diff --git a/.gitignore b/.gitignore index 342d4ff..18acd1e 100644 --- a/.gitignore +++ b/.gitignore @@ -6,3 +6,4 @@ build/ _glmnetmodule.c dist MANIFEST +.ipynb_checkpoints diff --git a/CHANGELOG.md b/CHANGELOG.md index 39ebca2..2c552e2 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,10 @@ All notable changes to this project will be documented in this file. This project adheres to [Semantic Versioning](http://semver.org/). ## Unreleased +## 2.2.2 - 2021-03-21 +### Added +* [#70](https://github.com/civisanalytics/python-glmnet/pull/70) + Add new plotting functionality for cross-validation score and coefficient path. ## 2.2.1 - 2020-06-30 ### Fix diff --git a/dev-requirements.txt b/dev-requirements.txt index 92ad1ad..24ebed7 100644 --- a/dev-requirements.txt +++ b/dev-requirements.txt @@ -3,3 +3,5 @@ numpy==1.19.0 pytest==5.4.3 scikit-learn==0.23.1 scipy==1.5.0 +pandas==1.0.1 +matplotlib==3.3.4 diff --git a/example/ElasticNet.ipynb b/example/ElasticNet.ipynb new file mode 100644 index 0000000..e1ef0f5 --- /dev/null +++ b/example/ElasticNet.ipynb @@ -0,0 +1,371 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# ElasticNet Example" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%cd .." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# loading required libraries\n", + "from sklearn.datasets import load_diabetes\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from glmnet.linear import ElasticNet\n", + "from sklearn.model_selection import train_test_split\n", + "from IPython.core.display import display, HTML\n", + "display(HTML(\"\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " age sex bmi bp s1 s2 s3 \\\n", + "0 0.038076 0.050680 0.061696 0.021872 -0.044223 -0.034821 -0.043401 \n", + "1 -0.001882 -0.044642 -0.051474 -0.026328 -0.008449 -0.019163 0.074412 \n", + "\n", + " s4 s5 s6 \n", + "0 -0.002592 0.019908 -0.017646 \n", + "1 -0.039493 -0.068330 -0.092204 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# loading example data from sklearn\n", + "data = load_diabetes()\n", + "X = data.data\n", + "y = data.target\n", + "cols = data.feature_names\n", + "\n", + "# putting features (X) into Pandas DataFrame\n", + "X = pd.DataFrame(data=X, columns=cols)\n", + "X.head(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# create stratified train/test splits\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y,\n", + " test_size=0.2,\n", + " shuffle=True,\n", + " random_state=1367)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "ElasticNet(alpha=0.95, random_state=1367)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# train a ElasticNet model\n", + "model = ElasticNet(alpha=0.95, random_state=1367)\n", + "model.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([222.27577342, 195.6992576 , 112.04844142, 179.44177231,\n", + " 145.98695195, 160.59908477, 101.36401537, 171.22799331,\n", + " 136.26498919, 211.33820247])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# predicted targets\n", + "y_pred = model.predict(X_test)\n", + "y_pred[:10]" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plotting coeff. paths\n", + "model.plot_coeff_path(bbox_to_anchor=(1.1, 0.5))" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# this can be done via plotting too!\n", + "from glmnet.plotting import coeff_path_plot\n", + "coeff_path_plot(model)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot cross-validation scores\n", + "model.plot_cv_score()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# this can be done via plotting too!\n", + "from glmnet.plotting import cv_score_plot\n", + "cv_score_plot(model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## You can customize the plots based on your preferences!" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# the figures are totally customizable based on user's preferences\n", + "model.plot_cv_score(figsize=(12, 8),\n", + " linestyle='-.',\n", + " linewidth=5,\n", + " colors=[\"purple\", \"pink\", \"green\", \"navy\"],\n", + " marker=\"*\",\n", + " markersize=10,\n", + " fontsize=24,\n", + " grid=False,\n", + " legend=True,\n", + " legendloc='best',\n", + " xlabel=\"Your X-Label\",\n", + " ylabel=\"Your Y-Label\",\n", + " title=\"Your Title\",\n", + " save_path=None\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/example/LogitNet.ipynb b/example/LogitNet.ipynb new file mode 100644 index 0000000..6d23882 --- /dev/null +++ b/example/LogitNet.ipynb @@ -0,0 +1,419 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%cd .." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# loading required libraries\n", + "from sklearn.datasets import load_breast_cancer\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from glmnet.logistic import LogitNet\n", + "from sklearn.model_selection import train_test_split\n", + "from IPython.core.display import display, HTML\n", + "display(HTML(\"\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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017.9910.38122.81001.00.118400.277600.30010.147100.24190.07871...25.3817.33184.62019.00.16220.66560.71190.26540.46010.11890
120.5717.77132.91326.00.084740.078640.08690.070170.18120.05667...24.9923.41158.81956.00.12380.18660.24160.18600.27500.08902
\n", + "

2 rows × 30 columns

\n", + "
" + ], + "text/plain": [ + " mean radius mean texture mean perimeter mean area mean smoothness \\\n", + "0 17.99 10.38 122.8 1001.0 0.11840 \n", + "1 20.57 17.77 132.9 1326.0 0.08474 \n", + "\n", + " mean compactness mean concavity mean concave points mean symmetry \\\n", + "0 0.27760 0.3001 0.14710 0.2419 \n", + "1 0.07864 0.0869 0.07017 0.1812 \n", + "\n", + " mean fractal dimension ... worst radius worst texture worst perimeter \\\n", + "0 0.07871 ... 25.38 17.33 184.6 \n", + "1 0.05667 ... 24.99 23.41 158.8 \n", + "\n", + " worst area worst smoothness worst compactness worst concavity \\\n", + "0 2019.0 0.1622 0.6656 0.7119 \n", + "1 1956.0 0.1238 0.1866 0.2416 \n", + "\n", + " worst concave points worst symmetry worst fractal dimension \n", + "0 0.2654 0.4601 0.11890 \n", + "1 0.1860 0.2750 0.08902 \n", + "\n", + "[2 rows x 30 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# loading example data from sklearn\n", + "data = load_breast_cancer()\n", + "X = data.data\n", + "y = data.target\n", + "cols = data.feature_names\n", + "\n", + "# putting features (X) into Pandas DataFrame\n", + "X = pd.DataFrame(data=X, columns=cols)\n", + "X.head(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# create stratified train/test splits\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y,\n", + " test_size=0.2,\n", + " shuffle=True,\n", + " stratify=y,\n", + " random_state=1367)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LogitNet(alpha=0.95, random_state=1367, scoring='roc_auc')" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# train a LogitNet model\n", + "model = LogitNet(alpha=0.95, scoring=\"roc_auc\", random_state=1367)\n", + "model.fit(X_train, y_train, )" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[9.99260250e-01, 7.39750030e-04],\n", + " [3.91632760e-04, 9.99608367e-01],\n", + " [5.01016678e-02, 9.49898332e-01],\n", + " [7.55603488e-03, 9.92443965e-01],\n", + " [1.13039291e-02, 9.88696071e-01],\n", + " [9.36176370e-01, 6.38236304e-02],\n", + " [2.49705376e-05, 9.99975029e-01],\n", + " [9.03234831e-04, 9.99096765e-01],\n", + " [8.06446885e-01, 1.93553115e-01],\n", + " [5.59913528e-03, 9.94400865e-01]])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_pred_proba = model.predict_proba(X_test)\n", + "y_pred_proba[:10]" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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WLV64+Za7cAEr5s8lf83qUo/JapdNh97b0bFXHzpGP9t160FGY/+645yrGv6viXPOOedqXFH+etauWM66lctZt2IF61auiO4v33y/eNOmUo9t0rQZHXr2pn3P3nTo2ZuOvcOIUovWbWr4WThXOZIuAa42sz7R45FAMzM7M51xuYo1+OTJL5LrnHPOVZ2SkmIK1q4lb1Uu61flsm7lCvJWrSQvd2W4n7uSdSuXs6GgoMK+stp3IDsq/x1KgXenQ8/etO7QcXPxBufqiSvSHYBLToNPnvwiuc4551zyCvLWsWbJYtauWMaa5ctYu3wZ61YuJy93JXmrcslfsxorKamwn8ZNm9KqfUdate9Aq/YdaN2hI606dKRV+47hfvsONGnarAaekXOVo/AFMsPMSh8iTYGZlX0hMVerNPjkyTnnnHOlMzPWLFvKwmnfsnDatyyY9h2rFi2o8LjmrVrTsl02We2yycpuT1Z2B1plt4/ut6dVh440a5nlBRscAJJygC+BlsDZQC7wm2jb48AgYDJwtpn9EHfcr4DfAz2A74HrzOx/0b6OwH3AwUAbYCrwf2b2ftzxBvwcOA0YAswBLjWzMWXE2Qf4ATgjOu/ewFGSCoBbgD2jpp8Cl5nZ7LhjTwL+AXQB3gYmJPQ9krhpe1Fsx5jZ6IR4jzGz0ZKygfuBI4DmwFzgj2Y2qrTYXdXx5Mk555xzQEiWchcuYMHUKSyY+i0Lpn5DXu7Krdo0zmxKu27dad2hE607dox+dqJVdgdatmtHy7btyGjcJE3PwNVhFwLXExKS3wJPAJ8B/wIuBx4D7gJOBJB0PnA1cCnwHXAo8JykQWY2kZBQfALcDKwHzgFek7SDmS2KO+8I4ErCtLk/AU9L6mNmReXEelMU43RgNbAX8DAwEWgG/BV4UdI+ZmaStgOeA24FngKOBm6Ijq2sG4FsYCiQBwyInqerZp48Oeeccw2QmZGXu5Llc39g+dwfWDp7JgumfUvB2q1nDzXLakX3/gPo3n8XevTfhU7b9fXqdXVMn6vfsJo+55xbj011WHG8md0JIOlG4NdATmwkRdI9wINx7a8DrjCz16PHsyUNIyRhE81sHiHZihkh6VTgWEKiE/OQmb0YneNa4AJgZ+DrcmL9u5m9Gff4vfidki4ElgP9gBnAxcBkM7suajJd0qGERLGyegIfm9nk6PHs8hq7quP/+jnnnHP1mJWUsC53JbmLFrBq0QJyFy1k5YJ5LJ83h8J1a3/UvmXbdvTYeVd6DNiNHv0H0L5HLy/O4GrClLj7S6Of3yZsay0pE8gEtgeeiqayxWQCOQCSGgN/AU4FugFNCKNRvRLOOznufuyKyp0qiHVi/ANJXQkjXIOjY2O/ML0IyVN/EqbpAePZtuTpIeB5SUcSkreX4hIpV408eXLOOefqODNj/apcVi1ZxKrFi1i9dDGrlyxi9ZLFrFqyiE1Fpc9AatYyK1wPqfd2dOyzPd132pm2Xbr5WqR6phKjQOmwMXYnmuq21TYgliQ1IqyNAjgPmJTQT6yM41WEEZ8rCOud8oEXCUlUReet6K8F+QmPRwJZhCmE8wEB3yScK9XRP4v6AUDSVnGb2evRdMDjgCOBCZKuMrN/pXgelyJPnpxzzrk6oqS4mFWLF7Fi/hxWLpgfLhy7aAGrFi9iY2HZpb9btGlLu67dye7WnexuPcju3pMOvfrQqn0HT5RcnWNmSyUtBvqY2UtlNBsEvGhmzwFIagn0rqaQBgHDzezt6FyDEvZPA4YlbDuggj6XA13jHu+R2MDMlgKPAo9Kug74JWGNmKtG9TJ5kvQx4S8JWcBzZvb3NIfknHPOJc3MyFu1khVz57B83hxWzJvDivlzyV04v8wLxzZr1Zp2XbvRrks32nbpGq6N1Dn8bJaVVcPPwLlqdxNwq6R1wAdAK8K0uUVm9gIwEzhO0v6E0agbgIxqimUmcJ6kyYRqercn7H8IuFLSCOBpwkjRMMovGJEDXCEpVvzib/E7Jd0AfEEoltGKUHVv2jY+D5eEepk8AUPNbEM0xDlN0n/MbFm6g3LOOecSbSwqZOX8sAZp+bwfNidMhXnrSm3fplNn2vfsTfsevcju2p123XqQ3a07zVu1ruHInUsfM7s/KhF+JWG0ZQ0hmRgRNbkJ6EtIrNYQEprsagrnF4QiFJMJidTlwOaS6GY2W9KZwB3A/wHvRvFcVE6fVxLKtH9CKEN+KaGcesxG4O+E0bQ84B1CBUBXzWRW4wVYyiXpZOBXwD5AO2A7M5uT0OZKwgekA+FDdYmZzSilrzbA68Dh5ZWcjF9sWNtej7osJyeHIUOGpDsMlyJ/3+omf99qv5LiYlYvXcyK+XNZMW8uK+bPYd60qRStXQ2l/N8TW4/UoXcfOvTsTYeefejQsxeZzVvUfPBuK+n+fYufamlmPu/SuRpUG0eeWgLjgJcJF//aiqTzCH9N+DlhMd4NwJuSdjGzDVGbDELGvwvhugAbaiZ055xzLrCSEhbPnM7Mz8czd/LXrFw4j+KNG3/UrlFGBtndetChV0iSOvbZjo69tiMru72vR3LOuVqm1iVPZvYkgKT+ZTS5HLjPzJ6J2p0PLCNUG3k56qMYGCKpGfAmYW7p29UcunPOuQZu08aNzPvma2Z+Pp5ZX3xG/prVW+1v3bETHXr2pn3P3nTo0Ys5y1Zw5Ikn0biJX1TWOefqglqXPJVHUlNgT+Da2DYzWyfpM2Ag8HJU/3+TmZUARYRykmWXIHLOOee2gZmxaPpUpn40humfjKNwfd7mfa07dqbfvgfQd98D6Lz9DjRtsfWUu2U5OZ44OedcHVLr1jzFRCNPU4lb8ySpG7AQ2NvMvopr+zxQYGbnS9qJsGivBGgKjDazG8o4x0WExXr7xLaNGTOmep5QA5SXl0eWV3iqc/x9q5v8fat5hatXkfv9t6z8fiob1q3ZvL15+4603X4H2vbpR/P2HcudeufvW92U7vdt6NChm+/7mifnaladGnlKhplNJ5SqTKbtQ8BD8QUjfMF11Un3glpXOf6+1U3+vtWMgrx1fP/pOL4d+wGLv99SFTgruz07HzyEnQ8ZSsdefZLuz9+3usnfN+carrqWPK0EioHOCds7ARMq06Gk47c1KOecc/VXSXExP3z9Bd9++D6zJ07YfJ2lJs2as+MBBzFg8GH0GLArjRpV1yVknHPO1RZ1KnkysyJJXxMuLDYaQFIW4SrN91Syz1Fezcg551yilQvm803Ou3w39oPNhR+kRvTefS92GXwY/fY7kCbNmqU3SOecczWq1iVPkrKBXkCfaNMASW2BmWaWR0iSHoiuuPwN4WJoCwnXc3LOOecqbUNBPtM+Gcs3Y95l8Yzpm7dnd+vBLkMOZ+dDhtAqu0MaI3TOOZdOtS55Ak4gXFE55o3o51Agx8yekNSJcJXm2EVyj4ld4ylVPm3POecaNjNj8YzpTPngHaZ/MpaNRYUAZDZvzk4HDWbXIUfQdYed/JpLzjnnal/yZGYjgZEVtLmDkDxVxfl82p5zzjVAhXl5fDfuA6a8/zYr5s/dvL3Hzruy69Aj2PGAQT4tzznn3FZqXfJU03zkyTnnGg4zY8nM75n07ltM/2QsmzaGSQvNW7dhl0OHsdthR5LdrUeao3TO1UalXUanivp9Fig0s+FV1aerPg0+efKRJ+ecq/82FBYwdVwOk957i+VzZm/e3nv3vdj98KPpu8/+ZDT2i9U65+ouSZmVXcbiktco3QE455xz1WXlgvm8/9gDPHjJebz3yH0snzObZq1as+/xJ/Pzux/i1D/fyI4HDPLEybk0kpQj6Z+SHpS0TtJcScdL6i7pHUnrJX0qabuE434laYakAkmTJJ0Yt6+jpOclLYqO/0LSsITjTdIFkt6UlC/pO0lDKdvU6OcP0bEjo34yJF0vaV50rvGSBkX7Wkj6XtLf4s47WFKRpH0ljQDOAM6P+jRJfSQNl7QkId6ttkkaKek5STdLWga8G23fQ9J70XNaEL22Pge5ijT4kSeftuecc/VLSXExM78Yz6R33mDeN5M3b+/efwB7HH4MOww8mMZNPFlyrpa5ELge2Bv4LfAE8BnwL+By4DHgLuBEAEnnA1cDlwLfAYcCz0kaZGYTgeaEomI3A+uBc4DXJO1gZovizjsCuBK4AvgT8LSkPmZWVEqMhwDjgP2B+UBBtP1a4GTgfGAecArwtqT+ZrYgijVH0ihCpegngL+Z2ReSpgF7AkVRDADLU3jdjgWeBAYDFlWtfg+4G/g10B74N3BbXP9uGzT45Mmn7TnnXP2Ql7uSKR+8w+T3R5OXuxKAxk2bMuDgoexx5E/o1Gf7NEfoXJqMaGM1f841qX65Gm9mdwJIupHwxT/HzEZF2+4BHoxrfx1whZnFLlUzOxpZuhCYaGbzCMnW5ogknUpINh6O2/6Qmb0YneNa4AJgZ+DrUmJcEf1cbmZLomOaAX8EBplZ7JjbJZ0A/Ay4zcw+lfQP4D/A54Tk6CYAM8uTVEhY8xQ/qlTBy7XZSuA3ZlYcHfcX4GMzuymurz8QEsffmlnNfxbqmQafPDnnnKu7zIz5305h0rtvMvPzTykpLgagXbce7HnkTxgw+DCatcxKc5TOuSRMibu/NPr5bcK21pIygUxge+ApSfHJQCaQAyCpMfAX4FSgG9CEMBrVK+G8k+PuL45+dkoh7r5AC+CjhISnKWFELGYEcBJhVGpPM9uUwjnKMymWOEV2B34iKS9umwjPvSsQP+rmKsGTJ+ecc3XO2uXL+Hbs+3z34QesXhq+76hRI3Y44CD2PPJYeu6yu1+XybmY1EeB0mFj7I6ZWfT7uzFufyxJagS0jO6fB0xK6Cc2le4q4GLCVLWpQD7wIiGJqui8qdQEiP115nC2jEzFrI273zO6NSIkcFMpXwkh6YlX2nzj/FLieZEwMpdoWQXndElo8MmTr3lyzrm6oSg/n5mff8q3H77P/G+3/LE4K7s9ux12FLsNO5JW2R3SGKFzriaY2VJJi4E+ZvZSGc0GAS+a2XMAkloCvbfx1LFKdhlx26ZG27ub2fjSDpLUiDBlbxQh2XtU0q5mtjqu34yEw5YD2ZKaxq2/2iOJGL8GfgLMNrOSJNq7FDX45MnXPDnnXO21fvUqZk38jJkTPmXeN5Mo3hRmujRukkm//Q9kl0OH0Wu3PWjUKPF7h3OunrsJuFXSOuADoBWhaMIiM3sBmAkcJ2l/wmjUDfw4QUnVYkKic4yk54ACM1sr6W7gXklNgAlAB+BIYJyZfQj8gTDN8ARgNXA8cC+hiAXAHOBUSdsTRqtyo342ADdJehA4GDiNLSNwZbmPMOL2uKS