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268 lines
7.7 KiB
268 lines
7.7 KiB
{
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" <th></th>\n",
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" <th>phase_no</th>\n",
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" <th>ring_type</th>\n",
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" <th>move_no</th>\n",
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" <th>angle_code</th>\n",
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" <td>A</td>\n",
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" <td>4</td>\n",
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" <td>B</td>\n",
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" <td>7</td>\n",
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" <td>8</td>\n",
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" <td>142359</td>\n",
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" <td>e5</td>\n",
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"text/plain": [
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" phase_no ring_type move_no angle_code inc_edge_id out_edge_id\n",
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"0 1 A 4 357140 e1 e6\n",
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"1 1 B 7 357088 e1 e4\n",
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"2 2 A 4 357140 e1 e6\n",
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"3 2 B 8 142359 e5 e2"
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>phase_no</th>\n",
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" <th>ring_type</th>\n",
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" <th>move_no</th>\n",
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" <th>angle_code</th>\n",
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" <th>inc_edge_id</th>\n",
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" <th>out_edge_id</th>\n",
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" <th>inc_angle</th>\n",
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" <td>7</td>\n",
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" <td>e5</td>\n",
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"text/plain": [
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" phase_no ring_type move_no angle_code inc_edge_id out_edge_id inc_angle \\\n",
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"0 1 A 4 357140 e1 e6 357 \n",
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"1 1 B 7 357088 e1 e4 357 \n",
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"2 2 A 4 357140 e1 e6 357 \n",
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"3 2 B 8 142359 e5 e2 142 \n",
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"\n",
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" out_angle \n",
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"0 140 \n",
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"1 88 \n",
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"2 140 \n",
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"3 359 "
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[357]\n",
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" [140]\n",
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" [357]\n",
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" [ 88]\n",
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" [357]\n",
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" [140]\n",
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" [142]\n",
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" [359]]\n",
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"[0 1 0 2 0 1 1 0]\n",
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"[[357.5 ]\n",
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" [140.66666667]\n",
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" [ 88. ]]\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"c:\\Github\\sts\\sts\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1416: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
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" super()._check_params_vs_input(X, default_n_init=10)\n"
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]
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}
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],
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"source": [
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"import pandas as pd\n",
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"data = [\n",
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" [1, 'A', 4, '357140', 'e1', 'e6'],\n",
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" [1, 'B', 7, '357088', 'e1', 'e4'],\n",
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" [2, 'A', 4, '357140', 'e1', 'e6'],\n",
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" [2, 'B', 8, '142359', 'e5', 'e2']\n",
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"]\n",
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"\n",
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"df = pd.DataFrame(data,\n",
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" columns=['phase_no', 'ring_type', 'move_no', 'angle_code', 'inc_edge_id', 'out_edge_id'])\n",
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"display(df)\n",
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"df['inc_angle'] = df['angle_code'].apply(lambda x:int(x[:3]))\n",
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"df['out_angle'] = df['angle_code'].apply(lambda x:int(x[3:]))\n",
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"display(df)\n",
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"\n",
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"angles = df[['inc_angle', 'out_angle']].values.flatten().reshape(-1, 1)\n",
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"angles\n",
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"\n",
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"from sklearn.cluster import KMeans\n",
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"# K-means 모델 생성 및 학습 (k=3)\n",
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"kmeans = KMeans(n_clusters=3, random_state=0).fit(angles)\n",
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"\n",
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"# 클러스터링 결과\n",
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"labels = kmeans.labels_\n",
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"\n",
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"# 클러스터 중심점 출력\n",
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"centroids = kmeans.cluster_centers_\n",
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"print(angles)\n",
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"print(labels)\n",
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"print(centroids)\n"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "sts",
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"language": "python",
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"name": "sts"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.10"
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}
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"nbformat": 4,
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"nbformat_minor": 2
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}
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