diff --git a/carl/learning/calibration.py b/carl/learning/calibration.py index 8a48dcf..4080d90 100644 --- a/carl/learning/calibration.py +++ b/carl/learning/calibration.py @@ -95,8 +95,8 @@ def fit(self, X, y, sample_weight=None): * `self` [object]: `self`. """ - # Check inputs - X, y = check_X_y(X, y) + # Check inputs. Avoid this in order to use RNNs + # X, y = check_X_y(X, y) # Convert y label_encoder = LabelEncoder() diff --git a/carl/ratios/utils.py b/carl/ratios/utils.py new file mode 100644 index 0000000..e8fd5b1 --- /dev/null +++ b/carl/ratios/utils.py @@ -0,0 +1,73 @@ +"""This module implements some utility functions.""" + +# Carl is free software; you can redistribute it and/or modify it +# under the terms of the Revised BSD License; see LICENSE file for +# more details. + +import numpy as np +from .classifier import ClassifierRatio +import matplotlib.pyplot as plt + + +def plot_score_(ratio, axis, reals, labels): + cal_num, cal_den = (ratio.classifier_.calibrators_[0].calibrator0, + ratio.classifier_.calibrators_[0].calibrator1) + axis.plot(reals, cal_num.pdf(reals.reshape(-1, 1)), + label="p(s_num), num~{0}".format(labels[0])) + axis.plot(reals, cal_den.pdf(reals.reshape(-1, 1)), + label="p(s_den), den~{0}".format(labels[1])) + axis.legend(frameon=False) + + +def plot_scores(classifier_ratios, num_den_labels=None, save_file=None): + """ + Plot score plots for a list of classifier ratios, + useful to check training and calibration quality + + Parameters + ---------- + * `classifier_ratios` [list of `ClassifierRatio`]: + List of ClassifierRatio to plot. + + * `num_den_labels` [list of (num_label, den_label) tuples]: + List of numeratod and denominator labels for each + ratio in `classifier_ratios` + + """ + + if len(classifier_ratios) == 0: + raise ValueError + for classifier in classifier_ratios: + if not isinstance(classifier, ClassifierRatio): + raise ValueError + + num_ratios = len(classifier_ratios) + if num_den_labels is None: + num_den_labels = [(l, 0) for l in + range(len(classifier_ratios))] + else: + # Ensure format for numbers + def rounds(n): return map(lambda x: round(x, 1), n) + num_den_labels = [(rounds(x[0]), rounds(x[1])) for x in num_den_labels] + + reals = np.linspace(0, 1) + + if num_ratios <= 3: + f, axarr = plt.subplots(1, num_ratios, sharex=True, sharey=True, + figsize=(12, 5)) + for k, (ratio, pos) in enumerate(zip(classifier_ratios, + num_den_labels)): + plot_score_(ratio, axarr[k], reals, labels=pos) + else: + f, axarr = plt.subplots((num_ratios // 3) + (num_ratios % 3 != 0), 3, + sharex=True, sharey=True) + for k, (ratio, pos) in enumerate(zip(classifier_ratios, + num_den_labels)): + plot_score_(ratio, axarr[k // 3, k % 3], reals, labels=pos) + f.subplots_adjust(hspace=0.05, wspace=0.05) + if save_file is None: + plt.show() + else: + plt.savefig(save_file) + plt.close() + plt.clf() diff --git a/examples/Likelihood ratio of VAR time series.ipynb b/examples/Likelihood ratio of VAR time series.ipynb new file mode 100644 index 0000000..1864ad8 --- /dev/null +++ b/examples/Likelihood ratio of VAR time series.ipynb @@ -0,0 +1,947 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# VAR Model estimation with approximated likelihood ratios\n", + "\n", + "Juan Pavez, Gilles Louppe, Kyle Cranmer, April 2017.\n", + "\n", + "In this notebook we study the usability of the method [Approximating Likelihood Ratios with Calibrated Discriminative Classifiers](http://inspirehep.net/record/1377273) for times series parameter estimation.\n", + "\n", + "In this case an Vector Autoregressive (VAR) model is used. The model is defines as\n", + "\\begin{equation}\n", + "y_t = c + A_1 y_{t-1} + u_t,\n", + "\\end{equation}\n", + "where $y_i \\in \\mathbb{R}^{Kx1}$, $A_1 \\in \\mathbb{R}^{KxK}$, $c \\in \\mathbb{R}^{Kx1}$ and $u_t$ is a white noise process in $K$-dimensions with covariance matrix $\\Sigma_u$. \n", + "We approximate the coefficients matrix $A_1 = diag(\\alpha_0, \\alpha_1)$, with $\\alpha_0 = 0.5$ and $\\alpha_1 = 0.4$ \n", + "for a 2D VAR(1) process.\n", + "\n", + "We approximate the likelihood of the time series using a recurrent neural network $s(x_{1:T})$ as:\n", + "\n", + "\\begin{equation}\n", + "\\frac{p_{X_{1:T}}(x_{1:T}\\vert\\theta_0)}{p_{X_{1:T}}(x_{1:T}\\vert\\theta_1)} = \\frac{p_U(u=s(x_{1:T})\\vert \\theta_0)}{p_U(u=s(x_{1:T})\\vert\\theta_1)}.\n", + "\\end{equation}\n", + "\n", + "\n", + "We also show how to produce the data and train the classifiers in parallel using python multiprocessing." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "%matplotlib inline\n", + "import numpy as np \n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib\n", + "import theano\n", + "import scipy.linalg as L\n", + "import pdb\n", + "import pickle\n", + "\n", + "import os, sys, inspect\n", + "\n", + "import carl\n", + "\n", + "import multiprocessing\n", + "\n", + "plt.set_cmap('viridis')\n", + "\n", + "np.random.seed(1234)\n", + "\n", + "sys.setrecursionlimit(10000)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import statsmodels.tsa.vector_ar.var_model as vector_ar" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "p_value_ = 1\n", + "ndims_ = 2\n", + "nparams_ = 2\n", + "N_ = 20000\n", + "T_ = 50\n", + "alpha_value_0 = 0.5\n", + "alpha_value_1 = 0.4\n", + "sigma_2_value = [[1.,0.],[0.,1.]]\n", + "intercept=[0.,0.]\n", + "alpha_value_0_bkg = 0.3\n", + "alpha_value_1_bkg = 0.3\n", + "sigma_2_value_bkg = [[1.,0.],[0.,1.]]\n", + "\n", + "target_position = (alpha_value_0, alpha_value_1)\n", + "bkg_position = (alpha_value_0_bkg, alpha_value_1_bkg)\n", + "bounds = [(0.3, 0.6), (0.3, 0.6)]\n", + "n_points = 5\n", + "\n", + "As = np.linspace(bounds[0][0],bounds[0][1], n_points)\n", + "Bs = np.linspace(bounds[1][0],bounds[1][1], n_points)\n", + "AA, BB = np.meshgrid(As, Bs)\n", + "AABB = np.hstack((AA.reshape(-1, 1),\n", + " BB.reshape(-1, 1)))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "class VAR:\n", + "\n", + " def sample(self, coefs, intercept, sigma_2, n_steps, rng=None):\n", + " return vector_ar.util.varsim(coefs, intercept, sigma_2, steps=n_steps)\n", + " \n", + " def plot(self,steps=1000):\n", + " self.VAR.plotsim(steps)\n", + "\n", + " def nll(self, X, alphas, intercept, sigma_2):\n", + " \"\"\"\n", + " Compute the negative log likelihood for a VAR process, \n", + " using formula from Lutkepohl (2005)\n", + " \"\"\"\n", + " lags = 1\n", + " trend = 'c'\n", + " alpha_0 = alphas[0]\n", + " alpha_1 = alphas[1]\n", + " coefs = np.array([alpha_0,0.,0.,alpha_1]\n", + " ).reshape(p_value_,ndims_,ndims_)\n", + " \n", + " VAR = vector_ar.VAR(X)\n", + " VAR.k_trend = k_trend = vector_ar.util.get_trendorder(trend)\n", + "\n", + " offset = 0\n", + " y = VAR.y[offset:]\n", + "\n", + " z = vector_ar.util.get_var_endog(y, lags, trend, \n", + " has_constant='skip')\n", + " y_sample = y[lags:]\n", + " intercept = intercept\n", + " params = np.vstack((intercept, coefs.reshape((2,2))))\n", + " #params = np.linalg.lstsq(z, y_sample)[0]\n", + " resid = y_sample - np.dot(z, params)\n", + " omega = np.array(sigma_2)\n", + " \n", + " lastterm = -np.trace(np.dot(np.dot(resid, L.inv(omega)),resid.T))\n", + " \n", + " varfit = vector_ar.VARResults(y, z, params, omega, lags, names=VAR.endog_names,\n", + " trend=trend, dates=VAR.data.dates, model=self)\n", + " llf = -varfit.llf\n", + " llf += 0.5*lastterm\n", + " return -llf\n", + " \n", + " def rvs(self, n_samples, alpha_0, alpha_1, intercept, sigma_2, random_state=1234):\n", + " rng = np.random.RandomState(random_state) if \\\n", + " isinstance(random_state,int) else random_state\n", + " coefs = np.array([alpha_0,0.,0.,alpha_1]\n", + " ).reshape(p_value_,ndims_,ndims_)\n", + " return self.sample(coefs=coefs,intercept=intercept,\n", + " sigma_2=sigma_2,\n", + " n_steps=n_samples,rng=rng)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "p0 = VAR()\n", + "p1 = VAR()\n", + "rng = np.random.RandomState(1234)\n", + "\n", + "n_true = 1000\n", + "X_true = np.array([p0.rvs(T_, alpha_value_0, alpha_value_1, intercept,\n", + " sigma_2_value, random_state=np.random.randint(0,5000))\n", + " for i in range(n_true)])" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "from itertools import product\n", + "bounds_values = [(np.linspace(bounds[0][0],bounds[0][1], num=5)),\n", + " (np.linspace(bounds[1][0],bounds[1][1], num=5))]\n", + "combinations = list(product(*bounds_values))" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def produce_data(value):\n", + " return np.array([p0.rvs(T_, value[0], value[1], intercept, sigma_2_value,\n", + " random_state=np.random.randint(0,5000))\n", + " for i in range(N_//2)]) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Producing data from the VAR model in parallel using multiprocessing map function." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "Xs = []\n", + "ys = []\n", + "num_cores = multiprocessing.cpu_count()\n", + "pool = multiprocessing.Pool(num_cores)\n", + "Xs = pool.map(produce_data, combinations)\n", + "pool.close()\n", + "X1_ = np.array([p1.rvs(T_, alpha_value_0_bkg, alpha_value_1_bkg, \n", + " intercept, sigma_2_value,\n", + " random_state=np.random.randint(0,5000))\n", + " for i in range(N_//2)])\n", + "Xs = np.array(Xs)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "X = Xs[0][0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Plotting a window from the VAR model." