{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(factor_analysis)=\n",
    "# Factor analysis\n",
    "\n",
    ":::{post} 19 Mar, 2022\n",
    ":tags: factor analysis, matrix factorization, PCA \n",
    ":category: advanced, how-to\n",
    ":author: Chris Hartl,  Christopher Krapu, Oriol Abril-Pla, Erik Werner\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Factor analysis is a widely used probabilistic model for identifying low-rank structure in multivariate data as encoded in latent variables. It is very closely related to principal components analysis, and differs only in the prior distributions assumed for these latent variables. It is also a good example of a linear Gaussian model as it can be described entirely as a linear transformation of underlying Gaussian variates. For a high-level view of how factor analysis relates to other models, you can check out [this diagram](https://www.cs.ubc.ca/~murphyk/Bayes/Figures/gmka.gif) originally published by Ghahramani and Roweis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{include} ../extra_installs.md\n",
    ":::"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on PyMC v5.28.0+58.gf58491a3\n"
     ]
    }
   ],
   "source": [
    "import arviz as az\n",
    "import numpy as np\n",
    "import pymc as pm\n",
    "import pytensor.tensor as pt\n",
    "import scipy as sp\n",
    "import seaborn as sns\n",
    "import xarray as xr\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "from numpy.random import default_rng\n",
    "from xarray_einstats import linalg\n",
    "from xarray_einstats.stats import XrContinuousRV\n",
    "\n",
    "print(f\"Running on PyMC v{pm.__version__}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format = 'retina'\n",
    "az.style.use(\"arviz-variat\")\n",
    "\n",
    "np.set_printoptions(precision=3, suppress=True)\n",
    "RANDOM_SEED = 31415\n",
    "rng = default_rng(RANDOM_SEED)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulated data generation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To work through a few examples, we'll first generate some data. The data will not follow the exact generative process assumed by the factor analysis model, as the latent variates will not be Gaussian. We'll assume that we have an observed data set with $N$ rows and $d$ columns which are actually a noisy linear function of $k_{true}$ latent variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "n = 250\n",
    "k_true = 4\n",
    "d = 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next code cell generates the data via creating latent variable arrays `M` and linear transformation `Q`. Then, the matrix product $QM$ is perturbed with additive Gaussian noise controlled by the variance parameter `err_sd`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "err_sd = 2\n",
    "M = rng.binomial(1, 0.25, size=(k_true, n))\n",
    "Q = np.hstack([rng.exponential(2 * k_true - k, size=(d, 1)) for k in range(k_true)]) * rng.binomial(\n",
    "    1, 0.75, size=(d, k_true)\n",
    ")\n",
    "Y = np.round(1000 * Q @ M + rng.standard_normal(size=(d, n)) * err_sd) / 1000"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because of the way we have generated the data, the covariance matrix expressing correlations between columns of $Y$ will be equal to $QQ^T$. The fundamental assumption of PCA and factor analysis is that $QQ^T$ is not full rank. We can see hints of this if we plot the covariance matrix:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 623,
       "width": 821
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4, 3))\n",
    "sns.heatmap(np.corrcoef(Y));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you squint long enough, you may be able to glimpse a few places where distinct columns are likely linear functions of each other."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model\n",
    "Probabilistic PCA (PPCA) and factor analysis (FA) are a common source of topics on [PyMC Discourse](https://discourse.pymc.io/). The posts linked below handle different aspects of the problem including:\n",
    "* [Minibatched FA for large datasets](https://discourse.pymc.io/t/large-scale-factor-analysis-with-minibatch-advi/246)\n",
    "* [Handling missing data in FA](https://discourse.pymc.io/t/dealing-with-missing-data/252)\n",
    "* [Identifiability in FA / PPCA](https://discourse.pymc.io/t/unique-solution-for-probabilistic-pca/1324/14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Direct implementation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model for factor analysis is the probabilistic matrix factorization\n",
    "\n",
    "$X_{(d,n)}|W_{(d,k)}, F_{(k,n)} \\sim \\mathcal{N}(WF, \\Psi)$\n",
    "\n",
    "with $\\Psi$ a diagonal matrix. Subscripts denote the dimensionality of the matrices. Probabilistic PCA is a variant that sets $\\Psi = \\sigma^2 I$. A basic implementation (taken from [this gist](https://gist.github.com/twiecki/c95578a6539d2098be2d83575e3d15fe)) is shown in the next cell. Unfortunately, it has undesirable properties for model fitting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [W, F, sigma]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4512bea23b5248ce8f14a74a7bebe5f6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 4 chains for 2_000 tune and 1_000 draw iterations (8_000 + 4_000 draws total) took 12 seconds.\n",
      "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n",
      "The effective sample size per chain is smaller than 100 for some parameters.  A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n"
     ]
    }
   ],
   "source": [
    "k = 2\n",
    "\n",
    "coords = {\"latent_columns\": np.arange(k), \"rows\": np.arange(n), \"observed_columns\": np.arange(d)}\n",
    "\n",
    "with pm.Model(coords=coords) as PPCA:\n",
    "    W = pm.Normal(\"W\", dims=(\"observed_columns\", \"latent_columns\"))\n",
    "    F = pm.Normal(\"F\", dims=(\"latent_columns\", \"rows\"))\n",
    "    sigma = pm.HalfNormal(\"sigma\", 1.0)\n",
    "    X = pm.Normal(\"X\", mu=W @ F, sigma=sigma, observed=Y, dims=(\"observed_columns\", \"rows\"))\n",
    "\n",
    "    trace = pm.sample(tune=2000, random_seed=rng)  # target_accept=0.9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this point, there are already several warnings regarding failed convergence checks. We can see further problems in the trace plot below. This plot shows the path taken by each sampler chain for a single entry in the matrix $W$ as well as the average evaluated over samples for each chain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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trT2T1jnRO4gvvHMUv90w32vUOxROj4oXdESoh8Y8tl6qa8fvjzUG3OZUX+QDFYE09A9j+Ox5PdaA4FIkDHs8qOkZhCQESuJtMEfxh9VDDVcf6Az9HDHkDhy0+kft5FDyOT/dW4vVmUnIjZ38gXBV03Coqx8Oj4ocuxWZNkvI4wSAQbcHz59uQ9uwEwlmBVfnpyHBYsx/fLe1pQe9Lu8/C48GvNrQERXh6lfrfU8u0ulwYW97Ly7KSJy6ARERERmgbciJv51owtHuASiSwJV5qbg0NxWKpC/G1+Nw4UBnP5oHHahOjUNpvG3KY9FtQ0585LX94ybGeeZ0G9ZnJ+OHK8ogMV5NRFFOU1V4Nm2F69V3RoJ7JgXysgUwXX0JRPz410IiKQFak+/XiQCgNbUAYYSrPfuO+F2uHj0JnA1Xax4PnL/7O1R/IeBp5tmxH5gQrjYiOgsA0DS4nngWIj0ZUlkx3C+/bchu3c+/Hna0OmT9Ov4+4S9oG8bkixFnsUAU5gJ+7q+ayz0S9f3Dk1CP107d2KKQ+7nX4Nl5QPf6Wmd3UPvXdIarg91vONT2Trjf2BZ4RQOizuqBY36Xe47UQIpQuNr1wqZJ0epztNp6aHWNEAW5ETl2ONRDx4GhwJMGR5LW3RvxYzBcbRwhSTC//0a4X34bni27oHUF/v2J5MTIDywYZ/9eJpUX+53AxPyhWyAvmjuVIzOEMM/iD/hbzJAKcqZ7FIaR55XrDlcLa3h/j6Lppay9CK6/PRvUNoLhaiIiIiIiIiIiIiIyiIgrxMgn7nRMOq2HJXHyMSxeYtZ+SMnVutYTiVVB7ZeIiIiIiIiIiIiIiIhmvugs/5FuqqpCMuBDw4H87W9/w29/+1u/62RmZuKaa66J+FgoPL86eCbsP2cPeVRsbukGADyvI5R6zne2n8B3L5qDL7xzxPAQapxJRnqMGUIIlCfaR2///aXVeK2hA4c6+yEJgUtzU1CZNP1BSPJveUYinjjZEtQ2/7x68aSgbUm8zchhGWZ+ciz2d/Ybvl8JwI9XVQQdrQaADTkp+PWhesPHBAADXoK1bWNCa9GuR2e4end7Lz795iE41cBn2dq+IWxt6cYlOSnhDg+apuFrW/3HP845Fw9++FAdHjms7/d9ehrD1Ue7B3DfnlPYdzaqblNk3FScgbvn5UOOoijf32ua8evD9aNB6DSrCZ+Ym49rC9OneWTehRquliDQNOBAlj34D+LrCVf7owLY2tKN3NiRiE1NzyD+eKwRz51pG7eeLIDL81Lx1cXFsMrBh+H3d/Thc+8cGRes/+XBOnz/ojlYm50c1vcAAH8+7j8W/4djjfjk/IKwjxOuN5q6/C7/Z20rw9VERD5omoZOhwtOj4Z0mzmqrlkuZDU9g/jo6wcwOOaa5O3mbjx/ph33raoIGK9+q6kL/7XzBLoc568RFqTE4f7VFVM6scrXtx4bF60+5/XGTvzhWCM+UD57QlFENDu5n3sN7hffPH+Dyw3POzuhnmmE5d4PQljGvt4M/P6K2tgyEl/99xtQT9UBsgSpvASmK9ZCxNoDbu9+9lW/yz27DwIfumXk39v3RXW0GgAwcD7ErLncECYFmsPA9+A0wLNtL7TuXnh26Y/8+tydwwnP/qMGDCyC/L23EKWTqwEjEUWhBBhf/wAcD/0OWqvvyasuBGpTa9Ahdq2jW9++65vg3rIb6olafTv2EWkNhtrZDfcLm+DZsQ9weyCy0qFcuQ7K4nnn16mth+NXfx53zvDJgMn5An3/7n+8BHX/UUgFOVA2rIRIiA/7mMDZyRICnLc9R05CisZwdW1k/lYTDK1V/99/Q2Zj/NNIwmSCaeN6KFddDNeTL8Czaav/DQI9T0wxcfZ5VcRYYf7wrXD+3x+BCX9vk9csg7Rwhn4IPgrD1fKqJdC6eqAePhHefhbNnVVhbqmyFFJxHtST/ifHFimJEHH8705mMnn5opHXeaf0T4TOSReIiIiIiIiIiIiIyChCtkLEl0LrPW7M/syJk280BfH5QksqpPx3jewrfSW01s0+V5Uy1gQ5OiIiIiIiIiIiIiIiIprpouvTaBS0j3/849iwYQNuvvlmmEyR+TDYH/7wB/zoRz8KuN7dd98dsTGQMd5p7sKjRxqm7fgv13fg5frIRBDWZiVDeAmCyULgstxUXJabGpHjUmQsTI2HhJFQqV7eYmFL0uOhCAG3ZtDs4wYoT7TjN5fMh0fT8MV3juDt5u6w97k0LR4FcTG4rTQL+XGhfViyKC4GcxJsON6jI1YRpAHX5GBt+/DsClcPuDz40jtHdEWrz9nd3mtIuPpE7yDeDBCZPWfIreJM3xAe1RmtBoADnf042TuI4ikOwTcODOPetw6NiwMOuj34w7FGDLk9+OKi4ikdjy/PnW7D/+w5Ne62tmEXvrezBnFmBRcbEDs22tifaTDeau7CWy90oSzBhrvn5WNVZpLubQfDDFcDI1Hnm0oycbR7AJ/YdNDrPj0a8MKZdrxwph3XF6ZjXXYyVmcmer1GmKjb4cIXNx8dF60GAIdHxde3HccfLq1GQYjn2HMicY6dDltbe6Z7CEQEwKNp2NTYicNjJukpSwwcaKTI2dfRh5/vPz066UaWzYIPVeTg+qKMiB/7TN8QHjlcj9cbO+FSNSxMjcOHK3KxND0h4seOdpqm4Uubj3i9dtjc0o0/HmvEByt8B5/P9A3hS5uPwDPhUn9vRx++8M4R/HLd3NFrjTN9Q2gadCDerKAi0a7rGkSvlkEH9p69b3nzcl07w9VEFNXUto7x0eoxtPomuN/aAdOlq8/fqOO9I8+W3fDsPTIuvuppaoN6+ATM//E+SEnGPQ969h0xbF+R5Prny1BrTo/E1yxmwMhwNUYC3p7t+wzZl9rYAjhDm1xrqgh/E8dGWfBzHKslcFjbo17w0WoAcP3zJUAN5i8RgNYZ+L1Y95vb4Xr82eD2G+bjVesfgPN/fw+trfP8bU2tcD32BNz/fAnmez8MkRAH5+//ri9aDQBhTp6sufS9D6mePAP15Bm4t+yC5XN3QcoI/2962plGYND/pIxae6ff5dPFc7x2uocAteZMxI8h+N8VRIQQAnJpYeBwdRT97RTAuOdVuaIElq99Eu5NW6C1dwFmE5SViyFVlhr6OntKRWHYWaQlQ1l3ERw6wtXKtRvgeXsHtK7e8fvIzYLphisiNcRpIWQZ5o/dAdffnoFn10Gf68nLFkzhqCgShEmB+dMfhPvFN+E5fAKanokjlOAnzSUiIiIiIiIiIiIi8kXKvRKeQ8aEq2Ge/PkeISTAlgUMNvndVGSshZx3DYR5ZKJpKXUJPL7C1XIMROIMnWyWiIiIiIiIiIiIiIiIQhbFn6omPVpbW/Gd73wHv/jFL/C+970PN910E1JSwo9gAkBXVxe+853v4IUXXgi4bnV1NW699VZDjkuR8/yZtukeQsRcmccw9WwSb1awPicZrzaEFw2INSn4wsIi/Gj3SYNGFr6KszFBWQjcv7oSjx6ux2NH6uEIIng80UNrq8L+oLYQAv+9ohw3/nt3WPvxZsBLIG4mhasnRmyBkQhvff8w8uOssMoytrd2o9dLoNufv55oxi0lmciLDS+E+7bOaDUADLk9ePpUC4K9t33ktf3458YliDNP3aXjX443+QwsP3GyBR+syEVajDkixz7WPYADnf2QBbAmKwkpVu/H0TQNvzrkO+Dxq4NnojRcHV4U6ljPID779hH8ZFUF1mTpi1cPeYILAHnTNOgAAPzXjhO6Qtj/qG3FP2pbsTYrCf+9shzyhPOkR9OgaYAkAEkIvN3c5fNn4/CoeKm+HR+tzAv7+4h2mp5gSbRFTWjaaZqGfR19ONM/DIssYW1WEmIuoIBDn9ONp0+14M2mLqiahqXpCbilJNPn84cRep1u/McbB8cF8R872oCbizPwhYVFMzfiM4PV9Azi3rcOYdB9/jmvadCBH+w6CVUD3l0cuXh104ADH990EJ1jnsd2tvViT/th3LeqPKjJJmaj4z2DqB9w+Fy+qbHDb7j6kSP1k6LV5+xu78OpviEkWUy4b8+pcZN1FcRa8cMV5ShJMGYCmNcb/b8+PtYziGGPB1b5wjn/EtHMoh475X/5oePApauhdnRBa2qF1qVjwhxV8xpf1Vra4f73Jphve1eow528zwb/H+CKFu6X3zr/hcHRaqNpbdEfTdZcft5DieKfr7BapiWsramq/9h3lNEGh6AeDP4DoGpHt//ldU1BR6sBQN17GJrHAxHk9Zza2Q3Ppq1wv+bjQ6MAtM4eOL79AORl1SMRWL2GHdB6+yDi44Iak6ZpcD//OtwvbApqOww54Pzt47B+5e7gtjt33L4BeI6dhNbeOTKxQQBqY0tIx4m4oeHpHgHNcFJxfsB1RHrKyJvjYfx90lAT3kuU0lNgvuWaaRqM8YQ5cu8ThkpKSx6Z7ELXuilQvnYP3Ju2jkyQ4vZAnl8B+aIFI9cds4ywxcD8wVugXn0JHD/8BTDhb1zS/HIoV108TaMjIwlZhmnjepg2rofnwFE4H/6L/w2i5ZxJRERERERERERERLOCSKqGSF0KrX1H+Ps6G52eSEpZBNVXuFoyQVl+P4RsHX9z8gJoOVdAbXhxwkFkyBWfgDDZwx4vERERERERERERERERzSwMV88Sra2t+MlPfoKf/exnWLt2LS699FKsW7cOGRnBh5EaGxvx2GOP4fHHH8fg4OTow0QJCQn4yU9+AmkGfRj9QlXTE/j3ORMlWUxYmp4w3cMgg31jSSnahw9jX0dfWPt5d3EGHB4VD+yrNWZgYbJN+OD1hytzcX1ROra39sCjaViYEo9XGzrw0AHfMdyJjAoT5sRa8c0lJfjezhpD9nfOwISgs0tVfQaJo1GP83ygZtDtwQ921mBTYyecqgYJwKW5KWgZCi1Uc88bh/DIJfPDCjA3D+o/9pBHxZ4QHlODbhVf3nIUblVDj9ONZKsJt5ZkYn12csTCmFtauv0uf6e5C9cXGRuAdHpUfGPbMWxqPB9vMUkCd1Xl4QPlk2OGDQMOvz//mt4h9DhcSLCYDB1nIKqmYWtLN452DyLWJGN9djJSx9zHwg1Xn/P5d47gQxU5uKsqb1IUGgDcqoq/HG/CpsZO7O/sN+SYDf3DOBbk9cybTV147EgDPlKZC2AkMPvokXo8faoFg24VKVYTbi/NwoEAY3y2tu2CCFe7dHzoPvwMOUVSbe8Qfn24Dm80dsKlaliYGocPV+TioozEiByv2+HCV7Ycxe72888vcSYZ31hSgvU5xkyqFM16nC587PWDqO0bGr1tf2c/nqltxa/Xz0eWPTLhlm9tOz4uWn3OEydbUJJgw43FmRE5Lvn2y4NnxkWrx/rFgdO4rjANSoTeN3nowOlx0epzPJqG/9l9Ck9dlXhBx8xfrGv3u/xQ1wA0TfP6M/JoGl4443/77a092Nzcjc0Trl9P9w/jnjcP4rEN1ci0hX8uONo9EHCdO1/ai0cvmT/l159ERHr4C6oCgHq8Fs4//wOebXsMiYF5dh+EdvPVEAbFe7WuXkP2Q+dpLf6fY6PCwJDPGLMWzWFZqxnCNPV/Ana//BaUdctnTMBS6+wObbsO/+Fn9/a9Ie0XAFy/fxKmD9ykOwDuOXYKzl/+YVJQ0+f62/cFPabhbz0A5cp1MG1cr3sb9z9fhvuVt4M+FgBojS1QO7shJSfqW1/ToNbWw/X4s9Dqm4M6lkj0/sHd6aQ5HAHvY7OByM+e7iHMaiLODlGQA+10g8915NICuGQZUEP/e51UVgStp8+Y5/RpmHBhSpmj73W6SE2GiLEGXhEArBYIiwWmK9ZFdlBRRkpPhfW+r0PdfxSeYycBRYE8dw6ksuIL+r22WUvP4yHWmAnqiIiIiIiIiIiIiIiAkc8DyoU3wm1AuBpyjNebpZwroHbsAQYbJ29SfNukaPXodoU3QyRVQ215A/A4ICypkHIuhbCmhT9WIiIiIiIiIiIiIiIimnFm+ae/LjxutxuvvfYaXnvtNQBAWloaKisrUVVVhaKiIiQkJCAuLg5xcXGwWq3o7e1FT08P2tvbsXfvXmzfvh0nTpyApukLQ5jNZjzwwAPIz8+P5LdFBimMs6GmdyjwijPMbaWZUCR+MHC2sZtkPHzxXGxp6cZn3j4S1r5um5MFqyLhh7tO6lo/RpbwX8vL8Pl3/B/35uIMJFhM2N3ei7q+IbQNB47BxpsnP/WmWM24Kv/8f7gxMW49lVLDCCj7MugeH67u0PFz+vHKcrzW0ImX6tt1RVQjqdc58qF9p0fF594+PC7MqQJ4qb4j5H23DDnxyOF6fGVxccj7CCZC3O1w4WCIAeGdbecDTbV9Q9jV1ou7KnPx0SrjQ76apuFMv//4z+M1zYaHq3+0++S4aDUwEvH9xYEzyLRZcGVe6rhl21q7A+7zSPcAlkcoFutN57ALn3zz4Ljn+5/vP42PVubivWXZEEIYFq4GgN8eaUD7sBPfWFI67vYhtwdf2XIUW1p6DDsWALzR1BnSdi/WteMjlblwqyMR9rH3545hl67JAhoHHSEde6YZmnDO9kbnSwWaBk0DDnzijQPjJojY3d6Hz7x9GPevqsSKzERDj6dqGr629di450YA6HN58I1tx/HwxRZUJccaesxo88De2nHR6nPahl343s4T+MW6uYYfs2PYOSmQO9Yzp9sYrp5iHk0b99wyUa/Lg/0d/ViUZnwUza1q2Nzc7XN506ADR7oHUJk0ux+L/hzuCnz961I1mOXJ7yuc0DFhxv17a30u63K48dzpNnz47AQa3sbWNuREvFnBgpQ4v9EjbxOFTFQ/4MBXtx7D/66tCjqg1DzowI7WHjQPOVCVFIslaQmwyJykjoiMo7UHjnB6tuw27oBDDjh+/DDgcgEaIFdXQLlsNUTcyHOi5tA/EZimcvqeSFCb26Z7CIFpGjA4BMTaJy8bjOK/tSgKMB3h6mdehWfvYVjueT+EzfsHIqNJMOeBcfoHoTmcEBbv76V73tkZ8pg8uw9CKs6DcvGKgOtqQ8NwPvJX3dHqkKkq3M+/DpEQB2XVksmLm9vgeuYVaE2tgCRBmlMIz1vhfahW3XcE0nodPwOPB87HnoC693BoBxqKvvf7tKYZcG40gFxRMt1DmPVMV10M56/+7HWZVFECkRAPyDLgCjFcHWeH6V2Xw/m3Z8IY5XlGTTYStaItXC1LEKlJ+oPhM2RSikgQsgx5YRXkhVXTPRSKMCknE5AkwM/rP7mE/20cERERERERERERERlMMWbSRGH3/t+pCsUOZd7noNY9C7V1C6C6IOw5kHI3Qkqd/N8AjG4nBERiOaTEckPGR0RERERERERERERERDPbLP/0F7W1taGtrQ1vvPGG4fu2Wq148MEHsXr1asP3TZFxVX4qXmkIPbAajSoS7bizLHu6h0ERIoTAysykgOulWgN/2Pei9ARdxyxNsOHri0tQlRyLLJsFTX5CpSsyErE2O3n0629uO4YX6/w/xhbriNXZTNMXrrZIxofJBlzjI6htQ4GDIPmxMfj2slJ8c2kJOodd2Nraje/uqDF8bHq82tCJx47UI95smhTmNMLbzYHDTf50O/VHiP9+siWsY03068P1WJ2VZHgIcUhHbKVxYPJjs9/lxhM1LXipvh0eVUNZoh0fKM9BSULg/5Brd1svnj3tOwryRE3zpHC1R0dUXU9g0CiapuHz7xyeNEnFsEfFQwfOoGXIiS8sLEK3geFqAPhXbRvunJONovjzP+f799YaHq0GgNN9/oPmvtT2DWHQ7cHL9R1+w6IEDLoDP/7YrY5eP9tfOy5afY5HA76/qwb/3Lg46JCpPyd6Bn0+plyqhqdPtczqcLVLVfFGo+/n8V1tvegYdiLFauzEIBMnWZjoYGc/3KoKJQLXdeTdgMszabKWiZ4/0xaRcPVTJ5sxEODYbzd1XdDhaj0ZvyG3B2YvkeZdBlw3vNXUNSlc3TLowNe3HsP+MZPKlCbY8J/LSlGa4CWMCf3XlTvbenHvW4dxrGcAQ24V85Jj8b6yHL+TFzx/pg0/3HUSjjHX4eWJdvz3inJk2S/cOBURGcykAKFGYkOkNbWO/tv92mZ4Dh2H5ZMfgEiIg9ar7z0erbsX8BGnpfBoMyFcDUDrH4TwEq7WBkN7j2IqCCGmJVwNAFpdE1z/fAnm2941LccPShDvq040/I37ILLSoVy0APLyRRBjf95h7BcA3Dv26wpXu198Exiauvuh+63tk8LVnsMn4PzN/xsXvvW0tId9LLVd3+R17n++HHq0GiPx72iinmmA41d/mu5hRF58LOTVS6d7FLOeVDUHynWXwv3sa+MirCI/G+YP3TLyhY7JikRyAuRlC6A5nFCP1gCqBqkoD8pVF0NKToSItRnzfvE0Tuo7FYQkjXyPOiaOlJdVw7N9X0THI1dXQpj1X+OKCzhcTRcOYbVAmlMI9aj3ydBFTsZI9J+IiIiIiIiIiIiIyEhy+BODi9gCCLPv97CFOQFyyR2QS+4I+1hERERERERERERERER0YWK4mkKSnZ2Nhx56CHPnzp3uoVAQ1mUn4845WfjT8abpHkpY0mPMSLGacHF2Mu6ckw0Tg2yz3g1F6Xj6VKvP5TcVZwbcR7KOuLUsgD9dtmD06435qXj0SIPXdc2SmBSe++S8Amxt6UGPc3IwEhgJf83TEW+0BfHh7EWpcbrX1cMsGx/ZPdjVj5ZBBzJsIx9qbh8OHClKjRn5fUlCIDXGjKVp+sLjkfLLg3UR23frkBNOj+o1lOeLW9WgSCO/q65hYyPEwXorAiFEPWFllzo+QTjk9uCeNw7hSPfA6G2n+obwakMH/ndtFRak+v6PsDRNw4P7a/0e70BH36Tfk1vTEa4++3t6vaED7zR3o2FgGPNT4rAxPw0Fcb7/AzOXqmLQ5UGCJfC565zjPYM41DXgc/njNc1YlBqPXlfgMEKwbntpL565egnSYszY1NiJf9b6PmeHY8Dt/fyqx6DLg20t3WEdX9M0Q6O/0WjIY8z9w+lRMexRYZYErFEaHfFoGgQw8r9Z8HtVNQ07W30H41uHnKjpHfQZRA3Fnnb/QddnTrfha0tKDDtetKnrH/YbDNYA7O3ow4acFEOPu7Mt8MQAwx4VsXydNGWGdESHOg2eOAIA/nSsEQ/uPx1wvdP9QwHXmdV0FLSGPCq8veLY3R7+RBwTJ0MadnvwuXeO4ETP4LjbT/QM4vPvHMFjG6qR5OUaUAriqWrrmOeDHW292NHWi+8uK8WV+WmT1j3aPYDvbD/h9favbj2K314yf1Y8TxJR+MJ+PWQ2TXm4eiKtpR2uf78B863XQOvRF64e/tb9kEoLIzuwC5TWpi9MO920/gEA459DNU0DhqL8GkuZvj8Be3YfhHbT1eNjztHIGcY5yeGEVlsPV209PPuPwvzxOyAkCdpg+PcL7XQDNFUdiZz64Hr633C/ujnsYwVDq2+GNjAIYR+ZvE7zeOD6+/PjotVG8by5He60ZEjzyiGleJ/cVFNVuHeEGXYdjo5wtaaqcP3p6YiHaqOByM+G+T3XQUqa3r/5XAiEEDBdvhbyvHKoNaeh9fRBKiuCVFIwen4xXbV+5HHsS3wsLN+61+/5SCrKh3po8mvKoE3j89aUMZsCh6tNCkw3XBHZ84FJgXLpquC2YbiaLhCmmzbC8cAjkycHMSkzY2IWIiIiIiIiIiIiIppxhAj3v/cWkPKuMWQsRERERERERERERERERL5cAJ/+IiMJIXDrrbfiC1/4AuLjfQcgKXp9an4BEi0mPHyoDi5VR70piiRZFDx6yXxk263TPRSaYuuzk/2Gq1dlJgbch1UOHM2cGEG/tTQLrzZ0orZvcmziS4uKETshvJFhs+Dhi+fh5/tP463mrnHLyhJseGB1BRQdAcFgwtWLDQ46BxNPDsa7X9iNzy8oxE0lmWgb8h8EsSnSpJ9tio7w+EzW43QjLcbsdx2PpuH3Rxvwwpl21PUPIdduxfVFGeiKQAQxGL85XI+7qvIM3aee72nic9hvDtePi1aPXe9rW4/hn1cvgewjsFXbN+Q3+AwAKoA+lxsp8vnfk1vH86imaXhgby3+34nzk0bsaOvF304048eryrFkwmP4WPcAfrCrBse6B+DRgOqUOHykMhcrMhIDHmtXm/+ALAD8aPdJODxqwPVCcdfrB/Dw+rn4zaHIhd4HwohuD7o9eKm+I7zjuz2Tzk+zzaCO+Kq/AqhLVfHI4Xr8vaYZvS4PzJLA1QVp+MTc/NEIZ6/TjZYhB8yS5DfgHinHewbwm0P12NTYCQ3A3KRY3FWVi5WZ3kNIkXSydxCdwy5k2MzIiw3vZ9HlcAUM079Y12FouPqvJ5r9Lvdo2qwOvnfqmDziZM+g4eFqPRweFbGz+/Ipqug5d+qJWwejbciJX+t8znV6ouO1f7fDhUG3B3EmBXHmqXs+1XSUq739DjVNw552fVFTfzodLrhUdfT15uaW7knR6nOaB514qa4dt5ZmTVrm61pWr29tP4FXGzrxzaUl465nfnuk3uc2h7sGsLW1B0vTEtDlcCHVapq153Qi8k5TVbj//QY8ew5Ba+uAlJsFecUiKKuW+N/O6YRn5wFofQMQsTbIS+ZDmEx65hKIOM9b2+HOzQQs/t+HGUs9URu5AVH06/fyvD3sAKbo7ytSaSFEnB2e3QeD2m5ao9FDDmiNzRAFuVN2SE3TgJ4+qK3tkNJTIRID/w1TM+h9VfXwCXje3A7l4uWGBdm1nj4IH2Ff964DUx6tPkfr7R8NV6tHaqC1hvdem+8DaXD9/QXgyX9DuWw1TNddNnmVtk6gz/97ugEPMzFKOcU8+47AvW0P1H1HpnUcU8H0nmshFeVBZKXzNcUUk7LSIWWle19WXux3W7lqjt9oNQAoa5bC/dpmIMxwf9RPdmAAYTZDGwxw3omxArF2wKREZGIAALB87qOQcgJPCj2WYLiaLhBSZhos935o5HXwwWOApkEqK4bpqnWQCnKme3hEREREREREREREROOZ4iAX3QIpZdF0j4SIiIiIiIiIiIiIiIhmudn/6a9Zbs6cOaipqYHLFdlopRACl156Ke655x5UVVVF9FgUWUIIvL88B5fnpuLpUy147GjDdA/Jr7xYKwbdHqzPTsZtpVmMVl+gVmQk4vrCdPyjdnK8+sMVOahIijXkOO+ZEAdLspjwfxfPxS8PnMErDR1wqRoKYq34aGUeLs5J9rqPwvgY/GR1BZoHHTjY2Y9epxtF8TFYkBKn+8P4NkVfPDrWJGNjfqqudfWy6Ahrh8KjafjxnlMoiItB27D/cHWqdXI4SE/weya79rmdmJ8cixuLM3FFXioUafx9RdU0/NeOGjx3pm30ttP9w3hw/+mpHqqhPJqGF+vacax7AC5Vw7qsJCxJT0CXI/CH8Semgd5q6vK6HgC0D7twvHsAFUmx6He5saO1Byd6B1EUZ8PS9Hhsb+3RNd4BlwcpY56GPFrgQNGmxq5x0erRfbk9+NqWY3jmmiWjEcN9HX345BsH4RgTPtrX0YcvvHME962qCBiv7tURMeh1RiZ0AABNgw788VgjjvkIMRphIIzo55ABwe4uhyvi4erpjvwOuQP/nAbdKra0dGN+chzspvOTLWiahh/sPDnuXOVUNTx9qhU1PYN4cG0VHjlcjydqmjF89vdRmWTHVxYVh/1c7lY1vFTfjqdPtWDA5UGmzYI75mRNmuDhTN8Q7nnjEHrGPBYOdvXjc28fwf2rK6YsXl3XP4Qf7jqJnWOC80vT4vFfy8tGA9/B0nNO+t3RBpQn2rE+JznsACqASc9X3vS63Egwz/yCcr/LjdYhJyyShJzYkSeDHh3nVD2/l2Dp2WWkJikg7/ScO/WsA4xMANDrdMOuyLD6mdDmhTNtup/bpvv+0DHsxE/31eKV+g54NMAsCVxbkI5PVRcENWlPKE72DmK3jvj0sJffT8uQU9fjXI/2IRey7CORpy0t3X7X3dnW6zVcLRlw3n69sRPNbzjwq4vnwqrIcKsqtjT7H8+9bx2GRRJwqBqyzz6/3uJlfEQUXTRNA1QVQsdEbj73oapw/t+foB6pGb1Nra2HWlsPrbsXpqsv8bqd5+QZOH/9F2DgfLzQ9c+XgECRvink+n//AmJt0z0MmiG0gcnvc2jtvt+HMppUXgTlinVQNqyE2tgK11/+qW9DZXr/BKy2dkCaonC11tcP5x+eGne+AgDTnddDKi6ASE3y/l6L0//71MHwHDgK5eLlUNsNCld3dgM+wtWenfsNOUYotDEhd/fWPVNwQA3ul96CSE6Esnrp+EVhRnIBjETWp/i9OK1/AO43tsH9wqYpO2Y0kEoKIGWmTfcwaAKRkQqpshTq4ROTF5oUKGuWBd6H3QbTDVfA9ed/hDeYCL8/EBV0vEcq7DEQQkCkp0BraInIMIKNVgMIatIXoplOys6A+UO3TPcwiIiIiIiIiIiIiIjGU2IBdz8AARFfCinvGoiEcgiJiQAiIiIiIiIiIiIiIiKKPP5Vaoa777778N3vfhe7du3C1q1bsWvXLhw5cgT9/f1h71sIgfLyclx++eV497vfjZycHANGTNEiy27B3fPycWNxBj779mHU9BrwAW+D/WB5GS7NTZnuYVAUEELgS4uKUZUciydPtqDX6Uay1YTbS7OCuo9cW5CGZ063+Vy+LH1yCCLJYsLXlpTgK4uLgwqFZdosyLRZdK8/lt54249WlCMvNiakY/hikSMXiNYA3PPmIeTF+g/Qp8Z4//Dz4rR47BoT+Jxt9nf2Y3/nCfznjhOINckoT7Tjrso8LEqLx+723nEh2NmgY9iJr289Ni4k+HhNMy7PTcFFXh6L3gy4PLCbZHg0DbV9/p/HXqxrhwbgK1uOonnwfJQmxWryGkv3pm9CGNqtoxz6eE2zz2XdTjfeaeoeDeH/5lDduGj1OS5Vw//uPx0wXN2vI1wdaX894fv7NcKAK/Rw9WAY0etzuh1u5BkzV4JPHk2DMo3har0/p3vfOowYWcIHK3LwgfIcCCFwsKvf57lqf2c/rvrX9kn38cNdA/j0W4fxm/XzkB8X2nOapmn44a6acc/xx3sG8WZTF76+pATvKkxHTc8g/nqiyeskGACgAvj+zhr86+olEY8VDbg8+MI7Ryedt3a09eKeNw7id5dWjwbtg+Hy6Askf23rMVxTkIZvLikJ+3u167hm6Rh2GRaurusfwpm+YVhkCQtT43WFs8PlVjX84sBpPHmyZTQSvCAlDl9cVIROR+AJpPrDOG/5ok2avmGy4SBCxf+ua8fvjzbgdN8QzJKEawrS8MGKHKTofH4kfefOQOt4NA2/PlSHp062oNvphiyAq/LTcPfcfKR5uT7+zeF63ePTc18N1v6OPjx9qgWtQ04kWUy4tTQT85LjJq037Pbg8+8cweGugdHbnKqGJ89u+z+ryiELAYdHxaDbA7MkjZsUIRzdDhc+9/YRXet6+/2cMHAyjtYhx2i4+ulT3p+Lznm90XvsUDbolHekewCbGjtxZX4aDnUN6Aqgn3v+bhx04L69tfjVoTp8fmERFqTEcYIxoiij9fXD9dS/4TleCwwOQSopgHL5WshzCkfXUds7AacLIjEewub7Glw9eGxSBPYc9wubIF+0AFLq+IndtN6+SdFqAFEVrR7VH7lJl2h20foHxn3tfmfnSPx8ikh52SMBy4JcSAW50IaG4X76RZ/ry6uXjPwjwhNvBaL1DQRe6dy6Dic82/ZArWsCZBny4rmQSgt1vWbVPB44fvZbaK0dk5a5/jQSURW5mTBdswHy3LLx2zqNu05Wj54c2aeXcYRC6+wBSnwca/9RQ44RCq2pFTj7nKLuOTRlx3W/tWNSuBpGTOqsaYDDCVhD+1tO0IfrH4Djod9Ba/T/mmBWmsb3O8k3IQTMH7oFzkf/Nv66L84O83uuhZSfrWs/8vKFUI/WwLPzQOiDmeYJF6aEjr8pSVnpI/+fkwlPhMLVoRCzfIJhIiIiIiIiIiIiIiKiaKcs/wmgeQAhQYgLYFJYIiIiIiIiIiIiIiIiiioXwKe/Zj+bzYY1a9ZgzZo1AEbCbfX19Th8+DBOnTqFxsZGNDc3o6mpCb29vRgaGsLw8DCcTicURYHFYkF8fDzS0tKQkZGBOXPmoLy8HEuWLEFKCqPBs12GzYLfXDIfvz/agL0dfRhye2CVpXEh0eni0fHhTbpwKJLADUUZuKEoI+R9XFOQhmdPt3lN/eXFWlGdMjm0dk4w0epw6QlXF8fHeA1th8scwXD1OXX9/mNFaT4iieuzk2d1uHqsfpcHO9t6sbPtICSMBFWj2bOnW7EhJwUxOqPrAPB/B+u8Pte8VN+BTT5ifRN9+LX9KE+0I8MWOKx5vGcQz54+jG7n+Lhzx7ALHcP6Iid9E+Kjbi+R6YkCPZft6ejFxTnJaBl0YGtrj8/1jvUMomXQgQw/Qfxwos4zRXcY4c3fHWmY1uPr5fBoUII4FW9q6MSfTzSioX8YMYqM64sycFNxRlCPx7GGggh8D3lU/PJgHQCBD1bkYEtLt9/1vYXZAaDH6cbjNc34/MKiIEZ63qsNnT4npvjRrpNoHBjGb3X8/tuGXTjVN4TieFtI49Drxbp2n7H9mt4hvNnUhQ05wb8Oc6j6ny2ePd2GyqRYOD0qmgYdsCkyritMC3pCDD1x2Y5hF4rjg9rtJMNuD763swav1HeMXsdl2sz42uISLA8Q9Q/XT/acwpOnxkdi9nb04d63DgecUAAA2oedPpepmoa/n2zBG42daBgYRmVSLN5dlIGlAa7x9LxKGnbruz88UdOMH+85Nfq1S/XgbzXN2N3ei4fXz9M9oYpep/uGsKd95HpuRUai3+e1mURPuNpfTLzH6cJXtxzDzjHXuh5t5LF6rHsAv14/b9x5vWXQEVScvHXIoXtdPZ4+1YIf7jo57rZ/17XjU/ML8N6y8VGrF+s7xkWrx3qruQubm7uxv6MPj9c0Y8DtgUkSuDIvFZ+cX4AkS3jR++fPtKFpUN/3fs+bh3BdYRo25KRgVWYSAKPD1b7PBXrJBr4mfbm+A1fmp2GHn+tPf/pcHnxn+wkoQuDe6gLcUpIZ8YkfiCgwtbMbzgcfg9bZff62IzVwHqkBzCZgYqDVbIK8aglM118OIU9+zne/tcPv8Tx7D0O6dPWk2yZFq4lmOG1M5NxzpAauvz4zpceX8rLGfS3PK4f7Hy/6fGEgzysHAIhpDld7dh2AsmQeEB/n9zpB7eqB86ePQOsacy389sj5R7lsNZT1KyHifc8i5tl1MGAsWqtvhvPXf4H5w7dCrq48v8AR/jXauLEcPmFcuLqr25D9GM31xHPwHD4B5eLlU3pcraEZ2uDQ+AkXjHqfbmh4SsLVmqrCcd/DI1HyC5CwcHKsaCWsFlj+431Q65ugtrRDmBRIFaUQQUxEJ4SA6b3vhkhMgHvzLmBwCJAEoONvKKOm4O+T001rC/y3L6lyDgBAZIf+93B/RGKYb9QSERERERERERERERHRtBBCAsTs/5saERERERERERERERERRSeGq2chIQTy8vKQl5c33UOhGcKmyPjE3PzRr0/2DuL2l/bq3t4sCXx+YREuy03BztZefGnLUUPGlRdrNWQ/ROcsTkvAFxcW4b49p8aFgNOsJty3sgKWKPlQtJ5AoFmKzFij4WeQavX+YfjrC9PxUl079nf2h7TfjBgzWgwIxk21qYpWV6fEYV9HaJMWfHdHDZ462YL7V1ci3nz+8vKV+g78q7YVR7r7URRnw8XZyXhPaSZah5x49nSrz/05dcYMavuGfMZfJ9oWYpRvrLebusZFSj3BRBd8+PPxJtxbXYjNAYK/wEj03V/gs/8CCFe36YyMe6PnZxxI1xSEq52qCjv0hWIfr2nGfWOCs4ALP99/GjvbenDfqoqQApeDOmO3Yz186AxWZibi14fqg972nDeaOkMOV7/e6DsK5dE0XdHqc95q6op4uPpctNeXNxo7QwpXO4OI2AKYcN8Bfn+0AZ9dUIj3lGb52GIyPdcsn3zzEN64YXlI1xgOj4p9HX340uajk8LAzYNOfHnzUTy8fh7KEu1B71uPpgHHpGj1OR3DLjzrI5g+1qsNnfjD0QZcmpuCbPv51zduVcP3dp7AC2faR29rGHDg5foOfHVxMVZlJmJLSw/ahpyYmxSLpenxUM5e/+mZ32fYE/g5odvhwv17T3lddrxnEH881oiPVRnzvoJH0/CDnTXjJpGRhcD7y7PHvRadiTyahv/ZfTLgev0u96Tb9nf04bs7TuCMn4ldjvcM4ulTLbh9zvkg9JtNXUGNscvhhsOjGnKtX9c/NClafc7/7j+NecmxWJh6PoK0LcDz7+ffOTLua5eq4ZnTbTjVN4RfrK2CNYx4+s4gJ735V20b/lXbho9X5eFDFTk40eM9uB0KI8LVRk7t9UZTFw519mNnW3jXyG5Nw0/21iLLZsHa7GSDRkdEoXK/+s64aPU4E6PVZ2/zvL4FGHbAfMf14xZpmgb18Am/x9OaJr+u9+w35n1homiidZ1/vnS/uU3fBblRLGaIuPHRZik9BaYbN8L19+cnrS6vWQZ5btnIF8r0/glYO9OI4W/eD5GXBfP7boSUmeZ1Pecjfx0XrR7L/fLbcL+5HZbPfgSSj4CnZ/dBfQNSNbiefhHSvHKIc++tezs3hsH5yz8ati9fcWNNx2u9SFMPHoPz4LEpP67W1z8uXK05jXmvXxt2QO87aJqqQt17GO7Nu6ANDUMkxkO5ZCXkYv+va7Xefjj+9/cXbrQ6KR5I8D1xLEUHKTcLUq7+9wUnErIM0/WXQ7l6/WgQfvgLPwhiB9P/98lIE9kZ0Bq9v9d4jlxVCgCQcjIjMgZ5WXVE9ktEREREREREREREREREREREREREREREREREs9fs//QXEQUtI8ai+0PaP1tTiZfetQw3FGUg1qRgYaoxHzy2yFLEo4F0YbqpJBNPbVyMj1fl4QPlOfja4mL8/arFKIyPCbzxFInREWcLoUWqS6SC2MFIizF7vd2qyLh/dSXumJOFeFNwAbtYk4zvLy/TfW67EG3MTw1r+/2d/fjvMdHGx4404Gtbj2FzSze6HG7sau/FA/tq8d0dNXijqQueKWz8GOVvNc14bkykdDjISKw35x5xJ3oGA647Mdoa7HIK3/d3nfQbXTeC3vhw65AD9+/xHpx9p7kb/zwV/DhdqjrucayXRwN+uKsm6O3Gah50whHiY+rFOt/h6mD1nQ3LvtbQga9vPYY7XtqD72w/jq0GhM/PeaGu3e/y58/4X+6L3ui/LxqAB/bWYncQoVe3zmP+38EzQY/npbp23PjCLnzyzUM+z29DHhV/P9kc9L71MiJ4DwAPHTiDm17YjUcOn4+7v9XUOS5aPdYPd53Edc/twvd31uDhQ3W49+3DuPPlfWgLInyr5zlqZ1uv3+fjQMHhYPzywBk8MyZaDZwPyz9R04wuhwvqFAUAO4adaBtywhPE8TRNw9HuAWxr6Ub9hMj0A3trdU2s0OfyjDvH72rrwcc3HfQbrT5na8v4uNn+ECYbCeb+44+v+y0wMuHKLw+egTbmZ/tSfWjn6IOd/fh3gPNlIMEGvs/51aE6HOrq13V9ppcR4WqnauyUNp944yB2BBn39uXRI6FPXkFExtBUFZ7t+0La1rNlN1zPvTbu/K21dwbebtvIxIeapkHr6x+JXR8J73UBTT2RGA8RoTDibKHWnn+eU4/X6t/QgEirVOZ9gifl4uUw3/1eSFWlENnpkEoKYPrgzTDdvPH8SqbomLtYq2uC4/7fQOsbPxmh5vHAvXU3tDON/nfgcI7Erb1cC2k9vVAP6A/ma+1d436fRoWPI2FsMH0cR/SOOeIGJ7x2MuhnoQ0Ffk0GjDzfuZ76N5y/fRzqkRpopxug7j0M508fhfudnX63czz8Z68TPlwopOpKiEj9UYuijjCZIOLjIMze/9bne8PIjCea+JrE4RyRmjQ6YYWU433ChnDJ1ZWTb1s81/9Gtuj5GzoREREREREREREREdFsJBXc4He5SF44JeMgIiIiIiIiIiIiIiIi8iU6PrVMRFHFbpJRHB+Dmt4hv+vNSbBhRUbiuNvizApkgbCDpJflpsAiT39Al2anTJsFH67Mne5h+KRIgT+dPSfBPm3HHut3G+bjtYZOPHa0wbAxpFp9f5g93qzg3upC3FtdiM5hFzY+uyPg/nLsFnxzaSnmp8RhbnIsDnT2B9zmQlSWGP596uX6DqRZa/F2c5fPCONzZ9rw3Jk2r8tmgv/ccQKbGjtxqKvfkADhucfc6T7/z7kA4AoQiO0/G9ylyPrujhp4NOBdhekR2b/eKOXm5m74W3NzSxfeXRxc3OL+PbVBrT/W4a6BkLc9p3nQgYK46Y1gyELgof2n8Ydj58NZNb1DeOFMOz5TXYjb5mRNyTjWPrUF+XEx+FhVHtZlJQWM+zg8Kr66RX+syxcNwIt17ViUFq9r/WGPvmD+X4434abiTOTGWn2u0zHsxDOn2zDg8qBxYFh37HZi0Ncfl6rCo2mwyvomwHjKwCi2CuDhQ3XIjbXiyrzUoJ8La/uG8Om3DuHPly3QFXjWE67+4zH/12/7DbpmcqsqnjzZ4nP5j/ecwo/3nIIiBC7JScbnFhQh2Woy5Nhj7W3vxUMHzmDf2ehzjt2Cj1bm4eoC/9Ggmp5BfH9XDQ6O+XmszEjEt5eVwqNqeKJG//2ky+FChs0CAPj14Xrd8eyJEfWa3uCDyi1DjnGPwY5hJ450DcAsS6hOidP9+vtggPvFnvY+bGvtwfIJ7xWE4u3mLlxf5Pu5rHXIgX0dfcixWzEnwQbFwEl4njrVgjP9ga/P9GoedOBAZx/2tQcfHdc0Daf6hnDcwJA2gJAnjPDmUNcAOoadSPHzWo6IIkvr6gF0hje9cb+wCVpnN0x3XA8hSVBP63ifxxYD179ehnvbXqCnD4jlJITRxPq9z2P4mz8JuJ7lPz8LOJwY/tIPp2BUM1RvP9xvbIO8YhEw7NC9meUTd8Lx3/8X1qHlylK/y/wthxJFfwIedsD17zdgvvlqAIDnSA1cTzwHrVXf6z6trRNaYwtE7vnX5Fr/AIa//dOgh+J+5W1IhbkQkgQ4A09AM120zm7vtwdxH5xttIEJ18NG/f50Pn+qh0/As2mr12Wux5+FVFYEKTV50jLtdEPgQPssJgpyYLrusukeBs0EF0DcXJpTCM+uAz6Xy6uXjv5bxNpHJsHoCf59BF+UazdAKsiZfNxF8+DZddD3disXGTYGIiIiIiIiIiIiIiIimkxKmgf19NM+l4vEyZOTEhEREREREREREREREU2lKPrUMhFFk3nJcQHD1Zlng1tjSUIgwWxCpyP0D4zPTY7FFxcWhbw90WxQlWTHIT8R0ECBvXCkxZjRpjPIW5EUiyy7xdhwdYy+2Fmy1YR5AULUD6yuwPKMRMhnP/D+uQWFuPuNQ4ZG2maLHLsVAiPR0nD85USTEcOJaq83dhq2L6eq4UTPAI73BI7+Drr9B2IHXPoCshS+7++swcb8VJgMDGSeEyhQfs5jR/yfdzc1dgV13AGXB8+ebg1qG6P9fP9p3LeqIqhtNJ3RV71O9AzizabJPzsNwIP7a3FJTvJodDaSRs4Ng/jS5qP45pISXHs2lH4uXnqsewB5sVaUJthhkSV8d8cJtA8bE2x68lQLvry4WNe6QzqfTzUAj9c047MLCr0uf+50G364qwZOnff/sZoGHVA1DZKfuE3HsBP3763FO83dGHZ7kB8Xg/+Ym4+LcyYHpcZqHDQ+CPb0qRZcmZca9GMUAE72DmFfR5+u88T+jj5UJNqRbfcdCzdiAgY9jnYPYCDAcxgAuDUNL9V34KX6DmTZLBj2eJAeY8GNxRm4vjA9YMDdn8Nd/fjM24cx6D5/n20YcOA/d5wA4PvausvhwuffOYKmCfeFzS3duOqZwBOoTNQxPBKubhl0YFdbb9DbAyMh8FodE15MdO737dE0PLC3Fk+dbIH77Dk01WrCZ6oLcXleasD91OmIOf9w10n88bJqxJrCe9vR1+Nk2OPBt7YdH7c81WrCj1dWoCo5NqxjnvOvWmMnWnm9sTOoa0iPpkEWAm81deHBfbU47WNSmGiyp70Pl+amTPcwiC5YWlv4r1M92/ZCrq6AXF2pL1w9OAT3S2+d/7rf2MA+hc5041UQCXG61hVCQLNw4oFAXE88BwRxOSqy0oBwf652G+SLFoS8uYjAexbh8LyxDdqNV0Fr64DzN/8v6OiweuI0pDHhatc/XgJ0Tv41bj/7j8Lxw1/AfOcNgGNqXhOFQuvqgaZp414HaZoGrWl637uZThPD1ZrTmN+fpjNc7dntO+oKjwr10AlI6y6atMj9dvCvHWc6ae4cAGLkumJZNUQ0hfQpel0A4Wp5fjlcz78O9E7+u6ZISoCydvw5RMrNgmpEuFqWYP7YHZAqSrwulsqLIZLioXV5ea9KkSEvrQ5/DEREREREREREREREROSbPR8ifRW01ncmLRKxBZAyVk/DoIiIiIiIiIiIiIiIiIjOi65PLRNR1JifEjhs4fQRqkuy6P8A8ifn5eOB1RW4sSgDt5Zk4gfLy/Cb9fMQo8i690E0G63N8h1STDQrmG9QkM2bJanxutZbm5UEALAb/HgtjIvRve6dZdk+l723LBurMpNGo9UAMDc5Dg+uqcTitPPf44KUOHykMje0wc4SEoB4s4I4E8+90+HOl/ehy+EOuN5QgOhnv44oKBlnzVNb0RyBqK3esL6eoO5fjjdiV1uPrn0e6OyDI4RosJHebOrCX080oa5/CH861oi/HG/Evg7/YY5+g4Pt3qLV53g04B+1gQNRqqbBY2BQ+749p9A25ETnsAsfee0Abn9pL769/QQ+/NoBfOCVfXijsRMv13cYdrxgONz6I2FPnWrxGuA/2j2AH4QYrT6n1+n7HNo25MRdrx/Ay/UdGHR7oAKo7RvCl7YcxeMBJluIRC5nV1svPvLa/pC3f6WhA5tbugOu9+fjTXj3C7tx9xsH0TRg/LkqGNtbe4LepmnQgS6HG0e7B/DDXSfxs32nwwrVP3K4fly0eqwH95/2+Zh9prZ1UrQ6HB3DI2G1TSFMgnHtcztx1+sH8NjRBt2THIxVe3Ziqof2n8bjNc2j0WoAaB924dvbT2Bnm+/f1ZDbgydPNqNex/2padCBe944hOEIXZt8ZfOxSVHr9mEXPrHpAM6EEPWORkNuD3a29eArW47OiGg1AOxpDy3GTkTG0NqMuR50v7l9ZH96wtUUveLsQa0ezgQhFxLXC5t0rytsMRDm0MPVIjkBlk9/MKx9RKPhz3wXju//b9DRagDwHD05+m9N0+A5dDzkcWgt7XD86k9Qm42drMRQTte4CQE0hxPOR/8G56/+PI2Dml7ahAkS1Jozxux4SN9rPs/WPX6Xu554Du5te+F65hU4f/8knE++AOeTLwTcbiaRly8MuI7p5o2wfPxOWD5+B5SVixmtJt2ktNk/EZKIj4Pl7vcC8eP/xisyUmH+yHsgzKZxt8uV3kPTwbJ8+kOQK0t9XvMJqwXmj90x+RrSpMB05w2QcjINGQcRERERERERERERERF5J4SAXPo+SLkbAdl29kYZIn0V5KpPQsiW6R0gERERERERERERERERXfD4SUEi8qpaR7h6RUai19uTLCYA+mJRt8/JhiIJrMpMCmJ0RLPf+8qzsa21G7vbxwc7FSHwgxVlUKTIzT3xgYocvNHU5TUuOday9ISRMUkSLLKkO7bqz9yk2LPnEH025KTg20tL8YNdNeMCfreXZuGeeflet1mYGo9frpsLh0eFpmmwKjIcHhV/ONoQVjRzJos3K5CFQKxJQa/BEVgyjq/gpqZpqOsfRsdw8NEfCs/dmw7ib1cuhMnAc7KviUFC8dN9pwEAxfEx+MmqCmTbrT7X3aIjhDsV7t9bi/v3jr9tXVYSvr+8DGZ58s+5O4TYVTgOdnoPabtUFY+faMafjzeibdiFFKsJ1+Sn4a6qvEnjTraY0OnQP+4hj4onaprxZlMnanrHX2Of6hvCFzcfDf4bMciwR/9zhsOjYldbL9Zkjb/uf7GuPaQI71idDhcSfVw//K2mCQ0+Qru/OlSHK/PTEG/2/tZIpAJ+Bzr7Q972ryeag1p/V1sv/uONg3hsw3wkBHGNdY5b1aBI4f0cjPg5/uVEE67MT0VlUvCTtwx7PNjc3O1zeZfDhUOd/V4nb9plcIi3w+FCTc8gfrK3Nuht24acaBtyBgz6+/LY0QYc7R7wGT73aBr+cLQRS9ISJi3rdrjwubeP4GCX/vvuke4B/PfuUyGN1Z8zfUM+vweHquG2l/bi+sJ0FMfrnwwnGg25VTx6uD7s8+NU2s1wNdG0UtuCnxTB636OnoSmaVAbWwzZ3wUpxqIrgioV50M9aVB0dQIRZLgaAEROJrSG4K41Lzh9A7pXFWkpgDX46LTyrssgZWdAKi2YddHqcKkHj8H1jxchVZRCys0M6vfh1cAQtIHonvREbW6FHFcEAHA+8leoR2qmeUTTbOB8uNqz+yDUwycM2a02NAy1sxvoHwBi7ZCSE0Pel+uPTxkypqhl1fFh6Njgn4OIRHZGSNcvM5GUkwnrf34W6pEaaJ09EInxkCpKIEyT35+UqyvheuL58A9qD/weiZSTCeu3PwPPzv3QunoAqwXKsgUXzO+FiIiIiIiIiIiIiIhouglJgVx4I6S8awHVAQgThOL78x9EREREREREREREREREU4nhaiLyKj/WikSzgm6n2+c6xfE2r7frjc4uSo0LO4JGNFuZJAkPrK7EP2tb8cKZNrhUDSUJNry3LBtzEiL7IeHieBvuW1WOH+8+hVN93uMd+bFWbMxPG/3afjb+HK6rC9ICr+RlmzVZSTjU2Y8+lxuL0+KRoiMMYxkTErXIEi7PS8Wzp9uCPv5scC72GaE+JxlkyEtM/sW6dvzq4BnU+4iyUmQ1Djrwz1OtuKkk07B9dgURNNbrZO8Q/uONQ3jiykU+r72MOIdHyhtNXXhgby2+vLh40rJuh+9r1UjY0tIz6TZN0/Dj3afwj9rW0ds6hl34/bFGHO8ZxH2ryqFIEvpdbhzvHgwqWn3OY0cbwhp3sDRNmxQbbhwYRr/Lg4wY82gAeSjI+83xnoFJ4eonasKP43UMu1AcP/n2Nxo78fujjT6363N58FpDB64vyvC6fLY8LTYOOvDs6TbcUZYd9LYOjwpFksM6vlE/x5frO8aFq1sGHTjeM4hBtwcrMhK9Bsjdqoo/HWuCW/Mf//3PHSfw8zVVyLKPj3C94yd4HYq6/mH85nC9ofsMhq/g8zm723uhahqkMY9/t6rhC+8EF60+57kz4V9bD3s8sMrn74NvNnX5Xd+jaXjy1MyPrd6/9xR2tM2sEPTxnkEc7R5AeSKjVkTTQWvrMG5fdU3AFE8QMxvIqxZDriqDNHcOPO/shOvx5/xvEOD6JBzibDRU2bAK7lff8bmeVFY0+m+5vAhuhqsNI+VlQZjNQQXBpeoKmC5bY+g4RFLCSHxylnC/8g7wyjsQhbnTPZQp4fz572C97+vQOroYrQag9Y+Eq7W+fjh//6Rh+3U/8wrcz74CjDktS0V5QHws5JICyCsXA14mU7sQSYW58GzaGnAdomApl62e7iFMKSHLkOeWBV4vMR6iMBdabRjvJdmsECn6JhAXZhOUlYtDPxYRERERERERERERERGFTchmQOZk50RERERERERERERERBRdGK4mIq+EELihKMNnJC/JYsLS9ASvy/LjYnQdI9vOWZ+J/IlRZLynNAvvKc2a8mMvSUvAXy5fgD3tffjR7pOoHROwvig9AV9eVDwuDmg3ySGFOMeSBXB5bkpI28abFazITAzr+B+pyMXrDZ0Y8BIHnu0Szv4uPRGMJlH4HjvagFiTjPU5yciLjcFLde341rbjMPK3ZpUlDEdxwDgavdzQoStcrffx9eUtx/Dxqjx8qCJnUjg4HE2DDrzR1IkNOSk40tWPJ0+2YG9HH1KsJqzJTMKAK7rPfc+cbsW9CwrGxUs9moYvbj465WPpdrhGg/8AsLejb1y0eqzNLd14vbETO1p78c/a1hlznnV4VFiVkZ/16b4h3LfnFLa1jsTOzJLAVflp+MLCIgy7gztftA85J91mxDmnY3jyfv99pg3f2n4i4LY/2HUS1xSkT4q6a5rmdcKAmeq1xs6Qw9V2k/9wtaZp2Nragxfr2tHlcCHLZsGtJVkojB95XehUjXle+eOxRnxqfgFUTcNjRxrw2yP1cKojjymTJPCB8hzcVZU3un5NzyDuffsw2rzc7yaq6x/GrS/uxjeWlKAo3oZ/nGrB0e4BQ8Y91uMnmuBQo/c8MOxRMeQe/zt/9Eg99ncGH602So/DDavt/HherGuftrFMpVcbOqd7CCH55YEz+OmayukeBtEFSWs1Llzt2X/EsH1dKJRrNsB05brRr6WqOYE30jRAlgGP8decInZkwkmpshTwF66eMyZcvWop3Jt3A0PDho/nQiTljryfq1y0AK6ndIars71PqBMOkZHqP1xtUgDX1E4IZYSwAp4zjPOxJyAV5kz3MKKCNjASrvbsO2L8uXPCyzT1VN3I/+89DNeTL0AqzvOy0YVHKsoD7DHAgPcJT0V2OkSS978dE/mi3HAFlKXV0z2MqKUsmgtXGM978rxyCDm8SemIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiI6MLGcDUR+XT7nCy8XN+O+gHHuNtlIfC5BYWT4m7nFMfrDVdbwh4jEUWOEAKL0uLx1ysWonXIgc5hF+wmGXmxkx/jGTFm1PWHF7ZJsZqRMCYEOtVyYq34/aXV+P7OGuzt6JsxcVEjJFrOhqujOKRIIx46cAa/OHAGH6rMxYt17YZGqwHgstwUxJsV/Pl4k8F79q0g1orTYZ4/ptOutl4MezzjgsoTeTQNn3nrsO59/upQHYQAPlSRa8QQR73T3IUYWcKXtxyD42wsuLZvCDvbeg09TiQ4VQ3HugdRnRI3etuvD9WhK8xJE0Jxomdw3AQuW1q6/a7/9a3HIzwi4/W7PLAqMnocLnzmrcNoHDz/esCpavhnbSu6Ha6gJ3t44mQLPlCRg/QYY18HdA6Pvx94NA0P7j+te/sf7qrBN5aUjIvFD7g9o1Hk2WBfRx80TRv9Ht2qivbhwI+fYY8HgO/rs/r+YXx/Zw12tY8/jzx1sgU/WFGGS3JS0O80Nij2TG0rfnWobtxtLlXDbw7XI96s4D2lWeh1unHvW4fQpuN7PMeparpi5+GI5mj1OYNuz2i4+qmTLXjk8PRGAduHnciwnT9njD0fUfTZ3NKNlkHHuN8ZEUWe5vFA6+g2bH+e/VM/OcxMJ2LGT9AoTIHf39I0DbBZgT5jJ8sQifFAXCwAQCotgMjPhnamcfKKcXYoyxeOfimlp8B8121w/fkf0Nq7DB3ThUjkjESo5fUroDa1wrNld8BtpBzjw9Vy1RyoR2q8L4yxwPrNT8Px419B64r+9wUuVOqBo1AP8LwMAOr+o3Dv2Af3W9un/tgn6wKvNEPJS+fDs2O/rnWF1QLlsjVw/+Mlr8uVDasNnYiPLgymDaumewhRTV61BO7XNkPrDv65WmSmwXTjVREYFRERERERERERERERERERERERERERERERERFdSKTpHgARRa9Eiwm/u7Qa7ypMR7bNAosksCIjAfevrsAVeak+tyuOt+naf7bNGnglIooK6TEWVCTFeo1WA0COPfzHc9I0RqvPyY214pcXz8Vr11+Ee+cXTPdwpkyieeRn776AYt0zmQrgkcP1YcfivYk1Kfj0/AL8dHUF1mUlGb7/iSySwKerCyN+nEjb197nd/lTJ1uwrbUnqH0+fLAOZ/qGRr/ucbiwv6MPPc7QQ83/qm3D93bWjEarZ5qansHRf7vPxpOnZRy9g+O+3jUDwt/BOhekfupUi89I7BtNocXsPvb6QXQMO0MemzcdEwLme9t7dUWZz3nmdBtWPLkFn337MHa2jTxWJ8awZ4POsz8nt6rhm9v0BdVfa+gc/bdLVfFWUxdebejApsZOPHK4Hjf9e/ekaDUw8lz1zW3Hcap3EL0utyHjB0ZC2j8/cMbn8r8cb4KmaXizqTOoaDWd13T2MX+8ZwA/3nNqmkcDfPi1A+gfcx+yK74niqDosKMtuGseIgqf1tUDqMZd42uNLYbt64IxIVwNk445YzUNwmp86F9aWDUaDRWyDMsn7oRUOv49LpGZBsvH7hiJXI8hlxbC8o1PQV4y3/BxXWiE2Tzy/0LAfMf1+rbJzjR8HPLqpZDKi70cDDBdeylErB3mT34AIilh8jpEUcj1+yehNVx4z1PS3DJY/+sLMN16DaTqCsBihshIhchMg7x4Lky3XQf4mGwYGInpm+9+L6SyIkCRAVsMpOoKWP/zszC//ybIS3We9y1mKBtWQbli7fjnOosZppuugnLRgjC/UyKaSFjMMH3w5pC2tXz2IxA2fROOExERERERERERERERERERERERERERERERERH5ouPT80R0IYs1Kfj6khIAgKppkITvDz6fkxerL2CbZTc+zEFE0yPbgHB1chSEq8+xyBKuyk/DLw6egUud/THnBPPIJaGi4xw/ncoT7bilJBP/tbNmuocya8WaZAghsDIzCSszk7CpsRNf2nw0Yse7sTgTlUn2iO1/qmxv68FFGYlel3k0Db89Uh/0PlUAP9x9Ep+cl4/fH23E642dAbfRo2MGh1wt8vl5l072Dk7b93KiZ3y4em+H/3D5TDTgGglX72g1PsrdNOjAc6fb8L7yHMP22THshFtVcbR7AHZFwaneocAbefFOcze2tvTg+8vnRMWEGkar7RtCitWMF+va8WqDvnPKg/tPozBuJHDznR0n0OvUH6F2qRp+tPsk9gSI+wfj32fa/Y6hadCB+oHhiNx3LxR3vX4Aj14yD/ftOQVPlExq8ssDZ/DFRSPBRTVKxkS+NfmY8ICIIkfIjPpPIglgCt/PEXETXtfqDFcrG1bB9ddnfK8THwu5shSebXsAPd+OLQamazeMH1usHZZPfwhqQzO0zm4gxgqpOB9C8j6vrZAkyNUV8Ozcr+OA5I28rDqk7URKorEDASBMCswfvQ3uV9+BZ+d+aMMOSOkpUK5aD7msCAAgpaXA8pW7oR49CbW2DiI9FSLODuev/5/h46HopFxzCdzPvhbRY0hlRdAcTminGyJ6nFlJEjB/8GYIixnKmmVQ1izzuprW2Q33i29OXhAfC/OHboWUngK5shSayw0o8ugkBwAgEuInbzeRSRm95jBdeymUdRdBrW8GPB5Ic4oiMhkDEY2Qi/OhXL4G7pfeCmo7MXFyFSIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiKiEDBcTUS66YlWA4DJR/RiomwbP8RMNFvkGBCiT7RE12VJstWEG4sz8NcTzdM9FN3mJcfiQGd/0NslnI1zvq88B/fvrTV4VMb51cVzJwVjyVixpvHBM7uiL4BmkgSqkmKDCviWJtjw8bl542LEM9WuNt+B1H3tfWgPMbC8q60XH37tQKjDmnVcqjr674aB4Wkbx8ne2X8e6neNhIG3t/VEZP+vNnQYGq5+/kw7Xm/oxJBHDbxyAB5Nw1e2HMMtJZkGjCy61PYOYUlaAv5d1xbUdp975wjMkoAzhPijkdFqAPjxnlMB1+lyuNE+7DT0uBeaaHvueaGuHZ+qLoBZkkJ+TqWp8+tD9ehxuHH3vHzYdF5LElGYYu2A2QQ4eY4EAPPd74VUkg+tpQMiIwXwqBj+8o8id0BFhlSUN/42PTFxTYM8rwyuv/peRS4thPnOG6BevhaO//p5wF1aPvNhCLPZ6zIpJxPI0XmNy/hoWKSKkkm3yYvmwrP7oN/tfMXEwyUsZpg2rodp43rf68RYIS+sgrywavQ25aqL4X5hU0TGRNFD5GVBuXwt1IYWqHsORe44cbGQF+TBNZXhakUGNA0w4L2C6WT57EcgLN7P7WMp12wAYqzwbNoKrbsXkCVIpYUwv/eGcWFq4WVyBZEQF3ggE54bRHwc5Cod2xGRIaR8495LJSIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIKRnQVIolo1rDIEhwBPgyeGhP4g9ZENDPk2K1h7yPpbDw5mnysKg+vNnSibSi644fvKkzHRekJWJudhPe8uAfNg8GNN9E8ckm4JC0+wJrT5+LsJMQoMlKs0Xc/mU3sE8IldlPg2NbC1Dg8uKYKFlnCy/Xt+Na24/D4aZvKQuDagjTcVZWHmLMxw+XpCdjaGplA7lQ41j0At6pC8RKZevZM6zSMaHYadHsAANtbe/CVLcembRxjnxO6HbMzDtjldKMzgnHYQ10Dhu/TiGj1WI/XzJyJK/Sq7RsCAGxpCf58G0q0OhJcOsbR53SPfq80O/S7PKjtHUJ6jAUeLTrui+Tf32qasbu9Fw+trUJiFL7OI5pthEmBcsU6uJ95ZbqHMu2kihJI5cUQkgSRlzV6u/W+r8H1r1fg2bTV8GPKa5ZNCooKPRNAahpEQjzkpdXw7Ng3ebkiQ7lkJQBASk/RNRZhi9G1XsD9JCUYsh8AkJdWA5KAZ9tew/YZ1RLiIC+aO+lmkZMJ+AlXKxtWRXJUIVGuuhie7XuhdXRP91Aogsy3vwtCkmC+8wa401Pg3rQVcBj/XrjIzYRUUWr4fv1RrloPZcVCqM1t8Ow/GpHngCkRa9e1mhACpktXQ9mwClpnN0R8LIRJ37W4rnA1EU0rqTgPEAD4tggRERERERERERERERERERERERERERERERERTTGGq4koIt5Xlo3fHK73uTzXboWsJ+BBRDNCjt0S9j6SozBoFmtS8Iu1VbjlxT0B1y1LsOFYz2DkBzXByoxEfH1JyejXi1MT8NyZtqD2cS4mVxJvw0XpCdgWhQHh2LNB5Wi8n8wmcRNC1XYlcLjarsiwyCPB5styU5FgNuFn+2pR0zMIWRJYlBqPzy4oRH5sDIY9HlhlaVLg+abizBkdrnaqGk72DqEscXxI5mTvIJ6pDe7xSL4NulX84WgDHjpwZlrH0T7sgqppeORwPR7xc707k31r2/GIH2PY44HC1wNTakdbD/pd7ukeRsT1u9wXXNz4+sJ0fGVxMZ6oacZP9tZO93Ai4nTfkL4IKEVUssWETp2TNhzvGcTfT7bgI5W5ER4VEQGAcslKaP0D8Ly+ZbqHEjEiIxWWL38CWk8foKrwbNsLz8790Nq7IJISIC+qgnLdZRBeJhQSZjPMN22EOz0FrsefM3Rcphuu8L7AbAKcvs+ZyvoVI9vf/i5A0+DZtf98iDAhDuabr4ZUkBPkYIz5k59ISwZkCTBgchhp7hyopxsMGFVwRFoytL4BYNgxpce1fOJOCGXy70GeXw7386/5/JnKKxdHemhBE5IEee1FcD/94nQPhSJEufoSSLkjkX9hMcN07aVQNq4HXG5o/QNwv/gmPIdPAD19YR9Lys2CSE0Kez/BEBYzRHwc5Pg4yGXFGJqh4WphtwW3vhAQKUH+rBN1TGg5xedTIhpPxMVCKimEeqJW1/ry2mWRHRARERERERERERERERERERERERERERERERERXTAYriaiiFiXnew3XL02a2o/oE5EkRVvDv+SIilKg8QJlsDfm12RcVleKo71TH1MtXdCgPJDFTl4o6kT/S6P7n0knP39CSHwwxVl+NqWY1EXEY49G1S26ggpU+hiJ0Su7KbAP29pQkRyWXoC/njZAgy5R+6DMWN+Z7GS98fTxTnJ+Ex1IX66rzbIEUePw139KEu0o7Z3CFtauuHRNPzhWCMurHRqZG1u7sL+zv7pHgY8moYf7TqJf9S2TvdQZrS2ISeSLebpHsYF5WTvEC795/bpHkbE7W7vQ7fOsO5skGQx4auLiyGEQGVS7HQPJ2IaBx14qb5juodxwXv+2qX487FG/Gz/aV3rP3yoDnX9Q9jb3ocUqwnrspNxx5ysSZOYEFH4hEmB+car4ARmbbxa2bgeQlFGY5zSNRtgumYDtKFhiBirrn2IBB1hziCYbt7oNZQNAPLCKni27fW5rVRWPDImkwLzB26Ceu0GaPXNgNkEqbQAwhTC+2RGhatlGSI9FVpTeK955IsWQF48D1rr1D+HK2svgrx8ITxbdsO9fe/Iz1YHaUEl1L2HQzvm9ZdDysn0vt+sdJhuvhquvz2DiW8UmG69BlJGakjHjDRhDX+yQope3u53QpYBWYawWmC+43pomgbX75+EZ+f+kI8jEuMhzSkcCSqnJUNr6wxn2PqZx59HpXnlUA8cnZpjGyXGCkzBeyciIS7wShfARFhkPJGSBK2ja7qHMWuYbrsWjp8+CvQHnkRXnlc+BSMiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiogsBKyFEFBHliXYsTfMeArFIAtcXpU/xiIgoksSEcG0oojVcPTHk641H0+BRpydPOzAhUJ0fF4Ofrq5EZZJd9z5