├── .DS_Store
├── .gitignore
├── LICENSE
├── Quick-Start.ipynb
├── README.rst
├── data
    ├── .DS_Store
    ├── .Rhistory
    ├── astro-ph.net
    ├── big_10_football_directed.gml
    ├── example.gml
    ├── example2.net
    ├── football.gml
    ├── jazz.net
    └── karate.net
├── modularity_maximization
    ├── __init__.py
    ├── _divide.py
    ├── community_newman.py
    └── utils.py
├── requirements.txt
└── setup.py


/.DS_Store:
--------------------------------------------------------------------------------
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/.gitignore:
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  1 | #
  2 | #
  3 | # My own
  4 | test.py
  5 | **/.DS_Store
  6 | **/*.swp
  7 |  
  8 | # Byte-compiled / optimized / DLL files
  9 | __pycache__/
 10 | *.py[cod]
 11 | *$py.class
 12 | 
 13 | # C extensions
 14 | *.so
 15 | 
 16 | # Distribution / packaging
 17 | .Python
 18 | env/
 19 | build/
 20 | develop-eggs/
 21 | dist/
 22 | downloads/
 23 | eggs/
 24 | .eggs/
 25 | lib/
 26 | lib64/
 27 | parts/
 28 | sdist/
 29 | var/
 30 | wheels/
 31 | *.egg-info/
 32 | .installed.cfg
 33 | *.egg
 34 | 
 35 | # PyInstaller
 36 | #  Usually these files are written by a python script from a template
 37 | #  before PyInstaller builds the exe, so as to inject date/other infos into it.
 38 | *.manifest
 39 | *.spec
 40 | 
 41 | # Installer logs
 42 | pip-log.txt
 43 | pip-delete-this-directory.txt
 44 | 
 45 | # Unit test / coverage reports
 46 | htmlcov/
 47 | .tox/
 48 | .coverage
 49 | .coverage.*
 50 | .cache
 51 | nosetests.xml
 52 | coverage.xml
 53 | *,cover
 54 | .hypothesis/
 55 | 
 56 | # Translations
 57 | *.mo
 58 | *.pot
 59 | 
 60 | # Django stuff:
 61 | *.log
 62 | local_settings.py
 63 | 
 64 | # Flask stuff:
 65 | instance/
 66 | .webassets-cache
 67 | 
 68 | # Scrapy stuff:
 69 | .scrapy
 70 | 
 71 | # Sphinx documentation
 72 | docs/_build/
 73 | 
 74 | # PyBuilder
 75 | target/
 76 | 
 77 | # Jupyter Notebook
 78 | .ipynb_checkpoints
 79 | 
 80 | # pyenv
 81 | .python-version
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 83 | # celery beat schedule file
 84 | celerybeat-schedule
 85 | 
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 87 | *.sage.py
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 90 | .env
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 93 | .venv
 94 | venv/
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 98 | .spyderproject
 99 | 
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105 | 
106 | ## My own ignore items
107 | data/.DS_Store
108 | .DS_Store
109 | *.log
110 | _site/
111 | 


--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
1 | Copyright 2018 Zhiya Zuo
2 | 
3 | Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
4 | 
5 | The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
6 | 
7 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
8 | 


--------------------------------------------------------------------------------
/Quick-Start.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "markdown",
  5 |    "metadata": {},
  6 |    "source": [
  7 |     "The following two examples use data in the both cited papers mentioned in the index page."
  8 |    ]
  9 |   },
 10 |   {
 11 |    "cell_type": "code",
 12 |    "execution_count": 1,
 13 |    "metadata": {
 14 |     "ExecuteTime": {
 15 |      "end_time": "2018-02-24T03:47:48.952511Z",
 16 |      "start_time": "2018-02-24T03:47:48.023031Z"
 17 |     }
 18 |    },
 19 |    "outputs": [
 20 |     {
 21 |      "data": {
 22 |       "text/plain": [
 23 |        "'2.0'"
 24 |       ]
 25 |      },
 26 |      "execution_count": 1,
 27 |      "metadata": {},
 28 |      "output_type": "execute_result"
 29 |     }
 30 |    ],
 31 |    "source": [
 32 |     "import networkx as nx\n",
 33 |     "nx.__version__"
 34 |    ]
 35 |   },
 36 |   {
 37 |    "cell_type": "code",
 38 |    "execution_count": 2,
 39 |    "metadata": {
 40 |     "ExecuteTime": {
 41 |      "end_time": "2018-02-24T03:47:48.967458Z",
 42 |      "start_time": "2018-02-24T03:47:48.955965Z"
 43 |     }
 44 |    },
 45 |    "outputs": [],
 46 |    "source": [
 47 |     "from modularity_maximization import partition\n",
 48 |     "from modularity_maximization.utils import get_modularity"
 49 |    ]
 50 |   },
 51 |   {
 52 |    "cell_type": "markdown",
 53 |    "metadata": {},
 54 |    "source": [
 55 |     "#### Undirected Network: Karate"
 56 |    ]
 57 |   },
 58 |   {
 59 |    "cell_type": "code",
 60 |    "execution_count": 3,
 61 |    "metadata": {
 62 |     "ExecuteTime": {
 63 |      "end_time": "2018-02-24T03:47:50.386389Z",
 64 |      "start_time": "2018-02-24T03:47:50.374798Z"
 65 |     }
 66 |    },
 67 |    "outputs": [],
 68 |    "source": [
 69 |     "karate = nx.Graph(nx.read_pajek(\"data/karate.net\"))"
 70 |    ]
 71 |   },
 72 |   {
 73 |    "cell_type": "code",
 74 |    "execution_count": 4,
 75 |    "metadata": {
 76 |     "ExecuteTime": {
 77 |      "end_time": "2018-02-24T03:47:50.910921Z",
 78 |      "start_time": "2018-02-24T03:47:50.906654Z"
 79 |     }
 80 |    },
 81 |    "outputs": [
 82 |     {
 83 |      "name": "stdout",
 84 |      "output_type": "stream",
 85 |      "text": [
 86 |       "Name: \n",
 87 |       "Type: Graph\n",
 88 |       "Number of nodes: 34\n",
 89 |       "Number of edges: 78\n",
 90 |       "Average degree:   4.5882\n"
 91 |      ]
 92 |     }
 93 |    ],
 94 |    "source": [
 95 |     "print(nx.info(karate))"
 96 |    ]
 97 |   },
 98 |   {
 99 |    "cell_type": "code",
100 |    "execution_count": 5,
101 |    "metadata": {
102 |     "ExecuteTime": {
103 |      "end_time": "2018-02-24T03:47:55.391813Z",
104 |      "start_time": "2018-02-24T03:47:51.870206Z"
105 |     }
106 |    },
107 |    "outputs": [],
108 |    "source": [
109 |     "comm_dict = partition(karate)"
110 |    ]
111 |   },
112 |   {
113 |    "cell_type": "code",
114 |    "execution_count": 6,
115 |    "metadata": {
116 |     "ExecuteTime": {
117 |      "end_time": "2018-02-24T03:47:56.754258Z",
118 |      "start_time": "2018-02-24T03:47:56.747997Z"
119 |     }
120 |    },
121 |    "outputs": [
122 |     {
123 |      "name": "stdout",
124 |      "output_type": "stream",
125 |      "text": [
126 |       "Community 3\n",
127 |       "24, 25, 26, 28, 29, 32\n",
128 |       "Community 4\n",
129 |       "9, 15, 16, 19, 21, 23, 27, 30, 31, 33, 34\n",
130 |       "Community 5\n",
131 |       "1, 2, 3, 4, 8, 10, 12, 13, 14, 18, 20, 22\n",
132 |       "Community 6\n",
133 |       "5, 6, 7, 11, 17\n"
134 |      ]
135 |     }
136 |    ],
137 |    "source": [
138 |     "for comm in set(comm_dict.values()):\n",
139 |     "    print(\"Community %d\"%comm)\n",
140 |     "    print(', '.join([node for node in comm_dict if comm_dict[node] == comm]))"
141 |    ]
142 |   },
143 |   {
144 |    "cell_type": "code",
145 |    "execution_count": 7,
146 |    "metadata": {
147 |     "ExecuteTime": {
148 |      "end_time": "2018-02-24T03:47:58.890844Z",
149 |      "start_time": "2018-02-24T03:47:58.860525Z"
150 |     }
151 |    },
152 |    "outputs": [
153 |     {
154 |      "name": "stdout",
155 |      "output_type": "stream",
156 |      "text": [
157 |       "Calculating modularity for undirected graph\n",
158 |       "Modularity of such partition for karate is 0.419\n"
159 |      ]
160 |     }
161 |    ],
162 |    "source": [
163 |     "print('Modularity of such partition for karate is %.3f' % get_modularity(karate, comm_dict))"
164 |    ]
165 |   },
166 |   {
167 |    "cell_type": "markdown",
168 |    "metadata": {},
169 |    "source": [
170 |     "#### Jazz Network"
171 |    ]
172 |   },
173 |   {
174 |    "cell_type": "code",
175 |    "execution_count": 8,
176 |    "metadata": {
177 |     "ExecuteTime": {
178 |      "end_time": "2018-02-24T03:48:02.357114Z",
179 |      "start_time": "2018-02-24T03:48:02.139954Z"
180 |     }
181 |    },
182 |    "outputs": [],
183 |    "source": [
184 |     "jazz = nx.Graph(nx.read_pajek(\"data/jazz.net\"))"
185 |    ]
186 |   },
187 |   {
188 |    "cell_type": "code",
189 |    "execution_count": 9,
190 |    "metadata": {
191 |     "ExecuteTime": {
192 |      "end_time": "2018-02-24T03:48:03.468349Z",
193 |      "start_time": "2018-02-24T03:48:03.464376Z"
194 |     }
195 |    },
196 |    "outputs": [
197 |     {
198 |      "name": "stdout",
199 |      "output_type": "stream",
200 |      "text": [
201 |       "Name: \n",
202 |       "Type: Graph\n",
203 |       "Number of nodes: 198\n",
204 |       "Number of edges: 2742\n",
205 |       "Average degree:  27.6970\n"
206 |      ]