7gDxgF8KarKu28fk7PHlyzjlXy6xdsZwZn33M9599wqLvp0JsfbNE9/67MGDwUHY68BCatmhZfkfOuXrLzO6XVEColPcvYA3wBWFtEYTkqi8hsVoD3A5kb+M5CyT9HrgGuIdQNW84oepfrAhEL8L0vU8I1f92Bf4KnGJmuQCSzgMmSTolGjn7N6GS3xTC+qntzGxO1O42QkXBt4C/RecqL8YFkg6OjvuQME1wJjByW56728KTJ+ecc2m3dsUyvh//Md+P/4jFM6Zv3p7RuDG9dtuTfvsdSL99D6BFm7bpC9I5Vy3MbEgp25TwOIeENUBm9jjweBl9riCM8MS7u7xzlLUtYf99hNGd+G0lwN+jW2m2usaSmc1iy1opzGwx8KPrS0WJVeK0xLvi9g8vI8bv+PFzd1XEkyfnnHNpUbBuLdM//Yip48aEEaZI48ymbL/XvuwwcBDb77Uvmc1bpDFK55xzbosGnzx5wQjnnKs5mzZsYPZXn/Pd2DH88NUXlBRHa5iihGnHAw9h+732pUmzZhX05JxzztW8Bp88ecEI55yrfsvmzGbKB+8w7aMcCteHy49Ijeizx97sfMhQ+u03kMxmzdMcpXPOOVe+Bp88Oeecqx6FeXlM/TiHbz54l2VzZm3e3rHP9gw4ZCj9Bx1KVrttWr/tnHPO1ShPnpxzzlWplQvm8+Vb/+O7sWPYtCFcnqRZyyz6HzyE3Q47kk59tk9zhM4551zlePLknHNum1lJCXMmf8WXb/6POZO+3Ly91657sOthR7LDfgfSODMzjRE655xz286TJ+ecc5VWvGkTUz/K4fPXXiJ34XwgFH/Y5dDD2OvoE2jfo2eaI3TOOeeqToNPnrzannPOpW7jhiK++eAdPh/1MutWLAcgK7s9ex19PLsNO4rmWa3SHKFzzjlX9Rp88uTV9pxzLnlF+fl8/c4bfPnm/8hfsxqA7G492P+np9F/0KFkNG7w/60455yrx/x/OeeccxUqys/nq9GjmPj6K5tLjXfefgcOOOk0+u07EDVqlOYInXPO1UaScoDxZnZ1umOpCp48OeecK1NR/nq+emsUE994dXPS1L3/Lgw8+Qx6774XPnLvnHOuAicDG5JtLOkS4Goz61NtEW0DT56cc879yKYNG/jyrdf4/H8vbk6aeuy8KweeejY9d9nNkybnnHNJMbPcdMdQlXyehXPOuc2spISp48bw2O8uZtzTIylcn0ePAbty+nW3cMaIW+m16+6eODnnqpSkHEn/lPSgpHWS5ko6XlJ3Se9IWi/pU0nbJRz3K0kzJBVImiTpxLh9HSU9L2lRdPwXkoYlHG+SLpD0pqR8Sd9JGlpBrNtJekXSGklro9i7RftaSHpA0sqov9GS+sUdO0LSeEm/lDRf0ipJj0hqGtemhaR7JC2OntdkSYdF+wZK+kBSbnR7Q9L20b4MSUsknZMQ7/Boe0b0eA9J70XxLYhe92blPN+Rkp6TdFsU70pJ1yW02T7uNcyV9JCklgnv763JvO6ShgD/BnpH7Sx6DpJ0YxRzkaR5kv5S3ntVXTx5cs45B8D8byfz1J9/z5v3/oN1K5bTsVcfTrnmr5xx/a303GX3dIfnnKvfLgSmAXsDrwNPAI8C/wL2AQy4K9ZY0vnA1cDvgF2ifc9J2idq0hz4BDgG2CPq87VYohNnBPBY1GY88HR8MhMv2v4O0Aw4HNgPeIotM7n+ARwFnA4MBEqAUbHEJTIAOCxqdxpwCnBJ3P4Ho5h/DuwK/CV67gBZwMNR30OAjcCLkmRmxcALwJkJYZ8JPG9mxZKygfeAHGDP6PyHAbeV9nzj/ATIBg4CLgeulnRm9Jo0Al6LXoMDCVP0hhH3XpVhBKW/7p8A/wcsALpGt+eAU4HzgbOAHYGzgdkVnKNa+LQ955xr4FYvWUzOk48y64vxAGS1y2bQGecy4NDDaNQoo4KjnXO13W7/2c0qblW1ppw/JdUh6vFmdieApBuBXwM5ZjYq2nYPIbGIuQ64wsxejx7PjkaWLgQmmtk8tv4CP0LSqcCxhAQk5iEzezE6x7XABcDOwNelxHg20A44zczyom3To2OzgF8Ap5vZ+9G2c4H50Tlfi9ob8Aszywe+k/QCMBS4OxpFOgc40MzGR+1nxU5uZu/FByPpQmA50A+YATwLjJHUzsxWSWpPSGRuiA65FPjYzG6K6+MPhKTyt2ZW1uckD/i1mW0EpkYJ6uXR+Y4AdgAOM7NlUZ+XRX3+0cxWldFnqa+7mX0taS1QbGZL4uLsGT3Hj6I45wIfldF3tWrwyZP8Ok/OuQZqQ0E+n73yPBPfeJXiTZto0rQZ+514CvseexJNmpU5i8M556rDlLj7S6Of3yZsay0pE8gEtgeekhT/hT+TMKqCpMaEUZtTgW5AE8JoVK+E806Ou784+tmpjBh3Bb6IS5zi9Y3O8Ulsg5mtlDQd6M+W5GlmlDjFn3PX6P4uQCHwWWknl9QVuBkYHMUYm0HWi5BYfBL1dwrwCOG5LzCzT6N2uwM/kRQfvwivS1dgURnP+6socYoZT0h2iJ7brFjiFPkYyCAkVRPK6DOV1x3gReD3wHRJo4HXzeydctpXmwafPPl1npxzDY2VlPDduDGMe+Y/rF8V1vEOGHwYh5x1PlnZ7dMcnXOuqlViFCgdNn85NzOLvpvFf2GPJUmNgNh6mvOASQn9FEQ/rwIuBq4ApgL5hC/gTZI4b3Uua9mY8NhSON9IwtS9SwkjWgK+IXpOUfzPEabqPQKcQRgdiskivAZbrVmKLCtlW3yMVS2l193M5knakTDd8QjCNL8cMzu1GmIrV4NPnpxzriFZOnsm7z/2bxbPmA5Al347MvT8i+i2Y/80R+acc8kxs6WSFgN9zOylMpoNAl40s+cAogIGvbfx1N8A50vKKmX0aRYhITgIeDU6Z3tgJ0LyloxvCeupDiCM7iQaBAw3s7ej/geV0uYZ4PeS9gQOBX4bt+9rwvql2WZWkmRMAHtJamxmm6LHBxDWpxH97CupU9zo0yCgmDAaVhkbCCNXW4lG7F4BXpH0LPChpOyarubnyZNzzjUABevW8tGzTzD5/bfBjJZt23HI2cMZcMhQv8Ctc64uugm4VdI64AOgFWE62yIzewGYCRwnaX/CaNQNlPKFPEVPE6YCPi/pemA1cDDwfjQy8ghwZ7RmZzmhEMNc4M1kOjez2ZKeBp6M1g1NJxSYWG9mOdFzOk/SZKALcHspfXwlaSah4MY0M4ufHncfYTTucUl3EdYy7QIMMrOrygmtFXCfpDuBvQgFLn4Z7XuXkCQ9KekqwpqwfwGPl7PeqSJzgC6SDiAkpesIo2mNCNMAiwijaksJ70GN8uTJOefqsZKSYqa8/zYfPfskhXnraJSRwV7HnMCBp5xF0xYt0h2ec85VipndL6kAuJLwZX0N8AWhihuE5KovIbFaQ0g0srfxnEWSjgTuBMYQqul9AYyOmvyB8AX/BaAFMBY4PqqEl6yLgL8Tkp9WwPeEqYcQClI8TFgvNJNQtOH9Uvp4FriekOjFx79A0sGEpO7DKNaZhOmA5XmTkMB8SpjCd4eZPR31WSLpBOBewmhZIWFq4O+SfcKlGAM8CbxFSMYuICRJ1wB3R20mAsemOIJWJVR2YY2GI36xob8eVScnJ4chQ4akOwyXIn/f6qbE962kpJgZn33C+JefY8W8OQD02nV3DrvgEtr3SFwv7dLFf9/qpnS/b/Frtc2sLqxncnWUpJFAMzNLLIHeYPnIk3PO1SMlxcVM/2Qs419+jtxFCwBo1b4jh577C3YcOMgvcOucc85tA0+enHOuHigp3sSUMe8w4dUXWL0kVH1t3bET+594KrsMOYLGTRILTDnnnHMuVZ48OedcHVaYl8ek997im/+9yMb89QC06dyFA046nQGHHEZG47r/z3zJhg0Ur1pN8epVWFERTXr2pHG7dukOyznn6j0zG57uGGqbuv+/aoKoBvwjhNr3TYCb4q4+7Zxz9cLa5cuY+Ob/mPLBO2wsDJc16dCrD/sdfzL9Bx1Ko4xtLSpVvWzDBjYtX87GpUvZtHQpm5YvZ9PKXDatXEHxipVsys2leOVKilevpmT9+h8dn5GdTdPttyezb1+a9utH1uBDyOy9rVWInXPOufLVu+QJyAVOiq7q3IlQjcOTJ+dcnbdp40ZmffEZ3+S8y5xJX0JU4KbXbnuS2asvJ5w7PO1rmqy4mOJVq9i0YgWbVqwMidGypVGStIyNS5ewaekyileuTL7Txo3JaNuWxu3aQuMmbJg7l+LcXPJzc8n/4gsAlt4MzQYMoNUxR9P66KPJ7Nmzep6gc865Bq3WJU+STgZ+BexDKE+4nZnNSWhzJeGiXx2AT4BLzGwGgJmtiGtaQPVcFdk552rM8nlz+GbMu3w3bgyF69YCkNG4MTsOPJh9jjuJztv1JScnp1oTp5KCgjA6tHw5m5aviLsf3VasYNOKFRTn5kJJEpVjGzWicceONO7cmSadO9G4YycyOrSncXZ7GndoT0b79jTOziYjO5tGWVmJ1cXYtGQJRbNms2H2LAomTyFvzBgKv/uOwu++Y/k//kmzXXah7Wmn0uaEE2jkJdmdc85VkVqXPAEtgXHAy8D9iTslnUeo3f9zwpWebwDelLSLmW2Iayfg38CtNRG0c85VpdVLlzD9k7FM+/hDVsyfu3l7x1592PWwI9n54CE0b9V6m89TUljIpmXL2LR0KRuXLWPTsigZWrYs3KLkqCQvL+k+M9q1o3GHDmR0aE+TTp1o3KkzjTt3pnHnTjTpHN1v3x5Vcj2WJJp07UqTrl3h4EHheRQVsf6jj1j71mjyPviAwm+/Zcm337Lszrtod/pptPvZz2jSpUulzuecc87F1LrkycyeBJDUv4wmlwP3mdkzUbvzgWXAcYSEK+ZeYI6Z/SgBc8652sbMWLV4IT989QXTPhnLkpnfb97XrGUWOx10CLsOPZLO2/dLeoSppKiIjQsXsnHhIjYtXcLGJUu3/FyyhE3LllG8Zk1SfalJkzBS1LEjjTuFnxkdOoTHHTrQuGMnGnfsQOPsbJSGyn6Nmjal1bBhtBo2jJLCQta9/z65TzxB4aTJrHz4EVY+9jitjzqK9hf9kmb9y/rvxTnnnCtfrb1IbpQ8TSVu2p6kpsB64DgzGx3XNgeYYGZ/jB7fDWwysysrOMdFhCs57xPbNmbMmKp9Ig1YXl4eWVlZ6Q7Dpcjft9LF/q2syqlxmwoLWLdwHmvnz2Ht/DlsyFu3eV+jxk1ou10/2vXrT+uefUovAFFSQqM1a8lYsZxNCxbQYl0eGStWhNvKlWQkkRhZRgYlbdpQ3LYtJW3aUNK2LcVt2lDStg0lrdtQ3KY1JW3bYi1aQB28RlST2bNp8cEHNP3yK1RSgkkUHjiQvBNOoKRt23SH579vdVS637ehQ4duvu8XyXWuZtW15KkbsBDY28y+imv7PFBgZudLOhwYDXwU191xZlbmnBNJm1+E2vp61EXpvgK7qxx/37ZWmJfH5PdH89Xbr7M+N5fmrVvTok1bWrRpS8s2bWneqjWZLVrStHlzMlu0ILN5CzKbNadRRkbcrTHFmzayatFCchfNZ+XCBeQunM/a5cu2OlezVq3pvese7HDAQWy/9340adoMCKW6N8yZw4ZZsyiaOYuiWbPYMGsmG+bNx4qKyg6+cWOadOsWbl260LhL5/Czc+fN0+cy2rVDjRpV50tYK2xcvJiVjz/OqmeehY0bUfPmtL/gAtr/4uc0atkybXH571vdlO73LWENoCdPNUjSEYTZTX2Be83st+mNaAtJI4CjzWxgCsc8CxTGSpJLmgPcamYPVEeMVSH63n5M/EBKTap10/a2lZm9RwrPS9Lx1RiOc66OWrVkEV+++Rrf5LzLprgEJX/NavLXrK6SczTKaEz3nXam9+570WePvenUZ3uKc3MpnDqNtU/+l8Jp0ymaPo2i2T9AcXGpfWRkZ5PZsye5mZn02HcfMnv0oEmPnmT26E7jzp0rva6ovmnStStdrrmG7J/9jGV3/IN1777LivvvZ/ULL9Dpj1fR+rjj0l6p0DlXJ9wLvAHcAayroG2llDaAUIP2A5Jf5JoeXQnVtdOirv2vuhIoBjonbO8ETKhMh2Y2yv/DdM7FLJszm/EvPcuMzz/dXAq89+57sc+xP6XXrrtTsHYt66MEKn/NagrWrmFDYQEbCvIpyg8/NxYVUlJcTMmmTZSUFFOyqRgaiXZdupHdrQfZPXqS3a0HLdWIjdOmU/jNtxS+/Q9mfvstm5Yv/3FQEk1696Jp33407duXpv36ktmvH5m9+5CRFUZN5uTk0MlHMCqU2bs3Pf51D/lffMHS226ncMoUFl31R/I+HEuXEdeT4VPonHPl6wu8a2aLStspKTO+gFldY2al/CdUu5jZknSev04lT2ZWJOlrYBhhah6SsoADgHvSGJpzro5bPm8On77wNDMmfAKEUuD9Dx7CPsf+lI69+mxul5Xdnqzs9in3X1JUROG331Lw9SQKxjxL7qRJLFu69EftGrVsSdP+/Wm200407b8Tzfr3p+kOO9CoefNKPzf3Yy323Zc+zz3L6pdeYuktf2Pt669T8PXXdL/j7zTfc890h+dcgxKtXf+SUHH5bMKowm+ibY8Dg4DJwNlm9kPccb8Cfg/0AL4HrjOz/0X7OgL3AQcDbQgjOf9nZu/HHW+E6s2nAUOAOcClZvajBfCS+gCxc78Z/eF9KNCHUNn5CuBmYDtJjYHzCUXOdgRWA68Bf4xfRiLpdODaqE0u8ISZXR3FCvBDdJ7/mNlwScMr6rMi0dS+y4BGwEOAEvbPIZq2F/ecTwP+COwGfAqcARwC3E64bNB/gN+ZWUnUR3vgn0BsdteHwGVmtiDaPxJoBnwbPR8jvM9Xm5lFFbP/ClwAdASWAg+b2Y3R8VtN24umUt4ODACWAPeY2T/inlPS73Myal3yJCkb6EX4MAIMkNQWmBl9OO4BHpA0kVCqfARhHVSlLoTr0/aca9hWzJ/Lpy8+w/fjwzLJxk0y2f2IY9jvhFPIapdd6X5twwYKJk9m/afjWT9+PAWTJ8PGjVu1adSqFc123YVmAwbQfJfws0mvXg1iDVJtoEaNaHfaabTYZ18W/uFKir6bypyfnUPHyy+n/YW/QKUV6XCuDpraf+caX9C987SpqU7ruRC4HtibcC3PJ4DPgH8RvmA/BtwFnAibqy1fDVwKfAccCjwnaZCZTQSaE64FejOh2Ng5wGuSdkgYNRoBXElIfv4EPC2pj5klLiidT5gutpiQ4I0hJDx9gLaEa5SeCcSOy4jimwH0Jlx+56bouSFpGPBfQvL0atRHrIDZIYTL9uwfnbcgmT4rIukc4Crgl8BXwB+AnwAvVXDodYT3YDXwAvA8YWrfT6M4XgZygFei9i8AK4DDCK/HdYTXft9YggUcQ0h0DiYkZc8Q3q//AacSks+zgHlAz+g8pT2nXsAowufkTMKAygOSlpjZU3FNR5Dc+1yhWpc8AScQss+YN6KfQ4EcM3tCUifCXNPYRXKPqewQqU/bc65hystdycfP/5dvct4DMzKaNGH3w49m/xNPq1TSZGZsmDmTvI8+Zv0nn5D/xRdYQcGWBhJNd9yR5nvsQfM996T5nnuQud12nijVAk23344+zz7L8n/eSe7IkSy/807yJ0ygx7/u8QvsOldzxpvZnQCSbgR+TfjeNyradg/wYFz764ArzCz2x/PZUUJyITDRzOYRkq2YEZJOBY4FHo7b/pCZvRid41rCaMfOwNfxwZlZMbAk+s64KjZ1LHrcFPilmc2IO+TRuPs/SLoOuJstic51wGNmdntcu9gSlBXRz+XxU9TMrKI+K/Ib4N9m9nQU+68Ir0dFbjWznOiYR4G/Ad3MbDHwjaQxhBGdVyQdQkiGupnZxuiYnwNrCOupPov6XEoYrTJgelQBeygheepJSBA/ivbPZetCcPF+BUwzs6uix9Ml7UpIlOKTp6Te52TUuuTJzEYCIytocwcheXLOuZRsKCzg89de5ovXX2ZTURGNMjLYbdjRHHDSabTK7pBSX8Xr1rH+o4/I++gj1n/8CZuWbD0NO7NfX1oOPJCWBw6kxX77kdF62y9q66pHo8xMOl/9f7QcdBCL/u9q1n/8MfMv+RU9H/i3J1CuzqvEKFA6TIm7H5vT/G3CttaSMoFMYHvgqfiKydH2HIBo6txfCKMY3YAmhNGoXgnnnRx3f3H0s1OKsa9LSJyQtD9htGM3wqhSY6CppMZmtgnYFfh3KidJos+K9CdMpwPAzDZI+jKJ4xLfm9wocYrf1jG6vzuQDaxKGJxoTFgvFkueptjWJa4Xs+V1f5EwHXO6pNHA62b2TjnP6ZOEbR8TRiTjVcX7DNTC5Kmm+bQ95xqGkuJivsl5l0+ef4r1q1cBsMMBB3HIWefTrmv3pPsxM/I//5w1L73E2tFvb1UqPKNDB7IGHUTLQYNoMXAgTTpV6t9ll0ZZhxxC76f+y7zzh5M/YQLzL7qYng8+kNZy5s41EJvnNUfrXrbaRlgXA2GtTuwX8jxgUkI/sSH/q4CLCdO0pgL5hC/liVfxLu28qU4JyI9/EK3Hf4swHe8mwkjSwYTRqMZAMonOVqqwz8pM4Ux8HzYm7De2vGZZhDVFR5XST/xC3zL7MLN5knaM+jiCMMUux8xOrUTsPzrfNrzPgCdPPm3PuXrOSkqY/uk4PnnhaVYtXghA1347cei5v6B7/wFJ97NpxQpWv/IKa158iQ1z527e3nzffcgafChZhxxM05128ml49UDT7baj9xP/Ye75w8n/4gvmXXwxvR580BMo52oJM1sqaTHQx8zKWq8zCHjRzJ4DkNSSMtbNVIP+hNGX/zOzFdH5T0to8w1hqtuzpRwfW4oSv/AymT4rMo2wjuqF6PgmwF7A2yn2U56vCQU81ieMTqXEzPIJa6heia5F9aGkbDNLLFE+DTg6YdugaHu1aPDJk3OufjIzZn85gY+ffZLl8+YA0LZzVwadcQ47HTQ46Wv6lBQWkvv446x46OHNa5gad+pEm5NPou0pp5DZs2d1PQWXRpl9+oQE6rzzKfhiIvMuupieDz64uTS8cy7tbgJulbQO+ABoBQwGFpnZC8BM4LhoqlsBcANbJyPVaR5hpOMySf8hFDG4JKHNzcDrkmYR1vm0AvY1swcJ08o2AMdIei6KP5k+K3I/cH9UdO1rwrqgqr4+w7uEYhSvSrqaMArVh1Dp7hozW11RB1ExkEaENWBFhOp+SwkFKxL9G/idpNsJo3D7E9Z2/XLbnkbZGnzy5NP2nKt/Fn0/jZwnHmbxjOkAZLXvwIGnnMkuhx5ORpIXjTUz1r37Lstuu52NC8OIVdahh9L2rDPJOvhgv/hsA5DZu/fmEaiCiROZf8nF9H78cdQkcdaPc66mmdn9kgoICcC/CAUJviCsCYKQXPUlJFZrCKWsK19CNbXYlkn6RRTDHwlrcK4lbk2/mb0TlR7/MyGRWk4o+Y2ZFUj6PXANocr0E1Gp8nL7TMKTwA6EJEqEZOPNyj7P0phZiaSjCeXbnyWszVpAGN0qTLKbNYTnfnf0eCJwbFylvvjzzYu+y99OKJyxBPhLQqW9KqWt12o1TPGLDf31qDo5OTkM8Yt21jl1+X0rzMtj3DMjmfz+22BG89ZtOOCnp7PHEcfQODMz+X6+/56lt/yN/PHjAWi6ww50/vOfaTnwgOoKfZvV5fetttswbx5zzz2PTUuX0vnPfyb73HOqrG9/3+qmdL9v8SPnZuZrD5yrQf6nU+dcnWdmTPsoh5wnHyV/zWoaZWSw73EnccDJZ5DZLPmLy1pxMSsffoTl994LmzaR0aYNHa64nHann+4jTQ1YZq9edLnuLyy49Dcs/9e/aH3csTRu1y7dYTnnnEsD/zbgnKvTVi9dwrsP38u8KV8D0L3/AA6/8FI69ExtXfCG+fNZ9Mf/o+CrrwBoe8YZdPztFf4l2QGQddhhtDzoQNZ/8ikr/vUvulx3XbpDcs45lwYNPnnyNU/O1V0zJnzC2/++m6L89TTLasXgcy5g10MPT6ninZmx5uWXWXrzLZTk59O4Y0e6/u1vZB08qBojd3WNJDpdfTU/nHQyq559jrZnnEmznXZMd1jOOedqWINPnrxUuXN1T/GmTYx7eiQT33gVgH77DeSIiy6jRes2qfWzbh2Lr7mGde++B0Cro4+my/XX+WiTK1WzHXek3Zlnsuqpp1j6t7/R6/HHkq7a6Jxzrn5o8MmTc65uWbtiOa/ffRuLv59Go4wMDjl7OPsc+9OUv8RuWLCA+ZdcwoaZs2iUlUWXv1xL6xNO8C/DrlwdL/sNa19/nfzx48l7/31aHX54ukNyzjlXg/xqjs65OmPulK958uorWPz9NLLad+D0629l3+NOSjnhyf/yK+acfgYbZs4is19ftnvlZdqceKInTq5CGW3b0uHyywBYetvtlBQVpTki55xzNanBJ0++5sm5umHWxAm8cusICtetpc8ee3PurXfTfaedU+5nzetvMG/4cIpzc2k5aBB9nnnGL3TrUtLujDNoukM/Ns6fT+5/nkh3OM4552pQg0+ezGxUumNwzpVvxoRPeO0ft1C8aRN7HnUsJ189IuX1TWbG8nvvY9Ef/oBt2EC7s8+i54MPkNGqVTVF7eorNW5M5z/9CYAVDzzAptzcNEfknHOupjT45Mk5V7tN//QjXr/rNkqKN7HPsSdy2AWXpFRND0LitOz2v7Pi3nuhUSM6//nPdLnuOr92k6u0lgcdRMuDDsTy88nL+TDd4TjnAEnNJJmkIdHjIdHjZumNzNUnnjw552qtqR/l8Mbdt1NSXMx+J57KoedeWKl1SSsfepjcxx+HJk3oce+/yD73nGqI1jU0WUMPA2D9xx+nORLnXBk+AbqaWWG6A3H1hydPzrlaaepHObx17z8xK2HgKWdyyFnnVypxWvXMMyy/806Q6H77bbQ67LBqiNY1RC2ja4Gt/+QTrKQkzdE4V39IyqyKfsxsg5ktqYq+qoKkDEk/+u4tqUlV9eWqn7/ozrlaZ0NhAe89cj9mJRx0+s8YdPo5lUqc1rz+Bkv+eiMAXUaMoPUxx1R1qK4By+zThybdulG8ahWF301NdzjO1VmSciTdKelBSauBhyU1kfS4pHmS8iV9I+nMhOO6S3pbUqGkqcCwhP1bTduTNFLSswltttom6TJJsyUVSVos6f4KYv+VpBmSCiRNknRiKec/RtIUoAjoLWmOpD9Jel7SeuDaqP1vo31FUV9HVdRXKq+zqxoNPnnyanvO1T7fjR3DhoJ8uu00gANPOatSfeR9+CGLrr4azOh45e9pd8bpVRyla+gk0XJQNPrkU/ec21a/BBYC+wF/BTKAH4CfArsC9wNPSto77pj/AG2Ag4CLgJu3JQBJ+wE3AZcCOwAnAl+X0/584Grgd8AuwF3Ac5L2SWj6V+DXUZtl0bY/AjnAbsBjks4A/gbcAOwOvAm8Jmm7JPpyNajBr5Y2s1F+bRfnag8z4+u3Xwdgr6OPq1QfBZMmseDyK2DTJtpf+As6/PKXVRmic5u1HDSI1S+8wPqPP6bDxRelOxznSnXfJR9YTZ/z0gcOS/XL1SQz+2vCtvjH90v6CXAK8KWk/oSRpt3M7BsASdcB/6tszEBPYAnwnpltBOYBE8ppfx1whZm9Hj2eLWkYcCEwMa7dNWY2LvYg+t75ppndH7ftWeBBM3s82vSnqK/LgN+X1ZereQ1+5Mk5V7vM/3YKKxfMo2W7bHbY/8CUjy9Zv56Ff7gKKyqizamn0PHKK6shSueClgcOhEaNyP/qK0rWr093OM7VZRMTN0i6XNJXklZKygOOAnpFu/sD+bHEKTJ+G2N4D9hESIIelnSSpFIHGiRlAdsDT0nKi92A04G+Cc1/9NxK2dafUOAi3sfR9or6cjWowY88Oedql9io0+7DjiajccpraFl62+1snD+fpv370/W66yq1Vsq5ZGW0aUPz3XajYNIk1k+YQKuhQ9MdknM/UolRoHTIj38g6SzgFuAKQsKQR5gWl/p/DFuUAImvxeb+zGytpD0JI1pHAvcAV0k6NBqJitcy+nkeMClhX0HC43x+rLRtyajsca6K+MiTc67WWLtiGTM/H0+jjAx2P/zolI/P+/BDVj//PGrShG633YYyq6Rgk3Pl2rLuKfGPxs65bTAIyDGzR83sa2A20C9u/zSghaRd4rYdUEGfy4GuCdt2j39gZhvNbLSZ/T6K4UDCuiQS2i0FFgN9zGxmwm1hEs8v0TTC2q14gwCvRlPLePLknKs1Jr83GrMSdhx4MFntslM6dtOqVSy69loAOv72CprttGN1hOjcj2wuWe5FI5yrSjOBAyUNjdY33Qd0i+00s2nAGEJlvr0kHUwotlCeHGCQpDMl7SjpdrZMA0TScZJ+I2kPSX0Io0oFwNwy+rsJuF7SRZL6RXFcIem0SjzfO4GLJQ2PYvsbsAdwbyX6ctXIkyfnXK2wacMGJr83GoA9j0qtUISZsWTEDRQvX0Hzffche/jwaojQudI13203GmVlseGHH9i4sDJ/cHbOleIBQsW5V4FxwGrglYQ25wHrCWudHgOuL69DM3uLUNHu7uiYTVH/MasJa5ZygG+BE4ATzWxlGf3dT5hWeHnU/m3Cuqyykq3yYnse+BMhAfwG+Alwgpn9kGpfrnr5mifnXK0w/dNxFKxbS6c+fem2Y+L62PKtff111r39No1atKDbrbeijIxqitK5H1OTJrQ8cCDr3n2PvI8/pt3pXhbfuVSY2ZBSthUC51Zw3ALgiITNitufQ8IaJzO7lui6SqX09xEwOJmY4455HHi8jH0/On+0vU8Z7e8irOtKui9X8xr8yJNf58m52iFWKGLPo49NqcjDxiVLNl8It/M1fyKzR49qic+58vi6J+ecaxgafPJkZqPSHYNzDd3imdNZMmsGzbJa0X/QoSkdu+yOf1Cybh1ZQ4fS5pRTqilC