{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "##Import libraries"
      ],
      "metadata": {
        "id": "WG4bQ0UNx-Mi"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "kgVMtNjjp6va"
      },
      "outputs": [],
      "source": [
        "from pathlib import Path\n",
        "import hashlib\n",
        "import json\n",
        "import platform\n",
        "import warnings\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import joblib\n",
        "import shap\n",
        "\n",
        "from scipy.stats import loguniform, randint, uniform\n",
        "\n",
        "from sklearn.model_selection import (\n",
        "    train_test_split,\n",
        "    StratifiedKFold,\n",
        "    RandomizedSearchCV,\n",
        "    cross_val_predict\n",
        ")\n",
        "\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "\n",
        "from sklearn.metrics import (\n",
        "    average_precision_score,\n",
        "    roc_auc_score,\n",
        "    brier_score_loss,\n",
        "    confusion_matrix,\n",
        "    recall_score,\n",
        "    precision_score,\n",
        "    f1_score,\n",
        "    fbeta_score,\n",
        "    matthews_corrcoef,\n",
        "    balanced_accuracy_score,\n",
        "    precision_recall_curve,\n",
        "    roc_curve\n",
        ")\n",
        "\n",
        "from sklearn.calibration import calibration_curve, CalibratedClassifierCV\n",
        "from sklearn.exceptions import ConvergenceWarning\n",
        "\n",
        "from imblearn.pipeline import Pipeline as ImbPipeline\n",
        "from imblearn.over_sampling import SMOTE\n",
        "\n",
        "from xgboost import XGBClassifier\n",
        "\n",
        "\n",
        "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
        "warnings.filterwarnings(\"ignore\", category=ConvergenceWarning)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Dataset Loading"
      ],
      "metadata": {
        "id": "8_SpOlvLytxX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from pathlib import Path\n",
        "import pandas as pd\n",
        "\n",
        "DATA_PATH = Path(\"/content/creditcard.csv\")\n",
        "\n",
        "df = pd.read_csv(DATA_PATH)\n",
        "\n",
        "print(\"Shape:\", df.shape)\n",
        "print(df.head())\n",
        "print(df.info())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "oH73kmlLyjvu",
        "outputId": "3179cb6b-3247-4d8c-8ca9-978eb43ad93e"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shape: (284807, 31)\n",
            "   Time        V1        V2        V3        V4        V5        V6        V7  \\\n",
            "0   0.0 -1.359807 -0.072781  2.536347  1.378155 -0.338321  0.462388  0.239599   \n",
            "1   0.0  1.191857  0.266151  0.166480  0.448154  0.060018 -0.082361 -0.078803   \n",
            "2   1.0 -1.358354 -1.340163  1.773209  0.379780 -0.503198  1.800499  0.791461   \n",
            "3   1.0 -0.966272 -0.185226  1.792993 -0.863291 -0.010309  1.247203  0.237609   \n",
            "4   2.0 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
            "\n",
            "         V8        V9  ...       V21       V22       V23       V24       V25  \\\n",
            "0  0.098698  0.363787  ... -0.018307  0.277838 -0.110474  0.066928  0.128539   \n",
            "1  0.085102 -0.255425  ... -0.225775 -0.638672  0.101288 -0.339846  0.167170   \n",
            "2  0.247676 -1.514654  ...  0.247998  0.771679  0.909412 -0.689281 -0.327642   \n",
            "3  0.377436 -1.387024  ... -0.108300  0.005274 -0.190321 -1.175575  0.647376   \n",
            "4 -0.270533  0.817739  ... -0.009431  0.798278 -0.137458  0.141267 -0.206010   \n",
            "\n",
            "        V26       V27       V28  Amount  Class  \n",
            "0 -0.189115  0.133558 -0.021053  149.62      0  \n",
            "1  0.125895 -0.008983  0.014724    2.69      0  \n",
            "2 -0.139097 -0.055353 -0.059752  378.66      0  \n",
            "3 -0.221929  0.062723  0.061458  123.50      0  \n",
            "4  0.502292  0.219422  0.215153   69.99      0  \n",
            "\n",
            "[5 rows x 31 columns]\n",
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 284807 entries, 0 to 284806\n",
            "Data columns (total 31 columns):\n",
            " #   Column  Non-Null Count   Dtype  \n",
            "---  ------  --------------   -----  \n",
            " 0   Time    284807 non-null  float64\n",
            " 1   V1      284807 non-null  float64\n",
            " 2   V2      284807 non-null  float64\n",
            " 3   V3      284807 non-null  float64\n",
            " 4   V4      284807 non-null  float64\n",
            " 5   V5      284807 non-null  float64\n",
            " 6   V6      284807 non-null  float64\n",
            " 7   V7      284807 non-null  float64\n",
            " 8   V8      284807 non-null  float64\n",
            " 9   V9      284807 non-null  float64\n",
            " 10  V10     284807 non-null  float64\n",
            " 11  V11     284807 non-null  float64\n",
            " 12  V12     284807 non-null  float64\n",
            " 13  V13     284807 non-null  float64\n",
            " 14  V14     284807 non-null  float64\n",
            " 15  V15     284807 non-null  float64\n",
            " 16  V16     284807 non-null  float64\n",
            " 17  V17     284807 non-null  float64\n",
            " 18  V18     284807 non-null  float64\n",
            " 19  V19     284807 non-null  float64\n",
            " 20  V20     284807 non-null  float64\n",
            " 21  V21     284807 non-null  float64\n",
            " 22  V22     284807 non-null  float64\n",
            " 23  V23     284807 non-null  float64\n",
            " 24  V24     284807 non-null  float64\n",
            " 25  V25     284807 non-null  float64\n",
            " 26  V26     284807 non-null  float64\n",
            " 27  V27     284807 non-null  float64\n",
            " 28  V28     284807 non-null  float64\n",
            " 29  Amount  284807 non-null  float64\n",
            " 30  Class   284807 non-null  int64  \n",
            "dtypes: float64(30), int64(1)\n",
            "memory usage: 67.4 MB\n",
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Configuration"
      ],
      "metadata": {
        "id": "jIxKZPK0yIlb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "SEED = 42\n",
        "\n",
        "DATA_PATH = Path(\"/content/creditcard.csv\")\n",
        "OUTPUT_DIR = Path(\"fraud_project_outputs\")\n",
        "FIG_DIR = OUTPUT_DIR / \"figures\"\n",
        "TABLE_DIR = OUTPUT_DIR / \"tables\"\n",
        "MODEL_DIR = OUTPUT_DIR / \"models\"\n",
        "\n",
        "for folder in [OUTPUT_DIR, FIG_DIR, TABLE_DIR, MODEL_DIR]:\n",
        "    folder.mkdir(parents=True, exist_ok=True)\n",
        "\n",
        "EXPECTED_COLUMNS = [\"Time\"] + [f\"V{i}\" for i in range(1, 29)] + [\"Amount\", \"Class\"]\n",
        "\n",
        "TEST_SIZE = 0.20\n",
        "\n",
        "CV_FOLDS = 3\n",
        "\n",
        "BOOTSTRAP_REPLICATES = 500\n",
        "SHAP_SAMPLE_SIZE = 300"
      ],
      "metadata": {
        "id": "u0LhAdLmyMwP"
      },
      "execution_count": 76,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Helper functions"
      ],
      "metadata": {
        "id": "Mu_ovEd-yTUM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "####Reproducibility helper functions"
      ],
      "metadata": {
        "id": "gducRognzlpg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def file_sha256(path, block_size=65536):\n",
        "    \"\"\"\n",
        "    Generate SHA-256 checksum for reproducibility.\n",
        "    \"\"\"\n",
        "    hasher = hashlib.sha256()\n",
        "\n",
        "    with open(path, \"rb\") as file:\n",
        "        for block in iter(lambda: file.read(block_size), b\"\"):\n",
        "            hasher.update(block)\n",
        "\n",
        "    return hasher.hexdigest()\n",
        "\n",
        "\n",
        "def save_json(obj, path):\n",
        "    \"\"\"\n",
        "    Save a dictionary as a JSON file.\n",
        "    \"\"\"\n",
        "    with open(path, \"w\", encoding=\"utf-8\") as file:\n",
        "        json.dump(obj, file, indent=2, default=str)\n",
        "\n",
        "\n",
        "def package_versions():\n",
        "    \"\"\"\n",
        "    Record package versions for reproducibility.\n",
        "    \"\"\"\n",
        "    import sklearn\n",
        "    import imblearn\n",
        "    import xgboost\n",
        "\n",
        "    return {\n",
        "        \"python\": platform.python_version(),\n",
        "        \"platform\": platform.platform(),\n",
        "        \"pandas\": pd.__version__,\n",
        "        \"numpy\": np.__version__,\n",
        "        \"sklearn\": sklearn.__version__,\n",
        "        \"imblearn\": imblearn.__version__,\n",
        "        \"xgboost\": xgboost.__version__,\n",
        "        \"shap\": shap.__version__\n",
        "    }"
      ],
      "metadata": {
        "id": "CyJ3w-I5zvqE"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####Dataset validation helper function"
      ],
      "metadata": {
        "id": "SGtRkPlYzyHu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def validate_dataset(df, data_path):\n",
        "    \"\"\"\n",
        "    Validate that the dataset matches the expected ULB credit-card fraud dataset.\n",
        "    \"\"\"\n",
        "    validation = {}\n",
        "\n",
        "    numeric_df = df.select_dtypes(include=[np.number])\n",
        "\n",
        "    validation[\"sha256\"] = file_sha256(data_path)\n",
        "    validation[\"rows\"] = int(df.shape[0])\n",
        "    validation[\"columns\"] = int(df.shape[1])\n",
        "    validation[\"column_names\"] = list(df.columns)\n",
        "    validation[\"columns_match_expected\"] = list(df.columns) == EXPECTED_COLUMNS\n",
        "    validation[\"missing_values_total\"] = int(df.isna().sum().sum())\n",
        "    validation[\"infinite_values_total\"] = int(np.isinf(numeric_df.to_numpy()).sum())\n",
        "    validation[\"non_numeric_columns\"] = df.select_dtypes(exclude=[np.number]).columns.tolist()\n",
        "    validation[\"target_values\"] = sorted(df[\"Class\"].dropna().unique().astype(int).tolist())\n",
        "    validation[\"class_counts\"] = df[\"Class\"].value_counts().sort_index().astype(int).to_dict()\n",
        "    validation[\"duplicate_rows_after_first\"] = int(df.duplicated().sum())\n",
        "\n",
        "    validation[\"zero_variance_columns\"] = [\n",
        "        col for col in df.columns\n",
        "        if df[col].nunique(dropna=False) <= 1\n",
        "    ]\n",
        "\n",
        "    validation[\"package_versions\"] = package_versions()\n",
        "\n",
        "    if list(df.columns) != EXPECTED_COLUMNS:\n",
        "        raise ValueError(\"Unexpected columns. Check that the uploaded file is creditcard.csv.\")\n",
        "\n",
        "    if validation[\"missing_values_total\"] != 0:\n",
        "        raise ValueError(\"Missing values found. Add fold-contained imputation before modelling.\")\n",
        "\n",
        "    if validation[\"infinite_values_total\"] != 0:\n",
        "        raise ValueError(\"Infinite values found. Clean the dataset before modelling.\")\n",
        "\n",
        "    if validation[\"non_numeric_columns\"]:\n",
        "        raise ValueError(\"Non-numeric columns found. Add encoding before modelling.\")\n",
        "\n",
        "    if validation[\"target_values\"] != [0, 1]:\n",
        "        raise ValueError(\"Target column Class must contain only 0 and 1.\")\n",
        "\n",
        "    return validation"
      ],
      "metadata": {
        "id": "FOWBa3PVz1Ut"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####Class imbalance helper function"
      ],
      "metadata": {
        "id": "-efqCo9uz31S"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def class_prevalence_table(y):\n",
        "    \"\"\"\n",
        "    Return class counts and percentages.\n",
        "    \"\"\"\n",
        "    counts = y.value_counts().sort_index()\n",
        "    percentages = counts / len(y) * 100\n",
        "\n",
        "    table = pd.DataFrame({\n",
        "        \"class\": counts.index,\n",
        "        \"count\": counts.values,\n",
        "        \"percentage\": percentages.values\n",
        "    })\n",
        "\n",
        "    table[\"label\"] = table[\"class\"].map({\n",
        "        0: \"Legitimate\",\n",
        "        1: \"Fraud\"\n",
        "    })\n",
        "\n",
        "    return table[[\"class\", \"label\", \"count\", \"percentage\"]]"
      ],
      "metadata": {
        "id": "DYOrRpelz843"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Plotting helper functions"
      ],
      "metadata": {
        "id": "VV0KzM1a0BZd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_class_distribution(y, output_path):\n",
        "    \"\"\"\n",
        "    Plot class distribution using a logarithmic y-axis.\n",
        "    \"\"\"\n",
        "    counts = y.value_counts().sort_index()\n",
        "\n",
        "    plt.figure(figsize=(7, 5))\n",
        "    plt.bar([\"Legitimate\", \"Fraud\"], counts.values)\n",
        "    plt.yscale(\"log\")\n",
        "    plt.ylabel(\"Number of transactions, log scale\")\n",
        "    plt.title(\"Class Distribution in Credit Card Fraud Dataset\")\n",
        "\n",
        "    for i, value in enumerate(counts.values):\n",
        "        plt.text(i, value, f\"{value:,}\", ha=\"center\", va=\"bottom\")\n",
        "\n",
        "    plt.tight_layout()\n",
        "    plt.savefig(output_path, dpi=300)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "def plot_amount_distribution(train_df, output_path):\n",
        "    \"\"\"\n",
        "    Plot transaction amount distribution using log(Amount + 1).\n",
        "    \"\"\"\n",
        "    plt.figure(figsize=(8, 5))\n",
        "\n",
        "    plt.hist(\n",
        "        np.log1p(train_df.loc[train_df[\"Class\"] == 0, \"Amount\"]),\n",
        "        bins=60,\n",
        "        alpha=0.7,\n",
        "        label=\"Legitimate\"\n",
        "    )\n",
        "\n",
        "    plt.hist(\n",
        "        np.log1p(train_df.loc[train_df[\"Class\"] == 1, \"Amount\"]),\n",
        "        bins=60,\n",
        "        alpha=0.7,\n",
        "        label=\"Fraud\"\n",
        "    )\n",
        "\n",
        "    plt.xlabel(\"log(Amount + 1)\")\n",
        "    plt.ylabel(\"Frequency\")\n",
        "    plt.title(\"Training-Set Amount Distribution\")\n",
        "    plt.legend()\n",
        "    plt.tight_layout()\n",
        "    plt.savefig(output_path, dpi=300)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "def plot_transactions_by_hour(train_df, output_path):\n",
        "    \"\"\"\n",
        "    Plot transaction counts by hour.\n",
        "    \"\"\"\n",
        "    temp = train_df.copy()\n",
        "    temp[\"hour\"] = (temp[\"Time\"] // 3600).astype(int)\n",
        "\n",
        "    hourly = temp.groupby([\"hour\", \"Class\"]).size().unstack(fill_value=0)\n",
        "\n",
        "    plt.figure(figsize=(10, 5))\n",
        "\n",
        "    if 0 in hourly.columns:\n",
        "        plt.plot(hourly.index, hourly[0], marker=\"o\", label=\"Legitimate\")\n",
        "\n",
        "    if 1 in hourly.columns:\n",
        "        plt.plot(hourly.index, hourly[1], marker=\"o\", label=\"Fraud\")\n",
        "\n",
        "    plt.xlabel(\"Hour from first transaction\")\n",
        "    plt.ylabel(\"Transaction count\")\n",
        "    plt.title(\"Training-Set Transactions by Hour\")\n",
        "    plt.legend()\n",
        "    plt.tight_layout()\n",
        "    plt.savefig(output_path, dpi=300)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "def plot_precision_recall_curve(y_true, y_score, output_path, title):\n",
        "    \"\"\"\n",
        "    Save precision-recall curve.\n",
        "    \"\"\"\n",
        "    precision, recall, _ = precision_recall_curve(y_true, y_score)\n",
        "    ap = average_precision_score(y_true, y_score)\n",
        "\n",
        "    plt.figure(figsize=(7, 5))\n",
        "    plt.plot(recall, precision, label=f\"Average precision = {ap:.4f}\")\n",
        "    plt.xlabel(\"Recall\")\n",
        "    plt.ylabel(\"Precision\")\n",
        "    plt.title(title)\n",
        "    plt.legend()\n",
        "    plt.tight_layout()\n",
        "    plt.savefig(output_path, dpi=300)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "def plot_roc_curve_custom(y_true, y_score, output_path, title):\n",
        "    \"\"\"\n",
        "    Save ROC curve.\n",
        "    \"\"\"\n",
        "    fpr, tpr, _ = roc_curve(y_true, y_score)\n",
        "    auc = roc_auc_score(y_true, y_score)\n",
        "\n",
        "    plt.figure(figsize=(7, 5))\n",
        "    plt.plot(fpr, tpr, label=f\"ROC-AUC = {auc:.4f}\")\n",
        "    plt.plot([0, 1], [0, 1], linestyle=\"--\")\n",
        "    plt.xlabel(\"False-positive rate\")\n",
        "    plt.ylabel(\"True-positive rate\")\n",
        "    plt.title(title)\n",
        "    plt.legend()\n",
        "    plt.tight_layout()\n",
        "    plt.savefig(output_path, dpi=300)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "def plot_confusion_matrix_from_metrics(metrics, output_path, title):\n",
        "    \"\"\"\n",
        "    Save confusion matrix using already-computed metrics.\n",
        "    \"\"\"\n",
        "    matrix = np.array([\n",
        "        [metrics[\"tn\"], metrics[\"fp\"]],\n",
        "        [metrics[\"fn\"], metrics[\"tp\"]]\n",
        "    ])\n",
        "\n",
        "    plt.figure(figsize=(6, 5))\n",
        "    plt.imshow(matrix)\n",
        "\n",
        "    plt.xticks(\n",
        "        [0, 1],\n",
        "        [\"Predicted legitimate\", \"Predicted fraud\"],\n",
        "        rotation=30,\n",
        "        ha=\"right\"\n",
        "    )\n",
        "\n",
        "    plt.yticks(\n",
        "        [0, 1],\n",
        "        [\"Actual legitimate\", \"Actual fraud\"]\n",
        "    )\n",
        "\n",
        "    for i in range(2):\n",
        "        for j in range(2):\n",
        "            plt.text(j, i, f\"{matrix[i, j]:,}\", ha=\"center\", va=\"center\")\n",
        "\n",
        "    plt.title(title)\n",
        "    plt.colorbar()\n",
        "    plt.tight_layout()\n",
        "    plt.savefig(output_path, dpi=300)\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "def plot_calibration_curve_custom(y_true, y_score, output_path, title):\n",
        "    \"\"\"\n",
        "    Save calibration curve.\n",
        "    \"\"\"\n",
        "    frac_pos, mean_pred = calibration_curve(\n",
        "        y_true,\n",
        "        y_score,\n",
        "        n_bins=10,\n",
        "        strategy=\"quantile\"\n",
        "    )\n",
        "\n",
        "    plt.figure(figsize=(6, 5))\n",
        "    plt.plot(mean_pred, frac_pos, marker=\"o\", label=\"Model\")\n",
        "    plt.plot([0, 1], [0, 1], linestyle=\"--\", label=\"Perfect calibration\")\n",
        "    plt.xlabel(\"Mean predicted probability\")\n",
        "    plt.ylabel(\"Fraction of positives\")\n",
        "    plt.title(title)\n",
        "    plt.legend()\n",
        "    plt.tight_layout()\n",
        "    plt.savefig(output_path, dpi=300)\n",
        "    plt.show()"
      ],
      "metadata": {
        "id": "BgtsC00Z0Gb0"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####Descriptive feature analysis helper function"
      ],
      "metadata": {
        "id": "21GjfQFB0J8Y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def top_class_correlations(train_df, n=15):\n",
        "    \"\"\"\n",
        "    Return features with strongest absolute Pearson correlation with Class.\n",
        "\n",
        "    This is descriptive only.\n",
        "    It should not be used for full-dataset feature selection.\n",
        "    \"\"\"\n",
        "    correlations = train_df.corr(numeric_only=True)[\"Class\"].drop(\"Class\")\n",
        "    top_features = correlations.abs().sort_values(ascending=False).head(n).index\n",
        "\n",
        "    output = correlations.loc[top_features].reset_index()\n",
        "    output.columns = [\"feature\", \"correlation_with_class\"]\n",
        "\n",
        "    return output"
      ],
      "metadata": {
        "id": "XzES5rPw0Men"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####Prediction evaluation helper function"
      ],
      "metadata": {
        "id": "OFP6qrTQ0QFn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def evaluate_predictions(y_true, y_score, threshold=0.5):\n",
        "    \"\"\"\n",
        "    Evaluate predictions at a specific threshold.\n",
        "    \"\"\"\n",
        "    y_pred = (y_score >= threshold).astype(int)\n",
        "\n",
        "    tn, fp, fn, tp = confusion_matrix(\n",
        "        y_true,\n",
        "        y_pred,\n",
        "        labels=[0, 1]\n",
        "    ).ravel()\n",
        "\n",
        "    return {\n",
        "        \"threshold\": float(threshold),\n",
        "        \"average_precision\": float(average_precision_score(y_true, y_score)),\n",
        "        \"roc_auc\": float(roc_auc_score(y_true, y_score)),\n",
        "        \"brier_score\": float(brier_score_loss(y_true, y_score)),\n",
        "        \"recall\": float(recall_score(y_true, y_pred, zero_division=0)),\n",
        "        \"precision\": float(precision_score(y_true, y_pred, zero_division=0)),\n",
        "        \"f1\": float(f1_score(y_true, y_pred, zero_division=0)),\n",
        "        \"f2\": float(fbeta_score(y_true, y_pred, beta=2, zero_division=0)),\n",
        "        \"mcc\": float(matthews_corrcoef(y_true, y_pred)),\n",
        "        \"balanced_accuracy\": float(balanced_accuracy_score(y_true, y_pred)),\n",
        "        \"tn\": int(tn),\n",
        "        \"fp\": int(fp),\n",
        "        \"fn\": int(fn),\n",
        "        \"tp\": int(tp),\n",
        "        \"frauds_detected\": int(tp),\n",
        "        \"frauds_missed\": int(fn),\n",
        "        \"legitimate_flagged\": int(fp)\n",
        "    }"
      ],
      "metadata": {
        "id": "2ubTCgyd0TH-"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####Threshold selection helper functions"
      ],
      "metadata": {
        "id": "cEhcZJSh0Xwm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def select_f2_threshold(y_true, y_score):\n",
        "    \"\"\"\n",
        "    Select threshold that maximises F2 score.\n",
        "\n",
        "    F2 gives more weight to recall than precision.\n",
        "    \"\"\"\n",
        "    precision, recall, thresholds = precision_recall_curve(y_true, y_score)\n",
        "\n",
        "    rows = []\n",
        "\n",
        "    for p, r, t in zip(precision[:-1], recall[:-1], thresholds):\n",
        "        beta = 2\n",
        "        beta_squared = beta ** 2\n",
        "\n",
        "        denominator = (beta_squared * p) + r\n",
        "\n",
        "        if denominator == 0:\n",
        "            f2 = 0\n",
        "        else:\n",
        "            f2 = (1 + beta_squared) * p * r / denominator\n",
        "\n",
        "        rows.append({\n",
        "            \"threshold\": float(t),\n",
        "            \"precision\": float(p),\n",
        "            \"recall\": float(r),\n",
        "            \"f2\": float(f2)\n",
        "        })\n",
        "\n",
        "    threshold_table = pd.DataFrame(rows)\n",
        "\n",
        "    threshold_table = threshold_table.sort_values(\n",
        "        [\"f2\", \"precision\"],\n",
        "        ascending=False\n",
        "    ).reset_index(drop=True)\n",
        "\n",
        "    best_threshold = float(threshold_table.loc[0, \"threshold\"])\n",
        "\n",
        "    return best_threshold, threshold_table\n",
        "\n",
        "\n",
        "def select_cost_threshold(y_true, y_score, fn_cost, fp_cost=1):\n",
        "    \"\"\"\n",
        "    Select threshold that minimises expected cost.\n",
        "\n",
        "    total cost = FN cost * false negatives + FP cost * false positives\n",
        "    \"\"\"\n",
        "    candidate_thresholds = np.unique(\n",
        "        np.r_[np.quantile(y_score, np.linspace(0, 1, 1001)), 0.5]\n",
        "    )\n",
        "\n",
        "    rows = []\n",
        "\n",
        "    for threshold in candidate_thresholds:\n",
        "        y_pred = (y_score >= threshold).astype(int)\n",
        "\n",
        "        tn, fp, fn, tp = confusion_matrix(\n",
        "            y_true,\n",
        "            y_pred,\n",
        "            labels=[0, 1]\n",
        "        ).ravel()\n",
        "\n",
        "        total_cost = (fn_cost * fn) + (fp_cost * fp)\n",
        "\n",
        "        rows.append({\n",
        "            \"threshold\": float(threshold),\n",
        "            \"fn_cost\": float(fn_cost),\n",
        "            \"fp_cost\": float(fp_cost),\n",
        "            \"total_cost\": float(total_cost),\n",
        "            \"tp\": int(tp),\n",
        "            \"fp\": int(fp),\n",
        "            \"fn\": int(fn),\n",
        "            \"tn\": int(tn),\n",
        "            \"recall\": float(recall_score(y_true, y_pred, zero_division=0)),\n",
        "            \"precision\": float(precision_score(y_true, y_pred, zero_division=0))\n",
        "        })\n",
        "\n",
        "    cost_table = pd.DataFrame(rows)\n",
        "\n",
        "    cost_table = cost_table.sort_values(\n",
        "        [\"total_cost\", \"fp\", \"fn\"],\n",
        "        ascending=True\n",
        "    ).reset_index(drop=True)\n",
        "\n",
        "    best_threshold = float(cost_table.loc[0, \"threshold\"])\n",
        "\n",
        "    return best_threshold, cost_table"
      ],
      "metadata": {
        "id": "JwmT4L770jUi"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####Bootstrap confidence interval helper function"
      ],
      "metadata": {
        "id": "jNj_GNJP0mUn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def bootstrap_confidence_intervals(\n",
        "    y_true,\n",
        "    y_score,\n",
        "    threshold,\n",
        "    n_reps=500,\n",
        "    seed=42\n",
        "):\n",
        "    \"\"\"\n",
        "    Bootstrap confidence intervals for selected test-set metrics.\n",
        "    \"\"\"\n",
        "    rng = np.random.default_rng(seed)\n",
        "\n",
        "    y_true = np.asarray(y_true)\n",
        "    y_score = np.asarray(y_score)\n",
        "\n",
        "    n = len(y_true)\n",
        "    rows = []\n",
        "\n",
        "    valid_replicates = 0\n",
        "    attempts = 0\n",
        "    max_attempts = n_reps * 10\n",
        "\n",
        "    while valid_replicates < n_reps and attempts < max_attempts:\n",
        "        attempts += 1\n",
        "\n",
        "        sample_index = rng.integers(0, n, size=n)\n",
        "        y_sample = y_true[sample_index]\n",
        "        score_sample = y_score[sample_index]\n",
        "\n",
        "        if len(np.unique(y_sample)) < 2:\n",
        "            continue\n",
        "\n",
        "        metrics = evaluate_predictions(\n",
        "            y_sample,\n",
        "            score_sample,\n",
        "            threshold\n",
        "        )\n",
        "\n",
        "        rows.append(metrics)\n",
        "        valid_replicates += 1\n",
        "\n",
        "    boot_df = pd.DataFrame(rows)\n",
        "\n",
        "    summary = []\n",
        "\n",
        "    for metric in [\n",
        "        \"average_precision\",\n",
        "        \"roc_auc\",\n",
        "        \"recall\",\n",
        "        \"precision\",\n",
        "        \"f1\",\n",
        "        \"f2\",\n",
        "        \"mcc\",\n",
        "        \"balanced_accuracy\"\n",
        "    ]:\n",
        "        summary.append({\n",
        "            \"metric\": metric,\n",
        "            \"mean\": boot_df[metric].mean(),\n",
        "            \"ci_2_5\": boot_df[metric].quantile(0.025),\n",
        "            \"ci_97_5\": boot_df[metric].quantile(0.975),\n",
        "            \"valid_replicates\": valid_replicates\n",
        "        })\n",
        "\n",
        "    return pd.DataFrame(summary)"
      ],
      "metadata": {
        "id": "bq4TLlPK0skE"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Validate dataset"
      ],
      "metadata": {
        "id": "zOQS0r6g1Az2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "validation = validate_dataset(df, DATA_PATH)\n",
        "\n",
        "save_json(validation, TABLE_DIR / \"dataset_validation.json\")\n",
        "\n",
        "print(\"\\nDataset validation summary:\")\n",
        "for key, value in validation.items():\n",
        "    if key != \"package_versions\":\n",
        "        print(f\"{key}: {value}\")\n",
        "\n",
        "print(\"\\nPackage versions:\")\n",
        "print(validation[\"package_versions\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "qGJ-3_y91DtE",
        "outputId": "f8ec7f40-267f-4651-fac5-653c0b6d39ae"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Dataset validation summary:\n",
            "sha256: 76274b691b16a6c49d3f159c883398e03ccd6d1ee12d9d8ee38f4b4b98551a89\n",
            "rows: 284807\n",
            "columns: 31\n",
            "column_names: ['Time', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6', 'V7', 'V8', 'V9', 'V10', 'V11', 'V12', 'V13', 'V14', 'V15', 'V16', 'V17', 'V18', 'V19', 'V20', 'V21', 'V22', 'V23', 'V24', 'V25', 'V26', 'V27', 'V28', 'Amount', 'Class']\n",
            "columns_match_expected: True\n",
            "missing_values_total: 0\n",
            "infinite_values_total: 0\n",
            "non_numeric_columns: []\n",
            "target_values: [0, 1]\n",
            "class_counts: {0: 284315, 1: 492}\n",
            "duplicate_rows_after_first: 1081\n",
            "zero_variance_columns: []\n",
            "\n",
            "Package versions:\n",
            "{'python': '3.12.13', 'platform': 'Linux-6.6.122+-x86_64-with-glibc2.35', 'pandas': '2.2.2', 'numpy': '2.0.2', 'sklearn': '1.6.1', 'imblearn': '0.14.2', 'xgboost': '3.3.0', 'shap': '0.52.0'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Full-dataset class prevalence"
      ],
      "metadata": {
        "id": "5GQ3qZov1PkF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class_table = class_prevalence_table(df[\"Class\"])\n",
        "class_table.to_csv(TABLE_DIR / \"full_dataset_class_prevalence.csv\", index=False)\n",
        "\n",
        "print(\"\\nClass prevalence:\")\n",
        "print(class_table)\n",
        "\n",
        "fraud_count = int((df[\"Class\"] == 1).sum())\n",
        "legitimate_count = int((df[\"Class\"] == 0).sum())\n",
        "fraud_prevalence = fraud_count / len(df) * 100\n",
        "imbalance_ratio = legitimate_count / fraud_count\n",
        "\n",
        "print(f\"\\nFraud cases: {fraud_count}\")\n",
        "print(f\"Legitimate cases: {legitimate_count}\")\n",
        "print(f\"Fraud prevalence: {fraud_prevalence:.4f}%\")\n",
        "print(f\"Majority-minority ratio: {imbalance_ratio:.2f}:1\")\n",
        "\n",
        "plot_class_distribution(\n",
        "    df[\"Class\"],\n",
        "    FIG_DIR / \"class_distribution_log_scale.png\"\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 695
        },
        "id": "AtIrv9dL1SaW",
        "outputId": "5653a2b1-fae6-4fde-a69f-35db93bce78a"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Class prevalence:\n",
            "   class       label   count  percentage\n",
            "0      0  Legitimate  284315   99.827251\n",
            "1      1       Fraud     492    0.172749\n",
            "\n",
            "Fraud cases: 492\n",
            "Legitimate cases: 284315\n",
            "Fraud prevalence: 0.1727%\n",
            "Majority-minority ratio: 577.88:1\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Separate predictors and target"
      ],
      "metadata": {
        "id": "ALlwZRtC1Xrm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X = df.drop(columns=[\"Class\"])\n",
        "y = df[\"Class\"].astype(int)\n",
        "\n",
        "print(\"\\nPredictor shape:\", X.shape)\n",
        "print(\"Target shape:\", y.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "W_hdKaTq1agB",
        "outputId": "b141b38b-2682-45e9-9d68-5bad536c0cf7"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Predictor shape: (284807, 30)\n",
            "Target shape: (284807,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Stratified train-test split"