207 |     }
208 |    ],
209 |    "source": [
210 |     "print(nx.info(jazz))"
211 |    ]
212 |   },
213 |   {
214 |    "cell_type": "code",
215 |    "execution_count": 10,
216 |    "metadata": {
217 |     "ExecuteTime": {
218 |      "end_time": "2018-02-24T03:50:17.408934Z",
219 |      "start_time": "2018-02-24T03:48:05.452336Z"
220 |     }
221 |    },
222 |    "outputs": [],
223 |    "source": [
224 |     "comm_dict = partition(jazz)"
225 |    ]
226 |   },
227 |   {
228 |    "cell_type": "code",
229 |    "execution_count": 11,
230 |    "metadata": {
231 |     "ExecuteTime": {
232 |      "end_time": "2018-02-24T03:50:20.113408Z",
233 |      "start_time": "2018-02-24T03:50:20.107210Z"
234 |     }
235 |    },
236 |    "outputs": [
237 |     {
238 |      "name": "stdout",
239 |      "output_type": "stream",
240 |      "text": [
241 |       "Community 3\n",
242 |       "3, 4, 5, 6, 13, 18, 21, 25, 26, 27, 28, 29, 37, 39, 41, 45, 47, 51, 73, 75, 76, 77, 79, 85, 86, 88, 90, 92, 96, 97, 102, 115, 124, 126, 128, 133, 136, 138, 140, 144, 145, 147, 148, 149, 152, 153, 155, 156, 157, 160, 163, 167, 169, 172, 173, 176, 180, 181, 184, 189, 191, 198\n",
243 |       "Community 4\n",
244 |       "2, 7, 10, 11, 12, 14, 19, 30, 31, 34, 36, 49, 52, 53, 54, 55, 56, 57, 61, 67, 69, 70, 71, 72, 74, 83, 87, 89, 103, 112, 113, 114, 127, 129, 130, 141, 142, 150, 151, 158, 161, 164, 165, 174, 178, 185, 186, 192, 194, 195, 196, 197\n",
245 |       "Community 5\n",
246 |       "1, 8, 15, 16, 17, 20, 22, 23, 24, 32, 33, 35, 38, 40, 42, 43, 44, 46, 48, 50, 58, 60, 62, 63, 64, 65, 66, 68, 78, 80, 81, 91, 95, 98, 99, 100, 101, 104, 105, 106, 107, 108, 109, 110, 119, 120, 122, 123, 131, 132, 134, 135, 139, 154, 159, 162, 166, 168, 170, 171, 179, 182, 187, 188\n",
247 |       "Community 6\n",
248 |       "9, 59, 82, 84, 93, 94, 111, 116, 117, 118, 121, 125, 137, 143, 146, 175, 177, 183, 190, 193\n"
249 |      ]
250 |     }
251 |    ],
252 |    "source": [
253 |     "for comm in set(comm_dict.values()):\n",
254 |     "    print(\"Community %d\"%comm)\n",
255 |     "    print(', '.join([node for node in comm_dict if comm_dict[node] == comm]))"
256 |    ]
257 |   },
258 |   {
259 |    "cell_type": "code",
260 |    "execution_count": 12,
261 |    "metadata": {
262 |     "ExecuteTime": {
263 |      "end_time": "2018-02-24T03:50:22.348238Z",
264 |      "start_time": "2018-02-24T03:50:21.746470Z"
265 |     }
266 |    },
267 |    "outputs": [
268 |     {
269 |      "name": "stdout",
270 |      "output_type": "stream",
271 |      "text": [
272 |       "Calculating modularity for undirected graph\n",
273 |       "Modularity of such partition for jazz is 0.442\n"
274 |      ]
275 |     }
276 |    ],
277 |    "source": [
278 |     "print('Modularity of such partition for jazz is %.3f' % get_modularity(jazz, comm_dict))"
279 |    ]
280 |   },
281 |   {
282 |    "cell_type": "markdown",
283 |    "metadata": {},
284 |    "source": [
285 |     "#### Directed Network: Big 10 Football Season 2005"
286 |    ]
287 |   },
288 |   {
289 |    "cell_type": "code",
290 |    "execution_count": 13,
291 |    "metadata": {
292 |     "ExecuteTime": {
293 |      "end_time": "2018-02-24T03:50:24.653189Z",
294 |      "start_time": "2018-02-24T03:50:24.642059Z"
295 |     }
296 |    },
297 |    "outputs": [],
298 |    "source": [
299 |     "big_10_football = nx.read_gml(\"data/big_10_football_directed.gml\")"
300 |    ]
301 |   },
302 |   {
303 |    "cell_type": "code",
304 |    "execution_count": 14,
305 |    "metadata": {
306 |     "ExecuteTime": {
307 |      "end_time": "2018-02-24T03:50:25.235785Z",
308 |      "start_time": "2018-02-24T03:50:25.232397Z"
309 |     }
310 |    },
311 |    "outputs": [
312 |     {
313 |      "name": "stdout",
314 |      "output_type": "stream",
315 |      "text": [
316 |       "Name: \n",
317 |       "Type: DiGraph\n",
318 |       "Number of nodes: 11\n",
319 |       "Number of edges: 44\n",
320 |       "Average in degree:   4.0000\n",
321 |       "Average out degree:   4.0000\n"
322 |      ]
323 |     }
324 |    ],
325 |    "source": [
326 |     "print(nx.info(big_10_football))"
327 |    ]
328 |   },
329 |   {
330 |    "cell_type": "code",
331 |    "execution_count": 15,
332 |    "metadata": {
333 |     "ExecuteTime": {
334 |      "end_time": "2018-02-24T03:50:26.936823Z",
335 |      "start_time": "2018-02-24T03:50:26.784698Z"
336 |     }
337 |    },
338 |    "outputs": [],
339 |    "source": [
340 |     "comm_dict = partition(big_10_football)"
341 |    ]
342 |   },
343 |   {
344 |    "cell_type": "code",
345 |    "execution_count": 16,
346 |    "metadata": {
347 |     "ExecuteTime": {
348 |      "end_time": "2018-02-24T03:50:27.764040Z",
349 |      "start_time": "2018-02-24T03:50:27.758440Z"
350 |     }
351 |    },
352 |    "outputs": [
353 |     {
354 |      "name": "stdout",
355 |      "output_type": "stream",
356 |      "text": [
357 |       "Community 1\n",
358 |       "Purdue, Illinois, MichiganState, Indiana\n",
359 |       "Community 2\n",
360 |       "Northwestern, Wisconsin, Iowa, PennState, OhioState, Michigan, Minnesota\n"
361 |      ]
362 |     }
363 |    ],
364 |    "source": [
365 |     "for comm in set(comm_dict.values()):\n",
366 |     "    print(\"Community %d\"%comm)\n",
367 |     "    print(', '.join([node for node in comm_dict if comm_dict[node] == comm]))"
368 |    ]
369 |   },
370 |   {
371 |    "cell_type": "code",
372 |    "execution_count": 17,
373 |    "metadata": {
374 |     "ExecuteTime": {
375 |      "end_time": "2018-02-24T03:50:30.539769Z",
376 |      "start_time": "2018-02-24T03:50:30.526547Z"
377 |     }
378 |    },
379 |    "outputs": [
380 |     {
381 |      "name": "stdout",
382 |      "output_type": "stream",
383 |      "text": [
384 |       "Calculating modularity for directed graph\n",
385 |       "Modularity of such partition for karate is 0.112\n"
386 |      ]
387 |     }
388 |    ],
389 |    "source": [
390 |     "print('Modularity of such partition for karate is %.3f' %\\\n",
391 |     "      get_modularity(big_10_football, comm_dict))"
392 |    ]
393 |   }
394 |  ],
395 |  "metadata": {
396 |   "kernelspec": {
397 |    "display_name": "Python 3",
398 |    "language": "python",
399 |    "name": "python3"
400 |   },
401 |   "language_info": {
402 |    "codemirror_mode": {
403 |     "name": "ipython",
404 |     "version": 3
405 |    },
406 |    "file_extension": ".py",
407 |    "mimetype": "text/x-python",
408 |    "name": "python",
409 |    "nbconvert_exporter": "python",
410 |    "pygments_lexer": "ipython3",
411 |    "version": "3.6.4"
412 |   },
413 |   "toc": {
414 |    "nav_menu": {},
415 |    "number_sections": true,
416 |    "sideBar": true,
417 |    "skip_h1_title": false,
418 |    "toc_cell": false,
419 |    "toc_position": {
420 |     "height": "836px",
421 |     "left": "0px",
422 |     "right": "1468px",
423 |     "top": "113px",
424 |     "width": "212px"
425 |    },
426 |    "toc_section_display": "block",
427 |    "toc_window_display": true
428 |   }
429 |  },
430 |  "nbformat": 4,
431 |  "nbformat_minor": 2
432 | }
433 | 


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/README.rst:
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 1 | Python implementation of Newman's spectral methods to maximize modularity.
 2 | ==========================================================================
 3 | 
 4 | See:
 5 |     - Leicht, E. A., & Newman, M. E. J. (2008). Community Structure in Directed Networks. Physical Review Letters, 100(11), 118703. https://doi.org/10.1103/PhysRevLett.100.118703
 6 | 
 7 |     - Newman, M. E. J. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America, 103(23), 8577–82. https://doi.org/10.1073/pnas.0601602103
 8 | 
 9 | A quick start: https://zhiyzuo.github.io/python-modularity-maximization/
10 | 
11 | All the datasets in ``./data`` comes from http://www-personal.umich.edu/~mejn/netdata/
12 | 
13 | Specifically, ``big_10_football_directed.gml`` is compiled by myself to test community detection for directed network. I combined data from http://www.sports-reference.com/cfb/conferences/big-ten/2005-schedule.html and the original ``football.gml`` to define the edge directions.
14 | 
15 | Change log:
16 | 
17 | - 02-23-2018
18 |   Test on Python 3
19 | 
20 | - 10-20-2017
21 |   Updated python codes to use NetworkX 2 APIs. See https://networkx.github.io/documentation/stable/release/release_2.0.html.
22 |   Later in the day, I added a wrapper function to retrieve the largest eigenvalue and vector for 2x2 matrices since scipy.sparse.linalg.eigs do not work in that case. 