SrefjF7EmBQ+urcLvNsw3bIxGiDMovkT+ZdnGB4nsOkLhso/Hf4wij4tWB3L7nCzMT565wc3DXQP48e6TuO2lPXhgXy0e3H8aXRdQOHUqREO0+hxGq8PXOuSEw6NO9zBoFnrqVAs8F9CsAWuyEkevxTNsszcG/3JdB95smlmxq7IE23QPwVDliSOvLzJswQUsnz/TjsZBB/Z39uN/D5zBxzcdhFvl+Z8oUkzXXgqpvHi6h2E484dvhbJ4ntdleqPVAEYCoAYSqck+lymXrJwUTT1HXr4QUlLCuNuklCTICyohV5aGFq0GANm4yb6krPDfvzfd/q6RUK0tJux9mT/1Qf1hbgHIi6ogYqxQLlkJ8y3X6DyICSI29OdvMeF3OpGyeiksX/oE5BWLIFXNgbxqMcyf/QiUNctCPmbEcbKhKSEtqJyeA+sIkwshgDAeFzCbYLrzhtHIvzDg3KLbhPuvlOs9LB/NpJxMQ/72EoiIn7nvyVJ0U65Y63/5VRdP0UhmByk9FZbPfRTy2mUQab6vQ+U1SyFVlEzhyIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIhoNmMBkIgi5r9XluNb247j7ebu0dsSzAruW1WBovjZFXAiIuCSnGS81tAZ8vbJ1ugMV/uK8o7l0bRpC9RekZc66bb5KXH47SXz0TToQE3PIL60+Sh8peHyYq3Isk+OlFQkRVesYmxAfEFKHPZ29E3jaGae6pQ4dDlcqOsf9rlOrt2CnAn3BYsswabIGHR7fGwFXFdoXHAmx26NqjhxMJ461TLdQ6BZojzRjqPdA9M9jIhrHXIi22ZsODBaWCQBxzRNaEEXnhUZiaP/TrGaIQsBjzZ1979smwWNg46IH+dE72DEj2G07y8vwze3HceRWXJOX5edBABIjwkvYHmgsx9/Ot6ED5TnGDEsIppAmE0w33Ub3C++Cc/O/dCGhiFSkgBJgna6YbqHFzJ5YZUh+5Ey0wzZzzn+wtVSTibMH74Vrsefg9ZxdvIFSUBetgCmW681dByj4zEwbhpuXFYU5ECcC2kbcN0vzymE5Wv3wLN5F9TmNogYK9SWdmi19RMOLEaC2QljJtXUEec9t56whxGu1hFGl3IyYb7j+pCPMdUEw9VTQl5YBXXv4Sk/rtD52NAbdJeXVUNkpkM9fAJabx+k0kIoa5ZCys0aXUdZvRTOfUdCGm+wxITJA8aOY6YQUxTbFgr/kxGKDLmqFK4YKzDk5e8Ssgx5usL9M5iUmjw6KYemaVD3HIJ70xZovf2ALQbK2mWQl1ZPSfSeiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiC4M/BQiEUVMrEnBT1ZV4Ez/MA529iPLZsG8lFiYJGm6h0ZEEbAiIzGscHWSJTrD1XrcWJyBuUmx+FvN1B97frL3wLQQAtl2K7LtVnxuYRHu23PK63r+gnFL0uKxs6036DG9fv1F2NHag9cbO/HM6bagt/cmziSP/pvh6uDFmmTcVZmLL2w+CodncsZcAvDVxSWTYgZCCCxJi8ebTV1e9ysLgUWp8V6XhcKmyIFXIprllmckXBDh6u9sP4H/XlE23cOIiHcXZ+L/nWia7mHQBWJZesLov2UhkB5jRlMEQ9KfX1CIeLMCVQNKE2ywKTJu+vfuiB1vKn1hQSG2tvb4vO4Jxsb8VOTHxeCHK8rwne0nZvy1a67dghuLRqJ5GbbwA5a/OHAGNT2DqOkZRLxZwVX5qbi2MF3XpEFEFJgwm2G69lKYrr103O1qWwcc3/v5NI0qOog4O0RBjmERb5Gc4He5XDUH0jc+CfVUHeDxQKSlQEpONOTYkSbSfEe5dfGcnwBL2GLCHM0IKSUJ0oT7tWf3QXj2HoLa3A4pLwvysmrIZcXjN9QZXxYWMxDGWKVs4yb2ihp+JjKjAKwWKGuWwf3yWwFXFTFWIM4O9BnzXoDISIWIs0M9cTrgGHXtT2fQXcTaYbp8DXD5Gp/rSCX5QKwN6J+CiWkmPPaFwZMXTAUpZ2rC1XpMVUSbZheREA/zB2+G8zf/D3C5zy+QJJhuuy6q7uMzkRAC8qK5kBfNne6hEBEREREREREREREREREREREREREREREREdEsxnosEUWUEAIFcTG4uiANi9LiGa0mmsUuzUlBWkzoEbNES/TOp3FNgf+oxbqsZMxNjgtqn4tT43FtgP0GkmRRsDgtcDT4lpJM3D03Hzbl/DnYrsj49PwCXFfoO6qzLiu4SJEA8LXFxYhRZKzNTsY3l5bi20tLg9qHL3Gm8/ePK/NTYZIYtQvG3KRYXJSRiIfWVmF9djJi5JH7giwE5ibF4hfr5mJpuvfg1vvLc3z+vG8rzYTdZFxsujDemJgV0UxllgSWpvmP380mX95ybLqHYDiTJPD+8mxYZb7uuRBMd2R3XnIsEszjJ39JD+N6PBCLJHBNQTquyk/D1QVpKEu0I8U6cyefmSgn1orKJO+Twugli5HXDl9bXAIAyLZb8auL5+Lhi+fiexfN8TnpTLQSANZlJeHBNVVIPvu7TrGaDbnv/7uuHSd6B7GrvRc/2HUSn3/7CFRNC3u/ROSblJYC6/c+D2nuzJo8RKSnGLo/07suAwy4VhNZ6RBK4PeyhCxDLi2EXF4yY6LVACBlhRdhFilJ578wKFztjbxoLswfvAXWr9wN8503TI5W42yQWg+LGcIe2lhFTgZEgnETe0WLkB9/cXZIFSXGDmYmscXA+u17oVy7Qd/6JgXCwPOD+WN3AObA1+kixqprf3rD1dCxP2E2Q9mwSt/+wiTME8LVyQnADJsoRZrCWLS8rNr/8qX+lxP5IleWwvqdz0DZuB7y6qVQLl8Dy7c+DWX5wukeGhERERERERERERERERERERERERERERERERER6RC9hUgiIiKaUeLMCh5aU4XPv3MY9QOO0dvtiowBtyfg9lbZuPit0a7OT8Nzp9vgLaOWa7egOiUOJkmgNMGGEz2DfvdlV2TcUJSOD1bkwqbIsMgS/n6yJegxxZtkPLC6EorOCQE+WJGDm4ozsL+zDwLA/JQ4xJr8XwreXJKJLS3d2NzSPWnZrSWZcHhUbG7pRr/Lg9IEGz5WlYdlE+LHRsUTY83n7x+lCXZ8c2kpvrfjBFxq5ON2n5yXj4cOnIn4cSJpfc5IhLw6JQ7VK8vhVjUMuN2wKwqUABHw6pQ4fP+iMty/7xSaB50ARuK6NxZn4p75BYaO89KcFPzywBkMeVRD90uhefvdywEIfPbtw9jW2jPdw7kgWGQJy9ITUBBrxen+4ekeDoVgRUYiUqxmrM1Kwkv1HdM9HIqgNKsJz1yzFFuau3Hv24enZQzeJlfJsJmBCN31VmYmTZqwIkaJ3mv4YJgkgeqUOBTExuDhQ3Uh7eMnqypQmmBDps0y7nYhBBakjoQs12Ql4eZ/70bHsCvsMUfaN5eUYE1WEhIt46OHshBIizGNXhcaZXNLN54+1YIbi6cuzkd0IRIJcbB8/A6oHV1w/PhXwGD0X3MaHb+V5xTBfNftcP3rFWgNzaHvZ5bHFkVGKhAfC/T2h7S9snrp+X3Z9MVxI0ZnuFpYLBA2nYHesRQZpluuCX67GUBkpAIxFmDIEXjlMWK+/0UAgPP3f4dnx/5IDC2qKZesHI09SyX5UGsCvK+oKJCSE+E53RD2sc0fugVSWjKg5z1TqyXwOpgQove3ns4QtrJhFdSTdVAPHNW1fsgmxLuFokAkxkPrmjnvcYmM1Ck7lrygCp7t+3wMBJCr5kzZWGj2EXGxMG1cP93DICIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiKiEDBcTURERIYpjI/B41cuwrbWHnQMO5FkMWF5RiIufnqr38Bwrl1fJGO6LE1PwGeqC/GzfbUYm9NNtpjwk1WVMMsj8egfLi/Dh1/bjz7X+FD3srQE3Le63Guc+0uLirEgNR7f2nZc11hWZSZiYWo8Ls9NQbY9uPBPnFnBqkx9oREAUCSBH60ow79qW/HM6TY4VRX5sTF4b1k25qfEAQA0TYMGQBLe48cZNmPC1XETIttX5qViSWo83vfKPnQ6Ihv+SzMovj1drsxLRWmCfdxtiiSQMCHe4s/FOclYnZWI/Z398KgaiuJjkGI1/ueSGmPGZxYU4oe7TvpcZ2FqHJoGHGgZMjaWSOPlx1pHw/g/XlmO/959Cs+daZvmUc1+VlmCJAS+urgEX9h8BP2uwBM/UHS5vjAdAPDFRUWGhKvXZCYhxWrCP2pbw94XGct2Nti8IjMRpfE2nOj1P3mJ0YriYvCus/e3sTJiInddfVluitfbyxJsOBZg8pZIS7Oa4FI1dDvdIW2/IiMRsSYFsSYFX11cjB/tOul10hp/1mQFvs62KTIeWT8fN7ywK6RxhirRrEAIga4grpuL4mMmRavPSY+xGB6uBoC3mroYriaaIlJKEuSKEnh2HZzuofgnBOQl8w3frVw1B1JlKdA3AGgqHA//BVpdk/5hFeZCWbnY8HFFEyFJUFYsgvvFN4Pf2GyCVJR3fl8xMQaOLHhC0fmn0BgLYA9urFJJAZRrN0Auzg9hZNFPyDLkixbCs2lraDvQGTIObp/Bh7Sn2tiAs1xdGTBcLUwKREEOsNuAc/LZGLXITAOO1PhfV2/UPScDsFkDT3ag8/ctJAmmjevhiHS42sv3J1KSZky4WuRm6j9/GUCaVwb5ogXwbNs7aZly3WWQMidPnERERERERERERERERERERERERERERERERERERESzH8PVREREZChJCKzISBx320cqc/F/B+t8blMcb4vwqMJ325wsrM1KwrNn2uDwqMixW3F1Qeq4GHV+3Ei4+y/Hm3CsewAAsCE3BVfkpXiNVp+TqTOMnGWz4IHVleF9I0GyKjJuKc3CLaVZXpcLIeA9WT3CqOhzrGnyzy81xoxfr5+Hm/6925Bj+FKVFBvR/Ufa7XO8/+6CpUgSFqXGG7Ivf24oysDJ3kH89UTzpGVJFhO+vbQUfz3RjP93Qn9UjIK3NC1h9N9WRca3lpbg1tJMHO8egBACZYl2vNnUiY4hF5481TKNI51dLGefKxalxePRS+bjj8ca8U8Gi2eMNZlJo+HaBLMJd1Xl4teH6oPaR7xJxlX5IzGoddnJWJoWDyEEPlqVi3+casVvDge3P/KuKsmOQ10DYe0jRjl/bfKVxcW4581DcHhUP1sYxyJLeHj9vNEJBsbKjtCEMDZFwmofYebVWUnTHq7+6ZpKfG9HTUjh6iybBV9eVDz69Q1FGSiIjcHzZ9pwqm8IOXYLnj/TbthYs+wWXF+YPqVB+o35aWgcHMamxi7d2/h7/VIcH4N9HX1GDG2choHojlASzTq26Y0JT2IxA44xUXwhYLppI+QxAWQjCSGA+JHX++aP3gbnTx+dFDOV110EuboS7tfegXqqHiIhDnJlCZSrL4Ewz+xJrvRQrlwHtb4Z6qHxk62JlCSYP/UBOH/7OLTTDZO2M7/vRoixwVhbBOLFESDlZI4ftw+md18Jec0yQJYgvFyPzTam6y+H1tY56X7gi1RVOvpvEYFwtYi1Q4vycPXYgLO8ZD5cT/8bPmdFMSkQGamQ7Ta4n30VcIU2Ecs5IjUZAKAsmQfP61t8r5eVPnIe1LNPWYY0pwjq3sP+1wvm922K/H+i4O3xLFKTgBO1ET+2EZQVi6b0eEKSYLr9XZAKc+HevAsYHIZIjINyyUpI8yumdCxEREREREREREREREREREREREREREREREREREQUPRiuJiIiooh7V2E6fn+0EYNuj9fll+SkTPGIQpMTa8XHqvwHk5IsJvzHvPyg9js2fOiPt3hztLPKMiqT7DgcZhwy1kfMJDfWirlJsTjY1R/U/jbkJGNPex86Ha6A6+bFWpERY0bLkDPguqG6Z14+ritMx1XP7DB833FTEIIx2merC1EYZ8PDh+rQ5XBBFsCClHh8c2kJsu1W3D0vD/s7+ib93i2SgCQEhqYoHDqbrcpMHPe1EAKVSbGoHBNyL0+0AwC+tKgIu9p78cDeWhyf5nCpUW4qzsDfT059kNuqnI+eFcTF4OtLShiuniEWpcbhRyvLxoW/iuKCn5jjppJMfGLu5OuI9BgL7qrKQ4wi4+f7T4c11gvdpTkp+MGKMpzsHcTtL+0NeT+2Mddl81Pi8It1VXjsSAO2tfZAFsLnda8vqzMT8XZzt651/7lxMeLN3p/f5yTYgzquXh8oz4XNxzXrbaVZeKmuA/UDwxE5diA3F2egNME+7hyqR2WSHasyk3BTcQZSrOOjdovS4rEo7fyEHZk2C357ZHKY85z3l2cHdex5ybEBw9UPrqnEp9/yHwfUY21WEj45Px/vNHcHFa6OM/t+7TEvOQ5PnzL++ckqz/74J1E0EXZ91yoiPxtaQwvgCe65Laix5GfDcvd74d66B1p7J4TVCnnlIkhpU/N+kZSUAMs3PgXP9r1QG1sASYKydD6k/BwAgFxWBE3TdEdeZwthMsF8121QDxyFZ+8RQBKQ8rIhr1oMYTKN/M42bYVn217A44HITINy+VrIcwrH70dRIDLToDW3Tc83AkAkJUwKk08kzysfidrKEuDnfQWpogRiBr7XEiqhKDB//A6ox09BPXEacLnhfuVtn+vLi+ed/8IagUlVQojuK5ethlrXBPXoSePH44UYE2sX8bGQL1oIz9Y9XteVyksgTCaIpASY338TnL/9G6D6qlwHOG5a8sh9GIDIyx6J8/d6f89UnlcW1L6VpfPhDBCuhj2I381UPIbMpkk3iRTvk/FMNZGRCuvXPwnXP1+C++XJjyeRngJ5+dSGq4GRSLmyZhmUNcum/NhEREREREREREREREREREREREREREREREREREQUnS6cT1YTERHRtEmxmvGp+QX4n90nMTG7cXluCq7IS52WcUULvYG2mRiuBoB3FWbgcJf3MIxdkTGgI+xo9/O9/8e8fNzz5iHd41mdmYjvXTQHPU43rn52Z8D1hRC4pSQTDx04o/sYegkAn5pfgDvLsuFWIxNb9hcdjFZCCNxYnIF3F6WjZciJOJMy7j5glWX88uK5eP5MG15r6ICqAdUpcbilJBNWWcJTp1qwubkbW1v9R6nIu1SrCcszEnWvL4TAkrQE/PGyBeh3ufFyfQf6nG40DzqQFmNBokXB6b4h/P1kCxwzJCo+Nzl2WsLVFi/PB0vT4rGjrXfKx0L6XZKTjB+tKJ90e6bN7GVt/1Isk8NaY63KTGS4OkzJ1pGfcbY9vIiefULEeV5yHO5bVTH69Xd3nMCzp/XFGXPtFqzPSdEVrr40JwWJfu4npQnBB9MDuak4A3eWZflcnmgx4edrK/HuF3Ybfmw9qpJHJlVIj9H/mFufnYz/Xjn5cevLuqxkPHakYdJrmXM25qfp3hcALE1P8Lv8stwUpAXx/fjyk1UVWJ2ZCCEE1mYl4bbSLPy/E00Bt8uyWZBm9X38+clxYY/NmwQfQXYiigyhM/5q+dQH4fzlH6CerIvcWEwmCLsNpg2rInaMwGNQoKxa4nv5BRatPkfIMuQFVZAXVE1eZouBaeN6mDauD7gfeWEV3C9sisAIdbLHAH7C1SIrDVLBSKhcKimAeuyU9/XSUyAyg3venw2EEJDLiiGXFQMA5BUL4XjgUWBwaNx68pplkJctOL9djBVGE7YYn9dkXtfPSody+VqIGCs8Nafh/NlvDR/TpGNmjH+v23TNBqgnz0Br6xy/XloyzLdfN/q1vKASlm9+Go7//FnwB5UkmO68YfRcJSQJ5g/dAudDv5sUYhcFOVCuvDi43VfNGQmRDzu8r2A2Qcrz/ZphIqFMwXWfl2OcC3tPO8vItbZy3WWA3QbP2zugtXcBFjPkeeUw3XoNhCX81wNERERERERERERERERERERERERERERERERERERE4WINhIiIiKbEjcUZKE2w4dHD9WgcGEacWcGVeam4sTgDinRhxn/O8RYq9SbWNDMv3d5dlI5TvYP4W03zuNtLE2z49tJSvO+VfQH3IfsJRC1NT8APlpfha1uPBdzPz1ZXYnlGAoQQSLGasTgtHrv8BGHXZycDAN5blo3mQQeeCDNk++zVS/B2cxdq+4YQo8i4Oj8NubEjER9F0nc/CJZ9KkIwESKEQKbNe1jUIku4oSgDNxRlTFp2+5xs3D4nG5f/azt6ne5ID3PWuasqD2ad56WJYk2K198JANxcnIl/1LaiYWAYWTYLrsxPxf/uP4PNLd1hjPa8JIuCLocxv+9IBTkD8TaRwSU5KQxXG+Te+QV4+FAdhgwMqFcl2fGNJSVel2XEBB9GTvYTigWAorgYXFOQpjuITJOlnA1XW2UZFlkKOahvU/xPDBHMhCNfXVzid5KOsfwFpAEgRgnv+wKA0ngbbijOgFtVsSQtAWWJ9oDbZNutmJ8ci/2d/SEfN1SVSSPh6ityU/FiXYeubVxBThhSlRyLj8/Nw/8dnBxt/Ux1AYrjgwuGZ9utWJWZiHd8xMo/UJ4zKY4einPRamDkuuoz1QVYnpGAZ0+34eV63z+rK/JS/QZa8+OMj1ACQIJl5l63Es1I9sDhapGSCGExQ6SlABEMV2uDgxHbN0UH5cp1UGtOQz1eO35BnB3oG/C/sQFvG0qlhfDUN/tcrly6evTfphuugOOnjwJO14SdSDC9+8oLNmI+lpSRBuu3Pg335l3QmloBRYG8rBpyScH4FQ0OV8tL5gN6s9WyDHlZNUxXXzIa0JZLCmD++B1w/urPho5rLJGVDik1efxtifGwfPkTcL/0FtS6RmBwGNL8CigrFkLExY5bV0pJgrx+BTyvb9F9TKmsCKbrLoVUkDvudrmkAJYvfhzul9+C2tAMSBLkJfOhrF4KYfY/adKk78tkgnLVxXA//aLX5fKiuRCmIPYZ4fe5RX6218eqlBId4WphHnntL4SA6dLVUDasAvoHgFg7zzFEREREREREREREREREREREREREREREREREREQUVVgDISIioilTnRKHn66pnO5hRJ0YnVG6LB8B32gnhMDnFxbhusJ0vNrQAZeqYV5yLNZmJUPTG5sJYEVGor71Msevd2lOit9w9ZqskZiJEAJfXFQcdrg6NcaM631EfQEgL9aKuv7hsI4xlk2RL+gwvPkC/t6DIQvAowHZNgvurS7A+pyUiBwnJ9aK/5iXP+62ddnJhoWrf762Cq81dOKRw/Vh7ys/LgZzk2JxsGtqA6zewtVX5afiqZMtONE7s2J+1xem48W6dkMj0eFYkZGA98zJwqDbg197uY/YFRm/Xj8Pd79xED1+gvdfWFiEpoFhyEKgIikWl+QkQ/IRlUq2BhcCAxDwnC2EwNcWF2PYreKVBn2BXhov134+nhdvktEW4n3UqGeYuypzsTQ9AR5NQ7bNgsZBh891V2UmYq6OsH6WzYLavqGQx3RRRgJuKckMervuaZgswipLKIgbCa8uSU/QHe12qcFfg36oIhfVKXH464kmdDncSLOacUNROi7SeR060Q+Wl+FLm49iW2vP6G3xJhnfWlqKskQ7+l3h/zwnRu+EEFiVmYRVmUn48iI3PrHpAGp6x99XVmYk4mNV46OHE0lCYE6CDcd7jH1uip+hE/UQzVTCFjhcjbMTLIn0yLxGOEfr7Am80oUuPhbo9fP6xOBAsNGELMP8H++DZ+d+ePYcBpxOSMX5UFYuxvC3HwiwcfgTfSnLF8Lzzs7JMWoAUnHe2SDy2a9zs2C55/1wPfsq1GOnRoaQnw3TxvWQ55aFPZbZQthiYBoT/Pa6jtHh6kVV8Bw6HnA90/tvhLywCsLLZG5SZSmkeeVQDxw1dGwAAIsZ5juv97pImM0wXbNB126krHR49KwoAOsD34LwMxmelJ0B8/tv0nXcQJSLl0NraIZn+/hJCKWyIphuvSbInUX2uk+u9v43CBEl4WpYxr9fIIQAJkTMiYiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiKIBayBERERE08xbqNSb4nhbhEcSWWWJdpQl2ifcakz20aLzZzjRJTnJ+O2RerQPTw4XZdrMWJdlXMxkQUrg0OTKjETU9Tcbdsx4s74o+mxl9hPuoRHZNgv+eNkCuFQViZbgI7vhWjUhJh8OmyzjrspcJJoVPHqkHl2O8IKf319ehk++eRD1A74jskbzdi6LNSl4cG0l7t9bi9cbOuHWjAn+R9rS9AQc6R7A0e6BKT3u2qwkWGQJL9ePRJ0VIXBFXio+s6AAshD4SGUuLLKEPx5rHI3slsbb8L3lc1Acb8P1Ren4/dFGr/suTbDh5uKMSSFYX3wFrf0pigsckFQkCd9fPgdvPt0JZwjx3QtdXuyYcLVZQZuXawA9hgPEkfU8VG8sysBHKkcCwbIQ+O5Fc/DJNw953XeWzYKvLy7RNbaKRHtY4Wq7zklVJuoM8WcZjrJEO+SzjzWbIuP20iw8drQh4HYuNbRg+ZK0BCxJSwhp24liFBk/X1uF2t4h7GrvRbbNgook++jzsS3E34Ne8WYFv7u0Gi/Xd2BXWy9kIbA2KwmrMhN1neeuyEvF8Z4zho4pYRquRYguaHb97zFIEQ5XMwYcmLJhFdxPv+hzuemqi6dwNKERsgzlooVQLloY3Ia28OPHUk4mzB+6Bc4/PAkMnp8wTCrMhen9N0HI4593paI8WD75AWhOF+DxGB5gvlAIq3GT8InkBEgVpfAcPRl43Vi712g1AAhJgvmj74H7xTfh2XsYWksbpPwcqCdDu64RmWnQBgYhV5ZCWb8CUm5WSPsZS8r2PendODab32i10YQsw/y+G+FZsQjqqTpgcBhS1RxIpQXBjyOC17pSZSmUS1d5Xxhrg8jJgNYQ3uSE4RJm87Qen4iIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiEgvhquJiIiIpplJ0he2LI4PHLO8UCk6f4YTpVjNuG9VBb665RiaBs/HaXPtFvxoZbmh8bx12ckB17l9ThZea+gIOaI5Uazpwr7cN4cYNDdaSXwManr1B0SDXT8cSRYT7CYZwPREzjNtFry3LBt/POY9FBwMqyJBCIFbS7NwS0km/nK8CT/bfzro/ZwLoGbZLXjkkvl4pb4D/7PnVEhjWpIWD4ss4Z3mbl3r++rcpljN+P7yMvQ53XB4VJzoGcS9bx8OaUxGWZ+djCG3B1tbeyYtW5IWjw05yXijsXPKw9ULUuLwvvIcfLbaiV6XGwlmBSnW80EoIQTeV56DO8uyUdM7iFSrGUljzvW3l2ZjS3M3jvUMjttvnEnGlxcV645Wn3NRegK2efkZeZMWYx4XVfZHCIH3lmXj0SOBA700Xl7s+eupeHPoz5PDHo/f5QtT4/G3Gv+TUXykMnfcfWp+Shz+esVCPHakAUe7+zHg8iAlxozFqfG4Y0722fN1YNcWpuOFunZd63qjhBi/u6UkM2A0OsmihD2xwFgVEyZF+cTcPDhVFX8+3uR3u2iKvhfGx6DQy3V+KPH7sT5UkRNwHZMkYWN+GjbmpwW9/+sL0/HbI/UYdIcWAfcmIYzHJBEFT9j0v8cgMvSdJ0y3XgN5XjnUplY4f/lH/ftPC/x6+UInz6+A+7nXAKeX9wvMJkjzy6d+UAaRivP9RoNN115qyHHkuWWwfvdz8Ow/CjhdIyHkMv/X+MJsAsCJFUJmQHQcAERSPMz/8b6R34cc+JpYWPxHgYUkwXTVxTBddTE0VYWQJAx9+jvBjys/G9YvfCzo7QLuNyttZK6/AJeswj497xXLc4ogzykKax+GB7cT4iDlZ0NePA/york+9y+EgLJ6KVx/e9bY4wcrwH2UiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIKFqwBkJEREQ0zfRGMIvjbREeSXSK1xlpDFVlUiyeuHIR3m7qQrfThSSLCauzkkbjtUaINyvYmJ8acL1suxU/X1uF+/fWYkdrD8LNAMZG+GcX7cwhBs2Nlm23BhWivmdeAb6y5eiURDXlKPgZ3TMvH/FmBb844DtUpodNOX9/F0LgjrJsNA858NcT/sOxE2XZLKP/TrSYcFNJJgCEFK92qRpSrfpfdg+5/Ydw48wK4gB0OoyJ24cjwazg28tK8eC+03juTBscHhWKELiuMB13z82DIkkoiDM+opVqNaHdT9x/TVbSyHoxZqTG+A5BSUJgToJ90u3JVhMeXj8Pjx6ux672XnQ73FiSFo/b5mSF9Dy8LitJd7j63UUZQYWxP1yZi7r+YbxU3xH0uC5UKVbTuPhzXBgTPDg8/p+ll6TFQwJ8Ppdn2yxIsU6OIGbaLPjK4uKQxwUAi1LjkWWzjJuUIxihTghSlRTrd/nKjET0udzocvSHtH9vKiccUwiBe6sLA4arl6YlGDaGSEqxmtAR4oQml+WmGDya8RIsJnxhYRF+uOskXAZdszBcTTS1ggmeioxUiOx0aI2tvleSJchLqyGsFkgmRVd09RypslT3WC5UUloyzO+7Ec7fPQGMfd0gyzC//yZIqTM3/i2VFfkNV0vl4V0bjSXMZihL5hu2P/JPWEMPV5vecy20YQek5ERI1RUQZ4PVQs8kZUFEgc8FjpVLVsL92uagxiiUyFy7CLMZIjMdWpOfcy6Cm4BgVrNZYf3Pz+qOYcurl0Lr7Yf7hU0RHpgfZgbxiYiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIaGbQ9wlOIiIiIpp2cbM05HbHnCy/y68vyoj4GBRJ4OKcZFxflIF12ck+o9WLU+ND2v9Da6uQYtUXzSmKt+Hna6vw7DVL8fUww5VmncGW2cqkJ2Y0BTLHhJD1WJWZiAfXVI0LKEeKPP3dakhC4APlOXj26iVh7cfi5ff92epCPLS2CpflpmBNZhJuLclEqpdQ7FgfqsiZdNv1RekoT5wcOQ6kadCBGEX//XDQrS9XHy1Repsi4yuLi/H8NUvxr6sX48XrluEri4uRYBn5GefYQ4+U+fLVxSU+JzRYl5WEIgMmeYhRZNwzvwCPXDIff79qEb62pCTkySOuyk9DkY6A97sK073e9/wxSRK+d9Ec/HhlOXLt3s8XlUnB32+DtS4rCYkz5BolL3b8fTI+jHFvyPEfBU60mLAyM9Hn8o0FaUGFyoOhSAIfrcwNffsQx7U8M2HcJAIT3VySiWwf99VQVfi4jwe6ZrskZ2bEPZenJ4a03a0lmSj1Euc32jUF6fj1+nm4oSjdkP0xXE00xWJ0XKtpI+VpIQSUK9aNxKh9UK5aD2EdOc8Luw1SeYmuYcjrLoJUlKdr3QudvKAS1u98BsrG9ZDXXQRl43pYv/MZyNUV0z20sCjrV0Cke7+2Ui5dBSklaYpHRIbRc57xQVm9FKZLV0NeNHc0Wg0AMEUm+CsvrQbkIF9rhzERTiBSkY7reYarAQDyRQt1R6uBkec009WXwPL1e2C68Spjx7K0GtDxekqY9cfViYiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiKZTdJTciIiIiOiCFSj8uCYregJFS9MTgt5mXnJsSMHbZKsJyTpj1774CnBfKCxREu4OJly9OC0eQggsSovHU1ctwt+vXIQ/XFqNv1y+ICJhWCmK7iMJltC/vxhZ8vq9CCGwLD0B319ehp+srsDnFxYFjOF7C80qkoRfrpsbdOTWLAm/EdeJBl0eXevZoyBc7VTPR7btJhnpMZZJ48qPMz5cXZlkx49XVaAk/nygSwJweW4K/mt5meHHC1ecWcGDayuxNitp9A0YsyRQnRKHu6py8en5BfjL5Qvw9SUlIT0ehRBYl52M311ajY9U5iLRrEAWAlk2Cz5TXYj/XTvX2G9ogq8uLsaPV1XgxuLITjKxMiMRMQZMRpAfOz7sFk64epmOa4JvLytFoZdw+dqsJHy4IvSwtB7XFqbjO8tKQ9q2OiUupO2ssoz/WVnudSKBG4sysCoz0fCgfa6P/V2W6/v6MsduQVkI12bT4fqi9KAmmSiMi8HnFxTicwsKIzamiSqTYvHVxSXYmJ8a9r4SzJEJURKRd0JHoFWaVz76b2XxPJg/chuQMOF5wmyC8q7LoFy+ZtzNysrFgfdfUQLTjVdFbDKH2UjEx8G0cT3MN18N08b1EBN/HzOQsMXAfPd7IS+eez6OHmuDcs0GKNddNq1jozCZFMDgScXk+QFC7ZKASEkMer9SXhZMd1wfXIxaiWC4uiDw6wVtcChix58xJAFl/YrQNs1Ig7J+BaRi4yZPkJdVw/zR9+hYUzPsmERERERERERERERERERERERERERERERERERERESRFLlP1BIRERGRbuWJdhztHvC5/JKc5CkczdSanxKH95Zl44/HGicte29ZNhamxk/DqLy7piANfzvRhG6nW/c25jDiyd5il8G40MPVJin077880Q63qqKmdyQCND85FnfPy8fP9p32+1j1JiuIcPWVeeejj0II5MaeD3L+7tJq/P1kM3a29cIiS0i3mvFCXbvPfS1MjcOe9j6/xwsmqh1ppjAeK9Yg4tB3zMnCq/UdONU3OfD08ao8pPgIxttNMl68dik+9eZhbG/r0XWsK/JSg4oRu8bEoP2xRzCOpZdLDRxZKom3wSpLGPbo+74CKU2wIcVqRorVjD9ctgBHuwbQ63KjOD4G6THRc1+eKD3GgvtWVaBj2IlBtweJZhPiDA7Rx5oUfKwqDx+rmhzcMksCTh2/r1Cce46LCybuFoIbitKxPicZ/7P7FDxa6N9LXuz4yHFCiL+HqiS7rufoBLMJf7ysGi/WtWNvex+EAC7JTsHyjIQpCXRenpuK72w/EdQ2CWYF5UmhR52XpSfgkUvm4YUz7djb3ou82BisykzE5Wef37INDFfbFAlmHyHEG4szsK+zDy+cGf88aVdk/HhlxYy5RlqYGo+vLS7B93bWBFz31XddNK0TGyRZwo9Oh/qYJKLQSeXFUI+e9LlcXlA5/uvqCljnl0Nr74LW3QMRY4XISIPwci0gzS8H4uxAn4/XT2YTzB++FSJKJhyi6SWlJMH8wVugvec6wO0BrBav9yuaWYQQgNUKDAwGt6Gf1/giJwOItQH93vcp5edAWEJ7fagsq4ZcUQz39n3QOrrgeXN7yOMMl1QYOFw90x8jIjsdWmNrWPuQL1oIKTkxrH0oG1bBefKv+te/6mK4X9g0+fbL1kCuLIWn5nTgnRj0PgkRERERERERERERERERERERERERERERERERERFRpM3sT7QSERERzRLzkmP9xnCvyU+bwtFMvU/Oy0dpgg1PnmxB57ATiRYT3lOahctyUww7hhEhvEybBT9eVYHvbD+OhgGHrm3CaCcjx25BeowZrUPOkLb30XK8YPiKWeqxMT8Nt5VmotvphgQg3qxACIHrC9PxP3tOBbUvveHq6wvTcX1hus/lmTYL7plXMO62WJOMJ062TFpXAvCB8hyc7juBLofv0LqRj7HpZFP0/65jTQp+tqYSvz5ch+dOt8Ojaci2WXBHWTZuLs7wu60QAj9aWYYvvnMUu9p7Ax5rfnIcjvXoD53fNidL13pKOCcWg+hpB8coMq7MS8U/asMLUZ1zW+n5n48sBKqSYw3Z71RJsZoxHY84kyTBqXoism/L2fNsgiVyby+ZJYElaQmIMysojrfhiZpm7OvoQ9OgvufhsfInhKtDCW7n2C3475XlusPTJknCNQXpuKbA9/k9UhRJwCIJOIIIl99UnBF21HlOgh1z5nuPX+fYjYvMJ5h9h5KFEPj20lJcmZeK58+0wa1qKI634ZaSTCQaEFieStcWpusKV4czYYcRDAlXR/BcQkTeyYvm+gxXi6R4r+FUIQREWjKQ5n+CLaEoMF1/BVx/fMr7sVcsgrBG7+QjND1EjHGTXFB0EDEWaEGGq5WNl/jenyTBtHE9XI8/52WhgLJxfZAjnLCLuFiYNqyCNjQcMFwdyXC0yEgNuI5UVhyx408FqbQQnjDD1aabrgp/HOUlgN2mO7BuuvoSyAur4H5tM7TuXsBqgbJm6ejvQ895TPNE5jU6ERERERERERERERERERERERERERERERERERERkdFYAyEiIiKKAtcWpOMfp1rh9lICzbZZsDIzaRpGNXWEENiYn4aNYQS6L8tNwcv1HT6Xf7wqL+R9j1WdEoe/XbEI21u7sa+jD48eafC7vhRG/FEIgfeWZeP+vbUhbR9ueHKmC+f7jzXJEEJMijDeWJyBbqcbDx+q07UfCUCGzaxr3a8uLtYdQj3nswsKMeRR8fzpNqhnb4s1yfhsdSFWZSZhZUYSnjvT5nXbGFnC4rT4oI4XaaXxNpzoDS5oBYwEkoORYbPgG0tK8ZVFxXBrGsySpPuxGmtS8It1VdjT0YcXzrTh6VPeI0v5sVYsSYvHoa5+3eNamBpdvw9/rswPHNECgI9U5mJfRx9O9Q2FdbzPVBfgOj9hd/LNLAsM+O7Xh6UoPgYAsDAlcvfdry8pQdzZySeqU+JQnRIHAOhyuPCnY434w7FGXfuRBbBowmMsXsekFhZZwntKM+FRNZQk2HBFXipM0syZGcJmUuBwuAKuJwBcX5SOuwy6XvIl22ZcjDIxQORYEgKrMpOwapZfR58z3ZMaGBEEtwf5fE5E4ZNXLoZ6qg6erXvGL/j/7N13nJ5VmTfw65mWmdRJmfROKiX0EiCgVBEEISBrBVZAUbG+2EVEXVldWaXY0BVdXXQhAV7BgoAvRECKSK/SQygJaSQhmWQy7x+JhpB5+v3U+X4/n/1jc+65z3nI3Ndc5zfx3H1aouX0d0WqsbjnsnHPWdG9+JXYcP2fI7o2bvnzPXaK5mMPL+reQI0oIJtp3HFaxvGmOXtF9/oNseG6BRFrNu01U4MHRtPRh0bjzCkFLXMbfVoiWpojOtP30o17zEpmrh6kGhqiYZftY+M9D6W9pmHqxJLNXw5Ne8yKrlvu2urnQz5aTn9npPoU/wKEVJ+WaD5sTqy/8g85f03D6BHR8u639zyYywH8Dq4GAAAAAAAAAAAAAAAAAGqEg6sBAKrA9kP6x2d3mxz/cc9TsfZ1h3WM7NsSF8yZWfGD6GrBPiPa0x5cnYqI2SPbE5urqSEVs0cOjjH9WnM4uLq4ud6x3ch/Hs7ZuXHTwebNDak4dtKI+N8nXsy6TgrTr7nnA9pSqVS8f+bYOHzcsLj9peVxw/OvxF8Xr0x7n52GDsjpYNR/3DtfTQ0NcfYeU+Lk6WPiiZVrIhURe49o/+dBzqfMGBO3vLgsVnRue2rtGTuOj9YiD6JL2h7DBxV2cHVjYYfINjU0FLQpTqVSseuwgbHrsIGx94j2OPuOx2P9xi0vHhjdt098a/aMaG1qjA0bt30hQU/2Hj4oJg1oy3kNQ1ub45W12Q+jzcUxE4fH6H594vsP5n4g+y7DBuR07Yi+feLHb94xLn3k+ZwPGH695oZU/PFte+Z9ODlblOqQ5aGtzf/8nh3TvzX2Gj4o7nh5RSL37mhtjnED2uLk6WNi7xHtPV4zuE9zfGSnCfGbp1+O5T3UuDc6cPSQGPSGg3Vzqc+TBrTFh3eckNO6q9EOg/vHn19clvGaT+48MfYbOTjG9k/uUOl0hvdtiaZUqseXteSrvaX4g5LrSTEvS0nCkAQOri6kFwKKk0qlovldx0TjbjtG1533Rvf6DdEwang0zdkzUgP6J3P/Iw+Kxr12jo1PLYx47bVomLFdNIwo/KVVQG3pznDwc0+ajjk0GkZlf2lR80H7RtN+e0T3opciGhsiNXpEpJqS+7V3qqEhGiaNi42PPplmAU3RMGViYvP1OMUh+8e6NAdXpzqGRMPEsSWdv9QaJo6NlpOOj86fXVHQ4dWpAf0SW0vjm/aJ7tfWxobf31T0vVI5HFzdMLG0LwwCAAAAAAAAAAAAAAAAAEiKg6sBAKrE2yYOj31Htsd1z70SKzrXx5RBfWPOqCHRp8ADWXubIyd0xE2LlsaCF7Y9nPGjO02I0f2SP4yxJYe/m1QUdwBfKpWKD+4wPo6fPDIeWPpqbOjujj06BkX/5qa48qmXtjos940OGzusqLl7s35ZDskd2781xvYfGcdNHhFfuP3xuOH5ng9NP367kSU7NPb1xg9oi/E9HHo8fkBbXDhn+7jwvmfizsWbDpQd0dYSJ00fE3O3G1nydeXr3dNGxfULl8SSPA9kruShxgeNGRq7vXVgXL/wlVi1fkOM6tsnDh47NJo2/72v35j98KWOtpb42t7T8jqwc8/hg+L3zy4peN2vN6ClKU6eMTb2GdEeJ914f9brj540PAblcWBs/+am+MhOE2L2yPb40M09H7rVkz4NqbjxmL0dwl+kiQPa4uXXOhO/70d3mrDV9+zX9p4an/jzI/HgslU9Xp+KTc9L/+bGuPrpl9Pe98QpI+OTO0/KeR1tTY05HVz9rqmjt/mzXA6u3pjAAcuV9OYxQ9IeXN3W2BA/fNOOMb09uQPfsmlMpWLW0AFx95L0L33I1aA+Ys1qMtjfB9SsVCoVjTOnROPMKSWbo6FjaDR0DC3Z/YEqtj6H/X1zUzRMHBtNB+4TDTtNz/nWqT4tkZpUugOAmw47IDoffzqih31900H7RqrEL1JpGD86mt9xZKyf//uIDV3//PPUkEHR8qH3RqoMeVOpNe6yfbROOyu67n04ul9b+8+fFZ2XXJb9i5M8qDyViqYD985+cHUO/81TrX0iNWp4dL+Qft9byp+5AAAAAAAAAAAAAAAAAABJcqIIAEAVGdraEu+cOqrSy6hJDalUfG2vqXHlUy/F/CdfijUbumJU3z7xzqmj46AxQ0oyZ3MOh6k25nEQbSbD2lriTWO2Puhr56ED4q7FPR/82JRKxW4dgxKZuzfq35zbQcipVCq+vOeUWL9xY9z8ukPTmxtScdr24+KwcZU/PHx6e7+46IDtY/m69bFhY3e092mu2oOAh7f1ie/uPzO+c++Wg7Zz0dZU2cOa2vs0x/FpDgLfY/ig+OXjL2T8+l8eMiunA3Rf7+AxQxM7uLpl8/fDtPZ+MbZfn1i4el3aa48YPyz+zy65Hyr8ekP65Heo14lTRlXt92otOWri8Ljj5dyfp2w6Wpvj9B3Gx1vGd2z154NamuMnb94x/vLS8nhi5WvRmErFwWOHxLJ1G2LNhq4Y0dYSo/u1xp0vr8h4cPXew9vzWk9rDi+RaExF7Dik/zZ/PrA5+3PXVeMHVx85oSMeWrYq5j350lZ/PrhPU3xtr2llPbT6H94+aXjGg6tPnTk2fvzwwqz3aS/xQYHkZ3CeNR4A6CU6sx9c3XreZyOVQ29ebo1TJ0bz+46L9Vf+IWLFq5v+sLkpmubsFU1HvKksa2jaf89omDIxNj76ZGx8ZVk0ThoXDdtPiVSfPmWZvxxSfduiafZu//z/ux5/KrcvTPolZrnsL3Kcs3GPnWLDb27ocaxh2qRIDdx2fwoAAAAAAAAAAAAAAAAAUI2q738FDAAABWptaox3Th0d75w6uizz5XKgakLnVvfoXVNHx18Xr4yejtR8+6Th0S/Hw5f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      "text/plain": [
       "<Figure size 2880x535.887 with 4 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 559,
       "width": 2903
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_trace(\n",
    "    trace,\n",
    "    var_names=\"W\",\n",
    "    coords={\"observed_columns\": 3, \"latent_columns\": 1},\n",
    "    sample_dims=[\"draw\"],\n",
    "    figure_kwargs={\"sharey\": True},\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each chain appears to have a different sample mean and we can also see that there is a great deal of autocorrelation across chains, manifest as long-range trends over sampling iterations.\n",
    "\n",
    "One of the primary drawbacks for this model formulation is its lack of identifiability. With this model representation, only the product $WF$ matters for the likelihood of $X$, so $P(X|W, F) = P(X|W\\Omega, \\Omega^{-1}F)$ for any invertible matrix $\\Omega$. While the priors on $W$ and $F$ constrain $|\\Omega|$ to be neither too large or too small, factors and loadings can still be rotated, reflected, and/or permuted *without changing the model likelihood*. Expect it to happen between runs of the sampler, or even for the parametrization to \"drift\" within run, and to produce the highly autocorrelated $W$ traceplot above.\n",
    "\n",
    "### Alternative parametrization\n",
    "\n",
    "This can be fixed by constraining the form of W to be:\n",
    "  + Lower triangular\n",
    "  + Positive and increasing values along the diagonal\n",
    "\n",
    "We can adapt `expand_block_triangular` to fill out a non-square matrix. This function mimics `pm.expand_packed_triangular`, but while the latter only works on packed versions of square matrices (i.e. $d=k$ in our model, the former can also be used with nonsquare matrices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def expand_packed_block_triangular(d, k, packed, diag=None, mtype=\"pytensor\"):\n",
    "    # like expand_packed_triangular, but with d > k.\n",
    "    assert mtype in {\"pytensor\", \"numpy\"}\n",
    "    assert d >= k\n",
    "\n",
    "    def set_(M, i_, v_):\n",
    "        if mtype == \"pytensor\":\n",
    "            return pt.set_subtensor(M[i_], v_)\n",
    "        M[i_] = v_\n",
    "        return M\n",
    "\n",
    "    out = pt.zeros((d, k), dtype=float) if mtype == \"pytensor\" else np.zeros((d, k), dtype=float)\n",
    "    if diag is None:\n",
    "        idxs = np.tril_indices(d, m=k)\n",
    "        out = set_(out, idxs, packed)\n",
    "    else:\n",
    "        idxs = np.tril_indices(d, k=-1, m=k)\n",
    "        out = set_(out, idxs, packed)\n",
    "        idxs = (np.arange(k), np.arange(k))\n",
    "        out = set_(out, idxs, diag)\n",
    "    return out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll also define another function which helps create a diagonal matrix with increasing entries along the main diagonal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def makeW(d, k, dim_names):\n",
    "    # make a W matrix adapted to the data shape\n",
    "    n_od = int(k * d - k * (k - 1) / 2 - k)\n",
    "\n",
    "    # trick: the cumulative sum of z will be positive increasing\n",
    "    z = pm.HalfNormal(\"W_z\", 1.0, dims=\"latent_columns\")\n",
    "    b = pm.Normal(\"W_b\", 0.0, 1.0, shape=(n_od,), dims=\"packed_dim\")\n",
    "    L = expand_packed_block_triangular(d, k, b, pt.ones(k))\n",
    "    W = pm.Deterministic(\"W\", L @ pt.diag(pt.extra_ops.cumsum(z)), dims=dim_names)\n",
    "    return W"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With these modifications, we remake the model and run the MCMC sampler again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [W_z, W_b, F, sigma]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1c874aeecd0349479e603a58847e182b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/osvaldo/anaconda3/envs/arviz_1/lib/python3.14/site-packages/pymc/step_methods/hmc/quadpotential.py:316: RuntimeWarning: overflow encountered in dot\n",
      "  return 0.5 * np.dot(x, v_out)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 4 chains for 2_000 tune and 1_000 draw iterations (8_000 + 4_000 draws total) took 15 seconds.\n",
      "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n",
      "The effective sample size per chain is smaller than 100 for some parameters.  A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n"
     ]
    }
   ],
   "source": [
    "with pm.Model(coords=coords) as PPCA_identified:\n",
    "    W = makeW(d, k, (\"observed_columns\", \"latent_columns\"))\n",
    "    F = pm.Normal(\"F\", dims=(\"latent_columns\", \"rows\"))\n",
    "    sigma = pm.HalfNormal(\"sigma\", 1.0)\n",
    "    X = pm.Normal(\"X\", mu=W @ F, sigma=sigma, observed=Y, dims=(\"observed_columns\", \"rows\"))\n",
    "    trace = pm.sample(tune=2000, random_seed=rng, target_accept=0.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$W$ (and $F$!) now have entries with identical posterior distributions as compared between sampler chains, although it's apparent that some autocorrelation remains.\n",
    "\n",
