{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv('./bearings.csv', index_col=0, parse_dates=[0])\n",
    "# this dataset contains 984 samples. Each sample contains vibration data for four bearings\n",
    "# the samples were taken 10 minutes apart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Bearing 1</th>\n",
       "      <th>Bearing 2</th>\n",
       "      <th>Bearing 3</th>\n",
       "      <th>Bearing 4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2004-02-12 10:32:39</th>\n",
       "      <td>0.058333</td>\n",
       "      <td>0.071832</td>\n",
       "      <td>0.083242</td>\n",
       "      <td>0.043067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 10:42:39</th>\n",
       "      <td>0.058995</td>\n",
       "      <td>0.074006</td>\n",
       "      <td>0.084435</td>\n",
       "      <td>0.044541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 10:52:39</th>\n",
       "      <td>0.060236</td>\n",
       "      <td>0.074227</td>\n",
       "      <td>0.083926</td>\n",
       "      <td>0.044443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 11:02:39</th>\n",
       "      <td>0.061455</td>\n",
       "      <td>0.073844</td>\n",
       "      <td>0.084457</td>\n",
       "      <td>0.045081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 11:12:39</th>\n",
       "      <td>0.061361</td>\n",
       "      <td>0.075609</td>\n",
       "      <td>0.082837</td>\n",
       "      <td>0.045118</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Bearing 1  Bearing 2  Bearing 3  Bearing 4\n",
       "2004-02-12 10:32:39   0.058333   0.071832   0.083242   0.043067\n",
       "2004-02-12 10:42:39   0.058995   0.074006   0.084435   0.044541\n",
       "2004-02-12 10:52:39   0.060236   0.074227   0.083926   0.044443\n",
       "2004-02-12 11:02:39   0.061455   0.073844   0.084457   0.045081\n",
       "2004-02-12 11:12:39   0.061361   0.075609   0.082837   0.045118"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "\n",
    "df.plot(figsize=(12,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# about four days into the test, vibrations in bearing #1 began increasing. They spiked a day later,\n",
    "# and about two days after that, bearing #1 suffered a faliure.\n",
    "# the goal is to recognize increased vibration as a sign of impending failure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "x_train = df['2004-02-12 10:32:39':'2004-02-13 23:42:39']\n",
    "x_test = df['2004-02-13 23:52:39':]\n",
    "\n",
    "pca = PCA(n_components=1, random_state=0)\n",
    "x_train_pca = pd.DataFrame(pca.fit_transform(x_train))\n",
    "x_train_pca.index = x_train.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_test_pca = pd.DataFrame(pca.transform(x_test))\n",
    "x_test_pca.index = x_test.index\n",
    "\n",
    "df_pca = pd.concat([x_train_pca, x_test_pca])\n",
    "df_pca.plot(figsize=(12,6))\n",
    "plt.legend().remove()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# now invert the PCA transform and plot the restored dataset\n",
    "df_restored = pd.DataFrame(pca.inverse_transform(df_pca), index=df_pca.index)\n",
    "df_restored.plot(figsize=(12,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Bearing 1</th>\n",
       "      <th>Bearing 2</th>\n",
       "      <th>Bearing 3</th>\n",
       "      <th>Bearing 4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2004-02-12 10:32:39</th>\n",
       "      <td>0.058333</td>\n",
       "      <td>0.071832</td>\n",
       "      <td>0.083242</td>\n",
       "      <td>0.043067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 10:42:39</th>\n",
       "      <td>0.058995</td>\n",
       "      <td>0.074006</td>\n",
       "      <td>0.084435</td>\n",
       "      <td>0.044541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 10:52:39</th>\n",
       "      <td>0.060236</td>\n",
       "      <td>0.074227</td>\n",
       "      <td>0.083926</td>\n",
       "      <td>0.044443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 11:02:39</th>\n",
       "      <td>0.061455</td>\n",
       "      <td>0.073844</td>\n",
