initial repo
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zhaojinghao
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"id": "70ae2cb0-c6f0-4080-b894-2246c9d880e2",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd"
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]
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|
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|
||||
" <th></th>\n",
|
||||
" <th>Unnamed: 0_level_0</th>\n",
|
||||
" <th>氢</th>\n",
|
||||
" <th>碳</th>\n",
|
||||
" <th>氮</th>\n",
|
||||
" <th>氧</th>\n",
|
||||
" <th>弹筒发热量</th>\n",
|
||||
" <th>挥发分</th>\n",
|
||||
" <th>固定炭</th>\n",
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||||
" </tr>\n",
|
||||
" <tr>\n",
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||||
" <th></th>\n",
|
||||
" <th>化验编号</th>\n",
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||||
" <th>Had</th>\n",
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||||
" <th>Cad</th>\n",
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" <th>Nad</th>\n",
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||||
" <th>Oad</th>\n",
|
||||
" <th>Qb,ad</th>\n",
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" <th>Vad</th>\n",
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" <th>Fcad</th>\n",
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" </tr>\n",
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" <th></th>\n",
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" <th>Unnamed: 0_level_2</th>\n",
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" <th>(%)</th>\n",
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||||
" <th>(%)</th>\n",
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" <th>(%)</th>\n",
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||||
" <th>(%)</th>\n",
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" <th>MJ/kg</th>\n",
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <td>3.93</td>\n",
|
||||
" <td>70.18</td>\n",
|
||||
" <td>0.81</td>\n",
|
||||
" <td>25.079</td>\n",
|
||||
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|
||||
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|
||||
" <td>55.68</td>\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <td>68.93</td>\n",
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||||
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||||
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|
||||
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||||
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|
||||
" <td>54.71</td>\n",
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <td>3.87</td>\n",
|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
" <td>0.92</td>\n",
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
],
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"text/plain": [
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||||
" Unnamed: 0_level_0 氢 碳 氮 氧 弹筒发热量 挥发分 固定炭\n",
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||||
" 化验编号 Had Cad Nad Oad Qb,ad Vad Fcad\n",
|
||||
" Unnamed: 0_level_2 (%) (%) (%) (%) MJ/kg (%) (%)\n",
|
||||
"0 2720110529 3.93 70.18 0.81 25.079 27.820 32.06 55.68\n",
|
||||
"1 2720096883 3.78 68.93 0.77 26.512 27.404 29.96 54.71\n",
|
||||
"2 2720109084 3.48 69.60 0.76 26.148 27.578 29.31 55.99\n",
|
||||
"3 2720084708 3.47 66.71 0.76 29.055 26.338 28.58 53.87\n",
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||||
"4 2720062721 3.87 68.78 0.80 26.542 27.280 29.97 54.78\n",
|
||||
".. ... ... ... ... ... ... ... ...\n",
|
||||
"223 2720030490 4.12 68.85 0.97 26.055 27.864 32.94 51.89\n",
|
||||
"224 2720028633 3.97 67.04 0.94 28.043 27.368 31.88 51.38\n",
|
||||
"225 2720028634 4.12 68.42 0.96 26.493 27.886 33.16 52.00\n",
|
||||
"226 2720017683 3.88 67.42 0.94 27.760 26.616 31.65 50.56\n",
|
||||
"227 2720017678 3.81 66.74 0.92 28.530 26.688 31.02 50.82\n",
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||||
"\n",
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||||
"[228 rows x 8 columns]"
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||||
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||||
},
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||||
"execution_count": 6,
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||||
"metadata": {},
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||||
"output_type": "execute_result"
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||||
}
|
||||
],
|
||||
"source": [
|
||||
"data_0102 = pd.read_excel('./data/20240102/20240102.xlsx', header=[0,1,2])\n",
|
||||
"data_0102"
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||||
]
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||||
},
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{
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||||
"cell_type": "code",
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||||
"execution_count": 10,
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||||
"id": "f72789a6-f3fa-4ab1-8b62-999413958608",
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||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
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||||
"['化验编号',\n",
|
||||
" '氢Had(%)',\n",
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||||
" '碳Cad(%)',\n",
|
||||
" '氮Nad(%)',\n",
|
||||
" '氧Oad(%)',\n",
|
||||
" '弹筒发热量Qb,adMJ/kg',\n",
|
||||
" '挥发分Vad(%)',\n",
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||||
" '固定炭Fcad(%)']"
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||||
]
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||||
},
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||||
"execution_count": 10,
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||||
"metadata": {},
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||||
"output_type": "execute_result"
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||||
}
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||||
],
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||||
"source": [
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||||
"cols = [''.join([y for y in x if 'Unnamed' not in y]) for x in data_0102.columns]\n",
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||||
"cols"
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]
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||||
},
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||||
{
|
||||
"cell_type": "code",
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||||
"execution_count": 11,
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"id": "6ffb1989-3f45-4d1c-84c9-59b1045b7d9e",
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||||
"metadata": {},
|
||||
"outputs": [],
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||||
"source": [
|
||||
"data_0102.columns = cols"
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]
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},
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{
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"cell_type": "code",
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||||
"execution_count": 27,
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"id": "9c708cc0-9f1b-4669-a350-6d24cb720794",
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"metadata": {},
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||||
"outputs": [],
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||||
"source": [
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||||
"import xgboost as xgb"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "103349e1-aa4a-427a-a489-9ab28787088b",
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||||
"metadata": {},
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||||
"outputs": [
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||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"['氢Had(%)', '碳Cad(%)', '氮Nad(%)', '氧Oad(%)', '弹筒发热量Qb,adMJ/kg']"
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]
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||||
},
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||||
"execution_count": 16,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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||||
"source": [
|
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"feature_cols = cols[1:6]\n",
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"feature_cols"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 44,
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||||
"id": "839e45dc-e9c8-4956-950b-035687469c81",
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"metadata": {},
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"outputs": [
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||||
{
|
||||
"data": {
|
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"text/html": [
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"<div>\n",
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||||
"<style scoped>\n",
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||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>化验编号</th>\n",
|
||||
" <th>氢Had(%)</th>\n",
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||||
" <th>碳Cad(%)</th>\n",
|
||||
" <th>氮Nad(%)</th>\n",
|
||||
" <th>氧Oad(%)</th>\n",
|
||||
" <th>弹筒发热量Qb,adMJ/kg</th>\n",
|
||||
" <th>挥发分Vad(%)</th>\n",
|
||||
" <th>固定炭Fcad(%)</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>2720110529</td>\n",
|
||||
" <td>3.93</td>\n",
|
||||
" <td>70.18</td>\n",
|
||||
" <td>0.81</td>\n",
|
||||
" <td>25.079</td>\n",
|
||||
" <td>27.820</td>\n",
|
||||
" <td>32.06</td>\n",
|
||||
" <td>55.68</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>2720096883</td>\n",
|
||||
" <td>3.78</td>\n",
|
||||
" <td>68.93</td>\n",
|
||||
" <td>0.77</td>\n",
|
||||
" <td>26.512</td>\n",
|
||||
" <td>27.404</td>\n",
|
||||
" <td>29.96</td>\n",
|
||||
" <td>54.71</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>2720109084</td>\n",
|
||||
" <td>3.48</td>\n",
|
||||
" <td>69.60</td>\n",
|
||||
" <td>0.76</td>\n",
|
||||
" <td>26.148</td>\n",
|
||||
" <td>27.578</td>\n",
|
||||
" <td>29.31</td>\n",
|
||||
" <td>55.99</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>2720084708</td>\n",
|
||||
" <td>3.47</td>\n",
|
||||
" <td>66.71</td>\n",
|
||||
" <td>0.76</td>\n",
|
||||
" <td>29.055</td>\n",
|
||||
" <td>26.338</td>\n",
|
||||
" <td>28.58</td>\n",
|
||||
" <td>53.87</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>2720062721</td>\n",
|
||||
" <td>3.87</td>\n",
|
||||
" <td>68.78</td>\n",
|
||||
" <td>0.80</td>\n",
|
||||
" <td>26.542</td>\n",
|
||||
" <td>27.280</td>\n",
|
||||
" <td>29.97</td>\n",
|
||||
" <td>54.78</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" 化验编号 氢Had(%) 碳Cad(%) 氮Nad(%) 氧Oad(%) 弹筒发热量Qb,adMJ/kg 挥发分Vad(%) \\\n",
|
||||
"0 2720110529 3.93 70.18 0.81 25.079 27.820 32.06 \n",
|
||||
"1 2720096883 3.78 68.93 0.77 26.512 27.404 29.96 \n",
|
||||
"2 2720109084 3.48 69.60 0.76 26.148 27.578 29.31 \n",
|
||||
"3 2720084708 3.47 66.71 0.76 29.055 26.338 28.58 \n",
|
||||
"4 2720062721 3.87 68.78 0.80 26.542 27.280 29.97 \n",
|
||||
"\n",
|
||||
" 固定炭Fcad(%) \n",
|
||||
"0 55.68 \n",
|
||||
"1 54.71 \n",
|
||||
"2 55.99 \n",
|
||||
"3 53.87 \n",
|
||||
"4 54.78 "
|
||||
]
|
||||
},
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||||
"execution_count": 44,
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||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"train_data = data_0102.copy()\n",
|
||||
"train_data.head()"
|
||||
]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