    "Because the $k \\times n$ parameters in F all need to be sampled, sampling can become quite expensive for very large `n`. In addition, the link between an observed data point $X_i$ and an associated latent value $F_i$ means that streaming inference with mini-batching cannot be performed.\n",
    "\n",
    "This scalability problem can be addressed analytically by integrating $F$ out of the model. By doing so, we postpone any calculation for individual values of $F_i$ until later. Hence, this approach is often described as *amortized inference*. However, this fixes the prior on $F$, allowing for less modeling flexibility. In keeping with $F_{ij} \\sim \\mathcal{N}(0, I)$ we have:\n",
    "\n",
    "$X|WF \\sim \\mathcal{N}(WF, \\sigma^2 I).$\n",
    "\n",
    "We can therefore write $X$ as\n",
    "\n",
    "$X = WF + \\sigma I \\epsilon,$\n",
    "\n",
    "where $\\epsilon \\sim \\mathcal{N}(0, I)$.\n",
    "Fixing $W$ but treating $F$ and $\\epsilon$ as random variables, both $\\sim\\mathcal{N}(0, I)$, we see that $X$ is the sum of two multivariate normal variables, with means $0$ and covariances $WW^T$ and $\\sigma^2 I$, respectively. It follows that\n",
    "\n",
    "$X|W \\sim \\mathcal{N}(0, WW^T + \\sigma^2 I )$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [W_z, W_b, sigma]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dadcd7700bf14e2eb5fee1b778e01f95",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/osvaldo/anaconda3/envs/arviz_1/lib/python3.14/site-packages/pymc/step_methods/hmc/quadpotential.py:316: RuntimeWarning: overflow encountered in dot\n",
      "  return 0.5 * np.dot(x, v_out)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 4 chains for 30 tune and 100 draw iterations (120 + 400 draws total) took 9 seconds.\n",
      "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n",
      "The effective sample size per chain is smaller than 100 for some parameters.  A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n"
     ]
    }
   ],
   "source": [
    "with pm.Model(coords=coords) as PPCA_amortized:\n",
    "    W = makeW(d, k, (\"observed_columns\", \"latent_columns\"))\n",
    "    sigma = pm.HalfNormal(\"sigma\", 1.0)\n",
    "    cov = W @ W.T + sigma**2 * pt.eye(d)\n",
    "    # MvNormal parametrizes covariance of columns, so transpose Y\n",
    "    X = pm.MvNormal(\"X\", 0.0, cov=cov, observed=Y.T, dims=(\"rows\", \"observed_columns\"))\n",
    "    trace_amortized = pm.sample(tune=30, draws=100, random_seed=rng)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unfortunately sampling of this model is very slow, presumably because calculating the logprob of the `MvNormal` requires inverting the covariance matrix. However, the explicit integration of $F$ also enables batching the observations for faster computation of `ADVI` and `FullRankADVI` approximations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/osvaldo/anaconda3/envs/arviz_1/lib/python3.14/site-packages/pymc/model/core.py:1256: UserWarning: total_size not provided for observed variable `X` that uses pm.Minibatch\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ec12909273304c0fa7192178e864f3a4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Finished [100%]: Average Loss = 1,758.4\n"
     ]
    }
   ],
   "source": [
    "coords[\"observed_columns2\"] = coords[\"observed_columns\"]\n",
    "with pm.Model(coords=coords) as PPCA_amortized_batched:\n",
    "    W = makeW(d, k, (\"observed_columns\", \"latent_columns\"))\n",
    "    Y_mb = pm.Minibatch(\n",
    "        Y.T, batch_size=50\n",
    "    )  # MvNormal parametrizes covariance of columns, so transpose Y\n",
    "    sigma = pm.HalfNormal(\"sigma\", 1.0)\n",
    "    cov = W @ W.T + sigma**2 * pt.eye(d)\n",
    "    X = pm.MvNormal(\"X\", 0.0, cov=cov, observed=Y_mb)\n",
    "    trace_vi = pm.fit(n=50000, method=\"fullrank_advi\", obj_n_mc=1).sample()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results\n",
    "When we compare the posteriors calculated using MCMC and VI, we find that (for at least this specific parameter we are looking at) the two distributions are close, but they do differ in their mean. The two MCMC posteriors agree with each other quite well with each other and the ADVI estimate is not far off."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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O6b777mtqisf56quv9Morr3hdj4yM1DPPPKPExMSAnHes2tpaXXfddVqyZElA9129erV+9rOfNbtItK1wu9164okndMstt6iggA77ABAoFHcBAAAAAVBQU6dat/W7JLslxPg2kjE+Vo6BfQOYXfib0CVVabGeR2Qc8e3hYhXZvdvZlMxc6zEUAAAAACBJEydOVMeOHT2uzZ8/v1l7e7u/U6dOmjBhQrP2trNu3TrLcWeSvHaxasva6vOWeObh6NChQ7ryyiu1YcOGkJy3ePFizZkzp0lFZBEREXrmmWeUkpLiNWbJkiV6/fXXm5HhD8Vu99xzj2WXsdmzZ2vkyJHNOscT0zR17733BnzE5BFZWVm6/vrrVV5eHpT9W4uGhgbdddddlgV8AICmiWjpBAAAAIC2IKei1jame3yM3HuzZRaVWsY5Rw2R4XQGKrVWIcJhaEafzvrLlmyvMaakhTXS5TZ7uXPz5ejRJaD5AQAAAGh7IiIiNG3aNL322muN1nbt2qWNGzdq+PDhfu+7adMm7dixw+PatGnTFBER3F/N2BWTxMXFadiw9tUtWmq7z1vimYebkpISXX311dq/f79tbOfOnXXqqadqzJgxGjx4sFJSUo4WWRUUFCg3N1fLly/Xl19+qc2bN1vu9cknn+i5557T7bff7nfOXbp00WOPPaabb77Za8wf/vAHnXTSSU36XnK5XLrzzjtVXFzsNea0007Tdddd5/fevvjHP/6hRYsWeVxLSkrSpEmTNGbMGPXt21dJSUlyu90qLi7W7t27j379a2qsO/bv3LlTt99+u/7617/KMIxgfBph7/7779fChQt9ik1NTdVZZ52l0aNHq1+/furWrZsSEhIkSWVlZSotLVVeXp42bdqkTZs2ad26dXRHA9CuUdwFAAAABEC2zUhGSeoWHy3X54xk9GZ673S9sjVbLosGaP/MLdPlcTFSlfevt5lLy3cAAAAAvpk5c6bHYh/ph25MTSn2mTdvnte1GTNm+L2fv7Zs2WK5PmLEiJAUHIWjtvi8JZ55OGloaNBtt92mffv2Wcb169dPv/jFL3TBBRd4fTY9evRQjx49NHr0aN16661avny5nnzyScvn/dJLL2ns2LEaN26c37mfffbZuuqqq/TGG294XK+vr9fs2bM1b968o0U4vvrTn/6kVatWeV3v3LmznnjiiaAUReXl5ekPf/hDo+txcXGaNWuWrrzySsXFxXm8d/To0br00ktVUlKil19+WW+88Ybq6+u9nvXNN9/o9ddf1zXXXBOo9FuNP//5z/rggw9s4/r376+bb75Z5557rtfv/U6dOqlTp07KzMw8+r1smqa+++47LVq0SB9//LEKC1uuc3/37t21ffv2RtfPOuss5eTkeLzn8ccf14UXXhjs1AC0YYxlBAAAAAIgx6a4q2NMpKIdhlzrrN9lqeREOTJ7BTCz1iMtNkqnd021jCmua1BFhw6WMe7D+YFMCwAAAEAbNmjQIA0aNMjj2sKFCy1/ie9JXV2d164lgwcP9npWIG3dutVyvX///kHPIVy1xect8czDyV/+8hetWLHCMua6667TBx98oBkzZvhVdDdu3Di9++67uvTSS73GmKaphx56SLW19h3mPbnrrrssO3Pt379fDz74oF97rlixQn/+85+9rjscDj311FNKTbV+Taip9u7dq4qKiuOu9e7dW++++65uvPFGr4Vdx0pJSdHdd9+tN954Q506dbKMnTt3rg4ePNisnFub77//Xs8//7xljMPh0K9+9SvNnz9fU6ZM8bvg1DAMnXTSSXrggQe0dOlSPfTQQ+rWrVtz0gaAVoXiLgAAACAA7Iq7usXHyL1rr1RWYRnnPGGoDEf7/Wf6RX0zbGN2xMRarpsUdwEAAADww8yZMz1eLykp0VdffeXXXl999ZVKSko8roWii5Npmjpw4IBlTL9+/YKeRzhrS89b4pmHk6ysLL344ote1x0Oh+bOnat77rmnyZ3UnE6nHn74Yd10001eY/bt26e///3vTdo/KipKc+fOtezM9dFHH+mf//ynT/sVFRXpzjvvlNvt9hpz8803a+zYsX7n2lS9evXSW2+9pczMTL/vPfHEE/XGG2+og8UbD2tqavT00083J8VWpaGhQffee69cLpfXmKioKP35z3/WLbfcEpAuglFRUbriiiv06aefev07HQDamvb7WyMAAAAggHIqrN8R2T0+Rq7v7EcyRrTTkYxHnJSWpB4JMZYxqxVpuW7mF8m0eEEJAAAAAI41bdo0r79sthq558n777/v8XpERISmTZvmd27+KioqUl1dnWVMe+900paet8QzDydz5861fBb33XefpkyZEpCzbr/9dk2YMMHr+l/+8hfb7wtvevbsqUceecQy5ne/+5127txpGWOapu666y7l53t/E96YMWN08803NynPpoiJidGf//xnpaWlNXmPzMxMzZ0713KE5KJFi7R3794mn9GavPfee9q9e7dlzNy5c3XGGWcE/OyIiAh179494PsCQDiiuAsAAAAIgGybzl3dYyPlWm89JsHomCKjV/t+wdUwDE3paf0C2+7YeOtN3G6ZBUUBzAoAAABAW9axY0dNnDjR49pXX32loiLffr4oKirSv//9b49rEydOVMeOHZuco68OHz5sG2M3Uqyta0vPW+KZh4tt27bps88+87p+wQUX6KqrrgrYeYZh6Mknn/Q6UjA/P19Llixp8v5TpkyxHP9YU1Oj22+/XdXV1V5j/vKXv+ibb77xut6hQwc99dRTcjqdTc7TXzfccEOTOnb92Lhx4zR9+nSv6263W6+//nqzzwl3LpfLsludJF1++eWaNGlSiDICgLar+X0PAQAAgHauor5BpXUNljHDCgukKu8veEmS88Rhlu/6ay+m9ErTy1sOyPSyvj/e+2iAI8zD+VJ609+FCQAA4E15XYPya5rWCQMIhLSYKCVG8dJ+oM2YMUNffvllo+v19fX66KOP9POf/9x2jwULFqi+vt7jWqjGRhUXF9vGhKroKJy1lect8czDxTvvvCPT9PxKRnR0tO64446An9mxY0ddcsklXouI5s+fr/POO6/J+//617/WunXrtGPHDo/ru3bt0iOPPKLHHnus0dq6dev07LPPet3bMAw98cQTSk9Pb3J+/urSpYtuuOGGgO03Z84cffrpp6qqqvK4/tFHH+m+++5TVFRUwM4MN19++aVlgWmvXr109913hzAjAGi7+AkQAAAAaKbsCuuuXZLUe/ce2xhnOx/JeERGXLROSkvSmvwyj+u50TGqdjgV6/Y+etF9uEDOkcHKEAAAtEcbCsr05Po92lXq+Rd4QKgYkjKT43TPCX01omNiS6fTZpx11llKTk5WaWlpo7V58+b5VOzjbaRfSkqKzjzzzGbn6IuaGvufT711+mlP2srzlnjm4aCmpkYfffSR1/VLL71UXbt2DcrZ11xzjdfirhUrVqiurq7JxUXR0dH64x//qIsvvthrAdN7772ncePGHTeGtLS0VHPmzFFDg/c3Ql577bU6/fTTm5RXU11zzTWKjY0N2H7p6em66KKL9Oabb3pcLy0t1bfffhvSvw9C7d1337VcnzVrFn//AECAMJYRAAAAaKacylrL9Qi3W4nbd1nGGJ07yugauncrhrupvTp7XTMNQwdsXhgyc/MDnRIAAGjHVuaW6Oavt1DYhbBgStpVWqVZX23WytySlk6nzYiKitKUKVM8rm3evFk7d+60vH/btm3aunWrx7UpU6aErHNLXZ19Z8G23EXGV23leUs883CwYsUKVVRUeF0/tvAp0Lp27ep1zGB1dbXWrVvXrP0zMzP1wAMPWMY89NBD2rt379GP77//fh08eNBr/IgRIzRnzpxm5eUvh8OhqVOnBnxfu2drNZaytaupqdHy5cu9rqekpHj9exYA4D+KuwAAAIBmyqm0fpfs+LJiGdXWMc4ThjKS8RhndEtVtNP7jyv74qxHM7rzCgOdEgAAaKdM09RLm/erwcuoJaClNJim/nfzAa9jwOC/Cy+80Ouaty5NR8yfP9/rWihH9PlS6BMZGRmCTMJfW3jeEs88HHz99dde17p166YRI0YE9fzRo0d7Xdu8eXOz97/wwgs1ffp0r+uVlZWaPXu26urq9MYbb+jzzz/3GpuYmKhnnnkm5N+TY8eOVVpaWsD3HTlypHr27Ol1fdWqVQE/M1ysXr3asnPghRdeqOjo6BBmBABtG8VdAAAAQDPZjWWcXJRnu4fzhKGBSqdNiItwakJGB6/rB2JtOnflFfJLLgAAEBAV9S5tKa5s6TQAjzYXV6ii3vu4cvhnxIgR6tu3r8e1BQsWyOXy/LVuaGjQggULPK5lZmYGvbDjWL4UTNTX14cgk/DXFp63xDMPB999953XtZNPPjno5w8YMMDr2rZt2wJyxkMPPaQ+ffp4Xd+yZYtuu+02Pfnkk5b7PProo+rRo0dAcvLH+PHjg7b3uHHjvK7t2rXLp9GprdGGDRss10877bQQZQIA7QPFXQAAAEAzHaryPpYxwu3WSYcPWd5vZKTJwUjGRib16Oh17UBcvPXNNbVSOb+EBQAAAOAfb12X8vLytGzZMo9r//73v1VQUOBxbcaMGYFKzSe+dEnxpdNTe9Han7fEM29pdXV12rVrl9d1byMTAyk5OdnrmtV4RH/Ex8frj3/8o+X325IlSywLCS+77DKdd955AcnHXwMHDmyRvd1ut+X3R2vmbTSt9MMYzOHDh4cwGwBo+yJaOgEAAACgtbMq7hpdXKgYm3fI0rXLs/EZKYp1OlTtcjdasy3ukuTOK5AzyXp8IwAAgJ2ESKeGdIinexfC0tAOCUqIdLZ0Gm3KT37yE82dO1dud+OfQ+bPn6+JEyc2uu5thJ/D4bAcZRYMMTExtjHV1dVKSOBnJan1P2+JZ97S9u3bZ1nQlJSUpOzs7KDm0NDQ4HXt8OHDATtn0KBBuvfee/Xb3/7W73sHDBig+++/P2C5+GvQoEEttve+ffs0bNiwoJ3fUvbu3et1LTMzk79zACDAKO4CAAAAmsFtmjpsUdx1Rr79i2jOUUMCmVKbEeN0amLXDvr0QGGjtWybsYzSD6MZ1a93EDIDAADtiWEYumloT835dpsaGPuMMBJhGLppaA8ZhtHSqbQpGRkZGjdunL799ttGa59//rkqKiqO+4V1SUmJlixZ4nGv8ePHKz09tF2aU1JSbGMKCwuVlpYW/GRagdb+vCWeeUs7dMi6W/tDDz0Uokw8Ky0tDeh+V1xxhVasWKFPPvnE53vi4uJsu34FU3x8fFD/2/Q23vWI/Pz8oJ3dkqwKB+2+JgAA/zGWEQAAAGiGgpo61bs9/5Iv0u3WhII8y/uNLp3l6NI5GKm1CZO6d/J4vcYZobxo63cnm3mNi8IAAACaYmx6iv58+lD1S44TZTRoaYakfslx+vPpQzUmPaWl02mTvI3Wq6mp0ccff3zctY8++shr156WGNGXkZFhG+NtpGB71Zqft8Qzb2l5edav+7S02lrvb0hsqt/97nfq3r27z/EPPPBASMZTepOYmNii+7fF//5qampUUVHhdT0pKSmE2QBA+0DnLgAAAKAZDlV6f5Hs5KICJbi8t8aXGMloZ2x6smKcDtV4Gs0YG6fOtTVe73Xntb0XzwAAQMsZ0TFRb08aqfK6BuXX1LV0OmjH0mKilBjFS/vBdM455yg+Pl6VlY3Hsc6bN0+XXHLJcR97kpCQoHPOOSdoOXrTsWNHRUZGWo6Jy8nJCWFG4a81P2+JZ97SrApcwkEwirsSExM1d+5cXXHFFZbfd5I0ffp0XXjhhQHPwR/BHg8YERGhmJgY1dR4fo2quro6qOe3BLvPKdgFdQDQHvETIAAAANAMhyxGMp7py0jGExjJaCXG6dTY9GR9dbC40dqBuHidVFLk9V46dwEAgGBIjIqgsAZo42JjY3Xeeefpvffea7S2du1a7d+/Xz179tTu3bu1ceNGj3ucd955iomx7jYcDIZhqEePHsrKyvIas2vXrhBmFP5a8/OWeOYtLRjFU62By+WS6cO46v/3//5fCLKxFuziriNneCvuaovfI3afE527ACDwGMsIAAAANIO34q4ol0unFtqMZOyaLkd6WjDSalMmdkn1eP1AbLzlfWZBsUyXKxgpAQAAAGjjZs6c6XVt/vz5krx3cbK7P9gGDx5sub5z584QZdJ6tObnLfHMW1JDg3XH9raotLRUd9xxh0+f+0MPPSRXC782YxjBH6ptdYYvRXCtjd3X1O1u3IEfANA8FHcBAAAAzeBtLOOY4gLF2bx4xUhG35ya0UGeXjI6EBdnfaPbLbOwcccvAAAAALAzevRode/e3ePaBx98oIaGBn3wwQce13v06KGTTjopmOlZGjLEukP0hg0b2mVBipXW/LwlnnlLio6ObukUQu7Xv/61z6M+V69erRdeeCHIGVnzNHI1lGe0xe8Ru8+pvLw8RJkAQPtB/3AAAACgGbx17jqDkYwBkxoTqeEdE/V94fEvDO236dwlSWZuodS5U7BSAwAAANBGGYahGTNmeCxKyM7O1nPPPae8PM/dmmfMmBGSTjHejBo1ynK9qqpKmzdv1siRI0OTUCvQmp+3xDNvSbGxsZbrL7/8sk4//fQQZRN8b731lj777DO/7nnppZc0duxYnXLKKUHKylpFRUVQ93e73aqqqvK63lIjW4MpzuYNl2VlZSHKBADaDzp3AQAAAM1w0EPnriiXS6cW5FveZ3TLkIOiI5+d1qVDo2t5MbGqM6x/pHHnFQQrJQAAAABtnFXRzssvv+zxumEYmj59ejDTsjVq1CglJSVZxixZsiRE2bQerfV5SzzzlpSammq5XlpaGqJMgm/r1q164okn/L7P7XbrrrvuUlFRURCyshfs4i67/Tt27BjU81tCVFSUUlJSvK5T3AUAgUdxFwAAANBEbtPUYQ+du04uLlSsm5GMgTQ+o3Fxl9swlBNr/U5BM78wWCkBAAAAaON69Oih0aNHe1wzTdPj9ZNPPlk9evQIZlq2IiIiNH78eMuYjz/+OETZtB6t9XlLPPOW1LVrV8v1kpKS0CQSZJWVlbr99ttVV1fnNSYxMdHrWl5enu655x6v/y0FU1lZmYqLi4O2/759+yzX09LSgnZ2S8rIyPC6tmPHjhBmAgDtA8VdAAAAQBMV1NSpwcOLUhMLcm3vZSSjf/omxSotJrLR9f02beDNXIq7AAAAADTdjBkzghofLOedd57l+r59+7R69eoQZdN6tNbnLfHMW0qvXr0s13Nz7V8jag3+53/+R3v37vW6Pnz4cM2bN8+ym9PXX3+tV155JfDJ+WDbtm0ttnc4FIAGQ9++fb2u7du3L6gFdQDQHlHcBQAAADSRp5GMTtOtcYU+jGRMa3st2YPJMAyNSU9pdD07Nt7yPsYyAgAAAGiO8847T7GxsT7FxsbGavLkyUHOyDdnn3227bi4//u//wtRNq1Ha33eEs+8paSkpKh79+5e19euXRvCbILj/fff14cffuh1PSEhQXPnzlWPHj30+OOPW+41d+5cff/994FO0db27dtbbO/+/fsH7eyWNGSI9RtXW+I5A0BbRnEXAAAA0ESHPIxkHF5SrOSGesv7nCMGBSulNu0UD8VdB+Ksi7tUXimzuiY4CQEAAABo8xISEjRp0iSfYs855xwlJCQEOSPfREVFaebMmZYxS5cu5ZfvP9Jan7fEM29Jo0aN8rq2adMmVVVVhS6ZANu9e7ceeeQRy5hHHnnkaHeqs846S1dddZXX2Pr6es2ePVvl5eUBzdPOqlWrWmTvXr16hdXfE4F0wgknWK5/8cUXIcoEANoHirsAAACAJjrkoXPXxMI82/ucIwcHI502b0znZBk/urbfpnOXJJl5jGYEAAAA0HR2BTP+xoXK1VdfrZiYGK/rpmnq4YcflmmaIcwq/LXW5y3xzFvKGWec4XWtvr5e3377beiSCaDa2lrNnj3bsjjtpz/9qaZMmXLctbvuuktDhw71ek92drYeeOCBgOXpi6+//lplZWUB33fXrl2