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" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.250000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>ALL</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 66 columns</p>\n",
"</div>"
],
"text/plain": [
" SBS1 SBS2 SBS3 SBS4 SBS5 SBS6 SBS7a SBS7b SBS7c \\\n",
"mut_tri \n",
"ALL::11 0.066667 0.0 0.0 0.0 0.066667 0.0 0.0 0.0 0.0 \n",
"ALL::2211636 0.000000 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 \n",
"ALL::2211638 0.000000 0.0 0.0 0.0 0.333333 0.0 0.0 0.0 0.0 \n",
"ALL::2211640 0.000000 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 \n",
"ALL::2211642 0.000000 0.0 0.0 0.0 0.250000 0.0 0.0 0.0 0.0 \n",
"\n",
" SBS7d ... SBS52 SBS53 SBS54 SBS55 SBS56 SBS57 SBS58 \\\n",
"mut_tri ... \n",
"ALL::11 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
"ALL::2211636 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
"ALL::2211638 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
"ALL::2211640 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
"ALL::2211642 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
"\n",
" SBS59 SBS60 tumor_types \n",
"mut_tri \n",
"ALL::11 0.000000 0.0 ALL \n",
"ALL::2211636 0.000000 0.0 ALL \n",
"ALL::2211638 0.666667 0.0 ALL \n",
"ALL::2211640 0.000000 0.0 ALL \n",
"ALL::2211642 0.000000 0.0 ALL \n",
"\n",
"[5 rows x 66 columns]"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print(\"Some content from the full act set:\")\n",
"act_mut_all.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 1800x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(25, 5))\n",
"sns.set_theme()\n",
"act_mut_all[\"tumor_types\"].value_counts().sort_index().plot(kind=\"bar\")\n",
"#sns.countplot(x=profile_mut_all[\"tumor_types\"], palette=sns.hls_palette(2))\n",
"plt.xticks(rotation=90);\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Testing with a single RandomForest binary classifier"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Dimension of the training data (16608, 96) and test data (7119, 96)\n",
" All Train Test Pred\n",
"0 23240 16280 6960 7119.0\n",
"1 487 328 159 NaN\n",
"Accuracy: 0.9776654024441636\n",
" precision recall f1-score support\n",
"\n",
" 0 0.98 1.00 0.99 6960\n",
" 1 0.00 0.00 0.00 159\n",
"\n",
" accuracy 0.98 7119\n",
" macro avg 0.49 0.50 0.49 7119\n",
"weighted avg 0.96 0.98 0.97 7119\n",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jr/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
" _warn_prf(average, modifier, msg_start, len(result))\n",
"/home/jr/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
" _warn_prf(average, modifier, msg_start, len(result))\n",
"/home/jr/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
" _warn_prf(average, modifier, msg_start, len(result))\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1080x576 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 864x720 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 504x432 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# For binary classification, construct y vector for a sigle selected tumor type\n",
"\n",
"target_type = \"Biliary-AdenoCA\"\n",
"\n",
"y_prf = profile_mut_all[\"tumor_types\"].values\n",
"\n",
"# Encode for classificaiton to two classes: if the type is the desired type, set to 1 otherwise 0\n",
"y_prf_bin = [1 if tumor_type == target_type else 0 for tumor_type in y_prf]\n",
"\n",
"# Split the data for fitting and prediction, use simple splitting here\n",
"X_prf_train, X_prf_test, y_prf_train, y_prf_test = train_test_split(X_prf, y_prf_bin, test_size = 0.3, random_state=898)\n",
"\n",
"print(f\"Dimension of the training data {X_prf_train.shape} and test data {X_prf_test.shape}\")\n",
"\n",
"# Make a model\n",
"model_rfs = RandomForestClassifier()\n",
"\n",
"# Fit the model \n",
"clf= model_rfs.fit(X_prf_train, y_prf_train)\n",
"\n",
"# Predict with unused (test) data \n",
"y_prf_pred = model_rfs.predict(X_prf_test)\n",
"\n",
"# What we got \n",
"plot_trn_tst_dist(y_prf_bin, y_prf_train, y_prf_test, y_prf_pred, in_cols=True)\n",
"print(f\"Accuracy:\", accuracy_score(y_prf_test, y_prf_pred))\n",
"print(classification_report(y_prf_test, y_prf_pred))\n",
"\n",
"# Plot some results\n",
"plot_confusion_mat(y_prf_test, y_prf_pred, labs=[\"0\", \"1\"])\n",
"plot_roc_auc(X_prf_test, y_prf_test, model_rfs)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We notice the training material is very skewed and results in classifier, which does not predict class 1 in any case. This is not good. Let's try oversampling, how it effects the situation. You need to install imbalanced-learn for this to work."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: imbalanced-learn in /home/jr/miniconda3/lib/python3.9/site-packages (0.9.0)\n",
"Requirement already satisfied: joblib>=0.11 in /home/jr/miniconda3/lib/python3.9/site-packages (from imbalanced-learn) (1.1.0)\n",
"Requirement already satisfied: numpy>=1.14.6 in /home/jr/miniconda3/lib/python3.9/site-packages (from imbalanced-learn) (1.19.2)\n",
"Requirement already satisfied: scipy>=1.1.0 in /home/jr/miniconda3/lib/python3.9/site-packages (from imbalanced-learn) (1.6.2)\n",
"Requirement already satisfied: scikit-learn>=1.0.1 in /home/jr/miniconda3/lib/python3.9/site-packages (from imbalanced-learn) (1.0.1)\n",
"Requirement already satisfied: threadpoolctl>=2.0.0 in /home/jr/miniconda3/lib/python3.9/site-packages (from imbalanced-learn) (2.2.0)\n"
]
}
],
"source": [
"# You need to install imbalanced-learn for the following cells to work.\n",
"# Install a pip package in the current Jupyter kernel\n",
"import sys\n",
"!{sys.executable} -m pip install imbalanced-learn"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Counter({0: 16280, 1: 16280})\n",
" All Train Test Pred\n",
"0 23240 16280 6960 7110\n",
"1 487 16280 159 9\n",
" precision recall f1-score support\n",
"\n",
" 0 0.98 1.00 0.99 6960\n",
" 1 0.00 0.00 0.00 159\n",
"\n",
" accuracy 0.98 7119\n",
" macro avg 0.49 0.50 0.49 7119\n",
"weighted avg 0.96 0.98 0.97 7119\n",
"\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1080x576 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 864x720 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 504x432 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from collections import Counter\n",
"from imblearn.over_sampling import RandomOverSampler\n",
"\n",
"oversample = RandomOverSampler(sampling_strategy='minority')\n",
"X_over, y_over = oversample.fit_resample(X_prf_train, y_prf_train)\n",
"print(Counter(y_over))\n",
"\n",
"# Make a model\n",
"model_rfs = RandomForestClassifier()\n",
"\n",
"# Fit the model \n",
"clf = model_rfs.fit(X_over, y_over)\n",
"\n",
"# Predict with unused (test) data \n",
"y_prf_pred = model_rfs.predict(X_prf_test)\n",
"\n",
"# What we got \n",
"plot_trn_tst_dist(y_prf_bin, y_over, y_prf_test, y_prf_pred, in_cols=True)\n",
"#print(f\"Accuracy:\", accuracy_score(y_prf_test, y_prf_pred))\n",
"print(classification_report(y_prf_test, y_prf_pred))\n",
"# Plot some results\n",
"plot_confusion_mat(y_prf_test, y_prf_pred, labs=[\"0\", \"1\"])\n",
"plot_roc_auc(X_prf_test, y_prf_test, model_rfs)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Area under curve has improved, but correctly predicted 1:s missing."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Counter({0: 16280, 1: 328})\n",
" All Train Test Pred\n",
"0 23240 328 6960 4854\n",
"1 487 328 159 2265\n",
" precision recall f1-score support\n",
"\n",
" 0 0.99 0.69 0.81 6960\n",
" 1 0.05 0.73 0.10 159\n",
"\n",
" accuracy 0.69 7119\n",
" macro avg 0.52 0.71 0.46 7119\n",
"weighted avg 0.97 0.69 0.80 7119\n",
"\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1080x576 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 864x720 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 504x432 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from imblearn.under_sampling import RandomUnderSampler\n",
"print(Counter(y_prf_train))\n",
"undersample = RandomUnderSampler(sampling_strategy='majority')\n",
"X_under, y_under = undersample.fit_resample(X_prf_train, y_prf_train)\n",
"\n",
"# Make a model\n",
"model_rfs = RandomForestClassifier()\n",
"\n",
"# Fit the model \n",
"clf = model_rfs.fit(X_under, y_under)\n",
"\n",
"# Predict with unused (test) data \n",
"y_prf_pred = model_rfs.predict(X_prf_test)\n",
"# What we got \n",
"plot_trn_tst_dist(y_prf_bin, y_under, y_prf_test, y_prf_pred, in_cols=True)\n",
"#print(f\"Accuracy:\", accuracy_score(y_prf_test, y_prf_pred))\n",
"print(classification_report(y_prf_test, y_prf_pred))\n",
"plot_confusion_mat(y_prf_test, y_prf_pred, labs=[\"0\", \"1\"])\n",
"plot_roc_auc(X_prf_test, y_prf_test, model_rfs)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This seems to make things worse. Let's try over and under sampling together."
]
},
{
"cell_type": "code",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" All Train Test Pred\n",
"0 23240 3256 6960 7107\n",
"1 487 1628 159 12\n",
" precision recall f1-score support\n",
"\n",
" 0 0.98 1.00 0.99 6960\n",
" 1 0.50 0.04 0.07 159\n",
"\n",
" accuracy 0.98 7119\n",
" macro avg 0.74 0.52 0.53 7119\n",
"weighted avg 0.97 0.98 0.97 7119\n",
"\n"
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{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1080x576 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 864x720 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 504x432 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"over = RandomOverSampler(sampling_strategy=0.1)\n",
"X_over_under, y_over_under = over.fit_resample(X_prf_train, y_prf_train)\n",
"under = RandomUnderSampler(sampling_strategy=0.5)\n",
"X_over_under, y_over_under = under.fit_resample(X_over_under, y_over_under)\n",
"\n",
"# Make a model\n",
"model_rfs = RandomForestClassifier()\n",
"\n",
"# Fit the model \n",
"clf = model_rfs.fit(X_over_under, y_over_under)\n",
"\n",
"# Predict with unused (test) data \n",
"y_prf_pred = model_rfs.predict(X_prf_test)\n",
"\n",
"# What we got \n",
"plot_trn_tst_dist(y_prf_bin, y_over_under, y_prf_test, y_prf_pred, in_cols=True)\n",
"#print(f\"Accuracy:\", accuracy_score(y_prf_test, y_prf_pred))\n",