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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Ieq+eu0oBDz3EptSpYGCIiAKvssCQUhxd7zYTZWSA9Hzo0UNKdchu+fmSMj5hgumV+CuR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\n9WYy70kMAUiWoBNDixfbh9qf/jS4xwxDcXGwFUOIl6FDrYqtEGzaZJu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yRqlnNiyDnXSNIISYMl9ZJ0tnOuezV3fdd736/i129yPS6A4GRW1Fcd7pjkxFCrVvamxer67K1a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\niIiITqG1VpVfczuVbAyA2wFcUF1QSCnVEECa1vqAUqoRgFEAJiezSCIiI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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "serie1 = X1_[0][:,0]\n", + "serie2 = Xs[0][0][:,0]\n", + "plt.figure(figsize=(20,10))\n", + "plt.subplot(211)\n", + "ts = pd.Series(serie1)\n", + "ts[0:100].plot()\n", + "plt.subplot(212)\n", + "ts = pd.Series(serie1)\n", + "ts.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Using Theano backend.\n" + ] + } + ], + "source": [ + "from keras.models import Sequential\n", + "from keras.layers import SimpleRNN, Dense, GRU, LSTM, Dropout\n", + "from keras.optimizers import SGD, Adam\n", + "from keras.callbacks import ModelCheckpoint, Callback, LearningRateScheduler\n", + "from keras.wrappers.scikit_learn import KerasClassifier\n", + "\n", + "from sklearn.pipeline import make_pipeline\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "from carl.ratios import ClassifierRatio\n", + "from carl.learning import CalibratedClassifierCV\n", + "from carl.learning import as_classifier\n", + "from sklearn.pipeline import make_pipeline\n", + "from sklearn.model_selection import StratifiedShuffleSplit\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Defining the RNN (in this case GRU) classifier to approximate the likelihood ratio." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "def make_model_join():\n", + " model = Sequential()\n", + " model.add(GRU(15, input_shape=(T_, ndims_,)))\n", + " model.add(Dense(5, activation='relu'))\n", + " model.add(Dense(1, activation='sigmoid'))\n", + " sgd = Adam(clipnorm=40.)\n", + " model.compile(loss=\"binary_crossentropy\", optimizer='adam')\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def make_ratio(num):\n", + " X_num = Xs[num]\n", + " X_den = X1_\n", + " X = np.vstack((X_num, X_den))\n", + " y = np.zeros(len(X_num) + len(X_den), dtype=np.int)\n", + " y[len(X_num):] = 1\n", + "\n", + " clf = KerasClassifier(make_model_join, nb_epoch=50, verbose=0)\n", + "\n", + " cv = StratifiedShuffleSplit(n_iter=1, test_size=0.5, random_state=1)\n", + "\n", + " ratio = ClassifierRatio(\n", + " base_estimator=CalibratedClassifierCV(clf, cv=cv, bins=20),\n", + " random_state=0)\n", + " ratio.fit(X, y)\n", + "\n", + " return ratio\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Training the classifiers at each grid point in parallel." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Start training\n", + "Iteration 0\n", + "Iteration 1\n", + "Iteration 2\n", + "Iteration 3\n", + "End training\n" + ] + } + ], + "source": [ + "print('Start training')\n", + "num_cores = multiprocessing.cpu_count()\n", + "pool = multiprocessing.Pool(num_cores)\n", + "\n", + "clf_ratios = []\n", + "n_sample_points = len(combinations)\n", + "points = list(range(n_sample_points))\n", + "for i, k in enumerate([points[n:n + num_cores] for n in range(0, n_sample_points, num_cores)]):\n", + " print('Iteration {0}'.format(i))\n", + " clf_ratios += pool.map(make_ratio, k)\n", + "#pool.close()\n", + "print('End training')" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "25" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(clf_ratios)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(0, (0.29999999999999999, 0.29999999999999999))\n", + "(0,)\n", + "0.0054962467896\n", + "(1, (0.29999999999999999, 0.375))\n", + "(0,)\n", + "-0.191834968388\n", + "(2, (0.29999999999999999, 0.44999999999999996))\n", + "(0,)\n", + "-0.237012807811\n", + "(3, (0.29999999999999999, 0.52499999999999991))\n", + "(0,)\n", + "0.124319079978\n", + "(4, (0.29999999999999999, 0.59999999999999998))\n", + "(0,)\n", + "0.762950198252\n", + "(5, (0.375, 0.29999999999999999))\n", + "(0,)\n", + "-0.395275614596\n", + "(6, (0.375, 0.375))\n", + "(0,)\n", + "-0.770527017802\n", + "(7, (0.375, 0.44999999999999996))\n", + "(0,)\n", + "-0.831173722626\n", + "(8, (0.375, 0.52499999999999991))\n", + "(0,)\n", + "-0.565415735516\n", + "(9, (0.375, 0.59999999999999998))\n", + "(0,)\n", + "0.000113244859618\n", + "(10, (0.44999999999999996, 0.29999999999999999))\n", + "(0,)\n", + "-0.938755570645\n", + "(11, (0.44999999999999996, 0.375))\n", + "(0,)\n", + "-1.24060498614\n", + "(12, (0.44999999999999996, 0.44999999999999996))\n", + "(0,)\n", + "-1.24707220876\n", + "(13, (0.44999999999999996, 0.52499999999999991))\n", + "(0,)\n", + "-0.963597355129\n", + "(14, (0.44999999999999996, 0.59999999999999998))\n", + "(0,)\n", + "-0.302930145881\n", + "(15, (0.52499999999999991, 0.29999999999999999))\n", + "(0,)\n", + "-1.02247543468\n", + "(16, (0.52499999999999991, 0.375))\n", + "(0,)\n", + "-1.15986384384\n", + "(17, (0.52499999999999991, 0.44999999999999996))\n", + "(0,)\n", + "-1.16579911981\n", + "(18, (0.52499999999999991, 0.52499999999999991))\n", + "(0,)\n", + "-0.837766913851\n", + "(19, (0.52499999999999991, 0.59999999999999998))\n", + "(0,)\n", + "-0.272463618997\n", + "(20, (0.59999999999999998, 0.29999999999999999))\n", + "(0,)\n", + "-0.752922580642\n", + "(21, (0.59999999999999998, 0.375))\n", + "(0,)\n", + "-0.931205046699\n", + "(22, (0.59999999999999998, 0.44999999999999996))\n", + "(0,)\n", + "-0.887838324554\n", + "(23, (0.59999999999999998, 0.52499999999999991))\n", + "(0,)\n", + "-0.590733282679\n", + "(24, (0.59999999999999998, 0.59999999999999998))\n", + "(0,)\n", + "0.0197703047802\n" + ] + } + ], + "source": [ + "llr = []\n", + "zeros = []\n", + "distances = []\n", + "\n", + "for i, theta in enumerate(combinations):\n", + " print(i, theta)\n", + " ratio = clf_ratios[i]\n", + " ratios = ratio.predict(X_true, log=True)\n", + " print ratios[np.isinf(ratios)].shape\n", + " zeros.append(ratios[np.isinf(ratios)].shape[0])\n", + " ratios = ratios[np.logical_and(np.isfinite(ratios),~np.isnan(ratios))]\n", + " nllr = -np.mean(ratios) \n", + " llr.append(nllr)\n", + " print(llr[-1])" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "llr = np.array(llr)\n", + "llr[np.isnan(llr)] = 0." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Computing exact likelihood at same points in order to compare results." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Computing exact likelihood\n", + "exact_contours = np.zeros(len(AABB))\n", + "combinations = product(As, Bs)\n", + "i = 0\n", + "for a in As: \n", + " for b in Bs:\n", + " exact_contours[i] = np.mean([p0.nll(X_true[k], [a,b], intercept, sigma_2_value) \n", + " for k in range(100)])\n", + " i += 1" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#llr, zeros = pickle.load(open('data/ar_results.dat', 'r'))" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib.mlab import griddata\n", + "plt.rcParams[\"figure.figsize\"] = (12, 10)\n", + "\n", + "from sklearn.gaussian_process import GaussianProcessRegressor\n", + "from sklearn.gaussian_process.kernels import ConstantKernel as C, Matern\n", + "\n", + "\n", + "# Define a class that forces representation of float to look a certain way\n", + "# This remove trailing zero so '1.0' becomes '1'\n", + "class nf(float):\n", + " def __repr__(self):\n", + " str = '%.1f' % (self.__float__(),)\n", + " if str[-1] == '0':\n", + " return '%.1f' % self.__float__()\n", + " else:\n", + " return '%.1f' % self.__float__()\n", + "\n", + "# Label levels with specially formatted floats\n", + "if plt.rcParams[\"text.usetex\"]:\n", + " fmt = r'%r '\n", + "else:\n", + " fmt = '%r '\n" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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WIytM5bi6HOFzpQ7E+PxBhONqPOKLq0EAXmz3/wLAUSHE9x3HWR/jexa3/rn0\nPUKItQAedRznZBz32a2sQA7mDbgfL514G0EnmOrNdcCwYlj1hGElj05hZXJUMaj8x3iSh/Eljy2h\nxcgKUzmu8lv/vhDj85GPx3PVwOcBbACwG0A1gDEAfgLgRwA+FkJc12lGqg7ALxC+mMWR1o9NAfAv\nABYAWCWEmJbKcsR0kYGFAx/BqyffR1OoMdmbiUqXsPISw6p7foYVo6oNo0o+BpX3GFB6ivXvxuhy\nlw2hZfuSQZXjyjVRLmSxB8CTQohaAD9DOJrubff151o/1t7nQoibAXyO8BULHwPwm2TGIxDAwoHf\nw+fnlqEu2JzMTcSkU1jp9ibBDKvEMazCGFXyMarcx4iyA6PLO5HtkqmRBdg5m6XyKyMyM5Uf4/OR\nj1elcB/PtP49J54vdhwnCOBPCC8pjOt7opk74D5sr1yBA7UMK7cxrGIL1AcYVhLoElYmvp+Jje9L\n45WM2lCXP2S3aM8JPi+SY8O2ysR9TCwqz1ztRzhixsf4/GWtf8c6Jyse51r/znX7e9b+ft+l/x41\nswijZhYBAK4tvB1HanZi18VYqx2Tw7BiWHXHlvOrGFWJM21nZ/LBiV94gEyp6Pz84QxXYkxfNuj1\nTFbNyUOoLTnkzY3HSeW4ilyk4qbOnxBC5AG4HuFzozancB/Xtf59pNuvSuJ75j05ocvHJufPwcWW\n89hSWZLA3cnBsApjWCWOYaVHWDGqCGBIkfeiPccYXPExedmgV+dl5Q0fh7zh4y79/7nNXS467jll\nn92O4xxB+DLso4QQP+n06V8gPHP0YuSiEkKIdCHE5a3vj3WJEGKCEKJLKQghRgH4LcJXJHyp0+em\nCyG6PJOFEAsB/H3r97ycyOMZkzsVWYEcfHZuTyLfFhcvZq28wLDqxLCwSq8V1odVWp36YWXS0gwb\nltK4iUu4SBV8LibG9G2dSfslQO2ZKwB4EsBGAL9uDZu9CL+v1TwA+wD8vN3XDm39/DGErwYYcR+A\nnwkh1gM4jvDVAscCuA1AFoCPAPxbp/v9JYDLhBCbAESmmaYgfKVAB8DPHceJe8ZsUK/RGJozHm+W\nLI/3W+Kmy3JAhlUnBoaVDKpEFaBHVJnC1AMMt/GAlXTC5YTxMXnZoCkXv1A6rhzHOSKEuBrhmaol\nAG4BcArAUwB+4ThO5xOXnNY/7X2G8Hlb0wHMRnjGqwrhS7O/6DjO0ih3/SKAbwG4uvV+MwCcAfAa\ngN85jrMf7xVQAAAgAElEQVQx3sfQN2MAJufPwcsn3o33W+LGsGJYxcKw8g+