23 | 


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/data/.Rhistory:
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  1 | installed.packages()
  2 | update.packages()
  3 | devtools::install_github('IRkernel/IRkernel')
  4 | IRkernel::installspec()
  5 | cat
  6 | iconv
  7 | setwd("~/Documents/OneDrive - University of Iowa/2017spring/MSCI3250/data")
  8 | df = read.table("./alcoholarm.txt")
  9 | df = read.table("./alcoholarm.txt", header = T)
 10 | View(df)
 11 | df = read.csv("alcoholarm.txt")
 12 | df = read.csv("alcoholarm.txt", sep = " ")
 13 | View(Df)
 14 | View(df)
 15 | df = read.table("./alcoholarm.txt", header = T)
 16 | View(df)
 17 | cor(df$alcohol, df$strength)
 18 | cor.test(df$alcohol, df$strength)
 19 | reg = lm(strength ~ alcohol, data = df)
 20 | summary(reg)
 21 | plot(reg)
 22 | library(ggplot2)
 23 | qplot(alcohol, strength, data = df, geom="point")
 24 | summary(reg)
 25 | qplot(alcohol, strength, data = df, geom="point") + geom_abline()
 26 | qplot(alcohol, strength, data = df, geom="point") + geom_abline(slope=reg$coefficients[1], intercept = reg$coefficients[2])
 27 | ggplot(data = df, mapping = aes(y=strength, x=alcohol)) + geom_point() + geom_smooth(method = "lm")
 28 | p = ggplot(data = df,
 29 | mapping = aes(y=strength, x=alcohol)) +
 30 | geom_point()
 31 | p
 32 | p + geom_smooth(method="lm")
 33 | setwd("~/Documents/OneDrive - University of Iowa/2017spring/MSCI3250/homework/twitter_check")
 34 | apiKey = "mQqEkrb8NiL3Z09vnkPCmFTmW"
 35 | apiSecret = "kgrwYe4rM1Gg4tgxaAseHkrXU75ox9HHoUhd2UDSSaDOaodksf"
 36 | accessToken = "181775227-wDaX2b40xsQ8By1rDrP2ZEv4xYDPeFU78OwdNmce"
 37 | tokenSecret = "vjHCedT2lsmpUKF4cGhu6iYmbknnJxmcmQof04lAVRtCX"
 38 | library(twitteR)
 39 | options(httr_oauth_cache=T) # Use direct authentication
 40 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
 41 | april = searchTwitter("April", n = 10)
 42 | april #to view the tweets
 43 | apiKey = "XhxIT07hmFHeIA4sybp0oIMYF"
 44 | apiSecret = "itnhVHyQNbgQPdNh8Ain0V3d4N1oQTMjezAQup8sCBTt2Kg0i7"
 45 | accessToken = "1228954634-ckpL7DZWv4nBIAGLyybzb3SMe9wRK67B3VwFaIZ"
 46 | tokenSecret = "qK4p7XZkLqiCUczfSevPJtw0nQlJm9i3rmwAaZqFmGVFp"
 47 | library(twitteR)
 48 | options(httr_oauth_cache=T) # Use direct authentication
 49 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
 50 | april = searchTwitter("April", n = 10)
 51 | april
 52 | apiKey<-"c6CzEhD3ZD4u4SoyckyzUlFgf"
 53 | apiSecret<-"0v2ZcNA4m7J41mdLf3qzsZ50nbfZmzvtyVIqiQJrjI3w3UEep4"
 54 | accessToken<-"380596541-wPwVpb00469zj8CfF6N7gkXf19FC3m9NSlfBL8zb"
 55 | tokenSecret<-	"bWyzE9aJcXw6J2w1MSqVJrRU0kIQjoCAfN1eSSbOyhZDk"
 56 | library(twitteR)
 57 | options(httr_oauth_cache=T) # Use direct authentication
 58 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
 59 | april = searchTwitter("April", n = 10)
 60 | april
 61 | apiKey = "IyAA5X5LRiVTMRRjGINcXgP5y"
 62 | apiSecret = "D9XMD57vankkHcQnS5OlDNfIS8X70DjaIPwv1h1YyKP7jAHViP"
 63 | accessToken = "845284982008561665-TZl8L02QKUiAnhvtxX7gU2yBEJkIdDh"
 64 | tokenSecret = "7DFK4MDNp9Od1115M6v6qpHCqzsMn9oEc3Nw6w8dx5b60"
 65 | library(twitteR)
 66 | options(httr_oauth_cache=T)
 67 | setup_twitter_oauth(apiKey,apiSecret,accessToken,tokenSecret)
 68 | april = searchTwitter("April", n = 10)
 69 | april
 70 | apikey<-"UoQM4IJkvMWGEb5EJNs8jb3KY"
 71 | apisec<-"dqs4yUG1llMRUUXZpSvF4X5aOsXUWLpsLElsMpVcBE1v2ASwom"
 72 | acctok<-"845015151375986693-yOXRaAD5BePI3yaORqrymp1bR5tBMVq"
 73 | accsec<-"SFR8UOQJjSfaoHsoWpxLSdIp7ewDnTRbQ0tnKKNoxwr2Y"
 74 | library(twitteR)
 75 | library(httr)
 76 | options(httr_oauth_cache=T)
 77 | setup_twitter_oauth(apikey, apisec, acctok, accsec)
 78 | april = searchTwitter("April", n = 10)
 79 | april
 80 | apikey ="n42YUPwSTCGfAynKyk8VB6nwb"
 81 | apisec=	"eZCusEgbeC2H149KcrhIVafMMHkYKEuurRjeSeO2gsw7K1G8DR"
 82 | acctok=	"1257096840-BjKtgc6a45YjzNMhBjs4FZ8Mc4x4taLjM2RPWyc"
 83 | accsec= "CJQCz2lSXKGJpToRUMydZoCBGqHsxMnvIVYB1n9AA2oI3"
 84 | library(twitteR)
 85 | options(httr_oauth_cache=T)
 86 | setup_twitter_oauth(apikey,apisec,acctok,accsec)
 87 | april=searchTwitter("April",n=10)
 88 | april
 89 | apiKey = "hObYCNtorNIYbvdnW9qJBwWcl"
 90 | apiSecret = "tY8Hgmv2JUHaR9qwqVodmSJ4UV6XHEVB7XbaTuU6wYNODpkscG"
 91 | accessToken = "AR1G0LD"
 92 | tokenSecret = "359579069"
 93 | library(twitteR)
 94 | options(httr_oauth_cache=T) # Use direct authentication
 95 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
 96 | april = searchTwitter("April", n = 10)
 97 | apikey = "gCxqH2gMddSF1RFiYlNzdhD0Z"
 98 | apisec = "1bcpXzqTJqTQBYcCIlWkwJTnIvJpssm2zxBUkS3ZaGCgV1DZmO"
 99 | acctok = "293665582-V1Pynxt2rnq4PxgiVbFq4IG7WZKnNXT26kNf4FrO"
100 | accsec = "cVEHe99LMfIcoSJaPhMeqYv33aQDHkd3TpV5lFfXdmxhN"
101 | library(twitteR)
102 | options(httr_oauth_cache=T) # Use direct authentication
103 | setup_twitter_oauth(apikey, apisec, acctok, accsec)
104 | apiKey = "TbYje1Bkyj1RUmyqQVl0LRvb4"
105 | apiSecret = "iVO3NRAsMPA9fByZr9wDkzVNnABDjHEQu7qzDZsNrl3gnP2DYx"
106 | accessToken = "509563108-cJGPp63OBKOSm51QoYNd6r2sjBWzfu88RDuKe6Hs"
107 | tokenSecret = "333WUmCmnDyaNP9LdFwj4XTehr0DMOmokd37Jst1vOEA1"
108 | library(twitteR)
109 | options(httr_oauth_cache=T) #use direct authentication
110 | setup_twitter_oauth(apiKey,apiSecret, accessToken, tokenSecret)
111 | april=searchTwitter("April", n=10)
112 | april
113 | apiKey = "9qmc8Y2PjPi9foFr2UVwhD2of"
114 | apiSecret = "hyb0sz5P70fbjTNJ2CaK23F6TWNlo6UXYimZsOfcCORAUtV3dq"
115 | accessToken = "2239835372-noEa9CNvvl9jy8MohOjJud3SRbFdiA5JbtSYC3h"
116 | tokenSecret = "MJH6uRoQUz5gsG2BLRCGC5olFlU9UNbSn2op1PJ9KQmd0"
117 | library(twitteR)
118 | options(httr_oauth_cache=T) # Use direct authentication
119 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
120 | apikey <- "RwjehvRsvPscmyJ7uFWvRqmvg"
121 | apiSecret <- "kZM4Nx7sbFY2tQGimEVQfV36K9fk1qVNR46nw0HXmVgp05a5hQ"
122 | acctok <- "56122401-Qy5O6YIKsj8p01Dlv9NzWW20CqQ4s1VzJmvD58bzg"
123 | accsec <- "qSUc6UCutmXvAFFKwyjAgLyTgnc5XbRDBJQ4fLwXL3ICr"
124 | library(twitteR)
125 | options(httr_oauth_cache=T)
126 | setup_twitter_oauth(apikey, apiSecret, acctok, accsec)
127 | april = searchTwitter("April", n = 10)
128 | april
129 | apiKey = "nwd4i75NJPDUlRaBEVcgQX5gX"
130 | apiSecret = "twm2IzKCCWVO4if7xG5x7a7dY9B1rIwcJ7NW3vtdACRfqqQd93"
131 | accessToken = "795124735-tUm068AALohasnA6hPV3qKZTx4xK4RdBxdxAVwSU"
132 | tokenSecret = "D0ru8sDlrvuYLqElM6ZD2GU4pYTvZT1jfDYF7aFJD0pZB"
133 | library(twitteR)
134 | options(httr_oauth_cache=T) # Use direct authentication
135 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
136 | april = searchTwitter("April", n = 10)
137 | apiKey = "TprUJKZN5zO2B5fk8M0i7yCdh"
138 | apiSecret = "kNEfkl2fT7RipO22IYEsueY3v0AqvmGwhJjLIOR1GQYh37J24N"
139 | accessToken = "849689974530297856-HiP6wwzum4UPp3rLsStzhUk6HalYWjY"
140 | tokenSecret = "PvUBifg6Th67rOoU140ulgADZaB4mxyaMItAXBRdyZ27g"
141 | library(twitteR)
142 | options(httr_oauth_cache=T) # Use direct authentication
143 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
144 | april = searchTwitter("April", n = 10)
145 | apiKey = "VDPsXl0aQitI5C5JaeucgXXfJ"
146 | apiSecret = "pWZjGiVnhjqzxQSiWGbLiUQdOKYtsr205oDb4Rjac8iFAXnK4E"
147 | accessToken = "839721192-puK8TwLvdfml9qrrLd4yzanMx8e6M88HZmI9kVVx"
148 | tokenSecret = "nIBQn2Y20PEPwzbeabeHO2NYgnXVLbwuPA1gT55RaCvt4"
149 | library(twitteR)
150 | options(httr_oauth_cache=T) # Use direct authentication
151 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
152 | april = searchTwitter("April", n = 10)
153 | apiKey = "VsanIG75M4Gs6FqLskEUrUVVJ"
154 | apiSecret = "vpxNfu5A2mRUa8M7k45RrbXny5038gMdbVbeWI7j2Vj5bRn23R"
155 | accessToken = "845014410972352513-wInew1zHFwSbCx4BCPZxAwG2yp2F7JF"
156 | tokenSecret = "SknZMMxYT8kM7A7gxG73X0My3tDjf7yhrNLdUrRUbfqRB"
157 | library(twitteR)
158 | options(httr_oauth_cache=T) # Use direct authentication