58q3OXn69FOsuDjN0TjnnKsuDT55cs6l39ejw6jTbocdSZPMpkkft3HJEta+9RZkZNDlL9d6WXKXNpk9e9KkVy9K1q6l8JtvKj7AOedcneTJk3MuraykhO/HhyplexxxTErHrnrqKSgupvVRR9KkW7eKD3CuGmVFVffyPvoozZE455yrLkknT5JaSeqQsO1nkm6S5FcFdM5VSkHeOjZt3ECzllm06dQl6eNK8vNZ9fwLAGSff351hedc0nzdk3PO1X+pjDz9F7gx9kDSdcCTwCXAu5K8vJBzLmUFa9cA0LxN25SOW/3qq5SsWUPzPfag+R57VENkzqWmxQEHQEYGBZMmUbxuXbrDcc45Vw1SSZ72A94BUFhYcClwi5l1AO4Brqr68Jxz9V3+mtUAtGjdOuljrKSEVU88CUD2cB91crVDRlYWzffcE4qLyZ84Md3hOOecqwapJE/ZwIro/j5AB8IFyQBeA3aqwriccw1EfjTy1KJ126SPyRs7lg1z5tC4W1daHZF4iQ/n0qdJ584AlOStT3MkzjnnqkMqydNSYEB0/1hgjpnNjh63JFyl2TnnUrI5eWrTJuljcv/zHwCyf3YOauzX+nbOOedczUgleXoeuF3SC8Afgf/E7dsLmFGVgW0LSf+TtFjSs+mOxTlXvvw10ZqnJEeeCqdPJ//T8ahFC9qedmo1Ruacc64mSGon6U1J6yWtTnc88ST1kWSS+qdwzNGSLO7xCEnjqyfCqiFppH9vTk4qf7L9E7COsPbpDuBvcfv2AV6owri21W+AvoRiFs65Wqxg7Wog+ZGn3CeeAKDtSSeRkcI6Keecc7XWJUA/wh/jV1fXSaIEZrSZjaiuc5ThDkJ9gNrsinQHUFcknTyZ2Sbgr2XsO6mqApJ0MvArQkLWDtjOzOYktLkS+C1h3dUnwCVmtnnky8zmS+pbVTE556pPbOQpmTVPm1auZO2o10Ei+7xzqzky55xzNaQv8JWZfV9WA0lNzGxjDcZUZcwsL90xVMTM1qQ7hkSSMs1sQynbU/4slNVXZaRynadiSfuXsW8fScVVERBh/dQ44M9lnOs84CbC1MH9gTXAm5Iyq+j8zrkalB8beUpiFGnVM89iGzaQNXQomb17V3NkzjnnqpukHOAXwOnR9LiR0XaTdJGkdyQVAOdI2lHS65KWSVor6UNJeyX0t52kVyStidrkSOoW9XsAcH3Ut0XtK+wziedwsKRvJBVGz6d3wv6tpu1FMf1T0oOS1kmaK+l4Sd2j57te0qeStkvo51eSZkgqkDRJ0olx+4ZEz2totG+9pA8k9YprM0zSREn5knIljZHUOtq31bQ9SR0kPRu9JuskPS+pU9z+kdH+v0haHr1+t0UVuct6nTIkXS9pXhTfeEmD4vYPl7RE0hmSZgIFCkr7LGRIullhmU6hpI8l7VtRX0m+peVKZc1TeSdsDFRJ8mRmT5rZX4ExZTS5HLjPzJ4xsynA+UAP4LiqOL9zrmZtHnlK4jpPeR98AEC7s86qzpCcc87VnJMJ6+r/B3Rl6+ljI4DHCQXL3gaygFeBoYQ/oE8DXpfUAkBSU8JldZoBhxOWmjxF+J56BfAl8I/oPF2jc5TbZ0Wi5OM14FPCtMOHKWOmVoILo3PtDbwOPAE8CvyLMPvKgLviznM+cDXwO2CXaN9zkvZJ6PevwK+BgUBr4O7o+MbAy4Trtg4ABlP+kpsngR2BI4DDgO0Ir2W8Y4D2wMHROX8PnFBOn9cS3u/zgd2jeN6W1COuTVvCDLQzgT3jto9g68/CHwjTPX9NeN2/B0ZLil8DUFZf26TcaXuSugDd4jbtJCmxql4z4OfA3KoKqpx4mhKe/LWxbWa2TtJnhA/Jy9Udg3Ouam2+SG7r8tc8WXExRbNmhbZ77F7tcTnnXH3xjzOOs4pbVa0rn3s9qb/ym1luNJpgZrYkYffjZvZM3ONFhAQICCMxhC/Gg4B3gbMJSz5Oi5sqNz2u/UYgL/48ZvZlBX1W5GygCPh1NJVsapTQ/K6C48ab2Z3ROW8kJAE5ZjYq2nYP8GBc++uAK8zs9ejxbEnDCElY/IXlrjazj6M+/gncH21vHd1eNrPYd/ZvSgtM0k7A0cBeZvZ1tO184FtJu5vZ5KjpUuB3ZmbAdEkXEZLQ/5XSZzPCrLFBsT4JhehOAH4G3BZtawr8Mn45TjRgtNVnQdJvgRvN7JXo8UXAHEJidk9ZfVWFitY8XQxcT8h+DRhZShsRRp1+XZWBlaE9kEF4s+ItAzpvDih84AYB3SW9B1xsZrMSO4te6Ivit+Xk5FRxyA1XXl6ev551UE2+byXFxRSuzwOJzyZ+GfsHslQZS5fSoaiI4nbtGPfll2W2a6j89612aLNsGc2AqVO/ozCrZYXt/X2rm/x9qzFbXW1aUivgRsKIRxfCd8IWQGxq2q7AF6msMUqiz4r0J6zXil+Dk0xlvSlx92Pfa79N2NZaYVlKJrA98JTiqvhF23MS+p0cd38x0EZhvU+upP8CUyS9TRihe9HMVpXxnArikhzM7DuFSoj9484xJUqc4s/XidL1JbyuHyX8X98U+C7u8boykp3Nn4VodKkLoe5BLL6NkiZE8VXU1zapKHkaSXhTBHwAXMrWTxBgA/C9ma2s6uAqy8wuT7LdQ8BD8R/EIUOGVFdYDU5OTo6/nnVQTb5vebkr+Qpo0boNQ4cOLbft2rffYSHQerdd2dU/Vz/iv2+1w8LXRrEW2HnnAbRJ4v3w961uqmvvW7KjQLVQfsLjO4BDgauA2UAhYbpck204R1X0WZmRvc3JlplZlFDEJ2CxPhsR6gEAnAdMSuinoKx+E/rAzM6N1gUdQxgguVnSAWb2QyXiTzxX7HxlLQnKin4eDqxI2Lc27n7ie17R9vJU5pgKlZs8RcN6cwEkDQW+NLN11RFIklYSRrk6J2zvBEyoTIeSjt/WoJxzlbPlArltK2xbNCP88ajZjjtWZ0jOOedqr0HAI2b2GkC0VqZ93P5vgPMlZZUx+rSBMLKUSp8VmUYodtE4qkwNoTBFlTGzpZIWA33M7KVt7OsL4AtJNxGu0XoS8M+EZtOA5pL2jJu2N4CwhmhqJU89lfD6dzezbbrmlZmtkbQEOIjo+7+kJoQ1breVd2xVSLpghJl9GEucJHWS1CvxVn1hbo6hCPgaGBbbJimL8CGt1BsRm1vqnKt5+WtWA8lV2iv6PlSwberJk3PONVQzgVMl7RaNoDxJGCmKeZowivG8pP0k7SDpgrjvqHOAQZJ6SuqQZJ8VeQZoDtwnqb+kswlreKraTYRKgRdJ6idpL0lXSDotmYMVqhDeImmgpN7AiYS6BtMS25rZdOAt4DFJ+0vaD/gP8F5UrC1lZraWULziXklnSto+6vtaSYdWoss7gb9IOlHSzsBDhDoMT1QmvlSkUqq8vaSnJRUS5jT+EHebE/3cZpKyJe3JljmLAyTtGSVJEBaBXRq98LsSphYuJFQqqcz5fOTJuTTZUiyibYVtNydPO+xQnSE555yrvX5PKM4wAXiOUFBhWWxn9Ef2IwmzlMYQ1smcy5bpZbcCrQgjLsuT6bMi0fWRTiRUnPuaUAHu+ko8t4rOcz+hYuDlhLVRbwNHkXzBtnxCpbpXCUU0/g78yczeLKP9+YQKdu8Rlu78wLYnhVcTRrluIiRtrxIKwS2qRF//AB6Ibl8TKgMeXRPXq0r6IrnAI4Q5oX8jrHuqkgtNleIEQinCmDein0MJVUieUKgzfwdbLpJ7TGUvfGVmo6qo7LtzLkVbpu2VX2mvpLCQDfPmQUYGmX39+tfOOVefmNnwUrb96MuZmc0mfBeN92xCm5lAqX8YN7PvCFO7ku7TzOZQ/uV6MLOxhPLh8R6M2z+CUGo79nhIKX0o4XFO4nnN7HG2/o5cUfv4bYXAT8t5DsMTHi8nVB1Mqn1Z2xL2lxCStr+XsX8kpRSnK+OzUEy4Jmyp14Utq6+qkEryNBS43MyqdTgsmSdrZncQkifnXB22Zdpe23LbFc2aBSUlZPbtS6NMvx62c84559IjlYvkrubH1THqPJ+251z6JDvyVPR9KBbRdEefsuecc8659EkleboduCy6QnG94QUjnEufpEeefL2Tc84552qBVBKhnQkLzWZJ+pAwEhXPzOyKqgrMOVf/5W8uGFHByJOXKXfOOedcLZBK8nQcUBLdP6SU/UaoAlKn+LQ959KnIOlpe16m3DnnnHPpl3TyZGbbVWcg6eLV9pxLn/w1UfJUzrS94tWr2bRsGWrenCY9etRQZM4555xzP5bKmifnnKsyGwsL2VhUSEaTJmQ2b15mu9iUvab9+qFG/k+Wc84559InpW8ikjpIulXS+5K+l7RLtP0KSQOrJ0TnXH20udJe67aUN/pbuHnKnheLcM4551x6JZ08SdqbcEXmM4EFQF+gabS7O/C7Ko+uBviaJ+fSI3/tagCat25dbrtYmXIvFuGcc865dEtl5OlO4FNgB+AXbH0V48+AOjny5KXKnUuPzeud2rQtt52XKXfOOVefRLO4cuIe50i6NY0huRSkUm1vP+BkM9soKSNh33KgU9WF5Zyr7zZX2iunTLmZbVnz5CNPzjnnqoGkJcDVZjYyTSGcDGxI07ldilJJntYDZc2v6QWs3PZwnHMNxeY1T+WMPG1avJiSvDwysrNp3KFDDUXmnHOuvpCUaWZVnphEAwlmZiUVNq6AmeVWQUiuhqQybe9t4FpJ7eO2maTmhOs7vVmlkdUQX/PkXHrkr1kNlD/yVOhT9pxzrl6TdJKkRXGPT5Rkkn4Wt22GpLOi+y0kPSBppaR8SaMl9YtrO0LSeEmXS5oPfB9tv0zSbElFkhZLuj/angN0Bh6PzjunjDiHRPuPkTQFKAJ6SzpW0ieS1khaKulpSR0Tjr1E0iJJeZIeZUvNgNj+zdP2JPWJztM/bv9W26LHb0haHfX5taQDUn/1XWWkkjz9H2HkaQbwPOGiuDcB3wHtgWurPLoa4GuenEuPZEaefMqec87Ve+OALpJifyU7lDCbaTCApG5AP2BstP8fwFHA6YT19iXAqIQlJbsCQ4BjgGMl7Uf4znopYe3+icDXUduTCctPfgt0JSxTKc9fgV8DuwDLgObAbcDewPGE2VgPxxpLOhi4F7gF2AdYAlxYwTkqch+QS3j+ewE349P+akwqF8ldKGlPQlW9I4BZhKTpKeCfPuTonEtFbOSpvGp7sUp7XqbcOecqb8HV46ymz9nj1kPKvgZFHDNbIWkqIVmaEf28C4iNPA0Gfoi+h2YRipadbmbvA0g6F5gPHAu8Fh0j4AIzWxO1OZmQtLxnZhuBecCE6Py5kkqANWa2JImQrzGzcXGPX4y7P0vSb4EJkpqaWRHwG+BVM7s3avNnScck89qUoyfwvJlNix7P2Mb+XApSus6Tma02s+vN7CAz29HMBprZtZ44OedSVbB2LRCu81SWWKW9Zj5tzznn6rOxwGBJrQgjOvcCPaLpb4PZMurUF2gCfBI70MxWAtOB/nH9zYolTpH3gE3AbEkPR1MFU1n3H29i/ANJO0p6QdIcSeuADwnJW4+oSX+iRC3O+EqeO+Ze4CFJ70m6WlLfbezPpaCyHxznnNsmses8tWhT+pon27iRDbNnA5DZz5Mn55yrrGRHgdJoLGFa2yBgspmtlvQZIXEaTLhcTiry4x+Y2dpo9tQw4EjgHuAqSYdGI1GV7hsYRUjehhNGt3oR6gQ0iQ8hhf5jBSji37P4vjCzhyS9AxwHHA2MkHSWmb2SwnlcJZWbPEmaDJxtZt9Ei+PKe/PNzPao0uicc/WSmW2+zlPzMgpGbJg7F9u4kSY9epCR1bImw3POOVezxgJ9gLPZMso0FjgJGBC3bRawETgIeBUgKmS2EzC1vBNESdJoYLSku4C5wG7Al4T1QomX4amQpA7AjsDPzOyLaNs+Cc2mAfsnbDsAWFdGt8ujn13Z8px+9P3azOYQRqDulfQYcAHgyVMNqGjkaSKhRHnsfo3Pma1uXm3PuZpXlL+ekuJNZDZvTpPMpqW3iVXa82IRzjlXr0XrmWYTkqeTos3jgOuApWY2I2qXJ+kR4E5JawmJxm2ERKjMqs+SjiMkZ+OANcA5QEF0HMAcYKikN4FCM1uVZOi50e0iSasIU/QSC6jdD7wv6deE6YPnEhKuiZTCzAokTQCuiaoQdk/sU9Kd0fOdSagUeCBhBMzVgHKTJzO7IO7+8GqPJg3MbJRU20eznatfYqNO5a138jLlrk6zeve3Rueq21jgPOCj6PF4oJiQ8MT7A2HN/gtAi+i4482suJy+VxOq890IZALfAidG66UgJCf/JiRTiwiJVoXMrETS2cDdUeyTgKuJRsWiNmOjIhJ/AW4nFJh4hFAlryw/Bx4FvgK+iY59LW5/E+BBoBuwijDidH0yMbtt52uenHM1LrbeqdxKezNmAl5pz9Ux/sc45yol+oN9/B/tC0i4HlK0PR+4JLqV1s8IYETCto+ISp+XccxYQqGK8uLLYet1SLHtb7N1sQoS25nZfYTy4mX1PSTh8beEMuSl9mlmvykvVle9kq62J+kxSc+Vse9ZSQ9VXVjOufqsIIlrPMWKRTT1YhHOOeecqyVSKVV+BPByGfteIlywzDnnKrRl2l7pxSIAbEO43l+jli1qJCbnnHPOuYqkkjx1ZEsFkEQrCQvWnHOuQlvKlLdNaxzOOeecc6lIJXlaSCitWJoDgMXbHo5zriFIZuTJOeecc662SSV5egb4s6TT4zdKOg24Bni6KgNzztVf+dGap+Y+8uScc865OiSVant/BfYEnpX0KGGkqSuhTORbwA1VHp1zrl7aXDCilY88Oeecc67uSDp5MrMNwHGSjgAOA9oT1jq9Z2bvV1N81c4vkutczctfsxqAFm08eXLOOedc3ZHydZ7M7F3g3WqIJS38IrnO1bz8JEqVO+ecc87VNuUmT5KygdXRFZSzK+rMzHKrLDLnXL1UUlJMwbq1ADRvVfZFcp1zzjnnapuKRp5WEK5wPCG6bxW0z6iKoJxz9VfhunVgRrNWrWmU4f9kOOecc67uqCh5ugCYFXffOee2yeb1Tj7q5JxzrhaQtAS42sxGltPmaOAtM6vStR6SxgOjzWxEVfbrqk9FydMewAeEwhA/AF+aWV61R+Wcq7fy14Ype77eyTnnXHWTlBkVPavXGsrzrA0qus7T5YRy5ABjgAHVG45zrr7LX7sa8AvkOuecA0knSVoU9/hESSbpZ3HbZkg6K7rfQtIDklZKypc0WlK/uLYjJI2XdLmk+cD30fbLJM2WVCRpsaT7o+05QGfg8ei8c0qJsQ/hsjxEbUzSiOhxc0l3S1oiaa2k9yUNiPZ1kbRC0sVxfZ0raY2kXpJGAgcA18f6jX8OCTFstU1SjqQ7JT0oaTXwcLR9SPT8C6Ln+2dJPke+ClU08rSM8KZOAETFa56cc65c+Wv8ArnOOVeTRowYUePf30aMGJHs9LZxQBdJO5jZDOBQwoynwcBTkroB/YCxUft/AEcBpwPLgVuBUZJ2NbPiqM2uwBDgGMAk7QfcBJwJfAt0IVy7FOBkYBpwM/AcEOsj3nzgbOBptgwqxGZi3Q/0Bn4axf1r4F1JO5nZEkm/Ah6T9C6wEfgXcIWZzZN0BbAbYYDijiRfr3i/BG4H9gNKJO0AjAKuIlTG3h54BMgH7qxE/64UFSVP/wXulnQXIXEaX15ZbzOrFZmtpNOB3xESvnvM7Ok0h+ScixT4yJNzzrmIma2QNJWQLM2Ift4FxEaeBgM/mNlCSVnAL4DTY9cYlXQuIbk5FngtOkbABWa2JmpzMrCEcG3SjcA8wsAAZpYrqQRYY2ZLyoixWNKq6P7mNpJ6A+cAXcxsZbTt98ApUTzPmdkLkk4CngCKgDGxtVVmtkbSRiCvrHNXYJKZ/TUunkeBR83sgWjTLEk3AlfiyVOVKTd5MrM/Snob2Bm4h/BhnlsDcVWapDbADYQs3IAJkkZ7GXXnaofYyJOveXLOuZqRwihQuowFBkt6HtgFOBz4P0kdCclTbNSpL9AE+CR2oJmtlDQd6M+W5GlWLHGKvAfcCMyWNBp4ExhlZpu2Me5dCZWm5yYMLjSPYo25lDB9UFTtEpiJCY93B3aTdGHctgy8GnaVqug6T7sDH5vZ+5JOAR4ys2nVGVD014FfAfsA7YDtzGxOQpsrgd8CHQi/QJdEQ70Qphl+EitsIWksMIgwjOmcS7Mta5682p5zzjkgJEe3EL6vTTaz1ZI+IyROg0l91CQ//oGZrZW0JzAMOJIwIHCVpEOjkajKyiKMJu1Zyr74P9oPANoAJYT1Vcsq6LeEkGjFa1JKu/yEx1mE5/ZQBf27bVBRwYivCHMxIcznbFq94QDQkjD/9c+l7ZR0HmHe6h+B/YE1wJuSMqMm7YFVcYfkEpIs51wtsLnaXuu26Q3EOedcbTEW6ENYVzQ2bttJhMQjtm0WYd3QQbEDJbUHdgKmlncCM9toZqPN7PeEJO1AtnzH3UDFozMbovPFt/saaAa0MbOZCbfcqH1L4D+EtVojgSckNUnoN/Hcy9mytipmjwrii8WzcymxzEziWJekipKn9YRMGcKHOrPsplXDzJ6M5m+OKaPJ5cB9ZvaMmU0Bzgd6AMdF+3MJI1Yx7QgX+HXO1QKxNU/N2/iaJ+ecc2BmC4HZbJ08jSMUeFgam10UzSp6BLhT0mGSdgOeJCwpebOs/iUdJ+k3kvaIKuedBxSwZSnKHGCopK6S2pXRzZzo5/GSOkhqYWbTgReAZyQdK2k7SYMk3Sapf9T+74QRousJa49aRffj+x0kqaek2B/7PwR6SPqtpH7ROqqDy3p+cW4HjpB0u6RdJe0s6SxJ1yRxrEtSRcnT58CDUSlFgOskPVbG7dHqDRUkNSUMjb4X22Zm64DPgIHRpvHAQIVSls0Jw72f4JyrFXzNk3POuVKMJUxV+yh6PJ5Q+W5cQrs/AG8TkpYJhFGb4+Mq7ZVmNaE6Xw6h2t4JwImxIg/AtcBehGTqq9I6MLPZhKmFDxJGhv4Y7ToXeBl4gFC172lCNb9cSUcQClycZ2YbzGw94Y/+V0k6IDr+VkJCNSPqFzP7DriMkGx9RVjP9e9ynl8sxq+Awwjr/icQXsMrqOX1CuoamZVdvTLKzm8kvGl7AzP58fzKGDOzvasssJCxTyVuzVNUrnIhsHf0AYm1fR4oMLPzo8dnEtZEGWGU6r9lnOMi4CLC+ioAxowpa8DLpSovL4+srKx0h+FSVJ3vW0nxJr566C5o1Ii9L/od5VXv7PDna8lYuZLlN91ISQefeVsR/32rHVo/+ijNP/+CNT+/gML996+wvb9vdVO637ehQ4duvm9mtb0YhHP1SkXV9uYQMmqiMo7nmtmEGohrm5jZs8CzSbR7CHgodlEygCFDhlRjZA1LTk6Ov551UHW+b3m5K/kKaNGq9Vb/+ZdmZrNmbAQGDhxIZo8e1RJPfeK/b7XDwlGvsxbYeecBtEni/fD3rW7y9825hquiaXvxtiMsREunlYQh3M4J2zsBSyvToaTjtzUo51xySkrCrIqMxqUVDXLOOeecq92STp7MbK6ZbZB0tKS/SHpIUi8ASYOjKXXVysyKCAncsNi26IJpBxDmdVamTy9h7pxzzjnnnKtQudP24kUXKnuVUJhhPtCTsDhuHvBzQmW+S7c1IEnZQC9CdT+AAZLaAjOjKiv3AA9Imgh8A4wgrIN6fVvP7ZxzzjnnnHNlSTp5Au4COhKupjyDqN595D1CpZKqcALweNzjN6KfQ4EcM3tCUifgDrZcJPcYM9tAJfi0Peecc84551wyUkmejgV+aWZTEy4QBmEkqkpWdJvZSMJFxMprcwcheaqK840qr+KXc84555xzzkFqBSMaE6bmlaYdW49E1Rk+8uScc84555xLRirJ02eEtU2lORP4eNvDqXleMMI555xzzjmXjFSm7V0LjJE0FniRcAHan0r6E2FK38HVEJ9zzjnnnHP1lqSRQDMzOzPdsbiKpVKq/FNC0QYD/gEI+DPQFRhmZl9WS4TVzKftOeecc841XJKWSBqexhCuAC6uzhNIukTSnOo8R0ORyshTLIE6VFJzwjqn1WaWXy2R1RAvGOGcc845Vz9JyqxsRebqFhVgMzNbk+5YklWbX8+aksqap0QW3Zxzzjm3Ff/v0blkSDpJ0qK4xydKMkk/i9s2Q9JZ0f0Wkh6QtFJSvqTRkvrFtR0habykyyXNB76Ptl8mabakIkmLJd0fbc8BOgOPR+edU0acQ6L9x0qaKqkwOnfXhHa/iuItkDRJ0oml9HGMpClAEdBb0khJz8a1myPpakkvRM9xqqSBkgZI+lRSnqS3JLWPOyZD0vWS5klaH70Gg2LnBf4dncui2/BoX3tJ/5GUG91ekdQjrt+Rkp6TdLOkZcC7Sb2x9VhKyZOk4yR9DqwDFgDrJH0u6SfVEp1zzjlXl/hMBudSNQ7oImmH6PGhwEpgMICkbkA/YGy0/x/AUcDpwECgBBiVcBmdXYEhwDHAsZL2A24CLgV2AE4Evo7angwsB35LWIqyXwXx3ghcBBwEZBN3bVJJ5wNXA78DdiFcI/U5Sfsk9PFX4NdRm2VlnOdKYBSwJzANeBL4F/AnQp2BfsB1ce2vjZ7L+cDuwMvA21Ei9Anwf4Tv7l2j23PRcS8AzYHDgEFAIfCapPgc4djouQ6OnnuDlvS0PUk/BV4CxgO/B5YCXYDTCC/yKWb2v+oIsjr5mifnnHPO1Wfvf9C3xodChx02K6m/JJjZCklTCV/MZ0Q/7wJiI0+DgR/MbKGkLOAXwOlm9j6ApHMJ1xs9FngtOkbABbHpcJJOBpYA75nZRmAeMCE6f66kEmCNmS1JIuTrzGxc1O+FwCRJO5nZdEIyc4WZvR61nS1pGHAhMDGuj2tifUT9lHaeV8zsiWj/bcCnwF/MLCfa9igQG41rBvwRGGRmX0fH3y7pBOBnZnabpLVAcfxzlHQIsBvQLXpdkPRzYA0hifwsaroS+I2ZFSfx+tR7qYw8XQ88Y2aDzOweM3vOzO42s4OBZ4ER1RJhNfNS5c4555xzaTUWGCypFWE05l6gh6SOhOQpNurUF2hCGEkBwMxWAtOB/nH9zUpYR/QesImQzDwcTRVMad1/nAlx554MFAD9o8Rue+CpaFpdnqQ8wghZ34Q+JlKxKXH3l0Y/v03Y1jG63xdoAXyUcO4DSjl3vN0JI0qr4o5ZThhciT9ukidOW6TywelPGPIrzZPAq9scjXPOOeecq1LJjgKl0VjgFsK0sclmtlrSZ4TEaTBwZ4r9bVXMzMzWStoTGAYcCdwDXCXp0NiISwrKGsVrGf08D5iUsK+gvPjKEB+XlbEtNgiSFf08HFiR0M/acs6RBcwhTINMtDTufp0uDlfVUkmecoGdgHdK2bdTtN8555xzzrlUjAX6AGezZZRpLHASMCBu2yxCAnEQ0R/to6IJOwFTyztBlCSNBkZLuguYS5iy9iWwAcgo++it7A+8EZ17N8J6oWlmtlTSYqCPmb2UZF9VZSrhOXQ3s/FltCntOX4N9ADWm9ni6guvfkkleXoOuEVSAfBi9FeBNoQ1TzcBD1dHgM4555xzrv6K1jPNJiRPJ0WbxxHWEC01sxlRuzxJjwB3Rmt4lgO3ERKhN8vqX9JxhORsHGE9zzmE0aC5UZM5wFBJbwKFZraqnHBvkLQ6Ov5+4N1ovROE78O3SloHfAC0IoycLTKzF5J7NVIXjazdDdwrqQlhamEHwijbODP7kPAcu0g6gJCEriNUzvsKeFXS1VGbPoTv9teY2erqirkuS2XN058Io04PASslFRJGmx6Ktl9T9eFVPy8Y4ZxzzjmXdmMJhR4+ih6PB4oJCU+8PwBvE6rETSCMphxfwZqc1YS1RzmEdUMnACdG66UgVKrbi5BMfVVBnDcQKux9SpgSNzy2w8zuJ1zw9vLoPG8TpsTN/VEvVe9q4J+EBG4aYWRuTyBWBn4MYZnNW4Sk8ywzKwGOJjznZ6PjHonaF9ZAzHVS0iNPZlYEnBINUR5CuEhuLvCRmU0p9+BazC+S65xzzjmXXmZ2AXBB3OMCoGkp7fKBS6Jbaf2MIKGImZl9RFT6vIxjxhIKVSTjXTPbsZy+HieufHnCvhxCgpi4fXjC4z4Jj+ckHmdmI4GRcY9LgL9Ht9LObcDPo1v89tWU/3oOL217Q1buyJOkHSRNjL+Ok5lNMbP7zexmM/s3oRrKREnbV3u0zjnnnHPOOZcmFU3buxLIM7My55Ga2VuEYcs/VGVgzrkGzmr8siTOOeecc+WqKHk6EngsiX4eo/Qyh845t418Wq1zzrn0MrMcM5OZ+VqgBq6i5Kk7oSJHRX6I2jrnnHPOOedcvVRR8pTHlqsXl6cDsH7bw6l5Xm3POeecc845l4yKkqcvgDOS6OfMqG2dY2aj0h2Dc84555xzrvarqFT5fYQLZ00FbkqsoS+pEaE2/mnAT6slQuecc84555yrBcpNnszsNUm3A9cDF0t6H5gHGNALGAZ0Af7uIzjOOeecc865+qzCi+Sa2dWSxhLKlp/KlguWFQIfAxdG5cqdc84555xzrt6qMHkCiK7z9KakDKB9tHll4jQ+55xzzjnnnKuvKioYsRUzKzazZdHNEyfnnHPOOVenSVoiaXi643B1Q0rJk3POOeecc3WFpMw0nrtJus7tqk+DT578Ok/OOeecc+kh6SRJi+IenyjJJP0sbtsMSWdF91tIekDSSkn5kkZL6hfXdoSk8ZIulzQf+D7afpmk2ZKKJC2WdH+0PQfoDDwenXdOGXF2lPS8pEWS1kv6QtKwhDYm6SJJ70gqAM6Jtv8qeg4FkiZJOjGVfl3t0uCTJ68S6JxzzjmXNuOALpJ2iB4fCqwEBgNI6gb0A8ZG+/8BHAWcDgwESoBR0br8mF2BIcAxwLGS9gNuAi4FdgBOBL6O2p4MLAd+C3QF9isjzubAJ1GfewCvA69F8cUbATwODADelnQ+cDXwO2AX4C7gOUn7pNivqyWSKhjhnHPOOefqpi5jvraaPueSoXsqmXZmtiK6nuhgYEb08y4gNvI0GPjBzBZKygJ+AZxuZu8DSDoXmA8cC7wWHSPgAjNbE7U5GVgCvGdmGwmX3ZkQnT9XUgmwxsyWlBPnvCiumBGSTo3O+3Dc9sfN7JnYA0nXAVeY2evRptnRyNKFwMQU+nW1RIMfeXLOOeecc2k1FhgsqRVhdOZeoIekjoTkKTbq1BdoQhipAcDMVgLTgf5x/c2KJU6R94BNhMTl4WiqYEoDCJIaS7pB0reSVknKA3YmXPc03sS4Y7KA7YGnJOXFboRRs74p9utqCR95cs4555yrx5IdBUqjscAtwCBgspmtlvQZIXEaDNyZYn/58Q/MbK2kPYFhwJHAPcBVkg6NRqKScRVwMXAFMDU6x4uEZK6sc7eMfp4HTEpoV5Biv66W8OTJOVdzanziiHPOuTpgLNAHOJsto0xjgZMIa4di22YBG4GDgFcBJLUHdiIkHmWKkqTRwGhJdwFzgd2AL4ENQEbZRwMhsXvRzJ6LztsS6F3BOZdKWgz0MbOXqqpfl16ePDnnal5t/xuoc865GhOtZ5pNSJ5OijaPA64DlprZjKhdnqRHgDslrSUUeriNkAi9WVb/ko4jJGfjgDWEKngF0XEAc4Chkt4ECs1sVSndzASOk7R/dOwNVJxwQShUcaukdcAHQCvCaNoiM3thG/p1aeJrnpxzzjnnXLqNJfxp7aPo8XigmJDwxPsD8DbwAqHoQwZwvJkVl9P3asI6oxzgW+AE4MRovRTAtcBehGTqqzL6uIkwuvUBYQTrQ8KoVbnM7H7ClLzLo3O/TagWGEvcKtWvSx8feXLOOeecc2llZhcAF8Q9LgCaltIuH7gkupXWzwhCufD4bR8RlT4v45ixhEIV5cW3Aki8NujdCW1KnVdhZo8TypdXql9Xu9TLkSdJ/4sugPZsumNxzjnnnHPO1Q/1MnkCfgOcle4gnHPOOeecc/VHjSdPkk6W9K6kXEkmqU8pba6UNF9SgaT34646nRQzm19lATvnnHPOOecc6Rl5aklY/Pfn0nZKOo+weO6PwP6EqihvSsqssQidc84555xzLkGNF4wwsycBJPUvo8nlwH1m9kzU7nxgGXAc8HK0bXwpx+Wb2WFVH7FzzjmXIvOLmjnnXH1Uq6rtSWoK7EkoGQmAma2LrjI9kCh5MrOBVXS+i4CL4rfl5ORURdcOyMvL89ezDqrO961o3Zrws7CwwnN0KCwkAxg/fjwlHdpXSzz1if++1Q6tly2jOTB16lQKW7eusL2/b3WTv2/ONVy1KnkC2hPq9S9N2L4M6JxsJ5LuIVyxubuk94CLzWxWYjszewh4SNLmPxEOGTKkEmG70uTk5PjrWQdV5/u2dvkyvvnvwzRt1qzCc8xs1oyNwMCBA8ns0b1a4qlP/Petdlj4xpusBXbeeWfaJPF++PtWN/n75lzDVduSpyphZpcn21ZSYm1955xzzjnnnPuR2laqfCXhatKJo0yd+PFoVJUws1HV0a9zzjnnnHOufqlVI09mViTpa2AYMBpAUhZwAHBPGkNzzjnnXNE6mPo6FBdBszbQtDU0awvNWkObntCkWbojdK5BkzQEGAM0N7PC9EZTP9V48iQpG+gF9Ik2DZDUFphpZnmEJOkBSROBb4ARwELg9WqKx6ftOeecc+VZuxg+ewC+eByK1pTeJiMTuu0NvQZCrwOh5/7QIrtm43SuEiQtAa42s5HpjiUVkp4FCs1seLpjaUjSMfJ0AvB43OM3op9DgRwze0JSJ+AOoAPwCXCMmW2ojmDMbJSk6ujaOeecq9uWTYNP/gWTn4OSjWFbz4HQoR8UroXCNVC0FgpWwaq5MH98uH18V2jbaQD0HgR9BkHvgyGrY9qeimuYJGVW13dI1zDV+JonMxtpZirllhPX5g4z62FmzczsMDObUdNxOueccw3W6vnw0i/h/gPg6/9CySbY+QT4xXvwi7fhxPvgjCfh/Nfgohy4YhL83w9w9gtw8O+h10GQ0RSWfQefPwwvDIc7+sG9+8MbV8L0t6AoL93P0tUCkk6StCju8YmSTNLP4rbNkHRWdL+FpAckrZSUL2m0pH5xbUdIGi/pcknzge+j7ZdJmi2pSNJiSfdH23MIa+0fj847p4w4syU9G3feqbHZS5KGRMceJenbaP+LkppL+pWkhZKWS/pTQp97SxonqVDSEkm3SsqI298hOudaSeskPR8NMCBpBHAGcH50bpPUJ677AyVNkrRe0geSesX1OzLq9y9RXMsk3aa40QRJ7SX9R1JudHtFUo+4/cMkTYyea66kMZJaV7SvPqhVa57SwaftOeecc5HCtfDRnTD+fthUGKbi7XUuHHgptO9b/rHN28GOR4YbwKYiWDgR5nwMc8bB/AmwYnq4ff5I6LvXgdDvcNjhCOjYH3wmSEM0DugiaYfoj+WHEgqIDQaektQN6AeMjdr/AzgKOB1YDtwKjJK0q5kVR212BYYAxwAmaT/gJuBM4FugC+G6ogAnA9OAm4HnCIXLSnMjkE2YKZUHDADWJ7S5BhgONAVeBV4jLD0ZRrhe6eOSRpvZV9Ga/tHA28DFQF/gMWBdFAvAk4TE7gigBLgfeCp6fEf0HIqAK6L2y9myLOavwK+BtYQZX3cDJ8XFegywBDgY2A14hjDb63/R/heAFcBh0TmuA16TtC9h8OVlwtKaV4AswvuFpMZl7asvGnzy5NP2nHPONXjFm+CrJ2DMLbB+edi2y8lw+PXQrk/l+mzcFHofFG6HXgWbNsCiL2F2Dsx8DxZ8AT98GG7v/gXa9oadfgI7HROOyWhSVc+uwetz9RtWcauqNefWY5P6cmVmKyRNJXzBnhH9vAuIjTwNBn4ws4VRwvEL4HQzex9A0rnAfOBYQrICIOACM1sTtTmZkCi8Z2YbgXnAhOj8uZJKgDVmtqScUHsCH5vZ5Ojx7FLa/MnMPo/O+SIhWTs+KtwwTdLVhKTuq+j5GXChmRUB30m6npCk3SxpJ+BoYC8z+zrq83zgW0m7m9lkSYWENU+b4477Tnu1mX0cbfsnIfGKtxT4nZkZMF3SRYTE8H+SDiEkVN2i1wtJPwfWAPsR3qfWwMtmNjfq75uoXXZZ++qLBp88Oeeccw3aoq9h1OWweFJ43GN/OOoW6Llf1Z6ncWZUTGIgDLka8nNh1gchkZrxLqyeC5/9O9yatoEdj4Kh10D2dlUbh6uNxgKDJT0P7AIcDvyfpI6E5Ck26tQXaEIYIQHAzFZKmg70Z0vyNCuWOEXeIyQlsyWNBt4ERpnZphRifAh4XtKRUX8vxSVSMVPi7i+N4ihM2BZb+NcfmBglTjEfA9nR1Lz+QEEscYqe63eSVkf7Es+dKH7/YqBNwvqvKVHiFN+mU3R/d8Io26qEAYbGQF8z+0zSf4Epkt4G3gFeNLNVUTJa6r4K4q0zGnzy5NP2nHPONUhFeZDztzBFz0qgdQ846iYY8NOamT7XIht2OzXcSorDFL/pb4b1UMunwZTnYeooOOzPcMCvIKPBf2WptGRHgdJoLHALMAiYbGarJX1GSJwGA3em2F9+/AMzWytpT8L0uSMJlZ2vknRobGSlImb2uqTtgOOiPiZIusrM/hXXLL4vS3gc21ZT9QYSYyHh3OXFlgXMIUyPTLQUwMzOjabwHUOYdnizpAPM7Ify9m3LE6otattFcmucXyTXOedcg/P923D/QPj03vB44KVw6Wewy0npWXfUKCOUNj98RIjjsi9ht9NgUwG8cy08ejgsmVJhN67OGktYq3M2W0aZxhLW6AyI2zaL8KX/oNiBktoDOwFTyzuBmW00s9Fm9ntCknYgYWoawAYgo8yDt/Sx1MweNbMzCMneL5N5cmWYBuwjqWnctkFArpkti/Y3j5I+ACQNANqy5bkmFXclfA30ANab2cyE27pYIzP7wsxuJEzlW0vcmqry9tV1DT55cs455xqMDevhlV/B06fDmvnQZXf45Qdw9C3QNCvd0W3Rvi+c8gic/XwYEVv0FTx4KLx3A2z0637WN2a2kLCGKD55GkdYM7Q0VnU5uh7oI8Cdkg6TtBuhqMJcwlS8Ukk6TtJvJO0RVaQ7DyiIjoMwyjJUUldJ7cro4wZJx0vqGyU0RxASnMp6irA262FJO0czoW4A/hk91+nAW8BjkvaPil78h7BuK/aXhDmEBGz7qDJfVX2vf5ewLutVSUMlbRf9vF9S2+jxLZIGSuoNnAh0I6zrKnNfFcWWdp48Oeeccw3B8unw8DCY9DQ0bg5H3gy/HAPd9kp3ZGXb8Si4dDzsf1GYWvjRP+GBg2HeZ+mOzFW9sYRk4qPo8XhC5btxCe3+QKhQ9wKh6EMGoShDWVXyAFYTqvPlEKrtnQCcaGYro/3XAnsRkqmvyuhjI/B3QvGDdwlFJy5N6pmVIkoEjwa2j875CPAooXpgzPmEUuvvAR8AP7ClkAbAvwnT6KYQKu31ogqYWUkU21fAs4TE55FodyFhWuQAQkXB6YTX5U9m9mYF++qFBj+B2Nc8Oeecq/cmvwCjroCN66H9DnD6E9B5QLqjSk7TVvCTv8Oup8Jrv4EV38NjR8EBl8Cwv0Bmy3RH6KqAmV0AXBD3uIBQ8juxXT5wSXQrrZ8RhDLZ8ds+opxy2WY2llCoorz4biKUOy9tXw4h8asojiEJj78klAov65zLCaNvZe1fTKiQF29OKbFsFZ+ZDS+lr+EJj1dT9utcCPy0jJiWlrWvvmjwI0++5sk551y9tbEQRv0WXr4wJE67nRYualtXEqd4vQ6Ai8fBIVeCGoWqfP8+CGZ/mO7InHMNSINPnpxztZNR45clca5+Kd4U1jZNfBwymsJxd8HJD9eutU2patIMhl0X1ml13g1WzYEnToA3/+hroZxzNcKTJ+dcrebXsHauksbcHC5A27ITXPgu7HtB/fmF6rYnXDQGhl4LjZrAhAfhkcNh+ffpjsw5V881+OTJ1zw555yrd6aPDsUVlAGnPQ5d90h3RFUvowkcehX84h3I3h6WToGHDoUvnwDzkWvnXPVo8MmTr3lyzjlXr6yaA69cFO4Puw76lLkevX7ovjdcPBZ2PwM25sNrl8GLP4fCNemOzDlXDzX45Mk555yrNzYWwvPnhcRhp5/AQZenO6Ka0bQVnPwQnPQgNGkJ374MDw2FZfXm0jLOuVrCkyfnnHOuvnj7T7B4ErTtDT+9Hxo1sP/m9zgTLhkXiknkzoJHhsHU19MdlXOuHmlg/6o655xz9dSk5+CLx0JlvdOfgObt0h1RerTvC794G3Y5GTbkwXM/gzG3QElJuiNzztUDnjw555xzdV3BanjzqnD/J7eHanQNWWZLOPUxOOKv4ZpQH94Gz57t66Ccc9uswSdPXm3POedcnffZA1C0BvocAnufn+5oagcJBl0BP3sRmrWF79+CR4+ENQvSHZlzNU7ScElL0h1HfdDgkyevtuecc65OK1gNn94f7g+5uv5cy6mq9BsWrgnVYSdYPg0eOQKWTU13VK4WkbRE0vB0x1HNngN2iz2Q9KykkekLp+5q8MmTc67mmF97xbmq99mDW0ad6ntZ8srK3h5+Php6HQjrFsFjR8HcT9IdlasBkjLTHUNtYGYFZrY83XHUB548OedqnPwv485VjcI1MP6+cP/Q/0tvLLVdi2w49xXof1x43Z74KUz1ySfpJukkSYviHp8oyST9LG7bDElnRfdbSHpA0kpJ+ZJGS+oX13aEpPGSLpc0H/g+2n6ZpNmSiiQtlnR/tD0H6Aw8Hp13Tjmx7iXpPUnrJa2S9Mb/t3fn8VbV9f7HX28BGRwTUcQhBAdQnDIVUhHMIa+aSjcb/OXQYN3StNIGMy+ZXa2rWd0yr1pgXnPIMqVMU+sEDiiUxiAooDigDIIgIIfx8/vj+92yPexzzkbOOesM7+fjcR7nrLW+67s+e20P7s/5fr+fJalbPrZ9Hs15U9JSSXdK2qHs3NH5+HckLZA0X9IPVPY/xNzHzfm1LZf0hKT98rETJT0maYmkeZJ+I6lXPvYeSaskHVEn3pGSJuSf3562J2kk8DHgrPyaQ1JfSc9JuqBOHx/J8TgJzToXHYCZmZm9S0/8b0oE3nsE7H5k0dG0fl26p0qEf/oa/GNUeibWidfA+z9ddGTNa+Q2LT/sP3JJtX8lGwf0lrRnRMwAjgIWAkOBWyX1AfYAxub21wDHA6cDC4CrgDGSBkXE2txmEDAMOAEISYcAVwAfB6YCvYEDc9sRwHTg+6SpbaU+3kHS9sDDwL3AB4A1wHGsH4i4hZSEHQusA64Dbs3bJScAc4EjSFPobgMeA+7Jx38PdANOA14FDgE65WPdgR8AU4CewI+AG4FTI+INSQ/k1/dI2fU+ltvUdXV+/SuBUrK0ABgNnAn8pKztWcBtEbGq0n3piJw8mZmZtUW1S+DxPOo07JvFxtKWbNYJTroWtu4Df/s+/PErEOvgkM8WHVmHFBGvS5pGSpZm5O8/BkojT0OBFyJijqQtgc8Ap0fEwwCSPgW8DJxISmwABJwTEUtymxGkpOWhiFgNvAQ8ma+/SNI6YElENFRQ4fzcx6cjolT3fmruf2/gQ8BBEfF03ncWMFXS/hExKbefB3wl0hz2ZyWdCwwH7pE0HBgM9I+Il3P7mWX36a6yWGZJuhB4UlLXiFgJ3A5cI+mCiFgr6QBgL1JCWPeeL5NUC9SWv2ZJNwOXS9o3IqbmkbMTSMmiZU6ezMzM2qInboDaxfDewz3qtLEkOOrrqQrfny9OI1GbdYaDzy46suZR/ShQUcYCQyXdCewLHAN8I09LG8r6Uaf+QBfSaA0AEbFQ0rPAANYnT7NKiVP2EPA94HlJ9wP3AWMiYs1GxDgIGFuWOJUbAKwoJU45rmckLc7HSsnT5Hjn4t/XgNLUvkHA82WJ0ztI2os0OnYIaeRpM1KSuAswizR6dSMpGXuINAo1LiLmVPsCc4L6F9Lo0zeATwIzImJCtX10BF7zZGZm1tbUvgmP/yz97LVO795h58LxV6afx1wIT/1foeF0YGNJSdLhwKSIWAw8kfcNJU3t2xhvlW9ExJukaWqfA5YCPwXGSuqySVFvvNV1toPqP4uPAboCZ5MSqNPy/i6QRpOAP5KSJkjTGm97FzGOAs6QtBkpibr5XfTRrnX45MnPeTIzsybX3JUln8yjTrt9AHYf2rzXau+GfDE9TJeAe86Df91edEQd0VigL2mkY2zZvtOAfcr2zSIlIG9PI5PUE9gbaLD+fESsjoj7I+KrpCRtCOtLd69i/dqi+kwhjY5V+uw8Hegu6cCyuPYBtm0srjr995O0a90Deb3VXsDlEVETEdOBXhX6uA0YIelwYFfgrgptSup7zfeQ1l1dCBwA+C8KdXT45MnPeTIzsybTEpOj1qxcP+o07Bt+rlNTOPwC+OBlQMAf/gMmN/SZ05panlr2PO9MnsaRRlHm5UISpdGVm4BrJR2dK9HdArxImopXkaSTJJ0n6QBJfUkjKivyeQCzgeGSdpL0nnq6+RnQB/hV7mdgrujXIyKeBf6cjx2aC1TcTFpjNbnKe/A3YALwO0lHSuov6fSckC3KX+fm/ScCl1bo5j5SQvQL4MGIWNjAJWcDB0vql6v8bZbjWEUqdHFVjr/qaX8dRYdPnszMzNqU52tgxRuw4yDY/aiio2k/jvwaDLskFY+4+/Pw4uNFR9TRjCX9+aFULW48qfJd3Sl7FwEPAL8lFX3oBJxcVmmvksWkaWw1pCIPHwZOKUsuLgUOIiVTT1XqID8j6RjSCNl40rqrUmU9SFXpniOtN/or8ALri15U6zRS0YwxpHVSXwXW5HVWnyRNYZwKXAZsUCUmF464m/WV/BryC1IBi8mkSnu7lR0bTZoO6Cl7FbhghJmZWVsyLa+J3+cUjzo1tWHfSNMhx18Hvz0bvjAOttyhsbOsCUTEOcA5ZdsrSGt86rZ7C/hC/qrUz0hgZJ19j5ASj/quPZZUqKKxGCeSSqBXOraA9euNKh0/u7F9ETGfehKuiHiAVHyi3Ab/AOQ+K11rNCkpKm2/RiouUclOwBJSImZ1eOTJzMysrVi7Bqbn2UkDvWS3WRx7eVpLtmwu3PXpdM/NOgBJXSXtRhqJG5UTWKvDyZOZmVlb8eKjsGIR9NwDetX9I7Q1iU5d4KOjYIsdYPY4+NsVRUdk1lI+QVp7FsDlBcfSajl5MjMzayum5RpHAz/sKXvNaave8NHRoE7wyLUw/U9FR2TW7CJidER0jojDI+KNouNprZw8mZmZtQXr1sH0P6afPWWv+fU9HI4ZmX6++z9g4axCwzGz1sHJk5mZWVswZyIsfQ222RX6HFR0NB3DB85PierKJXDnmbC6tuiIzKxg7TJ5krSXpLGSxkkaL+mkomMyMzPbJKUqewNP9pS9liLBKT+H7frBvCnwxPVFR2RmBWuXyRPpQWKnRcSRpFr+vyg4HjMzs3cvomy9k6fstahu28C/XZ1+HncNLH+92HjMrFCFJE+SRkh6UNIiSZGf9ly3zdckvSxphaSHJe1Zbf8R8XrZg89WkKqGmJmZtU3zpsAbs2GLXrDrYUVH0/Hs8UHY41hY+SbUXFl0NGZWoKJGnrYgPTH625UOSjoTuAL4OnAo6UFd90nafGMuIkmkUaerNilaMzOzIj2Tp+wNOBE261RsLB3VcVek6nsTR9Fj+UtFR2PWJkiaLaniA43bqs5FXDQibgGQVN9DKr4M/DwibsvtzgLmAycBv8/7xlc4762IOLps+2fA7Ii4rqliNzMza3HlJcqtGDsMgIPPhom/pP+s0cCZBQdkTUXSXOCbETG66FjaoUOAZdU2lnQVMDgihjVbRJuo1a15ktQVOBB4qLQvIpYCTwCDy/YNrvB1dFk/PwFqI+LSlovezMysib0+AxZMS2tv+h5ZdDQd27BvweZb0XPRP2Dmw0VHY1XY2FlL1rQiYkFErCg6jqZUyMhTI3oCnYB5dfbPB3aspgNJxwBfAh6RVJN3nxQRy+q0Oxc4t3xfTU0N1jSWLVvm+9kGNef7tvLNJQDU1tY2eo3ta1fSCXh8/HjW9ezZLPG0J/59ax22njeP7sC0adOp3WabRttX877t9uJd9APmbnMQ0x95rEnitHdv111Oo//zv2bZ3V9h4vuvTVP57F2TdBpptlGfvH0K8Afg/0XErXnfDOCyiLhNUg/gR8BHge7AWOC8iJiZ244EPgT8BrgYWAv0lXQ+8BVgZ1Jhsbsj4ov5c+KOwChJo4AXI6JvPbEeBPw3MARYBTwGfCQiaiVtT5rx9G+AgD/nuObnc0cD3YCppBlWAYwijXhFbrM9cA1pplU3YArw2YiYLOlE0nKXfYFa4GHggohYIOk9pM/NR0fEI2XxjgROjIhD8vYw0lKWA4DXgF8CV0XE2npebw3wFLA18DHgTWBkRNxQ1uZ9wE9II0yLgdHAt0t9Spqdr3F9rnHwAnAqaWnOQfl+fCYiJkk6G/hGPq9Ur2A48DjwY2AEsA0wB7gyIm6qFHdza43J0yaLiIeo4rXlN/+GsjeIYcOGNWNkHUtNTY3vZxvUnO/bkvnzmHLrjXTr1q3Ra8zo1pU1wJDBg+my887NEk974t+31mHOfffxJjBw4AC2qeL9qOp9u2EkAL2HfY7eAxvv05rZ6sHUXn0/Wy5/kWFbv5ym8tmmGAf0lrRnRMwAjgIWAkOBWyX1AfYgJUmQkovjgdOBBaRkYIykQWVJwCBgGHACEJIOIa2l/zjpw3pv0iwnSB/IpwPfB+4gJVsbyInNw8C9wAeANcBxrJ/FdQspCTsWWAdcB9yat0tOAOYCRwD7AbeRErB78vHfk5Km04BXSQlJKTvvDvyAlFD1JCWQNwKnRsQbkh7Ir+/t5ImU8NyY498TGENKKB8E+gE3AW8B11Z6zdln8/GDSff9OkmTI+JxSVsC9wMPAJ8H+gO/ApaS7md9rgAuAmaTkqKbSYnUHfk6B5PeF0iJ7gWk2Wcnkd7z/qT6CYVojcnTQtJ/uHVHmXYAnmzqi0lyzVczM2udls6DV5+CLj1SxTcrXpduzOp/Jvs+czX89QoY9BHoulXRUTVov5v3a/Gqw5PPmlzVw8gi4nVJ00jJ0oz8/cfAGbnJUOCFiJiTP6x/Bjg9Ih4GkPQp4GXgRFJiA2nk55yIWJLbjCAlLQ9FxGrgJfJnyohYJGkdsCQi5jYQ6vm5j09HxLq8b2ruf2/SaNdBEfF03ncWMFXS/hExKbefB3wljzQ9m2dADQfukTSclCD0j4iXc/uZZffprrJYZkm6EHhSUteIWAncDlwj6YKIWCvpAGAvUkIC8E3glxFxfVkf3wO+RsPJ07MRcVnp5zx6dT5pNOgM0gjaZ3MMz0j6T+B7NJw8XRURD+T79D3gUUnbRsRiScuBVeXvhaRdgaciYkLeNbuBvptdq1vzlG/+08Db/5fIvyyHAZWKRGzq9cY0dZ9mZmZNonZx+r7NLtCle6Gh2HoLeh0BuxwCyxfAv24vOpz2YCwwVNJWpGlpPwN2kdSLlDyVRp36A11IozUA5EfTPAuUFyGbVUqcsodII0XPS7pR0mmSNnYAYRAwtixxKjcAWFFKnHJcz5CmsZXHNbk0RS97jTQ4UOr/+bLE6R0k7SXpt7l63VLg76QkcZfc5B7S9LrhefvjwLiImJO39we+IGlZ6Qv4H9I9bUjdgYvxwMCy1/2P/Nm95FFgO0k7UL9JZT+/lr831P7XwGmSnpb0Q0kfaCTmZlXIyJOk7YDdgL551z6StgVm5nVJPwWul/QP0vDkSNL8xj82QyweeTIzM7PqSXDo5+GVCSl5OvRzRUfUoGpHgQo0Fvgv4HBgUh6BeIKUOA2l4ZGRSt4q34iINyUdSPrD/HGkz5kXSzoqj0S1lLrXCqofyBhDShLPJo2A7UaaLtcFICKWSfojKWl6iDSt8Ydl529Jet03sHGaY9Sy/D6U+q/3PkTEREm7k9aTHQv8RdL1EXFRM8TWqKJGnj5MWoB2d97+U95+P0BE/Bq4DLgamAhsB5wQEauaOhCPPJmZmdlGG3AibL4lzJkIr89svL01ZCzpD+qfZP0o01jS2p99yvbNIn3wfnvkQVJPYG9gWkMXiIjVEXF/RHyVlKQNIa07glT8obHKH1NIo2OVPjtPB7rnBK0U1z7Ato3FVaf/fnmK2jvk9VZ7AZdHRE1ETAd6VejjNmCEpMOBXYHyqX5PAwMjYmbdr0biOrTO9mGk10v+fnCulF1yOLCoVCjjXaj4XkTE4oj4TUScA3yROgXfWlIhyVNEjI4IVfiqKWtzdUTsEhHdIuLovIjQzMzMrHib91j/3K1JdzTc1hqUp5Y9zzuTp3GkUZR5pc+AeXbSTcC1ko6WtB+pUMOLwH319S/pJEnnSTogV3w7E1iRz4O0hma4pJ1y5bpKfgb0AX6V+xko6cuSekTEs6Tqer+SdGguUHEzaY3V5Crvwd+ACcDvJB0pqb+k03NCtih/nZv3nwhUehTPfaTE4xfAg3lKY8kPgWPztLdBOf5PSLqkkdAGSBqZpw2eB5yS7wWkghgCbsz9nQx8l1TM4t2ana+5j6TtJXWR9JV8L/aSNDDHML3hbppPq1vz1NI8bc/MzMzelQM+lr5PugOixWsytDdjSR/ES9XixpMKiI2r0+4i0nS135LW43QCTq6v3Ha2mDSNrYZU5OHDwCllycWlpGpvL5JmQm0gIhYAx5BGyMaT1l2VKusBnAU8R5oy91dSSe4zNuioYaeRimaMIa0L+iqwJq+z+iRpCuNU0uysb1aIcSVpVlepkl/5saeAo0kV/J7Mr+EC1ieQ9bmJ9Jr/SSqVfl5EPJr7XEYqlNGPdN9uIpc/36hX/U53kO7t46TKeocDy/O1n8rHNgc+sQnX2CStsdpei4qIMVJrnwpsZmbWsU2YvYjv/GEKe/feig/t25uj9u5Fj80L/hjT90jYqg8sfhFeGg/vHVJsPG1Yno51Ttn2CqBrhXZvAV/IX5X6GUlaK1++7xFS4lHftceSClU0FuNEUgn0SscWkEbK6jv37Mb25aluFROuXJ1uQJ3dG3yAzX1ucK187DHWF5So1spG+vwnqfR6RVH2zKyImE2dmOvui4jlpJGlcjVs/FqtZtPhkyczMzNr/f4ydS7T5y5l+tyl3PP0q3TtvBlH7tmLDw3qzSkH9qFLpwIm02zWCfb/KDz6E5h0u5Mnsw7A0/Y8bc/MzKzNGNxvOw7abVtWrlnHQ9PmcdFv/8WFtz9NFDVtbv882DD1blhdW0wMZtZiOnzy5Gp7Zq2Ulw+YWQVHD9iBu794OE9c8kG+d8q+bNm1M3+a/Bp3TKj4eJzmt+M+0Hs/qF0CMx4oJgazZhARwyJig7VVHV2HT57MrJXzmkQzq2DHrbvxqSF9ueLUQQCMHDOVmfOXFhNMafTpX666Z9beOXkyMzOzNuvUg3ZmxEE7U7t6Heff9jS1qxsqutZM9vt30GYw4y/w1qKWv76ZtZgOnzx5zZOZmVnbdvmpg3hvzx5Me+1NrvpzAY9/2ao39BsO61bDlN+1/PXNrMV0+OTJa57MzMzati27duanHz+IzpuJ0Y/N5uFp81o+iAPy1D0/MNesXevwyZOZtSRXgTCz5nHArtty0fF7A3DxXZOY/2YLV74bcCJ02QJemQALZ7Xstc2sxTh5MrMCuAiEmTW9c4/sxxF7bM+i5au46v4Wnr63+RYwMK8E8OiTWbvV4ZMnr3kyMzNrHzbbTIz88D4A/P3ZBS3/7Kf3nQmHfh4GnNSy1zWzFtPhkyeveTIzs6ZW2ANbjf69tmTHrbuycPkqnpu3rGUv3vdw+Lcfwk77t+x1bZNImivp7KLjaAmSbpc0uug42rIOnzyZmZk1Ffm5ZIWTxJB+PQF4fNbrBUdjRZO0edExtDWSOklyjlAP3xgzMzNrV4b0z8nT8wsLjsQaI+k0Sa+WbZ8iKSSdUbZvhqRP5