|
||||
"id": "24233d12-9468-49b8-a371-0c6c508c387e",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import seaborn as sns"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 21,
|
||||
"id": "54cd27a6-1a8a-47c0-93d9-c948960a7842",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 23,
|
||||
"id": "bba14f71-9d69-4c82-b6bc-b9b74c725b25",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"train_data.reset_index(drop=True, inplace=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 24,
|
||||
"id": "e3a9ad55-0132-430f-ac57-c2e7f8e8590a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from sklearn.metrics import mean_absolute_error, mean_squared_error, mean_absolute_percentage_error, r2_score"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 40,
|
||||
"id": "013c6a58-65f6-48e9-8d7f-b56c87de5b11",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"param_xgb = {\"silent\": True,\n",
|
||||
" \"obj\": 'reg:linear',\n",
|
||||
" \"subsample\": 1,\n",
|
||||
" \"max_depth\": 15,\n",
|
||||
" \"eta\": 0.3,\n",
|
||||
" \"gamma\": 0,\n",
|
||||
" \"lambda\": 1,\n",
|
||||
" \"alpha\": 0,\n",
|
||||
" \"colsample_bytree\": 0.9,}\n",
|
||||
"num_round = 1000"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 41,
|
||||
"id": "086f1901-8388-47e9-ae7c-1b2709bc1e22",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from sklearn.model_selection import KFold, train_test_split\n",
|
||||
"kf = KFold(n_splits=10, shuffle=True, random_state=42)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 43,
|
||||
"id": "fb7b06af-84bc-483c-b086-7826d7befc9c",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"MSE: 1.9436, RMSE: 1.3941, MAE: 1.1861, MAPE: 3.94 %, R_2: 0.6095\n",
|
||||
"MSE: 1.8735, RMSE: 1.3688, MAE: 1.132, MAPE: 3.77 %, R_2: 0.495\n",
|
||||
"MSE: 2.0587, RMSE: 1.4348, MAE: 1.0706, MAPE: 4.08 %, R_2: 0.7862\n",
|
||||
"MSE: 1.9298, RMSE: 1.3892, MAE: 1.1469, MAPE: 3.84 %, R_2: 0.5332\n",
|
||||
"MSE: 1.4583, RMSE: 1.2076, MAE: 1.097, MAPE: 3.67 %, R_2: 0.6894\n",
|
||||
"MSE: 2.0822, RMSE: 1.443, MAE: 1.1645, MAPE: 3.88 %, R_2: 0.5975\n",
|
||||
"MSE: 1.3521, RMSE: 1.1628, MAE: 0.9905, MAPE: 3.37 %, R_2: 0.7479\n",
|
||||
"MSE: 1.4057, RMSE: 1.1856, MAE: 0.9998, MAPE: 3.3 %, R_2: 0.2946\n",
|
||||
"MSE: 2.2274, RMSE: 1.4925, MAE: 1.2638, MAPE: 4.19 %, R_2: 0.6785\n",
|
||||
"MSE: 1.4866, RMSE: 1.2193, MAE: 1.0797, MAPE: 3.67 %, R_2: 0.7261\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"MSE 1.781792\n",
|
||||
"RMSE 1.329760\n",
|
||||
"MAE 1.113084\n",
|
||||
"MAPE 0.037719\n",
|
||||
"R_2 0.615796\n",
|
||||
"dtype: float64"
|
||||
]
|
||||
},
|
||||
"execution_count": 43,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"eva_list = list()\n",
|
||||
"for (train_index, test_index) in kf.split(train_data):\n",
|
||||
" train = train_data.loc[train_index]\n",
|
||||
" valid = train_data.loc[test_index]\n",
|
||||
" X_train, Y_train = train[feature_cols], np.log1p(train['挥发分Vad(%)'])\n",
|
||||
" X_valid, Y_valid = valid[feature_cols], np.log1p(valid['挥发分Vad(%)'])\n",
|
||||
" dtrain = xgb.DMatrix(X_train, Y_train)\n",
|
||||
" dvalid = xgb.DMatrix(X_valid, Y_valid)\n",
|
||||
" watchlist = [(dvalid, 'eval')]\n",
|
||||
" gb_model = xgb.train(params_xgb, dtrain, num_boost_round, evals=watchlist,\n",
|
||||
" early_stopping_rounds=50, verbose_eval=False)\n",
|
||||
" y_pred = np.expm1(gb_model.predict(xgb.DMatrix(X_valid)))\n",
|
||||
" y_true = np.expm1(Y_valid.values)\n",
|
||||
" MSE = mean_squared_error(y_true, y_pred)\n",
|
||||
" RMSE = np.sqrt(mean_squared_error(y_true, y_pred))\n",
|
||||
" MAE = mean_absolute_error(y_true, y_pred)\n",
|
||||
" MAPE = mean_absolute_percentage_error(y_true, y_pred)\n",
|
||||
" R_2 = r2_score(y_true, y_pred)\n",
|
||||
" print('MSE:', round(MSE, 4), end=', ')\n",
|
||||
" print('RMSE:', round(RMSE, 4), end=', ')\n",
|
||||
" print('MAE:', round(MAE, 4), end=', ')\n",
|
||||
" print('MAPE:', round(MAPE*100, 2), '%', end=', ')\n",
|
||||
" print('R_2:', round(R_2, 4)) #R方为负就说明拟合效果比平均值差\n",
|
||||
" eva_list.append([MSE, RMSE, MAE, MAPE, R_2])\n",
|
||||
"data_df = pd.DataFrame.from_records(eva_list, columns=['MSE', 'RMSE', 'MAE', 'MAPE', 'R_2'])\n",
|
||||
"data_df.mean()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 48,
|
||||
"id": "90841cb7-4f28-4a33-93ac-93df69f1a5a1",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"MSE: 4.6724, RMSE: 2.1616, MAE: 1.7297, MAPE: 3.42 %, R2: 0.8346\n",
|
||||
"MSE: 3.0512, RMSE: 1.7468, MAE: 1.4485, MAPE: 2.62 %, R2: 0.8011\n",
|
||||
"MSE: 7.6672, RMSE: 2.769, MAE: 1.951, MAPE: 4.56 %, R2: 0.8856\n",
|
||||
"MSE: 4.0334, RMSE: 2.0083, MAE: 1.487, MAPE: 2.77 %, R2: 0.8216\n",
|
||||
"MSE: 2.6382, RMSE: 1.6243, MAE: 1.1551, MAPE: 2.12 %, R2: 0.846\n",
|
||||
"MSE: 5.8097, RMSE: 2.4103, MAE: 1.8683, MAPE: 3.8 %, R2: 0.83\n",
|
||||
"MSE: 2.3446, RMSE: 1.5312, MAE: 1.1294, MAPE: 2.28 %, R2: 0.9069\n",
|
||||
"MSE: 3.0069, RMSE: 1.734, MAE: 1.3782, MAPE: 2.46 %, R2: 0.6541\n",
|
||||
"MSE: 4.1652, RMSE: 2.0409, MAE: 1.5685, MAPE: 3.2 %, R2: 0.859\n",
|
||||
"MSE: 4.2023, RMSE: 2.05, MAE: 1.6284, MAPE: 3.2 %, R2: 0.869\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"MSE 4.159107\n",
|
||||
"RMSE 2.007631\n",
|
||||
"MAE 1.534427\n",
|
||||
"MAPE 0.030424\n",
|
||||
"R2 0.830794\n",
|
||||
"dtype: float64"
|
||||
]
|
||||
},
|
||||
"execution_count": 48,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"eva_list = list()\n",
|
||||
"for (train_index, test_index) in kf.split(train_data):\n",
|
||||
" train = train_data.loc[train_index]\n",
|
||||
" valid = train_data.loc[test_index]\n",
|
||||
" X_train, Y_train = train[feature_cols], np.log1p(train['固定炭Fcad(%)'])\n",
|
||||
" X_valid, Y_valid = valid[feature_cols], np.log1p(valid['固定炭Fcad(%)'])\n",
|
||||
" dtrain = xgb.DMatrix(X_train, Y_train)\n",
|
||||
" dvalid = xgb.DMatrix(X_valid, Y_valid)\n",
|
||||
" watchlist = [(dvalid, 'eval')]\n",
|
||||
" gb_model = xgb.train(params_xgb, dtrain, num_boost_round, evals=watchlist,\n",
|
||||
" early_stopping_rounds=50, verbose_eval=False)\n",
|
||||
" y_pred = np.expm1(gb_model.predict(xgb.DMatrix(X_valid)))\n",
|
||||
" y_true = np.expm1(Y_valid.values)\n",
|
||||
" MSE = mean_squared_error(y_true, y_pred)\n",
|
||||
" RMSE = np.sqrt(mean_squared_error(y_true, y_pred))\n",
|
||||
" MAE = mean_absolute_error(y_true, y_pred)\n",
|
||||
" MAPE = mean_absolute_percentage_error(y_true, y_pred)\n",
|
||||
" R_2 = r2_score(y_true, y_pred)\n",
|
||||
" print('MSE:', round(MSE, 4), end=', ')\n",
|
||||
" print('RMSE:', round(RMSE, 4), end=', ')\n",
|
||||
" print('MAE:', round(MAE, 4), end=', ')\n",
|
||||
" print('MAPE:', round(MAPE*100, 2), '%', end=', ')\n",
|
||||
" print('R2:', round(R_2, 4)) #R方为负就说明拟合效果比平均值差\n",
|
||||
" eva_list.append([MSE, RMSE, MAE, MAPE, R_2])\n",
|
||||
"data_df = pd.DataFrame.from_records(eva_list, columns=['MSE', 'RMSE', 'MAE', 'MAPE', 'R2'])\n",
|
||||
"data_df.mean()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 67,
|
||||
"id": "aa67bc97-1258-44bb-9dae-14ace1661ff6",
|
||||
"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>MSE</th>\n",
|
||||
" <th>RMSE</th>\n",
|
||||
" <th>MAE</th>\n",
|
||||
" <th>MAPE</th>\n",
|
||||
" <th>R2</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>十折交叉验证均值</th>\n",
|
||||
" <td>4.159107</td>\n",
|
||||
" <td>2.007631</td>\n",
|
||||
" <td>1.534427</td>\n",
|
||||
" <td>0.030424</td>\n",
|
||||
" <td>0.830794</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" MSE RMSE MAE MAPE R2\n",
|
||||
"十折交叉验证均值 4.159107 2.007631 1.534427 0.030424 0.830794"
|
||||
]
|
||||
},
|
||||
"execution_count": 67,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ec6e136b-ed49-4469-bb8f-b86c4910bc05",
|
||||
"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": "3.8.16"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
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|
|
@ -0,0 +1,43 @@
|
|||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"\n# A demo for multi-output regression\n\nThe demo is adopted from scikit-learn:\n\nhttps://scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_regression_multioutput.html#sphx-glr-auto-examples-ensemble-plot-random-forest-regression-multioutput-py\n\nSee :doc:`/tutorials/multioutput` for more information.\n\n<div class=\"alert alert-info\"><h4>Note</h4><p>The feature is experimental. For the `multi_output_tree` strategy, many features are\n missing.</p></div>\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import argparse\nfrom typing import Dict, List, Tuple\n\nimport numpy as np\nfrom matplotlib import pyplot as plt\n\nimport xgboost as xgb\n\n\ndef plot_predt(y: np.ndarray, y_predt: np.ndarray, name: str) -> None:\n s = 25\n plt.scatter(y[:, 0], y[:, 1], c=\"navy\", s=s, edgecolor=\"black\", label=\"data\")\n plt.scatter(\n y_predt[:, 0], y_predt[:, 1], c=\"cornflowerblue\", s=s, edgecolor=\"black\"\n )\n plt.xlim([-1, 2])\n plt.ylim([-1, 2])\n plt.show()\n\n\ndef gen_circle() -> Tuple[np.ndarray, np.ndarray]:\n \"Generate a sample dataset that y is a 2 dim circle.\"\n rng = np.random.RandomState(1994)\n X = np.sort(200 * rng.rand(100, 1) - 100, axis=0)\n y = np.array([np.pi * np.sin(X).ravel(), np.pi * np.cos(X).ravel()]).T\n y[::5, :] += 0.5 - rng.rand(20, 2)\n y = y - y.min()\n y = y / y.max()\n return X, y\n\n\ndef rmse_model(plot_result: bool, strategy: str) -> None:\n \"\"\"Draw a circle with 2-dim coordinate as target variables.\"\"\"\n X, y = gen_circle()\n # Train a regressor on it\n reg = xgb.XGBRegressor(\n tree_method=\"hist\",\n n_estimators=128,\n n_jobs=16,\n max_depth=8,\n multi_strategy=strategy,\n subsample=0.6,\n )\n reg.fit(X, y, eval_set=[(X, y)])\n\n y_predt = reg.predict(X)\n if plot_result:\n plot_predt(y, y_predt, \"multi\")\n\n\ndef custom_rmse_model(plot_result: bool, strategy: str) -> None:\n \"\"\"Train using Python implementation of Squared Error.\"\"\"\n\n # As the experimental support status, custom objective doesn't support matrix as\n # gradient and hessian, which will be changed in future release.\n def gradient(predt: np.ndarray, dtrain: xgb.DMatrix) -> np.ndarray:\n \"\"\"Compute the gradient squared error.\"\"\"\n y = dtrain.get_label().reshape(predt.shape)\n return (predt - y).reshape(y.size)\n\n def hessian(predt: np.ndarray, dtrain: xgb.DMatrix) -> np.ndarray:\n \"\"\"Compute the hessian for squared error.\"\"\"\n return np.ones(predt.shape).reshape(predt.size)\n\n def squared_log(\n predt: np.ndarray, dtrain: xgb.DMatrix\n ) -> Tuple[np.ndarray, np.ndarray]:\n grad = gradient(predt, dtrain)\n hess = hessian(predt, dtrain)\n return grad, hess\n\n def rmse(predt: np.ndarray, dtrain: xgb.DMatrix) -> Tuple[str, float]:\n y = dtrain.get_label().reshape(predt.shape)\n v = np.sqrt(np.sum(np.power(y - predt, 2)))\n return \"PyRMSE\", v\n\n X, y = gen_circle()\n Xy = xgb.DMatrix(X, y)\n results: Dict[str, Dict[str, List[float]]] = {}\n # Make sure the `num_target` is passed to XGBoost when custom objective is used.\n # When builtin objective is used, XGBoost can figure out the number of targets\n # automatically.\n booster = xgb.train(\n {\n \"tree_method\": \"hist\",\n \"num_target\": y.shape[1],\n \"multi_strategy\": strategy,\n },\n dtrain=Xy,\n num_boost_round=128,\n obj=squared_log,\n evals=[(Xy, \"Train\")],\n evals_result=results,\n custom_metric=rmse,\n )\n\n y_predt = booster.inplace_predict(X)\n if plot_result:\n plot_predt(y, y_predt, \"multi\")\n\n\nif __name__ == \"__main__\":\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--plot\", choices=[0, 1], type=int, default=1)\n args = parser.parse_args()\n\n # Train with builtin RMSE objective\n # - One model per output.\n rmse_model(args.plot == 1, \"one_output_per_tree\")\n # - One model for all outputs, this is still working in progress, many features are\n # missing.\n rmse_model(args.plot == 1, \"multi_output_tree\")\n\n # Train with custom objective.\n # - One model per output.\n custom_rmse_model(args.plot == 1, \"one_output_per_tree\")\n # - One model for all outputs, this is still working in progress, many features are\n # missing.\n custom_rmse_model(args.plot == 1, \"multi_output_tree\")"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