       "      <td>0.084457</td>\n",
       "      <td>0.045081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 11:12:39</th>\n",
       "      <td>0.061361</td>\n",
       "      <td>0.075609</td>\n",
       "      <td>0.082837</td>\n",
       "      <td>0.045118</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Bearing 1  Bearing 2  Bearing 3  Bearing 4\n",
       "2004-02-12 10:32:39   0.058333   0.071832   0.083242   0.043067\n",
       "2004-02-12 10:42:39   0.058995   0.074006   0.084435   0.044541\n",
       "2004-02-12 10:52:39   0.060236   0.074227   0.083926   0.044443\n",
       "2004-02-12 11:02:39   0.061455   0.073844   0.084457   0.045081\n",
       "2004-02-12 11:12:39   0.061361   0.075609   0.082837   0.045118"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2004-02-12 10:32:39</th>\n",
       "      <td>0.061336</td>\n",
       "      <td>0.075812</td>\n",
       "      <td>0.082033</td>\n",
       "      <td>0.044257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 10:42:39</th>\n",
       "      <td>0.061697</td>\n",
       "      <td>0.075981</td>\n",
       "      <td>0.083626</td>\n",
       "      <td>0.044397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 10:52:39</th>\n",
       "      <td>0.061652</td>\n",
       "      <td>0.075960</td>\n",
       "      <td>0.083426</td>\n",
       "      <td>0.044380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 11:02:39</th>\n",
       "      <td>0.061826</td>\n",
       "      <td>0.076042</td>\n",
       "      <td>0.084195</td>\n",
       "      <td>0.044447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-12 11:12:39</th>\n",
       "      <td>0.061519</td>\n",
       "      <td>0.075898</td>\n",
       "      <td>0.082840</td>\n",
       "      <td>0.044328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            0         1         2         3\n",
       "2004-02-12 10:32:39  0.061336  0.075812  0.082033  0.044257\n",
       "2004-02-12 10:42:39  0.061697  0.075981  0.083626  0.044397\n",
       "2004-02-12 10:52:39  0.061652  0.075960  0.083426  0.044380\n",
       "2004-02-12 11:02:39  0.061826  0.076042  0.084195  0.044447\n",
       "2004-02-12 11:12:39  0.061519  0.075898  0.082840  0.044328"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_restored.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's define a function that computs the loss in a range of samples\n",
    "import numpy as np\n",
    "\n",
    "def get_anomaly_scores(df_original, df_restored):\n",
    "    loss = np.sum((np.array(df_original) - np.array(df_restored))**2, axis=1)\n",
    "    loss = pd.Series(data=loss, index=df_original.index)\n",
    "    return loss\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores = get_anomaly_scores(df, df_restored)\n",
    "scores.plot(figsize=(12,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# detect anomaly\n",
    "def is_anomaly(data, pca, threshold):\n",
    "    pca_data = pca.transform(data)\n",
    "    restored_data = pca.inverse_transform(pca_data)\n",
    "    loss = np.sum((data - restored_data)**2)\n",
    "    return loss > threshold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = [df.loc['2004-2-16 22:52:39']]\n",
    "is_anomaly(x, pca, 0.002)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = [df.loc['2004-2-18 22:52:39']]\n",
    "is_anomaly(x, pca, 0.002)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(figsize=(12,6))\n",
    "for index, row in df.iterrows():\n",
    "    if is_anomaly([row], pca, 0.002):\n",
    "        plt.axvline(row.name, color='r', alpha=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n",
      "/Users/zijun/Documents/anaconda3/envs/class/lib/python3.10/site-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but PCA was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# lower threshold\n",
    "df.plot(figsize=(12,6))\n",
    "for index, row in df.iterrows():\n",
    "    if is_anomaly([row], pca, 0.0002):\n",
    "        plt.axvline(row.name, color='r', alpha=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}