{ "cells": [ { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "# Diffusion coefficient from a VASP file\n", "\n", "[Previously](./vasp_msd.html), we looked at obtaining accurate estimates for the mean-squared displacement with `kinisi`. \n", "Here, we show that the same `DiffusionAnalyzer` can be used to evaluate the diffusion coefficient, using the `kinisi` [methodology](./methodology.html)." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import scipp as sc\n", "from pymatgen.io.vasp import Xdatcar\n", "from kinisi.analyze import DiffusionAnalyzer\n", "rng = np.random.RandomState(42)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As wil the [previous example](./vasp_msd.html), `params` dictionary will describe the details about the simulation." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "params = {'specie': 'Li',\n", " 'time_step': 2.0 * sc.Unit('fs'),\n", " 'step_skip': 50 * sc.Unit('dimensionless'),\n", " 'progress': False\n", " }" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this example, we will add an additional key-value pair to the dictionary. \n", "This argument means that the diffusion coefficient will only be calculated in the *xy* plane of the simulation box. " ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "params['dimension']= 'xy'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As with the previous example, we now use the `from_xdatcar` class method to construct the `DiffusionAnalyzer` object. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "xd = Xdatcar('./example_XDATCAR.gz')\n", "diff = DiffusionAnalyzer.from_xdatcar(xd, **params)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the above cells, we parse and determine the uncertainty on the mean-squared displacement as a function of the timestep. \n", "We should visualise this, to check that we are observing diffusion in our material and to determine the timescale at which this diffusion begins. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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Gzow2yq+1rCiLBjYztT1AVhGoAICbjUUZMse+UWAeH/s4lFceLCd+eVjmHq6Frh8AcAN/nE8wymsdFm6b16+JtPv6N7EyuntwNwQqAODiq8qq5e7XHjhv1B+pUlRW7btdL1nQX6yI4ASZRdcPALigZXvOGGUVpDjMNJbP/lHLnEYBOYCMCgC4iOs3k43yewv2GuXODcOkW5PS8oTF9uNxRAYF94pABQBcZNrxU19vNMoh+fPIxcSbuvz+k2n3TLMKghM4A4EKAFjUzeQU+XfUCaOeGpgoi15tJs1GrRErITBBTiBQAQCLZlGeHvebHLmQaNTfa1tVPvnld13287XGNGOCE+Q0BtMCgIX89od9JVkVpBQKyGPUn64balKr0g9O1KHKQE7iFQYAJk87TkmxGeVBs+wryfZpXlZ6Ny8rjUasEjORNYGZCFQAwERL95yRb9f+YdTz5fGW6zdTdPmNxyqZ2DLAGghUACCX2Wy2dJe7V9RePI99vl7MRhYFVsEYFQDI5X16+nwfZZSD8vlK/4fKG/VC+fM69XcBro6MCgDkgouJN4xydGycUV4xuIUE5ssj49fYu3/MQhYFVkSgAgC54LkJm4zyEzVLyJLdt5fAV0GKWQhM4Aro+gGAHOrqOXD2ilG+ct3+mB+3r+6Uxwc8ARkVAMgB/1q+X6ZvOmbUBz9WUcasOChmI4sCV0OgAsBj5eQKs1M2Hk1Tf6FRuCmBCoEJXB1dPwDgJG/N3WWUQwvmk/Fd6praHsAdkFEB4FGcnUW5lXJ7cTZl9f7zRvnngc1MW16eLAo8NqNy7do12bBhg8TExPzlvuvXr8v333/vzLYBgOV1n7zNKNcqFWyUcztIYf8diKcHKgcOHJCqVatKixYtpGbNmvLggw/K6dOnjfvj4uKkV69eOdVOALDMbJ74azeN8oGzCUb5ux71nPL4AO4hUHnnnXekRo0acu7cOdm/f78EBgZKs2bN5Pjx45l9CABweUt2n5Ynv9qQZk2UVN5eXrnWDjIo8BSZfnX/9ttv8uuvv0qRIkX0sWjRIunfv780b95cVq9eLfnz58/ZlgKABbzpMGA2dU2U1MXbchpjT+CJvLMyPsXX1x7XeHl5yYQJE6Rdu3a6G0h1DQGAO3b3fLf+iFHO6+stAx+2780DwCIZlSpVqkhkZKQep+Lo66+/1v8+9dRTzm8dAFjAxLWHjfKCAU2lTOH88vXq3NmbhywKPF2mMyrPPPOMzJo1K937VLDSuXPnNFuXA4CrZlFuJafImP/Ys8SFHXY0VkFKTmLsCXCPgUpERIQsWbIkw/vHjx8vKQ7rCQCAq3pxWqR8t8He3fNTv8amtgfwZKauTPvhhx/qsS6Oh+piAgAzRR67JPn9fIx6Tu9wTBYFyFiW3xEHDx6UihUrirNUr15dzyYyGuQwYBcAMrPCbMzHrbP9eMMX/26UKxUvIGOfryNPfGmfhuxMjDsBMi9LUUFUVJQeNHvy5EnnNcDXV0qUsK9DAABmWBh9yijP6tNY/PPaMyoAXCBQWbVqlTz33HPy5ZdfOrUBKkMTGhoq+fLlkyZNmsjIkSMlPDw8w/OTkpL0kSo+Pt6p7QHgOfv0RMzbbZRLFfKXE5eu6XJOBClkUYAcHKMyb948efLJJ3UQ0a1bN3GWRo0aybRp02TZsmV6TZYjR47oBeSuXLmS4c+oNgQHBxtHWFiY09oDwP2pGT2pVsScM8qzX25kUosAZDuj8vzzz+uBr3379hVnatOmjVGuVauWDlxKly4tc+bMkZdeeinD2UeDBw9Ok1EhWAGQGcv2nJGvVh0y6tVDg2TvqdtZ2Xx5yKIALptRKV++vPznP//Rq9PmpIIFC0qlSpXk0CH7B8md/Pz8JCgoKM0BwD05e4XZwXN2ypELiUZ9Ss/62X5MABYIVDZs2CBXr17Vi77dvGnfNdTZEhIS5I8//pCSJUvm2O8A4FlUcJIqIK+P9H/Ivvy9j7dzNxFkmjFgUqCiNiFUGw/euHFDOnbs6LRf/uabb8ratWvl6NGjetNDFQj5+PjoVW4B4F5dv5lslNcduGCU//NGCxn4SAWn/i6CE8AiC74VKFBAli5dKt7ezlsj7sSJEzooqVy5sg6AChcuLJs3b5aiRYs67XcA8Lzunm6TtxrlJuVCjHKIw1L4AFxDlsJ/NT5k7ty5Tvvls2fPdtpjAfBsjrN5jly4apS/7FxHGny6yqm/i0GyQO7JcnrkbhmV8+fPZ7c9ADxQdrMoRy8kSleHLErLqsWMstqaA4DrynY/TnJysixcuFDat28vpUqVck6rACALnp3wm+w6EWfURz1bw6mPzzgUwAUDld27d+v1TNSqsj179pTAwEC6cgDk2jiUc/HXjfL1mynS2GEsClkUwH3c9auBWqperRwbEhIiHTp0kEuXLsmMGTNkypQpsnfvXmnVqpX8+eefEh0dLTVqOPcbDADcTadvtxjliCeqSJeG4VLjw/847fEZhwK4QKDSpUsXvWlgsWLFZMSIEbJv3z6pU6eOXjW2U6dOepZOnjx5nDoTCIB7csY+PZev3jDK8dftmZhujUs7oYUAXC5Q2bRpk/zyyy96ZdpChQrJO++8I0OHDtXdPACQmzYeuiDvzt9j1Ps0LyuT1h9x2uOTQQGs6a6pkN69e+usyuOPP673+VHrqJQoUULv/bN48WK5dSv7S1oDcF/OXAK/z/dRcu6Kfef0Vx4s54QWAnDpjMpHH32kF2RTi72lzuhR41HUuJVevXrpekpKisTExEi1atVyp8UAPMaek/aZPEqXRuEyY8txpz0+WRTA+v52cEmVKlXSTDtWY1TGjh0rp06dkokTJ8oTTzyhgxl1zqBBg3K6vQA8aBPBl6ZFGeXvuteTd9tWzfZjAnAt97wggBpE+9xzz+njzJkz8v333+tMCwBkx/4zV4xyss1mlJtWKOKUxyeLArgWp0zXUeNW3n77bd0FBMCzODuL0n3yNqM80skLtwFwPSyxCMBUNptNVu47l24W5bFqxSVinn2mz70ggwK4NgIVAPe8HkrMx62z/Xidvt0su0/GG/V/daglb87dla3HJDgB3AcrtQHIddGxl42yClL88/oY9YcqFzWpVQBcOlBRy+ZfuHAhZ1sDwCP0nm6fzdOtcbgsf715th+TjQMBDw9UfvjhBz0FuWnTpjJ69Gj5/fffc7ZlANxqwOywhXuNso/DpoERT1SVIgX8nNJOAB4cqKxatUpOnz4t/fv3l6ioKGnUqJFUrFhRhgwZIuvWrdMLvwGAo8Qke1CzZPcZozy3X+NsPzYZFMAzZGmMitrvp2vXrjJnzhzdDfTVV1/JtWvX9DL7auPC7t27y08//SSJiYk512IALpFF+SnqhDz+xXqjXjesoFEODwlwWjsBuLd7HkybN29evQfQ+PHjJTY2VpYtWyZlypSR4cOHy5gxY5zbSgAuR3X1/Jlg3+342+73Z/sxyaIAnsdp7/T69evr4+OPP5abN28662EBuJCIebuNcpC/r/R/sLyMWrZf170cxqUAgKnTk9Xy+gA8o6vnVrJ9fNqKGPvCbcteay7dm5ZxejsBeBZypwDu2c7Yy/LRIvvWGTXvCzIWbysYkDfbj8/CbQBY8A3APXvhuy2yz2ETwck965vaHgDuh4wK4MEcl8OPfK9lpn5mw0H7wo9qW55n6t4n83ec1HVvJ4xDIYsCIFuBysGDB2XhwoVy9OhRPTiubNmy8vTTT0u5cuWy+lAAXNDrP+40yv/3UkOpV7qQEagAgKmBysiRI2XYsGF6cTe1bora9fT8+fMydOhQGTFihLz55ptObyAA8zcU3HL4olFWOZPU/Y1VkOIMZFEAZHuMyurVq+W9996Td999Vy/2plapPXPmjBGoqEOtUAvA/QyYucMoT+peL9uPx3ooADIr058QEydOlN69e8uHH36Y5vaQkBC9dooKWiZMmCAtWrTI9C8HYF2RR+1ZFEd1wu0rzAKAZTIqW7dulW7dumV4v7pv8+bNzmoXABPXRxm9dJ/0mLrNqI/vUjfb7SCLAuBeZPrT4uzZs3qJ/IyoQbUqqwLA9U3fdCxNvWHZENPaAsCzZTqjcv36db2/z91Wo71xw76vBwDXyqLM2HLcKBcL9JOJXdmbB4D5svTJ8d1330mBAgXSve/KFfuiT/dq1KhREhERIa+99pqMHTs2248HIPM+X3HQKC8c2EyC/bO+FQazdwCYFqiEh4fLpEmT/vace7Vt2zb55ptvpFatWvf8GICnutdpx+sPnjfKeXy85Gby7YnH9xKkAICpgYpa4C2nJCQkSJcuXXQg9Mknn9z13KSkJH2kio+/va8IgKx5c+5OWbLbPq5sSs/60m2yfQBtZpFFAeD2e/0MGDBA2rZtK48++mimFp0LDg42jrCwsFxpI+AO41BS1Jr3/6WCFG+HFe+rlgzKiWYCQO4EKps2bZLFixenue3777/Xs33UKrUvv/xymkxHZs2ePVu2b9+uA5DMUGNY4uLijCM2NjbLvxPwVH2mRxnlaiWD5MdXGmf5MRggC8CSgYpa1G3v3r1Gfffu3fLSSy/pLIhalXbRokWZDjZSqSBDDZydMWOG5MuXL1M/4+fnJ0FBQWkOABm7fjPZKO88EWeUZ7/cSKqHBpvUKgDInEx/HYqOjpbhw4enyYQ0atTIGGCrumA++OCDv6xcezdRUVFy7tw5uf9++zTI5ORkvRT/119/rTM0Pj4+mX48wN3dy27Hz3+zxSi3qFRE1h24vfuxr0/me34ZhwLALJn+pLp06ZIUL17cqK9du1batGlj1Bs0aJDlbpiWLVvqzIwKglKP+vXr64G1qkyQAtybCwn2btiTl68Z5TEda5vUIgDI4YyKClKOHDmiMydqYTc1ruSjjz5Ks46KWvQtKwIDA6VGjRppbsufP78ULlz4L7cDnuheph3PiYyVMf85YNQ7NwyTWVuzPpaLLAoAl8qoPPHEE3osyvr16/WA1oCAAGnevLlx/65du6R8+fI51U4AmfThzzESf90+C2hIq0qmtgcAciWjosanPPvss/Lggw/q1WmnT5+eZkn9KVOmSKtWrSS71qxZk+3HADzNuFWHjHJAXh95rWVFGbl0X5YegwwKAJcOVIoUKaIHuaopwSpQuXP8yNy5