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@rahuldave
Created February 7, 2013 04:45
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{
"metadata": {
"name": "Explain3"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"import nltk\n",
"import re"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"nltk.download()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"showing info http://nltk.github.com/nltk_data/\n"
]
},
{
"output_type": "pyout",
"prompt_number": 2,
"text": [
"True"
]
}
],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Link to JSON Data: https://dl.dropbox.com/u/75194/chandrainfo.json"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import urllib2\n",
"fp=urllib2.urlopen(\"https://dl.dropbox.com/u/75194/chandrainfo.json\")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Also check out the requests module"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import json\n",
"dadict=json.loads(fp.read())"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dadict.keys()[0:10]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 6,
"text": [
"[u'2010MNRAS.401.1620H',\n",
" u'2003A&A...406..483S',\n",
" u'2008ApJ...678L.121A',\n",
" u'2003ApJ...588..992R',\n",
" u'1993SPIE.1742....2W',\n",
" u'2004A&A...418..625D',\n",
" u'2010ApJ...712L.107W',\n",
" u'2004ApJ...609L..59G',\n",
" u'2009ApJ...707L..69K',\n",
" u'2006A&A...454..165P']"
]
}
],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sum([1 for ele in dadict.keys() if dadict[ele]['type']!='science'])\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 7,
"text": [
"339"
]
}
],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sum([1 for ele in dadict.keys() if dadict[ele]['type']=='science'])"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 8,
"text": [
"5281"
]
}
],
"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"newdict={}\n",
"sciencelist=[]\n",
"notsciencedict={}\n",
"sciencedict={}\n",
"for ele in dadict.keys():\n",
" if dadict[ele]['type']!='science':\n",
" newdict[ele]=dadict[ele]\n",
" notsciencedict[ele]=dadict[ele]\n",
" else:\n",
" sciencelist.append(dadict[ele])\n",
"import random\n",
"samplesciencelist=random.sample(sciencelist, 339)\n",
"for ele in samplesciencelist:\n",
" newdict[ele['bibcode']]=ele\n",
" sciencedict[ele['bibcode']]=ele"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def maketoklist(abstract, stopwords):\n",
" bigtoklist=nltk.word_tokenize(abstract)\n",
" mystopwords=['sup','/sup', 'sub', '/sub']\n",
" mystopwords.extend(stopwords)\n",
" newtext = [w for w in bigtoklist if w.lower() not in mystopwords]\n",
" punctuation = re.compile(r'[-.?!,\":;()<>~|0-9]')\n",
" word_list = [punctuation.sub(\"\", word) for word in newtext]\n",
" words=[x for x in word_list if x!='']\n",
" return words"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def makefreq(catalog, stopwords):\n",
" listoftoklists=[maketoklist(c['abstract'], stopwords) for c in catalog.values()]\n",
" bigtoklist=[token for sublist in listoftoklists for token in sublist]\n",
" wordtext=nltk.Text(bigtoklist)\n",
" wordfdist=nltk.FreqDist(wordtext)\n",
" return wordfdist"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 21
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"stopwords=nltk.corpus.stopwords.words('english')\n",
"totfreq=makefreq(newdict, stopwords)\n",
"sciencefreq=makefreq(sciencedict, stopwords)\n",
"notsciencefreq=makefreq(notsciencedict, stopwords)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 22
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"totfreq.plot(30)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "display_data",
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TJ0+GpaUlpkyZghcvXqB9+/Y4evQooqKiMHHiRISHh6ufgJZbIADo3Bk4dgw4dAjo3r2w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\nRK5CYII=\n"
}
],
"prompt_number": 23
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sciencefreq.plot(30)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "display_data",
"png": 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PwNKlRe2IYZiSDNcUBGH3bmDAAPntrVvl13xmGIYpKLimIDj9+wMrV8pve3nJ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\nR5MCIYQQjiYFQgghHE0KhBBCuP8AYDyi/ZHJVSgAAAAASUVORK5CYII=\n"
}
],
"prompt_number": 24
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"notsciencefreq.plot(30)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "display_data",
"png": 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ODV7nLenbF7h4EWjaVPjbubOwoExZeiivtnVNy4sPHrS8+NA1rTr0MvgT6mnX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\n94xzK/PhOAAAAABJRU5ErkJggg==\n"
}
],
"prompt_number": 25
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"from pandas import DataFrame"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def makedocfreq(abstract, stopwords):\n",
" toklist=maketoklist(abstract, stopwords)\n",
" wordtext=nltk.Text(toklist)\n",
" wordfdist=nltk.FreqDist(wordtext)\n",
" return wordfdist"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 27
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Concentrating on the non-science catalog"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"freqdists={k:makedocfreq(notsciencedict[k]['abstract'].encode('utf-8'),stopwords) for k in notsciencedict.keys()}\n",
"freqdistmaxs={k:{'bibcode':k, \n",
" 'mfw':freqdists[k].max().decode('utf-8'), \n",
" 'freq':freqdists[k][freqdists[k].max()]} for k in freqdists.keys() if freqdists[k].N()!=0}"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 32
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"freqdists.values()[0].tabulate()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"AstroVirgil based Java multiple paper photon program reviews using ADASS' Chandra ESO Filtered GIU GPLed GUI JSky Photons also analysis arrival available built collection components consequences coordinate custom described developed displayed energy event file files filtered filtering first friendly images integrates level lightcurves measures memory nondisk panels performance performing photons position processing pure reusable single spatial spectrums systems time tool top user visualization wwwSiliconSpaceshipscom\n",
" 4 3 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n"
]
}
],
"prompt_number": 65
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"notfoundcodes=[k for k in freqdists.keys() if freqdists[k].N()==0]\n",
"notfoundcodes"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 34,
"text": [
"[u'2004SPIE.5488..115K', u'2001AIPC..599..387T']"
]
}
],