159 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
160 | april = searchTwitter("April", n = 10)
161 | apiKey = "rPC5CGgsOcJs5sDXQaAGVvtKY"
162 | apiSecret = "5Admoi3aRpNrsnP2wTVKuUAtCDlNoueJs6rpF83TcBEISTPo5t"
163 | accessToken = "35209286-APLp2jav0Qf2lhuvl9zDcxeOzDP2yLbeQv3uixgbF"
164 | tokenSecret = "aZtR9A1cSsGNulkTTNuYUFAtn5pnmuuaJg4zNRtAzUF7E"
165 | library(twitteR)
166 | options(httr_oauth_cache=T) # Use direct authentication
167 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
168 | april = searchTwitter("April", n = 10)
169 | apiKey <- "jsQZVrQ7uAWwG15fr4PGJeo2H"
170 | apiSecret <- "gVXuvhpjk0HnUl5Fko9z0ltQyQA9tp0FK4GritnDbJaLv5rdbi"
171 | accessToken <- "2753008655-GnAOd5HMAAw230td5mEdyGavKN5fv5SCovxC6PV"
172 | tokenSecret <- "tEAn1Gi0UBduDJi065rGCcXzuKLJvQlhKvnCCm5jiikfd"
173 | library(twitteR)
174 | options(httr_oauth_cache = T) # Use direct authentication
175 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
176 | april = searchTwitter("April", n = 10)
177 | apiKey = "p0PFfno9nFSYEbnFYwQuUp8HJ"
178 | apiSecret = "OpjSKbQSc1nSC13RVEUcc9bBLVP4kofASZXlIeNO8I9n6p8vfe"
179 | accessToken = "3330611174-c0B2BNOiEmIAqBaXxIG8DX55hHrgUTsbbhXmPrW"
180 | tokenSecret = "EnSEaDdja6lctcONOu5WdeQscn2Mj7ELLpiJTfw19QzET"
181 | library(twitteR)
182 | options(httr_oauth_cache=T) # Use direct authentication
183 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
184 | april = searchTwitter("April", n = 10)
185 | apiKey ="Mwrofqc5eVhanVd78mtznKbvK"
186 | apiSecret ="VxdyGTRdvKyI8rqipa3eSzkEUbk6LKCNKi6uhPdQYqYoXcAFSz"
187 | accessToken ="415929583-f65h88QNaRZg4e0qylEMHzCInSPbXRbnET9GvPaH"
188 | tokenSecret ="0pmMILEb5AD58FVYFvNfTUZ5s37D2QTpUKyKzfz2F7EwB"
189 | library(twitteR)
190 | options(httr_oauth_cache=T) # Use direct authentication
191 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
192 | april = searchTwitter("April", n = 10)
193 | apiKey ="Mwrofqc5eVhanVd78mtznKbvK"
194 | apiSecret ="VxdyGTRdvKyI8rqipa3eSzkEUbk6LKCNKi6uhPdQYqYoXcAFSz"
195 | accessToken ="415929583-f65h88QNaRZg4e0qylEMHzCInSPbXRbnET9GvPaH"
196 | tokenSecret ="0pmMILEb5AD58FVYFvNfTUZ5s37D2QTpUKyKzfz2F7EwB"
197 | library(twitteR)
198 | options(httr_oauth_cache=T) # Use direct authentication
199 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
200 | april = searchTwitter("April", n = 10)
201 | apiKey = "AEc7TZeGdyrklpnFKDZtbuAdZ"
202 | apiSecret = "G5ayYj3CsAiKegVrE84PSdeOpuGoQ8gAnO3mBbaIztWlyYjSAS"
203 | accessToken = "833360383675072512-owtS6mffoZBPlLblVh0IUX51IdEVMOq"
204 | tokenSecret = "Ay1m0yB5XTVJatR6qww6OwBFiM9r0hbPamrHwhWfZgaJp"
205 | library(twitteR)
206 | options(httr_oauth_cache=T) # Use direct authentication
207 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
208 | april = searchTwitter("April", n = 10)
209 | apiKey = "AEc7TZeGdyrklpnFKDZtbuAdZ"
210 | apiSecret = "G5ayYj3CsAiKegVrE84PSdeOpuGoQ8gAnO3mBbaIztWlyYjSAS"
211 | accessToken = "833360383675072512-owtS6mffoZBPlLblVh0IUX51IdEVMOq"
212 | tokenSecret = "Ay1m0yB5XTVJatR6qww6OwBFiM9r0hbPamrHwhWfZgaJp"
213 | library(twitteR)
214 | options(httr_oauth_cache=T) # Use direct authentication
215 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
216 | april = searchTwitter("April", n = 10)
217 | apiKey = "Wi5yDU8114oHxYfi4eyFZaKAh"
218 | apiSecret = "uwgFPwUnly49S42XqeHd5biqmAZ02UQFGIXM0PudQzuV1vEWuG"
219 | accessToken = "849742355833999361-dEoHhqn2cqIAQM0sfdd2pof35YGUa9y"
220 | tokenSecret = "Tk0OULH5oNRmnwhEMb4Kpu7sIgf3fCoDFlr5SIROfYTR3"
221 | library(twitteR)
222 | options(httr_oauth_cache=T) # Use direct authentication
223 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
224 | april = searchTwitter("April", n = 10)
225 | apiKey = "EnzXLlpdpBGwBczzZOF1qDII8"
226 | apiSecret = "VUvRXoRDjlWo00qNI1kQOKUYjEIw1WCAuRb0eVLu5uzOyXvIZK"
227 | accessToken = "720438376961167360-6IgaWV2vXqgh7AbCCoECZzTWHIApGIN"
228 | tokenSecret = "SQHBvyi7zvn2VlJp6Rv3aNf5WRf7DSsEcySrsnRiE0DIr"
229 | library(twitteR)
230 | options(httr_oauth_cache=T) # Use direct authentication
231 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
232 | april = searchTwitter("April", n = 10)
233 | apikey =	"wBotLUrNGxorXCrKVnJQnTKXx"
234 | apisec = 	"TEA5crvF7Mv2Kuy1sqlCGBsJwDsNTzbJxB7iKxw7gZhionYJ9O"
235 | acctok = "845284983413657600-CoMllxVeOpJNLhqVP4wuKoXlz1ky4Du"
236 | accsec = "c78QEXLxpuFRxYn7tQ3QjpdSlkyhi7FT3VBBoqjY3iDvw"
237 | library(twitteR)
238 | options(httr_oauth_cache = T)
239 | setup_twitter_oauth(apikey,apisec,acctok,accsec)
240 | april = searchTwitter("April", n = 10)
241 | apiKey = "lineLPgwQmHKTmhWirjtetbAB"
242 | apiSecret = "Cse06Kvm755l0uCB5ujjWuAdKKf7Zpzi4OARsa40VHnsf5eiEr"
243 | accessToken = "2815731852-UmA0BVsKJ2p40lJGTKjCYRq8wS6WPEza6sVv4Pg"
244 | tokenSecret = "rust3taHRbmKtaRInhPCMHjnW8ttPfmBU9FsvBM0EJpoP"
245 | library(twitteR)
246 | options(httr_oauth_cache=T) # Use direct authentication
247 | setup_twitter_oauth(apiKey, apiSecret, accessToken, tokenSecret)
248 | april = searchTwitter("April", n = 10)
249 | setwd("~/Documents/OneDrive - University of Iowa/2017spring/MSCI3250/data")
250 | df = read.csv("alcoholarm.txt")
251 | View(df)
252 | df = read.csv("alcoholarm.txt", sep = "\t")
253 | df = read.table("alcoholarm.txt")
254 | df = read.table("alcoholarm.txt", header = T)
255 | cor(df$alcohol, df$strength)
256 | cor.test(df$alcohol, df$strength)
257 | reg = lm(strength ~ alcohol, data = df)
258 | summary(reg)
259 | p = ggplot(data = df,
260 | mapping = aes(y=strength,
261 | x=alcohol))
262 | + geom_point()
263 | library(ggplto2)
264 | library(ggplot2)
265 | p = ggplot(data = df,
266 | mapping = aes(y=strength,
267 | x=alcohol))
268 | + geom_point()
269 | p = ggplot(data = df,
270 | mapping = aes(y=strength,
271 | x=alcohol)) +
272 | geom_point()
273 | p
274 | p + geom_smooth()
275 | p + geom_smooth(method="lm")
276 | install.packages("modMax")
277 | setwd("~/Documents/python-modularity-maximization/data")
278 | library(modMax)
279 | g = read.graph("karate.gml",format="gml")
280 | A = adjacent_vertices(g)
281 | g
282 | A = get.adjacency(g)
283 | A
284 | comm = spectralOptimization(A)
285 | comm
286 | comm = spectralOptimization(A, refine = T)
287 | comm
288 | multiWay(A)
289 | A
290 | spectral1(A)
291 | spectral2(A)
292 | A
293 | g
294 | eb <- cluster_edge_betweenness(g)
295 | eb
296 | eb$membership
297 | eb
298 | eb <- cluster_edge_betweenness(g)
299 | eb
300 | remove.packages("modMax")
301 | spectrum
302 | comm = spectrum(g)
303 | com
304 | comm
305 | comm=leading.eigenvector.community(g)
306 | comm
307 | comm=leading.eigenvector.community(g)
308 | comm
309 | comm=leading.eigenvector.community(g)
310 | comm
311 | cluster_leading_eigen()
312 | cluster_leading_eigen(g)
313 | cluster_leading_eigen(g)
314 | cluster_edge_betweenness(g)
315 | cluster_edge_betweenness(g)
316 | cluster_fast_greedy(g)
317 | cluster_fast_greedy(g)
318 | cluster_fast_greedy(g)
319 | 


--------------------------------------------------------------------------------
/data/big_10_football_directed.gml:
--------------------------------------------------------------------------------
  1 | graph [
  2 |   directed 1
  3 |   node [
  4 |     id 0
  5 |     label "Northwestern"
  6 |     win 1
  7 |   ]
  8 |   node [
  9 |     id 1
 10 |     label "Wisconsin"
 11 |     win 1
 12 |   ]
 13 |   node [
 14 |     id 2
 15 |     label "Iowa"
 16 |     win 1
 17 |   ]
 18 |   node [
 19 |     id 3
 20 |     label "PennState"
 21 |     win 1
 22 |   ]
 23 |   node [
 24 |     id 4
 25 |     label "OhioState"
 26 |     win 1
 27 |   ]
 28 |   node [
 29 |     id 5
 30 |     label "Michigan"
 31 |     win 1
 32 |   ]
 33 |   node [
 34 |     id 6
 35 |     label "Purdue"
 36 |     win 0
 37 |   ]
 38 |   node [
 39 |     id 7
 40 |     label "Minnesota"
 41 |     win 1
 42 |   ]
 43 |   node [
 44 |     id 8
 45 |     label "Illinois"
 46 |     win 0
 47 |   ]
 48 |   node [