czNcXh9Azg6YnfqbfRPBRa82k5LB/lkOVADALRZ8U4uspTfINSQk5K6bFgJwrpFL7IFI8UA/o6yCFADwuIzKiy++mKnzVBcQgJz37+0njfKcvo3lwX+uzfJj0N0DwG0ClWnTpknp0qWlbt26YnNYhhtA7szsuZmcIhPXHk6TRTl75fY05Px+mXsrE5gAcNtApV+/fjJr1iw9RblXr17StWtX3d0DIHd0mbRF9pyyb8I56+VG8sj/rjO1TQBgmTEq48aNk9OnT8vbb7+tl8tX66l07NhRli9fToYFyKENBR3fWypICcpn/24R5J+5dYvYmweAxwymVfvsdO7cWVasWCExMTFSvXp16d+/v5QpU0YSEhJyrpWAh3p1VrRRblq+sCwc2MzU9gBAbrvnr1fe3t7i5eWlv/Gp/XkAON/mwxeN8rfd6om3t1emfo6xKAA8MqOiNglU41Qee+wxqVSpkt6nR20eePz4cdZQAZzQ3RN/7aa8/dMuo161ZKBRzmyQAgAemVFRXTxqx2Q1NkVNVVYBi1oEDoDzPD3uNzkTf92oT+1ZXxqPXP23P0cGBYB4eqAyceJECQ8Pl3Llyumdk9WRnnnz5jmzfYDbTzu+ftPedaqClPCQADl+8aqu+/pkeU1GAPDMQKV79+56TAoA5+o+eZtRfr5BmLzVupLU/2Tl3/4cWRQAniBLC74BcI7kFPu048MXEo3yB+2qmdQiALAmFlUATNhQsM/3UUb54SpFZfW+85l6fLIoADwNHeBALnFcvG3XiTij/NlzNU1qEQBYHxkVIBeyKBcSkuSDhXuN+v3hBWX78cu6fLexX2RQAHg6MipALlDTjlfvt3fvTOx2v6ntAQBXQUYFyCGJSfZF3S4m3pDKxQvI/rO3t5rwJosCAJlCRgXIIS9M2mKUez9QVn58pYmp7QEAV0RGBXDiQm63UlKM8snL9hVmB7eqlIstBAD3QaACONGAGTuMcrvaJWXRztN/+zN09QBAxuj6AZy0oaASdez2TB6FxdsAIPvIqADZNG/7SaNctkiAHLlwe5+euyGLAgCZQ0YFyIYvVx6U9xbsMerTejUwtT0A4G7IqADZ2Pl44trDaer5/TJ+S5FFAYCsI6MCZNH5K0lG2cfbS4a3r25qewDAnZFRAbKoy3f29VEmdLlfHqhYRN53WB4/FRkUAMg+MipAJmb2pKTYNxS8mHjTKKsgBQCQc8ioAH8j7tpNifj3bqPerlZJWbQr/fVRyKIAgHORUQH+RoeJm2TNAfuGgsPaVTW1PQDgSUwNVCZMmCC1atWSoKAgfTRp0kSWLl1qZpPgYTKzkNuJS9ekVCF/o+51lw0FAQBuFKiUKlVKRo0aJVFRURIZGSmPPPKItG/fXvbu/evARCA3ffrL70b54cpFZW7fjDcUTO3uUYcqAwCcx9RP1Xbt2qWpf/rppzrLsnnzZqlenSmfMM/8HaeM8led64q3N1kUADCDZb7+JScny9y5cyUxMVF3AWUkKSlJH6ni4+NzqYVw94XcIo9eNMrB/r4Sd+12V9CdQQoDZgHAgwbT7t69WwoUKCB+fn7St29fmT9/vlSrlvFmbiNHjpTg4GDjCAsLy9X2wn0NmBFtlL9/saGpbQEAWCRQqVy5skRHR8uWLVukX79+0qNHD4mJicnw/IiICImLizOO2NjYXG0v3GvAbMJ1ez3ZZl8r5T6HwbMAAA/u+smbN69UqFBBl+vVqyfbtm2TL774Qr755pt0z1eZF3UA2bXj+CV5x2F9lHceryyjl+1P91y6ewDAQzMqd0pJSUkzBgXIKd0mb9VTj1N1qF/K1PYAACyWUVHdOG3atJHw8HC5cuWKzJw5U9asWSPLl98e7Ag4Y9Bs5HstjdtPXLxqlNWq+O3rhMrCaPsMn1RkUADAGkwNVM6dOyfdu3eX06dP64GxavE3FaQ89thjZjYLbuyF77Ya5f/tUEva1CyZbqACALAGUwOVyZMnm/nr4SHTjtVePfbzko2yClIAANZm+mBaIKd1/naLUR74cHn5evUf6Z5Hdw8AWI/lBtMCznDjVopRPnfFPji7Z7MyJrUIAHAvyKjA7QbMqmnH7y+07xf1TN3QNEviOyKLAgDWRkYFbqfr5K1y+HyiUX+3bVVT2wMAuHdkVOAWA2b3nblilNUCs0/XDZUF6WRRyKAAgGshowK30GvqNqM8qXs9GfFMTVPbAwBwDgIVuKwr1+3Tjm8m2/fpaVahiEktAgA4G10/cMkBs7tPxsmQOTuN+huPVZTPVxxM9zHo7gEA10VGBS6py3db0uzT06VRuKntAQDkDDIqcBmOK8zeSrbJY9WKyYqYc+meSxYFANwDGRVYsrunzNBf9KHKqbpMsu/T827bKjL2+TomtRAAkFvIqMDSUtRc4/86E3/dKHdpVDrNeWRQAMA9kVGBZTMoyhs/2gfMqq4eAIBnIaMCS9t46E+jPOKZGrIiZpVRJ4sCAO6PjAosJTnFJhPW2Hc3Dg8JMMpeXl4mtQoAYBYyKrDU+ig9p26TqGOXjPoPvRtIi8/W6jIZFADwPGRUYCkqSAnI62PUVXACAPBcBCow3ae//G6Ua94XLPP6NzW1PQAA6+DrKkzv7pnvsMvxD70bSh4fe/xMdw8AeDYyKjDF95uOGeUiBfIaZccgBQAA/irAlPVRvlx5yCjPfrlRmvtSsyjqYIwKAHg2AhXkCpvNJj9H27t4/PPYB8wWDLBnVAAAcMTXVeSKwXN2yvK9Z436rD4N5enxm3SZcSgAgIyQUUGudPeoIMXX275gWymHhdwAAMgIgQpyzGfL9hvlskXyy8w+aceiAADwd+j6gdOmHMd83DrNfXMiTxjln/o2Ef87FnKjuwcA8HfIqMBpbiWnyMS1f6Q77dgxSAEAILPIqMBpekzZJjtiLxv12S83lkfHrDPqZFEAAFlFRgXZGjCbmHTTuF0FKQX87LFvwYA8JrUQAOAuCFSQLW//tNso1y9dSOYPsO/Tw8JtAIDs4q8HsrVPz+r9543y1F4NxMdhCjIAAC6dURk5cqQ0aNBAAgMDpVixYvL000/L/v32Ka2wpn8ud5x2bF8PRQUpZFEAAG4TqKxdu1YGDBggmzdvlhUrVsjNmzelVatWkpiYaGaz8Dd+3Gafdvx/LzU0tS0AAPdm6lfeZcuWpalPmzZNZ1aioqKkRYsWprULabt6ooc9Jt+tP2zcV7hAXvkz4YYuh+T3YyYPAMAzBtPGxcXpf0NCQjI8JykpSeLj49McyFnPf7NJvl5tXx9lNivMAgByiWUGEaSkpMjrr78uzZo1kxo1atx1XMtHH32Uq23zxCzKxqEPGbfvP5sghQLyyKWrt6ci31cogCwKAMCzMipqrMqePXtk9uzZdz0vIiJCZ15Sj9jY2Fxroyd5YdJWo/xEzRKy6NUHTG0PAMAzWSKjMnDgQFm8eLGsW7dOSpUqdddz/fz89AHnZ1HWv23Pohz786pR/leH2qa0DQAAUwMVm80mr776qsyfP1/WrFkjZcuWNbM5Hq/Tt5uN8lO1S8rPO08bdZa/BwB4XNeP6u754YcfZObMmXotlTNnzujj2rVrZjbLoyQm3TLKJy9fN8rD2lUzqUUAANh52VRawyReXumvYjp16lTp2bNnph5DzfoJDg7W41WCgoKc3EL37uqZ27exDJmzS45fvN3N06F+KZkbeXuNlJiPW7NgGwAgx2T277fpXT8wT+dJW+RWsv3/wTuPVzYCFQAArICvzB7mQkKSUVZBSsuqxWTl7+d0nXEoAACrIVDxsO4etR5KqnfbVpEXGoZL9Q/+Y2LrAADIGIGKhw2YTV20TenSqDRZFACApVlmwTc4N4NSZugv+th46Lw8O/43475uTcJNbRsAAFlBRsXNdZu8VVIcxixHtKkqw9vXNLNJAABkGhkVN8yiRB27aNyugpT2dUJNbRsAAPeKjIob6jkl0iiP6Vhbnr2/lHzRqa6pbQIA4F6QUXETO2MvG+Vkh/VpHq9RwqQWAQCQfWRU3GTaseMav//8R01566fdprULAABnIVBxYZFH7WNRHNf4bVsrVDrUZ3YPAMD1Eai4aAblhYZhMnNrrHHf2E615fXZO01sHQAAzkeg4qIcgxSlVbUScnRUKdPaAwBATiBQcaUsSqMw4/b7CvrLR+2rS+/p9hk+AAC4GwIVFzJziz2LsmBAUykamI/l7wEAbo3pyRaWnGKT79YfNuqF8+c1yvn9iDEBAO6Pv3YW7+5xtHBgMylVKMCUNgEAYAYyKhZjs9lk/o6TRj0gr49RDnHIqAAA4AnIqFjIxcQbEjFvlyzfezbNWJRKxYNMbRcAAGYhULFgV4+vj5fcSr69hBtdPQAAT0agYoEg5eNFMUa9XNH88mWnulLjvmBT2wUAgBUQqFhswOxPfZtISH4/U9oEAIDVEKiY4FZyioxffcioFwv0k//tWFuaVyxqarsAALAaAhUTMii1SwXLzhNxaQbMhhZkLAoAAHdienIuTjtOpYKUAg4LthUMYNoxAADpIaOSC/5MSJK3ftpl1BuUKSSfP1+HGT0AAPwNAhUTBsxO6dlAAvPlMaVNAAC4EgKVHBww+/mKA0a9QrEC8kWnOlI9lGnHAABkFoFKDjgXf11enbVDthy5aNw255XGTDsGACCLCFScbPW+s9JrWqSxT8/o52pJu9qhZjcLAACXRKDiJCkpNhm/5pCMcejuUYu3VaOrBwCAe0agkgMDZjvUKyUft68h/g47HwMAABdcR2XdunXSrl07CQ0NFS8vL1mwYIG4kujjl42yn6+3fPaPWvLPDrUJUgAAcIdAJTExUWrXri3jxo0TV1vAbfKGI9J9ylbjttkvN5aO9cNMbRcAAO7E9K6fNm3a6COzkpKS9JEqPj5ectvZ+GvSaMQqo962VkkZ9WxN1kYBAMDdMipZNXLkSAkODjaOsLDczWDsORkn/5i4yai/27aKfN25LkEKAAA5wOUClYiICImLizOO2NjYXOvqmbnluDw74TeJvXhN7ivoLwsHNJM+zcvrsTUAAMANu36yys/PTx+5KTHplgydt0sW7Tyt6w9VKipjO9VhM0EAAHKYywUquW3fmXjpP2O7HD6faNz29Qt1pQBdPQAA5DgClbt09cyJjJVhC/dK0q0UKRGUT756oa40KBNidtMAAPAYpgcqCQkJcujQIaN+5MgRiY6OlpCQEAkPDzelTXd29TxQoYh82bmuhOSnqwcAAI8KVCIjI+Xhhx826oMHD9b/9ujRQ6ZNm5br7dl/5or0nxElf5xPFB9vLxnSqpL0bVFevL0ZMAsAgMcFKg899JDuZrGCuZGx8tZPu3S5eJCffNX5fmlYlq4eAAA8NlCxglvJKTJ62T6ZtP6Icdu/+zWVUoUCTG0XAACezuMDlctXb8jAmTtkw6ELut7/ofIypFVl3e0DAADM5dGBysFzV+SxMet02T+Pj/yrQ229HD4AALAGjw1UYk7FS8+ptzcULBmcT6b0bCBVSwaZ3SwAAODpgcqmP/6Ul7+PlCtJt6Ry8UCZ9mIDKRnsb3azAACApwcq6w6cl+5TbmdS6pcuJJN7NpBgf1aZBQDAijwqUFE7Hw+YsV2XH65cVCZ0rSf58viY3SwAAOAuuyffq8PnE6THlK26u0etjUKQAgCA9XlEoHL+SpJ0m7xV/ky8ITXuC5LvetQnSAEAwAV4RKDyP/N3ycnL13R5Ytd6EsTOxwAAuAS3D1SW7D4tK2LOia+3lywZ1JzVZgEAcCFuHahcSrwhwxbu0eV+D5WXaqGskwIAgCtx60Bl+OIYuZBwQyoWKyADH6lgdnMAAEAWuW2gsnr/OZm346R4eYmM/kct8fNl8CwAAK7GLQOVhOs3pdfUbbrcvXFpuT+8kNlNAgAA98AtA5VNhy/qfwP9fGVI68pmNwcAANwjtwtUbDabjF9zSJe7NC7NVGQAAFyY2wUqW45clB3HL0teX2958YEyZjcHAABkg9sFKuPX/KH/7VCvlBQLzGd2cwAAQDZ4u9umg2p3ZG8vkZdblDO7OQAAIJvcKlCZsPZ2NuXJWqFSunB+s5sDAACyyW0ClaN/JsrS3ad1ue+D5c1uDgAAcAJfcRNqdo9aJv/EpWsslQ8AgJtwm0AlJH9eeat1FbObAQAAnMhtun4AAID7IVABAACWRaACAAAsi0AFAABYFoEKAACwLAIVAABgWZYIVMaNGydlypSRfPnySaNGjWTr1q1mNwkAAFiA6YHKjz/+KIMHD5YPPvhAtm/fLrVr15bWrVvLuXPnzG4aAADw9EBlzJgx0qdPH+nVq5dUq1ZNJk6cKAEBATJlyhSzmwYAADx5ZdobN25IVFSUREREGLd5e3vLo48+Kps2bUr3Z5KSkvSRKi4uTv8bHx+fCy0GAADOkPp322azWTdQuXDhgiQnJ0vx4sXT3K7q+/btS/dnRo4cKR999NFfbg8LC8uxdgIAgJxx5coVCQ4Odp+9flT2RY1pSXX58mUpXbq0HD9+/K5P1FOiUxWwxcbGSlAQGzNyPey4FmlxPey4FmlxPXLvWqhMigpSQkND73qeqYFKkSJFxMfHR86ePZvmdlUvUaJEuj/j5+enjzupIMXTX1Sp1HXgWthxPey4FmlxPey4FmlxPXLnWmQmwWDqYNq8efNKvXr1ZOXKlcZtKSkput6kSRMzmwYAACzA9K4f1Y3To0cPqV+/vjRs2FDGjh0riYmJehYQAADwbKYHKs8//7ycP39ehg0bJmfOnJE6derIsmXL/jLANiOqG0itwZJed5Cn4VqkxfWw41qkxfWw41qkxfWw3rXwsv3dvCAAAABPXfANAAAgIwQqAADAsghUAACAZRGoAAAAy3LpQGXcuHFSpkwZyZcvnzRq1Ei2bt0qrk5tEdCgQQMJDAyUYsWKydNPPy379+9Pc87169dlwIABUrhwYSlQoIA899xzf1k0T63U27ZtW73Bo3qct956S27dupXmnDVr1sj999+vR3RXqFBBpk2bJlY2atQo8fLyktdff91jr8XJkyela9eu+vn6+/tLzZo1JTIy0rhfjY1XM+hKliyp71f7Zh08eDDNY1y8eFG6dOmiF3AqWLCgvPTSS5KQkJDmnF27dknz5s31e0utTPnZZ5+JlaitN95//30pW7asfp7ly5eX4cOHp9kzxJ2vxbp166Rdu3Z6RU/1nliwYEGa+