"prompt_number": 34
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"for k in notfoundcodes:\n",
" freqdistmaxs[k]={'bibcode':k, 'mfw':'','freq':0}"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 35
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"records=[]\n",
"[records.append(newdict[ele]) for ele in newdict.keys()]\n",
"df=DataFrame(records)\n",
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 38,
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 678 entries, 0 to 677\n",
"Data columns:\n",
"abstract 678 non-null values\n",
"bibcode 678 non-null values\n",
"type 678 non-null values\n",
"dtypes: object(3)"
]
}
],
"prompt_number": 38
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.bibcode[:4]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 39,
"text": [
"0 1992SPIE.1546...26S\n",
"1 2010ATel.2585....1C\n",
"2 2009PASJ...61..109N\n",
"3 2004SPIE.5165..497M\n",
"Name: bibcode"
]
}
],
"prompt_number": 39
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['year']=[int(e[:4]) for e in df.bibcode]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 40
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['year'].value_counts()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 43,
"text": [
"2006 74\n",
"2003 67\n",
"2004 64\n",
"2008 59\n",
"2005 52\n",
"2000 40\n",
"2009 39\n",
"2007 37\n",
"2010 36\n",
"2001 33\n",
"2002 29\n",
"1997 24\n",
"1993 24\n",
"1998 23\n",
"1996 22\n",
"1995 17\n",
"1994 14\n",
"1990 9\n",
"1992 7\n",
"1999 6\n",
"1991 2"
]
}
],
"prompt_number": 43
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['year'].value_counts().plot(kind=\"bar\")"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 41,
"text": [
"<matplotlib.axes.AxesSubplot at 0x1dde0570>"
]
},
{
"output_type": "display_data",
"png": 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UvPrqq4b+tGnT5MEHH5TJkyfL5MmTZdKkSbJx40aZMWOGzJ4929BPSkpyf/3M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\n"
}
],
"prompt_number": 41
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.groupby(['year','type']).size().unstack()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\">\n",
" <thead>\n",
" <tr>\n",
" <th>type</th>\n",
" <th>observatory</th>\n",
" <th>science</th>\n",
" </tr>\n",
" <tr>\n",
" <th>year</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td><strong>1990</strong></td>\n",
" <td> 9</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>1991</strong></td>\n",
" <td> 2</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>1992</strong></td>\n",
" <td> 7</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>1993</strong></td>\n",
" <td> 24</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>1994</strong></td>\n",
" <td> 14</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>1995</strong></td>\n",
" <td> 17</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>1996</strong></td>\n",
" <td> 22</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>1997</strong></td>\n",
" <td> 24</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>1998</strong></td>\n",
" <td> 23</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>1999</strong></td>\n",
" <td> 6</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2000</strong></td>\n",
" <td> 33</td>\n",
" <td> 7</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2001</strong></td>\n",
" <td> 15</td>\n",
" <td> 18</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2002</strong></td>\n",
" <td> 11</td>\n",
" <td> 18</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2003</strong></td>\n",
" <td> 30</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2004</strong></td>\n",
" <td> 32</td>\n",
" <td> 32</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2005</strong></td>\n",
" <td> 14</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2006</strong></td>\n",
" <td> 17</td>\n",
" <td> 57</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2007</strong></td>\n",
" <td> 3</td>\n",
" <td> 34</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2008</strong></td>\n",
" <td> 15</td>\n",
" <td> 44</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2009</strong></td>\n",
" <td> 10</td>\n",
" <td> 29</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>2010</strong></td>\n",
" <td> 11</td>\n",
" <td> 25</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"output_type": "pyout",
"prompt_number": 47,
"text": [
"type observatory science\n",
"year \n",
"1990 9 NaN\n",
"1991 2 NaN\n",
"1992 7 NaN\n",
"1993 24 NaN\n",
"1994 14 NaN\n",
"1995 17 NaN\n",
"1996 22 NaN\n",
"1997 24 NaN\n",
"1998 23 NaN\n",
"1999 6 NaN\n",
"2000 33 7\n",
"2001 15 18\n",
"2002 11 18\n",
"2003 30 37\n",
"2004 32 32\n",
"2005 14 38\n",
"2006 17 57\n",
"2007 3 34\n",
"2008 15 44\n",
"2009 10 29\n",
"2010 11 25"
]
}
],
"prompt_number": 47
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df[df['year']==1999]['type']"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 55,
"text": [
"32 observatory\n",
"287 observatory\n",
"306 observatory\n",
"533 observatory\n",
"548 observatory\n",
"573 observatory\n",
"Name: type"
]
}
],
"prompt_number": 55
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.groupby(['year','type']).size().unstack().fillna(0).plot(kind='barh', stacked=True)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 56,
"text": [
"<matplotlib.axes.AxesSubplot at 0x1f4e39b0>"
]
},
{
"output_type": "display_data",
"png": 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cONG0TyiGYRhGVPSO868Z8urcuXO9Ia+FCxcCAG7evFkn5OXo6Ci8Vs+ePZGU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\nTkSuQmCC\n"
}
],
"prompt_number": 56
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df2=DataFrame([freqdistmaxs[e] for e in freqdistmaxs.keys()])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 57
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dfm=pd.merge(df,df2)\n",
"dfm"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 59,
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 339 entries, 0 to 338\n",
"Data columns:\n",
"abstract 339 non-null values\n",
"bibcode 339 non-null values\n",
"type 339 non-null values\n",
"year 339 non-null values\n",
"freq 339 non-null values\n",
"mfw 339 non-null values\n",
"dtypes: int64(2), object(4)"
]
}
],
"prompt_number": 59
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dfm.groupby(['mfw','freq']).size().unstack().fillna(0)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\">\n",
" <thead>\n",
" <tr>\n",
" <th>freq</th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" <th>5</th>\n",