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|
||||
"version": 3
|
||||
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|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.18"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 0
|
||||
}
|
||||
|
|
@ -0,0 +1,759 @@
|
|||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "e2fb2c7b-89ca-4e2b-aa44-19403cef590a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import pandas as pd"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "f47b0afa-9e2d-4f2d-a51b-6e2071ffd08a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"old_data = pd.read_excel('./data/煤质碳材料数据.xlsx')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "77fa919c-d186-4079-a7b1-70842c97c3ec",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"nature_data = pd.read_excel('./data/nature.xlsx')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "38a1f29b-06e1-47a4-8839-e37568bac6cf",
|
||||
"metadata": {},
|
||||
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|
||||
{
|
||||
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|
||||
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|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
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||||
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|
||||
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|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>编号</th>\n",
|
||||
" <th>煤种</th>\n",
|
||||
" <th>分析水Mad</th>\n",
|
||||
" <th>灰分</th>\n",
|
||||
" <th>挥发分</th>\n",
|
||||
" <th>碳</th>\n",
|
||||
" <th>氢</th>\n",
|
||||
" <th>氮</th>\n",
|
||||
" <th>硫</th>\n",
|
||||
" <th>氧</th>\n",
|
||||
" <th>碳化温度（℃）</th>\n",
|
||||
" <th>升温速率（℃/min)</th>\n",
|
||||
" <th>保温时间(h)</th>\n",
|
||||
" <th>KOH</th>\n",
|
||||
" <th>K2CO3</th>\n",
|
||||
" <th>BET比表面积（m2/g）</th>\n",
|
||||
" <th>孔体积（cm3/g)</th>\n",
|
||||
" <th>微孔体积（cm3/g)</th>\n",
|
||||
" <th>介孔体积（cm3/g)</th>\n",
|
||||
" </tr>\n",
|
||||
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|
||||
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|
||||
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|
||||
" <th>0</th>\n",
|
||||
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|
||||
" <td>中级烟煤</td>\n",
|
||||
" <td>2.12</td>\n",
|
||||
" <td>8.49</td>\n",
|
||||
" <td>37.14</td>\n",
|
||||
" <td>86.20</td>\n",
|
||||
" <td>5.42</td>\n",
|
||||
" <td>1.60</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>6.78</td>\n",
|
||||
" <td>1100.0</td>\n",
|
||||
" <td>2.0</td>\n",
|
||||
" <td>2.0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>296.0</td>\n",
|
||||
" <td>0.270</td>\n",
|
||||
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|
||||
" <td>NaN</td>\n",
|
||||
" </tr>\n",
|
||||
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|
||||
" <th>1</th>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>萃取中级烟煤</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>75.11</td>\n",
|
||||
" <td>4.73</td>\n",
|
||||
" <td>1.38</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>18.78</td>\n",
|
||||
" <td>1100.0</td>\n",
|
||||
" <td>2.0</td>\n",
|
||||
" <td>2.0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>316.0</td>\n",
|
||||
" <td>0.481</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
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|
||||
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|
||||
" <th>2</th>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>褐煤</td>\n",
|
||||
" <td>14.91</td>\n",
|
||||
" <td>4.35</td>\n",
|
||||
" <td>48.42</td>\n",
|
||||
" <td>67.76</td>\n",
|
||||
" <td>4.57</td>\n",
|
||||
" <td>1.29</td>\n",
|
||||
" <td>3.56</td>\n",
|
||||
" <td>22.82</td>\n",
|
||||
" <td>650.0</td>\n",
|
||||
" <td>10.0</td>\n",
|
||||
" <td>0.5</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>665.0</td>\n",
|
||||
" <td>0.356</td>\n",
|
||||
" <td>0.289</td>\n",
|
||||
" <td>0.067</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>褐煤</td>\n",
|
||||
" <td>14.91</td>\n",
|
||||
" <td>4.35</td>\n",
|
||||
" <td>48.42</td>\n",
|
||||
" <td>67.76</td>\n",
|
||||
" <td>4.57</td>\n",
|
||||
" <td>1.29</td>\n",
|
||||
" <td>3.56</td>\n",
|
||||
" <td>22.82</td>\n",
|
||||
" <td>650.0</td>\n",
|
||||
" <td>10.0</td>\n",
|
||||
" <td>0.5</td>\n",
|
||||
" <td>1</td>\n",
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||||
" <td>0</td>\n",
|
||||
" <td>1221.0</td>\n",
|
||||
" <td>0.608</td>\n",
|
||||
" <td>0.482</td>\n",
|
||||
" <td>0.126</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>褐煤</td>\n",
|
||||
" <td>14.91</td>\n",
|
||||
" <td>4.35</td>\n",
|
||||
" <td>48.42</td>\n",
|
||||
" <td>67.76</td>\n",
|
||||
" <td>4.57</td>\n",
|
||||
" <td>1.29</td>\n",
|
||||
" <td>3.56</td>\n",
|
||||
" <td>22.82</td>\n",
|
||||
" <td>650.0</td>\n",
|
||||
" <td>10.0</td>\n",
|
||||
" <td>0.5</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>2609.0</td>\n",
|
||||
" <td>1.438</td>\n",
|
||||
" <td>0.670</td>\n",
|
||||
" <td>0.768</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>66</th>\n",
|
||||
" <td>67</td>\n",
|
||||
" <td>无烟煤</td>\n",
|
||||
" <td>0.81</td>\n",
|
||||
" <td>4.15</td>\n",
|
||||
" <td>9.77</td>\n",
|
||||
" <td>91.59</td>\n",
|
||||
" <td>3.96</td>\n",
|
||||
" <td>1.76</td>\n",
|
||||
" <td>0.21</td>\n",
|
||||
" <td>2.48</td>\n",
|
||||
" <td>800.0</td>\n",
|
||||
" <td>5.0</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>3142.0</td>\n",
|
||||
" <td>1.608</td>\n",
|
||||
" <td>1.204</td>\n",
|
||||
" <td>0.404</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>67</th>\n",
|
||||
" <td>68</td>\n",
|
||||
" <td>无烟煤</td>\n",
|
||||
" <td>0.81</td>\n",
|
||||
" <td>4.15</td>\n",
|
||||
" <td>9.77</td>\n",
|
||||
" <td>91.59</td>\n",
|
||||
" <td>3.96</td>\n",
|
||||
" <td>1.76</td>\n",
|
||||
" <td>0.21</td>\n",
|
||||
" <td>2.48</td>\n",
|
||||
" <td>800.0</td>\n",
|
||||
" <td>5.0</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>3389.0</td>\n",
|
||||
" <td>2.041</td>\n",
|
||||
" <td>1.022</td>\n",
|
||||
" <td>1.019</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>68</th>\n",
|
||||
" <td>69</td>\n",
|
||||
" <td>无烟煤</td>\n",
|
||||
" <td>0.88</td>\n",
|
||||
" <td>8.42</td>\n",
|
||||
" <td>8.83</td>\n",
|
||||
" <td>91.69</td>\n",
|
||||
" <td>2.31</td>\n",
|
||||
" <td>2.04</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>3.96</td>\n",
|
||||
" <td>700.0</td>\n",
|
||||
" <td>5.0</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>2542.0</td>\n",
|
||||
" <td>1.135</td>\n",
|
||||
" <td>0.916</td>\n",
|
||||
" <td>0.219</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>69</th>\n",
|
||||
" <td>70</td>\n",
|
||||
" <td>无烟煤</td>\n",
|
||||
" <td>0.88</td>\n",
|
||||
" <td>8.42</td>\n",
|
||||
" <td>8.83</td>\n",
|
||||
" <td>91.69</td>\n",
|
||||
" <td>2.31</td>\n",
|
||||
" <td>2.04</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>3.96</td>\n",
|
||||
" <td>800.0</td>\n",
|
||||
" <td>5.0</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>2665.0</td>\n",
|
||||
" <td>1.219</td>\n",
|
||||
" <td>0.947</td>\n",
|
||||
" <td>0.272</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>70</th>\n",
|
||||
" <td>71</td>\n",
|
||||
" <td>无烟煤</td>\n",
|
||||
" <td>0.88</td>\n",
|
||||
" <td>8.42</td>\n",
|
||||
" <td>8.83</td>\n",
|
||||
" <td>91.69</td>\n",
|
||||
" <td>2.31</td>\n",
|
||||
" <td>2.04</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>3.96</td>\n",
|
||||
" <td>900.0</td>\n",
|
||||
" <td>5.0</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>2947.0</td>\n",
|
||||
" <td>1.473</td>\n",
|
||||
" <td>0.718</td>\n",
|
||||
" <td>0.755</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>71 rows × 19 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" 编号 煤种 分析水Mad 灰分 挥发分 碳 氢 氮 硫 氧 碳化温度（℃） \\\n",
|
||||
"0 1 中级烟煤 2.12 8.49 37.14 86.20 5.42 1.60 0.00 6.78 1100.0 \n",
|
||||
"1 2 萃取中级烟煤 NaN NaN NaN 75.11 4.73 1.38 0.00 18.78 1100.0 \n",
|
||||
"2 3 褐煤 14.91 4.35 48.42 67.76 4.57 1.29 3.56 22.82 650.0 \n",
|
||||
"3 4 褐煤 14.91 4.35 48.42 67.76 4.57 1.29 3.56 22.82 650.0 \n",
|
||||
"4 5 褐煤 14.91 4.35 48.42 67.76 4.57 1.29 3.56 22.82 650.0 \n",
|
||||
".. .. ... ... ... ... ... ... ... ... ... ... \n",
|
||||
"66 67 无烟煤 0.81 4.15 9.77 91.59 3.96 1.76 0.21 2.48 800.0 \n",
|
||||
"67 68 无烟煤 0.81 4.15 9.77 91.59 3.96 1.76 0.21 2.48 800.0 \n",
|
||||
"68 69 无烟煤 0.88 8.42 8.83 91.69 2.31 2.04 0.00 3.96 700.0 \n",
|
||||
"69 70 无烟煤 0.88 8.42 8.83 91.69 2.31 2.04 0.00 3.96 800.0 \n",
|
||||
"70 71 无烟煤 0.88 8.42 8.83 91.69 2.31 2.04 0.00 3.96 900.0 \n",
|
||||
"\n",
|
||||
" 升温速率（℃/min) 保温时间(h) KOH K2CO3 BET比表面积（m2/g） 孔体积（cm3/g) 微孔体积（cm3/g) \\\n",
|
||||
"0 2.0 2.0 0 0 296.0 0.270 NaN \n",
|
||||
"1 2.0 2.0 0 0 316.0 0.481 NaN \n",
|
||||
"2 10.0 0.5 1 0 665.0 0.356 0.289 \n",
|
||||
"3 10.0 0.5 1 0 1221.0 0.608 0.482 \n",
|
||||
"4 10.0 0.5 1 0 2609.0 1.438 0.670 \n",
|
||||
".. ... ... ... ... ... ... ... \n",
|
||||
"66 5.0 1.0 1 0 3142.0 1.608 1.204 \n",
|
||||
"67 5.0 1.0 1 0 3389.0 2.041 1.022 \n",
|
||||
"68 5.0 1.0 1 0 2542.0 1.135 0.916 \n",
|
||||
"69 5.0 1.0 1 0 2665.0 1.219 0.947 \n",
|
||||
"70 5.0 1.0 1 0 2947.0 1.473 0.718 \n",
|
||||
"\n",
|
||||
" 介孔体积（cm3/g) \n",
|
||||
"0 NaN \n",
|
||||
"1 NaN \n",
|
||||
"2 0.067 \n",
|
||||
"3 0.126 \n",
|
||||
"4 0.768 \n",
|
||||
".. ... \n",
|
||||
"66 0.404 \n",
|
||||
"67 1.019 \n",
|
||||
"68 0.219 \n",
|
||||
"69 0.272 \n",
|
||||
"70 0.755 \n",
|
||||
"\n",
|
||||
"[71 rows x 19 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"old_data"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
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||||
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|
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <th>Csp(F/g)</th>\n",
|
||||
" <th>electrolyte</th>\n",
|
||||
" <th>υ(mV/s)</th>\n",
|
||||
" <th>SAmicro(m2/g)</th>\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <td>6MKOH</td>\n",
|
||||
" <td>1</td>\n",
|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
" <tr>\n",
|
||||
" <th>283</th>\n",
|
||||
" <td>218.17</td>\n",
|
||||
" <td>1MH2SO4</td>\n",
|
||||
" <td>150</td>\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <th>284</th>\n",
|
||||
" <td>198.38</td>\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <th>285</th>\n",
|
||||
" <td>171.19</td>\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <th>286</th>\n",
|
||||
" <td>152.27</td>\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
" Csp(F/g) electrolyte υ(mV/s) SAmicro(m2/g) SAmeso(m2/g) O N\n",
|
||||
"0 0.00 6MKOH 1 0 0 0.00 0.00\n",
|
||||
"1 0.00 6MKOH 300 0 0 0.00 0.00\n",
|
||||
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|
||||
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|
||||
"4 0.00 6MKOH 300 0 0 17.00 15.60\n",
|
||||
".. ... ... ... ... ... ... ...\n",
|
||||
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|
||||
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|
||||
"285 171.19 1MH2SO4 300 1691 258 16.45 3.31\n",
|
||||