3Pzuc+dO1eqVKmiz1GvxyVLlohVrsXNmzflnXfe0e3Knz+/Pqd79+5y6tQpt7wWmXltOOrbt68+Ry0LYunrYXNRs2fPtuXNm9c2ZcoU2969e219+vSxFSxY0Hb27FmbK2vdurVt6tSptj179tiio6NtTzzxhC08PNyWkJBgnNO3b19bWFiYbeXKlbbIyEhb48aNbU2bNjXuv3Xrlq1GjRq2Rx991LZjxw7bkiVLbEWKFLFFREQY5xw+fNgWEBBgGzx4sC0mJsb21Vdf2Xx8fGzLli2zWdHWrVttZcqUsdWqVcv22muveeS1uHjxoq106dK2nj172rZs2aLbvXz5ctuhQ4eMc0aNGmULDg62LViwwLZz507bU089ZStbtqzt2rVrxjmPP/64rXbt2rbNmzfb1q9fb6tQoYKtc+fOxv1xcXG24sWL27p06aJfh7NmzbL5+/vbvvnmG5tVfPrpp7bChQvbFi9ebDty5Iht7ty5tgIFCti++OILj7gW6nX87rvv2ubNm6ciM9v8+fPT3J9bz33jxo36vfLZZ5/p9857771ny5Mnj2337t2WuBaXL1/W7/0ff/zRtm/fPtumTZtsDRs2tNWrVy/NY7jLtcjMayOVul8959DQUNvnn39u6evhsoGKerENGDDAqCcnJ+sLPnLkSJs7OXfunH6xrV271njjqf/Z6oM51e+//67PUW/C1Beqt7e37cyZM8Y5EyZMsAUFBdmSkpJ0/e2337ZVr149ze96/vnndaBkNVeuXLFVrFjRtmLFCtuDDz5oBCqedi3eeecd2wMPPJDh/SkpKbYSJUrY/vnPfxq3qWvk5+enP0gU9YGhrs+2bduMc5YuXWrz8vKynTx5UtfHjx9vK1SokHF9Un935cqVbVbRtm1b24svvpjmtmeffVZ/cHratbjzj1FuPveOHTvq/xeOGjVqZHvllVdsZrjbH2bHLz3qvGPHjrn1tbjb9Thx4oTtvvvu00GG+vLjGKhY8Xq4ZNfPjRs3JCoqSqczU3l7e+v6pk2bxJ3ExcXpf0NCQvS/6nmrdKbjc1eptfDwcOO5q39Vms1x0bzWrVvrDab27t1rnOP4GKnnWPH6qa4d1XVzZ3s97Vr8/PPPegXnDh066C6sunXryqRJk4z7jxw5ohdNdHwuah8N1S3qeD1UKlc9Tip1vnr/bNmyxTinRYsWeosLx+uhuiAvXbokVtC0aVO91caBAwd0fefOnbJhwwZp06aNx12LO+Xmc3eV986dn6mqu0M9f0+8FikpKdKtWzfdBV69evW/3G/F6+GSgcqFCxd0H/Wdq9equnqDugv1glLjMZo1ayY1atTQt6nnp14cqW+y9J67+je9a5N6393OUX/Ar127JlYxe/Zs2b59ux67cydPuxaHDx+WCRMmSMWKFWX58uXSr18/GTRokEyfPj3N87nb+0L9q4IcR76+vjoQzso1M9vQoUOlU6dOOjDNkyePDtrUe0X1q3vatbhTbj73jM6x6rVRY9rUmJXOnTsbm+x52rUYPXq0fn7qsyM9Vrwepi+hj7tnEvbs2aO/KXoitbX4a6+9JitWrNCDsTydClzVt5wRI0bouvrjrF4fEydO1PtleZI5c+bIjBkzZObMmfpbYXR0tA5U1ABCT7sWyByVfe3YsaMeaKwCfk8UFRUlX3zxhf7yp7JKrsIlMypFihQRHx+fv8zuUPUSJUqIOxg4cKAsXrxYVq9eLaVKlTJuV89PdX1dvnw5w+eu/k3v2qTed7dz1LcMNUvAKm+qc+fO6dk4KqJXx9q1a+XLL7/UZRWde8q1UNQMjmrVqqW5rWrVqnpWk+Pzudv7Qv2rrqkjNQNKjfLPyjUzm0pbp2ZVVNeeSmW/8cYbRubNk67FnXLzuWd0jtWuTWqQcuzYMf3FJzWb4mnXYv369fq5qu7x1M9UdU2GDBmiZ9Ba9Xq4ZKCi0v316tXTfdSO3zZVvUmTJuLKVLSvgpT58+fLqlWr9PRLR+p5q1S343NX/YLqj1Xqc1f/7t69O82LLfXNmfqHTp3j+Bip51jp+rVs2VI/D/VtOfVQGQWV3k8te8q1UFQX4J1T1dUYjdKlS+uyeq2oDwHH56K6r1S/suP1UIGdCgJTqdeZev+oMQyp56gpjurD3fF6VK5cWQoVKiRWcPXqVd1n7kh9eVHPw9OuxZ1y87m7wnsnNUhR07N//fVXPbXfkSddi27duulpxY6fqSoLqQJ/1Z1s2ethc+HpyWoU+7Rp0/Qo5ZdffllPT3ac3eGK+vXrp6cVrlmzxnb69GnjuHr1apopuWrK8qpVq/SU3CZNmujjzim5rVq10lOc1TTbokWLpjsl96233tIzZcaNG2fJKbl3cpz142nXQs1W8PX11VNzDx48aJsxY4Zu9w8//JBmWqp6HyxcuNC2a9cuW/v27dOdllq3bl09xXnDhg16RpXj1EM1Q0RNPezWrZueFaDea+r3mD0l11GPHj30rIXU6clqqqWadq5mcHnCtVAz4dR0e3Woj/ExY8bocupMltx67moKqnpN/utf/9LvnQ8++CDXp+Te7VrcuHFDT80uVaqUfv87fqY6zlhxl2uRmdfGne6c9WPF6+GygYqi1rtQf6TUeipqurKa8+3q1AsrvUOtrZJKfdj0799fTw9TL45nnnlGv/EcHT161NamTRs9t119gA8ZMsR28+bNNOesXr3aVqdOHX39ypUrl+Z3uEqg4mnXYtGiRTrwUkF6lSpVbN9++22a+9XU1Pfff19/iKhzWrZsadu/f3+ac/7880/9oaPWHVHTtHv16qU/3ByptTfUVGj1GCogUH/4rCQ+Pl6/DtT7P1++fPr/mVo7wvGPjztfC/V6Te9zQgVwuf3c58yZY6tUqZJ+76hp/r/88ovNKtdCBbEZfaaqn3O3a5GZ10ZmAhWrXQ8v9Z97TSMBAADkJJccowIAADwDgQoAALAsAhUAAGBZBCoAAMCyCFQAAIBlEagAAADLIlABAACWRaACAAAsi0AFgNP07NlTnn76abGqBQsWSIUKFfS+QGq3ZQDWx8q0ADLl77aF/+CDD/QOxuojpWDBgmIGtbt2165dJTY2Nt371Y7bvXr1kkGDBklgYKA+AFibr9kNAOAaTp8+bZR//PFHGTZsWJrdnAsUKKAPMy1cuFDatWuX7n0JCQl6F+3WrVvrHWMBuAa6fgBkSokSJYwjODhYZ1gcb1NByp1dPw899JC8+uqruptFbf+uMhqTJk2SxMREndlQGQ3VFbN06dI0v2vPnj3Spk0b/ZjqZ9T29BcuXPjbNv7888/y1FNP/eX2NWvWGNmTRx55RLdd3Xbs2DEd2Ki25c+fX6pXry5LlixxyvUC4BwEKgBy1PTp06VIkSKydetWHbT069dPOnToIE2bNpXt27dLq1atdCBy9epVff7ly5d1MFG3bl2JjIyUZcuWydmzZ6Vjx453/T179+7VGRP1s3dSvys1+/Pvf/9bZ4fUbQMGDJCkpCRZt26d7N69W0aPHm16VghAWnT9AMhRtWvXlvfee0+XIyIiZNSoUTpw6dOnj75NdSFNmDBBdu3aJY0bN5avv/5aBykjRowwHmPKlCkSFhYmBw4ckEqVKmXY7aO6dfLmzfuX+9RtxYoV0+WQkBCdAVKOHz8uzz33nNSsWVPXy5UrlwNXAEB2kFEBkKNq1apllNVsm8KFCxuBgaK6dhSVDVF27twpq1evNsa8qKNKlSr6vj/++CPD36MClfS6fe5GDar95JNPpFmzZnowsAqWAFgLgQqAHJUnT540dTU+xPG21NlEKSkpxqBXNW4kOjo6zXHw4EFp0aJFur9DdeXs2LFD2rZtm6W29e7dWw4fPqy7nlTXT/369eWrr766h2cJIKcQqACwlPvvv1+PNylTpoweaOt4qAGv6Vm0aJEec6K6dbJKdSn17dtX5s2bJ0OGDNGDfQFYB4EKAEtRA1wvXrwonTt3lm3btununuXLl+tZQsnJyVma7fN31Gwk9dhHjhzRA3tVl1PVqlWd8CwAOAuBCgBLUWucbNy4UQclakaQGs+iAgq1iJy3918/stRU55UrV95ToKJ+hwqMVHDy+OOP64G648ePd9IzAeAMrEwLwKWpLhs1qygmJsbspgDIAWRUALg0NStIrX8CwD2RUQEAAJZFRgUAAFgWgQoAALAsAhUAAGBZBCoAAMCyCFQAAIBlEagAAADLIlABAACWRaACAAAsi0AFAACIVf0/MtXqQhasNHkAAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.errorbar(diff.dt.values, diff.msd.values, np.sqrt(diff.msd.variances))\n", "ax.set_xlabel(f'Time / {diff.dt.unit}')\n", "ax.set_ylabel(f'MSD / {diff.msd.unit}')\n", "ax.set_xlim(0, None)\n", "ax.set_ylim(0, None)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can visualise this on a log-log scale, which helps to reveal the diffusive regime (the region where the gradient stops changing)." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.errorbar(diff.dt.values, diff.msd.values, np.sqrt(diff.msd.variances))\n", "ax.axvline(3000, color='g')\n", "ax.set_xlabel(f'Time / {diff.dt.unit}')\n", "ax.set_ylabel(f'MSD / {diff.msd.unit}')\n", "ax.set_xscale('log')\n", "ax.set_yscale('log')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The green line at 3000 fs appears to be a reasonable estimate of the start of the diffusive regime. \n", "Therefore, we want to pass `3000 * sc.Units('fs')` as the argument to the diffusion analysis below. \n", "At this stage, we pass the `random_state` argument to ensure reproducibility. " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "start_of_diffusion = 3000 * sc.Unit('fs')\n", "diff.diffusion(start_of_diffusion, progress=False, random_state=rng)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This method estimates the correlation matrix between the timesteps and uses posterior sampling to find the self-diffusion coefficient, $D*$ and intercept.\n", "We can find the mean of the marginal posterior samples of $D*$: " ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "Show/Hide data repr\n", "\n", "\n", "\n", "\n", "\n", "Show/Hide attributes\n", "\n", "\n", "\n", "\n", "\n", "\n", "
kinisi.Samples
    • (samples: 3200)
      float64
      cm^2/s
      (1.24+/-0.11)e-05
      Values:
      array([1.20904745e-05, 1.13377961e-05, 1.35476525e-05, ...,\n", " 1.04137386e-05, 1.08981500e-05, 1.33306816e-05], shape=(3200,))