J97SLpe0kJJb0m6X9IeZW1HShov6cuSXgaey/vPl/S8pJWSXpN0Xd5fA+wIjMrXnV1PnNvlUZvSdaeVln5Iek7SBXXafyS33VzSsNz38ZKm5vPvktRd0n9ImiNpgaRvlZ3fN5/z75KelLRC0l8l9ZI0QtJMSYsl/aQ80ZHUU9LNkhblr7sl7VK6N8DHgLNy35GvU4rvBEmTgZXAEEmrJG1f53WNkfSz6t/h9sfJk5mZmbUrQ/qlz3tPvLCIdes8hbKVGwf0lrRn3j4KWAgMBZDUB9gDGJuPXwMcD5wODAbWAWMkdSrrcxAwDDgBOFHSIcAVwJeAPYFTgKdz2xHAAuBCYCfgkHri/B6wHTA8938xUJoXOho4s077s4DbImJV2b5LgLOB43J89wKHAR/M/f2XpIPq9HMZ8HVgCLArcCdwDnAqcAbwhfx6Sn4LdAeOBg4HaoF7c4J1NXBP7mOn/PVy2bmXA18E9iXdnxeAT5QOStoB+FB+vR1W56IDMDMzM2tKu27XnZ237c6cxSuYPncp+/TZuuiQCjVtwMAWzyAHTp9W1RzWiHhd0jRSsjQjf/8xKTEgb78QEXMkbQl8Bjg9Ih4GkPQpUgJwIikZgVTS9ZyIWJLbjADmAg9FxGrgJeDJfP1FktYBSyJibgOh7go8GhGT8vbzZcduBi6XtG9ETM1JxgnAB+r08a2ImJBjugv4OHByRNQC0yV9k5RUPVV2zlURUZPP+SVwJdAnIl4Dpkj6Wz7nbklHAvvl46vzOZ8GlgCHRMQTkmqB2vLXWjbd+JKIGFe2fxQpKfyfvOsM4LmImNjAfWr3OvzIk6vtmZmZtS+SGNzPU/fakLHAUElbkUY9fgbsIqkXKXkqjTr1B7oAj5VOjIiFwLPAgLL+ZpUSp+whYA3wvKQb81TBjR1AuAH4hqRHJX1X0ttVQSJiDvAX1o8+fRKYUUqUykwu+3lejrO2zr5ejZyzKCdOlc7ZnzQ69oakZZKWkUbVOpPuXWP+UWf718BBkgbm7bNIiWKH1uFHniJijBf4mpmZtS9D+vfkd/98hcdnLeQzR+xedDiFqnYUqEBjgf8iTTObFBGLJT1BSpyGAtduZH9vlW9ExJuSDiRNjzsO+ClwsaSjSiM0jYmIP0raHTgp9/GkpIsjojQqMwq4Nq9bOpPKSUb5taLOdmlf3YGNjTlnS2A2aVpjXfMq7Kur7n17VdIDwJmSbiNNV/y/Kvpp1zr8yJOZmZm1P6WiEU+8sJC1XvfU2o0F+pJGbMaW7TsN2Kds3yxS8vD2dDhJPYG9gWkNXSAiVkfE/RHxVVKSNoQ0xQ1gFdCp3pPX9zEvIn4ZER8jJXufKzt8D9CNtHbqAIpJMp4GdgGWR8TMOl9Lc5uqXmuZX5Gm651Dmvb4aiPt2z0nT2ZmZtbu7Lxtd3bbrgdLa9fwzKtvFh2ONSBPe3uedyZP40hrguZFxIzcbhlwE2mE52hJ+wG3AC8C99XXv6STJJ0n6QBJfUkjQyvyeZBGa4ZL2knSe+rp47uSTpbUP49iHQtML3sNq4BbgatIScacjb8Tm+xB0nqpP0gaLmn3/P06SdvmNrOBgyX1k7S9Gi9Jfi+pAMWX8JQ9wMmTmZmZtVOD+20HwOPP+3lPbcBYUqGHR/L2eGAtKYkqdxHwAKmq3JOkUZSTI2JtA30vJlXnqwGmAh8GTsnrpQAuBQ4iJVNPVTgf0ojXfwNTSEnKS6SEotxo0pqsQpKMiFhHqob3FHA7Kbm7KR8ura36BWkK32TSeqjdGulzNfAb0pS+PzR50G1Qh1/zZGZmZu3TkP49uXNiWvd07tBq1stbUSLiHNLUsNL2CqBrhXZvkcpzf6GefkYCI+vse4Rc+ryec8aSClU0FN8VpHLnDdmJVNnu7jrn1pASw8biHFb28+wK54ymTpnwiDi7zvZiGr4/r5HKrZfb4Fp17ATcmd+TDs/Jk5mZmbVLpec9TZj9BmvWrqNzJ0+4saYnqSvpQbuXAqPaS5IhaRvgYNIzpQ4tNprWw/+KmJmZWasX76LmQ+9turH79luwbOUaJs9Z0vgJZu/OJ0hrtoL0oNn24h7SmqcrIuLpgmNpNZw8mZmZWZuhBmcXbcjPe7LmFhGjI6JzRBweEW8UHU9TiYhhEbFlRLSnhHCTdfjkyQ/JNTMza79KJcsfn+Xkycw2XYdPniJiTNExmJmZWfMoVdybOPsNVq1ZV3A0ZtbWdfjkyczMzNqvHbbqxh47bMmK1WuZ9MriosMxszbOyZOZmZm1a0P6eeqemTUNJ09mZmbWrpXWPY1/wcmTmW0aJ09mZmbWrvXrtQUAC5auLDgSM2vrnDyZmZlZu7ax5c3NzOrj5MnMzMzMzKwKnYsOoDlIehRYDWwJ3BER/11wSGZmZmZm1sa1y+QJGB4RqyR1AaZLujki5hcdlJmZmZmZtV0tPm1P0ghJD0paJCkk9a3Q5muSXpa0QtLDkvbcmGtExKr8Yw/gVWDJpkduZmZmZmYdWRFrnrYAxgHfrnRQ0pnAFcDXgUNJic99kjav9gKSOkmqAWYCjwGrGj7DzMzMzMysYS0+bS8ibgGQNKCeJl8Gfh4Rt+V2ZwHzgZOA3+d94yuc91ZEHJ2vsRYYJqkbcB9wHPBAU74OMzMzMzPrWFrVmidJXYEDgUtL+yJiqaQngMHk5CkiBjfQx+bAmohYB6wE3gJWNGPYZmZmZmbWAbSq5AnoCXQC5tXZPx/Ysco+dgdulLQO6ArcHxFjKzWUdC5wbvm+mpqajYnXGrBs2TLfzzaoOd+3lW8uBqC2dkWj19i+tpZOwOPjx7Nuu+2aJZ72xL9vrcPWc+fRHZg+fTq1Vbwfjb1vPZa/zKHA8rfeYkIHf39ffiU94HbmrFnUrHtpo859Zek6AJYvX94kvyf+fTPruFpb8rTJIuJZYGiVbW8AbpAUpX3Dhg1rpsg6npqaGt/PNqg537cl8+cy5dab6Nate6PXmNGtG2uAIYMH06VPn2aJpz3x71vr8Oqf/8wSYMCAAWxbxfvR6Pu24FmYAFv06NHh399Hlj0Ds19gj/79GTa030ad++zcpfDoWLbYYguGDTtqk2Px75tZx9XaHpK7EFjLhqNMO7DhaFSTkHRyc/RrZmZmZmbtS6tKniJiJfA08MHSPklbAocBlYpENMU1xzRHv2ZmZmZm1r60+LQ9SdsBuwF98659JG0LzIyIZcBPgesl/QOYAowE5gB/bOlYzczMzMzMShQRjbdqygtKZwOjKhwaHhE1uc1FwIXA9qTnNH0+ImY0UzwnA/c2R99mZmZmzSkiVHQMZh1JiydPrVF5wQgzMzOztsLJk1nLalVrnszMzMzMzForjzxZs5E0MSLeX3QctnH8vrVNft/aJr9vbZPfN7OOyyNPZmZmZmZmVXDyZM3phqIDsHfF71vb5PetbfL71jb5fTProDxtz8zMzMzMrAoeeTIzMzMzM6uCkyczMzMzM7MqOHmyJiXpEkn/lLRM0muSbpbUu+i4rHqSfiopJH2h6FiscZJ2k3SnpDckLZc0QdLORcdlDZO0jaQbJL2a37d/Sjql6LhsPUkjJD0oaVH+N7FvneP98/EVkl6R9PWCQjWzFuTkyZraEcCPgEOAU4C9gd8XGpFVTdJxwFDg1aJjscZJ6gk8AiwGjgH2By4HVhYYllXnR6R/Lz8K7AfcA9wlac9Co7JyWwDjgG/XPSCpC3AfUAscBnwF+E9Jn27RCM2sxblghDUrSYcATwI7RsT8ouOx+uUP4hOBU0kf5K6KiOsLDcoaJOmHwGERcVTRsdjGkTQVGBURV5ftWw6cFRF3FReZ1SVpADAN2D0iZud9J5H+MNg7Ihblfd8HTo6I/YuK1cyan0eerLltA6wB3iw6EGvU/wI3RcS/ig7EqnYy8E9Jv5c0X9KTnvrVZjwOnCppB0mbSToDWJv3W+s3GPhnKXHKHgQGSdqioJjMrAU4ebJmI6krcCVwS0TUFh2P1U/SWcAuwFVFx2IbZXfgi8Bk4HjgTuD3kj5QaFRWjfOBOcA80jTLnwOnRMScQqOyau1Aeu/KzQeUj5lZO9W56ACsfZLUCbgF6ARcUHA41gBJuwE/AI6KiLVFx2MbZTPgyYj4z7z9lKQjgXOBx4oLy6pwATAQ+BAwFxhBWvN0WETMLDQyMzOrl0eerMlJ2gz4JWkR9PERsbTgkKxh7wN2BKZKWiNpDfBe4OeSJhYbmjViLjC9zr5pwG4FxGJVktSdVNjjwoh4ICL+lRPgZ4DPFRudVWk+6d/NcjsAkY+ZWTvlkSdrUpIE3AAcCQyNiAUFh2SNe5iU6JZ7gJQA39zy4dhGeByoW51tL+DFAmKx6nXJX3VHetfiP2q2FeOBr0t6T0S8kfcdA0yJiOUFxmVmzczJkzW1X5BKlJ8ErC17xtOiiFhVXFhWnzwyOKV8n6TVwKsRMauYqKxKPwHGSroYuJv04e1kUglsa6Ui4k1J44BrJH2ZtHZmBOmPTpcVGpy9TdJ2pFHcvnnXPpK2BWaS/sD0AjBa0qWkx3JcCHy5xQM1sxblUuXWpCTV9x/U8IioaclY7N2TNBuXKm8TJP07cAVpquVzwHci4t5io7LGSOpDWmt4DLA1MIP0O3d7oYHZ2ySdDYyqcGh4RNRI6g9cT0p6FwI/jYgftGCIZlYAJ09mZmZmZmZV8NxqMzMzMzOzKjh5MjMzMzMzq4KTJzMzMzMzsyo4eTIzMzMzM6uCkyczMzMzM7MqOHkyMzMzMzOrgpMnMzMzMzOzKjh5MjMzMzMzq4KTJzOzOiRdKalWUucWvOaTkr5Utn2spHWSZkh6X4X2N0q6saXiMzMzMydPZmaV7A9Mi4g1LXExSacBfYFfle1+GjgN6AN8acOz+AFwpqQ9mzs+MzMzS5w8mZltaH9gUgte70LgtohYUdoREQsi4h7gfuCAuidExEzgUSonVmZmZtYMnDyZmZWR9B5gF2ByA226Srpc0vOSlkuaIGlYhXZbS7pO0uuSFku6RtKZklZJ2jy32R04ErirnsvNBPaRVOnf698CZ7Tk9EIzM7OOzP/DNTN7p/3z94ojT5K6An8hJVjfBeYAZwN/lrRfHhFCUhfgAWAn4OvAq8C3gRHAMxGxKnf5QWAN8GSFa20DfAroDvQHZtRp8hiwPXAgMHGjX6mZmZltFCdPZmbv1GDyREqABgH7RcSrAJL+DnwI+CRweW73VWDv3G5ObjeDNJJ0c1l/hwDPRcTKCte6CuiRf96PDZOnqcBa4DCcPJmZmTU7T9szsw5JSeeyr0750P7A6xExt8I5nYAvAteXEieAiFgNvALsXOob+DJwXSlxyl4AglQMomQnYEGFaw0BzgXOBFaSErZ3yAUtFuc+zMzMrJk5eTKzjuooYHXZ18N5f0PFIvYDepKm7dW1C2lqHsBAUpW8++u02QkQ70yeupGSo7flKX83AHdExL3AM/nalawkTeszMzOzZuZpe2bWUf2DNGWuZGkuyrAvUN/zk3rl7+8YlZI0iJRUjc27+uTv8+ucPyx/f7ps3yJSmfJyF+U+Ppi3J5Gm5lWyLbCwnmNmZmbWhDzyZGYdUkQsjYiJZV/PkooybEH9lfZeyt/7l3bkKXrfJ40O/T3vLiUze5S16wZ8C3gxIhaX9fkssHtZu/7Ad4CvRUQp+ZoM7JmLVVDWthdpTdSzVb1oMzMz2yQeeTIzW69ULGIHSafWOTaDlCA9AfwoJzIrgM8Dw4EjI2JdbjsFeDG325xU1OFi0rS9sXX6fRS4TNIuEfEKcD3waESMLmszCehEmg74dNn+9+fvj2z0KzUzM7ON5uTJzGy9UvJ0ZYVj50fEVEkfAf4H+GXe/zfg/RHxXKlhRKzO7f4XuI2UeF1JKm0+rk6/NaSRqhMkrQAOZ8P1TaU1WPvxzuTpBGBcRMyr9gWamZnZu6eIKDoGM7N2T9LHgVFAv4h4rc6xa4CDIuLojeivM2ka4Tcj4tdNGqyZmZlV5JEnM7MmJulIUjW/CaTqescA5wGX1E2csquBmZIOiIh/VXmZTwLLgN80QchmZmZWBSdPZmZNrwfwCeCSvD0JODMi7qzUOCJek3Q266v5VWMd8On8rCczMzNrAZ62Z2ZmZmZmVgWXKjczMzMzM6uCkyczMzMzM7MqOHkyMzMzMzOrgpMnMzMzMzOzKjh5MjMzMzMzq4KTJzMzMzMzsyo4eTIzMzMzM6uCkyczMzMzM7Mq/H+DyJqlYY71hQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plotting coeff. paths with log-yaxis\n", + "model.plot_coeff_path(yscale=\"log\")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# this can be done via plotting too!\n", + "from glmnet.plotting import coeff_path_plot\n", + "coeff_path_plot(model)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot cross-validation scores\n", + "model.plot_cv_score()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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e4IXtt6euW7d2GWPW9VTidm1r3Fm0589be0/oSs7dJwITzcxTbbW1tckFVGXq6ur0flagtWW7VeNrLMu2q6+HBx6AF16A7beHgw8O7a1tixKRJu0HHACHHALPPANLlkD37hB9UTN9ekFtix57jHWAmh492ta2665w//1wyCEsmjy5Wd9C48nWtuP06ayzZAlLu3dn3bYsr4UYs73GVr1n0XoO7dKF7YFL77mnYbse2rFjQW0ceGDBMZZ8Gz78cOv2xxx96+rqqF28uLBllpm5e8u94lhxOIfudWALd5+To88gYBawjbu/kdY+B/iNu//RzG4BOrr7t9Pmj47m9yOH9IQuqfegGq0tiUEiCv1SLeKPU6rt3TvuYIujj277F3Whba2IsbVth3Z8gO15gRfYnntXt88Y2/I+1k2eTO2yZfGtJ0+i1eQLdKedYPVqljz5JF2Bmm7dYNttwZ2lzz9PV6BD164weDCcdx5cfjnLX3+dzkCHzp2hVy9YsABWrWrc51NfivX1+ds6RGcPrVlTurYBA2DevKbtZuFn+ndGoW2lZgbrrw+ff97yujt0CO2FvI+Z/Tp2hF69WPHJJ3Qi2lYDBoAZK959t7Ft442hQwdWzJ7d2LbJJrDzznDHHa3brm1p69QJ+vZl+bx5YR/r2hUGDQIzlr3yCl2ADt26wTbbwBVXwE9/ytIZM8J+mtp3oWnbdtvx5eLF1LzxRuM+vt12YR9P9Uslkw89VPKkzlLbFnB3a9bB3ROZgK0BBwbm6dOBcPj0B2ltg6Ln7RD9/kPgI6BDWp9bgLtbWL+nJimdKVOmJB1C6axe7X7PPe6/+EX4uXp17vYi2r4BfjEU17Zihft++/mX4KvBvUcP9333dd9336Zt++1XeN9C22pr3WtrG9u6d3fffXf3XXf1xeD14N6tm/uOO7rvuKMvSW/bYQf37bdv2rbTTu7Tp7vvtpsvTi1znXXCMnffvWnbrrs2rKehbZdd3HfZpbEt23q6dnXfbjv3bbf1ZXTxevBldHEfMsR9yBBflurXpYv7Ntu4b7edL01/7tCh7rfc0rS9Sxf3bbd133bbpn2HD3cfMaL56872XmS2bb990+em4t5mm6YxDhrkPniwL0+1de7sPniw+1VX+eJNNmns27lz6DtoUNO+0fObLHPrrbOvZ8stG5/bqZP7Bhu4d+zoHlKEMJmFKb1NkyZNYerRI/zdLrGMvIXMqVlD3BOwATACODIK7JDo9x7R/DeAo9L6XwJ8AhwEbA88DjyesbxPgYnAtoTz41YB+7UQR/obIyXSHhO6Ztu5tQlUW5Olr32tIWHJmQRl+0Lv3Nm9b9/w5Zr+R6NDh+ZfqmbuvXtn/7LVF7Cm9jL165e9vUOHpr937Ng8mczVlvn56NSpeVuh/bp1cx89OvxMb+/cOUytaevSJUylaltnHfczzgg/W1p3ttdd6PtYU9O2bT1sWPZ4Ct2urW3L3JfyTT17Ftx3TSH9zNwvvTS277L2lNCNTg8qbaqN5jswOq1/DfCbKKlbAtwJbJixzJ2AZ4AVwDvAqALi8GZf9NJmcSV02bZVyRK1ffZx32uvxkSra1f3TTZp/keopsb9K19p/odC1Yrip+7dk4+hpSlX0tGepk02KewLpq1T5pd6587NE4yuXcPUUluPHu4/+1n4mblPfPWrod2syT9GZW9L++et1Ov5skcPX23mX7bjGJu0pbZJa7f1XXfFH2Nb4s61P+Z4jaszvxdyLTOBCl1i59AlTefQxaOYc+hS5wNkvv/N2uvrWz75NjrPp8mJtyNGwMqVLJ0+PZzb0Lkz9OwJCxfC6tVtfq1llzqnK6VTp3C+y8qVjW3dusHo0XDjjbB0aWN7ly7h54oVLbeZwfLljW1du4afpWrr0QPOOQd+9ztYvDi+9awlMa4eP56Oy5bFt57u3cO5R7Nnt/pCgFwn8zc5Ly/9JPYXXwyf3/Rz+srdln4OZQnXc+gDDzDixRd5ccQI7m2nMTZpa8vFKqlzyZLYhoXGnWt/zPEaFyxcyAazZhX2ust8Dp0SOpTQlVJdXR377LMP0PR9zZa8ZU3oMpO3zESte/dwsurKlSx/6aVwsmunTuFDtGhR04SnrTp0aHpCdJcucPTRcNddkP4F2rlz+JmeWGVLlkrwpbropZfyX7lW5B+nVJsvWYK19Yu6rV/oMa179dTp1KxYQn2X7nTco33G2Jb3ccHuu7PBW2/Fv71KmWjlSkQSuDKw3O6Jfr7yyitcOGxYorEUrC1JY5LbtNC4i0iM6+rqwkVICbxuJXQ5rK0JXaGJVWvbsiZ0hVTYUh+KAw5gyWOP0Y2ootajR7iKa02T4QTbJrPSla0qlS2BasUwAYUOHVDSL9VW/Nf+7p13ssVRR1V89WNtjLHhKte43wspKY0IUJmS3G5K6HKohISu1MlXyZeZJVGrq6tj/MiR+Q+F7rILuLNkypTGxK1375C8zZpV1HvURMeOTQ+lFlnpyjmGUXv5ko/xS1VfLpVL264yabtVJiV07VCSCV3cVbJcbcVUylp1ztouu7BgwQI6v/gi3YCarl2hTx+YP7/p4chilSNRg7W6KqEvl8qlbVeZtN0qU3tO6Na6O0VUnfp6vkEYz4V7721ITrK1ceCBTALWATj++JC4rF7NP4CuAN/6FgwZAtDYduyx8JWvgDv/AjoDfPObDRcXrJuKY/FieOwxegENe9ny5fDBB4W/lpEjYdq0cJgxpchEbd0sidq62RK1Qw8NU7psbSIiIhVACV0lyUzeoipZkyRtl11g9WpuA7oBHHMM9O8Pm28OTzzRNAF78klIPRfCif4vvti0bflyeO01IErwIFTbPvkka4jNh64m+8UFmees9egBP/whuDet+kWJ2vFdujACuGzSJCVqUpQBAxofz5uXXBwiAKndceXuu/NpopFItVFC1161lLwddxz07QsfftisSgbQPdW2YgXMmROmUstycUG9OzXph1eLqbBFidfxHTs2Td5qarg322FxJWpSgA8/TDoCkUYNu2PqSniRElFC1x7V1zc9PPqtb4VDnJ980pi8LV0K771X+DJ32y1Us0o8NlVmovbFwoV0euGFgips2RI3IHvyJiIiIjl1SDoAoaEadzGEatxNNzUcHq2BcCj0o4+yj7HWIWMTdunSmICl9OgBP/0p7Lkni4D6VNsee8Aee7SubbfdYPp0jgfGAkyaBA8/zMu//W3Ttocegs6duQ/4JYSKWk1NQ9XtMvfGNhEREWkVVeiSFlXj/o+oGnfEEbnHXMs8xFmKw5lkqZQV2lZTw33AfcBlqUOfOQ6Prq1XU4uIiJSDErpySz837pZbwlWddXX0SM1PJXOZFxLkGei2mMOZzRIwsh/iLLRNiZqIiEjylNCVU309HHAA/wK6AJx4Yu6+Awey6J13Wk7eslXJyJ64gRIwERGRaqRz6MrpgQfg6afpStrwHh06hJusp+vRA666qrBz0XJwdyVvIiIiawkldOX0wgtNb+oO4bDqpps2veAgOudNyZuIiIgUQgldOW2/ffYrULNV43IkcEreREREJJMSunI6+GDYemsAHFpVjRMRERHJpIsiyqmmBi67DL7xDd4GBmdcgZpJlTiRtnvuuaQjEGmU2h2fe+452GmnRGOR6qKErtyioUjeBAbrtlUisdtxx6QjEGmU2h0XLV6caBxSfXTItdyi+5yuSjgMERERqR6q0JVblNCtzGjW4VURERFpLVXoym1VqM2pQiciIiKlogpdueWo0IlIPMwaH6sQLklr2B1ra9HuKKWkCl25RRW6U8aMSTgQERERqRZK6MotqtDRuXOycYiIiEjVyJnQmVl/M7vdzA7M0+fAqE+/eMKrQlGFTgmdiIiIlEq+Ct25wFeAh/P0eRjYAvifUgZV1VIVuk6dko1DREREqka+hO5Q4FrPM55GNO864IhiVmpm55rZ+2a2zMwmm9ngPH0HmNkkM5tvZl+a2a1m1iujj2eZ2ucQ3KrQiYiISInlS+gGAq8VsIzXo74FMbOTgMuA84FdgC+A+82sWYZjZh2Au4BewEhgb2AAcGuWRZ8A9E+bXiw0prJShU5ERERKLN+wJcuB9QpYRg9gRRHrPAuY4O6TAMxsFDCfUBG8I6PvYGBnYEt3fyfq/0Ngpplt7e5vpPVd6O4fFRFHMlShExERkRLLV6F7GTi8gGUcEfVtkZl1AUYAj6ba3H0R8AywW5anpLKe5Wltqce7Z/T9c3RY9ikzK+oQcFmpQiciIiIllq9C9xdCkjTV3W/M1iE6fHoy8L0C19cbqAE+zmifD2yYpf+bwAfAZWZ2JiEBvSyat1Fav4uBKYRK4VHAnWZ2mLvflyXmMUCTQeDq6uoKDL/tBs+Zw8bArPfeY24Z11suixcvLuv7KaVR3duttuFRNb7G6t52Vai2tuGhtlvlac+fN8t3D1EzmwQcB8wAHgT+CziwGXAgsBNwm7ufUNDKzAYAc4Ed3P2FtPZ/AMvcfVSW5+wG3ABsBawG/gh8G/idu1+RYz03AJu4+8g8sTS88LLeR3XMGLj+erj2Wvj+98u33jKpq6ujNu0PllSGat5u1X6niGredtUobXfUnSIqUJKfN0v7Y+buljk/762/3P14M3uCMCzJRRmzZwM/dPc/FRHPZ0A9zatx/YDpOWJ4GtjazPoQboG6CjgTeDfPep4F9ioirvLRwMIiZTV3btIRiDRK7Y5Tp06FPfZINBapLi3ey9Xd/wj80cw2BjaOmue6e9F/Jt19hZm9COxHqPhhZj2AXYGrW3jup1H/Ewm3Qn00T/fhwJxi4yuL1EUROodOpCwGDEg6ApFGqd2xz0rd0VtKq8WELiVK4Erxv+7VwLVmNgOYCYyLlnsvgJm9AVzg7ndGvx8LfAh8BHwd+AMw1t0XRPMPBfoSLqxYTTiH7lTg2BLEWnqq0ImIiEiJ5UzozOySPM9bRbiQ4Ql3f6uYFbr7TdGtwsYDfYCpwMHunvp3ZQjQM+0pmwK/JyRt7wDnufu1afNXAz8CBgFrgDeA41MJYbujCp2IiIiUWL4K3Tl55tUQxp9zM7sFOMXd6wtdqbuPJyR02eZZxu9XAVflWdaDRIdvK4IqdCJlNW9e42MdfpWkpXbHT/UdICWWM6Fz91655kHDuW9HAdcCs2gcTkTy0cDCImW18caNj6vxKlepLA274x576CpXKal8Awvn5e6L3f1m4FfAiaULqcppYGEREREpsVYndGmeBjYvwXLWDqrQiYiISImVIqHbAFhaguWsHVShExERkRJrU0JnZh2AHxCuVJVCqEInIiIiJZZv2JL/yfO8GsK9VL9BGFakfd6VoT1ShU5ERERKLN+wJVmHFYnUA58A/wGOdfdXShpVNVOFTkREREos37AlpTi/TjKpQiciIiIl1uakzczWNbPRJYhl7aAKnYiIiJRYqxI6M+tkZkea2T+Bj4G/lDasKqYKnYiIiJRYvnPomjGzWuA7wNHA+oT7uf4JuLHEcVUv3fpLRERESqzFCp2ZjTCz35rZ+8Bk4DjgsWj2ce5+rru/HGeQVSV1yFUVOpGycG+cRJLm0TSlri7hSKTa5EzozOwiM3sVmAGcBTwPnABsCJwGWFkirDaq0ImIiEiJ5TvkeinhH4lHgdHu/mFqhpkpG2mN+vpQJujQAWpqko5GREREqkS+Q67XEM6R2x943cz+amYjzUyVudbSBREiIiISg3zj0P3IzM4BRhIOtX4TGEVI8u6h8VQAKZSGLBEpuxkzGh/vuGNycYhAOIcJ4M0ePahNMhCpOnmvcnX3NcDDwMNm9n3gcEJydxLhHLobzOxG4GZ3fzfuYCueKnQiZbfTTo2PdWGEJK1hd9xpJ76fZCBSdQoeh87dV7j7P939KMKFEWOAOcAlwNvxhFdlVKETERGRGBQ1Dl2Ku38B/Bn4s5ltTBjKRFqiCp2IiIjEoFUJXTp3nwtcVYJYqp8qdCIiIhKDNt/LVYqgCp2IiIjEQAldOalCJyIiIjFQQldOqtCJiIhIDJTQlZNu+yUiIiIxyHcv155mdqWZ7ZOnzz5Rn3XjCa/KpA65qkInIiIiJZSvQnc2cCTwVJ4+UwmDDZ9VzErN7Fwze9/MlpnZZDMbnKfvADObZGbzzexLM7vVzHpl9NnSzB6JlveBmZ1fTDxlowqdiIiIxCBfQnc0cI27r8zVwd1XABOAYwtdoZmdBFwGnA/sAnwB3G9mzbIcM+sA3AX0ItyCbG9gAHBrWp9OwP3AcmBX4BxgrJmdUmhMZaOLIkTKrn//xkkkaf2jqfeKFUmHIlUm3zh0g4EXCljGi1HfQp0FTHD3SQBmlro/7KHAHVli2BnY0t3fifr/EJhpZlu7+xvAgcAWwO7uvgB42cxGECqMfy0irvjpogiRsps3L+kIRBqldse6adOgtjbJUKTK5KvQ1QNdClhGZ2BNISszsy7ACODRVJu7LwKeAXbLsWwI1TcyHu8e/dwNeD5K5lIeAYaaWfdC4iobVehEREQkBvkqdG8QDnM+3MIy9o/6FqI3UAN8nNE+n3B/2ExvAh8Al5nZmYQE9LJo3kbRz345lmfRvHfTZ5jZGMJ9aBvU1dUVGH7bbPjSS2wDfLxgAa+XaZ3ltnjx4rK9n1I62m6VS9uuMmm7Vab2vN3yJXS3Ar8yswfcfUq2DmZWC5wBXFD60MDdV5rZscANwCJgNfBHQgJXUFUwyzInAhPNzFNtteUqe78bcssNN92UDau01F5XV1e+91NKRtutcmnbVSZtt8rUnrdbvoRuAuEq14fN7E7gIeC/gAObEc5dOxp4gpBkFeIzwqHczGpcP2B6tie4+9PA1mbWB1gVTWfSWHmbDwzPsjyP5rUfOodOpOzuuafx8WGHJReHCEBqd3yld29qkwxEqk7OhM7dV5nZgcClwOnAMYQkCcLhzMXAVcAl7r66kJW5+wozexHYD3gQwMx6EK5OvbqF534a9T8RWEnjeXhPA+ebWS93Xxi1jQRmuvuSQuIqG51DJ1J2hx/e+Ng9dz+RcmjYHYcN48IkA5Gqk69ClxqW5HwzuwTYEdg4mjUXmOHuy3M+ObergWvNbAYwExgXLe9eADN7A7jA3e+Mfj8W+BD4CPg68AdgbNpFEA8RqnU3mNnFwBDCFa5FjY1XFqrQiYiISAzyJnQpUeKWb4Dhgrn7TWbWDxgP9CEMTnxw2nh3Q4CeaU/ZFPg90Bd4BzjP3a9NW94qMzsEuBZ4lnBY91J3b19DloAqdCIiIhKLFhM6M9sQ+B5hUN9NouYPgP8Af3H3zCtMW+Tu4wkJXbZ5lvH7VYRDu/mWN5twtW37pgqdiIiIxCDfOHSY2THAW4Tz6HYEVkTTjoThQ96K+kghdOsvERERiUHOhM7MdgUmEQ5jfs3d+7j7DtHUB9iTcGXq381sl/KEW+FSh1xVoRMREZESylehuwh4HNjf3admznT3acABhGFLLoonvCqjCp2IiIjEIF9Ctyfwv+65L/SP5k2I+kpLdFGEiIiIxCBfQrcO4YrRlnwa9ZWW6KIIERERiUG+hO4d4GsFLGOvqK+0RBU6ERERiUG+YUsmAT81syfd/fFsHczsa8D5wBVxBFd1VKETKbsddkg6ApFGqd1x0aJFsO66icYi1SVfQjceOBSYYmYPE+7k8N9o3mbANwj3c30GuDLOIKuGKnQiZTdjRtIRiDRK7Y51M2ZAO73Ju1SmfPdyXW5m+xLGmzuNkLyl38t1CeEODj+LbhEmLVGFTkRERGLQ0r1clwL/Y2YXAjvR9F6uz7XyXq5rL1XoREREJAbF3Mv1yVzzzWwLd3+3ZFFVK1XoREREJAYFJXS5mNlXgZ8AxwAqO7VEFTqRsps4sfHxmDHJxSECkNod3+zfn9okA5GqkzehM7NvAScTLoJ4B/i1u081s6GEK1sPAhahq1wLowqdSNl9//uNj5XQSdIadschQ3Q1oZRUzoTOzL4L3AQsBGYB2wOPmtnZwNXAauBXwFXuvjD+UKuAbv0lIiIiMchXoTsbeBg42t2XmpkBVwF/Al4FDnH3D+IPsYqkDrmqQiciIiIllO9OEYOAq6MrXVP3bb2CMGTJJUrmWkEVOhEREYlBvoRuPcJ9WtN9Ev18P55wqpwqdCIiIhKDlq5yXc/MNsjSf92Mdtx9QUkjq0aq0ImIiEgMWkroHsrRPjlLW00bY6l+GrZEREREYpAvoTu5bFGsLTRsiYiIiMQg371cbyxnIGsFVehEREQkBvkuipBSU4VOREREYtCmW39JkVShEym7Qw9NOgKRRqnd8bNPP4U+fRKNRaqLErpyWbMG6uvD4xpdPyJSLvfck3QEIo1Su2PdzJlQW5tkKFJldMi1XNKrc2bJxiIiIiJVRQlduej8OREREYlJIgmdmZ1rZu+b2TIzm2xmg/P03djMbjOz+Wa2yMyeNLOvpc0faGaeZWpfJydoUGERERGJSUHn0JlZN+BnwDHAJkCXzD7uXtCJYWZ2EnAZcAowE/g5cL+ZbefuK7M85SagM3AQsAg4D7jPzDZz9y/S+u0FvJ32+2eFxFM2uu2XSCLGjcv+WCQJ46KfcwYOpDbBOKT6FHpRxATgBGAS8BqQLfEq1FnABHefBGBmo4D5hIt/7sjSfzdglLs/H/W/GBgDDAaeS+v3qbt/1Ia44qUKnUgifv7zxsdK6CRpDbvjwIHckGAcUn0KTegOA85z9/9ty8rMrAswArg41ebui8zsGULili2hmwZ828weBpYC3wM+ICSW6R42s87Aq8BYd3+yLbGWnCp0IiIiEpNCE7p64K0SrK834Z6vH2e0zwc2zPGcbwG3A19EcXwMHOTuS6P5i4FzgKmAAacCU8xsJ3d/KXNhZjaGUOFrUFdX15rXUpR13nuPXYClq1czvQzrS8rixYvL8n5KaVX3dqtteFSNr7G6t10VShuqRNut8rTnz5u5e8udzMYCg9z9xDatzGwAMBfYwd1fSGv/B7DM3Udlec6fgG0J5/AtJiRjBwHbu/vCHOupA9529+/liaXhhRfyHrTZyy/DV78Kw4aFx1Wqrq6OWo2tVHGqebuljxJUjo96uVXztqtG6YNWVeHuWPWS/LxZ2h8zd282/lmhFbqlwF5mNhV4FPg8Y767++8KWM5nhCpbZjWuHzA9s7OZDQJOB7Z093eitv8HvAd8G/hTjvU8C+xQQDzlo2FLREREJCaFJnRXRD83I5zrlsmBFhM6d19hZi8C+wEPAphZD2BX4OosT+kW/axPW4ab2RryD7kyHJjTUjxlpdt+iYiISEwKSujcvZTj1V0NXGtmMwjDlowjHIa9F8DM3gAucPc7gTeAd4DrzOwCYAnwfUKF7+Go/yhgOfAi4fWcTEgYsyWeyVGFTkRERGJS9nu5uvtNZtYPGA/0IVzMcHDaGHRDgJ5R31VmdgjwG0IC15WQBB7u7rPSFjsWGEhI7F4BDnD39CFNkqcKnYiIiMSkqITOzLoCXyEkVk2kxokrhLuPJyR02eZZxu9vAkfkWdaNwI2FrjsxqtCJiIhITAq9U0RnwgUI383znILuFLHWUoVOREREYlJohW4scAAwGrgV+AHhfLbvAlsCZ8YRXFVRhU4kEaedlnQEIo1Su+O8efNgwIBEY5HqUmhCdyzh4oV/EBK66e4+A7jJzG4k3Eni/lgirBa69ZdIIiZOTDoCkUap3bHurbeU0ElJFXr16ibAW+5eT7jwoFfavFsICZ/ko1t/iYiISEwKTeg+BNaPHr9L+r10YKsSxlO9VKETERGRmBR6yLUO2Au4B7geGG9m2wArgSOBv8cRXFVRhU5ERERiUmhCdxFhzDjc/fcWbih2DOFODlcDv4gnvCqiCp1IIsaMaXys8+kkaandcd5WWzU51CXSVoXeKeIj4KO0339HAbf6kjQatkQkEddf3/hYCZ0krWF31AURUmLFDizcCxgKbAo84O4Lo8GGV7r7mjgCrBoatkRERERiUtBFEWbWwcx+BbwP/Ae4Gdgimn0H8LN4wqsiqtCJiIhITAq9yvUXwA+BcwlXtabfnutuwjh0ko8qdCIiIhKTQg+5jgYudPfrzCzzFl+zCXeLkHxUoRMREZGYFFqh6w28nmNeDaCyU0tUoRMREZGYFJrQvQXsn2NeLTCzJNFUM1XoREREJCaFHnL9HXC9ma0C/hW1bWJmuwNnEQ7JSj6q0ImIiEhMCh2H7gYz2wAYB1wYNd8FLAEudvd/xBJdNdHAwiIiIhKTgsehc/erzGwisAfhrhELgGnu/kVcwVUV3fpLREREYlLUwMLuvhh4OKZYqpsqdCKJGDs26QhEGqV2xzlz5sDAgQlGItUmZ0JnZnsXsyB3f7zt4VQxVehEEjFuXNIRiDQaF/2sU0InJZavQlcHePTY8vQj6pc5Pp2kU4VOREREYtLSIdclwJ3A/wHz4g+nimnYEhEREYlJvoRuK+D4aDoBeAK4Fbjd3T+PP7Qqo2FLREREJCY5Ezp3fxu4FLjUzLYHvg1cAkwws4eAScC/3X1ZWSKtdKrQiSTisLQ7Td9zT3JxiEDjjc8/GzqUqYlGItWm0HHoXgBeAH5iZnsSBhK+Gfg3cExs0VUTVehEEnHvvUlHINKoYXfs0yfJMKQKFTVsiZntQzgEezSwFJgeR1BVSRU6ERERiUmL93I1s13N7PdmNg+4D+gFnAb0c/fftGalZnaumb1vZsvMbLKZDc7Td2Mzu83M5pvZIjN70sy+ltFnRzN72syWm9lsMxvVmrhipQqdiIiIxCRnQmdmvzKz2cDjwGDgJ8CG7n6su9/h7itas0IzOwm4DDgf2AX4ArjfzHKVrm4CBgAHATsArwL3mVnPaHm9gIeAmdH83wJ/NrP9WhNfbFShExERkZjkO+T6U2ARcDvwKbAzsLNZ1iHp3N1/VOA6zwImuPskgKiaNh84FLgjS//dgFHu/nzU/2JgDCHJfA74DlAPfN/d64HXzGwv4EfA5AJjip8qdCIiIhKTfAndfwkDBu9ewHKckEDlZWZdgBHAxQ1PdF9kZs8QErdsCd004Ntm9jDhvL3vAR8Ar0XzdwOmRMlcyiNAqw4Hx0YDC4uIiEhM8g1bMjCG9fUm3FHi44z2+cCGOZ7zLUKV8AtCJe5j4CB3XxrN7we8nmV5fc2sg7uvSZ9hZmMIFb4GdXV1xb2KVvjasmV0BJ585hlWr7tu7OtLyuLFi8vyfkppVfd2q214VI2vsbq3XRWqrW14qO1Wedrz583cveVepVqZ2QBgLrBDNBRKqv0fwDJ3b3Yxg5n9CdgW+BmwmJCMHQRs7+4Lo8rd6+mHfM3sEMIFHDWZCV1an4YXXpb3YJ11YNkyWLwYunePf30JqaurozbtD5ZUhmrebulniZTxz13ZVPO2q0bpJy1V4e5Y9ZL8vKWf8ubuzc5/a/Eq1xL7jFBly6zG9aN51Q4zGwScDpzs7o9H59H9P0Lc3466Zavu9QM+yZXMlZOZhY2QuihC59CJiIhIiZU1oYuujH0RaLgC1cx6ALsCT2d5SrfoZ8P5cR7KaWtojP1poNbM0l/LyBzLS87q1eGnEjoREREpsaIGFi6Rq4FrzWwGYaiRcYTDsPcCmNkbwAXufifwBvAOcJ2ZXQAsAb5PqMg9HC3v79EyrjWz3wNfA44jHJZtFxpSuE6dmh7/EZHYXXdd0hGINErtjm+++SYMGZJoLFJdyp7QuftNZtYPGA/0AaYCB7t7dBkoQ4CeUd9V0flwvyEkcF0JSeDh7j4r6rPAzA4CJhBuTzYX+J67t5shSxqua1V1TqTsxoxpuY9IuaR2x7oPP1RCJyWVM6Ezs3HALe7+dqlX6u7jCQldtnmW8fubwBEtLO85wmHbdqkhjdOQJSIiIhKDfOfQXQC8aWbPmtmPzGyjcgVVbVShExERkTjlS+g2IlxRuhi4EnjfzB4xs1FmVr0DqcVAFToRERGJU86Ezt0XuvtEd98H2IxwK7D1gb8BH5vZP83sCDNT2akFqtCJJGfHHRsnkaTtGE1jtENKiRV0UYS7zyNU6a40s8HACYRx4O4AvjCzf7m7Tj3OQRU6keQ8/3zSEYg0atgdq/iOQZKMosehc/dZ7v5zwkUIEwhXpJ5a6sCqiSp0IiIiEqeihi0xs87AoYQK3SGEYURmALeWPrTq0ZDQqUInIiIiMWgxoYvuwDCSkMQdCawHzAKuAP6eGg9OcmsysLCIiIhIieUbh24P4HjgWKAv4V6rfyUkcc+VJ7zqoAqdiIiIxClfhe5J4EvgdsLttR6L7qMqRVKFTkREROKUL6E7BrjP3VeUK5hqpQqdiIiIxCnfVa6TgV+Z2T65OpjZPmZ2pQYazk/DloiIiEic8iV0ZxMugngqT5+pwOHAWaULqfpo2BIRERGJU76E7mjgGndfmatDdDh2AuHCCclBFToRERGJU75z6AYDLxSwjBejvpKDKnQiybn77qQjEGmU2h1feeUVGDYs0VikuuRL6OqBLgUsozOwpjThVCdV6ESSc9hhSUcg0ii1O6772WeJxiHVJ98h1zcIAwq3ZP+or+SgCp2IiIjEKV9Cdyvwwxaucq0FzgBuLm1Y1UUVOhEREYlTvkOuEwhXuT5sZncCDwH/BRzYDDiQcOHEE8Af4w2zsqlCJyIiInHKmdC5+yozOxC4FDidMNBw6k4RBiwGrgIucffVcQdayVShE0nOgAGNj+fNSy4OEYDU7rhy9935NNFIpNrkq9ClhiU538wuAXYENo5mzQVmuPvymOOrCqrQiSTnww+TjkCkUcPu2KWQaw5FCpc3oUuJErd8AwxLHrr1l4iIiMQp30URUiINdTlV6ERERCQGSujKQBU6ERERiZMSujLQRREiIiISJyV0ZaCLIkRERCRObUrozEwlpwKoQiciIiJxKiihM7MTzezMtN+HmtksYKmZ1ZlZv2JWambnmtn7ZrbMzCab2eA8fT3HdGwLfXYqJqY4qUInIiIicSq0QvdjYE3a79cAK4Gzgf7ArwpdoZmdBFwGnA/sAnwB3J+n2tc/Y/oJsBR4MKPfCRn9Xiw0pripQiciIiJxKmgcOmAg8BqAmfUB9gIOdfcHzewTYHwR6zwLmODuk6LljQLmA4cCd2R2dveP0n83syOAf7n7ooyuCzP7theq0ImIiEicCq3QraExL9kHWAVMiX7/EOhdyELMrAswAng01RYlZs8AuxXw/CHAHsDfssz+s5nNN7OnoqSv3VCFTiQ5zz3XOIkk7bloulY7pJRYoRW6l4AzzOwDQoXtsei2YACbESpshegN1AAfZ7TPBzYs4PknA+8A/8lov5iQYK4AjgLuNLPD3P2+zAWY2RhgTHpbXV1dIbG3WiqNe+m111jYrVus60ra4sWLY38/pfTWlu1WjS9xbdl21WZjbbeK1J4/b+buLXcy2xO4F1gPWASMdPfnonm3A/Xu/q0CljOAcB/YHdz9hbT2fwDL3H1UnufWAO8Df3L3S1tYzw3AJu4+Mk+fhhdeyHvQWmbGf4C9Af7zH9h779jW1R7U1dVRW1ubdBhSJG23yqVtV5m03SpTktvNzBoeu7tlzi/0Xq5PmdlmwFbAbHf/PG32X4C3C4znM6Ce5tW4fsD0Fp57UPS8GwtYz7OE8/zaBZ1DJyIiInEqeBw6d1/k7jMykjnc/X53f6vAZawgXH26X6rNzHoAuwJPt/D0U4DJ7v7fAlY1HJhTSEzloFt/iYiISJxyVujM7JIiluMtHQZNczVwrZnNAGYC4wiHYe+N1vsGcIG735kWSx/gMKDZIVkzOxToS7iwYjXhHLpTgWMz+yaloS6nCp1I2aUdpSDGsytECtKwO9bWot1RSinfIddzMn7vDKTO6F8OdI0eLyNcjFBQQufuN0UDEY8H+gBTgYPdfWXUZQjQM+Np3wGWAHfS3GrgR8AgwtW4bwDHpyeESVOFTkREROKU85Cru/dKTcD+hCtTTwV6uvs6hKTre1H7gcWs1N3Hu/sm7t7V3fd191lp88zdb8jo/4coluVZlvWgu49w9x7uvp677+Lu/ywmnripQiciIiJxKnTYkv8FfuvuDeO/RePH/dXMugETCHd9kCxUoRMREZE4FXpRxFeBd3PMmw0MLU041UkDC4uIiEicCk3o5gCnW/ogKED0+xnAeyWOq6po2BIRERGJU6GHXH8K/AuYZWb3EO7s0I9w5enmwDHxhFcdVKETERGROBU6sPC/zWxnQmJ3BNCfcA/X6cAx7v5ibBFWAVXoREREJE6FVuiIkrZvxxdK9VJCJyIiInEq+E4R0joNGXNNDXTQ2y0iIiKll+9OEXcXsRx39yNKEE/V0flzIiIiErd8h1zXA92ZpK10uFUkWXPnJh2BSKPU7jh16lTYY49EY5HqkjOhc/faMsZRtTSosEiyBgxIOgKRRqndsc/KlXn7iRRLJ3XFTLf9EhERkbgVnNCZ2fZm9k8z+9DMVkQ//2Fm28cZYKVThU5ERETiVtCwJWa2F/AI8BEwCfgY2BA4CphqZvu7+5OxRVnBVKETSda8eY2PdfhVkpbaHT/VP/lSYoWOQ3c5UAcc6u6rU41m9mPgvmj+10oeXRVQhU4kWRtv3PjYdZmXJKxhd9xjD111KCVV6CHX7YGr05M5AHevB64Gdih1YNVCw5aIiIhI3ApN6JYQ7t2azYbRfMlCw5aIiIhI3ApN6O4BrjCzkemN0e+/BooZhHitogqdiIiIxK3Qc+jOBbYDHjKzL4H5hIrdesCzwHnxhFf5VKETERGRuBWU0Ln7QjPbHTiUcPFDL2AB8CRwn7uviS/EyqYKnYiIiMQt371cNwA+TyVr0c+70eHVoqhCJyIiInHLdw7dJ8BOqV8smGhmm8YfVvVQhU5ERETili+hsyx9TwX6xhdO9VGFTkREROJW7L1cM5M8aYEGFhYREZG4FZvQSZF06y8RERGJW0tXuQ4xs9TdIWqin1ubNS/UufvzpQysWqhCJ5Is3e5L2pPU7lhXVwe1tQlGItWmpQrdDYRx5p4Fno7abklrexZ4LvpZMDM718zeN7NlZjbZzAbn6es5pmPT+mxpZo9Ey/vAzM4vJp44qUInIiIicctXodsnjhWa2UnAZcApwEzg58D9Zradu6/M8pT+Gb+fBIwFHoyW1wm4H3gL2BUYAtxgZp+6+1/jeA3FUIVORERE4pYzoXP3/8S0zrOACe4+CcDMRhHuPHEocEeWOD5K/93MjgD+5e6LoqYDgS2A3d19AfCymY0AzgYST+g0bImIiIjEreiLIqLx6C4xs41a8dwuwAjg0VRblJg9A+xWwPOHAHsAf0tr3g14PkrmUh4BhppZ92JjLDUNWyKSrBkzGieRpM2Ipjd79Eg6FKkyhd7LNV0HwiHPe4GPWuibqTfh4oqPM9rnAxsW8PyTgXeA9OphvxzLs2jeu+kzzGwMMCa9ra6uroBVt04qjXt37lzei3E97cXixYtjfT8lHtW83fbZp7bh8ZQpdQlFEZ9q3nbVaJ/UhRA77cQQbbeK054/b61J6CCB8ejMrIZw/tyf3Ft/3Zq7TwQmmlnDMmpjvNJoevRzi622You14Iqmurq6WN9Picfast2q8TWuLduuGmm7VZ72/Hkr9zh0nwH1NK/GZauyZTooet6NGe3Zqnv9CFeHz29dmKWjc+hEREQkbq1J6NYQrkydV+wT3X0F8CKwX6rNzHoQrk59OsfTUk4BJrv7fzPanwZ2MLNeaW0jgZnuvqTYGEtN59CJiIhI3IpO6Dz4eebVp0W4GviBmX3bzIYSxrqbSzgnDzN7w8yOSn+CmfUBDqPpxRApDxHOk7vBzIaZ2TGEK1x/38r4SkoVOhEREYlbi+fQRVezdk5VxizcJuIoYBAwG/i3u6/Os4gm3P0mM+sHjAf6AFOBg9PGoBsC9Mx42neAJcCdWZa3yswOAa4lDHD8GXBpexiDDlShExERkfjlTOjMbD3gH8D+0e//JiRW9xIGHV5FKEC9aGZ7u/viQlfq7uMJCV22ec0uuHD3PwB/yLO82ak42xsNLCwiIiJxy3fIdSywI/B94FjC4L3/Ar4CjHD3LoQx4TYCzo05zoqlW3+JiIhI3PIdcj0SGOvufwYwszmE+7Z+z91fBnD3p81sPDCacKGEZFCFTkREROKWr0K3MeFeqymvZvxMeREYWLqQqosqdCIiIhK3fBW6Lwl3dkhZRbgaNXMokG6EoUwkC1XoRJLVv3/SEYg0Su2OK1esgC5dEo1Fqku+Ct1rhPHhAHD3Ne6+qbvPzOg3nHC1q2ShYUtEkjVvXuMkkrR50fSvadOSDkWqTL4K3RXABgUsYyfgttKEU300bImIiIjELWdC5+4PFLIAd/9m6cKpPqrQiYiISNzKfS/XtY4qdCIiIhK3Fu8UIW2jCp1Isu65p/HxYYclF4cIQGp3fKV3b2qTDESqjhK6mKlCJ5Ksww9vfOyeXBwiAA2747BhXJhkIFJ1dMg1ZqrQiYiISNyU0MVMFToRERGJmxK6mGlgYREREYmbErqY6dZfIiIiEjcldDFThU5ERETipoQuTu6q0ImIiKylHnnkETp06MDgwYN5/vnnY12XEro41dfTAagHqKlJOBgREREppxEjRnDnnXcyb948JkyYEOu6lNDFadUqAFYmHIaIiIiUX9++fTniiCM46KCDeOmll2JdlxK6OK0MqdyqhMMQERGpVqNHj2bo0KE8+uijDB8+nG7duvH1r3+dOXPmsGDBAr71rW+x3nrrseWWW3Lbbbc1PG/atGkcfvjhDBgwgO7duzNixAhuvvnmJsv+8ssv2XzzzTnmmGOatJ9++un07t2befPmFRTjoEGDeO2111izZk3bX3AOulNEnFShE0ncDjskHYFIo9TuuGjRIlh33URjqSYfffQR5557LhdddBGdOnXirLPO4jvf+Q7rrLMOe++9N6eddhrXX3893/3ud9ltt93YfPPNee+999hzzz05/fTT6dq1K0899RSnnnoqa9asYdSoUQCst956/O1vf2PkyJHcfPPNbLrppjzwwANcd911/N///R8DBgxoMbYvvviCm2++mWXLljF79mwGDx4cz5vg7mvlBHhqis3cue7g8+JcRzszZcqUpEOQVtB2q1zadpWpvW63sV74F+lpWZ5/WhHPH1uimEeNGuVm5jNnzmxou+aaaxzwn/zkJw1tCxcu9JqaGv/973/fbBlr1qzxVatW+ZgxY3z33XdvNv+ss87ynj17+vXXX+/9+/f3448/vuD4Tj/9dO/Zs6cDfvvttxf56hpl5C3N3lIdco2TKnQiIiKxGzBgANttt13D71tttRUAI0eObGhbf/316devH++//z4ACxcu5KyzzmLzzTenU6dOdOrUiYkTJ/LWW281W/7ll19O//79OeOMM+jQoUPBFzhMmzaNiRMnctNNN9GlSxdmzpzZlpeZlxK6OOkcOhERkditv/76TX7vHI39mq19+fLlQDj3btKkSZx33nk8/PDDPPvss5xyyikN89N169aNI488klWrVnHCCSfQq1evFmNatWoVY8aM4bjjjuPwww9n22235ZVXXmndCyyAzqGLkyp0IiJSQcZFU2tNjKb2bvny5dx7771cddVVnHnmmQ3tuS5aePnll7nqqqsYPHgw11xzDSeffDLbbLNN3nWMHz+eefPmMXnyZACGDx/OM888U7oXkUEVujipQieSuIkTGyeRpKUSnnv69086lLXaihUrWLNmTUMlD8KFKnfffXezvitXruTEE09kl112YcKECQwdOpSTTjqJ1atX51z+7NmzufTSS7nyyivp168fAMOGDWPWrFmsWLGi9C8IVejiFSV0qtCJJOf73298PGZMcnGIADTsjkOGcGWSgazlevbsyc4778zll19O37596dixI5dffjk9e/Zk/vz5TfpecsklzJ49m5deeon333+fm266iR122IHLLruMcePGZV3+6aefzp577sno0aMb2oYPH059fT2vv/46I0aMKPlrSqRCZ2bnmtn7ZrbMzCabWd5reM1smJk9YGaLzWyRmT1uZl3S5nuWaaf4X0kLokOuqtCJiIi0L3//+98ZNGgQo0aN4qyzzuKYY47hpJNOatJn6tSp/Pa3v+XKK69kyy23BGCbbbbh17/+Nb/85S957rnnmi33lltu4amnnuLaa69t0j58+HCA2M6js3AlbPmY2UnAdcApwEzg58AwYDt3b1bMipK9Z4A/AbcBy4GvAne5+6qojwMnAFPSnvqpu+esh0bPASC29+DRR2H//XkX2OKee+Dgg6v+FmB1dXXU1tYmHYYUqZq3m1nj4zL/uSuLat521Shtd6QKd8eql+TnzdL+mLm7Zc5P4pDrWcAEd58EYGajgPnAocAdWfr/ErjH3S9Ka2t+TTEsdPePSh1sq9XXw49/DMBAgOOPh113hYceqvqkTkRERMqrrBW66DDpEuBQd38wrb0OmO7u52f0rwG+AK4Avg4MB94ALnT3J9P6OTAX6AzMAn7j7v/OEcMYYAywY6ptypQp2bq2Se9p09h23DhqVjYWHVd37crrl1zCZ7vvXvL1tReLFy+mR48eSYchRarm7bbPPrUNj6dMqUsoivhU87arRvukVXem1NUlFoe0TpKft3322afhcXuo0PUGaoCPM9rnAxtm6d8X6A78BLgA+DHh0OojZratu78b9buYcLh1BXAUcKeZHebu92Uu0N0nAhPTD7nGUj594omGc+hSOq5YwbD6eqjiwyM6/FOZ1pbtVo2vcW3ZdtVI263ytOfPW3u/yjV10cZd7n5N9PgFMzsAGEU0XI67/zLtOTPMbBPgHKBZQlc2228P3brB0qWNbd27QwxXtoiIiMjardxXuX4G1NO8GteP5lU7gE+j/m9ktL8ObJZnPc8CW7QyxtI4+GDYfXcWEV4APXqEc+gOPjjRsERERKT6lDWhc/cVwIvAfqk2M+sB7Ao8naX/SmAGkDmsyVbAe3lWNRyY07Zo26imBh56iOOBsQCTJumCCBEREYlFEodcrwauNbMZhGFLxhEuaLgXwMzeAC5w9zuj/lcBN5vZFOBJ4DvAEODGqP+hhHPtngFWE86hOxU4tkyvJ7eaGu4jHPe97NBDk45GREREqlTZEzp3v8nM+gHjgT7AVODgtDHohgA90/rfZma9CYlfX+Bl4AB3nxN1WQ38CBgErCEcnj0+LSEUkbWY/peS9iS1O3726afQp0+isUh1SeSiCHcfT0joss1rdimuu/8R+GOO/g8CD2abJyJyzz1JRyDSKLU71s2cWdUjHkj5JXLrLxEREREpHSV0IiIiIhVOCZ2IiIhUrNGjRzN06NCyrOvJJ5/kj3/MegZYM4888ggdOnRg8ODBPP/88zFHpoRORKrcuHGNk0jSxkXTDQMHJhqHtE4xCd2IESO48847mTdvHhMmTIg5svZ/pwgRkTb5+c8bHyupk6Q17I4DB3JDgnFI/Pr27csRRxzBQQcdxEsvvRT7+lShExERkYr3wAMPMHToULp27cqOO+7I0083vV/BtGnT2HfffenevTs9e/bkhBNOYP78+U36vPrqqxxyyCH07t2bddZZhyFDhvCb3/wGCId2H3roIV599VXMDDNj9OjRLcY1aNAgXnvtNdasWVOy15qNKnQiIiJS0T788EPOOOMMxo0bR69evbj88ss58MADmTVrFv369WPatGnU1tZyyCGHcNttt7FkyRIuvvhijjjiCKZNm9awnMMOO4wNN9yQv/zlL/Ts2ZO3336bDz74AICf/exnvPHGG3zyySfceuutQKjC5fPFF19w8803s2zZMmbPns3gwZk3viohd18rJ8BTU5zKsY72ZMqUKUmHIK1QzdsNGqdqVM3brhqlfxG1R2PHNv3M5JtOO6358087rfDnjx1bmphHjRrlgE+ePLmh7fPPP/d1113Xf/rTn7q7+9577+177LGHr1mzpqHPq6++6mbm9913n7u7f/LJJw743XffnXNdBx54oG+33XYFx3b66ad7z549HfDbb7+92JfWREbe0iyv0SFXERERqWg9e/Zk3333bfL7yJEjeeaZZ1i6dClPPfUUxx57LPX19axevZrVq1ez1VZbsemmm/Lss88C0Lt3bzbffHMuuOACbrzxxobKXGtNmzaNiRMnctNNN9GlSxdmzpzZpuW1RAmdiIiIVLRshz433HBDPvzwQxYuXEh9fT3nnHMOnTp1ajL997//5f333wfAzHj44YfZZptt+MEPfsCmm27KTjvtxOOPP150PKtWrWLMmDEcd9xxHH744Wy77ba88sorbX6d+egcOhEREQHaPsTPxIlhKrdPPvmkWdvHH39M//79WX/99TEzLrzwQo488shm/fqk3VN3q6224p///CerVq1i6tSpXHjhhRx22GHMnTuXHj16FBzP+PHjmTdvHpMnTwZg+PDhPPPMM8W/sCKoQiciIiIV7YsvvuCxxx5r8vujjz7KrrvuSvfu3dl99915/fXX2WmnnZpNA7OMCdipUye+/vWv89Of/pQvv/ySefPmAdCxY0eWL1+eN5bZs2dz6aWXcuWVV9KvXz8Ahg0bxqxZs1ixYkXpXnQGJXQiIiJS0TbYYANOPfVUbrrpJu6++24OPvhg3J2zzz4bgN/+9rfcd999HHfccdx5553U1dVxyy23MGrUKOrq6gB4+eWX2X///fnzn//MlClTuOuuu7jssssYOHAgW265JQCbb745c+bMYdKkSTz33HPMmTOnWSynn346e+65Z5MhTYYPH059fT2vv/56bO+BDrmKiIhIRevfvz9XXHEFP/7xj5k9ezbbbbcdDz30EBtuuCEAe+yxB08++SRjx47l5JNPZuXKlWyyySbst99+DBo0CICNNtqIjTbaiF//+tfMnTuXnj17stdee3HLLbdQU1MDwCGHHMKCBQs488wz+eyzzxg1ahQ33HBDQxy33HILTz31VLPz5YYPHw7AK6+8wogRI2J5DyxcCbv2MbOGFx7ne2Bmsa+jPamrq6O2tjbpMKRI1bzdxoxpfJzEuT1xq+ZtV41Su+O8efO4d8CARGOR4iX5eUvlEwDubpnzVaETkapWjUmcVK7U7lj31lughE5KSOfQiYiIiFQ4JXQiIiIiFU4JnYiIiEiF0zl0IlLVqv2iCKksDRdFbLUVtUkGIlVHCZ2IVLXrr298rIROktawO+qCCCkxHXIVERERqXBK6EREREQqnBI6ERERkQqnhE5ERESkwiWS0JnZuWb2vpktM7PJZja4hf7DzOwBM1tsZovM7HEz65I2f0szeyRa3gdmdn78r0JERESkfSh7QmdmJwGXAecDuwBfAPebWecc/QcD/wGeB/YAdgSuAdZE8zsB9wPLgV2Bc4CxZnZKvK9EREREpH1IYtiSs4AJ7j4JwMxGAfOBQ4E7svT/JXCPu1+U1vZW2uMDgS2A3d19AfCymY0Azgb+WvLoRURERNqZslboosOkI4BHU23uvgh4BtgtS/8a4BDgbTN71MzmR4dbv5bWbTfg+SiZS3kEGGpm3WN4GSIiIiLtSrkrdL2BGuDjjPb5wIZZ+vcFugM/AS4AfgycADxiZtu6+7tAvxzLs2jeu+kzzGwMjYN1p9pa81qKUo51iEh++hhKe6LdUUqpvV/lmorvLne/xt1fcPcfEw65jmrNAt19orvvVLIIRURERBJW7oTuM6Ce5tW4bFU2gE+j/m9ktL8ObBY9zlbd6wd4NE9ERESkqpX1kKu7rzCzF4H9gAcBzKwH4erUq7P0X2lmM4DMYU22Av4dPX4aON/Mern7wqhtJDDT3ZfkiUXV7hiY2XOqgFYebbfKpW1XmbTdKlN73m5JHHK9GviBmX3bzIYCNwBzgXsBzOwNMzsqrf9VwPFmNtrMBpnZWGAIcGM0/yHCeXI3ROPVHUO4wvX35XgxIiIiIkkr+7Al7n6TmfUDxgN9gKnAwe6+MuoyBOiZ1v82M+sNjCNcJPEycIC7z4nmrzKzQ4BrgWcJh3UvdXcNWZKMiUkHIK2i7Va5tO0qk7ZbZWq3283cPekYRERERKQN2vtVriIiIiLSAiV0IiIiIhVOCZ20mZldaGbPm9liM/vQzG40s42SjkuKY2ZXm5mb2elJxyL5mdlmZvYPM1toZkvM7Fkz2zjpuCQ/M+tpZhPNbF603Z43syOSjkuaMrOjzewRM1sQ/U0cmDF/y2j+MjP7wMzOTyjUJpTQSSl8jXA18s7AEYQLW7Ldl1faKTM7ANgbmJd0LJJfdJHYk8DnhCGahgO/AFYkGJYU5irC38tjgWGE4bf+ZWaZQ3NJsroDTwAXZc4ws07A/cBywpBr5wBjzeyUskaYhS6KkJIzs52B6cCG7q7Bndu5KEF4DjiS8AVzubtfm2hQkpOZ/QbY1d2/nnQsUhwzexX4m7uPT2tbAoxy938lF5lkY2ZbE25ksEVqZA0zO5RQsNgodQ95M/slcJi7D08qVlCFTuLRE1gNfJl0IFKQ64A/u/tLSQciBTkMeN7M7jCz+WY2XYftKsY04Egz62dmHczsO4S7IU1LOC4p3G7A86lkLvIIMNTMuicUE6CETkrMzLoAvwZudvflSccj+ZnZKGAT4PKkY5GCbQGcAbwCHAj8A7jDzPZINCopxJmEgfQ/JhwinwAc4e5zE41KipHtVqXzAYvmJabsAwtL9TKzGuBmoAb4UcLhSAvMbDPgCuDr7l6fdDxSsA7AdHcfG/3+gpntBYwhDNQu7dePgG2Ag4CPgKMJ59Dt6u5vJxqZVDxV6KQkzKwD8BfCib4HuvuihEOSlu0AbAi8amarzWw1sDkwwcyeSzY0yeMj4I2MtteBzRKIRQpkZt0IF6+c7e4PuftLUVL+GnBastFJEeYT/m6m6wd4NC8xqtBJm5mZEW6Hshewt7t/knBIUpjJhAQ83UOExPzG5t2lnZgGZF4VuRXwXgKxSOE6RVNmNbweFVcqydPA+WbWy90XRm0jgZnuviTBuJTQSUn8iTBcyaFAfdoYdAvS7tEr7UxURZ2Z3mZmq4B57j47maikAH8AHjezHwN3Er5MDiMMhyHtlLt/aWZPAFea2VmE87COJvwjfEmiwUkTZrYBoeI9MGra1szWB94m/NP7LnCDmV1MGKbrbOCssgeaQcOWSJuZWa6daB93rytnLNI2ZjYHDVvS7pnZMcBlhEPkbwE/c/e7k41KWmJmAwjnrY4E1gNmET5v/5doYNKEmY0G/pZl1j7uXmdmWwLXEpLxz4Cr3f2KMoaYlRI6ERERkQqn4/YiIiIiFU4JnYiIiEiFU0InIiIiUuGU0ImIiIhUOCV0IiIiIhVOCZ2IiIhIhVNCJyIiIlLhlNCJiIiIVDgldCIigJn92syWm1nZboloZtPN7Adpv+9vZmvMbJaZ7ZCl//Vmdn254hORyqGETkQkGA687u6ry7EyMzuKcK/Iv6Y1vwgcBQwAftD8WVwBnGRmg+OOT0QqixI6EZFgOPByGdd3NjDJ3ZelGtz9E3f/N/Ag8NXMJ7j728BTZE/2RGQtpoRORNZ6ZtYL2AR4JU+fLmb2CzN7x8yWmNmzZlabpd96ZvZHM/vUzD43syvN7CQzW2lmnaM+WxBu7P2vHKt7G9jWzLL9jf4n8J1yHhoWkfZPfxBEREJ1DnJU6MysC/AwIen7OTAXGA08YGbDosoZZtYJeAjoD5wPzAMuAo4GXnP3ldEi9wNWA9OzrKsncCLQDdgSmJXRZSrQBxgBPFf0KxWRqqSETkSkhYSOkJQNBYa5+zwAM/sPcBBwAvCLqN//AEOifnOjfrMIFbcb05a3M/CWu6/Isq7LgXWix8NontC9CtQDu6KETkQiOuQqImsNCzqmTTXRrOHAp+7+UZbn1ABnANemkjkAd18FfABsnFo2cBbwx1QyF3kXcMIFDyn9gU+yrGt3YAxwErCCkEQ2EV208Xm0DBERQAmdiKxdvg6sSpsmR+35LogYBvQmHHLNtAnhsCrANoSrUx/M6NMfMJomdF0JCVuD6HDtROA2d78beC1adzYrCIdkRUQAHXIVkbXLDMLhzpRF0YUH2wG5xnfrG/1sUr0zs6GERO/xqGlA9HN+xvNro58vprUtIAxZku68aBn7Rb+/TDisms36wGc55onIWkgVOhFZa7j7Ind/Lm16k3DhQXdyX+H63+jnlqmG6PDqLwlVtP9EzakEa1Bav67ABcB77v552jLfBLZI67cl8DPgXHdPJYSvAIOjCzJI69uXcI7dmwW9aBFZK6hCJyJru9QFEf3M7MiMebMISdszwFVRcrUM+D6wD7CXu6+J+s4E3ov6dSZcuPBjwiHXxzOW+xRwiZlt4u4fANcCT7n7DWl9XgZqCIdyX0xr3yn6+WTRr1REqpYSOhFZ26USul9nmXemu79qZt8ErgH+ErVPAXZy97dSHd19VdTvOmASIRn8NWGYkycylltHqOgdbGbLgD1pfr5c6py+YTRN6A4GnnD3jwt9gSJS/czdk45BRKQqmdm3gb8BX3H3DzPmXQls7+77FrG8joRDwD9195tKGqyIVDRV6ERESsDM9iJcRfss4arWkcAPgQszk7nIeOBtM/uqu79U4GpOABYDfy9ByCJSRZTQiYiUxjrA8cCF0e8vAye5+z+ydXb3D81sNI1X0RZiDXBKNBadiEgDHXIVERERqXAatkRERESkwimhExEREalwSuhEREREKpwSOhEREZEKp4ROREREpMIpoRMRERGpcEroRERERCqcEjoRERGRCvf/AVd+VLWUYu46AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# this can be done via plotting too!\n", + "from glmnet.plotting import cv_score_plot\n", + "cv_score_plot(model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## You can customize the plots based on your preferences!" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# the figures are totally customizable based on user's preferences\n", + "model.plot_cv_score(figsize=(12, 8),\n", + " linestyle='-.',\n", + " linewidth=5,\n", + " colors=[\"purple\", \"pink\", \"green\", \"navy\"],\n", + " marker=\"*\",\n", + " markersize=10,\n", + " fontsize=24,\n", + " grid=False,\n", + " legend=True,\n", + " legendloc='best',\n", + " xlabel=\"Your X-Label\",\n", + " ylabel=\"Your Y-Label\",\n", + " title=\"Your Title\",\n", + " save_path=None\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/glmnet/linear.py b/glmnet/linear.py index 30ae747..0150b93 100644 --- a/glmnet/linear.py +++ b/glmnet/linear.py @@ -14,7 +14,7 @@ _check_user_lambda, _interpolate_model, _score_lambda_path) - +from glmnet.plotting import coeff_path_plot, cv_score_plot class ElasticNet(BaseEstimator): """Elastic Net with squared error loss. @@ -198,6 +198,8 @@ def fit(self, X, y, sample_weight=None, relative_penalties=None, groups=None): self : object Returns self. """ + # keep local copy of features + self.X_ = X X, y = check_X_y(X, y, accept_sparse='csr', ensure_min_samples=2) if sample_weight is None: @@ -446,3 +448,150 @@ def r2_reverse(y_pred, y_true): # compute the score for each value of lambda return np.apply_along_axis(r2_reverse, 0, pred, y) + + def plot_coeff_path(self, feature_names=None, figsize=(10, 6), linestyle="-", fontsize=18, + grid=True, legend=True, legendloc="center", xlabel=None, ylabel=None, + title=None, yscale=None, bbox_to_anchor=None, save_path=None): + """Plot coefficient's paths vs -Log(lambda). + + Parameters + ---------- + feature_names : list, shape (n_features,) + Input features names neede for legend. + + figsize : tuple or list, as (width, height) + Figure size. + + linestyle: string + Linestyle of coefficients' paths. + + fontsize : int, float + Fontsize of the title. The fontsizes of xlabel, ylabel, + tick_params, and legend are resized with 0.85, 0.85, 0.75, + and 0.75 fraction of title fontsize, respectively. + + grid : bool + Whether to show (x,y) grid on the plot. + + legend: bool + Whether to show legend on the plot. + + legendloc: string + Legend location. + + xlabel : string or None + Xlabel of the plot. + + ylabel : string or None + Ylabel of the plot. + + title : string or None + Title of the plot. + + yscale: string or None + Scale for y-axis (coefficients). Valid options are + "linear", "log", "symlog", "logit". More on: + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.yscale.html + + bbox_to_anchor: tuple, list or None + Relative coordinates for legend location outside of the plot. + + save_path: string or None + The full or relative path to save the plot including the image format. + For example "myplot.png" or "../../myplot.pdf" + + Returns None + """ + coeff_path_plot(self, + feature_names=feature_names, + figsize=figsize, + linestyle=linestyle, + fontsize=fontsize, + grid=grid, + legend=legend, + legendloc=legendloc, + xlabel=xlabel, + ylabel=ylabel, + title=title, + yscale=yscale, + bbox_to_anchor=bbox_to_anchor, + save_path=save_path + ) + return None + + def plot_cv_score(self, figsize=(10, 6), linestyle="--", linewidth=3, colors=None, + marker="o", markersize=5, fontsize=18, grid=True, legend=True, + legendloc="best", xlabel=None, ylabel=None, title=None, save_path=None + ): + """Plot n-folds cross-validation scores vs -Log(lambda). + + Parameters + ---------- + figsize : tuple or list, as (width, height) + Figure size. + + linestyle: string + Linestyle of the vertical lamda lines. + + linewidth: integer or float + Linewidth of the vertical lamda lines. + + colors: list or tuple + Colors of the marker, errorbar line, max_lambda line, + and best_lambda line, respectively. The default colors + are ("red", "black", "cyan", "blue"). The length of the + passed tuple/list should be always four. + + marker: str, optional, (default="o") + Marker style. More details on: + (https://matplotlib.org/2.1.1/api/markers_api.html#module-matplotlib.markers) + + markersize: intger or float + Markersize. + + fontsize : int, float + Fontsize of the title. The fontsizes of xlabel, ylabel, + tick_params, and legend are resized with 0.85, 0.85, 0.75, + and 0.85 fraction of title fontsize, respectively. + + grid : bool + Whether to show (x,y) grid on the plot. + + legend: bool + Whether to show legend on the plot. + + legendloc: string + Legend location. + + xlabel : string or None + Xlabel of the plot. + + ylabel : string or None + Ylabel of the plot. + + title : string or None + Title of the plot. + + save_path: string or None + The full or relative path to save the image including the image format. + For example "myplot.png" or "../../myplot.pdf" + + Returns None + """ + cv_score_plot(self, + figsize=figsize, + linestyle=linestyle, + linewidth=linewidth, + colors=colors, + marker=marker, + markersize=markersize, + fontsize=fontsize, + grid=grid, + legend=legend, + legendloc=legendloc, + xlabel=xlabel, + ylabel=ylabel, + title=title, + save_path=save_path) + + return None \ No newline at end of file diff --git a/glmnet/logistic.py b/glmnet/logistic.py index cc8a190..fd3c149 100644 --- a/glmnet/logistic.py +++ b/glmnet/logistic.py @@ -16,6 +16,7 @@ _check_user_lambda, _interpolate_model, _score_lambda_path) +from glmnet.plotting import coeff_path_plot, cv_score_plot class LogitNet(BaseEstimator): @@ -203,6 +204,9 @@ def fit(self, X, y, sample_weight=None, relative_penalties=None, groups=None): self : object Returns self. """ + # keep local copy of features + self.X_ = X + X, y = check_X_y(X, y, accept_sparse='csr', ensure_min_samples=2) if sample_weight is None: sample_weight = np.ones(X.shape[0]) @@ -565,3 +569,158 @@ def score(self, X, y, lamb=None): """ pred = self.predict(X, lamb=lamb) return np.apply_along_axis(accuracy_score, 0, pred, y) + + def plot_coeff_path(self, feature_names=None, figsize=(10, 6), linestyle="-", fontsize=18, + grid=True, legend=True, legendloc="center", xlabel=None, ylabel=None, + title=None, yscale=None, bbox_to_anchor=None, save_path=None): + """Plot coefficient's paths vs -Log(lambda). + + Parameters + ---------- + est : estimator + The previously fitted estimator. + + feature_names : list, shape (n_features,) + Input features names neede for legend. + + figsize : tuple or list, as (width, height) + Figure size. + + linestyle: string + Linestyle of coefficients' paths. + + fontsize : int, float + Fontsize of the title. The fontsizes of xlabel, ylabel, + tick_params, and legend are resized with 0.85, 0.85, 0.75, + and 0.75 fraction of title fontsize, respectively. + + grid : bool + Whether to show (x,y) grid on the plot. + + legend: bool + Whether to show legend on the plot. + + legendloc: string + Legend location. + + xlabel : string or None + Xlabel of the plot. + + ylabel : string or None + Ylabel of the plot. + + title : string or None + Title of the plot. + + yscale: string or None + Scale for y-axis (coefficients). Valid options are + "linear", "log", "symlog", "logit". More on: + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.yscale.html + + bbox_to_anchor: tuple, list or None + Relative coordinates for legend location outside of the plot. + + save_path: string or None + The full or relative path to save the plot including the image format. + For example "myplot.png" or "../../myplot.pdf" + + Returns None + """ + coeff_path_plot(self, + feature_names=feature_names, + figsize=figsize, + linestyle=linestyle, + fontsize=fontsize, + grid=grid, + legend=legend, + legendloc=legendloc, + xlabel=xlabel, + ylabel=ylabel, + title=title, + yscale=yscale, + bbox_to_anchor=bbox_to_anchor, + save_path=save_path + ) + return None + + def plot_cv_score(self, figsize=(10, 6), linestyle="--", linewidth=3, colors=None, + marker="o", markersize=5, fontsize=18, grid=True, legend=True, + legendloc="best", xlabel=None, ylabel=None, title=None, save_path=None + ): + """Plot n-folds cross-validation scores vs -Log(lambda). + + Parameters + ---------- + figsize : tuple or list, as (width, height) + Figure size. + + linestyle: string + Linestyle of the vertical lamda lines. + + linewidth: integer or float + Linewidth of the vertical lamda lines. + + colors: list or tuple + Colors of the marker, errorbar line, max_lambda line, + and best_lambda line, respectively. The default colors + are ("red", "black", "cyan", "blue"). The length of the + passed tuple/list should be always four. + + marker: str, optional, (default="o") + Marker style. More details on: + (https://matplotlib.org/2.1.1/api/markers_api.html#module-matplotlib.markers) + + markersize: intger or float + Markersize. + + fontsize : int, float + Fontsize of the title. The fontsizes of xlabel, ylabel, + tick_params, and legend are resized with 0.85, 0.85, 0.75, + and 0.85 fraction of title fontsize, respectively. + + grid : bool + Whether to show (x,y) grid on the plot. + + legend: bool + Whether to show legend on the plot. + + legendloc: string + Legend location. + + xlabel : string or None + Xlabel of the plot. + + ylabel : string or None + Ylabel of the plot. + + title : string or None + Title of the plot. + + save_path: string or None + The full or relative path to save the image including the image format. + For example "myplot.png" or "../../myplot.pdf" + + Returns None + """ + cv_score_plot(self, + figsize=figsize, + linestyle=linestyle, + linewidth=linewidth, + colors=colors, + marker=marker, + markersize=markersize, + fontsize=fontsize, + grid=grid, + legend=legend, + legendloc=legendloc, + xlabel=xlabel, + ylabel=ylabel, + title=title, + save_path=save_path) + + return None + + + + + \ No newline at end of file diff --git a/glmnet/plotting.py b/glmnet/plotting.py new file mode 100644 index 0000000..a568d02 --- /dev/null +++ b/glmnet/plotting.py @@ -0,0 +1,403 @@ +import numpy as np +import pandas as pd +import matplotlib.pyplot as plt +import matplotlib as mpl + +mpl.rcParams["axes.linewidth"] = 3 +mpl.rcParams["lines.linewidth"] = 2 + + +def coeff_path_plot( + est, + feature_names=None, + figsize=(10, 6), + linestyle="-", + fontsize=18, + grid=True, + legend=True, + legendloc="center", + xlabel=None, + ylabel=None, + title=None, + bbox_to_anchor=None, + yscale=None, + save_path=None, +): + """Plot coefficient's paths vs -Log(lambda). + + Parameters + ---------- + est : estimator + The previously fitted estimator. + + feature_names : list, shape (n_features,) + Input features names neede for legend. + + figsize : tuple or list, as (width, height) + Figure size. + + linestyle: string + Linestyle of coefficients' paths. + + fontsize : int, float + Fontsize of the title. The fontsizes of xlabel, ylabel, + tick_params, and legend are resized with 0.85, 0.85, 0.75, + and 0.75 fraction of title fontsize, respectively. + + grid : bool + Whether to show (x,y) grid on the plot. + + legend: bool + Whether to show legend on the plot. + + legendloc: string + Legend location. + + xlabel : string or None + Xlabel of the plot. + + ylabel : string or None + Ylabel of the plot. + + title : string or None + Title of the plot. + + yscale: string or None + Scale for y-axis (coefficients). Valid options are + "linear", "log", "symlog", "logit". More on: + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.yscale.html + + bbox_to_anchor: tuple, list or None + Relative coordinates for legend location outside of the plot. + + save_path: string or None + The full or relative path to save the plot including the image format. + For example "myplot.png" or "../../myplot.pdf" + + Returns None + """ + # initializing feature_names + if feature_names is None: + if isinstance(est.X_, pd.DataFrame): + feature_names = est.X_.columns.tolist() + else: + feature_names = ["F_{i}" for i in range(est.X_.shape[1])] + else: + if ( + isinstance(feature_names, list) or isinstance(feature_names, tuple) + ) and len(feature_names) == est.X_.shape[1]: + feature_names = feature_names + else: + raise TypeError("Only tuple and list types are allowed for figsize.") + + # initializing figsize + if isinstance(figsize, list) or isinstance(figsize, tuple): + figsize = figsize + else: + raise TypeError("Only tuple and list types are allowed for figsize.") + + # initializing fontsize + if isinstance(fontsize, float) or isinstance(fontsize, int): + fontsize = fontsize + else: + raise TypeError("Only integer and float types are allowed for fontsize.") + + # initializing linestyle + if isinstance(linestyle, str): + linestyle = linestyle + else: + raise TypeError("Only string type is allowed for linestyle.") + + # initializing grid + if isinstance(grid, bool): + grid = grid + else: + raise TypeError("Only bool type is allowed for grid.") + + # initializing legend + if isinstance(legend, bool): + legend = legend + else: + raise TypeError("Only bool type is allowed for legend.") + + # initializing xlabel + if xlabel is None: + xlabel = r"-$Log(\lambda)$" + elif isinstance(xlabel, str): + xlabel = xlabel + else: + raise TypeError("Only string type is allowed for xlabel.") + + # initializing ylabel + if ylabel is None: + ylabel = "Coefficients" + elif isinstance(xlabel, str): + ylabel = ylabel + else: + raise TypeError("Only string type is allowed for ylabel.") + + # initializing title + if title is None: + title = fr"Best $\lambda$ = {est.lambda_best_[0]:.2} with {len(np.nonzero(np.reshape(est.coef_, (1,-1)))[1])} Features" + elif isinstance(title, str): + title = title + else: + raise TypeError("Only string type is allowed for title.") + + # initializing bbox_to_anchor + if bbox_to_anchor is None: + bbox_to_anchor = (1.2, 0.5) + elif isinstance(bbox_to_anchor, tuple) or isinstance(bbox_to_anchor, list): + bbox_to_anchor = bbox_to_anchor + else: + raise TypeError("Only tuple or list type is allowed for bbox_to_anchor.") + + # initializing yscale + if yscale is None: + yscale = "linear" + elif isinstance(yscale, str): + yscale = yscale + else: + raise TypeError("Only string type is allowed for yscale.") + + # plotting + fig, ax = plt.subplots(figsize=figsize) + for i in list(np.nonzero(np.reshape(est.coef_, (1, -1)))[1]): + plt.plot( + -np.log(est.lambda_path_), + (est.coef_path_.reshape(-1, est.coef_path_.shape[-1]))[i, :], + label=feature_names[i], + ) + + ax.tick_params(axis="both", which="major", labelsize=fontsize * 0.75) + ax.set_xlabel(xlabel, fontsize=fontsize * 0.85) + ax.set_title(title, fontsize=fontsize) + ax.set_ylabel(ylabel, fontsize=fontsize * 0.85) + ax.grid(grid) + ax.set_yscale(yscale) + + if legend: + ax.legend( + loc=legendloc, + bbox_to_anchor=bbox_to_anchor, + ncol=1, + prop={"size": fontsize * 0.75}, + framealpha=0.0, + fancybox=True, + ) + + if save_path: + plt.savefig(save_path, bbox_inches="tight", dpi=200) + + plt.show() + + +def cv_score_plot( + est, + figsize=(10, 6), + linestyle="--", + linewidth=3, + colors=None, + marker="o", + markersize=5, + fontsize=18, + grid=True, + legend=True, + legendloc="best", + xlabel=None, + ylabel=None, + title=None, + save_path=None, +): + """Plot n-folds cross-validation scores vs -Log(lambda). + + Parameters + ---------- + est : estimator + The previously fitted estimator. + + figsize : tuple or list, as (width, height) + Figure size. + + linestyle: string + Linestyle of the vertical lamda lines. + + linewidth: integer or float + Linewidth of the vertical lamda lines. + + colors: list or tuple + Colors of the marker, errorbar line, max_lambda line, + and best_lambda line, respectively. The default colors + are ("red", "black", "cyan", "blue"). The length of the + passed tuple/list should be always four. + + marker: str, optional, (default="o") + Marker style. More details on: + (https://matplotlib.org/2.1.1/api/markers_api.html#module-matplotlib.markers) + + markersize: intger or float + Markersize. + + fontsize : int, float + Fontsize of the title. The fontsizes of xlabel, ylabel, + tick_params, and legend are resized with 0.85, 0.85, 0.75, + and 0.85 fraction of title fontsize, respectively. + + grid : bool + Whether to show (x,y) grid on the plot. + + legend: bool + Whether to show legend on the plot. + + legendloc: string + Legend location. + + xlabel : string or None + Xlabel of the plot. + + ylabel : string or None + Ylabel of the plot. + + title : string or None + Title of the plot. + + save_path: string or None + The full or relative path to save the image including the image format. + For example "myplot.png" or "../../myplot.pdf" + + Returns None + """ + + # initializing figsize + if isinstance(figsize, list) or isinstance(figsize, tuple): + figsize = figsize + else: + raise TypeError("Only tuple and list types are allowed for figsize.") + + # initializing colors + if colors is None: + colors = ["red", "black", "cyan", "blue"] + elif (isinstance(colors, tuple) or isinstance(colors, list)) and len(colors) == 4: + colors = colors + else: + raise TypeError("Only tuple or list with length 4 is allowed for colors.") + + # initializing marker + if isinstance(marker, str): + marker = marker + else: + raise TypeError("Only str type is allowed for marker.") + + # initializing markersize + if isinstance(markersize, float) or isinstance(markersize, int): + markersize = markersize + else: + raise TypeError("Only int and float types are allowed for markersize.") + + # initializing fontsize + if isinstance(fontsize, float) or isinstance(fontsize, int): + fontsize = fontsize + else: + raise TypeError("Only integer and float types are allowed for fontsize.") + + # initializing linestyle + if isinstance(linestyle, str): + linestyle = linestyle + else: + raise TypeError("Only string type is allowed for linestyle.") + + # initializing linewidth + if isinstance(linewidth, int) or isinstance(linewidth, float): + linewidth = linewidth + else: + raise TypeError("Only string type is allowed for linewidth.") + + # initializing grid + if isinstance(grid, bool): + grid = grid + else: + raise TypeError("Only bool type is allowed for grid.") + + # initializing legend + if isinstance(legend, bool): + legend = legend + else: + raise TypeError("Only bool type is allowed for legend.") + + # initializing xlabel + if xlabel is None: + xlabel = r"-$Log(\lambda)$" + elif isinstance(xlabel, str): + xlabel = xlabel + else: + raise TypeError("Only string type is allowed for xlabel.") + + # initializing ylabel + if ylabel is None: + if est.scoring is None: + if est.__module__ == "glmnet.linear": + ylabel = fr"""{est.n_splits}-Folds CV Mean $R^2$""" + elif est.__module__ == "glmnet.logistic": + ylabel = f"""{est.n_splits}-Folds CV Mean ACCURACY""" + else: + ylabel = f"""{est.n_splits}-Folds CV Mean {' '.join((est.scoring).split("_")).upper()}""" + elif isinstance(ylabel, str): + ylabel = ylabel + else: + raise TypeError("Only string type is allowed for ylabel.") + + # initializing title + if title is None: + title = fr"Best $\lambda$ = {est.lambda_best_[0]:.2} with {len(np.nonzero(np.reshape(est.coef_, (1,-1)))[1])} Features" + elif isinstance(title, str): + title = title + else: + raise TypeError("Only string type is allowed for title.") + + # plotting + fig, ax = plt.subplots(figsize=figsize) + + ax.errorbar( + -np.log(est.lambda_path_), + est.cv_mean_score_, + yerr=est.cv_standard_error_, + c=colors[0], + ecolor=colors[1], + marker=marker, + markersize=markersize, + ) + + ax.vlines( + -np.log(est.lambda_max_), + ymin=min(est.cv_mean_score_) - 0.05, + ymax=max(est.cv_mean_score_) + 0.05, + linewidth=linewidth, + linestyles=linestyle, + colors=colors[2], + label=r"max $\lambda$", + ) + + ax.vlines( + -np.log(est.lambda_best_), + ymin=min(est.cv_mean_score_) - 0.05, + ymax=max(est.cv_mean_score_) + 0.05, + linewidth=linewidth, + linestyles=linestyle, + colors=colors[3], + label=r"best $\lambda$", + ) + + ax.set_ylim([min(est.cv_mean_score_) - 0.05, max(est.cv_mean_score_) + 0.05]) + ax.tick_params(axis="both", which="major", labelsize=fontsize * 0.75) + ax.set_xlabel(xlabel, fontsize=fontsize * 0.85) + ax.set_title(title, fontsize=fontsize) + ax.set_ylabel(ylabel, fontsize=fontsize * 0.85) + ax.grid(grid) + + if legend: + ax.legend(loc=legendloc, prop={"size": fontsize * 0.85}, framealpha=0.0) + + if save_path: + plt.savefig(save_path, bbox_inches="tight", dpi=200) + + plt.show()