"286 152.27 1MH2SO4 400 1691 258 16.45 3.31\n",
|
||||
"287 137.40 1MH2SO4 500 1691 258 16.45 3.31\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
"source": [
|
||||
"基于微孔介孔，推一下CHS？"
|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
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|
||||
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||||
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||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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|
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|
||||
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||||
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|
||||
" O N SAmicro(m2/g) SAmeso(m2/g)\n",
|
||||
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|
||||
"3 17.00 15.60 0 0\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
||||
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>2720110529</td>\n",
|
||||
" <td>3.93</td>\n",
|
||||
" <td>70.18</td>\n",
|
||||
" <td>0.81</td>\n",
|
||||
" <td>25.079</td>\n",
|
||||
" <td>27.820</td>\n",
|
||||
" <td>32.06</td>\n",
|
||||
" <td>55.68</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>2720096883</td>\n",
|
||||
" <td>3.78</td>\n",
|
||||
" <td>68.93</td>\n",
|
||||
" <td>0.77</td>\n",
|
||||
" <td>26.512</td>\n",
|
||||
" <td>27.404</td>\n",
|
||||
" <td>29.96</td>\n",
|
||||
" <td>54.71</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>2720109084</td>\n",
|
||||
" <td>3.48</td>\n",
|
||||
" <td>69.60</td>\n",
|
||||
" <td>0.76</td>\n",
|
||||
" <td>26.148</td>\n",
|
||||
" <td>27.578</td>\n",
|
||||
" <td>29.31</td>\n",
|
||||
" <td>55.99</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>2720084708</td>\n",
|
||||
" <td>3.47</td>\n",
|
||||
" <td>66.71</td>\n",
|
||||
" <td>0.76</td>\n",
|
||||
" <td>29.055</td>\n",
|
||||
" <td>26.338</td>\n",
|
||||
" <td>28.58</td>\n",
|
||||
" <td>53.87</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>2720062721</td>\n",
|
||||
" <td>3.87</td>\n",
|
||||
" <td>68.78</td>\n",
|
||||
" <td>0.80</td>\n",
|
||||
" <td>26.542</td>\n",
|
||||
" <td>27.280</td>\n",
|
||||
" <td>29.97</td>\n",
|
||||
" <td>54.78</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>223</th>\n",
|
||||
" <td>2720030490</td>\n",
|
||||
" <td>4.12</td>\n",
|
||||
" <td>68.85</td>\n",
|
||||
" <td>0.97</td>\n",
|
||||
" <td>26.055</td>\n",
|
||||
" <td>27.864</td>\n",
|
||||
" <td>32.94</td>\n",
|
||||
" <td>51.89</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>224</th>\n",
|
||||
" <td>2720028633</td>\n",
|
||||
" <td>3.97</td>\n",
|
||||
" <td>67.04</td>\n",
|
||||
" <td>0.94</td>\n",
|
||||
" <td>28.043</td>\n",
|
||||
" <td>27.368</td>\n",
|
||||
" <td>31.88</td>\n",
|
||||
" <td>51.38</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>225</th>\n",
|
||||
" <td>2720028634</td>\n",
|
||||
" <td>4.12</td>\n",
|
||||
" <td>68.42</td>\n",
|
||||
" <td>0.96</td>\n",
|
||||
" <td>26.493</td>\n",
|
||||
" <td>27.886</td>\n",
|
||||
" <td>33.16</td>\n",
|
||||
" <td>52.00</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>226</th>\n",
|
||||
" <td>2720017683</td>\n",
|
||||
" <td>3.88</td>\n",
|
||||
" <td>67.42</td>\n",
|
||||
" <td>0.94</td>\n",
|
||||
" <td>27.760</td>\n",
|
||||
" <td>26.616</td>\n",
|
||||
" <td>31.65</td>\n",
|
||||
" <td>50.56</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>227</th>\n",
|
||||
" <td>2720017678</td>\n",
|
||||
" <td>3.81</td>\n",
|
||||
" <td>66.74</td>\n",
|
||||
" <td>0.92</td>\n",
|
||||
" <td>28.530</td>\n",
|
||||
" <td>26.688</td>\n",
|
||||
" <td>31.02</td>\n",
|
||||
" <td>50.82</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>228 rows × 8 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Unnamed: 0_level_0 氢 碳 氮 氧 弹筒发热量 挥发分 固定炭\n",
|
||||
" 化验编号 Had Cad Nad Oad Qb,ad Vad Fcad\n",
|
||||
" Unnamed: 0_level_2 (%) (%) (%) (%) MJ/kg (%) (%)\n",
|
||||
"0 2720110529 3.93 70.18 0.81 25.079 27.820 32.06 55.68\n",
|
||||
"1 2720096883 3.78 68.93 0.77 26.512 27.404 29.96 54.71\n",
|
||||
"2 2720109084 3.48 69.60 0.76 26.148 27.578 29.31 55.99\n",
|
||||
"3 2720084708 3.47 66.71 0.76 29.055 26.338 28.58 53.87\n",
|
||||
"4 2720062721 3.87 68.78 0.80 26.542 27.280 29.97 54.78\n",
|
||||
".. ... ... ... ... ... ... ... ...\n",
|
||||
"223 2720030490 4.12 68.85 0.97 26.055 27.864 32.94 51.89\n",
|
||||
"224 2720028633 3.97 67.04 0.94 28.043 27.368 31.88 51.38\n",
|
||||
"225 2720028634 4.12 68.42 0.96 26.493 27.886 33.16 52.00\n",
|
||||
"226 2720017683 3.88 67.42 0.94 27.760 26.616 31.65 50.56\n",
|
||||
"227 2720017678 3.81 66.74 0.92 28.530 26.688 31.02 50.82\n",
|
||||
"\n",
|
||||
"[228 rows x 8 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"data_0102 = pd.read_excel('./data/20240102/20240102.xlsx', header=[0,1,2])\n",
|
||||
"data_0102"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"id": "f72789a6-f3fa-4ab1-8b62-999413958608",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"['化验编号',\n",
|
||||
" '氢Had(%)',\n",
|
||||
" '碳Cad(%)',\n",
|
||||
" '氮Nad(%)',\n",
|
||||
" '氧Oad(%)',\n",
|
||||
" '弹筒发热量Qb,adMJ/kg',\n",
|
||||
" '挥发分Vad(%)',\n",
|
||||
" '固定炭Fcad(%)']"
|
||||
]
|
||||
},
|
||||
"execution_count": 10,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"cols = [''.join([y for y in x if 'Unnamed' not in y]) for x in data_0102.columns]\n",
|
||||
"cols"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"id": "6ffb1989-3f45-4d1c-84c9-59b1045b7d9e",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"data_0102.columns = cols"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 27,
|
||||
"id": "9c708cc0-9f1b-4669-a350-6d24cb720794",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import xgboost as xgb"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"id": "103349e1-aa4a-427a-a489-9ab28787088b",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"['氢Had(%)', '碳Cad(%)', '氮Nad(%)', '氧Oad(%)', '弹筒发热量Qb,adMJ/kg']"
|
||||
]
|
||||
},
|
||||
"execution_count": 16,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"feature_cols = cols[1:6]\n",
|
||||
"feature_cols"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 44,
|
||||
"id": "839e45dc-e9c8-4956-950b-035687469c81",
|
||||
"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>化验编号</th>\n",
|
||||
" <th>氢Had(%)</th>\n",
|
||||
" <th>碳Cad(%)</th>\n",
|
||||
" <th>氮Nad(%)</th>\n",
|
||||
" <th>氧Oad(%)</th>\n",
|
||||
" <th>弹筒发热量Qb,adMJ/kg</th>\n",
|
||||
" <th>挥发分Vad(%)</th>\n",
|
||||
" <th>固定炭Fcad(%)</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>2720110529</td>\n",
|
||||
" <td>3.93</td>\n",
|
||||
" <td>70.18</td>\n",
|
||||
" <td>0.81</td>\n",
|
||||
" <td>25.079</td>\n",
|
||||
" <td>27.820</td>\n",
|
||||
" <td>32.06</td>\n",
|
||||
" <td>55.68</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>2720096883</td>\n",
|
||||
" <td>3.78</td>\n",
|
||||
" <td>68.93</td>\n",
|
||||
" <td>0.77</td>\n",
|
||||
" <td>26.512</td>\n",
|
||||
" <td>27.404</td>\n",
|
||||
" <td>29.96</td>\n",
|
||||
" <td>54.71</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>2720109084</td>\n",
|
||||
" <td>3.48</td>\n",
|
||||
" <td>69.60</td>\n",
|
||||
" <td>0.76</td>\n",
|
||||
" <td>26.148</td>\n",
|
||||
" <td>27.578</td>\n",
|
||||
" <td>29.31</td>\n",
|
||||
" <td>55.99</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>2720084708</td>\n",
|
||||
" <td>3.47</td>\n",
|
||||
" <td>66.71</td>\n",
|
||||
" <td>0.76</td>\n",
|
||||
" <td>29.055</td>\n",
|
||||
" <td>26.338</td>\n",
|
||||
" <td>28.58</td>\n",
|
||||
" <td>53.87</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>2720062721</td>\n",
|
||||
" <td>3.87</td>\n",
|
||||
" <td>68.78</td>\n",
|
||||
" <td>0.80</td>\n",
|
||||
" <td>26.542</td>\n",
|
||||
" <td>27.280</td>\n",
|
||||
" <td>29.97</td>\n",
|
||||
" <td>54.78</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" 化验编号 氢Had(%) 碳Cad(%) 氮Nad(%) 氧Oad(%) 弹筒发热量Qb,adMJ/kg 挥发分Vad(%) \\\n",
|
||||
"0 2720110529 3.93 70.18 0.81 25.079 27.820 32.06 \n",
|
||||
"1 2720096883 3.78 68.93 0.77 26.512 27.404 29.96 \n",
|
||||
"2 2720109084 3.48 69.60 0.76 26.148 27.578 29.31 \n",
|
||||
"3 2720084708 3.47 66.71 0.76 29.055 26.338 28.58 \n",
|
||||
"4 2720062721 3.87 68.78 0.80 26.542 27.280 29.97 \n",
|
||||
"\n",
|
||||
" 固定炭Fcad(%) \n",
|
||||
"0 55.68 \n",
|
||||
"1 54.71 \n",
|
||||
"2 55.99 \n",
|
||||
"3 53.87 \n",
|
||||
"4 54.78 "
|
||||
]
|
||||
},
|
||||
"execution_count": 44,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"train_data = data_0102.copy()\n",
|
||||
"train_data.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 19,
|
||||
"id": "24233d12-9468-49b8-a371-0c6c508c387e",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import seaborn as sns"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 21,
|
||||
"id": "54cd27a6-1a8a-47c0-93d9-c948960a7842",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 23,
|
||||
"id": "bba14f71-9d69-4c82-b6bc-b9b74c725b25",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"train_data.reset_index(drop=True, inplace=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 24,
|
||||
"id": "e3a9ad55-0132-430f-ac57-c2e7f8e8590a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from sklearn.metrics import mean_absolute_error, mean_squared_error, mean_absolute_percentage_error, r2_score"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 40,
|
||||
"id": "013c6a58-65f6-48e9-8d7f-b56c87de5b11",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"param_xgb = {\"silent\": True,\n",
|
||||
" \"obj\": 'reg:linear',\n",
|
||||
" \"subsample\": 1,\n",
|
||||
" \"max_depth\": 15,\n",
|
||||
" \"eta\": 0.3,\n",
|
||||
" \"gamma\": 0,\n",
|
||||
" \"lambda\": 1,\n",
|
||||
" \"alpha\": 0,\n",
|
||||
" \"colsample_bytree\": 0.9,}\n",
|
||||
"num_round = 1000"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 41,
|
||||
"id": "086f1901-8388-47e9-ae7c-1b2709bc1e22",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from sklearn.model_selection import KFold, train_test_split\n",
|
||||
"kf = KFold(n_splits=10, shuffle=True, random_state=42)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 43,
|
||||
"id": "fb7b06af-84bc-483c-b086-7826d7befc9c",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"MSE: 1.9436, RMSE: 1.3941, MAE: 1.1861, MAPE: 3.94 %, R_2: 0.6095\n",
|
||||
"MSE: 1.8735, RMSE: 1.3688, MAE: 1.132, MAPE: 3.77 %, R_2: 0.495\n",
|
||||
"MSE: 2.0587, RMSE: 1.4348, MAE: 1.0706, MAPE: 4.08 %, R_2: 0.7862\n",
|
||||
"MSE: 1.9298, RMSE: 1.3892, MAE: 1.1469, MAPE: 3.84 %, R_2: 0.5332\n",
|
||||
"MSE: 1.4583, RMSE: 1.2076, MAE: 1.097, MAPE: 3.67 %, R_2: 0.6894\n",
|
||||
"MSE: 2.0822, RMSE: 1.443, MAE: 1.1645, MAPE: 3.88 %, R_2: 0.5975\n",
|
||||
"MSE: 1.3521, RMSE: 1.1628, MAE: 0.9905, MAPE: 3.37 %, R_2: 0.7479\n",
|
||||
"MSE: 1.4057, RMSE: 1.1856, MAE: 0.9998, MAPE: 3.3 %, R_2: 0.2946\n",
|
||||
"MSE: 2.2274, RMSE: 1.4925, MAE: 1.2638, MAPE: 4.19 %, R_2: 0.6785\n",
|
||||
"MSE: 1.4866, RMSE: 1.2193, MAE: 1.0797, MAPE: 3.67 %, R_2: 0.7261\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"MSE 1.781792\n",
|
||||
"RMSE 1.329760\n",
|
||||
"MAE 1.113084\n",
|
||||
"MAPE 0.037719\n",
|
||||
"R_2 0.615796\n",
|
||||
"dtype: float64"
|
||||
]
|
||||
},
|
||||
"execution_count": 43,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"eva_list = list()\n",
|
||||
"for (train_index, test_index) in kf.split(train_data):\n",
|
||||
" train = train_data.loc[train_index]\n",
|
||||
" valid = train_data.loc[test_index]\n",
|
||||
" X_train, Y_train = train[feature_cols], np.log1p(train['挥发分Vad(%)'])\n",
|
||||
" X_valid, Y_valid = valid[feature_cols], np.log1p(valid['挥发分Vad(%)'])\n",