" ], "text/plain": [ " (samples: 3200) float64 [cm^2/s] [1.20905e-05, 1.13378e-05, ..., 1.08981e-05, 1.33307e-05]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "diff.D" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The same for the intercept can be found from `diff.intercept`. \n", "A histogram of the marginal posterior probability distribution for $D*$ can be plotted as shown below. " ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.hist(diff.D.values, density=True)\n", "ax.axvline(sc.mean(diff.D).value, c='k')\n", "ax.set_xlabel(f'D* / [{diff.D.unit}]')\n", "ax.set_ylabel(f'p(D*) / [{(1 / diff.D.unit).unit}]')\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is also possible to plot the posterior distribution of the models on the data. \n", "We represent this distribution with 1σ-, 2σ-, and 3σ-credible intervals. \n", "Here we remove the measured error bars, in the interest of clarity." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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+3GkHo/TYC1TXDgOTvjFQISIiTQ1va3EFsLi6LS7dQl25fSEVoDQ6Y19PE/K60brkUzR98zY81Rva79TpULDPsRhxzAUwlU+ElukyMjCmwISDxyR/ui0DFSIiGhBvIKRqUWI9vE0KcVfXO9X24XgmUeTUZWOzC5ub3TGd7SLBm7tyLZq/fVcFKbJzR8jE2OKDZ6PkqHNgLCxDKgQoEwrNMGbpYMpK/oRbBipERJT04W3NTr+qRXH6g3G/fgmG3DEMsoJuO1oXfYKm795Vc0+ipBi2+NBTVTux3pqPVApQtISBChERJW14mxSxrqx3YHOzK65ZFE8ghLX1zphtOJZJsc7Ny9D87XtoWzEfkWB7sW+G3oD8vY9C8SGnwjJ+T83Xn+gyMlCRb8KEIjOyNRagRDFQISKipAxva5IsSpUNrkAwrsc80smzMQYbjuVox1O7CW1L56F16WfwN9d0vk5qTooOPkW1FuvNOdA6XUYGRudnY6IKUJJ/vNMXBipERJTQ4W1ByaLU2bG5xY14kqLcVXV2OId4zBMJBdG84H00zH8VvsbKbpNiC/c7HkUHz4Zp9BTNZ0+EXOLoPBMmFps1UX/SHwxUiIhoJ3ZvAFtbPDFf9lfv8GFJtQ3uQOy3KHfdcLym3oka+9A3HNvXL0T12//orD3J0Gchd7dDULD30cidPgOZRhNSQgYwOjcbk4otMBlSI0CJYqBCRERxH97mC4axotaujpDiRep7K9s8avT9UI+p/C11qHrzYdhWfaVuZ5pyMHLmpSg66GRkZpuRSspzszG52AKzMbUClCgGKkREFNfhbdVtHiyttatgResbjuWYp+GL11D34dPt7cU6HUoOO1MFKXpzLlLJyFyjClCsxtR+qk/tqyciIs0Ob5N5K0ur7ahxDP0Ipq96F9kDtE1G3w+RbCyufvtReGo2qduWCXuh4uxfwTRyPFLJyBwjJpVYkJPiAUpUenwVRESkqeFt21o9WFFjhz/GNS5d1di8quXYN8QliLKDp+a9J9T2YpFpzsWoU65C4YEnIUOnzZbdnpRYDZhSbEWuKb2e2tPrqyEion5rcPhUPUosh7d5/CEsqbGjLo5ZFJcvpI55mt1D60ZybVuF+rkvwbbiC3U7I1OP4kNPw4gTLkGWxge0dVVsMWBysRX55vR8Sk/Pr4qIiBI+vG1biwfLa+0x7xSKkg8r4/WljmawwZUMarOv+Rb1816Ca/Py9jszMlCw73EoO+kKGIvKkSqKzAZMLrGgwJyFdMZAhYhoGGmR4W2tHoRinEVZXG1DfYw7hXbM/qyud8AzyA3H4aAfrYs/RcO8l+Ct39aZQSnY7wSUHn0eTCPHIVXkm7MwtdiKQkt6ByhRDFSIiIaBeA1vk8zMilpH3LIoEgTJbp7BtktHwiE0L/gAdR8+g4C9Sd2ny7aoI56SI86CIa8EqSIvO0tlUKQWZThhoEJElObiMbwt3lkUGX2/ucWFTc3uQY++lxqUytcfhKdqvbqdlVuMkiN/hOJDTkGmyYpUkZutV23GpTlGDEcMVIiI0lS8hrfFO4sy1NH3QZcN1e88jpbvP+jMoJTNvAzFh50OnT51shHSXjy5I0BJgen8ccNAhYgoDbl8QWxtje3wNrd09MQxizLU0fcyD6Z10cdqFooEK0JajMtn/xRZOYVIFVZDphp1PzI3e1gHKFEMVIiI0og8Wdfafao9OJIiWRSp661q82DtEEbf+5qqUPnfv8OxYZG6nT1yPCp+dCOs4/dAqjAbMlUGpYwBSjcMVIiI0mh425YWd0wX/sU7i+LwBrGyzoE2T2DQI+/r572Muo/+jUjQjwy9QY27Lz3qXOj0qdEVYzLoMLnIqnbyZKTOfLmEYaBCRJQG4jG8LZ5ZFBl9v6HJpabiDjb1465ci20v3Qtv3RZ1O2fy/qj40Q0wFo9CKjBl6TCp2IpRDFD6xECFiCiFSV2H7LmJ5fC2eGdRamX0fYMT3kEuKZTjraav30L1W48iEgpAb8nDqNOvVTNRMlLgzCRbr8PEYgsq8kwMUPqBgQoRUYqKx/C2Lc2SRbEjGMOPGcvR9yGfG5Wv/i9al3yqbuftcTjGnPsbFaxonTFThwlFZowpMMtSZk2LXuv+o5P/uDJQISJKMcFQGNvbPGgdZF1HorMoMhNlY7MTm5sHP/o+ut248r/3q8JZeaaXxYElR56j+SxKVseT/th8EzIztX2t5qz2gt5xBWZ1rUZ9ZrIviYEKEdFwH94WzyxKo9OvRt9LIDRYAUcLqt95TLUeRwe3jbv4Nlgn7AUt0+syMK7QjPGFZug1HqDkycyWEitG52VDp9PWtTJQISJKkeFtVTYPGl3+mB7FSBalweWLSweSzESpcwz+Y4cDPjR++QbqP30OIY9TLQ8sPvR0lJ38Y+hNOdCqTF0GxheYMK7IrLIpWl9sOLWkfWaLVjFQISIahsPbNje5sbIu9lkUOebZ0urGxibXoEffS8tx83fvoe7j/3Tu5zGNmqw6eixjdoOWA5Qx+SZMlABFr+0ApSwnG1NKrChKgcWGDFSIiIbR8DYJehZV2dA0hILW3rS6AlhZb4fTN/iAylO3Bdue/xM8NZvU7ayCEWr8feH+J6htx1qky8jAmIL2AMWg4QBFlwHVaSSLDXOztR+gRGnzb52IaJiL9fA2CXpkwZ903cSySyjaIi3txtU27+CvLxxG41dvoObdxxEJBpBpzlWD24oPPVWz+3kkQKnIN6lC2ews7QYo+oz2WhkpkjUZkl8cO1AMVIiI0nx4m0x/XVxlQ7MntlkUubzKNg/WDWH0fTSLUv3mI53j73OnHYwx5/0WWblF0CJpMhqdZ8LEYjNMWZmabjGeWGTGhCKLpjM9u8JAhYhIIyQzIZNaHTEa3iZZFJn+KkWtsc6i2DxBlZ2xeQffIu23NaJuztNo/n6OKm6R8fejTrsGxTNO12bLsQQoudlqYaCWMxM5Bungsahsj9TNpDoGKkREaTi8TdqYJYvSEsNZK9HR9+sbXWoa7mDJHJSGz19D84L3EQm0dwXl7Xmk2nKcXTIaWlTeEaBYjNoNUEosRkwuNmu6g2cwGKgQEaXR8DZpY17f6MTaRieGcBrT6+j7NQ1O+AYx+l5qUJyblqLxy9dhW/VV+7kRAMu4PVB+ylWa3XI8MseISSUW5Bi1+XSp6ziGkiAq35Q6BbIDoc1HnohoGLB5AtjWGrvhbfLxFla1weaN3d6faKfQqjrnoEbf+5pr0bJwDloWfgh/S13n/VKHIlNlc6bsr8ljnhE5kp2wICdbm0+TBp0O44vMqgYlW8N1MrGgzb8BIqI0FuvhbfLxJNOxoSm2WZRQCNjU7MSWloGNvve3NqBt+Xy0LpsL97bVnffrsi0o2PdYlBx+Nkwjx0GLSqwGTCm2ItekzadHq0GPiUUy4l774/hjRZt/E0REaUqyE9J27AvFJovS6g5gUVVbTLcni3q7D2saHPAE+nedAVsTWpfPR9vSuXBtXfnDKzIyYJ20L4oOnIX8PY+AzqDN+olis0EVoOabszR7fZOKLSjLNWoyA5XWgUp1dTVuuukmfPDBB3C73Zg0aRKefvppHHDAAcm+NCIizQ5vk6mvq+ud2NjkjNkwOOHxh7Cq3qF29PQl6LbDtWUlnJuXw7l5GdyVazvrTiQ4sYzfEwV7H438vY7SbJuxKDBLBsWCQg1OaJX6k1G57QPa0rX+RPOBSmtrKw477DAcc8wxKlApKSnBhg0bUFBQkMzLIiLS9PC2Zqcfi6ptcPpjl0WRMplN/dhw7Nq6Cg2fv4q2FZ+3v1MXlrG7I3+fY5C/91Ew5JVAy+SJXwKAYov2hsllSf1JYXv9iUnDbdDDIlC59957UVFRoTIoUePHj0/mJRERaXZ4WygUwcp6BzY3u2KaRZFrXC3HPP5wrx07tpVfon7ui3BvX9N5v7GkQm0wtkzYCzkT94WhoBRal5utV0WypTlGaI0lS49JxWaMLdD+tuVhE6i8/fbbOPHEE3HOOedg/vz5GDVqFK655hpceeWVvb6Pz+dTL1F2uz1BV0tElLzhbXIUI3NRXIFgTI95Vtc70NDLMY8cV0mAUvfRM527dzL0WSjY7wSUHvkjmMomIFVYDZkqgzIiJ1tNltWSIlN7/Ul53vCrP9F8oLJ582Y89thjuOGGG/C73/0O33//PX7xi1/AYDDg0ksv7fF97rnnHtxxxx0Jv1YiomQMb5MBaytq7WojcSw3HG9qdqndPz1lesLBgCqKbZj/Cjw1G9V9OqMZJUecpTp2snJS53jeLAGKKkLVVoCS0bHBeHKKbDBOpoyIhMxJIgGJFM1+/fXXnfdJoCIByzfffNPvjIocH9lsNuTm5ibkuomIEjG8rd7hw5JqW8xqW0Sj06eKcN3+nT9m0GVD0zfvqOWAQXuzuk9nNKngpPToc6E3p87vWFkSOLnYilESoGhozU2mbFrON6ngyarRGS1dFZoMal5LPMjzd15e3i6fv5P6KJWVlWH69Ond7tttt93w2muv9fo+RqNRvRARpevwtkAwguV1NvXxYnvM40SD84d/6EV567eh4Yv/omXhR50j7fW5RSg57Ey1vVhvyUOqUIv4ii0qGNBSgBId0CZHPMYUXhCYDEkNVKTjZ926dd3uW79+PcaOHZu0ayIiSubwNhlTv6TGDm8wFLNjHjk22tjkUi3NXXlqN6P2g3+1j7TvYBo1GaVHnYP8vY+BTp86RxJZHZuCx+SbkZmpvQLZcQVyXRo6e+oHvS4DVg3sNkpqoPKrX/0KM2bMwN13341zzz0XCxYswBNPPKFeiIiG0/A2Kb5dVmNHpS12WZRWVwAr6+xw7nDM42upRd2Hz6Bl0Ufts08yMpA3fQZKjjoH1gl7p1RBpzyZTijSXiAg7c8yn2VUntTGaOe6+sNiyFQLDgtMWdBpYPtyUmtUxLvvvotbbrlFzU+R1mQprO2r62ewZ1xERLEivzZr7F5VQxKLX6DVbV4srbUNatlfb0HP2nqnaovuKuBoRf2nz6Hp67cRCbXX0chAtrKTrkD2iNTKZEuAMq7QhPGFFk218o6wGjGlxKpG8acSXUYGCk1Z6rrNhsTkMPr7/J30QGWoGKgQUSJ5AiFsjdHwNglMllbbdgooBkt+m1e1ebC2wYlgl2OekNelOnjkJexrz9jkTN4fZSdfCcuYaUglmRKgFJhUvYcc92hpg7G0P+dlp85xmcjWS/bEgCKLQT22iZQSxbRERKlEMijVNk9MsiiVbR4sr7HHbOePzSMbjh2weQPdxtw3fv4aGr98DSGPU91nrpiqApTcKam1pkSeRMcWmDCh0IwsjRSjygTZcYVmTEqxCbIZsjrAZFDZE6tR+2GA9q+QiCiNhrfJOP2l1XbUOGKTRQmEwljf6FJzWzrvc7SgYf6raPr6zc4MihztjDzxcnXUk0o1E3IkMabApAplDRoJUExZmep6xhdYkKVPncfSkKlT2RNZG6DXSDYq5oGKx+PBokWLUFhYuFNbsdfrxSuvvIJLLrkk1tdIRJQ0zS6/yn7EYnibtBuvqLHDH4MWZrmcapsX6xqc8HdkZfytDWiY9xKavn0XkWB7F5KpfBJGnnAx8vY4Ahm61Hly0mKAkmvUqwFtFXnZmigy7S85jpIAJS9FFxv2u0ZF2oZnzpyJ7du3q2j88MMPx0svvaRmoYj6+nqUl5cjFIrdYKL+YI0KEcVreJsEFm1djlIGS4aryeC2+h5mmAyGwxtUO3/a3AFV2OvasgKNX70J24rPEQm1Z33MY3bDyBMuQe5uh6RcBqUi36Q6eWRomxZIB8zkYjNG5mYjlYqNiy0Gde1aCfTiXqNy0003YY899sDChQvR1taGX/7yl2oOyrx58zBmzJhYXTcRUVoNb9vS7MbKOkdMPpaM09/Q5FLHUCGPG62LP0bj12/BW7u5822sE/fGyOMvgXXyfikVoEjhxOjcbEwqsaijlWSTR648N1t18BSYUycTYTXoVe2JtBan1N9/H/odqMiY+08++QTFxcXq5Z133lELBI844gjMnTsXFoslvldKRJSA4W1yzNPk9sdkxsqiKltMPlZ0EJx087RWbVa1JzJFNuxr3/+TkWVE4X7Ho3jG6TCPnoJUIwGBjJQ3a2C4mIy4l5ksMqTNkgKFptFrLjRLa7FRE0FerOkHUp+i1//w5hKpyULB6667DkcddRReeOGFeF0jEVHcOX1B1XY81C4cOYqRrMeaemdM6lpcvhBW1dqxbeVC1M99EfY133a+zlhSoYKTwgNPhN6Ug1QzMseoWnq10HmiRu9LgWxR6oy4N0lrsdWAIrMhpWpmBqrf3x3Tpk1Txz6yi6erRx55RP3/tNNOi/3VERElaHhbnWPo9SPSGixZlLYYLCWUcr+NTQ4s+2ouaj5+Fu5tq9tfIVNkdz9M7eFJueOdDqVWgzpSydHAUj4ZcS/ZHGl91tJk295kyKJAs9SeGFIm4zNU/f4qzzzzTLz44ou4+OKLd3qdBCvhcBiPP/54rK+PiEjzw9tkh45036xvcmKHdTqDUm/34ut5n2Db+0/DvX2Nui9Dn4WiA2epLcbG4tFIRVLcKQFKnin5T7AyhVW2K5fnGVMi2DNKa7HViCJzVkq1FscCJ9MS0bAUq+Ftza4AFle1weEf+owVl8eHuR+8g40fvgB35Vp1n86QjeIZZ6gAJSunEKmo2GxQRzz5GihKLcvJVjt4ilJgxH1GtLXYakBuik287Q9OpiUiiuPwNunAWVXvwOZm15CDHY/Dgc/efAFr5rwEf2u9ui9Db0DJYWeg9JgLkJVTgFRU1BGgJLtrJrOj5VmOeLRw3NSfibeSfZIXQ4rUy8TTgP/GZHng5MmT43M1REQpMLxNsjEyF2WoR0a2+mp8/t9/Y/WnryPkbe/g0VvzVQZFimRTNUCRGgrJWhRYspL+hC/zWKRINjsFumFyjHpVeyKbl1PhOEqTgYpMpZWi2erq6vhdERGRRoe3STZmhXTgtP0wrn4wWmsrMf+5R7Fm/nuIhEOdI+5LjjwHhfufAF2WEalIjnbUsYoluccq5qxMTCq2qDZjLW1W7i3bI4+XBCipEExpOlD57LPPcPbZZ+Ohhx6K7xUREWlweFuNzYulNXZ4g4PPotib6vDVC49j6cevIdIxxTtnygEoPeoc