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epassaro/chianti_duplicated_levels.ipynb

Created November 2, 2019 21:34
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chianti_duplicated_levels.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Chianti duplicated levels"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"`H` and `He` levels come from Chianti."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"levels = pd.read_hdf('./kurucz_cd23_chianti_H_He.h5', key='levels')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are 6 duplicated levels for ion (1,0) and 3 in (2,1):"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
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" <th>energy</th>\n",
" <th>g</th>\n",
" <th>metastable</th>\n",
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" <tr>\n",
" <th>level_number</th>\n",
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" <td>2</td>\n",
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" <th>2</th>\n",
" <td>10.198810</td>\n",
" <td>2</td>\n",
" <td>True</td>\n",
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" <td>10.198851</td>\n",
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" <th>5</th>\n",
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" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>12.087507</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>12.087507</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>8</th>\n",
" <td>12.087511</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>9</th>\n",
" <td>12.748532</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
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" <th>10</th>\n",
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" <td>12.748538</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>12</th>\n",
" <td>12.748538</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>13</th>\n",
" <td>12.748540</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>12.748540</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
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" <th>15</th>\n",
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" <td>8</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>16</th>\n",
" <td>13.054498</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>17</th>\n",
" <td>13.054498</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>13.054501</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>13.054501</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>13.054502</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>13.054502</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>13.054502</td>\n",
" <td>8</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>13.054502</td>\n",
" <td>8</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>13.054502</td>\n",
" <td>10</td>\n",
" <td>False</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" energy g metastable\n",
"level_number \n",
"0 0.000000 2 True\n",
"1 10.198806 2 False\n",
"2 10.198810 2 True\n",
"3 10.198851 4 False\n",
"4 12.087493 2 False\n",
"5 12.087495 2 False\n",
"6 12.087507 4 False\n",
"7 12.087507 4 False\n",
"8 12.087511 6 False\n",
"9 12.748532 2 False\n",
"10 12.748533 2 False\n",
"11 12.748538 4 False\n",
"12 12.748538 4 False\n",
"13 12.748540 6 False\n",
"14 12.748540 6 False\n",
"15 12.748541 8 False\n",
"16 13.054498 2 False\n",
"17 13.054498 2 False\n",
"18 13.054501 4 False\n",
"19 13.054501 4 False\n",
"20 13.054502 6 False\n",
"21 13.054502 6 False\n",
"22 13.054502 8 False\n",
"23 13.054502 8 False\n",
"24 13.054502 10 False"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"levels.loc[(1,0)]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
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" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
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" <th>7</th>\n",
" <td>48.371511</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>8</th>\n",
" <td>48.371583</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>9</th>\n",
" <td>51.016660</td>\n",
" <td>2</td>\n",
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" <tr>\n",
" <th>10</th>\n",
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" <td>4</td>\n",
" <td>False</td>\n",
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" <td>6</td>\n",
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" <th>14</th>\n",
" <td>51.016781</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>15</th>\n",
" <td>51.016796</td>\n",
" <td>8</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>16</th>\n",
" <td>52.241073</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>17</th>\n",
" <td>52.241076</td>\n",
" <td>2</td>\n",
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" <tr>\n",