"print(classification_report(y_prf_test, y_prf_pred))\n",
"# Plot some results\n",
"plot_confusion_mat(y_prf_test, y_prf_pred, labs=[\"0\", \"1\"])\n",
"plot_roc_auc(X_prf_test, y_prf_test, model_rfs)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We see that the area under curve value improves a little."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Multiple RandomForest models experiment, but still binary classification\n",
"\n",
"Note: this takes quite a while to compute"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'\\nfor tgt_tumor_type in prf_unique_tumor_types:\\n y_prf = [1 if tumor_type == tgt_tumor_type else 0 for tumor_type in profile_mut_all[\"tumor_types\"]]\\n X_prf_train, X_prf_test, y_prf_train, y_prf_test = train_test_split(X_prf, y_prf, test_size = 0.3, random_state=1)\\n model = RandomForestClassifier(n_estimators=100, random_state=0)\\n model.fit(X_prf_train, y_prf_train)\\n y_prf_pred = model.predict(X_prf_test)\\n print(f\"Accuracy score for {tgt_tumor_type}: {accuracy_score(y_prf_test, y_prf_pred)}\")\\n'"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
"\"\"\"\n",
"for tgt_tumor_type in prf_unique_tumor_types:\n",
" y_prf = [1 if tumor_type == tgt_tumor_type else 0 for tumor_type in profile_mut_all[\"tumor_types\"]]\n",
" X_prf_train, X_prf_test, y_prf_train, y_prf_test = train_test_split(X_prf, y_prf, test_size = 0.3, random_state=1)\n",
" model = RandomForestClassifier(n_estimators=100, random_state=0)\n",
" model.fit(X_prf_train, y_prf_train)\n",
" y_prf_pred = model.predict(X_prf_test)\n",
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" print(f\"Accuracy score for {tgt_tumor_type}: {accuracy_score(y_prf_test, y_prf_pred)}\")\n",
"\"\"\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Multiple class RandomForest classification (slow to run)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"label_encoder = LabelEncoder()\n",
"\n",
"y_prf = profile_mut_all[\"tumor_types\"].values\n",
"y_prfm = label_encoder.fit_transform(y_prf)\n",
"\n",
"X_prfm_train, X_prfm_test, y_prfm_train, y_prfm_test = train_test_split(X_prf, y_prfm, test_size = 0.2)\n",
"\n",
"model_rfm = RandomForestClassifier(n_estimators=1000)\n",
"model_rfm.fit(X_prfm_train, y_prfm_train)\n",
"\n",
"y_prfm_pred = model_rfm.predict(X_prfm_test)\n",
"\n",
"#print(f\"Test accuracy:\", accuracy_score(y_prfm_test, y_prfm_pred))\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Test accuracy is poor with the current data and these parameters."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jr/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
" _warn_prf(average, modifier, msg_start, len(result))\n",
"/home/jr/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
" _warn_prf(average, modifier, msg_start, len(result))\n",
"/home/jr/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
" _warn_prf(average, modifier, msg_start, len(result))\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 0 0.32 0.13 0.19 61\n",
" 1 0.44 0.35 0.39 105\n",
" 2 0.23 0.06 0.09 54\n",
" 3 0.50 0.02 0.04 99\n",
" 4 1.00 0.15 0.26 33\n",
" 5 0.64 0.47 0.54 73\n",
" 6 1.00 0.08 0.15 12\n",
" 7 0.32 0.68 0.43 352\n",
" 8 0.36 0.61 0.45 309\n",
" 9 0.00 0.00 0.00 23\n",
" 10 0.40 0.18 0.25 56\n",
" 11 0.41 0.69 0.51 230\n",
" 12 0.43 0.46 0.45 97\n",
" 13 0.55 0.28 0.38 109\n",
" 14 0.27 0.16 0.20 114\n",
" 15 0.00 0.00 0.00 55\n",
" 16 0.50 0.09 0.16 32\n",
" 17 0.40 0.15 0.22 175\n",
" 18 0.46 0.74 0.57 262\n",
" 19 0.66 0.80 0.72 276\n",
" 20 0.65 0.68 0.67 333\n",
" 21 0.42 0.56 0.48 229\n",
" 22 0.00 0.00 0.00 9\n",
" 23 0.50 0.04 0.08 24\n",
" 24 0.82 0.60 0.69 15\n",
" 25 0.46 0.52 0.49 73\n",
" 26 0.73 0.32 0.44 25\n",
" 27 0.71 0.19 0.30 105\n",
" 28 0.57 0.33 0.42 236\n",
" 29 0.17 0.03 0.05 31\n",
" 30 0.57 0.51 0.54 229\n",
" 31 0.00 0.00 0.00 15\n",
" 32 0.50 0.02 0.03 64\n",
" 33 0.00 0.00 0.00 49\n",
" 34 0.81 0.52 0.63 33\n",
" 35 0.82 0.83 0.83 225\n",
" 36 0.75 0.30 0.43 10\n",
" 37 0.00 0.00 0.00 4\n",
" 38 0.51 0.27 0.36 146\n",
" 39 0.00 0.00 0.00 46\n",
" 40 0.39 0.49 0.44 87\n",
" 41 1.00 0.05 0.10 20\n",
" 42 0.38 0.57 0.46 76\n",
" 43 0.00 0.00 0.00 11\n",
" 44 0.79 0.33 0.47 124\n",
"\n",
" accuracy 0.47 4746\n",
" macro avg 0.45 0.30 0.31 4746\n",
"weighted avg 0.49 0.47 0.44 4746\n",
"\n",
" All Train Test Pred\n",
"0 308 61 61 25.0\n",
"1 556 105 105 85.0\n",
"2 247 54 54 13.0\n",
"3 487 99 99 4.0\n",
"4 168 33 33 5.0\n",
"5 357 73 73 53.0\n",
"6 67 12 12 1.0\n",
"7 1858 352 352 764.0\n",
"8 1595 309 309 529.0\n",
"9 128 23 23 4.0\n",
"10 291 56 56 25.0\n",
"11 1185 230 230 391.0\n",
"12 512 97 97 105.0\n",
"13 486 109 109 56.0\n",
"14 599 114 114 66.0\n",
"15 275 55 55 17.0\n",
"16 165 32 32 6.0\n",
"17 798 175 175 68.0\n",
"18 1269 262 262 421.0\n",
"19 1358 276 276 335.0\n",
"20 1668 333 333 348.0\n",
"21 1192 229 229 309.0\n",
"22 65 9 9 NaN\n",
"23 112 24 24 2.0\n",
"24 71 15 15 11.0\n",
"25 379 73 73 82.0\n",
"26 126 25 25 11.0\n",
"27 549 105 105 28.0\n",
"28 1157 236 236 137.0\n",
"29 182 31 31 6.0\n",
"30 1091 229 229 206.0\n",
"31 63 15 15 NaN\n",
"32 346 64 64 2.0\n",
"33 203 49 49 20.0\n",
"34 129 33 33 21.0\n",
"35 1070 225 225 227.0\n",
"36 46 10 10 4.0\n",
"37 34 4 4 2.0\n",
"38 667 146 146 79.0\n",
"39 191 46 46 3.0\n",
"40 560 87 87 110.0\n",
"41 123 20 20 1.0\n",
"42 389 76 76 112.0\n",
"43 57 11 11 NaN\n",
"44 548 124 124 52.0\n"
]
},
{
"data": {
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",
"text/plain": [
"<Figure size 1080x576 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 2160x2160 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"integer_mapping = {l: i for i, l in enumerate(label_encoder.classes_)}\n",
"labs = list(integer_mapping.keys())\n",
"\n",
"print(classification_report(y_prfm_test, y_prfm_pred))\n",
"\n",
"plot_trn_tst_dist(y_prfm, y_prfm_test, y_prfm_test, y_prfm_pred, in_cols=False)\n",
"plot_confusion_mat(y_prfm_test, y_prfm_pred, labs=labs, size=(30, 30))\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We see from the reports that some classes are not predicted at all (Nans produced in the report above). From the confusion matrix above, with this grouping Breast cancer group has quite a few miss classifications."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Multiple class RandomForest with over sampling (SMOTE), takes a long time to run!"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" All Train Test Pred\n",
"0 308 1506 61 68\n",
"1 556 1506 105 127\n",
"2 247 1506 54 23\n",
"3 487 1506 99 24\n",
"4 168 1506 33 30\n",
"5 357 1506 73 98\n",
"6 67 1506 12 11\n",
"7 1858 1506 352 369\n",
"8 1595 1506 309 255\n",
"9 128 1506 23 11\n",
"10 291 1506 56 63\n",
"11 1185 1506 230 275\n",
"12 512 1506 97 415\n",
"13 486 1506 109 96\n",
"14 599 1506 114 182\n",
"15 275 1506 55 33\n",
"16 165 1506 32 12\n",
"17 798 1506 175 44\n",
"18 1269 1506 262 245\n",
"19 1358 1506 276 281\n",
"20 1668 1506 333 274\n",
"21 1192 1506 229 211\n",
"22 65 1506 9 39\n",
"23 112 1506 24 33\n",
"24 71 1506 15 14\n",
"25 379 1506 73 195\n",
"26 126 1506 25 31\n",
"27 549 1506 105 80\n",
"28 1157 1506 236 127\n",
"29 182 1506 31 74\n",
"30 1091 1506 229 155\n",
"31 63 1506 15 4\n",
"32 346 1506 64 37\n",
"33 203 1506 49 43\n",
"34 129 1506 33 29\n",
"35 1070 1506 225 220\n",
"36 46 1506 10 9\n",
"37 34 1506 4 11\n",
"38 667 1506 146 77\n",
"39 191 1506 46 49\n",
"40 560 1506 87 121\n",
"41 123 1506 20 55\n",
"42 389 1506 76 113\n",
"43 57 1506 11 5\n",
"44 548 1506 124 78\n",
" precision recall f1-score support\n",
"\n",
" 0 0.22 0.25 0.23 61\n",
" 1 0.34 0.41 0.37 105\n",
" 2 0.13 0.06 0.08 54\n",
" 3 0.38 0.09 0.15 99\n",
" 4 0.57 0.52 0.54 33\n",
" 5 0.43 0.58 0.49 73\n",
" 6 0.64 0.58 0.61 12\n",
" 7 0.51 0.53 0.52 352\n",
" 8 0.45 0.38 0.41 309\n",
" 9 0.09 0.04 0.06 23\n",
" 10 0.41 0.46 0.44 56\n",
" 11 0.47 0.56 0.51 230\n",
" 12 0.18 0.78 0.30 97\n",
" 13 0.50 0.44 0.47 109\n",
" 14 0.24 0.38 0.29 114\n",
" 15 0.09 0.05 0.07 55\n",
" 16 0.58 0.22 0.32 32\n",
" 17 0.48 0.12 0.19 175\n",
" 18 0.63 0.59 0.61 262\n",
" 19 0.73 0.75 0.74 276\n",
" 20 0.79 0.65 0.71 333\n",
" 21 0.55 0.50 0.52 229\n",
" 22 0.03 0.11 0.04 9\n",
" 23 0.09 0.12 0.11 24\n",
" 24 0.86 0.80 0.83 15\n",
" 25 0.25 0.66 0.36 73\n",
" 26 0.55 0.68 0.61 25\n",
" 27 0.49 0.37 0.42 105\n",
" 28 0.61 0.33 0.42 236\n",
" 29 0.08 0.19 0.11 31\n",
" 30 0.63 0.43 0.51 229\n",
" 31 0.00 0.00 0.00 15\n",
" 32 0.16 0.09 0.12 64\n",
" 33 0.07 0.06 0.07 49\n",
" 34 0.79 0.70 0.74 33\n",
" 35 0.86 0.84 0.85 225\n",
" 36 0.89 0.80 0.84 10\n",
" 37 0.00 0.00 0.00 4\n",
" 38 0.51 0.27 0.35 146\n",
" 39 0.16 0.17 0.17 46\n",
" 40 0.37 0.52 0.43 87\n",
" 41 0.13 0.35 0.19 20\n",
" 42 0.39 0.58 0.47 76\n",
" 43 0.20 0.09 0.13 11\n",
" 44 0.65 0.41 0.50 124\n",
"\n",
" accuracy 0.47 4746\n",
" macro avg 0.40 0.39 0.38 4746\n",
"weighted avg 0.51 0.47 0.47 4746\n",