5Ew5MKVG3HcldRRyxCO1FMm9DungsWJ0Coy4l2BKHq9CU3q3FicsUHn99ddx0UUX4f777++x64eIKF2Ht/mCYSyrsaHKNvglgn6PC9/89yl899rTCPrbP07O1ANRdtKPYRkzDalK5p9IBmVEbnIzQCOsRpVBGZFj1Px6AOk2kgDFbNB+rYxW9OuROu+88/DHP/4RV111VfyviIhII8Pbqts8Kosy2I8TCYex4rO3Me+ZB+BsaVD3WcbvifKTr4R1wl5IVRZDpipMld03ySqlkCTEqFxTezeRxpftZctgNotBHfFkMnsSn0Bl4sSJ+Oijj3DDDTfAZDIN/LMQEaXQ8DbJoiyttqHaPvgsSuWqRfj4iXtRt2Glum0oLMOoU69C3p5HpmyhpMmgw6QiK0ZJgKJL4oj7QnP7yH2Ddms65G9YAihZCpgKnUZa1q9H78svv8SsWbPU0DfZ8ZOVpe3olYiG5/A2WQDoGUINidje6sHyGjv8g6xpaaurwmdP/S/Wfvmhuq0zmtUW45IjzoJOr/3ZHT2RLcaTiiwYnWdKWoAiA8+kg2eCxkfcGzJ/aC3OGmaD2ZI+8M3pdKqOHxnO8sYbb0ArOPCNiGIxvM3jD2FJjR11jsFlUXxuJ75++QksePNZhAJ+yDN60cGzUXbS5Sk7qC1bL/tvLGoGSbIClGgHz/gCs6ZH3OdKa7HVqAp6UzVjlvID36xWKz744AP8z//8T6yukYhoyO3CW1rccA5xKuy2Fg+W19oH1RkUDoWw/OM3MP8/D8LV2qzukx08o0+/DqayCUjVAEUyF2OSGKDIE//kEisqNNzBo9dlqKF2Uhxr1Gv3GCrVDejgzGg04tVXX43f1RARJXB4m1uyKNU21DsHV9Oyddl3+OTJv6Bh8zp1W3bwjDrtGuROPzQl/1UdPV4ZU2BGsjqli0yyD8iCsrxsaLmYuNRqRAEHsyXEgCt8dH189zY2NqKkpGSo10REFPfhbZub3FhZZ0dwEIFOS802fPavv2H9N5+q25kmK0bOvFRNlNXpU6+GL6sjQBmbL8crybmGkR07eIo1uoNHWotlIaAc75g4mC2hhlyKHAqF8O677+Kpp57CnDlz4PMNfVU6EVFP2tTwNjeCQ1hR7PIFsbjajkbXwH9XeZ12fPXS4/j+7ecQDgYBXSaKDz0NZSdeBr0lD6lGji5UgJKkCa7RFuMppRY1NE6LTPqOwWxmthanXKCyYsUKPP3003j++efh9/sxe/ZsvPTSS7G9OiKiGA1vk76Bzc2SRXEM+LgoHApiyZz/4vP/PAyPvVXdlzvtYJSfejVMI8chFQOUcYUm1eabjM4UrbcYSzhSYGqvPZGhdpRcff4NSHbkmWeeQWFhIc455xy0traqwESyJ6tWrcLMmTPR3NyMpUuXYo899kjcVRPRsBGL4W1ObxCLqm1oHkSgs3nxV/jkyXvRtG1j504eVYcy7WCkGskIjC0wYYIEKElo8ZXBZ7IgcHyhWZNbgY1dWov1bC1OjUDlwgsvhF6vR2lpKe6++26sXbsW++yzD3784x/j/PPPR1FRkZqp0lfdChHRYDMg1TbvoAtdox9jQ5MLa+qdA86i2BtrMeeRO7Hx+/nqthztjJx5GYoPPRUZman1r2yprxhTYFJBQjIChDyjHpM03MEjx04yOTZP4xNuh6s+f9q++eYbvPfee2oybUFBAW666SbcfPPNyMnJSdwVEtGwE4vhbXZvAIurbGjxDLzodtX89/Hho3eqmpSMzEwUH3aWGtqmN+ekXIAiM1CkDkWGtiVaqcWoRtxrcQePHH9J5kQmx2oxu0P9DFR+8pOfqKxKfn6+2vMjc1QeeOABnHLKKWo54UknndTXuxMRDVid3avG4EeGUM+yvtGJtY1ODLTm1uOw4aPH/oRV895Tty1jp2PM+Tcju3QMUkoG1AZhmSZrSnANiCRMZIKt1J9oMUNhNehRajWo8fZsLU6DQOWOO+7ABRdcoIa9jR49Wt0n9ShSt3L55Zer2+FwGKtXr8b06dMTc8VElJZ8wRC2tniGNLzN5gmoWhTpDhroEdHKz97Bp/+6D+62ZmToMjHi+Isx8viLUuuYR7pocrLVJFezMbEBSpauY8R9oTnhwVF/indlIaBkUNhanMYj9HcUCATw9ttvq6BF2pJHjBiBs846Cw899BASiSP0iVJfk8uHqjbvoIe3SRZlbYMT65sGnkVp3LYBcx69C5UrF6rbxtIxGHv+zSqbkkpG5rQfsyS6S8WSpcek4uS1OO9q/L5qLTYZNFkbM9zZ+/n8PehApau6ujo8++yzKmiR7EoiMVAhGt7D2yR7sqiyDTbfwDIxblsrvnj+USx+/2VEwiHoDNntywOPPCelhrZJlmBKiRV5psQGKIWmLHW8U56XrakjFKnLkYmxUhxrYWuxpiU0UEkmBipEw3N4WyiaRWl0DqieJej3YdG7L+LLFx+Dz+VQ9+XteSRGn34tDAUjkCpkx4xkUArMiQuqJBwpy8lWAUqRxibISmuxTI2V6bFsLR6mSwmJiLQyvK3FFcCiqjY4BlDP4ve6seT9V/Dta0/B1dqk7jOVT8So069DzqR9kSokMJlSbEWhJSuhNR4yf0WKc63Z2nnayIi2FlsNyNXoZFsaOu18xxFR2hvq8LZQKILVDU5sbOp/FiXg9WDhO8+rAMVjb1P3GfJLMOKES1F00CxVOJsK5AlZlvUlcheOUa/DxEIzxhdZ1J+1Qgp3VWux1ZCUybqUWAxUiCju5IS51u5DnWPwbcdNTj8WVdngCvQvixIKBrD0w9fw1YuPwdnSqO4zl4xC8TH/g4L9Z6ZMHUputl4dtZQmcBaJtPDK55QhcVrab5Nr1KvjnbxsvabqYkgjgYqMzT/ttNNQXFwc3ysiorTileFtLW64A4Mb3hYMRbCqzoFNLa5+v8+WJV9jzqN3orVmu7ptKS5HycxLkb/PcSnTbizdO1M6ApREPScXmdrrXspyjZoJBGQwm9TjSPbEqE+N7BfFVr9/Yp977jlcc8012G+//XD66aeroGW33XaL8eUQUTppdPpQZfMiPMia/QanD0uq7P3Ookgnz6f/91es+PQtdduUX4TyEy6B9YBZ0Om1VfzZG6sxU2UzRuRIN01iPme5BgtkJasjwYl08GglaCKNByqfffaZWkooI/Vlfsqf//xnNTtFAhYJXA4//HDu/CEiJdDRdmwbZNtxIBjByjo7trS6+320tGruO/j4iXvbtxvLdt5jzkbucZcjM9uCVGA1ZKpBbSNzExOgZHaM15cAJUcjBbJyTYVmKY41cjAbDb092e/3q+BFgpZ33nkHHo8HJ598sgpcZs2aBYslMb8c2J5MlF5tx/UOH5ZU2/p9VNRaW4k5j9yhjntEfsVElJ/9axgrUiPjm+gAxaDTYXyRWS0ozNZIMMDBbMOTPdFzVBYuXKiClrfeegs/+tGPcOuttyIRGKgQpUfbsT8YxopaO7a1efpdLLvgjWfxxQuPIujzIjPLgLGzLkfu4eekRB2K2dB+xFOWoABFggH5fFqZICuD2WRonAQoZoP2/74ozQa+yXj9rKzEVNQzUCFKPpcvqApmB9t2XGPzYmmNHd5+bkuuWb8C7z90Gxo2r1O3S3Y7AMVn/BLZxe07ybTMlKXDpGIrRkmAkoDTclm+JwGKfD4tZCtM+kzVWiy7d7TUUUTDbOBbooIUIkrttmNfMIxlNTZVcNsffo8L8//zMBa+/Rwi4TCM1jyMOu0a5O43U/MFl9kSoBRZ1GbhRAQoI6ztu39KrYlra+6N/M0UmNo7dxK9i4hSH79jiGjQ244li+LyD67tWI6JltfY+52F2bhgvmo5tjfWqtsjD5qJ4pOvRlZOAbRMRrtPKJIjl/gHKBIQjMrLVrt/JJOSbBxrT7HAQIWIEtp27PGH1DFPraN/WRQZ1vbxP+/Bmi/mqNvm4jKUn/kr5Ew7CFpmUAFK+1bheDdESrfMmHyTmlyb7EV8HGtPscZAhYgS1nYs4/NX1DoQCO86iyJHO8s+eh2fPfU3eJ12ZGToUHbsuSg+7lJkGk3QKhlQJgHKuAIzMuNctCqj5McXmjGpOPkdPBKYSe2JvHCsPSU1UNmwYYPq7Nm6das6Ex4/fjzOOOMMTJgwIaYXRkTp03bs9odUy3G909evt2+q3IwPHv4jKlcuVLdzx0xF2dk3wjx6CrQcoIwrNGF8oSXuXTWyd0fqXSYUWpClT25tjsqeWCR7wrH2pIFA5Z577sFtt92GcDiM0tJSVUjX2NiIm2++GXfffTd+/etfx+kyiShV2443N7nV8LZgP46JpFj2q5f+ie/eeAbhYBCZhmyUzboCxYedpdmWY+lckfqTCYVmZMV5cZ9WdvBIJqfIIgGKEQYNLSuk9NTvn/y5c+fiD3/4g5qPcv3116OgoL2AraWlBQ888IAKVg466CAceeSR8bxeIkqRtmN5X1ki2J8AR/7Rs3r++/jsX3+Do7le3Vcw/RCUnXk9jIVl0CJdx2RXGZxmzIrvk7XMG5lcbEV5XnJ38OTIUkCLQRXqMntCidLvOSrnnXce8vPz8c9//rPH1//0pz+Fw+HAiy++iETiHBUibbUdy/tubHJjdb0DoV38epE6lLVffaSyKA1b1nVuOB556rXInX6oNp8MM4DRudlqmqzJEN+6kLKcbLWYMJk7eLgUkFJmjsqCBQvwn//8p9fXX3zxxbjkkksGfqVElDZtx1LHsrjapv7fl3AoiNWff6AClObKzeo+fbYZI445H8VHnQddVvJnf/SkPLd9eZ/ZmJn2O3jkmEkKY2UpoBYGxdHw1e+fgvr6eowbN67X10tRbV1dXayui4iSoMnlQ2XbwNuOQ6EIVjc4sbHJ2WcGJhTwY+Xcd/D1K0+itWa7us9oycHIo85B7qFnQG/WZlZ0ZK5RBQ7xHFamhR08XApIWtTvnzqv1wuDwdDnNFpZVEhEqScYCmPrINuOG51+LK6ywRUI9v7x/T4s+/gNfPPKk50D20y5BRh3/PnI2v8UzW44HpljVEc88cxsWLL0qr04Ee3MveFSQNKyAf30/d///R+sVmuPr5P6FCJKPTZPAFsH0XYcCEawos6u3rfXt/F5seSDV/Dta0/B2dyg7rMUFGP67EuAPU9EUK/NI54ROe0ZlHgGKFKQKvUnMkk2GbU4UgwsxzpSHJvsIXFEfen3d+eYMWPw5JNP7vJtiCj92453tUQwHAqpI575zz4ER1P7kXBuyUjsd8YV0O1xAlqD2vxXe6nVoLprck36uO7gkRH3ksFIhmx9pgpOuBSQUkW/fxplwBsRDe+2Y1kiuLTahmp77+PvNy/6Ep899b+dXTy5JWU47PyrYd7nOGy1BREOxnxh+5BJ0agED3lxClCiO3imqs+R+LHyXApIqYzfsUTDiLQO1zl8qLUPvO14V0sE6zetUQHKliVfq9vZ1lzMOO+nGHvMOVjf6kdd2+DG7sc7QJEjnnxzVlru4DF2GWvPpYCUqvr9k/PNN9+gubkZp5xySud9zz77LG6//Xa4XC41Rv/hhx+G0ajNM2ei4W6wbceyRHBJjV3NVOmJraFGHfHIUQ8iEWTqs7D/qf+D/c/6CbZ69Fha74HWyFyQySUWFMQpQNFnyL4fS1J28HApIA3bQOXOO+/E0Ucf3RmorFixAj/+8Y9x2WWXYbfddsN9992H8vJy/PGPf4zn9RJRAtuOtzTL+PuelwjKokBpM/7+rf+otmMx/ajZOOri69FmLMT3TS6Ewv3b7ZMoBWaDKmAttGTFLYMhXULJ2MHDpYCE4R6oLF26FHfddVfn7ZdeegkHH3xwZ4FtRUWFyq4wUCHSVtuxbDtuG2DbsdSwLK62o9Hl67FQVjp5Pv/PQ/A4bOq+MXsdhOOu+DWyR09VgY3T5oSWqA6bEosqII1Xe68U4Y6THTwJbjGW7IkEJ3lcCkjDPVBpbW3FiBEjOm/Pnz8fs2bN6rx94IEHorKyMvZXSESDbjuWIKWnbEhfNSybmt1YVdfz+HupQ5GtxjXrV6jbxWMm4tgrfo0x+x6OdY0uVG1rhZbIRl8JUGSAWVw+vlE+vhWj87ITOn+ESwFpOOl3oCJBypYtW1TmRAa7LV68GHfccUe3OSoy9I2Ikt92XGXzoNE1sLZjuzegBre19DD+XrYaf/7cI/j+recQCYdgMFlw9GW/xL6zzkONI4DPt7QiMIjFhfFiNWZiSrEVpTmyxC/2H79YjpBKLBiZm41E4lJAGo76HaicfPLJakPyvffeizfffBNmsxlHHHFE5+uXL1+OiRMnxus6iagf3H5pO/b0Ot+kt8BmQ5MLaxucPWZR1n/zKT56/M+wN7bPQ5l2+Ik44We3IGwuxHeVjkFNs40Xi0GOYNoDiFg/j2d07vqxxq3Gpa+lgHK8k6zR+kQpEahIfcpZZ52Fo446Sk2n/fe//91tpP5TTz2FmTNnxus6iSgObcetbsmitMHm23n8vYy6/+ixP2P9t5+p23kjRuGka27FmP3aj3kqt7ZAK8yGTFXEWp6TjQxd7FuMxxWaManInNAWYwm65GiHSwFpuMuIyG+4AZB1zBKoZGZ2j+xbWlrU/X3tA0rmmmiidDWYtuO+lgjKZmM54vn8uYcR8Hqgy9Tj4LMuw+EXXI0GXwbW1jvh18gxj8mgw6QiK0blxj5AkQ4eWRAobcaJqgPhUkAaTuz9fP4e8D8P5IP2pLCwcKAfioiS0Hbc1xLB2vUr8f5Dt6F+81p1e/T0/XDSdbfDVDYei+qcaB3EuP14MGXpMLHYgtG5ppgHKO1LAi0J7eCRriE52pEjHmZPiAYZqFxxxRX9ejs5AiIi7bUdB0MRrKyzY3PLzksEQ8EAvnrpn+pFimVlquyxP/4Ndj/2DGxs8WDrlhYMeJRtHGRnSQbFgtF5sQ9Q5IhFZqyUJ2hJIJcCEvVPv386nnnmGYwdOxb77ruvOg+Ph7/85S+45ZZbcP311+OBBx6Iy+cgGo5tx/UOH5ZU2+AO7Hw81LR9E97+282o27hK3d7tyFmYedXvYM+w4MutrfAGw2kdoCR6SSCXAhLFKVC5+uqr8eKLL6oW5csvvxwXXXRRTI97vv/+e/zzn//EXnvtFbOPSTTc244DwQiW19lUYLMjn9uFb155At+9/ozKqEgW5cRrb8O4Q07E6joHmtx2JJtRL3UiFrUvJ5YBisQHo3