|
||||
" dtrain = xgb.DMatrix(X_train, Y_train)\n",
|
||||
" dvalid = xgb.DMatrix(X_valid, Y_valid)\n",
|
||||
" watchlist = [(dvalid, 'eval')]\n",
|
||||
" gb_model = xgb.train(params_xgb, dtrain, num_boost_round, evals=watchlist,\n",
|
||||
" early_stopping_rounds=50, verbose_eval=False)\n",
|
||||
" y_pred = np.expm1(gb_model.predict(xgb.DMatrix(X_valid)))\n",
|
||||
" y_true = np.expm1(Y_valid.values)\n",
|
||||
" MSE = mean_squared_error(y_true, y_pred)\n",
|
||||
" RMSE = np.sqrt(mean_squared_error(y_true, y_pred))\n",
|
||||
" MAE = mean_absolute_error(y_true, y_pred)\n",
|
||||
" MAPE = mean_absolute_percentage_error(y_true, y_pred)\n",
|
||||
" R_2 = r2_score(y_true, y_pred)\n",
|
||||
" print('MSE:', round(MSE, 4), end=', ')\n",
|
||||
" print('RMSE:', round(RMSE, 4), end=', ')\n",
|
||||
" print('MAE:', round(MAE, 4), end=', ')\n",
|
||||
" print('MAPE:', round(MAPE*100, 2), '%', end=', ')\n",
|
||||
" print('R_2:', round(R_2, 4)) #R方为负就说明拟合效果比平均值差\n",
|
||||
" eva_list.append([MSE, RMSE, MAE, MAPE, R_2])\n",
|
||||
"data_df = pd.DataFrame.from_records(eva_list, columns=['MSE', 'RMSE', 'MAE', 'MAPE', 'R_2'])\n",
|
||||
"data_df.mean()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 48,
|
||||
"id": "90841cb7-4f28-4a33-93ac-93df69f1a5a1",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"MSE: 4.6724, RMSE: 2.1616, MAE: 1.7297, MAPE: 3.42 %, R2: 0.8346\n",
|
||||
"MSE: 3.0512, RMSE: 1.7468, MAE: 1.4485, MAPE: 2.62 %, R2: 0.8011\n",
|
||||
"MSE: 7.6672, RMSE: 2.769, MAE: 1.951, MAPE: 4.56 %, R2: 0.8856\n",
|
||||
"MSE: 4.0334, RMSE: 2.0083, MAE: 1.487, MAPE: 2.77 %, R2: 0.8216\n",
|
||||
"MSE: 2.6382, RMSE: 1.6243, MAE: 1.1551, MAPE: 2.12 %, R2: 0.846\n",
|
||||
"MSE: 5.8097, RMSE: 2.4103, MAE: 1.8683, MAPE: 3.8 %, R2: 0.83\n",
|
||||
"MSE: 2.3446, RMSE: 1.5312, MAE: 1.1294, MAPE: 2.28 %, R2: 0.9069\n",
|
||||
"MSE: 3.0069, RMSE: 1.734, MAE: 1.3782, MAPE: 2.46 %, R2: 0.6541\n",
|
||||
"MSE: 4.1652, RMSE: 2.0409, MAE: 1.5685, MAPE: 3.2 %, R2: 0.859\n",
|
||||
"MSE: 4.2023, RMSE: 2.05, MAE: 1.6284, MAPE: 3.2 %, R2: 0.869\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"MSE 4.159107\n",
|
||||
"RMSE 2.007631\n",
|
||||
"MAE 1.534427\n",
|
||||
"MAPE 0.030424\n",
|
||||
"R2 0.830794\n",
|
||||
"dtype: float64"
|
||||
]
|
||||
},
|
||||
"execution_count": 48,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"eva_list = list()\n",
|
||||
"for (train_index, test_index) in kf.split(train_data):\n",
|
||||
" train = train_data.loc[train_index]\n",
|
||||
" valid = train_data.loc[test_index]\n",
|
||||
" X_train, Y_train = train[feature_cols], np.log1p(train['固定炭Fcad(%)'])\n",
|
||||
" X_valid, Y_valid = valid[feature_cols], np.log1p(valid['固定炭Fcad(%)'])\n",
|
||||
" dtrain = xgb.DMatrix(X_train, Y_train)\n",
|
||||
" dvalid = xgb.DMatrix(X_valid, Y_valid)\n",
|
||||
" watchlist = [(dvalid, 'eval')]\n",
|
||||
" gb_model = xgb.train(params_xgb, dtrain, num_boost_round, evals=watchlist,\n",
|
||||
" early_stopping_rounds=50, verbose_eval=False)\n",
|
||||
" y_pred = np.expm1(gb_model.predict(xgb.DMatrix(X_valid)))\n",
|
||||
" y_true = np.expm1(Y_valid.values)\n",
|
||||
" MSE = mean_squared_error(y_true, y_pred)\n",
|
||||
" RMSE = np.sqrt(mean_squared_error(y_true, y_pred))\n",
|
||||
" MAE = mean_absolute_error(y_true, y_pred)\n",
|
||||
" MAPE = mean_absolute_percentage_error(y_true, y_pred)\n",
|
||||
" R_2 = r2_score(y_true, y_pred)\n",
|
||||
" print('MSE:', round(MSE, 4), end=', ')\n",
|
||||
" print('RMSE:', round(RMSE, 4), end=', ')\n",
|
||||
" print('MAE:', round(MAE, 4), end=', ')\n",
|
||||
" print('MAPE:', round(MAPE*100, 2), '%', end=', ')\n",
|
||||
" print('R2:', round(R_2, 4)) #R方为负就说明拟合效果比平均值差\n",
|
||||
" eva_list.append([MSE, RMSE, MAE, MAPE, R_2])\n",
|
||||
"data_df = pd.DataFrame.from_records(eva_list, columns=['MSE', 'RMSE', 'MAE', 'MAPE', 'R2'])\n",
|
||||
"data_df.mean()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 67,
|
||||
"id": "aa67bc97-1258-44bb-9dae-14ace1661ff6",
|
||||
"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",
|
||||
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||||
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|
||||
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||||
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|
||||
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|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>MSE</th>\n",
|
||||
" <th>RMSE</th>\n",
|
||||
" <th>MAE</th>\n",
|
||||
" <th>MAPE</th>\n",
|
||||
" <th>R2</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>十折交叉验证均值</th>\n",
|
||||
" <td>4.159107</td>\n",
|
||||
" <td>2.007631</td>\n",
|
||||
" <td>1.534427</td>\n",
|
||||
" <td>0.030424</td>\n",
|
||||
" <td>0.830794</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" MSE RMSE MAE MAPE R2\n",
|
||||
"十折交叉验证均值 4.159107 2.007631 1.534427 0.030424 0.830794"
|
||||
]
|
||||
},
|
||||
"execution_count": 67,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
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|
||||
],
|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"metadata": {},
|
||||
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|
||||
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|
||||
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|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
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|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
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|
||||
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|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
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"pygments_lexer": "ipython3",
|
||||
"version": "3.8.16"
|
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}
|
||||
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|
||||
"nbformat": 4,
|
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"nbformat_minor": 5
|
||||
}
|
||||
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|
@ -0,0 +1,150 @@
|
|||
热处理条件-热处理次数,热处理条件-是否是中温停留,第一次热处理-温度,第一次热处理-升温速率,第一次热处理-保留时间,第二次热处理-温度,第二次热处理-升温速率·,第二次热处理-保留时间,共碳化-是否是共碳化物质,共碳化-共碳化物质/沥青,模板剂-与沥青比例,活化剂-是否KOH活化,活化剂-比例,混合方式-混合方式,碳材料结构特征-比表面积,碳材料结构特征-总孔体积,碳材料结构特征-微孔体积,碳材料结构特征-平均孔径,共碳化-种类_2-甲基咪唑,共碳化-种类_三聚氰胺,共碳化-种类_尿素,共碳化-种类_硫酸铵,共碳化-种类_聚磷酸铵,模板剂-模板剂制备方式_无,模板剂-模板剂制备方式_溶液合成,模板剂-模板剂制备方式_热分解,模板剂-模板剂制备方式_直接购买,模板剂-模板剂制备方式_自己合成,模板剂-种类_Al2O3,模板剂-种类_TiO2,模板剂-种类_α-Fe2O3,模板剂-种类_γ-Fe2O3,模板剂-种类_二氧化硅,模板剂-种类_氢氧化镁,模板剂-种类_氧化钙,模板剂-种类_氧化锌,模板剂-种类_氧化镁,模板剂-种类_氯化钠,模板剂-种类_氯化钾,模板剂-种类_碱式碳酸镁,模板剂-种类_碳酸钙,模板剂-种类_纤维素
|
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1,0,500,3,1,600.0,5.0,1.0,1,5.0,,1,4.0,1,1181.0,0.638,0.586,2.162,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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||||
1,0,500,3,1,700.0,5.0,1.0,1,5.0,,1,4.0,1,1849.0,0.856,0.784,1.85,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,3,1,800.0,5.0,1.0,1,5.0,,1,4.0,1,2236.0,1.167,1.043,2.088,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,600,5,1,,,,0,,,1,4.0,1,692.0,0.399,0.353,2.303,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,1,800,5,1,,,,0,,6.0,1,2.0,1,2438.0,1.49,0.8,2.45,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0
|
||||
0,1,800,5,1,,,,0,,6.0,1,4.0,1,2619.0,1.65,0.91,2.54,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0
|
||||
0,1,800,5,1,,,,0,,6.0,1,6.0,1,3145.0,1.68,1.13,2.3,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0
|
||||
0,1,900,5,1,,,,0,,6.0,1,6.0,1,3079.0,2.23,1.25,2.9,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0
|
||||
0,0,600,10,1,,,,0,,,1,2.0,1,907.0,0.5,0.4,2.12,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,10,1,,,,0,,,1,2.0,1,1382.0,0.7,0.5,1.96,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,10,1,,,,0,,,1,2.0,1,1993.0,0.7,0.8,1.96,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,10,1,,,,0,,,1,1.0,1,642.0,0.3,0.2,1.93,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,10,1,,,,0,,,1,3.0,1,1673.0,0.8,0.7,2.02,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,10,1,,,,0,,,1,4.0,1,2342.0,1.2,0.9,2.1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,900,10,1,700.0,10.0,1.0,0,,1.0,1,1.0,1,964.0,0.66,0.36,2.73,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,900,10,1,700.0,10.0,1.0,0,,1.0,1,2.0,1,1663.0,1.13,0.65,2.72,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,900,10,1,700.0,10.0,1.0,0,,1.0,1,3.0,1,2003.0,1.29,0.84,2.57,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,900,10,1,700.0,10.0,1.0,0,,1.0,1,4.0,1,1013.0,0.82,0.41,3.25,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,2.0,0,1012.0,0.37,0.28,2.68,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,2.0,1,837.0,0.34,0.23,2.79,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,1.0,0,755.0,0.33,0.19,2.81,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,5,1,800.0,5.0,2.0,0,,1.0,0,0.0,0,528.0,0.74,0.03,6.55,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
1,0,500,5,1,800.0,5.0,2.0,0,,1.0,1,1.0,0,1604.0,1.15,0.11,4.93,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
1,0,500,5,1,800.0,5.0,2.0,0,,1.0,1,2.0,0,1455.0,0.91,0.18,5.04,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,0,,1.0,1,5.0,1,3060.0,1.96,0.14,2.15,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0
|
||||
0,0,800,5,1,,,,0,,2.5,1,5.0,1,2139.0,1.12,0.44,2.09,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0
|
||||
0,0,800,5,1,,,,0,,4.0,1,5.0,1,1843.0,0.96,0.42,2.07,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0
|
||||
0,0,850,5,1,,,,0,,2.5,1,5.0,1,2850.0,1.58,0.16,2.11,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0
|
||||
0,0,600,5,1,,,,0,,5.0,1,7.5,1,938.0,1.05,0.46,4.49,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,700,5,1,,,,0,,5.0,1,7.5,1,2003.0,1.98,0.93,3.96,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,0,,5.0,1,7.5,1,2480.0,2.52,1.06,4.06,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,0.25,5.0,1,7.5,1,2574.0,2.57,1.09,3.99,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,1.0,5.0,1,7.5,1,1519.0,2.14,0.68,5.64,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,2.0,5.0,1,7.5,1,1510.0,2.15,0.71,5.68,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,0.25,5.0,1,7.5,1,2589.0,2.25,1.12,3.47,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,1.0,5.0,1,7.5,1,2969.0,2.52,1.21,3.4,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,2.0,5.0,1,7.5,1,2706.0,2.85,1.17,4.21,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,910,5,1,,,,0,,,1,0.43,1,274.0,0.12,0.1,1.68,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,910,5,1,,,,0,,,1,0.86,1,1213.0,0.48,0.47,1.58,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,910,5,1,,,,0,,,1,1.43,1,1522.0,0.65,0.62,1.7,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,910,5,1,,,,0,,,1,2.0,1,1760.0,0.84,0.81,1.91,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,850,5,3,,,,0,,0.0,1,4.0,1,1760.0,0.9533,0.735,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0
|
||||
0,0,850,5,3,,,,0,,0.5,1,4.0,1,2536.0,1.398,0.912,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0
|
||||
0,0,850,5,3,,,,0,,1.0,1,4.0,1,1387.0,0.7526,0.611,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0
|
||||
0,0,850,5,3,,,,0,,2.0,1,4.0,1,2487.0,1.324,1.007,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0
|
||||