jyj+Mqu4xpsgkjK2e\nmbpsUPfIUjquAMBxnFIAP4zj644DSIvy8fUAYr1JcKzb+jOAPyfyPdHkpPXGdUV34cXjy+B0ab7U\nMKwYVrEwrPyjcliZElUMqtgYU2QTxlZsps5m6RpZyseVrjJEJuYNeBCvnHgHQSfo6m0zrBhWsZge\nVoyq+JgQVoyqrhhTRG0YW9GZOJulW2QxrjyycOAjWFbyMRpCDa7eLsOKYRULw8ofKocVo8o8DCqi\n+LR/rTC0zJzN0iWyGFce2VrxKS62VLt6mwwrhlUsfoWVzcsAGVXeYVC1YUwRpY6zWh2ZNpvl1WXc\n3cK48sjuaoaVmxhWsZkcVipEFaBuWDGqzMCgIvIWZ7XCOJvlD8aVBhhWDKtouAzQe6pGFaB3WNke\nVYwpInk4qxVm6myWCpHFuLIQw4phlQiGlVoYVXpiUBGpyfZZLUaW+xhXinN71sqLsPKKV2HlOYZV\navcpOR4YVe6zNaoYVER6sTm0TFsyKHOfybhSmBfLAb3gxayVl2Hl6awVwyr5+1MgHhhW7mFQEZHO\nGFpmRJYMjCtF2XyeFcMqOoaVt1QMK0aVHhhURGazNbQYWclhXCmIYeUNhlXPuAxQDYwq9TGoiOxk\nY2iZtmTQa4wrxdgcVl5iWPWMYaUG3cLKpqhiUBFRezaHFiMrNsaVQmwPKy2vDMiwSv4+JUYEoyp1\ntkQVg8osuvx72nKgbpLIc8uWfztGVmyMK0UwrBhWnZkaVpyt6kqnsGJUkUpM/XdK9HHZckCvA9tm\nsxhZXTGuDMWwYljFg2ElF6NKLaYeqOuI/xaJ6ennZcNBvopsCi1GVhvGlQJ0eC8rhlU7DKvk7o/L\nAC/RKaoAs8OKB/Hy8GfvH8aXfLaEFi9+wbiSTpf3svICw6orhpX7GFbJY1RRqvhz1kOsfyeTI0Am\nW87PsnU2i3Elkc3nWTGsumJYuU+lsGJUyccDfW/x52seRpe3bJvNsiWyGFeSMKzcx7DqmZ9hxahq\no0tYMaooHvx5EqPLfTaEli2RxbiSgGHlPoZVzxhW/mNUycMAcAd/jpSIzs8XUyPBa6YvGzQ9shhX\nBmBYMax6wrDynw5hxaiizvjzIzdFez6ZGgxeMH02y9TIYlz5zOYrA2qHYZX4fTGstIgqwKywYhAk\nhz83koGzW8kxeTbLtMhiXPnI5rDSbtaKYZX4fUmKClWiCtAjrBhV9uLPi1TE2EqMybNZpkQW48on\nOlxynWHlD4aVexhW8WNU2Yc/J9IRYyt+ps5m6R5ZjCsf6HIBCy9oGVYezloxrNyjSlgxqvzDWOge\nfz5kIsZWzxhZamFceUyXsOIFLFoxrBK7L4aV0kwJK0ZDbPzZkG1MXhaXKlN/NrpFFuNKMwwrhlV3\nTA8rRlV8TIgqRkN0/LkQteGsVmwmzmbpElmMKw/ZegELhlVHfoSV6VEFMKziwagyE38mRPExdeYm\nFYws/zGuPGJrWHlF17DyA8PKPwwr7zAg2vBnQZQ6hlZHJv48VI0svY8qKWk6XRlQ57DyetaKYeUP\nRpV3GBJh/DkQeYfLBzsybTZLtchiXGnA9isDeoZhFf99MayUw6jSH38GRHKYOIuTDEaWR+OQeu/U\nI12WA2p3nhXDKv77svTCFapGFaB3WNkeFLY/fiLVMLQYWa7fv5R7pbgwrBhW0TCsvKdqWDGq9GTz\nYyfSie2hZWpk+X6/Uu6VesSwYlhFw7DyHsPKXbaGha2Pm8gUNoeWzY/dDYwrSzCsvOfXe1n5gWGl\nDkaVPmx8zEQ2MG1GJxE2P/ZkMa4UpMsFLLyg65UBTXovKxvDSsWoAvQMKxsDw8bHTGQjm2d0GFnx\nY1wpxvblgJ5hWMV3PwwrJTCq1Gfb4yWijmwNLUZWzxhXCrE9rHQ8z4phlRqGVVcMK3XZ8jhNJASQ\nnZ2J3Jws5OVmITfyJyf8sdzcLPTq1boPirwERbv/TvgOo3xvZFPutP13MBhCY2MLGhub0djYgobG\nZtQ3NKPqQh2qqupQWVWHpqaWJAdBfrExOGx8zPFiXCmCYcWwioZh5R3VwopRpS5bHqeO+vTuhaJ+\nvVHULw9F/fLQrzAPaenhbbMQAo7T+rpygLr6JtTWNqKmthF1dY2oO1uNc7WNqK1pRG1tIxoamn0f\nfyBNICszA1m9MtCrVzoyMzOQk5OJwkF9MGZUfxTk5yAzq91+LBJmDnChuh6VlbXhCGuNsYvV9XD0\n25QYw8bZLEZWV4wrQzGswLCK9358jgxGVVe6hZUNsWHDY1Rdfp9sDBtagIED+qCoX2/k5ma1xRIA\nOMDF6nqUV9SgoqQKO/afRkV5DVpa9Pm3CwUd1Nc3ob6+qeMn9pZ1+31CAL37ZKNv31z0GRwOsb59\nc5DfO7tthgxAXV0Tyk5VouzUBZw6XYV6CQFpK9tCi5HVhnGlAF7AwgMeX3Ldawwrb6gWVowq9djw\nGFWSlZWOoYMLMHxYAYYOKUBWVnif4DgOLl6sR0lZJY7tLsNX56pRV9fUw63Zw3GAixfqcfFCPXD8\nfMyvy83NwuAhfTF8TBGuuXp029JHAMGWEE6fvYBTpy+g7FQVKipr/Ri6lWwKD5seayx6H4EawObl\ngLzkenQMK28wrJJnenCY/vhkCwQEBg7og+FDCzFsaAHy88P7Pcdx0NTUgtKySpQdPIev1u5HYyPP\nL3JTbW0jDh08g0MHz3T5XFpaAAMH5WPgmCLcOPsyFBTkAggvp6ysrMXho2dx+Og5Rq2LbJrNsjmy\nGFcS2RxWntJ4OSDDyhsMq+SZHB4mPzZZMjLSMHpkES4bNxAD+/cBAIRCDk6fuYCTpRVY+9HXuHhR\nsRekpYLBEMpKK1FWWoniTp8rKMzFqIlDcMct05CTEz4GaG5uwbET5Th85CxOnb7g/4ANY0t82PI4\n22NcGUSnsNJxOSDDKjkyw4pRlTyTw8Pkx+an7OxMjBvTH+PGDkRB62xUc3MQR4+fQ/GGgzh79qLk\nEVKyKitqUbnhIIo3HLz0sYzMNIwc1R9TJw/HzYsmQYjwPuvc+WocPnIWh4+cRVNzUNaQtWXLbJZN\nkcW48kB6es8/VrdnrRhWYFjFcz8uxUZ6IICWUM8HqAyrNrqElanhkejjSksLIBg082eRjOzsTIwf\nNxCXXzYIeblZAID6hiYcPnIOGz79BlU8X0dLiTzPm5uCOHTgNA4dON3h4/0H9MaoiUNx373XICMj\nDcFgCAcOncGuPSWoqWn0YtjGsiFAMmpDvj6+eI7J3SYcXrPTC86p+rN4u3Q51pz9ossnbV4OyLDq\nSqewuueqiXh8zkyMLCrA8fOV+OP6rXh7++6oX8uwCmNUyZXo47rlpsl46LuzMGxoAUpKK7H0jc34\nZMUuj0anrtycTEyeOAwTxg9GWnoA9XVN2H/wNI58XYLq6gbZw6MULbl1Ku5/eDaGDStESUkFXnt5\nEz79eKcrt52WFsCYqcMweeIw9M7LQsgBjhw9h127S3jRjASZHFmAt4/vjhsn4tHbr8GIQQVAh2to\neo9x5Y1LP9TfHXqpQ2AxrDzAsOr5flwKq3+956YuH//52yu6BBbDKoxhJU8yj+mWmybjn/7hli4f\n//+e+sT4wMrLzcLkScNw+bhBSEsTqK1rwtfflODwjpOcwTPMklun4j/8x9u7fPx//Y8PXQus9oQA\nhl85BFMnD0Nh60UzSsoqsXNXCU6f4blb8TI5tNx+bHfcOBH/92M3t/+Qr3HFZYEeu2fozVFnr9yi\nS1iRPG4tBXx8zsyYH28fVwyrMB3CilHV0UPfnRXz46bFVV5eFqZMHI7xlw1EWkCgprYJu3afxKvP\nrWdMGe7+h2fH/LgXceU4wIndZTixu+29u4YOK8BVM0dj8KB8AEDZ6QvY8tVRlFfUuH7/pjB5yaDb\nj+3R269x5XaSxbjy2ODsAQgggBBCPM/KC5y16v4+XDzHamRRQdTPjSwqQFpAIBhyGFbQI6oA88Iq\n1ceTlhbAsKHRn+PDhrY9x3WV3SsD06eObBdTjfj6mxK8+ifGlE3S0gIYNqww6ueGDStEIE0gFPT+\neV5aUonSkspL/z9kaAHm3HgZCgvz0NTUgp27TmL33jI+N6NgZHUvLS0QWQooDePKY6fqz3oSVjph\nWHWlU1gBQEsohOPnK6MG1vHzlVLDSpWoAvQIK0ZVdMFgCCWllVEDq6S0UsuwGjqkALNmjkFB3xzU\nNzSjeOdxvPKndb4cPJOagsEQSkoqogZWSUmFtOdGWWklyl7bAgDIzEzHpOvG4HsPzkZaQKD0VBVn\ntaJgZEUXDIZw4nSl1MBiXHns7dLlPM/KCwyr7u/Dg+D44/qtUc+5+uP6rQwrMKz85sVjWfrG5qjn\nXC19Y7Pr9+WF9PQApk4ajsmThiE9LYDSU1XYsPwbVJTzoJTavPbypqjnXL328iYJo+mqqakF29cd\nwPZ1BwBwVqsnpkdWMo/rLx9u6XzOla94QQtvdLhaoK3LARlWXekaVhHRrhb43ufRrxboNYZV/BhV\n8dPtaoGFBbmYNXMMBg/ui5bmIL7eXYK9W46ipcWcf3Nyn5dXC/RSZFZr4hVDkRYQKDtVhc1bj/Aq\nhO2YGFlA4o+LVws0THp6unPX+icA8P2sPOFRXJkQVoA/bxIs+xwrVcJK9agCzAkrvx+HqudYCQFM\nGD8YV00biV69MlBRWYuv1u3HqbIq2UMjDfl1jpVXhgwtwDXzLkdB31ycL6/G518cxLnznKmNMDG0\nEn1M25f+I1paWni1QN0Fg+F3KOd5Vh7wcNbKSyaFFQCGFdQPK0ZValQKq7SAwNQpwzF9yggAwL4D\np/Heq5vRUN8seWSkO53DCgifq/Xu0vCy3aL+vXHDwitQ1K83KqtqsWHTQZw5e1HyCOUycclgoksF\nI8fkftLzSNVSusxa6RhWXs5amRZWgLzLrTOsesaoMkMgIDBl0nBcNXUEhAB2fH0SL/1hrfYHw0Re\nOX+uGh+0XhSjoDAX1y28EgMH9MHF6np8vukgSk/ZO7trWmSp/ni4LNADQghn7qqfuXqbDCs9wwrQ\n/zyrzhhW6m4zTQgSEx5DsgIBgUlXDsWM6aMQEMDOb0qwa9NhnrhPlIL8/BzMWngFhgzui5raBmzc\nfAgnTlbIHpZUqkZJsrp7PFtf/Bkcx+GyQOqIYcWw6vY+GFa+YFR5y4THkAwhcCmo0gICu3aX4tU/\nreMFKYhccuFCHZa/vQ0AkJfXC9cunICbF05CXX0TNn5xEMdOlEseof9Un/lJlGqPh3FlIa8uYKEb\nhlViZISVClEFMKy8pPv4kzVh/CDMmjkW6ekBfLOnFK89t55BReSxmpoGrH5vBwAgJycT1y2+Ejcv\nmoQzZy9i9dq9qK5pkDxCf6kWJalK9tLtbmNcKc6LWSsv6DZrxbBKDMNKTTqHic5jT1ZhQS4WL5iI\n/D69sHf/Kbz+wgY0N/l/sjURAXV1TZdCa+CgfNxxy1Tk5WVhW/FxbN95HDadNWNSZKnwWBhXCuNy\nQD2fngyr1DGsuqdzmOg89mQIAcy8ajSmTx2BisparP5gB6r4njxESjlz+gLeeOHz8IVkrh+Hx/9q\nDi5WN2D12r04d75a9vB8o0KYuEXmvkbPo1dKilbLATU9z4phlToVwkrVqAL0jhOdx56ofoV5WDT/\nSuTnZ+Or7Ufx/G9XWfWbcCIdhUIOdmw4iB0bDqJPfjbm3joFA4p6Y9+BU9i4+ZA1S3dNiiwZGFeK\nsn45oEe8Xg7oNYaV91QNK53DROexJyIQELj6qlGYPmUEyitqsfr9YlRVSboKDBGl5OKFenzw6pcA\ngHHTh+N7D8xGMBjCus/3W3MRDFXOYdIN40pBXA7I86xkY1ipRdc40XXciepXmIfFC65E77xe2Lr9\nGGepiAxzqPgkDhWfRK9eGbj+5om4aeFEnCipwJp1+9DU1CJ7eJ7iLFbiGFcWYFh5z6TlgAwrtegY\nKDqOOVGBgMDMGaMxbfJwlFfUYOW7xbhwgbNURCZraGi+dBGMIRMG4qH7ZqGlOYgVa3bjzNmLkkfn\nLUZW/PQ8kjWYLssBPcHzrGLfB8PKUyqGla6Bouu449U7rxduuWky+uZnY8tXR/Hcb1bJHhIRSVC2\n7wxe2ncGublZWHDHVPTv3wdbtx1F8c4TsofmKUZWzxhXCrF+OaBHGFbxYVipQ8dA0XHMiRg2tAA3\nLZiIxqYWrHqvGOXlNbKHREQKqK1txAevbYEQwPQ54/GjH8xF6akqrP5sD+obmmUPzzOMrNgYV4qw\nPqw0Pc/Ka35ewMJvDKvodIsU3cabqGlTRuC6a8agpLQSr/95AxobzT6/goiS4zjA9nUHsH3dAQy8\nbAC+e89MAMDKz/ag7FSV5NF5hxe96IpxZSiGlf4XsDD5yoCyw4pR5Q4dxxyPjIw0zJ8zAWNH90fx\nzhP407+v5AUqDJRW3SR7CN0K9tbo7VOogzMHz2LpwbPIzs7E/NunYsitfbGt+Bi+Kj5m5LaEs1gd\nMa4UwPOs9MMrAyaPYdWVbpGi23jjld8nG0sWT0bvvCx8tn4f1ry/Q/aQKAGqx1KiEnk8DDE11dc3\n4eM3twIApt4wDk98fy7OnL2IFWt2o67OrOcrwMiK0PPI1iDWLwf0CM+zig/DSj7dQkW38cZjxPBC\nLJ5/JeobmrHyvWJUVtTKHhJFYVo8uam7nw3DSw07Pz+EnZ8fQv+xRfjO3Vcj5Dj4ZMUunDfw/E3b\nI4txZRitwkrD5YAMq+QxrLrSKVR0Gmu8pk0ejuuuHYsTJyvw6nMbjH+/Gh0woNzH8FLLucPnsfTw\nOuTl9cJN37oKfXr3wicrv0FpWaXsobnO1shiXEnE5YDu4wUs4sOwkkunUNFprPGaNnk4bph9Gc+n\nkogRpYZY/w6MLu/V1DTg7Zc2ISsrHYvvvgq33jQZn678BidLK2QPzXW2XfSCcSWJ1csBeZ5V9Ntn\nWHmCYZU8ncYajysnDMb8OVdg5zcn8cwvl8sejjUYUvqJ9m/G4PJGY2MLPnx9CzIy07D4rqtwy82T\nsWLVNzh2olz20Fxl0yyWnke51IU2YeUhnZcDmhpWsjGskqPLOOM1bswALF4wEfsPnsYff70CoZBa\nzwvTMKbM1PnflbHlruamID5+cysyMtKw4I5puHnRJKxcswdHjp2TPTRX2TCLxbiSgMsB3adzWPnF\ntjcJZlglR5dxxmPE8ELcetMUHDtxHs/9diVCQbWeEyZgSNmLs1veaG4OYvnb25CWFsD8O6bipoUT\nsWrtHhw6fFb20Fxj+iwW48oA2sxaaboc0GumvlEwwypMl1jRZZzxGDK4L25fMgWnz1zEX55eg+bm\noOwhGYMxRd1p//xgaKUmGAxh1bvFSEsLYN7tU7B4/pVYs34f9h84LXtorjE1sni06zO3Z620CSsP\n6TxrZepyQIZVmC7Boss4e9K/qDfuvHUqKqvqsPSP69DYyKv/pYoxRcniMkJ3BIMhrH5vBz5LE5hz\nyxQsmHMFVq/dgwOHzsgemmtMWyrIuPIRlwO6j2HVM4aVHLoEiy7j7E5hQS7uvG0a6uub8MYLG1Ff\nzyBIBYOKvMDYSk0o6GDthzuxPk1gwe3TsGDuFfjw050oKTXjEu4mzWIxrjSmzawVw0oahpUcOgSL\nDmPsSZ/evXDXbdMRchy8u3QzamoaZA9JS4wpkoGxlZxQ0MGq94qRkZmGJffMwM0LJ+K9j3YY82bE\nJsxiMa58wuWA1J4fs1YMKzl0iBYdxtid9PQA7rh1GvL7ZOPD17egqsqyy2CmiDFFKuL5Wolpbgri\ng9e2ICcnE7d+ZyYyMtLw7gfFqDbgl0y6z2IxrnzA5YDu03nWysQLWDCswnSIFh3G2J0brhuHKZOG\n48NPdqJsvznnHHiNQUU6YWjFr66uCcv+shH5+Tm457szUd/QjPc/2oGGxmbZQ0uZrrNYjCsNaTNr\nxbDqevsGnmfFsNIjWHQYY3fGjR2AJYsm4Ysth/GHX62QPRwtMKjIBAyt+Fy4EL6QT7/R/fDw/bNw\n9lw1Pl7xNVpa9N726ziLxbjyGJcD6oNhlTiGlR7RosMYYyksyMW9d81A2akq/OFXfAPgnjCoyGQM\nrZ6VHy3HC79fgyETBuKxR+fg8JGzWL1ur/bbTp1msRhXHuJyQPd5OWtlAhlvFCwDwyo+qo+vOxkZ\nabj79unIykrH63/egLo6RkMsDCqyEUOre2X7zuBP+1Zi3PTh+PFj87F121Fs2XZU9rBSosssFuNK\nI9rMWmkYVibMWtlyAQuGVXxUH193rpkxGjNnjMa7H2zHmUPnZA9HSQwqojYMrdgOFZ/EoeKTuHre\n5fibJxbgvY+Ktb98u+qzWIwrj+gwa8XlgGEmhJXfGFZqh4vq44tl4IA+uOfOGdi56ySefWq57OEo\nh0FF1DOGVnRfrd2PHZ8fxO33XYvM69Pw1nvbtH6jdZVnsRhXmvBi1soTGs5aeYnnWbmHYdUzlcfW\nncgSwPT0AF58Zo3WO3wvMKqIkhN57TCywlpaQnh36RfoN7offvi9G1H89Ql88eVh2cNKiYqzWGqN\nhqLickB9lwP6gWHlH5XjReWxdWfG9JF44vtzsWnzIbz5wkaGVau06qZLf4goNXw9dVR+tPzSBYL+\n5okFGDSgj+whpSSjNqTUPpAzVxbicsAwE5YDMqz8o9KGuzOVxxZLXl4WHvj2tdh/8DSXALbDgz8i\nb3E2q822tfuxa9Nh3PnAtQiFHLzzwXY0NwdlDytpqsxiMa4Ux+WA8l8kyWBYuYNh1TOVxxbLDdeN\nwxWXD8GyFzeiurpB9nCkY1AR+Y/nZoU1NbVg2V82YuC4/vjRD+biiy8PY9uO47KHlTQVAkvPI1dK\nGpcDhpmwHNB0DKvuqbYMIh5983Pw48fmoak5iD//brX1YcVlSkRq4GsROHPoHJ755XLk5GTir384\nD0X98mQPKWmy94+cuVKYNrNWmuFywMTImLViWHVP1XF1Z+G8KzByeD8s/eM6q9+zyvYDOCKVcckg\n8MXKPSj+/CDufnAWamsb8f7HOxEM6rfPAeTtKzlzpShexELPpybDyhyqBoyq44qlqF8e/uaJBSgv\nr8GLz3xmbVjxN+NE+rD9AhgN9c147bkN2L7zBH782DxMnjhU9pC0ovwRrBBiqBDieSFEqRCiQQhx\nVAjxlBCibwK3cUwIEYrxp6yb75sthPhYCFEuhKgTQuwUQvxUCKH8z60zhlWYl7NWDCt3qDBrpWrA\nqDquWG65aTJuvXkK/vL0Gnyz+Yjs4Uhh8wEakQlsfg2X7j2NZ365HAP698HjfzUH+fnqv4erCpRe\nFiiEGAPgCwBFAN4FsB/ANQB+CuBmIcT1juPE8zbTDoAqAE8B6Hx0XRPjvu8CsAxAPYDXAVQAuKP1\nNmYDuC/RxxMvLgf0Bs+zih/DSj2qjiuawYPy8e27r8bqtXuw8p3tsocjha0HY0SmsnnJ4LqPvsZX\neVn49iOzcfR4Odas2yt7SEoTjiP/YCYWIcRyAIsA/K3jOL9v9/F/A/APAJ5xHOfJOG7nKADHcZwx\ncd5vbwCHAfQGMNtxnOLWj2cC+AzALAAPOI7zRozvd6Z++PN47ioqt+OKs1Y8zypRtp5npWLAqDim\nWAIBgTtumYrcnCy8s/QLrS/pmwwGFZE9bIwsAJh03VjccN04vP7WVpw7Xy17OD1a9+k/wXEcX3+7\nruzyttZZq8UAjrUPq1b/DKAWwCNCCC/mKL+D8GzZq5GwAgDHcZoA/Bzh2a8fe3C/Vs9a8Tyr2BhW\n3lMxYlQcUyxDhxTgJz9agN17y/DGC59bFVY2LxsispWtr/tvvjiMP/9uNZYsmoRbb5osezhKUvlo\ndn7r3ys6f8JxnBoAGwHkIDyLFI8sIcRDQoj/JIT4OyHEvG7OnZqP8FLCaO9suR5AHYDZQghXp4Rs\nv4iFV3RfDsiw8p6KEaPimGJZsngS5l4/Hn/41Qoc21Uqezi+sfXgioja2LgdaGxswavPrcexE+X4\nyY8WoLAgV/aQlKLyUfLlCAfOgRifP4jwzNZ4hJfq9WQQgBfb/b8AcFQI8X3HcdZHuW9Eu2/HcYKt\nywyvBDAG4fPAlKRTWHHWSj6GlTpUHFM02dmZePTB2dj05SGsere4528whG0HUkTUMxvPyTqw7ThO\n7CnDfd+/EfsPnsbnmw7KHpISVD6izW/9+0KMz0c+Hs9VA58HsBDhwMoFMBnAMwBGAfhYCNF5XtPN\n+44LlwN6g1cHVBfDKjoVxxTN6FFFeOzRG7HsxY3Y8+VR2cPxhY2/oSaixNi2nWiob8Zffr8GLc1B\nPPH9OcjNsfd4NkLlmSvXOI7z3zp9aA+AJ4UQtQB+BuBfANzr97i8pNOslVe4HDB+Nr6flYoRo+KY\nolmyaBLy87Px7FPLEQrJj2Sv2XSgZLNAjdwNYSiPl7k2iW0zWV+t3Y+DxSfx6PdvwMbNh7Bz10nZ\nQ5JG5aPlyOxQfozPRz5elcJ9PINwXM1x+75PL1136b/zJo9E3pRRMQfBWSv9cDlgamTPWqkYMSqO\nqbNeWRn43kOzsXXbUax6z/xlgIwqvcmOpUTFO15GmF5siqwLF+rwh1+twPw7puKRB67Da8u2+H5x\no6ryw6iqkPu+iirH1X6Ez4saH+Pzl7X+HeucrHica/2785l4+wHMaL3vDkcQQog0AKMBtACI+a83\n6KG5KQwrNZy14nLAeDGs1KDimDobOaIf7rptGl59fgMqK2plD8dzDCs96BZQbojnMTPA1GNTZH32\nwU4Uje6HHz82Dx9+8jWOHDvX8ze5pG+/sejbb+yl/z9+eJVv9x2h8rRB5CIVN3X+hBAiD8D1CF+1\nb3MK93Fd69+dI2kNwmG3JMr3zEX4KoUbHcdpTuG+AfA9rbzA5YDqYlh1lFEbUm5M0SyafyVmXzsW\nzwnFdVAAACAASURBVPxyufFhZdv5EjoI1NTH/EPR8WelLlu2MeePluOZXy7HtCnDce9dMxAI6H1s\nlghl48pxnCMIX4Z9lBDiJ50+/QuEZ5tedBynHgCEEOlCiMtb3x/rEiHEBCFETufbF0KMAvBbhK9I\n+FKnTy8DcB7A/UKIGe2+JwvAv7Z+z9PJP7owLgfUD5cDJo9h1ZFq44kmMzMdjz16I6ou1OHNFzYa\nfX6VLQc8qmMUeIeBqhYbtjmhkIP3X/0SxTtP4Cc/WoB+hXmyh+QL4Tjq7ixbQ2kjgAEA3gewF+H3\ntZoHYB+A6x3HqWz92pEAjiL8psNj2t3GPyN8XtV6AMcBVAMYC+A2AFkAPgJwj+M4LZ3u+y4AbwJo\nBPAagAoAdyK8VPBNx3Hu72bcztQPf97j4+Oslfu4HDA+DCu5VBtPNMOHFuKeO6/C0jc2o+pEpezh\neMb0gxuV8cBeXVxW6D/TlwtmZaXj/h/OwTd7SvHlVv/OiVr36T/BcRxfp82UjisAEEIMRXimagmA\nfgBOAXgbwC8cx7nQ7utGIry875jjOGPbfXwOgB8BmI62S7FXAdiB8MzX0m7u+zoA/xnh5YO9ABwC\n8ByA3zjd/ODiiSub3zBYx7ACvI8rU8MKkBtXqoWMauOJZv6cCRg6pC/eeOFzhIJq7yOSxajyF0NK\nb4wtf5geWABww5JJGDG8H155YzNaWrzfHzKuDCEjrnQJK0DPuGJYJY9h1Ua18XSWmZGGRx64Drv3\nluGrtcq+P3pKGFX+YEyZjbHlLdMjq//YInz3nplY9s5XKD2VykW/eyYjrvS6BJwheK6V+3QOK5Mx\nrNqoNp7Ohg7ui29/62q8+uaXqDhWIXs4nmBYeYcxZZdo/94MLveYfmXBc4fP49mnluM7j96A0lNV\nWLNur+whuUrPqwpQB7rMWul6EQuvmTprxbBqo9p4Opt51SgsXjARzz613MiwsuHEcb/xogjUGZ8P\n7jN529XSEsKrz61HdXU9Hv+rOcjMNGe+x5xHogktZq34nlZtt83lgEmRfQELlageVksWTUIgIPDy\nH9bKHorrTD0okYEHzJSI9s8XzmilLq26ydhZrOINB3HsxHn8+LF5eG3ZFpw5e1H2kFLGqQTNeTJr\n5QEdlwOSnlSKGZXGEs2D37kWlRfqsOKd7bKH4jqGVeo4E0Fu4PPIHSbPYlUer8QffrUCd9wyFTOm\njZQ9nJQxrnzEWSu9cNYqOVwOGKbSWDrLyEjDX/9wHr4qPoZthl24wuQDED/wQJi8xOWkqTN1G9fc\nHMQLv1+D/v174967ZvT8DQpjXGmMs1ZcDtgThpUcKo2ls7y8LDz52Hy888F2HNlZIns4rjLxgMMP\nPNglWfi8S56p27tV7xZjz74yPPn4fGRnazApEQWnKXxi86XXibymUsyoNJbOBg3og/vuvQYvPLMG\ntTWNsofjGlMPMrzGg1pSBc/RSo6pVxU8uP0Ezh0txxM/nIO33t+GklK93sieM1fkKc5adcVZK3ep\nFDMqjaWz8eMG4u47rsIffr3CmLAydXmMlzhLRarjczRxJm4Hqypr8cxTy7Fw7hWYNXOM7OEkhHHl\nA85a6cOU97SyJaxUonJYzZo5BldPH4U//ftKNDcHZQ/HFSYeTHiFB6ukKz5v42fiL5uCwRCW/nEd\nevfuhXvuvEr2cOLGuCLP6Dhr5TW/Zq38xPOs1BlHNLfdPAV983Pwxgufyx6Ka0w7gPAKD0zJFPwF\nQfxM3D5+9sFOHDh0Bk/8YC4yMtJkD6dHnK7wmK2zVjqGFZcD6kWVoFFlHJ0JATx833XYd+AUijcc\nlD0cV5h40OA2HnyS6Xh+Vs9MPBdr39ZjOHe+Gk8+Ph9/WboJVRfU/W01Z66IDGLLckBVgkaVcXSW\n2Xqp9S+2HGZYWYC/1Sdb8XnfPdO2m+VHy/Hcb1fhoftmYcyo/rKHExPjykOctXIXZ63UYntYqapP\n71748WPzsezdbTi2q1T2cFJm4nkEbuGBJVEYXwuxmbYNbahvxh9+tRyzZo7B7GvHyR5OVIwrsp4p\nYeXnrBUvYKFm5A0elI/vP3wDXnh6DSqPV8geTspMOiBwC2epiGLj6yM2k7anjgO88cLn6NUrA9++\n+2rZw+mCceURzlq5S+eLWPiB51n5S5VxtDd2dH/cees0PPur5ait1ftS66b9ptUNPGAkSgxfM12Z\ntm1d//HX2L23FE/8YC7S09VJGnVGQv7ipdcBmDNr5SfblwOqMo72xozqj3lzJuD5365CS4t640uE\nSTt+N/AAkSg1fA11ZdJ29uD2E3j/w2I8+fh85OSocQEPxpUGPJm18gBnreSwYTmgKkGjyjjaGz2y\nCAvmTsCLT6+Bo/lqTZN2+KniASGRu/ia6sik7e35o+V4+Y/r8PhfzUFhQa7s4TCurMRZKwBmzFox\nrPyjyjjaGzWiHxYvuBJ/0TysTFuqkgoeABJ5i6+xNiZtey9eqMdzv1mFB797LYYNLZA6FsaV4jhr\npeeslYnLAW2mYliNHNEPNy2ahBd+r39YEQ/4iPzG11wbU7bDDQ3N+MOvV+CWxZMxYfwgaeNgXJGy\ndL70uh84a2XPGDobMbwQSxZNwgu/W41QSN+yMmWHngoe4BHJxddgmCnb41DQwZ9/txrTp47AtTPH\nSBkD40phtl8hUFdcDugOFaJGhTF0NmJYIW69aQr+rHFYmbQUJVk8oCNSC1+TZm2b33xhI4oK86Tc\nN4+KSUmctbKbilGjguFDC3Hbkil4/rertA4rm/EAjkhtfI2as51e/vY2KffLuFIUZ628wYtYJMbm\nNwtWLfCGDS3A7bdMxXMMKy3xgI1IL7a/Zm3eXqeKl40j5eh6EQtyhwpRo8IY2hs6pAB33joNf/rN\nSoSCDCud2HxwRmSCyGs4lJcteST+i2y3g73VeP8oXeg17WAJzlp5g7NWiZExa6VC1KgwhvaGDu6L\nu2+fjud+s0rLsDJpDX+iGFZE5rD59WzrNjxZnLkipeg6a8WwMoNqYTVkcF/cfcdV+NO/r0QwqNbY\n4mHrDtnmgzAik9k+i8UZrPjoNfVAyeGsFS9ioQHVwka2wYPycc+dDCud2H6OBpEtbH2t27hdTwZn\nrhSjy5sGe4GzVrGZPmulQlipMIaIAf174967ZjCsNGHjQRYR2TmTxfOweqbX9AMljrNWnLVKAMNK\nvvw+2Xjg29fiud+uQkuLOuOKl01hZetvr4moIxu3AzZt6xOl11Gy4ThrpR/TZq1spFJYZffKwF89\nfD2e/91qNDcFZQ8nIbZduMLGgykiis3GX7bYtM1PBOPKZJy10n7WissBzb7/9gIBgR8+eiOW/nEd\n6uv12mHZtIO18QCKiOJn2/bBpu1/vPQ6UjYYZ63048eslV9sDCvVfO+B2Xj/4x2oqtLriWXTjtW2\ngyYiSo5tv4SxaT8QD17QwlScteKsFXVLpbi789Zp2PnNSZTtOyN7KAmxZYdq00GS1apr5Nxv7zw5\n90ueC9TUW3OxC16qvQ3jSgGctdIPZ61SIztsZN9/eyNH9ENDYzN2bToseygJYViRNmRFU7ziHR8j\nTEs2XVGQVxIMY1yZiLNWns5a8SIWqZEdNrLvv7PjJ8pRuve07GEkxIawYlRpSPWISlV3j4/hpTzb\nIsvmwGJcScZZK5JJxqwVdZRe2yx7CAlhWJF0pkdUMqL9TBhcSrJlqaDNgcW4Mg1nrThrFScuB5SP\nYaUWRpWCGFLJY3Apy5ZZLFsDi3FFUnDWyj6yw0b2/XfGsFILw0oRjClvMbiUYsMslo2BxbiSSIcl\ngZy1asNZK32pFla6MTmsGFWSMabk6/xvwNjyFQPLPIwrk3iwJNALnLWKjhexsIdOs1YMK3IVY0p9\n7f+NGFq+sGGZoE2BpcfRuIF0mLXSje6zVn7xe9ZKdljJvv/OGFbyMap8xJjSG2e1fGX6LJYtgcW4\nMgUvZKE1Lgf0BsMqeQwrShqDylyc1fKc6bNYNgQW40oCm2etvFoSyFkrNcmMG7/v+9qZY5Cbk4mG\nhhZs+vJQl88zrORjWHmIQWUfhpanTJ7FMj2wODVhAs5aaY2zVvqbe8N4/MPfLEa/wjz86Adz8Xc/\nXogRwwsvfZ5hJR/DygPVNW1/yG58LnjC5O2WqfsagHFFPuKslV1smbXKyEjDjbPH49dPr8Kb73yF\nJ/7uLwCA7z98A8aM6u/bONxg4s4uUFNv9AGK73gQTT3h88NVJm+/TNznAIwr3+mwJJCzVv4xddZK\ntXOdvNTcHMS+A6dw9fRRyM/PRmNjC/796dU4eOgM/uX/uhNj++fLHmJcTNzJmXxQ4jseMFOiGOKu\nMfmXREbue2QPgFJk+eXXOWtFnckIux27TqJXVgauvHwIcnPC68hfefNLrPp0F664cqjv40mUkTs3\nQw9EfMWDY3ILn0euMHW7Zto+SI8jc0PoMGtF/uGslTn3fejwWez4+gTuun0aBvTvjb37T+HIzhL0\nK8pD7z69pIwpXqbt1Ew9+PAVD4LJK7wIRspMvdCFSRe5YFzpTJMLWeg4a0WUqJWf7UHpqSrcdvMU\nTBg/GAO+dyOyszPxjz97RfbQYmJYUQeMKvJT5PnGyEoYA0ttjCuiKLxeEshZK/3vOxAQCIU6/nz3\n7CvD0ePnkS8CKCjIRUV5DRrq1bxSIMOKADCoSD5GVlJMfT8sEwKL51z5RIclgbyQBaXClrBaMHcC\nACAUchAIdJ2VbT5fi/PnqnHwwGmUl6t54MqwIp4DQ8rhOX5JMXH7p/s+ikfTuuKFLDzDWSuK5adP\nLsJ//D9uxX//l3tQWJDbZeYqvbYZi5dMxqTJwySNsGe677TaM/kKWp7hwSvpgM/ThJi4HdR5X8W4\n8gFnrchvXA7ovsGD8jF0cF/89U9fwoFDZ/D//td7MWPayA5fEwgIlJ+rxje7SnwZU6J03ll1ZuLB\nhKd4sEo64vM2biZuE3XdZ+kx/UEdcdbKM6bMWtnCz6g7dfoCfvvsGpw9V40XXt6IslNV+PHj87Fy\nzR68/tYWDOuTg4x+6di+7ZhvY0qErjupaEw8iPAMD0zJBDwvKy4mXuhCx3Ow9DhKJ6K42TRr5bcT\nJRWX/nvF6t0oLavEow/OxqTLBmH85YPxi39+W+Lo7MCwihOjikzEyOqRiRe60C2wuBbMY7YuCeSs\nVVectXKXClG3e28Z/vt/eQfXzhqHjz4oxv69ZbKHFJUps1YMqzhwGRXZgM/zHpm2vdRpP8a40o0m\nSwJJDltmrVQIq4i7770am784iFde2ih7KFHptEPqjmkHCq7jwSbZiM/7bpm23dRlf8YjdcvxQhZh\nnLVKnEqBI0t6bTM2bzqIpS9+LnsoUemyI+qJaQcIruKBJVH4dcClglGZdh6WDksEeWTtIdeXBGoy\na6XjkkAT2HLpdVWiLr02/ObAhw6egaPgj55hZTj+xp6oI74mYjJtO6r6/o1xReQxzlqR31Tf8cTL\ntAMCV/AAkqh7fI1EZdr2VOX9HOPKI7yQhcu3q/GFLPzAWSt/RWatyDumHQi4ggeMRPHj66ULblf9\nwbjShSZLAsl8tl/EQvWwUvm3efHiAUAn/E08UXL42unCpO2rqvs7xhVZzYQLWdgya0U9U3VHkwiT\ndvyu4IEhUer4OurApO2sivs9xpWluCSQkmHrrNWwoQW4fPwgpWetVNzBJCJQU2/UDj9l/I07kbv4\nmurApO2tavs/xpUOuCTQE5y1onikBQTuufMqHPu6VPZQYlJtx5Iok3byKeMBIJG3+Bq7xKRtr0r7\nQcaVhThrRcmwddbqW3dehfc/2oFgUI1zvkxj0s49ZTzgI/IPX28AzNoGqxJYjCvVcdbKEybMWtlA\ndliNHlmEUMhByd7TUsfRHVV2JskwaaeeEv4mnUgOvvYAmLUtVmGfyLgiZXHWqnt+LgmUHTkyCAHc\nfstUfPjGFtlDiUmFnQiliAd2RPLxdWhUYMnGuLKMTksCdcVZK3fIDrpbFk/GijW7EQqqeV6b7mFl\n/Y6cvzEnUgtfk8Zsl2XvHxlXKuOSQE/wTYMTIztyZCjom4MBA/rgcPFJ2UMxkik78KRZfgBHpDTL\nX5+mbJ9lBhbjipTEJYF2kx103777arzz8hdSx9Ad2b+VS4UpO+6kWX7gRqQFy1+npmynZe0rOTVi\nES4J9J5pl1+XHTkyXHH5YBw/WY7a2kbZQ4mKYaUpyw/WiLQTec32zpM7DkkCNfUI5WXLHoaWOHOl\nKi4J9IQJSwJNJzPohAAWzb8Sn32wQ9oYTMWwIiItWfz6tXq7nQLGFSlH1yWBnLXS3+IFE7Hqsz1w\n1LyGhbazVlbvoC0+MCMyhsWvY6u330liXFmCSwI5a6UDmUGXk5OJkcP74eD2E9LG0B2GlWZ45TEi\ns1j8mrZ2O54kxpWKuCSQouCslbfuvWsG3n11s+xhRMWw0oylB2BEVrD09W3t9jwJjCtSCpcE2ktm\n0A0fWoi6uiZUVtRKG4NprN0RW3rgRWQVvs6pG4wrC3BJIJcEJsLGWas7b5uGj97YInsYUek6a2Ud\ni5cMEVnJwte7tb80SxDjSjUWLwnkrFVsfi4JlEFm0M2aOQZfFR9DS4t6UalrWFm3A7bwIIuIYOUv\nVazbvieBcUUJ46yVuWybtUpPD2DG9FHYtna/7KEYw7odr2UHVkQUhWXbAeu28wliXBnOiyWB1Iaz\nVqmTGXS3LJ6Mjz7dKe3+u6PjrJV1O1zLDqiIqBuWbQ+s294ngEfeKuGSQCLf9MrKwOBB+SjZe1r2\nULpgWGnAsgMpIoqDZdsF67b7cWJcUUK4JNBcMmaQZM5a3XHrVLz/0Q5p928S63awlh1AEVECLNs+\nWLf9jwPjymBcEugtLgnUV15eFnJzs3D+aLnsoXSh46yVNSw8eZ2IksDthNV49K0KLgkkiWybtbr7\n9un48I2t0u4/Fh3DyprfWvJgiYgSYdE2w5r9QJzsPaKnhHFJoL84a+WNwoJchEIOqir5hsGpsmaH\natFBks1CF6ql3G8gv7eU+yUfVNcAvfNkj8IXgZp6hPKyZQ9DCYwrQ3FJoLf8WBLoFxtnrd56aZO0\n+49Ft1krhhXpSFZAdae7MTG8DMDAsg7jiqTikkDy05DBfXHhYj1qaxtlD4V0wLDSlooRlYxoj4PB\npSGLAosYV2qw+Hwrr3BJoLpkzlrdfstUvPzsWmn3HwtnrRTEsNKKKTEVDwaXpiLbFMMji7NXPsaV\nEGKa4zi87rEPvFgSqNv5Vl7ikkA9jR3dHyUlFWhqapE9lA4YVgpiWCnPppiKR+efB2NLYRbMYtke\nWH