      ],
      "metadata": {
        "id": "RaPbKsPq1dtk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(\n",
        "    X,\n",
        "    y,\n",
        "    test_size=TEST_SIZE,\n",
        "    stratify=y,\n",
        "    random_state=SEED\n",
        ")\n",
        "\n",
        "split_summary = {\n",
        "    \"train_rows\": int(len(X_train)),\n",
        "    \"test_rows\": int(len(X_test)),\n",
        "    \"train_class_counts\": y_train.value_counts().sort_index().astype(int).to_dict(),\n",
        "    \"test_class_counts\": y_test.value_counts().sort_index().astype(int).to_dict(),\n",
        "    \"test_size\": TEST_SIZE,\n",
        "    \"random_state\": SEED\n",
        "}\n",
        "\n",
        "save_json(split_summary, TABLE_DIR / \"train_test_split_summary.json\")\n",
        "\n",
        "print(\"\\nTrain-test split summary:\")\n",
        "print(split_summary)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "JItZNjNd1hM1",
        "outputId": "76b2f3c2-6d9a-4ce7-88ae-e0ed033bf9ef"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Train-test split summary:\n",
            "{'train_rows': 227845, 'test_rows': 56962, 'train_class_counts': {0: 227451, 1: 394}, 'test_class_counts': {0: 56864, 1: 98}, 'test_size': 0.2, 'random_state': 42}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Training-set EDA"
      ],
      "metadata": {
        "id": "63IGU1lQ1kl4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "train_df = X_train.copy()\n",
        "train_df[\"Class\"] = y_train\n",
        "\n",
        "descriptive_stats = train_df.describe().T\n",
        "descriptive_stats.to_csv(TABLE_DIR / \"training_descriptive_statistics.csv\")\n",
        "\n",
        "print(\"\\nTraining descriptive statistics:\")\n",
        "print(descriptive_stats.head())\n",
        "\n",
        "correlation_table = top_class_correlations(train_df, n=15)\n",
        "correlation_table.to_csv(TABLE_DIR / \"training_top_class_correlations.csv\", index=False)\n",
        "\n",
        "print(\"\\nTop correlations with Class in training set:\")\n",
        "print(correlation_table)\n",
        "\n",
        "plot_amount_distribution(\n",
        "    train_df,\n",
        "    FIG_DIR / \"training_amount_distribution_log1p.png\"\n",
        ")\n",
        "\n",
        "plot_transactions_by_hour(\n",
        "    train_df,\n",
        "    FIG_DIR / \"training_transactions_by_hour.png\"\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1567
        },
        "id": "NW3g-nPn1nlh",
        "outputId": "4b658789-9f5c-4832-8d8f-91bf089c02bb"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Training descriptive statistics:\n",
            "         count          mean           std        min           25%  \\\n",
            "Time  227845.0  94885.093704  47488.415034   0.000000  54228.000000   \n",
            "V1    227845.0      0.000795      1.958926 -56.407510     -0.919893   \n",
            "V2    227845.0     -0.000481      1.649092 -72.715728     -0.598761   \n",
            "V3    227845.0     -0.000383      1.515292 -48.325589     -0.891767   \n",
            "V4    227845.0     -0.000020      1.415867  -5.683171     -0.847111   \n",
            "\n",
            "               50%            75%            max  \n",
            "Time  84805.000000  139364.000000  172792.000000  \n",
            "V1        0.018692       1.315616       2.451888  \n",
            "V2        0.064746       0.803876      22.057729  \n",
            "V3        0.179859       1.026457       9.382558  \n",
            "V4       -0.021361       0.742281      16.875344  \n",
            "\n",
            "Top correlations with Class in training set:\n",
            "   feature  correlation_with_class\n",
            "0      V17               -0.321937\n",
            "1      V14               -0.301054\n",
            "2      V12               -0.259989\n",
            "3      V10               -0.217894\n",
            "4       V3               -0.194135\n",
            "5      V16               -0.193826\n",
            "6       V7               -0.186184\n",
            "7      V11                0.153709\n",
            "8       V4                0.135014\n",
            "9      V18               -0.108732\n",
            "10      V1               -0.100041\n",
            "11      V9               -0.098247\n",
            "12      V5               -0.093578\n",
            "13      V2                0.090586\n",
            "14      V6               -0.043334\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Fraud prevalence by hour"
      ],
      "metadata": {
        "id": "nohD5v6X7AHj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "temp = train_df.copy()\n",
        "temp[\"hour\"] = (temp[\"Time\"] // 3600).astype(int)\n",
        "\n",
        "hourly_summary = temp.groupby(\"hour\")[\"Class\"].agg(\n",
        "    total_transactions=\"count\",\n",
        "    fraud_count=\"sum\"\n",
        ").reset_index()\n",
        "\n",
        "hourly_summary[\"fraud_prevalence_percent\"] = (\n",
        "    hourly_summary[\"fraud_count\"] / hourly_summary[\"total_transactions\"] * 100\n",
        ")\n",
        "\n",
        "hourly_summary.to_csv(\n",
        "    TABLE_DIR / \"training_fraud_prevalence_by_hour.csv\",\n",
        "    index=False\n",
        ")\n",
        "\n",
        "plt.figure(figsize=(10, 5))\n",
        "plt.plot(\n",
        "    hourly_summary[\"hour\"],\n",
        "    hourly_summary[\"fraud_prevalence_percent\"],\n",
        "    marker=\"o\"\n",
        ")\n",
        "\n",
        "plt.xlabel(\"Hour from first transaction\")\n",
        "plt.ylabel(\"Fraud prevalence (%)\")\n",
        "plt.title(\"Training-Set Fraud Prevalence by Hour\")\n",
        "plt.tight_layout()\n",
        "plt.savefig(FIG_DIR / \"training_fraud_prevalence_by_hour.png\", dpi=300)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "Bb382_9x6_gw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 507
        },
        "outputId": "456b2729-3126-4b95-edb3-1cc050f5844d"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Amount boxplot by class"
      ],
      "metadata": {
        "id": "xVgaNkV67Ghs"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "legitimate_amount = np.log1p(train_df.loc[train_df[\"Class\"] == 0, \"Amount\"])\n",
        "fraud_amount = np.log1p(train_df.loc[train_df[\"Class\"] == 1, \"Amount\"])\n",
        "\n",
        "plt.figure(figsize=(7, 5))\n",
        "plt.boxplot(\n",
        "    [legitimate_amount, fraud_amount],\n",
        "    labels=[\"Legitimate\", \"Fraud\"],\n",
        "    showfliers=False\n",
        ")\n",
        "\n",
        "plt.ylabel(\"log(Amount + 1)\")\n",
        "plt.title(\"Training-Set Transaction Amount by Class\")\n",
        "plt.tight_layout()\n",
        "plt.savefig(FIG_DIR / \"training_amount_boxplot_by_class.png\", dpi=300)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "SfKeDAR87JXz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 565
        },
        "outputId": "28c2826b-4fcc-4869-edd1-095b21a3fa48"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/tmp/ipykernel_621/4232311760.py:5: MatplotlibDeprecationWarning: The 'labels' parameter of boxplot() has been renamed 'tick_labels' since Matplotlib 3.9; support for the old name will be dropped in 3.11.\n",
            "  plt.boxplot(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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vzZ566imVKlXKdrt5PWWGwMBAvfDCC9q8ebN8fHxsM0oZj/WNN97Q6tWrs7xlFajzSlZfnyNHjqh58+Y6f/68JkyYoP/9739avXq1bV3izV+f7DyfjRs31pEjRzRjxgyFhYXpiy++UK1atfTFF1/Y+jz77LOaPn26XnrpJS1evFirVq2ynYR3L11rNaevn0OHDmn79u3atGmTKlasaLtlnHj0z1nGOx0rL1/Dt5rFvvnEy/w4dk707NlTR48e1ZYtW3TlyhUtXbpU3bp1y/SLyM2Cg4MVHx+vkydP5ui4P//8s9q3by93d3d99tlnWr58uVavXq3nnnvO7rF7eHho48aNWrNmjZ5//nn99ttv6tKli1q2bGl7TkNCQnTgwAEtWLBADRs21KJFi9SwYUPbL6/A3cDJXkAOrV+/XhcuXNDixYvVuHFjW/uxY8ecWNX/V6JECbm7u+vw4cOZ7ru5bfz48XYzUf9cipCVokWLqnz58tq3b58kqVy5cpL+/lP2nS7BdLc+pWzZsmVKSUnR0qVL7Wbf1q1bl6txfX191bt3b/Xu3VuJiYlq3LixRo4cqb59++rSpUtau3atRo0apeHDh9v2uXkpgp+fn4oUKWJ7/m7FkecqMDBQv/32m9LT0+3CUMYSl4wT93Jr7ty5cnV11VdffZUpDG7atEmTJk3SiRMnspzhdlRGzQcOHMg0U3ngwAG7x1S0aNEslwXkZtY2J6/VjL9O/HPfjGu6/nN5xRNPPCE/Pz/NnTtX9erVU1JSUrZO4GrXrp3mz5+vOXPmKDIy0uH6Fi1aJHd3d61cudLuutYzZ87M1LdAgQJq3ry5mjdvrgkTJuj999/X22+/rXXr1tm+zwsVKqQuXbqoS5cuSk1N1VNPPaUxY8YoMjLSKde+xoOHGVkghzJ+iP9zFiM1NVWfffaZs0qyU7BgQbVo0UJLliyx+6Sfw4cP68cff7TrW7t2bbVo0cJ2q1KliiRp7969On/+fKaxjx8/rj/++MP2J98SJUqoadOmmjZtms6cOZOp/19//WX7f8YHF1y+fDnXj/F2svr6xMfHZ/kDO7tuvoRW4cKFVaFCBdta4ayOKUkTJ0602y5QoIA6duyoZcuWaceOHZmOk7G/I8/Vk08+qbNnz+rrr7+2td24cUOffPKJChcurCZNmtxxjOyYO3euGjVqpC5duuiZZ56xu2Wspb7d5aMcUadOHZUoUUJTp061PceS9OOPPyo6Otp2hr0klS9fXjExMXavtb179+bqT905ea2ePn3a7oM8EhIS9N///lc1atRQyZIlbe0uLi7q1q2bvvnmG82aNUtVq1ZVtWrV7jj+M888o6pVq2rMmDH65ZdfMt1/5coVvf3227fcv2DBgrJYLHYz1bGxsVqyZIldv4sXL2bat0aNGpJk+1rc/P3g5uamKlWqyDAMXb9+/Y6PBcgLzMgCOdSgQQMVLVpUERERGjx4sCwWi7766qu79qfJ7Bg5cqRWrVql8PBwDRgwQGlpafr0008VFhamPXv23HH/1atXa8SIEWrfvr0effRRFS5cWEePHtWMGTOUkpJi9/GdkydPVsOGDVW1alX169dP5cqV07lz5/TLL7/ozz//1N69eyX9/cOwYMGCGjt2rOLj42W1Wm3Xes1Ljz/+uNzc3NSuXTv1799fiYmJmj59ukqUKJFl2M6OKlWqqGnTpqpdu7Z8fX21Y8cOffvtt3r55Zcl/b1+sXHjxho3bpyuX7+uhx56SKtWrcpylv7999/XqlWr1KRJE7344osKCQnRmTNntHDhQm3atEk+Pj4OPVcvvviipk2bpl69emnnzp0KCgrSt99+q82bN2vixIm5PkFIkrZt22a7vFdWHnroIdWqVUtz587VsGHDcn08V1dXjR07Vr1791aTJk3UrVs32+W3goKC7C5f9cILL2jChAlq1aqV+vTpo7i4OE2dOlWhoaFKSEjI0fFr164tSRo8eLBatWqlggULqmvXrrfdp1KlSurTp4+2b98uf39/zZgxQ+fOncvyF6iePXtq0qRJWrduXbY/xMDV1VWLFy9WixYt1LhxYz377LMKDw+Xq6ur9u/fr3nz5qlo0aK3vJZsmzZtNGHCBD3xxBN67rnnFBcXp8mTJ6tChQp2671Hjx6tjRs3qk2bNgoMDFRcXJw+++wzlSlTxraM5PHHH1fJkiUVHh4uf39/RUdH69NPP1WbNm3y5PUGZIsTrpQA3LNudfmtW11iZvPmzcajjz5qeHh4GKVLlzb+9a9/GStXrsx0yaRbXQLoP//5T6YxJRkjRoywbd/q8luDBg3KtG9gYGCmy/esXbvWqFmzpuHm5maUL1/e+OKLL4zXX3/dcHd3v8Wz8P8dPXrUGD58uPHoo48aJUqUMFxcXAw/Pz+jTZs2xk8//ZSp/5EjR4yePXsaJUuWNFxdXY2HHnrIaNu2rfHtt9/a9Zs+fbpRrlw5o2DBgg5diutWl9+61SWxli5dalSrVs1wd3c3goKCjLFjxxozZsywu8TT7ca4+ZJO7733nlG3bl3Dx8fH8PDwMIKDg40xY8YYqamptj5//vmn0alTJ8PHx8fw9vY2OnfubJw+fTrT19UwDOP48eNGz549DT8/P8NqtRrlypUzBg0aZKSkpNzxucrqclPnzp0zevfubRQvXtxwc3MzqlatasycOdOujyOvvZu98sorhiTjyJEjt+wzcuRIQ5Kxd+9e25g3v1ZvVcO6desMScbChQvt2r/++mujZs2ahtVqNXx9fY3u3bsbf/75Z6Zjz5kzxyhXrpzh5uZm1KhRw1i5cmWuvvdu3LhhvPLKK4afn59hsVjueCmujNfRypUrjWrVqhlWq9UIDg7O9Hj+KTQ01ChQoECWj+d2Ll26ZAwfPtyoWrWq4enpabi7uxthYWFGZGSkcebMGVu/rC6/9eWXXxoVK1a01Tdz5sxM7zNr1641OnToYJQuXdpwc3MzSpcubXTr1s04ePCgrc+0adOMxo0bG8WKFTOsVqtRvnx548033zTi4+MdeixAblgM4x6aPgJwV3Ts2PGOl5ECkP9q1qwpX19frV271tmlAKbEGlngPpecnGy3fejQIS1fvjzLj/MEcPfs2LFDe/bsUc+ePZ1dCmBazMgC97lSpUqpV69eKleunI4fP64pU6YoJSVFu3fvVsWKFZ1dHvDA2bdvn3bu3Knx48fr/PnzOnr0KGf4AznEyV7Afe6JJ57Q/PnzdfbsWVmtVtWvX1/vv/8+IRZwkm+//VajR49W5cqVNX/+fEIskAvMyAIAAMCUWCMLAAAAUyLIAgAAwJRMvUY2PT1dp0+flpeX11372EsAAADkH8MwdOXKFZUuXdruI7ezYuoge/r0aQUEBDi7DAAAAOSxkydPqkyZMrftY+ogm/EReCdPnlSRIkWcXA0AAAByKyEhQQEBAdn6qGNTB9mM5QRFihQhyAIAANxHsrNslJO9AAAAYEoEWQAAAJgSQRYAAACmRJAFAACAKRFkAQAAYEoEWQAAAJgSQRYAAACmRJAFAACAKRFkAQAAYEoEWQAAAJgSQRYAAACmRJAFAACAKRFkAQAAYEoEWQAAAJgSQRYAAACm5NQgm5aWpnfeeUdly5aVh4eHypcvr3fffVeGYTizLAAAAJiAizMPPnbsWE2ZMkWzZ89WaGioduzYod69e8vb21uDBw92Zml4gCQlJSkmJibb/ZOTkxUbG6ugoCB5eHhke7/g4GB5enrmpEQAAJAFpwbZLVu2qEOHDmrTpo0kKSgoSPPnz9evv/7qzLLwgImJiVHt2rXz/Tg7d+5UrVq18v04AAA8KJwaZBs0aKDPP/9cBw8eVKVKlbR3715t2rRJEyZMyLJ/SkqKUlJSbNsJCQl3q1Tcx4KDg7Vz585s94+OjlaPHj00Z84chYSEOHQcAACQd5waZN966y0lJCQoODhYBQsWVFpamsaMGaPu3btn2T8qKkqjRo26y1Xifufp6ZmjmdKQkBBmWAEAcCKnnuz1zTffaO7cuZo3b5527dql2bNn68MPP9Ts2bOz7B8ZGan4+Hjb7eTJk3e5YgAAANwrnDoj++abb+qtt95S165dJUlVq1bV8ePHFRUVpYiIiEz9rVarrFbr3S4TAAAA9yCnzsgmJSWpQAH7EgoWLKj09HQnVQQAAACzcOqMbLt27TRmzBg9/PDDCg0N1e7duzVhwgS98MILziwLAAAAJuDUIPvJJ5/onXfe0cCBAxUXF6fSpUurf//+Gj58uDPLAgAAgAk4Nch6eXlp4sSJmjhxojPLAAAAgAk5dY0sAAAAkFMEWQAAAJgSQRYAAACmRJAFAACAKRFkAQAAYEoEWQAAAJgSQRYAAACmRJAFAACAKTn1AxEAAMDdk5SUpJiYmGz3T05OVmxsrIKCguTh4ZHt/YKDg+Xp6ZmTEgGHEGQBAHhAxMTEqHbt2vl+nJ07d6pWrVr5fhyAIAsAwAMiODhYO3fuzHb/6Oho9ejRQ3PmzFFISIhDxwHuBoIsAAAPCE9PzxzNlIaEhDDDinsSJ3sBAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTcmqQDQoKksViyXQbNGiQM8sCAACACbg48+Dbt29XWlqabXvfvn1q2bKlOnfu7MSqAAAAYAZODbJ+fn522x988IHKly+vJk2aOKkiAAAAmMU9s0Y2NTVVc+bM0QsvvCCLxeLscgAAAHCPc+qM7D8tWbJEly9fVq9evW7ZJyUlRSkpKbbthISEu1AZAAAA7kX3zIzsl19+qdatW6t06dK37BMVFSVvb2/bLSAg4C5WCAAAgHvJPRFkjx8/rjVr1qhv37637RcZGan4+Hjb7eTJk3epQgAAANxr7omlBTNnzlSJEiXUpk2b2/azWq2yWq13qSoAAADcy5w+I5uenq6ZM2cqIiJCLi73RK4GAACACTg9yK5Zs0YnTpzQCy+84OxSAAAAYCJOnwJ9/PHHZRiGs8sAAACAyTh9RhYAAADICYIsAAAATIkgCwAAAFMiyAIAAMCUCLIAAAAwJYIsAAAATIkgCwAAAFMiyAIAAMCUCLIAAAAwJYIsAAAATIkgCwAAAFMiyAIAAMCUCLIAAAAwJYIsAAAATIkgCwAAAFMiyAIAAMCUCLIAAAAwJYIsAAAATIkgCwAAAFMiyAIAAMCUCLIAAAAwJYIsAAAATIkgCwAAAFMiyAIAAMCUCLIAAAAwJYIsAAAATIkgCwAAAFMiyAIAAMCUCLIAAAAwJYIsAAAATIkgCwAAAFMiyAIAAMCUCLIAAAAwJYIsAAAATIkgCwAAAFMiyAIAAMCUCLIAAAAwJacH2VOnTqlHjx4qVqyYPDw8VLVqVe3YscPZZQEAAOAe5+LMg1+6dEnh4eFq1qyZfvzxR/n5+enQoUMqWrSoM8sCAACACTg1yI4dO1YBAQGaOXOmra1s2bJOrAgAAABm4dSlBUuXLlWdOnXUuXNnlShRQjVr1tT06dOdWRIAAABMwqlB9ujRo5oyZYoqVqyolStXasCAARo8eLBmz56dZf+UlBQlJCTY3QAAAPBgcurSgvT0dNWpU0fvv/++JKlmzZrat2+fpk6dqoiIiEz9o6KiNGrUqLtdJgAAAO5BTp2RLVWqlKpUqWLXFhISohMnTmTZPzIyUvHx8bbbyZMn70aZAAAAuAc5dUY2PDxcBw4csGs7ePCgAgMDs+xvtVpltVrvRmkAAAC4xzl1Rva1117T1q1b9f777+vw4cOaN2+ePv/8cw0aNMiZZQEAAMAEnBpkH3nkEX333XeaP3++wsLC9O6772rixInq3r27M8sCAACACTh1aYEktW3bVm3btnV2GQAAADAZp39ELQAAAJATBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCm5ONI5PT1dGzZs0M8//6zjx48rKSlJfn5+qlmzplq0aKGAgID8qhMAAACwk60Z2eTkZL333nsKCAjQk08+qR9//FGXL19WwYIFdfjwYY0YMUJly5bVk08+qa1bt+Z3zQAAAED2ZmQrVaqk+vXra/r06WrZsqVcXV0z9Tl+/LjmzZunrl276u2331a/fv3yvFgAAAAgQ7aC7KpVqxQSEnLbPoGBgYqMjNQbb7yhEydO5ElxAAAAwK1ka2nBnULsP7m6uqp8+fI5LggAAADIjjy7asHVq1e1ceNGh/YZOXKkLBaL3S04ODivSgIAAMB9zKGrFtzO4cOH1axZM6WlpTm0X2hoqNasWfP/C3LJs5IAAABwH3N6anRxcVHJkiWdXQYAAABMJttB1tfX97b3OzoTm+HQoUMqXbq03N3dVb9+fUVFRenhhx/O0VgAAAB4cGQ7yKakpGjAgAGqWrVqlvcfP35co0aNcujg9erV06xZs1S5cmWdOXNGo0aNUqNGjbRv3z55eXllWUNKSoptOyEhwaHjAQAA4P6R7SBbo0YNBQQEKCIiIsv79+7d63CQbd26te3/1apVU7169RQYGKhvvvlGffr0ydQ/KirK4WMAAADg/pTtqxa0adNGly9fvuX9vr6+6tmzZ66K8fHxUaVKlXT48OEs74+MjFR8fLztdvLkyVwdDwAAAOaV7RnZf//737e9PyAgQDNnzsxVMYmJiTpy5Iief/75LO+3Wq2yWq25OgYAAADuD3l2HdmceOONN7RhwwbFxsZqy5Yt6tSpkwoWLKhu3bo5sywAAACYgFMvv/Xnn3+qW7duunDhgvz8/NSwYUNt3bpVfn5+ziwLAAAAJuDUILtgwQJnHh4AAAAm5tSlBQAAAEBOEWQBAABgSgRZAAAAmFKugmybNm105syZvKoFAAAAyLZcBdmNGzcqOTk5r2oBAAAAso2lBQAAADClXAdZi8WSF3UAAAAADnHoOrIFChTIFFwrVKggSTIMQxaLRWlpaXlXHQAAAHALDgXZY8eO2f5vGIbCwsK0fPlyBQYG5nlhAADgzg4dOqQrV67ky9jR0dF2/+YHLy8vVaxYMd/Gx/3NoSB7c2C1WCwqU6YMQRYAACc4dOiQKlWqlO/H6dGjR76Of/DgQcIscsSpH1ELAAByLmMmds6cOQoJCcnz8ZOTkxUbG6ugoCB5eHjk+fjR0dHq0aNHvs0o4/6XqyAbGBgoV1fXvKoFAADkQEhIiGrVqpUvY4eHh+fLuEBeyFWQ3bdvX17VAQAAADiE68gCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlBwOsuXKldOFCxcytV++fFnlypXLk6IAAACAO3E4yMbGxiotLS1Te0pKik6dOpUnRQEAAAB3ku3ryC5dutT2/5UrV8rb29u2nZaWprVr1yooKChPiwMAAABuJdtBtmPHjpIki8WiiIgIu/tcXV0VFBSk8ePH52lxAAAAwK1kO8imp6dLksqWLavt27erePHi+VYUAAAAcCcOf0TtsWPH8qMOIE8dOnRIV65cyZexo6Oj7f7ND15eXqpYsWK+jQ8AwP3A4SArSWvXrtXatWsVFxdnm6nNMGPGjDwpDMipQ4cOqVKlSvl+nB49euTr+AcPHiTMAgBwGw4H2VGjRmn06NGqU6eOSpUqJYvFkh91ATmWMRM7Z84chYSE5Pn4ycnJio2NVVBQkDw8PPJ8/OjoaPXo0SPfZpQBALhfOBxkp06dqlmzZun555/Pj3qAPBMSEqJatWrly9jh4eH5Mi4AAMg+h68jm5qaqgYNGuRHLQAAAEC2ORxk+/btq3nz5uVHLQAAAEC2Oby04Nq1a/r888+1Zs0aVatWTa6urnb3T5gwIc+KAwAAAG7F4SD722+/qUaNGpKkffv22d3HiV8AAAC4WxwOsuvWrcuPOgAAAACHOLxGFgAAALgXODwj26xZs9suIfjpp59yVRAAAACQHQ4H2Yz1sRmuX7+uPXv2aN++fYqIiMirugAAAIDbcjjIfvTRR1m2jxw5UomJibkuCAAAAMiOPFsj26NHD82YMSOvhgMAAABuK8+C7C+//CJ3d/cc7//BBx/IYrHo1VdfzauSAAAAcB9zeGnBU089ZbdtGIbOnDmjHTt26J133slREdu3b9e0adNUrVq1HO0PAACAB4/DM7Le3t52N19fXzVt2lTLly/XiBEjHC4gMTFR3bt31/Tp01W0aFGH9wcAAMCDyeEZ2ZkzZ+ZpAYMGDVKbNm3UokULvffee3k6NgAAAO5fDgfZDDt37lR0dLQkKTQ0VDVr1nR4jAULFmjXrl3avn17tvqnpKQoJSXFtp2QkODwMQEAAHB/cDjIxsXFqWvXrlq/fr18fHwkSZcvX1azZs20YMEC+fn5ZWuckydPasiQIVq9enW2TxKLiorSqFGjHC0ZAAAA9yGH18i+8sorunLlivbv36+LFy/q4sWL2rdvnxISEjR48OBsj7Nz507FxcWpVq1acnFxkYuLizZs2KBJkybJxcVFaWlpmfaJjIxUfHy87Xby5ElHywcAAMB9wuEZ2RUrVmjNmjUKCQmxtVWpUkWTJ0/W448/nu1xmjdvrt9//92urXfv3goODtawYcNUsGDBTPtYrVZZrVZHSwYAAMB9yOEgm56eLldX10ztrq6uSk9Pz/Y4Xl5eCgsLs2srVKiQihUrlqkdAAAAuJnDSwsee+wxDRkyRKdPn7a1nTp1Sq+99pqaN2+ep8UBAAAAt+LwjOynn36q9u3bKygoSAEBAZL+PnErLCxMc+bMyVUx69evz9X+AAAAeHA4HGQDAgK0a9curVmzRjExMZKkkJAQtWjRIs+LAwAAAG4lR9eRtVgsatmypVq2bJnX9QAAAADZkqMgu337dq1bt05xcXGZTvCaMGFCnhQGAAAA3I7DQfb999/X//3f/6ly5cry9/eXxWKx3ffP/wMAAAD5yeEg+/HHH2vGjBnq1atXPpQDAAAAZI/Dl98qUKCAwsPD86MWAAAAINscDrKvvfaaJk+enB+1AAAAANnm8NKCN954Q23atFH58uVVpUqVTJ/ytXjx4jwrDgAAALgVh4Ps4MGDtW7dOjVr1kzFihXjBC8AAAA4hcNBdvbs2Vq0aJHatGmTH/UAAAAA2eLwGllfX1+VL18+P2oBAAAAss3hIDty5EiNGDFCSUlJ+VEPAAAAkC0OLy2YNGmSjhw5In9/fwUFBWU62WvXrl15VhwAAABwKw4H2Y4dO+ZDGQAAAIBjHA6yI0aMuOV9aWlpuSoGAAAAyC6H18hm5eDBgxo2bJjKlCmTF8MBAAAAd5TjIJuUlKSZM2eqUaNGqlKlijZs2KChQ4fmZW0AAADALTm8tGDr1q364osvtHDhQj388MOKjo7WunXr1KhRo/yoDwAAAMhStmdkx48fr9DQUD3zzDMqWrSoNm7cqN9//10Wi0XFihXLzxoBAACATLI9Izts2DANGzZMo0ePVsGCBfOzJgAAAOCOsj0j++6772rhwoUqW7ashg0bpn379uVnXQAAAMBtZTvIRkZG6uDBg/rqq6909uxZ1atXT9WrV5dhGLp06VJ+1ggAAABk4vBVC5o0aaLZs2fr7NmzGjhwoGrXrq0mTZqoQYMGmjBhQn7UCAAAAGSS48tveXl5qX///tq2bZt2796tunXr6oMPPsjL2gAAAIBbypMPRKhataomTpyoU6dO5cVwAAAAwB1lK8guWLAgW4O5urrq5MmT2rx5c66KAgAAAO4kW0F2ypQpCgkJ0bhx4xQdHZ3p/vj4eC1fvlzPPfecatWqpQsXLuR5oQAAAMA/Zes6shs2bNDSpUv1ySefKDIyUoUKFZK/v7/c3d116dIlnT17VsWLF1evXr20b98++fv753fdAAAAeMBl+wMR2rdvr/bt2+v8+fPatGmTjh8/ruTkZBUvXlw1a9ZUzZo1VaBAniy5BQAAAO4o20E2Q/HixdWxY8d8KAUAAADIPqZQAQAAYEoOz8gWLVpUFoslU7vFYpG7u7sqVKigXr16qXfv3nlSIAAAAJAVh4Ps8OHDNWbMGLVu3Vp169aVJP36669asWKFBg0apGPHjmnAgAG6ceOG+vXrl+cFAwAAAFIOguymTZv03nvv6aWXXrJrnzZtmlatWqVFixapWrVqmjRpEkEWAAAA+cbhILty5UqNHTs2U3vz5s31+uuvS5KefPJJvfXWW7mvDsihkoUt8rh8UDptvmXgHpcPqmThzMt3AACAPYeDrK+vr5YtW6bXXnvNrn3ZsmXy9fWVJF29elVeXl55UyGQA/1ruylkY39po7MrcVyI/q4fAADcnsNB9p133tGAAQO0bt062xrZ7du3a/ny5Zo6daokafXq1WrSpEneVgo4YNrOVHUZPkshwcHOLsVh0TExmjb+ObV3diEAANzjHA6y/fr1U5UqVfTpp59q8eLFkqTKlStrw4YNatCggSTZlhjcyZQpUzRlyhTFxsZKkkJDQzV8+HC1bt3a0bIAO2cTDSX7VJJK13B2KQ5LPpuus4mGs8sAAOCe53CQlaTw8HCFh4fn+uBlypTRBx98oIoVK8owDM2ePVsdOnTQ7t27FRoamuvxAQAAcP/KUZBNS0vTkiVLFB0dLenvmdT27durYMGCDo3Trl07u+0xY8ZoypQp2rp1K0EWAAAAt+VwkD18+LCefPJJnTp1SpUrV5YkRUVFKSAgQP/73/9Uvnz5HBWSlpamhQsX6urVq6pfv36WfVJSUpSSkmLbTkhIyNGxAAAAYH4OX5to8ODBKl++vE6ePKldu3Zp165dOnHihMqWLavBgwc7XMDvv/+uwoULy2q16qWXXtJ3332nKlWqZNk3KipK3t7etltAQIDDxwMAAMD9weEgu2HDBo0bN852qS1JKlasmD744ANt2LDB4QIqV66sPXv2aNu2bRowYIAiIiL0xx9/ZNk3MjJS8fHxttvJkycdPh4AAADuDw4vLbBarbpy5Uqm9sTERLm5OX7tSzc3N1WoUEGSVLt2bW3fvl0ff/yxpk2bluWxrVarw8cAAADA/cfhGdm2bdvqxRdf1LZt22QYhgzD0NatW/XSSy+pffvcX/kyPT3dbh0sAAAAkBWHZ2QnTZqkiIgI1a9fX66urpKkGzduqH379vr4448dGisyMlKtW7fWww8/rCtXrmjevHlav369Vq5c6WhZAAAAeMA4HGR9fHz0/fff69ChQ4qJiZEkhYSE2JYHOCIuLk49e/bUmTNn5O3trWrVqmnlypVq2bKlw2MBAADgwZKj68hKUsWKFVWxYsVcHfzLL7/M1f4AAAB4cGUryA4dOjTbA06YMCHHxQAAAADZla0gu3v37mwNZrFYclUMAAAAkF3ZCrLr1q3L7zoAAAAAhzh8+S0AAADgXkCQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCm5OLsAAACQcyULW+Rx+aB02nxzUx6XD6pkYYuzy4CJEWQBADCx/rXdFLKxv7TR2ZU4LkR/1w/kFEEWAAATm7YzVV2Gz1JIcLCzS3FYdEyMpo1/Tu2dXQhMiyALAICJnU00lOxTSSpdw9mlOCz5bLrOJhrOLgMmZr4FNQAAAIAIsgAAADApgiwAAABMiSALAAAAUyLIAgAAwJQIsgAAADAlgiwAAABMiSALAAAAU3JqkI2KitIjjzwiLy8vlShRQh07dtSBAwecWRIAAABMwqlBdsOGDRo0aJC2bt2q1atX6/r163r88cd19epVZ5YFAAAAE3DqR9SuWLHCbnvWrFkqUaKEdu7cqcaNGzupKgAAAJiBU4PszeLj4yVJvr6+Wd6fkpKilJQU23ZCQsJdqQsAAAD3nnvmZK/09HS9+uqrCg8PV1hYWJZ9oqKi5O3tbbsFBATc5SoBAABwr7hnguygQYO0b98+LViw4JZ9IiMjFR8fb7udPHnyLlYIAACAe8k9sbTg5Zdf1g8//KCNGzeqTJkyt+xntVpltVrvYmUAAAC4Vzk1yBqGoVdeeUXfffed1q9fr7JlyzqzHAAAAJiIU4PsoEGDNG/ePH3//ffy8vLS2bNnJUne3t7y8PBwZmkwsaSkJEnSrl278mX85ORkxcbGKigoKF9ep9HR0Xk+JgAA9yOnBtkpU6ZIkpo2bWrXPnPmTPXq1evuF4T7QkxMjCSpX79+Tq4kd7y8vJxdAgAA9zSnLy0A8lrHjh0lScHBwfL09Mzz8aOjo9WjRw/NmTNHISEheT6+9HeIrVixYr6MDQDA/eKeONkLyEvFixdX37598/04ISEhqlWrVr4fBwAAZO2eufwWAAAA4AiCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlAiyAAAAMCWCLAAAAEyJIAsAAABTIsgCAADAlJwaZDdu3Kh27dqpdOnSslgsWrJkiTPLAQAAgIk4NchevXpV1atX1+TJk51ZBgAAAEzIxZkHb926tVq3bu3MEgAAAGBSTg2yjkpJSVFKSoptOyEhwYnVAAAAwJlMdbJXVFSUvL29bbeAgABnlwQAAAAnMVWQjYyMVHx8vO128uRJZ5cEAAAAJzHV0gKr1Sqr1ersMgAAAHAPMNWMLAAAAJDBqTOyiYmJOnz4sG372LFj2rNnj3x9ffXwww87sTIAAADc65waZHfs2KFmzZrZtocOHSpJioiI0KxZs5xUFQAAAMzAqUG2adOmMgzDmSUAAADApFgjCwAAAFMiyAIAAMCUCLIAAAAwJYIsAAAATIkgCwAAAFMiyAIAAMCUCLIAAAAwJadeRxYAAORcUlKSJGnXrl35Mn5ycrJiY2MVFBQkDw+PPB8/Ojo6z8fEg4UgCwCAScXExEiS+vXr5+RKcsfLy8vZJcCkCLIAAJhUx44dJUnBwcHy9PTM8/Gjo6PVo0cPzZkzRyEhIXk+vvR3iK1YsWK+jI37H0EWAACTKl68uPr27ZvvxwkJCVGtWrXy/TiAozjZCwAAAKZEkAUAAIApEWQBAABgSgRZAAAAmBJBFgAAAKZEkAUAAIApEWQBAABgSgRZAAAAmBJBFgAAAKZEkAUAAIApEWQBAABgSgRZAAAAmBJBFgAAAKZEkAUAAIApEWQBAABgSgRZAAAAmBJBFgAAAKZEkAUAAIApEWQBAABgSgRZAAAAmBJBFgAAAKZEkAUAAIApEWQBAABgSgRZAAAAmBJBFgAAAKZEkAUAAIAp3RNBdvLkyQoKCpK7u7vq1aunX3/91dklAQAA4B7n9CD79ddfa+jQoRoxYoR27dql6tWrq1WrVoqLi3N2aQAAALiHOT3ITpgwQf369VPv3r1VpUoVTZ06VZ6enpoxY4azSwMAAMA9zMWZB09NTdXOnTsVGRlpaytQoIBatGihX375JVP/lJQUpaSk2LYTEhLuSp24vyUlJSkmJibb/aOjo+3+za7g4GB5eno6tA8A5CXe73C/cWqQPX/+vNLS0uTv72/X7u/vn+U3WlRUlEaNGnW3ysMDIiYmRrVr13Z4vx49ejjUf+fOnapVq5bDxwGAvML7He43Tg2yjoqMjNTQoUNt2wkJCQoICHBiRbgfBAcHa+fOndnun5ycrNjYWAUFBcnDw8Oh4wCAM/F+h/uNU4Ns8eLFVbBgQZ07d86u/dy5cypZsmSm/larVVar9W6VhweEp6enwzMH4eHh+VQNAOQf3u9wv3HqyV5ubm6qXbu21q5da2tLT0/X2rVrVb9+fSdWBgAAgHud05cWDB06VBEREapTp47q1q2riRMn6urVq+rdu7ezSwMAAMA9zOlBtkuXLvrrr780fPhwnT17VjVq1NCKFSsynQAGAAAA/JPFMAzD2UXkVEJCgry9vRUfH68iRYo4uxwAAADkkiP5zukfiAAAAADkBEEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCkRZAEAAGBKBFkAAACYEkEWAAAApkSQBQAAgCm5OLuA3DAMQ9Lfn8kLAAAA88vIdRk573ZMHWSvXLkiSQoICHByJQAAAMhLV65ckbe39237WIzsxN17VHp6uk6fPi0vLy9ZLBZnl4MHREJCggICAnTy5EkVKVLE2eUAQL7h/Q7OYBiGrly5otKlS6tAgduvgjX1jGyBAgVUpkwZZ5eBB1SRIkV4YwfwQOD9DnfbnWZiM3CyFwAAAEyJIAsAAABTIsgCDrJarRoxYoSsVquzSwGAfMX7He51pj7ZCwAAAA8uZmQBAABgSgRZAAAAmBJBFgAAAKZEkAUkBQUFaeLEibftM3LkSNWoUeOu1AMA94tevXqpY8eOzi4D9ymCLEwhv98It2/frhdffNG2bbFYtGTJErs+b7zxhtauXZtvNWQgMAPIC7169ZLFYsl0O3z4sLNLA/KMqT/ZC8grfn5+d+xTuHBhFS5c+C5UAwB544knntDMmTPt2m5+v0tNTZWbm9vdLAvIM8zIwvT27dun1q1bq3DhwvL399fzzz+v8+fP2+6/cuWKunfvrkKFCqlUqVL66KOP1LRpU7366qu2Pv9cWhAUFCRJ6tSpkywWi2375pnSjFni999/X/7+/vLx8dHo0aN148YNvfnmm/L19VWZMmUy/RAZNmyYKlWqJE9PT5UrV07vvPOOrl+/LkmaNWuWRo0apb1799pmT2bNmiVJunz5svr27Ss/Pz8VKVJEjz32mPbu3ZunzyWA+4vValXJkiXtbs2bN9fLL7+sV199VcWLF1erVq0kSRMmTFDVqlVVqFAhBQQEaODAgUpMTLSNldVfiyZOnGh7j5SktLQ0DR06VD4+PipWrJj+9a9/iat8Ij8RZGFqly9f1mOPPaaaNWtqx44dWrFihc6dO6dnn33W1mfo0KHavHmzli5dqtWrV+vnn3/Wrl27bjnm9u3bJUkzZ87UmTNnbNtZ+emnn3T69Glt3LhREyZM0IgRI9S2bVsVLVpU27Zt00svvaT+/fvrzz//tO3j5eWlWbNm6Y8//tDHH3+s6dOn66OPPpIkdenSRa+//rpCQ0N15swZnTlzRl26dJEkde7cWXFxcfrxxx+1c+dO1apVS82bN9fFixdz9RwCePDMnj1bbm5u2rx5s6ZOnSpJKlCggCZNmqT9+/dr9uzZ+umnn/Svf/3LoXHHjx+vWbNmacaMGdq0aZMuXryo7777Lj8eAvA3AzCBiIgIo0OHDpna3333XePxxx+3azt58qQhyThw4ICRkJBguLq6GgsXLrTdf/nyZcPT09MYMmSIrS0wMND46KOPbNuSjO+++85u3BEjRhjVq1e3qykwMNBIS0uztVWuXNlo1KiRbfvGjRtGoUKFjPnz59/ysf3nP/8xateufcvjGIZh/Pzzz0aRIkWMa9eu2bWXL1/emDZt2i3HBvDgioiIMAoWLGgUKlTIdnvmmWeMJk2aGDVr1rzj/gsXLjSKFStm287qvemjjz4yAgMDbdulSpUyxo0bZ9u+fv26UaZMmSzfv4G8wBpZmNrevXu1bt26LNeuHjlyRMnJybp+/brq1q1ra/f29lblypXz5PihoaEqUOD//2HD399fYWFhtu2CBQuqWLFiiouLs7V9/fXXmjRpko4cOaLExETduHFDRYoUue1x9u7dq8TERBUrVsyuPTk5WUeOHMmTxwLg/tOsWTNNmTLFtl2oUCF169ZNtWvXztR3zZo1ioqKUkxMjBISEnTjxg1du3ZNSUlJ8vT0vOOx4uPjdebMGdWrV8/W5uLiojp16rC8APmGIAtTS0xMVLt27TR27NhM95UqVSrfz851dXW127ZYLFm2paenS5J++eUXde/eXaNGjVKrVq3k7e2tBQsWaPz48bc9TmJiokqVKqX169dnus/HxydXjwHA/atQoUKqUKFClu3/FBsbq7Zt22rAgAEaM2aMfH19tWnTJvXp00epqany9PRUgQIFMgXSjPX9gLMQZGFqtWrV0qJFixQUFCQXl8wv53LlysnV1VXbt2/Xww8/LOnvWYODBw+qcePGtxzX1dVVaWlpeV7vli1bFBgYqLffftvWdvz4cbs+bm5umY5dq1YtnT17Vi4uLnYnVgBAXti5c6fS09M1fvx421+ZvvnmG7s+fn5+Onv2rAzDkMVikSTt2bPHdr+3t7dKlSqlbdu22d5fb9y4YVvTD+QHTvaCacTHx2vPnj12txdffFEXL15Ut27dtH37dh05ckQrV65U7969lZaWJi8vL0VEROjNN9/UunXrtH//fvXp00cFChSwvRFnJSgoSGvXrtXZs2d16dKlPHsMFStW1IkTJ7RgwQIdOXJEkyZNynQiRFBQkI4dO6Y9e/bo/PnzSklJUYsWLVS/fn117NhRq1atUmxsrLZs2aK3335bO3bsyLP6ADyYKlSooOvXr+uTTz7R0aNH9dVXX9lOAsvQtGlT/fXXXxo3bpyOHDmiyZMn68cff7TrM2TIEH3wwQdasmSJYmJiNHDgQF2+fPkuPhI8aAiyMI3169erZs2adrd3331XmzdvVlpamh5//HFVrVpVr776qnx8fGyzChMmTFD9+vXVtm1btWjRQuHh4QoJCZG7u/stjzV+/HitXr1aAQEBqlmzZp49hvbt2+u1117Tyy+/rBo1amjLli1655137Po8/fTTeuKJJ9SsWTP5+flp/vz5slgsWr58uRo3bqzevXurUqVK6tq1q44fPy5/f/88qw/Ag6l69eqaMGGCxo4dq7CwMM2dO1dRUVF2fUJCQvTZZ59p8uTJql69un799Ve98cYbdn1ef/11Pf/884qIiFD9+vXl5eWlTp063c2HggeMxWAFNh4wV69e1UMPPaTx48erT58+zi4HAADkEGtkcd/bvXu3YmJiVLduXcXHx2v06NGSpA4dOji5MgAAkBsEWTwQPvzwQx04cEBubm6qXbu2fv75ZxUvXtzZZQEAgFxgaQEAAABMiZO9AAAAYEoEWQAAAJgSQRYAAACmRJAFAACAKRFkAQAAYEoEWQAAAJgSQRYAAACmRJAFAACAKRFkAQAAYEr/D7dZmCp7UL8gAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Top feature correlations with fraud class"
      ],
      "metadata": {
        "id": "wF8pnwaX7Lnt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "top_corr = top_class_correlations(train_df, n=15)\n",
        "\n",
        "plt.figure(figsize=(8, 6))\n",
        "plt.barh(\n",
        "    top_corr[\"feature\"],\n",
        "    top_corr[\"correlation_with_class\"]\n",
        ")\n",
        "\n",
        "plt.xlabel(\"Pearson correlation with Class\")\n",
        "plt.ylabel(\"Feature\")\n",
        "plt.title(\"Top Training-Set Feature Correlations with Fraud Class\")\n",
        "plt.gca().invert_yaxis()\n",
        "plt.tight_layout()\n",
        "plt.savefig(FIG_DIR / \"training_top_feature_correlations.png\", dpi=300)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "TGYxKAzv7P20",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "outputId": "39de0a90-f808-4519-e4e6-f9a60695d28f"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Define model configurations"
      ],
      "metadata": {
        "id": "0hZK9WZZ1xky"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "configs = []\n",
        "\n",
        "print(\"Configs reset.\")\n",
        "print(\"Total configurations:\", len(configs))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "UhuK3IZ6GM0E",
        "outputId": "e08c495b-70ba-4d9b-de16-d24bccf1e74d"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Configs reset.\n",
            "Total configurations: 0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "configs = []\n",
        "\n",
        "negative_count = int((y_train == 0).sum())\n",
        "positive_count = int((y_train == 1).sum())\n",
        "training_imbalance_ratio = negative_count / positive_count\n",
        "\n",
        "class_weight_candidates = [\n",
        "    \"balanced\",\n",
        "    {0: 1, 1: training_imbalance_ratio}\n",
        "]\n",
        "\n",
        "smote_ratio_candidates = [0.10]\n",
        "smote_k_candidates = [5]"
      ],
      "metadata": {
        "id": "kpeTzBug10kq"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Logistic Regression"
      ],
      "metadata": {
        "id": "Yasg7v5913vo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "configs.append({\n",
        "    \"name\": \"LR_original\",\n",
        "    \"pipeline\": ImbPipeline([\n",
        "        (\"scaler\", StandardScaler()),\n",
        "        (\"model\", LogisticRegression(\n",
        "            penalty=\"l2\",\n",
        "            solver=\"liblinear\",\n",
        "            max_iter=3000,\n",
        "            class_weight=None,\n",
        "            random_state=SEED\n",
        "        ))\n",
        "    ])\n",
        "})\n",
        "\n",
        "configs.append({\n",
        "    \"name\": \"LR_weighted\",\n",
        "    \"pipeline\": ImbPipeline([\n",
        "        (\"scaler\", StandardScaler()),\n",
        "        (\"model\", LogisticRegression(\n",
        "            penalty=\"l2\",\n",
        "            solver=\"liblinear\",\n",
        "            max_iter=3000,\n",
        "            class_weight=\"balanced\",\n",
        "            random_state=SEED\n",
        "        ))\n",
        "    ])\n",
        "})\n",
        "\n",
        "configs.append({\n",
        "    \"name\": \"LR_SMOTE\",\n",
        "    \"pipeline\": ImbPipeline([\n",
        "        (\"scaler\", StandardScaler()),\n",
        "        (\"smote\", SMOTE(\n",
        "            sampling_strategy=0.10,\n",
        "            k_neighbors=5,\n",
        "            random_state=SEED\n",
        "        )),\n",
        "        (\"model\", LogisticRegression(\n",
        "            penalty=\"l2\",\n",
        "            solver=\"liblinear\",\n",
        "            max_iter=3000,\n",
        "            class_weight=None,\n",
        "            random_state=SEED\n",
        "        ))\n",
        "    ])\n",
        "})"
      ],
      "metadata": {
        "id": "hAz23l1L2wVT"
      },
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Random Forest"
      ],
      "metadata": {
        "id": "w1YzI6Sg36GA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "configs.append({\n",
        "    \"name\": \"RF_original\",\n",
        "    \"pipeline\": ImbPipeline([\n",
        "        (\"model\", RandomForestClassifier(\n",
        "            n_estimators=50,\n",
        "            max_depth=6,\n",
        "            min_samples_leaf=10,\n",
        "            max_features=\"sqrt\",\n",
        "            class_weight=None,\n",
        "            random_state=SEED,\n",
        "            n_jobs=-1,\n",
        "            bootstrap=True,\n",
        "            max_samples=0.3\n",
        "        ))\n",
        "    ])\n",
        "})\n",
        "\n",
        "configs.append({\n",
        "    \"name\": \"RF_weighted\",\n",
        "    \"pipeline\": ImbPipeline([\n",
        "        (\"model\", RandomForestClassifier(\n",
        "            n_estimators=50,\n",
        "            max_depth=6,\n",
        "            min_samples_leaf=10,\n",
        "            max_features=\"sqrt\",\n",
        "            class_weight=\"balanced\",\n",
        "            random_state=SEED,\n",
        "            n_jobs=-1,\n",
        "            bootstrap=True,\n",
        "            max_samples=0.3\n",
        "        ))\n",
        "    ])\n",
        "})\n",
        "\n",
        "configs.append({\n",
        "    \"name\": \"RF_SMOTE\",\n",
        "    \"pipeline\": ImbPipeline([\n",
        "        (\"scaler\", StandardScaler()),\n",
        "        (\"smote\", SMOTE(\n",
        "            sampling_strategy=0.10,\n",
        "            k_neighbors=5,\n",
        "            random_state=SEED\n",
        "        )),\n",
        "        (\"model\", RandomForestClassifier(\n",
        "            n_estimators=50,\n",
        "            max_depth=6,\n",
        "            min_samples_leaf=10,\n",
        "            max_features=\"sqrt\",\n",
        "            class_weight=None,\n",
        "            random_state=SEED,\n",
        "            n_jobs=-1,\n",
        "            bootstrap=True,\n",
        "            max_samples=0.3\n",
        "        ))\n",
        "    ])\n",
        "})"
      ],
      "metadata": {
        "id": "nkd7U4x33ZME"
      },
      "execution_count": 59,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##XGBoost"
      ],
      "metadata": {
        "id": "NX1XVzSZ4ExQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "configs.append({\n",
        "    \"name\": \"XGB_original\",\n",
        "    \"pipeline\": ImbPipeline([\n",
        "        (\"model\", XGBClassifier(\n",
        "            n_estimators=100,\n",
        "            learning_rate=0.05,\n",
        "            max_depth=3,\n",
        "            min_child_weight=5,\n",
        "            subsample=0.8,\n",
        "            colsample_bytree=0.8,\n",
        "            reg_lambda=1.0,\n",
        "            scale_pos_weight=1,\n",
        "            objective=\"binary:logistic\",\n",
        "            eval_metric=\"logloss\",\n",
        "            tree_method=\"hist\",\n",
        "            random_state=SEED,\n",
        "            n_jobs=-1\n",
        "        ))\n",
        "    ])\n",
        "})\n",
        "\n",
        "configs.append({\n",
        "    \"name\": \"XGB_weighted\",\n",
        "    \"pipeline\": ImbPipeline([\n",
        "        (\"model\", XGBClassifier(\n",
        "            n_estimators=100,\n",
        "            learning_rate=0.05,\n",
        "            max_depth=3,\n",
        "            min_child_weight=5,\n",
        "            subsample=0.8,\n",
        "            colsample_bytree=0.8,\n",
        "            reg_lambda=1.0,\n",
        "            scale_pos_weight=training_imbalance_ratio,\n",
        "            objective=\"binary:logistic\",\n",
        "            eval_metric=\"logloss\",\n",
        "            tree_method=\"hist\",\n",
        "            random_state=SEED,\n",
        "            n_jobs=-1\n",
        "        ))\n",
        "    ])\n",
        "})\n",
        "\n",
        "configs.append({\n",
        "    \"name\": \"XGB_SMOTE\",\n",
        "    \"pipeline\": ImbPipeline([\n",