JNmFJqUQPTErUUUI53crKZPSGKWzGtz+fD66+/ro53vv76a8yePVuN0Zdun6GkSp1OJ/bbbz/84x//wJ/+9Cfss88+vWZU5BrkpWsxjsx2YTEtpbPBtB1Xt3mwrNax0/tEwmG1l2fu0/fD2dKo7pt4wBE46bo7UQ+L+jwDHbUfj3HwE4rMGFtghk4X4w6eArPa8yOdQvHGpYBEQy+mHXDXT9S2bdvUcZAsJgwGg1i1apXq+hmMSy+9VGVn/v73v6t9Qn0FKjKiv+uguSgGKpSOBtN27PKFsKy25yWCVWuW4pN/3tM5WbagrALHXXkT8qbPwJoGJzyB5B7zZEUDlPzYFrIadO0fVwpwJUsTT1wKSJTkrp8onU6nsijyizQUGtg21q5kZ5BMuZWjn/6QGpYbbrhhp4wKUTq2HW9t8cDp37k7pyfys7ixyY3V9TuPv5eZKJJBWTXvPXXbYDLjsPOvwh4nX4h1LT5sqk7uMY8MNYtmUPQxDFCkxVdqW8YXxvbj9oRLAYniY0CBStejny+//FJtUn7kkUdw0kknqcBloGQ3kBTOfvzxx8jO7t8oaqPRqF6I0tlA244d3qBqOW72dK9fkTko3/z3X/j2tacQ9Hkh41r3PuFMHHnx9agLm/F1pTOpxzwSoIwrNGF8oSWmgUSOoX0HT0V+/HfwyL4fmXvCpYBE8dHvo59rrrlGZT8keyGtyhdeeCGKi4uH9MllFP+ZZ57ZbXicZGfkh10CHwmMdhwstyMOfKPh3HbcWxZF7l81713MffrvcDS1j76v2H1/Nfo+c+Qk9fbuAQyIizXpdpE5JZLpyIrhUUyh2pJsVS3G8Q6wotkTo56D2Yg0UaMigcOYMWNUe3Jf/2qQjEt/ySJDqXXpSjqKpk2bhptuugl77LHHLj8GAxVKF7IUUI56+tt2LFmURVVtOy0RrF67DJ888Rf1f5FXWo5jf/xrjDv4eKxtcKmal2QGKNLBIxNfYxmgSIvx1BIriuPcYhwday/TY5k9IdJYjcoll1wS8x/MnJycnYIRi8WCoqKifgUpROnSdlxt96LB2b8AQv5tIUsE19R3XyLoaKpXdSjS0SOysk2Ycd5PcdDpl6HKFcIXW1oRCifnmEeGm40paA9QYjWOXk50ZK6KdPDEs8U4Opit1GqA2cDWYiJND3wjouS2HcumYqlFae2SRZE6lG9ffxrfvvovBHzt81L2Ov4MHH3ZrxDMLsCCWjvs3v4V5MbjSb4i36QKZWVoWyzoMzIwvsiilgSa4thiLMWxMpiNrcVEyaW5fx7Mmzcv2ZdAlBB1di9q+tl2LFmXtQ1OrG+S4tcfMitrvpiDz/51H+yNdZ27eU746c0onjgd6xpcqKxvSVqAMio/WwUT2TFarictxhOLzWoAXDyXBOYY9ShlcSyRZmguUCFKd/5gGFtb3XD4+pflaHUHVC2Kvcvb2+qrMefRO7Fp4Rfqdm5JGY694tfY7ciTUGPz4fNNLcnZcKyOYyRAscQs25GIFmMJrIrMcrxjjFlgRUSxwUCFKIFa3H5sb/XsNOekJ6FoFqXR2Zl1CYdCWPjO85j/7IPqyCdTn4VDz70Sh57zE/igx4LtNvU5khKg5GarrcOxClAS0WLMvTtE2sdAhSgBJOiQAKVlhzknvWl2BbCkunsWpX7zWrz/0O2o7ZgqK+3Gs35xBwrKJ2BjsxNbWuxIxkiU8txsTC62wGyMTYBSZDKoAtl4thhL8a0Ux3JyLJH2MVAhijNpI5ajnv4cxQRDEayss2Nzi7vzvoDPi69efAzfvvY0wqEgjGYrjrniRux70jlodAXwxZampIy+H5lrxJRiCyzGof8akVxGWU57wFMUpxZj2fMjhbEy2p6zT4hSBwMVojiRYtdqmxf1/Ww7rrV5sbTWDk/ghw6grcu+wwcP347Wmu3q9tQZJ2Dm1b+HPqcIi6vtaHAm/phnRI5RZTyk6DQWwcPYApMKUGIR8PTEpM9EaY4BhSZD3KfUElHsMVAhigNvIIQtLW64uwQdvfEFw1habVOzVKI8jjZ89q+/YdlH7QMUrUWlOPHqP2DKIcdjc4sLm7a0JHwmimQjpGYkz6SPyVZhmakibcbxWBIo4Ui+mn1ihDVOARARJQZ/golirMHhU0FHf3boyLj8FTV2+Dum0UZbjj96/G6425rVffvNPl/NRHHBiC+3NMOZ4NH3BWYDphZbUGAZej2H1aBX2RMZ/haP4tUsna7zeIeLAYnSAwMVohgJhMLY2uLuVgDbG9mzs6Ta1u1YSDYcz3n0Lmxc0D5LqKhiAk7+xR0YMXVfNYW2xt6GRJKMhBzxyBN/LHbwTC6WHTzGuMwmkdH2kj2RCbKcfUKUXhioEMVAmyeAba1uBPtxHLOpyY1VdXYEOzIu0nK86L0XMf/fD8DvcUOn12PGuT/Foef8FNXOIOZvau7Xx41lR4wEKJKV0PIOHglHCs0GjrYnSnP86SYaApkYW9nmQVM/Zpc4ZYlgtQ3NXd62YesGvP/grahZt1zdHr3bvph1/R3QF4/Fd9WOfg+Fi4Xc7PZjmdIc45ADiFF52SpAyTPFvv2Xo+2JhhcGKkSD5PLJnh43fLtoO+5piWDQ78OXLz6Ob//7L9VybDBZcMzlN2DPmedgXZMbVdtaE/RVQBWbSpvxiFyjpjt4ONqeaHhioEI0QBJ41Np9qHPsek9PT0sEt634Hh88dDtaqreq21MOORYnXP0HOLLy8fnWNlXrkghmQ6YKUEbmZmMoz/tSwCpLB2Uqbaw7eKKj7UusRjVKn4iGHwYqRAPgC7a3Hbt20XkjR0LrGp3qJVpe4nXa8dlT/4ulc15Vty0FxarluHz/Y7Cq3ok2jz0RX4LaYixBxehcEzJ0Qxs/P6nYjPEFFmTpY5vhkPZlyZ5wtD0RMVAh6qcmlw+VbbtuO5bC2kWVbbB11JdIBmbtVx/ho8f+DFdrk7pvn1nn4MhLbkClNxNfyTFPAmpl5cl/QpFFHc8MJUDJNeoxWXbw5MV+Bw9H2xPRjhioEO1CMBTG9jZPt+Ob/i4RtDfV4cN/3IUN385VtwtHjcPJv7gTWWP2wIIGJ3zB/k2tHQqZJyJHM2PzzcjMHFoHj2RiZDJtLHG0PRH1hYEK0S729MhRT6BjIFtvmp1+LK62weHvyKKEw1j8/suY+/T98Htc0GXq1Ybjfc78Cda1+NFcE/9jHr0uA+MKzRhfaIY+M2PQQURFvkkd8cQ6y8HR9kTUHwxUiIawpycQjGBFnV0tHYxq3L4RHzx4O6rWLFG3R03bGydedyfs1jJ8W+3q18TaoQcoJhWkDHY6qwQo8v5SbGsyxC7LwdH2RDRQ/E1BNMg9PdVtHiyrdcAbDHUGNwvffk4VzIYCfhhMZjX6ftQRZ2Jtkxue5h+CmXiQotNxBSaVQcnSDz5AkTqWycVmZMewy0Zmn8jxjrxwtD0RDQQDFaIB7unpaYmgs7UJ7/3999i08At1e+IBR+Don92GyrAFS2udcb1maeGV3Tmy5M8wyAAlXi3GnH1CREPFQIWoo2B2a6tHzT3py/ZWD5Z3WSIoti77Dm/e+2u1RFBvMOKYK36DvENOxdIWCXh2PbF2KAGK1I9IgCEtx4NtMZYAZ0Jh7FqMJSsjbcUyPTaWWRkiGp4YqNCwZ/MEVI1JX/t0ZIng0hq7GvIWJUc937/5LD79198QCYdQMnYyjrjubtQZR6Cp2RO/C84AKvJMmFhsHvQQtBzZYlxiwZh8U8wKWc1Zmapzh8WxRBRLDFRo2JKhbFU2DxpdfWc9Nje5sbLLEkER8Hrw/sO3Y9Xcd9Xt3Y45DeVn/Qpb/BlAIE6TZTOA0bnZ6nhmsAWuRSYDppRYUJaXHatLQoGpfTFgPMbmExHxNwsNS26/tB17Ogthe2tNXrzDEkHRsGUd3vrrb9G4bQMydJnY+4JfQrffqWiJ1ylPBjAqpz1AMRsHF6CU5WSrDp6iGG0xNnYpjuViQCKKJwYqNOzUS8GszdPrMFjJtMjQtnWNrs4lgtHZKAvefBbznvk7QsEATHmFmHTpH5Exdq+4DZYdmWtUAcZgshVy+iI1LFOKrcjJ1sckeyKTY+V4h5NjiShRGKjQsCHL/qTt2NEx2r4nrW5ZIvjD+PsoR1M93rn/Fmxd+q26Xbr34Sg980bocwricq3SKSNHNIMJMKIzUGSLsSweHCrpCIpmTwbbVURENFgMVGhYaHX71Rj83gpmexp/H7Xmyw/VtmNZKphpMGL06deh4OBT4tJuW2w2YEqpFXmmgf9o6qMzUEpi02IsrcXSuSMD2thaTETJwkCF0poc40iAsmOdSVfNrgCWVLfBvkMWxed24ePH/4zln7ypbueMmYbRF/wO2aVjYn6dhRKgFFtQYMkaVL2IajEusgw548HWYiLSGgYqlLZcvvY9Pb5Qz104wVAEq+oc2Nzi2imLUrN+Bd6699dora0EMjIw4tgLUXbiZcjIjO2PjGQr5IhHgoPBzECR450JhbJscGgZD+7dISKtYqBCaUfmm9Q5fKi1e3stcq21ebG01g7PDmPypWD229eewvxnH0I4FIShYATG/s/vYZ2wV0yvUYpSJ5eYUWId+CZiS5YeU0uHPgMloyOTI9kTthYTkVbxtxOlFX+wvWDW2bHFuKc9Pstq7N3G30c5mhvwzv/e3Fkwm7/30aj40Y3Qm3Nidn1S9yEZlNIc46CyL1OLLSjPyx5SzQhbi4kolTBQobTRIgWzrZ5uLcVdbWmWwW0OBLqMv4/a8N1cvHv/7+FxtEFnyMboM36OwoNOjlkRqdWQiUklFozMkSBjYO9bajGqAtkRgwhuulKtxRYD8kxsLSai1MFAhVKedOxIgNLi8Q9ocFt0wqxsO1707gvqtql8EsZdfFvMCmalPVjqSMpyBxagyJuOzjOpAEUyKUMpjpXMicw+MepZHEtEqYeBCqU0CUJkT4+/h4LZ3ga3dV0m+N4Dt8JWX6Vulxx5DspnXwmdfujTW01ZOkwqtmKUBCi6gQUWYwtMmFxshWWQU2ije3dkFkuBKYvFsUSU0hioUMoWzFbbvKh3+np8fbPTr7Iojh5qVbwuBz7719+wdM6r6nZWXgnGnPtr5E47eMjXJVuMJxVZVDZkIAGKDFWTLcgyJn+wM1Bkm3KhqX1yrNnAH20iSg/8bUYpRzp1pN7E08OenkAwohYIbml19/i+G76bh/cf/iNcLQ3qdvGhp6H8lJ8hM9sypGuS4GJiUXsnzkACFGkxnlRsxvgCC7L0g8t8yMeQ2hNpcc5k9oSI0gwDFUqbPT3VbR4sq3X0uGjQbWvFh4/fjTXz31O3DUXlGHPub5Azad8hXU9Wx7C1sQVm6HQDazGW2pWxhaZBBRfyHlK7UmIxxmSPDxGRVvE3HKVM27HUovS0p8ftD2FpjR11Dm+PR0Sr532AOY//CT5HGyTdUXrUOSg78XLV3TNYep2Mq28PUPQDGLaWZ9RjUokVFXnZg6odMXRpLZYgiYgo3TFQoZRtO5YgZGOTG2vqHQj2UCyrFgk+dAe2LpynbmePHI8x590Ey5hpQwpQxhWYMK7IPKBAQTIfU4bQYpwre3esRuRl67l3h4iGFQYqlJJtx7LleEmNDW2ewE6vk4my37/7MuY/+yCCHqcaez/iuIsw4rgLodMPrtVXjmekG0fG1Wf1s9hVwony3GxMLbUOqsVYgqIimRzL1mIiGsYYqFBKtR2HZD9PvQObmnfezyO2r1iEdx+9C23b16vb5oppGHPeb2EqmzDoThoVoBSZ+73w74cWY8ugRtNbDFIcy9ZiIiLBQIU0RWafyHj7hh7ajqWQdkm1De4d9vMIj8OGDx7/C9bOfUvdzjTloOzkn6D4kFOQocscVIAypsCkCmX7G6DIaPoJHVuMB9pizNZiIqKe8TciaYbbH8TWFs9Obce+YBgrau3Y3ubp8f3WfPMZ3n/4DvjaGtWm46KDT0H5rB9Db80f8DVI+cfofJOahSIzUfojx6BX80+kNXmgW4zZWkxE1DcGKqQJdXYvanrYdlzZ5sHyGjt8PUye9TgceOPhO7H1y/aWY2NJhSqWtY7fY+AXIAFKbrYKOEyG/mVg5HhmcrEZI3MH1j3E1mIiov7jb0nS5LbjvlqOxerF3+OD+2+Gr6W2o+X4XJSddDl0WQPvqinLNWJKsRXmfoyslyBjVF42ppQMvECWrcVERAPHQIWSptnlVxmTrm3H0Zbj1fWOHvfzuL0+vPv0o9j47lNAJAxDYRnGXfgHWMbtPuDPL63CsvQvpx8Fr0PZwcPWYiKiwWOgQgkXDIWxrdWDNm/31mJpNZb9PD21HEfCwLJVqzH/0Vvh2r5G3Vew/0xUnHX9gMffS0ZDMiJ5pv4FKFIcK0c82Vn9D1DYWkxEFBsMVCihbJ6AClIC4R9qToIdLcebe2k5bnR48clLT2HrO08gEvSrwGT02TegcL/jBvS5C80SoFhQYM7qV5GrdPyML+x/149gazERUWwxUKGEtR1X2TxodHUf3lZj82JZrV0tGtyRNxDGwpVrsOhfd8G1ebm6L2faQWpHjyGvpN+fW2pJ5IhHMin96eCRt62QDp5+BhrSWlxkzlIfn63FRESxxd+qFHcunwxv83RbFugNhLCsxq5mpvR0zLO5xYVv3n4BVW8/hrDfC53RhFGnXYuig2f3u84jN1uvMihSH7IrxWaDGtBWltf/Dh7JupRaDSpTw9ZiIqL4YKBCcSOFsbV2n+rc6XqkI0c/K2rs8Hc5/olqcvmxePVGrHvuHjg2LFL3WSfugzHn3wRjYVm/Pq/VmKm6eEpzjGouSl/Kc9o7eAot/evgkQ+Xl52FUitbi4mIEoG/aSkufMGQajt2+UPdWo5lsmx9D1Nn5ehnTZ0Dqz97C1VvPYKw14WMLCPKZ/8UJYediQzdrutEzAYJUCxqrklfAYokP+RoR4KZ/gYbUlQrhbFSfzKQmhUiIhoaBioUcw0OnzrSCXdpL97U5MaqOvtOW46jxzxrNldi6yv3wb76G3W/ZezuGHPBzcguqdjl55MJsjKobXSuSUaq9BlsSHHs5AEMdYse70gHD4tjiYgSj4EKxTSLIiPwuw5vs3sDWFJtR7N75w3IjU4fVtU5UPnF26h55zGEJIuSmYWyk65A6dHn7nJHj+zTmVjUPrq+rwBloDt4ODmWiEg7+FuY4pJFCYUjWNfgxPomJ8I