WnbvGjBkT8DPDxQknnKDk5GSv6wsWLFBFRUUIM2p5ERERXtdqaxu/jgwA/qC4CwAAAGiiRp27TFMTCqyLu4xOHWR06RzErNqulOhIDepwfDHXgbg42/sYzQgAAACgOcaNG6f09HTLmIyMDJ1yyikhysg36enpuuKKKyxjNm7cqP/93/8NUUbemaapb775pqXTkNR6n7fEM28pZ5xxhqKioryuh8PXuykee+wxy8Kl/v3769e//nWj61FRUZo7d67i472/Ie/jjz/WP/7xj4Dk6Yv6+np98sknAd93wYIFluvjx48P+Jnhwul0WhY2VlVVaf78+SHLJxxER0d7XaupYbIAgObxXj4KAAAAwNKPO3cNrChTeq31D+rOEYNlGD/uPwVfje2coq3FlUc/Lo+MUmlEpOUoTDp3AQAAAGgOh8OhW2+9VcuWLfMaM378eDkc4fd++v/3//6f5s+fr6KiIq8xzz33nEaOHKlx48aFMLP/qqur03333afq6mpNmDChRXI4Vmt+3hLPvCUkJiZqypQpXgtZNm7cqK+//lqnnXZaaBNrhsWLF+vvf/+71/WYmBj98Y9/9NoprlevXvrtb3+rO++80+sejz32mE444QQNGDCg2fn64vXXX9eFF14op9MZkP3Ky8v1z3/+0+t6bGysZfFTW3DxxRfrgw8+8Lr+0ksvaerUqerQoUMIs2o5Vp3MCgp48ymA5qG4CwAAAGiiQ1XHF3LZde2SJMeIQcFKp104uXOyXtuec9y1/XHxGl5W4vUeirsAAAAANNcll1yiSy65pKXT8FtKSooeeOABzZ4922uMy+XSLbfcotdee00jRowIYXZSTk6O5syZo/Xr1+vss88O6dlWWuvzlnjmLeXnP/+5ZZei//mf/9G7776r1NTU0CXVRL6MTfzNb36jfv36WcZMmzZNy5cv13vvvedxvaamRrNnz9a7776r2NjYJufrq507d+pvf/ubrrzyyoDs96c//cmyiPKcc85RnA8d51uzMWPGaMCAAdqxY4fH9fz8fD300EN67rnnQpxZy+jUqZPXtf3794cwEwBtUXi+rQAAAAAIcy7T1OGquuOuTSzItb4pKUGO3t2DmFXbNyw1QZGO4zufHYjz3uZfYiwjAAAAgPZtypQpOv/88y1jKisrdd111+nrr78OUVbSokWLNGPGDK1fvz5kZ7YXPPPQGzZsmCZPnux1PScnR7feeqvq6uq8xgSay+Xy+576+nrNmTNHZWVlXmOmTp3qc/HjAw88oMzMTK/ru3bt0qOPPup3nk31/PPPKy/P/s2ZdrZv36633nrLMuaaa65p9jmtwa9+9SvL9U8++UTvvPNOiLJpWb169fK69t1338ntdocwGwBtDcVdAAAAQBMUVNepwTSPftyjqlK9qyot7pCcwwfKCNOxDa1FTIRTQzokHHctO9b6XZBmfpFMXjwBAAAA0I797ne/08CBAy1jysvLddNNN+mFF14IagHK3r17df3112v27NmWBSRoHp556N11112WHajWrFmjG2+8UYWFweswbpqmvvrqK1199dX68ssv/b5/7ty52rBhg9f1nj176uGHH/Z5v9jYWM2dO1fR0dFeY95991199NFHfuXZVCUlJbr11ltVVVXV5D0KCgr0y1/+UvX19V5jJkyYoKFDhzb5jNbknHPO0ejRoy1jHnnkEcsxn01VWlqqrVu3Bnzfpho8eLDXtYKCAv373/8OYTYA2hp+swQAAAA0waGq2uM+tu3aJck5wvsP+PDdiWlJx32836Zzl+rqZZaWBzEjAAAAAAhv8fHxeumll5SWlmYZ53K59Pzzz2vmzJn64osvZB7zpqbm2r17t+69915NnTpV33zzTcD2hWc889Dr0aOH7r33XsuY5cuXa/r06QEv8igpKdG//vUvTZs2TTfeeKNWrFjh9x5ff/21Xnn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      "text/plain": [
       "<Figure size 1200x535.887 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 559,
       "width": 1211
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "col_selection = dict(observed_columns=3, latent_columns=1)\n",
    "\n",
    "dt = az.from_dict(\n",
    "    {\n",
    "        \"posterior\": {\n",
    "            \"MCMC_explicit\": trace.posterior[\"W\"].sel(**col_selection),\n",
    "            \"MCMC_amortized\": trace_amortized.posterior[\"W\"].sel(**col_selection),\n",
    "            \"FR-ADVI_amortized\": trace_vi.posterior[\"W\"].sel(**col_selection),\n",
    "        }\n",
    "    }\n",
    ")\n",
    "\n",
    "pc = az.plot_dist(\n",
    "    dt,\n",
    "    cols=None,\n",
    "    aes={\"color\": [\"__variable__\"]},\n",
    "    visuals={\n",
    "        \"title\": False,\n",
    "        \"point_estimate_text\": False,\n",
    "        \"point_estimate\": False,\n",
    "        \"credible_interval\": False,\n",
    "    },\n",
    ")\n",
    "pc.add_legend(\"__variable__\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Post-hoc identification of F\n",
    "\n",
    "The matrix $F$ is typically of interest for factor analysis, and is often used as a feature matrix for dimensionality reduction. However, $F$ has been\n",
    "marginalized away in order to make fitting the model easier; and now we need it back. Transforming\n",
    "\n",
    "$X|WF \\sim \\mathcal{N}(WF, \\sigma^2)$\n",
    "\n",
    "into\n",
    "\n",
    "$(W^TW)^{-1}W^T X|W,F \\sim \\mathcal{N}(F, \\sigma^2(W^TW)^{-1})$\n",
    "\n",
    "we have represented $F$ as the mean of a multivariate normal distribution with a known covariance matrix. Using the prior $ F \\sim \\mathcal{N}(0, I) $ and updating according to the expression for the [conjugate prior](https://en.wikipedia.org/wiki/Conjugate_prior), we find\n",
    "\n",
    "$ F | X, W \\sim \\mathcal{N}(\\mu_F, \\Sigma_F) $,\n",
    "\n",
    "where\n",
    "\n",
    "$\\mu_F = \\left(I + \\sigma^{-2} W^T W\\right)^{-1} \\sigma^{-2} W^T X$\n",
    "\n",
    "$\\Sigma_F = \\left(I + \\sigma^{-2} W^T W\\right)^{-1}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For each value of $W$ and $X$ found in the trace, we now draw a sample from this distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# configure xarray-einstats\n",
    "def get_default_dims(dims, dims2):\n",
    "    proposed_dims = [dim for dim in dims if dim not in {\"chain\", \"draw\"}]\n",
    "    assert len(proposed_dims) == 2\n",
    "    if dims2 is None:\n",
    "        return proposed_dims\n",
    "\n",
    "\n",
    "linalg.get_default_dims = get_default_dims"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "post = trace_vi.posterior\n",
    "obs = trace.observed_data\n",
    "\n",
    "WW = linalg.matmul(\n",
    "    post[\"W\"], post[\"W\"], dims=(\"latent_columns\", \"observed_columns\", \"latent_columns\")\n",
    ")\n",
    "\n",
    "# Constructing an identity matrix following https://einstats.python.arviz.org/en/latest/tutorials/np_linalg_tutorial_port.html\n",
    "I = xr.zeros_like(WW)\n",
    "idx = xr.DataArray(WW.coords[\"latent_columns\"])\n",
    "I.loc[{\"latent_columns\": idx, \"latent_columns2\": idx}] = 1\n",
    "Sigma_F = linalg.inv(I + post[\"sigma\"] ** (-2) * WW)\n",
    "X_transform = linalg.matmul(\n",
    "    Sigma_F,\n",
    "    post[\"sigma\"] ** (-2) * post[\"W\"],\n",
    "    dims=(\"latent_columns2\", \"latent_columns\", \"observed_columns\"),\n",
    ")\n",
    "mu_F = xr.dot(X_transform, obs[\"X\"], dims=\"observed_columns\").rename(\n",
    "    latent_columns2=\"latent_columns\"\n",
    ")\n",
    "Sigma_chol = linalg.cholesky(Sigma_F)\n",
    "norm_dist = XrContinuousRV(sp.stats.norm, xr.zeros_like(mu_F))  # the zeros_like defines the shape\n",
    "F_sampled = mu_F + linalg.matmul(\n",
    "    post[\"sigma\"] * Sigma_F,\n",
    "    norm_dist.rvs(),\n",
    "    dims=((\"latent_columns\", \"latent_columns2\"), (\"latent_columns\", \"rows\")),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comparison to original data\n",
    "\n",
    "To check how well our model has captured the original data, we will test how well we can reconstruct it from the sampled $W$ and $F$ matrices. For each element of $Y$ we plot the mean and standard deviation of $X = W F$, which is the reconstructed value based on our model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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vv2rp0qVed67KyMjQ2LFj9dZbbxW6z7Fjxyo1NdV0jM1mU/PmzdWpUyc1aNBAtWvXVoUKFRQREaHQ0FClp6crLS1NqampSkxM1I4dO7Rjxw5t2LBBiYmJhe6tpDAMQyNGjPC4k2nVqlXVpUsXtW7dWvHx8apYsaJCQ0OVmpqqv/76S7///ruWLFkS4K6Lh1GjRmnhwoX5GluhQgVddtllatOmjS644IJT1ytJp65Xhw4d0qZNm7Rp0yb99ttvfj8OuDQYMWJEvr4+hoWF6fLLL1eXLl3UqFEjValSRREREcrMzFRiYqI2bdqkJUuW6IcffvAaClu4cKEqV66skSNH+urDOMfJz8sdO3bkWW/QoIE6deqkZs2aqWLFiqpQoYIcDoeSkpL0xx9/6Pvvv9fq1au9fizTpk1Tz549VatWLX98GAAAAMA53DLk9PDLjsk5TiWmZSnDmff3sT169FD79u29/rx5ypQp6tOnjzp27FjkfgH4FsExAAAAFCurV6/2OqZGjRpex7z88sv65ptvTMfExcXptttu06233qry5cvnOaZq1aqqWrWqmjZtqttuu0179uzRiy++qG+//dbjvKtXr9arr76q+++/32ufhTF69Ohzdi2y2+267bbbdM8993j8WCSpQ4cOGjhwoPbu3XtqjkmTJik7OzvP8TfffLPHN0hHjBih7t2757vvSpUqeR2zYsUKPffcc6Zj7Ha7rr32Wt1xxx0e31CrWLGiKlasqIYNG6pXr15KSUnRa6+9prlz53r8WI8cOaKHH35Yb7/9tiwWi/cPyINVq1Zp3LhxXsfFxcXpjjvu0I033ugx2BMXF6e4uDjVqlVLLVq00E033SQpN2C5aNEiLVq0KF9HEtaoUUPbt28/5/7LLrtM+/bty/Mxzz77rK677jqvc5dUqampeb7WIiMjNWTIEPXv318RERF5PjYhIUGdO3fWXXfdpW3btpm+tj/++GPNmTPHtJfIyEjdeOONGjRokCpXrpznmMqVK6ty5cpKSEhQv379dOjQIU2dOlULFizw+Ab0zp07NX78eD3//POm63vz2Wefafr06V7HVatWTffcc4+uueYaj0cKV6hQQRUqVFCdOnXUpk2bU/dv3bpVixYt0pdffunxNZkfDodD999/v9cdmuLj4/XII4/o6quvltV67mbs8fHxio+PV9u2bTVs2DB99913euaZZ0x7y8nJ0f3336/PPvtM5cqVK/THYGb48OHnHOccGRmpQYMG6fbbb1dUVJTHx3bt2lUjR47Uxx9/rBdffNF0d8xffvlFy5cvV6dOnQrc4/r167V8+XLTMddcc43uvfdenX/++R7HlC9f/tTXs4YNG6pr166najt27NDSpUv17bff5vso4JJ2Hfzkk0+0f//+c+5v2LChHnvsMV100UUeH9usWTP16tVLjz32mN+OYi6upk+frs8++8zruPr162vo0KG6/PLLPQb9T14H6tWrd+rf2zAMrVu3Tl9++aW++uqrfB3Fet11153zOkpMTDzjNX22JUuW5Ov73eJo5syZWrx4sekYi8Wim266Sffdd58qVKhwTj06OloJCQlKSEhQ3759lZiYqOeee87rvLNmzVLr1q3VrVu3In0Mnrz77rt5XnMuueQSPfLII2rQoIHHx1588cUaOHCgtm/frvHjx5t+bjocDk2ZMkWTJk3ySd8AAACAP9lsNs2ePVstWrTw+HNXKfe/p4YPH65ff/21SD97BeB7BMcAAABQrHjbISw8PFz16tUzHbNmzRq9+uqrpmMuvvhivfDCC3m+WWWmdu3aevnll7VgwQI9/vjjHo9se+ONN3TFFVfoggsuKND8+XH2G8n16tXTK6+8ojp16uR7jpo1a576s1noxWzXtLi4OJ++qXn8+HGNGDHCdBeGmjVrasqUKWrSpEmB5i5fvrxGjBihK664QnfffbeOHDmS57jVq1dr/vz56tevX4HmPyk1NTVfR8h1795dY8eOLfDr76TatWvr3nvv1b333qsffvghX6EenCmvHejatGmjl156yWN4Ky8JCQkea3/99Zeeeuop08c3adJEU6ZMOeNzMj8qV66sp59+WpdffrkeeOABj7trffrpp+rdu7c6dOhQoPlPSkxMzFcQ8pZbbtHDDz+c76OEz9aoUSM1atRI//3vf/Xll18W+piumTNnasuWLaZjWrZsqWnTpik+Pj7f83br1k0XXnihHnzwQf34448ex+3bt0+TJk3Sk08+me+5C+LswML//d//6ZVXXsn3TokWi0V9+/ZVmzZt1L9/f4+7WUnSW2+9VajgmLdjlP/3v/+pb9++BZ73dA0aNFCDBg10zz33aN26dZozZ45sNluR5ixu8gqNPfjgg7rjjjvy/bHabDa1b9/e160VWxs2bNDLL79sOsZqtWrYsGG6++67C7UzrMViUevWrdW6dWuNHDlS8+fP14wZMwrbcqmzd+9eTZkyxXRMZGSkJk+erM6dO+d73ho1amjatGl677339PTTT5t+rzh27Fi1b9/eJ7ttnu3sa3BERIReeOGFAgXVGjZsqLfeekuPPPKIFi1a5HHcN998owMHDqhq1aqF7hcAAAAIlISEBI0fP14jRozwOKZ79+564403CI0BxdC5v1YLAAAABMnmzZv1008/mY5p1qyZ6Rt9OTk5ee7Idbr+/ftrxowZhQ7tSLm7R0yfPt3jm7cOhyNfxy0WVcOGDTV37twChcaKq+eee85joEuSWrVqpU8++aTAobHTNW3aVB988IFpyGLKlCmmvx1nZsKECTpw4IDpmCFDhmjq1KlFev2drnPnznr//ffzfTQm8ta+fXvNmDGjQKExb8aMGaOsrCyP9e7du+v9998vcGjsdJdcconmzp1rGtiaOHFioed/4oknlJ6e7rFusVg0fvx4PfHEE4UOjZ3OZrOpV69e+vzzzzV06NACPfbgwYNeQ5StWrXSrFmzChQaO6lcuXJ69dVX1aVLF9Nx77//vrZt21bg+QuqY8eOevvttwt1vG7t2rU1Y8YM06+nK1as0OHDhws894oVKzzWbr311iKHxs7WqlUrTZ06Vffdd59P5y1OLBaLnnzySd19992lLiDnK06nU48++qhpoCg0NFTTp0/Xvffe65PjxENDQ3XzzTfr22+/1bXXXlvk+UqDZ5991vR7qPDwcM2aNatAobHT3XzzzXr++edN32g6fPiwpk2bVqj5CyI2NlZvvfVWoXY3s9lsmjhxolq2bOlxjNPpzPeRqwAAAEBx8OCDD+b5y0vly5fXjBkz9NVXX5nuPA4geAiOAQAAoFhwuVz5Ok7N25szH3zwgfbs2eOx3r17d40ePTrPo8kK6pJLLjF9o3rJkiV5HovlK7GxsZo5c6bPAkjBtG3bNn366ace67Vr19arr77qk+PfatSooRdffNHjm++HDx/WRx99VOB5d+7c6XWnnQEDBmj48OEFnjs/ateu7Zd5y4JatWrptdde83g0ZWEsXbrU9Ojdli1bauLEiQoNDS3yWk2aNDHdFWzLli1ed3PMy08//WQaApKkxx57TNdff32B5/bGYrEU+IeJM2fONA3qVapUSa+88kqRAm52u10vvvii6eeb2+32uutlUZ3c/bIoH0vDhg112223eay73W4tXbq0QHMmJyd7PPbRYrHo9ttvL9B8BeGLIFBxdffdd+vmm28OdhvF2scff+z16OaXXnrJa/CzMEJCQkrssZK+tG3bNi1ZssR0zFNPPWUalsqPXr166e677zYd8/7775sex1tUFotFL774opo3b17oOWw2m8aOHWsaBv3uu+8KPT8AAAAQaCePrAwLCzt1X48ePbRp0ybdfvvt7DQGFGOl96dqAIAS5ewjH85Wo0YNxcTEFHjebdu2mf7W+XnnnVeowMWff/5p+pvUlSpVKtSOJbt37/Z41JSUeyxctWrVCjzv3r178zyS66Ty5csXareT/fv369ixYx7rkZGRhdoF6dChQ6Y7XISFhRXq+L+jR4/qn3/+Oef+ouxeBN+ZOHGiVq1aZTomNDRUV111lcd6Tk6OXn/9dY/1mjVrasKECT79j9S7775by5Yt0++//35OzTAMffDBB3riiSd8tt7pRowYYXrMZEkybdo0j7vEhYSEaNq0aYqLi/PZem3bttXAgQM1c+bMPOsffPCBbr311gLN+corr5h+zUlISNDDDz9coDkRGOPGjfNpaEyS6W4n5cqV0yuvvHLGD9KK6uqrr9aSJUv09ddf51l///33demllxZoTm9HvnXu3FkDBgwo0Jz+kpaW5jXw+cgjj/gkaBsdHa0nnnhCgwcP9jhm8eLF2rt3b5F2k/PkZHjNFzu83XnnnXr77bc9Hru8evVq3XDDDfmeL6/jFU+qUaNGob6PLetq165d4N33yhqXy+U1rHnTTTcVamco5N+sWbNM6x06dFDv3r19sta9996rRYsWae/evXnWMzMz9d5772nYsGE+We9sAwcOVMeOHYs8T0JCgrp06eIxcLdp0yZlZmb6/HsUAAAAwF9OHln59NNPa/LkyRo4cCCBMaAEIDgGACgWmjZtalr/8MMP1a9fvwLP26lTJ9Njz6ZNm6Z77723wPP27t1bW7Zs8Vh/8sknNXbs2ALPO2jQIP3www8e60OHDtUrr7xS4HkffPBBzZ8/32O9b9++hdpd53//+5/pmzSdO3fW999/X+B5X331VdOdUxo3buw1bJiXefPm5fnmgdmRhvC/nJwcjR8/Xh9++KHXsddee60qVqzosb548WLT0OFDDz2k8PDwQvXpidVq1V133eXxWrJw4UKNGjXK5zuh/N///Z/69Onj0zmD5eDBg6a72lx//fWqX7++z9cdPHiw5s6dm2cQeMeOHdq8eXO+g6VJSUn69ttvPdbtdrsmTJjgk92l4Fvdu3fXRRdd5NM5169fb/p16p577jG9lhXWkCFDPAbHli9frqSkpHyvu3XrVq1fv95jPTY2Vk8//XRh2vSLb775xjR837p1a58FFiTp4osv1uWXX+7x897tduuzzz7zS2ihV69eXr93zq8KFSqoQ4cO+vHHH/Osb9iwoUDzmR1rWpjjQZG7q58vQ6al0bJly0yPia5Vq5ZGjBgRwI7KnvT0dC1evNhj3W63a8yYMT5bLzQ0VKNGjdKQIUM8jvn000/9cg2Ojo726bxXXXWVx+CYw+HQ5s2b1aZNG5+tBwAAAOSHYRiFDnw9+OCDuuWWW/jlMaAE4ahKAAAABIXb7dZXX32lPn365Cs0Vq5cOd1///2mY8wCko0aNVLPnj0L3Gd+dO3a1eORasnJyabhi8Lyx9FwwbJgwQKPO3XZ7Xa/7RYRHx9vuoOdWZD3bJ9//rkcDofHeq9evdSwYcMC9YfAKMhuSvlldi2Kj483PR6wKBISEtS+ffs8ay6XSz/99FO+5/J27Gr//v0Ltbuqv3z55ZemdW/HmhWGt18+8NZTYfl6lzezo/sSExOVk5OT77nMwtnHjx8vQFeQcndHvuSSS4LdRrFnds2VckO1vtihD559//33puHdbt26qV69ej5d87LLLlOjRo081vfu3Vvg8Gt+9O3bV9HR0T6br3PnzqZvyO3atctnawEAAADeOJKPadsLY3T4R8+/IOuNzWYjNAaUMATHAAAAUGjZ2dlKTEz0etu7d6+2bdumX375RQsWLNBjjz2myy67TMOHD9eOHTvytdbjjz9uultJamqqVq9e7bFuFhAqKovFoosvvthj/eeff/bpehEREbriiit8Omcwfffddx5rHTp08MvOTCeZHTNUkOfNbMc0KfeILBQ/1apV8/luY4ZhmL4eLr/8cr/uPBeI13RISEixCq/m5ORozZo1Huvx8fE+OVLsbAkJCWrQoIHH+s6dO3Xw4EGfrtm0aVMlJCT4dE6zUKvb7VZiYmK