1,0,500,5,2,900.0,5.0,1.5,0,,0.5,1,3.0,1,1468.9,0.8593,0.2326,2.34,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,5,2,700.0,5.0,1.5,0,,1.0,1,3.0,1,2071.6,1.1639,0.5631,2.25,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,5,2,900.0,5.0,1.5,0,,0.334,1,3.0,1,935.7,0.5851,0.2401,2.5,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,5,2,700.0,5.0,1.5,0,,0.5,1,3.0,1,1450.4,0.8558,0.4953,2.36,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,5,2,800.0,5.0,1.5,0,,1.0,1,3.0,1,1513.2,1.0132,0.5912,2.33,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,1,800,5,1,,,,0,,6.0,1,2.0,1,1947.0,1.16,0.76,2.39,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,1,800,5,1,,,,0,,4.0,1,1.43,1,1858.0,1.1,0.76,2.39,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
1,0,500,5,1,700.0,5.0,1.0,0,,10.0,0,0.0,0,289.0,0.55,0.04,6.0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0
|
||||
1,0,500,5,1,600.0,5.0,1.0,0,,10.0,1,1.0,0,1470.0,0.8,0.48,6.0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0
|
||||
1,0,500,5,1,700.0,5.0,1.0,0,,10.0,1,1.0,0,1777.0,0.94,0.52,5.7,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0
|
||||
1,0,500,5,1,800.0,5.0,1.0,0,,10.0,1,1.0,0,1927.0,0.98,0.53,4.5,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0
|
||||
0,0,800,5,2,,,,0,,0.05,1,4.0,1,2851.0,1.29,0.98,1.81,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
|
||||
0,0,800,5,2,,,,0,,0.1,1,4.0,1,3305.0,1.66,0.88,2.01,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
|
||||
0,0,800,5,2,,,,0,,0.3,1,4.0,1,2066.0,1.02,0.54,1.97,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
|
||||
0,0,800,5,2,,,,0,,0.1,1,3.0,1,2511.0,1.13,0.85,1.8,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
|
||||
0,0,800,5,2,,,,0,,0.1,1,5.0,1,2117.0,0.98,0.65,1.85,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
|
||||
1,0,400,5,2,850.0,5.0,2.0,0,,0.25,1,4.0,0,413.0,0.3218,0.1211,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0
|
||||
1,0,400,5,2,850.0,5.0,2.0,0,,0.334,1,4.0,0,1369.0,0.8037,0.3361,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0
|
||||
1,0,400,5,2,850.0,5.0,2.0,0,,0.5,1,4.0,0,1481.0,0.8928,0.0848,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0
|
||||
1,0,400,5,2,850.0,5.0,2.0,0,,1.0,1,4.0,0,1338.0,0.9356,0.4083,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,0.0,1,0.862,1,1006.0,0.48,0.46,1.91,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,2.0,1,0.857,1,1255.0,0.72,0.56,2.3,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,4.0,1,1.43,1,1330.0,1.35,0.46,4.05,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,2.0,1,0.857,1,1234.0,0.93,0.45,3.01,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,1.333,1,0.667,1,1157.0,0.69,0.43,2.39,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,0.5,1,0.429,1,761.0,0.34,0.29,1.78,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,2.0,0,0.0,1,348.0,0.58,0.1,6.61,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,12,1,,,,0,,,0,0.0,1,14.0,0.009,0.002,2.614,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,600,12,1,,,,0,,,1,2.0,1,837.0,0.362,0.321,1.731,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,12,1,,,,0,,,1,2.0,1,901.0,0.414,0.347,1.838,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,12,1,,,,0,,,1,2.0,1,1153.0,0.534,0.453,1.854,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,12,1,,,,0,,,1,2.0,1,1088.0,0.486,0.431,1.785,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,12,1,,,,0,,,0,0.0,1,8.0,0.027,0.003,3.413,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,12,1,,,,0,,0.5,0,0.0,1,23.0,0.024,0.004,2.769,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0
|
||||
0,0,900,12,1,,,,0,,0.5,1,2.0,1,1517.0,0.748,0.623,1.973,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0
|
||||
0,0,900,12,1,,,,0,,1.0,1,2.0,1,1855.0,0.945,0.767,2.038,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0
|
||||
0,0,900,12,1,,,,0,,1.5,1,2.0,1,1288.0,0.626,0.505,1.945,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0
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||||
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热处理条件-热处理次数,热处理条件-是否是中温停留,第一次热处理-温度,第一次热处理-升温速率,第一次热处理-保留时间,第二次热处理-温度,第二次热处理-升温速率·,第二次热处理-保留时间,共碳化-是否是共碳化物质,共碳化-共碳化物质/沥青,模板剂-与沥青比例,活化剂-是否KOH活化,活化剂-比例,混合方式-混合方式,碳材料结构特征-比表面积,碳材料结构特征-总孔体积,碳材料结构特征-微孔体积,碳材料结构特征-平均孔径,共碳化-种类_2-甲基咪唑,共碳化-种类_三聚氰胺,共碳化-种类_尿素,共碳化-种类_硫酸铵,共碳化-种类_聚磷酸铵,模板剂-模板剂制备方式_无,模板剂-模板剂制备方式_溶液合成,模板剂-模板剂制备方式_热分解,模板剂-模板剂制备方式_直接购买,模板剂-模板剂制备方式_自己合成,模板剂-种类_Al2O3,模板剂-种类_TiO2,模板剂-种类_α-Fe2O3,模板剂-种类_γ-Fe2O3,模板剂-种类_二氧化硅,模板剂-种类_氢氧化镁,模板剂-种类_氧化钙,模板剂-种类_氧化锌,模板剂-种类_氧化镁,模板剂-种类_氯化钠,模板剂-种类_氯化钾,模板剂-种类_碱式碳酸镁,模板剂-种类_碳酸钙,模板剂-种类_纤维素
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||||
0,0,600,10,1,,,,0,,,1,2.0,1,907.0,0.5,0.4,2.12,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,10,1,,,,0,,,1,2.0,1,1382.0,0.7,0.5,1.96,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,10,1,,,,0,,,1,2.0,1,1993.0,0.7,0.8,1.96,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,10,1,,,,0,,,1,1.0,1,642.0,0.3,0.2,1.93,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,10,1,,,,0,,,1,3.0,1,1673.0,0.8,0.7,2.02,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,10,1,,,,0,,,1,4.0,1,2342.0,1.2,0.9,2.1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,900,10,1,700.0,10.0,1.0,0,,1.0,1,1.0,1,964.0,0.66,0.36,2.73,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,900,10,1,700.0,10.0,1.0,0,,1.0,1,2.0,1,1663.0,1.13,0.65,2.72,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,900,10,1,700.0,10.0,1.0,0,,1.0,1,3.0,1,2003.0,1.29,0.84,2.57,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,900,10,1,700.0,10.0,1.0,0,,1.0,1,4.0,1,1013.0,0.82,0.41,3.25,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,2.0,0,1012.0,0.37,0.28,2.68,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,2.0,1,837.0,0.34,0.23,2.79,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,1.0,0,755.0,0.33,0.19,2.81,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,5,1,800.0,5.0,2.0,0,,1.0,0,0.0,0,528.0,0.74,0.03,6.55,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
1,0,500,5,1,800.0,5.0,2.0,0,,1.0,1,1.0,0,1604.0,1.15,0.11,4.93,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
1,0,500,5,1,800.0,5.0,2.0,0,,1.0,1,2.0,0,1455.0,0.91,0.18,5.04,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,0,,1.0,1,5.0,1,3060.0,1.96,0.14,2.15,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0
|
||||
0,0,800,5,1,,,,0,,2.5,1,5.0,1,2139.0,1.12,0.44,2.09,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0
|
||||
0,0,800,5,1,,,,0,,4.0,1,5.0,1,1843.0,0.96,0.42,2.07,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0
|
||||
0,0,850,5,1,,,,0,,2.5,1,5.0,1,2850.0,1.58,0.16,2.11,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0
|
||||
0,0,600,5,1,,,,0,,5.0,1,7.5,1,938.0,1.05,0.46,4.49,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,700,5,1,,,,0,,5.0,1,7.5,1,2003.0,1.98,0.93,3.96,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,0,,5.0,1,7.5,1,2480.0,2.52,1.06,4.06,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,0.25,5.0,1,7.5,1,2574.0,2.57,1.09,3.99,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,1.0,5.0,1,7.5,1,1519.0,2.14,0.68,5.64,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,2.0,5.0,1,7.5,1,1510.0,2.15,0.71,5.68,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,0.25,5.0,1,7.5,1,2589.0,2.25,1.12,3.47,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,1.0,5.0,1,7.5,1,2969.0,2.52,1.21,3.4,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,800,5,1,,,,1,2.0,5.0,1,7.5,1,2706.0,2.85,1.17,4.21,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,910,5,1,,,,0,,,1,0.43,1,274.0,0.12,0.1,1.68,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,910,5,1,,,,0,,,1,0.86,1,1213.0,0.48,0.47,1.58,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,910,5,1,,,,0,,,1,1.43,1,1522.0,0.65,0.62,1.7,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,910,5,1,,,,0,,,1,2.0,1,1760.0,0.84,0.81,1.91,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,850,5,3,,,,0,,0.0,1,4.0,1,1760.0,0.9533,0.735,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0
|
||||
0,0,850,5,3,,,,0,,0.5,1,4.0,1,2536.0,1.398,0.912,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0
|
||||
0,0,850,5,3,,,,0,,1.0,1,4.0,1,1387.0,0.7526,0.611,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0
|
||||
0,0,850,5,3,,,,0,,2.0,1,4.0,1,2487.0,1.324,1.007,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0
|
||||
1,0,500,5,2,900.0,5.0,1.5,0,,0.5,1,3.0,1,1468.9,0.8593,0.2326,2.34,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,5,2,700.0,5.0,1.5,0,,1.0,1,3.0,1,2071.6,1.1639,0.5631,2.25,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,5,2,900.0,5.0,1.5,0,,0.334,1,3.0,1,935.7,0.5851,0.2401,2.5,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,5,2,700.0,5.0,1.5,0,,0.5,1,3.0,1,1450.4,0.8558,0.4953,2.36,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
1,0,500,5,2,800.0,5.0,1.5,0,,1.0,1,3.0,1,1513.2,1.0132,0.5912,2.33,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,1,800,5,1,,,,0,,6.0,1,2.0,1,1947.0,1.16,0.76,2.39,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,1,800,5,1,,,,0,,4.0,1,1.43,1,1858.0,1.1,0.76,2.39,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
1,0,500,5,1,700.0,5.0,1.0,0,,10.0,0,0.0,0,289.0,0.55,0.04,6.0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0
|
||||
1,0,500,5,1,600.0,5.0,1.0,0,,10.0,1,1.0,0,1470.0,0.8,0.48,6.0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0
|
||||
1,0,500,5,1,700.0,5.0,1.0,0,,10.0,1,1.0,0,1777.0,0.94,0.52,5.7,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0
|
||||
1,0,500,5,1,800.0,5.0,1.0,0,,10.0,1,1.0,0,1927.0,0.98,0.53,4.5,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0
|
||||
0,0,800,5,2,,,,0,,0.05,1,4.0,1,2851.0,1.29,0.98,1.81,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
|
||||
0,0,800,5,2,,,,0,,0.1,1,4.0,1,3305.0,1.66,0.88,2.01,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
|
||||
0,0,800,5,2,,,,0,,0.3,1,4.0,1,2066.0,1.02,0.54,1.97,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
|
||||
0,0,800,5,2,,,,0,,0.1,1,3.0,1,2511.0,1.13,0.85,1.8,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
|
||||
0,0,800,5,2,,,,0,,0.1,1,5.0,1,2117.0,0.98,0.65,1.85,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
|
||||
1,0,400,5,2,850.0,5.0,2.0,0,,0.25,1,4.0,0,413.0,0.3218,0.1211,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0
|
||||
1,0,400,5,2,850.0,5.0,2.0,0,,0.334,1,4.0,0,1369.0,0.8037,0.3361,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0
|
||||
1,0,400,5,2,850.0,5.0,2.0,0,,0.5,1,4.0,0,1481.0,0.8928,0.0848,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0
|
||||
1,0,400,5,2,850.0,5.0,2.0,0,,1.0,1,4.0,0,1338.0,0.9356,0.4083,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,0.0,1,0.862,1,1006.0,0.48,0.46,1.91,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,2.0,1,0.857,1,1255.0,0.72,0.56,2.3,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,4.0,1,1.43,1,1330.0,1.35,0.46,4.05,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,2.0,1,0.857,1,1234.0,0.93,0.45,3.01,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,1.333,1,0.667,1,1157.0,0.69,0.43,2.39,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,0.5,1,0.429,1,761.0,0.34,0.29,1.78,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,5,1,,,,0,,2.0,0,0.0,1,348.0,0.58,0.1,6.61,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,12,1,,,,0,,,0,0.0,1,14.0,0.009,0.002,2.614,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,600,12,1,,,,0,,,1,2.0,1,837.0,0.362,0.321,1.731,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,700,12,1,,,,0,,,1,2.0,1,901.0,0.414,0.347,1.838,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,12,1,,,,0,,,1,2.0,1,1153.0,0.534,0.453,1.854,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,12,1,,,,0,,,1,2.0,1,1088.0,0.486,0.431,1.785,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,12,1,,,,0,,,0,0.0,1,8.0,0.027,0.003,3.413,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,900,12,1,,,,0,,0.5,0,0.0,1,23.0,0.024,0.004,2.769,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0