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" <td>52.241119</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>20</th>\n",
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" <td>6</td>\n",
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" <td>6</td>\n",
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" <td>52.241142</td>\n",
" <td>8</td>\n",
" <td>False</td>\n",
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" <th>24</th>\n",
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],
"text/plain": [
" energy g metastable\n",
"level_number \n",
"0 0.000000 2 True\n",
"1 40.813030 2 False\n",
"2 40.813088 2 True\n",
"3 40.813756 4 False\n",
"4 48.371296 2 False\n",
"5 48.371313 2 False\n",
"6 48.371511 4 False\n",
"7 48.371511 4 False\n",
"8 48.371583 6 False\n",
"9 51.016660 2 False\n",
"10 51.016667 2 False\n",
"11 51.016750 4 False\n",
"12 51.016751 4 False\n",
"13 51.016781 6 False\n",
"14 51.016781 6 False\n",
"15 51.016796 8 False\n",
"16 52.241073 2 False\n",
"17 52.241076 2 False\n",
"18 52.241119 4 False\n",
"19 52.241119 4 False\n",
"20 52.241135 6 False\n",
"21 52.241135 6 False\n",
"22 52.241142 8 False\n",
"23 52.241142 8 False\n",
"24 52.241147 10 False"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"levels.loc[(2,1)]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"((25, 3), (19, 3))"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"levels.loc[(1,0)].shape, levels.loc[(1,0)].drop_duplicates(subset=['energy','g']).shape"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"((25, 3), (22, 3))"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"levels.loc[(2,1)].shape, levels.loc[(2,1)].drop_duplicates(subset=['energy','g']).shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Look at the Chianti levels"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/epassaro/miniconda3/envs/carsus/lib/python3.6/site-packages/tqdm/autonotebook.py:17: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
" \" (e.g. in jupyter console)\", TqdmExperimentalWarning)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" ChiantiPy version 0.8.4 \n",
" found PyQt5 widgets\n",
" using PyQt5 widgets\n"
]
}
],
"source": [
"from carsus.io.chianti_ import ChiantiIonReader\n",
"from carsus.io.util import convert_species_tuple2chianti_str"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"('h_1', 'he_2')"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"convert_species_tuple2chianti_str((1,0)), convert_species_tuple2chianti_str((2,1))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
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" <td>3p</td>\n",
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" <td>1.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>3d</td>\n",
" <td>2D1.5</td>\n",
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" <tr>\n",
" <th>9</th>\n",
" <td>97492.357</td>\n",
" <td>97544.0</td>\n",
" <td>2.5</td>\n",
" <td>D</td>\n",
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" <td>102879.0</td>\n",
" <td>0.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4p</td>\n",
" <td>2P0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>102823.896</td>\n",
" <td>102879.0</td>\n",
" <td>1.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4p</td>\n",
" <td>2P1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>102823.896</td>\n",
" <td>102879.0</td>\n",
" <td>1.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4d</td>\n",
" <td>2D1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>102823.911</td>\n",
" <td>102879.0</td>\n",
" <td>2.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4d</td>\n",
" <td>2D2.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>102823.911</td>\n",
" <td>102879.0</td>\n",
" <td>2.5</td>\n",
" <td>F</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4f</td>\n",
" <td>2F2.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>102823.919</td>\n",
" <td>102879.0</td>\n",
" <td>3.5</td>\n",
" <td>F</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4f</td>\n",
" <td>2F3.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>105291.633</td>\n",
" <td>105348.0</td>\n",
" <td>0.5</td>\n",
" <td>S</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5s</td>\n",
" <td>2S0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>105291.631</td>\n",
" <td>105348.0</td>\n",
" <td>0.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5p</td>\n",
" <td>2P0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>105291.654</td>\n",
" <td>105348.0</td>\n",
" <td>1.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5p</td>\n",
" <td>2P1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>105291.654</td>\n",
" <td>105348.0</td>\n",
" <td>1.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5d</td>\n",
" <td>2D1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>105291.662</td>\n",