+5zI7UnjPnj0FmgvSNddcI6uVH92ZycrKMr22xcbGlqrvmYorb8FkX+74WJB5V6xY4fM1+/bt69P5oqKiVKNGDY91T8dxAgAAAL52ZOVSrXvgFh1ZuUS7Zr6onGNJwW4JQIBwVCUAAAAK7ffff1fXrl39vs7gwYPz9caQ0+n0WO/Ro4ev2zpDmzZtNG/evDxrhTla1Uzr1q19utNBMCUlJZn++/hrl7iTzI7+2bJlS762ZU9PT9e6des81ps2bapmzZoVukf4T6dOnXweyti0aZOSkjz/YC2Yr+n8Xot27dqlffv2eax37dq1WO02tn79emVlZXmsX3HFFbLZbH5Zu3fv3po4caLH+i+//OLTwIQ/jivzdhRwUlKS6tatm6+5KlWqpPDw8DyfD8MwNGHCBE2ZMqXQx12UNWa7wSHXr7/+avr5f91113HUZwCsWrXKYy0uLk6dOnXyy7pXXXWVJk6c6HHn2lWrVpkeZ1lQsbGxuuCCC3w230n169f3GBA7cuSIz9cDAAAATpd1/KjWT3tOB1f8e4S6My1Vf74+QY1GPhfEzgAECr+2CAAAgGLtjjvu0MiRI72OMwvuVKtWzfQ3+X3BbNeZbdu2+XStpk2b+nS+YPrtt99kGIbHuj9CEqerXLmyYmNj86ylpaXla3ecLVu2mIYW/fVmKYrOH59LZteikJAQtWzZ0udrns7sWrRr1658HTvo7Wiv4vaa3rp1q2nd17vKnc5st0nJe28F1apVK5/OJ0kxMTGmwbrk5OR8zxUaGqrWrVt7rH/zzTd6+OGHCzRnWWWz2Xy+u1xp9Pvvv5vWOerT/1JSUkzDxm3btlVIiH9+d7lSpUqm4VdfX4Nbtmzpl+BrhQoVPNa4XgIAAMCfvv3sE317d78zQmMnHV39ow4vL/yRlQBKDoJjAAAAKJZiYmI0adIkPfLII/kav2XLFo+1/O6UUhQxMTEeawcPHjQNFhVU48aNfTZXsJk9b+Hh4apevbrfe/AUHJNk+kboSWYfgyQ1b968oC0hQPzxuWT2eqhZs6bsdrvP1zxdVFSUxzWcTme+jk4saa9pb0ce+/OaecEFF5g+p/k9jjm/6tSp49P5ToqKivJYy87OLtBc3bp1M60vXLhQl19+uV566aV8XWPLqnr16ik8PDzYbRR7ZsEgq9Wq//u//wtgN2WTt+tco0aN/Lq+2TX++PHjPj0yuCRcgwEAAID8Gjp0qB69c5ByUo57HLNrxiRlHmUXXKC046hKAAAAFCuhoaG67rrr9MADD5j+9v3Z/vzzT4+1ypUr52vnqKIw28XH7Xbr8OHDOu+883yyVq1atXwyT3Fg9rxVq1ZN+/fv93sPERERHmsHDhzw+vg9e/aY1otbyAb/ql27ts/nNHtNn3feeX6/FklSdHS0jh07lmft4MGDqlmzpunjzV7TUVFRfjmmqyjM/k3j4uJUtWpVv61tt9tVv359j2E7Xz/fZiHlooiKilJKSkqetfzsUne6Pn366NVXX9Xhw4c9jjl+/Lhee+01vf7662rSpIm6du2qDh06qGnTpn7bmaikKU1f6/3J7HpVr169UnO0d3Hm7Trn71948BZMS0xMVJUqVXyylj+vwZ4U9BoMAAAA5FfXrl01ffp00zHOtBStefkZ1Z/wSoC6AhAM/DQOAAAAxUJCQoKuvPJKXXvttapUqVKBHpudne0xJCFJCxYs0IIFC4raYpEkJyf7LDhWrlw5n8xTHJgFs3bt2qWuXbsGsJtz5ed4ILOPIS4urkABSASO1Wo1faO2sMxeDytXrgz6a/r48eNex5h9DHXq1JHVWrw2Lz906JDHmj/CgWerU6eOx+CYWXiqMPwVWjB7Ts2OE85LWFiYRo0apf/+979exxqGoU2bNmnTpk2aMmWKIiMj1aJFC7Vs2fLU/5emr3kFUVY/7oIyu14FYsdZmF+DJf9fh73tAuatv4IoX768z+Y6XXH7ugoAAICyoU+fPvpP72u1+LNPTMclrlymbUu+lJoNDVBnAAKN4BgAoFjYtGmTab1GjRqFmnf58uVyuVwe64UNcXz22WemR0YUNPRy0uzZs5WRkeGxHhcXV6h5J02apLFjx3qsF/YH4KNHj9bQoZ7/YyEyMrJQ8w4dOlT9+vXzWA8LCyvUvDfddJO6dOlSqMei6Ox2u+x2u8qVK6f4+Hidd955qlevnhISEtSuXTvFx8cXem5fviHkL748ZqY0vZlc3J+7/DxvR4543q7dX28wouiioqJksVh8OqfT6VRSUpJP5/S1/OxcUtJe02bB4UBcL812NMrIyFBmZqbpzoYFUVKOLrziiiu0Y8cOr7+5fLaMjAytXLlSK1eulJQbpmjQoIE6dOigzp07q23btrLZbP5oudhhpyzvsrKylJaW5rFeHK9XpZHZNVjy/3XY2/xHjx712Vol5RoMAAAA5Nejz07UD8uWmR5XWb19Z9Vs0TZwTQEIOIJjAIBioUmTJn6ZNyEhwS/z+uuIJm+/LV1Y3o6kKqxq1aqpWrVqPp+3cuXKqly5ss/nrVChAjv/+Fi7du30zjvvBLsN0zcNiwtfBsf8sUtSsBT35y4/IZusrCyPtdIU8itt/PF5lJGRUeDdmQItP9eizMxMj7Xi+Jo2+xwMRPjG279JVlaWz4JjJcnw4cMVHx+v5557Tg6Ho1BzuN1ubdu2Tdu2bdOsWbNUsWJFXXXVVbrhhhtUr149H3dcvJSmr/X+Ynatkorn9ao0MrsGS/6/Dnt7nn35PTgAAABQ2sTFx6vVsEf1yzOPnlMLiS6nurc/pFY9r1Z0ubL3cw2gLGEfbAAAAJR43t6wKg58GSYpTbutFPfnLj/Pm9nHwG4nxZc/Po+K++tZyt9r2uxN9uL4mjYLeBaH4FhZDi3ceuut+vDDD9WhQwefzJeUlKS33npLV155pYYNG6adO3f6ZN7iqDR9rfcXb59bxfF6VRqZXYPtdnuhd4vOL2/X+ZLwtRkAAAAIphqd/qMqF3c9474K7S5RqynzVLlzd5/v2A+g+CE4BgAAgBLP7EhaFG+l4bkz++GJ2+0OYCcIttLwepZK12s6EDvAefs3Kes/YG3cuLFmz56tOXPmqEePHgoNDS3ynIZhaPHixerdu7deeeWVEve6hG94+9zidRF8gbgGe1ujrF+DAQAAgPxodPfDCikfq5Do8mowfKwajXxOoXEVg90WgADhqEoAAACUeL54ExrBERYW5vWoqeLObCeN1NTUAHaCYPP3riqBEhYWJqfTmWetOL6mw8LClJGRkWctEP16W6O0vC6K6qKLLtJFF12k5ORkfffdd1q5cqVWrVqlw4cPF3pOh8OhqVOnatu2bZo8eTK7dJUx3j63iuP1qjQyex6cTqcyMzP9elyvt+c5PDzcb2sDAAAApUVYbAU1GvGsIs6rSWAMKIMIjgEAAKDE8/Zm1B133KFHHnkkQN2gIMLDwz0Gx5o1a6aPPvoowB0VXGRkpMdaSkpKADtBsHl7c7pnz56aPHlyYJopgsjISKWnp+dZK46v6fDwcI/BsbS0NL+v7+nf6iR/BiZKopiYGPXp00d9+vSRJO3atUtr167VunXrtG7dOu3Zs6fAc3777bd65pln9Pjjj/u4WxRnZl9/peJ5vSqNvH3tS0tL8+t10Nt1nuAYAAAAyoJ//vlHL774op599lnZ7fZCzRHTuIVvmwJQYhAcAwAAQIlXsaL5b0ElJycHqBMUVMWKFXXs2LE8ayXleatcubLHGm9aly2RkZGKiIjwGIYsSa9pT7tAFcfXdHx8vI4ePZpnLRA7Dpn9m0RHR7PjmBd169ZV3bp11a9fP0nS0aNHtWrVKv3000/64Ycf8r0j2dy5c3XJJZeoc+fO/mwXReTLXUZDQ0MVGxur48eP51kvjter0ig+Pt60npKSokqVKvltfW/Ps7f+AAAAgJLMMAy9++67uv/++3Xs2DHFxsZqzJgxwW4LQAljDXYDAAAAQFFVqFDBdDcBT28oIvjOO+88j7WS8rxVrVrVYy05OVkHDx4MYDcIttL+mt61a5fHYyyDxSy8uWvXLr+vv3PnTo81s96QtwoVKqhnz5763//+p+XLl+vdd9/Vtddem69jqadMmSLDMALQZelgsVg81txut1/W9HWA1ux6tWPHDp+uhbx5u875+zpsdg2WuA4DAACg9Prnn3/Uu3dv9e/f/9Qv5j711FPauHFjkDsDUNIQHAMAAECpcP7553usEdwpvmrXru2xlpKS4tOdSfylbt26pvX169cHphEUC7Vq1fJYO3ToUAA7KTyz13RWVpa2bdsWwG68q1mzpsdaamqq9u7d67e1s7OzTUMRZl+b4J3FYlGbNm303HPP6ZtvvlHHjh1Nx2/evFmbNm0KUHclX0iI54MIPB3/WlS+Do6ZXa/++usvj7uawne8Xee2bt3q1/W3bNliWjf7GgEAAACURIZh6J133lHjxo31xRdfnFFzOBwaOHCgHA5HkLoDUBIRHAMAAECp0LRpU4+1rVu3+u0NUBSN2fNmGIbWrVsXwG4Kp0mTJqb133//PUCdoDgwe00fOXJEe/bsCVwzhdS4cWPTenF7TTdo0MC07s/Qwvbt2013YGvYsKHf1i5rqlWrptdee02dOnUyHffzzz8HqKOSz+wY1fT0dL+s6etroLfr1YYNG3y6Hs51wQUXmO5e5y3YVVRm1/hKlSqpQoUKfl0fAAAACKSkpCRdffXVuu222zzubL9u3TpNnDgxsI0BKNEIjgEAAKBUaNmypceaw+EoEQGksqhFixam9VWrVgWmkSJISEhQRESEx/qyZcsC2A2CzexaJJWM17S3j2Hp0qUB6iR/vIU3ly9f7re1vc3tLdSCgrHb7Ro/frzsdrvHMcUt2FicxcTEeKw5nU6lpKT4fE1ffz/m7Xq1ZMkSn67nK2ZBq5ImMjJSderU8Vj/9ddflZ2d7Ze19+3bZ3pUpbevDwAAAEBJExUVpT///NPruLFjx7IjN4B8IzgGAACAUqFz586mb8J9//33gWsG+Va7dm3T4ypLwvMWGhqq9u3be6zv2rWr2O6AY3ZMmb/e5C3t2rZtq6ioKI/1kvCaPu+880x38VqxYoX+/vvvAHZkrmnTpipXrpzH+jfffKOcnBy/rP355597rFksFl144YV+WbcsO++889S2bVuP9aSkpALNV5avg/Hx8ab1HTt2+HzNNWvW+HS+li1bmgbgvvjiC6Wlpfl0TV8we91JJe+1d9FFF3mspaWl+S3A98UXX8gwDI91s+/PAAAAgJIoPDxcs2fPltVqHvNwOBwaNGiQ6S7pAHASwTEAAACUClWqVFHz5s091ufPn6+jR48GsCPk1+WXX+6xtn37dv3www8B7KZwunXrZlqfN29egDopGLNjyrKysgLYSekRGhqqLl26eKwvW7bML2EMXzN7TRuGUaxe0zabTR06dPBYT05O9ktgb/369abH7jVp0kRxcXE+XxdSvXr1PNaOHTtWoLnK8nWwRo0apm82bN++3afrbdu2zee/8W6z2UyvuRkZGfr00099uqYvhIaGmtZL2mvP2xGyZiHbovjss89M6x07dvTLugAAAEAwtW/fXg899JDXcXXr1lVGRkYAOgJQ0hEcAwAAQKlx/fXXe6xlZmZq1qxZAewG+dWvXz/TN65fffXVAHZTOD179jTdZWrx4sU+32XFF8x2aTly5EgAOyldzK5FhmFo+vTpAeymcPr06WO6i+O8efNMQ1OBduWVV5rWX3nlFblcLp+uOXXqVNN6r169fLoe/mUW9vK2k9PZyvJ1MCwsTNWrV/dY//HHH3263pw5c3w630l9+/Y1rb/22msFDhT6W/ny5U2vsSXttXfxxRcrNjbWY/3777/Xhg0bfLrm559/rl27dnmsN2zYUPXr1/fpmgAAAEBxMW7cODVs2DDPWqVKlfTRRx/pgw8+UPny5QPcGYCSiOAYAAAASo2rrrpKFSpU8FifM2eO1q5dG8COkB/nn3++Onfu7LG+fv16zZgxI4AdFVxUVJSuvfZaj3W3262RI0cWu+OyzI4pK05HEZY07du39/jDO0n66quv9NVXXwWwo4KrUaOG6S4+mZmZGjFihM/DWIV16aWXmoYWtm3bpvfff99n633zzTdasWKFx7rdbtdVV13ls/Vwpv3793usmX0fkJeyfh002611xYoVPgtcbdq0SQsXLvTJXGdr166d6fG6hw8f1pNPPumXtQvLZrOZvlZL2msvNDTU9JpnGIbGjx9veqxkQaSlpWnixImmY6677jqfrAUAAAAURxEREZozZ845v4x74403asuWLV5/wQYATkdwDAAAAKVGWFiYhg0b5rHucDh03333mb7h7GvFJVRR3A0fPtx017EXX3zRL0fNeVKY5+2uu+5SeHi4x3piYqKeeOIJn71p6gu1atXyWFu3bp3cbncAuyldHnzwQY81wzD02GOPafPmzQHrpzCv6fvuu890R5zff/9dkyZNKkpbPhMaGqr+/fubjpk8ebISExOLvNbRo0f17LPPmo659tprTQNJpdXx48f9vkZWVpaWL1/usW52jGVeyvp18MILL/RYczgcPtmtNT09XQ899JAcDkeR5/Lk/vvvN61/8803eu+99/y2fmGcf/75HmvFcZdSbwYOHGi649+GDRv09ttv+2StiRMn6tChQx7rsbGx6tevn0/WAgAAAIqr9u3bn/r5U+XKlfXxxx9r3rx5ZfLnEQCKhuAYAAAASpUbbrjBdNeJpKQk9e/fXxs3bvRrH9u3b9ejjz5abEIVxV1CQoLp8X5ut1vDhw/Xp59+6tc+jhw5osmTJ+v2228v8GOrVKmiwYMHm45ZtGiRRo0a5fM3z51OZ6HeZG7UqJHH2pEjR0zDGTDXpUsXdezY0WM9MzNTt99+u9//jffu3aunn35aI0eOLPBjmzRpoquvvtp0zIwZMzR58mSfByIzMzP1+++/F+gxt912m+muYykpKRoyZIiOHj1a6L7S09N177336p9//vE4JjQ0VHfddVeh1yjJXn31Vd12221auXKlX9dITU31WG/fvn2B5ivr18GuXbuaBrdnz56tP//8s9DzZ2Rk6P777/f70bb/+c9/1KZNG9Mx48eP9+nOgyclJydr69atBX5c48aNPdZ+/PFHJSUlFaWtgKtZs6Z69+5tOmbChAlatmxZkdaZM2eO1+dx8ODBpkeIAwAAAKXFU089pYceekibN29m110AhUZwDAAAAKVKSEiIJk6cqNDQUI9jEhMTddNNN2nOnDlyOp0+WzsnJ0fLli3T7bffrquvvlqffPKJcnJyfDZ/aTdixAjTnV8yMzM1cuRIjRo1SsnJyT5b1zAMbdiwQWPGjNGll16q6dOnF/poriFDhpgGFyVpwYIF6t+/v3bv3l2oNU6Xk5Oj9957T5dffrmmTJlS4Me3adPGdEepsWPHavv27UVpsUx75plnTINMx44d05133qlJkyYpMzPTZ+u6XC798ssvGj58uLp376533nlHGRkZhZpr1KhRqlSpkumY6dOna8iQIaa7v+RXWlqa3njjDV122WWaN29egR5bvnx5Pfzww6ZjduzYoVtvvbVQn38HDhzQoEGDtG7dOtNxd999t2rWrFng+UsDwzC0atUqDRo0SFdeeaXeffddn+5CNnv2bL3xxhse6+XLlzc9+jgvZf06WLFiRXXq1Mlj3eFw6I477tDevXsLPPfBgwfVv39//fTTT0VpMd+eeeYZRUREeKy73W49+eSTGj16tGn4ML+SkpL0wgsv6NJLL9V3331X4MebBd0yMjL08MMPB2QXP196+OGHFRMT47HudDp13333af78+QWe2+12a8qUKV53fKxTp44GDRpU4PkBAACAYNi7d69WrVpV6MdHRETohRdeYJcxAEXief9wAAAAoIRKSEjQ448/rscff9zjGIfDoWeffVZz5szRbbfdpn79+qlcuXIFXistLU0//fSTFi9erGXLlik9Pb0orZdpUVFRmjx5sm655RbTkMvHH3+sr776Sn379tVtt91WqIBGTk6OfvvtNy1evFiLFy/WgQMHitL6KaGhoXrxxRd14403mr4WfvvtN1199dXq16+fBgwYYBqYO9vJUNCiRYv03XffnQrRVa9evcD9xsfHq2XLlh6DMPv371efPn3UsWNHdezYUfXq1VNcXJwiIyNNd6ipWrWq6XFVZUWVKlU0YcIEDR061GNI1TAMvf766/rggw90880365ZbbinUD/syMzO1evVqffvtt1qyZEmhw49ni42N1cSJE3XHHXeYBm2XLVumnj176tZbb9XNN9+sKlWq5HuNnJwc/fjjj1q0aJGWLVtWpBBd37599fXXX5sGVXbu3KnrrrtO99xzj2699Vavu9JkZ2dr/vz5mjp1qtcQR+PGjcvsbmNn+/PPP/XUU0/p2WefVceOHdW1a1ddcsklBXptnLRu3Tq9/PLLXncyu/XWW02DQ3nhOigNGjRIP/zwg8f6P//8oxtvvFGPPPKIevfubRq0k3K/N5o5c6bmzJlzztfzJk2a+O2Y3lq1aunJJ5/Uo48+ajpu/vz5+v777zVw4ED169fPNOB7tvT0dC1ZskRffvmlfvrppyLtIHrJJZcoLCxM2dnZedZXrlypbt26qXv37mrVqpXq1KmjcuXKKTw83ONzEBISoqpVqxa6p6KqUKGCHn/8cdMQr8Ph0OjRo7V06VI99NBD+Tpedt26dXr++ee1fv1603F2u13PPPOM6S+QAAAAAMWBYRiaOXOmHnzwQcXExGjTpk2mv4QBAP5UMn6CBQAAABTQ9ddfrwMHDuiVV14xHffPP//o+eef1wsvvKBGjRqpTZs2atKkieLi4hQTE6OYmBjl5OQoNTVVqampSklJ0V9//aXt27dr69atSkxM9PkRbWVZ48aNNXXqVA0ZMsT0zdiMjAy9/fbbevvtt1W7dm21bt1aLVu2VKVKlVS+fHnFxMTIYrEoLS1NKSkpSk1N1YEDB7Rt2zZt3bpVu3bt8vlxkSc1aNBAkyZN0tChQ+VyuTyOy8nJ0bvvvqt3331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      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1023,
       "width": 1223
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_sampled_amortized = linalg.matmul(\n",
    "    post[\"W\"],\n",
    "    F_sampled,\n",
    "    dims=(\"observed_columns\", \"latent_columns\", \"rows\"),\n",
    ")\n",
    "reconstruction_mean = X_sampled_amortized.mean(dim=(\"chain\", \"draw\")).values\n",
    "reconstruction_sd = X_sampled_amortized.std(dim=(\"chain\", \"draw\")).values\n",
    "plt.errorbar(\n",
    "    Y.ravel(),\n",
    "    reconstruction_mean.ravel(),\n",
    "    yerr=reconstruction_sd.ravel(),\n",
    "    marker=\".\",\n",
    "    ls=\"none\",\n",
    "    alpha=0.3,\n",
    ")\n",
    "\n",
    "slope, intercept, r_value, p_value, std_err = sp.stats.linregress(\n",
    "    Y.ravel(), reconstruction_mean.ravel()\n",
    ")\n",
    "plt.plot(\n",
    "    [Y.min(), Y.max()],\n",
    "    np.array([Y.min(), Y.max()]) * slope + intercept,\n",
    "    \"k--\",\n",
    "    label=f\"Linear regression for the mean, R²={r_value**2:.2f}\",\n",
    ")\n",
    "plt.plot([Y.min(), Y.max()], [Y.min(), Y.max()], \"k:\", label=\"Perfect reconstruction\")\n",
    "\n",
    "plt.xlabel(\"Elements of Y\")\n",
    "plt.ylabel(\"Model reconstruction\")\n",
    "plt.legend(loc=\"upper left\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We find that our model does a decent job of capturing the variation in the original data, despite only using two latent factors instead of the actual four."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Authors\n",
    "* Authored by [chartl](https://github.com/chartl) on May 6, 2019\n",
    "* Updated by [Christopher Krapu](https://github.com/ckrapu) on April 4, 2021\n",
    "* Updated by Oriol Abril-Pla to use PyMC v4 and xarray-einstats on March, 2022\n",
    "* Updated by Erik Werner on Dec, 2023 ([pymc-examples#612](https://github.com/pymc-devs/pymc-examples/pull/612))\n",
    "* Updated by Osvaldo Martin on January, 2026\n",
    "* Updated by Osvaldo Martin on April, 2026\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Watermark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last updated: Sat, 25 Apr 2026\n",
      "\n",
      "Python implementation: CPython\n",
      "Python version       : 3.14.4\n",
      "IPython version      : 9.12.0\n",
      "\n",
      "arviz          : 1.1.0\n",
      "matplotlib     : 3.10.8\n",
      "numpy          : 2.4.4\n",
      "pymc           : 5.28.0+58.gf58491a3\n",
      "pytensor       : 2.38.0+133.g80cc113b5\n",
      "scipy          : 1.17.1\n",
      "seaborn        : 0.13.2\n",
      "xarray         : 2026.4.0\n",
      "xarray_einstats: 0.10.0\n",
      "\n",
      "Watermark: 2.6.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -n -u -v -iv -w"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{include} ../page_footer.md\n",
    ":::"
   ]
  }
 ],
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   "language": "python",
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   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "myst": {
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    "extra_dependencies": "seaborn"
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 },
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