 49 |     id 9
 50 |     label "MichiganState"
 51 |     win 0
 52 |   ]
 53 |   node [
 54 |     id 10
 55 |     label "Indiana"
 56 |     win 0
 57 |   ]
 58 |   edge [
 59 |     source 0
 60 |     target 8
 61 |   ]
 62 |   edge [
 63 |     source 0
 64 |     target 9
 65 |   ]
 66 |   edge [
 67 |     source 0
 68 |     target 2
 69 |   ]
 70 |   edge [
 71 |     source 0
 72 |     target 1
 73 |   ]
 74 |   edge [
 75 |     source 0
 76 |     target 6
 77 |   ]
 78 |   edge [
 79 |     source 1
 80 |     target 10
 81 |   ]
 82 |   edge [
 83 |     source 1
 84 |     target 5
 85 |   ]
 86 |   edge [
 87 |     source 1
 88 |     target 8
 89 |   ]
 90 |   edge [
 91 |     source 1
 92 |     target 7
 93 |   ]
 94 |   edge [
 95 |     source 1
 96 |     target 6
 97 |   ]
 98 |   edge [
 99 |     source 2
100 |     target 10
101 |   ]
102 |   edge [
103 |     source 2
104 |     target 6
105 |   ]
106 |   edge [
107 |     source 2
108 |     target 1
109 |   ]
110 |   edge [
111 |     source 2
112 |     target 7
113 |   ]
114 |   edge [
115 |     source 2
116 |     target 8
117 |   ]
118 |   edge [
119 |     source 3
120 |     target 4
121 |   ]
122 |   edge [
123 |     source 3
124 |     target 0
125 |   ]
126 |   edge [
127 |     source 3
128 |     target 1
129 |   ]
130 |   edge [
131 |     source 3
132 |     target 6
133 |   ]
134 |   edge [
135 |     source 3
136 |     target 7
137 |   ]
138 |   edge [
139 |     source 3
140 |     target 8
141 |   ]
142 |   edge [
143 |     source 3
144 |     target 9
145 |   ]
146 |   edge [
147 |     source 4
148 |     target 0
149 |   ]
150 |   edge [
151 |     source 4
152 |     target 2
153 |   ]
154 |   edge [
155 |     source 4
156 |     target 5
157 |   ]
158 |   edge [
159 |     source 4
160 |     target 7
161 |   ]
162 |   edge [
163 |     source 4
164 |     target 8
165 |   ]
166 |   edge [
167 |     source 4
168 |     target 9
169 |   ]
170 |   edge [
171 |     source 4
172 |     target 10
173 |   ]
174 |   edge [
175 |     source 5
176 |     target 3
177 |   ]
178 |   edge [
179 |     source 5
180 |     target 2
181 |   ]
182 |   edge [
183 |     source 5
184 |     target 9
185 |   ]
186 |   edge [
187 |     source 5
188 |     target 10
189 |   ]
190 |   edge [
191 |     source 5
192 |     target 0
193 |   ]
194 |   edge [
195 |     source 6
196 |     target 10
197 |   ]
198 |   edge [
199 |     source 6
200 |     target 9
201 |   ]
202 |   edge [
203 |     source 6
204 |     target 8
205 |   ]
206 |   edge [
207 |     source 7
208 |     target 10
209 |   ]
210 |   edge [
211 |     source 7
212 |     target 5
213 |   ]
214 |   edge [
215 |     source 7
216 |     target 9
217 |   ]
218 |   edge [
219 |     source 7
220 |     target 6
221 |   ]
222 |   edge [
223 |     source 9
224 |     target 10
225 |   ]
226 |   edge [
227 |     source 9
228 |     target 8
229 |   ]
230 |   edge [
231 |     source 10
232 |     target 8
233 |   ]
234 | ]
235 | 


--------------------------------------------------------------------------------
/data/example.gml:
--------------------------------------------------------------------------------
 1 | graph [
 2 |   node [
 3 |     id 0
 4 |     label 1
 5 |   ]
 6 |   node [
 7 |     id 1
 8 |     label 2
 9 |   ]
10 |   node [
11 |     id 2
12 |     label 3
13 |   ]
14 |   node [
15 |     id 3
16 |     label 4
17 |   ]
18 |   node [
19 |     id 4
20 |     label 5
21 |   ]
22 |   edge [
23 |     source 0
24 |     target 1
25 |   ]
26 |   edge [
27 |     source 2
28 |     target 3
29 |   ]
30 |   edge [
31 |     source 2
32 |     target 4
33 |   ]
34 |   edge [
35 |     source 3
36 |     target 4
37 |   ]
38 | ]
39 | 


--------------------------------------------------------------------------------
/data/example2.net:
--------------------------------------------------------------------------------
 1 | *Vertices 9
 2 | 1 "1" -449.1672 497.33185 0.0
 3 | 2 "2" -399.04553 441.4302 0.0
 4 | 3 "3" -510.8554 429.86435 0.0
 5 | 4 "4" -71.32698 489.62128 0.0
 6 | 5 "5" -125.30415 439.50256 0.0
 7 | 6 "6" -17.349806 427.9367 0.0
 8 | 7 "7" -318.07977 262.15942 0.0
 9 | 8 "8" -381.69574 200.47485 0.0
10 | 9 "9" -256.39157 200.47485 0.0
11 | *Edges
12 | 1 2 1.0
13 | 1 3 1.0
14 | 3 2 1.0
15 | 4 5 1.0
16 | 5 6 1.0
17 | 6 4 1.0
18 | 7 8 1.0
19 | 8 9 1.0
20 | 9 7 1.0
21 | 7 2 1.0
22 | 


--------------------------------------------------------------------------------
/data/football.gml:
--------------------------------------------------------------------------------
   1 | Creator "Mark Newman on Sat Jul 22 05:32:16 2006"
   2 | graph
   3 | [
   4 |   directed 0
   5 |   node
   6 |   [
   7 |     id 0
   8 |     label "BrighamYoung"
   9 |     value 7
  10 |   ]
  11 |   node
  12 |   [
  13 |     id 1
  14 |     label "FloridaState"
  15 |     value 0
  16 |   ]
  17 |   node
  18 |   [
  19 |     id 2
  20 |     label "Iowa"
  21 |     value 2
  22 |   ]
  23 |   node
  24 |   [
  25 |     id 3
  26 |     label "KansasState"
  27 |     value 3
  28 |   ]
  29 |   node
  30 |   [
  31 |     id 4
  32 |     label "NewMexico"
  33 |     value 7
  34 |   ]
  35 |   node
  36 |   [
  37 |     id 5
  38 |     label "TexasTech"
  39 |     value 3
  40 |   ]
  41 |   node
  42 |   [
  43 |     id 6
  44 |     label "PennState"
  45 |     value 2
  46 |   ]
  47 |   node
  48 |   [
  49 |     id 7
  50 |     label "SouthernCalifornia"
  51 |     value 8
  52 |   ]
  53 |   node
  54 |   [
  55 |     id 8
  56 |     label "ArizonaState"
  57 |     value 8
  58 |   ]
  59 |   node
  60 |   [
  61 |     id 9
  62 |     label "SanDiegoState"
  63 |     value 7
  64 |   ]
  65 |   node
  66 |   [
  67 |     id 10
  68 |     label "Baylor"
  69 |     value 3
  70 |   ]
  71 |   node
  72 |   [
  73 |     id 11
  74 |     label "NorthTexas"
  75 |     value 10
  76 |   ]
  77 |   node
  78 |   [
  79 |     id 12
  80 |     label "NorthernIllinois"
  81 |     value 6
  82 |   ]
  83 |   node
  84 |   [
  85 |     id 13
  86 |     label "Northwestern"
  87 |     value 2
  88 |   ]
  89 |   node
  90 |   [
  91 |     id 14
  92 |     label "WesternMichigan"
  93 |     value 6
  94 |   ]
  95 |   node
  96 |   [
  97 |     id 15
  98 |     label "Wisconsin"
  99 |     value 2
 100 |   ]
 101 |   node
 102 |   [
 103 |     id 16
 104 |     label "Wyoming"
 105 |     value 7
 106 |   ]
 107 |   node
 108 |   [
 109 |     id 17
 110 |     label "Auburn"
 111 |     value 9
 112 |   ]
 113 |   node
 114 |   [
 115 |     id 18
 116 |     label "Akron"
 117 |     value 6
 118 |   ]
 119 |   node
 120 |   [
 121 |     id 19
 122 |     label "VirginiaTech"
 123 |     value 1
 124 |   ]
 125 |   node
 126 |   [
 127 |     id 20
 128 |     label "Alabama"
 129 |     value 9
 130 |   ]
 131 |   node
 132 |   [
 133 |     id 21
 134 |     label "UCLA"
 135 |     value 8
 136 |   ]
 137 |   node
 138 |   [
 139 |     id 22
 140 |     label "Arizona"
 141 |     value 8
 142 |   ]
 143 |   node
 144 |   [
 145 |     id 23
 146 |     label "Utah"
 147 |     value 7
 148 |   ]
 149 |   node
 150 |   [
 151 |     id 24
 152 |     label "ArkansasState"
 153 |     value 10
 154 |   ]
 155 |   node
 156 |   [
 157 |     id 25
 158 |     label "NorthCarolinaState"
 159 |     value 0
 160 |   ]
 161 |   node
 162 |   [
 163 |     id 26
 164 |     label "BallState"
 165 |     value 6
 166 |   ]
 167 |   node
 168 |   [
 169 |     id 27
 170 |     label "Florida"
 171 |     value 9
 172 |   ]
 173 |   node
 174 |   [
 175 |     id 28
 176 |     label "BoiseState"
 177 |     value 11
 178 |   ]
 179 |   node
 180 |   [
 181 |     id 29
 182 |     label "BostonCollege"
 183 |     value 1
 184 |   ]
 185 |   node
 186 |   [
 187 |     id 30
 188 |     label "WestVirginia"
 189 |     value 1
 190 |   ]
 191 |   node
 192 |   [
 193 |     id 31