" <td>105348.0</td>\n",
" <td>2.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5d</td>\n",
" <td>2D2.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>105291.662</td>\n",
" <td>105348.0</td>\n",
" <td>2.5</td>\n",
" <td>F</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5f</td>\n",
" <td>2F2.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>105291.666</td>\n",
" <td>105348.0</td>\n",
" <td>3.5</td>\n",
" <td>F</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5f</td>\n",
" <td>2F3.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>105291.666</td>\n",
" <td>105348.0</td>\n",
" <td>3.5</td>\n",
" <td>G</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5g</td>\n",
" <td>2G3.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>105291.668</td>\n",
" <td>105348.0</td>\n",
" <td>4.5</td>\n",
" <td>G</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5g</td>\n",
" <td>2G4.5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" energy energy_theoretical J L spin_multiplicity label \\\n",
"level_index \n",
"1 0.000 0.0 0.5 S 2 NaN \n",
"2 82258.956 82303.0 0.5 S 2 NaN \n",
"3 82258.921 82303.0 0.5 P 2 NaN \n",
"4 82259.287 82303.0 1.5 P 2 NaN \n",
"5 97492.224 97544.0 0.5 S 2 NaN \n",
"6 97492.213 97544.0 0.5 P 2 NaN \n",
"7 97492.321 97544.0 1.5 P 2 NaN \n",
"8 97492.321 97544.0 1.5 D 2 NaN \n",
"9 97492.357 97544.0 2.5 D 2 NaN \n",
"10 102823.855 102879.0 0.5 S 2 NaN \n",
"11 102823.851 102879.0 0.5 P 2 NaN \n",
"12 102823.896 102879.0 1.5 P 2 NaN \n",
"13 102823.896 102879.0 1.5 D 2 NaN \n",
"14 102823.911 102879.0 2.5 D 2 NaN \n",
"15 102823.911 102879.0 2.5 F 2 NaN \n",
"16 102823.919 102879.0 3.5 F 2 NaN \n",
"17 105291.633 105348.0 0.5 S 2 NaN \n",
"18 105291.631 105348.0 0.5 P 2 NaN \n",
"19 105291.654 105348.0 1.5 P 2 NaN \n",
"20 105291.654 105348.0 1.5 D 2 NaN \n",
"21 105291.662 105348.0 2.5 D 2 NaN \n",
"22 105291.662 105348.0 2.5 F 2 NaN \n",
"23 105291.666 105348.0 3.5 F 2 NaN \n",
"24 105291.666 105348.0 3.5 G 2 NaN \n",
"25 105291.668 105348.0 4.5 G 2 NaN \n",
"\n",
" term configuration \n",
"level_index \n",
"1 1s 2S0.5 \n",
"2 2s 2S0.5 \n",
"3 2p 2P0.5 \n",
"4 2p 2P1.5 \n",
"5 3s 2S0.5 \n",
"6 3p 2P0.5 \n",
"7 3p 2P1.5 \n",
"8 3d 2D1.5 \n",
"9 3d 2D2.5 \n",
"10 4s 2S0.5 \n",
"11 4p 2P0.5 \n",
"12 4p 2P1.5 \n",
"13 4d 2D1.5 \n",
"14 4d 2D2.5 \n",
"15 4f 2F2.5 \n",
"16 4f 2F3.5 \n",
"17 5s 2S0.5 \n",
"18 5p 2P0.5 \n",
"19 5p 2P1.5 \n",
"20 5d 2D1.5 \n",
"21 5d 2D2.5 \n",
"22 5f 2F2.5 \n",
"23 5f 2F3.5 \n",
"24 5g 2G3.5 \n",
"25 5g 2G4.5 "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Levels with same J and different L. `g` is 2J+1\n",
"\n",
"ChiantiIonReader('h_1').levels"
]
},
{
"cell_type": "code",
"execution_count": 10,
"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>energy</th>\n",
" <th>energy_theoretical</th>\n",
" <th>J</th>\n",
" <th>L</th>\n",
" <th>spin_multiplicity</th>\n",
" <th>label</th>\n",
" <th>term</th>\n",
" <th>configuration</th>\n",
" </tr>\n",
" <tr>\n",
" <th>level_index</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.000</td>\n",
" <td>0.0</td>\n",
" <td>0.5</td>\n",
" <td>S</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>1s</td>\n",
" <td>2S0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>329179.767</td>\n",
" <td>329212.0</td>\n",
" <td>0.5</td>\n",
" <td>S</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>2s</td>\n",
" <td>2S0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>329179.299</td>\n",
" <td>329212.0</td>\n",
" <td>0.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>2p</td>\n",
" <td>2P0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>329185.156</td>\n",
" <td>329212.0</td>\n",
" <td>1.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>2p</td>\n",
" <td>2P1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>390140.971</td>\n",
" <td>390177.0</td>\n",
" <td>0.5</td>\n",
" <td>S</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>3s</td>\n",
" <td>2S0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>390140.831</td>\n",
" <td>390177.0</td>\n",
" <td>0.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>3p</td>\n",
" <td>2P0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>390142.567</td>\n",
" <td>390177.0</td>\n",
" <td>1.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>3p</td>\n",
" <td>2P1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>390142.564</td>\n",
" <td>390177.0</td>\n",
" <td>1.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>3d</td>\n",
" <td>2D1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>390143.142</td>\n",
" <td>390177.0</td>\n",
" <td>2.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>3d</td>\n",
" <td>2D2.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>411477.188</td>\n",
" <td>411515.0</td>\n",