" <th>6</th>\n",
" <th>7</th>\n",
" <th>8</th>\n",
" <th>9</th>\n",
" <th>10</th>\n",
" <th>11</th>\n",
" <th>12</th>\n",
" <th>13</th>\n",
" </tr>\n",
" <tr>\n",
" <th>mfw</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",
" <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",
" <td><strong></strong></td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>%</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>'s</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>ACA</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>ACIS</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>AGASC</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>AXAF</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 4</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>AstroVirgil</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>Available</strong></td>\n",
" <td> 0</td>\n",
" <td> 35</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>CCD</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>CCDs</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>CIAO</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>CTI</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>CXO</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>CalDB</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>Chandra</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>HEASARC</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>HETG</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>HRC</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>HRCS</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>HRMA</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>JTS</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>LETG</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>MCPs</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>Observatory</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>PSF</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>Readout</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>SER</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>SIM</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>SLang</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>Sherpa</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>Transform</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>VETAI</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>Xray</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 3</td>\n",
" <td> 4</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>ZERODUR</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>absolute</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>archive</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>aspect</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>axial</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>background</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>bias</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>binned</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>calibration</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>camera</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>catalog</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>changes</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>charge</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>cluster</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>coating</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>constraint</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>contaminant</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>damage</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>data</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 2</td>\n",
" <td> 3</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>database</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>delta</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>design</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>detector</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 3</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>detectors</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>development</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>devices</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>dictionary</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>different</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>edges</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>effect</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>effective</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>efficiency</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>endtoend</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>energies</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>energy</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>event</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>events</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>facility</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>fitting</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>four</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>functions</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>gain</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>grating</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>gratings</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>holes</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>image</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>inner</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>instability</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>installation</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>instrument</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>interface</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>keV</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>layer</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>library</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>line</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>loads</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>logs</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>maps</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>measured</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>measurements</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>mesh</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>metrology</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>micrometers</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>million</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>mirror</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 3</td>\n",