"\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1080x576 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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zfKcwttVsHkU+ER5bCeu2n+Je9FMyM7Lp1N6ar2c789mkH/jr8XO1d02SCjW5AkwFGo0m3+0nTpwgKCgIBwcHHBwcOHHiBFFRUfrHu3btSokSJf72+Zs2bcovv/yCl5cXP//882v/nxs3bpCQkEDr1q0pVqwYn3zyCYGBgQCEh4fj6OiImZkZxYsXp1ev/6tBe+LECc6ePYuTkxMODg7s2rWLhw8f6h9v164dpUuXRqPR0KRJE/1rCAsLo2/fvmg0GkqWLEmPHj0ICwtDq/375b0+Pj44OTkB4OjoyKFDh0hLS/vb/+/fJiUplRKlDS8qLEoX52ViSqGLa0yv1RjjvqpK7Qos2DWedbP3cT38tqKxRVPrb1y3SS0+sGuM38pDQuO8TkpyKiVKGSa7SpQqxsukVKFxm7Wtx/AZ9kzv/z3277kz3WU1k7xcqNuw4FeevS3fH6UY07lAR6PRMH3bODLTM1k9YasiMSWxjO18a4zfW6Wp9XrTU3MmdgSu+4lnMS9IiEvCb/VhPuzy+kmD/yu1ri3U/kwpfS5Q+/UqyZiOjcYW15g+xyDfW6Xe2z8u3CElKZWM9EyO7TzDjbA/+bCruPOe0m7eekRKSgYZmVkc/vk6V28+pHULsWV3pX9Amy3/KYh/3kJyBZhA5cqV4/nz51hYWAA5ZfySkpIoV65cvv+9Vqtlzpw52NjY5Pt47kRWkSJFDBJHuZNBzZs3JyAggLNnzxIYGMiGDRvYvXs348aN068c27lzJz4+PiQkJNCpUycgp+yhhYUFI0eOfGNSSqvVMmbMGPr06ZPv40WLFtX/bGpqqt83rVabJ/mn0Wh45513qFSpEleuXKFdu3Z5nu/p06f88ssvREREsGbNGgBSUlI4evQo9vb2r93Pf6OHtx5hWsSUau9W5uHtxwDUbVJbeBkONeIa02s1xri5VaxejiX7J7J7xUFO+JxXLK5S1PobN7VtQKVa77Djz5VAzkw9E1MTalpXY7zNbKGxAe5H/EXn/m30vxctYU6V2hW4HyF21rRVw6pcO3+HP69GA3DrSjQRv9+nedt63L1RsLHfhu+PkozpXKAzZeMoylSyZLb912RlZikSUxLL2M63xvi9VZparzfp+UtiH8SBgq1A1Lq2UPszpfS5QO3XqyRjOjYaW1xj+hyDfG/Vem/zG0csTAr765Okt4VcASZQmzZt2Lt3r/73vXv30rRpU4oXz5lJYWFhQWLi/5WPsrOzY9u2baSm5syeT0pK4s6dO/k+9zvvvENGRgb3798H4MCBA/rHoqOj9SusZsyYwfXr18nOzub7778nMDCQwMBAzM3NCQkJwcfHhxMnTnDixAnOnDmDRqPh4sWL2NjYEBgYSGZmJqmpqQbPb2dnx65du/SlFdPT04mIiPiP/h4+Pj5otVqSkpI4ePCgPtk3duxYvv76a4MVb6dPn+by5cv4+/vz6aefcvLkSf2+Ll682KBnmQgmpiaYFTXDxNTE4GeRUl+mccYvnCHzXChWoiiN2tSnjcOHHNsRWujiGtNrNYa4Od+RIpiYanL9bEL5ypZ87TuJ4K2hHNx+ukBjvn4/jON7e3DzCYY2nMLYVjMZ22omIRuPc/7Q78yy9yrQOIbvrUb/3p498Bu1G1Slrf0HmBUtgpu7PZE3HvLgz8cFHNcEE5P/+/nWlWgafVhXv+LLqlE1Gn9Yl8iIgu8BptZ7q8bnGIzrXAAw4fvh1LSuhqfjUtJTM4THA/XeW2OKW9jPt29DXDW/t8b0mQI4+uNpeo3ujGWFUpQsUwKncV0IP/y7sHhKXVu8ytjOBcZ0fWFMx0ZjiyvPBfK9LWgWliVo0fl9/fv5cf82vN/Oml9/uiI0rlKfp5IWRfmweW3MzUwxNdHwSYcGNG1UnfO/RQJgVsQUczPTPD9LkvS/02j/k/pz0n/l2bNnLFq0iFu3bmFiYkKVKlWYPXu2vpfW/v372bRpE8WKFWP58uXUqlWL1atXc/z4cTQaDRqNhvHjx9OlSxc8PDxo3LgxAwcO1D+/j48Pa9asoVq1arRq1YodO3YQHh6Or68vW7duxdTUlOzsbD777DN9+UCdgwcPsnXrVvbv32+wffXq1Tx8+JB58+axYMECzp8/T+XKlWnYsCEPHz5k5cqc2YDbtm3TJ6C0Wi2urq64ubmxatUqXr58yfTp0wEMfk9OTmbBggVcu3YNgF69ejFy5Eh97ICAAH0C0MTEBGtra9zd3Rk+fDjTp0+nQ4cO+v82JSWFdu3aERgYqP97vsknpi7/8fumM8izD4Pn9DXYtn3efnbM9/nPn+S/WPpZqmxJpm4ewwefNCExLolNM3by8+4z//h5/g1xjem1/tvjFqnwzhsfd5vWg4HuPQ22/eh9AK0WBn3Zk5Rkw7J4znUn/23MzKf/vPfEv/l7a2Ju/o/j5jZwtjNVrSqxdNjaf/T/af6mtO7A6fYMnN7LYNuPXkH86BVM8w4NGOvlSsUa5fnj10iWj9tKTHTc38csXfJv/xu3SZ8ycFJXw7jfHmbnt0ewH9wOx89sKfNOKV48S+bA9jP4bTr5t8+ZGfXPZy0WyPdW889uoArkcwz/mnNQQcTUmP6zG8SKNd/hxzurSU9NJyvz//5O343dyIndv/zHz6PN/meX0QX23v5D/+q4/5LPsbHFVePYCP/uz5TJf1DK/lWmRUwZ4+3Gx31bk56WwSm/82yavY+MtH+QqMnM/Mdxdf7ba4vs9H/el/NffS7I+uerxv611xfymCzjFnRMIzsX/Df+re+tSdF/1hva8p1SLAiYRo16VcjOyib61iO2z/Pl0olr/+h5/uk5qKCuk9N6tnzj45ali7PUsze1qpcnKyubqIfP2LzzDBcv5yxs2LthJFUqWRr8P/1GrOfxk4Q3Pu+pQPd/tJ/S63Ux66/2LhQKRzP2qL0LecgEmGQU/psEWIF4S2ufStI/9XcJMBH+mwRYgVDpe/u/JsD+W3+XABMS8z9IgInw3yTACsR/cWNfIIzoHPRPBz0Lyj9NgEn/BSP6HBsdIzs2/jcJsALxPyTA/lv/TQKsIKh2LvgvEmAFQo3vkDwmSwXNyM4FxuSfJsAKilrnoL9LgIkiE2AFRybACsbbmACTJRAlSZIkSZIkSZIkSZIkSZIkSZKkQqWI2jsgSZIkSZIkSZIkSZIkSZIkSZKkBlndo/CSK8AkSZIkSZIkSZIkSZIkSZIkSZKkQkUmwCRJkiRJkiRJkiRJkiRJkiRJkqRCRSbAJEmSJEmSJEmSJEmSJEmSJEmSpEJFJsAkSZIkSZIkSZIkSZIkSZIkSZKkQkUmwCRJkiRJkiRJkiRJkiRJkiRJkqRCpYjaOyBJkiRJkiRJkiRJkiRJkiRJkqQKbbbaeyAJIleASZIkSZIkSZIkSZIkSZIkSZIkSYWKTIBJkiRJkiRJkiRJkiRJkiRJkiRJhYpMgEmSJEmSJEmSJEmSJEmSJEmSJEmKiIyMxMXFhU8//RQXFxfu3bsnJI5MgEmSJEmSJEmSJEmSJEmSJEmSJEmKmDNnDgMGDODIkSMMGDAAT09PIXFkAkySJEmSJEmSJEmSJEmSJEmSJEkSLi4ujhs3btCzZ08AevbsyY0bN3j27FmBxypS4M8oSZIkSZIkSZIkSZIkSZIkSZIkGY2EhAQSEhLybC9dujSlS5fW//7o0SMqVaqEqakpAKamplSsWJFHjx5Rrly5At0nmQCTjMJPWXvV3gVJkiRJkiRJkiRJkiRJkiTpLfNT9n61d6FQWLVqFatXr86zffz48XzxxRcq7JFMgEmSJEmSJEmSJEmSJEmSJEmSJEn/gyFDhuDk5JRne+7VXwBVqlQhJiaGrKwsTE1NycrK4smTJ1SpUqXA90kmwCRJkiRJkiRJkiRJkiRJkiRJkqT/2qulDl+nfPnyNGjQgAMHDuDg4MCBAwdo0KBBgZc/BNBotVptgT+rJEmSJEmSJEmSJEmSJEmSJEmSJL3izp07eHh4kJCQQOnSpfHy8qJu3boFHkcmwCRJkiRJkiRJkiRJkiRJkiRJkqRCxUTtHZAkSZIkSZIkSZIkSZIkSZIkSZKkgiQTYJIkSZIkSZIkSZIkSZIkSZIkSVKhIhNgkiRJkiRJkiRJkiRJkiRJkiRJUqEiE2CSJEmSJEmSJEmSJEmSJEmSJElSoSITYJIkSZIkSZIkSZIkSZIkSZIkSVKhIhNgkiRJkiRJkiRJkiRJkiRJkiRJUqEiE2CS9B+YMWOGKnETExNViStJ/2aZmZncvHmTZ8+eKR47ISFB8Zhqu3jxotq7IEmSJEmFnjzfStLfy8rKIiUlJc/2lJQUsrKyVNgjcZKSknjw4EGe7dHR0SQlJamwR+pR+vh46dIlZs2apWhMgMePH7NmzRrF4xoTte/n//rrL1XjS1JhVUTtHZCkf4OwsDBV4trb23Py5EnhccLCwoiKiiIzM1O/zc3NTXjc/KSmplKsWDFVYksFJywsDBsbm7/dVhCWLl2Ko6Mj9erVIzU1lf79+/Pw4UMyMzPx9vamc+fOBR4TYNu2bbRv3x4rKyuysrIYNWoUZ86cwdLSkjVr1tCiRQshcQH27t2Li4uL/vfs7Gy+/fZbpkyZIixmbk+ePCEgIABfX1+0Wi1Hjx5VJO7b4OLFi7Rs2VLt3RAuLi6O6OhomjVrpvauFCq///674n/T7Oxsbt26hbW1taJxJenfbv/+/Wi1Wvr162ewffv27VhYWNC7d2/h+2DM51u1/PXXX1StWlXt3RDizJkz3Lx5k7S0NP228ePHC48bFhbGnTt3GDhwIE+fPiUxMZE6deoIibVs2TLq1q1L3759Dbbv37+fx48f8+WXXwqJqxMREcGcOXOIiIggPT1dv/3mzZsFHmvp0qXY2tpSvXp1g+2///47Fy5cYP78+QUeE6B3795oNJrXPu7j4yMk7quUPj7GxsYSEBCAn58fGo2Gnj17Co2nk5GRwU8//YSvry/Xrl0Tdm+bW2JiIpGRkQbHig8//FB4XKWPUWrez+eWnp7OTz/9hI+PD9euXePChQuKxJUkYyITYJL0H9BqtYU2rru7O3/88QfW1taYmpoKj/c6v//+Oz4+Phw5ckTICX/Dhg1YWFjkSext3LgRgBEjRhR4zLeFkjedOkuXLsXf399gm7e3N35+fgUe6+TJk7i7uwMQFBSEmZkZZ8+e5e7du8ycOVPYTYKPj4/+8xQSEsKjR4/45ZdfuHbtGsuWLWP37t1C4gIcOnSIc+fOsXDhQpKSkpg8eTI1atQQFg9yVtadOHECHx8fLl++TGZmJps3bxY6mP+2fG+VusH+888/iY2NpU2bNgbbT58+TZUqVXj33XeFxNUZMGAA69evR6vV4ujoSOnSpbG1tWX69OnCYqakpLBu3ToePHjA8uXLuXPnDpGRkcK+t8ePHycpKQkHBweD7fv376d8+fLY2dkJiaszZ84cTE1NGTBgAPb29hQtWlRoPAATExNmzZqFr6+v8Fivym+QrFSpUjRr1ozPP/8cCwsLIXHVmNij5KBnbpmZmfj6+uYZMFqyZImQeK1bt37jwKfoSWN3797N8zd2dHQUEmv37t1s3749z3ZHR0eGDh0qLAGmxvk2t1u3blG9enVKlCgBQHJyMn/99Rfvvfee0LhqDbiC8oOPiYmJbNy4Mc/3Nr/PW0FZtmwZV69e5fbt23Tq1Injx48LmZj2qg0bNhAaGkpsbCwDBw4kMzOTmTNnCrtOPnXqFNOmTcuz3c3NDQcHB+EJsLlz5zJp0iSWLFnCpk2b2Llzp7Bz3cWLF/NNctnb27Nu3TohMQH9deHJkye5e/cuffr0AcDPz4+GDRsKiwvKHx+zsrL4+eef8fHx4ffff+eTTz4hKSmJ06dPC4mX282bN/Hx8eHgwYM0aNCAiIgITp8+jbm5udC4Bw8exMvLi4SEBCpWrEhUVBTW1tZ57u0LmhrHKDXv5wGuX7+uf4/T0tJYtGgRa9euFRpTkoyVLIEoSf+BN93o/9vjXr16FX9/f5YuXcqSJUv0/yghLi6OzZs3061bNwYNGkTNmjUJDAwUEis4ODjPTECAwYMHExwcLCQm5AwU2djY5PlHt120DRs2sHr1av0Nte6mU5T79+8TGhpKUlISoaGh+n8OHDiQbzmSgmBubq7/roSHh9OjRw/MzMyoX7++0FInpqammJmZATkDfg4ODpQvX54OHToIe606W7du5d1338XZ2RlXV1f69u2Ll5eXsHhLliyhY8eO7NmzB3t7e0JDQ7G0tBQ+GKfW9xZyvitHjx5l5MiR2Nvbs379ery8vITOLl2+fDnlypXLs93S0pJly5YJi6vz8uVLSpUqxc8//4y9vT3BwcGcOXNGaMy5c+eSlZVFREQEAJUrV2b16tXC4m3cuJG2bdvm2d6hQwc2bNggLK5OYGAgM2fO5OzZs3Tq1AkvLy+io6OFx7Wyssq3TJJoNjY2VKlShTFjxjBmzBiqVq1K48aNiYmJYe7cuUJienh4sGjRIn799VeuXbum/0c03aBnrVq1CA0NZeTIkUyePFl4XE9PTy5dusTJkyepXbs2165dE7qS3tfXFx8fH/r370/Xrl3ZunUrW7ZsoUePHnz22WfC4kJOcuCLL75g7ty5BAcHM2fOHA4cOCAsXkZGBiVLlsyzvXTp0gbJ1YKk1vk2Nw8PD/31DYCZmZnQiRCQM+Das2dPhgwZwuzZsxk8eDCLFy8WGhNyBh/nzZtH+/btmTVrFn369FFkYHvmzJmYmJhw7949+vXrh6mpKU2aNBEaMzQ0lM2bN1O+fHnmz5+Pn58fL1++FBoT4MCBA2zbtk2fUK1cubLQ8nwmJib5Tuo0NTVV5N46PT0dGxsbtFotFStWZPLkycI+UyYmrx/OE/laP/roIz766COuXr3K2rVr6dy5M507d2bVqlWEh4cLi6vG8bF9+/Zs2rSJHj16EBoayoIFC4QnoACcnJyYNGkSFSpUwN/fny1btlCsWDFFYq9btw4/Pz9q1arFkSNH2LRpk/DjE6hzjFLrfn779u04ODgwZcoUKleuTEBAAOXKlaNHjx6yGpIkCSJXgEnS//e6pfxarZa4uDhhcW/fvv3ax0TdXOdWq1YtUlNThc1My8/x48fx9fXl119/5dNPP2XhwoW4u7szcuRIoXHzu2AUPftejRn3uR04cABfX199EkH0TeelS5fw8/Pj6dOnbNq0Sb+9ZMmSwgZPsrKySEpKonjx4ly8eJFhw4bpH8s9Q1xE3IyMDMzMzLh06ZJ+9iPkDJqJlJ2dTVJSEkWKFCE9PV3453j37t00b96ckSNH0rp1a0C5iQFqfG+XLFlCSEgI9erVw8nJiZUrV9K9e3fhA5APHjzIt0xdkyZNePjwodDY8H/fl/DwcLp37/7aQaSCdOvWLby8vPSJNgsLC7Kzs4XFS05O5p133smzvWLFiooMBAK0bNmSli1bcvPmTcaMGcMPP/yAra0t7u7uWFlZCYn57NkzevXqRYsWLfSDkADfffedkHg6Fy5cYO/evfrfP/74Y4YOHcoPP/xA9+7dhcT87bffOHDggMEAvhLyG/QcNGiQ8Gubq1evEhwcjL29PaNGjWLAgAFMmjRJWLxq1aoBOe/tjz/+qN8+e/ZsBg4cKHRl7r59+9i/fz+urq5s3ryZW7dusX79emHx3jT4lZycLCSmmudbnaysLIPvj7m5ufDeSboB1+HDhxMQEMAvv/widMLJ9u3b8fX1JTU1FWdnZwICAnBzc6NHjx7CYuZ2//59Vq1axfHjx+nZsyddunRR5D6oSJEiaDQaMjIyqFSpEo8fPxYaE6BYsWJ5jsciP9Pp6emkpKRQvHhxg+3JyclC7wt0dNdNlpaWREREUKlSJaHXcM+ePcszeerZs2eKVJKJiYkhLS1NP2Cfnp7OkydPhMVT4/j44Ycfcu7cOc6cOUOlSpX46KOPhMbTMTU1JSMjg/T0dP2YkFLngiJFilC+fHn9cb9t27asWrVKeFw1jlFq3c8vXrwYGxsb5s+fr6/iotake0kyFjIBJkn/n+iZja/zppsdJUojffnllwwcOJAWLVoYDDSLLA8xbtw4bGxsOHTokP6CXfQJPy0tjczMTIoUMTzsZWRkCJ3doxsogpybESDfFR6iKH3T6eTkhJOTE35+fjg7OwuLk1v//v3p3bs3pUqVonLlyjRu3BjIKScn8m/dpUsXhg4dStmyZdFoNDRv3hyAhw8fCk8ou7q6Uq9ePfz8/Hjy5AlTpkzh3Llzwmr9nzlzhuDgYJYuXcqLFy9wdHRUpJG4Wt9btQYg33SjJTqpCjkzej/99FO0Wi1z584lISHhjbOLC8Krx6e0tDShgzapqamvfUz0yk2dixcvsnPnTi5fvkyfPn3o27cv586dY+zYsRw5ckRIzB49eig2sJtbfHw8aWlp+uuZ9PR0YmJi0Gg0wma4Vq5cWcjz/h2lBz11dH9bU1NTUlJSKFWqlNABSJ0nT54YDLw+e/aM2NhYoTHNzc0pUaIE2dnZaLVa6tWrR1RUlLB4LVq0YOPGjXmSelu2bOGDDz4QElOt821uRYoUITo6Wj8oFxUVJXwyhNIDrmoPPuruuczMzHj+/DmWlpbCB3otLCxISUmhefPmeHh4UKFCBUXK31euXJmLFy+i0WjIzs5m3bp1Qstpdu/enenTp7N48WL9Cs7ExEQ8PT3p2rWrsLi548fHxzNy5EhcXV3Jzs5mwoQJQmL17duXCRMmsGjRImrVqgXkJFe/+uqrfCsoFLRu3brh4uKin9By6NAhunXrJiyeGsfH7777jhcvXhAUFMSSJUt48eIFSUlJBsdIEXx8fLh9+zY+Pj64uLhQt25dXr58mW9yt6CZm5uj1WqpVasWO3bsoFq1asTHxwuNCeoco9S6nw8JCcHHxwdXV1fq1KmDk5OTam1XJMlYyASYJP1/b5rNs3LlSmGzfU6cOCHkef9TCxcupFKlSpQqVUqxHmDr16/H19eXbt26YWdnJ6x3Q262trZ8/fXXzJgxQ/86s7Oz8fb2pn379kJjb9u2jY0bN+oTYOXLl2fEiBEMGTJEaFxQ/qZTp0aNGiQnJ2NhYcH+/fu5evUqI0aMEHKj4Obmxvvvv8+TJ08MSpuZmpoKLfc4YcIEDh8+zOPHj5kzZ44+UfD8+XNhN7o6uj4GkPO33rlzp9ASeaVLl8bNzQ03NzciIiLw8fEhNTUVNzc37O3t6d+/v5C4an1v1RqALFeuHDdu3MjTP+HGjRuUKVNGeHxd/6IaNWpgbm5OUlISCxcuFBqzZcuWrFu3jvT0dMLDw9m6davQPlz169fXr5bJLSQkRJFjo729PRYWFgwcOBBvb299ctfBwYGgoCBhcZ2cnIQ995voBse6deuGRqPh8OHDfPrppyQnJxtMECkIO3fuBKB27doMHTqUzp07G0zsEd0DTMlBz9wsLS158eIF7du3Z8SIEZQtWzbfVY4FbciQITg6OtKxY0cgp3TRqFGjhMYsXrw4GRkZWFtb4+3tTZUqVd6Y1P5fubu7M3DgQI4fP07Tpk0BuHLlCs+ePTNY/VaQ1Drf5jZ+/HhcXV3p0KEDkPPeij4XKD3gqvbgY+3atXn+/Dn29va4uLhQqlQpGjRoIDTmihUrMDU1Zfr06WzdupXExEThq4ABvvrqK6ZPn86ff/5J06ZNadmypdBr1nHjxuHh4UH79u2pXbs2APfu3cPOzo4vvvhCWFwdXSUKW1tbzp8/T1paWr6lVAvCkCFD9Cu8dZMh0tLSGDJkCEOHDhUSM7fJkyfTtGlTzp8/j1arZdKkSfpzgghqHR8tLS0ZNGgQgwYN4saNG/j4+NCnTx9q165tsMq9oL377rt4eHgwbdo0fv75Z3x9fWnXrh0dOnRgxYoVwuJOnDiRpKQkpk2bxty5c0lMTGTOnDnC4umocYxS637eysqK6dOnG7y3T58+5csvv8Te3l74+JQkGSONVqaZJelvdezYkZMnT6q9G0J069aNQ4cOqRL7+fPnBAYG4ufnx507dxgxYgT29vbUrVu3wGMlJyczcuRIHj16pB9cvnHjBpUrV2bjxo3CZvgEBgaydu1aZs2aRdOmTdFqtVy5coUlS5YwevRoevXqJSSuTmxsLNOnT+f8+fNoNBr9TWf58uWFxrW3tycoKIjbt28zceJEevXqxdmzZ4U291bTy5cv0Wg0wmfkvU0yMjI4duwYfn5+bNy4UUiM5ORkRo0axV9//aXo9zY33Q32gQMHsLKyEnqDffr0ab766ivGjRvH+++/D+SUN1uzZg3z5s3D1tZWSFyd/ErylipVikqVKgmLmZGRwaZNmzhx4gRarRY7OztGjhyZZ9VfQYmMjGTQoEG0atVKP6B9+fJlwsPD2bFjB3Xq1BESV+fq1av691ZJ9+7dY8aMGcTExHDixAmuX7/OiRMnFBkMPHHihH5wrFWrVsISnDNmzHjj40r1N4Wcz7XIQc/csrKyMDU1JTs7m6CgIJKSknB0dFQkdkREBBcuXNC/t/Xr1xca79atW1SvXp2UlBRWrFhBYmIiY8aMEZo4SE1NJTg4mBs3bqDVamnUqBE9e/ZU9HyvxPn2VZGRkZw9exaAdu3a6VeXiBIWFkbjxo2Ji4vTD7hOnTqVNm3aCI2blZWlH3z85Zdf6Nq1q+KDjxcvXiQxMRFbW1vFJiOqISUlhezsbMXK7t+/f9/geyv6M5xbVFQUUVFRBpOndAllEV6+fKm/hnv33XcNSh0XdmocHyFnRfuxY8eElXN+ndjYWAICAoSWGzYmSUlJPH/+nOrVqxtsj46OpmzZsopcS+nExcXh7+9PQECA0P6mkmSsZAJMkv4DHTp0IDQ0VMhz29jY6H/WarX68hu6n8PCwoTE1Zk0aRIzZ86kYsWKQuP8nWvXruHr68vBgweFNs8NCwvj+vXraLVaGjdubPD3F8HNzY2vvvoqT1+fiIgIFixYoJ+xLprSN51OTk74+/uzefNmzM3NGTRoEI6OjgQEBBR4rNf174Occjb79+8v8Jg6wcHBrFy5kgcPHgBQvXp1vvjiC2GJTW9vb9zd3ZkwYUK+r1nULLk///yT2NjYPANRp06domrVqrz77rtC4uqcPXtWP4ihxPc2P0rdYJ85c4Y1a9Zw48YNABo1asTo0aMVGYyzs7Pj0aNHlCpVCsgpGVS+fHnMzc1ZsWKFkB5oucvjKSU2NpadO3caDIwNGDBAkfOgVqvFx8eHe/fu4e7uzoMHD3jy5Imwcmo6Q4cO5bPPPmP58uUEBgaSnZ2Nvb09ISEhQuMaG6UHPSWx1BgYU/t8a8zUGHxMT083OF6ITKzevXuXdevWERUVZdBn2sfHR1hMHSWPja/7Dp0+fZoqVaoI/w4tXbqUgIAA6tSpo19NotFohEwCvHjxIvHx8XzyyScG2w8ePEjlypWFXVsY0/3I/v370Wq19OvXz2D79u3bsbCwoHfv3gUeE3J6piclJekrfuTen/LlywutlpCamsqBAwfyHCtEtsgAdY5Rnp6e2Nra0rlzZ4PtwcHBXLhwQVh7gcePHxMbG5tnUtyVK1eoWLGiauW8JakwkyUQJek/ILImfIkSJShTpgzOzs7Y2toK77fyqsTEROzt7WnevLnBIKTI5eb5DSg0btwYS0tLxo0bJySm7iLDxsbGYPD8ypUrVKpUSdgKh6dPn+ZJfgFYW1vz9OlTITFfpcaAXGZmJr/++itHjhxh0aJFAMJKyOXXvy8qKoq1a9eSnZ0tJCbk3ID88MMPfPXVVzRr1gyNRsOlS5dYtmwZqampeW6UCkKLFi0A+Pjjjwv8ud9k+fLlTJo0Kc/2MmXKsGzZMtatWyc0fps2bWjTpg1Pnjzht99+448//hC60iC/G2wzMzMsLCyE94ts164d7dq1ExrjdTp16kSrVq30N4HHjh3jypUrtG3blkWLFglJJtvZ2dGrVy9cXV2pWbNmgT//q7KysihZsmSez3NKSop+JY1IS5YsIS4ujuvXr+Pu7o6FhQWLFy8WPgCpW12gK5ljYmKSp/+aCHfv3mXt2rVER0crNpiRmZnJ3r179ZNpWrduTb9+/YStKtR53aCn6PPtr7/+yvLly/Oc50VNoHJ3d8fb2/u1k09EvrdxcXH8+OOPeQbHRF2zLl26FFtb2zwJsN9//13YwJja51uAS5cu4e3tTXR0NFlZWYpMylN6wDW/wcfy5cvz0Ucf0bNnTyExczt8+DBLlizR9+vT/Y1v3rwpLObEiRNxcHDAyclJ0ZVmy5cvZ//+/VhZWSlybHzdd8jS0lKR79CxY8c4fvy4IqtEV61alW950gYNGjBv3jy2bdsmJK4x3Y/s3r073+Slo6MjQ4cOFZYA27hxI6tXr86zvUOHDkyYMEFoAmz8+PGYmJjQqFEjg1LSoqlxjLp48WK+53J7e3uhxwpvb+98K4okJCTwww8/sHz5cmGxJclYyQSYJP1/r5vBpNVqefHihbC4x48fJzw8HH9/f7Zv306nTp1wdnZWbIZnz549FbnRy02NAQW1LjLetOJKifIUSt906kycOJH58+fTunVr3nvvPSIjI4WVHsndn+/p06d8//33HDt2jM8++0xoz5cffviBzZs3GyRPO3ToQL169fj888+FJMB0NzutWrWiatWqBf78r/PgwYN8E7lNmjTh4cOHwuIePHiQWbNmUbp0aWbNmsW8efOoVq0a9+/fZ+LEiQwYMEBIXLUGINWaZapz/vx5Zs2apf+9c+fObNy4kSlTpgjrsxMUFMTevXsZMmQIVlZWuLm50bFjR2ETT5YtW0bdunXzNIffv38/jx8/Fj67NTw8nICAAH1PrrJly5KWliY0JuT0RMzIyND/XWNiYhSZcDNlyhS6du2Ks7OzYoMZ8+fP5+HDhzg6OqLVagkKCiIiIkLYLF4dJQc9c5s5cyaTJk2icePGirynuv6loicD5Gfs2LE0bNgQGxsbRT5PagyMqXW+zW3WrFmMHTuWZs2aKTYxT+kBV7UHH729vVm1apVi31uAIkWK8PnnnysSK7fDhw9z7NgxxUqJqf0dqlKliiITTACePXuWb3/lOnXq6HtPi6C7H1G6v6ga721GRka+n93SpUsbJOsLWnJycr79PCtWrMjLly+FxQV49OiRKhUC1DhGven4K3ISfEREBB9++GGe7e3atePrr78WFleSjJlMgEnS//emGUz5XWgVpFatWtGqVStevnxJSEgIgwYN4osvvhA2uJub0heuoM6AgloXGXFxca8tcyiyubeO0jedOp07dzYoJVCnTp18Z7EVlKSkJDZs2ICvry/9+vXj0KFDwl+zVqvNd+VglSpVhMYFcHFxwcrKCmdnZz799FPhJeQyMjL+q8f+V+vWrcPHx4eEhASGDRuGr68vVlZWxMTEMHz4cGHHSLUGT9SaZaqTnZ3NpUuX9CVzfvvtN1JSUoA33yD+L8qXL8/YsWMZNWoUx48fZ968eSxYsICBAwfi5uZW4J/tU6dOMW3atDzb3dzccHBwEJ4AK1q0qMENtchVqrkNGDCA8ePHEx8fz6pVqwgICGDy5MnC42ZnZzN69GjhcXK7cOECISEh+s9s9+7dsbe3Fx5XyUHP3EqXLk23bt0Ui9e4cWPg/yaf6AbilJjUk5KSwpw5c4TH0VFjYEyt821uxYoVU+Q7k5vSA65qDz5WqFCBJk2aCI+TW/v27Tl16pTwfqKvqlChgqL3IWp/hzw8PBg9ejRt27Y1SOaKmJT3pslJoiYu5fbs2TMWLFhAWFgYGo2GNm3aMGvWLMqVKycknhrvre46OD/JyclCYsKb37837VNBeO+993jy5IniLTLUOkY9e/Ysz2f22bNniOwW9KbnVureQJKMjUyASdL/92oi6MmTJwQEBODr64tWq2Xs2LFC49+5cwd/f39++uknbG1tadWqldB4Ol9//TXjxo2jePHiDB48mBs3bjBv3rw89aYLkhoDCmpdZLRp04Zr167l+5gSfYyUvunM7cyZM9y8edNgdcP48eMLPM6mTZvYtm0bXbt2JTg4WNhN16syMzNJTEzU90vSSUhIEDojEODkyZOcOnUKf39/Fi9ezCeffIKzszPNmzcXEq9cuXLcuHGDhg0bGmy/ceMGZcqUERITco4VVlZWQM7gsu7nSpUqCS1nptbgiVqzTHXmzJnD5MmTKVasGBqNhpSUFJYvX05ycjJDhw4VFjclJYXAwEB27dpFzZo16du3L+Hh4YwYMaLAe2aYmJjku3LE1NRU6ExPnXr16hEUFIRWq+XBgwds2LBBX0pIJEdHR6pXr87PP/9MSkoKXl5etGzZUnjcZs2aERERIXwiUW6VK1cmPT2dYsWKATnHaiUmJig56Jlbz5492b17N926dTNIGIteiRYdHc3UqVO5efMmGo2Ghg0b4u3tne9qhILStGlT4SVwX6X0wJha59vcbG1tCQ0NVbR/ndIDrmoPPg4aNIhvv/2WTz75xOB7K7ICiI2NDWPHjsXExARzc3PF+k03a9ZMvxo492sV9flS+zu0YcMGYmNjuXnzpvCVqjVq1ODs2bN5emKFhYUpUilizpw5vPvuu3h4eKDVatm3bx+enp7CJj2q8d62aNGCjRs3MmLECIPtW7ZsEdq/tX79+gQHB+eZjBASEsJ7770nLC7k3K/369cPa2trxVpkgDrHqL59+zJhwgQWLVqkr1Zz//59vvrqqzzVIgpS0aJFiY6OznPNFB0drXhvZEkyFjIBJkm5ZGZmcuLECXx9ffn999/JzMxk8+bNNGvWTFjMXbt2ERgYiLm5OU5OTgQEBChaPufs2bN4eHhw8uRJKlWqxDfffMPIkSOFJsBA+QEFtS4ylixZIuy5/xNK33TqLFu2jKtXr3L79m06derE8ePHhSX8li1bRoUKFfjtt98YOXJknsdF9SNxcnJi7NixLFiwgNq1awMQGRnJnDlzhK+sNDU15eOPP+bjjz/m+fPnrFixggEDBgjrHTF27FjGjh3LuHHj9P0yrl69ypo1a5g3b56QmGCYENcNZuf3WEFTa/BErVmmOi1btuSnn34iMjISrVZL3bp19QP5oj7TCxYs4MiRI9jZ2bF8+XL9Tb29vT1du3Yt8Hjp6emkpKTkOc8mJyeTnp5e4PFe5eHhwddff01sbCz9+vXDzs5OkVJyFy9epGXLlookvXK7cuUKfn5+1KlTx+AcJLJPVPXq1XFxcaF79+5Azkroli1b6ldji0pIKTnomVv58uX56quv9CvrleglBDmN4/v166dfmern54enpydbt24VFrN///4MHDiQypUrK/J5UmNgTK3zbW579+5l/fr1WFhYKDYIqfSAq9qDjzExMWzbto2AgACDEuXHjx8XFtPT05MlS5bQqFEjRXtOX716FYAdO3bot4ksx672d+j69escOXJEkUk1kyZNYvTo0fTt21e/ovDKlSvs379fkX6BUVFRrFq1Sv/7hAkThI4hqPHeuru7M3DgQI4fP07Tpk0BuHz5MvHx8fz4449CYgJMnTqVQYMGcfLkSYO44eHhBt8lEb788kvs7Oxo2LChotczahyjhgwZwrNnz+jVq5f+2J+WlsbQoUOFTv4bNmwYY8aMYebMmQbf3SVLlqhSqlaSjIFGK3JdpyT9iyxZsoSQkBDq1auHk5MTn3zyCd27d+fEiRNC41pbW9OwYUOqV6+e74Wy6Jk2vXr1IigoCG9vbxo1akT37t1xdHQkICBAWMwffviBn376Kd8BBTs7OyEXG0FBQWzYsOG1FxmiLtZv3779xsdF93obNGhQnm0ajabAV1W8yt7eHn9/f5ydnQkKCiImJoZ58+axZs2aAo919uxZ0tPT85RfevnyJebm5nlmRRYUrVbLmjVr2Lhxoz5JkJGRweeff87YsWOF3/g+f/6cAwcO4O/vT1JSEo6OjowZM0ZYvDNnzrBmzRpu3LgBQMOGDRkzZgzt27cXFrNZs2b678jt27f1P2u1Wu7evctvv/0mJO7p06f56quvXnuDLao0x/Tp03n33XfznWV68+ZNvL29hcTNLSUlhcePH5OVlaXfJuI49ddff1G1alU2bdqEi4uLwUrK69ev06hRIyGrAb777jvu3LnD4sWL9avtEhMT8fT0pGbNmoqUBVSDs7MzSUlJODk54eTkROXKlRWJe/78+Xy35+7dWNBmzJjxxsdFTUzp0qWLYoOeudnZ2fHdd98pPqjt4OBAYGDg324rSN27d6d37955BuVEfp6++eYbtm3bZjAwNmTIEKZMmSIsphrn29xeV+q3WrVqwmI6OzvTrFmzPO+tqMkXat0X6Hz88cfs3btX0RJjffr0ETr54G2i5ndo5MiRfPPNN2/sA12Q/vjjDzZt2sSNGzfQarU0atSI4cOHK7Ly2t7enm3btlG+fHkgp/T/0KFDCQ4OFhZTjfc2NTWV4OBgg79xz549hU9ajo2NZefOnQZxBwwYIPy4YW9vL/Q9fB01j1EvX77Uj9u8++67ipR13r9/P99//z0xMTFotVoqV67MmDFjcHFxER5bkoyRTIBJ0v/XpEkTmjdvzpgxY2jdujWAfuWKSP7+/q997NGjR8JLLw4bNoxq1arxyy+/EBAQgIWFBU5OTsIvevIbUBg6dKjQwcfcFxmQU0ZN9EWGtbU1lStXxtTUNM/qNtEzPdXUu3dvfH19cXBwwMfHBzMzM5ydnfHz8yvwWF5eXtStWzfPbOzt27fz+PFj4T190tPTuX//Plqtltq1ayvSvH38+PH8+uuvdOrUCUdHR8VXdSjldYPnOiIHPdW4wX769CkDBw6kTJky+c4yrVChgrDYADt37mTZsmWUKVNGP4gv6jjl5OSkP/+9esOb+7GClpmZiYeHB8ePH9ev3Lx37x52dnZ4eXkJLa2pExYWRlRUlEFZS9Fl8gBu3bqFv78/Bw4c4L333sPZ2ZmePXsKj2sslB701Onfvz979uxRNCbkfE+XL19O3bp1gZwV0FOnThVyns8dU9Sx4U3UGBgzNmoMuKo5+Ojm5vbaHsGirFu3DktLS8XLpULOxKKzZ8+i0Who27Ytbdu2FR5TLVOmTOH69eu0b9/e4J5A9P2IGgICAli+fDkdO3ZEo9EQGhrKlClThCeQ1Xbv3j39NWRh9NVXXzFw4EBFyw2DOseov/76y+B3jUZDuXLlFC1DqKuCpEskS5IkhkyASdL/l5CQQHBwML6+vrx48QJHR0d8fX05efKkovvxau+xo0ePCo337NkzgoKCaNasGc2aNePBgwecP38eZ2dnoXFB2QGFzz//nE2bNgHKXmRMnz6d3377jc6dO+Ps7Cx8xVd+1LjpHDx4MOvXr8fLy4vExEQqVKjAr7/+yv79+ws8Vo8ePQgKCspToiErKwsHBwcOHDhQ4DHh7xsQi7xYDwwM5NNPP81TFlA0rVbL3r179Z+nNm3a0K9fP8VXPACsXLmSCRMmKB5XNLVmmULOpI/t27cLneWvk3ul8aurjkWvQoacVce5/8a61ciieXh4cO3atTyrHJQsl5uens7ChQvZv3+/8DJ5vXv3zvf4IHqGrxpJRrUGPb/99lsyMjLo3r27Yr2EAE6dOsX06dNp0KCBvuTi0qVLadeunbCYK1asoGXLlsJW4f6dqKgoTpw4QY0aNejUqZPQWGqebx89eoS3tzcREREGfVxFTtpSa8AV1Bl89PLyIiYmRtES5fmtCFKiXOrGjRsJDAykR48eABw8eBBHR0eGDx8uJF5SUhJ79uzB0tISR0dHli1bxtmzZ6lduzYzZ84U3hPydf2vRPRBDg8Pp1atWvpV3Rs3buTAgQNUr14dT09PKlWqVOAxX3Xr1i3Onz+PVqvFxsZGkXtdte9HlJyM8ezZMxYuXGjwWmfNmiW057WDgwN37txRtHw1qHOMat26NRqNxmCiclJSEs2aNWPp0qWK9NIzpgkCkqQmmQCTpHxERETg4+PDgQMHsLKywt7env79+wuLp0bvsbfF7du3CQ8PB3IuQKysrITEUWJA9XVevnzJ4cOH8ff3Jy0tDUdHR+zt7Q1Kfomi9E2nztOnTyldujRZWVls3bqVxMREBg0aJOQi8k2zhkXOKLa2ts5zwZx71Yxu5VBB02q1ODg4EBQUJOT538TLy4ubN2/qE+QBAQFYW1urMqu1Y8eOwicoqH2DDTmTM0qXLq1ILCVXkuQePHh1IEHJgYWEhATOnz9P9erVFSkX9Omnn3LgwAHMzMyEx3pV7hVg7777Lk5OTvTq1UtozNyrONPS0ggJCaFixYpCy8dNmzaNW7duYW1trWiSUclBz9zs7OzybFNqhXlcXBxXrlxBq9XSrFkzoQNykHOd+Pz5c8V6Uw0dOhQPDw+sra15/Pgx9vb2+sliDg4OjB49WkhcUPd8O2zYMLp3786WLVtYvHgxu3fvpmbNmkI/y2oNuII6g49qlShXg729Pbt379aXHU5KSsLV1VXY9fmECRMwNTUlJSWF58+f89577/HJJ58QHh7On3/+yYYNG4TEVYOTkxPbtm3D0tKSc+fOMWnSJDw9Pbl58yb37t0z6M9VmKh9P6LkuMIXX3zBu+++S//+/dFqtezbt49bt2699pqjIKhRvvptkpWVxZ49ezhz5gxr164VGkutsRpJMkbi67xI0r+QtbU1s2fPZvr06fz000/4+/sLS4C92nvsu+++o3v37oolv9SY5akTEBDAsmXL6NixIwDr169n2rRpQgbktFotqampecoQ6ohcXVGiRAmcnZ1xdnYmNDSU6dOnk5ycnKfPjwhBQUHs2bNHf9M5aNAgXF1dhV9UvfPOO0DOrDXRZTzT09NJSUnJ8x4mJyeTnp4uLG5ERITB71qtlsDAQFavXk3Dhg2FxdVoNNSoUYMXL15gaWkpLE5+zpw5g7+/v75MXLdu3XB2dlYlAabE/J2lS5fmucG+f/++sNe7bds22rdvj5WVFVlZWYwePZrTp09jaWnJmjVraNGihZC4Om3atGHp0qX06NFD+EqStLQ07ty5g1arNfhZ95go06ZN4/PPP8fa2prnz5/j4OBAyZIliY+PZ/LkyXlKqRY0pXpvvcrJyYmXL1/i4ODAvn37hM+A13l1sKRdu3Z89tlnQmNeu3aNkJAQRRu3g/hE1+uI7lX7JuXLl+fjjz9WLJ6vr69isSCnKoMuMR4UFISNjQ0rV64kISEBNzc3oQkwNc+38fHx9O3bl+3bt9O8eXOaNm0qpD9vbrNmzRL6/K/z6uDj119/rcjg444dO4Q+/+vEx8dz+fJlNBoNTZs2pUyZMorE1d2HvPqzCHfu3CEkJISMjAzatWvH7t270Wg02NraKlL2NyUlhTVr1hgkVUePHi3kXjMzM1N/L3DixAl69+5N9+7d6datm/AJLgCXLl3C29ub6OhosrKyhE9K0FH7fuSDDz5QJA7krDzOncicMGGC8BKTumu3ly9fAiha9letY1RupqamuLm5KTIBQ62xGkkyRjIBJklvYGZmRvfu3enevbuwGLt376Z58+aMHDlS33tMydUFM2fOpHv37ty8eZNly5bpZ3kqYcuWLfj7++v72sTGxjJ8+HAhF+x//PEHzZs3z7NaR3ehLnJpfWJiIsHBwQQGBmJubo67uzvdunUTFu9VSt506ly+fJlJkyaRnZ1NaGgoV69eZd++fSxYsKDAY3Xv3p3p06ezePFi/etLTEzE09OTrl27Fni8/Jw4cYJvvvmGChUq8O2339K4cWOh8UqUKIGTkxO2trYGNyVK3PjlPj6pUfpQydhK32D7+Pjoy7SFhITw8OFDfvnlF65du6Y/Poukm816+PBh/TZRK0lSU1MNJgHk/lnke3vjxg39gHZgYCBWVlZs2bKFx48fM2rUKOEJsNq1azN06FA6d+5sUCZPdHm+WbNmvRW9ApOSkoiOjhYao1atWqSmpirei0vJQc9XKbWaXvf8+X1HlRj4rFatGpmZmURGRqLRaKhdu7bQvn25JwJcunSJzp07A1C6dGlFEqxqnW91K1RLlCjBX3/9xTvvvJOnT0pBU2vAVc3BR6VXnp0+fRp3d3caNGgA5NwbeXt7C4/buHFjZsyYQd++fdFoNOzfv1/odbLu3GpmZkaVKlUMvjtKrL5esGABWVlZzJw5E8i5tps/f77wVci///47Y8aMAZQ7XsyaNYuxY8fSrFkzTExMFImpo+b9iIeHB7GxscJ78wJkZ2cTFxenL9EaFxdHdna20JjR0dFMnTqVmzdvotFoaNiwId7e3tSoUUNoXLWOUa+TlZWlSBw1xmokyRjJBJgkqezMmTMEBwezdOlSfe8xpU62oM4sz9xyXziKvIi0trZWpQTipEmTuHXrFt26dWP58uVUr15d0fiv3nTu27dPeHIGclY2bty4kWnTpgHw/vvv4+HhISTWuHHj8PDwoH379vqGxPfu3cPOzo4vvvhCSEydixcvsmzZMrKzs5k5cyY2NjZC4+nUqlVLsZ5FubVr144RI0bg5OSERqPB399faL+XCRMmvHag9cWLF8Li5qbkDbapqal+cCYsLAxHR0fKly9Phw4d+Oabb4TGBmVXkqi1aiX3gPavv/6qH9CuXLmyIgMo6enp1KxZk1u3bgmPBTmDGDVq1KBMmTL6npu5ie7VkbsHWHZ2Ng8ePGDYsGFCY3755ZcMHDiQFi1aKNqLS61BTyVX04Pyq7Byu3r1KhMmTNCXP8zMzGTVqlU0atRISDwzMzP+/PNPypcvz4ULF5g9e7b+MZErVUH5863O8+fPKVmyJC9evGDAgAE4Oztjbm4ufEKRWgOuoM7goxorz7755ht27typT5DfuXMHd3d34YPLX331Fd9//z0LFy4Eclabi6wOkZiYSGhoKJBTDUL3M+RMwhDt6tWrBuUdP/jgA2HH43r16uHt7U3FihW5d+8erVq1ApR5nQDFihXD3t5ekVi5qXF8nDx5MvPnz8fMzAwHBwfi4+MZNWqU8GT58OHDcXR0pGPHjmg0GkJDQ4WWkQbw9PSkX79+9O7dGwA/Pz88PT3ZunWr0LhqHKPy6+n9/Plz9uzZw3vvvScsro7SEwQkyZjJBJgkqax06dK4ubnh5uam7z2WmpqKm5ub8N5joM4sT52aNWuycuVKXFxc9MkZUTe6aq1UOXz4MJaWluzcuZNdu3bptytVIuLVm862bdvqZweKlJGRkWdgVdSsyyJFirBs2TLu37/PjRs30Gq1NGrUSHiCaOTIkdy9e5fx48fz6aefAoYX0SJn/atVasvd3Z09e/bw008/odVq6dy5My4uLsLi5S6tpfsO61ZxKlF2S+kb7KysLDIyMjAzM+PSpUv06dNH/1hGRoawuOnp6Zibm+d7EwhiP8tqiImJwdLSkvPnzzNhwgT9dtED2iC+D9WrFi5cyPr16xk5cmSexxITE7lw4YLQ+NOnT9f/bGpqSvXq1XFxcRF6Hlq4cCGVKlWiVKlSipZBVHLQMzclV9NDziosnaSkJO7fvy8sAfWqRYsWsXjxYv1kk3PnzrFgwQJhvQunTJnCwIEDSUlJoW/fvvpJTL/88gt16tQRElNH6fMt5PQemTFjBhYWFnTq1IlVq1bh5+dHUlIS9erVExpbrQFXtQYf1Vh5lpmZabA61MrKiszMTGHxdEqUKIG7u7vwODpVqlRh06ZNQM7kFt3Put+V8PLlS/0qxtddWxWEOXPm8O233xIeHs53332nj3nlyhV9+W6RbG1tCQ0NpUOHDsJj5abG8TEyMpJSpUpx+PBhWrVqxYwZM+jXr5/wBJijoyMNGzbk/PnzaLVaBg8eLHzy0rNnzwzuQXr37q1If0I1jlHNmzc36Omt0WgoV64cbdq0UaQ071dffcWaNWsUmyAgScZMJsAk6S2iZO8xnZYtW/L8+XNcXV0Vm+WpM2/ePBYuXKgfpGnbti3z588XEiv3gI3Oli1bhPciUaKXWn6ysrI4evQolpaWuLu788MPP3D27FkyMjIUWWFobm5OcnKyPmlx+/Ztg5UXIii9KurUqVNAThmMGTNmABhcPIssqxkXF8eSJUt49OgRO3fuJCIigt9++w1XV1dhMQFMTEwYMGAAAwYMEBpHx8nJiStXrrB582bu3LkDwHvvvcewYcNo0qSJ8PhK32B36dKFoUOHUrZsWTQaDc2bNwfg4cOHQsu5ubi44O/vn+cmEMR/lpU2cuRIHB0dMTMzo0WLFvpBhN9//52qVasKi7tz5843Pi6qBOL69euB/FfcKTFglV/DdNH9+x4/fsyhQ4eExngdpQY9X6XUavrcQkND8fT0xNTUlBMnTnD16lW+//571q1bJyxmSkqKwUrr1q1bC/07t27dmrNnz5KcnEzp0qX125s3by68V6/S51uAtWvXsmfPHho0aMC5c+f4/vvvFetVpdaAq5qDj0qvPCtXrhx+fn76xIi/vz/lypUTHjcpKYk1a9Zw7tw5NBoNrVu3ZsyYMcJes1r91XTs7e1xcXGhR48eaDQaQkJChPVsKl26NJ6ennm2t2nThjZt2giJmdvevXtZv349FhYW+pW5SkzwVOP4qEvEXLhwgQ4dOlC8eHHFyj7Wq1dP+CSE3ExMTLh79y5169YFcpJ/SkwoUuMY9WpPb6WVKFFCXzFHkiSxNFolushLkvSv8Ndffykyy/Nt4eTkhL+/v9AYSUlJPH/+PE/pw+joaMqWLSvs5s/T05Nbt26Rnp5O9erVSU9Pp0OHDly4cAGtViu8nFpoaChr164lOjqa9u3bc/r0aby9vRW5GTMGY8aMwdbWll27dhEcHEx6ejq9e/c2WH0gQlxcHDt27CA6OtpgRt53330nJN5vv/3GyJEj6d+/P02bNkWr1XL16lX27NnDxo0badq0qZC4ajp8+DCPHz+mR48e+oHs69evEx8fr0j5K2MQGxvL06dPsba21ifpY2JiyMrKEpYE0yXJ4+PjOX/+vH4QPywsjHbt2rFy5Uohcd+kY8eOnDx5stDFnTRpEjNnzqRixYrCYuRnw4YNBAcHGwx69urVi88//1xo3PHjx1OvXj2D1fQ3b97k+++/Fxq3d+/erFu3jhEjRuhLTHfv3p2DBw8Ki9m/f38mTZqk75l7/vx5VqxYIWwFWH6UmDwFyp9vARwcHAgMDNT/7ujoqFj5cCcnJ5YvX24w4Dp16lT8/PwUia803Tkh98ozrVYrdJVwVFQU06ZN0w/4NmjQAG9vb+G9nydMmEDJkiXp06cPWq0Wf39/EhISFD3vDRw4kB9//FGxeKGhoZw7dw6tVkubNm2wtbVVLLaSr/Xhw4f5bs9v4mlBUuP4OHHiRBITE7l79y4HDx7ExMQEFxcXg2OmCJcuXcLb25vo6GiysrIUSTKeOnWK6dOn63txRUREsHTpUuH3IbpjlK4UrlLHKDWlpaURFBSU57OsRF9vSTI2cgWYJBmp/GbMli1blrJly5KSkqJYyauwsDCioqIMTviiZsK/Son8/9KlS7G1tc2TAPv999+5cOGCsBVvFy9eJCQkhJSUFNq1a8e5c+cwNzfHxcVFkZJMH3zwAd7e3pw+fRqtVsuYMWNU6VmltPPnz+e74qGgxcTE4Orqyt69e4GcFXdKzEL84osvsLKywsbGRpGZgJs2bWLx4sV88skn+m2ffPIJTZo0Yf369axZs0ZofDVusF9dgXvv3j3Fyovt378fGxsbxXsVKq1ChQoGq2QOHDhAz549hcbUDWqOGzeOwMBAfbnf6OhoVqxYITS2GvLrN6YjupxNYmIi9vb2NG/e3GDlscjvLeSsLqxfv75+0HPatGmKDHrmXk2v0Who06aNsGuLV7262ix3zzURZs6cycSJE/VxMjIyhL+vrwoODlYkAab0+RZy/p537tzRXx+np6cb/C6y7NbkyZNxc3OjQYMG+pXHS5cuFRZPR63BRzVWntWsWZN9+/aRnJyMVqtVrN/Z3bt3OXDggP73Fi1aCD/nvkqpnlg6HTp0ULwsoE5ycrJisUQnul5HjeOjl5cXZ86coX79+pQoUYKYmBimTp0qPO6sWbMYO3YszZo1U2zFma2tLQcOHODKlStotVqaNWumyGpRtY5Rapo4cSIZGRk0adJE+DWUJBk7mQCTJCOVX6krHaVKXnl4eHDt2jUaNmyoyMVrVlYW48aN05fnUWK5+cWLF/MdiLK3txdaJsjc3ByNRkOJEiWoWbOm/oLKxMREWC8uHa1Wi5ubG0FBQYqWpngbLFmyRPiqQsjpe5ZbQkKCIgndhIQEFixYIDyOzu3btw2SXzqdO3fG29tbeHw1brBfNXnyZEU+UwA3btxg8+bNZGRk0Lp1a2xsbGjdujXvvPOOIvHVsnnzZsUG4x4+fGjQ67JGjRpERkYKi6dWIiq/nmM6osvh9uzZU/HBVR01Bj3Lly8vfFV3fiwsLHj69Kl+FWV4eDilSpUSGrNJkyYcPXqUyMhItFotdevWFX5N8yqliqcofb4FSE1NZcSIEQbbdL9rNBqhZb1tbW0JCQnh8uXLig64qjX4qEbZq4CAAD7++GMsLS0BeP78OadOnRI+Ma5q1ao8e/ZM/37Gx8crPtFGyff27t27+ioYuc+zPj4+isRX4pjo7u6Ot7c3vXv3zrfPtujXqsbxsVixYnTu3Fn/e6VKlahUqZIice3t7YXHeVX58uVp27atvnWCUhOko6KiiIqKMmjZoFYyWQn3799XrWy3JBkbmQCTJCOldr1jyClvduDAAcUGL0xNTUlNTSU7OxsTExNFyom9aaZWfjcMBSX3rN1XZ/CmpaUJiws5r6tGjRq8ePFCf5NtLJQaGOvSpQuenp4kJyfj5+fHrl27FGl2/d577xETE6PIDR/k3PT9N48VFDVusF+lZKXqOXPmADk9lE6ePMmKFSt49OhRoeoBlh8l/8ZlypTh+++/p2/fvgD4+vpSpkwZYfHUSkTl13NMKW3atFHsGAXg7e2Nu7s7EyZMyPe8LmqF0q+//kqLFi0IDQ3N93HRA0ZTp05lxIgRPHjwgEGDBnHv3j3Wrl0rNObEiRP57rvvDEp167YpRamkhdLnW1D3e7to0SJmzZrFxx9/nGebSGoNPqqx8mzLli04Ojrqfy9TpgxbtmwRlgDTreArUaIEDg4O+vf25MmTBr38lLBv3z7FYk2ZMoWuXbvi7OysyuQpJV7rkCFDAJg+fbrwWPlR8vg4ZMgQfvjhB1q3bm1wjleq35mtrS2hoaGKJoGOHDnC4sWLefLkCfB/r1X0/cDy5cvZv38/VlZW+jEUjUZTqBNgNWrUICkpyShWu0mS2mQCTJIknj17xuXLl9FoNDRt2pSyZcsqErdy5cqKxMmtadOmjB8/np49e2JhYaHfLvLCKvesx9zbRA66vjqLN/fPIhNvOiVKlMDJyQlbW1tKlCih317Y61m/Wr6uoGVlZZGens7nn39OUFAQCQkJhIaGMnjwYHr06CE0NuQkhHr16qVYabFXyzG9+phoagxAvuqDDz5QLNa1a9cICwsjLCyM2NhY2rVrp/gglRoGDx6sWCwvLy8WLVqkn83bunVrvLy8hMVTc0BbLb1796Z58+a4ubnpe0WJ1KJFCwCDgXsl+Pv706JFCzZt2pTnMSUGjJo2bcr27du5dOkSkFNZoHTp0kJjRkVF5dl29+5dYfHyKxfeokUL/XaRs+GVPt+q7eLFi3m2XbhwQXhctQYf35ayV7lXWRQ03fX/u+++a1A+s1+/fsJi5qZWecvs7GxGjx4tNMarlH6tjRs3BlCk7Ht+lDw+6ipO+Pr6Fvhz/yf27t3L+vXrsbCwwNzcXJHE29KlS1m1ahWNGzdWrOwi5PRBPnbsmFElg0qVKkXv3r1p3769wbmgsI+ZSJIaZAJMkozc0aNH+eqrr2jUqBFarZaIiAgWLFhgsMRflNq1azN06FA6d+5scMIX2QNMN1Cze/du/TaRA0V9+/ZlwoQJLFq0SN8D6/79+3z11Vf6FQAiqD3oWatWLaPo+ZVbZmYmHTp0yDfhWVCWLVtG3bp16du3L7169dLP2t2+fTvLly8XfrGsdGmx/Mox6SiRyH0bBiA9PT0Vi9WnTx+aN2/O1KlTadmypWJxlZTfgHa3bt0UGdCGnJI5K1euFBrD2J04cYKDBw/yzTffkJiYiJubGw4ODsIGVOzs7ABwcnIS8vyvo+sdtGPHDkXj6mzYsIG+ffsqMjN737597N27l3v37tGnTx/99sTEROrUqSMsbn7lwnW/i54Nr2YpTyUdOnSIQ4cO8fDhQyZOnKjfnpSUpMhKb7UGH9VYeVahQgWOHj1Kly5dgJxVHuXLlxcWb/z48cKe+z+hVpKxWbNmREREYG1trVhMtV6rq6sr69atMyirOW7cOHbu3Ck0rpLHx4oVKwJw8ODBPPckGzdufO19SkFRI/FWoUIFmjRpokpcY0p+AdSpU0fodYwkSf9Ho1Wy7oskSW+dbt26sWbNGv2J9969e4wZM0aRm7IZM2bku33JkiXCYyvpm2++Ydu2bfoB9LS0NIYOHcrkyZNV3rOCl5WVxdGjR7G0tKRNmzb88MMPnD17ljp16jBu3Djh/UGUtHTpUhwdHalXrx6pqan079+fhw8fkpmZibe3t5Akco8ePQgKCspTUiU7O5tevXoZNBmX/nev670leqA7JSWFNWvWcPbsWTQaDW3atGHMmDHCkzNXrlzh3LlzhIWFERcXxwcffECbNm30g2WFgbW19RuTp6IGtNUuV2esLl26xJQpU0hISMDJyYmxY8cKG/DNrwRiqVKlaNasGc7OzgU+i/pN/d0AgxUXIixcuJCDBw/Srl073NzcaNq0qbBYDx8+5MGDByxYsMBgUkDJkiWpX7++aj0apf9dREQEN27cYNWqVUyYMEG/vWTJktjY2AgfDF29enW+20Unb0aOHMmKFSsUHey9c+cOY8eOJTs7G8gpDb9mzRrq1q2r2D4MHDiQH3/8UZFY3bp1U6W8paOjI7dv36ZOnToGk6dE9sVS67U6ODgQGBj4t9sKAycnpzz3BfltEyEpKYn79+/TqFEj4bEAQkJC+PPPP/nkk08MPsOiryuWLl3K48eP6dq1q0FceY0sSVJBkCvAJMnIWVpaGsw6qV27ttB+JLmpkejSarX4+Phw//59pk2bxoMHD3jy5InQMmOTJ09m1KhR+sGqd99916AsYGEyb948bt26RXp6OtWrVyctLY2OHTty4cIF5syZw4oVK9TexQJz8uRJ3N3dAQgKCsLMzIyzZ89y9+5dZs6cKSQBZmJiku9An4mJiSIrou7du8eMGTOIiYnhxIkTXL9+nRMnTvDFF18Ij60GpVd06CxYsICsrCxmzpwJ5AyazJ8/X/gxs0mTJjRp0gQHBwdOnjzJ+vVYu0kCAABr2ElEQVTr2bt3b6HqAabrf7l27VrMzMxwcXFBq9Wyf/9+of0ofX19X1uuLjY2Vt7cF7CHDx+yZ88eDhw4gI2NDX379uXcuXMMHz6cgIAAITErVKjAtWvX9OVoDx48SIUKFTh06BARERHMnj27QOO9qb+bRqPh+PHjBRrvVbNnz2bq1KkEBATw1VdfUaRIEdzc3OjZs2eB95erVq0a1apVM5jkkZ6ezosXLwpt8stYzrfW1tZYW1tjY2NDlSpVFI+v1iolpVeeZWdn8+DBAw4ePEhkZCRarZa6desq/v1JSkpSLJZa5S11125KUuu1Zmdn8/LlS/19bXJystCymjpKHh9/+eUXzpw5w5MnT/R97UC5z3JoaCienp6Ymppy4sQJrl69yvfff8+6deuExYyJiWHbtm0EBAQY9OISfV1x9epVwHBle2HvARYXF8eSJUt49OgRO3fuJCIigt9++w1XV1e1d02SCh2ZAJMkI9euXTvWrl1Lnz590Gq1+Pn58cknnyhSDiolJYX169cTHR3N8uXLuXPnDpGRkULLLy5ZsoS4uDiuX7/OtGnTsLCwYPHixUJn5UFOHXxdKYEtW7bw2WefCY2nlosXLxISEkJKSgrt2rXj3LlzmJub4+LiIqzJtlrMzc31Safw8HB69OiBmZkZ9evXF3bzl56eTkpKSp7vZXJyMunp6UJi5jZ37lzGjBnD8uXLAWjQoAFffvlloRuQ01FrAPLq1asEBwfrf//ggw8U+f7Mnz+fsLAw0tLSaN26NZMmTVKkh5IaTp06ZVAKd/jw4bi6ugrvB/ZqubrY2FgGDRokNKaxGT16NLdu3aJ///74+flRtmxZOnbsyMmTJzl48KCwuBEREezYsUM/mO3i4sKYMWNYt24djo6OBR5P7VLHkHON6OLiQvny5Vm8eDEbNmzgu+++w8PDg+7duxd4vMmTJzN//nzMzMxwcHAgPj6eUaNGMXz48AKPlVtERARz5swhIiLC4FwrcnKAsZ1v+/btq2jvPh21Bh+VLntlYmLC2rVr6dChg/BVHG+iZHk+tcpbqtEXS63X2rNnTz777DP992X37t2KXK8qeXw0MzPDwsICjUZjMIG1YsWKb5yIUlBWrlyJj4+PvtTi+++/n28/zIK0Y8cOjh49qi//qBS1Sjqrafbs2dja2rJr1y4A6tati7u7u0yASZIAMgEmSUZOV/rj1Z42S5cuFd7fYO7cuVSoUEE/I79y5cpMnTpVaAIsPDycgIAA/cqOsmXLkpaWJixefoKDgwttAkyXFCpRogQ1a9bU34SZmJgIXV2hhqysLJKSkihevDgXL15k2LBh+sdEJaO6d+/O9OnTWbx4sX6WZ2JiIp6ennTt2lVIzNwSExOxtbXVr+QrjO9rbmoOQOaeUZtf36qC9Ndff1G1alXq16/PsGHDqFGjhv6x69evK34DrITnz59z//59fa/CqKgonj9/LixeTEwMS5YsMSj9+/TpUwYPHqzaSsPCysHBgS5duhisbNBVfBdZJvbp06cGx8MiRYrw6NEjzM3NhQ/6hoWFcefOHQYOHEhcXBwJCQnCB9efPn3Knj178PPz4/3338fb25sPP/yQ6OhoBg0aJCQBFhkZSalSpTh8+DCtWrVixowZ9OvXT3gCbO7cuUyaNIklS5awadMmdu7ciYWFhdCYxna+Vbp3n45ag49qrDxr3LgxV65cUaW3j86+ffsUi6VWb53ExEQ2btzIzZs3De4xt2/fLiymWq911KhRVKxYkRMnTqDVaunfv7+QCR+vUvL4+NFHH/HRRx/RpUsX6tWrJyTG36lQoYLB76KvKapWrarotX90dDQ1atR4bWlnNZP2osXExODq6srevXuBnPe2oEtmS5KUQybAJMnI6ZJParh16xZeXl6cOXMGAAsLC31delGKFi1qUCpOdLz8FObWi+np6dy5cwetVmvwM6B4olG0/v3707t3b0qVKkXlypVp3LgxAH/++SflypUTEnPcuHF4eHjQvn17ateuDeSsUrKzs1MkKWNqakpGRob+OxQTE1OoL9LVGoC0t7fHxcWFHj16oNFoCAkJwcHBQVi8cePG4e/vj4uLC3369DFYETt79mxF+hsobfLkyfTr10//vb1x4wYLFiwQFm/16tUMHz6c1atXM378eP3KLycnJ0aNGiUsrjHq1q1bnm1KlIj96KOPGDlyJA4ODmg0GoKCgmjRogXJyclCB6s2bNhAaGgosbGxDBw4kIyMDGbOnGmwwlEER0dHnJ2d2bVrF5UrV9Zvr1GjBs7OzkJiZmZmAnDhwgU6dOhA8eLFFTkHpaenY2Njg1arpWLFikyePJlBgwYJnf1vbOdbc3NzHB0dcXR01PfuW758ufDefWoNPqqx8uzixYvs3r2bWrVqGaxkEV0FA+DMmTN5EkKik4BqlbecOXMmVlZW3Lt3j4kTJ+Lr6yu8d5MarzUrK4tx48axbt06xSfyqHF8/OWXX6hSpQqlSpXC3d2dq1evMnv2bNq1ayc0roWFBU+fPjWoOiK6p3aTJk2YMmWKYr24Fi5cyPr16/M9pypRelFNRYoYDsknJCQU6rEiSVKTTIBJkkR8fDyXL19Go9HQtGlTxXqAvTqQnJaWJvyEX69ePYKCgtBqtTx48IANGzbQokULoTFfNW3aNEXjKSk1NVVfogEw+FmJAUglubm58f777/PkyRPatm2r325qaiqs/n+RIkVYtmwZ9+/f58aNG2i1Who1aqRfxSLagAEDGD9+PPHx8axatYqAgAAmT56sSGw1qDUAOXLkSKytrQkLC0Or1TJt2jRsbW2Fxct93NUNMOf3WGHSpUsXWrRoweXLl9FqtTRv3lxY4hpySsWtX7+ewYMHo9VqOXjwIM7OzoqUzzEWr5s5DHk/1yJ4enqyZ88ejhw5glarpV27dvTv3x8zMzOhqx4OHDiAr68vffv2BXJW04vsTbJz504gp9RkfgNTbm5uTJgwQUhsKysrPvvsM+7evcvUqVNJTU0VEudVuuO+paUlERERVKpUiYcPHwqNaWznW1Cnd59ag49qrDxTozcVwLJly7h69Sq3b9+mU6dOHD9+HBsbG2HxDh06RLdu3fTHqle5ubkJiw1w//59Vq1axfHjx+nZsyddunQRdq5X87WampqSmpqKVqtV/B5PjeOjn58fw4YN49y5czx79ozFixezcOFC4QmwadOmMWLECB48eMCgQYO4d+8ea9euFRrz2rVrgHK9uNavXw+8HaWdldalSxc8PT1JTk7Gz8+PXbt20bt3b7V3S5IKJZkAkyQjd/r0adzd3WnQoAEAf/zxB97e3gYD+qK0bNmSdevWkZ6eTnh4OFu3bsXOzk5oTA8PD77++mtiY2Pp168fdnZ2TJ8+XVi8/AbkKleurN9e2Jb0G9uFa35lZOrWrSs8bq1atRRLeuXm6OhI9erV+fnnn0lJScHLy4uWLVsqvh9KUXMA0tbWFltbW9LT03nx4oXQWLkHLl4dxChsievcypcvL/yco6M75k+fPp1JkybRsWNH7OzsCu25QA1vGmDMPYNZFDMzMwYNGqR4T7dixYrlmVAk8nu7YMECGjduzHvvvScsxuvoqgbUr1+fEiVKEBMTw9SpU4XH7dGjB/Hx8YwcORJXV1eys7OFJfl0jO18m1/vPsjpgSmyd59ag49qrDxTozcVQGhoKP7+/jg7OzN//nzGjRvHvHnzhMX7888/6datm34QX2m6Fb9mZmY8f/4cS0tLHj9+LCSW2q+1adOmjBs3jp49exqUhRWVKNFR4/ioK6scHh6Ovb09H3zwgSLJ8iZNmrB9+3YuXboEQPPmzSldurTQmGr14jp79izvv/++foVbQkIC169fF5owV9vnn39OUFAQCQkJhIaGMmjQIKFVPyTJmMkEmCQZuW+++YadO3diZWUFwJ07d3B3d1ckATZ58mQ2bdqEhYUF3t7e2NnZCZ8NX7JkSRYuXCg0Rm4jR45Eo9Gg1Wp59OiRvpdBUlISVapUMbqEUWHSu3fv1w4yajQa9u/fr/AeKaNly5aFehAuN7UGICdPnsz8+fMxMzPDwcGB+Ph4Ro0aJazPTVpamr5cae6fdY8VRhEREcyZM4eIiAiDnn2i+l7mPreVKFGC8+fPc/78eaDwl3dRitrn07i4OHbs2EF0dLTBirNXe6wWtMqVK3Px4kU0Gg3Z2dmsW7dOaHJq0aJFBAQEcPv2bRwdHenZsyeWlpbC4uVWrFgxgz6xlSpVolKlSkJjZmdnY2NjQ9myZbG1teX8+fOkpaUJ700FxnW+za93n47I3n1qDT6qsfJMjd5UkJMQKlKkCBqNhoyMDCpVqiQsIQTok9Pz5s3LU342ISFBWFyd2rVr8/z5c30561KlSuknmhY0tV+rLimTu+SuyJVCuSl9fCxWrBhr164lODiY3bt3o9VqycjIEBYvd//fIkWKGCSwU1JSKF68uLDYw4cPZ+DAgXTs2FHRiXBLly41KLtesmTJPNsKo169etGrVy+1d0OSCj2NtrDWtpEk6T/Sq1cvgoKC/nbbv93rSkPoiC6HsXDhQlq0aKHvTXL48GFu3LjBlClThMaVxNENXucWFRXF2rVryc7O5ueff1Zhr8R4U7IPlOkfYUwcHR0JCAjg8OHDnD17lhkzZtCvXz+Cg4OFxHvTKqjCmpzp378/EydOZMmSJWzatImdO3diYWEhSxJK/7UBAwZgZWVF06ZNDQbxRfdGiY2NZfr06Zw/fx6NRkPLli1ZtmyZsJ5JOg8ePMDf359Dhw5Rr149xowZQ/369YXGVDpxrdO7d298fX2FxsgdyxjPt8Y283/Tpk1ERUURFhbGmDFj2LVrF/b29gwZMkRYzC+++AIrKytCQkIMelOJLs0+ePBg1q9fj5eXF4mJiVSoUIFff/1V+ESxqVOnsnz5cv3vSUlJfPbZZ0JL0r7q4sWL+n6y+SV3C8rb8FqVoObxMTIykl27dvHhhx/SpUsXoqKiOHTokLA+rtbW1m98rSLPe0ePHmXXrl1ER0fj4uJC37599atyRXJwcCAwMNBgW2Ecl4Kc5PWb3l/Rk6ckyRjJFWCSZOTKlSuHn5+fvmG5v7+/0D4okDO7502+/PLLAo+pKw0RHx/P+fPn9TfUYWFhtGvXTngC7MqVK8yePVv/e9euXdmyZYvQmJJYuWfiPX36lO+//55jx47x2WefCf88KU1XJvTkyZPcvXuXPn36ADn18Bs2bKjmrgmh9gCkbvXIhQsX6NChA8WLFxdaGkntlTNqSE9Px8bGBq1WS8WKFZk8eTKDBg2SCTDpv5aQkMCCBQsUj1uhQgW2bNlCSkoK2dnZBmWoRKpevTpDhw7lnXfeYeXKlbRt21Z4Amzu3LlMmjQpT+JaNCsrKx48eED16tWFxzK2862O0jP/1R58VGPlmZK9qXJbsWIFpqamTJ8+na1bt5KYmKjI4O4777zD0qVL+fLLL0lJSWH06NHY29sLj5ubUiuU1HytiYmJREZGGqwq/PDDD4XEUvP4WKdOHWbNmsWzZ88AqFmzprDkF+RM+ABYu3YtZmZmuLi4oNVq2b9/f56yxwWtS5cudOnShbt377Jr1y569uxJ27ZtGTx4MI0bNxYW18LCgsuXL9O0aVMALl++TIkSJYTFU9PHH38M5IwRXblyRb8C7MCBA6qVq5Wkwk4mwCTJyM2fP59p06YxZ84cNBoNDRo0wNvbW2hM3YVMVFQUFy5c4JNPPgHg2LFjwhrJLlmyBIBx48YRGBhIjRo1AIiOjmbFihVCYuaWkpLCxYsX9TdCFy9eNChtIP07JSUlsWHDBnx9fenXrx+HDh1SpCyS0nQX4qtWrWL79u36QaOPP/6YoUOHMn78eDV3r8CpPQBpZWXFsGHDiIyMZOrUqaSmpgqPaWx0M7EtLS2JiIigUqVKPHz4UOW9kv7N3nvvPWJiYoSX5MtPVFQUUVFRZGVl6beJKkGl1Wo5ffo0fn5+3Lp1i27durFv3z79dZVIaiWunz17Rq9evWjRooXBYJyIQXxjO9/qaLVag4SUiYmJwee5oL0Ng49Kl71SsjdVbu+8847+57FjxwqPp+Ph4cHEiRPZunUrp0+fpkOHDkJ7NLZu3TrfpKrusx0WFiYsttKvVefgwYN4eXmRkJBAxYoViYqKwtraWljiWs3j4+XLl5k0aRLZ2dmEhoZy9epV9u3bJ3ziy6lTpwxKTA4fPhxXV1cGDx4sNG5uZmZmFC1alOnTp9O+fXs8PDyExHF3d2fcuHH6vri3b99m9erVQmKpTVcdIDAwkJ07d1KsWDEAXFxcGDNmjJq7JkmFlkyASZKRq1mzJvv27SM5ORmtVqvI4L3u4nTEiBEGja7HjBkj7IJK5+HDhwaDNDVq1CAyMlJoTIA5c+YwZcoUfb3utLQ0g1IV0r/Ppk2b2LZtG127diU4OFj4ysm3QUxMDGlpafqL9PT0dJ48eaLyXhU8tW6w//rrL6pWrYqXlxdnzpyhfv36lChRgpiYGLp27SokprHq3r078fHxjBw5EldXV7Kzs/W9NCTpv5GQkECvXr1o3rw5RYsW1W8XvdJh+fLl7N+/HysrK/1KUZE9WGxtbalQoQLOzs6MGzcOjUZDWloat2/fBtAPXImgVuK6R48e9OjRQ9/TVQnGcr7VUXrmv1qDj2quPFOyN1Vud+/eZd26dURFRRn0RxS1mj73BMN58+YxYsQIWrVqxcCBA4X2TlKqTGpuar1WnXXr1uHn58fw4cMJCAjgl19+4ejRo0JjgjrHxyVLlrBx40Z9ydD3339f+LgFwPPnz7l//z61atUCcia8PH/+XGjMo0eP8uOPPxIXF8eAAQMICQnBwsKCzMxMunTpIuR1Z2dnU7x4cUJCQvj999/RarU0b95csR6jann8+LFB/z4zMzMePXqk4h5JUuElE2CSZOS0Wi0+Pj7cv3+fadOm8eDBA548ecIHH3wgPPajR48M6kmXLVtW+EBGmTJl+P777+nbty+Qc7NSpkwZoTEhpwTGsWPHiIyMRKvVUrdu3TzNiqV/l2XLllGhQgV+++23fGefF8Y+Hd26dcPFxYXu3bsDcOjQoUKdmFH6BnvcuHH4+/tTrFgx1q1bp/8MVapUiaNHj8oZgQVo2LBhQM5g/vnz50lLSyuUqzcl5fTs2ZOePXsqHvfw4cMcO3ZMsc+vbvXIli1b2Lp1q0FCSHTPQDUS1xcvXiQwMJCIiAg0Gg3169dn/PjxwkubGdv5NvfMf61Wy507dxSZ+a/04KOaK8+WLVsG5JR5Tk5OxtTUVGgJN52JEyfi4OCAk5OT0D5YOs2bN9cnq3X/vnbtGps3b0aj0QjrnVStWjX9z0lJSdy/f59GjRoJiaWj1mvVKVKkCOXLl9ev1mzbti2rVq0SGhPUOT5mZGTkmeAhuhQhwOTJk+nXrx+NGzdGq9Vy8+ZN5s+fLzSmj48PI0aMoH379gbbixQpYtDSoSCZmJgwa9YsfH19hU3geRt99NFHjBgxwmBShiyBKEliyASYJBm5JUuWEBcXx/Xr15k2bRoWFhYsXrxYkcH7unXrMmvWLIPyYnXr1hUa08vLi0WLFunrordu3RovLy+hMXWioqK4ePEikHPBbGVlpUhcSYwtW7aQnp6eZ4byy5cvC21yc/LkyTRt2pTz58+j1WqZNGkSHTt2VHu3hFH6Bjv3QHLuWdKvPib973STP+7du4e7uzsxMTHcunVLkckfUuGkG7xQWoUKFRRN3qrZM1DpxPWxY8dYsGABo0eP1pfG/e2335g2bRqzZ8+mc+fOwmIb2/m2efPmqsz8V3rwUY2VZ9OmTePzzz/H2tqa58+f4+DgQMmSJYmPj+edd97RTwoUpUiRInz++edCY+Sm652k8+LFC86fP0+NGjWwtrYWHj80NBRPT09MTU05ceIEV69e5fvvv2fdunUFHkvt12pubo5Wq6VWrVrs2LGDatWqER8fLzyuksfHmTNnsnjxYszNzUlOTtav4Lx9+7bBam9RunTpQsuWLQ2OjaL7Ym3YsOG1j9nZ2QmLq2S/zbfFV199xd69ezly5AharZaOHTvi4uKi9m5JUqGk0coRFUkyag4ODgQEBODk5ERAQAAA9vb2BAcHC4+dlJTE999/T3h4OFqtltatWzNu3LhCOQs/ICCAZcuW6S/OT506xbRp0xSt/S8VLC8vL+rWrZtn4GD79u08fvyYL7/8UqU9U0Z6ejqHDx/Gz8+Pbdu2qb07wpw4cUJ/g21jYyN0ANLJyUnfNyH3z/n9Lv1vFi9erJ/8cfjwYeLj4xkxYkShXLkpifXDDz8wZMgQli5dmu/jos4FoaGhAISHh/P48WO6du1qMBhXmGZQ68orvo6osovOzs54eXnx3nvvGWy/desW06dPV+yYbCzn2/j4eC5fvoxGo6FJkyYGVSJEycjIYO/evfp7ERsbG1xcXChSROw84a5du3Lw4EF92dKsrCx69OjB4cOHCzxW9+7dOXjwIJBzvAoNDWXLli08fvyYUaNGERgYWOAxc1uxYgUtW7bE1tZWaBydNyX8Jk+eLDzh17t3b9atW8eIESP099a534OCpPZrDQsLo3HjxsTFxTF37lwSExOZOnUqbdq0ERo3N9HHR931d2hoKGvXriUqKgpbW1tOnz7N0qVLadu2bYHHfJ3ff/8dHx8fjhw5woULF4TFuXv3LmvXriU6OlqRsqU6n3/+OZcuXVKk3+bb6tdff8XPz49FixapvSuSVOjIFWCSZOSKFi1qUIs+OztbsdglS5bUz6iFnJKI27dvF9IgeefOnW983M3NrcBj5rZlyxb8/f2pUKECALGxsQwfPlwmwP7FdEnMV7m5ueHg4FBoE2BXr17F19eXQ4cO8f777+Po6Kj2LgllZ2eHnZ2d/gZ76NChwgYg09LSuHPnDlqt1uBn3WNSwQkPD9dP/oCcErzybyz9N3RJJ9Ezsl+1adMmg9937Nih/1lkDzA15FdmWEdk2cXU1NQ8yS+AevXqKXK8MKbz7enTp3F3d6dhw4ZotVr++OMPvL29hQ8um5mZMXDgQAYOHAjkDD7OmTNH+OCjkivPcifGf/31V/3KxcqVK7+xH1lBsbGxYezYsZiYmOhXDGk0GsLCwoTEu379un71U2BgIFZWVgYJP9FJIUB/v6cjqjKE2q/VxsYGgFKlSimenFf6+NihQwfq1q3L6dOnARg7diw1a9YUGhMgLi6OgIAAfHx8ePDgAV988YXwpPWUKVPo2rUrzs7OipQt1dH12zQ2sbGxBAQE4Ofnh0ajUaWctiQZA5kAkyQjV69ePYKCgtBqtTx48IANGzbQokULxeJnZGTw008/4evry7Vr14SVk7l27RqQM7v0/Pnz+gv2sLAw2rVrJzwBBoY3Q6/eGEn/PiYmJvneFJiamioyoKCk+Ph4AgMD8fX1JSMjA0dHR4oXL55nALYwUvIGOzU1lREjRuh/z/1zYftMqU3NyR9S4dK/f38Axo8fr2jc3Amvwk6tsosZGRlkZGTk6fOSnp5Oenq6kJjGer795ptv2Llzp748+J07d3B3d1dkdYUag49Kl72KiYnB0tKS8+fPG/TNUyKR6+npyZIlS2jUqJF+xZtIurKSoE7Cz8LCgqdPn+pjhYeHU6pUKSGx1H6tCxcuZPz48fp+2vHx8axZs4ZZs2YJiafG8fHWrVv6cQP4v5Lkul5nohK5x48fx9fXl19//ZVPP/2UhQsX4u7u/sYJIQUlOzub0aNHC4/zKrVKSashKyuLn3/+GR8fH37//Xc++eQTkpKS9AlWSZIKnkyASZKR8/Dw4OuvvyY2NpZ+/fphZ2dnsCpLlJs3b+Lj48PBgwdp0KABERERnD59WtgMuSVLlgAwbtw4AgMDqVGjBgDR0dGsWLFCSMzcatasycqVK3FxcUGj0bBv3z79Pkj/Tunp6aSkpFC8eHGD7cnJycIGxtTSvn17WrZsybx58/Q9kvbv36/yXomj1gCkmr11jI3akz+kwictLY2goKA8JYNErwZ2dXVl9+7df7utsLh16xbnz59Ho9HQqlUrYeUPATp16sT06dOZN2+efgA7ISGBuXPn0qlTJyExje18q5OZmWnQG9fKyipPL8yCpPbgo5Irz0aOHImjoyNmZma0aNFC/535/fffqVq1aoHHe5WlpaXQ/qn5UTPhN23aNEaMGMGDBw8YNGgQ9+7dY+3atcLiqflaL168qE9+Qc5qepGl+dQ4PtauXfuNPbFEGTduHDY2Nhw6dIhy5coByk2Ga9asGREREYr0kcstMzMTX19fbt68afD51Y3jFCbt27enZs2auLm58d1331G0aFFh1xWSJOWQCTBJMnIlS5Zk4cKFisZ0cnLi5cuX+pralStXxs7OTljyK7eHDx8aJJ5q1KhBZGSk8Ljz5s1j4cKF+pKHbdu2Zf78+cLjSuJ0796d6dOns3jxYn3fusTERDw9PRW/0Rdt8ODBBAcHs2LFCnr37s2nn36q9i4JZawDkMYkv8kfHh4eau+W9C82ceJEMjIyaNKkiSLXMzqpqakGv2dlZfHixQvF4itp586drFu3jo4dO6LValm/fj2jR49mwIABQuJNmTKFuXPn0qFDB2rVqgXA/fv36dq1K1OnThUS09jOtzrlypXDz88PZ2dnAPz9/fWDviK8DYOPSq0869atGy1btuTp06cGA9pVqlRhwYIFQmLm1rlzZ3bv3k23bt0MyjG+OoGsoKid8GvSpAnbt2/n0qVLADRv3pzSpUsLiaX2a83KysqzTWTiWo3jo7m5OdWqVRMe51Xr16/H19eXbt26YWdnp0gJ3D59+gA576Gfnx916tQx+M6K7gHm6elJVlYW4eHhuLq6cuDAAVq2bCk0plo+/PBDzp07x5kzZ6hUqZKwEriSJP0fjVa3hleSJKMVFhZGVFSUwQWryJKAffr04dmzZzg6OuLs7Ez16tXp1KmTsB4OuQ0dOpQPP/xQXxPd19eX8PDwQt1UXBIjMzMTDw8Pjh8/Tu3atQG4d+8ednZ2eHl5CW+grrSsrCxCQ0Px9fXl/PnzZGVlsWbNGlq3bq32rhW4pUuXEhwcTK1atfQ32Pb29oocoySxXp2ZrLsM1s2q/fDDDxXfJ6lw6NatG4cOHVIs3qZNm9i0aRNJSUkG5bVSU1Oxt7cvlJNsPv30U3bt2kX58uUBePbsGa6urhw5ckRo3L/++otbt26h1WqpV6+e8MFQYzrf6kRFRTFt2jRu3ryJRqOhQYMGeHt7C+uxM3HiRM6dO0fHjh3p3bs3H330kSL3IvmtPDt58mShLnuV3yoSjUbDzZs3hcWMjY3VJ/x05/eYmBiysrIUSQwpSc3XOnPmTEqUKMGIESPQarVs2rSJ5ORkoSt2lD4+9uvXj3379gl57v/E8+fPCQwMxM/Pjzt37jBixAjs7e2pW7dugcfq1KnTG9870Ukae3t7goOD9f9OTExk0qRJbN68WWhctbx48YKgoCD8/Px48eIFSUlJ+Pr6yipBkiSITIBJkpHz8PDg2rVrNGzY0KCfkeil5rdv38bHx4fg4GDq1q3L7du3OXHihLDZgDoxMTEsWrSI8PBwAFq3bs3MmTOpVKmS0LharZa9e/dy9uxZNBoNbdu2pW/fvrKvTyFw//59bty4gVarpVGjRvpZ4oXZs2fP8Pf3x9/fn4SEBE6dOqX2LhU4YxyANAa9e/fW/3z37l19yS2tVotGoxE+u1UqvEaOHMmKFSv0K4JFS0xM5MWLFyxYsABPT0/99pIlS2JpaanIPiht4MCB/Pjjjwbb3Nzc2Llzp0p7JJ4xnG9zS05ORqvVKvI9UmPwsU2bNvqVZ126dNGvPJMTbP79cveJyk13fSGqV5SakpKSWLRoESdPngTg448/ZsaMGcJ6nr3K2I6P165dw9fXl4MHD+rHMgqSo6MjAQEBBf68/6k+ffrg4+ODo6Mju3fvpnjx4vpkWGF348YNfHx8CAkJoXbt2uzdu1ftXZKkQkcmwCTJyH366accOHAgT4NvpWRmZupnQv7666/Y2toq0pNLaV5eXty8eVNf2iUgIABra2vhvUEkSZR79+5Ru3Ztrly5QpMmTdTeHaGM7QbbWKh9oy8VLlOnTuXatWu0b9/eoASiEuf5zMxMIiMj0Wg01K5du9CtQL59+zYAQUFBxMXF6cs0+fv7U6VKFcaMGaPm7glnLOfbqKgooqKiDMqqdejQQZHYSg0+qrXyTG3x8fFcvnwZjUZD06ZNDfpGFRadOnWiTJkyODs7Y2tri4mJicHjapTRMwbGcnwEOHDgAD179iQ9PV1IqWVdewq1DB8+nBUrVrBp0yZ+++03ypYtS1JSElu3blVtn5T08uVLihQpwrFjx+jevbvauyNJhY5MgEmSkRsyZAibNm1SLQGW25MnTwgMDGTEiBFC49y9e5eIiAjS09P120TX1ba3t8ff318/KJWRkYGzs7NRzGiSCie1b5KUZkw32MbC2D7DklirV6/Od/v48eOFxr127RpffPEF5ubmaLVaMjMzWbVqFY0aNRIaV0l2dnavfUyj0RT65IExHKuWLl1KQEAAderU0ScONBoN27dvV2wflBp8NLayV6dPn8bd3Z0GDRoA8Mcff+Dt7U3btm1V3rOCFx4ejr+/P7/99hudOnXC2dlZ35ersJsyZYoqk1iN4fioI/q1NmrUKN9+dUqtYszKysLU1JTs7Gx9CURHR0fFVtarzZg+y5KkhsI1PVCSpH+sdu3aDB06lM6dOxvMJBLZAyw/urI2opNf27dvZ+/evcTGxvL+++9z8eJFPvzwQ0Uay+YudyhLH0r/dsY2f2by5Mn4+/vL5JckSfkSneh6nYULF7J48WJ9+a1z586xYMEC9uzZo8r+iHDixAm1d0FVxnC+PXbsGMePHxdeCv1N3Nzc8Pf3Fz7z3tLSkkGDBjFo0CD9yrM+ffoU2rJX33zzDTt37tSXHL5z5w7u7u6FMgHWqlUrWrVqxcuXLwkJCWHQoEF88cUXDBgwQO1dEy4yMlKVuMZwfNQR/Vpr167Nhg0bhMZ4kxcvXlCyZEnMzc1xcHAgPT2dpKQk1fZHacb0WZYkNcgEmCQZufT0dGrWrMmtW7dU3Q+lLm727dvH/v37cXV1ZfPmzdy6dYv169cLj9uuXTtGjBiBk5MTGo0Gf39/2rVrJzyuJInywQcfqL0LipI3JYWDrpQaQFpaGnfu3DF4b41lprZU8OLi4liyZAmPHj1i586dRERE8Ntvv+Hq6io0bkpKikHvmdatW5OSkiI0pppu375t0MdVN6hemBnD+bZKlSqqV6NQ4zzfsGFDpk2bhoeHB8eOHVM8vhIyMzMNvqdWVlZkZmaquEdi3blzB39/f3766SdsbW1p1aqV2rukCLWuk43h+KgzePBgoc9vbm6uaqnOUaNGGaz6zczMZPTo0ezbt0+1fVJS9erV1d4FSSrUZAJMkozckiVL1N4FACF1rF8Xp0SJEmRnZ6PVaqlXrx5RUVHC47q7u7Nnzx5++ukntFotnTt3xsXFRXhcSSpIgYGBODg4AODp6ZlnW2FmTDfYhdnIkSMNfs+96tgYSqlJ4syePRtbW1t27doFQN26dXF3dxeeACtevDjnzp2jdevWAJw/f17VVTQiBQQEsGzZMjp27AjA+vXrmTZtGr169VJ3xwTYsGEDffv2pWzZsvrzbWHm4eHB6NGjadu2rWoVKdQafFRq5ZlaypUrh5+fn74Psr+/P+XKlVN5rwrerl27CAwMxNzcHCcnJwICAgrtsTg/27ZtUyVuYT8+Dh8+nIEDB9KxY0f9d0gUtSchpKenG3xnSpQoQVpamop7pKzXldKWJKlgyASYJEl6Stfu/v3332nWrBmAYjN7ihcvTkZGBtbW1nh7e1OlShVSU1OFxzUxMWHAgAFGUQJDKry2bduWJ9mV37bCqLDfYBsLYy+lJokTExODq6urvoSZubm5vpeRSDNnzmTixIn6pEFGRgYrV64UHlcNW7Zswd/fnwoVKgAQGxvL8OHDC2UC7MmTJ/To0YN27doxcODAQl9+d8OGDcTGxnLz5k1MTU0VixsWFqZfQakbfMy9TQmFfYX5/PnzmTZtGnPnzgWgQYMGeHt7q7tTAsyfP5+GDRtSqVIlQkNDCQ0NNXj8u+++U2nPxElJSWHdunU8ePCA5cuXc+fOHSIjI+ncubPQuHfv3mXt2rVER0cbrCb08fERGlcNLi4u/PDDDyxcuBAXFxf9xAgR3oaVVs+ePdMnyOPi4sjOzlZ5j8T6+uuvGTduHMWLF2fw4MHcuHGDefPmGcW9tSQpTSbAJEnSU7p295w5czA1NWXAgAHY29tTtGhRRWJmZGTg4eHBihUrePDgAUuXLhUW7++e+8svvxQWW5IKytWrV7ly5Qrx8fHs3LlTvz0pKYmMjAwV90yslJQU1qxZw9mzZ9FoNLRp04YxY8YY1YxeSZL+M0WKGN5WJSQkKDKw3aRJE44ePUpkZCRarZa6deuqPotbJF3y69WfC5vZs2czdepUAgICmD17NkWKFMHNzY2ePXsqcr2stOvXr3PkyBHFe+QuXboUf39/g23e3t74+fkptg+FvexVzZo12bdvH8nJyWi1WkqWLKn2LgnxtlRVUdLcuXOpUKECERERAFSuXJmpU6cKT4BNmTKFrl274