6emPNPPt4XaYBLAqPjrJU3bl40CaveL5Z2/yZgWJEsoQvVHf5Q9/izUpwF2xkr9hcxpBRXQoih\nQogRcfwZBWB6CvfxvBCiVAjRIIQ4KoR4SgjRN4VxPyyECLX++UGUz49s9/lof15J9r674JJA13m5\nJJCzVnqaPHEo9uwrQyioVrjqNmtlPAsOeHTCQHAHw1RRFmxvbA2sVI/s3wZwdRxfJwAkfFQjhBgD\n4AsARQDeBbAfwDUAfgrgZiHE9Y7jVCZ4m8MB/AZANfC/2bvzODuqOv//79O3O0l3ZyEBQkizJCEB\n2VchgAIGCKCDuCKKy9cF/cmoDIN+HUcfgnz15/idUWbUcRkRFRcQd3FjERVZAio7KJKV0ASyr52l\nl/P9o26HTufe7rtU1Vnq9Xw8+tFwb3fVSdetOp9PnXM+pdHGZR8q73e4x+rZZ56YEghfuUzmTn/J\nIfrqNbc4238Mou8kCxDohIDgP3tD/8ZMH3SsAFMEi6jZ5OpSSf8o6Vuj/FxJ0jca2P6XlSRW77fW\nfmnwRWPMZyVdLulT5TbU4xuSVitJDD84ys8+ZK29us7towZMCaws5imBrhx1xH566NHlsp79aUMa\ntSKxQpZIqNwh0fJA5AlWEddfNZVcWWv/Yowx1to/jPazxpj769l2edTqbElLhiZWZVdKerektxhj\nrrDW1tTzG2Muk3RG+evMetqTCaYEpo4pgbUp0pTAU+fO0bWfv9V1M3YRUmIVPRIrZ0iq/DJ4PEiy\nkLaiJVhpzCH7RY0/9z91bvdl5e+7RUXW2s2S7pbUIWluLRszxhwq6dOS/tNae1eNbZhujHm3MeYj\n5e9H1vJLra1ukiamBCIvpVJ9nzVXydycg/bRwsXPezdqFZKoR61GSKxKrTyIPQus/fFLqbW022sc\nIwcKcJPHVV/iIiZveo/W2h/V+HO31bnpQ5Ss0/p7lfefUjKydbCk3420IWNMSdK3JS2V9NE62nB2\n+WvIpszvJb3NWru82i/19vZqyca1+tJjC/SDhY/UsbtiYEpgZXlNCWwm0XnFvCP0llefpP33nazl\nK9bp2z+5T7+8w9sliJp3+ov0zS/d4boZuwhp1KqIidX8N56sC99/jrpmTVX34pW66Qu36NYb7s25\ncfEhUPfL/Leepos+dL66Zk9T98LndOO/36xbr79zt59jNCtHkU8PzNv8C47VRe94qboO+ETu+24o\nuTLGfFBJIYufS7rRWjsw5L2SpC9K+ri1dlUTbZtU/r6hyvuDr9dSNfBKSUdLOtVau72Gn++RdLWS\nYhaLy68dJekqSfMk3V5+blfVyGPmxCn691NeLkkkWDlhSmC2XjHvCP3rpefu/P/995288/9HSrBc\njVrt3zVFz65Yr/7+4kyBRI1GSKwuv+YtO/+/a9bUnf9PgtUYkir/zH/rabriq5fs/P+u2dN2/n+l\nBEsiycpN5AlWXtMD519wrK646lWZ76eahuY9WGv/Q9JblFQB/Ikx5lVD3utXUojiv1NpYZOMMSdJ\n+oik/7DW1rTuy1q7ylp7lbX2IWvtxvLXXZLOkXSfpNmS3lXLti49osqsxQDWWzElEEO95dUn1fW6\na/PPOly//blfzy1n1MoDI0y/ufD959T1OqpjWpm/LvrQ+XW9PhTHNQeRTxHMo2+56B0vzXwfI2l4\nUrm1ttda+11Jr5F0sDHmC8aYdmNMh5LqgIc22bbBkalJVd4ffH19tQ2UR9GuV1LC/ePD3663QeXE\n8dry755Wy+/MnDhFvU8urXdXdctivRXy4/uUwFKpRfvvO7nie/vvO1mlFr8S8SmTO7Vly3bt2NHn\nuilBijaxGkGptUVds6ZWfK9r1lS11LnOsKgIvv1Wai2pa/a0iu91zZ5W8+ec45yxyBOsLG3Yulxd\nB+zptA0N9RbGmE5jzP8xxvxV0hYlhSIulbRZyfOj/izpgSbb9qSSJObgKu/PKX+vtiZLSp5jNUdJ\nord96IOA9UKydW35tc/V2K7BqY6dtfzwko1r1XbIjBo3Hb+s1lsxJTBb/f0DWr6i8iPllq9Yp/6B\nysmhqymB5559hG776YNO9l1NKKNWUSdWIwQs/X0D6l68suJ73YtXaoDppSMi2A5Df1+/uhc+V/G9\n7oXP1f0557hnKOIEK8t+ZlL7/up+ek1m269F3cmVMWaKkuTpo5JmKnlm1NPlr6VKkqsPSnpnk20b\nLFIxv0Ibxks6VcnaqAUjbGO7kpGmr5e/D/0aTP7+WP7/WifUn1z+vnjEnyr70mMVmhfAlEDkx/dR\nq0Hf/sl9db3uytixrRo3tk0bNmSYcSM8NQQqN32h8oOmq70OgusQ3fjvN9f1ei34HGSEBKshN173\nx8y2XYtGovxPSlou6W2S/mTtrkWOjTGvkXSQtbap+TjW2sXGmFslnW2MeZ+19otD3r5aycjRlweL\nShhjWiUdJKnXWru4vI1tSp6HtRtjzJWSjpX0LWvtdcPeO1bJA4SH/9vOlPRPSqoYfmek9odeLZD1\nVhhusGhFrdUCXY1anT3vcN12xxNO9l0No1aO1RigDBatoFrg6AikwzVYtKKWaoH1ovAFfHDrz5KZ\nK0m1wPynCBpb5wNgjDF/kTTXWts7ws98T9I/W2srjz3Xvq9ZSp5nNVVJZcK/Knmu1RmS/qak+t+6\n8s8eKGmJpKXW2lk1bPtKJVUE31UhufqdkumE90h6pvzyUUoqBVpJH7PWfrratltbW+1+132y+s5T\nHrkK5flWTAmsLJSRq6FKLabqVMAs9lcrY6T3vOMMXfv5ep/8kK0QkquiJ1bDtZRamApYAUlVXLL8\nnJNgpSjiCoJZVw/87aOfUl9fX64jBo1E5RtGSqzKPi/pHxvY9i7KI1AnSPqmpBMl/bOSqYjXSDp5\nMLEa+ivlr5p3UeX165VMGzxBSVXA9yqpEHijpNNGSqwkqb+/v44moMhCTKwkjZpYuTL3xIO04P5F\nrpuxixASq2g1MaWGxGpXTPuKU5afcz4zKWJ6YMNcxOSNDKF0GGM6rLVVxwustQuMMVc30a6h2+pW\nDeu3rLXLlFQprHW7n5BU8cli1tpvSPpGrduqSwDrrZgSiGa5mhJ4zJH762v/5c+oVSiJVZSjVhEH\nI3kiOEazmCqYksifgRWTRkaublEycpTFtlGnUEqwMyUQWTtgvyla5rhCEBATEiukiZGsFER60yi2\nG3yNRObXSDrfGPNzY8xeI/xctedTAVC4UwJ929+gl532It35m0ed7LsSRq0cijQAyQtBMLLEZ6tJ\nkV7fYuqL6k6urLXrlTw4+GxJy4wxXzXGnGeMmSQlZdKNMZ/RC4UgACBTbW0ltba2aNvW0ZaDInqR\nBh55IfBFHkjgEbOGFgCV11SdIekmSZcoKfogY8x2SWOVPEz4pJTaGA/WWwGZeOkpc3Tn3U+5bkZw\nYrpTKInEqkkEu8jbwIZNrMVqRKTrr1o2b828emAeGl6wY629T9Jhki5X8lDhTZK2SvqZklLtf0ul\nhaiK9VbZbFfKfr0VUwLTNeegfbTkEX8Gy0OYEhhdYoWGMYoAl/jsNSjSm0kx9E1NDaVYa7dI+q/y\nFwDkrmv6ZHWvWO+6GXAt0kAjawS28AEVBRsU6QhW6MIY+gCAKuad/iLd+atHXDdjJ0atHCCxEQiD\njQAAIABJREFUqhujVfARn0lI4fdRJFd5Yb1VMGIpwV6EKYGtrS0aM6ZVPT3+JzTICIlV3Qhg4TM+\nn3XiGugdkqtAsd4qm+3mIa/1VkVw6tw5uutefwpZMGoFnzFahVDwWa1ThAlWyH1VGBE6AFTwooOn\nadGDy103A65EGFBkhUAVIeJzW4cIr4ehJlgkV0CEijAlcN9pk7Ti+Q2577caRq1yFmEgkRUCVISM\nzy9CQ3KVh4KutwpxSmAsJdiL4KwzDtMffulPIQvkiMSqZgSmiAGf4xpFeG0M8aYgyVWAQllvhWJw\nMWpVajEaO7ZVW7Zsz33flTBqBR8RkCImrMOqUYQJVmiI0oHIuHqQb56OPeZA/eWhZa6bARcIHEZF\nEIqY8dkuntBuDpJcAWVMCQzH0Ufur8cXLHbdjGCE1jFVRWI1KgJPFAGf81FwrXSK5CprBV1vlZWQ\nS7DHyMUoWVtbSf39AxoY8CNZDWFKIIqBgBNFwud9FJElWCHdJCS5Ckwo662yKmYBnHTCTN3/Z0at\nahVShzSiyAKFtBFoooj43MNHYUTqAGpShPVWhx4yXX//y9OumyGJUSv4gQATRcbnfwSR3ZQK5WYh\nyRUg1luFon1cm7Zt73XdjGCE0hGNKrIAIU0ElgDnwYi4fuaO5KrgWG+FRrkYJTtl7mzdfe/C3PcL\nhwgMqiKgBF7A+VAMIdw0JLnKUgDFLLLAeis3ijAl8KCZe+vpx5913QxJ/k8JDKEDQuMIJIHdcV5U\nEdlNKt/7N5KrgIRSzALIwoTx47Rp8zbXzUCeIgsI0kIACVTH+QHXiNZReKy3qp+LUbLTTj1Yd9/2\nRO77DZHvd/XQOAJHYHScJxVEdrPK536O5KrAWG+FkHRN30PPdq9z3QxJ/k8JjEJkgUAaCBiB2nG+\nVMB1NRckV1lhvRVyFPt6qymTO7V23RbXzQiCz3fzakYAsBsCRaB+nDdx87W/I7kKBOut4AtXUwLv\nuvXx3PdbCaNWyBsBItA4zp9huHmVOSJ2FBrrrcKw157jtXoVHeRofL2LVxc6/l0QGALN4zyKl4/9\nHskVAK91dIxRz1ZGiwAASAU3sTJFclVQFLOIR+zrrU44dob+/MBS182QxJTAzNHh74K77UB6OJ+G\n4XqbGZIrpIZiFvFzkcjNOWiqljzyTO77DY2PUyPQOAJBIH2cV3Hyrf8juQoAxSzCxHqr5pnyAKvl\nTxk/7qLuRAAIZIfzawiuu5kgakdhZV3MAs07ZM40PfnUc66bIcnvKYG+3bWrGx38TgR+QPY4z+Lj\nUz9IcgUELM9pei6mBB5/7Aw9dPfC3PcLAEAhcHMrdSRXBUQxC4Ri3Lg2bdva67oZyBId+07cTQfy\nw/kWH19Gr0iukAqKWSBtkya1a8MGP7JrpgQiawR6QP4478q4yZUqkivPUcwiTBSzaJ5PJdiBLBHg\nAe5w/sXFhxuORO4opBiKWcS+3mrGgXvpmb/6UcwCGeFuKQD4getxakiuAHjHGHlTf50pgcgSd80B\n9zgPkSaSq4KhmAVCcNDMqVq4eJXrZiBL3CUloAM8wvmoaK7Lrm88klyhaRSz2BXrrZp35BH76fH7\nl7huhtdcdx5oDoEcAMSJ5AoIUOzrrSZP6tD6dVty3+9wPk8JDFokd0cBxIWbHorm+uzyBiTJlceo\nFJiNGIpZxM6EM3sVqBsBHOAvzk80i+gdgFf2mTpRz63c6LoZXgt6SmAkd0UbReAGAHEjuYKXKGZR\nXEcc1qW//WWZ62YAAAqq8DdBIrkJ5upGJMkVAK8cuP+eenrZatfNYL0VUlf4gA0ACoDkqkCyKMNO\npcBd5VEpMPZiFsZ484grpC2Su6EA4lf4myFcrxtGcgXAGx0dY9SzlRGjkQS93qrACh+oAQHivEUj\nSK48RaXAbFAp0G+HvWi6nvjbCtfNQBa4CwoAKAAieADeeNHB07TwwaddN4P1VkgVd7+BcBX6/OWm\nWENIruAdKgUW19gxrdq+vc91M7zFlMDwFDowA4ACIrkCUkIxi+aUWoz6B6hkESXufgIIWKFvknD9\nrhvJVUFQKRC+mzlzby1Zusp1M4DUFDogAyLD+YxakVyhMChm4bc5B+2jRY8847oZ3q63YkogAMAJ\nRq/qQnIFwAvT9pmk55/b4LoZSFtBO2XucgPx4bxGLUiuPEQZdhQVDw8GAAAhI4oHACBF3N0GEJ2C\nzkJoBMkVvEIZ9upirhS455TxWrPG/YWb9VYpozMGEBlunmA0JFdACvIowx6zg2burUVLVrpuBtA0\nAi8AKDaSqwKgDDt8N3PG3lr+xArXzQAAYFTcRMFISK4AONfRMUY9PX5OyUODmBIIAHHhul4TkisU\nAs+4QqiCXW9VQNzNBoqD8x3VkFwBcKqtraS+3n7XzfC2mAUAAAgHyZVneMYVXMu7UuAB+03RsuVr\nct0nkDbuYgMoBKYGjopIHghA3glPnmbN3FvLnnjWdTOQJjpfAAXATRVUQnIFb4T6jCvKsDena9/J\nWvHsetfN8BLrrcJAgAUAGERyBcAtIw0MkKACAMJTyJsrzE4YEckVACA9dLoAgAIjuYocDxAGRkel\nQDSqkHetAQBVkVwhejzjyl8Txo/T5s3bXDcDAICGcZMFQ5FcAdgp76qE+06bpBXPbch1nwAAoElM\nAa+K5AqAM/tOm6SVS3jGVSVUCvQfd6sBAMORXAFwZto+e+i5FZRhjwZ3MgEABUdy5ZGWrRwO7C7m\nBwi3j2vT1q0UkwAAhI2RbAwimgeawAOEgWIikAIAVEJyBS+Uely3AEVFGXYAABrAVPCKSK4AOGGM\nZC0jf5UEWcyCThZAwTGiDYnkCoAjUyaP19p1W1w3AwAAIDUkVwCcmLbPRD33PM+4Qni4Ow0AqIbk\nKmKtW0z62wxwthJqk3dVwsmTO7XhWZIrAAAQD5IrRK2NZNBbkya2a8MGDhAAIB6FG9lmve1uSK4A\nODFpYrs2bqRMJAAAiAfJFQAnxrS1qndHv+tmAAAApIbkCoAb6S8JrBvPuEpJgaaFFG7KDwCgLiRX\ngMfyLjIB94J8xhUAAJBEcgXAFZ4fDAAAIkNyBcAND6YFAgCQNqYPFxvJFdCg1h6GXgAAQMEVaN1t\nLUiuPNGylUOB4ii1GPX3s54MAADEhYgeQO4mTGjXpk3bXDcDqAtTfQAAoyG5gnMlniNbOJMmtWvD\nRqriAQCAuJBcAcjdxAnt2khyFQfm2gMAsJP3yZUxpssYc50xptsYs80Ys8QYc40xZo8mtvlmY8xA\n+esdI/zcKcaYXxlj1hhjeowxDxtjLjPGeP93A3w2dmyrejeQXAEA4sQ04uLyOkkwxsyS9ICkt0la\nIOlzkhZJukzSPcaYyQ1sc39JX5C0SSM8accYc4GkP0h6iaQfl3+nTdI1km6od78AXtDWWlJfLwUt\nAABAXLxOriR9WdJekt5vrX2ttfZfrbVnKUlwXiTpUw1s8xuSVkv6SrUfMMZMkPQ1SX2STrfWXmKt\n/bCkYyTdK+l1xpgLG9g3AEmtrS3q7e133QwAAIBUeZtclUetzpa01Fr7pWFvXylpi6S3GGPa69jm\nZZLOkPR2SSOVUXi9kqTuBmvtg4MvWmt3SPqYksefvrfW/QK+a9uS7yhSW1tJfX0kVwAAIC7eJleS\nXlb+fuvwN6y1myXdLalD0txaNmaMOVTSpyX9p7X2rhr2bSXdUuG9O5UkZqcYY9pq2TeAXbW2ltTH\nyBUATwy0ME0ZQDpaXTdgBIcoSXD+XuX9p5SMbB0s6XcjbcgYU5L0bUlLJX20xn2r0r6ttf3GmCWS\nDpM0S9KTNWwPwBBtrSX1MnIFwLHuoxZqydzH1TNlkzrWTtDMBYer65HZrpsFIGA+J1eTyt83VHl/\n8PVaqgZeKeloSadaa7fnvG8Aw7S2tjByBcCp7qMW6vGXL9j5/z1TNu38fxIsAI3yeVpgKowxJ0n6\niKT/sNbe77o9AAbXXDENB4A7S+Y+XtfrAFALn0euBkeHJlV5f/D19dU2UJ4OeL2SqXsfH/52lvte\nf/MLS8XGHXyQxh1y0Ai7A4qlVKKgBQB3BloG1DOl8nOIeqZs0oAZUIuN/v4zEJ01PU9r7dblTtvg\nc3L1pJIE6OAq788pf6+2JkuSxpd/zkrabsxu+ZSVdK0x5lolhS7+eci+jy/v+8Ghv1BO2GYqKdO+\nuNqO9zh//gjNAoqtrY1S7JW0bObBykAeWgZa1LF2QsUEq2PthKYTq5IdUL8hOQPytmfHAdqz44Cd\n/79o3T25t8Hn5GqwSMVuWYoxZrykU5VU7Vsw/P0htku6tsp7x0k6VtIflSRT9w557w5JF0s6V9L3\nh/3e6UqqFP7eWts78j8BQCWtpZL6+91OCyxt2uF0/wDcmrng8F3WXA19vVHz+xbqov7H1WU3qdtM\n0I2lw3VrK+u3gCLxNrmy1i42xtwq6WxjzPustV8c8vbVkjolfdlau1WSjDGtkg6S1GutXVzexjZJ\n7660fWPMlUqSq29Za68b9vYPJX1G0kXGmC9aa/9S/p2xkj6pZMTryyn9UwEAQM4Gi1akVS1wft9C\nXdH3QrLWZTft/H8SLKA4vE2uyi5V8jyr/zLGnCnpr0qea3WGpL8peaDvoK7y+0uVlEivRcV1V9ba\nTcaYSyT9QNLvjTE3Slor6ZVKpgr+wFr7g3r/MQCAMA1sqLw+B2HremS2uh6Zncoaq4v6KxfCuKj/\ncZIrxG/TZmnCeNet8ILXE4LLI1AnSPqmpBMl/bOS9U7XSDrZWrtu+K+Uv2rexQj7/pmSKYB/kPQa\nSe+TtEPS5ZLeWMc+AACBa5k0wXUTkKE01lh12coJeJfdpBZLdVREjsRqJ99HrmSt7Zb0zhp+bpmk\nUh3b/YSkT4zyM/dK+odatwmgNtbWcw8EAPzWb1rUbSZUTLC6zQQNUNwCKAzOdgC56+3tV9uYmu+F\nZKJ/whin+69kYHy76yYAaNCNpcqFMKq9DiBO3o9cAYjPjt4+jRnTqt4dlGMHEIfBdVVUCwSKjeQK\nQO527OjXmDGt2qLtrpsCAKm5tXW2bm2drRY7wFRAoKA48wGotzPfS8GOHcnIFQDEiMQKFMEpLs5+\nALkbnBYIAAAQE5IrONff4boFyBsjVwAAIEYkVwByl6y5clstEAAAIG0kVwByt2NHn0oTx7luBtLA\ngyMBANiJ5ApA7nb09mnMWKYFAgCAuJBcAcjdYCl2AACAmJBcAcjdjh19GktyhcBQWhkAMBqSK08M\ntA+4bgLq1NdhXDchWBs2bdXECay5AgAgeKy93QXJFYDcbdq0TRMntLtuBgAAqWOUu9hIrgDkbmDA\nyrQw8gcAAOJCcgV4rLeTUxQAACAURG6IWi8zzwCkiOk+AICRkFyhLn0kK0CmBsYHeJKxmBkAJHED\nBiRXUevrtK6bAHitf8IY100AACBc3FzbDckVACd27OjjQcIAACAqJFcAnFi3vkd7TO5w3QwAAIDU\nkFwBkJR/ZcL163s0eXJnrvsE0sCaCgCVcG2ARHIFT/QzgFE4a9dv0YRpE103AwAAIDUkVwCcYOQK\nAADEhuQKaEJfh3HdhGCtW9+jyXswZBkNKkYBQLFw3a+I5AqAE1QLrC7IZ10BQIGx3gqDSK48MtA+\n4LoJ8FDehSbyZAwjfwgTgRQAoJJ4ozagrJdBAIyABwkDAIC0kFwBcGb7tl6NHcvUwGgUbP49o1cA\npIJeCwp2va8HyVXk+jpt+ttkJAgp6V6xXtO7JrtuBgAAQCpIrgDslPf6ru5n12naQXvnus9QUNQC\nAIDwkFzBGzxIuHi6n12nrumMXCFchZwOBGCnQl4DmBI4IpIroEk866pxW7f1qr2dghIAACAOJFcA\nnLI2/XWB9aJiYIq4owmgIAo5aoVRkVwBAYj5WVdA6AiwAACDiNg8w4OEUTTbt/dq3Lg2183wEkUt\nAABeYXbCqEiuUAg8SNhf3c9Sjh0AEBZGrFENyRUawrOu4pX3FMRnutdp39lTc90nMlbAO5sEWgAA\nieSqELJ4kDCQluXda3XA/lNcNwMAgJoU9mZKAW+cNYLkCl4J9VlXlGNvXG9vv1pbS66bQcVANK2w\nARcAYCeSKwDOkZpWF2xRC+5wAogQN1EwGpIrIBAxl2N/ftVGTZ060XUzgKYReAGIEjfMahZvtBYw\nyrFng4qB/vr7U89r1tH7uW4GAABVcfMEtSC5QsOoGBivvEfJlixbpZkH7pXrPivxdd0VUwPDQgAG\nICoFvZY3iuQqA62tra6bsBsqBiJNpVK6l46+vgG1eVDUAhhUaqV7RPxKXHdrxk2TMLmIyf3LAiLQ\n29urJRvW6UsP3qcfPPmY6+YEp79DKvW4bkX9+jqMWnviTmLPm3+kLr5wrvbrmqxnutfpuzct0K9v\nfTSVbcf9l0Mo5r/xZF34/nPUNWuquhev1E1fuEW33nBv3dtpmTRBAxs2ZdBCoHnz33qaLvrQ+eqa\nPU3dC5/Tjf9+s269/k7XzQJSM/91J+jC98xT14z/m/u+S1dddVXuOy2AqyaPa9f8GbPVvXmjnliz\nsu4NmL7066e19Gawzb7UN5lstzeb7ZYyau+grNo9qNSbXwoyfF/nzT9SH778PE2cmExRmzixXS85\neY6eX7VRCxfV/xkfrmv6Htq0Zou2bNne9Laa0bKj3+n+qzE7Mv7wZmXsGGnHDtetqMn8N56sy695\niyZO7pQkTZzcqZPPPVqrutdq0WPP1L09uz2MfzeKZf5bT9MVX71EE6ckU70mThmvU84/XiuXr9Gi\nh5c5bp2fCj1qFeCUwPmvO0GXf/pCTdxj5/N9PpHn/pn3kLFLjz3JdRMQEZcVAy++cG5dr9fryaee\n00EUtagq2HVXAbnw/efU9fpoCh2QwVsXfej8ul4HQnPhe+Y53T/JVcZmTpqskuEpPr6gYmDthiZy\npVKL9uuaXPHn9uuarFJL85/xpctWawZFLeBIqbVFXbOmVnyva9ZUtaS8zhBwodRaUtfsaRXf65o9\njc95BYW+SRLgqFWptUVdM9zGEpxFGVuyYZ36bf1TuSjHDp/09w/ome51Fd97pnud+gean65IUYuI\nBdBB9/cNqHtx5emt3YtXaqC/sWtyoQMzeKe/r1/dC5+r+F73wuca/pzHivM3PP19A+peutppG0iu\nMvalB+9z3YRMUY69OL5704K6XgdCc9MXbqnrdSBEN/77zXW9joIK4KZYNTd99Q6n+6egRTauWrJh\nnf7/BX9oqlpg2kUtBsaEU9TCtoVZ1GKgzURb1GLhopV6ftVGzThgL02c2K5nutfpy1//fWrVAiVp\nypRO2R392rDBbblIX4ta2DFtFLbI0KLHntGq7rU64OB9NXFyp7oXr9TXr/5xQ9UChzLjxlLcAt5Y\n9PAyrVy+Rgce2qWJU8are+Fz+tpHbqBa4DCFH7UaG+4U+UVPPKtVK9bpgNn7DBa1yLWghbENTFnD\nyFpbW+1+//1vTW+nZWv6A4utW9JPrlq3pr5JSdmVY2/LqL2D8ijH3rYln6kb1fZTajGpTAUcbsrk\nTp126sH6xffvT33b9Spt8jMYbtmc8Qc4S5s2u25BzVpKLalOkaIsO3yU9uc8JoVOrgIetRrutiWf\nU19fBiW4R8C0wAz09/t51xsJilrUrlp1wiwSK0lau26L9pzSmcm2gXqkHXAWOlCDt0isKuN8jYeL\nmJzkymMUtUARWStRYLO6oEuyR3Q3tBEEbID/Cn+eRnSddtVfklyhaRS12FVfB5lBMxYtWaUDj+hy\n3QxKsgNAwRQ+sUIqSK4Kpq8znDV2/R2j/0xRuXyYcNYeevRpHXPU/q6b4TVGr8JF8AbAWxFdn132\nk/FGaABSkXcit2HDVk2aGHDyAAAIDjc+kBaSKxQSRS381j9g1VJiemW0Iro72giCOMAvnJOK6rrs\nenYHyZXnKGqBInpq4fOaddR+rpvh9bor150HmkMwBwBxIrlCKihqsas8ilrEvO7q4UeX6+gjWXeF\nuJFgAe5xHiqqUSsfxBudoSqKWqBeeSdym7ds1/jOsbnuEzmjMwfgGIlVfHyY1UFyBcBLfX0Dam11\nf4liaiCyRHAHwCludKXOfeQCOEJRC7/99e8rNOe4A103A1miU5dEggW4wHkXH19uOJJcBSCUohas\nu9oVDxNuzkOPLOd5VygMAj0gP5xvZdzgygTJVUGx7ioOea6Fynvd1Y4dfRo3ti3XfVbD1MAM0bkD\nyBGJVVlk116f+kKSKwDeWrJstfY/bF/XzQByQdAHZItzDHkguUKhse7Kb/fet1Ann3SQ62Z4z6c7\ndg2J7A5qMwj+gGxwbg0R2TXXtz6Q5CoQrLsKU2zPu8p7auCWnh3q7PCjJLvPUwMRF4JAIF2cU8gT\nyVWBse4KIVj+zFpNP2Qf181A1iK7k9osgkEgHZxLw0R2rfVt1EoiucpOe5/rFgBRuHvBQp0yd7br\nZkjye/TKxw6mbpF1+s0iKASawzk0TGTXWF/7PZIrFB7rrvy2afM2TRg/znUzACcIDgEgLCRXSB3r\nrnbFuqvmPbtivfadvkfu+w2Nr3fx6hLZnVUAbnBjYpjIrq0+93ckVwHJoqgF664QgrsWPKWTzzzM\ndTMk+T01EHEiSATqwzkzTGSJle9IrgB4b8OGrZo00d+7VD7x+W5ezQgEdkOwCNSGcyV+vvdzJFdZ\noqhFMGJYdxX71MDnV23U1H0m5r5fwBcEjcDIOEcq4GZV7kiukAnWXe0qj3VXsbvrHqYGFgoBQUUE\nj0BlnBsVRHgd9X3USiK5Cg7rrly3AK6sXbdFe07pdN2MIITQ+dQkwsAgDQSRwK44J+ATkqusMTUw\nGDFMDcyTi6mBCxev1IyjunLfbyWMXsElgkkgwblQRYQ3p0K5cUhyBeQktpLsLtx1z1N6yclzXDcj\nCKF0QqOKMEBIC0Elio5zoIoIr5sh9WlxR2KRymJqYBayWnfF1MDi2tHbL2OM2saUXDclCCF1RiOK\nMFBIC8EliorPfhVcL50juYKksNZdwR8uRsruWbBQJ807NPf9VsLUQPiAIBNF0jJpAp/5ggntRiHJ\nVR5YdxWMGNZdxT418MmnntPBc6a5bkYwQuuUquJu7IgIOFEEfMZHEeF1MsQ+LO4oDM5Rkn1XlGRP\nx+rVm7TX3n50soxe5SjCwCFtBJ+IFZ/tUXB99AbJVaBCWXeVFdZd+cPFSNlv//BXnX7ekbnvN1Qh\n3vlD4whCERs+06OINLEKte8iucJOrLtKMDXQfxs2bNWkSf5k2Ixe5SjSICJtBKOIBZ9lhCbuCMwn\nrLtCGVMD0/Ho48/o0BNnuG5GMEK9A1gRCVZNCEoRMtYR1ijS62HIfRbJFTJHSfb4uRgpu/9Pi3Xi\nCbNy3y8QEoJThIjPbY1IrLxEchWwLNZdMTUwwdRA//UPWPX29mtce5vrpkgKY2pg6B3WLiINKrJA\noIqQ8HmtEddAb8UdfQGeYmpgOv5w15N6yTlHuG4GXCG4qBlTrBACPqOI4SYgyVWeCrzuipLs8XMx\nUrbs6TWaeeBeue+3Gkav4DuCV/iI5L9Okd5YiqV/IrkKXNGnBma57oqpgWF49IluHXLCga6bAVci\nDTKyRCALn/BZrFOk17xYEispgOTKGNNljLnOGNNtjNlmjFlijLnGGLNHHdv4jDHmdmPM08aYHmPM\nWmPMw8aYTxpj9qnw8wcaYwZG+Ppeuv9KFFGMUwNdJHP3LlioU+fOzn2/1TB65UCkwUbWCGrhEkl+\nA7jWBaHVdQNGYoyZJeleSXtJ+qmkJyWdKOkySecYY0611q6rYVP/JOkvkm6VtFJSp6S5kv5V0ruN\nMadYaxdW+L2Hyvsd7rF6/y07tfdJW73+s2emr11q3eq6FYhN/4DV2nU92mvvCVq9apPr5gRjYHy7\nWjZHdEJOGC9t2uy6FcEZDG4HNnDuID8kVQ2IOLGK7Yaf71H+l5UkVu+31n5p8EVjzGclXS7pU5Iu\nrWE7E6y1O4a/aIz5pJIE618kvavC7z1krb26kYbnaaB9QC1b0x0x6Ou0at0SxshKf4dU6slm273t\nUlvg8WdvZ4vatqQ/fdQnt9z+mC545TG68et/dN0UScnoVWnTbpccZI0Eq2EtkyaQYCFzJFUNIrEK\nirfTAsujVmdLWjo0sSq7UtIWSW8xxox6VColVmU3lb93NdxQoAlMDUzHps3bNHZsm8aM8f1+kV9i\n7NTQOKZpIUt8thpEYhUcb5MrSS8rf791+BvW2s2S7pbUoWR6X6NeKclK+l2V96cbY95tjPlI+fuR\nTezrBQWuGghk5Y7f/1WnvTydUzQNIay9ilLEgUheCIKRJpL2JnA9C5LPt3kPUZL4/L3K+08pGdk6\nWNWTo10YYz6oZL3VJEkvlnSSpGslXVPlV84ufw3ZhPm9pLdZa5fXss+8ZDE1MAtZrbtiauDI8p4a\n6GIq4pJlq3Xu2Tzzql7Rrb2SmB6YAtZioVkkVE2KPLGKddRK8nvkalL5+4Yq7w++XnPVQElXSPq4\nkoIYp0haIOlGa23vsJ/rkXS1pOMlTS5/nS7pDklnSLq9lumIoQupJHvIYpwa6Mojjz2jQ0+c6boZ\nO4UyehVlJxd5YJIXRh3QCD4zTYr8+hVlnzOEz8lV6qy1+1prS5KmSXqNpKmSbjPGXDzs51ZZa6+y\n1j5krd1Y/rpL0jmS7pM0W5ULYNSOqYHIWRGeeXXv/Yt0ykkHuW4GfBF5gJIngmXUgmQc8Du5GhyZ\nmlTl/cHX19e74XLy9DNJ8yX1Sfpsjb/Xr2QaoZF0Wr37RaIvoxsWPFDYLy6SuYEBq9VrNmvq1Im5\n77saRq8cI8FKDYEzRsJnIyWRX7Oi7WuG8HnN1ZNKkpiDq7w/p/y92pqsUVlrnzbGPCHpaGPMPtba\n52v4tVXl750j/dD6n9y+87/HvWiWxh06q9Fm1qzoJdlD1tdh1NrDNMw03PLbx/Tq849iklsWAAAg\nAElEQVTTDV+/03VTgCixHgtDkVSliMSqaWs3LdXazUsz389IfE6uBotUzB/+hjFmvKRTlayNWtDk\nfqYrKZxR6+rnk8vfF4/0Q3u8+qxm2gRkogjPvNq8ebva2koaO7ZV27f7Mf02lOdeRVncQqLARUZI\nsoqNpCplJFapmDJhhqZMmLHz/xc/n/+NVm+nBVprFyspwz7DGPO+YW9frWTk6Hpr7VZJMsa0GmMO\nKT8faydjzBxjzG5zhEziUyqvu7LWbhny3rHGmN2Ga4wxZ0r6JyXJ2Hea+xeq0OuumBq4uxgLW7ha\n53XL7Y/p7Fcd52TfoYt2ykbkgYtLTBcsFo53BiK/PkXbr1Th88iVJF2q5HlW/1VObP6q5LlWZ0j6\nm6SPDfnZrvL7SyUNTbBeLunTxpi7JC2RtEbSPkqq/80q//x7h+33c5LmGGPukfRM+bWjJM1Tklh9\nzFrb7IhZJpgaiNEUYfSqe8V6vWLvCWprK6m3t991cySFM3olMYKFxjCSFTcSqoxEnlgVkdfJlbV2\nsTHmBCUjVedKOk/SCiXPpbraWju8TLstfw11u6SDJL1E0jFKSrdvVpKcXSvpi+WHEg91vaRXSzqh\nvN82Sc9LulHSf1tr707lHwgUgKtk7je3PaazLjhWv/7hn3PfdzUhJVjRIsHKHElWPEioMlaAxKpo\no1aS58mVJFlruyW9s4afWyapVOH1xyV9oM59fkPSN+r5nYa190lbvT8MmeCBwrujsEV6nn5mrc49\n+wi1jSmpd4cfo1chiXb0SiLByglJVrhIqnJAYhUtb9dcoXED7emPEvBA4bjkvRbK1dqrX97yqOZ7\ntvYqlNLsUuQdYwECG18MrtEhYPcfxyknBbj+RN1/jILkCk6FWNgiazEWtnCl+9l12nuvCRo7tpij\nwxhFAQIc3xC8+4fkN2cFuO4UObGSSK78kEHVwCxGr5CI5YHCxRm9ekTnvOZ4J/uuhtErjxQg0PER\nAb17/P0dKMD1Jvo+owbczkXNqBqIEK14boMmT+7UuPY2bdva67o5QYp6/ZXEGizHhgb4rM/KFsmU\nQyRWhcHIFZwLcWogz7wKyy9//bDOfc0Jrpuxi5BGr6QCdJoFCHxCwIhW+vibeoDrS6GQXPkikKmB\nFLaIS1GmBj63cqMmTRynjg6/EprQEqzoEQB5haSgcfztPDFhfGGuK9HfgKsDyRWAQvj5rx7Wea/z\na/QqNIXoPAsSCIVmaLJAwlAZfx/PFOhaUoi+oQ4kV/ACUwN3l9fUwKKMXq1avUnt7WPUOX6sk/1X\nE9roVSE60QIFRaEqerI1/N9fxL+B1wp0DSlEn1AnkiufMDUQyNTNv3pYr3jdi103AyEoUHAUg9gT\njdj/fVEp0LWDxKoyqgUiev0dUqnHdSsa09dh1NqTfTLb29miti35le/Pe3+D1qzdrJaS0ZQ9x2vt\nGn+qw/VPGKPSph2um1Gz6KsHDqKKYLCqJSAhVCMkeQoYiRVEcuWf9j5pazEPS1+71BpYvNbbLrUF\n1uai+/HPH9Ab33CSvvWlO1w3ZRckWJ4iwYrKaIlLlskXSVPkSKxQVswovmAG2gfUsjXdGaA88wrN\ncjV61dOzQytXbtQBh0/X048/m/v+Y0KChdiQAKEhJFYYgjVX8AqFLXYXa2ELl351yyM6b/6Rrpux\nm9CKW0gF6mgLVFIZQB24LmCY4kRTIcmgsAXgI1cJXf+A1QMPLdNxpx3sZP8jCTHBKhQCKQBSIW+4\nFOZmWpNIrgqCqoFhY/Qqfffev0gnnjBTLSWmtzarcB1uwQIqAMMU8BpQuOt8E4oTSSEYTA0sFpcJ\n3W9uf0xnvfJYZ/uvJsTRq8J1vAUMrgCokOd+4a7vTSK58hXPvMIwjF6lb+GileqaPlnt7f4lMyRY\nAShgkAUUWgHP+cJd11NQnCgKQWH0qlhcJnQ/ufkBnf+GE53tPzaF64gLuO4CKJyCnueFu56nhOTK\nZxS2gCNFGr1aXX6Y8F57+1eCOcTRK6mgHXIBAy+gEAp6bhfyOp6S4kRQkMTUwKzFUpbdBaejV794\nUOdf6OfoFQlWQAoahAHRKug5Xcjrd4pIruCtEKcGIkxbt+5Q97PrNOOoLtdNQegKGowB0SnouRxT\nYuXq5iTJle+YGohhYi5s4bpy4LlnHeFs/yNh9CowBV2fAUShwOdvTNdsl/0myVUBMTWQwhbY3cCA\n1V33PKWXnEuClaaYOuu6FTRAA4JV4HO20NfqlJFcwWtZTQ0MHaNX2Xjo0eU6eM40L0uzSyRYQSpw\nsAYEpcDnamzXaNd9JclVCHjmVXAYvQrXD3/yZ73q4rmumxGd2DrvuhR4mhHgvYKfn7Fdm10nVhLJ\nFQJAYYvKGL3Kxtp1W7Rx41YdcPh0Z20YiQ8dR6Ni68TrVuAADvBSwc/J2K7JvvSPJFehCKSwBaNX\nL2D0Klw3//ph/cN5R6ml5Gfpe186kEbE1pnXreDBHOCNgp+LsV2LfeoXSa4KLIupgVlh9KoyRq+y\nMTBgdfOvHtYrPH32leRXR1Kv2Dr1uhV8GhLgFOdfdNdg3/pDkquMjOnodd0EIHguE6wly1ZrTFur\n9pm9t7M2xCy2zr0hBHlAvjjforv2+pZYSSRXYaGwRSYoy14bl4mOKz/62Z/1mguOd92MqnzsVOoR\nWyffMAI+IFvcyJAU3zXX1z6weNESgkVZ9srymhroisukrq9vQLf/7gmd/erjnLVhNL52LrWKrbNv\nGMEfkA3OKw2Mb4/uWutz30dylaFMpgZS2CI4jF6F7a9PrtDUvSZozz397aB97mRqEVun3xQCQSAd\n3LCQFOf11fc+r3iREnZDYQsKW/jOdVL3/R/9Sa99yylO2xC7GAOAhhEUAs3h/JEU53XV98RKIrnK\nHIUtIDF6Fbpt23t1358W69RzDnfdlKpC6HBGE2Mg0BQCRKA+3JjYKcbraSj9XPGipBhQ2CITjF75\nzXVS95eHlung2dM0caK/HVYoHc9IYgwImkKwCNSG82QnrqNukVwhOBS2cM9VouM6wbrhB/fpDW9/\nqdM2jIYEK1IEjkBl3IDYRazXz5D6NpKrHFDYIhyhl2XPc/TKdaLjwuYt23XvfQv1sn842nVTRhRS\nJ1RNrAFCUwgigRdwPuwm1utmaH1a8aIjVEVhC4TAdVL30KPLNW3aJO01c0+n7SiCWAOFphFUouj4\n/O8m1utlaImVRHKVGwpbhIPRq9q5TnRcufGH9+vC175YLS3+rnMLsUOqJNaAIRUkWSgaPvMVxXqd\nDLUfK2ZkFIuCF7Zg9Kq4XCd1vb39+sWvH9E/vOFEp+0YTagd03CxBg6pIeBE7PiMVxTjw4EHhdx/\nkVwBOWP0Kuz9Dlq8dJUk6cAjpjttx2hC7qCGijmISA0BKGLDZ7qqmK+HofdbJFc5CqWwRUijV1kJ\nvSw78vHTXzyoV5x7lNrGlFw3ZUShd1RDxRxQpIaAFKHjMzyimK+DMfRXJFcIWqhTAxm9Cnu/gwYG\nrL7/oz/p9W97idN21CKGDmtQzIFFqghQERo+s6OK9frXP2FMNP0UyVXOilzYgtErxOj5lRu1YsV6\nHXnKQa6bMqpYOi4p3gAjEwSsCAGf0VHFet2LqW+SSK7iEMjUwKwwelUdo1f5uO13T2juiw9S5/ix\nrptSKLEGGpkhyYKP+FzWJNbrXWyJlURyBYyI0asw+JBgfff79+qit7/UdTNGFVtHFmvAkSmCWfiA\nz2FNYi7mE1t/NMh9RFJAFLZIH6NX1RVh9MoHGzdt0wMPLdNLzj3CdVNGFVuHFmvgkTmCW7jA565m\nMV/bYuuHhipuJATUiNGrMPiQ2P3pgaWaceBemnzgFNdNGVVsHVvMd3czR7CLrA1+xvic1Szm61ls\n/c9w7qORgqKwRQbbDfQ6xOhVXL73/QV604UneV+eXYqzg4s5IMkcATDSxuepITFfx2Lsd4YrdhQU\nm0CmBoaI0av6FLm4xY7efn3vpvv05kvOcN2UmsTY0cUcmOSGoBjN4PPTkNhH4GPsbypxH4mgkEIr\ny5612EavXPIhwVq1epPu+/Ninfu6E1w3pSYxdnixBym5IUhGPfi8NCz261WM/Uw17qOQAityYYus\nhDo1MEY+JDkuPfLYMzKSDjtppuum1CTWji/2gCU3TBlENXw2mhb7dSrW/qWaYkc/cCq00auspwYy\nepUeXxK7m3/9sE46YVYQBS6keDvA2AOX3BFMg89AamK/PsXar4zEjwikwBi9Sh+jV/5wmeT4kmB9\n67t3B1PgQoq3I2SaYEYIsouFY52aIlyTYu1PRuNH9AEEgtGr+vmS5LgyWODiLe8+w3VTahZzhxh7\nMOMUiVacOK6pK8J1KOZ+ZDTFjno8EUpZdh4qHA+mB+Zr1epNWvCnxTovkAIXUtwdYxECG+cIyMPG\n8ctMEa4/MfcftfAj8kD6MpgaiEQMo1d5Y3pgUuBCCqfAhRR3B1mEAMcbBOph4DhlqgjTAKW4+41a\n+RF1oNAYvXKjKKNXPrn51w9r7ovDKXAhxd1RFiXY8crQAJ4g3j2ORS6Kcp2Jub+oB8mVJyhsERZG\nr+rH6FXim99JClyMGdPquik1i73DLErg4yWSrXzx985dUa4vsfcT9fAn4kChMXrlRpGKW/iSYCUF\nLhboze85w3VT6hJ7x8kolicI/NNFMuVMUa4p/RPGRN8/1MuPaAOSGL0KDaNX4fElwVq1erPuvW+R\nXv76F7tuSl2K0IEWIRgKxvDEgORgdPy9vFCU60gR+oRG+BFpAGL0ypUijV755NHHn9GO3j4dd/rB\nrptSlyJ0pkW54xykSglXEZMI/g5eKtK1owh9QaOIcjzD6FVYGL0Kj0/J3W9ue0yHzJmmAw6f7rop\ndSlKp1qUICkKsSYbsf67IlSk60VR+oBGhbOiGoXQ12nVuoUqdnnr6zBq7clm5LCS3s4WtW1xl6C7\n3v9Q37nxXl16yTzdtGKD1q3d4ro5NeufMEalTTtcNyNzgwFTy+atjluChtSaiGzanG07KiFJikKR\nkiqJxKoWJFdo2ED7gFq2+jMKMJK+dqk1o9iov0Mq9WSzbSkZvWrLIa4jwXLDWunab92p/++dZ+ja\nz9+m7dvDeUZdURIsKQmgSLAiRqKDBpBYoZIwIuOCCWVqIIB0bN/ep2/fcK/e9t55MoEN3Bapsy3S\negoAIyvataBI1/pmkVzBOyEWtohl7VXRilu43v9Qa9dt0S23P6Y3vut0102pW9E63aIFVQBeULSb\nLJRar58/kQV2EcroFYUt0CzXCY7r/Q+1aMkqPfLocl3wprmum1K3onXARQuwABTvxkqRrulp8ieq\nAIZg9Gp3sY5eYVcPPbpcz6/coDMvOMZ1UxpStM6YJAuIXxHP86Jdy9NEcuUxRq9QFK5Hj1zvf7i7\n7l0oI6OTzjzUdVMaUsROuWiBF1AERUyqpGJew9PkV0QBDMHo1e5iHr1yneC43v9wv7n9Me07bZIO\nnzvLdVMaUsTOuaiBGBCjop7LRbx2p82vaAL5YPQqaDEnWK75lmD98Kd/0TFH7q8ZR3a5bkpDitpJ\nk2QB4Srq+RvjutkpM6Y42a9fkQR2k8nUwIAwelUsviU3Prj+hnt05hmHaursvV03pSGxddb1KGKA\nBoSsqOdsjNfp6Yfso9e/+sVO9k0kg9QwepWfmEevXCdYrvc/XPKQ4T/qtRccr0n7T3bdnIbE2HHX\nqqh3wYGQFPk8jfH6PPOo/XTu2UfoK9f+zsn+/YoiUFEohS2ywugV8uZbgtXfP6D/+cYf9OY3zNUe\ne4T54Ypxykk9ihy8AT4r8nkZ4zW5r7NNe+05Xv/zjTvVP5BN/DgavyIIBI/Rq/wwehV/G4bavr1P\n//ONP+jiS07XxInhBgMxdub1KHIgB/ik6Dc8YrwW93W2SZLuvX+R03b4FT2gKkavGL1yiQTLD1u3\n9epr37xTb3nPGeocP9Z1cxoWY6dej6IHdYBLRT//Yp1FMJhY+cCvyAFAXfIavYI/enp26OvX/1H/\n673z1N4ebgcZY+der6IHeUCeON/ive76lFhJJFdBCWX0KqupgYxeucXolT82b96ub37nbr3jH8/U\n2LGtrpvTsFjvoNaLoA/IDudXItZrrW+JlURylZmO9h2umwBPxPJgYVd8SG58aMNwGzZu1fU33KN3\nvv8stY0puW5OU2Lt9OtFEAiki/MpEes11sfESiK5gsTolbIdvcpDzMUtfOFjgrVufY++d9N9euf7\nzlJrq3/tq0esnX8jSLKA5nAOJUKeHXDZP5+rN775FP3DK4+r+L6viZVEcpWpLEaviv5Q4VAxPbA5\nviQ2vrRjqNVrNusHP/mz3vn+s1Uq+de+eoQcCGSBABGoD+fMC0K9lpZKLfrwR1+pjs6xevJvK/Tq\n152g11900s41xn2dbV4nVhLJFTLE6FW+mB6YD1/aMdTzKzfqJzc/oHe+P/wRLCncoCArBIzAyDhH\ndhXyNbRUatHEie26/ht/1AN/XqIrP/pDHXf8TJ0x7zDvk6pB4ffCngtm9CqgsuyhYvSqeT4mNr54\ndsV6/fjnD+hdHzg7+DVYUtjBQVYIIIFdcU7sKobR/97ePi1a+LwOOXRfjR3bqmeWr9UN37lH511w\nrA6ZM81182pCpIJMhfZQYUavasf6K/889/wGff9H9+vdH5ivcePCuMM3khgChSwMBpQElSgqPv+7\ni+Vaaa208vmNOuaYAzV1n0kyRnpg4Qr94a6/691vP81182riZ4SAURV99CqrqYFZi2n0yhVfEhtf\n2jHcqtWbd1YR7OiIo7ONJWjIAkEmioTPe2WxXSN/8fMH1Nc3oFecf6z2P2y6JOm2Ox7XM8+uc9yy\n2vgZHUSm6GXZGb3KVxFGr3xJbHxpx3Dr1vfouuvv0tv/8UxNnBT4B7ostuAhbQSdiBmf7+pCvjZO\n2XO8JKml5YVYwpT/83++8ltpbEmvfdXxeu+7XqZPXfka9fb2u2hm3Yy1YY4A+MwYY4/+xcd2ea1n\nazYf/h09GUz92Zr+Q0lbtmYThLZuySa4b92ayWZ3KvVku31Jasv43zBUa4+b60jbFj8Sd1/aMVxH\nxxhd8rbTdMMP79PapWtdNyc1pU3FvmFVi5bNOV4AgIyQUFUXclI1aVKHPvO5N6ltTElXfOA7Wr9u\ni1pajAYGkliipWS0Y1yrOjvGaJ+pk3TiCTO1Zu1m3XbHE3Xv6w+/+bCstbneCSa5ykCl5ErKJsEK\nJbmSskmwskqupGwTLJKrdPiU1PjUlqHGtJV0ydtP182/fkjP/u15181JDQlW7Ui0EBqSqpGFnFi1\ntBi96z0v05gxrdq4cZsOPWy6PvKhG3e+NzBgd1YF7OwYoy09zV3rXSRXfs5pgVusvcpcHmuvmB6Y\nL5/aMtSO3n59+drf6ex5h2vOcQe4bk5qQg4u8saUKoSAQi21Cf3aNzBg9eMf/kk33bBA3/v2XVq/\nvkcf/tfzJUk72lt3JlbHHLm/znrZYWprC6/6rZ/RQKSCKcueEdZexY0Ey18DA1Zf/9YfdcxR++vY\nl85x3ZzUUE2wPgSv8BGfydrEdL1bvWqTVq7cqL6+AX3li7drj8mdesf7z9r5fkuL0arVm3TL7Y8H\ns85qKO+jEmNMlzHmOmNMtzFmmzFmiTHmGmPMHnVs4zPGmNuNMU8bY3qMMWuNMQ8bYz5pjNlnhN87\nxRjzK2PMmvLvPWyMucwY4/3frWmMXiXbzvB6H9volUu+JFi+tKOaG35wv6btM0kvPe9I101JVSwB\nR54IaOEan8HaxXyN27ChR1+87vc67EXT9doLjtcVHzhHRx2xv7pXrNe27eEMIAzldSRgjJkl6QFJ\nb5O0QNLnJC2SdJmke4wxk2vc1D9J6pB0q6T/lPRtSdsk/aukR40xsyvs+wJJf5D0Ekk/lvQFSW2S\nrpF0Q6P/Jkavwhq9ylpsCVaRn301yPcE6+ZfPyxJevnrX+y4JemK6a5unhjNQp74vNWnCNe1vs42\nLXt6jX7564f1j++ep4GBAT30yNOum9UUrwtaGGNukXSWpPdba7805PXPSrpc0lestZfWsJ0x1trd\nshpjzCeVJFjXWWvfNeT1CUqSuAmSTrHWPji4HUm/kzRX0huttTdV2V/FghaDgilsIVE5cHDbFLeo\nCwUu/GpLJS8+bobmHLSPbvrmXa6bkjqKXTSPIhhIC4lUY2JPqiTtXF/VNX2yPvHRC/SrWx7Rj3/+\nQKr7oKDFEOVRq7MlLR2aWJVdKWmLpLcYY0Y9ayslVmWDyVHXsNdfL2kvSTcMJlZDtvMxSUbSe0f9\nR+SI0atwxTZ65ZJPo0Y+taWSPz2wVA8+8rTedum8XZ4xEoMi3O3NGiMMaBafn8YU5fo1mFhJ0qrV\nm/Rvn/tV6omVKz73/i8rf791+BvW2s2S7lYy1W9uE/t4pSSrZDRq+L6tpFsq/M6dknoknWKMaWi4\nqOgPFc5KqGuvYuRyeqBPSY1Pbankr0+u0G13PK5LLpuvtjHhVWQaTREClDyQaKFWfFaaU4RrVl9n\n2y6JlSTt2NGnhYtWOmpR+nzu+Q9RkuD8vcr7T5W/H1zrBo0xHzTGXGmM+Zwx5o+SPi7pWiXrqIbv\nW5X2ba3tl7REUqukWZX209qazXOiRpPJ6FVAhS1c2LJsYSrbCW30qrVl9EtHjOuvNqxaVPfv+J5g\nPb18rW768Z/07svma+LE+AKiRu8Cb9i6PIPWhC/W4HlNT9hrPBpVam3++hTiZ2LtpqWum7CboiRW\neXMRk7vJAmozqfx9Q5X3B1+vuWqgpCskTR3y/3dLutFaOzwraWrfvb29enrLGn194Z362TOVhzg7\n2ndksvYqFAPtA5msverrtJmtvepr333tVc+yheo8cLd6KN7qbW9u/dUFJx+ut5/7Yh0wdbKeXrlO\n3/jNn/Szex9Pr4Ep6e1syWTN04ZVizRp74O8aU9aVq3epGu/eafe+e7T9eOfP6Dn/h7PHcRBg4HL\naOux5l9wrC56x0vVdcCe6n56jW687o+69WcPjvg7RTU0mA59jdbarcu1Z0c8z4EbzfzXnaAL3zNP\nXTP2UvfS1brpq3fo1h/+uebfDymRqmTt5qWaMmGG62ZIKkZSJeWfWJ03/0hdfOFc7df1v3Pdr+T3\nyFXqrLX7WmtLkqZJeo2SROs2Y8zFae/rgM499YmjX60L9jsu7U2PiNGrcOUxetWMC04+XFe+db4O\nmJoU6Txg6mRd+db5uuDkw6v+DtMDX+Bbe4bb0rND//3VOzR/3uE64uT6E8hQjBTIzL/gWF1x1avU\ndcCekqSuA/bUFVe9SvMvODav5gVr6OhF6IF37Oa/7gRd/ukL1TVjL0lS14y9dPmnL9T8150w4u9x\nfNNXhMTKGGnPmXvmus/z5h+pD19+nvbrqrWoeLp87u0HR4cmVXl/8PX19W7YWrvKWvszSfMl9Un6\nbFb7fufs06q+V/S1V1kVtgh57ZXP0wPffm7l0t3VXh9EgvUC39ozXP+A1XXfvksH7DdFBx8f7138\nagHNRe94aV2vozqCcH9d+J55Nb9OQpWdIiRWkvSqi09WZ8fYXPd58YXNlGNonrel2I0x75T0NUlf\ntdbuVpnPGPMbJdUEz7LWDi9IUc9+HpB0tKTp1trny699W9KbJL3JWvv9YT9fUpJ8tUkaX2FKoZSs\nFduptbVV/f3hPWEaGNTa2qre3uqjonzGETo+4ygCPueIXZXPeK53eX1eczWYMM0f/oYxZrykU5VU\n7VvQ5H6mK0mGNg957Q5JF0s6V9L3h/386UqqFP6+SmIlDTuIfX1Mq0Pc+IwjdnzGUQR8zoHmeTtH\nxVq7WEkZ9hnGmPcNe/tqSZ2SrrfWbpUkY0yrMeaQ8vOxdjLGzDHGTBy+fZP4lMrrrqy1W4a8/UNJ\nqyVdZIw5fsjvjJX0SSXJ2Jeb/kcCAAAAiIa30wKlnQ8SvltJAvRzSX9V8lyrMyT9TdKp1tp15Z89\nUEmJ9KXW2llDtnGZpE9Luqv8/hpJ+ygZgZolaamkedbapcP2fYGkH0jaLulGSWuVPBfrYEk/sNZe\nlME/GQAAAECgvE6uJMkY06VkpOpcSXtKWiHpx5KuttZuGPJzB0parCS5OmjI64dLeo+kl0jaT0n5\n9M1KkrOfS/pi+aHElfZ9sqSPSjpZ0jhJCyV9XdIXrO9/OAAAAAC58nZa4CBrbbe19p3W2i5r7Thr\n7Uxr7RVDE6vyzy2z1paGJlbl1x+31n7AWnuctXaqtXaMtXaKtfYUa+2/DSZWxpguY8x1xphuY8w2\nY8wSSRdKerO1dk9rbae19mhr7eerJVbGmM8YY243xjxtjOkxxqw1xjxsjPmkMWafav9GY8wpxphf\nGWPWlH/vYWPMZcYY749PiCoda2PMNcaYmp+ZVu+xNsYcaIwZGOHre+n+KzEojeNdYZtvHnLs3jHC\nz3Fu58zF8eb8diOla/nSEY7bsyP8Hud2zlwcb85tN9K8jhtjzjTG/MQYs6K8rW5jzG+MMedW+fmm\nz23vR67yYJLph/dK2kvSTyU9KelESfM0bPrhKNvZLukvkp6QtFLJurC5kl6sZA3XKdbahcN+5wIl\na7y2KimesVbS+ZJepGT64RtS+CeizNWxNi9MW32ovN/hHrPW/rjxfxkqSet4D9vm/pIeUXJzaryk\nS6y111X4Oc7tnLk63pzf+UvxWr5EyeNVrtHuFcU2W2s/V+F3OLdz5up4c27nL83ruDHm/0r6oKTl\nkn6tJD7bW9Lxkm631v7LsJ9P59y21hb+S9ItkvolXTrs9c9KGpD0pRq3M6bK658sb+faYa9PUBKY\nb5V07NDtKFlr1i/pQtd/n5i+HB7rA8uvX+f6b1Ckr7SO97DfvV3SU5I+U972Oyr8DOd2sY4353eg\nx1pJ4Ly4jv1ybhfreHNuh3usLyn//NcltVZ4vzTs/1M7t53/EV1/KSlqMSBpUdTGQ4cAAAmsSURB\nVIX3xkvaVP5qb2IfR5X38ethr7+j2kkr6WXl937n+m8Uy5fjY80FOoLjLekyJQ8ef4mkK0cItjm3\ni3W8Ob8DPdYNBNuc28U63pzbAR5rJQnR8+XjvVtiVeV3Uju3mRuc/MGkpOz7LmyyHutuJc+1auZx\nz69UUr59+MOOX1Z+/ZYKv3Onkud4nWKMaWti33iBy2M9aLox5t3GmI+Uvx/ZxL4wslSPtzHmUCWV\nR//TWntXDfvm3M6Xy+M9iPM7H2lfy8caYy4uH7cPGGPOGGF9Bed2/lwe70Gc2/lI61ifrWT6348k\nWWPMK4wx/7t8vKv9bmrnts8PEc7LIUr+mH+v8v5TSg7SwaoeMO/CGPNBJWtwJilZg3OSpGuVzPEd\nvm9V2re1tr88N/gwJZn8k7XsGyNyeawHnV3+GrIJ83tJb7PWLq9ln6hZasfbGFOS9G0lj274aI37\nVqV9c25nxuXxHsT5nY+0r+XTJF0/5P+NpCXGmLdba++ssG9V2jfndmZcHu9BnNv5SOtYv7i8nR2S\nHpR0RPn/peTY3Snpddba1cP2rUr7rvfcZuQqCYolaUOV9wdfr6dCyRWSPq5kSskpkhZIutFa25vD\nvlGdy2Pdo+SRAsdLmlz+Ol3SHUqe23a7Maa9jv1idGke7yslHS3pf1lrt+e8b9TG5fHm/M5Xmsf6\nOklnKgm4OyUdKekrkmZI+lWFEQrO7fy5PN6c2/lK61hPVZI0f0jJdL5TlaypOkrJyNRpkm7KaN8k\nV1mw1u5rrS0pOXlfo+Qg32aMudhty5C2Wo+1tXaVtfYqa+1D1tqN5a+7JJ0j6T5JsyW9K+/2Y3TG\nmJMkfUTSf1hr73fdHmSrkePN+R0ua+3/sdb+vnwMt1lrn7DWXirpc0qmH13ltoVIU73Hm3M7WIP5\nTa+k862191pre6y1jyuJ1Z6RdHr5ep/ZzotsMBOdVOX9wdfX17vh8kn5M0nzlSyK/mxe+0ZFLo91\ntd/rVzKN0Ci5k4L0NH28y9PDrlcyBeDjw9/Oct+om8vjXRHnd2byOL++Uv4+/LhxbufP5fGuiHM7\nM2kd68H3Hxw+bdNau1UvrKs6MYN9k1wp6USNkvmblcwpf682/3NU1tqnlTwPaW+z6wNmB+ds7rbv\ncic/U0mgvrjRfWMXLo/1SFaVv3c2ul9UlMbxHl/+uUMlbR/68Ei9EHxfW35t6PNROLfz5/J4j4Tz\nO32ZX8tV/bhxbufP5fFO+3cwsrSO9eB5Wi0RGnxO1tApnamd2xS0eGFB3PzhbxhjxiuZp9mjZC1N\nM6YrWUy3echrd0i6WNK5Sh5WNtTpSoaof19h/Q4a4/JYj+Tk8nc643Slcby3K7k7Wclxko6V9Ecl\nF+V7h7zHuZ0/l8d7JJzf6cvjWl7tuHFu58/l8U77dzCytI71b5XEYYdVef+I8vclQ15L79xutBZ9\nTF+SfqPk+SXvG/b655QshPvvIa+1KqkoMmvYz86RNLHCto2kT6nys4+GPrDs+CGvj5V0T7lNr3f9\n94npy+GxPlaSqfA7Z5aPf7+kua7/PrF9pXG8R9j2SM894twu1vHm/A7wWEt6kaSOCtueoaQqWb+k\nDw97j3O7WMebczvAY11+76fl7fzTsNfnl19fLWnCkNdTO7dN+RcLzRgzS0nt/KmSfi7pr0pq6J8h\n6W+STrXWriv/7IFKMt2l1tpZQ7ZxmZJnotxVfn+NpH2UZLuzlJT0nWetXTps3xdI+oGSO6Y3Slqr\n5FlJB0v6gbX2ogz+yYXl6lgbY36nJCm7R8lCSimpWjNPyd2Vj1lrP53BP7nQ0jjeI2z7SiUB97us\ntddVeJ9zO2eujjfnd/5SupZfqaTi652Slil5OOlBkl6hJKD6paTXWGv7hu2bcztnro4353b+0rqO\nG2O6ytvZX8mo1INKYrQLlCRpb7DW/nTY76RzbrvOUH35ktQl6euSuiVtKx+sz0qaNOznDlSSvS4a\n9vrhkj4v6QElme+O8kG5R9K/SBo/wr5PlvQLJUH6FkkPS/qAKtwt4SvMYy3p7UouEoslbVRyZ2Sp\npO8puVA4/7vE+tXs8R5hu1VHMob8DOd2AY4353eYx1pJIYLvKlknu1ZJQPW8ksXuF4+yb87tAhxv\nzu0wj/WQ9/eU9F/l39+mJGb7oaQTRth30+c2I1cAAAAAkAKqBQIAAABACkiuAAAAACAFJFcAAAAA\nkAKSKwAAAABIAckVAAAAAKSA5AoAAAAAUkByBQAAAAApILkCAAAAgBSQXAEAAABACkiuAAAAACAF\nJFcAAAAAkAKSKwAAAABIAckVAAAAAKSA5AoAAAAAUkByBQAAAAApaHXdAAAA8maM2UPS5ZLOkdQj\naZKk+yR9zFq71mXbAADhYuQKAFAoxpi5kp6QNE3SPGvtPElzJc2WdLcxpnPIz37QTSsBACEiuQIA\nFIYx5iRJv5P0Z2vte6y1PZJkre2V9DFJh0j6l/LPtkk6wVVbAQDhMdZa120AACBz5RGpJyTtJelA\na+3qYe8bSVslLbHWHmqMuViStdZ+r/z+eyUdI+lZSYdL+oy19i95/hsAAH5jzRUAoCjeJWl/SV8b\nnlhJSRZljFktaaYxpiTpQkmvliRjzNvKv39C+edOkHSrMeaQStsCABQT0wIBAEXxJklW0k9H+Jle\nSW2SrpD0/9q7WxepwigOwL+DisEPUItlQRRZk6DJYDGo3f/AKDaDRQ0ms2AQFBSDyWA3bRFEm8hm\n2aLN9SMIrscws7CMsmu4+zHM85ThnvvO5bThN/fc9z7p7t/j+u0kT3s87tHd75IsJbm2ee0CMG2E\nKwBmxfz48/V/rJ3r7pdJUlXHk5xI8mFizfskl4ZrD4BpJ1wBMCtWkvzs7uV11qzeqbq5pnYyozte\nXyfWfktybLDuAJh6whUAs2Ihyd6q2v+vk1V1JcmR1cNxbVeSw+Paj4mvfE9yaBP6BGBKCVcAzIpb\nGQWiO2uLVXWuqp5nNPp3d1yer6rTSR4k+TWurUxcb09sDAXAGn4UAJgJ3b04fs/Vvap6m2Q5ozHA\nN0ludPenqtqd0Xbrz5IsJrme0bbryd9/SO5L8mVLmgdgKnjPFQCso6rmknxMcqG7F9bUXyQ52t3n\nt605AHYUY4EAsI7uXsroLtapiVNnk7za+o4A2KmEKwDY2KMkV1cPqupykoNJHm5bRwDsOJ65AoCN\n3U9yoKoeZzQieCbJxe7+vL1tAbCTeOYKAABgAMYCAQAABiBcAQAADEC4AgAAGIBwBQAAMADhCgAA\nYADCFQAAwACEKwAAgAEIVwAAAAP4A8g+0i3EksB/AAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "thetas = np.array([v for v in product(As, Bs)])\n", + "\n", + "gp = GaussianProcessRegressor(alpha=0., normalize_y=True, \n", + " kernel=C(1.0) * Matern(1.0, length_scale_bounds=\"fixed\"))\n", + "gp.fit(thetas, exact_contours)\n", + "\n", + "xi = np.linspace(bounds[0][0], bounds[0][1], 50)\n", + "yi = np.linspace(bounds[1][0], bounds[1][1], 50)\n", + " \n", + "xx, yy = np.meshgrid(xi, yi)\n", + "zz, std = gp.predict(np.c_[xx.ravel(), yy.ravel()], return_std=True)\n", + "zi = zz.reshape(xx.shape)\n", + "\n", + "mle = np.unravel_index(zi.argmin(),zi.shape)\n", + "zi -= zi[mle]\n", + "zi *= 2.\n", + "\n", + "cs = plt.contour(xi, yi, zi, [1.,4.,9.,16.,25.], linewidths=0.5, colors='w')\n", + "plt.clabel(cs, cs.levels, inline=1, fontsize=10, fmt = fmt)\n", + "\n", + "cs = plt.contourf(xi, yi, zi, 30,\n", + " vmax=abs(zi).max(), vmin=0.0)\n", + "\n", + "#plt.colorbar()\n", + "plt.scatter(thetas[:,0],thetas[:,1], marker='o', c='w', s=50, lw=0, zorder=10)\n", + "plt.scatter([xi[mle[1]]], [yi[mle[0]]], marker='o', c='r', s=50, lw=0, zorder=10)\n", + "plt.scatter([alpha_value_0],[alpha_value_1], marker='o', c='g', s=50, lw=0, zorder=10)\n", + "\n", + "plt.xlim(bounds[0][0], bounds[0][1])\n", + "plt.ylim(bounds[1][0], bounds[1][1])\n", + "plt.tick_params(axis='both', which='major', labelsize=20)\n", + "plt.xlabel(r\"$\\alpha_0$\", fontsize=25)\n", + "plt.ylabel(r\"$\\alpha_1$\", fontsize=25)\n", + "plt.tight_layout()\n", + "#plt.savefig('plots/alpha_gp_exact.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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MKaLcmT7d0uH8LBWnWcptGQSknGYxriTFsOqMYWUPtwHaJ1NY6RRVjCki75kaW5xmhYfT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\niYmTWXCmQDf1qe+F1pAHYE5mUT1bvsSJiAGLKEqmVq/MSwCOM3UyC84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OAAAg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\no3J7c/9OVpTb+hYAZ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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "thetas = np.array([v for v in product(As, Bs)])\n", + "\n", + "gp = GaussianProcessRegressor(alpha=0., normalize_y=True, \n", + " kernel=C(1.0) * Matern(1.0, length_scale_bounds=\"fixed\"))\n", + "gp.fit(thetas, llr)\n", + "\n", + "xi = np.linspace(bounds[0][0], bounds[0][1], 50)\n", + "yi = np.linspace(bounds[1][0], bounds[1][1], 50)\n", + " \n", + "xx, yy = np.meshgrid(xi, yi)\n", + "zz, std = gp.predict(np.c_[xx.ravel(), yy.ravel()], return_std=True)\n", + "zi = zz.reshape(xx.shape)\n", + "\n", + "mle = np.unravel_index(zi.argmin(),zi.shape)\n", + "zi -= zi[mle]\n", + "zi *= 2.\n", + "\n", + "cs = plt.contour(xi, yi, zi, [1.,4.,9.,16.,25.], linewidths=0.5, colors='w')\n", + "plt.clabel(cs, cs.levels, inline=1, fontsize=10, fmt = fmt)\n", + "\n", + "cs = plt.contourf(xi, yi, zi, 30,\n", + " vmax=abs(zi).max(), vmin=0.0)\n", + "\n", + "#plt.colorbar()\n", + "plt.scatter(thetas[:,0],thetas[:,1], marker='o', c='w', s=50, lw=0, zorder=10)\n", + "plt.scatter([xi[mle[1]]], [yi[mle[0]]], marker='o', c='r', s=50, lw=0, zorder=10)\n", + "plt.scatter([alpha_value_0],[alpha_value_1], marker='o', c='g', s=50, lw=0, zorder=10)\n", + "\n", + "plt.xlim(bounds[0][0], bounds[0][1])\n", + "plt.ylim(bounds[1][0], bounds[1][1])\n", + "plt.tick_params(axis='both', which='major', labelsize=20)\n", + "plt.xlabel(r\"$\\alpha_0$\", fontsize=25)\n", + "plt.ylabel(r\"$\\alpha_1$\", fontsize=25)\n", + "plt.tight_layout()\n", + "#plt.savefig('plots/alpha_gp_approx.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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Mw/ClZasT25JZAGNG85eJaBMR3W7iuYLgOkqpz2bKVkk8HpZsFUEQBFuQOEIQBEEQBFZE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\nKNlHRbdnP4L9iFD7qZtzZCKOp5D7iMdS59uwHxHBP6umAkkpc0KI9oVmU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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(20,10))\n", + "ax = axes.flat[0]\n", + "\n", + "gp = GaussianProcessRegressor(alpha=0.0, normalize_y=True, \n", + " kernel=C(1.0) * Matern(1.0, length_scale_bounds=\"fixed\"))\n", + "gp.fit(thetas, llr)\n", + "\n", + "xi = np.linspace(bounds[0][0], bounds[0][1], 500)\n", + "yi = np.linspace(bounds[1][0], bounds[1][1], 500)\n", + " \n", + "xx, yy = np.meshgrid(xi, yi)\n", + "zz, std = gp.predict(np.c_[xx.ravel(), yy.ravel()], return_std=True)\n", + "zi = zz.reshape(xx.shape)\n", + "\n", + "mle = np.unravel_index(zi.argmin(),zi.shape)\n", + "zi -= zi[mle]\n", + "zi *= 2.\n", + "\n", + "cs = ax.contour(xi, yi, zi, [1.,4.,9.,16.,25.], linewidths=0.5, colors='w')\n", + "cs.levels = [nf(val) for val in cs.levels]\n", + "ax.clabel(cs, cs.levels, inline=1, fontsize=10, fmt = fmt)\n", + "cs = ax.contourf(xi, yi, zi, 30, cmap=\"viridis\",\n", + " vmax=abs(zi).max(), vmin=0.0)\n", + "\n", + "#plt.colorbar()\n", + "ax.scatter(thetas[:,0],thetas[:,1], marker='o', c='b', s=50, lw=0, zorder=10)\n", + "ax.scatter([xi[mle[1]]], [yi[mle[0]]], marker='o', c='r', s=50, lw=0, zorder=10)\n", + "ax.scatter([alpha_value_0],[alpha_value_1], marker='o', c='w', s=50, lw=0, zorder=10)\n", + "\n", + "ax.set_xlim(bounds[0][0], bounds[0][1])\n", + "ax.set_ylim(bounds[1][0], bounds[1][1])\n", + "ax.set_xlabel(r\"$\\alpha_0$\", size=16)\n", + "ax.set_ylabel(r\"$\\alpha_1$\", size=16)\n", + "ax.set_title(\"Approx. -2lnL (VAR(2,1))\")\n", + "\n", + "ax = axes.flat[1]\n", + "\n", + "gp = GaussianProcessRegressor(alpha=0.0, normalize_y=True, \n", + " kernel=C(1.0) * Matern(1.0, length_scale_bounds=\"fixed\"))\n", + "gp.fit(thetas, exact_contours)\n", + "\n", + "xi = np.linspace(bounds[0][0], bounds[0][1], 500)\n", + "yi = np.linspace(bounds[1][0], bounds[1][1], 500)\n", + " \n", + "xx, yy = np.meshgrid(xi, yi)\n", + "zz, std = gp.predict(np.c_[xx.ravel(), yy.ravel()], return_std=True)\n", + "zi = zz.reshape(xx.shape)\n", + "\n", + "mle = np.unravel_index(zi.argmin(),zi.shape)\n", + "zi -= zi[mle]\n", + "zi *= 2.\n", + "\n", + "cs2 = ax.contour(xi, yi, zi, [1.,4.,9.,16.,25.], linewidths=0.5, colors='w')\n", + "cs2.levels = [nf(val) for val in cs2.levels]\n", + "ax.clabel(cs2, cs2.levels, inline=1, fontsize=10, fmt = fmt)\n", + "cs2 = ax.contourf(xi, yi, zi, 30, cmap=\"viridis\",\n", + " vmax=abs(zi).max(), vmin=0.0)\n", + "\n", + "fig.subplots_adjust(right=0.8)\n", + "cbar_ax = fig.add_axes([0.81, 0.12, 0.03, 0.775])\n", + "fig.colorbar(cs2, cax=cbar_ax)\n", + "\n", + "ax.scatter(thetas[:,0],thetas[:,1], marker='o', c='b', s=50, lw=0, zorder=10)\n", + "smle = ax.scatter([xi[mle[1]]], [yi[mle[0]]], marker='o', c='r', s=50, lw=0, zorder=10)\n", + "sobs = ax.scatter([alpha_value_0],[alpha_value_1], marker='o', c='w', s=50, lw=0, zorder=10)\n", + "\n", + "lines = [smle, sobs]\n", + "labels = ['MLE', 'Observed']\n", + "\n", + "ax.legend(lines, labels, frameon=False, prop={'size':12}, scatterpoints=1)\n", + "\n", + "ax.set_xlim(bounds[0][0], bounds[0][1])\n", + "ax.set_ylim(bounds[1][0], bounds[1][1])\n", + "ax.set_xlabel(r\"$\\alpha_0$\", size=16)\n", + "ax.set_ylabel(r\"$\\alpha_1$\", size=16)\n", + "ax.set_title(\"Exact. -2lnL (VAR(2,1))\")\n", + "\n", + "plt.show()\n", + "#plt.savefig('ar_2d_approx.pdf')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Plot grid of score distributions to check calibration" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "from carl.ratios.utils import plot_scores" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "combinations = list(combinations)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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IrVYrH330UZmenl5u2/j4eBkSEiL9/f1l8+bN5Zw5c8q0iY6ONruik61QA1fHqghz0bGY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\nGb3HaNMW/vvfyo/5wvJWCdR1t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