" <td> 2</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>mirrors</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>mission</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>mm</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>model</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>nonlinearities</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>observatories</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>observatory</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>operations</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>optical</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>optics</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>optimal</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>percent</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>performance</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>pileup</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>pixel</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>point</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>polarization</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>positions</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>pressure</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>processing</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>program</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>programs</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>properties</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>protons</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>provide</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>radiation</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>range</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>reflectance</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>reflectivity</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>requirements</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>resolution</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>response</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>results</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>ring</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>rms</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>samples</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>scans</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>scattering</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>science</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>scientific</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>services</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>shields</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>signals</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>simulation</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>source</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>sources</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>spacecraft</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>spectral</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>spectrum</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>star</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>studies</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>successfully</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>support</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>surface</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>system</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>telescope</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>temperature</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>test</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>tests</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>time</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>tools</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>transmission</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 3</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>trap</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>two</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>uncertainties</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>understanding</strong></td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>used</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>using</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>witness</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>xray</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 2</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>years</strong></td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>\u00c5</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <td><strong>\u03a9</strong></td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
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"prompt_number": 64,
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"maps 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
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"mirrors 0 0 0 1 1 0 0 0 0 0 0 0 0 0\n",
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"observatory 0 0 0 0 1 0 0 0 0 0 0 0 0 0\n",
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"system 0 0 1 0 0 1 1 0 0 0 0 0 0 0\n",
"telescope 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
"temperature 0 0 0 0 0 1 0 0 0 0 0 0 0 0\n",
"test 0 0 1 0 0 1 0 0 0 0 0 0 0 0\n",
"tests 0 0 1 0 0 0 0 0 0 0 0 0 0 0\n",
"time 0 0 1 0 0 0 0 0 0 0 0 0 0 0\n",
"tools 0 0 2 1 0 1 0 0 0 0 0 0 0 0\n",
"transmission 0 0 0 0 0 3 1 0 0 0 0 0 0 0\n",
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"two 0 0 2 1 0 0 0 0 0 0 0 0 0 0\n",
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"understanding 0 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
"used 0 0 0 0 1 1 0 0 0 0 0 0 0 0\n",
"using 0 0 1 0 0 0 0 0 0 0 0 0 0 0\n",
"witness 0 0 0 0 1 0 0 0 0 0 0 0 0 0\n",
"xray 0 0 1 0 2 2 0 1 0 0 0 0 0 0\n",
"years 0 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
"? 0 0 1 0 0 0 0 0 0 0 0 0 0 0\n",
"? 0 0 0 0 0 0 1 0 0 0 0 0 0 0"
]
}
],
"prompt_number": 64
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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