|
||||
0,0,900,12,1,,,,0,,0.5,1,2.0,1,1517.0,0.748,0.623,1.973,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0
|
||||
0,0,900,12,1,,,,0,,1.0,1,2.0,1,1855.0,0.945,0.767,2.038,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0
|
||||
0,0,900,12,1,,,,0,,1.5,1,2.0,1,1288.0,0.626,0.505,1.945,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0
|
||||
0,0,700,12,1,,,,0,,0.5,1,2.0,1,1549.0,0.677,0.607,1.749,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0
|
||||
0,0,800,5,2,,,,0,,,1,1.0,1,1316.87,,,2.8,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,2.0,1,1371.66,,,2.39,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,3.0,1,1405.96,,,2.31,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,1.0,0,907.94,,,3.41,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,2.0,0,1496.84,,,2.42,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,0,,,1,3.0,0,2018.62,,,1.91,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
0,0,800,5,2,,,,1,1.0,,1,2.0,1,1694.42,1.1,0.71,2.58,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
|
||||
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0,1,1000,5,2,,,,0,,,0,0.0,1,18.0,0.07,,,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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0,1,1100,5,2,,,,0,,,0,0.0,1,6.0,0.03,,,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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0,0,650,5,2,,,,0,,,1,2.0,1,1333.0,0.66,0.54,1.94,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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0,0,850,5,2,,,,0,,,1,2.0,1,1538.0,0.75,0.57,1.97,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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0,0,900,5,4,,,,0,,3.0,0,0.0,0,100.6,,,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0
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0,0,500,5,2,,,,0,,4.0,0,0.0,0,375.8,0.45,,,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0
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1,0,500,5,2,850.0,5.0,2.0,0,,4.0,1,0.5,0,761.5,0.49,0.24,,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0
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0,0,800,5,1,,,,0,,6.0,1,3.0,0,1555.51,0.8112,,2.09,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0
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1,0,500,5,1,900.0,,3.0,0,,,1,4.0,1,2683.0,1.42,0.61,2.12,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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1,0,600,5,1,900.0,,3.0,0,,,1,4.0,1,2331.0,1.36,0.47,2.26,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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1,0,700,5,1,900.0,,3.0,0,,,1,4.0,1,1157.0,0.6,0.4,2.03,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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1,0,800,5,1,900.0,,3.0,0,,,1,4.0,1,243.0,0.163,0.11,2.51,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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1,0,900,5,1,900.0,,3.0,0,,,1,4.0,1,24.0,0.039,0.002,5.46,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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1,0,1000,5,1,900.0,,3.0,0,,,1,4.0,1,10.0,0.019,0.002,6.94,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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0,1,700,5,2,,,,0,,10.0,0,0.0,1,33.0,0.069,,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0
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0,1,700,5,2,,,,1,2.0,10.0,0,0.0,1,332.0,0.422,,,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0
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0,0,800,2,1,,,,0,,,1,2.0,0,1132.0,0.599,0.5482,2.117,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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0,0,750,5,1,,,,0,,2.0,0,0.0,0,460.0,0.93,,7.7,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0
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0,0,950,5,1,,,,0,,2.0,0,0.0,0,403.0,0.929,,9.2,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0
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0,0,600,5,1,,,,0,,,1,4.0,1,1960.0,0.95,0.8,1.93,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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0,0,700,5,1,,,,0,,,1,4.0,1,2789.0,1.35,1.18,1.93,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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0,0,800,5,1,,,,0,,,1,4.0,1,2258.0,1.08,0.98,1.92,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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0,0,700,5,1,,,,0,,,1,3.0,1,1885.0,0.84,0.77,1.78,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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0,0,700,5,1,,,,0,,,1,5.0,1,2569.0,1.13,1.11,2.05,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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||||
|
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|
@ -0,0 +1,193 @@
|
|||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"\n",
|
||||
"# A demo for multi-output regression\n",
|
||||
"\n",
|
||||
"The demo is adopted from scikit-learn:\n",
|
||||
"\n",
|
||||
"https://scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_regression_multioutput.html#sphx-glr-auto-examples-ensemble-plot-random-forest-regression-multioutput-py\n",
|
||||
"\n",
|
||||
"See :doc:`/tutorials/multioutput` for more information.\n",
|
||||
"\n",
|
||||
"<div class=\"alert alert-info\"><h4>Note</h4><p>The feature is experimental. For the `multi_output_tree` strategy, many features are\n",
|
||||
" missing.</p></div>\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {
|
||||
"collapsed": false,
|
||||
"jupyter": {
|
||||
"outputs_hidden": false
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"ename": "ModuleNotFoundError",
|
||||
"evalue": "No module named 'xgboost'",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
|
||||
"Cell \u001b[0;32mIn[1], line 7\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m pyplot \u001b[38;5;28;01mas\u001b[39;00m plt\n\u001b[0;32m----> 7\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mxgboost\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mxgb\u001b[39;00m\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mplot_predt\u001b[39m(y: np\u001b[38;5;241m.\u001b[39mndarray, y_predt: np\u001b[38;5;241m.\u001b[39mndarray, name: \u001b[38;5;28mstr\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 11\u001b[0m s \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m25\u001b[39m\n",
|
||||
"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'xgboost'"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import argparse\n",
|
||||
"from typing import Dict, List, Tuple\n",
|
||||
"\n",
|
||||
"import numpy as np\n",
|
||||
"from matplotlib import pyplot as plt\n",
|
||||
"\n",
|
||||
"import xgboost as xgb\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def plot_predt(y: np.ndarray, y_predt: np.ndarray, name: str) -> None:\n",
|
||||
" s = 25\n",
|
||||
" plt.scatter(y[:, 0], y[:, 1], c=\"navy\", s=s, edgecolor=\"black\", label=\"data\")\n",
|
||||
" plt.scatter(\n",
|
||||
" y_predt[:, 0], y_predt[:, 1], c=\"cornflowerblue\", s=s, edgecolor=\"black\"\n",
|
||||
" )\n",
|
||||
" plt.xlim([-1, 2])\n",
|
||||
" plt.ylim([-1, 2])\n",
|
||||
" plt.show()\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def gen_circle() -> Tuple[np.ndarray, np.ndarray]:\n",
|
||||
" \"Generate a sample dataset that y is a 2 dim circle.\"\n",
|
||||
" rng = np.random.RandomState(1994)\n",
|
||||
" X = np.sort(200 * rng.rand(100, 1) - 100, axis=0)\n",
|
||||
" y = np.array([np.pi * np.sin(X).ravel(), np.pi * np.cos(X).ravel()]).T\n",
|
||||
" y[::5, :] += 0.5 - rng.rand(20, 2)\n",
|
||||
" y = y - y.min()\n",
|
||||
" y = y / y.max()\n",
|
||||
" return X, y\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def rmse_model(plot_result: bool, strategy: str) -> None:\n",
|
||||
" \"\"\"Draw a circle with 2-dim coordinate as target variables.\"\"\"\n",
|
||||
" X, y = gen_circle()\n",
|
||||
" # Train a regressor on it\n",
|
||||
" reg = xgb.XGBRegressor(\n",
|
||||
" tree_method=\"hist\",\n",
|
||||
" n_estimators=128,\n",
|
||||
" n_jobs=16,\n",
|
||||
" max_depth=8,\n",
|
||||
" multi_strategy=strategy,\n",
|
||||
" subsample=0.6,\n",
|
||||
" )\n",
|
||||
" reg.fit(X, y, eval_set=[(X, y)])\n",
|
||||
"\n",
|
||||
" y_predt = reg.predict(X)\n",
|
||||
" if plot_result:\n",
|
||||
" plot_predt(y, y_predt, \"multi\")\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def custom_rmse_model(plot_result: bool, strategy: str) -> None:\n",
|
||||
" \"\"\"Train using Python implementation of Squared Error.\"\"\"\n",
|
||||
"\n",
|
||||
" # As the experimental support status, custom objective doesn't support matrix as\n",
|
||||
" # gradient and hessian, which will be changed in future release.\n",
|
||||
" def gradient(predt: np.ndarray, dtrain: xgb.DMatrix) -> np.ndarray:\n",
|
||||
" \"\"\"Compute the gradient squared error.\"\"\"\n",
|
||||
" y = dtrain.get_label().reshape(predt.shape)\n",
|
||||
" return (predt - y).reshape(y.size)\n",
|
||||
"\n",
|
||||
" def hessian(predt: np.ndarray, dtrain: xgb.DMatrix) -> np.ndarray:\n",
|
||||
" \"\"\"Compute the hessian for squared error.\"\"\"\n",
|
||||
" return np.ones(predt.shape).reshape(predt.size)\n",
|
||||
"\n",
|
||||
" def squared_log(\n",
|
||||
" predt: np.ndarray, dtrain: xgb.DMatrix\n",
|
||||
" ) -> Tuple[np.ndarray, np.ndarray]:\n",
|
||||
" grad = gradient(predt, dtrain)\n",
|
||||
" hess = hessian(predt, dtrain)\n",
|
||||
" return grad, hess\n",
|
||||
"\n",
|
||||
" def rmse(predt: np.ndarray, dtrain: xgb.DMatrix) -> Tuple[str, float]:\n",
|
||||
" y = dtrain.get_label().reshape(predt.shape)\n",
|
||||
" v = np.sqrt(np.sum(np.power(y - predt, 2)))\n",
|
||||
" return \"PyRMSE\", v\n",
|
||||
"\n",
|
||||
" X, y = gen_circle()\n",
|
||||
" Xy = xgb.DMatrix(X, y)\n",
|
||||
" results: Dict[str, Dict[str, List[float]]] = {}\n",
|
||||
" # Make sure the `num_target` is passed to XGBoost when custom objective is used.\n",
|
||||
" # When builtin objective is used, XGBoost can figure out the number of targets\n",
|
||||
" # automatically.\n",
|
||||
" booster = xgb.train(\n",
|
||||
" {\n",
|
||||
" \"tree_method\": \"hist\",\n",
|
||||
" \"num_target\": y.shape[1],\n",
|
||||
" \"multi_strategy\": strategy,\n",
|
||||
" },\n",
|
||||
" dtrain=Xy,\n",
|
||||
" num_boost_round=128,\n",
|
||||
" obj=squared_log,\n",
|
||||
" evals=[(Xy, \"Train\")],\n",
|
||||
" evals_result=results,\n",
|
||||
" custom_metric=rmse,\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" y_predt = booster.inplace_predict(X)\n",
|
||||
" if plot_result:\n",
|
||||
" plot_predt(y, y_predt, \"multi\")\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"if __name__ == \"__main__\":\n",
|
||||
" parser = argparse.ArgumentParser()\n",
|
||||
" parser.add_argument(\"--plot\", choices=[0, 1], type=int, default=1)\n",
|
||||
" args = parser.parse_args()\n",
|
||||
"\n",
|
||||
" # Train with builtin RMSE objective\n",
|
||||
" # - One model per output.\n",
|
||||
" rmse_model(args.plot == 1, \"one_output_per_tree\")\n",
|
||||
" # - One model for all outputs, this is still working in progress, many features are\n",
|
||||
" # missing.\n",
|
||||
" rmse_model(args.plot == 1, \"multi_output_tree\")\n",
|
||||
"\n",
|
||||
" # Train with custom objective.\n",
|
||||
" # - One model per output.\n",
|
||||
" custom_rmse_model(args.plot == 1, \"one_output_per_tree\")\n",
|
||||
" # - One model for all outputs, this is still working in progress, many features are\n",
|
||||
" # missing.\n",
|
||||
" custom_rmse_model(args.plot == 1, \"multi_output_tree\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"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": "3.8.16"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 4
|
||||
}
|
||||
|
|
@ -0,0 +1,761 @@
|
|||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "e2fb2c7b-89ca-4e2b-aa44-19403cef590a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import pandas as pd"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "f47b0afa-9e2d-4f2d-a51b-6e2071ffd08a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"old_data = pd.read_excel('./data/煤质碳材料数据.xlsx')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "77fa919c-d186-4079-a7b1-70842c97c3ec",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"nature_data = pd.read_excel('./data/nature.xlsx')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
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|
||||
"id": "38a1f29b-06e1-47a4-8839-e37568bac6cf",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <tr>\n",
|
||||
" <th>66</th>\n",
|
||||
" <td>67</td>\n",
|
||||
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|
||||
" <td>0.81</td>\n",
|
||||
" <td>4.15</td>\n",
|
||||
" <td>9.77</td>\n",
|
||||
" <td>91.59</td>\n",
|
||||
" <td>3.96</td>\n",
|
||||
" <td>1.76</td>\n",
|
||||
" <td>0.21</td>\n",
|
||||
" <td>2.48</td>\n",
|
||||
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|
||||
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|
||||
" <td>1.0</td>\n",
|
||||
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|
||||
" <td>0</td>\n",
|
||||
" <td>3142.0</td>\n",
|
||||
" <td>1.608</td>\n",
|
||||
" <td>1.204</td>\n",
|
||||
" <td>0.404</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>67</th>\n",
|
||||
" <td>68</td>\n",
|
||||
" <td>无烟煤</td>\n",
|
||||
" <td>0.81</td>\n",
|
||||
" <td>4.15</td>\n",
|
||||
" <td>9.77</td>\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <td>2.041</td>\n",
|
||||
" <td>1.022</td>\n",
|
||||
" <td>1.019</td>\n",
|
||||
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|
||||
" <tr>\n",
|
||||
" <th>68</th>\n",
|
||||
" <td>69</td>\n",
|
||||
" <td>无烟煤</td>\n",
|
||||
" <td>0.88</td>\n",
|
||||
" <td>8.42</td>\n",
|
||||
" <td>8.83</td>\n",
|
||||
" <td>91.69</td>\n",
|
||||
" <td>2.31</td>\n",
|
||||
" <td>2.04</td>\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <td>1.135</td>\n",
|
||||
" <td>0.916</td>\n",
|
||||
" <td>0.219</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>69</th>\n",
|
||||
" <td>70</td>\n",
|
||||
" <td>无烟煤</td>\n",
|
||||
" <td>0.88</td>\n",
|
||||
" <td>8.42</td>\n",
|
||||
" <td>8.83</td>\n",
|
||||
" <td>91.69</td>\n",
|
||||
" <td>2.31</td>\n",
|
||||
" <td>2.04</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>3.96</td>\n",
|
||||
" <td>800.0</td>\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <td>0.272</td>\n",
|
||||
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|
||||
" <tr>\n",
|
||||
" <th>70</th>\n",
|
||||
" <td>71</td>\n",
|
||||
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|
||||
" <td>0.88</td>\n",
|
||||
" <td>8.42</td>\n",
|
||||
" <td>8.83</td>\n",
|
||||
" <td>91.69</td>\n",
|
||||
" <td>2.31</td>\n",
|
||||
" <td>2.04</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>3.96</td>\n",
|
||||
" <td>900.0</td>\n",
|
||||
" <td>5.0</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>2947.0</td>\n",
|
||||
" <td>1.473</td>\n",
|
||||
" <td>0.718</td>\n",
|
||||
" <td>0.755</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
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|
||||
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|
||||
],
|
||||
"text/plain": [
|
||||
" 编号 煤种 分析水Mad 灰分 挥发分 碳 氢 氮 硫 氧 碳化温度（℃） \\\n",
|
||||
"0 1 中级烟煤 2.12 8.49 37.14 86.20 5.42 1.60 0.00 6.78 1100.0 \n",
|
||||
"1 2 萃取中级烟煤 NaN NaN NaN 75.11 4.73 1.38 0.00 18.78 1100.0 \n",
|
||||
"2 3 褐煤 14.91 4.35 48.42 67.76 4.57 1.29 3.56 22.82 650.0 \n",
|
||||
"3 4 褐煤 14.91 4.35 48.42 67.76 4.57 1.29 3.56 22.82 650.0 \n",
|
||||
"4 5 褐煤 14.91 4.35 48.42 67.76 4.57 1.29 3.56 22.82 650.0 \n",
|
||||
".. .. ... ... ... ... ... ... ... ... ... ... \n",
|
||||
"66 67 无烟煤 0.81 4.15 9.77 91.59 3.96 1.76 0.21 2.48 800.0 \n",
|
||||
"67 68 无烟煤 0.81 4.15 9.77 91.59 3.96 1.76 0.21 2.48 800.0 \n",
|
||||
"68 69 无烟煤 0.88 8.42 8.83 91.69 2.31 2.04 0.00 3.96 700.0 \n",
|
||||
"69 70 无烟煤 0.88 8.42 8.83 91.69 2.31 2.04 0.00 3.96 800.0 \n",
|
||||
"70 71 无烟煤 0.88 8.42 8.83 91.69 2.31 2.04 0.00 3.96 900.0 \n",
|
||||
"\n",
|
||||
" 升温速率（℃/min) 保温时间(h) KOH K2CO3 BET比表面积（m2/g） 孔体积（cm3/g) 微孔体积（cm3/g) \\\n",
|
||||
"0 2.0 2.0 0 0 296.0 0.270 NaN \n",
|
||||
"1 2.0 2.0 0 0 316.0 0.481 NaN \n",
|
||||
"2 10.0 0.5 1 0 665.0 0.356 0.289 \n",
|
||||
"3 10.0 0.5 1 0 1221.0 0.608 0.482 \n",
|
||||
"4 10.0 0.5 1 0 2609.0 1.438 0.670 \n",
|
||||
".. ... ... ... ... ... ... ... \n",
|
||||
"66 5.0 1.0 1 0 3142.0 1.608 1.204 \n",
|
||||
"67 5.0 1.0 1 0 3389.0 2.041 1.022 \n",
|
||||
"68 5.0 1.0 1 0 2542.0 1.135 0.916 \n",
|
||||
"69 5.0 1.0 1 0 2665.0 1.219 0.947 \n",
|
||||
"70 5.0 1.0 1 0 2947.0 1.473 0.718 \n",
|
||||
"\n",
|
||||
" 介孔体积（cm3/g) \n",
|
||||
"0 NaN \n",
|
||||
"1 NaN \n",
|
||||
"2 0.067 \n",
|
||||
"3 0.126 \n",
|
||||
"4 0.768 \n",
|
||||
".. ... \n",
|
||||
"66 0.404 \n",
|
||||
"67 1.019 \n",
|
||||
"68 0.219 \n",
|
||||
"69 0.272 \n",
|
||||
"70 0.755 \n",
|
||||
"\n",
|
||||
"[71 rows x 19 columns]"
|
||||
]
|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>Csp(F/g)</th>\n",
|
||||
" <th>electrolyte</th>\n",
|
||||
" <th>υ(mV/s)</th>\n",
|
||||
" <th>SAmicro(m2/g)</th>\n",
|
||||
" <th>SAmeso(m2/g)</th>\n",
|
||||
" <th>O</th>\n",
|
||||
" <th>N</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>6MKOH</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>6MKOH</td>\n",
|
||||
" <td>300</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>6MKOH</td>\n",
|
||||
" <td>500</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>6MKOH</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>17.00</td>\n",
|
||||
" <td>15.60</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>6MKOH</td>\n",
|
||||
" <td>300</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>17.00</td>\n",
|
||||
" <td>15.60</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>283</th>\n",
|
||||
" <td>218.17</td>\n",
|
||||
" <td>1MH2SO4</td>\n",
|
||||
" <td>150</td>\n",
|
||||
" <td>1691</td>\n",
|
||||
" <td>258</td>\n",
|
||||
" <td>16.45</td>\n",
|
||||
" <td>3.31</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>284</th>\n",
|
||||
" <td>198.38</td>\n",
|
||||
" <td>1MH2SO4</td>\n",
|
||||
" <td>200</td>\n",
|
||||
" <td>1691</td>\n",
|
||||
" <td>258</td>\n",
|
||||
" <td>16.45</td>\n",
|
||||
" <td>3.31</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>285</th>\n",
|
||||
" <td>171.19</td>\n",
|
||||
" <td>1MH2SO4</td>\n",
|
||||
" <td>300</td>\n",
|
||||
" <td>1691</td>\n",
|
||||
" <td>258</td>\n",
|
||||
" <td>16.45</td>\n",
|
||||
" <td>3.31</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>286</th>\n",
|
||||
" <td>152.27</td>\n",
|
||||
" <td>1MH2SO4</td>\n",
|
||||
" <td>400</td>\n",
|
||||
" <td>1691</td>\n",
|
||||
" <td>258</td>\n",
|
||||
" <td>16.45</td>\n",
|
||||
" <td>3.31</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>287</th>\n",
|
||||
" <td>137.40</td>\n",
|
||||
" <td>1MH2SO4</td>\n",
|
||||
" <td>500</td>\n",
|
||||
" <td>1691</td>\n",
|
||||
" <td>258</td>\n",
|
||||
" <td>16.45</td>\n",
|
||||
" <td>3.31</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>288 rows × 7 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Csp(F/g) electrolyte υ(mV/s) SAmicro(m2/g) SAmeso(m2/g) O N\n",
|
||||
"0 0.00 6MKOH 1 0 0 0.00 0.00\n",
|
||||
"1 0.00 6MKOH 300 0 0 0.00 0.00\n",
|
||||
"2 0.00 6MKOH 500 0 0 0.00 0.00\n",
|
||||
"3 0.00 6MKOH 1 0 0 17.00 15.60\n",
|
||||
"4 0.00 6MKOH 300 0 0 17.00 15.60\n",
|
||||
".. ... ... ... ... ... ... ...\n",
|
||||
"283 218.17 1MH2SO4 150 1691 258 16.45 3.31\n",
|
||||
"284 198.38 1MH2SO4 200 1691 258 16.45 3.31\n",
|
||||
"285 171.19 1MH2SO4 300 1691 258 16.45 3.31\n",
|
||||
"286 152.27 1MH2SO4 400 1691 258 16.45 3.31\n",
|
||||
"287 137.40 1MH2SO4 500 1691 258 16.45 3.31\n",
|
||||
"\n",
|
||||
"[288 rows x 7 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"nature_data"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "11ae5919-681c-4667-8c8f-bf71cde0f036",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"基于微孔介孔，推一下CHS？"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "435c980c-251f-42d5-883c-233d083df3a3",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"fea_cols = ['微孔体积（cm3/g)', '介孔体积（cm3/g)', '氧', '氮']"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "c787ae5c-db4a-4424-ac97-fafdd60a0b5c",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"out_cols = ['碳', '氢', '硫']"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"id": "361dce5d-3d08-4c7b-9bcf-9823a75b1f9e",
|
||||
"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>O</th>\n",
|
||||
" <th>N</th>\n",
|
||||
" <th>SAmicro(m2/g)</th>\n",
|
||||
" <th>SAmeso(m2/g)</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>17.00</td>\n",
|
||||
" <td>15.60</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>6</th>\n",
|
||||
" <td>8.50</td>\n",
|
||||
" <td>7.80</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>9</th>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>120</td>\n",
|
||||
" <td>216</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>13</th>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>107</td>\n",
|
||||
" <td>315</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>159</th>\n",
|
||||
" <td>6.25</td>\n",
|
||||
" <td>9.57</td>\n",
|
||||
" <td>640</td>\n",
|
||||
" <td>184</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>160</th>\n",
|
||||
" <td>8.49</td>\n",
|
||||
" <td>5.38</td>\n",
|
||||
" <td>563</td>\n",
|
||||
" <td>120</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>161</th>\n",
|
||||
" <td>7.84</td>\n",
|
||||
" <td>7.02</td>\n",
|
||||
" <td>680</td>\n",
|
||||
" <td>641</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>164</th>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>1082</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>165</th>\n",
|
||||
" <td>14.97</td>\n",
|
||||
" <td>0.00</td>\n",
|
||||
" <td>1590</td>\n",
|
||||
" <td>1030</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>63 rows × 4 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" O N SAmicro(m2/g) SAmeso(m2/g)\n",
|
||||
"0 0.00 0.00 0 0\n",
|
||||
"3 17.00 15.60 0 0\n",
|
||||
"6 8.50 7.80 0 0\n",
|
||||
"9 0.00 0.00 120 216\n",
|
||||
"13 0.00 0.00 107 315\n",
|
||||
".. ... ... ... ...\n",
|
||||
"159 6.25 9.57 640 184\n",
|
||||
"160 8.49 5.38 563 120\n",
|
||||
"161 7.84 7.02 680 641\n",
|
||||
"164 0.00 0.00 0 1082\n",
|
||||
"165 14.97 0.00 1590 1030\n",
|
||||
"\n",
|
||||
"[63 rows x 4 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 10,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"nature_data[nature_data.electrolyte=='6MKOH'][['O', 'N', 'SAmicro(m2/g)', 'SAmeso(m2/g)']].drop_duplicates()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "101dba3e-4029-4d53-b64a-89c5a90f3471",
|
||||
"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": "3.8.16"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
Loading…
Reference in New Issue