 194 |     label "BowlingGreenState"
 195 |     value 6
 196 |   ]
 197 |   node
 198 |   [
 199 |     id 32
 200 |     label "Michigan"
 201 |     value 2
 202 |   ]
 203 |   node
 204 |   [
 205 |     id 33
 206 |     label "Virginia"
 207 |     value 0
 208 |   ]
 209 |   node
 210 |   [
 211 |     id 34
 212 |     label "Buffalo"
 213 |     value 6
 214 |   ]
 215 |   node
 216 |   [
 217 |     id 35
 218 |     label "Syracuse"
 219 |     value 1
 220 |   ]
 221 |   node
 222 |   [
 223 |     id 36
 224 |     label "CentralFlorida"
 225 |     value 5
 226 |   ]
 227 |   node
 228 |   [
 229 |     id 37
 230 |     label "GeorgiaTech"
 231 |     value 0
 232 |   ]
 233 |   node
 234 |   [
 235 |     id 38
 236 |     label "CentralMichigan"
 237 |     value 6
 238 |   ]
 239 |   node
 240 |   [
 241 |     id 39
 242 |     label "Purdue"
 243 |     value 2
 244 |   ]
 245 |   node
 246 |   [
 247 |     id 40
 248 |     label "Colorado"
 249 |     value 3
 250 |   ]
 251 |   node
 252 |   [
 253 |     id 41
 254 |     label "ColoradoState"
 255 |     value 7
 256 |   ]
 257 |   node
 258 |   [
 259 |     id 42
 260 |     label "Connecticut"
 261 |     value 5
 262 |   ]
 263 |   node
 264 |   [
 265 |     id 43
 266 |     label "EasternMichigan"
 267 |     value 6
 268 |   ]
 269 |   node
 270 |   [
 271 |     id 44
 272 |     label "EastCarolina"
 273 |     value 4
 274 |   ]
 275 |   node
 276 |   [
 277 |     id 45
 278 |     label "Duke"
 279 |     value 0
 280 |   ]
 281 |   node
 282 |   [
 283 |     id 46
 284 |     label "FresnoState"
 285 |     value 11
 286 |   ]
 287 |   node
 288 |   [
 289 |     id 47
 290 |     label "OhioState"
 291 |     value 2
 292 |   ]
 293 |   node
 294 |   [
 295 |     id 48
 296 |     label "Houston"
 297 |     value 4
 298 |   ]
 299 |   node
 300 |   [
 301 |     id 49
 302 |     label "Rice"
 303 |     value 11
 304 |   ]
 305 |   node
 306 |   [
 307 |     id 50
 308 |     label "Idaho"
 309 |     value 10
 310 |   ]
 311 |   node
 312 |   [
 313 |     id 51
 314 |     label "Washington"
 315 |     value 8
 316 |   ]
 317 |   node
 318 |   [
 319 |     id 52
 320 |     label "Kansas"
 321 |     value 3
 322 |   ]
 323 |   node
 324 |   [
 325 |     id 53
 326 |     label "SouthernMethodist"
 327 |     value 11
 328 |   ]
 329 |   node
 330 |   [
 331 |     id 54
 332 |     label "Kent"
 333 |     value 6
 334 |   ]
 335 |   node
 336 |   [
 337 |     id 55
 338 |     label "Pittsburgh"
 339 |     value 1
 340 |   ]
 341 |   node
 342 |   [
 343 |     id 56
 344 |     label "Kentucky"
 345 |     value 9
 346 |   ]
 347 |   node
 348 |   [
 349 |     id 57
 350 |     label "Louisville"
 351 |     value 4
 352 |   ]
 353 |   node
 354 |   [
 355 |     id 58
 356 |     label "LouisianaTech"
 357 |     value 11
 358 |   ]
 359 |   node
 360 |   [
 361 |     id 59
 362 |     label "LouisianaMonroe"
 363 |     value 10
 364 |   ]
 365 |   node
 366 |   [
 367 |     id 60
 368 |     label "Minnesota"
 369 |     value 2
 370 |   ]
 371 |   node
 372 |   [
 373 |     id 61
 374 |     label "MiamiOhio"
 375 |     value 6
 376 |   ]
 377 |   node
 378 |   [
 379 |     id 62
 380 |     label "Vanderbilt"
 381 |     value 9
 382 |   ]
 383 |   node
 384 |   [
 385 |     id 63
 386 |     label "MiddleTennesseeState"
 387 |     value 10
 388 |   ]
 389 |   node
 390 |   [
 391 |     id 64
 392 |     label "Illinois"
 393 |     value 2
 394 |   ]
 395 |   node
 396 |   [
 397 |     id 65
 398 |     label "MississippiState"
 399 |     value 9
 400 |   ]
 401 |   node
 402 |   [
 403 |     id 66
 404 |     label "Memphis"
 405 |     value 4
 406 |   ]
 407 |   node
 408 |   [
 409 |     id 67
 410 |     label "Nevada"
 411 |     value 11
 412 |   ]
 413 |   node
 414 |   [
 415 |     id 68
 416 |     label "Oregon"
 417 |     value 8
 418 |   ]
 419 |   node
 420 |   [
 421 |     id 69
 422 |     label "NewMexicoState"
 423 |     value 10
 424 |   ]
 425 |   node
 426 |   [
 427 |     id 70
 428 |     label "SouthCarolina"
 429 |     value 9
 430 |   ]
 431 |   node
 432 |   [
 433 |     id 71
 434 |     label "Ohio"
 435 |     value 6
 436 |   ]
 437 |   node
 438 |   [
 439 |     id 72
 440 |     label "IowaState"
 441 |     value 3
 442 |   ]
 443 |   node
 444 |   [
 445 |     id 73
 446 |     label "SanJoseState"
 447 |     value 11
 448 |   ]
 449 |   node
 450 |   [
 451 |     id 74
 452 |     label "Nebraska"
 453 |     value 3
 454 |   ]
 455 |   node
 456 |   [
 457 |     id 75
 458 |     label "SouthernMississippi"
 459 |     value 4
 460 |   ]
 461 |   node
 462 |   [
 463 |     id 76
 464 |     label "Tennessee"
 465 |     value 9
 466 |   ]
 467 |   node
 468 |   [
 469 |     id 77
 470 |     label "Stanford"
 471 |     value 8
 472 |   ]
 473 |   node
 474 |   [
 475 |     id 78
 476 |     label "WashingtonState"
 477 |     value 8
 478 |   ]
 479 |   node
 480 |   [
 481 |     id 79
 482 |     label "Temple"
 483 |     value 1
 484 |   ]
 485 |   node
 486 |   [
 487 |     id 80
 488 |     label "Navy"
 489 |     value 5
 490 |   ]
 491 |   node
 492 |   [
 493 |     id 81
 494 |     label "TexasA&M"
 495 |     value 3
 496 |   ]
 497 |   node
 498 |   [
 499 |     id 82
 500 |     label "NotreDame"
 501 |     value 5
 502 |   ]
 503 |   node
 504 |   [
 505 |     id 83
 506 |     label "TexasElPaso"
 507 |     value 11
 508 |   ]
 509 |   node
 510 |   [
 511 |     id 84
 512 |     label "Oklahoma"
 513 |     value 3
 514 |   ]
 515 |   node
 516 |   [
 517 |     id 85
 518 |     label "Toledo"
 519 |     value 6
 520 |   ]
 521 |   node
 522 |   [
 523 |     id 86
 524 |     label "Tulane"
 525 |     value 4
 526 |   ]
 527 |   node
 528 |   [
 529 |     id 87
 530 |     label "Mississippi"
 531 |     value 9
 532 |   ]
 533 |   node
 534 |   [
 535 |     id 88
 536 |     label "Tulsa"
 537 |     value 11
 538 |   ]
 539 |   node
 540 |   [
 541 |     id 89
 542 |     label "NorthCarolina"
 543 |     value 0
 544 |   ]
 545 |   node
 546 |   [
 547 |     id 90
 548 |     label "UtahState"
 549 |     value 5
 550 |   ]
 551 |   node
 552 |   [
 553 |     id 91
 554 |     label "Army"
 555 |     value 4
 556 |   ]
 557 |   node
 558 |   [
 559 |     id 92
 560 |     label "Cincinnati"
 561 |     value 4
 562 |   ]
 563 |   node
 564 |   [
 565 |     id 93
 566 |     label "AirForce"
 567 |     value 7
 568 |   ]
 569 |   node
 570 |   [
 571 |     id 94
 572 |     label "Rutgers"
 573 |     value 1
 574 |   ]
 575 |   node
 576 |   [
 577 |     id 95
 578 |     label "Georgia"
 579 |     value 9
 580 |   ]
 581 |   node
 582 |   [
 583 |     id 96
 584 |     label "LouisianaState"
 585 |     value 9
 586 |   ]
 587 |   node
 588 |   [
 589 |     id 97
 590 |     label "LouisianaLafayette"
 591 |     value 10
 592 |   ]
 593 |   node
 594 |   [
 595 |     id 98
 596 |     label "Texas"
 597 |     value 3
 598 |   ]
 599 |   node
 600 |   [
 601 |     id 99
 602 |     label "Marshall"
 603 |     value 6
 604 |   ]
 605 |   node
 606 |   [
 607 |     id 100
 608 |     label "MichiganState"
 609 |     value 2
 610 |   ]
 611 |   node
 612 |   [
 613 |     id 101
 614 |     label "MiamiFlorida"
 615 |     value 1
 616 |   ]
 617 |   node
 618 |   [
 619 |     id 102
 620 |     label "Missouri"
 621 |     value 3
 622 |   ]
 623 |   node
 624 |   [
 625 |     id 103
 626 |     label "Clemson"
 627 |     value 0
 628 |   ]
 629 |   node
 630 |   [
 631 |     id 104
 632 |     label "NevadaLasVegas"
 633 |     value 7
 634 |   ]
 635 |   node
 636 |   [
 637 |     id 105
 638 |     label "WakeForest"
 639 |     value 0
 640 |   ]
 641 |   node
 642 |   [
 643 |     id 106
 644 |     label "Indiana"
 645 |     value 2
 646 |   ]
 647 |   node
 648 |   [
 649 |     id 107
 650 |     label "OklahomaState"
 651 |     value 3
 652 |   ]
 653 |   node
 654 |   [
 655 |     id 108