uzsrGjCXA1dunShS5cu3L17l127dtGzZ0/atm3L4MGDady4sdq7V6AGDRqEq6urPvkTGBiYp3JDYXP27Fk8PDw4efIklSpV4ptvvmHkyJEyASZJAsgEmCRJekrPQAwMDOTixYvs2rWLb7/9Fnt7ewYMGECNGjWExaxXrx6Qs6R+0aJFwuLolChRQngMSRItJiaGa9eukZKSwrVr1/TbLSwsCvUN/4IFC8jKymLmzJlAzszS+fPnF+rXLEnSf6dLly54enqSnJyMn58fu3btonfv3sLjRkZGUrVqVerVq8fp06cJDQ3FxcUFS0tL4bGVVrNmTVauXImLiwsajYZ9+/YJvWZUW/HixXFxcaF8+fIsXryYDRs28N133+Hh4VHoyuXVrl2bly9fYmFhoUi8+/fvc+/ePZKSkgxW6iQmJirSQ+9tWHmmlICAAD7++GP9Men58+ecOnWq0K3cdHJyUnsXFHfr1i28vLw4c+YMkHNfoMSKnezsbEaPHi08ztvIzMyMokWLMn36dNq3b4+Hh4fau1Rg+vTpQ40aNQgNDUWr1bJw4UI+/PBDtXdLERcuXOCTTz6hUqVKik8EkSRjodEW9jX3kiT9x54/f06ZMmVUiX3z5k3GjBnDkydPsLW1xd3dvUAbm6u1EiszM5OffvoJS0tL2rRpww8//MDZs2epU6cO48aNo1SpUkLiSpIIZ86coV27dmrvhmLs7e0JDg7W/67VaunVq5fBNkmSJJ2goCBOnDiBVqvFzs5OkRm8Dg4O+Pj48PjxY4YMGULbtm2JjY1l3bp1wmMrLS4ujoULFxqsyp01axbly5dXe9cK3NOnT9mzZw9+fn68//77DBw4kA8//JDo6GgGDRrEyZMn1d7FAjVlyhSuX79O+/btDXqAibo+9/f3x8/Pj2vXrhmsoihZsiQuLi76PnOiODk55Vl55uzsrOjKM6X06tWLoKAgg22Ojo4EBASos0MKGjhwID/++KPauyFMv3792Ldvn/79TEtLo0+fPsKvkz09PRkwYADW1tZC47wNjh49yo8//khcXBwDBgzA0dERCwsLMjMz6dKlS6Et7X3v3j1q166t9m4IN2zYMKpVq8Yvv/xCQEAAFhYWODk5yXtNSRJArgCTJCP1al3yV3Xo0EGR/bh48SI7d+7k8uXL9OnTh759+3Lu3DnGjh3LkSNHCiyOWiux5s+fz61bt0hPT6d69eqkpaXRsWNHLly4wJw5cxTtuSZJ/6sbN27QuHFjfaI8Pj4eX19fPv/8c3V3TKCXL1/qjx9KzAqXJOnfq1evXoqvajAxMcHMzIzQ0FBcXV0ZMWJEoSydk5WVxc6dO/nmm2/U3hVFODo64uzszK5du6hcubJ+e40aNXB2dlZxz8SoW7cudevWVSyek5MTTk5O+Pn5Kfr3VHvl2dsiKytL7V1QRFJSktq7IFTLli1Zt24d6enphIeHs3XrVuzs7ITF6927NxqNhszMTPz8/KhTp45BSdjC2APMx8eHESNG0L59e4PtRYoUYfbs2SrtlXiTJ0/OM0mgMFq+fDlBQUH06dMHS0tLHjx4wLBhw9TeLUkqlGQCTJKM1KZNm177mEajUSQBZm9vj4WFBQMHDsTb21vfP8PBwSHPTMH/1ejRo9+4EkuUixcvEhISQkpKCu3atePcuXOYm5vj4uJS6Ep/SIVfSEiIQS32smXLcuDAgUKbALO3t8fFxYUePXqg0WgICQkplAPLkiT999Tu9ZmWlkZMTAwnTpxg8uTJgPIlrZVgamrKhQsX1N4NRWRlZTFu3DhcXV3zfXzChAkK75F448ePVyVujRo1SE5OxsLCgv3793P16lVGjBghrLTmpUuX8PPz4+nTpwb3YiVLlmT69OlCYqqtQoUKHD16lC5dugBw5MiRQrlqMz+5VzMWRpMnT2bTpk1YWFjg7e2NnZ2d0J5NhfU78iYbNmx47WMik41qK4zXMfkpV64cQ4cO1f9evXr1Qt8XUpLUIksgSpKkiuzsbK5fv87777+vSDxPT8/XrsQChK3Eyl3i49VyH/mVP5Gkt1l+ZWxeLRNY2Jw6dYqwsDC0Wi1t2rTB1tZW7V2SJOktYm1tTePGjWnfvj2mpqZ5Hhc9sL937168vb2xsbFh1apVREdH4+Hhwc6dO4XGVcPmzZuBnOup3Cv7ixcvrtYuCePm5lYo38PXSUlJYc2aNfrylm3btmX06NHC31t7e3uCgoK4ffs2EydOpFevXpw9e5bt27cLjav0yjM13blzh7Fjx+p7Q5mamrJmzRpFV/xJ0r/V3bt3Wbt2LdHR0WRmZuq3F8bVbrnNnz8fT09PtXdDuNatW+fb8yssLEyFvZGkwk2uAJMkicTERCIjI0lLS9NvE91w1MTEhLlz5+Lr6ys0jo5aK7HS09O5c+cOWq3W4GfA4O8tSf8GtWvXZuvWrQwdOhStVsu2bduoWbOm2rsllK2tLba2tqSnp/PixQu1d0eSpLfMtm3bCAgIICQkhM6dO+Ps7My7776rWHwXFxdcXFz0v1etWpWtW7cqFl9J3t7e+n9rNBq0Wi0ajYabN2+qvGcFz8bGhsOHD9O1a1e1d0URCxYsICsri5kzZwI5g7vz589nyZIlQuMWKVIEjUbDqVOncHV1ZdCgQRw+fFhoTFB+5ZlasrOzefDgAQcPHiQyMhKtVkvdunXznSxQWKSlpREUFJQnYSF6NbAa1Hqtrq6urFu3DktLSyCnj/m4ceMK5aSBKVOm0LVrV5ydnQv19+ZVxpD8AgzGwtLS0ggODtZXRZIkqWDJb5YkGbmDBw/i5eVFQkICFStWJCoqCmtra0VWJllZWfHgwQNFlnmbm5uj0WgoUaIENWvW1Jek0PXOECU1NZURI0bof8/9c36zfSTpbTZr1izc3d1ZsWIFGo2G5s2b/235r3+zyZMnM3/+fMzMzHBwcCA+Pp5Ro0YxfPhwtXdNkqS3ROvWrWndujUvX77k8OHDzJ8/n7S0NNzd3WnZsqXw+CkpKaxfv57o6GiWL1/OvXv3iIyMpHPnzsJjKy0iIkLtXVDMjz/+yPPnzylWrBjFixfXJ/sK66zwq1evGqwm/+CDDxQpFZ6Zmcmvv/7KkSNHWLRoEaBMf6r58+cTFBTEn3/+ydatW+nVqxezZs0SvvJMaSYmJqxdu5YOHTooOjFATRMnTiQjI4MmTZoU+hKIar3Wly9f6pNfAGXKlCm0/days7MZPXq02rsh1IQJE944LvLdd98puDfKqlatmsHvEydOZPDgwUJbdEiSsZIJMEkycuvWrcPPz4/hw4cTEBDAL7/8wtGjRxWJ/ezZM3r16kWLFi0MStmIuMhRayXWiRMnhD23JCmtUqVKbN++nZcvXwIYfG8Lo8jISEqVKsXhw4dp1aoVM2bMoF+/fjIBJklSHiVKlKBZs2ZERkZy4MABYmNjFYk7d+5cKlSooE8OVa5cmalTpxbKBFhKSkq+2wtjCUSlKiS8TV6+fKm/rnjde13QJk6cyPz582ndujXvvfcekZGR1KpVS3hctVaeqaFx48ZcuXKFJk2aqL0rirh//z6HDh1SezcUodZrzc7ONjheJCcnK5K4VkOzZs2IiIjA2tpa7V0R5uOPP1Z7F94a0dHRPHz4UO3dkKRCSSbAJMnIFSlShPLly+svGtu2bcuqVasUid2jRw969OihSCy5EkuS/ndarRYfHx/u37/PtGnTePDgAU+ePOGDDz5Qe9eE0JVzuXDhAh06dKB48eKYmJiovFeSJL1NEhISCAkJITAwEDMzM5ycnAgJCVFsgsCtW7fw8vLizJkzAFhYWOh77RQ2zZs3Nyh9qFMYSyC+Oiu8sLO3t8fFxYUePXqg0WgICQnBwcFBeNzOnTsbJIvr1KnD6tWrhcdVa+WZGi5evMju3bupVauWwXGxsPYwqlGjBklJSZQsWVLtXRFOrdfas2dPPvvsM1xdXQHYvXu3IitGldSnTx8g51jh5+dHnTp1KFq0qP7xwvT9cXJyUnsXVJO7B1h2djaZmZnMmjVL5b2SpMJJJsAkyciZm5uj1WqpVasWO3bsoFq1asTHxysSW8mLHbkSS5L+d0uWLCEuLo7r168zbdo0LCwsWLx4caG6CcvNysqKYcOGERkZydSpU0lNTVV7lyRJesu0a9eOd999F2dnZ33/ngsXLugf79Chg9D4r5ZxTktL069wL2xyl0DU9cpQ6ppVaY8ePcLb25uIiAiDSgXHjx9Xca/EGTlyJNbW1oSFhaHVapk2bRq2trbC46akpLBmzRrOnj2LRqOhTZs2jBkzRviqQrVWnqlB19fNWJQqVYrevXvTvn17g7KAhbEHmFqvddSoUVSsWJETJ06g1Wrp378/jo6OQmMqLT4+XngPxLfF35XTL4zfHZ3cq72LFCnCO++8Y1S93iRJSTIBJklGbuLEiSQlJTFt2jTmzp1LYmIic+bMUSR2ZmYmvr6+3Lx50+Dm3lgu9iTp3yY8PJyAgAB98rps2bJCS4iq5a+//qJq1ar6VRX169enRIkSxMTE0LVrV7V3T5Kkt0jTpk0BOHLkSJ7HNBqN8ARYy5YtWbduHenp6YSHh7N161bs7OyExnwbFC1alD59+jBw4ECDVf2FxcyZM+nevTs3b95k2bJl7N69m5o1a6q9W0JkZWXRr18/fH19FUl65bZgwQKysrL0SRofHx/mz58v/F5ErZVnavjoo4/U3gVF1alThzp16qi9G4pQ87U6OTkV6pVDpUqVMprvTmEvqf86WVlZTJgwwShLHkuSGmQCTJKMnI2NDZBzkbVt2zZFY3t6epKVlUV4eDiurq4cOHBAkYbxkiT9d4oWLWpQdqqwltkaN24c/v7+FCtWjHXr1ulXuFWqVImjR48yZswYlfdQkqS3xY4dO1SNP3nyZDZt2oSFhQXe3t7Y2dkxcuRIVfdJlNx9obKzs7l69SpPnjxRcY/EiY+Pp2/fvmzfvp3mzZvTtGlThg4dqvZuCWFqaqqfUJO7xJcSrl69SnBwsP73Dz74QJFSamqtPFNDYmIiGzduzDPhcfv27SrulTjjx49XexcUo9ZrNYZJtMbUosGYvjO5qXnukyRjJBNgkmTk0tLSCAoKIjo6Wt/vBpRZaq676bS3t2fUqFEMGDCASZMmCY8rSdJ/p169egQFBaHVannw4AEbNmygRYsWau9WgctdPiz3cfHVxyRJkvKzZcsWPvvsM0VimZmZMWbMGKNIzOfuAWZqakrNmjULba8MXWnLEiVK8Ndff/HOO+/w/9q796gq63yP458HBFNQupFIQ2le0rykSYnXiqOOmAroEeMgaSfFTNTMC2ZlKubdpsmc0EzKyUteQFFjsuQM6oo0PTpp6SDmrUnRSEUUue7zh4t9JM0c5dkP7P1+rTVr9v49uL8fWCawv8/v+/vpp58sTmWeevXqKSoqSn/84x/L7QaIiooyvfalS5fsNa9usprJqp1nVpg4caIaNGigo0ePatSoUVq7dq2aNWtmdawKl5qaqpCQEC1btuy61x3xd9lRrP5cXeEm2szMTPuNylcrOwMzIyPDglTmysnJ0YwZM3Ty5EktW7ZMBw8e1J49e+xnvTkjK7/3Aa6GBhjg4kaNGqWioiK1bNmy3OxuRyi708Xd3V35+fmqVauW097JCziDCRMmaObMmTpz5owiIiL09NNPa8KECVbHqnBX33X56zswXemOTAC3ZsOGDaY3wH7rjccyzvjmydVngDm7wMBAnTt3TpGRkerTp488PT2degTvxYsX1ahRI/3www8OrdurVy/1799fzzzzjAzD0KZNmxQaGmp6Xat2nlnh2LFjmj9/vrZs2aKePXuqW7duTrlL9dChQwoJCdH+/futjmI6qz9XV7iJtl69elq0aJHVMRzq9ddfV+fOnbV8+XJJ0kMPPaRx48Y5dQPMqu99gCuiAQa4uGPHjik1NdWS2j4+Pjp//rw6deqkIUOG6K677tK9995rSRYAv8/b21vTpk0rt5aWluZ0580UFBTo8OHDstls5R6XXQOAG3HETtH4+Hg1b95cjRo1Mr1WZZKRkaHDhw9rwIABysnJUW5urlOetxMXFydJCgsL0xNPPKG8vDw1btzY4lTmsWrnU0xMjJo0aaKMjAzZbDaNHTvWYeeQWbHzzAplN1h6eHjo3Llz8vHx0alTpyxOVfFGjhwpSZoyZco1N5Xm5uZaEck0ZZ/ra6+9Jm9v73LX8vLyTK/vCjfRenp66v7777c6hkNlZ2crMjJSn376qaQrXwM3NzeLU5nLGXf9ApUVDTDAxQUEBCgvL++aH14dYdGiRXJ3d9fo0aOVkpKivLw8hYWFOTwHgN+XmpqqkydP6umnn1b9+vW1detWvfPOO8rPz3e6Btjly5c1ZMgQ+/OrH7MDDMDvGTt2rOk13nrrLa1bt05ZWVkKCwtTz5495ePjY3pdKy1atEjp6ek6c+aMBgwYoKKiIk2cOFErVqywOlqFmzhxovr27as2bdrI39/f6jgOkZGRoePHj5cbPWzmTsaSkhJFRERo7dq1Dmt6lbFq55kV6tWrp3Pnztk/51q1aqlp06ZWxzLNq6++qnnz5tmf5+XlafDgwVq1apWFqcwRHR2t5OTk312raK5wE23ZGFxXUq1a+benc3NznX70fH5+vhYuXKgTJ05o3rx5Onz4sI4cOaIuXbpYHQ1wOjTAABdXq1Yt9e3bV506dSp3t5ojzgBzd3eXJLm5udH4AiqxadOmaevWrWrWrJnWrl2rp556SmvWrNHIkSP17LPPWh2vwqWlpVkdAUAVc+TIEfn7+6t69eqy2WxatGiR+vfvb1pTqm/fvurbt69+/PFHJScnKzIyUo0bN9awYcP08MMPm1LTahs3btTatWvVr18/SZKfn59DdhtY4ZFHHtFbb72lixcvKiwsTOHh4fLz87M6lmni4uL03Xff6ZFHHrH/fmA2d3d33XXXXSooKLDvKHEUK3eeOdrcuXMlXfk36+LFi3J3d9fQoUMtTmWee++9V7Nnz9b48eOVn5+vF198Ub169bI6VoUqLi5WUVGRSktLdfnyZXuT4sKFCw7ZzegKN9E6Y8P093Tr1k2TJk3SxYsXlZSUpOXLl6tv375WxzLV5MmT5evrax/x7OfnpzFjxtAAA0xAAwxwcfXr13f46Jhx48Zpzpw56tu373V3U6xZs8aheQDc2Pbt25WcnCwvLy/l5OToqaeeUkpKilOOnQKAW/Hyyy9rzZo1OnHihN5880116NBBcXFxSkhIMLXuH/7wBw0aNEj33nuv3n33XXXo0MFpG2B33HHHNXfFO+uu3AEDBmjAgAHKzMxUcnKyIiIi1KhRI3344YdWRzPF3r17tXHjRofveqhXr56ioqL0xz/+0T6OUHLenWeONHbsWA0ePFhNmjTRuXPnFBoaKm9vb509e1b33nuvvZHtbCZMmKBRo0YpMTFR27Zt05NPPqno6GirY1WohIQEvffeezIMQ61atbKve3t76/nnnze9PjfROqfBgwcrJSVFubm5Sk9PV3R0tNPujC2TmZmpWbNmafv27ZIkLy8vlZaWWpwKcE40wAAXFxsb6/CaAwcOlPT/5xsAqNxq1KghLy8vSdI999yjevXq0fwCgKu4ubnJw8ND6enpevbZZxUTE2PqGzc2m03btm1TUlKSMjMzFRISolWrVikgIMC0mlbz8/PTrl27ZBiGSkpKtHDhQqc/A61hw4Z64okndOzYMe3cudPqOKaxYnfbuXPndOLECfn5+emHH35wWF0rd5450vfff68mTZpIktavX68GDRpoyZIlOnXqlIYOHep0DbCrdz5NmTJFQ4YMUdu2bTVgwADl5+erRo0aFqarWLGxsYqNjdXUqVM1adIkh9ffvXu35s2bp+PHj6ukpMS+npGR4fAsqFi9e/dW7969rY7hML++6aOgoMDpxz4CVqEBBri4nJwczZgxQydPntSyZct08OBB7dmzR5GRkabVbN68uSTpiSeeMK0GgIrzyy+/aNmyZfbnFy5cKPfczDulAaAqKCgoUHZ2ttLS0jR69GhJMvVNjM6dO8vX11d9+vTR8OHDZRiGCgoKlJWVJelK48TZvPHGG4qLi9OhQ4fUqlUrBQYG2serOZt//vOfSk5O1saNG9WoUSOFh4fr7bfftjpWhSv7WaJevXoaNGiQunTpUm4ku1k/X3z22Wd69dVX5eXlpcLCQs2fP1/t2rUzpdb1WLHzzNGubu7t3r3bPtLLz8/PKXdutm7dWoZhyGaz2f9///79+vDDD2UYhg4cOGB1xAr3yiuvqLS0VG5ubsrMzNShQ4fUtWvXcv8Nm2HixIl6+eWX1bx5c7m5uZlaC44zYsQIxcfH684775QknT17VpMnT9af//xna4OZKDAwUAkJCSosLNSOHTuUmJjodGdrA5UFDTDAxb3++uvq3Lmzli9fLkl66KGHNG7cOFMbYCNHjrzhLz7O/EMOUBW1b99e+/fvtz9v165duecA4OoGDhyoZ555Ru3atVOLFi104sQJ1apVy7R6Hh4eOnfunJYsWaLExMRyzTbDMLRlyxbTajtaWVNPuvLGZ3Fxsdzc3OTm5qazZ8/qnnvusTCdOUaOHKmwsDCtWbPGqc/+uvpniQceeECZmZkOqfv+++9r5cqVatq0qb7++mstWLDAYQ0wq3aeWSE7O1s+Pj7auXOnRo4caV8vKCiwMJU5ys7wKXP+/Hnt3LlTAQEB9p1wzua5557TJ598oosXL+qFF15Q48aNtW3bNs2cOdPUurVr11ZISIipNeB4J06csDe/JOmuu+7S8ePHrQvkAKNHj9bixYvl5eWlOXPmKDg42KnPSASsRAMMcHHZ2dmKjIzUp59+Kkny9PQ0/U6qp59+2tTXB1CxZsyYYXUEAKjU+vfvr/79+9uf+/v7KzEx0bR6aWlppr12ZRMTE3PNmmEYunjxos6fP+90Oyt27dqlunXr6uOPP9bSpUv18MMPKzY2VoGBgVZHq3BW/Xzh5uampk2bSpKCgoJMf8O+jNU7zxwpJiZGYWFh8vDwUJs2bey7Uvfu3St/f3+L01W8G515Nnr0aKcb+Shd2eVcs2ZNbdq0SRERERoxYoR69eplet2ePXtqxYoVCgkJKbfT0JnGTLqikpISlZSU2M94KyoqUmFhocWpzHX8+HENGzZMw4YNs68dPnxYDRo0sDAV4JxogAEurlq18v8M5Obmmj53ODw83NTXB2Cebdu26auvvpJhGOrQoYM6dOhgdSQAsFx+fr4WLlyoEydOaN68eTp69KiOHDliH/vlCBs3blTPnj0dVs9Rft3su3TpkhITE7V8+XINGjTImlAm+fLLLxUfH69hw4bZz8rds2ePxowZozfeeMOhf58cadGiRYqIiCg3+mrt2rUaPHiwKfWKiop0+PBh++88hYWF5Z6bNULUyp1njhYSEqLAwED9/PPP5XZA1a1bV/Hx8RYmM8d3333nUmeeSVd28hUWFmrbtm167rnnJMkhIwnvuecevfHGG5o6daok2cdOOtvNEK6mY8eOGj16tP3v0tKlS9WpUyeLU5lr7NixSk5O/t01ALePBhjg4rp166ZJkybp4sWLSkpK0vLly9W3b19Ta3788ccaOHCgZs+efd3r48ePN7U+gFvzwQcfaP369XrmmWckSTNnzlRYWJheeOEFi5MBgLUmT54sX19f+xgsPz8/jRkzxqENiw8//NApG2BliouLtWLFCn3wwQd68sknlZSUpDp16lgdq0L95S9/0eLFi9WoUSP7WtOmTRUYGKi4uDinbYBt2rSp3E6/u+66Sxs3bjStAXb58mUNGTKk3FrZczNHiFq188wqvr6+8vX1LbfmbP/Nlrnjjjvsj13hzDNJ6tGjh4KCgvTQQw/pscce05kzZ8rtyDLL22+/raVLl6pZs2acAeZEXnnlFS1cuFAzZ86UzWbT008/fd0d4M7gl19+0S+//KKCgoJyN19cuHBBly5dsjgd4JxogAEubvDgwUpJSVFubq7S09MVHR2t0NBQU2uW/WB89aHPACq/lJQUrVy5Ut7e3pKk6OhoRUZG0gAD4PIyMzM1a9Ysbd++XZLk5eWl0tJSh2Ywewe/ldatW6f58+erRYsW+vjjj1W/fn2rI5ni8uXL5ZpfZRo3buyU5yaVud7f3ZKSEtPqWTVC1KqdZ3AMVzrzTJJiY2P13HPPydvbW25ubqpZs6bmz59vet377rtPLVq0ML0OHMvDw0OxsbGKjY21OorpNmzYoI8//linT58udzNGrVq1TLvxA3B1NMAAF1ZSUqLhw4crISFBvXv3dljd//zP/1Rqaqoee+wxtW/fXh9//LG++uor1a9fX8OHD3dYDgD/vrLm168fA4Ar8/DwKPe8oKDA4Q2psrFBzqZXr166dOmSRowYoebNm6ukpERZWVn2687UNCgqKlJRUdE1f58KCwud+iyUevXqKTExUYMGDZLNZtNHH32kBx54wOpYFc6qnWcwn6udeSZdaVx//vnnOnr0qMaNG6ezZ8/q9OnTpu/yCwoK0pw5c9SjR49yO86c6XuBqxswYIA++eQTq2OYZuDAgRo4cKASEhL04osvWh0HcAmGzZlvFQTwuwYNGqTExESHjmaYNGmSMjMzVVhYqD/84Q8qKCjQU089pW+++UbSlbEGACqfV199VZLUr18/GYah1atXy2azWXaIPQBUFrNnz1bt2rWVkpKiN998U4mJiXr44Yc1evRoh9QvLCwst2OmRo0aDqnrCMHBwfbHhmGUayw6W9Ng5syZOn36tKZMmaJatWpJunI+b9mIzbLvw84mOztb48aN0549e2QYhlq3bq05c+bovvvuszoacNPOnDljP/Os7Hfr7OxslZSUOGUTbPr06crJydF3332nv/3tbzp79qyGDBmiNWvWmFr36u8JZZzte4GrCwsL07p166yOYZqffvqp3HPDMHT33Xc7ZIQo4KpogAEu7k9/+pMOHTqknj17ysvLy77+5JNPmlazR48e2rRpk/Lz89WxY0d9/fXX8vT0VGlpqXr37q2NGzeaVhvArbt06ZIWLFigjIwMSVL79u310ksvMc4UgMsrKirS4sWLlZaWJpvNpuDgYMXExKhaNXMHbnz++eeaPn26Tp8+LenKHfmGYejAgQOm1oU5CgsLNXnyZP3tb3/Tgw8+KEk6duyYunfvrsmTJ8vT09PihOYqO/uEnyuAyi80NFTr1q1TeHi4vVnRq1cvbdiwwdpgqPIiIiK0atUqq2OYJigo6JobevLy8tSqVSvNnj3bKRvmgNUYgQi4uP/93/+VJK1YscK+ZhiGqQ0wT09PGYahmjVr6oEHHrD/Mu/m5nbNyBcAlUfNmjU1btw4q2MAQKXj4eGhYcOGadiwYQ6tO3v2bM2fP1/NmzeXm5ubQ2uj4nl6emr69OmKjY1VZmambDabGjdurPvvv9/qaKbbtm2bvvrqKxmGoQ4dOqhDhw5WRwJwA9WrVy83RcaR515mZWVpx44dkq40Exo0aOCw2jCfMze/JOnrr7++Zq2kpEQrV65UfHy83n//fQtSAc6NBhjg4v761786vObVBz7/+vBnZz0kGKjKli1bdsPrUVFRDkoCAJXT7Nmzr1mrVauWWrVqpXbt2plW19fXVy1btjTt9WENf39/l7oD/IMPPtD69ev1zDPPSLoyCjIsLEwvvPCCxckA/JbGjRsrJSVFNptNP/74oxYtWqQ2bdqYXnfdunWaO3eunnrqKUnSwoULNXbsWIeeaY6Kw++ZV7i7uysqKsr0EaKAq6IBBrio9PT0G143cwfYrw+AvvqxI88iA3Bz9u/fb3UEAKjUcnJytGvXLnXp0kWStGXLFrVp00apqakKCQkxbWdYdHS03nnnHXXt2rXc2RENGzY0pR5ghpSUFK1cuVLe3t6Srvy9joyMpAEGVGITJkzQzJkzdebMGUVERCg4OFhxcXGm112yZImSk5Pl6+sr6crZay+88AINsCqK3zPLu/o8VwAVhwYY4KIWL14s6cpurH379qlx48aSpMzMTLVq1crUBlhaWppprw2g4s2YMcPqCABQqZ0+fVpJSUny8fGRJL300kuKi4vT8uXLFRERYVoDLDs7Wx999JHWrVtnH4FoGIa2bNliSj3ALGXNr18/BlB5TZs2rdzzvLw8h9Qta379+jGqHlf8PTM/P/+atXPnzmnlypVq1KiRBYkA50cDDHBRZaMPx40bp4kTJ+rRRx+VJH377bdsuwZwXTabTZ9++mm5Mzr69evHzk0ALi87O9ve/JIkHx8f/etf/5K3t7f9rFMz/PWvf9XmzZt13333mVYDMFvz5s316quv2n+mWL16tZo3b251LAA3EB0dreTk5N9dq2gPPPCA3n33XfXv31+GYWjVqlUKCAgwtSYc44cfftDBgwdVWFhoXwsLC7MukElat24twzDsx4AYhqG7775b7du312uvvWZxOsA50QADXNzhw4ftzS9JatmypSZPnmxdIACV1uzZs3XgwAH16dNH0pUZ/EePHtX48eMtTgYA1mrYsKHeeOMN9enTR4ZhKCkpSfXq1VNhYaF9Z5YZ/P39aX6hynvjjTe0YMEC+26S9u3b66WXXrI4FYDrKS4uVlFRkUpLS3X58mX7m/gXLly47s6WijZlyhRNmzZNvXv3lmEYat++vaZOnWp6XZhr6dKl+vTTT3XmzBm1aNFCu3bt0uOPP+6UDbCDBw9aHQFwOYat7LsVAJcUERGhqKgohYaGSroyg/+TTz7RqlWrLE4GoLLp1auXkpOTVa3alftnioqK1KdPH23YsMHiZABgrby8PC1YsEA7duyQzWZT27ZtNXz4cNWoUUO5ubm6++67Tak7a9YsZWdnq3v37uXOADNzlDUAwHW99957eu+998rtYJGujC59/vnnNXz4cFPr5+XlXTMm9XprqFp69uypVatWKTIyUuvXr1dmZqYWLlyoefPmWR0NgBNgBxjg4qZPn67x48fr9ddfl5ubmxo1aqQJEyZYHQtAJXX1uENGHwLAFd7e3oqLi7vuNbOaX9L/Hx5fNtpauvJvMw0wVCU5OTmaMWOGTp48qWXLlungwYPas2ePIiMjrY4G4FdiY2MVGxurqVOnatKkSQ6vb9XoRZjL09NTNWvWVGlpqWw2mxo3bqzjx49bHQuAk6ABBri4hg0bKikpST/99JOSk5OVkpKiiRMnavPmzVZHA1DJdOzYUUOGDFF4eLgMw1BycrI6duxodSwAsFxBQYFSUlJ04sQJFRcX29fNHhF7deMLqKpef/11de7cWcuXL5ckPfTQQxo3bhwNMKASK2t+FRYWqqSkxL5eo0YNU+r91ujF3Nxch4xehLlq1KihoqIiNWnSRHPmzFHdunV1+fJlq2MBcBI0wAAXVlxcrLS0NK1du1Z79+5VcXGxlixZUu5MMAAoKSlRYWGhxo0bp08//VRffPGFbDabgoODFRERYXU8ALDcqFGjVFRUpJYtW8rT09NhddPT06+7zg4wVCXZ2dmKjIzUp59+KunKTgAzz84DcPu++OILxcfH6/Tp0/ZxiIZh6MCBA6bUS0hIsI9ebNWqlaQrO569vLz0/PPPm1ITjvPmm2+qqKhIEyZM0Ntvv60ff/xRs2fPtjoWACfBGWCAi5oxY4Y2bdqkxo0bKzw8XF27dlWPHj2UlpZmdTQAlcysWbP00EMPqV+/fuXWly5dqlOnTpm+wwEAKruQkBClpqY6vG50dLT9cWFhoQ4cOKBHHnlEK1eudHgW4FZFRERo1apVCgsL07p165Sbm6sBAwYoJSXF6mgAfkPXrl01a9YstWrVyqEN67LRi+fPn9fOnTsVEBCgJk2aOKw+AKDqYQcY4KJWrFih1q1bKyYmRkFBQZI4zwfA9W3dulVjx469Zn3AgAHq3bs3DTAALi8gIEB5eXny9vZ2aN1fj0DMyspSYmKiQzMAt6tbt26aNGmSLl68qKSkJC1fvlx9+/a1OhaAG/Dx8dFjjz3msHpjx47V4MGDNWnSJJ07d06hoaHy9vbW2bNnNXr06Gtu1EPVkpOTo7/+9a/XjJL+85//bGEqAM6CBhjgorZv364NGzZo9uzZOn/+vMLCwsrN7gaAMm5ubnJ3d7/uOo1zAJBq1aqlvn37qlOnTuVGIDr6BoGGDRvqn//8p0NrArdr8ODBSklJUW5urtLT0xUdHa3Q0FCrYwG4ga5du2r58uXq0aOHqlevbl836wyw7777zr7Ta/369WrQoIGWLFmiU6dOaejQoTTAqrgRI0aoQYMGateu3XV/7wSA20EDDHBRtWvXVlRUlKKionTw4EGtWbNGly9fVlRUlHr16qVnn33W6ogAKonCwkLl5+df8wvtxYsXVVhYaFEqAKg86tevr/r16zu87tVngJWWlmrfvn0qLS11eA7gdvXu3Vu9e/e2OgaAm/SnP/1J0pWRhI44A+yOO+6wP969e7e6dOkiSfLz8+OGPCeQm5ur+Ph4q2MAcFI0wACoSZMmev311xUXF6cvvvhCycnJNMAA2PXo0UNxcXGaPn26fbzXhQsXNGnSJHXv3t3idABgvdjYWEvqLl682P64WrVqCggIYFwQqhxGXwFVz8GDBx1eMzs7Wz4+Ptq5c6dGjhxpXy8oKHB4FlSsRo0aKTs7W3Xq1LE6CgAnRAMMgJ2Hh4d69OihHj16WB0FQCUyfPhwTZgwQZ06dVK9evUkSUePHlVwcLBGjBhhbTgAsFBqaqpCQkK0bNmy616Piooytf6vzwADqiJGXwH4PTExMQoLC5OHh4fatGmjhg0bSpL27t0rf39/i9PhduXm5qp3795q3bp1uZGa3AgBoCLQAAMAADdUrVo1zZ07V8eOHdP3338vm82mZs2a6cEHH7Q6GgBY6tChQwoJCdH+/fsdWnf37t1q06ZNuRGIV3vyyScdmge4HYy+AqqOoKCg644cLBuBmJGRYUrdkJAQBQYG6ueff7afBSZJdevW5d8PJ9CzZ0/17NnT6hgAnJRhs9lsVocAAAAAANyc119/XdOmTVN0dPQ11wzD0NKlSy1IBdya0aNHa8KECYy+AqqAf/3rXze8fv/99zsoCQAAN4cGGAAAAADcpoyMDB0/frzcGUZmj0AEqrKRI0fKMAzl5eVp//79jL4CqqijR4/ax6QDt+KXX35RfHy8MjIyZBiG2rdvr9dee01333231dEAOAEaYAAAAABwG+Li4vTdd9/pkUceKXeG0YwZM0ypl5WVdcPrZWejAJVZcnKyzp07J5vNJnd3d9WuXbvc9fDwcIuSAfh3hIeHKzk52eoYqMJGjBihhg0b6tlnn5XNZtOqVauUmZmp9957z+poAJwAZ4ABAAAAwG3Yu3evNm7cKA8PD4fUi4mJ+c1rhmFoy5YtDskB3I7q1avrnXfekZeXlwoLCzV//ny1a9fO6lgA/k3cV4/bdfz4cc2fP9/+fOTIkQoNDbUwEQBnQgMMAAAAAG6Dn5+fQ+ulpaU5tB5ghvfff18rV65U06ZN9fXXX2vBggU0wIAq6LHHHrM6Aqq40tJS5eTk6J577pEk5eTkqLS01OJUAJwFDTAAAAAAuA316tXToEGD1KVLF3l6etrXHXEGWEZGhg4fPqwBAwYoJydHubm5ql+/vul1gdvl5uampk2bSpKCgoI0c+ZMixMBuBWTJk2yOgKquBdeeEFhYWF66qmnZBiG0tPT9corr1gdC4CToAEGAAAAALehsLBQDzzwgDIzMx1ad9GiRUpPT9eZM2c0YMAAFRUVaeLEiVqxYoVDcwC3oqioSIcPH7aPTyssLCz3nLPsgMpn5MiRMgzjN6//+c9/dmAaOIuwsDA98sgj2rlzp2w2m5577jm+BwCoMIaNYb0AAAAAUOX07t1ba9euVb9+/bRu3TpJUq9evbRhwwZrgwE3ITg4+DevcZYdUDklJyff8Hp4eLiDkgAAcHPYAQYAAAAAtyE/P18LFy7UiRMnNG/ePB0+fFhHjhxRly5dTK17xx13yMPDo9zaje7MByoTzrIDqh4aXKhI48aN05w5c9S3b9/r/vyyZs0aC1IBcDY0wAAAAADgNkyePFm+vr46ePCgJMnPz09jxowxvQHm5+enXbt2yTAMlZaWKiEhQY0aNTK1JgDAdc2ePfuG18ePH++gJHAGAwcOlCTFxcVZnASAM6MBBgAAAAC3ITMzU7NmzdL27dslSV5eXiotLTW97htvvKG4uDgdOnRIjz76qAIDAzV37lzT6wIAXFPNmjWtjgAn0rx5c0nSyZMnFRoaWu7a+vXrrYgEwAnRAAMAAACA2/DrMYQFBQVyxFHLvr6+WrJkifLz81VaWiovLy/TawIAXFdsbKzVEeCEPvroo2saYNdbA4BbQQMMAAAAAG5DYGCgEhISVFhYqB07digxMVHBwcEOqX38+HEdP35cJSUl9rUnn3zSIbUBAK5r+/btOnDggAoKCuxrNMjw79i3b5++/fZbnT17VsuWLbOv5+XlqaioyMJkAJwJDTAAAAAAuA2jR4/W4sWL5eXlpblz5yo4OFgxMTGm1503b55Wr16tBg0ayM3NTZJkGAYNMACAqebOnat9+/YpKytL//Ef/6EtW7aoXbt2VsdCFZOdna39+/crPz9f+/fvt697eXlpxowZFiYD4EwMmyNmcwAAAACAk7n6buXriYqKMrV+165dlZycLG9vb1PrAABwtV69eik5OVl9+vRRSkqKsrOzNWXKFP3lL3+xOhqqoO3bt6tjx45WxwDgpNgBBgAAAAC3ID4+Xs2bN1ejRo0sqe/r60vzCwDgcJ6enqpWrZoMw1BRUZHq1KmjU6dOWR0LVczu3bvVpk0blZSUKD09/Zrr7GgHUBFogAEAAADALXjrrbe0bt06ZWVlKSwsTD179pSPj4/pdcveJGrVqpVeeeUVde/eXdWrV7df5w0jAICZvLy8lJ+fr9atW2vChAny9fWVu7u71bFQxSQnJ6tNmzZavHjxNdcY6QygojACEQAAAABuw48//qjk5GSlpqaqcePGGjZsmB5++GHT6kVHR//mNcMwtHTpUtNqAwDw888/q3bt2iopKVFiYqIuXLig6Oho+fv7Wx0NAIByaIABAAAAwG26cOGCNm7cqHfffVevvPKK+vXrZ3UkAACASu+bb77RI488Ii8vL61evVr79u3TkCFDFBAQYHU0AE6ABhgAAAAA3AKbzaZt27YpKSlJmZmZCgkJUVhYmMPesImMjNSKFSt+dw0AgIr0ww8/KCEhQcePH1dxcbF9fc2aNRamQlXVq1cvpaSkKCsrS6NGjVLv3r311VdfsaMdQIXgDDAAAAAAuAWdO3eWr6+v+vTpo+HDh8swDBUUFCgrK0uS1LBhQ1PrX758udzzkpISnT9/3tSaAACMGjVKoaGhCg8P5+wv3LZq1arJMAxt3bpVkZGRio6O1t/+9jerYwFwEjTAAAAAAOAWeHh46Ny5c1qyZIkSExN19XANwzC0ZcsWU+ouXrxYixcvVl5entq1a2dfv3z5snr16mVKTQAAylSrVk2DBw+2OgacRHFxsXbv3q3PP/9cb731lqQrN/UAQEWgAQYAAAAAtyAtLc2Suv3791f37t0VHx+vSZMm2de9vb3l4+NjSSYAgOvo1KmTtm7dqs6dO1sdBU5g1KhRmjp1qoKCgtSoUSMdOXJEDz74oNWxADgJzgADAAAAgCqquLhYR44ckWEYqlevnqpV4x5HAIC5MjIy9NJLL8nNzU2enp6y2WwyDEMZGRlWRwMAoBwaYAAAAABQBe3fv18jRoywv/lYXFys+fPnq1mzZlZHAwA4sa5du2rMmDFq1qyZ3Nzc7Ov333+/halQVRUUFCglJUUnTpxQcXGxfX38+PEWpgLgLLg9EAAAAACqoGnTpmn69On2c8C+/vprxcfHa+XKlRYnAwA4Mx8fH3Xv3t3qGHASo0aNUlFRkVq2bCl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"text/plain": [
"<Figure size 2160x2160 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from imblearn.over_sampling import SMOTE\n",
"\n",
"over_m = SMOTE()\n",
"X_sm, y_sm = over_m.fit_resample(X_prfm_train, y_prfm_train)\n",
"\n",
"# Make a model\n",
"model_rfsm = RandomForestClassifier(n_estimators=1000)\n",
"\n",
"# Fit the model \n",
"clf = model_rfsm.fit(X_sm, y_sm)\n",
"\n",
"# Predict with unused (test) data \n",
"y_prf_pred_m = model_rfsm.predict(X_prfm_test)\n",
"\n",
"# What we got \n",
"\n",
"plot_trn_tst_dist(y_prfm, y_sm, y_prfm_test, y_prf_pred_m, in_cols=True)\n",
"#print(f\"Accuracy:\", accuracy_score(y_prfm_test, y_prf_pred_m))\n",
"print(classification_report(y_prfm_test, y_prf_pred_m))\n",
"# Plot some results\n",
"#plot_confusion_mat(y_prfm_test, y_prfm_pred, labs=labs, size=(30, 30))\n",
"plot_confusion_mat(y_prfm_test, y_prf_pred_m, labs=labs, size=(30, 30))\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Multiple class RandomForest classification with hyper parameter search, very slow one!"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"def print_res(res):\n",
" print(f\"Best parameters are: {res.best_params_}\")\n",
" print(\"\\n\")\n",
" mean_score = res.cv_results_['mean_test_score']\n",
" std_score = res.cv_results_['std_test_score']\n",
" params = res.cv_results_['params']\n",
" for mean,std,params in zip(mean_score,std_score,params):\n",
" print(f'{round(mean,3)} + or -{round(std,3)} for the {params}')\n",
"\n",
"param_grid_rf = {\n",
" 'n_estimators': [100, 200, 500, 1000],\n",
" 'max_depth': [2, 4, 8, 16, 32, None]\n",
"}\n",
"\n",
"cv = GridSearchCV(model_rfsm, param_grid_rf, cv=5, n_jobs=-1)\n",
"\n",
"cv.fit(X_sm, y_sm)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print_res(cv)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's use values obtained from above to run the classifier."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"model_mrfh = RandomForestClassifier(n_estimators=1000, max_depth=None)\n",
"model_mrfh.fit(X_sm, y_sm)\n",
"\n",
"y_prfmh_pred = model_mrfh.predict(X_prf_test)\n",
"print(classification_report(y_prfm_test, y_prf_pred_m))\n",
"\n",
"#print(f\"Test accuracy:\", accuracy_score(y_prfm_test, y_prfmh_pred))\n",
"plot_confusion_mat(y_prfm_test, y_prfmh_pred, labs=labs)"
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": true,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}