        "        (\"scaler\", StandardScaler()),\n",
        "        (\"smote\", SMOTE(\n",
        "            sampling_strategy=0.10,\n",
        "            k_neighbors=5,\n",
        "            random_state=SEED\n",
        "        )),\n",
        "        (\"model\", XGBClassifier(\n",
        "            n_estimators=100,\n",
        "            learning_rate=0.05,\n",
        "            max_depth=3,\n",
        "            min_child_weight=5,\n",
        "            subsample=0.8,\n",
        "            colsample_bytree=0.8,\n",
        "            reg_lambda=1.0,\n",
        "            scale_pos_weight=1,\n",
        "            objective=\"binary:logistic\",\n",
        "            eval_metric=\"logloss\",\n",
        "            tree_method=\"hist\",\n",
        "            random_state=SEED,\n",
        "            n_jobs=-1\n",
        "        ))\n",
        "    ])\n",
        "})"
      ],
      "metadata": {
        "id": "9VUy8BJA4W0_"
      },
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Total configurations:\", len(configs))\n",
        "\n",
        "for config in configs:\n",
        "    print(config[\"name\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "E_GmVuG82NTm",
        "outputId": "ec1d7d65-bee9-47f2-e0ea-5509f5623b45"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Total configurations: 9\n",
            "LR_original\n",
            "LR_weighted\n",
            "LR_SMOTE\n",
            "RF_original\n",
            "RF_weighted\n",
            "RF_SMOTE\n",
            "XGB_original\n",
            "XGB_weighted\n",
            "XGB_SMOTE\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Cross-validation and hyperparameter tuning"
      ],
      "metadata": {
        "id": "7TgCeYOo5NmL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import cross_validate\n",
        "\n",
        "cv = StratifiedKFold(\n",
        "    n_splits=3,\n",
        "    shuffle=True,\n",
        "    random_state=SEED\n",
        ")\n",
        "\n",
        "screening_rows = {}\n",
        "\n",
        "scoring = {\n",
        "    \"average_precision\": \"average_precision\",\n",
        "    \"roc_auc\": \"roc_auc\",\n",
        "    \"recall\": \"recall\",\n",
        "    \"precision\": \"precision\",\n",
        "    \"f1\": \"f1\"\n",
        "}\n",
        "\n",
        "search_objects = {}\n",
        "cv_summary_rows = []\n",
        "\n",
        "print(\"Starting fast screening...\")\n",
        "print(\"Number of configurations:\", len(configs))\n",
        "\n",
        "for config in configs:\n",
        "    name = config[\"name\"]\n",
        "    print(\"\\n===================================================\")\n",
        "    print(\"Running fast CV screening:\", name)\n",
        "    print(\"===================================================\")\n",
        "\n",
        "    pipeline = config[\"pipeline\"]\n",
        "\n",
        "    scores = cross_validate(\n",
        "        estimator=pipeline,\n",
        "        X=X_train,\n",
        "        y=y_train,\n",
        "        cv=cv,\n",
        "        scoring=scoring,\n",
        "        n_jobs=1,\n",
        "        return_train_score=False\n",
        "    )\n",
        "\n",
        "    row = {\n",
        "        \"configuration\": name,\n",
        "        \"best_cv_average_precision\": scores[\"test_average_precision\"].mean(),\n",
        "        \"std_cv_average_precision\": scores[\"test_average_precision\"].std(),\n",
        "        \"mean_cv_roc_auc\": scores[\"test_roc_auc\"].mean(),\n",
        "        \"std_cv_roc_auc\": scores[\"test_roc_auc\"].std(),\n",
        "        \"mean_cv_recall\": scores[\"test_recall\"].mean(),\n",
        "        \"std_cv_recall\": scores[\"test_recall\"].std(),\n",
        "        \"mean_cv_precision\": scores[\"test_precision\"].mean(),\n",
        "        \"std_cv_precision\": scores[\"test_precision\"].std(),\n",
        "        \"mean_cv_f1\": scores[\"test_f1\"].mean(),\n",
        "        \"std_cv_f1\": scores[\"test_f1\"].std()\n",
        "    }\n",
        "\n",
        "    cv_summary_rows.append(row)\n",
        "\n",
        "    print(\"Mean CV average precision:\", row[\"best_cv_average_precision\"])\n",
        "    print(\"Mean CV ROC-AUC:\", row[\"mean_cv_roc_auc\"])\n",
        "    print(\"Mean CV recall:\", row[\"mean_cv_recall\"])\n",
        "    print(\"Mean CV precision:\", row[\"mean_cv_precision\"])\n",
        "\n",
        "\n",
        "cv_summary = pd.DataFrame(cv_summary_rows)\n",
        "\n",
        "cv_summary = cv_summary.sort_values(\n",
        "    \"best_cv_average_precision\",\n",
        "    ascending=False\n",
        ").reset_index(drop=True)\n",
        "\n",
        "cv_summary.to_csv(\n",
        "    TABLE_DIR / \"cv_model_comparison_summary_fast_screening.csv\",\n",
        "    index=False\n",
        ")\n",
        "\n",
        "print(\"\\nFast cross-validation model comparison:\")\n",
        "print(\n",
        "    cv_summary[\n",
        "        [\n",
        "            \"configuration\",\n",
        "            \"best_cv_average_precision\",\n",
        "            \"std_cv_average_precision\",\n",
        "            \"mean_cv_roc_auc\",\n",
        "            \"mean_cv_recall\",\n",
        "            \"mean_cv_precision\",\n",
        "            \"mean_cv_f1\"\n",
        "        ]\n",
        "    ]\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "dt2vVYMX5R8x",
        "outputId": "36fd98da-1048-4a89-ca0b-7f1f6a1f3c75"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Starting fast screening...\n",
            "Number of configurations: 9\n",
            "\n",
            "===================================================\n",
            "Running fast CV screening: LR_original\n",
            "===================================================\n",
            "Mean CV average precision: 0.7606856142574889\n",
            "Mean CV ROC-AUC: 0.9748182934975017\n",
            "Mean CV recall: 0.6421852108875009\n",
            "Mean CV precision: 0.869276167028976\n",
            "\n",
            "===================================================\n",
            "Running fast CV screening: LR_weighted\n",
            "===================================================\n",
            "Mean CV average precision: 0.7514551902527454\n",
            "Mean CV ROC-AUC: 0.9764935758436883\n",
            "Mean CV recall: 0.9086089906700593\n",
            "Mean CV precision: 0.06060783933976716\n",
            "\n",
            "===================================================\n",
            "Running fast CV screening: LR_SMOTE\n",
            "===================================================\n",
            "Mean CV average precision: 0.7542573857985232\n",
            "Mean CV ROC-AUC: 0.9752220788039306\n",
            "Mean CV recall: 0.8452270799599044\n",
            "Mean CV precision: 0.3393345764540158\n",
            "\n",
            "===================================================\n",
            "Running fast CV screening: RF_original\n",
            "===================================================\n",
            "Mean CV average precision: 0.7881962705586587\n",
            "Mean CV ROC-AUC: 0.9669484400202385\n",
            "Mean CV recall: 0.6877939702367183\n",
            "Mean CV precision: 0.8747011589559176\n",
            "\n",
            "===================================================\n",
            "Running fast CV screening: RF_weighted\n",
            "===================================================\n",
            "Mean CV average precision: 0.7615195825247576\n",
            "Mean CV ROC-AUC: 0.9678704305513238\n",
            "Mean CV recall: 0.7994833834528491\n",
            "Mean CV precision: 0.8250012590603922\n",
            "\n",
            "===================================================\n",
            "Running fast CV screening: RF_SMOTE\n",
            "===================================================\n",
            "Mean CV average precision: 0.8114887222783448\n",
            "Mean CV ROC-AUC: 0.9831562431588967\n",
            "Mean CV recall: 0.8350296861747243\n",
            "Mean CV precision: 0.7729315236561614\n",
            "\n",
            "===================================================\n",
            "Running fast CV screening: XGB_original\n",
            "===================================================\n",
            "Mean CV average precision: 0.823335134535942\n",
            "Mean CV ROC-AUC: 0.9816912097611192\n",
            "Mean CV recall: 0.7766404503045724\n",
            "Mean CV precision: 0.913570487483531\n",
            "\n",
            "===================================================\n",
            "Running fast CV screening: XGB_weighted\n",
            "===================================================\n",
            "Mean CV average precision: 0.7142453299482178\n",
            "Mean CV ROC-AUC: 0.9804948096677343\n",
            "Mean CV recall: 0.8680507363713471\n",
            "Mean CV precision: 0.12207107928746071\n",
            "\n",
            "===================================================\n",
            "Running fast CV screening: XGB_SMOTE\n",
            "===================================================\n",
            "Mean CV average precision: 0.7758118034242338\n",
            "Mean CV ROC-AUC: 0.9819484776802653\n",
            "Mean CV recall: 0.8502968617472434\n",
            "Mean CV precision: 0.5460447604038665\n",
            "\n",
            "Fast cross-validation model comparison:\n",
            "  configuration  best_cv_average_precision  std_cv_average_precision  \\\n",
            "0  XGB_original                   0.823335                  0.009167   \n",
            "1      RF_SMOTE                   0.811489                  0.007942   \n",
            "2   RF_original                   0.788196                  0.012211   \n",
            "3     XGB_SMOTE                   0.775812                  0.019588   \n",
            "4   RF_weighted                   0.761520                  0.001905   \n",
            "5   LR_original                   0.760686                  0.014970   \n",
            "6      LR_SMOTE                   0.754257                  0.016063   \n",
            "7   LR_weighted                   0.751455                  0.026036   \n",
            "8  XGB_weighted                   0.714245                  0.015893   \n",
            "\n",
            "   mean_cv_roc_auc  mean_cv_recall  mean_cv_precision  mean_cv_f1  \n",
            "0         0.981691        0.776640           0.913570    0.839448  \n",
            "1         0.983156        0.835030           0.772932    0.802098  \n",
            "2         0.966948        0.687794           0.874701    0.769923  \n",
            "3         0.981948        0.850297           0.546045    0.663757  \n",
            "4         0.967870        0.799483           0.825001    0.811016  \n",
            "5         0.974818        0.642185           0.869276    0.737832  \n",
            "6         0.975222        0.845227           0.339335    0.482884  \n",
            "7         0.976494        0.908609           0.060608    0.113615  \n",
            "8         0.980495        0.868051           0.122071    0.213798  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Evaluate all tuned models on untouched test set"
      ],
      "metadata": {
        "id": "VcpR8GHD5XEv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "test_rows = []\n",
        "\n",
        "for config in configs:\n",
        "    name = config[\"name\"]\n",
        "    print(\"\\nEvaluating on untouched test set:\", name)\n",
        "\n",
        "    estimator = config[\"pipeline\"]\n",
        "    estimator.fit(X_train, y_train)\n",
        "    y_test_score = estimator.predict_proba(X_test)[:, 1]\n",
        "\n",
        "    metrics = evaluate_predictions(\n",
        "        y_true=y_test,\n",
        "        y_score=y_test_score,\n",
        "        threshold=0.5\n",
        "    )\n",
        "\n",
        "    metrics[\"configuration\"] = name\n",
        "    test_rows.append(metrics)\n",
        "\n",
        "    plot_precision_recall_curve(\n",
        "        y_test,\n",
        "        y_test_score,\n",
        "        FIG_DIR / f\"test_pr_curve_{name}.png\",\n",
        "        f\"Test Precision-Recall Curve: {name}\"\n",
        "    )\n",
        "\n",
        "    plot_roc_curve_custom(\n",
        "        y_test,\n",
        "        y_test_score,\n",
        "        FIG_DIR / f\"test_roc_curve_{name}.png\",\n",
        "        f\"Test ROC Curve: {name}\"\n",
        "    )\n",
        "\n",
        "\n",
        "test_summary = pd.DataFrame(test_rows)\n",
        "\n",
        "if test_summary.empty:\n",
        "    raise ValueError(\"No test results were produced. Check that configs contains model pipelines.\")\n",
        "\n",
        "test_summary = test_summary.sort_values(\n",
        "    \"average_precision\",\n",
        "    ascending=False\n",
        ").reset_index(drop=True)\n",
        "\n",
        "test_summary.to_csv(\n",
        "    TABLE_DIR / \"test_results_all_models_threshold_0_5.csv\",\n",
        "    index=False\n",
        ")\n",
        "\n",
        "print(\"\\nTest-set results at default threshold 0.5:\")\n",
        "print(\n",
        "    test_summary[\n",
        "        [\n",
        "            \"configuration\",\n",
        "            \"average_precision\",\n",
        "            \"roc_auc\",\n",
        "            \"recall\",\n",
        "            \"precision\",\n",
        "            \"f1\",\n",
        "            \"f2\",\n",
        "            \"mcc\",\n",
        "            \"tp\",\n",
        "            \"fp\",\n",
        "            \"fn\",\n",
        "            \"tn\"\n",
        "        ]\n",
        "    ]\n",
        ")"
      ],
      "metadata": {
        "id": "oVKSojnj5azY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 9548
        },
        "outputId": "e910281b-83f2-49f9-b668-a44c6f018159"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Evaluating on untouched test set: LR_original\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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juLg4eXt7a+3atXr00UfLPXp9Oi1atNC6deu0f//+ctVW1sh6UVFRqZ/fU7+Wig0aNEiTJk1SSkqK/P399f3332vw4MH2f1gVn9utt95aYi5tscrMC6+IkJAQ+/Xu27evWrRooauuukqvv/56idHV8ijvwwLK+pxVhzN9TxQVFalPnz46duyYHn30UbVo0UK+vr46ePCghg8fXiVfg0BVIcgC1SguLk4LFy5U9+7dy/WD6sILL9SFF16oSZMm6fPPP9eQIUM0c+ZM3X777TX+9Jy4uDgZY9SoUSM1a9bstP0k6c8//yxXYD6Zm5ubevXqpV69eunVV1/Vc889pyeeeEJLliwpdV8xMTGSTtwYc6qtW7cqJCSkwsuGvfLKKw4jTmdaW/euu+7Sa6+9pieffFLXXnutLBaL4uLitGHDBvXq1eu01ykuLk42m02bN292+NXwyZYuXaqjR4/qm2++0cUXX2xvL15loioMGDBA//3vf/Xpp5+WuQTbyYKDg5Wamlqife/evWrcuHG5jzto0CBNnDhRX3/9tcLDw5Wenq6bb77Z/n5oaKj8/f1VVFRU4a+l6tK/f3/17NlTzz33nO66665yf33FxMTIZrNpx44dDutIJyUlKTU11f61XFExMTElVhiQVGpbZW3cuFHbt2/XjBkzNHToUHv7ggULquwYQFVhjixQjW666SYVFRXp2WefLfFeYWGhPRwcP368xFy/4qBTvFRPnTp1JKnUQFEdrrvuOrm7u2vixIklajPG6OjRo5Kkjh07qlGjRpoyZUqJ2k43f/HYsWMl2k4951NFRkaqQ4cOmjFjhsOx/vzzT/3000/q169fOc7MUadOndS7d2/7x5l+7e/h4aEHH3xQW7Zs0XfffSfpxHU+ePCg3nvvvRL9c3JylJWVJUkaOHCg3Nzc9Mwzz5QY1Sr+XBWPlp38ucvPz9dbb71V4XMryw033KC2bdtq0qRJWrFiRYn3MzIy9MQTT9hfx8XF6ffff3eYgjFnzpxSl2E7nZYtW6pt27aaNWuWZs2apcjISIew7u7uruuvv15ff/21/vzzzxLbJycnO7yuieW3JOnRRx/V0aNHS72+ZSn+WpwyZYpDe/Goff/+/StVS9++fbVixQqtX7/e3nbs2LEyf+tTGaV9DRpjHJbTA2oLRmSBatSzZ0/dddddmjx5stavX6/LL79cnp6e2rFjh7788ku9/vrruuGGGzRjxgy99dZbuvbaaxUXF6eMjAy99957CggIsP9A9PHxUatWrTRr1iw1a9ZMdevWVZs2bSo8N7W84uLi9O9//1vjxo3Tnj17NHDgQPn7+yshIUGzZ8/WnXfeqYceekhubm72p1116NBBI0aMUGRkpLZu3apNmzbpxx9/LHX/zzzzjH755Rf1799fMTExOnLkiN566y01aNCg1LVNi7300ku68sorFR8fr1GjRtmX3woMDKzUurqVMXz4cI0fP14vvPCCBg4cqNtuu01ffPGF7r77bi1ZskTdu3dXUVGRtm7dqi+++MK+PmiTJk30xBNP6Nlnn1WPHj103XXXyWq1avXq1YqKitLkyZPVrVs3BQcHa9iwYfrXv/4li8WiTz75pEpvavL09NQ333yj3r176+KLL9ZNN92k7t27y9PTU5s2bdLnn3+u4OBg+1qyt99+u7766itdccUVuummm7Rr1y59+umnDkuQldegQYM0fvx4eXt7a9SoUSXmQz///PNasmSJunbtqjvuuEOtWrXSsWPHtHbtWi1cuNDhH0AVXX5r0aJFys3NLdE+cODA034fXXnllWrTpo1effVVjR49ulxPmmvfvr2GDRumd9991z5dZNWqVZoxY4YGDhyoSy+9tFw1n+qRRx7Rp59+qj59+ujee++1L7/VsGFDHTt2rEp+c9OiRQvFxcXpoYce0sGDBxUQEKCvv/66xFxZoFao6WUSgHPZqctvFXv33XdNp06djI+Pj/H39zdt27Y1jzzyiDl06JAxxpi1a9eawYMHm4YNGxqr1WrCwsLMVVddZf744w+H/fz222+mU6dOxsvL64zLLBUvtfPll1+etubi5XPKWgbr66+/NhdddJHx9fU1vr6+pkWLFmb06NFm27ZtDv2WLVtm+vTpY/z9/Y2vr69p166deeONN0ocp9iiRYvMNddcY6KiooyXl5eJiooygwcPNtu3b7f3KW35LWOMWbhwoenevbvx8fExAQEBZsCAAWbz5s3lOq8PP/ywxDJFZdFpll16+umnjSSzZMkSY4wx+fn55oUXXjCtW7c2VqvVBAcHm06dOpmJEyeatLQ0h20/+OADc8EFF9j79ezZ0yxYsMD+/vLly82FF15ofHx8TFRUlHnkkUfMjz/+6HA8Yyq//Fax48ePm/Hjx5u2bduaOnXqGG9vb9OmTRszbtw4c/jwYYe+r7zyiqlfv76xWq2me/fu5o8//ihzeafTfc3t2LHDSDKSzLJly0rtk5SUZEaPHm2io6ONp6eniYiIML169TLvvvuuQ7+KLr9V1scnn3xijDmx1FX//v1L3cdHH31U6tfi6RQUFJiJEyeaRo0aGU9PTxMdHW3GjRvnsITamY5b2tJn69atMz169DBWq9U0aNDATJ482fznP/8xkkxiYqK9X3mvT2nfZ5s3bza9e/c2fn5+JiQkxNxxxx1mw4YNJfqx/BaczWJMNa4kDQAAqt3999+vd955R5mZmVV2oyTgCpgjCwCACzn1MbFHjx7VJ598oosuuogQi/MOc2QBAKiAxMTE075/6lrEVS0+Pl6XXHKJWrZsqaSkJE2fPl3p6el66qmnqu2YQG3F1AIAACrgTDdUnboWcVV7/PHH9dVXX+nAgQOyWCzq2LGjJkyYUGuWLANqEkEWAIAKWLhw4Wnfj4qKOuMybgCqBkEWAAAALombvQAAAOCSzrubvWw2mw4dOiR/f/8af+QnAAAATs8Yo4yMDEVFRZV4aMqpzrsge+jQIUVHRzu7DAAAAJzG/v371aBBg9P2Oe+CrL+/v6QTn5yAgAAnVwMAAICTpaenKzo62p7ZTue8C7LF0wkCAgIIsgAAALVUeaaAcrMXAAAAXBJBFgAAAC6JIAsAAACXdN7NkQUAnBuKiopUUFDg7DIAVJCnp6fc3d2rZF8EWQCASzHGKDExUampqc4uBUAlBQUFKSIi4qzX9CfIAgBcSnGIDQsLU506dXi4DeBCjDHKzs7WkSNHJEmRkZFntT+CLADAZRQVFdlDbL169ZxdDoBK8PHxkSQdOXJEYWFhZzXNgJu9AAAuo3hObJ06dZxcCYCzUfw9fLbz3AmyAACXw3QCwLVV1fcwQRYAAAAuiSALAADOOcOHD9fAgQOrvC9qF6cG2V9++UUDBgxQVFSULBaLvv322zNus3TpUnXs2FFWq1VNmjTRRx99VO11AgBQVVasWCF3d3f179/f2aWc015//fVyZ4SK9HWmY8eOaciQIQoICFBQUJBGjRqlzMzMMvvv2bNHFoul1I8vv/yyRP+jR4+qQYMGslgsDsvbLV26tNR9JCYm2vu8/fbbateunQICAhQQEKD4+Hj98MMPVXr+pXFqkM3KylL79u01derUcvVPSEhQ//79demll2r9+vW6//77dfvtt+vHH3+s5koBAKga06dP17333qtffvlFhw4dqtZjGWNUWFhYrceoalVVc2BgoIKCgqq8rzMNGTJEmzZt0oIFCzRnzhz98ssvuvPOO8vsHx0drcOHDzt8TJw4UX5+frryyitL9B81apTatWtX5v62bdvmsK+wsDD7ew0aNNDzzz+vNWvW6I8//tBll12ma665Rps2bTq7kz4TU0tIMrNnzz5tn0ceecS0bt3aoW3QoEGmb9++5T5OWlqakWTS0tIqUyYAwIlycnLM5s2bTU5OjrNLqZSMjAzj5+dntm7dagYNGmQmTZpkf2/w4MHmpptucuifn59v6tWrZ2bMmGGMMaaoqMg899xzJjY21nh7e5t27dqZL7/80t5/yZIlRpKZN2+e6dixo/H09DRLliwxO3fuNFdffbUJCwszvr6+pnPnzmbBggUOxzp06JDp16+f8fb2NrGxseazzz4zMTEx5rXXXrP3OX78uBk1apQJCQkx/v7+5tJLLzXr168v83wTEhKMJPPf//7XxMfHG6vValq3bm2WLl16xprPdK7GGPPnn3+a/v37G39/f+Pn52cuuugis3PnTmOMMcOGDTPXXHONve+XX35p2rRpY7y9vU3dunVNr169TGZmZql9c3Nzzb333mtCQ0ON1Wo13bt3N6tWrSpR88KFC02nTp2Mj4+PiY+PN1u3bi3zc3G2Nm/ebCSZ1atX29t++OEHY7FYzMGDB8u9nw4dOpiRI0eWaH/rrbdMz549zaJFi4wkc/z4cft7xed7clt5BAcHm/fff7/U9073vVyRrOZS68iuWLFCvXv3dmjr27ev7r//fucUVA7r96fqUGqOs8uApLb1AxVdlyV7gHONMUY5BUVOObaPp3uF7r7+4osv1KJFCzVv3ly33nqr7r//fo0bN04Wi0VDhgzRjTfeqMzMTPn5+UmSfvzxR2VnZ+vaa6+VJE2ePFmffvqppk2bpqZNm+qXX37RrbfeqtDQUPXs2dN+nMcee0wvv/yyGjdurODgYO3fv1/9+vXTpEmTZLVa9fHHH2vAgAHatm2bGjZsKEkaOnSoUlJStHTpUnl6emrs2LH2ReuL3XjjjfLx8dEPP/ygwMBAvfPOO+rVq5e2b9+uunXrlnneDz/8sKZMmaJWrVrp1Vdf1YABA5SQkOCwFvCpNZ/pXA8ePKiLL75Yl1xyiRYvXqyAgAAtX7681NHcw4cPa/DgwXrxxRd17bXXKiMjQ7/++quMMaXW+8gjj+jrr7/WjBkzFBMToxdffFF9+/bVzp07Hc7ziSee0CuvvKLQ0FDdfffdGjlypJYvX17m56F169bau3dvme/36NGjzF/Hr1ixQkFBQercubO9rXfv3nJzc9PKlSvtXyOns2bNGq1fv77Eb8I3b96sZ555RitXrtTu3bvL3L5Dhw7Ky8tTmzZt9PTTT6t79+6l9isqKtKXX36prKwsxcfHn7Gus+FSQTYxMVHh4eEObeHh4UpPT1dOTo59gd2T5eXlKS8vz/46PT292us82UfLE/Tt+ur91RHKJ8TPqlWP95KbG8v2AOeSnIIitRrvnClmm5/pqzpe5f9ROn36dN16662SpCuuuEJpaWn6+eefdckll6hv377y9fXV7Nmzddttt0mSPv/8c1199dXy9/dXXl6ennvuOS1cuNAeDho3bqxly5bpnXfecQiyzzzzjPr06WN/XbduXbVv397++tlnn9Xs2bP1/fffa8yYMdq6dasWLlyo1atX24PS+++/r6ZNm9q3WbZsmVatWqUjR47IarVKkl5++WV9++23+uqrr077K+4xY8bo+uuvl3RiLuX8+fM1ffp0PfLII6XWXJ5znTp1qgIDAzVz5kx5enpKkpo1a1bq8Q8fPqzCwkJdd911iomJkSS1bdu21L5ZWVl6++239dFHH9l//f7ee+9pwYIFmj59uh5++GF730mTJtk/74899pj69++v3NxceXt7l7rvefPmnXbd1NJyTLHExESHX+VLkoeHh+rWreswV/V0pk+frpYtW6pbt272try8PA0ePFgvvfSSGjZsWGqQjYyM1LRp09S5c2fl5eXp/fff1yWXXKKVK1eqY8eO9n4bN25UfHy8cnNz5efnp9mzZ6tVq1blqq2yXCrIVsbkyZM1ceJEpx2/caifusSW/a9UVL8Cm03r9qUqJTNPNmPkJoIsgJq3bds2rVq1SrNnz5Z0IoQMGjRI06dP1yWXXCIPDw/ddNNN+uyzz3TbbbcpKytL3333nWbOnClJ2rlzp7Kzsx0CqiTl5+frggsucGg7edROkjIzM/X0009r7ty59lCXk5Ojffv22Wvz8PBwCCVNmjRRcHCw/fWGDRuUmZlZ4olqOTk52rVr12nP/eRROQ8PD3Xu3Flbtmwps+bynOv69evVo0cPe4g9nfbt26tXr15q27at+vbtq8svv1w33HCDw/kV27VrlwoKChxGGz09PdWlS5cSNZ88n7T4UatHjhyxj3KfqjhEO0NOTo4+//xzPfXUUw7t48aNU8uWLe3/wCpN8+bN1bx5c/vrbt26adeuXXrttdf0ySefOPRbv3690tLS9NVXX2nYsGH6+eefqzXMulSQjYiIUFJSkkNbUlKSAgICyvxXzLhx4zR27Fj76/T0dEVHR1drnSf7V6+m+levpmfuiGqTll2g9s/85OwyAFQTH093bX6mr9OOXV7Tp09XYWGhoqKi7G3GGFmtVr355psKDAzUkCFD1LNnTx05ckQLFiyQj4+PrrjiCkmy350+d+5c1a9f32HfxSOkxXx9fR1eP/TQQ1qwYIFefvllNWnSRD4+PrrhhhuUn59f7vozMzMVGRmppUuXlnivKm6UOrnm8pzr6UYvT+Xu7q4FCxbot99+008//aQ33nhDTzzxhFauXKlGjRpVuuaTQ3TxFBObzVZm/7OZWhAREVFiqkdhYaGOHTumiIiIM9b61VdfKTs7W0OHDnVoX7x4sTZu3KivvvpKkuzTLUJCQvTEE0+UORjYpUsXLVu2zKHNy8tLTZo0kSR16tRJq1ev1uuvv6533nnnjPVVlksF2fj4eM2bN8+hbcGCBaedf2G1Wkt8gwMAzh0Wi6VCv953hsLCQn388cd65ZVXdPnllzu8N3DgQP33v//V3XffrW7duik6OlqzZs3SDz/8oBtvvNEellq1aiWr1ap9+/Y5TCMoj+XLl2v48OH2eZSZmZnas2eP/f3mzZursLBQ69atU6dOnSSdGBU9fvy4vU/Hjh2VmJgoDw8PxcbGVuj4v//+uy6++GL752LNmjUaM2ZMmf3Lc67t2rXTjBkzVFBQUK5RWYvFou7du6t79+4aP368YmJiNHv2bIfBLkmKi4uTl5eXli9fbh9BLSgo0OrVq8/6npyzmVoQHx+v1NRUrVmzxn6NFi9eLJvNpq5du57x2NOnT9fVV1+t0NBQh/avv/5aOTl/38uzevVqjRw5Ur/++qvi4uLK3N/69evto9BlsdlsDtM7q4NTv/MzMzO1c+dO++uEhAStX79edevWVcOGDTVu3DgdPHhQH3/8sSTp7rvv1ptvvqlHHnlEI0eO1OLFi/XFF19o7ty5zjoFAADOaM6cOTp+/LhGjRqlwMBAh/euv/56TZ8+XXfffbck6ZZbbtG0adO0fft2LVmyxN7P399fDz30kB544AHZbDZddNFFSktL0/LlyxUQEKBhw4aVefymTZvqm2++0YABA2SxWPTUU085jBy2aNFCvXv31p133qm3335bnp6eevDBB+Xj42Mfaezdu7fi4+M1cOBAvfjii2rWrJkOHTqkuXPn6tprry0xneFkU6dOVdOmTdWyZUu99tprOn78uEaOHFlm//Kc65gxY/TGG2/o5ptv1rhx4xQYGKjff/9dXbp0cfg1uCStXLlSixYt0uWXX66wsDCtXLlSycnJatmyZYlj+/r66p577tHDDz9szyMvvviisrOzNWrUqDJrLo+zmVrQsmVLXXHFFbrjjjs0bdo0FRQUaMyYMbr55pvto/wHDx5Ur1699PHHH6tLly72bXfu3KlffvmlxGCgpBJhNSUlxX684pH2KVOmqFGjRmrdurVyc3P1/vvva/Hixfrpp79/2zlu3DhdeeWVatiwoTIyMvT5559r6dKl1b9EaoXWUahixcs5nPoxbNgwY8yJ5TB69uxZYpsOHToYLy8v07hxY/Phhx9W6Jgsv3X+Sc3KNzGPzjExj84xBYVFzi4HwFlw1eW3rrrqKtOvX79S31u5cqWRZDZs2GCM+XuZpZiYGGOz2Rz62mw2M2XKFNO8eXPj6elpQkNDTd++fc3PP/9sjCl7maSEhARz6aWXGh8fHxMdHW3efPNN07NnT3PffffZ+xw6dMhceeWVxmq1mpiYGPP555+bsLAwM23aNHuf9PR0c++995qoqCjj6elpoqOjzZAhQ8y+fftKPbfi5bc+//xz06VLF+Pl5WVatWplFi9ebO9TVs1nOldjjNmwYYO5/PLLTZ06dYy/v7/p0aOH2bVrlzHGcUmtzZs3m759+9qX02rWrJl544037Ps5dfmtnJwcc++995qQkJDTLr91cs3r1q0zkkxCQkKpn4uqcPToUTN48GDj5+dnAgICzIgRI0xGRob9/eLP95IlSxy2GzdunImOjjZFRWf+GVjaub3wwgsmLi7OvnTZJZdc4nANjTFm5MiRJiYmxnh5eZnQ0FDTq1cv89NPP5V5nKpafstiTBlrT5yj0tPTFRgYqLS0NAUEBDi7HNSAk+fI7px0pTzceTIz4Kpyc3OVkJCgRo0alXlnOKrGgQMHFB0drYULF6pXr16V2seePXvUqFEjrVu3Th06dKjaAuHSTve9XJGsVrsnFQEAgBqxePFiZWZmqm3btjp8+LAeeeQRxcbG2ue2ArURQRYAAKigoECPP/64du/eLX9/f3Xr1k2fffZZuW6kApyFIAsAANS3b1/17Vu1y5jFxsaW+fQsoCowWRAAAAAuiSALAAAAl0SQBQC4nNM9PQlA7VdV38PMkQUAuAwvLy+5ubnp0KFDCg0NlZeXl33BfgC1nzFG+fn5Sk5Olpubm7y8vM5qfwRZAIDLcHNzU6NGjXT48GEdOnTI2eUAqKQ6deqoYcOGcnM7u8kBBFkAgEvx8vJSw4YNVVhYqKKiImeXA6CC3N3d5eHhUSW/TSHIAgBcjsVikaenJ2ucAuc5bvYCAACAS2JEFue9jNwCbUvM0NbEDG1NTNfWwxnKyC3UKze1V5v6gc4uDwAAlIEgi/PKruQs7TiSoa2H/wqtiRk6cDyn1L6LthwhyAIAUIsRZHFe6Tvll1LbIwO91TzCXy0iArR273Gt2nNMRjxWEQCA2owgi3NeHau7IgK8lZieqzpe7moW7q+WkSdC64nw6q+gOn+vY/fE7I1ateeYEysGAADlQZDFOc/T3U2LHuypo5n5ahDsIzc3Fk8HAOBcQJDFecHX6iFfK1/uAACcS1h+CwAAAC6JIAsAAACXRJAFajGbjZUTAAAoC5MGgVoiI7dAWw5naPOhNG06lK5Nh9K180imrmwboddvvsDZ5QEAUOsQZAEnOJKRq02H0rX5r49Nh9K052h2qX2Xbkuu4eoAAHANBFmgmuXkF2nDgVSt3Xdca/emasOBVCVn5JXaNzLQW62jAtQqKlBBPp56Zs7mGq4WAADXQZAFqpAxRvuP5ZwIrX99bDmcoaJT5rq6WaTGoX5qFRmg1lEBah0VqFZRAarr+/eDGXYlZ0pzavoMAABwHQRZ4CzkF9r0vwOp+mPvca3de1xr96UqJbPkaGtEgLc6xgSpY8NgXdAwSK0iA+Xj5e6EigEAOHcQZIEKKCyy6X8H07Ri11H9vvuo/thzXDkFRQ59PN0tahUVqE4Ng+3hNSrIx0kVAwBw7iLIAmewJyVLP29P1i/bk7Uy4Zgy8wod3q/r66V/xAarU0ywOjYMVpv6gfL2ZLQVAIDqRpAFyjBv42F9s/ag9h1zXE0g0MdTFzauq/jG9RQfF6KmYX5yc7M4qUoAAM5fBFngFG6WE6F0e1KmpBNTBTrH1NXFzULVo2mIWkUGEFwBAKgFCLLAKW7o1EAJKVmKC/XVxc1CdWHjevK11u5vlcS0XK3Ze1wZuQW6rmMDeXnw0D4AwLmvdv90BpygfXSQPr29q7PLKFORzWhrYrrW7D2uP/Yc15q9x3UwNcf+vq/VQwPaRzmxQgAAagZBFqjlbDajX3ck20Prun3HlZXvuFKCm0XydHdTXqFNqTkFTqoUAICaRZAFarmMvELdNn2VQ5uf1UMXNAxSp5hgdY6pqw4Ng/Twlxv0w5+JTqoSAICaR5AFaqnwAG/5e3soI7dQDYJ91DkmWJ1i66pTw2A1j/CXu5NvOEtMy9WGA6mKCvRR2waBTq0FAHB+IsgCtZSf1UO/PXaZcvKLFBbg7dRa0nIKtPFAmjYcSNX6/anasD9VRzJOPMHM29NNq5/oLX9vT6fWCAA4/xBkgVrM39uzxgNibkGRNh9O14b9qfrfgTRt2J+q3SlZJfq5u1lUZDPKLbApM6+QIAsAqHEEWeA8dzwrX3/sPa7Ve45p9Z5j+vNgmgqKTIl+MfXqqF2DILVvEKgO0UFqHRWodhN/LLUvAAA1gSALnEeMMTpwPOev0HoivO48klmiX4ifl9o3CFL76CC1axCo9g2CFOzr5YSKAQAoG0EWOIfZbEbbj2RoVcIxrUo4pj/2HFdiem6Jfk3C/PSP2Lr6R2yw/hFbVw2CfWSx8PQyAEDtRpAFzjGHU3P0+cp9+m1XilbsOqqjWfkO73u4WdS2QaD+EVtXnWOC1Tm2ruoy2goAcEEEWeAc89bSXQ6vfTzd1fmvkdZ/xNZVh+gg+Xi5O6k6AACqDkEWOEfE1POVJHm6W3RBw2B1i6unbnEh6hAdJC8Pt2o9tjHS7uRMrdl7XGv3HdfmQ+m6rmMDDesWW63HBQCc3wiywDlibJ9murp9lGJD6qiOV81+a/ed8osycgsd2jLyCgmyAIBqVb3DNABqjJeHm1pFBdRoiA34a+3YjNxCeXm4qXNMsPq1jTjxJqtyAQCqGSOyACrtnds6aePBNLWPDlLrqABZPdy1es8xzduY6OzSAADnAYIsgErrHFtXnWPrOrsMAMB5iiALwGky8wq1Zu9xFRTa1KtlGGvXAgAqhCALoMYczczT6j3HtSrhxONwNx1Kk+2vubRf3BWvLo0Y3QUAlB9BFkC1OZSac+KpYntOPFmstMfhWiwnlu9KycxzQoU4V2XkFmjv0WztO5atPUeztO9otvYezZaPl7veGHyBfK38+APOBXwnA6gWu1Oy1O35xSXam4WfeBxul0YnPu7773qt2nPMCRXClRljdDQrX3uPZmvv0awSofXUJ9qdbNWeY7q0eVgNVguguhBkAVSpED+r/e/ubha1jgpQl7+CK4/DRUUYY5SSma+ElCztTs5Uwkkjq3uPZikrv+i029fz9VLDenUUW89XDevW0VdrDuhgao6MYW044FxBkAVQpRqF+GrmnRcqv9CmjjHB8uNXuDiD7PzCv8Jq1t+hNSVLu1OySjxo42QWixQV6KOGdesoNqSOGtb1VUy9OoqpV0cN69aR/1/rHBdbuu2IDqbmVPfpAKhB/IQBUOUubFzP2SWglimyGR04nq3d9sCaaQ+uh9Nyy9zOYpEaBPuocYifGoWcHFR9FV3XR1YP9xo8CwC1DUEWAFBl8gqLlJCSpR1JmdpxJFM7j2RoR1Km9h7NVn6Rrczt6vp6qVGIrxqH+KpRqK8ah/ipceiJKQHenoRVAKUjyAIAKiy3oEi7k7O046+guuNIhnYcORFYi2ylz0G1eripUYjvicAa6qtGf4XVxiG+CqpTu+ZO22xGiem52pOSpT1HT9xEduLvWcopKNKUQReoU0yws8sEznsEWQBAmXLyi7Qr+URQ3Z6UqR1JJ0ZZ9x3LVhl5Vf7eHmoa5qemYf5qGu6nuDA/NQn1U/0gH7m51Z6HXthsRofTc7U3JUsJf618kJCSZV8FIa+w7BHkpduOEGSBWoAgCwCQzWZ0MDVHmw+na+vhDG1NTNfWxAztOZqlsm7yD/TxVLNwPzUJ81fTMD81Cz8RXMP8rbX6KW1TFu7Q5HlbtfdYtvJPE1Y93CyKrntiTm5sPV/F1qujpduTtXRbcg1WC+B0CLIAcJ7JzCvUtsR0bTmcoS2HTwTWbYkZyswrfYWAer5eahLmp6bhJ8Jqk79GW0P8vGp1YD1VHa8TP/L+dyDN3lYcVmPr1VFMPV/7DWWNQnxVP8hHHu5uDvvYczRbEkEWqC0IsgBwjrLZjPYey9bWw+nakpjx15/p2n+s9CWovNzd1DTcTy0iAtQy0l8tIgLUItLfYW1gV/ZE/5aa87/Digz0VmzIiRHW0sIqANdBkAWAc0BBkU07kjL156E0bTqYpj8PpWvL4XRll/HQgIgAb7WI9FfLyAC1iDjxZ6MQX3mew6GuTf1Atakf6OwyAFQhgiwAuJjcgiJtT8rQnwfT7cF1S2JGqfM9rR5uah7hrxYR/n+NtJ4IrsE8YQ3AOYAgCwC1WEGRTdsSM7ThQKr+tz9NGw+maXtShgpLWTLA3+qh1vUD1CYqUG0bBKp1VIBi6/nyq3MA5yyCLADUEsYY7T2arQ0HUrV+f6r+dyBNfx5MK3UZqKA6nmpbP1CtowLVpn6A2tYPVHRwnVq1vBUAVDenB9mpU6fqpZdeUmJiotq3b6833nhDXbp0KbP/lClT9Pbbb2vfvn0KCQnRDTfcoMmTJ8vb27sGqwaAs3c0M0/r9qVqw4FUbTiQpg37U5WWU1Cin7+3h9o3CFL76EC1/WueZ/0gH5daMeB8U2QzOpSao4SULDUJ81NUkI+zSwLOSU4NsrNmzdLYsWM1bdo0de3aVVOmTFHfvn21bds2hYWFlej/+eef67HHHtMHH3ygbt26afv27Ro+fLgsFoteffVVJ5wBgHNJbkFRtT0OtchmtD0pQ2v2Htfafce1du/xv5ZycuTl4abWUQH24Nq+QZBi6/ky0lpLpeUUaHdypnYnZ2l3yl9/Jp94wELxnOX6QT5a/thlTq4UODc5Nci++uqruuOOOzRixAhJ0rRp0zR37lx98MEHeuyxx0r0/+2339S9e3fdcsstkqTY2FgNHjxYK1eurNG6AZwbjmXl6/fdR/XbrhSt2HVUu5KzdNfFjTWuX8uz3ndaToHW7TuutftStXbvca3fn1rqOq1Nw/zUITpI7aKD1KFBkJpH+MvLgzmttd3M1fv131X7lJKZX2YfDzeLCm1Gh9JKX+4MwNlzWpDNz8/XmjVrNG7cOHubm5ubevfurRUrVpS6Tbdu3fTpp59q1apV6tKli3bv3q158+bptttuK/M4eXl5ysvLs79OT0+vupMA4FLScwu0avcx/bbrRHjdmphRos+avccrte+DqTlalXBUqxKO6Y89x7XjSGaJPr5e7rqgYbA6NgxSx5hgXRAdrMA6npU6HpwjwOfE9UrO+PvnSpi/VXGhfmoc6qvGf/0ZF+Inq6ebuj63yFmlAucFpwXZlJQUFRUVKTw83KE9PDxcW7duLXWbW265RSkpKbroootkjFFhYaHuvvtuPf7442UeZ/LkyZo4cWKV1g7ANeTkF2n1nhPBdcWuFG08mKZTb/ZvHu6v+Lh6slikD5fvKdd+jTFKSMnSqoRjWpVwTCsTjulgaslRt5h6ddSpYbA6xgSrY8NgNY/wlztTBFzaiG6xqufrpUAfTzUOPfEkMH/v0v8xcnLYBVA9nH6zV0UsXbpUzz33nN566y117dpVO3fu1H333adnn31WTz31VKnbjBs3TmPHjrW/Tk9PV3R0dE2VDKAGGWO0PSlTP28/ol+2p2jVnmMl1lZtHOKrC+PqqVtcPV3YuJ79qVXz/zxcZpC12Yy2JWU4BNeUTMeQ4u5mUZv6geoSG6zOsXXVKSb4nHkiFv4W7OulYd1inV0GgL84LciGhITI3d1dSUlJDu1JSUmKiIgodZunnnpKt912m26//XZJUtu2bZWVlaU777xTTzzxhNzcSs4rs1qtslr5YQKcq1Kz87VsZ4p+3pasX3ekKDE91+H9qEBvdWsSom5x9RQfV0+RgWe+e7w4EBfPnV2ZcKzEagJeHm7qEB2kro3qqkujuurYMFi+VpcaGwAAl+e0/+t6eXmpU6dOWrRokQYOHChJstlsWrRokcaMGVPqNtnZ2SXCqrv7iTuMjSm5ODiAc09hkU0bDqTpl+3J+nl7sv53INVhuoC3p5u6Nqqnns1CdXGzUMWF+lZomaqtiRnq/O+FOprleBNPHS93dYoJ/iu41lO7BoHVtsIBAKB8nDp8MHbsWA0bNkydO3dWly5dNGXKFGVlZdlXMRg6dKjq16+vyZMnS5IGDBigV199VRdccIF9asFTTz2lAQMG2AMtgHNPem6Bft6WrEVbkrRkW3KJ0dFm4X66uGmoejYP1T9i61YqYFr/2iYzr1CZeZKPp7s6xwarW1yI4uPqqU1UAE/IAoBaxqlBdtCgQUpOTtb48eOVmJioDh06aP78+fYbwPbt2+cwAvvkk0/KYrHoySef1MGDBxUaGqoBAwZo0qRJzjoFANVk/7FsLdySpEVbjuj33UcdHska6OOpi5qEqGezUPVoFlKu6QJnclGTEI2+NE5e7u7q1qSe2jcIYhksAKjlLOY8+518enq6AgMDlZaWpoCAAGeXA5z3bpq2Qqv2HNObt1yg+kE+9vB66tJYcaG+6t0qXL1bhuuC6CBGR1HrJWfk6R+TFspikRIm93d2OYDLqEhW484EALXC2C82OKww4O5mUeeYYPVpFa5eLcPVKMTXidUBAGojgiwAp/K1npibml9ok5/VQz2bh6pPy3Bd0jxUQXW8nFwdAKA2I8gCcKpHrmihDtHB6hgTpK6N6jEvFQBQbgRZAE7VMjJALSOZrw4AqDiGPgAAAOCSGJEFAKCGHM/K17akDB08nqMeTUMUFuDt7JIAl0aQBQCgGhkj3fr+Sm1LylByRp69/er2UfrP4AucWBng+giyAABUAy8PN1ksJ4Lssp0p9nZ/bw9l5Bbq2EmPQS4ssmnvsWxl5RWqTVSg3NzK/1hl4HxGkAUAoBoE+nhq8rVtteNIppqH+6tZhL+ahvlp4ZYk3TdzvRJSsvTArPXalpihncmZ9nWU/zP4Al3dPsrJ1QOugSALAEA1ublLwxJt7n+Nth5MzdHsdQdLvL//WHa11wWcKwiyAADUoIubhap/u0i5WSxqEeGvZuH+ah7ur/8s3qGv1hxwdnmASyHIAgBQgwK8PTX1lo4l2pkWC1Qc68gCAADAJRFkAQAA4JIIsgAAAHBJBFkAAAC4JG72AgDgPGaM0eG0XG1LytD2xAxtS8rQ7uQs9W8bqTsubuzs8oDTIsgCAHCeSMnMs4fV7UkZ2p6Uqe2JGcrIKyzR92BqDkEWtR5BFgCAc0x6boF2JGVoW2KmtidlaFviieB69KTH4p7Mw82ixqG+ahbur0AfT322cp+MMTVcNVBxBFkAAFxUkc0oISVLWxPTteVwurYcztDWw+k6lJZban+LRYqpW+fEQxiKH8YQ4a/Yer7y8jhx28zWxHR9tnJfTZ4GUGkEWQAAXEBadoG2JKZr61+BdUtiurYlZiiv0FZq/8hAb8fAGu6vJmF+8vFyr+HKgepDkAUAoBax2Yx2JWdq6+GMv0ZZ07U1MUMHU3NK7e/j6a7mEf5qGRmglpH+ahERoOYRJ6YIAOc6giwAALXIKwu265UF20t9r36Qjz2wnvgzQA3r1pE7z7fFeYogCwBALRAV5GP/u7enm5pHBKhlxN+BlVFWoCSCLAAAtcDdPePUtVE9hQVYFVvPl1FWoBwIsgAA1ALenu6Kj6vn7DIcnPywhG2JGUpKz9WQrjFqEubn7NIASQRZAABQimNZ+Wo/8Sel5zo+LCErr1Av3tD+rPZtjNGRjDz7+rbbEk+scXt/76Zq1yDorPaN8wtBFgAA2AX6eMpikWxGSs8tlLubRY1DfCVJO45kKreg9OW+ypKanf93YE3K0PbETG1LylBaTkGJvhGB3gRZVAhBFgAA2EUG+uiTkV2VnJmr5uEBigvzldXDXR8sS9AzczaXuV1WXqF2HMl0eATutsQMHcnIK7W/m0VqFHLiaWIpmXlavee4bDaeJoaKIcgCAAAHFzUNKfO9giKbthxOd3j07bakDO0/Vvo6t9KJZcOKH8zQ4q8/G4f6ytvzxMMZpi7ZqdV7jlf5eeDcR5AFAADl9sOfifrhz8RS3wvxs6p5hJ/9SWLNIvzVNMxP/t4sG4bqQZAFAABnFBtSx/53f28Pe1BtHn5ihLVZuJ/q+VmdWCHORwRZAABwRpc2D9PiB3vKx8tdEQHeslhY5xbOR5AFAABnZLFY1DiU9WNRu7g5uwAAAACgMgiyAAAAcElMLQAAALVGckaefWmvbYkZMjKaMKC1fK1EFpTEVwUAAKgVvvhjv2au3l+i/ZLmYerXNtIJFaG2Y2oBAABwqogAb0knHotr+euJX31bh9vbC4oq9lhcnD8YkQUAAE51TYcoRQZ5y9/qqSZhfvLxOvHEr1ve+12J6blOrg61GUEWAAA4lYe7m7rFlf1YXKAsTC0AAACASyLIAgAAwCURZAEAAOCSCLIAAABwSQRZAAAAuCSCLAAAAFwSQRYAAAAuiSALAAAAl0SQBQAAgEsiyAIAAMAlEWQBAADgkgiyAAAAcEkEWQAAALgkgiwAAABcEkEWAAAALokgCwAAAJdEkAUAAIBLIsgCAADAJRFkAQAA4JIIsgAAAHBJBFkAAAC4JIIsAAAAXJLTg+zUqVMVGxsrb29vde3aVatWrTpt/9TUVI0ePVqRkZGyWq1q1qyZ5s2bV0PVAgAAoLbwcObBZ82apbFjx2ratGnq2rWrpkyZor59+2rbtm0KCwsr0T8/P199+vRRWFiYvvrqK9WvX1979+5VUFBQzRcPAAAAp3JqkH311Vd1xx13aMSIEZKkadOmae7cufrggw/02GOPlej/wQcf6NixY/rtt9/k6ekpSYqNja3JkgEAQC1isxntOZqlzYfTtTs5S5e1CFOb+oEOfYwxslgsTqoQ1clpQTY/P19r1qzRuHHj7G1ubm7q3bu3VqxYUeo233//veLj4zV69Gh99913Cg0N1S233KJHH31U7u7upW6Tl5envLw8++v09PSqPREAAFAjcguKtC0xQ5sPp2vToTRtPpSurYkZys4vsvf576p9evaaNtpyOF1bEtO1+VC6jmbla8qgDurVMly5BUXanpShLYfT5e7mpus71ifkujCnBdmUlBQVFRUpPDzcoT08PFxbt24tdZvdu3dr8eLFGjJkiObNm6edO3fqn//8pwoKCjRhwoRSt5k8ebImTpxY5fUDAICa8cGyBL25eKd2JWfKZkq+b/VwU16hTZJ0OC1Xt3/8R4k+o2b8oSZhftp9yj4a1q2jLo3qVlfpqGZOnVpQUTabTWFhYXr33Xfl7u6uTp066eDBg3rppZfKDLLjxo3T2LFj7a/T09MVHR1dUyUDAIBK8vI4cU/6hgNp9rZ6vl5qFRVw4iMyQK2jAhRbz1fHsvN12cs/K6egSE3D/NQqMkAtIwO0aGuSft99TJK080imJKmur5ey8wuVW2BTWk5BzZ8YqozTgmxISIjc3d2VlJTk0J6UlKSIiIhSt4mMjJSnp6fDNIKWLVsqMTFR+fn58vLyKrGN1WqV1Wqt2uIBAEC1u/eyJgrztyqmnq9aRZ4Ir2H+1lKnAoT5e2vtU31kZGT1+DsnXNMhStOXJyjIx0stI/3VKjJAof5WXfvWb1q/P7UGzwbVwWlB1svLS506ddKiRYs0cOBASSdGXBctWqQxY8aUuk337t31+eefy2azyc3txL/Stm/frsjIyFJDLAAAcF2dYuqqU0z5f+1fPIJ7srAAb427smVVloVaxKnryI4dO1bvvfeeZsyYoS1btuiee+5RVlaWfRWDoUOHOtwMds899+jYsWO67777tH37ds2dO1fPPfecRo8e7axTAAAAgJM4dY7soEGDlJycrPHjxysxMVEdOnTQ/Pnz7TeA7du3zz7yKknR0dH68ccf9cADD6hdu3aqX7++7rvvPj366KPOOgUAAAA4icUYU8r9f+eu9PR0BQYGKi0tTQEBAc4uBwAAOMHAqcu1fn+q3hvaWX1ahZ95A9SYimQ1pz+iFgAAAKgMgiwAAABcUqXmyBYVFemjjz7SokWLdOTIEdlsNof3Fy9eXCXFAQAAAGWpVJC977779NFHH6l///5q06YNj3YDAABAjatUkJ05c6a++OIL9evXr6rrAQAAAMqlUnNkvby81KRJk6quBQAAwKmKbOfVYk4ur1Ijsg8++KBef/11vfnmm0wrAAAALuvPg2nadyxbWw6na8vhdO1IylS7BoH68u54Mo4LqFSQXbZsmZYsWaIffvhBrVu3lqenp8P733zzTZUUBwAAUJ1eX7SjRNsfe48rp6BIdbyc+twolEOlrlBQUJCuvfbaqq4FAACgRsTH1dOGA6lqEOyjlhEBahkZoMahvrpv5npnl4YKqFSQ/fDDD6u6DgAAgBrz6BUtNLZPM3m6/327UE5+kRMrQmWc1Zh5cnKytm3bJklq3ry5QkNDq6QoAACA6nZyiIVrqtQVzMrK0siRIxUZGamLL75YF198saKiojRq1ChlZ2dXdY0AAABACZUKsmPHjtXPP/+s//u//1NqaqpSU1P13Xff6eeff9aDDz5Y1TUCAAAAJVRqasHXX3+tr776Spdccom9rV+/fvLx8dFNN92kt99+u6rqAwAAAEpVqRHZ7OxshYeHl2gPCwtjagEAAABqRKWCbHx8vCZMmKDc3Fx7W