 656 |     label "OregonState"
 657 |     value 8
 658 |   ]
 659 |   node
 660 |   [
 661 |     id 109
 662 |     label "Maryland"
 663 |     value 0
 664 |   ]
 665 |   node
 666 |   [
 667 |     id 110
 668 |     label "TexasChristian"
 669 |     value 4
 670 |   ]
 671 |   node
 672 |   [
 673 |     id 111
 674 |     label "California"
 675 |     value 8
 676 |   ]
 677 |   node
 678 |   [
 679 |     id 112
 680 |     label "AlabamaBirmingham"
 681 |     value 4
 682 |   ]
 683 |   node
 684 |   [
 685 |     id 113
 686 |     label "Arkansas"
 687 |     value 9
 688 |   ]
 689 |   node
 690 |   [
 691 |     id 114
 692 |     label "Hawaii"
 693 |     value 11
 694 |   ]
 695 |   edge
 696 |   [
 697 |     source 1
 698 |     target 0
 699 |   ]
 700 |   edge
 701 |   [
 702 |     source 3
 703 |     target 2
 704 |   ]
 705 |   edge
 706 |   [
 707 |     source 4
 708 |     target 0
 709 |   ]
 710 |   edge
 711 |   [
 712 |     source 5
 713 |     target 4
 714 |   ]
 715 |   edge
 716 |   [
 717 |     source 5
 718 |     target 3
 719 |   ]
 720 |   edge
 721 |   [
 722 |     source 6
 723 |     target 2
 724 |   ]
 725 |   edge
 726 |   [
 727 |     source 7
 728 |     target 6
 729 |   ]
 730 |   edge
 731 |   [
 732 |     source 8
 733 |     target 7
 734 |   ]
 735 |   edge
 736 |   [
 737 |     source 9
 738 |     target 8
 739 |   ]
 740 |   edge
 741 |   [
 742 |     source 9
 743 |     target 0
 744 |   ]
 745 |   edge
 746 |   [
 747 |     source 9
 748 |     target 4
 749 |   ]
 750 |   edge
 751 |   [
 752 |     source 10
 753 |     target 5
 754 |   ]
 755 |   edge
 756 |   [
 757 |     source 11
 758 |     target 10
 759 |   ]
 760 |   edge
 761 |   [
 762 |     source 11
 763 |     target 5
 764 |   ]
 765 |   edge
 766 |   [
 767 |     source 11
 768 |     target 3
 769 |   ]
 770 |   edge
 771 |   [
 772 |     source 13
 773 |     target 12
 774 |   ]
 775 |   edge
 776 |   [
 777 |     source 13
 778 |     target 2
 779 |   ]
 780 |   edge
 781 |   [
 782 |     source 14
 783 |     target 2
 784 |   ]
 785 |   edge
 786 |   [
 787 |     source 14
 788 |     target 12
 789 |   ]
 790 |   edge
 791 |   [
 792 |     source 15
 793 |     target 14
 794 |   ]
 795 |   edge
 796 |   [
 797 |     source 15
 798 |     target 13
 799 |   ]
 800 |   edge
 801 |   [
 802 |     source 15
 803 |     target 2
 804 |   ]
 805 |   edge
 806 |   [
 807 |     source 16
 808 |     target 4
 809 |   ]
 810 |   edge
 811 |   [
 812 |     source 16
 813 |     target 9
 814 |   ]
 815 |   edge
 816 |   [
 817 |     source 16
 818 |     target 0
 819 |   ]
 820 |   edge
 821 |   [
 822 |     source 17
 823 |     target 16
 824 |   ]
 825 |   edge
 826 |   [
 827 |     source 17
 828 |     target 12
 829 |   ]
 830 |   edge
 831 |   [
 832 |     source 18
 833 |     target 12
 834 |   ]
 835 |   edge
 836 |   [
 837 |     source 19
 838 |     target 18
 839 |   ]
 840 |   edge
 841 |   [
 842 |     source 20
 843 |     target 17
 844 |   ]
 845 |   edge
 846 |   [
 847 |     source 21
 848 |     target 20
 849 |   ]
 850 |   edge
 851 |   [
 852 |     source 21
 853 |     target 8
 854 |   ]
 855 |   edge
 856 |   [
 857 |     source 21
 858 |     target 7
 859 |   ]
 860 |   edge
 861 |   [
 862 |     source 22
 863 |     target 9
 864 |   ]
 865 |   edge
 866 |   [
 867 |     source 22
 868 |     target 7
 869 |   ]
 870 |   edge
 871 |   [
 872 |     source 22
 873 |     target 21
 874 |   ]
 875 |   edge
 876 |   [
 877 |     source 22
 878 |     target 8
 879 |   ]
 880 |   edge
 881 |   [
 882 |     source 23
 883 |     target 22
 884 |   ]
 885 |   edge
 886 |   [
 887 |     source 23
 888 |     target 9
 889 |   ]
 890 |   edge
 891 |   [
 892 |     source 23
 893 |     target 4
 894 |   ]
 895 |   edge
 896 |   [
 897 |     source 23
 898 |     target 16
 899 |   ]
 900 |   edge
 901 |   [
 902 |     source 23
 903 |     target 0
 904 |   ]
 905 |   edge
 906 |   [
 907 |     source 24
 908 |     target 11
 909 |   ]
 910 |   edge
 911 |   [
 912 |     source 25
 913 |     target 24
 914 |   ]
 915 |   edge
 916 |   [
 917 |     source 25
 918 |     target 1
 919 |   ]
 920 |   edge
 921 |   [
 922 |     source 26
 923 |     target 3
 924 |   ]
 925 |   edge
 926 |   [
 927 |     source 26
 928 |     target 12
 929 |   ]
 930 |   edge
 931 |   [
 932 |     source 26
 933 |     target 14
 934 |   ]
 935 |   edge
 936 |   [
 937 |     source 27
 938 |     target 26
 939 |   ]
 940 |   edge
 941 |   [
 942 |     source 27
 943 |     target 17
 944 |   ]
 945 |   edge
 946 |   [
 947 |     source 27
 948 |     target 1
 949 |   ]
 950 |   edge
 951 |   [
 952 |     source 28
 953 |     target 4
 954 |   ]
 955 |   edge
 956 |   [
 957 |     source 28
 958 |     target 11
 959 |   ]
 960 |   edge
 961 |   [
 962 |     source 28
 963 |     target 24
 964 |   ]
 965 |   edge
 966 |   [
 967 |     source 29
 968 |     target 19
 969 |   ]
 970 |   edge
 971 |   [
 972 |     source 30
 973 |     target 29
 974 |   ]
 975 |   edge
 976 |   [
 977 |     source 30
 978 |     target 19
 979 |   ]
 980 |   edge
 981 |   [
 982 |     source 31
 983 |     target 18
 984 |   ]
 985 |   edge
 986 |   [
 987 |     source 32
 988 |     target 31
 989 |   ]
 990 |   edge
 991 |   [
 992 |     source 32
 993 |     target 21
 994 |   ]
 995 |   edge
 996 |   [
 997 |     source 32
 998 |     target 15
 999 |   ]
1000 |   edge
1001 |   [
1002 |     source 32
1003 |     target 13
1004 |   ]
1005 |   edge
1006 |   [
1007 |     source 32
1008 |     target 6
1009 |   ]
1010 |   edge
1011 |   [
1012 |     source 33
1013 |     target 0
1014 |   ]
1015 |   edge
1016 |   [
1017 |     source 33
1018 |     target 1
1019 |   ]
1020 |   edge
1021 |   [
1022 |     source 33
1023 |     target 25
1024 |   ]
1025 |   edge
1026 |   [
1027 |     source 33
1028 |     target 19
1029 |   ]
1030 |   edge
1031 |   [
1032 |     source 34
1033 |     target 31
1034 |   ]
1035 |   edge
1036 |   [
1037 |     source 34
1038 |     target 26
1039 |   ]
1040 |   edge
1041 |   [
1042 |     source 34
1043 |     target 12
1044 |   ]
1045 |   edge
1046 |   [
1047 |     source 34
1048 |     target 18
1049 |   ]
1050 |   edge
1051 |   [
1052 |     source 35
1053 |     target 34
1054 |   ]
1055 |   edge
1056 |   [
1057 |     source 35
1058 |     target 0
1059 |   ]
1060 |   edge
1061 |   [
1062 |     source 35
1063 |     target 29
1064 |   ]
1065 |   edge
1066 |   [
1067 |     source 35
1068 |     target 19
1069 |   ]
1070 |   edge
1071 |   [
1072 |     source 35
1073 |     target 30
1074 |   ]
1075 |   edge
1076 |   [
1077 |     source 36
1078 |     target 18
1079 |   ]
1080 |   edge
1081 |   [
1082 |     source 36
1083 |     target 12
1084 |   ]
1085 |   edge
1086 |   [
1087 |     source 36
1088 |     target 20
1089 |   ]
1090 |   edge
1091 |   [
1092 |     source 36
1093 |     target 19
1094 |   ]
1095 |   edge
1096 |   [
1097 |     source 37
1098 |     target 36
1099 |   ]
1100 |   edge
1101 |   [
1102 |     source 37
1103 |     target 1
1104 |   ]
1105 |   edge
1106 |   [
1107 |     source 37
1108 |     target 25
1109 |   ]
1110 |   edge
1111 |   [
1112 |     source 37
1113 |     target 33
1114 |   ]
1115 |   edge
1116 |   [
1117 |     source 38
1118 |     target 18
1119 |   ]
1120 |   edge
1121 |   [
1122 |     source 38
1123 |     target 16
1124 |   ]
1125 |   edge
1126 |   [
1127 |     source 38
1128 |     target 28
1129 |   ]
1130 |   edge
1131 |   [
1132 |     source 38
1133 |     target 26
1134 |   ]
1135 |   edge
1136 |   [
1137 |     source 38
1138 |     target 14
1139 |   ]
1140 |   edge
1141 |   [
1142 |     source 38
1143 |     target 12
1144 |   ]
1145 |   edge
1146 |   [
1147 |     source 39
1148 |     target 38
1149 |   ]
1150 |   edge
1151 |   [
1152 |     source 39
1153 |     target 6
1154 |   ]
1155 |   edge