79Bx7/CE10G37ls2ofPVvcG5aqu43V0xVI/B3tenY0BF4jC0wo68TIXNWpsqejCsw92sHT5aufXKsHPFwciwRkTYwUKEhke4dKY7tmkVpdPpVLcqOY/GldnZTsxObGhyom/cyaj98Rs1F0RmyUXbSj1FyxFl9ZlGyogHKLpb/WbL0mFranmnpz3GNTKaVxYCSReHkWCIibWGgQoPu6Glw+tUiwWgWRbYcr6y1Y1sPW47lmGd1vRNNm1Zj+yv3wVOzUd2fM+UAVPzoRhiLyvoMUMYXmnaZGckz6jGl1IrRedm7DDjktdJWLPUnnH1CRKRd/A1Ng8qibG3t3tEjWRUJUnbcctx+zONEXYsNtR8+jYb5r6oK2kxzLkadfi0K95/Za1AhY+jHFbZPh9X3EaAUmrIwtcTarxkocrzT3r1jgJ7HO0REmsdAhQaURal3+FQWJVp24vQGsaTGjkZX95bjUAjY3OzE5hYPbOsWYvt//xf+5hr1uvx9jsXoM36OrJyCHj+PDE8bX2DCuCJzn7UiI6xGNQNFAo/+jLaX2Scy2p7HO0REqYOBCvWLzDnZ2uKGu2PUvYzEX9/oxLpG105bjmttXqxtdMJps6H6ncfQsuB9dX9WXgkqfvQr5E2f0esoetlQLDt2svrozhmV2z6kbVc7e6LdOxLQWPqxIZmIiLSHv71pwNNlmzqKZR07FMs6fEGsqXOiyeVD2/L5qHrjQQQdrZDpa8UzTkf5yVf2uOk4o2MA2yRpH87S9T6kLc+kApRdtQzLkZF070gGhd07RESpjYEK9crtD6q5KJ6OHT3+YBgr6uyqHqUr2X68ocml6lb8bY2oeu0B2FZ9pV6XPWIsKs75Nazj9+zxc5Sr7EjvA9hkSJsU0cqiQJk82xeTDGfLMaDQxOFsRETpgoEK7USOdWodXlWPEs2ibJf9PD0Uy1bbvFhX74Q3EETzt++g+r0n2sffZ+ox4tgLMeL4C6HT71xDItmOKaUW1RrcE31GhhrQJgHKroa05XP3DhFR2uJvdurG4Q1iW6u7MyBx+UJYWrPzfh55u1X1TrS6/fA2bMf2V/8G1+bl6nXmMbthzLm/6XFwm9pSXGJFvlnfa1eO1KjISPy+dupIpiU6nM2o7984fCIiSj0MVEgJhsKosnk7R91LbcrGJreaINu1WDYQCmNDoxvb2tyIBIOon/sS6j7+NyLBQPvgtpOvRMlhZ+w0uC3fnIWpxb1vKZasidSoTCi0IEuf0ec4fMmeFFkMqjuIiIjSGwMVQovbj8o2D4Ids+7bPAEsrrap/0dJrFLV5lFdPhKsuCvXYfsrf4WnZpN6fc7UAzHmRzfCUDiy28fOzdarGpQSq7HXKbLy+jEFpj4Dj1yjXgUoeaa+O32IiCi9JDVQueeee/D6669j7dq1MJlMmDFjBu69915MnTo1mZc1bEhx7PY2D2ze9oAkFIpgdYMTG5ucnbUpotUdUJkVuzeIsN+rRt83fP6Kmokvg9tGn34dCvY/odt8EqsxE1OKrSjNMaqunh3lZevVkLZRfUyRlXblInN7/Ul2Fo93iIiGo6QGKvPnz8e1116LAw88EMFgEL/73e8wc+ZMrF69GhbLzm2sFBtyrCP7eGRwW/RYRwpnl1bb4QoEuwUya+udatmgcGxcopYI+pqqex3cJoPVZBHgyFwJQHb+3EVmA6aVWjEip+cMS3TpoAQnUoPC4x0iouEtIyLPWhrR2NiI0tJSFcAceeSRPb6Nz+dTL1F2ux0VFRWw2WzIzc1N4NWmJpcvqLIo0cFtMg5/WY29MxgRkTBUq/HGJpc6Dgo4WlDz7j/RsvBD9fqsvGJUnH0D8nb/YXCbKUuHScVWNYwto4caWBm6Nq3EiqI+pshaDXK8w+WARETDgd1uR15e3i6fvzVVoyIXKwoLC/s8LrrjjjsSeFXp03IswUhDR/eOxKebm6VY1omArDXu0OTyY02dA05/CJFQEI1fv4XaOU+plmNJkRQdcgpGzf4ZMk1W9fbZEqAUWTA6z9RjgDIyJxu7lfY+RVaOd2SsPZcDEhGRpjMq4XAYp512Gtra2vDll1/2+nbMqAyc0yeD235oObZ1FMu2dimWjS4PjAYyzs3LUfn6g/DWthfLmiumYvRZv4RlzG6dxzMTiyxq5P1gAhR5f1kMKMc7XA5IRDT82FMtoyK1KitXruwzSBFGo1G9UP+yKFKHEp2BIsWya6RYttmJjgYfqYfFJlke2OxBOLLzMY8Uy5af/BMUHTxbtRzLePoJRWY1LTazh43GcvQztdSqjm96IjUsEsRIMS2Pd4iIaFc0Eahcd911ePfdd/H5559j9OjRyb6ctCBZE2k5jmZR6uxeLKtxdCuWbXD4VDePJxDu+Zjn4Nkon/UT6K35fS4MlHBDjn6mllqQm53Va3uxBCicHktERAOR1GcNOXX6+c9/jjfeeAPz5s3D+PHjk3k5aUFmnMi4+7aOlmO3P4TlNXbUOLzdCmrlmEfqUXZ5zJMhQUi26uTZsUVYLQrMN6ki2Z62E7P+hIiIhkqf7OOeF154AW+99RZycnJQV1en7pczK5mrQgPT6PSp3TvScizHPhubXVhT7+xsQZYgRqbNSkePDEoJ+dzqmKfp67d6POYZmWtUs1AsxsydMihjJEAp7TlAYf0JERGlRTFtbzUKTz/9NC677LKYFuOkM2kxlo3GTn/7sU6z06/289h8wR6nygrnpmXY9vK98DfXqNvqmOfkK9Uxj+zPkWFsOx7TyN+WDGjbrTSnxyMcWTAo8096q08hIiJKqWJajTQcpSzJmtQ5fKhzeNUkWV8wjFV1jvaMSYdWVwCr6h1wdAQtkkWp/eBfaPzydRXBZBWMwNhzf4ucKfurfTzTiq0o2GEfjzriyTNhSi/BS4HJoLIvJk6PJSKiGGPhQIqSrcWyRNAfCquAb0uzRxXG+jtmokiWRTp86uw/tHLb1nyHytfuR6C1Xt0uOuhkjDr9WhXRTi2xqHH3OwYhYwvMKrvS0/GPTJmVAIXbi4mIKF4YqKQYXzCkimXtHRmSFlcAS2t/WCDY3m7swpYWN0IdPcgBZxuq33oErYs/UbcNBSNQ8aMbMGKvQ1UNSlkP4+6lzXj3ETmw7pBBkQJZqT2RSbOGHbp/iIiIYo2BSooe88genpU7HPPU2rxY1+hU7cZCMi2tiz5G1VuPIOS2QyazlRxxNsad8mNMLS9RHTs7Dmsrk0FtI3aegyIBihTIyo6eLBbIEhFRgjBQSQGSLanqMhNFpsxKLcoPk2aDWNPgUFuOo3zNNaj879/hWP+9up1dNhETLvgt9tp3fzWsTbdDrCEZEimSLbT0HKCMzDGyg4eIiBKOgYqGeQIhNbQtWggrgciyGhtaOo55vIEw1jc6VUtyVDjgQ/1nL6L+s+cRCQaQoc9C+YmX4ZAzL8fEEXnQ7zBNtrcARSbQSgePvHCDMRERJQsDFQ0KdYy+l7koXY95trW61W0Zhb+5RepQPJ11KMK25ltUvfFQZ8uxdPIcfPnN2Gf33XaqJ5EpsTKobccAJVufqQa0SaGsjgEKERElGQMVjWlytQ9tC3YEIF2PeaSbW163odEJb/CHjce+llpUv/kIbKu+Urezcouxx/nX46hZp8O8w0C23mpQZMS9ZE/yOAOFiIg0hIGKhjYcyzGPOxDqrEtZVmNHs9vfOQ9F2o1tHaPxRTjoR8O8l1H3yXOIBHyALhNjjjsfJ156HUoK8/q1LFBG3Ev9CUfcExGRFvHZSQPtxlVt3s7dPNGhbdFjHo8/hLWN3eehCPvaBeqYx9dUpW7nTd4XJ1z9e0yZNn2XywKjM1Ckg2fH/T1ERERawkAlSaS2RFqN6x3tdSjSfryp2Y21DU4EwuHOOpTNzR6Eu0zw9bc1qJkobcs/V7ezcotwyCU34rCTTu9WUzK6h1H3nIFCRESphoGKBupQ6uxeLK91qF09vdWhRMJhtTyw5v0nEPZ51DHP1JnnYfYVv0S21drtiGfaCCvydsiglFiNKGOLMRERpRgGKgnk8LbXoXiC7XUoUm+ystaBeqevc8qszEOxe9vbkaM8dVtR+erf4Nq6Ut0unLgnTvvlHSifOK1bF8/0HYpko0c8MnmWGRQiIkpFDFSSUIfi9oewpt6B7W0edewjhbRy5NPobC+c7VosW//p8+olEgoi02jGUZf9CgefegEyOia2lViMmD4iB0U7tBlLRkWOf1iDQkREqYyBSpzrUGrtXjR0zEMJBCNqxL3s4glFImo+yvpGFyptHqg36MK5ZSUqX70P3vpt6vb4A47C7J/fhtySMnW70JSF6SNzVEtxV+asTFVAu+OWYyIiolTEZ7M4kB07TS6/GtomdShSKCvD2dY2tM9DkcWBW1pcqni268A2EfK6UPP+k6oeRQpWTHmFOOmaP2Da4SciIyMDeUY9dhuRg/K87G7vl6XTYVReNooshgR/tURERPHDQCXGAUqLO6CyKNE9PDU2r2o3dviDnYsDpd1Yxt/vyLbyK1S+/ncEbE3q9l4nnIXjfvJrmHLyYcmSAMWKinzZdPxDd09mRoZqM5ZOHk6SJSKidMNAJU4BiuzlWVFrR1PHwDZZHLi6wYG2LosDowL2ZlS9+TDals1Tt/PLKjDr53/E+H0OhVGvw7SSHIwvNHULRCRAkWMfCVK4i4eIiNIVA5UhBigyOVaGsUUDFOnsWV3vQLW9fVGgNxDC+gZX5+0d379lwQeofucfCHmcyNBl4uCzLsMR/3MNTCYzJpdYMLnY2m2RoAQoJdb2WShsNSYionTHQGWQWtx+dawTDVBUJ0+DA9tb2zt5gjKwrbl9cWDXgW1RMlF2+6v3w7lxsbo9ctJ0nHz9nSifNB3jCsyqDkWyKVHcZkxERMMRA5UBsnsDaiBbdCePdO6sa5QJsu2dPJEwUGXzqG4ef0cQ05W0GTd8/l/UffgUwgE/9MZsHHnRdTjojEtQUWDF7iNyYO3SsWPI1KnsiUyUZQ0KERENNwxU+snlC6rjG4evvShWRtxvanFhXYNLjbwXMgdFOnucvvYgZkfu6g2oksFtlevU7XH7HKJqUaZNnqxmoRSYf5iFYszUqUFtheasbsWzREREwwkDlV2QGhPJoESHtUldybZWj9pk7OnIqkjwsrbeqVqSexIO+FD/0bOon/cSIuEQsq25OO4nv8WRp52LvcryVM1J1yOespxsdR8DFCIiGu4YqPRCjnRkDorUokQ6AhQJWNbUOztbjaXFWHbyVNl2LpSNcm5ejppX74OroVLdnnb4TJx63W04ZPoEjOnSaswuHiIiop0xUNlBIBRWG40bXf7OItjqtvYMir3j2EcKZbdIoWyrZ6eBbV3H37d8/AwqP31RDW6zFpbg5Gtvw2mnn646eTI7Onlko3GJxYCRXBhIRES0EwYqXY54JECRduNo6CFdPbKTx9YRoEihrOzn2dDkUgFNb8INW7H9pbvRum29ur33zLPwk9/+EftNHNWtk0cWBso02SwGKERERD0a9oGKFMnWOXydNSiizu7F6gYn2jzRupT2+9Y1OeHx9x6gZEQiCC16Eytf/QdCwQBMuQW48KZ7cNG5Z3fr5Mkx6lGRb4KJCwOJiIj6NGwDFZsnoAIUZ0e9iZDlgavrHGjpCFBEiyugNhvbugQyPSkI2rDhuT+jcsUCdXvqwUfj1vsexrTxo7t18ozONyHf1H3TMREREfVsWAUqshxQjnYanH54gz+0EDe7AmqabKPL13mfTJiVAKW3Tp6ovOws6Nd/ji/+7274XA5kGU249Ne348orr0Rmx5GO1KGUyT6eHCM7eYiIiAZAP1w6eCRbIkGKbDOOkn08EqDUO38IUDz+EDY09jzyviupNRlrCmP5c3/Gms/fV/eN330f3PPwE5g0eXLn2xWYstQxD+tQiIiIBi6tAxXJikiA0rX+JHrss7reiVqHt1sws7HJjcq2nkfeR0l2ZEKRCbrKFXj/zt/B0VwPXWYmLr72Blz9q99Cr9d3HvNIgJLHYx4iIqJB06frosAGhx+eLsc7QupM1tQ5UdMlQFGtxi3tO3l6azWOKss1YmKeHt++8DC+f/NZdV/52Am4++EnsMe++6vbcrAzMidbtRtz5D0REdHQpF2gUmv3dcuURI941jV0D1Ck1Xhrqxubmt19thpH61Cmj7DCV7sRL971WzRt36TuP/uiK/DLW++EyWxRt3M7unmy2c1DREQUE2kXqEQ6p6AAzbJ7p9HZrQZFTnVkwuyGJqeaLNuXbL0OU0qtGGnJwnevP4XPn3sY4WAQhcWluO1/H8bhx85Ub5elk2OebBSYfxiFT0REREOXdoGKUDNPGl3qCKirBocP6xqdvS4N7FqHMr7QhIlFFtgbKvH8nbegas0S9bqjT5yN39/7AAqKitUxj3TyyG4eHvMQERHFXtoFKivrHPh6W2u3+1plFkqTE23uvmehCKktmVZqRXaWDks+eAWf/t99CHjdsFit+M2df8XsH52vWoxlaNsYHvMQERHFVdoFKlIc27XrRzIojc6+Z6EIq1Gv6lCKLAY4WxrxygN/wKaFX6jX7X/o4fjj/Y+ibPQYGGRoWx6PeYiIiBIh7QIV4faF1Lj7OvsPtSm90esyMKXEqrIjGTpgzRdz8OGjd8Jtb4PBaMR1N9+O86/4GTJ1Oh7zEBERJVjaBSprGhyYv6VZqmp3STp0ppZYkKXXwe9149N//gVLPvyvet20PffGnQ88jglTpqmuHymWNep5zENERJRIaReoqEWCuwhSZNfO9BE5yDO1f/kNW9bj3ft+jbqtG1X9yRU/vxFX/vK3sGQbObSNiIgoidIuUOmL1JdMLbViVF42oit31s97G28/+Ef4fV4Ul47Enx5+AgcddiR38xAREWnA8AhUMoCx+WZMLjF37tzJCIew+MUH8cHz/6duzzjmeNzx98cwcXQ5RudnczcPERGRBqR9oFJkNmC3kVbVThyVDz/+e+8NWPDFZ+r2lb+6Cdf/5haMLbSo7h8iIiLShrR9VjZl6dQ8lJG52Z33WbL0GGPw4PYrz8fm9WuRbTLjzr8/hssuPA8lVmNSr5eIiIiGQaAi7caTis2YWGSFruP0RrqJpxRbURC249oLzsb2zRtROrIc/3rxvzjxiIN5zENERKRRaReoHFCRj0CXLchFJgP2HZ0LT2sDrjrvNFRu3YyyURX44KOPsff0