXHR3NzctKpVq2o//PCDMonB1owbN06rVKmS5unpqTk6Omr+/v7a4MGDtVu3bulefu3atVqlSpU0Z2dnrVChQtr48eOz7HXE+TA5zoepw/nwfzgfJmfN86FxL3xcXJzZ/7gnn4iIiIjIihj35D9/Yq60KF68OICXY0++fX8eSURERET0EuIin4iIiIjIzthVhCYRERER2beXKes+Pbgnn4iIiIjIznCRT0REREQkiImJwZgxY1CgQAG4urqiZs2a2L59e1Zv1gtxkU9ERERENsNgMJj9zxy9e/fGjBkz0L17d8yaNQvZsmVDy5YtsX///gy+ZxmLEZpEREREZPWMEZr//fef2ddRtGhRAKmP0Dxy5Ahq1qyJ6dOnY+TIkQCA6OholCtXDt7e3jhw4IDZ25LZuCefiIiIiGyGJffkr169GtmyZcOAAQNMNRcXF/Tt2xcHDx5ESEhIRt61DMVFPhERERGRjpMnT6JEiRLw8PBIVq9RowYA4NSpU1mwVanDCE0iIiIisgnXr183HbZj7niDwZDiOqTDd8LCwuDr65uibqzdvHnT7G3JbFzkExEREZHV8/PzS/d1+Pv7IywsLNWXj4qKgrOzc4q6i4uLqW+tuMgnIiIiIqu3Z88ei9+mq6srYmJiUtSjo6NNfWvFY/KJiIiIiHT4+vrq7vk31goUKGDpTUo1LvKJiIiIiHRUqlQJQUFBCA8PT1Y/fPiwqW+tuMgnIiIiItLRsWNHJCQkYP78+aZaTEwMFi1ahJo1a2bI9wQyC4/JJyIiIiLSUbNmTXTq1Aljx47FnTt3UKxYMSxZsgTBwcH46aefsnrzlHjGWyIiIiIiQXR0NCZMmIBffvkFDx8+RIUKFfDZZ5+hWbNmWb1pSlzkExERERHZGR6TT0RERERkZ7jIJyIiIiKyM1zkExERERHZGS7yiYiIiIjsDBf5RERERER2hot8IiIiIiI7w0U+EREREZGd4SKfiIiIiMjOcJFPRERERGRnuMgnIiIiIrIzXOQTEREREdkZLvKJiIiIiOwMF/lERERERHbm/wCbSUqdncJu5gAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pol_chisq_image = ((q_image - q_pred)**2 + (u_image - u_pred)**2) / (2 * i_image)\n", "pol_chisq_image_uncorr = ((q_image)**2 + (u_image)**2) / (2 * i_image)\n", "\n", "fig, axs = plt.subplots(ncols=2, figsize=(9,4))\n", "axs[0].set_title(\"Before correction\")\n", "axs[0].pcolormesh(source.pixel_centers, source.pixel_centers, pol_chisq_image_uncorr, vmin=0, vmax=8, cmap=\"Greys\")\n", "axs[1].set_title(\"After correction\")\n", "c = axs[1].pcolormesh(source.pixel_centers, source.pixel_centers, pol_chisq_image, vmin=0, vmax=8, cmap=\"Greys\")\n", "cbar = plt.colorbar(c, ax=axs)\n", "cbar.set_label(\"Local $\\\\chi^2$\")\n", "\n", "for ax in axs:\n", " ax.set_aspect(\"equal\")\n", " ax.set_xlim(source.pixel_centers[-1], source.pixel_centers[0])\n", " ax.set_ylim(source.pixel_centers[0], source.pixel_centers[-1])" ] } ], "metadata": { "kernelspec": { "display_name": "base", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.2" } }, "nbformat": 4, "nbformat_minor": 2 }