05OjiZOnKj4+PgqKw4AAAAoS6WmFrz++uvq27evGjRooPbt20uSNmzYIG9vb/34449VWiAAAABQmkoF2TZt2mjHjh367LPPtHXrVknS4MGDNWTIEPn4+FRpgQAAAEBpKr2ObJ06dXTHHXdUZS0AAABAuZU7yH7//fe68sor5enpqe+///60fa+++uqzLgwAAAA4nXIH2YEDByoxMVFhYWEaOHBgmf0sFouKinjEGwAAAKpXuYOszWYr9e8AAACAM1TZQ4ZTU1OralcAAADAGVUqyL7wwguaNWuW/fWNN96ounXrqn79+tqwYUOVFQcAAACUpVJBdtq0aYqOjpYkLViwQAsXLtT8+fN15ZVX6uGHH67SAgEAAIDSVGr5rcTERHuQnTNnjm666SZdfvnlio2NVdeuXau0QAAAAKA0lRqRDQ4O1v79+yVJ8+fPV+/evSVJxhhWLAAAAOcMY4z2H8vWrzuSlZZd4OxycIpKjched911uuWWW9S0aVMdPXpUV155pSRp3bp1atKkSZUWCAAAUNP+PXeLdiZlasvhdGXkFUqS+rWN0FtDOjm5MpysUkH2tddeU2xsrPbv368XX3xRfn5+kqTDhw/rn//8Z5UWCAAAUBMslr///vnKfSXeP5SaW4PVoDwsxhjj7CJqUnp6ugIDA5WWlqaAgABnlwMAAGqRl3/cpg0HUtU83F+togLUMjJAe1KydM9na9UhOkjfju7u7BLPeRXJajyiFgAA4C8P9W1eou3g8RwnVILy4BG1AAAAcEk8ohYAAAAuqcoeUQsAAADUpEoF2X/961/6z3/+U6L9zTff1P3333+2NQEAAABnVKkg+/XXX6t795J37XXr1k1fffXVWRcFAAAAnEmlguzRo0cVGBhYoj0gIEApKSlnXRQAAABwJpUKsk2aNNH8+fNLtP/www9q3LjxWRcFAAAAnEmlnuw1duxYjRkzRsnJybrsssskSYsWLdIrr7yiKVOmVGV9AAAAQKkqFWRHjhypvLw8TZo0Sc8++6wkKTY2Vm+//baGDh1apQUCAAAApalUkJWke+65R/fcc4+Sk5Pl4+MjPz+/qqwLAAAAOK1KryNbWFiohQsX6ptvvpExRpJ06NAhZWZmVllxAAAAQFkqNSK7d+9eXXHFFdq3b5/y8vLUp08f+fv764UXXlBeXp6mTZtW1XUCAAAADio1Invfffepc+fOOn78uHx8fOzt1157rRYtWlRlxQEAAABlqdSI7K+//qrffvtNXl5eDu2xsbE6ePBglRQGAAAAnE6lRmRtNpuKiopKtB84cED+/v5nXRQAAABwJpUKspdffrnDerEWi0WZmZmaMGGC+vXrV1W1AQAAAGWq1NSCl19+WVdccYVatWql3Nxc3XLLLdqxY4dCQkL03//+t6prBAAAAEqoVJCNjo7Whg0bNGvWLG3YsEGZmZkaNWqUhgwZ4nDzFwAAAFBdKhxkCwoK1KJFC82ZM0dDhgzRkCFDqqMuAAAA4LQqPEfW09NTubm51VELAAAAUG6Vutlr9OjReuGFF1RYWFjV9QAAAADlUqk5sqtXr9aiRYv0008/qW3btvL19XV4/5tvvqmS4gAAAICyVCrIBgUF6frrr6/qWgAAAIByq1CQtdlseumll7R9+3bl5+frsssu09NPP81KBQAAAKhxFZojO2nSJD3++OPy8/NT/fr19Z///EejR4+urtoAAACAMlUoyH788cd666239OOPP+rbb7/V//3f/+mzzz6TzWarrvoAAACAUlUoyO7bt8/hEbS9e/eWxWLRoUOHqrwwAAAA4HQqFGQLCwvl7e3t0Obp6amCgoIqLQoAAAA4kwrd7GWM0fDhw2W1Wu1tubm5uvvuux2W4GL5LQAAAFS3CgXZYcOGlWi79dZbq6wYAAAAoLwqFGQ//PDD6qoDAAAAqJBKPaK2qk2dOlWxsbHy9vZW165dtWrVqnJtN3PmTFksFg0cOLB6CwQAAECt4/QgO2vWLI0dO1YTJkzQ2rVr1b59e/Xt21dHjhw57XZ79uzRQw89pB49etRQpQAAAKhNnB5kX331Vd1xxx0aMWKEWrVqpWnTpqlOnTr64IMPytymqKhIQ4YM0cSJE9W4ceMarBYAAAC1hVODbH5+vtasWaPevXvb29zc3NS7d2+tWLGizO2eeeYZhYWFadSoUTVRJgAAAGqhCt3sVdVSUlJUVFSk8PBwh/bw8HBt3bq11G2WLVum6dOna/369eU6Rl5envLy8uyv09PTK10vAAAAag+nTy2oiIyMDN1222167733FBISUq5tJk+erMDAQPtHdHR0NVcJAACAmuDUEdmQkBC5u7srKSnJoT0pKUkREREl+u/atUt79uzRgAED7G02m02S5OHhoW3btikuLs5hm3Hjxmns2LH21+np6YRZAACAc4BTg6yXl5c6deqkRYsW2ZfQstlsWrRokcaMGVOif4sWLbRx40aHtieffFIZGRl6/fXXSw2oVqvV4UlkAAAAODc4NchK0tixYzVs2DB17txZXbp00ZQpU5SVlaURI0ZIkoYOHar69etr8uTJ8vb2Vps2bRy2DwoKkqQS7QAAADi3OT3IDho0SMnJyRo/frwSExPVoUMHzZ8/334D2L59++Tm5lJTeQEAAFADLMYY4+wialJ6eroCAwOVlpamgIAAZ5cDAABquYWbk3T7x3+oQ3SQvh3d3dnlnPMqktUY6gQAAIBLIsgCAADAJRFkAQAA4JIIsgAAAHBJBFkAAAC4JIIsAAAAXBJBFgAAAC6JIAsAAACXRJAFAACASyLIAgAAwCURZAEAAOCSCLIAAABwSQRZAAAAuCSCLAAAAFwSQRYAAAAuiSALAAAAl0SQBQAAgEsiyAIAAMAlEWQBAADgkgiyAAAAcEkEWQAAALgkgiwAAABcEkEWAAAALokgCwAAAJdEkAUAAIBLIsgCAADAJRFkAQAA4JIIsgAAAHBJBFkAAAC4JIIsAAAAXBJBFgAAAC6JIAsAAACXRJAFAACASyLIAgAAwCURZAEAAOCSCLIAAABwSQRZAAAAuCSCLAAAAFwSQRYAAAAuiSALAAAAl0SQBQAAgEsiyAIAAMAlEWQBAADgkgiyAAAAcEkEWQAAALgkgiwAAABcEkEWAAAALokgCwAAAJdEkAUAAIBLIsgCAADAJRFkAQAA4JIIsgAAAHBJBFkAAAC4JIIsAAAAXBJBFgAAAC6JIAsAAACXRJAFAACASyLIAgAAwCURZAEAAOCSCLIAAABwSQRZAAAAuCSCLAAAAFwSQRYAAAAuqVYE2alTpyo2Nlbe3t7q2rWrVq1aVWbf9957Tz169FBwcLCCg4PVu3fv0/YHAADAucnpQXbWrFkaO3asJkyYoLVr16p9+/bq27evjhw5Umr/pUuXavDgwVqyZIlWrFih6OhoXX755Tp48GANVw4AAABncnqQffXVV3XHHXdoxIgRatWqlaZNm6Y6derogw8+KLX/Z599pn/+85/q0KGDWrRooffff182m02LFi2q4coBAADgTE4Nsvn5+VqzZo169+5tb3Nzc1Pv3r21YsWKcu0jOztbBQUFqlu3bqnv5+XlKT093eEDAAAArs+pQTYlJUVFRUUKDw93aA8PD1diYmK59vHoo48qKirKIQyfbPLkyQoMDLR/REdHn3XdAAAAcD6nTy04G88//7xmzpyp2bNny9vbu9Q+48aNU1pamv1j//79NVwlAAAAqoOHMw8eEhIid3d3JSUlObQnJSUpIiLitNu+/PLLev7557Vw4UK1a9euzH5Wq1VWq7VK6gUAAEDt4dQRWS8vL3Xq1MnhRq3iG7fi4+PL3O7FF1/Us88+q/nz56tz5841USoAAABqGaeOyErS2LFjNWzYMHXu3FldunTRlClTlJWVpREjRkiShg4dqvr162vy5MmSpBdeeEHjx4/X559/rtjYWPtcWj8/P/n5+TntPAAAAFCznB5kBw0apOTkZI0fP16JiYnq0KGD5s+fb78BbN++fXJz+3vg+O2331Z+fr5uuOEGh/1MmDBBTz/9dE2WDgAAACdyepCVpDFjxmjMmDGlvrd06VKH13v27Kn+ggAAAFDrufSqBQAAADh/EWQBAADgkgiyAAAAcEkEWQAAALgkgiwAAABcEkEWAAAALokgCwAAAJdEkAUAAIBLIsgCAADAJRFkAQAA4JIIsgAAAHBJBFkAAAC4JIIsAAAAXBJBFgAAAC6JIAsAAACXRJAFAACASyLIAgAAwCURZAEAAOCSCLIAAABwSQRZAAAAuCSCLAAAAFwSQRYAAAAuiSALAAAAl0SQBQAAgEsiyAIAAMAlEWQBAADgkgiyAAAAcEkEWQAAALgkgiwAAABcEkEWAAAALokgCwAAAJdEkAUAAIBLIsgCAADAJRFkAQAA4JIIsgAAAHBJBFkAAAC4JIIsAAAAXBJBFgAAAC6JIAsAAACXRJAFAACASyLIAgAAwCURZAEAAOCSCLIAAABwSQRZAACASrDZjAqLbM4u47zm4ewCAAAAXMH6/anq/vxi5RQUKSe/SDkFRfL2dNO0WzvpkuZhzi7vvMSILAAAwGnUD/ax//1gao6OZeUrp6BIkpRbYNOqhGPOKu28x4gsAADAabSMDNCCBy5WSma+fLzcVcfLXT6e7pq6ZKdmrt7v7PLOawRZAACAM2ga7q+m4Y5tPl7uzikGdkwtAAAAgEsiyAIAAMAlEWQBAADgkgiyAAAAcEkEWQAAALgkgiwAAABcEkEWAAAALokgCwAAAJfEAxEAAADOwr5j2dqVnKkim1FhkVGhzabwAG+FB3g7u7RzHkEWAADgLMz532HN+d9hhzZ3N4uWPnSJouvWcVJV5wemFgAAAFTCJc3DFFzHU3W83OXv7aG6vl4K9bfKw82iIpvRvmPZzi7xnMeILAAAQCX0bBaqdeMvL9F+xZRftDUxwwkVnX8YkQUAAIBLIsgCAADAJdWKIDt16lTFxsbK29tbXbt21apVq07b/8svv1SLFi3k7e2ttm3bat68eTVUKQAAQPlM/L9Nevr7TRr/3Z966ts/9cTsjZr/5+Ezb4hyc/oc2VmzZmns2LGaNm2aunbtqilTpqhv377atm2bwsLCSvT/7bffNHjwYE2ePFlXXXWVPv/8cw0cOFBr165VmzZtnHAGAAAAf/O1nohX25MytT0p0+G9z1bu01tDOsoYycjIGKmgyKaoIB/5WT0c2gN8PNUoxNcZp+AyLMYY48wCunbtqn/84x968803JUk2m03R0dG699579dhjj5XoP2jQIGVlZWnOnDn2tgsvvFAdOnTQtGnTzni89PR0BQYGKi0tTQEBAVV3IgAAAJI2H0rX3I2HJEkWWeRmkdJzC/XRb3sqtb+LmoTYw60kHU7L1a0XxsjD7cS+ZTnxp0UWWSxy+Huhzahh3Try+ytcF4c+Xy931Q/2se+zuN3H013ubpZK1VlVKpLVnDoim5+frzVr1mjcuHH2Njc3N/Xu3VsrVqwodZsVK1Zo7NixDm19+/bVt99+W52lAgAAlEurqAC1iioZwHy83PXHnmOyyKK//lNKZp52JWcpPMBqD58WSYfScu3bLduZUmJfz87ZXG31t6kfoDqeHjL6e6xz4AX1NaRrTLUds7KcGmRTUlJUVFSk8PBwh/bw8HBt3bq11G0SExNL7Z+YmFhq/7y8POXl5dlfp6enn2XVAAAAFffoFS3K3Tcnv0hLtx1RbmGRPeBK0q87UpSVVyg3i8U+Smsz5q8pCTrxpzkRQQ8ez9G2pAzVD/Jx2PfB1JzTHvvPgyWz0p6j2QRZZ5g8ebImTpzo7DIAAADKzcfLXVe2jSzRfk2H+lWy/7zCItlsJ/5eHJJTMvP0vwNpOnliQXpugdbsPa7uTUKq5LhVzalBNiQkRO7u7kpKSnJoT0pKUkRERKnbREREVKj/uHHjHKYipKenKzo6+iwrBwAAcF1WD/cSbQ2C66hBcMlH6g76R8OaKKlSnLr8lpeXlzp16qRFixbZ22w2mxYtWqT4+PhSt4mPj3foL0kLFiwos7/ValVAQIDDBwAAAFyf06cWjB07VsOGDVPnzp3VpUsXTZkyRVlZWRoxYoQkaejQoapfv74mT54sSbrvvvvUs2dPvfLKK+rfv79mzpypP/74Q++++64zTwMAAAA1zOlBdtCgQUpOTtb48eOVmJioDh06aP78+fYbuvbt2yc3t78Hjrt166bPP/9cTz75pB5//HE1bdpU3377LWvIAgAAnGecvo5sTWMdWQAAgNqrIlmtVjyiFgAAAKgogiwAAABcEkEWAAAALokgCwAAAJdEkAUAAIBLIsgCAADAJRFkAQAA4JIIsgAAAHBJBFkAAAC4JIIsAAAAXBJBFgAAAC7Jw9kF1DRjjKQTz/EFAABA7VKc0Yoz2+mcd0E2IyNDkhQdHe3kSgAAAFCWjIwMBQYGnraPxZQn7p5DbDabDh06JH9/f1kslmo/Xnp6uqKjo7V//34FBARU+/FQ9biGro3r5/q4hq6N6+f6avoaGmOUkZGhqKgoubmdfhbseTci6+bmpgYNGtT4cQMCAvgGdnFcQ9fG9XN9XEPXxvVzfTV5Dc80EluMm70AAADgkgiyAAAAcEkE2WpmtVo1YcIEWa1WZ5eCSuIaujaun+vjGro2rp/rq83X8Ly72QsAAADnBkZkAQAA4JIIsgAAAHBJBFkAAAC4JIJsFZg6dapiY2Pl7e2trl27atWqVaft/+WXX6pFixby9vZW27ZtNW/evBqqFGWpyDV877331KNHDwUHBys4OFi9e/c+4zVH9aro92CxmTNnymKxaODAgdVbIM6ootcwNTVVo0ePVmRkpKxWq5o1a8b/S52ootdvypQpat68uXx8fBQdHa0HHnhAubm5NVQtTvbLL79owIABioqKksVi0bfffnvGbZYuXaqOHTvKarWqSZMm+uijj6q9zjIZnJWZM2caLy8v88EHH5hNmzaZO+64wwQFBZmkpKRS+y9fvty4u7ubF1980WzevNk8+eSTxtPT02zcuLGGK0exil7DW265xUydOtWsW7fObNmyxQwfPtwEBgaaAwcO1HDlMKbi169YQkKCqV+/vunRo4e55ppraqZYlKqi1zAvL8907tzZ9OvXzyxbtswkJCSYpUuXmvXr19dw5TCm4tfvs88+M1ar1Xz22WcmISHB/PjjjyYyMtI88MADNVw5jDFm3rx55oknnjDffPONkWRmz5592v67d+82derUMWPHjjWbN282b7zxhnF3dzfz58+vmYJPQZA9S126dDGjR4+2vy4qKjJRUVFm8uTJpfa/6aabTP/+/R3aunbtau66665qrRNlq+g1PFVhYaHx9/c3M2bMqK4ScRqVuX6FhYWmW7du5v333zfDhg0jyDpZRa/h22+/bRo3bmzy8/NrqkScRkWv3+jRo81ll13m0DZ27FjTvXv3aq0TZ1aeIPvII4+Y1q1bO7QNGjTI9O3btxorKxtTC85Cfn6+1qxZo969e9vb3Nzc1Lt3b61YsaLUbVasWOHQX5L69u1bZn9Ur8pcw1NlZ2eroKBAdevWra4yUYbKXr9nnnlGYWFhGjVqVE2UidOozDX8/vvvFR8fr9GjRys8PFxt2rTRc889p6KiopoqG3+pzPXr1q2b1qxZY59+sHv3bs2bN0/9+vWrkZpxdmpbjvFwylHPESkpKSoqKlJ4eLhDe3h4uLZu3VrqNomJiaX2T0xMrLY6UbbKXMNTPfroo4qKiirxjY3qV5nrt2zZMk2fPl3r16+vgQpxJpW5hrt379bixYs1ZMgQzZs3Tzt37tQ///lPFRQUaMKECTVRNv5Smet3yy23KCUlRRdddJGMMSosLNTdd9+txx9/vCZKxlkqK8ekp6crJydHPj4+NVoPI7LAWXj++ec1c+ZMzZ49W97e3s4uB2eQkZGh2267Te+9955CQkKcXQ4qyWazKSwsTO+++646deqkQYMG6YknntC0adOcXRrKYenSpXruuef01ltvae3atfrmm280d+5cPfvss84uDS6IEdmzEBISInd3dyUlJTm0JyUlKSIiotRtIiIiKtQf1asy17DYyy+/rOeff14LFy5Uu3btqrNMlKGi12/Xrl3as2ePBgwYYG+z2WySJA8PD23btk1xcXHVWzQcVOZ7MDIyUp6ennJ3d7e3tWzZUomJicrPz5eXl1e11oy/Veb6PfXUU7rtttt0++23S5Latm2rrKws3XnnnXriiSfk5sYYW21WVo4JCAio8dFYiRHZs+Ll5aVOnTpp0aJF9jabzaZFixYpPj6+1G3i4+Md+kvSggULyuyP6lWZayhJL774op599lnNnz9fnTt3rolSUYqKXr8WLVpo48aNWr9+vf3j6quv1qWXXqr169crOjq6JsuHKvc92L17d+3cudP+jxBJ2r59uyIjIwmxNawy1y87O7tEWC3+R4kxpvqKRZWodTnGKbeYnUNmzpxprFar+eijj8zmzZvNnXfeaYKCgkxiYqIxxpjbbrvNPPbYY/b+y5cvNx4eHubll182W7ZsMRMmTGD5LSer6DV8/vnnjZeXl/nqq6/M4cOH7R8ZGRnOOoXzWkWv36lYtcD5KnoN9+3bZ/z9/c2YMWPMtm3bzJw5c0xYWJj597//7axTOK9V9PpNmDDB+Pv7m//+979m9+7d5qeffjJxcXHmpptuctYpnNcyMjLMunXrzLp164wk8+qrr5p169aZvXv3GmOMeeyxx8xtt91m71+8/NbDDz9stmzZYqZOncryW67ujTfeMA0bNjReXl6mS5cu5vfff7e/17NnTzNs2DCH/l988YVp1qyZ8fLyMq1btzZz586t4Ypxqopcw5iYGCOpxMeECRNqvnAYYyr+PXgygmztUNFr+Ntvv5muXbsaq9VqGjdubCZNmmQKCwtruGoUq8j1KygoME8//bSJi4sz3t7eJjo62vzzn/80x48fr/nCYZYsWVLqz7TiazZs2DDTs2fPEtt06NDBeHl5mcaNG5sPP/ywxusuZjGGcXwAAAC4HubIAgAAwCURZAEAAOCSCLIAAABwSQRZAAAAuCSCLAAAAFwSQRYAAAAuiSALAAAAl0SQBQAAgEsiyALAecpisejbb7+VJO3Zs0cWi0Xr1693ak0AUBEEWQBwguHDh8tischiscjT01ONGjXSI488otzcXGeXBgAuw8PZBQDA+eqKK67Qhx9+qIKCAq1Zs0bDhg2TxWLRCy+84OzSAMAlMCILAE5itVoVERGh6OhoDRw4UL1799aCBQskSTabTZMnT1ajRo3k4+Oj9u3b66uvvnLYftOmTbrqqqsUEBAgf39/9ejRQ7t27ZIkrV69Wn369FFISIgCAwPVs2dPrV27tsbPEQCqE0EWAGqBP//8U7/99pu8vLwkSZMnT9bHH3+sadOmadOmTXrggQd066236ueff5YkHTx4UBdffLGsVqsWL16sNWvWaOTIkSosLJQkZWRkaNiwYVq2bJl+//13NW3aVP369VNGRobTzhEAqhpTCwDASebMmSM/Pz8VFhYqLy9Pbm5uevPNN5WXl6fnnntOCxcuVHx8vCSpcePGWrZsmd555x317NlTU6dOVWBgoGbOnClPT09JUrNmzez7vuyyyxyO9e677yooKEg///yzrrrqqpo7SQCoRgRZAHCSSy+9VG+//baysrL02muvycPDQ9dff702bdqk7Oxs9enTx6F/fn6+LrjgAknS+vXr1aNHD3uIPVVSUpKefPJJLV26VEeOHFFRUZGys7O1b9++aj8vAKgpBFkAcBJfX181adJEkvTBBx+offv2mj59utq0aSNJmjt3rurXr++wjdVqlST5+Picdt/Dhg3T0aNH9frrrysmJkZWq1Xx8fHKz8+vhjMBAOcgyAJALeDm5qbHH39cY8eO1fbt22W1WrVv3z717Nmz1P7t2rXTjBkzVFBQUOqo7PLly/XWW2+pX79+kqT9+/crJSWlWs8BAGoaN3sBQC1x4403yt3dXe+8844eeughPfDAA5oxY4Z27dqltWvX6o033tCMGTMkSWPGjFF6erpuvvlm/fHHH9qxY4c++eQTbdu2TZLUtGlTffLJJ9qyZYtWrlypIUOGnHEUFwBcDSOyAFBLeHh4aMyYMXrxxReVkJCg0NBQTZ48Wbt371ZQUJA6duyoxx9/XJJUr149LV68WA8//LB69uwpd3d3dejQQd27d5ckTZ8+XXfeeac6duyo6OhoPffcc3rooYeceXoAUOUsxhjj7CIAAACAimJqAQAAAFwSQRYAAAAuiSALAAAAl0SQBQAAgEsiyAIAAMAlEWQBAADgkgiyAAAAcEkEWQAAALgkgiwAAABcEkEWAAAALokgCwAAAJdEkAUAAIBL+n+GvcxXQA1QPQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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Tdcc4Ly8v3njjDXr37k2zZs3o1q0bZ86cYerUqZQqVYrBgwff8jWS06FDB+rWrcvzzz/PoUOHqFixIsuWLePixYtA+n2C0KZNG+bNm0dgYCCVK1cmPDyc7777joIFC6bL64sIWn5LREwp3dnrww8/NGrXrm34+fkZefPmNapVq2YMGzbMOHXqlGEYhrFjxw6jW7duRokSJQwfHx8jKCjIaNOmjbFt27ZEr7Nlyxajdu3ahre39y2X4krpzl7XNW/e3AgICDAuXbqUqH/JkiXG/fffb+TPn9/w8fExypUrZzz//PPGuXPnUjzW+vXrjfbt2xtBQUFGrly5jMKFCxtt27Y1li5dmuI+/5aQkGB89NFHRpMmTYzAwEDDy8vLKFmypNG7d+8kS3OtXbvWqFq1quHt7W1UqFDB+Oyzz1Jc3qlfv34pHtPhcBghISEGYLz66qvJbhMXF2e88cYbRpUqVQwfHx8jf/78Ru3atY1x48YZkZGRzu1cXX4LSPbxxBNPGIaR/J29rjt8+LDh6elp9OrV65bH+rdFixYZNWvWNHx8fIwCBQoYPXr0MP7+++9E29zsuMktfXbu3Dmje/fuRt68eY3AwEDjscceMzZv3mwAxsKFC53buXJ+SpYsmei9/fPPP0bv3r2NQoUKGXny5DHCwsKMAwcOJNlOy2+JpJ3NMP7zuYeIiEgOtGTJEjp27MimTZto1KiR1eWISCooyIqISI5z9erVRCtD2O12WrRowbZt24iIiHB5qTARsYbmyIqISKa7ePFiklvt/punp2eK6+Cmh+eee46rV6/SoEEDYmNj+frrr9myZQsTJkxQiBVxIxqRFRGRTNe8eXN++OGHFJ8vWbIkx44dy7DjL1iwgEmTJnHo0CGuXbtGuXLleOaZZ+jfv3+GHVNE0p+CrIiIZLrt27cnugvWf/n5+WmeqojckoKsiIiIiLgl3RBBRERERNxSjrvYy+FwcOrUKfLmzZtui16LiIiISPowDIPLly9TrFgxPDxuPuaa44LsqVOnCAkJsboMEREREbmJv/76izvuuOOm2+S4IJs3b17A/OYEBARYXI2IiIiI/FtUVBQhISHOzHYzOS7IXp9OEBAQoCArIiIikkWlZgqoLvYSEREREbekICsiIiIibklBVkRERETcUo6bI5tadrud+Ph4q8sQuW1eXl54enpaXYaIiEi6U5D9D8MwiIiI4NKlS1aXIpJu8uXLR5EiRbR2soiIZCsKsv9xPcQGBQXh7++vX/zi1gzDICYmhrNnzwJQtGhRiysSERFJPwqy/2K3250htmDBglaXI5Iu/Pz8ADh79ixBQUGaZiAiItmGLvb6l+tzYv39/S2uRCR9Xf87rXnfIiKSnSjIJkPTCSS70d9pERHJjhRkRURERMQtKciKiIiIiFuyNMj++OOPtG3blmLFimGz2ViyZMkt99m4cSO1atXCx8eHcuXKMXfu3Ayv0x089thj2Gw2bDYbXl5elC5dmmHDhnHt2rUk265YsYJmzZqRN29e/P39ufvuu1P8Pn711Vc0b96cwMBA8uTJw1133cX48eO5ePHiLWv6/PPP8fT0pF+/fkmemzt3Lvny5Ut2v+T+LtxOHWl18eJFevToQUBAAPny5eOJJ57gypUrN93n8OHDdOzYkcKFCxMQEEDnzp05c+ZMom1KlSrlPFfXH6+//rrz+bFjxyZ53mazkTt3buc2c+fOTfK8r69v+n4DREREsjhLg2x0dDTVq1dnxowZqdr+6NGjtG7dmnvuuYddu3YxaNAgnnzySdasWZPBlbqHli1bcvr0aY4cOcI777zDBx98wJgxYxJtM23aNNq3b0+jRo345Zdf+O233+jatStPP/00Q4cOTbTtSy+9RJcuXbj77rv59ttv2bt3L5MmTWL37t3MmzfvlvV8/PHHDBs2jM8//zzZQJ1at1tHWvXo0YPff/+ddevWsWLFCn788Uf69u2b4vbR0dG0aNECm83G999/z+bNm4mLi6Nt27Y4HI5E244fP57Tp087H88995zzuaFDhyZ67vTp01SuXJmHH3440WsEBAQk2ub48ePp+w0QERHJ6owsAjC++eabm24zbNgwo0qVKon6unTpYoSFhaX6OJGRkQZgREZGJnnu6tWrxr59+4yrV6+m+vWyil69ehnt27dP1Pfggw8aNWvWdLZPnDhheHl5GUOGDEmy/7vvvmsAxs8//2wYhmH88ssvBmBMmTIl2eP9888/N63nyJEjhp+fn3Hp0iWjXr16xvz58xM9P2fOHCMwMDDZff/9d+F260irffv2GYDx66+/Ovu+/fZbw2azGSdPnkx2nzVr1hgeHh6J/m5dunTJsNlsxrp165x9JUuWNN55551U17Jr1y4DMH788Udn382+f8lx57/bIiKSs9wsq/2XW82RDQ8PJzQ0NFFfWFgY4eHhGXZMwzCIiUuw5GEYRprr3rt3L1u2bMHb29vZ9+WXXxIfH59k5BXgqaeeIk+ePHz++ecAzJ8/nzx58vDss88m+/opTQu4bs6cObRu3ZrAwEAeeeQRPv744zS9j9upo0qVKuTJkyfFxwMPPJDivuHh4eTLl486deo4+0JDQ/Hw8OCXX35Jdp/Y2FhsNhs+Pj7OPl9fXzw8PNi0aVOibV9//XUKFixIzZo1eeutt0hISEixlo8++ojy5cvTpEmTRP1XrlyhZMmShISE0L59e37//fcUX0NERKxhZY7ISrkko7jVDREiIiIIDg5O1BccHExUVBRXr151Lvz+b7GxscTGxjrbUVFRLh3zarydyqOtmbqwb3wY/t6pP0UrVqwgT548JCQkEBsbi4eHB9OnT3c+/8cffxAYGJjs3Z28vb0pU6YMf/zxBwB//vknZcqUwcvLy+W6HQ4Hc+fOZdq0aQB07dqV559/nqNHj1K6dGmXXut26li1atVN101N7u/LdREREQQFBSXqy5UrFwUKFCAiIiLZferXr0/u3LkZPnw4EyZMwDAMRowYgd1u5/Tp087tBgwYQK1atShQoABbtmxh5MiRnD59msmTJyd5zWvXrjF//nxGjBiRqL9ChQrMnj2bu+66i8jISN5++20aNmzI77//zh133JHi+xIRkcxjGAYPzQxn+/F/rC4lTfy5Rgw3rr9wNZdkBrcakU2LiRMnEhgY6HyEhIRYXVKGuT53+JdffqFXr1707t2bTp06pem1UvO/rhMnTiQa4ZwwYQIA69atIzo6mlatWgFQqFAh7r//fmbPnp0hdaSkZMmSlCtXLsVH8eLF0/zaySlcuDCLFy9m+fLl5MmTh8DAQC5dukStWrXw8LjxT23IkCE0b96cu+66i6effppJkyYxbdq0RP/huu6bb77h8uXL9OrVK1F/gwYNePTRR6lRowbNmjXj66+/pnDhwnzwwQfp+p5ERCTtrsbb3TbEPuDxCz/4DOI+j+1Wl3JTWStW30KRIkWSXAF+5swZAgICUhxdGzlyJEOGDHG2o6KiXAqzfl6e7BsflraCb5Ofl2u3Es2dOzflypUDYPbs2VSvXp2PP/6YJ554AoDy5csTGRnJqVOnKFasWKJ94+LiOHz4MPfcc49z202bNhEfH5/iaGixYsXYtWuXs12gQAHAvMjr4sWLic6Jw+Hgt99+Y9y4cXh4eBAQEEB0dDQOhyNRyLt06RIAgYGBqa4jJVWqVLnpBVBNmjTh22+/Tfa5IkWKcPbs2UR9CQkJXLx4kSJFiqT4mi1atODw4cOcP3+eXLlykS9fPooUKUKZMmVS3KdevXokJCRw7NgxKlSokOi5jz76iDZt2iT5JOK/vLy8qFmzJocOHbrpdiJiMgyDq/F2q8uQbC4m7sbfsW2jQvH3doNbhF85g/ea4eQ6uByADytsJ7bbi4DruSQzuFWQbdCgAatWrUrUt27dOho0aJDiPj4+PonmLLrKZrNluWH01PDw8ODFF19kyJAhdO/eHT8/Pzp16sTw4cOZNGkSkyZNSrT9zJkziY6Oplu3bgB0796dd999l/fee4+BAwcmef1Lly6RL18+Z3C+7sKFCyxdupSFCxdSpUoVZ7/dbqdx48asXbuWli1bUqFCBRISEti1axe1atVybrdjxw7ADLCu1JGc25la0KBBAy5dusT27dupXbs2AN9//z0Oh4N69eqluN91hQoVcu5z9uxZ2rVrl+K2u3btwsPDI8lUhqNHj7JhwwaWLVt2y+PZ7Xb27NnjHAUXkZS5+8e94p78vT2zdp4wDNi9EFaPgGuXwCMXNB6MZ9MX8M+Vdeu2tLIrV64kGkE6evQou3btokCBApQoUYKRI0dy8uRJPv30UwCefvpppk+fzrBhw3j88cf5/vvv+eKLL1i5cqVVbyFLe/jhh3nhhReYMWMGQ4cOpUSJErz55ps8//zz+Pr60rNnT7y8vFi6dCkvvvgizz//vDOk1atXj2HDhvH8889z8uRJOnbsSLFixTh06BAzZ86kcePGyQbLefPmUbBgQTp37pzktqitWrXi448/pmXLllSpUoUWLVrw+OOPM2nSJMqUKcPBgwcZNGgQXbp0cX7sn9Y6wJxakFaVKlWiZcuW9OnTh5kzZxIfH0///v3p2rWrczT75MmT3HfffXz66afUrVsXMC9yq1SpEoULFyY8PJyBAwcyePBg50hreHg4v/zyC/fccw958+YlPDycwYMH88gjj5A/f/5ENcyePZuiRYsme1Ha+PHjqV+/PuXKlePSpUu89dZbHD9+nCeffDLN71kkp3Dnj3vFPdUpmT9LjmY6Rf4NywfBoXVmu8hd0OE9KFLN0rJSJcPWTkiFDRs2GECSR69evQzDMJeUatasWZJ9atSoYXh7extlypQx5syZ49Ixc9LyW4ZhGBMnTjQKFy5sXLlyxdm3dOlSo0mTJkbu3LkNX19fo3bt2sbs2bOTfd1FixYZTZs2NfLmzWvkzp3buOuuu4zx48enuOxVtWrVjGeffTbF1/L29jbOnTtnGIa5dNaAAQOMsmXLGn5+fsadd95pDBs2zLh8+fJt15EeLly4YHTr1s3IkyePERAQYPTu3TtRbUePHjUAY8OGDc6+4cOHG8HBwYaXl5dx5513GpMmTTIcDofz+e3btxv16tUzAgMDDV9fX6NSpUrGhAkTjGvXriU6tt1uN+644w7jxRdfTLa2QYMGGSVKlDC8vb2N4OBgo1WrVsaOHTtSfC/u/HdbJL1Fx8YbJYevMEoOX2Gcu3zNiI6N10OPDH38+/dAlnTgW8MYE2AY4wsZxo9vG0ZCnKXluLL8ls0wsuBaChkoKiqKwMBAIiMjCQgISPTctWvXnFfW6y5Jkp3o77aklZEN55LGxNmp8+p3QNa8ClskU8RfA69//T748W2o1BYKV0h5n0xys6z2X/rXKyIiyTI0l1Qk+3HY4ef3IHwG9N0Ief9/AXPTpGvMu4Nsv/yWiIikTXafS5rl5y2KpLez++HjFrB2FFw+DdvnWl3RbdOIrIiI3JLbLB3kAj8vzyQXpYpkS/Z42DQFfnwT7HHgEwAtXoVaj1pd2W1TkBURsVhWnYf67zUws/zSQSKSvNO7YWk/iNhjtsu3hNaTITB9bwpkFf1UEhGxkOahikiG2vW5GWL9CsADb0K1hyAbfRKhIJsMh8NhdQki6Up/p7Mud5iHqrmkIm7GngCe/494944Cww5Nh0GewtbWlQEUZP/F29sbDw8PTp06ReHChfH29tb8KXFrhmEQFxfHuXPn8PDwwNvb2+qS5Cay6jxUzSUVcRNx0bD+FTizFx5dBh4e4JMHWr1ldWUZRkH2Xzw8PChdujSnT5/m1KlTVpcjkm78/f0pUaIEHh5aqCQ9pcfcVs1DFZF0cWQjLBsAl46b7WM/QpnmVlaUKfQT8z+8vb0pUaIECQkJ2O1Z7+ILEVd5enqSK1cujailM81tFZEs4VokrH0ZdnxitgNDoO2UHBFiQUE2WTabDS8vL7y8vKwuRUSyqPSe26p5qCLisoOrYcVguPz/T5HvfhJCx4JPXkvLykwKsiJiuay6/NTN/HtKQHrMbdU8VBFxicMO379qhtgCZaDddCjVyOqqMp2CrIhYKjt8RK+5rSKSKQzDfHh4gIcntJ8Ge7+C5i+Ct7/V1VlCP3lFxFLusPzUzWhKgIhkissRsPJ5KHIXNB9u9hWraT5yMAVZEckysuryUzejKQEikqEMA3YtgDUjzQu7Dm+Aun3Av4DVlWUJCrIi2Yi7zzXVR/QiIv9y6S9YPhAOrzfbRWtA++kKsf+i3xgi2UR2mGsqIiKAwwHbZ8O6MRB3BTx94J6R0OC5G3fsEkBBViTb0FxTEZFsIupvWPMSJFyDkPrmKGyhO62uKktSkBXJhjTXVETEzRgGXP8ZmK8EtHgVDAfc3cdcpUCSpSArksWldt6r5pqKiLips/th2XNmeC1R3+yr28famtyEftOJZGGa9yoiko0lxMGmd+DHt8ARb04nePK7GyOzcksKsiJZWFrmvWquqYiIGzi1E5b2hzN7zXb5B6DNZIVYFynIiriJ1M571VxTEZEsLP4qbHwdtkwDww5+BaDVW1C1k0JsGijISrbjjmuppkTzXkVEspmDq2DzFPPrKg/CA29CnsKWluTO9FtRshXNKRURkSytyoPw53dQsTVUamN1NW5P6zlItuLua6mmRPNeRUTc1OEN8HEYXL1ktm026Pi+Qmw60YhsDpKdPnJPyb8/infHtVRTonmvIiJu5uolWDsKds4z2z9NghavWFpSdqQgm0PkxI/cNadUREQscfBbWDEYLp8223X7QrPh1taUTem3fA6RXT9yT4k+ihcRkUwXfQG+HQZ7vzTbBcqat5ct2dDaurIxBdkcKDt95J4SfRQvIiKZbsOrZoi1eUDD56D5SPDys7qqbE1BNotK7/msWsZJREQkg90zCi4cgtCxULy21dXkCEozWVBOnM8qIiLiVgwDdn4Gx7dAh/fM1QhyF4Rey62uLEdRkM2CMnI+q+aOioiI3KZ/jsPygXBkg9mu0gHKh1laUk6lIJvFpfd8Vs0dFRERSSOHA7Z9DOvGQHw05PKFe16EsvdZXVmOpSCbCVyd76r5rCIiIlnM+UOw7Dk4scVsl2gA7aZDoXLW1pXDKSFlMM13FRERcXMOByzsDucPgldu82Kuu58ED90g1WoKshnsdua7aj6riIhIFuDhAQ+8AVvehTZTIH9JqyuS/1OQzUSuznfVfFYRERELJMTBpsmQJwjqPG72lb0HyjQ3VyeQLENBNhNpvquIiEgWd3IHLO0PZ383pxFUbGMGWlCIzYKUqkRERETir8LGibBlGhgO8C8Ird6C3IWtrkxuQkFWREREcrbj4bC0H1w8bLarPmTOic1dyNq65JYUZEVERCTnijoFn7QFRzzkLQpt3oEKD1hdlaSSgqyIiIjkXAHFoGF/iD4PLV4Fv3xWVyQuUJAVERGRnOPqP7BuNNR7BoIrm333jdGFXG5KQVZERERyhgMrYcUQuBIBZ/fDE+vMAKsQ67YUZEVERCR7iz4Pq16A37822wXvNKcRKMC6PQVZERERyZ4MA/Z+Bd8Og5gLYPOERgOg2Qjw8rW6OkkHCrIiIiKSPe1fBl89YX4dXBXaT4diNa2tSdKVgqyIiIhkTxXbQImG5u1lGw2CXN5WVyTpTEFWREREsod/jsNPk+CBN82pAx6e8NgK80/JlhRkRURExL05HPDrLPhuHMRHm3fkum+0+ZxCbLamICsiIiLu6/yfsLQ//PWz2S7ZGGr0sLYmyTQKsiIiIuJ+7AkQPg02TAR7LHjngfvHQe3HwcPD6uokkyjIioiIiPtZ9zL8/J75ddn7oO0UyFfC0pIk8ynIioiIiPup/yzsXw73vAjVu+nmBjmUgqyIiIhkfX9vhyPfQ9MXzHa+EBiwEzy9rK1LLKUgKyIiIllXXAxsnADhM8BwwB13Q5nm5nMKsTmegqyIiIhkTcc2w7L+cPGI2a7WGYKrWVuTZCkKsiIiIpK1xF6G78bCrx+Z7bzFzIu5yodZWZVkQQqyIiIiknUYBnzSDk7tMNu1H4P7x4NvoKVlSdakhdZEREQk67DZoGF/yFcSHl0GbacqxEqKNCIrIiIi1tq/HGyeULGV2a7yIFRoDV6+1tYlWZ6CrIiIiFjjyjn49gX4/RvwLwQh9SB3QXNUViFWUkFBVkRERDKXYcCexfDtcLh60RyNrd0LvHNbXZm4GcvnyM6YMYNSpUrh6+tLvXr12Lp16023nzJlChUqVMDPz4+QkBAGDx7MtWvXMqlaERERuS1Rp+DzrvB1HzPEBleDPt/DfaM1Cisus3REdtGiRQwZMoSZM2dSr149pkyZQlhYGAcPHiQoKCjJ9gsWLGDEiBHMnj2bhg0b8scff/DYY49hs9mYPHmyBe9AREREUu3KOZhRH2IjwdMbmg2DRoN0YwNJM0tHZCdPnkyfPn3o3bs3lStXZubMmfj7+zN79uxkt9+yZQuNGjWie/fulCpVihYtWtCtW7dbjuKKiIhIFpCnMFRpD8XrwFM/mbebVYiV22BZkI2Li2P79u2EhobeKMbDg9DQUMLDw5Pdp2HDhmzfvt0ZXI8cOcKqVato1apViseJjY0lKioq0UNEREQygcMOv3wAl07c6Gv5BjyxFoIqWleXZBuWTS04f/48drud4ODgRP3BwcEcOHAg2X26d+/O+fPnady4MYZhkJCQwNNPP82LL76Y4nEmTpzIuHHj0rV2ERERuYVzf8DSfvD3VvhjDTzylbkagbe/1ZVJNmL5xV6u2LhxIxMmTOC9995jx44dfP3116xcuZJXXnklxX1GjhxJZGSk8/HXX39lYsUiIiI5jD0efpoEMxubIdY7L1RsbXVVkk1ZNiJbqFAhPD09OXPmTKL+M2fOUKRIkWT3efnll+nZsydPPvkkANWqVSM6Opq+ffvy0ksv4eGRNJf7+Pjg4+OT/m9AREREEjv9mzkKG/Gb2S53P7SdAoF3WFqWZF+Wjch6e3tTu3Zt1q9f7+xzOBysX7+eBg0aJLtPTExMkrDq6ekJgGEYGVesiIiI3Nzh72HWPWaI9c0HHT+AHosVYiVDWbr81pAhQ+jVqxd16tShbt26TJkyhejoaHr37g3Ao48+SvHixZk4cSIAbdu2ZfLkydSsWZN69epx6NAhXn75Zdq2besMtCIiImKBEg0gf2kIqgSt3oa8wbfeR+Q2WRpku3Tpwrlz5xg9ejQRERHUqFGD1atXOy8AO3HiRKIR2FGjRmGz2Rg1ahQnT56kcOHCtG3bltdee82qtyAiIpIzxcXA9jlQ72nw8AQvP3M1Av8CVlcmOYjNyGGfyUdFRREYGEhkZCQBAQEZfryYuAQqj14DwL7xYfh7667AIiLi5o5tgqX94Z+j0OJVaPic1RVJNuJKVlOqEhERkdS5FgXfjYFt/79xUUBxKKz1YMU6CrIiIiJya3+ug+WDIOpvs127N9w/Hnwz/tNNkZQoyIqIiMjN/fg2fP//Ndvzl4J206B0U0tLEgE3uyGCiIiIWKBCK8jlC/X7wTNbFGIly9CIrIiIiCR25Swc/RGqPWS2gyvDwN+0pJZkOQqyIiIiYjIM+O0LWD3cvLCrYFkoVtN8TiFWsiAFWREREYHIv2HFYPhzrdkuUg08va2tSeQWFGRFRERyMocDdsyFtaMh7rIZXpsNh0YDwdPL6upEbkpBVkREJKcyDFjUAw6uMtt33A3tpkOQ1oYV96BVC0RERHIqmw3K3gu5/CBsIjy+RiFW3IpGZEVERHKScwfNC7lC7jbbdZ6A8i0hX4i1dYmkgUZkRUREcgJ7vHljg5mN4avHIfaK2e/hoRArbksjsiIiItnd6d2wtB9E7DHbhStC/FXwyWNtXSK3SUFWREQku4q/Bj++CZumgGEHv/zQ8g24q7M5P1bEzSnIioiIZEcxF2F2Szh/0GxXbg+t3oY8QdbWJZKOFGRFRESyI7/8UOhOuPoPtJ4EldtZXZFIulOQFRERyS6O/gRBlSF3QXPqQJsp4OEJ/gWsrkwkQ2jVAhEREXd3LRKWD4RP2sDq4Tf68xRWiJVsTSOyIiIi7uyPtbBiEESdNNs+ecFhN0diRbI5BVkRERF3FHMRVo+E3xaa7fylod00KN3E2rpEMpGCrIiIiLs5uR0WdIHoc2DzgPrPwj0vgbe/1ZWJZCoFWREREXdToCx45DJvbNB+BtxRx+qKRCyhICsiIpLVGQYcXg9l7zNXI/DLBz2XQIHSkMvH6upELKNVC0RERLKyyL9h/sPwWSfYteBGf1BFhVjJ8TQiKyIikhU5HLB9DqwbA3GXwdMH4q5YXZVIlqIgKyIiktVcOAzLBsDxTWY7pB60mw6Fy1tbl0gWoyArIiKSlexeCMsHQcJV8PKH+8ZA3T5aF1YkGQqyIiIiWUn+UpBwDUo3hbbvmhd0iUiyFGRFRESsZI+HU7sg5G6zXaI+PL4GQuqaKxSISIq0aoGIiIhVTu2CD++BT9qY82KvK1FPIVYkFTQiKyIiktnir8EPb8DmqWDYwa8AXDoOBctaXZmIW1GQFRERyUwnfoFl/eH8H2a7yoPwwJuQp7C1dYm4IQVZERGRzLJuNGx+FzAgTzC0ngyV2lhdlYjbUpAVERHJLF65AQNq9ICw18Avv9UVibg1BVkREZGMci0Sos/fmPvaeDCUbAilm1hbl0g2oVULREREMsLB1TCjHnzxKCTEmX25vBViRdKRRmRFRETSU/QFWD0c9iw2215+EHVSNzYQyQAKsiIiIunBMOD3b2DVCxBzHmwe0KA/3POiGWZFJN0pyIqIiNyu2MvwzdNwYIXZLlwJ2s+AO2pbW5dINqcgKyIicru8csPVf8AjFzR53nzk8rG6KpFsT0FWREQkLS79ZS6f5ZMHPDyg3TSIj4Ei1ayuTCTH0KoFIiIirnA4YOsseK8+fP/Kjf6CZRViRTKZRmRFRERS68JhWPYcHN9stiP2gD0ePL2srUskh1KQFRERuRWHHcJnwIbXIOGaOSc2dCzc/aQ5rUBELJGmf33z5s2jUaNGFCtWjOPHjwMwZcoUli5dmq7FiYiIWO7CYfj4flj3shliyzSHZ8OhXl+FWBGLufwv8P3332fIkCG0atWKS5cuYbfbAciXLx9TpkxJ7/pERESs5eUPFw6BTyC0mw49l0D+klZXJSKkIchOmzaNWbNm8dJLL+Hp6ensr1OnDnv27EnX4kRERCzxz7EbXwcUhYc/gX6/QK2eYLNZVpaIJOZykD169Cg1a9ZM0u/j40N0dHS6FCUiImKJ+KuwbjS8WwsOrr7RX/YeM9CKSJbicpAtXbo0u3btStK/evVqKlWqlB41iYiIZL7j4TCzMWyeCoYdjv5gdUUicgsur1owZMgQ+vXrx7Vr1zAMg61bt/L5558zceJEPvroo4yoUUREJOPEXoH148y1YTEgTxFo8w5UbGV1ZSJyCy4H2SeffBI/Pz9GjRpFTEwM3bt3p1ixYkydOpWuXbtmRI0iIiIZ4+hPsPRZuHTCbNd8BFq8Bn75LC1LRFInTevI9ujRgx49ehATE8OVK1cICgpK77pEREQyXuxlM8QGloB2U6HsvVZXJCIucHmO7L333sulS5cA8Pf3d4bYqKgo7r1XPwBERCSLizp94+uKraDD++a6sAqxIm7H5SC7ceNG4uLikvRfu3aNn376KV2KEhERSXfR5+HLJ+C9enA54kZ/je7gk8e6ukQkzVI9teC3335zfr1v3z4iIm78ELDb7axevZrixYunb3UiIiK3yzBg71fw7TCIuQA2Dzj6I9zV2erKROQ2pTrI1qhRA5vNhs1mS3YKgZ+fH9OmTUvX4kRERG5L1GlYOQQOrjLbQVWg/XQoXsvaukQkXaQ6yB49ehTDMChTpgxbt26lcOHCzue8vb0JCgpKdKcvERERS+2cD6tHQmwkeHhB06HQeAjk8ra6MhFJJ6kOsiVLmveVdjgcGVaMiIhIujm92wyxxWpC+xkQXMXqikQknaVp+S0w58meOHEiyYVf7dq1u+2iREREXOZwwLVL4F/AbN83GgrdCbV7g2eaf92JSBbm8r/sI0eO0LFjR/bs2YPNZsMwDABsNhtgXvglIiKSqc4fgmX9zQu5eq0ADw9zJYK6fayuTEQykMvLbw0cOJDSpUtz9uxZ/P39+f333/nxxx+pU6cOGzduzIASRUREUmBPgE1T4P2GcCIcTu2CcwesrkpEMonLI7Lh4eF8//33FCpUCA8PDzw8PGjcuDETJ05kwIAB7Ny5MyPqFBERSezM77C0H5z6/++dsvdC26mQr4S1dYlIpnF5RNZut5M3b14AChUqxKlTpwDzYrCDBw+6XMCMGTMoVaoUvr6+1KtXj61bt950+0uXLtGvXz+KFi2Kj48P5cuXZ9WqVS4fV0RE3FRCHGyYCB80M0Osb6B5MdcjXyvEiuQwLo/IVq1ald27d1O6dGnq1avHm2++ibe3Nx9++CFlypRx6bUWLVrEkCFDmDlzJvXq1WPKlCmEhYVx8OBB561v/y0uLo7777+foKAgvvzyS4oXL87x48fJly+fq29DRETc2f7l4IiHCq2h9SQIKGp1RSJiAZeD7KhRo4iOjgZg/PjxtGnThiZNmlCwYEEWLVrk0mtNnjyZPn360Lt3bwBmzpzJypUrmT17NiNGjEiy/ezZs7l48SJbtmzBy8sLgFKlSrn6FkRExN3EXwWbp7kGbC5v6DADLh6BKg/C/y82FpGcx+WpBWFhYTz44IMAlCtXjgMHDnD+/HnOnj2b7B2/UhIXF8f27dsJDQ29UYyHB6GhoYSHhye7z7Jly2jQoAH9+vUjODiYqlWrMmHCBK2UICKSnR3fAu83gs1TbvQVqwlVOynEiuRwLgXZ+Ph4cuXKxd69exP1FyhQwLn8VmqdP38eu91OcHBwov7g4GAiIiKS3efIkSN8+eWX2O12Vq1axcsvv8ykSZN49dVXUzxObGwsUVFRiR4iIuIGYi/DyqEw5wG4eBh2zoP4a1ZXJSJZiEtTC7y8vChRooRlI6AOh4OgoCA+/PBDPD09qV27NidPnuStt95izJgxye4zceJExo0bl8mViojIbTm0HpYPhMi/zHatR+H+V8DL19q6RCRLcXlqwUsvvcSLL77IxYsXb+vAhQoVwtPTkzNnziTqP3PmDEWKFEl2n6JFi1K+fHk8PT2dfZUqVSIiIiLJHcauGzlyJJGRkc7HX3/9dVt1i4hIBrr6DyzpB589aIbYfCWg5xJoNw388lldnYhkMS5f7DV9+nQOHTpEsWLFKFmyJLlz5070/I4dO1L1Ot7e3tSuXZv169fToUMHwBxxXb9+Pf379092n0aNGrFgwQIcDgceHmYG/+OPPyhatCje3t7J7uPj44OPj08q352IiFgq5iLs/RKwQd2+5m1mffJYXZWIZFEuB9nroTM9DBkyhF69elGnTh3q1q3LlClTiI6Odq5i8Oijj1K8eHEmTpwIwDPPPMP06dMZOHAgzz33HH/++ScTJkxgwIAB6VaTiIhksrgY8PY3vy5YFtq8AwXKQIn61tYlIlmey0E2pbmoadGlSxfOnTvH6NGjiYiIoEaNGqxevdp5AdiJEyecI68AISEhrFmzhsGDB3PXXXdRvHhxBg4cyPDhw9OtJhERySSGAXu/gm+HQ9f5N4Jrje7W1iUibsNmGIZhdRGZKSoqisDAQCIjIwkICMjw48XEJVB59BoA9o0Pw9/b5f87iIhkP1GnYMUQ+ONbs12pHXSZZ21NIpIluJLVlKpERCTzGAbs+BTWvgyxkeDhBU1fgMaDra5MRNyQgqyIiGSOf46ZS2od2Wi2i9WC9jMguLKVVYmIG1OQFRGRzHFssxlic/nCPS9B/WfBU7+GRCTt0vwTJC4ujqNHj1K2bFly5dIPIhERSUZCHOT6//KINbrDhUNQ8xFzdQIRkdvk8g0RYmJieOKJJ/D396dKlSqcOHECgOeee47XX3893QsUERE3ZE+ATe/AjLpwLdLss9kgdIxCrIikG5eD7MiRI9m9ezcbN27E1/fGrQJDQ0NZtGhRuhYnIiJuKGIvfHQffDcW/jkKuxZYXZGIZFMuzwlYsmQJixYton79+thsNmd/lSpVOHz4cLoWJyIibiQhFn58GzZNBkcC+AZCy9ehejerKxORbMrlIHvu3DmCgoKS9EdHRycKtiIikoP8vR2W9oNz+812xTbQehLkLWJtXSKSrbk8taBOnTqsXLnS2b4eXj/66CMaNGiQfpWJiIj72PqBGWL9C8HDc6HLZwqxIpLhXB6RnTBhAg888AD79u0jISGBqVOnsm/fPrZs2cIPP/yQETWKiEhW5LCDh6f5ddhE8M4N94yC3AWtrUtEcgyXR2QbN27Mrl27SEhIoFq1aqxdu5agoCDCw8OpXbt2RtQoIiJZSexl8/ayi3uZd+oCM7y2eUchVkQyVZoWgC1btiyzZs1K71pERCSrO/QdLB8EkX+Z7VM7oXgtS0sSkZzL5RHZ0NBQ5s6dS1RUVEbUIyIiWVHMRfjmGfiskxli85WER5cpxIqIpVwOslWqVGHkyJEUKVKEhx9+mKVLlxIfH58RtYmISFawfzm8Vx92LwBsUO8ZeDYcyjSzujIRyeFcDrJTp07l5MmTLFmyhNy5c/Poo48SHBxM3759dbGXiEh2E38N1rwIV85AofLw+Bp44HXzwi4REYu5HGQBPDw8aNGiBXPnzuXMmTN88MEHbN26lXvvvTe96xMRkcxmGDcu4vLyhbbvQpPn4amfoEQ9a2sTEfmXNF3sdV1ERAQLFy7ks88+47fffqNu3brpVZeIiFgh8iSsGAzlW8DdT5p9Ze8xHyIiWYzLI7JRUVHMmTOH+++/n5CQEN5//33atWvHn3/+yc8//5wRNYqISEYzDNg+15wL++ca+P41iIuxuioRkZtyeUQ2ODiY/Pnz06VLFyZOnEidOnUyoi4REcksF4/C8gFw9EezXbwOtJ8B3v7W1iUicgsuB9lly5Zx33334eGRpum1IiKSVTjssPVDWD8e4mMglx/cOwrqP3Pjjl0iIlmYy0H2/vvvz4g6REQks507aK5IYDigVBNoOxUKlrW6KhGRVEtVkK1Vqxbr168nf/781KxZE5vNluK2O3bsSLfiREQknRkGXP8ZHlwZmo+E3IWg1mOgT9pExM2kKsi2b98eHx8f59c3C7IiIpJFnf4NVg6BdtMgqJLZ12yYtTWJiNyGVAXZMWPGOL8eO3ZsRtUiIiIZISEWfngTNk8BRwKsHQWPfGV1VSIit83lz5HKlCnDhQsXkvRfunSJMmXKpEtRIiKSTv7eBh80hZ/eNkNspXbQ/j2rqxIRSRcuX+x17Ngx7HZ7kv7Y2Fj+/vvvdClKRERuU1wMbHgNfn7PvJgrd2Fo9TZU6WB1ZSIi6SbVQXbZsmXOr9esWUNgYKCzbbfbWb9+PaVLl07f6kREJG12L4Dw6ebXd3WFlhPBv4C1NYmIpLNUB9kOHToAYLPZ6NWrV6LnvLy8KFWqFJMmTUrX4kREJI1qPQZHNkLNR83bzYqIZEOpDrIOhwOA0qVL8+uvv1KoUKEMK0pERFz05zoInwHdFoKXL3jmgi6fWV2ViEiGcnmO7NGjRzOiDhERSYuYi7B6JPy20Gz//B40GWJtTSIimSRVQfbdd9+lb9+++Pr68u6779502wEDBqRLYSIicgv7lsLKoRB9FrBB/Weh3lNWVyUikmlSFWTfeecdevToga+vL++8806K29lsNgVZEZGMdvkMrBoK+/9/EW6hCtB+OoTUtbYuEZFMlqog++/pBJpaICJisdXDzRBr84TGg827c+XysboqEZFM5/Ic2f+y2+3s2bOHkiVLkj9//vSoSUREbub+8eao7AOvQ9HqVlcjImIZl+/sNWjQID7++GPADLFNmzalVq1ahISEsHHjxvSuT0QkZ3M4YNtsWPPSjb58JeDxbxViRSTHcznIfvnll1Svbv7wXL58OceOHePAgQMMHjyYl1566RZ7i4hIql08Ap+2gxWDzZsb/LXV6opERLIUl4Ps+fPnKVKkCACrVq3i4Ycfpnz58jz++OPs2bMn3QsUEclxHHZzTdj3GsKxn8DLH8ImQvHaVlcmIpKluDxHNjg4mH379lG0aFFWr17N+++/D0BMTAyenp7pXqCISI5y7iAs7Qd//2q2SzeFtu9CAd0CXETkv1wOsr1796Zz584ULVoUm81GaGgoAL/88gsVK1ZM9wJFRHIMezzM6whRJ8E7L4S9CrV6gc1mdWUiIlmSy0F27NixVK1alb/++ouHH34YHx9zyRdPT09GjBiR7gWKiOQYnl7Q4hXYvQjavAOBxa2uSEQkS0vT8lsPPfRQkr5evXrddjEiIjlK/DX48S0oUg2qdDD7qjxoPjQKKyJySy5f7AXwww8/0LZtW8qVK0e5cuVo164dP/30U3rXJiKSff21FT5oAj+9DSufh2tRZr/NphArIpJKLgfZzz77jNDQUPz9/RkwYAADBgzAz8+P++67jwULFmREjSIi2UdcNKweCR+3gPN/QO4gcxqBb4DVlYmIuB2Xpxa89tprvPnmmwwePNjZN2DAACZPnswrr7xC9+7d07VAEZFs4+iPsOw5+OeY2a7eDcImgH8BS8sSEXFXLo/IHjlyhLZt2ybpb9euHUePHk2XokREsp1zf8An7cwQG3AH9PgSOs5UiBURuQ0uj8iGhISwfv16ypUrl6j/u+++IyQkJN0KExHJVgqXh1o9wSMXhI7TVAIRkXTgcpB9/vnnGTBgALt27aJhw4YAbN68mblz5zJ16tR0L1BExC3FXITvxkDTFyBfCbOvzVTwSNM1tiIikgyXg+wzzzxDkSJFmDRpEl988QUAlSpVYtGiRbRv3z7dCxQRcTu/L4FVQyH6HFyOgB6LzX6FWBGRdJWmdWQ7duxIx44d07sWERH3dvkMrHoe9i8324UrQrPh1tYkIpKNpSnIAmzbto39+/cDULlyZWrXrp1uRYmIuBXDgN0LYfUIuHbJnAfbeAg0HQq5fKyuTkQk23I5yP79999069aNzZs3ky9fPgAuXbpEw4YNWbhwIXfccUd61ygikrXtnGcuqwVQtDq0n2HerUtERDKUyxO2nnzySeLj49m/fz8XL17k4sWL7N+/H4fDwZNPPpkRNYqIZG3VHobganDfGHjye4VYEZFM4vKI7A8//MCWLVuoUKGCs69ChQpMmzaNJk2apGtxIiJZ0oXD8MtMaPk6eHiClx/03QieaZ6tJSIiaZCmdWTj4+OT9NvtdooVK5YuRYmIZEkOO/z8Hnz/GiRchXwloWF/8zmFWBGRTOfy1IK33nqL5557jm3btjn7tm3bxsCBA3n77bfTtTgRkSzj7H74uAWsHWWG2NLNoFIbq6sSEcnRbIZhGK7skD9/fmJiYkhISCBXLnME4vrXuXPnTrTtxYsX06/SdBIVFUVgYCCRkZEEBGT8nXVi4hKoPHoNAPvGh+HvrVEbEbdij4dNU+CHN8ARDz4B0OJVqPUo2GxWVyciku24ktVcTlVTpkxJa10iIu5n+UDYNd/8uvwD0GYyBGgalYhIVuBykO3Vq1dG1CEikjU16A+HvzdHYat20iisiEgWclv3S2zdujWnT59Or1pERKx34hf45YMb7eDKMHA3VHtIIVZEJIu5rQmbP/74I1evXk2vWkRErBMXDevHmyHW5gEh9aBYDfM53Z1LRCRL0pVHIiJHNsKyAXDpuNmu3g3yl7S0JBERubXbCrIlS5bEy8srvWoREclc1yLN5bR2fGq2A0Og7VQod5+1dYmISKrcVpDdu3dvetUhIpK5HHaYdR9c+NNs390HQseAT15r6xIRkVRL08VeP/30E4888ggNGzbk5MmTAMybN49NmzalqYgZM2ZQqlQpfH19qVevHlu3bk3VfgsXLsRms9GhQ4c0HVdEcjAPT6j3FBQoA4+tgtZvK8SKiLgZl4PsV199RVhYGH5+fuzYsYPY2FgAIiMjmTBhgssFLFq0iCFDhjBmzBh27NhB9erVCQsL4+zZszfd79ixYwwdOpQmTZq4fEwRyYEMA/Z+DUd/utFX5wl4ZguUamRdXSIikmYuB9lXX32VmTNnMmvWrETzYxs1asSOHTtcLmDy5Mn06dOH3r17U7lyZWbOnIm/vz+zZ89OcR+73U6PHj0YN24cZcqUcfmYIpLDXI6ARY/Al71haT9zhQIADw/w8rO2NhERSTOXg+zBgwdp2rRpkv7AwEAuXbrk0mvFxcWxfft2QkNDbxTk4UFoaCjh4eEp7jd+/HiCgoJ44oknbnmM2NhYoqKiEj1EJIcwDNg5H2bUhQMrwCMXVO9q/ikiIm7P5Z/mRYoU4dChQ5QqVSpR/6ZNm1weHT1//jx2u53g4OBE/cHBwRw4cCDZfTZt2sTHH3/Mrl27UnWMiRMnMm7cOJfqEpFs4NIJWD4IDq8320VrQPsZUKSqlVWJiEg6cnlEtk+fPgwcOJBffvkFm83GqVOnmD9/PkOHDuWZZ57JiBqdLl++TM+ePZk1axaFChVK1T4jR44kMjLS+fjrr78ytEYRyQIuHoX3Gpgh1tMHQsfBk+sVYkVEshmXR2RHjBiBw+HgvvvuIyYmhqZNm+Lj48PQoUN57rnnXHqtQoUK4enpyZkzZxL1nzlzhiJFiiTZ/vDhwxw7doy2bds6+xwOh/lGcuXi4MGDlC1bNtE+Pj4++PjorjwiOUr+UlC6GVy9CO2mQ6FyVlckIiIZwOUga7PZeOmll3jhhRc4dOgQV65coXLlyuTJk8flg3t7e1O7dm3Wr1/vXELL4XCwfv16+vfvn2T7ihUrsmfPnkR9o0aN4vLly0ydOpWQkBCXaxCRbMCeAL/OgmqdIXdBsNmg40zwzmNe0CUiItlSmq948Pb2pnLlyrddwJAhQ+jVqxd16tShbt26TJkyhejoaHr37g3Ao48+SvHixZk4cSK+vr5UrZr4o8F8+fIBJOkXkRzizD5zJYJTO+DkDug0y+z3DbC2LhERyXAuB9l77rkHm82W4vPff/+9S6/XpUsXzp07x+jRo4mIiKBGjRqsXr3aeQHYiRMn8NCIioj8V0IcbHoHfnwLHPHgEwilm5orFdzkZ5SIiGQfLgfZGjVqJGrHx8eza9cu9u7dS69evdJURP/+/ZOdSgCwcePGm+47d+7cNB1TRNzYyR2wtD+c/d1sV2gFrSdDQFFr6xIRkUzlcpB95513ku0fO3YsV65cue2CRERuat8yWNwLDAf4F4QH3oSqnTQKKyKSA6XbZ/aPPPLITe/GJSKSLko3hTzBZnjttxWqPaQQKyKSQ6Xb7W3Cw8Px9fVNr5cTETHFXoHdn8PdT5qB1S8fPL0JcqduLWkREcm+XA6yDz74YKK2YRicPn2abdu28fLLL6dbYSIiHP4elg8079LlnRtqdDf7FWJFRIQ0BNnAwMBEbQ8PDypUqMD48eNp0aJFuhUmIjnY1Uuw9iXY+ZnZDiwBAcUsLUlERLIel4Ks3W6nd+/eVKtWjfz582dUTSKSkx1YBSsGw5UIs123L9w3Bnxcv+mKiIhkby4FWU9PT1q0aMH+/fsVZEUk/X031lwbFqBgOfP2siUbWFqSiIhkXS6vWlC1alWOHDmSEbVkS4ZhdQUibuTOMPDIBY0GmRd0KcSKiMhNuBxkX331VYYOHcqKFSs4ffo0UVFRiR5yg2EYPDwz3OoyRLKuqNPmVILrSjaAgb/B/ePAy8+6ukRExC2kemrB+PHjef7552nVqhUA7dq1S3SrWsMwsNls2O329K/STV2Nt7PvtBnuKxcNwM/L0+KKRLIIwzAv5FrzEthj4ZktULCs+VxgcWtrExERt5HqIDtu3DiefvppNmzYkJH1ZFuLn26QKPiL5Fj/HDeX1Dry/58lxWqZd+kSERFxUaqDrPH/yZ7NmjXLsGKyM2VYyfEcDvh1Fnw3DuKjIZcv3PMS1H8WPNPt3iwiIpKDuPTbQyOKIpImDgfMaw9HfzTbJRpCu2lQqJy1dYmIiFtzKciWL1/+lmH24sWLt1WQiGRDHh5QshH8vd28kKvOE2afiIjIbXApyI4bNy7Jnb1ERJJ15nfzz+Aq5p+Nh0CNHpAvxLqaREQkW3EpyHbt2pWgoKCMqkVEsoOEOPhpkvkoXBH6bgBPL8jlrRArIiLpKtVBVvNjReSWTm6Hpf3h7D6zna8ExF0BP90JUERE0p/LqxaIiCQRfxU2TIDw6eZSWv6FoNWbUOVBLdkhIiIZJtVB1uHQOo8ikoyoUzC3DVw8bLarPQwt34DcBa2tS0REsj0t3igitydPEcgTDPEx0OYdqPCA1RWJiEgOoSArIq478gPcUQe8c5vLaHWaBd55wC+f1ZWJiEgOooUcRST1rv4DS/rBp+1g/Ss3+gPvUIgVEZFMpxFZEUmd/Stg5RC4cgawmRdxGYYu5hIREcsoyIrIzV05B9++AL9/Y7YL3gntp0OJ+tbWJSIiOZ6CrIik7NgmWNQTrl4Emyc0GgDNRoCXr9WViYiIKMiKyE0UKAsOOwRXNUdhi9W0uiIREREnBVkRucEw4OiPUKaZ2Q4oCo8th8KVzFvMioiIZCFatUBETP8cg3kdzBUJDq6+0V+0ukKsiIhkSRqRFcnpHA74dRZ8N9a8qUEu3/+vTCAiIpK1KciK5GTn/4Sl/eGvn812yUbQbhoULGttXSIiIqmgICuSU22bDd+OAHuseVeu+8dB7cfNO3WJiIi4AQVZkZwqTxEzxJYLhTZTIF+I1RWJiIi4REFWJKdIiIVzB8yLtwAqtoLHVprTCXR3LhERcUP6DFEkJ/h7O3zQDD5pB5f/dSFXqcYKsSIi4rY0IiuSncXFwMYJED4DDAfkLgwXj0DeYKsrExERuW0KsiLZ1bHNsKy/GVwB7uoCLV8H/wLW1iUiIpJOFGRFshvDgFUvmGvDAuQtBm2nQPkwS8sSERFJbwqyItmNzQa2/09/r9ULWrwCvoHW1iQiIpIBFGRFsoOr/0BcNATeYbbvGw2V2kLpJtbWJSIikoG0aoGIu9u/HGbUg6/7mrebBfDJoxArIiLZnkZkRdzVlXOwaijsW2K2ffNB9FnIW8TKqkRERDKNgqyIuzEM2LMYvh0OVy+CzRMaD4Kmw8DL1+rqREREMo2CrIg7ibkIS56BP1ab7SLVoP2MG3frEhERyUEUZEXciXceuPQXeHpDs2HQaBB4elldlYiIiCUUZEWyun+OQ0AxM7Dm8oYHPwSPXBBU0erKRERELKVVC0SyKocdfn4f3qsPm6bc6C9SVSFWREQEjciKZE3nDsLS/vD3VrN9ItxcWstD//cUERG5TkFWJCuxx8OWd2Hj62CPA++80GI81HpMIVZEROQ/FGRFsoqzB+DrPhDxm9kudz+0nXLjbl0iIiKSiIKsSFbhkQvO/2He2OCBN+CuLmCzWV2ViIhIlqUgK2KlyL9vjLgWKgcPzYHitSFvsLV1iYiIuAFNuhOxQlwMrHkJplaHE7/c6K/YSiFWREQklTQiK5LZjv4Ey56Df46a7UPfQYl61tYkIiLihhRkRTLLtSj4bgxsm222A4pD26lw5/3W1iUiIuKmFGRFMsOh9bBsAET9bbbrPA6h48A3wNq6RERE3JiCrEhmiDplhtj8paHdNCjdxOqKRERE3J6CrEhGuXIW8gSZX9d8xLzBQfVu4O1vbV0iIiLZhFYtEElvl8/Aop7wQTO4Fmn22Wxw9xMKsSIiIulIQVYkvRgG7PocZtSF/cvgyhk4tsnqqkRERLItTS0QSQ+Rf8PyQXBondkuche0nwFF77K0LBERkexMQVbkdhgGbJ8Da0dD3GXw9IbmI6DhAPD0sro6ERGRbE1BVuR22GxwbLMZYu+oC+2nQ+EKVlclIiKSI2SJObIzZsygVKlS+Pr6Uq9ePbZu3ZritrNmzaJJkybkz5+f/PnzExoaetPtRdKdw27e3OC6B96AVm/D46sVYkVERDKR5UF20aJFDBkyhDFjxrBjxw6qV69OWFgYZ8+eTXb7jRs30q1bNzZs2EB4eDghISG0aNGCkydPZnLlkiOdPQCzw2DJM+a0AoDchaBuH/DwtLY2ERGRHMZmGNd/G1ujXr163H333UyfPh0Ah8NBSEgIzz33HCNGjLjl/na7nfz58zN9+nQeffTRW24fFRVFYGAgkZGRBARk7F2VYuISqDx6DQD7xofh762ZHG7LHg+bp8APb5rrwfoEwNObIH9JqysTERHJVlzJapaOyMbFxbF9+3ZCQ0OdfR4eHoSGhhIeHp6q14iJiSE+Pp4CBQpkVJmS053eDbPuge9fNUPsnWHw7M8KsSIiIhazdIjw/Pnz2O12goODE/UHBwdz4MCBVL3G8OHDKVasWKIw/G+xsbHExsY621FRUcluJ5JEQiz88AZsmgKGHfzywwNvQrWHzYu8RERExFKWz5G9Ha+//joLFy7km2++wdfXN9ltJk6cSGBgoPMREhKSyVWK27LHw2+LzRBbuQP02wp3dVaIFRERySIsDbKFChXC09OTM2fOJOo/c+YMRYoUuem+b7/9Nq+//jpr167lrrtSXnR+5MiRREZGOh9//fVXutQu2VRcDDgc5tc+eaDDDOg8Dzp/AnmCrK1NREREErE0yHp7e1O7dm3Wr1/v7HM4HKxfv54GDRqkuN+bb77JK6+8wurVq6lTp85Nj+Hj40NAQECih0iyjvwA79WH7bNv9JVuCpXbWVeTiIiIpMjyqQVDhgxh1qxZfPLJJ+zfv59nnnmG6OhoevfuDcCjjz7KyJEjndu/8cYbvPzyy8yePZtSpUoRERFBREQEV65cseotiLu7FgnLBsCn7eDScdj6kblWrIiIiGRplq8H1aVLF86dO8fo0aOJiIigRo0arF692nkB2IkTJ/DwuJG333//feLi4njooYcSvc6YMWMYO3ZsZpYu2cEfa2D5ILh8ymzXeQJCx2pNWBERETdg+TqymU3ryAoAMRfh2+Gw5wuzXaAMtJsGpRpbW5eIiEgO50pWU7KSnOmfY7D3S7B5QP1n4Z6XwNvf6qpERETEBQqyknMkxEIuH/Pr4rWg5RtQvDbcUdvaukRERCRNLL/YSyTDGQbsWgBTqsHZ/Tf66/VViBUREXFjCrKSvV36C+Y/BEuegStnIHyG1RWJiIhIOtHUAsmeHA5zPdh1YyDuCnj6QPMR0HCA1ZWJiIhIOlGQleznwmFY9hwc32y2Q+pBu+lQuLy1dYmIiEi6UpCV7OfASjPEevnDfWOgbh+tCysiIpINKchK9mBPAM///3Wu/yxEnYR6T0OB0tbWJSIiIhlGF3uJe7PHww9vwofNIP6a2eeZCx54QyFWREQkm9OIrLivUzthaX84s9ds7/0KavawtiYRERHJNAqy4n7ir8EPr8Pmd8Gwg18BeOBNqPaQ1ZWJiIhIJlKQFfdy4mdzFPbCn2a7yoNmiM1T2Nq6REREJNMpyIp7+fEtM8TmCYbWk6FSG6srEhEREYsoyErW53CAx/+vS2zzDvw0GULHgF9+a+sSERERSynIStZ1LRLWjgKbB7SdavblKwFtp1haloiIiGQNCrKSNR1cDSsGweXTgM28tWzBslZXJSIiIlmIgqxkLdEXYPVw2LPYbBcoC+2mKcSKiIhIEgqykjUYBvz+Dax6AWLOm9MJGvSHe14ELz+rqxMREZEsSEFWsobYKFg1FGIuQOFK0GEGFK9tdVUiIiKShSnIinUMw/zTZgPfQGg9Cc7uhybPQy4fa2sTERGRLM/D6gIkh7p0Aj7rBPuW3Oir0tGcSqAQKyIiIqmgEVnJXA4HbPsYvhsLcVfg/B9QsQ14elldmYiIiLgZBVnJPBcOw7Ln4Phms12iAbSbrhArIiIiaaIgKxnPngA/vwcbXoOEa+CVG0LHwt1P3rhjl4iIiIiLFGQl453cButeNr8uc495l678Ja2tSURERNyegqxkvBL1oX4/CK4MNXqYqxSIiIiI3CZ9rivp7+QO+DgMLv11o6/lBKj5iEKsiIiIpBsFWUk/8Vdh3Wj46D7462dzZQIRERGRDKKpBZI+jofDsv5w4ZDZrvoQPPCGtTWJiIhItqYgK7cn9gqsHwdbZwEG5CkCbd6Biq2srkxERESyOQVZuT2/vA9bPzS/rtkTWrwKfvksLUlERERyBgVZuT0N+sPxLdDwOSh7r9XViIiISA6ii73ENQdWwsIe4LCbbS8/6PmNQqyIiIhkOo3ISupEn4dvh8Her8z2jk+hTm9raxIREZEcTUFWbs4wzPD67TCIuQA2D2g4AKp3tboyERERyeEUZCVlUadh5RA4uMpsB1WB9tOheC1r6xIRERFBQVZuZsnTcGQjeHhB0xeg8WDI5W11VSIiIiKALvaSmwmbACH14akfoflwhVgRERHJUjQiKyaHA379CGIjzdFXgOAq8PhqsNmsrU1EREQkGQqyAucPmbeXPREONk+o2BaCKprPKcSKiIhIFqUgm5PZEyB8OmyYAPZY8M4DoWOhUHmrKxMRERG5JQXZnCpiLyztB6d3me2y90LbqZCvhKVliYiIiKSWgmxOFHsF5raGa5fAN9C8qKtGD00jEBEREbeiIJsT+eSBe16Coz9A60mQt4jVFYmIiIi4TMtv5QTxV2HtKHNN2Ovq9oEunynEioiIiNtSkM3ujm+B9xvBlmmwbAAkxJr9NpumEoiIiIhb09SC7Cr2Mnw3Dn6dZbbzFoMH3oRcPtbWJSIiIpJOFGSzo0PrYflAiPzLbNfqBS1eMS/sEhEREckmFGSzm7+3wWcPml/nKwnt3oUyzS0tSURERCQjKMhmN8VrQ8U2EBgC970M3rmtrkhEREQkQyjIurvo8/D9K3DfGPAvYF7A1flT8PC0ujIRERGRDKUg664MA/Z8Cd8Og6sXIf4aPPiB+ZxCrIiIiOQACrLuKOoUrBgMf6w228FVof7T1tYkIiIikskUZN2JYcCOT82bG8RGgYcXNBsGjQZBLm+rqxMRERHJVAqy7iR8uhliwbyoq910CK5sbU0iIiIiFlGQdSc1e8KvH8PdT0D9ZzUXVkRERHI0Bdms7PyfsPMzCB1rrkbglw/6/wqeXlZXJiIiImI5BdmsyJ4AW96Fja+DPRYKV4Aa3c3nFGJFREREAAXZrCdiDyztB6d3m+1yoVCqibU1iYiIiGRBCrJZRUIs/Pg2bJoMjgTwzQctJ0L1bua0AhERERFJREE2q/jycTiwwvy6UltoNQnyBltbk4iIiEgWpiCbVTToD3//Cg+8CVU6WF2NiIiISJanIGuVY5vg0okbF3GVbAADd4OXn7V1iYiIiLgJD6sLAJgxYwalSpXC19eXevXqsXXr1ptuv3jxYipWrIivry/VqlVj1apVmVRpOrgWBSuGwNzW5p8XDt94TiFWREREJNUsD7KLFi1iyJAhjBkzhh07dlC9enXCwsI4e/Zssttv2bKFbt268cQTT7Bz5046dOhAhw4d2Lt3byZXngZ/fgfvNYBtH5vt6l0gdyFraxIRERFxUzbDMAwrC6hXrx53330306dPB8DhcBASEsJzzz3HiBEjkmzfpUsXoqOjWbFihbOvfv361KhRg5kzZ97yeFFRUQQGBhIZGUlAQED6vZFkxMQlUHn0GgK5wva7vyfXnoXmE/lLQbtpULpphh5fRERExN24ktUsHZGNi4tj+/bthIaGOvs8PDwIDQ0lPDw82X3Cw8MTbQ8QFhaW4vaxsbFERUUlemQmH+JY6fPi/0Oszby17DNbFGJFREREbpOlQfb8+fPY7XaCgxMvMxUcHExERESy+0RERLi0/cSJEwkMDHQ+QkJC0qf4VIrFm8UJzXAULA9PrDXXhvXOnak1iIiIiGRH2X7VgpEjRzJkyBBnOyoqKtPCrJ+XJ/vGh4H9Hmy5bLqYS0RERCQdWRpkCxUqhKenJ2fOnEnUf+bMGYoUKZLsPkWKFHFpex8fH3x8fNKnYBfZbDb8vXORA/6/ICIiIpLpLJ1a4O3tTe3atVm/fr2zz+FwsH79eho0aJDsPg0aNEi0PcC6detS3F5EREREsifLhwqHDBlCr169qFOnDnXr1mXKlClER0fTu3dvAB599FGKFy/OxIkTARg4cCDNmjVj0qRJtG7dmoULF7Jt2zY+/PBDK9+GiIiIiGQyy4Nsly5dOHfuHKNHjyYiIoIaNWqwevVq5wVdJ06cwMPjxsBxw4YNWbBgAaNGjeLFF1/kzjvvZMmSJVStWtWqtyAiIiIiFrB8HdnMlpnryIqIiIiIa9xmHVkRERERkbRSkBURERERt6QgKyIiIiJuSUFWRERERNySgqyIiIiIuCUFWRERERFxSwqyIiIiIuKWFGRFRERExC0pyIqIiIiIW1KQFRERERG3pCArIiIiIm4pl9UFZDbDMADzPr4iIiIikrVcz2jXM9vN5Lgge/nyZQBCQkIsrkREREREUnL58mUCAwNvuo3NSE3czUYcDgenTp0ib9682Gy2DD9eVFQUISEh/PXXXwQEBGT48ST96Ry6N50/96dz6N50/txfZp9DwzC4fPkyxYoVw8Pj5rNgc9yIrIeHB3fccUemHzcgIED/gN2czqF70/lzfzqH7k3nz/1l5jm81UjsdbrYS0RERETckoKsiIiIiLglBdkM5uPjw5gxY/Dx8bG6FEkjnUP3pvPn/nQO3ZvOn/vLyucwx13sJSIiIiLZg0ZkRURERMQtKciKiIiIiFtSkBURERERt6Qgmw5mzJhBqVKl8PX1pV69emzduvWm2y9evJiKFSvi6+tLtWrVWLVqVSZVKilx5RzOmjWLJk2akD9/fvLnz09oaOgtz7lkLFf/DV63cOFCbDYbHTp0yNgC5ZZcPYeXLl2iX79+FC1aFB8fH8qXL6+fpRZy9fxNmTKFChUq4OfnR0hICIMHD+batWuZVK38248//kjbtm0pVqwYNpuNJUuW3HKfjRs3UqtWLXx8fChXrhxz587N8DpTZMhtWbhwoeHt7W3Mnj3b+P33340+ffoY+fLlM86cOZPs9ps3bzY8PT2NN99809i3b58xatQow8vLy9izZ08mVy7XuXoOu3fvbsyYMcPYuXOnsX//fuOxxx4zAgMDjb///juTKxfDcP38XXf06FGjePHiRpMmTYz27dtnTrGSLFfPYWxsrFGnTh2jVatWxqZNm4yjR48aGzduNHbt2pXJlYthuH7+5s+fb/j4+Bjz5883jh49aqxZs8YoWrSoMXjw4EyuXAzDMFatWmW89NJLxtdff20AxjfffHPT7Y8cOWL4+/sbQ4YMMfbt22dMmzbN8PT0NFavXp05Bf+Hguxtqlu3rtGvXz9n2263G8WKFTMmTpyY7PadO3c2WrdunaivXr16xlNPPZWhdUrKXD2H/5WQkGDkzZvX+OSTTzKqRLmJtJy/hIQEo2HDhsZHH31k9OrVS0HWYq6ew/fff98oU6aMERcXl1klyk24ev769etn3HvvvYn6hgwZYjRq1ChD65RbS02QHTZsmFGlSpVEfV26dDHCwsIysLKUaWrBbYiLi2P79u2EhoY6+zw8PAgNDSU8PDzZfcLDwxNtDxAWFpbi9pKx0nIO/ysmJob4+HgKFCiQUWVKCtJ6/saPH09QUBBPPPFEZpQpN5GWc7hs2TIaNGhAv379CA4OpmrVqkyYMAG73Z5ZZcv/peX8NWzYkO3btzunHxw5coRVq1bRqlWrTKlZbk9WyzG5LDlqNnH+/HnsdjvBwcGJ+oODgzlw4ECy+0RERCS7fURERIbVKSlLyzn8r+HDh1OsWLEk/7Al46Xl/G3atImPP/6YXbt2ZUKFcitpOYdHjhzh+++/p0ePHqxatYpDhw7x7LPPEh8fz5gxYzKjbPm/tJy/7t27c/78eRo3boxhGCQkJPD000/z4osvZkbJcptSyjFRUVFcvXoVPz+/TK1HI7Iit+H1119n4cKFfPPNN/j6+lpdjtzC5cuX6dmzJ7NmzaJQoUJWlyNp5HA4CAoK4sMPP6R27dp06dKFl156iZkzZ1pdmqTCxo0bmTBhAu+99x47duzg66+/ZuXKlbzyyitWlyZuSCOyt6FQoUJ4enpy5syZRP1nzpyhSJEiye5TpEgRl7aXjJWWc3jd22+/zeuvv853333HXXfdlZFlSgpcPX+HDx/m2LFjtG3b1tnncDgAyJUrFwcPHqRs2bIZW7QkkpZ/g0WLFsXLywtPT09nX6VKlYiIiCAuLg5vb+8MrVluSMv5e/nll+nZsydPPvkkANWqVSM6Opq+ffvy0ksv4eGhMbasLKUcExAQkOmjsaAR2dvi7e1N7dq1Wb9+vbPP4XCwfv16GjRokOw+DRo0SLQ9wLp161LcXjJWWs4hwJtvvskrr7zC6tWrqVOnTmaUKslw9fxVrFiRPXv2sGvXLuejXbt23HPPPezatYuQkJDMLF9I27/BRo0acejQIed/QgD++OMPihYtqhCbydJy/mJiYpKE1ev/KTEMI+OKlXSR5XKMJZeYZSMLFy40fHx8jLlz5xr79u0z+vbta+TLl8+IiIgwDMMwevbsaYwYMcK5/ebNm41cuXIZb7/9trF//35jzJgxWn7LYq6ew9dff93w9vY2vvzyS+P06dPOx+XLl616Czmaq+fvv7RqgfVcPYcnTpww8ubNa/Tv3984ePCgsWLFCiMoKMh49dVXrXoLOZqr52/MmDFG3rx5jc8//9w4cuSIsXbtWqNs2bJG586drXoLOdrly5eNnTt3Gjt37jQAY/LkycbOnTuN48ePG4ZhGCNGjDB69uzp3P768lsvvPCCsX//fmPGjBlafsvdTZs2zShRooTh7e1t1K1b1/j555+dzzVr1szo1atXou2/+OILo3z58oa3t7dRpUoVY+XKlZlcsfyXK+ewZMmSBpDkMWbMmMwvXAzDcP3f4L8pyGYNrp7DLVu2GPXq1TN8fHyMMmXKGK+99pqRkJCQyVXLda6cv/j4eGPs2LFG2bJlDV9fXyMkJMR49tlnjX/++SfzCxdjw4YNyf5Ou37OevXqZTRr1izJPjVq1DC8vb2NMmXKGHPmzMn0uq+zGYbG8UVERETE/WiOrIiIiIi4JQVZEREREXFLCrIiIiIi4pYUZEVERETELSnIioiIiIhbUpAVEREREbekICsiIiIibklBVkRERETckoKsiAgwd+5c8uXLZ3UZt2Xs2LHUqFHjptscO3YMm83Grl27MqUmEZGMpCArItnGY489hs1mS/I4dOiQ1aVliqFDh7J+/Xpn+7HHHqNDhw6JtgkJCeH06dNUrVo1k6tLnebNmzNo0CCryxARN5HL6gJERNJTy5YtmTNnTqK+woULW1RN5sqTJw958uS56Taenp4UKVIkkyq6IT4+Hi8vr0w/rohkbxqRFZFsxcfHhyJFiiR6eHp6MnnyZKpVq0bu3LkJCQnh2Wef5cqVKym+zu7du7nnnnvImzcvAQEB1K5dm23btjmf37RpE02aNMHPz4+QkBAGDBhAdHT0TWuz2Wy8//77PPDAA/j5+VGmTBm+/PLLRNvs2bOHe++9Fz8/PwoWLEjfvn0T1blx40bq1q1L7ty5yZcvH40aNeL48eNA4qkFY8eO5ZNPPmHp0qXOkemNGzcmmlrgcDi44447eP/99xPVsHPnTjw8PJyve+nSJZ588kkKFy5MQEAA9957L7t3707xfV4/xqJFi2jWrBm+vr7Mnz+fCxcu0K1bN4oXL46/vz/VqlXj888/d+732GOP8cMPPzB16lRnzceOHQNg7969PPDAA+TJk4fg4GB69uzJ+fPnb/r9FpHsT0FWRHIEDw8P3n33XX7//Xc++eQTvv/+e4YNG5bi9j169OCOO+7g119/Zfv27YwYMcI5onj48GFatmxJp06d+O2331i0aBGbNm2if//+t6zj5ZdfplOnTuzevZsePXrQtWtX9u/fD0B0dDRhYWHkz5+fX3/9lcWLF/Pdd985XzchIYEOHTrQrFkzfvvtN8LDw+nbty82my3JcYYOHUrnzp1p2bIlp0+f5vTp0zRs2DDJ96Rbt24sWLAgUf/8+fNp1KgRJUuWBODhhx/m7NmzfPvtt2zfvp1atWpx3333cfHixZu+1xEjRjBw4ED2799PWFgY165do3bt2qxcuZK9e/fSt29fevbsydatWwGYOnUqDRo0oE+fPs6aQ0JCuHTpEvfeey81a9Zk27ZtrF69mjNnztC5c+dbfr9FJJszRESyiV69ehmenp5G7ty5nY+HHnoo2W0XL15sFCxY0NmeM2eOERgY6GznzZvXmDt3brL7PvHEE0bfvn0T9f3000+Gh4eHcfXq1RTrA4ynn346UV+9evWMZ555xjAMw/jwww+N/PnzG1euXHE+v3LlSsPDw8OIiIgwLly4YADGxo0bk339MWPGGNWrV3e2e/XqZbRv3z7RNkePHjUAY+fOnYZhGMbOnTsNm81mHD9+3DAMw7Db7Ubx4sWN999/3/m+AgICjGvXriV6nbJlyxoffPBBsnVcP8aUKVNS/F5c17p1a+P55593tps1a2YMHDgw0TavvPKK0aJFi0R9f/31lwEYBw8evOUxRCT70hxZEclW7rnnnkQflefOnRuA7777jokTJ3LgwAGioqJISEjg2rVrxMTE4O/vn+R1hgwZwpNPPsm8efMIDQ3l4YcfpmzZsoA57eC3335j/vz5zu0Nw8DhcHD06FG++eYbJkyY4Hxu3759lChRAoAGDRokOk6DBg2cKwjs37+f6tWrO2sGaNSoEQ6Hg4MHD9K0aVMee+wxwsLCuP/++wkNDaVz584ULVo0zd+vGjVqUKlSJRYsWMCIESP44YcfOHv2LA8//LDzvV65coWCBQsm2u/q1ascPnz4pq9dp06dRG273c6ECRP44osvOHnyJHFxccTGxib7/f+33bt3s2HDhmTn/x4+fJjy5cun5q2KSDakICsi2Uru3LkpV65cor5jx47Rpk0bnnnmGV577TUKFCjApk2beOKJJ4iLi0s2SI0dO5bu3buzcuVKvv32W8aMGcPChQvp2LEjV65c4amnnmLAgAFJ9itRogRPP/10oo+9ixUrlm7vb86cOQwYMIDVq1ezaNEiRo0axbp166hfv36aX7NHjx7OILtgwQJatmzpDK5XrlyhaNGibNy4Mcl+t1qu7N+BHOCtt95i6tSpTJkyxTlfedCgQcTFxd30da5cuULbtm154403kjx3OyFeRNyfgqyIZHvbt2/H4XAwadIkPDzMSwO++OKLW+5Xvnx5ypcvz+DBg+nWrRtz5syhY8eO1KpVi3379iUJzNcVKFCAAgUKJPvczz//zKOPPpqoXbNmTQAqVarE3LlziY6OdobAzZs34+HhQYUKFZz71KxZk5o1azJy5EgaNGjAggULkg2y3t7e2O32W77P7t27M2rUKLZv386XX37JzJkznc/VqlWLiIgIcuXKRalSpW75WjezefNm2rdvzyOPPAKAw+Hgjz/+oHLlyjetuVatWnz11VeUKlWKXLn0a0tEbtDFXiKS7ZUrV474+HimTZvGkSNHmDdvXqKw9l9Xr16lf//+bNy4kePHj7N582Z+/fVXKlWqBMDw4cPZsmUL/fv3Z9euXfz5558sXbo0VRd7LV68mNmzZ/PHH38wZswYtm7d6tyvR48e+Pr60qtXL/bu3cuGDRt47rnn6NmzJ8HBwRw9epSRI0cSHh7O8ePHWbt2LX/++aezrv8qVaoUv/32GwcPHuT8+fPEx8enuF3Dhg154oknsNvttGvXzvlcaGgoDRo0oEOHDqxdu5Zjx46xZcsWXnrppUSrOKTGnXfeybp169iyZQv79+/nqaee4syZM0lq+eWXXzh27Bjnz5/H4XDQr18/Ll68SLdu3fj11185fPgwa9asoXfv3qkK6iKSfSnIiki2V716dSZPnswbb7xB1apVmT9/PhMnTkxxe09PTy5cuMCjjz5K+fLl6dy5Mw888ADjxo0D4K677uKHH37gjz/+oEmTJtSsWZPRo0enagrBuHHjWLhwIXfddReffvopn3/+uXNE0t/fnzVr1nDx4kXuvvtuHnroIe677z6mT5/ufP7AgQN06tSJ8uXL07dvX/r168dTTz2V7LH69OlDhQoVqFOnDoULF2bz5s0p1tWjRw92795Nx44d8fPzc/bbbDZWrVpF06ZN6d27N+XLl6dr164cP36c4ODgW77ffxs1ahS1atUiLCyM5s2bU6RIkSQ3bBg6dCienp5UrlyZwoULc+LECYoVK8bmzZux2+20aNGCatWqMWjQIPLly+ccYReRnMlmGIZhdREiIjmBzWbjm2++SRLeREQkbfRfWRERERFxSwqyIiIiIuKWdPmniEgm0UwuEZH0pRFZEREREXFLCrIiIiIi4pYUZEVERETELSnIioiIiIhbUpAVEREREbekICsiIiIibklBVkRERETckoKsiIiIiLglBVkRERERcUv/A4WOl6j81jreAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Evaluating on untouched test set: LR_weighted\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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hS5cuCAoKumu/O0fQtFqt7iIUhUJRqf+91FTxen/++ScOHDiAHTt2YNeuXdi4cSMee+wx7Nmzp8rXrI/qnqdiJG/48OE4dOiQrj0kJETv4rKWLVvqPn+DBg2Cvb09pk6dikcffVQ3V1mr1aJLly5YsmRJla9Vl3mAmZmZCAwMhKWlJebNmwcvLy8YGxvjzJkzeO+992o9el2T9u3b4+zZs7h582ataqtuZF2j0VT5+b3za6nCqFGjsGDBAqSmpsLCwgK///47Ro8erfvDquLYXnjhhUpzaSvUZ154Xdjb2+vOd3BwMNq3b48nn3wSX3zxhd4ofG08/PDDWLBgAQoLC3H48GHMnDkT1tbW6Ny5Mw4fPgwnJycA0AuyWq0Wjz/+OKZNm1blc7Zt27aeR1bZ3b43atLYPx+IGgKDLNE98vLywr59+xAQEFDtL/fb9enTB3369MGCBQvw008/YcyYMdiwYQNefPHFOt8V6155eXlBCIHWrVvX+Muz4q3Jf/75p1aB+XZyuRz9+/dH//79sWTJEixcuBAzZ87EgQMHqnwud3d3AMDVq1crbbty5Qrs7e3rvGzY559/rjcCdbe1dSdPnoylS5figw8+wNNPPw2ZTAYvLy+cP38e/fv3r/E8eXl5QavV4tKlS/Dx8amyz8GDB5GWloYtW7agX79+uvaKVSYawpAhQ/Dzzz/jv//9b7VLsN3OxsamygXxb9y4UadRtVGjRmHu3Ln49ddf4eTkhOzsbDz33HO67Q4ODrCwsIBGo6nz11JjGTx4MAIDA7Fw4UJMnjy5Tl9fffv2RXFxMX7++WfExcXpAmu/fv10QbZt27a6QAuUfY3k5ubW+fgdHR1hbGyMiIiIStuqaqut6r6ea/vzoeJ79vr167qRdwAoKSlBdHQ0unXrVu/aiO6Gc2SJ7tHIkSOh0Wgwf/78SttKS0t14SAjI6PSKEhF0KlYvsnU1BQAmuwOO8OHD4dCocDcuXMr1SaEQFpaGgCgR48eaN26NZYtW1aptppGdtLT0yu13XnMd3J2doaPjw/Wr1+v91r//PMP9uzZg0GDBtXiyPT5+voiKChI97jb2/5GRkZ4++23cfnyZfz2228Ays5zXFwcvvnmm0r9CwoKkJeXBwAYNmwY5HI55s2bV2lkteJzVTG6dfvnrri4GF999VWdj606zzzzDLp06YIFCxYgPDy80vacnBzMnDlT97GXlxeOHz+uNwVj+/btVS6zVJMOHTqgS5cu2LhxIzZu3AhnZ2e9sK5QKDBixAj8+uuv+Oeffyrtn5KSovdxUyy/BQDvvfce0tLSqjy/NenduzeUSiUWL14MW1tbdOrUCUBZwD1+/DgOHTqkNxoLlH0thYeHY/fu3ZWeLzMzE6WlpVW+lkKhQFBQELZt26Z3V7aIiAi9pb3qqiK43/m9XdufDz179oSDgwNWrVql9/Wzbt063i2MGh1HZInuUWBgICZPnoxFixbh3LlzGDBgAJRKJa5fv45Nmzbhiy++wDPPPIP169fjq6++wtNPPw0vLy/k5OTgm2++gaWlpS6cmZiYoGPHjti4cSPatm0LW1tbdO7cuc5zU2vLy8sLH330EWbMmIGYmBgMGzYMFhYWiI6OxtatW/Hyyy/jnXfegVwu193tysfHBxMmTICzszOuXLmCixcvVvkLGQDmzZuHP//8E4MHD4a7uzuSk5Px1VdfoWXLllWubVrh008/xRNPPAE/Pz9MmjRJt/yWlZVVve87X1fjx4/HrFmzsHjxYgwbNgxjx47FL7/8gldeeQUHDhxAQEAANBoNrly5gl9++QW7d+9Gz5494e3tjZkzZ2L+/Pno27cvhg8fDrVajVOnTsHFxQWLFi2Cv78/bGxsEBISgtdffx0ymQw//PBDg17UpFQqsWXLFgQFBaFfv34YOXIkAgICoFQqcfHiRfz000+wsbHRrSX74osvYvPmzRg4cCBGjhyJyMhI/Pe//9W7UKi2Ro0ahVmzZsHY2BiTJk2qNB/6448/xoEDB9C7d2+89NJL6NixI9LT03HmzBns27dP7w+gui6/FRYWhsLCwkrtw4YNq/H76IknnkDnzp2xZMkSTJkypdZ3mjM1NYWvry+OHz+uW0MWKBuRzcvLQ15eXqUg++677+L333/Hk08+ifHjx8PX1xd5eXm4cOECNm/ejJiYGN0yWHeaM2cO9uzZg4CAALz66qvQaDT48ssv0blzZ5w7d65WNd/J19cXADBz5kw899xzUCqVGDJkSK1/PiiVSnz00UeYPHkyHnvsMYwaNQrR0dH47rvvOEeWGl/TLpJAJH13Lr9VYfXq1cLX11eYmJgICwsL0aVLFzFt2jQRHx8vhBDizJkzYvTo0aJVq1ZCrVYLR0dH8eSTT4q//vpL73mOHTsmfH19hUqluusySxVLIW3atKnGmiuWqapuGaxff/1VPPzww8LMzEyYmZmJ9u3biylTpoirV6/q9Tty5Ih4/PHHhYWFhTAzMxNdu3bVW8bnzuW3wsLCxFNPPSVcXFyESqUSLi4uYvTo0XrLDlW1/JYQQuzbt08EBAQIExMTYWlpKYYMGSIuXbpUq+P67rvvqlxOqCqoYdmlOXPmCADiwIEDQoiyZYYWL14sOnXqJNRqtbCxsRG+vr5i7ty5IisrS2/ftWvXiu7du+v6BQYGir179+q2Hz16VPTp00eYmJgIFxcXMW3aNLF792691xOi/stvVcjIyBCzZs0SXbp0EaampsLY2Fh07txZzJgxQyQkJOj1/fzzz4Wrq6tQq9UiICBA/PXXX9Uuv1XT19z169cFAAFAHDlypMo+SUlJYsqUKcLNzU0olUrRokUL0b9/f7F69Wq9fnVdfqu6xw8//CCEKFt+a/DgwVU+x7p166r8Wrybd999VwAQixcv1mv39vYWAERkZGSlfXJycsSMGTOEt7e3UKlUwt7eXvj7+4vPPvtMFBcX6/pVda7DwsJE9+7dhUqlEl5eXuLbb78Vb7/9tjA2NtbrV93XdlVLrc2fP1+4uroKuVxe6Xuntj8fvvrqK9G6dWuhVqtFz549xZ9//lnp64eoocmEaMRVpomIiKjRDRs2DBcvXsT169cNXQpRk+IcWSIiIgkpKCjQ+/j69evYuXOn3q2EiR4UHJElIiK6Q2JiYo3b71yLuCk5Oztj/Pjx8PT0xI0bN7By5UoUFRXh7Nmz1a75SnS/YpAlIiK6w92WwrtzLeKmNGHCBBw4cACJiYlQq9Xw8/PDwoUL0aNHD4PUQ2RIDLJERER32LdvX43bXVxc7rqMGxE1PgZZIiIiIpIkXuxFRERERJL0wN0QQavVIj4+HhYWFk1+O1AiIiIiqpkQAjk5OXBxcal0Q5U7PXBBNj4+Hm5uboYug4iIiIhqcPPmTbRs2bLGPg9ckLWwsABQ9smxtLQ0cDVEREREdLvs7Gy4ubnpMltNHrggWzGdwNLSkkGWiIiIqJmqzRRQXuxFRERERJLEIEtEREREksQgS0RERESS9MDNkSUiovuDRqNBSUmJocsgojpSKpVQKBQN8lwMskREJClCCCQmJiIzM9PQpRBRPVlbW6NFixb3vKY/gywREUlKRYh1dHSEqakpb25DJCFCCOTn5yM5ORkA4OzsfE/PxyBLRESSodFodCHWzs7O0OUQUT2YmJgAAJKTk+Ho6HhP0wx4sRcREUlGxZxYU1NTA1dCRPei4nv4Xue5M8gSEZHkcDoBkbQ11PcwgywRERERSRKDLBEREd1Xxo8fj2HDhjV4X2p+DBpk//zzTwwZMgQuLi6QyWTYtm3bXfc5ePAgevToAbVaDW9vb6xbt67R6yQiImoI4eHhUCgUGDx4sKFLua998cUXtc4HdelrSOnp6RgzZgwsLS1hbW2NSZMmITc3t9r+MTExkMlkVT42bdqk6/f666/D19cXarUaPj4+VT7X7t270adPH1hYWMDBwQEjRoxATEyMXp8VK1agQ4cOMDExQbt27fD99983xGHflUGDbF5eHrp164YVK1bUqn90dDQGDx6MRx99FOfOncObb76JF198Ebt3727kSomIiO7dmjVr8J///Ad//vkn4uPjG/W1hBAoLS1t1NdoaA1Vs5WVFaytrRu8ryGNGTMGFy9exN69e7F9+3b8+eefePnll6vt7+bmhoSEBL3H3LlzYW5ujieeeEKv78SJEzFq1Kgqnyc6OhpPPfUUHnvsMZw7dw67d+9Gamoqhg8fruuzcuVKzJgxA3PmzMHFixcxd+5cTJkyBf/73/8a5uBrIpoJAGLr1q019pk2bZro1KmTXtuoUaNEcHBwrV8nKytLABBZWVn1KZOIiAyooKBAXLp0SRQUFBi6lDrLyckR5ubm4sqVK2LUqFFiwYIFum2jR48WI0eO1OtfXFws7OzsxPr164UQQmg0GrFw4ULh4eEhjI2NRdeuXcWmTZt0/Q8cOCAAiJ07d4oePXoIpVIpDhw4ICIiIsTQoUOFo6OjMDMzEz179hR79+7Ve634+HgxaNAgYWxsLDw8PMSPP/4o3N3dxdKlS3V9MjIyxKRJk4S9vb2wsLAQjz76qDh37ly1xxsdHS0AiJ9//ln4+fkJtVotOnXqJA4ePHjXmu92rEII8c8//4jBgwcLCwsLYW5uLh5++GEREREhhBAiJCREPPXUU7q+mzZtEp07dxbGxsbC1tZW9O/fX+Tm5lbZt7CwUPznP/8RDg4OQq1Wi4CAAHHy5MlKNe/bt0/4+voKExMT4efnJ65cuVLt5+JeXbp0SQAQp06d0rX98ccfQiaTibi4uFo/j4+Pj5g4cWKV22bPni26detWqX3Tpk3CyMhIaDQaXdvvv/8uZDKZKC4uFkII4efnJ9555x29/UJDQ0VAQEC1tdT0vVyXrCapObLh4eEICgrSawsODkZ4eLiBKrq7M7EZ2P53PFJziwxdChHRfUcIgfziUoM8hBB1qvWXX35B+/bt0a5dO7zwwgtYu3at7jnGjBmD//3vf3pvFe/evRv5+fl4+umnAQCLFi3C999/j1WrVuHixYt466238MILL+DQoUN6rzN9+nR8/PHHuHz5Mrp27Yrc3FwMGjQIYWFhOHv2LAYOHIghQ4YgNjZWt8+4ceMQHx+PgwcP4tdff8Xq1at1C9ZXePbZZ5GcnIw//vgDp0+fRo8ePdC/f3+kp6fXeNzvvvsu3n77bZw9exZ+fn4YMmQI0tLSaqz5bscaFxeHfv36Qa1WY//+/Th9+jQmTpxY5WhuQkICRo8ejYkTJ+Ly5cs4ePAghg8fXu35mzZtGn799VesX78eZ86cgbe3N4KDgysd58yZM/H555/jr7/+gpGRESZOnFjj56FTp04wNzev9nHnKOntwsPDYW1tjZ49e+ragoKCIJfLceLEiRpft8Lp06dx7tw5TJo0qVb9K/j6+kIul+O7776DRqNBVlYWfvjhBwQFBUGpVAIAioqKYGxsrLefiYkJTp482ei3kZbUDRESExPh5OSk1+bk5ITs7GwUFBToFti9XVFREYqK/g2R2dnZjV7n7X46EYvNp28BANq3sICflx0CvOzRy9MWlsbKJq2FiOh+U1CiQcdZhpledmleMExVtf81umbNGrzwwgsAgIEDByIrKwuHDh3CI488guDgYJiZmWHr1q0YO3YsAOCnn37C0KFDYWFhgaKiIixcuBD79u2Dn58fAMDT0xNHjhzB119/jcDAQN3rzJs3D48//rjuY1tbW3Tr1k338fz587F161b8/vvvmDp1Kq5cuYJ9+/bh1KlTuqD07bffok2bNrp9jhw5gpMnTyI5ORlqtRoA8Nlnn2Hbtm3YvHlzjW9xT506FSNGjABQ9hb0rl27sGbNGkybNq3KmmtzrCtWrICVlRU2bNigC1Nt27at8vUTEhJQWlqK4cOHw93dHQDQpUuXKvvm5eVh5cqVWLdunS5YfvPNN9i7dy/WrFmDd999V9d3wYIFus/79OnTMXjwYBQWFlYKdBV27txZY6irKsNUSExMhKOjo16bkZERbG1tkZiYWO1+t1uzZg06dOgAf3//WvWv0Lp1a+zZswcjR47E5MmTodFo4Ofnh507d+r6BAcH49tvv8WwYcPQo0cPnD59Gt9++y1KSkqQmpp6z3fvqomkgmx9LFq0CHPnzjXY67e2N0MHZ0tcTsjGlcQcXEnMwXdHYyCXAV1aWiPAyw7+XvbwdbeBiar+d7YgIqLm6+rVqzh58iS2bt0KoCyEjBo1CmvWrMEjjzwCIyMjjBw5Ej/++CPGjh2LvLw8/Pbbb9iwYQMAICIiAvn5+XoBFQCKi4vRvXt3vbbbR+0AIDc3F3PmzMGOHTt0oa6goEA3Inv16lUYGRmhR48eun28vb1hY2Oj+/j8+fPIzc2tdDe1goICREZG1njsFWG04rh79uyJy5cvV1tzbY713Llz6Nu3ry7E1qRbt27o378/unTpguDgYAwYMADPPPOM3vFViIyMRElJCQICAnRtSqUSvXr1qlRz165ddf+vCGrJyclo1apVlXVUhGhDKCgowE8//YQPP/ywzvsmJibipZdeQkhICEaPHo2cnBzMmjULzzzzDPbu3QuZTIYPP/wQiYmJ6NOnD4QQcHJyQkhICD755BPI5Y375r+kgmyLFi2QlJSk15aUlARLS8tq/5KZMWMGQkNDdR9nZ2fDzc2tUeu83ZRHvTHlUW+k5RbheFQ6jkWm4lhkGqJT83D+ZibO38zEVwcjoVLI0b2VNQK87eHvZYdubtZQKiQ184OIqMmZKBW4NC/YYK9dW2vWrEFpaSlcXFx0bUIIqNVqfPnll7CyssKYMWMQGBiI5ORk7N27FyYmJhg4cCAA6KYc7NixA66urnrPXTFCWsHMzEzv43feeQd79+7FZ599Bm9vb5iYmOCZZ55BcXFxrevPzc2Fs7MzDh48WGlbQ1wodXvNtTnWmkYv76RQKLB3714cO3YMe/bswfLlyzFz5kycOHECrVu3rnfNt4foisX9tVpttf07deqEGzduVLu9b9+++OOPP6rc1qJFi0pTPUpLS5Geno4WLVrctdbNmzcjPz8f48aNu2vfO1WMfn/yySe6tv/+979wc3PDiRMn0KdPH5iYmGDt2rX4+uuvkZSUBGdnZ6xevVq3ykFjklSQvXMoGwD27t2r99fendRqdaVvckOwM1djcFdnDO5a9ldbfGYBwiPTcCwyDcciU5GQVYgT0ek4EZ2OJXsBU5UCvVrbwr98xLaDsyUUct7JhojodjKZrE5v7xtCaWkpvv/+e3z++ecYMGCA3rZhw4bh559/xiuvvAJ/f3+4ublh48aN+OOPP/Dss8/qwlLHjh2hVqsRGxurN42gNo4ePYrx48fr5trm5ubqLZ3Url07lJaW4uzZs/D19QVQNiqakZGh69OjRw8kJibCyMgIHh4edXr948ePo1+/frrPxenTpzF16tRq+9fmWLt27Yr169ejpKSkVqOyMpkMAQEBCAgIwKxZs+Du7o6tW7fqDXQBgJeXF1QqFY4ePaobQS0pKcGpU6fw5ptv1vKIq3YvUwv8/PyQmZmJ06dP687R/v37odVq0bt377u+9po1azB06NB6hcr8/PxKo6oKRdkfcXcGd6VSiZYtWwIANmzYgCeffPL+HpHNzc1FRESE7uPo6GicO3cOtra2aNWqFWbMmIG4uDjdWmSvvPIKvvzyS0ybNg0TJ07E/v378csvv2DHjh2GOoR6c7E2wQjflhjh2xJCCMSk5etGa8Mj05CeV4yDV1Nw8GoKAMDKRAk/Tzv4e9vB38sOXg7mvEUjEZEEbN++HRkZGZg0aRKsrKz0to0YMQJr1qzBK6+8AgB4/vnnsWrVKly7dg0HDhzQ9bOwsMA777yDt956C1qtFg8//DCysrJw9OhRWFpaIiQkpNrXb9OmDbZs2YIhQ4bo3ga+PYC0b98eQUFBePnll7Fy5UoolUq8/fbbMDEx0f2eCQoKgp+fH4YNG4ZPPvkEbdu2RXx8PHbs2IGnn3660nSG261YsQJt2rRBhw4dsHTpUmRkZNR4YVRtjnXq1KlYvnw5nnvuOcyYMQNWVlY4fvw4evXqhXbt2uk934kTJxAWFoYBAwbA0dERJ06cQEpKCjp06FDptc3MzPDqq6/i3Xff1WWRTz75BPn5+XW+SOpO9zK1oEOHDhg4cCBeeuklrFq1CiUlJZg6dSqee+453Sh/XFwc+vfvj++//x69evXS7RsREYE///yz0kDg7dtzc3ORmJiIgoICnDt3DkDZHxQqlQqDBw/G0qVLMW/ePN3Ugvfffx/u7u66qR7Xrl3DyZMn0bt3b2RkZGDJkiX4559/sH79+nofc63ddV2DRlSxhMWdj5CQECFE2ZIYgYGBlfbx8fERKpVKeHp6iu+++65OrymF5bc0Gq24FJ8lvj0cJSZ+d1J0mrVLuL+3Xe/x0Ed7xRs/nxEbT8aK2LQ8Q5dMRNQkpLj81pNPPikGDRpU5bYTJ04IAOL8+fNCiH+XWXJ3dxdarVavr1arFcuWLRPt2rUTSqVSODg4iODgYHHo0CEhxL+/UzMyMvT2i46OFo8++qgwMTERbm5u4ssvvxSBgYHijTfe0PWJj48XTzzxhFCr1cLd3V389NNPwtHRUaxatUrXJzs7W/znP/8RLi4uQqlUCjc3NzFmzBgRGxtb5bFVLL/1008/iV69egmVSiU6duwo9u/fr+tTXc13O1YhhDh//rwYMGCAMDU1FRYWFqJv374iMjJSCKG/pNalS5dEcHCwbjmttm3biuXLl+ue587ltwoKCsR//vMfYW9vX+PyW7fXfPbsWQFAREdHV/m5aAhpaWli9OjRwtzcXFhaWooJEyaInJwc3faKz/eBAwf09psxY4Zwc3PTWz7rdoGBgVVmsduP5eeffxbdu3cXZmZmwsHBQQwdOlRcvnxZt/3SpUvCx8dHmJiYCEtLS/HUU0/ddTmyhlp+SyZEHdcPkbjs7GxYWVkhKysLlpaWhi6nVko1WlyIy9JNQ/grJgNFpfrD+a1sTeHvZQe/8qkIDhaGn05BRNTQCgsLER0djdatW1d7dTjdu1u3bsHNzQ379u1D//796/UcMTExaN26Nc6ePVvtHaPowVXT93JdslrznlhEAAAjhRzdW9mgeysbTHnUG4UlGpyNzdRNRTh/MxOx6fmITc/HhlM3AQBtnczh72UPPy879PG0g5UJl/oiIqKq7d+/H7m5uejSpQsSEhIwbdo0eHh46Oa2EjVXDLISZKxUwK989PVtALlFpTgVk45jEWXB9lJCNq4l5eJaUi7WHStb6quzq5VutPYhD5tmf3EEERE1nZKSErz//vuIioqChYUF/P398eOPP9bqQioiQ+LUgvtQRl4xjkf9uyJCZEqe3nalQobubjZlN2fwtoePmzVURlzqi4iaP04tILo/cGoBVcvGTIUnujjjiS5lS30lZhUiPCoVxyLKwm1cZgFOxqTjZEw6vgi7DhOlAj09bODvZY8Abzt0crHiUl9ERETU7DHIPgBaWBnj6e4t8XT3sqW+YtPzy0dr0xAemYrU3GIcvp6Kw9dTAQAWxkbo42lXdtcxb3u0ceRSX0RERNT8MMg+YGQyGdztzOBuZ4bRvVpBCIFrSbm6C8eOR6Uhp7AUey8lYe+lsruo2Zury6YhlM+xdbM1YbAlIoOq6Q5KRNT8NdT3MOfIkh6NVuCf25b6OhWTjsIS/S82V2sTBHjb6VZFcLLkPDUiahparRbXr1+HQqGAg4MDVCoV/7AmkhAhBIqLi5GSkgKNRoM2bdpUuvtXXbIagyzVqKhUg3OxmbpgezY2E6Va/S8ZLwczBHjbw798qS9rU5WBqiWiB0FxcTESEhKQn59v6FKIqJ5MTU3h7OwMlapyZmCQrQGD7L3JLy7FqZiMsqkIEWn4Jz4Lt38FyWRAR2dLBHiXjdb28rCFmZozWIioYQkhUFpaCo1GY+hSiKiOFAoFjIyMqn03hUG2BgyyDSsrvwTHo9MQHpmGoxGpuJ6cq7fdSC6Dj5t1+V3H7NG9lTWMlQoDVUtERETNHYNsDRhkG1dyTiHCI9PKlvqKSsXN9AK97WojOR7ysC2/OYMdurhawUjBNWyJiIioDINsDRhkm9bN9HzdigjHItOQklOkt91CbYTenrbw8yqbY9vOyQJyrmFLRET0wGKQrQGDrOEIIRCZkoujEWUXjoVHpiG7sFSvj52ZCn3KR2v9vezhYWfKK5KJiIgeIAyyNWCQbT40WoHLCdk4GlE2YnsyOh0FJfoXbrhYGetGa/297eBsZWKgaomIiKgpMMjWgEG2+Sou1eL8rczyW+mWLfVVrNFfw9bT3qzs5gze9ujjaQdbMy71RUREdD9hkK0Bg6x0FBRr8NeNdN382gu3MnHHErbo4GwJfy87BHjb4SEPW1gYKw1TLBERETUIBtkaMMhKV1ZBCU5Gp+vm115JzNHbrpDL0LWlVVmw9bJHD3cbLvVFREQkMQyyNWCQvX+k5BTheFSa7q5jN9L07/KjMpLDt5UNArzL1rDt2tIKSi71RURE1KwxyNaAQfb+dSsjH+GR5TdniExFUrb+Ul9mKgV6tbbV3XWsQwtLLvVFRETUzDDI1oBB9sEghEBUal7ZaG1EKsKj0pCZX6LXx8ZUCb/yO475e9nB096MS30REREZGINsDRhkH0xarcDlxGzdrXRPRqcjr1h/qa8Wlsblt9K1g7+3PVytudQXERFRU2OQrQGDLAFAiUaLv29l4Vj5GranYzNQXKq/1Je7nSn8y0dr/bzsYG+uNlC1REREDw4G2RowyFJVCks0OHMjA0fLb6f7960saO5Y66udkwX8vcvuONbb0xaWXOqLiIiowTHI1oBBlmojp7AEp2LSy2+nm4bLCdl62+UyoEtL6/Jb6dqhp7stTFRc6ouIiOheMcjWgEGW6iM9rxjh5ct8hUemISo1T2+7SiFH91bWZVMRvO3QraU1VEZc6ouIiKiuGGRrwCBLDSEhq6D8Vrpl4TYhq1Bvu6lKgYc8bMtHbO3R0cUSCi71RUREdFcMsjVgkKWGJoRATFo+jpXPrw2PTEN6XrFeHysTJfp42sLfyx4B3nbwcjDnUl9ERERVYJCtAYMsNTatVuBqUk55qE3Fiah05BSV6vVxsFDrbqXr52UHN1tTA1VLRETUvDDI1oBBlppaqUaLC3FZutHaUzHpKLpjqS83WxP4e5bNr/XzsoOjhbGBqiUiIjIsBtkaMMiSoRWWaHA2NhPhkak4GpmG8zczUXrHUl9tHM3L5td626NPaztYmXKpLyIiejAwyNaAQZaam9yiUpyKSdfddexSQjZu/66UyYDOLla6YPuQhw1MVUaGK5iIiKgRMcjWgEGWmruMvGKciC5bEeFoRCoiU/SX+lIqZPBxs9bddcynlTXURlzDloiI7g8MsjVgkCWpScou1I3WHotMQ1xmgd52Y6W8fKmvsmDb2dWKS30REZFkMcjWgEGWpEwIgZvpBThWPr82PDIVqbn6S31ZGBuhj6edbg3btk5c6ouIiKSDQbYGDLJ0PxFC4Hpyrm609nhUGnIK9Zf6sjdXwa98tNbfyw6tbE0ZbImIqNlikK0BgyzdzzRagYvxWTgaUXbHsVMx6Sgs0V/qy9XapPzCsbIRWydLLvVFRETNB4NsDRhk6UFSVKrB+ZtZOBqRivDINJy9mYESjf63vJeDmW5+bR9PO9iYqQxULREREYNsjRhk6UGWX1yKUzEZOBZZFmwvxGVVWuqro7Olbn7tQ61tYa7mUl9ERNR0GGRrwCBL9K+s/BIcjy6749ixyFRcS8rV224kl6GbmzX8vcruONajlQ2MlVzqi4iIGg+DbA0YZImql5xTttRXWbBNQ2x6vt52tZEcPT1s4O9lDz8vO3R1tYKRQm6gaomI6H7EIFsDBlmi2ruZnq8brT0amYaUnCK97eZqI/RubQs/LzsEeNujnZMF5FzDloiI7gGDbA0YZInqRwiByJRc3R3HjkelI6ugRK+PrZkKfp7/rojgYcelvoiIqG4YZGvAIEvUMDRagcsJ2WWjtRFpOBWTjvxijV4fZyvjstFaL3v4e9vB2crEQNUSEZFUMMjWgEGWqHEUl2rx961M3Yjt2dhMFGv017BtbW+mC7Z9PG1hZ642ULVERNRcMcjWgEGWqGkUFGtw+kYGjkaW3XXswq1MaO/4adO+hQUCvMvWsO3V2hYWxkrDFEtERM0Gg2wNGGSJDCO7sAQnotJ1a9heSczR266Qy9C1pZVuDVtfdy71RUT0IGKQrQGDLFHzkJpbpFvmKzwyFTFp+kt9qYzk8G1lo7udbteW1lByqS8iovseg2wNGGSJmqe4zAIcK7+V7tHIVCRl6y/1ZaZSoFdrW90ath2dLbnUF1E9lWi0SMouRHxmIZws1XC3MzN0SUQ6DLI1YJAlav6EEIhKzdON1oZHpiEjX3+pL2tTZdlSX1528POyh5eDGZf6IgBlXz+lWvHAjuALIZCeV4z4zELEZxUgPrMACVmFiMssQEJmAeIzC5GcU6ibs65SyHH8/f6wNVMZtnCicgyyNWCQJZIerVbgcmK2birCiag05N2x1JeTpVo3WhvgbQ9Xay71dT+rCGsxaXmISc3HjbQ8RKeV/RuTmofCEi3+b3R3DOzcwtClNri8olIkZJUF0vjMAsRnFZaH1X/bikq1d30elUKuW1lkz1v90NbJ4q77aLWC74RQo6tLVjNqopqIiOpNLpehk4sVOrlY4cW+nijRaPH3rSyEl6+I8NeNDCRlF2Hr2ThsPRsHAHC3M9WN1vp72cGeS31JjhACqbnFZSE1NQ830vLLgmtaHm6k5iOnqLTG/U/FpEsyyGbll+BmRj5uZeTjZnoBbmXkIy6zAHGZhUjIKkDmHe9OVMfBQg0XaxO4WBmX/Xvb/52tjWFvpsZDC/YhLa8YQNkSeolZZaO4FaE4IasACZmFiM8q+39eUSk+GtYZox5q1ZifAqJaY5AlIslRKuTwdbeBr7sNpj7WBoUlGpy5kYFj5bfTPX8rCzfS8nEjLR8/n7wJAGjnZAE/r7KpCL097WBlwqW+movcolJEpeQiMiUXUSl5iEopD6tp+ci9S1h1sTKGh70Z3O3M0NreFO52Zth9MRFbzsTd9XWz8kvKXic9H22dzNG+RdO8S5dXVIqbt4VU3b8ZZf/mFNZ8zEDZ7aFdrKsIqFYmcLU2gZOVGmqj2q/68eyq8Ep36qvO0Yg0BllqNhhkiUjyjJUK+Hvbw9/bHkA75BSW4FRMOo5FpOFoZBouJ2TjalIOriblYN2xGMhlQBdXK/h52SPA2w493W1houJSX41JqxVIyC5EZHJueWjNQ2R5eL3zwr7byWSAi5UJPMpDams7M7jbmaK1vRncbE2rXKLt3M1MAIAQZatj3EirGM0tn3pQ/u/tI5tWJkqc/iAIRg0wr7awRINbGQVlo6rp+f/+P6MAN9PzK833roq9uQquNqZwszFBSxtTtLQpC6gVo6mWDbTmspOlMdLyinUhVm0kLw/ExnC2MoGLddm/ztbGOBaRim8OR+v2FUIgI79ENwe38ihuAdo4mmNNyEOcjkCNhnNkiei+l55XjONRZXccC49MQ1Rqnt52pUKG7uVLfQV426NbS2uojB7MC4XuVUGxBlGpZSOrkRWBNTkX0al5KCjRVLufvbkKng7m8HIwh6e9GVrbm8HD3hQtbaoOqzVZvOsKVh6MhExWFmZrYm+uQmpu2VvrV+YPrNVrCSGQllesF5Bjy0d2b2UUICWn+mBewcpECTdbE7iVh1Q32/J/bUzhamMCU1XTjDMlZxfiQlwWnCzLRnRtTJXVXjS59kg05m2/BBtTJaxNVUjIKkBhyd3n4h6e9ijcbE0bunS6j3GOLBHRbWzNVBjUxRmDujgDABKyCsqW+Yoom4qQkFWIk9HpOBmdjmX7rsNEqcBDrW0RUH5zho4ullBwRElPYYkGEcm5uJaUg2tJFf/m4FZGQbX7GMllcLczhZeDObwcywKrl6M5vOzNYWXacFM9WtqUXegnxL8juu52ZSO6Hnamuv+725lCK4DOs3dXeg6tViAxu7B8ikrZKG5setmFZbHpd5/yYK42Qsvy0VQ32/J/K0ZXbU0abET1XjlaGqO/pXGt+tqYldWckV+iN6psb66qchT37V/O692mOr+4VHcxmt7obfnFavnFGix4ujMea+/UsAdJ9zWOyBLRA00IgRtp+ThWvn5teGQa0ssvfqlgaWyEPp52utvpejuaPzBLfRWXahGdmoerSTm4npSDq4k5uJ6cixtpeZVuOVzB2lRZFlYdzHSjrF4OZVMBmmJJLI1W4EJcFszViruO6OYWleqCbIifO+IyC8rCa3o+imu48r8iILeyNYWHvSla2ZYF44oRVusaRjalqqhUg+3nEyCTQRdYW1gZVzsXt8OHu1BQooGngxnScotrNQf3uYfc8PGIrg1dOkkMR2SJiGpJJpPBw94MHvZmeL53K2i1AteSc3A0omwN2xNR6cguLMWeS0nYcykJAGBvri6fhlA2Yns/vG1aqtEiJi2/LKwm5eB6+ShrdGoeSqtJrNamSrR1skBbJ3O0c7JAGycLtHE0h52BV4hQyGXwcbOuXd/bwub68Bt624zkMrjZmpaFVTtTtLptRLc+Ux6kTm2kwAjflrXub2umQlxmAaJS/p3KU3GRmt78WytjhEel1eoCPaI7McgSEd1GLpehfQtLtG9hiUkPt0apRosLcVnlN2dIw6mYdKTmFuH38/H4/Xw8gLK3sgO87OHvbQc/Tzs41vKtWkPJKSzBlcQcXIrPLnuUXwxX3QikhdoIbZzM0a6FBdo4WpT962QOB3O15EcdTVQKTBvYDudiM+F+W1j1sDODs5Vxg1z89aBaM74nzsVmwsnKGC5WNV+kllyLecVEVWGQJSKqgZFCju6tbNC9lQ2mPOqNolINztzI1K1he+5mJm5lFGDjXzex8a+ypb68Hc0RUL6GbR9PW1ibGuaOSUIIJGQV6sLqpfhsXE7Mxo20/Cr7mygVaOtkjjZOFuUjrOZo62QBZytjyQfWmrz2iLehS7gvVfxBSNSYGGSJiOpAbaSAn5cd/LzsEIqyNUFPxqSX33UsFRfjsxGRnIuI5FysD78BmQzo7GJVfnMGOzzkYQszdcP/6C3RaBGRnFsptFa3eL6LlTE6OFuio4slOpb/62ZjymWSiEhSGGSJiO6BmdoIj7ZzxKPtHAEAmfllS30dK7+dbkRyLi7EZeFCXBa+/jMKRnIZurey1t1xrHsr6zotXA+UXYB1NTEHf8dl4sKtsue+npSrd4V4BSO5DN6O5rqw2tHZEh2cLWFjZphRYiKihsQgS0TUgKxNVRjY2RkDO5ct9ZWUXagbrT0akYa4zAKcisnAqZgM/F/YdRgr5XjIw7b8rmP26OxiqTcvs0SjxbWkHPwTl4W/y0PrlYScKkOrhbGRLqhWhNY2TuZ1DspERFLBIEtE1IicLI0xrLsrhnV3hRACN9MLcKx8fu2xyDSk5hbh8PVUHL6eCuAqLIyN0Lu1HVpYqfFPXNk0gaouwrI2VaKLqxW6trRCF1crdHKxQksbk/t6LisR0Z0MHmRXrFiBTz/9FImJiejWrRuWL1+OXr16Vdt/2bJlWLlyJWJjY2Fvb49nnnkGixYtgrFx875KmIhIJpOhlZ0pWtm1wnO9WkEIgevJuTgWkYqjkWk4HpWGnMJS7LucpLefhbERurhaoUtLK3R1tUbXlgytRESAgYPsxo0bERoailWrVqF3795YtmwZgoODcfXqVTg6Olbq/9NPP2H69OlYu3Yt/P39ce3aNYwfPx4ymQxLliwxwBEQEdWfTCYrX4fVAuMDWkOjFbgYn4WjEWnIzC9GRxdLdG1pDXdbXoRFRFQVgwbZJUuW4KWXXsKECRMAAKtWrcKOHTuwdu1aTJ8+vVL/Y8eOISAgAM8//zwAwMPDA6NHj8aJEyeatG4iosagkMvQtaU1ura0NnQpRESSYLCVnouLi3H69GkEBQX9W4xcjqCgIISHh1e5j7+/P06fPo2TJ08CAKKiorBz504MGjSo2tcpKipCdna23oOIiIiIpM9gI7KpqanQaDRwcnLSa3dycsKVK1eq3Of5559HamoqHn74YQghUFpaildeeQXvv/9+ta+zaNEizJ07t0FrJyIiIiLDk9S99w4ePIiFCxfiq6++wpkzZ7Blyxbs2LED8+fPr3afGTNmICsrS/e4efNmE1ZMRERERI3FYCOy9vb2UCgUSErSvzo3KSkJLVq0qHKfDz/8EGPHjsWLL74IAOjSpQvy8vLw8ssvY+bMmZDLK+dytVoNtVrd8AdARERERAZlsBFZlUoFX19fhIWF6dq0Wi3CwsLg5+dX5T75+fmVwqpCUbbQtxCi8YolIiIiombHoKsWhIaGIiQkBD179kSvXr2wbNky5OXl6VYxGDduHFxdXbFo0SIAwJAhQ7BkyRJ0794dvXv3RkREBD788EMMGTJEF2iJiIiI6MFg0CA7atQopKSkYNasWUhMTISPjw927dqluwAsNjZWbwT2gw8+gEwmwwcffIC4uDg4ODhgyJAhWLBggaEOgYiIiIgMRCYesPfks7OzYWVlhaysLFhaWhq6HCIiogfeigMR+HT3VTz3kBs+HtG10vacwhLcSMtHbHq+7t+OzhYY6+fR9MVSo6tLVjP4LWqJiIiIACAhqxCbT99CbFoebtwWWtPziiv1lcmAoT6usDJRGqBSai4YZImIiKhZOHQtBYeupVS5zc5MhVZ2pmhla4rfzsVDCKBEo23iCqm5YZAlIiIig/L3soOjhRoqIznc7UzRytYM7namcLc11YVXC+N/R15/OxdvwGqpOWGQJSIiIoPq3soGJ2cG3b0j0R0kdWcvIiIiIqIKDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJElGhi6AiIiIqL7yikpxLSkH15JyEJOWjwEdndC9lY2hy6ImwiBLREREkjR0+RHEZxXqtR2PSsPW1wIMVBE1NU4tICIiIkmxMlECgC7EOlio0b6FBQAgv0hjsLqo6XFEloiIiCRl7fiHcCk+C96OFmjXwgK2Zioci0jF89+eMHRp1MQYZImIiEhSfN1t4OvOebDEqQVEREREJFEMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkMskREREQkSQyyRERERCRJDLJEREREJEkGD7IrVqyAh4cHjI2N0bt3b5w8ebLG/pmZmZgyZQqcnZ2hVqvRtm1b7Ny5s4mqJSIiIqLmwsiQL75x40aEhoZi1apV6N27N5YtW4bg4GBcvXoVjo6OlfoXFxfj8ccfh6OjIzZv3gxXV1fcuHED1tbWTV88ERERERmUQYPskiVL8NJLL2HChAkAgFWrVmHHjh1Yu3Ytpk+fXqn/2rVrkZ6ejmPHjkGpVAIAPDw8mrJkIiIiImomDDa1oLi4GKdPn0ZQUNC/xcjlCAoKQnh4eJX7/P777/Dz88OUKVPg5OSEzp07Y+HChdBoNNW+TlFREbKzs/UeRERERCR9Bguyqamp0Gg0cHJy0mt3cnJCYmJilftERUVh8+bN0Gg02LlzJz788EN8/vnn+Oijj6p9nUWLFsHKykr3cHNza9DjICIiIiLDMPjFXnWh1Wrh6OiI1atXw9fXF6NGjcLMmTOxatWqaveZMWMGsrKydI+bN282YcVERERE1FgMNkfW3t4eCoUCSUlJeu1JSUlo0aJFlfs4OztDqVRCoVDo2jp06IDExEQUFxdDpVJV2ketVkOtVjds8URERERkcAYbkVWpVPD19UVYWJiuTavVIiwsDH5+flXuExAQgIiICGi1Wl3btWvX4OzsXGWIJSIiIqL7l0GnFoSGhuKbb77B+vXrcfnyZbz66qvIy8vTrWIwbtw4zJgxQ9f/1VdfRXp6Ot544w1cu3YNO3bswMKFCzFlyhRDHQIRERERGYhBl98aNWoUUlJSMGvWLCQmJsLHxwe7du3SXQAWGxsLufzfrO3m5obdu3fjrbfeQteuXeHq6oo33ngD7733nqEOgYiIiIgMRCaEEIYuoillZ2fDysoKWVlZsLS0NHQ5RERE1ACORaTi+W9PoJ2TBXa/1c/Q5dA9qEtWk9SqBUREREREFRhkiYiIiEiS6jVHVqPRYN26dQgLC0NycrLeKgIAsH///gYpjoiIiIioOvUKsm+88QbWrVuHwYMHo3PnzpDJZA1dFxERERFRjeoVZDds2IBffvkFgwYNauh6iIiIiIhqpV5zZFUqFby9vRu6FiIiIiKiWqtXkH377bfxxRdf4AFbuYuIiIiImpF6TS04cuQIDhw4gD/++AOdOnWCUqnU275ly5YGKY6IiIiIqDr1CrLW1tZ4+umnG7oWIiIiIqJaq1eQ/e677xq6DiIiIiKiOqlXkK2QkpKCq1evAgDatWsHBweHBimKiIiIiOhu6nWxV15eHiZOnAhnZ2f069cP/fr1g4uLCyZNmoT8/PyGrpGIiIiIqJJ6BdnQ0FAcOnQI//vf/5CZmYnMzEz89ttvOHToEN5+++2GrpGIiIiIqJJ6TS349ddfsXnzZjzyyCO6tkGDBsHExAQjR47EypUrG6o+IiIiojpLzS3CxfhsXIrPRmpuESYEeKCljSmEELiZXoBLCVmQy2R4vKMT71AqYfUKsvn5+XBycqrU7ujoyKkFREREZDAxaXnovXAfkrKL9NrXHIlGr9a2uByfjZyiUl37r6/6w9fdpqnLpAZSr6kFfn5+mD17NgoLC3VtBQUFmDt3Lvz8/BqsOCIiIqLasDAuW9O+qFSLpOwiyGSAp72ZXp+T0enIKSqFSiGHSlEWgdLzipu8Vmo49RqR/eKLLxAcHIyWLVuiW7duAIDz58/D2NgYu3fvbtACiYiIiO6ms6slFo/ogqJSLTo6W6KDsyXM1Ea4mZ6PpXuvwcZMhY7OlujkagkvB3M8uyoc525mGrpsukf1CrKdO3fG9evX8eOPP+LKlSsAgNGjR2PMmDEwMTFp0AKJiIiI7kYmk2HUQ60qtbvZmmLJKJ+mL4iaRL3XkTU1NcVLL73UkLUQEREREdVarYPs77//jieeeAJKpRK///57jX2HDh16z4UREREREdWk1kF22LBhSExMhKOjI4YNG1ZtP5lMBo1G0xC1ERERERFVq9ZBVqvVVvl/IiIiIiJDqNfyW1XJzMxsqKciIiIiIrqregXZxYsXY+PGjbqPn332Wdja2sLV1RXnz59vsOKIiIiIiKpTryC7atUquLm5AQD27t2Lffv2YdeuXXjiiSfw7rvvNmiBRERERI1JCIHYtHzs+icBS/dew+6LiYYuiWqpXstvJSYm6oLs9u3bMXLkSAwYMAAeHh7o3bt3gxZIRERE1FgW7ryM0I3n9G5bqzKS48KcAVAbKQxYGdVGvUZkbWxscPPmTQDArl27EBQUBKDsLxquWEBERETNnbm6bCwvOjVPd9vaDs6WAIDiUi00WmHI8qiW6jUiO3z4cDz//PNo06YN0tLS8MQTTwAAzp49C29v7wYtkIiIiKihzRjUHrv/SYSHvRk6upTdtrZUI9Bh1i5Dl0Z1UK8gu3TpUnh4eODmzZv45JNPYG5uDgBISEjAa6+91qAFEhERETW0Ti5W6ORipddWyneVJadeQVapVOKdd96p1P7WW2/dc0FERERERLXBW9QSERERkSTxFrVEREREd1Gi0UKpaLD7SFED4S1qiYiIiO6w73IyolJycTkhG5cSsnErowCvBHrhvYHtDV0a3aZec2SJiIiI7mev/3y2Ult4ZJoBKqGa1GuM/PXXX8f//d//VWr/8ssv8eabb95rTURERERNzlgph6+7DZQKGTo4W2JEj5b4YHAHvNG/jaFLo2rUa0T2119/rfKCL39/f3z88cdYtmzZvdZFRERE1KRkMhk2v+IHjVbA6Lb5sPsuJRmwKqpJvYJsWloarKysKrVbWloiNTX1nosiIiIiMgSZTAYjhczQZVAt1Wtqgbe3N3btqnzniz/++AOenp73XBQRERER0d3Ua0Q2NDQUU6dORUpKCh577DEAQFhYGD7//HNOKyAiIiKiJlGvIDtx4kQUFRVhwYIFmD9/PgDAw8MDK1euxLhx4xq0QCIiIiKiqtR7+a1XX30Vr776KlJSUmBiYgJzc/OGrIuIiIiIqEb1vkVFaWkp9u3bhy1btkAIAQCIj49Hbm5ugxVHRERERFSdeo3I3rhxAwMHDkRsbCyKiorw+OOPw8LCAosXL0ZRURFWrVrV0HUSEREREemp14jsG2+8gZ49eyIjIwMmJia69qeffhphYWENVhwRERERUXXqNSJ7+PBhHDt2DCqVSq/dw8MDcXFxDVIYEREREVFN6jUiq9VqodFoKrXfunULFhYW91wUEREREdHd1CvIDhgwQG+9WJlMhtzcXMyePRuDBg1qqNqIiIiIiKpVr6kFn332GQYOHIiOHTuisLAQzz//PK5fvw57e3v8/PPPDV0jEREREVEl9Qqybm5uOH/+PDZu3Ijz588jNzcXkyZNwpgxY/Qu/iIiIiIiaix1DrIlJSVo3749tm/fjjFjxmDMmDGNURcRERERUY3qPEdWqVSisLCwMWohIiIiIqq1el3sNWXKFCxevBilpaUNXQ8RERERUa3Ua47sqVOnEBYWhj179qBLly4wMzPT275ly5YGKY6IiIiIqDr1CrLW1tYYMWJEQ9dCRERERFRrdQqyWq0Wn376Ka5du4bi4mI89thjmDNnDlcqICIiIqImV6c5sgsWLMD7778Pc3NzuLq64v/+7/8wZcqUxqqNiIiIiKhadQqy33//Pb766ivs3r0b27Ztw//+9z/8+OOP0Gq1jVUfEREREVGV6hRkY2Nj9W5BGxQUBJlMhvj4+AYvjIiIiIioJnUKsqWlpTA2NtZrUyqVKCkpadCiiIiIiIjupk4XewkhMH78eKjVal1bYWEhXnnlFb0luLj8FhERERE1tjoF2ZCQkEptL7zwQoMVQ0RERERUW3UKst99911j1UFEREREVCf1ukVtQ1uxYgU8PDxgbGyM3r174+TJk7Xab8OGDZDJZBg2bFjjFkhEREREzY7Bg+zGjRsRGhqK2bNn48yZM+jWrRuCg4ORnJxc434xMTF455130Ldv3yaqlIiIiIiaE4MH2SVLluCll17ChAkT0LFjR6xatQqmpqZYu3ZttftoNBqMGTMGc+fOhaenZxNWS0RERETNhUGDbHFxMU6fPo2goCBdm1wuR1BQEMLDw6vdb968eXB0dMSkSZOaokwiIiIiaobqdLFXQ0tNTYVGo4GTk5Neu5OTE65cuVLlPkeOHMGaNWtw7ty5Wr1GUVERioqKdB9nZ2fXu14iIiIiaj4MPrWgLnJycjB27Fh88803sLe3r9U+ixYtgpWVle7h5ubWyFUSERERUVMw6Iisvb09FAoFkpKS9NqTkpLQokWLSv0jIyMRExODIUOG6Nq0Wi0AwMjICFevXoWXl5fePjNmzEBoaKju4+zsbIZZIiIiovuAQYOsSqWCr68vwsLCdEtoabVahIWFYerUqZX6t2/fHhcuXNBr++CDD5CTk4MvvviiyoCqVqv17kRGRERERPcHgwZZAAgNDUVISAh69uyJXr16YdmyZcjLy8OECRMAAOPGjYOrqysWLVoEY2NjdO7cWW9/a2trAKjUTkRERET3N4MH2VGjRiElJQWzZs1CYmIifHx8sGvXLt0FYLGxsZDLJTWVl4iIiIiagEwIIQxdRFPKzs6GlZUVsrKyYGlpaehyiIiIqJnbdykJL37/F3zcrLFtSoChy7nv1SWrcaiTiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkqVkE2RUrVsDDwwPGxsbo3bs3Tp48WW3fb775Bn379oWNjQ1sbGwQFBRUY38iIiIiuj8ZPMhu3LgRoaGhmD17Ns6cOYNu3bohODgYycnJVfY/ePAgRo8ejQMHDiA8PBxubm4YMGAA4uLimrhyIiIiIjIkgwfZJUuW4KWXXsKECRPQsWNHrFq1Cqampli7dm2V/X/88Ue89tpr8PHxQfv27fHtt99Cq9UiLCysiSsnIiIiIkMyaJAtLi7G6dOnERQUpGuTy+UICgpCeHh4rZ4jPz8fJSUlsLW1rXJ7UVERsrOz9R5EREREJH0GDbKpqanQaDRwcnLSa3dyckJiYmKtnuO9996Di4uLXhi+3aJFi2BlZaV7uLm53XPdRERERGR4Bp9acC8+/vhjbNiwAVu3boWxsXGVfWbMmIGsrCzd4+bNm01cJRERERE1BiNDvri9vT0UCgWSkpL02pOSktCiRYsa9/3ss8/w8ccfY9++fejatWu1/dRqNdRqdYPUS0RERETNh0FHZFUqFXx9ffUu1Kq4cMvPz6/a/T755BPMnz8fu3btQs+ePZuiVCIiIiJqZgw6IgsAoaGhCAkJQc+ePdGrVy8sW7YMeXl5mDBhAgBg3LhxcHV1xaJFiwAAixcvxqxZs/DTTz/Bw8NDN5fW3Nwc5ubmBjsOIiIiImpaBg+yo0aNQkpKCmbNmoXExET4+Phg165dugvAYmNjIZf/O3C8cuVKFBcX45lnntF7ntmzZ2POnDlNWToRERERGZDBgywATJ06FVOnTq1y28GDB/U+jomJafyCiIiIiKjZk/SqBURERET04GKQJSIiIiJJYpAlIiIiIklikCUiIiIiSWKQJSIiIiJJYpAlIiIiIklikCUiIiIiSWoW68gSERERNXfnbmZi6d5rSM4pQkpOIZJzilCqEVg8oiu6tLQydHkPJAZZIiIiohooFDLd/78Iu15p+66LCQyyBsIgS0RERFSDPq3tMMzHBblFpXCwMIaTpRqOFsbYeykRB66mQAhDV/jgYpAlIiIiqoGJSoFlz3Wv1H49OQe4mmKAiqgCL/YiIiIiIklikCUiIiIiSWKQJSIiImoghSUaxGUWICu/xNClPBA4R5aIiIjoHnx1MBI7LyQgLbcYOUWlAACVQo6D7z4CF2sTA1d3f+OILBEREVE92Jurdf+PScvXhVgAKNZoEZ2aZ4iyHigckSUiIiKqh/H+HmhpYwKlQg57czXszFWwN1dj5KpwXE3KMXR5DwQGWSIiIqJ6MFMb4Skf10rtMlkVnalRcGoBEREREUkSgywRERERSRKDLBERERFJEoMsEREREUkSgywRERERSRKDLBERERFJEoMsEREREUkSgywRERERSRKDLBERERFJEoMsEREREUkSgywRERERSRKDLBERERFJEoMsEREREUkSgywRERERSRKDLBERERFJEoMsERERUSMSQqCgWIPknEJotMLQ5dxXjAxdABEREdH9aMy3J2BlokRuUakuwHZraYXfpj5s4MruHxyRJSIiImpALtYmuv9nFZTojcKev5VliJLuWxyRJSIiImpAy0d3x/mbmTBRKWBhbAQLYyWKS7Xo+8kBQ5d232GQJSIiImpAZmoj+Hvb67Wl5RYZqJr7G6cWEBEREZEkMcgSERERkSQxyBIRERGRJDHIEhEREZEkMcgSERERkSQxyBIRERGRJDHIEhEREZEkMcgSERERkSQxyBIRERGRJDHIEhEREZEkMcgSERERkSQxyBIRERGRJDHIEhEREZEkMcgSERERkSQxyBIRERGRJDHIEhEREZEkMcgSERERkSQxyBIRERGRJDHIEhEREZEkMcgSERERkSQxyBIRERGRJBkZugAiIiKiB8kjnx6ARghoNAIaIVBQrEGXllZ4untLaLVlbRqtgIWxEYI7tYCxUmHokpstBlkiIiKiRmZubARrUyUy80sQk5ZfafvRiDQcjUirct92ThbQirKAq9UKuNuZYfU4X6iNGHAZZImIiIgamdpIgb1vBSIyJRcKuazsIZMhv1iDZfuuQWUkh1xW1i6XybDvcpJu36tJOXrPFZOWj0vx2ejeyqapD6PZaRZBdsWKFfj000+RmJiIbt26Yfny5ejVq1e1/Tdt2oQPP/wQMTExaNOmDRYvXoxBgwY1YcVEREREdeNgoYaDhbpSu5+XX6W2Uo0Wp29koKhUqwu3chnwn5/PIjmnCKIpCpYAgwfZjRs3IjQ0FKtWrULv3r2xbNkyBAcH4+rVq3B0dKzU/9ixYxg9ejQWLVqEJ598Ej/99BOGDRuGM2fOoHPnzgY4AiIiIqKGZaSQo7enXaX2ivmyO/9OQHxmAYQABAAhBHp62MLV2qSJKzUsmRDCoKG+d+/eeOihh/Dll18CALRaLdzc3PCf//wH06dPr9R/1KhRyMvLw/bt23Vtffr0gY+PD1atWnXX18vOzoaVlRWysrJgaWnZcAdCRERE1Mge++wgolLzqt3+rG9LyGUyyGSATAYAZSO5Mhkg0/1fhvS8YnRvZQ0zdfmYZnka9HI0h6+7Yacs1CWrGXREtri4GKdPn8aMGTN0bXK5HEFBQQgPD69yn/DwcISGhuq1BQcHY9u2bY1ZKhEREZHBTX3MGxtO3SwLnjJABiCroARXEsvm0W46favWz/X7+fgq2x0s1HCyVOP2oc7hPVpi0sOt76HyxmHQIJuamgqNRgMnJye9dicnJ1y5cqXKfRITE6vsn5iYWGX/oqIiFBUV6T7Ozs6+x6qJiIiIDGN4j5YY3qNlpfY/r6Xgn/gsXfgUQkAIQCsAAaE3BeGfuCzkFWlgqlZAVr6/TCbD/ivJAICUnCKk5BTpPX9SdgSDrCEsWrQIc+fONXQZRERERI2mX1sH9GvrcE/PkVVQgrOxGXpt2YWlOBGVhl6tbe/puRuLQYOsvb09FAoFkpKS9NqTkpLQokWLKvdp0aJFnfrPmDFDbypCdnY23Nzc7rFyIiIiovuLlYkSj7SrfKH90G4uBqimdgx6i1qVSgVfX1+EhYXp2rRaLcLCwuDnV3kpCgDw8/PT6w8Ae/furba/Wq2GpaWl3oOIiIiIpM/gUwtCQ0MREhKCnj17olevXli2bBny8vIwYcIEAMC4cePg6uqKRYsWAQDeeOMNBAYG4vPPP8fgwYOxYcMG/PXXX1i9erUhD4OIiIiImpjBg+yoUaOQkpKCWbNmITExET4+Pti1a5fugq7Y2FjI5f8OHPv7++Onn37CBx98gPfffx9t2rTBtm3buIYsERER0QPG4OvINjWuI0tERETUfNUlqxl0jiwRERERUX0xyBIRERGRJDHIEhEREZEkMcgSERERkSQxyBIRERGRJDHIEhEREZEkMcgSERERkSQxyBIRERGRJDHIEhEREZEkMcgSERERkSQxyBIRERGRJBkZuoCmJoQAUHYfXyIiIiJqXioyWkVmq8kDF2RzcnIAAG5ubgauhIiIiIiqk5OTAysrqxr7yERt4u59RKvVIj4+HhYWFpDJZI3+etnZ2XBzc8PNmzdhaWnZ6K9HDY/nUNp4/qSP51DaeP6kr6nPoRACOTk5cHFxgVxe8yzYB25EVi6Xo2XLlk3+upaWlvwGljieQ2nj+ZM+nkNp4/mTvqY8h3cbia3Ai72IiIiISJIYZImIiIhIkhhkG5larcbs2bOhVqsNXQrVE8+htPH8SR/PobTx/Elfcz6HD9zFXkRERER0f+CILBERERFJEoMsEREREUkSgywRERERSRKDbANYsWIFPDw8YGxsjN69e+PkyZM19t+0aRPat28PY2NjdOnSBTt37myiSqk6dTmH33zzDfr27QsbGxvY2NggKCjoruecGlddvwcrbNiwATKZDMOGDWvcAumu6noOMzMzMWXKFDg7O0OtVqNt27b8WWpAdT1/y5YtQ7t27WBiYgI3Nze89dZbKCwsbKJq6XZ//vknhgwZAhcXF8hkMmzbtu2u+xw8eBA9evSAWq2Gt7c31q1b1+h1VkvQPdmwYYNQqVRi7dq14uLFi+Kll14S1tbWIikpqcr+R48eFQqFQnzyySfi0qVL4oMPPhBKpVJcuHChiSunCnU9h88//7xYsWKFOHv2rLh8+bIYP368sLKyErdu3WriykmIup+/CtHR0cLV1VX07dtXPPXUU01TLFWpruewqKhI9OzZUwwaNEgcOXJEREdHi4MHD4pz5841ceUkRN3P348//ijUarX48ccfRXR0tNi9e7dwdnYWb731VhNXTkIIsXPnTjFz5kyxZcsWAUBs3bq1xv5RUVHC1NRUhIaGikuXLonly5cLhUIhdu3a1TQF34FB9h716tVLTJkyRfexRqMRLi4uYtGiRVX2HzlypBg8eLBeW+/evcXkyZMbtU6qXl3P4Z1KS0uFhYWFWL9+fWOVSDWoz/krLS0V/v7+4ttvvxUhISEMsgZW13O4cuVK4enpKYqLi5uqRKpBXc/flClTxGOPPabXFhoaKgICAhq1Trq72gTZadOmiU6dOum1jRo1SgQHBzdiZdXj1IJ7UFxcjNOnTyMoKEjXJpfLERQUhPDw8Cr3CQ8P1+sPAMHBwdX2p8ZVn3N4p/z8fJSUlMDW1raxyqRq1Pf8zZs3D46Ojpg0aVJTlEk1qM85/P333+Hn54cpU6bAyckJnTt3xsKFC6HRaJqqbCpXn/Pn7++P06dP66YfREVFYefOnRg0aFCT1Ez3prnlGCODvOp9IjU1FRqNBk5OTnrtTk5OuHLlSpX7JCYmVtk/MTGx0eqk6tXnHN7pvffeg4uLS6VvbGp89Tl/R44cwZo1a3Du3LkmqJDupj7nMCoqCvv378eYMWOwc+dORERE4LXXXkNJSQlmz57dFGVTufqcv+effx6pqal4+OGHIYRAaWkpXnnlFbz//vtNUTLdo+pyTHZ2NgoKCmBiYtKk9XBElugefPzxx9iwYQO2bt0KY2NjQ5dDd5GTk4OxY8fim2++gb29vaHLoXrSarVwdHTE6tWr4evri1GjRmHmzJlYtWqVoUujWjh48CAWLlyIr776CmfOnMGWLVuwY8cOzJ8/39ClkQRxRPYe2NvbQ6FQICkpSa89KSkJLVq0qHKfFi1a1Kk/Na76nMMKn332GT7++GPs27cPXbt2bcwyqRp1PX+RkZGIiYnBkCFDdG1arRYAYGRkhKtXr8LLy6txiyY99fkedHZ2hlKphEKh0LV16NABiYmJKC4uhkqlatSa6V/1OX8ffvghxo4dixdffBEA0KVLF+Tl5eHll1/GzJkzIZdzjK05qy7HWFpaNvloLMAR2XuiUqng6+uLsLAwXZtWq0VYWBj8/Pyq3MfPz0+vPwDs3bu32v7UuOpzDgHgk08+wfz587Fr1y707NmzKUqlKtT1/LVv3x4XLlzAuXPndI+hQ4fi0Ucfxblz5+Dm5taU5RPq9z0YEBCAiIgI3R8hAHDt2jU4OzszxDax+py//Pz8SmG14o8SIUTjFUsNotnlGINcYnYf2bBhg1Cr1WLdunXi0qVL4uWXXxbW1tYiMTFRCCHE2LFjxfTp03X9jx49KoyMjMRnn30mLl++LGbPns3ltwysrufw448/FiqVSmzevFkkJCToHjk5OYY6hAdaXc/fnbhqgeHV9RzGxsYKCwsLMXXqVHH16lWxfft24ejoKD766CNDHcIDra7nb/bs2cLCwkL8/PPPIioqSuzZs0d4eXmJkSNHGuoQHmg5OTni7Nmz4uzZswKAWLJkiTh79qy4ceOGEEKI6dOni7Fjx+r6Vyy/9e6774rLly+LFStWcPktqVu+fLlo1aqVUKlUolevXuL48eO6bYGBgSIkJESv/y+//CLatm0rVCqV6NSpk9ixY0cTV0x3qss5dHd3FwAqPWbPnt30hZMQou7fg7djkG0e6noOjx07Jnr37i3UarXw9PQUCxYsEKWlpU1cNVWoy/krKSkRc+bMEV5eXsLY2Fi4ubmJ1157TWRkZDR94SQOHDhQ5e+0inMWEhIiAgMDK+3j4+MjVCqV8PT0FN99912T111BJgTH8YmIiIhIejhHloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaIiIiIJIlBloiIiIgkiUGWiIiIiCSJQZaI6AElk8mwbds2AEBMTAxkMhnOnTtn0JqIiOqCQZaIyADGjx8PmUwGmUwGpVKJ1q1bY9q0aSgsLDR0aUREkmFk6AKIiB5UAwcOxHfffYeSkhKcPn0aISEhkMlkWLx4saFLIyKSBI7IEhEZiFqtRosWLeDm5oZhw4YhKCgIe/fuBQBotVosWrQIrVu3homJCbp164bNmzfr7X/x4kU8+eSTsLS0hIWFBfr27YvIyEgAwKlTp/D444/D3t4eVlZWCAwMxJkzZ5r8GImIGhODLBFRM/DPP//g2LFjUKlUAIBFixbh+++/x6pVq3Dx4kW89dZbeOGFF3Do0CEAQFxcHPr16we1Wo39+/fj9OnTmDhxIkpLSwEAOTk5CAkJwZEjR3D8+HG0adMGgwYNQk5OjsGOkYiooXFqARGRgWzfvh3m5uYoLS1FUVER5HI5vvzySxQVFWHhwoXYt28f/Pz8AACenp44cuQIvv76awQGBmLFihWwsrLChg0boFQqAQBt27bVPfdjjz2m91qrV6+GtbU1Dh06hCeffLLpDpKIqBExyBIRGcijjz6KlStXIi8vD0uXLoWRkRFGjBiBixcvIj8/H48//rhe/+LiYnTv3h0AcO7cOfTt21cXYu+UlJSEDz74AAcPHkRycjI0Gg3y8/MRGxvb6MdFRNRUGGSJiAzEzMwM3t7eAIC1a9eiW7duWLNmDTp37gwA2LFjB1xdXfX2UavVAAATE5ManzskJARpaWn44osv4O7uDrVaDT8/PxQXFzfCkRARGQaDLBFRMyCXy/H+++8jNDQU165dg1qtRmxsLAIDA6vs37VrV6xfvx4lJSVVjsoePXoUX331FQYNGgQAuHnzJlJTUxv1GIiImhov9iIiaiaeffZZKBQKfP3113jnnXfw1ltvYf369YiMjMSZM2ewfPlyrF+/HgAwdepUZGdn47nnnsNff/2F69ev44cffsDVq1cBAG3atMEPP/yAy5cv48SJExgzZsxdR3GJiKSGI7JERM2EkZERpk6dik8++QTR0dFwcHDAokWLEBUVBWtra/To0QPvv/8+AMDOzg779+/Hu+++i8DAQCgUCvj4+CAgIAAAsGbNGrz88svo0aMH3NzcsHDhQrzzzjuGPDwiogYnE0IIQxdBRERERFRXnFpARERERJLEIEtEREREksQgS0RERESSxCBLRERERJLEIEtEREREksQgS0RERESSxCBLRERERJLEIEtEREREksQgS0RERESSxCBLRERERJLEIEtEREREksQgS0RERESS9P+A8IGR2oqgaAAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Evaluating on untouched test set: LR_SMOTE\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Evaluating on untouched test set: RF_original\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Evaluating on untouched test set: RF_weighted\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Evaluating on untouched test set: RF_SMOTE\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Evaluating on untouched test set: XGB_original\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Evaluating on untouched test set: XGB_weighted\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Evaluating on untouched test set: XGB_SMOTE\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Test-set results at default threshold 0.5:\n",
            "  configuration  average_precision   roc_auc    recall  precision        f1  \\\n",
            "0  XGB_original           0.862997  0.970832  0.775510   0.894118  0.830601   \n",
            "1      RF_SMOTE           0.825270  0.975709  0.877551   0.677165  0.764444   \n",
            "2   RF_original           0.824401  0.961499  0.714286   0.833333  0.769231   \n",
            "3     XGB_SMOTE           0.800073  0.975357  0.887755   0.428571  0.578073   \n",
            "4   RF_weighted           0.759974  0.975766  0.857143   0.677419  0.756757   \n",
            "5      LR_SMOTE           0.750396  0.967293  0.887755   0.350806  0.502890   \n",
            "6   LR_original           0.745337  0.957472  0.642857   0.828947  0.724138   \n",
            "7   LR_weighted           0.718935  0.972093  0.918367   0.061017  0.114431   \n",
            "8  XGB_weighted           0.690960  0.981417  0.897959   0.103165  0.185068   \n",
            "\n",
            "         f2       mcc  tp    fp  fn     tn  \n",
            "0  0.796646  0.832440  76     9  22  56855  \n",
            "1  0.828516  0.770437  86    41  12  56823  \n",
            "2  0.735294  0.771156  70    14  28  56850  \n",
            "3  0.731092  0.615971  87   116  11  56748  \n",
            "4  0.813953  0.761550  84    40  14  56824  \n",
            "5  0.679688  0.557015  87   161  11  56703  \n",
            "6  0.673077  0.729596  63    13  35  56851  \n",
            "7  0.241028  0.233283  90  1385   8  55479  \n",
            "8  0.353414  0.301816  88   765  10  56099  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Select final model using CV average precision"
      ],
      "metadata": {
        "id": "aQnagPtT5fj0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "selected_name = cv_summary.loc[0, \"configuration\"]\n",
        "\n",
        "selected_estimator = None\n",
        "\n",
        "for config in configs:\n",
        "    if config[\"name\"] == selected_name:\n",
        "        selected_estimator = config[\"pipeline\"]\n",
        "        break\n",
        "\n",
        "if selected_estimator is None:\n",
        "    raise ValueError(f\"Selected model {selected_name} was not found in configs.\")\n",
        "\n",
        "print(\"\\nSelected model based on CV average precision:\")\n",
        "print(selected_name)"
      ],
      "metadata": {
        "id": "l2V2o5R25iXS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "outputId": "df93bfcf-0d03-4a2b-9dad-85e719b8d288"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Selected model based on CV average precision:\n",
            "XGB_original\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Out-of-fold probabilities for threshold selection"
      ],
      "metadata": {
        "id": "0JvQZuoa5pTe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "oof_scores = cross_val_predict(\n",
        "    selected_estimator,\n",
        "    X_train,\n",
        "    y_train,\n",
        "    cv=cv,\n",
        "    method=\"predict_proba\",\n",
        "    n_jobs=1\n",
        ")[:, 1]\n",
        "\n",
        "f2_threshold, f2_threshold_table = select_f2_threshold(\n",
        "    y_train,\n",
        "    oof_scores\n",
        ")\n",
        "\n",
        "f2_threshold_table.to_csv(\n",
        "    TABLE_DIR / f\"threshold_selection_F2_{selected_name}.csv\",\n",
        "    index=False\n",
        ")\n",
        "\n",
        "print(\"\\nF2-selected threshold:\")\n",
        "print(f2_threshold)\n",
        "\n",
        "\n",
        "cost_thresholds = []\n",
        "\n",
        "for ratio in [10, 50, 100]:\n",
        "    threshold, cost_table = select_cost_threshold(\n",
        "        y_true=y_train,\n",
        "        y_score=oof_scores,\n",
        "        fn_cost=ratio,\n",
        "        fp_cost=1\n",
        "    )\n",
        "\n",
        "    cost_table.to_csv(\n",
        "        TABLE_DIR / f\"threshold_selection_cost_{ratio}_to_1_{selected_name}.csv\",\n",
        "        index=False\n",
        "    )\n",
        "\n",
        "    cost_thresholds.append({\n",
        "        \"scenario\": f\"FN:FP = {ratio}:1\",\n",
        "        \"threshold\": threshold\n",
        "    })\n",
        "\n",
        "\n",
        "cost_thresholds_df = pd.DataFrame(cost_thresholds)\n",
        "\n",
        "cost_thresholds_df.to_csv(\n",
        "    TABLE_DIR / f\"selected_cost_thresholds_{selected_name}.csv\",\n",
        "    index=False\n",
        ")\n",
        "\n",
        "print(\"\\nCost-selected thresholds:\")\n",
        "print(cost_thresholds_df)"
      ],
      "metadata": {
        "id": "SBz0tDcG5tGg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "outputId": "747cf333-1572-4ef9-a96e-e001a4e44eba"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "F2-selected threshold:\n",
            "0.2191600352525711\n",
            "\n",
            "Cost-selected thresholds:\n",
            "        scenario  threshold\n",
            "0   FN:FP = 10:1   0.064901\n",
            "1   FN:FP = 50:1   0.022887\n",
            "2  FN:FP = 100:1   0.022887\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Final selected model evaluation using locked thresholds"
      ],
      "metadata": {
        "id": "YRDKve-m5wSY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "selected_estimator.fit(X_train, y_train)\n",
        "y_test_selected_score = selected_estimator.predict_proba(X_test)[:, 1]\n",
        "\n",
        "joblib.dump(\n",
        "    selected_estimator,\n",
        "    MODEL_DIR / f\"final_selected_model_{selected_name}.joblib\"\n",
        ")\n",
        "\n",
        "threshold_specs = [\n",
        "    (\"default_0_5\", 0.5),\n",
        "    (\"F2_OOF\", f2_threshold)\n",
        "]\n",
        "\n",
        "for _, row in cost_thresholds_df.iterrows():\n",
        "    threshold_specs.append(\n",
        "        (row[\"scenario\"], row[\"threshold\"])\n",
        "    )\n",
        "\n",
        "threshold_result_rows = []\n",
        "\n",
        "for label, threshold in threshold_specs:\n",
        "    metrics = evaluate_predictions(\n",
        "        y_true=y_test,\n",
        "        y_score=y_test_selected_score,\n",
        "        threshold=threshold\n",
        "    )\n",
        "\n",
        "    metrics[\"selected_configuration\"] = selected_name\n",
        "    metrics[\"threshold_label\"] = label\n",
        "\n",
        "    threshold_result_rows.append(metrics)\n",
        "\n",
        "    clean_label = (\n",
        "        str(label)\n",
        "        .replace(\" \", \"_\")\n",
        "        .replace(\":\", \"\")\n",
        "        .replace(\"=\", \"\")\n",
        "        .replace(\"/\", \"_\")\n",
        "    )\n",
        "\n",
        "    plot_confusion_matrix_from_metrics(\n",
        "        metrics,\n",
        "        FIG_DIR / f\"confusion_matrix_{selected_name}_{clean_label}.png\",\n",
        "        f\"{selected_name}: {label}\"\n",
        "    )\n",
        "\n",
        "threshold_test_results = pd.DataFrame(threshold_result_rows)\n",
        "\n",
        "threshold_test_results.to_csv(\n",
        "    TABLE_DIR / f\"test_threshold_results_{selected_name}.csv\",\n",
        "    index=False\n",
        ")\n",
        "\n",
        "print(\"\\nSelected model threshold results on untouched test set:\")\n",
        "\n",
        "print(\n",
        "    threshold_test_results[\n",
        "        [\n",
        "            \"threshold_label\",\n",
        "            \"threshold\",\n",
        "            \"recall\",\n",
        "            \"precision\",\n",
        "            \"f1\",\n",
        "            \"f2\",\n",
        "            \"mcc\",\n",
        "            \"tp\",\n",
        "            \"fp\",\n",
        "            \"fn\",\n",
        "            \"tn\"\n",
        "        ]\n",
        "    ]\n",
        ")"
      ],
      "metadata": {
        "id": "tWDR97ZI50SU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 2702
        },
        "outputId": "99036856-197e-48ce-b51d-7410359ad532"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x500 with 2 Axes>"
            ],
            "image/png": 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ZMmUMV1dXo0SJEsbUqVMNs9ls08bye/Hv/2aW/xYpbV27dn1Id+i44uLiDL98zvf8mad18/PzM+Li4jL7tjKFyTD0vKmIpN+NGzfIlSsXEyZM4K233srs4YjIA0RFReHj48Ofh4ri7WVfaXRUtJkiNc4QGRmZrjKBrE7pPBFJtbi4uLue5Js2bRpwew0gEck6PL1MeHrZl4Y3kzFp/KxKQZRIFhITE/PAuiBfX98HLpyZXitWrGDRokW0aNECT09Pdu3axRdffEHTpk158sknH8o1ReThSDbMJNuZi0o2Mn/ZkcykIEokC/nwww8f+AqY06dPW5/Iy2iVK1fGxcWFSZMmERUVZS02txQBi4g4EtVEiWQhf/zxx12Le/5bvXr1HPdJGRF5IEtNVMTJwhlSE+VX5qxqokTk8Ve8eHGb9+GJiKSXGTP2JuPs7yFrUxAlIiLigJINg2Q7k1H2np/VKYiSBzKbzYSHh+Pl5ZVhCyqKiMj9GYZBdHQ0/v7+ODnpLW2PIwVR8kDh4eHpeteaiIjY79y5cxQqVCjD+zVjYMa+mSR7z8/qFETJA1leZfLn4aJ4e+qvIclaWpeulNlDEEmXJBLZxdfWf4MzmhmDZAVRdlEQJQ9kSeF5ezrZ/SSHyKPmYsqW2UMQSZ+/4xOVUTy+FESJiIg4IKXz7KcgSkRExAHp6Tz7KTcjIiIikg6aiRIREXFA5r83e/twZAqiREREHFByBjydZ+/5WZ3SeSIiIiLpoJkoERERB5Rs3N7s7cORKYgSERFxQKqJsp+CKBEREQdkxkQy9i3kabbz/KxONVEiIiIi6aCZKBEREQdkNm5v9vbhyBREiYiIOKDkDEjn2Xt+Vqd0noiIiEg6aCZKRETEAWkmyn4KokRERByQ2TBhNux8Os/O87M6pfNERERE0kEzUSIiIg5I6Tz7KYgSERFxQMk4kWxnQio5g8aSVSmIEhERcUBGBtREGaqJEhEREZG00kyUiIiIA1JNlP0URImIiDigZMOJZMPOmigHf+2L0nkiIiIi6aCZKBEREQdkxoTZzrkUM449FaUgSkRExAGpJsp+SueJiIiIpINmokRERBxQxhSWK50nIiIiDuZ2TZSdLyBWOk9ERETk4Ro7diwmk8lmK1u2rPX4rVu36Nu3L3ny5MHT05M2bdpw8eJFmz7Onj1LcHAw2bNnJ1++fAwdOpSkpCSbNtu2baN69eq4ublRsmRJFi1adNdYZs6cSdGiRXF3d6d27docOHAgXfekIEpERMQBmf9+d549W1qf7qtQoQIXLlywbrt27bIeGzRoEBs2bGDVqlVs376d8PBwXnjhBevx5ORkgoODSUhIYM+ePSxevJhFixYxevRoa5vTp08THBxMw4YNOXLkCAMHDqRnz55s3rzZ2mbFihUMHjyYMWPGcPjwYapUqUJQUBCXLl1K88/QZBgOntCUB4qKisLHx4frvxbH20txt2QtQf5VM3sIIumSZCSyjXVERkbi7e2dYf1a/k1ffqQ82b2c7errZnQy7ar+kqoxjh07lrVr13LkyJG7jkVGRuLr68uyZct48cUXAThx4gTlypVj79691KlTh02bNtGyZUvCw8PJnz8/AHPmzGH48OFcvnwZV1dXhg8fTkhICD///LO173bt2nHjxg1CQ0MBqF27Nk888QQzZswAwGw2ExAQQP/+/RkxYkSa7l/fiCIiIg7I/PdMkr0b3A7M7tzi4+NTvOapU6fw9/enePHidOzYkbNnzwJw6NAhEhMTadKkibVt2bJlKVy4MHv37gVg7969VKpUyRpAAQQFBREVFcWxY8esbe7sw9LG0kdCQgKHDh2yaePk5ESTJk2sbdJCQZSIiIjYJSAgAB8fH+s2ceLEu9rUrl2bRYsWERoayuzZszl9+jRPPfUU0dHRRERE4OrqSs6cOW3OyZ8/PxEREQBERETYBFCW45Zj92sTFRVFXFwcV65cITk5OcU2lj7SQk/niYiIOKBkw0SyYedim3+ff+7cOZt0npub211tmzdvbv3flStXpnbt2hQpUoSVK1fi4eFh1zgyi2aiREREHJC9ReWWDcDb29tmSymI+recOXNSunRpfvvtN/z8/EhISODGjRs2bS5evIifnx8Afn5+dz2tZ/n8oDbe3t54eHiQN29enJ2dU2xj6SMtFESJiIjIIxcTE8Pvv/9OgQIFqFGjBtmyZSMsLMx6/OTJk5w9e5bAwEAAAgMDOXr0qM1TdFu2bMHb25vy5ctb29zZh6WNpQ9XV1dq1Khh08ZsNhMWFmZtkxZK54mIiDggs+GE2c4Vy81peMB/yJAhPPvssxQpUoTw8HDGjBmDs7Mz7du3x8fHhx49ejB48GBy586Nt7c3/fv3JzAwkDp16gDQtGlTypcvT+fOnZk0aRIRERGMGjWKvn37Wme+evfuzYwZMxg2bBjdu3dn69atrFy5kpCQEOs4Bg8eTNeuXalZsya1atVi2rRpxMbG8sorr6T5/hVEiYiIOKA703Hp7yP1QdT58+dp3749V69exdfXl3r16rFv3z58fX0BmDp1Kk5OTrRp04b4+HiCgoKYNWuW9XxnZ2c2btxInz59CAwMJEeOHHTt2pXx48db2xQrVoyQkBAGDRrE9OnTKVSoEPPnzycoKMjapm3btly+fJnRo0cTERFB1apVCQ0NvavYPDW0TpQ8kNaJkqxM60RJVvWw14mad7hGhqwT1av6oQwfY1ahmSgREREHZAa7n84zZ8xQsiwFUSIiIg7ozsUy7enDkTn23YuIiIikk2aiREREHFCy4USynU/n2Xt+VqcgSkRExAGZMWHG3poo+87P6hREiYiIOCDNRNnPse9eREREJJ00EyUiIuKAMmaxTceei1EQJSIi4oDMhgmzvetE2Xl+VufYIaSIiIhIOmkmSkRExAGZMyCd5+iLbSqIEhERcUBmwwmznU/X2Xt+VufYdy8iIiKSTpqJEhERcUDJmEi2c7FMe8/P6hREiYiIOCCl8+ynIEpERMQBJWP/TFJyxgwly3LsEFJEREQknTQTJSIi4oCUzrOfgigREREHpBcQ28+x715EREQknTQTJSIi4oAMTJjtLCw3tMSBiIiIOBql8+zn2HcvIiIikk6aiRIREXFAZsOE2bAvHWfv+VmdgigREREHlIwTyXYmpOw9P6tz7LsXERERSSfNRImIiDggpfPspyBKRETEAZlxwmxnQsre87M6BVEiIiIOKNkwkWznTJK952d1jh1CioiIiKSTZqJEREQckGqi7KcgSkRExAEZhhNmO1ccN7RiuYiIiIiklWaiREREHFAyJpLtfIGwvedndQqiREREHJDZsL+myWxk0GCyKKXzRERERNJBM1EiIiIOyJwBheX2np/VKYgSERFxQGZMmO2sabL3/KzOsUNIERERkXTSTJSIiIgD0mtf7KeZKJFUGvfhVZwL/Gazla/3p02bvQfjaPLiX3gV/52cpX6nQavzxMWZ79ln8SfO3NWnc4Hf6Dfycpr6vXY9mU6vRZCz1O/kLvMHPQdfJCb23tcVuZ/rxmWOGLvZYWzkW+NLLhl/2Rw3DIPfjWPsMDay1VjNYWMHN43oFPsyG8nsM7bwrfEl0caNRzB6SS1LTZS9myP7T929yWRi7dq19zzeoEEDBg4cmKHXHDt2LFWrVr1vmzNnzmAymThy5EiGXlsevQplXPnrx6LWbce6QtZjew/G0aLDBZ6pn519mwqxf1MAr3X3wcnp3n+p7d8UYNPf5hX+ALz4bI409dup70V++TWBzSsKsv6zAuzcd4v/G3rpIfwExBEkk4QnPpSlWorH/+Qk5/iNslTnCRrhhDM/sItkI/mutqc4ihseD3vIkg5mTNZXv6R7U01U2u3duxdnZ2eCg4PTfG7RokWZNm1aei77WBoyZAhhYWHWz926daNVq1Y2bQICArhw4QIVK1Z8qGNRsPbwubiAXz4X65Y3j7P12BtjrtC/hw/D++eiQhk3ypR05eXnvHBzu/c/Mr55nW36C9kSS4mi2agf6JHqfo//msDm727yyYf5qF3dnXq1PZg+IS8r1sYQHpH08H4Y8p+V11SAkqaK5DMVvOuYYRic5TeKUZZ8Jn+8TDmpSC3iieMy4TZtrxgXuMpFSlH5UQ1d5JFKVxC1YMEC+vfvz44dOwgPD3/wCf9hnp6e5MmT575tnJ2d8fPzw8VFJWhZ3ak/EilU9TQla5+h02sRnD2fCMClK0nsPxxPvrzO1Hv2PAUqnaZh6/Ps2h+X6r4TEgyWfhXNK+28MJlMqe5376Fb5PRxomZVd+u+Jk9nx8kJ9h++lUF3LnJbHLEkcIvc5LfuczFlw5vcRHLVui/euMVxDlORJ3DGOaWuJJMZfz+dZ89maCYqbWJiYlixYgV9+vQhODiYRYsW3dVmw4YNPPHEE7i7u5M3b15at24N3E6n/fnnnwwaNAiTyWT9okgpJTZt2jSKFi1q/fz999/zzDPPkDdvXnx8fKhfvz6HDx9O6/BtxMfHM2TIEAoWLEiOHDmoXbs227Zts2kzb948AgICyJ49O61bt2bKlCnkzJnTevzOsY8dO5bFixezbt066/1t27btrhmibdu2YTKZ2Lx5M9WqVcPDw4NGjRpx6dIlNm3aRLly5fD29qZDhw7cvHnTeq3Q0FDq1atHzpw5yZMnDy1btuT333+3Hi9WrBgA1apVw2Qy0aBBA+ux+fPnU65cOdzd3SlbtiyzZs2y62fniGpVc+fT6fn5epk/M9/35cy5JOq3+ovoGDN//Hl7xmfc5Gv06OjN18v8qVbJjWde/otTfySkqv+1oTHciDLTta23dV9q+r14KYl8eW2/pFxcTOTO6UzE5bvTKyL2SOB2YO6Km81+V9ytxwzD4Be+pyDF8TblfuRjlNSxO5X39+bI0hxErVy5krJly1KmTBk6derEp59+imH8s+57SEgIrVu3pkWLFvzwww+EhYVRq1YtAFavXk2hQoUYP348Fy5c4MKFC6m+bnR0NF27dmXXrl3s27ePUqVK0aJFC6KjUy5mTI1+/fqxd+9eli9fzk8//cRLL71Es2bNOHXqFAC7d++md+/eDBgwgCNHjvDMM8/w7rvv3rO/IUOG8PLLL9OsWTPr/dWtW/ee7ceOHcuMGTPYs2cP586d4+WXX2batGksW7aMkJAQvvnmGz7++GNr+9jYWAYPHszBgwcJCwvDycmJ1q1bYzbfLiA+cOAAAN9++y0XLlxg9erVACxdupTRo0fz7rvvcvz4cd577z3efvttFi9enOK44uPjiYqKstkEmjfOwUvPelK5vBtBDXOw8fMC3Igys3J9DOa/333waicfXmnnTbVKbkwZ70uZEq4s/CJ1P79Pl0XRrFF2/P3+mbHMiH5FHrVz/EYSSRSjbGYPReShSnN+acGCBXTq1AmAZs2aERkZyfbt262zHu+++y7t2rVj3Lhx1nOqVKkCQO7cuXF2dsbLyws/P780XbdRo0Y2nz/55BNy5szJ9u3badmyZVpvg7Nnz7Jw4ULOnj2Lv//tYt4hQ4YQGhrKwoULee+99/j4449p3rw5Q4YMAaB06dLs2bOHjRs3ptinp6cnHh4exMfHp+r+JkyYwJNPPglAjx49GDlyJL///jvFixcH4MUXX+S7775j+PDhALRp08bm/E8//RRfX19++eUXKlasiK+vLwB58uSxuf6YMWOYPHkyL7zwAnB7xuqXX35h7ty5dO3a9a5xTZw40ea/n6Qsp48zpYtn4/fTCTSqd7uGqVxpV5s2ZUu5cvavB9cl/XkukbCdcXy5wPb3pkB+lwf2mz+fC5eu2M44JSUZXLuRjJ+v0iiSsVy5nTZOIN6mYDyBW3iRE4DrXCaSq2xlNdzxbrUDhOFnFKaC6YlHOWS5B61Ybr803f3Jkyc5cOAA7du3B8DFxYW2bduyYMECa5sjR47QuHHjjB0lcPHiRXr16kWpUqXw8fHB29ubmJgYzp49m67+jh49SnJyMqVLl8bT09O6bd++3ZoiO3nypHUWzeLfn+1RufI/xZb58+cne/bs1gDKsu/SpX+esDp16hTt27enePHieHt7W9Od9/sZxMbG8vvvv9OjRw+b+5wwYYJNKvBOI0eOJDIy0rqdO3fOzjv9b4qJNfP7n4kUyO9C0QAX/P2c+fV329TdqT8SKFIo2wP7WrQiinx5nQluksNmf2r6Dazhzo1IM4d+/Kf+aeuuOMxmqF3dHZGM5EEOXHHnGv/825RkJBLFNXy4XR9ahqrU4Rlq04TaNKEqt/9YrEhtSlAhU8Ytd1M6z35pmolasGABSUlJ1pkbuJ37dnNzY8aMGfj4+ODhkfZHWZ2cnGxSggCJiYk2n7t27crVq1eZPn06RYoUwc3NjcDAQBISUldv8m8xMTE4Oztz6NAhnJ1t/1r39PRMV59plS3bP1+uJpPJ5rNlnyVVB/Dss89SpEgR5s2bh7+/P2azmYoVK973ZxATEwPcru2qXbu2zbF/37eFm5sbbm5uKR5zZEPHXaHlMzkoEuBCeEQSYz+8hrMTtGt1uxB8SJ9cjP3wGpUruFG1giufrYzmxG+JrJznfd9+zWaDRcuj6fKyFy4utv8gpabfcqVdCWqYnf8bcplZk3xJTDR4/a3LtG3laZMaFEmtJCOJOGKsn+OIJdq4QTZccTdlp7BRktMcJ7vhiQc5+J1juOGBL7e/G9xN2W36czZu/x5mx/OuYyJZWar/hU1KSuKzzz5j8uTJNG3a1OZYq1at+OKLL+jduzeVK1cmLCyMV155JcV+XF1dSU62TT34+voSERGBYRjWYvN/P6a/e/duZs2aRYsWLQA4d+4cV65cSe3w71KtWjWSk5O5dOkSTz31VIptypQpw/fff2+z79+f/y2l+8sIV69e5eTJk8ybN8863l27dt11bcDm+vnz58ff358//viDjh07Zvi4HMn5C0l0fC2Cq9eT8c3jzJO1PNgTEoDv30XdA17Nya14gzfGXOHa9WSqVHBj83J/ShT9Jzhu9MJ5igRkY+H0f55s+nZHHGf/SuKVdikHW6np9/OZ+en/1mWeeekvnJxMvBCcg+kTfB/ST0L+66K4xmF2WD+f4icAClCECjxBEcqQTDLHOUQSieQkL1Wph7NJ6eOsRO/Os1+qg6iNGzdy/fp1evTogY+Pj82xNm3asGDBAnr37s2YMWNo3LgxJUqUoF27diQlJfH1119b63qKFi3Kjh07aNeuHW5ubuTNm5cGDRpw+fJlJk2axIsvvkhoaCibNm3C2/ufL5VSpUqxZMkSatasSVRUFEOHDk3XrJdF6dKl6dixI126dGHy5MlUq1aNy5cvExYWRuXKlQkODqZ///48/fTTTJkyhWeffZatW7eyadMma6CXkqJFi7J582ZOnjxJnjx57vpZpVeuXLnIkycPn3zyCQUKFODs2bOMGDHCpk2+fPnw8PAgNDSUQoUK4e7ujo+PD+PGjeP111/Hx8eHZs2aER8fz8GDB7l+/TqDBw/OkPE5gi/mPLjObXj/XAzvn+uex0+fTaJLW9tgqWmD7CRfKGlXv7lzObN0VtrqDEXuJbcpH0148Z7HTSYTJaiQ6tSchynHffuTzJER6ThHT+eluiZqwYIFNGnSJMWgoE2bNhw8eJCffvqJBg0asGrVKtavX0/VqlVp1KiR9akxgPHjx3PmzBlKlChhLYQuV64cs2bNYubMmVSpUoUDBw5Yi7nvvP7169epXr06nTt35vXXXydfvnzpvW8AFi5cSJcuXXjjjTcoU6YMrVq14vvvv6dw4cIAPPnkk8yZM4cpU6ZQpUoVQkNDGTRoEO7u964z6dWrF2XKlKFmzZr4+vqye/duu8Zo4eTkxPLlyzl06BAVK1Zk0KBBfPDBBzZtXFxc+Oijj5g7dy7+/v48//zzAPTs2ZP58+ezcOFCKlWqRP369Vm0aJF1SQR5NI6djMfH24kuL3ll9lBERFQTlQFMxr+LkeS+evXqxYkTJ9i5c2dmD+WRiYqKwsfHh+u/Fsfby7GfxJCsJ8i/amYPQSRdkoxEtrGOyMhIm8yMvSz/pjcP7UW2HK4PPuE+EmMT2NRsXoaPMatQ1ekDfPjhhzzzzDPkyJGDTZs2sXjxYi1UKSIiWZ7SefbTtMIDHDhwgGeeeYZKlSoxZ84cPvroI3r27JnZwxIREbFLZqfz3n//fUwmEwMHDrTuu3XrFn379iVPnjx4enrSpk0bLl68aHPe2bNnCQ4OJnv27OTLl4+hQ4eSlGS7Ht+2bduoXr06bm5ulCxZMsW3q8ycOZOiRYvi7u5O7dq1bUqPUktB1AOsXLmSS5cuERcXx7Fjx+jdu3dmD0lERCRL+/7775k7d67NeokAgwYNYsOGDaxatYrt27cTHh5uXSgabj99HhwcTEJCAnv27GHx4sUsWrSI0aNHW9ucPn2a4OBgGjZsyJEjRxg4cCA9e/Zk8+bN1jYrVqxg8ODBjBkzhsOHD1OlShWCgoJs1mZMDQVRIiIiDsiADHgBcdrFxMTQsWNH5s2bR65c/zx1HBkZyYIFC5gyZQqNGjWiRo0aLFy4kD179rBv3z4AvvnmG3755Rc+//xzqlatSvPmzXnnnXeYOXOmdc3EOXPmUKxYMSZPnky5cuXo168fL774IlOnTrVea8qUKfTq1YtXXnmF8uXLM2fOHLJnz86nn36apntRECUiIuKAMjKd9+/3rcbHx9/zun379iU4OJgmTZrY7D906BCJiYk2+8uWLUvhwoXZu3cvAHv37qVSpUrkz//PWntBQUFERUVx7Ngxa5t/9x0UFGTtIyEhgUOHDtm0cXJyokmTJtY2qaUgSkREROwSEBCAj4+PdZs4cWKK7ZYvX87hw4dTPB4REYGrqys5c+a02Z8/f34iIiKsbe4MoCzHLcfu1yYqKoq4uDiuXLlCcnJyim0sfaSWns4TERFxQBn5dN65c+dsljhI6dVh586dY8CAAWzZsuW+6y1mJZqJEhERcUAZmc7z9va22VIKog4dOsSlS5eoXr06Li4uuLi4sH37dj766CNcXFzInz8/CQkJ3Lhxw+a8ixcv4ud3+40Mfn5+dz2tZ/n8oDbe3t54eHiQN29enJ2dU2xj6SO1FESJiIjIQ9e4cWOOHj3KkSNHrFvNmjXp2LGj9X9ny5aNsLAw6zknT57k7NmzBAYGAhAYGMjRo0dtnqLbsmUL3t7elC9f3trmzj4sbSx9uLq6UqNGDZs2ZrOZsLAwa5vUUjpPRETEAT3qxTa9vLyoWLGizb4cOXKQJ08e6/4ePXowePBgcufOjbe3N/379ycwMJA6deoA0LRpU8qXL0/nzp2ZNGkSERERjBo1ir59+1pnv3r37s2MGTMYNmwY3bt3Z+vWraxcuZKQkBDrdQcPHkzXrl2pWbMmtWrVYtq0acTGxvLKK6+k6f4VRImIiDggwzBh2BlE2Xv+v02dOhUnJyfatGlDfHw8QUFBNm8JcXZ2ZuPGjfTp04fAwEBy5MhB165dGT9+vLVNsWLFCAkJYdCgQUyfPp1ChQoxf/58goKCrG3atm3L5cuXGT16NBEREVStWpXQ0NC7is0fRO/OkwfSu/MkK9O78ySretjvzgtc1x+XHHfXLqVFUmw8e5//2GHfnadvRBEREZF0UDpPRETEAekFxPZTECUiIuKAHseaqKxG6TwRERGRdNBMlIiIiANSOs9+CqJEREQckNJ59lM6T0RERCQdNBMlIiLigIwMSOc5+kyUgigREREHZAD2Lrft6Kt1K50nIiIikg6aiRIREXFAZkyYsPPpPDvPz+oURImIiDggPZ1nPwVRIiIiDshsmDBpnSi7qCZKREREJB00EyUiIuKADCMDns5z8MfzFESJiIg4INVE2U/pPBEREZF00EyUiIiIA9JMlP0URImIiDggPZ1nP6XzRERERNJBM1EiIiIOSE/n2U9BlIiIiAO6HUTZWxOVQYPJohREiYiIOCAVlttPNVEiIiIi6aCZKBEREQdk/L3Z24cjUxAlIiLigJTOs5/SeSIiIiLpoJkoERERR6R8nt0URImIiDiiDEjnoXSeiIiIiKSVZqJEREQckFYst5+CKBEREQekp/Psp3SeiIiISDpoJkpERMQRGSb7C8MdfCZKQZSIiIgDUk2U/RREiYiIOCKtE2U31USJiIiIpINmokRERByQns6zn4IoERERR+Xg6Th7KZ0nIiIikg6aiRIREXFASufZT0GUiIiII9LTeXZTOk9EREQkHTQTJSIi4pBMf2/29uG4FESJiIg4IqXz7KZ0noiIiEg6aCZKRETEEWkmym4KokRERByRYbq92duHA1MQJSIi4oAM4/Zmbx+OTDVRIiIiIumgmSgRERFHpJoouymIEhERcUSqibKb0nkiIiIi6aCZKBEREQdkMm5v9vbhyDQTJSIi4oiMDNpSafbs2VSuXBlvb2+8vb0JDAxk06ZN1uO3bt2ib9++5MmTB09PT9q0acPFixdt+jh79izBwcFkz56dfPnyMXToUJKSkmzabNu2jerVq+Pm5kbJkiVZtGjRXWOZOXMmRYsWxd3dndq1a3PgwIHU38gdFESJiIjIQ1eoUCHef/99Dh06xMGDB2nUqBHPP/88x44dA2DQoEFs2LCBVatWsX37dsLDw3nhhRes5ycnJxMcHExCQgJ79uxh8eLFLFq0iNGjR1vbnD59muDgYBo2bMiRI0cYOHAgPXv2ZPPmzdY2K1asYPDgwYwZM4bDhw9TpUoVgoKCuHTpUprvyWQYjr7KgzxIVFQUPj4+XP+1ON5eirslawnyr5rZQxBJlyQjkW2sIzIyEm9v7wzr1/JvesDUd3DycLerL3PcLc4NejvdY8ydOzcffPABL774Ir6+vixbtowXX3wRgBMnTlCuXDn27t1LnTp12LRpEy1btiQ8PJz8+fMDMGfOHIYPH87ly5dxdXVl+PDhhISE8PPPP1uv0a5dO27cuEFoaCgAtWvX5oknnmDGjBm378FsJiAggP79+zNixIg0jV/fiCIiIo4oA9N5UVFRNlt8fPx9L52cnMzy5cuJjY0lMDCQQ4cOkZiYSJMmTaxtypYtS+HChdm7dy8Ae/fupVKlStYACiAoKIioqCjrbNbevXtt+rC0sfSRkJDAoUOHbNo4OTnRpEkTa5u0UBAlIiLiiDIwiAoICMDHx8e6TZw4McVLHj16FE9PT9zc3Ojduzdr1qyhfPnyRERE4OrqSs6cOW3a58+fn4iICAAiIiJsAijLccux+7WJiooiLi6OK1eukJycnGIbSx9poafzRERExC7nzp2zSee5ubml2K5MmTIcOXKEyMhIvvzyS7p27cr27dsf1TAznIIoERERR5SBK5Zbnrh7EFdXV0qWLAlAjRo1+P7775k+fTpt27YlISGBGzdu2MxGXbx4ET8/PwD8/PzueorO8vTenW3+/UTfxYsX8fb2xsPDA2dnZ5ydnVNsY+kjLZTOExERcUSWFcvt3exgNpuJj4+nRo0aZMuWjbCwMOuxkydPcvbsWQIDAwEIDAzk6NGjNk/RbdmyBW9vb8qXL29tc2cfljaWPlxdXalRo4ZNG7PZTFhYmLVNWmgmSkRERB66kSNH0rx5cwoXLkx0dDTLli1j27ZtbN68GR8fH3r06MHgwYPJnTs33t7e9O/fn8DAQOrUqQNA06ZNKV++PJ07d2bSpElEREQwatQo+vbta00f9u7dmxkzZjBs2DC6d+/O1q1bWblyJSEhIdZxDB48mK5du1KzZk1q1arFtGnTiI2N5ZVXXknzPSmIEhERcUCPesXyS5cu0aVLFy5cuICPjw+VK1dm8+bNPPPMMwBMnToVJycn2rRpQ3x8PEFBQcyaNct6vrOzMxs3bqRPnz4EBgaSI0cOunbtyvjx461tihUrRkhICIMGDWL69OkUKlSI+fPnExQUZG3Ttm1bLl++zOjRo4mIiKBq1aqEhobeVWyeuvvXOlHyAFonSrIyrRMlWdXDXieq8P8mZMg6UWeHj8rwMWYV+kYUERERSQcFUSIiIiLpoJooERERB2QiA2qiMmQkWZeCKEm11qUr4WLKltnDEBEReSwoiBIREXFEGbDOk93nZ3EKokRERBxRBq5Y7qgURImIiDgiBVF209N5IiIiIumgmSgREREH9KhXLP8vUhAlIiLiiJTOs5vSeSIiIiLpoJkoERERR6SZKLspiBIREXFAqomyn9J5IiIiIumgmSgRERFHpBXL7aYgSkRExBGpJspuSueJiIiIpINmokRERByQCsvtpyBKRETEESmdZzcFUSIiIo4oA2aiHD2IUk2UiIiISDpoJkpERMQRKZ1nNwVRIiIijkhBlN2UzhMRERFJB81EiYiIOCAtcWA/zUSJiIiIpIOCKBEREZF0UDpPRETEEamw3G4KokRERByQaqLspyBKRETEUTl4EGQv1USJiIiIpINmokRERByRaqLspiBKRETEAakmyn5K54mIiIikg2aiREREHJHSeXZTECUiIuKAlM6zn9J5IiIiIumgmSgRERFHpHSe3RREiYiIOCIFUXZTOk9EREQkHTQTJSIi4oBUWG4/BVEiIiKOSOk8uymIEhERcUQKouymmigRERGRdNBMlIiIiANSTZT9FESJiIg4IqXz7KZ0noiIiEg6aCZKRETEASmdZz8FUSIiIo5I6Ty7KZ0nIiIikg6aiRIREXFEmomym4IoERERB2T6e7O3D0emdJ6IiIhIOmgmSkRExBEpnWc3zUSJiIg4IMsSB/ZuqTVx4kSeeOIJvLy8yJcvH61ateLkyZM2bW7dukXfvn3JkycPnp6etGnThosXL9q0OXv2LMHBwWTPnp18+fIxdOhQkpKSbNps27aN6tWr4+bmRsmSJVm0aNFd45k5cyZFixbF3d2d2rVrc+DAgdTfzN8URImIiDgiI4O2VNq+fTt9+/Zl3759bNmyhcTERJo2bUpsbKy1zaBBg9iwYQOrVq1i+/bthIeH88ILL1iPJycnExwcTEJCAnv27GHx4sUsWrSI0aNHW9ucPn2a4OBgGjZsyJEjRxg4cCA9e/Zk8+bN1jYrVqxg8ODBjBkzhsOHD1OlShWCgoK4dOlSmn6EJsMwHHwyTh4kKioKHx8fGvA8LqZsmT0cERGHkGQkso11REZG4u3tnWH9Wv5Nr/B/7+Hs5m5XX8nxtzg29810jfHy5cvky5eP7du38/TTTxMZGYmvry/Lli3jxRdfBODEiROUK1eOvXv3UqdOHTZt2kTLli0JDw8nf/78AMyZM4fhw4dz+fJlXF1dGT58OCEhIfz888/Wa7Vr144bN24QGhoKQO3atXniiSeYMWMGAGazmYCAAPr378+IESNSfQ+aiRIREXFUGTQLFRUVZbPFx8c/8NKRkZEA5M6dG4BDhw6RmJhIkyZNrG3Kli1L4cKF2bt3LwB79+6lUqVK1gAKICgoiKioKI4dO2Ztc2cfljaWPhISEjh06JBNGycnJ5o0aWJtk1oKokRERBxQRtZEBQQE4OPjY90mTpx432ubzWYGDhzIk08+ScWKFQGIiIjA1dWVnDlz2rTNnz8/ERER1jZ3BlCW45Zj92sTFRVFXFwcV65cITk5OcU2lj5SS0/niYiIiF3OnTtnk85zc3O7b/u+ffvy888/s2vXroc9tIdKQZSIiIgjysAlDry9vVNdE9WvXz82btzIjh07KFSokHW/n58fCQkJ3Lhxw2Y26uLFi/j5+Vnb/PspOsvTe3e2+fcTfRcvXsTb2xsPDw+cnZ1xdnZOsY2lj9RSOk9ERMQBPeolDgzDoF+/fqxZs4atW7dSrFgxm+M1atQgW7ZshIWFWfedPHmSs2fPEhgYCEBgYCBHjx61eYpuy5YteHt7U758eWubO/uwtLH04erqSo0aNWzamM1mwsLCrG1SSzNRIiIi8tD17duXZcuWsW7dOry8vKz1Rz4+Pnh4eODj40OPHj0YPHgwuXPnxtvbm/79+xMYGEidOnUAaNq0KeXLl6dz585MmjSJiIgIRo0aRd++fa0pxN69ezNjxgyGDRtG9+7d2bp1KytXriQkJMQ6lsGDB9O1a1dq1qxJrVq1mDZtGrGxsbzyyitpuicFUSIiIo7oEa9YPnv2bAAaNGhgs3/hwoV069YNgKlTp+Lk5ESbNm2Ij48nKCiIWbNmWds6OzuzceNG+vTpQ2BgIDly5KBr166MHz/e2qZYsWKEhIQwaNAgpk+fTqFChZg/fz5BQUHWNm3btuXy5cuMHj2aiIgIqlatSmho6F3F5g+idaLkgbROlIjIo/ew14mq3P09nF3tXCcq4RY/fZq+daL+CzQTJSIi4oj07jy7qbBcREREJB00EyUiIuKINBNlNwVRIiIiDiitSxTcqw9HpnSeiIiISDpoJkpERMQRKZ1nNwVRIiIiDshkGJjsXOXI3vOzOqXzRERERNJBM1EiIiKOSOk8uymIEhERcUB6Os9+SueJiIiIpINmokRERByR0nl2UxAlIiLigJTOs5+CKBEREUekmSi7qSZKREREJB00EyUiIuKAlM6zn4IoERERR6R0nt2UzhMRERFJB81EiYiIOChHT8fZS0GUiIiIIzKM25u9fTgwBVEij8h14zJ/8itRXCeBW1QmkHymgtbjl4y/OM/vRHODRBKoTRO8TDkzb8AifzMMgz84xgXOksAt3PCgAEUoRjlMJhMA3xpfpnhuSSpR1FTmUQ5X5JFRTdRDYDKZWLt27T2PG4bBq6++Su7cuTGZTBw5cuSRjc2iW7dutGrV6pFf15Elk4QnPpSl2j2P5yQvJan0iEcmcn9nOMF5/qAs1QgkiJJU4k9+5Ry/Wds8RUubrTw1AchHwXt1K5nM8nSevZsjy9JB1N69e3F2diY4ODjN5xYtWpRp06Zl/KBSITQ0lEWLFrFx40YuXLhAxYoVM2Uc8mjlNRWgpKmizezTnQqYilDcVJ7c5HvEIxO5v0iu4os/eU0F8DDlIL+pELnJTxTXrW3cTO4222XCyYUv2U2emThyuS8jgzYHlqWDqAULFtC/f3927NhBeHh4Zg8n1X7//XcKFChA3bp18fPzw8Xl7qxqQkJCJoxMRORuPuThGpeINaIBiDZuEMkV8uCXYvt44xZXuEBBij3KYYo8clk2iIqJiWHFihX06dOH4OBgFi1adFebDRs28MQTT+Du7k7evHlp3bo1AA0aNODPP/9k0KBBmEwma05/7NixVK1a1aaPadOmUbRoUevn77//nmeeeYa8efPi4+ND/fr1OXz4cKrH3a1bN/r378/Zs2cxmUzWvhs0aEC/fv0YOHAgefPmJSgoCIApU6ZQqVIlcuTIQUBAAK+99hoxMTHW/lIz5uTkZAYPHkzOnDnJkycPw4YNw3DwYkARSb2ilCU/AexlM2HGV+znWwIoRQFT4RTbX+BPnHHBV6m8x5rJnDGbI8uyQdTKlSspW7YsZcqUoVOnTnz66ac2gUFISAitW7emRYsW/PDDD4SFhVGrVi0AVq9eTaFChRg/fjwXLlzgwoULqb5udHQ0Xbt2ZdeuXezbt49SpUrRokULoqOjU3X+9OnTGT9+PIUKFeLChQt8//331mOLFy/G1dWV3bt3M2fOHACcnJz46KOPOHbsGIsXL2br1q0MGzYs1eMFmDx5MosWLeLTTz9l165dXLt2jTVr1tyzfXx8PFFRUTabiDiui5wngrNUpDa1aUIFnuAsvxJunEmxfThn8KMwzibnRztQSRul8+yWZZ/OW7BgAZ06dQKgWbNmREZGsn37dho0aADAu+++S7t27Rg3bpz1nCpVqgCQO3dunJ2d8fLyws8v5enoe2nUqJHN508++YScOXOyfft2WrZs+cDzfXx88PLywtnZ+a5rlypVikmTJtnsGzhwoPV/Fy1alAkTJtC7d29mzZqV6jFPmzaNkSNH8sILLwAwZ84cNm/efM/2EydOtPm5iYhjO8VPFKUMfqYAADzxIc64yRlO4k9Rm7bXjcvcJJpK1M6EkUpa6LUv9suSM1EnT57kwIEDtG/fHgAXFxfatm3LggULrG2OHDlC48aNM/zaFy9epFevXpQqVQofHx+8vb2JiYnh7Nmzdvddo0aNu/Z9++23NG7cmIIFC+Ll5UXnzp25evUqN2/eTFWfkZGRXLhwgdq1//kHzcXFhZo1a97znJEjRxIZGWndzp07l/abEZH/DDPJmDDZ7Lv9+e5v0HDO4EUuLc8hDiFLzkQtWLCApKQk/P39rfsMw8DNzY0ZM2bg4+ODh4dHmvt1cnK6q1YoMTHR5nPXrl25evUq06dPp0iRIri5uREYGJghheA5cuSw+XzmzBlatmxJnz59ePfdd8mdOze7du2iR48eJCQkkD179lSNOa3c3Nxwc3Ozqw+5W5KRRBz/1LPFEUu0cYNsuOJuyk6ikcAtbhJPHACxRIMBrtx+2kkks+SlAKc5gbuRnRx4E80NzvLrXbNQSUYiFzlPaSpnzkAlbbTYpt2y3ExUUlISn332GZMnT+bIkSPW7ccff8Tf358vvvgCgMqVKxMWFnbPflxdXUlOTrbZ5+vrS0REhE1Q8u81nHbv3s3rr79OixYtqFChAm5ubly5ciXjbvAOhw4dwmw2M3nyZOrUqUPp0qXvegrxQWP28fGhQIEC7N+/37ovKSmJQ4cOPZQxy71FcY39fMt+vgVup0j28y2/cwyAy4Szn285wm4AfmY/+/mW8/yeaWMWAShDVfJRkBP8wF42c4qfKEhxSmC7PEsEt2et/Ui54FweL1onyn5ZbiZq48aNXL9+nR49euDj42NzrE2bNixYsIDevXszZswYGjduTIkSJWjXrh1JSUl8/fXXDB8+HLhdX7Rjxw7atWuHm5sbefPmpUGDBly+fJlJkybx4osvEhoayqZNm/D29rZeo1SpUixZsoSaNWsSFRXF0KFD0zXrlRolS5YkMTGRjz/+mGeffdam4NwiNWMeMGAA77//PqVKlaJs2bJMmTKFGzduPJQxy73lNuWjCS/e87i/qehdf9mLPA5cTNkoQ1XKUPW+7QqZilOI4o9mUCKPgSw3E7VgwQKaNGlyVwAFt4OogwcP8tNPP9GgQQNWrVrF+vXrqVq1Ko0aNeLAgQPWtuPHj+fMmTOUKFECX19fAMqVK8esWbOYOXMmVapU4cCBAwwZMuSu61+/fp3q1avTuXNnXn/9dfLleziLI1apUoUpU6bwv//9j4oVK7J06VImTpxo0yY1Y37jjTfo3LkzXbt2JTAwEC8vL+tyDyIi4qD0dJ7dTIYWDJIHiIqKwsfHhwY8j4spW2YPR0TEISQZiWxjHZGRkTbZBXtZ/k2vE/wOLtnsq7dMSrzFvpC3M3yMWUWWm4kSEREReRxkuZooERERyQB6Os9uCqJEREQckBbbtJ+CKBEREUeUEYXhDh5EqSZKREREJB00EyUiIuKAlM6zn4IoERERR2Q2bm/29uHAlM4TERERSQfNRImIiDgiFZbbTUGUiIiIAzKRATVRGTKSrEvpPBEREZF00EyUiIiII9KK5XZTECUiIuKAtMSB/ZTOExEREUkHzUSJiIg4Ij2dZzcFUSIiIg7IZBiY7Kxpsvf8rE5BlIiIiCMy/73Z24cDU02UiIiISDpoJkpERMQBKZ1nPwVRIiIijkiF5XZTOk9EREQkHRREiYiIOCLLiuX2bmmwY8cOnn32Wfz9/TGZTKxdu/ZfQzIYPXo0BQoUwMPDgyZNmnDq1CmbNteuXaNjx454e3uTM2dOevToQUxMjE2bn376iaeeegp3d3cCAgKYNGnSXWNZtWoVZcuWxd3dnUqVKvH111+n6V5AQZSIiIhDsqxYbu+WFrGxsVSpUoWZM2emeHzSpEl89NFHzJkzh/3795MjRw6CgoK4deuWtU3Hjh05duwYW7ZsYePGjezYsYNXX33VejwqKoqmTZtSpEgRDh06xAcffMDYsWP55JNPrG327NlD+/bt6dGjBz/88AOtWrWiVatW/Pzzz2n8GRoOXhUmDxQVFYWPjw8NeB4XU7bMHo6IiENIMhLZxjoiIyPx9vbOsH4t/6bXr/s2Li7udvWVlHSL7XveSdcYTSYTa9asoVWrVsDtWSh/f3/eeOMNhgwZAkBkZCT58+dn0aJFtGvXjuPHj1O+fHm+//57atasCUBoaCgtWrTg/Pnz+Pv7M3v2bN566y0iIiJwdXUFYMSIEaxdu5YTJ04A0LZtW2JjY9m4caN1PHXq1KFq1arMmTMn1fegmSgRERFHlIHpvKioKJstPj4+zcM5ffo0ERERNGnSxLrPx8eH2rVrs3fvXgD27t1Lzpw5rQEUQJMmTXBycmL//v3WNk8//bQ1gAIICgri5MmTXL9+3drmzutY2liuk1oKokRERByQyZwxG0BAQAA+Pj7WbeLEiWkeT0REBAD58+e32Z8/f37rsYiICPLly2dz3MXFhdy5c9u0SamPO69xrzaW46mlJQ5ERETELufOnbNJ57m5uWXiaB4dzUSJiIg4ogxM53l7e9ts6Qmi/Pz8ALh48aLN/osXL1qP+fn5cenSJZvjSUlJXLt2zaZNSn3ceY17tbEcTy0FUSIiIo7IyKAtgxQrVgw/Pz/CwsKs+6Kioti/fz+BgYEABAYGcuPGDQ4dOmRts3XrVsxmM7Vr17a22bFjB4mJidY2W7ZsoUyZMuTKlcva5s7rWNpYrpNaCqJEREQckOW1L/ZuaRETE8ORI0c4cuQIcLuY/MiRI5w9exaTycTAgQOZMGEC69ev5+jRo3Tp0gV/f3/rE3zlypWjWbNm9OrViwMHDrB792769etHu3bt8Pf3B6BDhw64urrSo0cPjh07xooVK5g+fTqDBw+2jmPAgAGEhoYyefJkTpw4wdixYzl48CD9+vVL0/2oJkpEREQeiYMHD9KwYUPrZ0tg07VrVxYtWsSwYcOIjY3l1Vdf5caNG9SrV4/Q0FDc3f9ZimHp0qX069ePxo0b4+TkRJs2bfjoo4+sx318fPjmm2/o27cvNWrUIG/evIwePdpmLam6deuybNkyRo0axZtvvkmpUqVYu3YtFStWTNP9aJ0oeSCtEyUi8ug97HWiGtYYmSHrRH13aGKGjzGr0EyUiIiIIzIAcwb04cBUEyUiIiKSDpqJEhERcUDpKQxPqQ9HpiBKRETEERlY13myqw8HpnSeiIiISDpoJkpERMQR3bHiuF19ODAFUSIiIo7IDJgyoA8HpiBKRETEAamw3H6qiRIRERFJB81EiYiIOCLVRNlNQZSIiIgjUhBlN6XzRERERNJBM1EiIiKOSDNRdlMQJSIi4oi0xIHdlM4TERERSQfNRImIiDggrRNlPwVRIiIijkg1UXZTOk9EREQkHTQTJSIi4ojMBpjsnEkyO/ZMlIIoERERR6R0nt0URImIiDikDAiicOwgSjVRIiIiIumgmSgRERFHpHSe3RREiYiIOCKzgd3pOAcvLFc6T0RERCQdNBMlIiLiiAzz7c3ePhyYgigRERFHpJoouymdJyIiIpIOmokSERFxRCost5uCKBEREUekdJ7dlM4TERERSQfNRImIiDgigwyYicqQkWRZCqJEREQckdJ5dlMQJSIi4ojMZsDOdZ7Mjr1OlGqiRERERNJBM1EiIiKOSOk8uymIEhERcUQKouymdJ6IiIhIOmgmSkRExBFpxXK7KYgSERFxQIZhxjDse7rO3vOzOqXzRERERNJBM1EiIiKOyDDsT8c5eGG5gigRERFHZGRATZSCKBEREXE4ZjOY7KxpUk2UiIiIiKSVZqJEREQckdJ5dlMQJSIi4oAMsxnDznSeljgQERERkTTTTJQ8kPH3dG0SiXbP/IqISOokkQj8829whlM6z24KouSBoqOjAdjF15k8EhERxxMdHY2Pj0/Gd2w2wKQgyh4KouSB/P39OXfuHF5eXphMpswezn9OVFQUAQEBnDt3Dm9v78wejkiq6Xf34TIMg+joaPz9/TN7KHIPCqLkgZycnChUqFBmD+M/z9vbW19EkiXpd/fheSgzUBaGAdi7TpRmokRERMTBGGYDw8503kOr18oi9HSeiIiISDpoJkokk7m5uTFmzBjc3NwyeygiaaLf3SzOMGN/Os+x14kyGY4+FyciIuJAoqKi8PHxoYGpNS6mbHb1lWQkss1YQ2RkpEPWxWkmSkRExBFpJspuCqJEREQcUEYsoGxZENRRKYgSERFxIK6urvj5+bErImMWUPbz88PV1TVD+spqVBMlIiL3FB0djZeXV2YPQzLYrVu3SEhIyJC+XF1dcXd3z5C+shoFUSIikqIhQ4Zw/fp13n33Xfz8/DJ7OCKPHa0TJfKQJCcnZ/YQRNLF8rd1oUKF2Lp1K3v27MnkEYk8nhREiWQwwzAwDANnZ2cAfv31V6KiojJ5VCKpZ/kDYODAgRQpUoQvvviCU6dOZfKoRB4/CqJEMpjJZMJkMhEWFkbFihVp164dFStWZPbs2YSHh2f28ETuy2w24+Jy+5mjmzdv0rNnTw4ePMiWLVtISkrK5NGJPF4URImkw79LCS0Fmpb9Gzdu5NVXX+Wll15i3bp1vPPOO3zyySeMHz/+kY9VJC2cnJyIiYnh5ZdfpnTp0oSGhnLu3DmWLFnC0aNHM3t4Io8VBVEi6WAymQCYP38+gPXx3sjISAC+++47nnrqKcaMGUNAQACnT5/m6NGjFChQgLi4uMwZtEgKzOa7F0ucPn06P/30Ezt37mT8+PF8+eWXHD58mNWrVxMdHZ0JoxR5PCmIEkmnb775hldffZVVq1axZMkSKlasyL59+0hOTmbfvn106NCBNWvW4Ofnx6ZNm/jmm28YM2YMHh4eDv/mc3l8ODnd/hqw/AEQGxvLrl27qF+/PsWKFaNYsWK0atWKwYMHs3TpUg4cOJCZwxV5rGixTZF0atiwIc8//zyvvPIKnp6eTJkyhWbNmgFQtmxZmjVrRrFixRg3bhzdu3cnW7ZsREdHs2XLFsqVK0e5cuUy+Q5Ebq8X9NZbbxEVFcXcuXPJkSMH165do1SpUgDEx8fj7u7OO++8w9y5c1m2bBnly5enQIECmTxykcynmSiRVLI8sWRJf/z111+cPHkSwzDo0qULHTp0sBbetmvXjly5cvHmm2/yf//3f2TLdvsln9988w0LFixQSk8yRUozoO7u7iQlJXHixAnWr18P3P79XbhwITdv3sTd3Z3k5GScnZ0pUaIEW7duJSQk5FEPXeSxpCBK5AEswZNlyYJbt24BULRoUbZu3crEiROZN28eZ86csT7VVKNGDTp16sSAAQMYMmQIK1asoFu3bvTs2ZMnn3ySatWqZc7NiEOz1PJ98803/Prrr9b9AwcOxMPDg9WrVxMZGUmbNm0ICAiga9euJCUl4ezszIkTJyhRogReXl4kJycrJS2CViwXSbUVK1bwySefkD17dp588kn69OmDj48PR48epXfv3uTPn5/Vq1djNputdSZjxoxh79693Lp1Cy8vL6ZMmUKZMmUy+U7EUVj+ebcETwA7d+6kQ4cO9OrVi9GjR1v3z5o1i8WLF9OrVy969uzJ9u3bef755ylRogQVKlQgJCSEYcOG8dprr+k1MCJ/UxAl8gCXL1+mb9++7Nixg4EDB3L9+nV27dpFQEAAy5cvJzExkeXLl9OvXz82bNjA008/Ddi+c+zy5cv4+voCt2e2nJycbL7YRDJaUlKSdWb0zsAe4NVXX+XMmTO8/fbbPPXUU8DtwnJLSnrWrFmUKFGCXbt2sWfPHvbt20fr1q3p3LlzptyLyONK6TyRO6T0qpb9+/eTI0cOvv/+e0aMGMFbb72Fj48PK1euZPPmzWTLlo0GDRoQHBxMhw4dCAsLIygoiDfeeMP6xNOdAZSzs7MCKHnoXFxcMJvNjB8/npEjR7Js2TIuXLgAQJ8+fbhx4wZr1qwhJiYGAB8fH4KCgjhw4ABLly4FoF69egwbNozVq1crgBJJgYIoEf5Je1jqnhITE63HAgMD6dWrFwEBAcycOZNSpUqRlJREkyZN6N+/PwABAQGMGzeOihUr0q9fPzw9PZk8eTI+Pj4217H0L5LR/r3e08qVKylYsCAhISGcP3+ecePG8dZbbxEdHU21atUICgpi3759hIaGWs8JDw/H29ubb775hhMnTjzqWxDJcpTOE4dmGIbNrND69euZPXs2/v7+vP7661SsWNEa+Hz55ZeMHTuWESNG0KlTJ9avX0+rVq2YM2cOr776KnC76DwqKop8+fIBd6dRRDKS5ff3zt+zmJgYoqOjefnll+nYsSO9e/cGYMKECXz00UcMGDCAt956i0uXLtGrVy/Cw8MZMGAAJpOJr776irZt21KjRg1KliyZmbcmkjUYIg4qMTHR5nNISIhRpkwZY/DgwUblypWNatWqGSEhIYZhGEZCQoLRuHFjo2fPntb206dPN1xcXAyTyWRERkba9JWcnGwkJyc//JsQhxMeHm40a9bMOH78uM3+K1euGK1btzZGjx5tGIZhLF261EhMTDTCw8ONdu3aGV5eXkbdunWNsmXLGseOHTMMwzB2795tdOrUyShevLjh7+9vzJ8//5Hfj0hWpsU2xWEY//qr3cXFhaSkJFasWEHNmjU5efIkQ4cOpUePHkRHR/Pcc8+xdOlSypQpQ4kSJciZMyc///wzSUlJ/PHHH+zevZsvvviCW7du4e3tbXMtzT7Jw7B//35efPFFqlevbq2zAzh27BiLFi0CoGvXrgB06NCB8+fP8/LLL5M/f36OHTvGmTNnePnll5k5cyYzZ86kbt261K1bl+PHj1O2bFnV6omkkf6ll/+8devWAf885m0JcPbs2YOPjw9vv/02VatWZebMmTRo0AAALy8v/u///o/jx4+zYcMGAAYMGMDx48epXLkyFStWxNXVlRYtWtCpU6dHf1PikH7//Xc8PT1Zt24defLk4datW0yaNIlKlSqxd+9e/ve//1G8eHFr+zVr1hAdHc3cuXMJCAggV65cmM1mFi9ebP3/C4By5copgBJJBwVR8p+2fv16hg4dSkREhLV4/NSpU/Tv35/Q0FBmzJjBiRMnGDFiBDdv3mTlypXWc9u1a0e5cuXYvHkzhw8f5qmnnmLPnj2MGjWKvXv3smTJErJnz55ZtyYOyDAMcuXKxYQJE6hduzYzZ85k6NChBAQEcOHCBeuSGmazGcMwiI2Ntc64wu1FNoODgxk+fDhFixbNxDsR+W9QYbn8pxj/KhSPiYnB09PTps3s2bOZMGECHh4e7Nq1Cz8/P+Li4ujbty/nz5/n448/ti6IuW/fPl599VWefvpppk6dan19C/zzNJRSd/KwWVLQJ06coFGjRly6dIlu3boxb948TCYTn376Kf/3f/9HaGgojRs3tp63fv16xo0bx61bt/Dx8eHPP/9k2bJl1K9fPxPvRuS/Q//6y3/Kv1MSlgDqww8/ZOrUqQAEBwfTsmVLLl++TK5cuQDw8PDgpZdeIi4ujvnz51vPr1OnDk2bNqVatWo2AZRhGDg5OSmAkgx3+PBhwHbJAsvv2dSpU8mVKxeVKlWiRo0a1t/37t27U6ZMGWbPns21a9es57Vs2ZJPPvmE5557jkaNGvHbb78pgBLJSJlX0y6S8UJCQoz33nvP+vnAgQOGYRhGz549jZw5cxrR0dHWdpUrVzZGjhxpc/7w4cONevXqGaGhodZ9espOHpVZs2YZJpPJuHr1qs1+y+9gUlKSYRiG0aVLFyMoKMj44YcfrG22b99umEwm46uvvjLMZrNhGMZd/1dEMpb+jJYs7eeff2bUqFFcvnwZgEOHDjF37lymTp1K6dKlCQoKIiEhgddee43ChQvzxhtvAPDkk0/y7LPPsnbtWo4dO2bt76WXXuLWrVvs3r3bus/JyQnDMPTCVXnogoODKV++PCNGjAD+WQT23zOenTp1IioqiuXLl1v3Pf3007Ru3ZrRo0dz5swZ4J+ZWRWNizwcCqIkS9uxYwe5cuUid+7cALz++uvExsbyxhtvEBQUxNWrV3F1daVChQr06tWLL774gqNHj+Lj40Pz5s0pWLAgH3zwgbW/GjVqsHDhQsaPH29zHZPJpC8ieWgsK+QXLlyYN998k/nz5/Pjjz9iMplsgnfLwq/PPPMMgYGB7Nmzh2+++cZ6/OOPP+bMmTNcv3790d6AiINSECVZkuWL5bXXXuONN97A2dmZmzdvsnPnTipUqICfnx/169e3Bj6W5Qhq167NoEGDAKhbty4tW7Zk48aN1mUMACpWrAjc/RoNkYfFUm+3ZMkSDMOgUKFCjBkzBrh7Fsnye9mjRw/c3NxYtWoV0dHRAPj7+3P16lWqV6/+CEcv4rgUREmWc+df5mazmYsXL9KyZUvef/99WrZsybZt26hevTrz58+3SdUVK1aM3r17c+TIEb766itMJhMNGzZk2LBh1KhR467rqGhcHpWzZ89SqVIl3n33XX7++WdcXFxYv349q1evBlIuMi9fvjwNGzZkx44d7Nmzx3rczc3t0Q5exIFpiQPJUu58R9jFixfJnz8/cHtNp+vXrzNixAgaNmzIwYMHadWqFQMGDKB///64u7tbzxk0aBCbNm1SykMyhfGvZTgA5s2bx9y5c9mwYQMFChTg1KlTvPnmmxw4cIAzZ86kOBvl5OTEjRs3OH78OIGBgY/yFkTkb/pTW7KEO9dkSkpKYtOmTbRu3ZpVq1YBMGLECK5fv86GDRuIjo6mZs2aPPfcc3z11Vfs27cPgHPnzpEnTx6GDBnChx9+aNOv/paQhy05ORlIuch73759ZMuWjQIFCgBQqlQpRo0aRVRUFO+99x6Q8mxUzpw5FUCJZCIFUZIlWL40Jk6cyHPPPcecOXP45ZdfWLduHbGxsVStWpWgoCD27t3L119/DcA777zDzZs3GT9+PN26daNIkSJ8/vnnVK9enR49etj0q6JxedgsReFLlizhvffeY/Hixdy4cQPAunr4X3/9ZW1fpkwZgoKCmDp1KpcuXbI+JSoijw8FUZIlGIbBiBEjmDVrFq+88grdunWjfv36bNu2jSVLlgBY03Zff/01Z8+eJU+ePEybNo3AwEBiYmLYv38/3bp1y9wbkf+0+z2M8Mcff/DEE08wcuRIzp49y8iRI+nbty/Hjh2jXr16mM1mvvzyS2t7d3d3bt68ybVr16xBv4J9kceLS2YPQOTfkpOTcXZ2tqkdMQyD7du306FDB1566SUAGjVqRPfu3VmzZg1NmzalePHidOjQgfnz57N27Vpef/11GjVqRP369a2zAGazWcsVyEPj5OREYmKizer2FgsWLKBYsWLs3r0bV1dXWrVqxUsvvUT27NmZN28elSpV4rPPPiNv3rw8//zzHDlyBA8PD5YtW2ZdAkFEHi+aiZLHhqVmxBJAWR7bhttPL8XExFC6dGngdlDl4+PDCy+8wIkTJ1i6dCkAvXr1Inv27GzdupVLly5Z+7P07+TkpABKHpoNGzZQrVo16+dPP/2U06dPk5SUxIEDB+jSpQuurq6MGjWKdu3a0aJFCwYPHgzAkCFDaNSoEZ07d6Zu3bo0atSI0qVL065dOzp37pxZtyQi96Gn8yTTxMbGkiNHjrv2z5w5k9mzZ5MvXz48PDyYM2cOAQEB1KtXD39/f5YsWWLzGLe/vz/58+dn5syZ1K1bl6NHjxIQEEDOnDkf4d2I3E7ZVahQgZdffpnVq1dTrVo1VqxYgbe3N6VLl6ZDhw6sXr0aLy8vJk6cSPPmzYHbDz34+fmRLVs2Dhw4wG+//UadOnUoXrx4Jt+RiNyPgih55MxmM/Xr16dBgwaMGjUKNzc3zGYzhmEwcOBANmzYwNixYylYsCDTp0/n3LlzrFq1ioiICBo0aMDatWt57rnngNsva+3Xrx9ubm5UrVrV+pJhy3W01pM8TIZhYDabrbOd4eHhFCtWDMMw+PDDD3n99detbQcPHsy0adP4+OOP6d27t/WcQ4cOsWbNGjp06ED58uUz5T5EJH30DSOPlCWwqVu3LvPmzeP48ePA7VqSixcvcvjwYRYtWkS3bt148skncXFx4a+//iI8PJynn36aDh06MGzYMHr16sWaNWsYPHgwLVu2pEyZMvzyyy82KUAFUPIwJScnYzKZcHZ2JjY2loMHD+Li4sKbb75JQEAAp06dAiApKQm4/b67HDlyEBkZyYULFzCbzfz000+MGDGC48ePkytXrsy8HRFJj0f3rmMR27fJ+/v7G7169TKioqIMwzCM3bt3G8WLFzcMwzDefvttw8vLy3jhhReM48ePW8+5deuWMXnyZCMwMNAoXry48corrxiGYRiTJk0yfH19jZiYmEd4N+JILl68aBiG7e+wYRjGhAkTjLx58xo9evQwDhw4YBiGYXz++eeGk5OT8eOPP9q0/fTTT40iRYoY/v7+RnBwsOHu7m5069bNuHnz5qO5CRHJUErnySOXlJSEi4sLX375Je3btyckJISmTZty9OhRXnrpJc6fP0/58uUZP348zZo1A+CXX37h2rVr1KtXD4D4+HiSkpLIkSMH8fHxPPfcc1SrVo33338/M29N/mPMZjOXL1+mY8eOPPfcc9b0nGEYxMfHM2DAAHbu3Mm7775LzZo1yZUrF56enty4cYOXXnqJhIQEtm/fbn3iFODEiRP89NNPRERE0KRJE6XwRLIwBVHyUMTGxvL888/Tt29fWrdufc/6pCeffBJ3d3dWr15NUlIS/fr149ixY2zbto3cuXMDt7/IRowYwa1bt5gyZQouLi4kJiby448/8s033/DZZ5/h4eHB559/ToUKFR71rcp/1JUrV8ibNy8AmzdvJigoyOb46dOnadKkCZMmTaJNmzZ3nb99+3aCgoKYP38+nTp14uDBg/z5558pthWRrElFI/JQODk54e3tzYgRI6yf72RZzuCTTz7hu+++46uvviJPnjy0atUKwzB45ZVXWL16NWFhYTzzzDOsWbOGZs2a4eJye2kzFxcX4uPj+eabb+jduzc//PCDAijJMFu3bqVZs2Z89tlnAAQFBZGUlMTatWuJjIwEYMeOHcTFxVG/fn3reXf+TVqvXj369etH7969eeqpp6hTp451hXL97Sry36CZKMlwllmn48ePU7duXUaOHMmwYcPumo2ypDi6d+/Ozp072bp1KwULFmTfvn30798fk8lEZGQkTz31FDNnzsTDw+Oua92ZJhHJKCdOnGDo0KF4eHgwb948fHx8mDx5MjNmzGD8+PF07tyZH3/8kWrVqrF//36eeOIJa5oabr++pWDBgsDtRTavXLlC9+7d8fX1zczbEpEMpiBKMtSdgdKpU6dYtWoVH3zwAadPn75r3SZL27i4OPLmzcvQoUMZNmwY2bNnJy4ujvj4eG7duoWfnx+ggEkePrPZTHJyMtmyZWPhwoV8+umnPP/88wwZMoTr16/Tvn178ubNy3vvvYevry8tWrQgOTmZHTt2WPu4fPkyCxYsIDg4mEqVKmXi3YjIw6Z0nmQoJycnfvvtN55++mk6duzIrl27iIyMZNy4cYBtGsPJyYmkpCQ8PDyYMGECEydO5PDhwwB4eHjg4+ODn58fZrPZZi0ekYfFycmJbNmyERkZibe3NwULFuTrr7/m1KlT5MqViw4dOnDs2DHWrVuHh4cH7777LgcPHqRr1658+umnhIaGEhwcTGhoKF5eXpl9OyLykCmIkgx169YtBg0ahLe3N1999RXDhw+nR48eTJ8+nR9//BGTyWQTSFnSH4MGDaJEiRLExMRYj1lez+Lk5KQ1n+SRGTt2LPny5eOrr77i6NGj7Ny501ob1aVLF0qXLs3XX3/NDz/8QN26dfnyyy+5dOkSkydPpk+fPtStW5dt27ZRtGjRzL0REXnolM6TdLnXe+hOnTpFlSpV2LBhA40bNwZu14d06dKFpKQktm/ffldflloSpevkUTLueMG1xcGDB3n55ZeZNm0azZo1Izo6mk6dOnHlyhXef/99GjduzPbt2xk8eDDBwcG8/fbbZMuWDbPZzF9//YWnp6cWzRRxIPrzXtLMklozmUycOHGCP//807oqc86cOfH19bU+wWQYBgUKFOC1115j586dbNiwwdqHhWU2ytnZ2Wa/yMNgGIZ1tXELy9Oiv//+O4mJiVSpUgVXV1fy5MnD6NGjyZEjB0uXLrW+sqh+/fp8/fXXhISEALdnSwMCAhRAiTgYBVGSZk5OTpw7d46mTZvSrFkzmjZtSvv27dm9ezceHh6UKlWKsLAwoqKiMJlMODk5WdfbeeONN+77Tjul7eRhssw+OTs7c+3aNRYuXMihQ4eIiooC4MaNG7i7u9v8HgYGBlKuXDk2bdrEmjVrAOjduze+vr7ky5cvU+5DRB4P+saSB0pMTLT5fP78ebp27UrevHnZunUr69atw93dnW7dupGcnExwcDA//PADy5Yts54THh5O27ZtiY6OZufOnY/6FsTBWaoWLLNP7733HsWKFWPWrFm0b9+epk2bcu7cOTp06EB4eDjr1q2zqd0rWbIkMTExTJs2jYiICGtdVN26dTPlfkTk8eCS2QOQx9fy5cupWbMmJUuWBODs2bMULlyYkydPEh4ezubNm8mWLRsrV65k/fr11KlTh/j4eLp06cIff/zB0KFD2bFjB56enmzcuJGpU6eyaNEi3NzcMvnOxJH8e+YzNDSUL774ghUrVlhfK5QjRw4GDhzIF198wYgRIxg7dizFixe31vWdOHGCVq1aUbp0adzd3VOspxIRx6MgSlJ0/fp13nvvPfz9/XnnnXfo2rUrTZs2Zdq0aRw5coTAwECOHj1Kjx49uHbtGpMnT6Znz57W8z/++GNq1qzJjh07+P3331m6dCkNGzYE7v5SE3kYLL9nTk5OHDp0iC+++IIPP/yQZcuW0aRJE5o1a8b+/fsZP348bm5uPP/887i6uvL2229z6NAh+vTpQ+HChTl37hxFixZl0aJFeuJORGzo6TyxcecTcsuXL6dTp05ky5aN4cOHWxfC/O6772jcuDGenp707duXoUOHkjt3bgzDYOvWrdy4ccP6frA7+/t3SkUkI9wvKE9MTGTv3r28+uqrBAYGsnDhQnr27ElycjK+vr7Mnj2bzp07M2bMGPLnz098fDxubm7cuHGDI0eOsGXLFgoUKEC/fv0e8V2JSFagmSgB/gl2LAFPQkKCtVA8f/78jB071tqudu3aNG7cGLPZzMSJE619nDx5ko8//phmzZqRkJCAq6urtT8tXyAZzZJSswRQq1evJiEhgWrVqlGyZEmOHTvGyJEjuXnzJj179mTIkCGYzWbKlSvHuHHjKFOmDD/88IM1XX3t2jU++OADunfvTqlSpWjQoAENGjTIxDsUkcedcioCYA1wli1bxosvvsjatWuZPHkyP/74I1euXGHKlCnA7afnsmfPzqhRo9i+fTvPPfcc7733HqNHj6Zu3bq4u7vTpk0bXF1dU+xfJKNYZjTXrl1L0aJFGT58OIMGDaJp06YsXbqUggULEhcXx/fff8/TTz8N3P79rV27NlWrVqVkyZKULFnSuiL+kiVL2LJlC3/99Vdm3paIZCEKohzMyZMneeutt4iIiLDZf/HiRZo3b86gQYOoVq0aOXPmxDAMAgICGDRoEOPGjePGjRuYTCYSExOpX78+GzZsIH/+/OzZs4edO3eyePFili9fjq+vr95SLw/djRs3aNeuHS+88AJvvvkm+/fvZ926dZQvX55x48ZhNpvp378/OXLkYMuWLdbz6tWrR5cuXdixYweVK1emV69e1KhRgw8++IAxY8Zo9klEUk01UQ5m3rx5XLlyheHDh9vUkcyZM4dFixaxatUqAgICbM45f/48jRs3pkmTJsycORO4XXhuWVgwKioKb29va3ul7uRROHr0KF27dqV06dIsX77cuv/zzz+nT58+fPHFFzRo0IC+ffvy119/MWfOHGvqDuDnn39m7dq1REREUKRIEYYOHZoZtyEiWZiCKAfw1VdfcezYMUaPHm2z/+rVq+TJk4eYmBhatWpFQEAAn376qTVNYgmGDMNg5cqVtG/fnsmTJ3Py5El2797NwoULqVmzprU/BU/yqE2bNo0VK1bQq1cvunfvDsDu3bt57rnnCAsLo2rVqmzYsIFJkyZRr149aw3fncXoWq5ARNJL6bz/OLPZzPr169mwYQP79+8H4NKlS7Rp04aJEydiNpvx9PTkxo0b5MiRA5PJREJCAvBPHZPZbKZt27a8/fbbrF69ml9++YUlS5bYBFB3thd5VF5++WUCAgKsrxP6/vvveemllwgMDKRIkSIAPPvss9SuXZs9e/bw3XffAbZPiCqAEpH0UhD1H5aUlISTkxN9+/bFx8eHBQsWAJAvXz5y5MjBDz/8wNatWwF44YUXWLJkCbGxsTZF4UePHmXz5s0AjBs3jtWrV7Njxw6qVq2q99xJpvP39+f5558nPDycUqVK0bx5c3r16sXGjRvJlSuX9Xf05ZdfJjo6mvXr1wMKnEQkYyiI+o8ym83WF/vWqlWLp59+ml9//ZWVK1cCMHLkSGJjY1m3bh03b96kXbt2BAQE0LZtW86dO0d8fDwnT55k1KhRHD58mJs3bwLg6+sL3E7dacFMeRy8+OKLVK9enbi4OD799FNrUfmdv6O1atXio48+YurUqZk8WhH5L9G34H+U5cvjgw8+oEWLFvz4448cPXqUFStWEBkZSbly5Xj22WfZt28fISEhFC9enMWLF/PLL79Qp04dgoKCqFmzJq6urrz++utkz57dpn+l7uRx4ebmRtu2bSlZsiRhYWHA7d//fy/yWq9evUwbo4j8NymI+g+bMGECU6dOpVOnTrRv35769euze/duFi9eDEDfvn3JmTMna9as4fTp09SoUYPNmzczf/58nn32WbZt28aqVavw9vbWkgXyWGvQoAFPP/00hw8ftqbstEK+iDxsejrvP+DOp+ju/MJo1KgR5cqVsy5LEBcXR9euXbl27RozZ86kTJkyLFmyhI8//pi2bdvyxhtv3NW3paZEqTt53P3yyy90796dihUrMnfuXM2WishDp2/GLMwS4Fi+LCIjI63HwsPDiY6Oply5csDtv8o9PDx4+eWX+fXXX/n8888B6Ny5M7ly5SIsLOyuBTgNw7C+wFXkcVe+fHkmT57M7NmzFUCJyCOhmaj/gHnz5vHRRx+RN29e3NzcmDlzJiVKlCAoKAhXV1dWrVqFu7u7tX2RIkXw8fHhww8/pGnTphw/fhxfX1/y5s2biXchIiKStWiKIQsxDIPk5GQA69NHb7zxBu+88w4DBw7krbfewtPTk5YtW3Ls2DEmTJhASEgIGzZssM5aHTlyhHz58uHs7Mzu3bsBKFeuHHnz5tWSBSIiImngktkDkNSxrLDs7OzMxYsXcXd3x9XVlX379vHJJ5/QrFkz4uPjWbBgAX/99Rd//fUXTZs2pWfPnrz55puEhITw/PPPM2PGDBo3bkz79u2pUqWKzTWUthMREUk9fWs+Zu6VXbUEOEuWLKFAgQKsW7eOP/74g/Pnz9OsWTPee+898uXLR2xsLHv27KFp06bA7XfiDRw4kDNnzjBs2DACAgKYMGGCNYDS7JOIiEj6qCbqMWEYhrWQG+DcuXP4+fmRLVs2APbs2UNYWBhnzpyhVatWNG/enFOnTtG2bVv++OMPSpUqxfjx43n22WcBOHnyJBcuXLC+kf7WrVvExcVZXxp857vDREREJO2UznsMWJYmMJlMHDlyhCFDhnD9+nVcXV3p3Lkzr732GgsWLGDt2rVUrVqV4OBgnJycyJcvH9WqVcNsNhMSEoK/v7+1zyVLlnDlyhXq1q2Lq6srbm5uuLu7a8kCERGRDKJv0seAyWTi1q1bdOnShVq1alGqVCmGDRuGYRi88847hISE8Pbbb1OkSBGioqKsAVCePHlo2bIlrq6udO/endWrV/Pdd9/RrFkzli5dSrNmzazvwbOsH6UlC0RERDKG0nmPgaSkJAYMGMDcuXNZt24dwcHBAPz555+0bdsWPz8/1q5dy//+9z8+//xzxowZw4svvmg99/Dhw/Tr1w+z2UxUVBS1atVi9uzZeHl5ZeZtiYiI/KcpnfcYcHFxITg4mOPHj7N7926Cg4NJTk6mSJEieHh4kJCQAEDr1q3Zs2cPy5cvp2nTpnh7e2MymahVqxY7d+4kPj6emJgYa1rPspK5iIiIZDzldR4TLVq04IknnuC7775j165dODs788MPP/Drr79St25dAEqXLk3Lli3566+/WLJkCfBPbZObmxve3t74+/tjNpsxm80KoERERB4ipfMeI0eOHGHkyJHkyZMHLy8vlixZQrdu3ZgxY4a1TWRkJK+//jpHjx5l1apVlChRIhNHLCIi4riUznuMVK1alaCgID788EPc3d3Zv38/FSpUAG4vSWAymfDx8aFVq1aULVvW5mk8ERERebQ0E/WYiYiIoH///sTFxfHZZ5+RO3dua22TZSkEERERyXyqiXrM+Pn50bp1a65du8b8+fMBrLVN/w6gFP+KiIhkHgVRj6E2bdpQuXJllixZwpEjR+7ZTrNSIiIimUc1UY8hNzc32rRpg5+fH8WKFcvs4YiIiEgKVBMlIiIikg5K5z3mLO+6ExERkceLZqJERERE0kEzUSIiIiLpoCBKREREJB0URImIiIikg4IoERERkXRQECUiIiKSDgqiRERERNJBQZSIiIhIOiiIEhEREUkHBVEiIiIi6aAgSkRERCQd/h9RU4x3Kfv/LwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Selected model threshold results on untouched test set:\n",
            "  threshold_label  threshold    recall  precision        f1        f2  \\\n",
            "0     default_0_5   0.500000  0.775510   0.894118  0.830601  0.796646   \n",
            "1          F2_OOF   0.219160  0.857143   0.777778  0.815534  0.840000   \n",
            "2    FN:FP = 10:1   0.064901  0.877551   0.661538  0.754386  0.823755   \n",
            "3    FN:FP = 50:1   0.022887  0.887755   0.455497  0.602076  0.746141   \n",
            "4   FN:FP = 100:1   0.022887  0.887755   0.455497  0.602076  0.746141   \n",
            "\n",
            "        mcc  tp   fp  fn     tn  \n",
            "0  0.832440  76    9  22  56855  \n",
            "1  0.816166  84   24  14  56840  \n",
            "2  0.761470  86   44  12  56820  \n",
            "3  0.635111  87  104  11  56760  \n",
            "4  0.635111  87  104  11  56760  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Bootstrap confidence intervals"
      ],
      "metadata": {
        "id": "P5CMOnVV54y5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "bootstrap_ci = bootstrap_confidence_intervals(\n",
        "    y_true=y_test,\n",
        "    y_score=y_test_selected_score,\n",
        "    threshold=f2_threshold,\n",
        "    n_reps=BOOTSTRAP_REPLICATES,\n",
        "    seed=SEED\n",
        ")\n",
        "\n",
        "bootstrap_ci.to_csv(\n",
        "    TABLE_DIR / f\"bootstrap_ci_selected_{selected_name}_F2_threshold.csv\",\n",
        "    index=False\n",
        ")\n",
        "\n",
        "print(\"\\nBootstrap confidence intervals:\")\n",
        "print(bootstrap_ci)"
      ],
      "metadata": {
        "id": "n2GLpvfL57o6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "outputId": "d8802d0d-e533-4b81-c6f6-d914c8679c8b"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Bootstrap confidence intervals:\n",
            "              metric      mean    ci_2_5   ci_97_5  valid_replicates\n",
            "0  average_precision  0.862877  0.794749  0.920799               500\n",
            "1            roc_auc  0.970701  0.940195  0.993311               500\n",
            "2             recall  0.856305  0.782049  0.921084               500\n",
            "3          precision  0.779985  0.693323  0.859185               500\n",
            "4                 f1  0.815590  0.749254  0.871922               500\n",
            "5                 f2  0.839326  0.773409  0.893214               500\n",
            "6                mcc  0.816536  0.749881  0.872826               500\n",
            "7  balanced_accuracy  0.927943  0.890773  0.960226               500\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Calibration diagnostics"
      ],
      "metadata": {
        "id": "n8hDqj_F5-fa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plot_calibration_curve_custom(\n",
        "    y_test,\n",
        "    y_test_selected_score,\n",
        "    FIG_DIR / f\"calibration_curve_{selected_name}.png\",\n",
        "    f\"Calibration Curve: {selected_name}\"\n",
        ")\n",
        "\n",
        "calibration_summary = {\n",
        "    \"selected_configuration\": selected_name,\n",
        "    \"test_brier_score\": float(\n",
        "        brier_score_loss(y_test, y_test_selected_score)\n",
        "    ),\n",
        "    \"note\": (\n",
        "        \"Lower Brier score indicates better probability calibration. \"\n",
        "        \"Inspect the calibration curve before deciding whether calibration is needed.\"\n",
        "    )\n",
        "}\n",
        "\n",
        "save_json(\n",
        "    calibration_summary,\n",
        "    TABLE_DIR / f\"calibration_summary_{selected_name}.json\"\n",
        ")\n",
        "\n",
        "print(\"\\nCalibration summary:\")\n",
        "print(calibration_summary)\n",
        "\n",
        "RUN_SIGMOID_CALIBRATION = False\n",
        "\n",
        "if RUN_SIGMOID_CALIBRATION:\n",
        "    calibrated_model = CalibratedClassifierCV(\n",
        "        selected_estimator,\n",
        "        method=\"sigmoid\",\n",
        "        cv=cv\n",
        "    )\n",
        "\n",
        "    calibrated_model.fit(X_train, y_train)\n",
        "\n",
        "    y_test_calibrated_score = calibrated_model.predict_proba(X_test)[:, 1]\n",
        "\n",
        "    calibrated_metrics = evaluate_predictions(\n",
        "        y_true=y_test,\n",
        "        y_score=y_test_calibrated_score,\n",
        "        threshold=f2_threshold\n",
        "    )\n",
        "\n",
        "    save_json(\n",
        "        calibrated_metrics,\n",
        "        TABLE_DIR / f\"calibrated_sigmoid_test_metrics_{selected_name}.json\"\n",
        "    )\n",
        "\n",
        "    plot_calibration_curve_custom(\n",
        "        y_test,\n",
        "        y_test_calibrated_score,\n",
        "        FIG_DIR / f\"calibration_curve_sigmoid_{selected_name}.png\",\n",
        "        f\"Sigmoid Calibration Curve: {selected_name}\"\n",
        "    )"
      ],
      "metadata": {
        "id": "grpt7Evg6Ccs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 583
        },
        "outputId": "81f4513c-796b-43ed-9e83-85a65213ac1d"
      },
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x500 with 1 Axes>"
            ],
            "image/png": 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2bdvedBvOaNSoEa1ateLzzz9n0aJF6d5PTk7m+eefty9XqlSJvXv3OozT2bFjB+vXr3dpv0WKFKFly5bMmTOHWbNm4eXlRceOHR36dO3alQ0bNrB8+fJ061+4cIHU1FT78okTJ9JdJr2eV155hRMnTvDpp5/av3cffvgh7u7uDmPdwPYonLNnz/Lkk09muO2bndH7r9WrVxMfH0+dOnWcXqdNmzakpaU5/HwCfPDBB1gsFpfGJF3h7u5OREQEixYt4vjx4/b2gwcPphszdSsy+v8iOTmZTz75JMv2IQWbzjhJgVWpUiVmzpxJZGQk1atXd5g5/LfffmPu3Ln2Z2U98MADeHl50b59e55++mni4+OZMmUKQUFBnDhxIlP79/HxYdmyZURFRREWFsaPP/7IkiVLeOmll5y6Pbtdu3YsWLCAhx56iLZt2xITE8PkyZOpUaOGw9kFX19fatSowezZs6latSrFihWjZs2a1KxZM90269SpQ1RUFJ999pn9ksfmzZuZMWMGHTt2pHnz5pn6rBn58ssveeCBB+jUqRPt27enRYsWFCpUiAMHDjBr1ixOnDjBu+++C8ATTzzB+++/T8uWLenduzenT59m8uTJ3HHHHenGsNxMZGQkjz/+OJ988gktW7ZMN8Zq2LBhLF68mHbt2tmnVrh06RI7d+5k3rx5HDlyxH5pz9npCLZs2cLEiRMZMGAADRs2tLeXKVOGV199lSFDhjB//nw6d+4MwKOPPsquXbsYO3Ysmzdv5pFHHiE0NJRLly6xa9cuvv32WwoXLmwf33NFbGwsX3/9NWCbFX7fvn1MmjQJX19fhg8f7vQxat++Pc2bN+fll1/myJEj1KlTh59++onvvvuO5557jkqVKjm9rf8aPXo0P/30E02aNKFfv372cFazZs10A90zq3HjxhQtWpSoqCieffZZLBYLX331lUthU+SGTLqbTyTX2L9/v/Hkk08aFSpUMLy8vIzChQsbTZo0MT7++GOHW5cXL15s1K5d2/Dx8TEqVKhgvPXWW8bUqVPT3Y6e2QkwS5YsaURHRztMhvjfCR2vZbVajTfffNMoX7684e3tbdSrV8/44YcfMrzF+rfffjMaNGhgeHl5OTUB5pgxY4zQ0FDD09PTCAkJueEEmNdyZub0KxISEox3333XuPPOOw1/f3/Dy8vLqFKlivHMM8843PJuGIbx9ddf2yflrFu3rrF8+fIbToB5PXFxcYavr68BGF9//XWGfS5evGiMGDHCqFy5suHl5WUUL17caNy4sfHuu+86THbpzHQEqampRv369Y3g4GAjNjY2w/fr1q1rlC1bNt2El2vWrDG6dOlilC5d2vD09DQCAgKMhg0bGtHR0caJEycc+l47HYHFYjGKFStmPPjgg8aWLVuuW9/1XLx40Rg8eLARHBxseHp6GlWqVLnhBJgZgfTTYKxatcqoV6+efWLRzz//3Bg6dKjh4+Pj0O960xH8/vvvDv1Wr15tAMbq1avtbevXrzfuvvtuw9fX1wgODjZeeOEFY/ny5en6aToCyQw9q05EREzVsWNH/vzzTw4cOGB2KSI3pTFOIiKSYy5fvuywfODAAZYuXWp/OLZIbqczTiIiBURaWtpNJ8L09/d3+VEvrihdujQ9e/akYsWK/PXXX0yaNImkpCS2bdtGlSpVsm2/IllFg8NFRAqIY8eO3XSyyujoaEaPHp1tNbRq1Ypvv/2WkydP4u3tTaNGjXjzzTcVmiTP0BknEZECIjExkXXr1t2wT8WKFdPNaC8iVyk4iYiIiDhJg8NFREREnFTgxjhZrVaOHz9O4cKFXXoUhYiIiORPhmFw8eJFgoODcXO78TmlAhecjh8/TkhIiNlliIiISC5z7NgxypYte8M+BS44XXlg5bFjxwgICDC5GhERETFbXFwcISEhDg+1vp4CF5yuXJ4LCAhQcBIRERE7Z4bwaHC4iIiIiJMUnEREREScpOAkIiIi4qQCN8bJWWlpaaSkpJhdhojTPD09cXd3N7sMEZF8TcHpGoZhcPLkSS5cuGB2KSIuK1KkCKVKldIcZSIi2UTB6RpXQlNQUBB+fn76BSR5gmEYJCQkcPr0acD2BHoREcl6Ck7/kZaWZg9Nt912m9nliLjE19cXgNOnTxMUFKTLdiIi2UCDw//jypgmPz8/kysRyZwrP7sanycikj0UnDKgy3OSV+lnV0Qkeyk4iYiIiDhJwUmcsmbNGiwWi0t3G1aoUIHx48dnW00iIiI5zdTg9Msvv9C+fXuCg4OxWCwsWrTopuusWbOG+vXr4+3tTeXKlZk+fXq215kZaVaDDYf+5bvt/7Dh0L+kWY1s3V/Pnj2xWCz07ds33XsDBgzAYrHQs2fPbK1BREQkvzM1OF26dIk6deowceJEp/rHxMTQtm1bmjdvzvbt23nuuefo06cPy5cvz+ZKXbNs1wnueetnuk3ZyKBZ2+k2ZSP3vPUzy3adyNb9hoSEMGvWLC5fvmxvS0xMZObMmZQrVy5b9y0iIlIQmBqcWrduzeuvv85DDz3kVP/JkycTGhrKe++9R/Xq1Rk4cCBdunThgw8+yOZKnbds1wn6fb2VE7GJDu0nYxPp9/XWbA1P9evXJyQkhAULFtjbFixYQLly5ahXr569LSkpiWeffZagoCB8fHy45557+P333x22tXTpUqpWrYqvry/NmzfnyJEj6fa3bt06mjZtiq+vLyEhITz77LNcunQp2z6fiIiI2fLUGKcNGzYQERHh0NayZUs2bNiQbfs0DIOE5FSnXhcTU4he/CcZXZS70jZ68W4uJqY4tT3DcP3y3hNPPMG0adPsy1OnTqVXr14OfV544QXmz5/PjBkz2Lp1K5UrV6Zly5acO3cOgGPHjtGpUyfat2/P9u3b6dOnD8OHD3fYxqFDh2jVqhWdO3fmjz/+YPbs2axbt46BAwe6XLOIiMgNWdPMrsAuT02AefLkSUqWLOnQVrJkSeLi4rh8+bJ9AsD/SkpKIikpyb4cFxfn0j4vp6RRY1TWXAo0gJNxidQa/ZNT/Xe/2hI/L9e+RY8//jgjRozgr7/+AmD9+vXMmjWLNWvWALbLo5MmTWL69Om0bt0agClTprBixQq++OILhg0bxqRJk6hUqRLvvfceALfffjs7d+7krbfesu9n7NixPPbYYzz33HMAVKlShY8++ojw8HAmTZqEj4+PS3WLiIhk6Mx+mNMDWr0Jle4zu5q8FZwyY+zYsYwZM8bsMnJMiRIlaNu2LdOnT8cwDNq2bUvx4sXt7x86dIiUlBSaNGlib/P09OSuu+5iz549AOzZs4ewsDCH7TZq1MhheceOHfzxxx9888039jbDMLBarcTExFC9evXs+HgiIlIQxR6DFaMg9F5wM/diWZ4KTqVKleLUqVMObadOnSIgICDDs00AI0aMYMiQIfbluLg4QkJCnN6nr6c7u19t6VTfzTHn6Dnt95v2m97rTu4KLebUvjPjiSeesF8yc3bgvavi4+N5+umnefbZZ9O9p4HoIiJySwwDrkzoW6IqdPsWSlQ3PTRBHgtOjRo1YunSpQ5tK1asSHc25L+8vb3x9vbO9D4tFovTl8uaVilB6UAfTsYmZjjOyQKUCvShaZUSuLtl3wzPrVq1Ijk5GYvFQsuWjqGvUqVKeHl5sX79esqXLw/YHs/x+++/2y+7Va9encWLFzust3HjRofl+vXrs3v3bipXrpxtn0NERAqgiydhfh8IfxFCm9raQpuZW9N/mBrd4uPj2b59O9u3bwds0w1s376do0ePArazRT169LD379u3L4cPH+aFF15g7969fPLJJ8yZM4fBgwebUX467m4WotvXAGwh6b+uLEe3r5GtoQnA3d2dPXv2sHv37nQPei1UqBD9+vVj2LBhLFu2jN27d/Pkk0+SkJBA7969AdtxPnDgAMOGDWPfvn3MnDkz3XxZL774Ir/99hsDBw5k+/btHDhwgO+++06Dw0VEJPP+2gCfNoMjv8L3g3LVoPArTA1O//vf/6hXr579VvkhQ4ZQr149Ro0aBcCJEyfsIQogNDSUJUuWsGLFCurUqcN7773H559/nu6sipla1SzNpMfrUyrQcXB0qUAfJj1en1Y1S+dIHQEBAQQEBGT43rhx4+jcuTPdu3enfv36HDx4kOXLl1O0aFHAdqlt/vz5LFq0iDp16jB58mTefPNNh23Url2btWvXsn//fpo2bWr/vgUHB2f7ZxMRkXzGMGDjJJjRDuJP2S7LPToH3DI3ZCU7WYzM3POeh8XFxREYGEhsbGy6YJGYmEhMTAyhoaG3fFdYmtVgc8w5Tl9MJKiwD3eFFsv2M00iWfkzLCKSI5LiYfEz8Of/z0FYswu0/xC8/XOshBtlg2vlqTFOeYm7m4VGlW4zuwwREZHcK+EcTGsNZ/aCmwc88AaEPX11YHgupOAkIiIi5vAtCqVqweUL0HUGlLvb7IpuSsFJREREck5aKqQm2i7FWSy2y3JJ8VC45M3XzQXMnxBBRERECob40/BVR1jwFFittjavQnkmNIHOOImIiEhOOLYZ5kTBxePgWQj+PQAlbje7KpfpjJOIiIhkH8OATZ/BtDa20FS8Kjy1Ok+GJtAZJxEREckuyZfg++dg5xzbco0O0GEieBc2taxboeAkIiIi2WNuTzjwE1jc4f5XodGAXD3VgDMUnERERCR7hL8Ip/fAQ5Ohwj1mV5MlNMZJbmr06NGULFkSi8XCokWLzC7HadOnT6dIkSL25dGjR1O3bl37cs+ePenYsWOO1lShQgXGjx+fo/sUEckx1jQ4vv3qctmG8MzWfBOaQMEp3+jZsycWiwWLxYKXlxeVK1fm1VdfJTU19Za2u2fPHsaMGcOnn37KiRMnaN269S3Xem2AySnPP/88q1atypF9XRvarvj999956qmncqQGEZEcdelf+LoTTG0JJ/642u7hZV5N2UCX6vKRVq1aMW3aNJKSkli6dCkDBgzA09OTESNGuLyttLQ0LBYLhw4dAqBDhw5Y8vh1aX9/f/z9b+3ZR8nJyXh5Zf4fgRIlStzS/kVEcqW/t8CcHhD3N3j6QewxKF3b7Kqyhc445SPe3t6UKlWK8uXL069fPyIiIli8eDEASUlJPP/885QpU4ZChQoRFhbGmjVr7OteOUOyePFiatSogbe3N0888QTt27cHwM3NzSE4ff7551SvXh0fHx+qVavGJ5984lDL33//Tbdu3ShWrBiFChWiYcOGbNq0ienTpzNmzBh27NhhP0M2ffr0636mqVOncscdd+Dt7U3p0qUZOHCg/b3333+fWrVqUahQIUJCQujfvz/x8fHX3db1znSNGTOGEiVKEBAQQN++fUlOTra/d++99zJw4ECee+45ihcvTsuWLW+67zVr1tCrVy9iY2Ptn3H06NFA+kt1R48epUOHDvj7+xMQEEDXrl05depUupq/+uorKlSoQGBgII888ggXL1687ucUEckxhgG/fwHTWtlCU7FK0GcVVGtrdmXZRmecnJV86frvWdzB08fJvm7g6Xvzvl6FXKsvA76+vvz7778ADBw4kN27dzNr1iyCg4NZuHAhrVq1YufOnVSpUgWAhIQE3nrrLT7//HNuu+02Spcuzb333kuvXr04ceKEfbvffPMNo0aNYsKECdSrV49t27bx5JNPUqhQIaKiooiPjyc8PJwyZcqwePFiSpUqxdatW7FarURGRrJr1y6WLVvGypUrAQgMDMyw/kmTJjFkyBDGjRtH69atiY2NZf369fb33dzc+OijjwgNDeXw4cP079+fF154IV2Iu5FVq1bh4+PDmjVrOHLkCL169eK2227jjTfesPeZMWMG/fr1c3rfjRs3Zvz48YwaNYp9+/YBZHimy2q12kPT2rVrSU1NZcCAAURGRjqE2kOHDrFo0SJ++OEHzp8/T9euXRk3bpxDjSIiOS7lMvwwBHbMtC1XawcdPwGfjP9NzzeMAiY2NtYAjNjY2HTvXb582di9e7dx+fLl9CtGB1z/9XUXx76vl7p+36ltHPu+FZpxPxdFRUUZHTp0MAzDMKxWq7FixQrD29vbeP75542//vrLcHd3N/755x+HdVq0aGGMGDHCMAzDmDZtmgEY27dvd+izcOFC49ofk0qVKhkzZ850aHvttdeMRo0aGYZhGJ9++qlRuHBh499//82w1ujoaKNOnTo3/UzBwcHGyy+/fNN+V8ydO9e47bbb7MvTpk0zAgMDr7vfqKgoo1ixYsalS5fsbZMmTTL8/f2NtLQ0wzAMIzw83KhXr94t7/uK8uXLGx988IFhGIbx008/Ge7u7sbRo0ft7//5558GYGzevNles5+fnxEXF2fvM2zYMCMsLCzDOm74MywikpU2Trb9vhpdxDB+/cAwrFazK8q0G2WDa+mMUz7yww8/4O/vT0pKClarlUcffZTRo0ezZs0a0tLSqFq1qkP/pKQkbrvtNvuyl5cXtWvf+Jr0pUuXOHToEL179+bJJ5+0t6emptrPHG3fvp169epRrFixTH+W06dPc/z4cVq0aHHdPitXrmTs2LHs3buXuLg4UlNTSUxMJCEhAT8/P6f2U6dOHYe+jRo1Ij4+nmPHjlG+fHkAGjRokC373rNnDyEhIYSEhNjbatSoQZEiRdizZw933nknYLu8V7jw1cniSpcuzenTp53ah4hItrmzD/z9P6j3OFQMN7uaHKPg5KyXjl//PYu74/Kwgzfoe82wsud2Zr6mazRv3pxJkybh5eVFcHAwHh62b298fDzu7u5s2bIFd3fHWv97CcnX1/emA8CvjOOZMmUKYWFhDu9d2bavr2+69Vx1s20cOXKEdu3a0a9fP9544w2KFSvGunXr6N27N8nJyU6HF2cUKuR42TQn9w3g6enpsGyxWLBeeTimiEhOsabBlmlQ93Hb8BQ3d+g8xeyqcpyCk7NcGXOUXX1volChQlSuXDlde7169UhLS+P06dM0bdr0lvZRsmRJgoODOXz4MI899liGfWrXrs3nn3/OuXPnMjzr5OXlRVpa2g33U7hwYSpUqMCqVato3rx5uve3bNmC1Wrlvffew83NFkbnzJnj8ufZsWMHly9ftge1jRs34u/v73AWKDP7duYzVq9enWPHjnHs2DH7/nbv3s2FCxeoUaOGy59FRCTbJJyD+X3g0CrbVAMPfmR2RabRXXUFQNWqVXnsscfo0aMHCxYsICYmhs2bNzN27FiWLFni8vbGjBnD2LFj+eijj9i/fz87d+5k2rRpvP/++wB069aNUqVK0bFjR9avX8/hw4eZP38+GzZsAGyXnmJiYti+fTtnz54lKSkpw/2MHj2a9957j48++ogDBw6wdetWPv74YwAqV65MSkoKH3/8MYcPH+arr75i8uTJLn+W5ORkevfuze7du1m6dCnR0dEMHDjQHogy4sy+K1SoQHx8PKtWreLs2bMkJCSk205ERAS1atXiscceY+vWrWzevJkePXoQHh5Ow4YNXf4sIiLZ4vg2+DTcFpo8fKF8E7MrMpWCUwExbdo0evTowdChQ7n99tvp2LEjv//+O+XKlXN5W3369OHzzz9n2rRp1KpVi/DwcKZPn05oaChgO9vy008/ERQURJs2bahVqxbjxo2zX8rr3LkzrVq1onnz5pQoUYJvv/02w/1ERUUxfvx4PvnkE+644w7atWvHgQMHANvYpPfff5+33nqLmjVr8s033zB27FiXP0uLFi2oUqUKzZo1IzIykgcffNA+dcD1OLPvxo0b07dvXyIjIylRogRvv/12uu1YLBa+++47ihYtSrNmzYiIiKBixYrMnj3b5c8hIpIttn4JX7SE2KNQNBT6rIQ6kWZXZSqLYRiG2UXkpLi4OAIDA4mNjSUgIMDhvcTERGJiYggNDcXHx+c6WxDJvfQzLCJZIiURlj4P276yLVdtbXvenG8RU8vKLjfKBtfSGCcRERFxdOk07PkesMB9r8A9Q+AGQxgKEgUnERERcVSkHHSZavu68vWnhSmIFJxEREQKOqsVfn0XSteFqg/Y2hSYMqTgJCIiUpBdPg8LnoYDy22PS3lmGxS67ebrFVAKTiIiIgXViT9gTnc4fwQ8fKDlWIWmm1BwyoBmZZa8Sj+7IuK07d/CD89BaiIUKQ+RX0HpOmZXlespOP2Hl5cXbm5uHD9+nBIlSuDl5XXTR5CI5AaGYZCcnMyZM2dwc3PDy8vL7JJEJLeyptmmGvjflcHf90Onz8Av888XLUgUnP7Dzc2N0NBQTpw4wfHjN3g2nUgu5efnR7ly5W4487mIFHBu7mBYAQvcOxyavaCpBlyg4HQNLy8vypUrR2pq6k2fNSaSm7i7u+Ph4aGzpCKSMav1akBq/TbU7AKht/b80oJIwSkDFosFT0/PdE+lFxERyXOsVlj/Afz1Gzw6x3bGycNboSmTFJxERETyq8RYWNgP9v3/A933LoEaD5pbUx6n4CQiIpIfnfoTZj8O5w6Duxe0eVehKQsoOImIiOQ3f8yB7wdBSgIEhkDXGVCmgdlV5QsKTiIiIvnJr+/BqldtX1dsDp2/0KSWWUj3H4qIiOQnVR4ATz9oNgwen6/QlMV0xklERCSviz8D/iVsX5eqBc9ug8KlzK0pn9IZJxERkbzKMGD9RzC+Fhz7/Wq7QlO2UXASERHJixLjYE4PWDESUi/Dnu/MrqhA0KU6ERGRvOb0XttUA/8eADdPaP0WNHzC7KoKBAUnERGRvGTXfPjuGUi5BAFloOuXULah2VUVGApOIiIiecXhNTDv/88shTaDLtOgUHFTSypoFJxERETyitBwqN4ebqsMzV8Bd/0az2k64iIiIrnZsd+hZA3wKgQWCzw8w/agXjGF7qoTERHJjQwDNnwCU1vaHp9iGLZ2hSZT6YyTiIhIbpMUD4ufgT8XXG1LSwEPL/NqEkDBSUREJHc5sx/mdIcze8HNA1qOhbuetF2mE9MpOImIiOQWu7+DRf0hOR4Kl7aNZyoXZnZV8h8KTiIiIrlBUjwsed4WmsrfAw9PA/8gs6uSayg4iYiI5Abe/rawtH85tIjWVAO5lL4rIiIiZjm6CRL+hWptbMsV7rG9JNfSdAQiIiI5zTBg02cwvQ0seNI2IFzyBJ1xEhERyUnJl+D752DnHNtylfshINjUksR5Ck4iIiI55d9DMPtxOL0bLO7wwGtwd39NNZCHKDiJiIjkhL1LYGFfSIoD/5K2B/RWaGJ2VeIiBScREZGc8NdvttBUrhE8PB0KlzK7IskEBScREZGcEDEaipSDhk+Au6fZ1Ugm6a46ERGR7PD3Fpjby/aMObCFpbCnFZryOJ1xEhERyUqGAf+bCsuGQ1oyBNWA8GFmVyVZRMFJREQkqyQnwJKhsGOmbbl6e9tZJsk3FJxERESywrnDMLsHnNoJFjfbmKbGz2qqgXxGwUlERORWHV4Lc7pDYiwUKgFdpkJoM7Orkmyg4CQiInKrAoLBaoWyd0HXGZoJPB8z/a66iRMnUqFCBXx8fAgLC2Pz5s037D9+/Hhuv/12fH19CQkJYfDgwSQmJuZQtSIiIv/vyt1yAMWrQM8foOcShaZ8ztTgNHv2bIYMGUJ0dDRbt26lTp06tGzZktOnT2fYf+bMmQwfPpzo6Gj27NnDF198wezZs3nppZdyuHIRESnQ/tkKExraLtFdEVwXPLxMK0lyhqnB6f333+fJJ5+kV69e1KhRg8mTJ+Pn58fUqVMz7P/bb7/RpEkTHn30USpUqMADDzxAt27dbnqWSkREJMtsmQFTW8L5I7D6Ddv0A1JgmBackpOT2bJlCxEREVeLcXMjIiKCDRs2ZLhO48aN2bJliz0oHT58mKVLl9KmTZvr7icpKYm4uDiHl4iIiMtSEuG7gfD9s7b5mW5vC4/O0V1zBYxpg8PPnj1LWloaJUuWdGgvWbIke/fuzXCdRx99lLNnz3LPPfdgGAapqan07dv3hpfqxo4dy5gxY7K0dhERKWDO/2W7a+7EDttUA/e9Ak0Gg5vpQ4Ulh+Wp7/iaNWt48803+eSTT9i6dSsLFixgyZIlvPbaa9ddZ8SIEcTGxtpfx44dy8GKRUQkz7twDD4Lt4Umv9vg8QXQdKhCUwFl2hmn4sWL4+7uzqlTpxzaT506RalSGT8xeuTIkXTv3p0+ffoAUKtWLS5dusRTTz3Fyy+/jFsGP8Te3t54e3tn/QcQEZGCIbAsVL4f/j0IXb+EIiFmVyQmMi0ue3l50aBBA1atWmVvs1qtrFq1ikaNGmW4TkJCQrpw5O7uDoChwXkiIpJVEs7B5Qu2ry0WaP8hPLFMoUnMnQBzyJAhREVF0bBhQ+666y7Gjx/PpUuX6NWrFwA9evSgTJkyjB07FoD27dvz/vvvU69ePcLCwjh48CAjR46kffv29gAlIiJyS07sgNndoeQdEPmN7ZKcl5/ZVUkuYWpwioyM5MyZM4waNYqTJ09St25dli1bZh8wfvToUYczTK+88goWi4VXXnmFf/75hxIlStC+fXveeOMNsz6CiIjkJ9u+gSVDIPX/J1aOPwUBpc2tSXIVi1HArnHFxcURGBhIbGwsAQEBZpcjIiK5QWoS/PgCbJluW67yAHT6DHyLmlqW5AxXsoGeVSciIgXbhWMwpwcc3wpYoPlL0PR53TUnGVJwEhGRgsswYPZjtnFNvkWh0+dQJeLm60mBpTgtIiIFl8UCbT+AsnfBU2sVmuSmFJxERKRguXwBDq2+uly2AfT+CYqWN60kyTsUnEREpOA4uQs+uxe+fQRO/HG1Xc+bEydpjJOIiBQMO2bD94Mg9TIElgPDanZFkgcpOImISP6WmgzLX4Lfp9iWK7WAzp+DXzFz65I8ScFJRETyr9h/YG4U/P27bbnZC3DvcHDT0yYkcxScREQk//pjti00+QTCQ5/B7a3MrkjyOAUnERHJv5oMgktn4K4noVhFs6uRfEB31YmISP6RGAcroiHl/5815+YOrcYqNEmW0RknERHJH07vgdmPw78HITEW2o83uyLJhxScREQk79s5DxY/AykJEFAG6j1udkWSTyk4iYhI3pWWAj+NhE2TbMuh4dBlKhQqbm5dkm8pOImISN4UdwLm9oRjG23L9wyB+17RVAOSrRScREQkb0pLhrP7wDsAHpoM1dqaXZEUAApOIiKSNxUtD5FfQ+HScFsls6uRAkLTEYiISN6QdBHm9oL9y6+2VbhHoUlylIKTiIjkfmf2wZQW8OcC+G4AJCeYXZEUULpUJyIiudufi/4/LMXbLss9PAO8/MyuSgooBScREcmd0lJhZTRsmGBbrtDUNtWAf5C5dUmBpuAkIiK5T0oifN0Z/lpnW278LLSIBnf92hJz6SdQRERyH08fKF4FTmyHjp9AjQ5mVyQCKDiJiEhuYRiQcvnq+KXWb0HjZ3TXnOQquqtORETMl3wJ5veBbx8Ba5qtzcNboUlyHZ1xEhERc509CHO6w+nd4OYBf/8O5e42uyqRDCk4iYiIefZ8D4v6Q1Ic+JeEh6crNEmupuAkIiI5Ly0Vfn4N1o+3LZdrZAtNhUuZWZXITSk4iYhIzlsyGLZ+afv67gFw/xhw9zS3JhEnaHC4iIjkvLuehkIloMs0aPWmQpPkGTrjJCIi2c8w4MxeCKpuWy5VEwb9oUenSJ6jM04iIpK9khNgUT+YfA8c3XS1XaFJ8iAFJxERyT7nDsMX98OOb21nnU7vNrsikVuiS3UiIpI99i2DBU9BUuzV8UyhTc2uSuSWKDiJiEjWsqbBmrHwyzu25bJ3QdcZEBBsbl0iWcDlS3XLli1j3bp19uWJEydSt25dHn30Uc6fP5+lxYmISB60e9HV0HTX09BziUKT5BsuB6dhw4YRFxcHwM6dOxk6dCht2rQhJiaGIUOGZHmBIiKSx9zRCWo/Ap2mQJu3wcPL7IpEsozLl+piYmKoUaMGAPPnz6ddu3a8+eabbN26lTZt2mR5gSIikgfsnAdVW4G3P1gs0OlTsysSyRYun3Hy8vIiISEBgJUrV/LAAw8AUKxYMfuZKBERKSBSLsN3A2B+b1j8jO3OOZF8zOUzTvfccw9DhgyhSZMmbN68mdmzZwOwf/9+ypYtm+UFiohILnX+CMzuDif/AIsblKpldkUi2c7lM04TJkzAw8ODefPmMWnSJMqUKQPAjz/+SKtWrbK8QBERyYUOrIBPw22hye826L4Qmg6xXaYTyccshlGwzqvGxcURGBhIbGwsAQEBZpcjIpK3WK3wy9uwZhxgQJkG0PVLCNQVB8m7XMkGmZo5/NChQ7zyyit069aN06dPA7YzTn/++WdmNiciInnF5XPw+xeAAQ17Q68fFZqkQHE5OK1du5ZatWqxadMmFixYQHx8PAA7duwgOjo6ywsUEZFcpFBxeHg6dJwE7d4HD2+zKxLJUS4Hp+HDh/P666+zYsUKvLyuzs1x3333sXHjxiwtTkREcoFtX8Ofi64uV2gCdR81rRwRM7l8V93OnTuZOXNmuvagoCDOnj2bJUWJiEgukJIIy16ELdPBsxAE14WiFUwuSsRcLp9xKlKkCCdOnEjXvm3bNvsddiIiksddOArTWtlCExa4ZzAEljO7KhHTuRycHnnkEV588UVOnjyJxWLBarWyfv16nn/+eXr06JEdNYqISE469LNtqoHj28C3KDw+D8KHgVum7icSyVdc/r/gzTffpFq1aoSEhBAfH0+NGjVo1qwZjRs35pVXXsmOGkVEJKf88i581cl291xwPXj6F6gcYXZVIrmGy2OcvLy8mDJlCiNHjmTXrl3Ex8dTr149qlSpkh31iYhITkq8ABhQPwpavw2ePmZXJJKruByc1q1bxz333EO5cuUoV07Xu0VE8jzDuDrjd4vRUK4xVNND20Uy4vKluvvuu4/Q0FBeeukldu/enR01iYhITtkxG77qCKnJtmV3D4UmkRtwOTgdP36coUOHsnbtWmrWrEndunV55513+Pvvv7OjPhERyQ6pybBkKCx8Cg6vgW1fml2RSJ5wS8+qi4mJYebMmXz77bfs3buXZs2a8fPPP2dlfVlOz6oTkQIv9h+YGwV//25bDh8O4S+Am7u5dYmYxJVscMsP+U1LS+PHH39k5MiR/PHHH6Slpd3K5rKdgpOIFGiH18K8JyDhLPgEQqfPoeoDZlclYqpsf8gvwPr16+nfvz+lS5fm0UcfpWbNmixZsiSzmxMRkey27RvbeKaEs1CqFjy1VqFJxEUu31U3YsQIZs2axfHjx7n//vv58MMP6dChA35+ftlRn4iIZJWQMPDyh+rtoe174OlrdkUieY7LwemXX35h2LBhdO3aleLFi2dHTSIiklUun7fN/g1QvDL0XQdFyl2dfkBEXOJycFq/fn121CEiIllt5zz4/jl45GuoeK+trWh5MysSyfOcCk6LFy+mdevWeHp6snjx4hv2ffDBB7OkMBERyaTUZFgxEjZNti1v/fJqcBKRW+LUXXVubm6cPHmSoKAg3G7wkEeLxaK76kREzBR3wjbVwLFNtuWmQ6H5y5pqQOQGXMkGTp1xslqtGX4tIiK5yJF1MLcXXDoN3oHw0GTNAi6SxVyejuDLL78kKSkpXXtycjJffun6zLMTJ06kQoUK+Pj4EBYWxubNm2/Y/8KFCwwYMIDSpUvj7e1N1apVWbp0qcv7FRHJV07uhBkP2kJT0B3w1GqFJpFs4PIEmO7u7pw4cYKgoCCH9n///ZegoCCXLtXNnj2bHj16MHnyZMLCwhg/fjxz585l37596bYPtnDWpEkTgoKCeOmllyhTpgx//fUXRYoUoU6dOk7tU5fqRCRfMgxY2BcwoN148NIUMSLOyvJLdf9lGAaWDG5j/fvvvwkMDHRpW++//z5PPvkkvXr1AmDy5MksWbKEqVOnMnz48HT9p06dyrlz5/jtt9/w9PQEoEKFCq5+BBGR/OHMPvAvCb5FbNMLdJgAbh6aakAkGzkdnOrVq4fFYsFisdCiRQs8PK6umpaWRkxMDK1atXJ6x8nJyWzZsoURI0bY29zc3IiIiGDDhg0ZrrN48WIaNWrEgAED+O677yhRogSPPvooL774Iu7uGvgoIgXIrgXw3UAIbQaPzAQ3N3D3NLsqkXzP6eDUsWNHALZv307Lli3x9/e3v+fl5UWFChXo3Lmz0zs+e/YsaWlplCxZ0qG9ZMmS7N27N8N1Dh8+zM8//8xjjz3G0qVLOXjwIP379yclJYXo6OgM10lKSnIYkxUXF+d0jSIiuU5aCqwcDRsm2JaT420vHw09EMkJTgenK8GkQoUKREZG4uPjk21FXY/VaiUoKIjPPvsMd3d3GjRowD///MM777xz3eA0duxYxowZk8OViohkg4unYF4v+Ov/JyJu8hzcNxLcXR51ISKZ5PJddVFRUVkSmooXL467uzunTp1yaD916hSlSpXKcJ3SpUtTtWpVh8ty1atX5+TJkyQnJ2e4zogRI4iNjbW/jh07dsu1i4jkuKMb4dNmttDkVRi6fgX3j1FoEslhTgWnYsWKcfbsWQCKFi1KsWLFrvtylpeXFw0aNGDVqlX2NqvVyqpVq2jUqFGG6zRp0oSDBw86zCW1f/9+SpcujZeXV4breHt7ExAQ4PASEclT0lJsd8zFn4QS1W1TDdTQUxpEzODUnyoffPABhQsXtn+d0V11mTFkyBCioqJo2LAhd911F+PHj+fSpUv2u+x69OhBmTJlGDt2LAD9+vVjwoQJDBo0iGeeeYYDBw7w5ptv8uyzz2ZJPSIiuZK7J3T5AjZPgTbvgrf/zdcRkWzhVHCKioqyf92zZ88s23lkZCRnzpxh1KhRnDx5krp167Js2TL7gPGjR486POIlJCSE5cuXM3jwYGrXrk2ZMmUYNGgQL774YpbVJCKSK5w9CKd3Xz2zVKYBPNTA3JpExPUJMLdu3Yqnpye1atUC4LvvvmPatGnUqFGD0aNHX/eSWW6hCTBFJNfb8z0s7AdpydD7Jwiua3ZFIvmaK9nA5cHhTz/9NPv37wds0wNERkbi5+fH3LlzeeGFFzJXsYiIQFoqrIiG2Y9D8kXbWabCGd8sIyLmcDk47d+/n7p16wIwd+5cwsPDmTlzJtOnT2f+/PlZXZ+ISMEQfwa+6gjrx9uWGw2EqMUKTiK5TKYeuXLlrraVK1fSrl07wDb+6MqddyIi4oJjv8OcHnDxOHgWsj06pWYns6sSkQy4HJwaNmzI66+/TkREBGvXrmXSpEkAxMTEpJsFXEREnHBolS00Fa8KkV9DidvNrkhErsPl4DR+/Hgee+wxFi1axMsvv0zlypUBmDdvHo0bN87yAkVE8r1mL4CHN9zZB7wLm12NiNyAy3fVXU9iYiLu7u54eubuh0zqrjoRMd2/h2DtW9D+Q/D0NbsakQLPlWyQ6bn6t2zZwp49ewCoUaMG9evXz+ymREQKjr1LbbOAJ8WC323QaqzZFYmIC1wOTqdPnyYyMpK1a9dSpEgRAC5cuEDz5s2ZNWsWJUqUyOoaRUTyPmsarH4Tfn3XthwSBo2fMbcmEXGZy9MRPPPMM8THx/Pnn39y7tw5zp07x65du4iLi9OjT0REMnLpX/i689XQFNYXon6AgGBz6xIRl7k8xikwMJCVK1dy5513OrRv3ryZBx54gAsXLmRlfVlOY5xEJEed+AO+7QZxf4OnHzz4MdTqYnZVIvIf2TrGyWq1ZjgA3NPT0z6/k4iI/D/fIpCSAMUq2aYaKFnD7IpE5Ba4fKnuvvvuY9CgQRw/ftze9s8//zB48GBatGiRpcWJiORJ1rSrXxcpB4/Ph6dWKzSJ5AMuB6cJEyYQFxdHhQoVqFSpEpUqVSI0NJS4uDg+/vjj7KhRRCTvOBcDU5rDvh+vtpWpDz6B5tUkIlnG5Ut1ISEhbN26lZUrV7J3714AqlevTkRERJYXJyKSp+z/CRb0gcRYWP4SVL4f3DM964uI5EJZNgFmXqHB4SKS5axptgkt175lWy7TELrOgMCy5tYlIk5xJRu4fKkOYNWqVbRr185+qa5du3asXLkyU8WKiORpCedgZteroenOPtBrqUKTSD7lcnD65JNPaNWqFYULF2bQoEEMGjSIgIAA2rRpw8SJE7OjRhGR3Onyefg0HA6uBA9feOhTaPue7blzIpIvuXyprmzZsgwfPpyBAwc6tE+cOJE333yTf/75J0sLzGq6VCciWeqHIXDoZ4j8CkrVMrsaEcmEbL1Ud+HCBVq1apWu/YEHHiA2NtbVzYmI5C0pibbLc1e0GgtPrVFoEikgXA5ODz74IAsXLkzX/t1339GuXbssKUpEJFe6cBSmtoS5UZCWamvz8LZNcikiBYLL98nWqFGDN954gzVr1tCoUSMANm7cyPr16xk6dCgfffSRva+eXSci+cbBlTC/j21ck29ROHcYSlQ1uyoRyWEuj3EKDQ11bsMWC4cPH85UUdlJY5xExCVWq+3hvKvfBAwIrgddv7TNCC4i+UK2PqsuJiYm04WJiOQpl8/DgqfhwHLbcoOe0Oot8PQxtSwRMY+mtBURuZ75fWyX6Ny9bdMM1O9udkUiYjIFJxGR67n/VYj9Bx6aDMF1za5GRHKBTM0cLiKSL6UmQcyvV5dL3gH9flNoEhE7BScREYDYv2Faa/iqIxzddLXdTf9MishVTv2L0KlTJ+Li4gD48ssvSUpKytaiRERy1OE18Gkz+GcLePlDcrzZFYlILuVUcPrhhx+4dOkSAL169dIM4SKSPxgG/Po+fPUQJPwLpWrD02uhcguzKxORXMqpweHVqlVjxIgRNG/eHMMwmDNnznXnOejRo0eWFigiki0SY2FRf9j7g2257mO2O+c8fc2tS0RyNacmwPztt98YMmQIhw4d4ty5cxQuXBiLxZJ+YxYL586dy2ALuYcmwBQRAP43DX54Dty9oPXbtjmaMvh3TUTyP1eygcszh7u5uXHy5EmCgoJuqUizKDiJCGC7TLdsONTuCmUamF2NiJjIlWzg8u0iMTExlChRItPFiYiYIjUZfnkHki7ali0WaP2WQpOIuMTlCTDLly/PhQsX+OKLL9izZw9ge/Bv7969CQwMzPICRURuWdxxmNsTjm2CU3/Cw9PNrkhE8iiXzzj973//o1KlSnzwwQecO3eOc+fO8cEHH1CpUiW2bt2aHTWKiGRezK+2qQaObQLvQKgdaXZFIpKHuTzGqWnTplSuXJkpU6bg4WE7YZWamkqfPn04fPgwv/zyS7YUmlU0xkmkgDAM+O1jWDkajDQoWRO6fgm3VTK7MhHJZbJ1cLivry/btm2jWrVqDu27d++mYcOGJCQkuF5xDlJwEikAEuPguwGwZ7FtufYj0O4D8PIzty4RyZWydXB4QEAAR48eTdd+7NgxChcu7OrmRESyXkqC7dKcm6dtbqaHJis0iUiWcHlweGRkJL179+bdd9+lcePGAKxfv55hw4bRrVu3LC9QRMRlhUtB16/A4gYhd5pdjYjkIy4Hp3fffReLxUKPHj1ITU0FwNPTk379+jFu3LgsL1BE5KbSUmBFNJRtADU729rKhZlbk4jkSy6PcboiISGBQ4cOAVCpUiX8/PLGaXCNcRLJZy6ehLm94Ohvtgf0DtoBhYqbXZWI5CGuZAOXzzhd4efnR61atTK7uojIrftrA8yNgvhT4B0AHScpNIlItsp0cBIRMY1hwMZJsGIkWFOhRHWI/BqKVza7MhHJ5xScRCRvsVphQR/YNd+2XLMLPPgReBUyty4RKRAUnEQkb3Fzg4Ay4OYBD7wBYU/bnjsnIpIDFJxEJG9ITQYPL9vXLaKhVhcoXcfcmkSkwMlUcDpw4ACrV6/m9OnTWK1Wh/dGjRqVJYWJiACQlgqrxtgmtIz6wRae3D0UmkTEFC4HpylTptCvXz+KFy9OqVKlsPznFLnFYlFwEpGsE38a5j0BR361LR/4Caq3M7cmESnQXA5Or7/+Om+88QYvvvhidtQjImJzbDPMiYKLx23zM3WYqNAkIqZzOTidP3+ehx9+ODtqERGxTTWweQosfwmsKVC8qm2qgRK3m12ZiIjrD/l9+OGH+emnn7KjFhERWDMWfhxmC001OsCTPys0iUiu4fIZp8qVKzNy5Eg2btxIrVq18PT0dHj/2WefzbLiRKQAqh1pO+PUdCg0GqCpBkQkV3H5WXWhoaHX35jFwuHDh2+5qOykZ9WJ5ELnDkOxileXE2PBJ9C8ekSkQMnWZ9XFxMRkujAREQfWNFj9BqwbD4/Ph0rNbe0KTSKSS7k8xum/DMPAxRNWIiI2l/6FrzvBr++BkQZHN5pdkYjITWUqOH355ZfUqlULX19ffH19qV27Nl999VVW1yYi+dXfW+DTZnB4DXj6QecvoPkIs6sSEbkply/Vvf/++4wcOZKBAwfSpEkTANatW0ffvn05e/YsgwcPzvIiRSSfMAzYMg1+fBHSkuG2yrapBoKqm12ZiIhTMjU4fMyYMfTo0cOhfcaMGYwePTrXj4HS4HARE8X8AjPa276u1g46TgIf/X8oIubK1sHhJ06coHHjxunaGzduzIkTJ1zdnIgUJBWaQv0etjNNjZ/VVAMikue4PMapcuXKzJkzJ1377NmzqVKlSpYUJSL5yMFVcPm87WuLBdp/BE0GKTSJSJ7k8hmnMWPGEBkZyS+//GIf47R+/XpWrVqVYaASkQLKmgZr37K9qjwA3WaDm5sCk4jkaS4Hp86dO7Np0yY++OADFi1aBED16tXZvHkz9erVy+r6RCQvSjgH8/vAoVW25SLlbFMO3NoMKCIipnN5cHhep8HhItns+DaY3QNij4KHL7T/EOpEml2ViMh1uZINnPrzLy4uzuHrG70yY+LEiVSoUAEfHx/CwsLYvHmzU+vNmjULi8VCx44dM7VfEcliW7+EL1raQlPRUOizUqFJRPIVpy7VFS1alBMnThAUFESRIkWwZDBGwTAMLBYLaWlpLhUwe/ZshgwZwuTJkwkLC2P8+PG0bNmSffv2ERQUdN31jhw5wvPPP0/Tpk1d2p+IZJOkeFj7DqQlwe1tbFMN+BYxuyoRkSzl1KW6tWvX0qRJEzw8PFi7du0N+4aHh7tUQFhYGHfeeScTJkwAwGq1EhISwjPPPMPw4cMzXCctLY1mzZrxxBNP8Ouvv3LhwgX7eKub0aU6kWx0fBscWg1NnrMNBBcRyQOyfB6n/4ah0NBQQkJC0p11MgyDY8eOuVRocnIyW7ZsYcSIq49acHNzIyIigg0bNlx3vVdffZWgoCB69+7Nr7/+esN9JCUlkZSUZF/O7OVEEcnAgZWQ8O/Vy3HB9WwvEZF8yuU/CUNDQzlz5ky69nPnzhEaGurSts6ePUtaWholS5Z0aC9ZsiQnT57McJ1169bxxRdfMGXKFKf2MXbsWAIDA+2vkJAQl2oUkQxYrbD2bfimCyx+Bk7uMrsiEZEc4XJwujKW6Vrx8fH4+PhkSVHXc/HiRbp3786UKVMoXry4U+uMGDGC2NhY+8vVs2Iico3L5+HbR2D1G4ABdR+F4pr8VkQKBqfncRoyZAgAFouFkSNH4ufnZ38vLS2NTZs2UbduXZd2Xrx4cdzd3Tl16pRD+6lTpyhVqlS6/ocOHeLIkSO0b9/e3ma1Wm0fxMODffv2UalSJYd1vL298fb2dqkuEbmOE3/AnO5w/gh4+EDb96HeY2ZXJSKSY5wOTtu2bQNsZ5x27tyJl5eX/T0vLy/q1KnD888/79LOvby8aNCgAatWrbJPKWC1Wlm1ahUDBw5M179atWrs3LnToe2VV17h4sWLfPjhh7oMJ5Kdtn8LPzwHqYlQpDxEfgWl65hdlYhIjnI6OK1evRqAXr168eGHH2bZHWlDhgwhKiqKhg0bctdddzF+/HguXbpEr169AOjRowdlypRh7Nix+Pj4ULNmTYf1ixQpApCuXUSy2IWjttBU5QHo9Bn4FjW7IhGRHOfyI1fGjx9PampquvZz587h4eHhcqCKjIzkzJkzjBo1ipMnT1K3bl2WLVtmHzB+9OhR3HRbs4j5mg2DYqFQs4umGhCRAsvlR660bt2a9u3b079/f4f2yZMns3jxYpYuXZqlBWY1zeMk4qRDq2H9h9DtW/D0NbsaEZFsk+WPXPmvTZs20bx583Tt9957L5s2bXJ1cyKS21it8Ot78HUnOPz/4UlERIBMXKpLSkrK8FJdSkoKly9fzpKiRMQkly/Aon6w7//PHNd73DYLuIiIAJk443TXXXfx2WefpWufPHkyDRo0yJKiRMQEp/6EKc1tocndG9p/BB0mgmf2zs8mIpKXuHzG6fXXXyciIoIdO3bQokULAFatWsXvv//OTz/9lOUFikgOOLACZneH1MsQGAJdv4Qy9c2uSkQk13H5jFOTJk3YsGEDISEhzJkzh++//57KlSvzxx9/0LRp0+yoUUSyW4lqtgHgle6Dp9YqNImIXIfLd9XldbqrTuT/JcWDt//V5bMHbdMNuLmbV5OIiAmy9a66/0pMTCQuLs7hJSJ5QMwv8FE92LvkalvxygpNIiI34XJwSkhIYODAgQQFBVGoUCGKFi3q8BKRXMwwbNMLfNkBLp2GDRNtbSIi4hSXg9OwYcP4+eefmTRpEt7e3nz++eeMGTOG4OBgvvzyy+yoUUSyQmKc7QG9K0aBYYU63eCxeWCxmF2ZiEie4fJddd9//z1ffvkl9957L7169aJp06ZUrlyZ8uXL88033/DYY3pSukiuc3ovzH4c/j0Abp7Q+i1o+IRCk4iIi1w+43Tu3DkqVqwIQEBAAOfOnQPgnnvu4Zdffsna6kTk1sX+DVPus4WmgDLwxDK4s7dCk4hIJrgcnCpWrEhMTAwA1apVY86cOYDtTFSRIkWytDgRyQKBZaFuNwgNh6d/gbINza5IRCTPcvlSXa9evdixYwfh4eEMHz6c9u3bM2HCBFJSUnj//fezo0YRcdXFk2BxB/8StuWWY213zOmuORGRW3LL8zj99ddfbNmyhcqVK1O7du2sqivbaB4nyff++g3m9oTiVaH7InB3+e8jEZECJdvmcUpJSaFFixYcOHDA3la+fHk6deqUJ0KTSL5mGLbpBaa3g/hTkPCv7SUiIlnGpT9FPT09+eOPP7KrFhHJrKSLsPgZ+HOhbbnWw9D+Q/AqZG5dIiL5jMuDwx9//HG++OKL7KhFRDLjzH6Y0sIWmtw8oPU70GmKQpOISDZwefBDamoqU6dOZeXKlTRo0IBChRz/cdYAcZEcZBiw8Ck4uw8Kl4aHZ0C5MLOrEhHJt1wOTrt27aJ+fduT0/fv3+/wnkXzwojkLIsFOk6CFdHQYQL4B5ldkYhIvub0XXWHDx8mNDQ0z4cj3VUneV78aTi6EWo8aHYlIiL5QrbcVVelShXOnDljX46MjOTUqVOZr1JEXHd0E3zaDOb1soUnERHJUU4Hp2tPTC1dupRLly5leUEikgHDgE2fwvQ2cPEEFKsEvsXMrkpEpMDRzHgiuV3yJfh+EOyca1u+4yF4cAJ4+5tbl4hIAeR0cLJYLOnGN+X18U4iud7ZgzCnO5zebXuEygOvwd399YBeERGTOB2cDMOgZ8+eeHt7A5CYmEjfvn3TTUewYMGCrK1QpCA7uMIWmvxLwsPToXxjsysSESnQnA5OUVFRDsuPP/54lhcjItcI62ubFbx+DyhcyuxqREQKvFt+yG9eo+kIJFe7dBZWvQot3wDvwmZXIyJSILiSDTQ4XCS3+Pt/MKcHxP0Dacnw0GSzKxIRkWsoOImYzTDgf1PhxxfBmgK3VYYmg8yuSkREMqDgJGKm5ARYMgR2fGtbrtbO9ggVH11GFhHJjRScRMxy/i+Y9Ric2gkWN4gYDY2f1VQDIiK5mIKTiFk8fODSGfArDg9Pg9BmZlckIiI3oeAkkpMM4+oZpcIl4dFZUCgIAsuYW5eIiDjF6WfVicgtSjgHX3eGnfOutgXXU2gSEclDdMZJJCf8sxXmREHsUTixHW5vDV6FbrqaiIjkLgpOItltywxY+rxtbqZiFaHrVwpNIiJ5lIKTSHZJuWwLTNu+ti3f3sY21YBvEVPLEhGRzFNwEskOKYkwtZXtspzFDe57BZoMBjcNKxQRycsUnESyg6cPVAyH2GPQ+Quo1NzsikREJAsoOIlkFasVkmLBt6ht+b5RENYPAkqbW5eIiGQZXTcQyQoJ5+DbSPi6C6Qm2drcPRSaRETyGZ1xErlVJ3bA7O5w4S/bbOAndkDIXWZXJSIi2UDBSeRWbPsalgyF1EQoUh4iv4bStc2uSkREsomCk0hmpCbBjy/Alum25SotodOnV8c3iYhIvqTgJJIZPwyG7d8AFmj+MjQdqqkGREQKAAUnkcxoOhT+Wg9t34PKEWZXIyIiOUTBScQZViv8/TuUC7Mt31YJBm6x3TknIiIFhq4tiNzM5Qsw61GY2hIOrrrartAkIlLg6F9+kRs5uQtmPw7nY8DdGy6dNbsiERExkYKTyPXsmA3fD4LUyxBYDiK/hOB6ZlclIiImUnASuVZqMix/CX6fYluu1AI6fw5+xcytS0RETKfgJHKt/T9eDU3hL9pebu7m1iQiIrmCgpPItao/CHf3h9BwuL2V2dWIiEguorvqRAwDNk+xPagXwGKBVmMVmkREJB0FJynYEuNgTndY+jwseMo2X5OIiMh16FKdFFyn99imGvj3ILh7QbU2trNNIiIi16HgJAXTznmw+BlISYCAstD1SyjbwOyqREQkl1NwkoIlLQV+GgmbJtmWK94Lnb+AQsVNLUtERPIGBScpWJLjYe8S29dNh0LzlzXVgIiIOE3BSQoW36K2GcDjjkO1tmZXIyIieYyCk+RvhgEbPwHvwlC/h60tuJ4enSIiIpmi4CT5V9JF2wDwPxfa7pqrcA8Uq2h2VSIikoflinmcJk6cSIUKFfDx8SEsLIzNmzdft++UKVNo2rQpRYsWpWjRokRERNywvxRQZ/bBlBa20OTmCS3fhKKhZlclIiJ5nOnBafbs2QwZMoTo6Gi2bt1KnTp1aNmyJadPn86w/5o1a+jWrRurV69mw4YNhISE8MADD/DPP//kcOWSa/25CKbcB2f3QeFg6LUU7npSczSJiMgtsxiGYZhZQFhYGHfeeScTJkwAwGq1EhISwjPPPMPw4cNvun5aWhpFixZlwoQJ9OjR46b94+LiCAwMJDY2loCAgFuuX3KZFaNg/Ye2rys0hS7TwL+EuTWJiEiu5ko2MPWMU3JyMlu2bCEiIsLe5ubmRkREBBs2bHBqGwkJCaSkpFCsWLHsKlPyEq/Ctv82GQTdFyk0iYhIljJ1cPjZs2dJS0ujZMmSDu0lS5Zk7969Tm3jxRdfJDg42CF8/VdSUhJJSUn25bi4uMwXLLmTNe3qXExNh0KFJlC+sbk1iYhIvmT6GKdbMW7cOGbNmsXChQvx8fHJsM/YsWMJDAy0v0JCQnK4Ssk2hgEbJ8PnLSA5wdbm5qbQJCIi2cbU4FS8eHHc3d05deqUQ/upU6coVarUDdd99913GTduHD/99BO1a9e+br8RI0YQGxtrfx07dixLaheTJV+C+X1g2YtwfBvs+NbsikREpAAwNTh5eXnRoEEDVq1aZW+zWq2sWrWKRo0aXXe9t99+m9dee41ly5bRsGHDG+7D29ubgIAAh5fkcWcPwucRsGseuHlAq3HQ8AmzqxIRkQLA9AkwhwwZQlRUFA0bNuSuu+5i/PjxXLp0iV69egHQo0cPypQpw9ixYwF46623GDVqFDNnzqRChQqcPHkSAH9/f/z9/U37HJJD9nwPi/pDUhz4l4SHZ0D564dsERGRrGR6cIqMjOTMmTOMGjWKkydPUrduXZYtW2YfMH706FHc3K6eGJs0aRLJycl06dLFYTvR0dGMHj06J0uXnPa/qfDDYNvX5RrDw9Og8I0v6YqIiGQl0+dxymmaxykPi/0bPg2H2pFw/xhw9zS7IhERyQdcyQamn3ESuaHYfyCwjO3rwLIwYDMUus3cmkREpMDK09MRSD5mGLB5CnxUF/b8cLVdoUlEREyk4CS5T3ICLOwLS5+HtGTY96PZFYmIiAC6VCe5zbnDMLs7nNoFFneIGA2NnzG7KhEREUDBSXKTfT/CgqchKRYKlbA9oDe0qdlViYiI2Ck4Se5w6k/49hHb1yFh8PB0CAg2tSQREZFrKThJ7lDyDrjradvXD7wOHl7m1iMiIpIBBScxzz9bIaAMFLZNdkqrcbaH9IqIiORS+i0lOc8wYMt0mNoS5j0Baam2doUmERHJ5XTGSXJWymVY8jxs/9q27BMIqYngrucMiohI7qfgJDnn/BHbVAMn/wCLG9w3Epo8pzNNIiKSZyg4Sc44sALm94HEC+B3G3SZChXvNbsqERERlyg4SfZLS4XlL9tCU5mG0HWG7blzIiIieYyCk2Q/dw/o+qVtQPj9Y8DD2+yKREREMkWDSyR7HN8O276+uhxUDVqPU2gSEZE8TWecJOtt+xp+GALWVLitMpS72+yKREREsoSCk2SdlET48QXYOsO2XLUVlLjd3JpERESykIKTZI0LR2FODzi+DbBA85eh6VBNNSAiIvmKgpPcukM/w7zecPkc+BaFzp9D5QizqxIREclyCk5y607vsYWm4Hq2u+eKlDO7IhERkWyh4CS37u7+4FUIaj8Cnj5mVyMiIpJtNABFXHdyJ3zzMCTG2ZYtFmjQU6FJRETyPQUncc32b+Hz++HAT7DqVbOrERERyVG6VCfOSU2CZSPgf1/YlitHQPOXzK1JREQkhyk4yc3F/g1zouCf/wEWCH8Rwl8AN3ezKxMREclRCk5yY39vgZkPQ8K/4BMInT6Hqg+YXZWIiIgpFJzkxoqEgLsXlKoFXb+CYqFmVyQiImIaBSdJLyXx6h1y/kHQY7EtQHn6mluXiIiIyXRXnTg6tRsmNYY/5lxtK1FVoUlERAQFJ/mvnfPg8xZw7hD88g6kpZpdkYiISK6iS3UCqcnw0yuw+VPbcsV7ofNUcNePh4iIyH/pN2NBF3cC5kbBsU225aZDofnLmmpAREQkAwpOBdnlC/BZOMSfAu8AeOhTqNbG7KpERERyLQWngsy3CNR9DPYvh8iv4LZKZlckIiKSq1kMwzDMLiInxcXFERgYSGxsLAEBAWaXk/OSLkLyJShcyrZsTbM9TsXLz9y6RERETOJKNtBddQXJmX0w5T6Y9agtLIFtLJNCk4iIiFMUnAqKPxfaQtPZ/bYB4ReOmV2RiIhInqMxTvldWgqsiIaNE23LFZpCl2ngX8LcukRERPIgBaf87OIpmNsTjv5mW24yCO4bpfmZREREMkm/QfOz7/rbQpNXYej4CdR40OyKRERE8jSNccrP2rwDIXfDU6sVmkRERLKAglN+khQPe364ulysIjyxDIpXMa8mERGRfETBKb84e8D2gN7Zj8PBVVfbLRbzahIREclnNMYpP9i9GBb1h+SL4F8KvAqZXZGIiEi+pOCUl6Wlws+vwvoPbcvlm9imGihc0ty6RERE8ikFp7wq/gzM6wVHfrUtNxoIEaPB3dPUskRERPIzBae86uBKW2jyLAQdJkDNTmZXJCIiku8pOOVVdbvBhb/gjoegxO1mVyMiIlIg6K66vCI5AZa/DAnnrrbdO1yhSUREJAfpjFNe8O8hmN0dTv8J/x6ER2ebXZGIiEiBpOCU2+1dCgv7QlIsFAqCxs+aXZGIiEiBpeCUW1nTYPWb8Ou7tuWQMHh4BgSUNrcuERGRAkzBKTdKOAfznoDDq23LYX3h/tfAw8vcukRERAo4Bafc6txh8PSDBz+GWl3MrkZERERQcMo9DMP2X4sF/IrBI9+AxR1K1jC3LhEREbHTdAS5Qcpl+G4AbJl+ta1ULYUmERGRXEZnnHJQmtVgc8w5Tl9MJKiwD3eFFsP9whGY0x1O7oRdC6BaO/AvYXapIiIikgEFpxyybNcJxny/mxOxifa2Tv5/8pblYzxT4sCvOHSZqtAkIiKSiyk45YBlu07Q7+ut/P8oJtywMshjAYNSFwBwoVgdikR9C4FlzCtSREREbkrBKZulWQ3GfL/bHposWJni+R4t3LcB8FXq/UyJ78PqwsG4m1emiIiIOEGDw7PZ5phzDpfnDNzYaq3CZcOLwcn9GJnai6NxaWyOOXeDrYiIiEhuoDNO2ez0RVtoKsRlLuELwCdpD/KD9W7+Mkql6yciIiK5l4JTFvrn3GVaf7SWS0lpFPJ258dnwynpB2M9plDX7RAPJY8hEW8M3BxCE0BQYR+TqhYRERFn5YpLdRMnTqRChQr4+PgQFhbG5s2bb9h/7ty5VKtWDR8fH2rVqsXSpUtzqNLrq/ryUpq8/TNxiWmkGRCXmEbXt2fj93Vbunms5nbLMZq47Uq3ngUoHWibmkBERERyN9OD0+zZsxkyZAjR0dFs3bqVOnXq0LJlS06fPp1h/99++41u3brRu3dvtm3bRseOHenYsSO7dqUPJTml6stLSU4zHNqaue3gB++Xqe0WwznDn6iUF/nZ2sChj+X//xvdvgbubhZEREQkd7MYhmHcvFv2CQsL484772TChAkAWK1WQkJCeOaZZxg+fHi6/pGRkVy6dIkffvjB3nb33XdTt25dJk+efNP9xcXFERgYSGxsLAEBAbdc/z/nLtPk7Z/tyxasDHRfxGCP+bhZDHZYK9I/eRD9OzZnwuqDDgPFSwf6EN2+Bq1qlr7lOkRERCRzXMkGpo5xSk5OZsuWLYwYMcLe5ubmRkREBBs2bMhwnQ0bNjBkyBCHtpYtW7Jo0aIM+yclJZGUlGRfjouLu/XC/6P1R2sdlod5zKG/x2IAZqbex5jUHiThxVvL9rBtVMv0M4frTJOIiEieYWpwOnv2LGlpaZQsWdKhvWTJkuzduzfDdU6ePJlh/5MnT2bYf+zYsYwZMyZrCs7ApaQ0h+UvU+/nQfff+DC1E3PT7nXo5+5moVGl27KtFhEREclepo9xym4jRowgNjbW/jp27FiWbr+Qt+O0lSe5jRZJ7zqEpoz6iYiISN5janAqXrw47u7unDp1yqH91KlTlCpVKsN1SpUq5VJ/b29vAgICHF5Z6cdnw9O1JeHlVD8RERHJW0wNTl5eXjRo0IBVq1bZ26xWK6tWraJRo0YZrtOoUSOH/gArVqy4bv/sVqaYL17uNx6n5OVuoUwx3xyqSERERLKL6ZfqhgwZwpQpU5gxYwZ79uyhX79+XLp0iV69egHQo0cPh8HjgwYNYtmyZbz33nvs3buX0aNH87///Y+BAwea9RHY/0ab64YnL3cL+99ok8MViYiISHYwfebwyMhIzpw5w6hRozh58iR169Zl2bJl9gHgR48exc3tar5r3LgxM2fO5JVXXuGll16iSpUqLFq0iJo1a5r1EQBbeMpo5nCdaRIREck/TJ/HKadl9TxOIiIikre5kg1Mv1QnIiIiklcoOImIiIg4ScFJRERExEkKTiIiIiJOUnASERERcZKCk4iIiIiTFJxEREREnKTgJCIiIuIkBScRERERJyk4iYiIiDhJwUlERETESaY/5DenXXk0X1xcnMmViIiISG5wJRM48/jeAhecLl68CEBISIjJlYiIiEhucvHiRQIDA2/Yx2I4E6/yEavVyvHjxylcuDAWiyXLtx8XF0dISAjHjh276ROWJevouJtDx908Ovbm0HE3R3Yfd8MwuHjxIsHBwbi53XgUU4E74+Tm5kbZsmWzfT8BAQH6n8oEOu7m0HE3j469OXTczZGdx/1mZ5qu0OBwEREREScpOImIiIg4ScEpi3l7exMdHY23t7fZpRQoOu7m0HE3j469OXTczZGbjnuBGxwuIiIiklk64yQiIiLiJAUnEREREScpOImIiIg4ScEpEyZOnEiFChXw8fEhLCyMzZs337D/3LlzqVatGj4+PtSqVYulS5fmUKX5iyvHfcqUKTRt2pSiRYtStGhRIiIibvp9koy5+vN+xaxZs7BYLHTs2DF7C8zHXD32Fy5cYMCAAZQuXRpvb2+qVq2qf28ywdXjPn78eG6//XZ8fX0JCQlh8ODBJCYm5lC1+cMvv/xC+/btCQ4OxmKxsGjRopuus2bNGurXr4+3tzeVK1dm+vTp2V4nAIa4ZNasWYaXl5cxdepU488//zSefPJJo0iRIsapU6cy7L9+/XrD3d3dePvtt43du3cbr7zyiuHp6Wns3LkzhyvP21w97o8++qgxceJEY9u2bcaePXuMnj17GoGBgcbff/+dw5Xnba4e9ytiYmKMMmXKGE2bNjU6dOiQM8XmM64e+6SkJKNhw4ZGmzZtjHXr1hkxMTHGmjVrjO3bt+dw5Xmbq8f9m2++Mby9vY1vvvnGiImJMZYvX26ULl3aGDx4cA5XnrctXbrUePnll40FCxYYgLFw4cIb9j98+LDh5+dnDBkyxNi9e7fx8ccfG+7u7sayZcuyvVYFJxfdddddxoABA+zLaWlpRnBwsDF27NgM+3ft2tVo27atQ1tYWJjx9NNPZ2ud+Y2rx/1aqampRuHChY0ZM2ZkV4n5UmaOe2pqqtG4cWPj888/N6KiohScMsnVYz9p0iSjYsWKRnJyck6VmC+5etwHDBhg3HfffQ5tQ4YMMZo0aZKtdeZnzgSnF154wbjjjjsc2iIjI42WLVtmY2U2ulTnguTkZLZs2UJERIS9zc3NjYiICDZs2JDhOhs2bHDoD9CyZcvr9pf0MnPcr5WQkEBKSgrFihXLrjLzncwe91dffZWgoCB69+6dE2XmS5k59osXL6ZRo0YMGDCAkiVLUrNmTd58803S0tJyquw8LzPHvXHjxmzZssV+Oe/w4cMsXbqUNm3a5EjNBZWZv1sL3LPqbsXZs2dJS0ujZMmSDu0lS5Zk7969Ga5z8uTJDPufPHky2+rMbzJz3K/14osvEhwcnO5/NLm+zBz3devW8cUXX7B9+/YcqDD/ysyxP3z4MD///DOPPfYYS5cu5eDBg/Tv35+UlBSio6Nzouw8LzPH/dFHH+Xs2bPcc889GIZBamoqffv25aWXXsqJkgus6/1ujYuL4/Lly/j6+mbbvnXGSfK9cePGMWvWLBYuXIiPj4/Z5eRbFy9epHv37kyZMoXixYubXU6BY7VaCQoK4rPPPqNBgwZERkby8ssvM3nyZLNLy9fWrFnDm2++ySeffMLWrVtZsGABS5Ys4bXXXjO7NMkmOuPkguLFi+Pu7s6pU6cc2k+dOkWpUqUyXKdUqVIu9Zf0MnPcr3j33XcZN24cK1eupHbt2tlZZr7j6nE/dOgQR44coX379vY2q9UKgIeHB/v27aNSpUrZW3Q+kZmf+dKlS+Pp6Ym7u7u9rXr16pw8eZLk5GS8vLyyteb8IDPHfeTIkXTv3p0+ffoAUKtWLS5dusRTTz3Fyy+/jJubzk9kh+v9bg0ICMjWs02gM04u8fLyokGDBqxatcreZrVaWbVqFY0aNcpwnUaNGjn0B1ixYsV1+0t6mTnuAG+//TavvfYay5Yto2HDhjlRar7i6nGvVq0aO3fuZPv27fbXgw8+SPPmzdm+fTshISE5WX6elpmf+SZNmnDw4EF7WAXYv38/pUuXVmhyUmaOe0JCQrpwdCW8GnqiWbYx9Xdrtg8/z2dmzZpleHt7G9OnTzd2795tPPXUU0aRIkWMkydPGoZhGN27dzeGDx9u779+/XrDw8PDePfdd409e/YY0dHRmo4gE1w97uPGjTO8vLyMefPmGSdOnLC/Ll68aNZHyJNcPe7X0l11mefqsT969KhRuHBhY+DAgca+ffuMH374wQgKCjJef/11sz5CnuTqcY+OjjYKFy5sfPvtt8bhw4eNn376yahUqZLRtWtXsz5CnnTx4kVj27ZtxrZt2wzAeP/9941t27YZf/31l2EYhjF8+HCje/fu9v5XpiMYNmyYsWfPHmPixImajiA3+/jjj41y5coZXl5exl133WVs3LjR/l54eLgRFRXl0H/OnDlG1apVDS8vL+OOO+4wlixZksMV5w+uHPfy5csbQLpXdHR0zheex7n68/5fCk63xtVj/9tvvxlhYWGGt7e3UbFiReONN94wUlNTc7jqvM+V456SkmKMHj3aqFSpkuHj42OEhIQY/fv3N86fP5/zhedhq1evzvDf7CvHOioqyggPD0+3Tt26dQ0vLy+jYsWKxrRp03KkVoth6FyiiIiIiDM0xklERETESQpOIiIiIk5ScBIRERFxkoKTiIiIiJMUnEREREScpOAkIiIi4iQFJxEREREnKTiJiIiIOEnBSURyvZ49e9KxY0f78r333stzzz2X43WsWbMGi8XChQsXcnzfR44cwWKxsH379lvazrXHMiPXHt8KFSowfvx4+7LFYmHRokW3VIdIXqXgJJKL9OzZE4vFQt++fdO9N2DAACwWCz179sz5wnKZBQsW8NprrznV18ywk1fd7PieOHGC1q1bA1kX6ETyCgUnkVwmJCSEWbNmcfnyZXtbYmIiM2fOpFy5ciZWdmuSk5OzbFvFihWjcOHCWbY9s6WkpJhdgoObHd9SpUrh7e2dgxWJ5B4KTiK5TP369QkJCWHBggX2tgULFlCuXDnq1avn0NdqtTJ27FhCQ0Px9fWlTp06zJs3z/5+WloavXv3tr9/++238+GHHzps48qlm3fffZfSpUtz2223MWDAgBv+Mh89ejR169bl008/JSQkBD8/P7p27UpsbGy67b7xxhsEBwdz++23A3Ds2DG6du1KkSJFKFasGB06dODIkSMONQ8ZMoQiRYpw22238cILL3DtIzWvvZSUlJTEiy++SEhICN7e3lSuXJkvvviCI0eO0Lx5cwCKFi3qcMbuZscOYOnSpVStWhVfX1+aN2/uUOf1WCwWJk2aROvWrfH19aVixYoO271yhmb27NmEh4fj4+PDN998g9Vq5dVXX6Vs2bJ4e3tTt25dli1blm77e/fupXHjxvj4+FCzZk3Wrl3rcOxu9v2+YsyYMZQoUYKAgAD69u3rEGxvdin0v5fqQkNDAahXrx4Wi4V7772XX375BU9PT06ePOmw3nPPPUfTpk1vegxFcjMFJ5Fc6IknnmDatGn25alTp9KrV690/caOHcuXX37J5MmT+fPPPxk8eDCPP/64/Zep1WqlbNmyzJ07l927dzNq1Cheeukl5syZ47Cd1atXc+jQIVavXs2MGTOYPn0606dPv2GNBw8eZM6cOXz//fcsW7aMbdu20b9/f4c+q1atYt++faxYsYIffviBlJQUWrZsSeHChfn1119Zv349/v7+tGrVyv6L+7333mP69OlMnTqVdevWce7cORYuXHjDWnr06MG3337LRx99xJ49e/j000/x9/cnJCSE+fPnA7Bv3z5OnDhhDxI3O3bHjh2jU6dOtG/fnu3bt9OnTx+GDx9+wzquGDlyJJ07d2bHjh089thjPPLII+zZs8ehz/Dhwxk0aBB79uyhZcuWfPjhh7z33nu8++67/PHHH7Rs2ZIHH3yQAwcOOKw3bNgwhg4dyrZt22jUqBHt27fn33//BZz/fq9atYo9e/awZs0avv32WxYsWMCYMWOc+mzX2rx5MwArV67kxIkTLFiwgGbNmlGxYkW++uore7+UlBS++eYbnnjiiUztRyTXMEQk14iKijI6dOhgnD592vD29jaOHDliHDlyxPDx8THOnDljdOjQwYiKijIMwzASExMNPz8/47fffnPYRu/evY1u3bpddx8DBgwwOnfu7LDP8uXLG6mpqfa2hx9+2IiMjLzuNqKjow13d3fj77//trf9+OOPhpubm3HixAn7dkuWLGkkJSXZ+3z11VfG7bffblitVntbUlKS4evrayxfvtwwDMMoXbq08fbbb9vfT0lJMcqWLWt06NDB3hYeHm4MGjTIMAzD2LdvnwEYK1asyLDW1atXG4Bx/vx5e5szx27EiBFGjRo1HN5/8cUX023rWoDRt29fh7awsDCjX79+hmEYRkxMjAEY48ePd+gTHBxsvPHGGw5td955p9G/f3+H9caNG2d//8qxeeutt65bT0bf72LFihmXLl2yt02aNMnw9/c30tLSDMNwPL6GYRjly5c3PvjgA4fPuHDhQoe6tm3b5rDft956y6hevbp9ef78+Ya/v78RHx9/3VpF8gIP8yKbiFxPiRIlaNu2LdOnT8cwDNq2bUvx4sUd+hw8eJCEhATuv/9+h/bk5GSHS3oTJ05k6tSpHD16lMuXL5OcnEzdunUd1rnjjjtwd3e3L5cuXZqdO3fesMZy5cpRpkwZ+3KjRo2wWq3s27ePUqVKAVCrVi28vLzsfXbs2MHBgwfTjZ9JTEzk0KFDxMbGcuLECcLCwuzveXh40LBhw3SX667Yvn077u7uhIeH37De/3Lm2O3Zs8ehjiuf0RnX9mvUqFG6wdMNGza0fx0XF8fx48dp0qSJQ58mTZqwY8eO6277yrH579ksZ77fderUwc/Pz2Gb8fHxHDt2jPLlyzv1GW+mZ8+evPLKK2zcuJG7776b6dOn07VrVwoVKpQl2xcxi4KTSC71xBNPMHDgQMD2y/Ba8fHxACxZssQhwAD2gbuzZs3i+eef57333qNRo0YULlyYd955h02bNjn09/T0dFi2WCxYrdZb/gzX/pKMj4+nQYMGfPPNN+n6lihRIlP78PX1dXkdZ45ddsuOAOHs9zsnBAUF0b59e6ZNm0ZoaCg//vgja9asyfE6RLKagpNILnVl3I/FYqFly5bp3q9Rowbe3t4cPXr0umdb1q9fT+PGjR3GHh06dChL6jt69CjHjx8nODgYgI0bN+Lm5mYfBJ6R+vXrM3v2bIKCgggICMiwT+nSpdm0aRPNmjUDIDU1lS1btlC/fv0M+9eqVQur1cratWuJiIhI9/6VM15paWn2NmeOXfXq1Vm8eLFD28aNG6/72a7t16NHD4flawf2/1dAQADBwcGsX7/eoZ7169dz1113pdv2tcfmSsB29vu9Y8cOLl++bA+dGzdutI8Jc1VGx/eKPn360K1bN8qWLUulSpXSnVETyYs0OFwkl3J3d2fPnj3s3r3b4TLaFYULF+b5559n8ODBzJgxg0OHDrF161Y+/vhjZsyYAUCVKlX43//+x/Lly9m/fz8jR47k999/z5L6fHx8iIqKYseOHfz66688++yzdO3a1X6ZLiOPPfYYxYsXp0OHDvz666/ExMSwZs0ann32Wf7++28ABg0axLhx41i0aBF79+6lf//+N5yDqUKFCkRFRfHEE0+waNEi+zavDIguX748FouFH374gTNnzhAfH+/Usevbty8HDhxg2LBh7Nu3j5kzZ950wPwVc+fOZerUqezfv5/o6Gg2b95sDzfXM2zYMN566y1mz57Nvn37GD58ONu3b2fQoEEO/SZOnMjChQvZu3cvAwYM4Pz58/YB185+v5OTk+nduze7d+9m6dKlREdHM3DgQNzcXP+VEBQUhK+vL8uWLePUqVMOd1a2bNmSgIAAXn/99QxvbhDJixScRHKxgICA656ZAXjttdcYOXIkY8eOpXr16rRq1YolS5bYbxF/+umn6dSpE5GRkYSFhfHvv/+mu/MtsypXrkynTp1o06YNDzzwALVr1+aTTz654Tp+fn788ssvlCtXjk6dOlG9enV69+5NYmKi/XMOHTqU7t27ExUVZb/c9NBDD91wu5MmTaJLly7079+fatWq8eSTT3Lp0iUAypQpw5gxYxg+fDglS5a0B5ibHbty5coxf/58Fi1aRJ06dZg8eTJvvvmmU8dmzJgxzJo1i9q1a/Pll1/y7bffUqNGjRuu8+yzzzJkyBCGDh1KrVq1WLZsGYsXL6ZKlSoO/caNG8e4ceOoU6cO69atY/Hixfbxb85+v1u0aEGVKlVo1qwZkZGRPPjgg4wePdqpz3YtDw8PPvroIz799FOCg4Pp0KGD/T03Nzd69uxJWlqawxk4kbzMYlxvxKWIyHWMHj2aRYsWabboDFgsFhYuXHjTx5oUFL179+bMmTPpLnuK5FUa4yQiIlkuNjaWnTt3MnPmTIUmyVcUnEREJMt16NCBzZs307dv33TTPojkZbpUJyIiIuIkDQ4XERERcZKCk4iIiIiTFJxEREREnKTgJCIiIuIkBScRERERJyk4iYiIiDhJwUlERETESQpOIiIiIk5ScBIRERFx0v8BxFLHSTB2lJYAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Calibration summary:\n",
            "{'selected_configuration': 'XGB_original', 'test_brier_score': 0.000432366612495127, 'note': 'Lower Brier score indicates better probability calibration. Inspect the calibration curve before deciding whether calibration is needed.'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Model interpretation: SHAP or Logistic Regression coefficients"
      ],
      "metadata": {
        "id": "hUKvanVs6FKh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def transform_for_underlying_model(pipeline, X_data):\n",
        "    \"\"\"\n",
        "    Apply inference-time transformers before the final model.\n",
        "    SMOTE is skipped because it is a training-only sampler.\n",
        "    \"\"\"\n",
        "    X_transformed = X_data.copy()\n",
        "    feature_names = list(X_data.columns)\n",
        "\n",
        "    for step_name, step in pipeline.steps[:-1]:\n",
        "        if hasattr(step, \"transform\"):\n",
        "            X_transformed = step.transform(X_transformed)\n",
        "\n",
        "            X_transformed = pd.DataFrame(\n",
        "                X_transformed,\n",
        "                columns=feature_names,\n",
        "                index=X_data.index\n",
        "            )\n",
        "\n",
        "    return X_transformed\n",
        "\n",
        "\n",
        "def run_model_interpretation(selected_pipeline, X_test, selected_name):\n",
        "    \"\"\"\n",
        "    Interpret selected model.\n",
        "    Tree models use SHAP.\n",
        "    Logistic Regression uses standardised coefficients.\n",
        "    \"\"\"\n",
        "    rng = np.random.default_rng(SEED)\n",
        "\n",
        "    sample_size = min(SHAP_SAMPLE_SIZE, len(X_test))\n",
        "    sample_index = rng.choice(\n",
        "        X_test.index.to_numpy(),\n",
        "        size=sample_size,\n",
        "        replace=False\n",
        "    )\n",
        "\n",
        "    X_sample = X_test.loc[sample_index]\n",
        "    X_model_space = transform_for_underlying_model(\n",
        "        selected_pipeline,\n",
        "        X_sample\n",
        "    )\n",
        "\n",
        "    model = selected_pipeline.named_steps[\"model\"]\n",
        "    model_type = model.__class__.__name__\n",
        "\n",
        "    print(\"\\nSelected model type:\", model_type)\n",
        "\n",
        "    if model_type in [\"RandomForestClassifier\", \"XGBClassifier\"]:\n",
        "\n",
        "        explainer = shap.TreeExplainer(model)\n",
        "        shap_values = explainer(X_model_space)\n",
        "\n",
        "        shap.summary_plot(\n",
        "            shap_values,\n",
        "            X_model_space,\n",
        "            show=False,\n",
        "            max_display=15\n",
        "        )\n",
        "\n",
        "        plt.tight_layout()\n",
        "        plt.savefig(\n",
        "            FIG_DIR / f\"{selected_name}_shap_summary.png\",\n",
        "            dpi=300,\n",
        "            bbox_inches=\"tight\"\n",
        "        )\n",
        "        plt.show()\n",
        "\n",
        "    elif model_type == \"LogisticRegression\":\n",
        "\n",
        "        coefficient_table = pd.DataFrame({\n",
        "            \"feature\": X_model_space.columns,\n",
        "            \"coefficient\": model.coef_[0],\n",
        "            \"absolute_coefficient\": np.abs(model.coef_[0])\n",
        "        })\n",
        "\n",
        "        coefficient_table = coefficient_table.sort_values(\n",
        "            \"absolute_coefficient\",\n",
        "            ascending=False\n",
        "        )\n",
        "\n",
        "        coefficient_table.to_csv(\n",
        "            TABLE_DIR / f\"{selected_name}_logistic_coefficients.csv\",\n",
        "            index=False\n",
        "        )\n",
        "\n",
        "        top_coefficients = coefficient_table.head(15).sort_values(\n",
        "            \"coefficient\"\n",
        "        )\n",
        "\n",
        "        plt.figure(figsize=(8, 6))\n",
        "        plt.barh(\n",
        "            top_coefficients[\"feature\"],\n",
        "            top_coefficients[\"coefficient\"]\n",
        "        )\n",
        "        plt.xlabel(\"Standardised coefficient\")\n",
        "        plt.title(\"Top Logistic Regression Coefficients\")\n",
        "        plt.tight_layout()\n",
        "        plt.savefig(\n",
        "            FIG_DIR / f\"{selected_name}_logistic_coefficients.png\",\n",
        "            dpi=300\n",
        "        )\n",
        "        plt.show()\n",
        "\n",
        "        print(\"\\nTop Logistic Regression coefficients:\")\n",
        "        print(coefficient_table.head(15))\n",
        "\n",
        "    else:\n",
        "        print(\"Interpretation not implemented for this model type.\")\n",
        "\n",
        "\n",
        "run_model_interpretation(\n",
        "    selected_estimator,\n",
        "    X_test,\n",
        "    selected_name\n",
        ")"
      ],
      "metadata": {
        "id": "cQsdc00j6Pwp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 795
        },
        "outputId": "e1bbb548-bda6-47d6-f980-13af236eeaea"
      },
      "execution_count": 72,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Selected model type: XGBClassifier\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x750 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Error analysis"
      ],
      "metadata": {
        "id": "54D8Hk0N6Vp6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "y_test_pred_f2 = (y_test_selected_score >= f2_threshold).astype(int)\n",
        "\n",
        "error_df = X_test.copy()\n",
        "error_df[\"y_true\"] = y_test.to_numpy()\n",
        "error_df[\"y_score\"] = y_test_selected_score\n",
        "error_df[\"y_pred_F2\"] = y_test_pred_f2\n",
        "\n",
        "error_df[\"error_type\"] = np.select(\n",
        "    [\n",
        "        (error_df[\"y_true\"] == 1) & (error_df[\"y_pred_F2\"] == 1),\n",
        "        (error_df[\"y_true\"] == 1) & (error_df[\"y_pred_F2\"] == 0),\n",
        "        (error_df[\"y_true\"] == 0) & (error_df[\"y_pred_F2\"] == 1),\n",
        "        (error_df[\"y_true\"] == 0) & (error_df[\"y_pred_F2\"] == 0)\n",
        "    ],\n",
        "    [\n",
        "        \"TP_detected_fraud\",\n",
        "        \"FN_missed_fraud\",\n",
        "        \"FP_flagged_legitimate\",\n",
        "        \"TN_correct_legitimate\"\n",
        "    ],\n",
        "    default=\"unknown\"\n",
        ")\n",
        "\n",
        "error_summary = error_df.groupby(\"error_type\").agg(\n",
        "    count=(\"y_true\", \"size\"),\n",
        "    mean_amount=(\"Amount\", \"mean\"),\n",
        "    median_amount=(\"Amount\", \"median\"),\n",
        "    mean_time=(\"Time\", \"mean\"),\n",
        "    median_score=(\"y_score\", \"median\")\n",
        ").reset_index()\n",
        "\n",
        "error_summary.to_csv(\n",
        "    TABLE_DIR / f\"error_analysis_summary_{selected_name}_F2_threshold.csv\",\n",
        "    index=False\n",
        ")\n",
        "\n",
        "print(\"\\nError analysis summary:\")\n",
        "print(error_summary)\n",
        "\n",
        "local_cases = (\n",
        "    error_df\n",
        "    .sort_values(\"y_score\", ascending=False)\n",
        "    .groupby(\"error_type\", group_keys=False)\n",
        "    .head(5)\n",
        ")\n",
        "\n",
        "local_cases.to_csv(\n",
        "    TABLE_DIR / f\"local_cases_for_interpretation_{selected_name}_F2_threshold.csv\",\n",
        "    index=True\n",
        ")\n",
        "\n",
        "print(\"\\nLocal cases for interpretation:\")\n",
        "print(local_cases.head())"
      ],
      "metadata": {
        "id": "vRgishnO6Yvk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "outputId": "c59aded2-524c-48b7-f956-c3f08c5f623c"
      },
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Error analysis summary:\n",
            "              error_type  count  mean_amount  median_amount     mean_time  \\\n",
            "0        FN_missed_fraud     14   132.544286          4.140  75541.642857   \n",
            "1  FP_flagged_legitimate     24    85.667083         45.495  73002.666667   \n",
            "2  TN_correct_legitimate  56840    89.010565         22.000  94576.233533   \n",
            "3      TP_detected_fraud     84   104.634643         11.045  71832.952381   \n",
            "\n",
            "   median_score  \n",
            "0      0.000810  \n",
            "1      0.461897  \n",
            "2      0.000100  \n",
            "3      0.906643  \n",
            "\n",
            "Local cases for interpretation:\n",
            "            Time         V1         V2        V3        V4        V5  \\\n",
            "42009    40919.0  -2.740483   3.658095 -4.110636  5.340242 -2.666775   \n",
            "102444   68207.0 -13.192671  12.785971 -9.906650  3.320337 -4.801176   \n",
            "102442   68207.0 -13.192671  12.785971 -9.906650  3.320337 -4.801176   \n",
            "77682    57163.0 -10.363049   4.543672 -9.795898  5.508003 -6.037156   \n",
            "243699  152036.0  -4.320609   3.199939 -5.799736  6.502330  0.378479   \n",
            "\n",
            "              V6         V7         V8        V9  ...       V24       V25  \\\n",
            "42009  -0.092782  -4.388699  -0.280133 -2.821895  ... -0.154757 -0.403956   \n",
            "102444  5.760059 -18.750889 -37.353443 -0.391540  ... -0.639435  0.263203   \n",
            "102442  5.760059 -18.750889 -37.353443 -0.391540  ... -0.639435  0.263203   \n",
            "77682  -0.133493 -11.724346  -3.198346 -4.767842  ... -0.543369 -0.289125   \n",
            "243699 -1.948246  -2.167860  -0.728207 -1.977238  ... -0.620072  0.642531   \n",
            "\n",
            "             V26       V27       V28  Amount  y_true   y_score  y_pred_F2  \\\n",
            "42009   0.277895  0.830062  0.218690  112.33       1  0.980310          1   \n",
            "102444 -0.108877  1.269566  0.939407    1.00       1  0.977001          1   \n",
            "102442 -0.108877  1.269566  0.939407    1.00       1  0.977001          1   \n",
            "77682  -0.107586  0.330642  0.163577    1.00       1  0.973474          1   \n",
            "243699  0.280717 -2.649107  0.533641    1.00       1  0.970601          1   \n",
            "\n",
            "               error_type  \n",
            "42009   TP_detected_fraud  \n",
            "102444  TP_detected_fraud  \n",
            "102442  TP_detected_fraud  \n",
            "77682   TP_detected_fraud  \n",
            "243699  TP_detected_fraud  \n",
            "\n",
            "[5 rows x 34 columns]\n"
          ]
        }
      ]
    }
  ]
}