qUm9ViIiIhpmgUqG2sDTvihw9xE5GF9kQktTI352zqmo2rYFFWPHYv7cuRg/fnyyL5WIiIiGW6AiRuVmY+/yXLWHJxKJ4I4br1VBigQnc+fOxdixY5N9iURERDQcA5XdRkgB7Q+Fsa8/+y98PfcTZGdn45133mGQQkRElELSrorUqO+YkyJTais34v67/qBu33fffdh9992TfHVEREQ0rDMqIteoR0l2Bo48+Qr4fD6cfPLJuPbaa5N9WURERDTcA5URViP0mTrcfPPNWLFiBUpKSvDUU09xFD4REVEKSrujHwlSampq8OCDD6rbTz75JEaMGJHsyyIiIqJBSLtARdx9993wer047LDDcNpppyX7coiIiGiQ0i5Q2bZtG5544gn15z/96U888iEiIkphaReoSHASCARw7LHH4uijj0725RAREdEQpFWgsnHjRjz99NPqz3fddVeyL4eIiIiGKK0ClTvvvBOhUAgnnXQSZsyYkezLISIioiFKm0Bl/fr1eP7559WfmU0hIiJKD2kzR0XmpcjslO3bt+OAAw5I9uUQERFRDGREZGtfCrPb7cjLy4PNZkNubm6yL4eIiIhi+PydNkc/RERElH4YqBAREZFmMVAhIiIizWKgQkRERJrFQIWIiIg0SxOByqOPPopx48YhOzsbBx98MBYsWJDsSyIiIiINSHqg8vLLL+OGG27A7bffjsWLF2PvvffGiSeeiIaGhmRfGhEREQ33QOX+++/HlVdeicsvvxzTp0/H448/DrPZjKeeeirZl0ZERETDeTKt3+/HokWLcMstt3Tep9PpcPzxx+Obb77p8X18Pp96iZJBMdHBMURERJQaos/bu5o7m9RApampSS0RHDFiRLf75fbatWt7fJ977rkHd9xxx073V1RUxO06iYiIKD4cDoeaUJs2u34k+yI1LVFtbW0YO3as2vHT1xc6XKJTCdgqKyu5ToCPRzd8LLrj4/EDPhbd8fFI3GMhmRQJUsrLy/t8u6QGKsXFxcjMzER9fX23++X2yJEje3wfo9GoXnYkQcpw/6aKkseBj8UP+Hj8gI9Fd3w8fsDHojs+Hol5LPqTYEhqMa3BYMD++++PTz/9tPO+cDisbh966KHJvDQiIiLSgKQf/cgxzqWXXooDDjgABx10EB544AG4XC7VBURERETDW9IDlfPOOw+NjY247bbbUFdXh3322Qdz5szZqcC2N3IMJDNYejoOGm74WHTHx+MHfCy64+PxAz4W3fHx0N5jkRHZVV8QERER0XAd+EZERETUGwYqREREpFkMVIiIiEizGKgQERGRZqV0oPLoo49i3LhxyM7OxsEHH4wFCxYg1cmKgAMPPBA5OTkoLS3FGWecgXXr1nV7G6/Xi2uvvRZFRUWwWq04++yzdxqaJ5N6Z8+erRY8ysf5zW9+g2Aw2O1t5s2bh/32209VdE+aNAnPPPMMtOwvf/kLMjIy8Mtf/nLYPhbV1dW46KKL1NdrMpmw5557YuHChZ2vl9p46aArKytTr5e9WRs2bOj2MVpaWnDhhReqAU75+fn48Y9/DKfT2e1tli9fjiOOOEL9bMlkyr/+9a/QElm9ceutt2L8+PHq65w4cSLuuuuubjtD0vmx+Pzzz3HqqaeqiZ7yM/Hmm292e30iv/ZXX30V06ZNU28j34/vv/8+tPJYBAIB3HTTTeq6LBaLeptLLrkENTU1aflY9Od7o6urrrpKvY2MBdH04xFJUS+99FLEYDBEnnrqqciqVasiV155ZSQ/Pz9SX18fSWUnnnhi5Omnn46sXLkysnTp0sjJJ58cGTNmTMTpdHa+zVVXXRWpqKiIfPrpp5GFCxdGDjnkkMiMGTM6Xx8MBiN77LFH5Pjjj48sWbIk8v7770eKi4sjt9xyS+fbbN68OWI2myM33HBDZPXq1ZGHH344kpmZGZkzZ05EixYsWBAZN25cZK+99opcf/31w/KxaGlpiYwdOzZy2WWXRb777jt13R9++GFk48aNnW/zl7/8JZKXlxd58803I8uWLYucdtppkfHjx0c8Hk/n25x00kmRvffeO/Ltt99Gvvjii8ikSZMiF1xwQefrbTZbZMSIEZELL7xQfR+++OKLEZPJFPnnP/8Z0Yo///nPkaKiosi7774b2bJlS+TVV1+NWK3WyIMPPjgsHgv5Pv79738fef311yUyi7zxxhvdXp+or/2rr75SPyt//etf1c/OH/7wh0hWVlZkxYoVmngs2tra1M/+yy+/HFm7dm3km2++iRx00EGR/fffv9vHSJfHoj/fG1Hyevmay8vLI3//+981/XikbKAi32zXXntt5+1QKKQe8HvuuSeSThoaGtQ32/z58zt/8OQvW34xR61Zs0a9jfwQRr9RdTpdpK6urvNtHnvssUhubm7E5/Op27/97W8ju+++e7fPdd5556lASWscDkdk8uTJkY8//jhy1FFHdQYqw+2xuOmmmyKHH354r68Ph8ORkSNHRu67777O++QxMhqN6heJkF8Y8vh8//33nW/zwQcfRDIyMiLV1dXq9j/+8Y9IQUFB5+MT/dxTp06NaMXs2bMjV1xxRbf7zjrrLPWLc7g9Fjs+GSXyaz/33HPV30VXBx98cORnP/tZJBn6emLu+o8eebtt27al9WPR1+NRVVUVGTVqlAoy5B8/XQMVLT4eKXn04/f7sWjRIpXOjNLpdOr2N998g3Ris9nU/wsLC9X/5euWdGbXr11Sa2PGjOn82uX/kmbrOjTvxBNPVAumVq1a1fk2XT9G9G20+PjJ0Y4c3ex4vcPtsXj77bfVBOdzzjlHHWHtu+++ePLJJztfv2XLFjU0sevXIns05Fi06+MhqVz5OFHy9vLz891333W+zZFHHqlWXHR9POQIsrW1FVowY8YMtWpj/fr16vayZcvw5ZdfYtasWcPusdhRIr/2VPnZ2fF3qhx3yNc/HB+LcDiMiy++WB2B77777ju9XouPR0oGKk1NTeqMesfptXJbfkDThXxDST3GYYcdhj322EPdJ1+ffHNEf8h6+trl/z09NtHX9fU28gTu8XigFS+99BIWL16sand2NNwei82bN+Oxxx7D5MmT8eGHH+Lqq6/GL37xC/z73//u9vX09XMh/5cgpyu9Xq8C4YE8Zsl288034/zzz1eBaVZWlgra5GdFztWH22Oxo0R+7b29jVYfG6lpk5qVCy64oHPJ3nB7LO6991719cnvjp5o8fFI+gh96juTsHLlSvUvxeFIVotff/31+Pjjj1Ux1nAngav8K+fuu+9Wt+XJWb4/Hn/8cbUvazh55ZVX8Pzzz+OFF15Q/ypcunSpClSkgHC4PRbUP5J9Pffcc1WhsQT8w9GiRYvw4IMPqn/8SVYpVaRkRqW4uBiZmZk7dXfI7ZEjRyIdXHfddXj33Xcxd+5cjB49uvN++frk6Kutra3Xr13+39NjE31dX28j/8qQLgGt/FA1NDSobhyJ6OVl/vz5eOihh9SfJTofLo+FkA6O6dOnd7tvt912U11NXb+evn4u5P/ymHYlHVBS5T+QxyzZJG0dzarI0Z6ksn/1q191Zt6G02Oxo0R+7b29jdYem2iQsm3bNvUPn2g2Zbg9Fl988YX6WuV4PPo7VR6TG2+8UXXQavXxSMlARdL9+++/vzqj7vqvTbl96KGHIpVJtC9ByhtvvIHPPvtMtV92JV+3pLq7fu1yLihPVtGvXf6/YsWKbt9s0R/O6BOdvE3XjxF9Gy09fscdd5z6OuRfy9EXyShIej/65+HyWAg5AtyxVV1qNMaOHav+LN8r8kug69cix1dyrtz18ZDAToLAKPk+k58fqWGIvo20OMov966Px9SpU1FQUAAtcLvd6sy8K/nHi3wdw+2x2FEiv/ZU+NmJBinSnv3JJ5+o1v6uhtNjcfHFF6u24q6/UyULKYG/HCdr9vGIpHB7slSxP/PMM6pK+ac//alqT+7a3ZGKrr76atVWOG/evEhtbW3ni9vt7taSKy3Ln332mWrJPfTQQ9XLji25M2fOVC3O0mZbUlLSY0vub37zG9Up8+ijj2qyJXdHXbt+httjId0Ker1eteZu2LAh8vzzz6vrfu6557q1pcrPwVtvvRVZvnx55PTTT++xLXXfffdVLc5ffvml6qjq2nooHSLSenjxxRerrgD5WZPPk+yW3K4uvfRS1bUQbU+WVktpO5cOruHwWEgnnLTby4v8Gr///vvVn6OdLIn62qUFVb4n//a3v6mfndtvvz3hLbl9PRZ+v1+1Zo8ePVr9/Hf9ndq1YyVdHov+fG/saMeuHy0+HikbqAiZdyFPUjJPRdqVpec71ck3Vk8vMlslSn7ZXHPNNao9TL45zjzzTPWD19XWrVsjs2bNUr3t8gv8xhtvjAQCgW5vM3fu3Mg+++yjHr8JEyZ0+xypEqgMt8finXfeUYGXBOnTpk2LPPHEE91eL62pt956q/olIm9z3HHHRdatW9ftbZqbm9UvHZk7Im3al19+ufrl1pXM3pBWaPkYEhDIE5+W2O129X0gP//Z2dnq70xmR3R98knnx0K+X3v6PSEBXKK/9ldeeSUyZcoU9bMjbf7vvfdeRCuPhQSxvf1OlfdLt8eiP98b/QlUtPZ4ZMh/BptGIiIiIoqnlKxRISIiouGBgQoRERFpFgMVIiIi0iwGKkRERKRZDFSIiIhIsxioEBERkWYxUCEiIiLNYqBCREREmsVAhYhi5rLLLsMZZ5wBrXrzzTcxadIktRdIti0TkfZxMi0R9cuu1sLffvvtaoOx/ErJz89HMsh27YsuugiVlZU9vl42bl9++eX4xS9+gZycHPVCRNqmT/YFEFFqqK2t7fzzyy+/jNtuu63bNmer1apekumtt97Cqaee2uPrnE6n2qJ94oknqo2xRJQaePRDRP0ycuTIzpe8vDyVYel6nwQpOx79HH300fj5z3+ujllk/btkNJ588km4XC6V2ZCMhhzFfPDBB90+18qVKzFr1iz1MeV9ZD19U1PTLq/x7bffxmmnnbbT/fPmzevMnhx77LHq2uW+bdu2qcBGrs1isWD33XfH+++/H5PHi4hig4EKEcXVv//9bxQXF2PBggUqaLn66qtxzjnnYMaMGVi8eDFmzpypAhG3263evq2tTQUT++67LxYuXIg5c+agvr4e5557bp+fZ9WqVSpjIu+7I/lc0ezPa6+9prJDct+1114Ln8+Hzz//HCtWrMC9996b9KwQEXXHox8iiqu9994bf/jDH9Sfb7nlFvzlL39RgcuVV16p7pMjpMceewzLly/HIYccgkceeUQFKXfffXfnx3jqqadQUVGB9evXY8qUKb0e+8ixjsFg2Ol1cl9paan6c2FhocoAie3bt+Pss8/GnnvuqW5PmDAhDo8AEQ0FMypEFFd77bVX55+l26aoqKgzMBBytCMkGyKWLVuGuXPndta8yMu0adPU6zZt2tTr55FApadjn75IUe2f/vQnHHbYYaoYWIIlItIWBipEFFdZWVndbkt9SNf7ot1E4XC4s+hV6kaWLl3a7WXDhg048sgje/wccpSzZMkSzJ49e0DX9pOf/ASbN29WR09y9HPAAQfg4YcfHsRXSUTxwkCFiDRlv/32U/Um48aNU4W2XV+k4LUn77zzjqo5kWOdgZIjpauuugqvv/46brzxRlXsS0TawUCFiDRFClxbWlpwwQUX4Pvvv1fHPR9++KHqEgqFQgPq9tkV6UaSj71lyxZV2CtHTrvttlsMvgoiihUGKkSkKTLj5KuvvlJBiXQEST2LBBQyRE6n2/lXlrQ6f/rpp4MKVORzSGAkwclJJ52kCnX/8Y9/xOgrIaJY4GRaIkppcmQjXUWrV69O9qUQURwwo0JEKU26gmT+CRGlJ2ZUiIiISLOYUSEiIiLNYqBCREREmsVAhYiIiDSLgQoRERFpFgMVIiIi0iwGKkRERKRZDFSIiIhIsxioEBERkWYxUCEiIiJo1f8DTA/hTS9aUQIAAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "credible_intervals = [[16, 84], [2.5, 97.5], [0.15, 99.85]]\n", "alpha = [0.6, 0.4, 0.2]\n", "\n", "fig, ax = plt.subplots()\n", "ax.plot(diff.dt.values, diff.msd.values, 'k-')\n", "for i, ci in enumerate(credible_intervals):\n", " ax.fill_between(diff.dt.values,\n", " *np.percentile(diff.distributions, ci, axis=1),\n", " alpha=alpha[i],\n", " color='#0173B2',\n", " lw=0)\n", "ax.set_xlabel(f'Time / {diff.dt.unit}')\n", "ax.set_ylabel(f'MSD / {diff.msd.unit}')\n", "ax.set_xlim(0, None)\n", "ax.set_ylim(0, None)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, the joint posterior probability distribution for the diffusion coefficient and intercept can be visualised with the `corner` library. " ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "from corner import corner" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "corner(np.array([i.values for i in diff.flatchain.values()]).T, \n", " labels=['/'.join([k, str(v.unit)]) for k, v in diff.flatchain.items()])\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "kinisi-dev", "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": "3.11.13" } }, "nbformat": 4, "nbformat_minor": 4 }