" <td>0.5</td>\n",
" <td>S</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4s</td>\n",
" <td>2S0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>411477.129</td>\n",
" <td>411515.0</td>\n",
" <td>0.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4p</td>\n",
" <td>2P0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>411477.861</td>\n",
" <td>411515.0</td>\n",
" <td>1.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4p</td>\n",
" <td>2P1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>411477.860</td>\n",
" <td>411515.0</td>\n",
" <td>1.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4d</td>\n",
" <td>2D1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>411478.104</td>\n",
" <td>411515.0</td>\n",
" <td>2.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4d</td>\n",
" <td>2D2.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>411478.104</td>\n",
" <td>411515.0</td>\n",
" <td>2.5</td>\n",
" <td>F</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4f</td>\n",
" <td>2F2.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>411478.226</td>\n",
" <td>411515.0</td>\n",
" <td>3.5</td>\n",
" <td>F</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>4f</td>\n",
" <td>2F3.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>421352.716</td>\n",
" <td>421391.0</td>\n",
" <td>0.5</td>\n",
" <td>S</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5s</td>\n",
" <td>2S0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>421352.686</td>\n",
" <td>421391.0</td>\n",
" <td>0.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5p</td>\n",
" <td>2P0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>421353.061</td>\n",
" <td>421391.0</td>\n",
" <td>1.5</td>\n",
" <td>P</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5p</td>\n",
" <td>2P1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>421353.060</td>\n",
" <td>421391.0</td>\n",
" <td>1.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5d</td>\n",
" <td>2D1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>421353.185</td>\n",
" <td>421391.0</td>\n",
" <td>2.5</td>\n",
" <td>D</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5d</td>\n",
" <td>2D2.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>421353.185</td>\n",
" <td>421391.0</td>\n",
" <td>2.5</td>\n",
" <td>F</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5f</td>\n",
" <td>2F2.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>421353.247</td>\n",
" <td>421391.0</td>\n",
" <td>3.5</td>\n",
" <td>F</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5f</td>\n",
" <td>2F3.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>421353.247</td>\n",
" <td>421391.0</td>\n",
" <td>3.5</td>\n",
" <td>G</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5g</td>\n",
" <td>2G3.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>421353.284</td>\n",
" <td>421391.0</td>\n",
" <td>4.5</td>\n",
" <td>G</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>5g</td>\n",
" <td>2G4.5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" energy energy_theoretical J L spin_multiplicity label \\\n",
"level_index \n",
"1 0.000 0.0 0.5 S 2 NaN \n",
"2 329179.767 329212.0 0.5 S 2 NaN \n",
"3 329179.299 329212.0 0.5 P 2 NaN \n",
"4 329185.156 329212.0 1.5 P 2 NaN \n",
"5 390140.971 390177.0 0.5 S 2 NaN \n",
"6 390140.831 390177.0 0.5 P 2 NaN \n",
"7 390142.567 390177.0 1.5 P 2 NaN \n",
"8 390142.564 390177.0 1.5 D 2 NaN \n",
"9 390143.142 390177.0 2.5 D 2 NaN \n",
"10 411477.188 411515.0 0.5 S 2 NaN \n",
"11 411477.129 411515.0 0.5 P 2 NaN \n",
"12 411477.861 411515.0 1.5 P 2 NaN \n",
"13 411477.860 411515.0 1.5 D 2 NaN \n",
"14 411478.104 411515.0 2.5 D 2 NaN \n",
"15 411478.104 411515.0 2.5 F 2 NaN \n",
"16 411478.226 411515.0 3.5 F 2 NaN \n",
"17 421352.716 421391.0 0.5 S 2 NaN \n",
"18 421352.686 421391.0 0.5 P 2 NaN \n",
"19 421353.061 421391.0 1.5 P 2 NaN \n",
"20 421353.060 421391.0 1.5 D 2 NaN \n",
"21 421353.185 421391.0 2.5 D 2 NaN \n",
"22 421353.185 421391.0 2.5 F 2 NaN \n",
"23 421353.247 421391.0 3.5 F 2 NaN \n",
"24 421353.247 421391.0 3.5 G 2 NaN \n",
"25 421353.284 421391.0 4.5 G 2 NaN \n",
"\n",
" term configuration \n",
"level_index \n",
"1 1s 2S0.5 \n",
"2 2s 2S0.5 \n",
"3 2p 2P0.5 \n",
"4 2p 2P1.5 \n",
"5 3s 2S0.5 \n",
"6 3p 2P0.5 \n",
"7 3p 2P1.5 \n",
"8 3d 2D1.5 \n",
"9 3d 2D2.5 \n",
"10 4s 2S0.5 \n",
"11 4p 2P0.5 \n",
"12 4p 2P1.5 \n",
"13 4d 2D1.5 \n",
"14 4d 2D2.5 \n",
"15 4f 2F2.5 \n",
"16 4f 2F3.5 \n",
"17 5s 2S0.5 \n",
"18 5p 2P0.5 \n",
"19 5p 2P1.5 \n",
"20 5d 2D1.5 \n",
"21 5d 2D2.5 \n",
"22 5f 2F2.5 \n",
"23 5f 2F3.5 \n",
"24 5g 2G3.5 \n",
"25 5g 2G4.5 "
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ChiantiIonReader('he_2').levels"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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