1156 |   [
1157 |     source 39
1158 |     target 32
1159 |   ]
1160 |   edge
1161 |   [
1162 |     source 39
1163 |     target 13
1164 |   ]
1165 |   edge
1166 |   [
1167 |     source 39
1168 |     target 15
1169 |   ]
1170 |   edge
1171 |   [
1172 |     source 40
1173 |     target 7
1174 |   ]
1175 |   edge
1176 |   [
1177 |     source 40
1178 |     target 3
1179 |   ]
1180 |   edge
1181 |   [
1182 |     source 41
1183 |     target 40
1184 |   ]
1185 |   edge
1186 |   [
1187 |     source 41
1188 |     target 8
1189 |   ]
1190 |   edge
1191 |   [
1192 |     source 41
1193 |     target 4
1194 |   ]
1195 |   edge
1196 |   [
1197 |     source 41
1198 |     target 23
1199 |   ]
1200 |   edge
1201 |   [
1202 |     source 41
1203 |     target 9
1204 |   ]
1205 |   edge
1206 |   [
1207 |     source 41
1208 |     target 0
1209 |   ]
1210 |   edge
1211 |   [
1212 |     source 41
1213 |     target 16
1214 |   ]
1215 |   edge
1216 |   [
1217 |     source 42
1218 |     target 34
1219 |   ]
1220 |   edge
1221 |   [
1222 |     source 42
1223 |     target 29
1224 |   ]
1225 |   edge
1226 |   [
1227 |     source 42
1228 |     target 18
1229 |   ]
1230 |   edge
1231 |   [
1232 |     source 42
1233 |     target 26
1234 |   ]
1235 |   edge
1236 |   [
1237 |     source 43
1238 |     target 42
1239 |   ]
1240 |   edge
1241 |   [
1242 |     source 43
1243 |     target 36
1244 |   ]
1245 |   edge
1246 |   [
1247 |     source 43
1248 |     target 26
1249 |   ]
1250 |   edge
1251 |   [
1252 |     source 43
1253 |     target 31
1254 |   ]
1255 |   edge
1256 |   [
1257 |     source 43
1258 |     target 38
1259 |   ]
1260 |   edge
1261 |   [
1262 |     source 43
1263 |     target 12
1264 |   ]
1265 |   edge
1266 |   [
1267 |     source 43
1268 |     target 14
1269 |   ]
1270 |   edge
1271 |   [
1272 |     source 44
1273 |     target 19
1274 |   ]
1275 |   edge
1276 |   [
1277 |     source 44
1278 |     target 35
1279 |   ]
1280 |   edge
1281 |   [
1282 |     source 44
1283 |     target 30
1284 |   ]
1285 |   edge
1286 |   [
1287 |     source 45
1288 |     target 44
1289 |   ]
1290 |   edge
1291 |   [
1292 |     source 45
1293 |     target 13
1294 |   ]
1295 |   edge
1296 |   [
1297 |     source 45
1298 |     target 33
1299 |   ]
1300 |   edge
1301 |   [
1302 |     source 45
1303 |     target 1
1304 |   ]
1305 |   edge
1306 |   [
1307 |     source 45
1308 |     target 37
1309 |   ]
1310 |   edge
1311 |   [
1312 |     source 45
1313 |     target 25
1314 |   ]
1315 |   edge
1316 |   [
1317 |     source 46
1318 |     target 21
1319 |   ]
1320 |   edge
1321 |   [
1322 |     source 47
1323 |     target 46
1324 |   ]
1325 |   edge
1326 |   [
1327 |     source 47
1328 |     target 22
1329 |   ]
1330 |   edge
1331 |   [
1332 |     source 47
1333 |     target 6
1334 |   ]
1335 |   edge
1336 |   [
1337 |     source 47
1338 |     target 15
1339 |   ]
1340 |   edge
1341 |   [
1342 |     source 47
1343 |     target 2
1344 |   ]
1345 |   edge
1346 |   [
1347 |     source 47
1348 |     target 39
1349 |   ]
1350 |   edge
1351 |   [
1352 |     source 47
1353 |     target 32
1354 |   ]
1355 |   edge
1356 |   [
1357 |     source 48
1358 |     target 44
1359 |   ]
1360 |   edge
1361 |   [
1362 |     source 49
1363 |     target 48
1364 |   ]
1365 |   edge
1366 |   [
1367 |     source 49
1368 |     target 32
1369 |   ]
1370 |   edge
1371 |   [
1372 |     source 49
1373 |     target 46
1374 |   ]
1375 |   edge
1376 |   [
1377 |     source 50
1378 |     target 30
1379 |   ]
1380 |   edge
1381 |   [
1382 |     source 50
1383 |     target 24
1384 |   ]
1385 |   edge
1386 |   [
1387 |     source 50
1388 |     target 11
1389 |   ]
1390 |   edge
1391 |   [
1392 |     source 50
1393 |     target 28
1394 |   ]
1395 |   edge
1396 |   [
1397 |     source 51
1398 |     target 50
1399 |   ]
1400 |   edge
1401 |   [
1402 |     source 51
1403 |     target 40
1404 |   ]
1405 |   edge
1406 |   [
1407 |     source 51
1408 |     target 8
1409 |   ]
1410 |   edge
1411 |   [
1412 |     source 51
1413 |     target 22
1414 |   ]
1415 |   edge
1416 |   [
1417 |     source 51
1418 |     target 21
1419 |   ]
1420 |   edge
1421 |   [
1422 |     source 52
1423 |     target 3
1424 |   ]
1425 |   edge
1426 |   [
1427 |     source 52
1428 |     target 40
1429 |   ]
1430 |   edge
1431 |   [
1432 |     source 52
1433 |     target 5
1434 |   ]
1435 |   edge
1436 |   [
1437 |     source 53
1438 |     target 52
1439 |   ]
1440 |   edge
1441 |   [
1442 |     source 53
1443 |     target 25
1444 |   ]
1445 |   edge
1446 |   [
1447 |     source 53
1448 |     target 48
1449 |   ]
1450 |   edge
1451 |   [
1452 |     source 53
1453 |     target 49
1454 |   ]
1455 |   edge
1456 |   [
1457 |     source 53
1458 |     target 46
1459 |   ]
1460 |   edge
1461 |   [
1462 |     source 54
1463 |     target 39
1464 |   ]
1465 |   edge
1466 |   [
1467 |     source 54
1468 |     target 31
1469 |   ]
1470 |   edge
1471 |   [
1472 |     source 54
1473 |     target 38
1474 |   ]
1475 |   edge
1476 |   [
1477 |     source 54
1478 |     target 14
1479 |   ]
1480 |   edge
1481 |   [
1482 |     source 54
1483 |     target 34
1484 |   ]
1485 |   edge
1486 |   [
1487 |     source 54
1488 |     target 18
1489 |   ]
1490 |   edge
1491 |   [
1492 |     source 55
1493 |     target 54
1494 |   ]
1495 |   edge
1496 |   [
1497 |     source 55
1498 |     target 31
1499 |   ]
1500 |   edge
1501 |   [
1502 |     source 55
1503 |     target 6
1504 |   ]
1505 |   edge
1506 |   [
1507 |     source 55
1508 |     target 35
1509 |   ]
1510 |   edge
1511 |   [
1512 |     source 55
1513 |     target 29
1514 |   ]
1515 |   edge
1516 |   [
1517 |     source 55
1518 |     target 19
1519 |   ]
1520 |   edge
1521 |   [
1522 |     source 55
1523 |     target 30
1524 |   ]
1525 |   edge
1526 |   [
1527 |     source 56
1528 |     target 27
1529 |   ]
1530 |   edge
1531 |   [
1532 |     source 57
1533 |     target 56
1534 |   ]
1535 |   edge
1536 |   [
1537 |     source 57
1538 |     target 1
1539 |   ]
1540 |   edge
1541 |   [
1542 |     source 57
1543 |     target 42
1544 |   ]
1545 |   edge
1546 |   [
1547 |     source 57
1548 |     target 44
1549 |   ]
1550 |   edge
1551 |   [
1552 |     source 57
1553 |     target 48
1554 |   ]
1555 |   edge
1556 |   [
1557 |     source 58
1558 |     target 3
1559 |   ]
1560 |   edge
1561 |   [
1562 |     source 58
1563 |     target 6
1564 |   ]
1565 |   edge
1566 |   [
1567 |     source 58
1568 |     target 17
1569 |   ]
1570 |   edge
1571 |   [
1572 |     source 58
1573 |     target 36
1574 |   ]
1575 |   edge
1576 |   [
1577 |     source 59
1578 |     target 36
1579 |   ]
1580 |   edge
1581 |   [
1582 |     source 59
1583 |     target 58
1584 |   ]
1585 |   edge
1586 |   [
1587 |     source 60
1588 |     target 59
1589 |   ]
1590 |   edge
1591 |   [
1592 |     source 60
1593 |     target 10
1594 |   ]
1595 |   edge
1596 |   [
1597 |     source 60
1598 |     target 39
1599 |   ]
1600 |   edge
1601 |   [
1602 |     source 60
1603 |     target 6
1604 |   ]
1605 |   edge
1606 |   [
1607 |     source 60
1608 |     target 47
1609 |   ]
1610 |   edge
1611 |   [
1612 |     source 60
1613 |     target 13
1614 |   ]
1615 |   edge
1616 |   [
1617 |     source 60
1618 |     target 15
1619 |   ]
1620 |   edge
1621 |   [
1622 |     source 60
1623 |     target 2
1624 |   ]
1625 |   edge
1626 |   [
1627 |     source 61
1628 |     target 43
1629 |   ]
1630 |   edge
1631 |   [
1632 |     source 61
1633 |     target 47
1634 |   ]
1635 |   edge
1636 |   [
1637 |     source 61
1638 |     target 54
1639 |   ]
1640 |   edge
1641 |   [
1642 |     source 61
1643 |     target 18
1644 |   ]
1645 |   edge
1646 |   [
1647 |     source 61
1648 |     target 26
1649 |   ]
1650 |   edge
1651 |   [
1652 |     source 61
1653 |     target 31
1654 |   ]
1655 |   edge
1656 |   [
1657 |     source 61
1658 |     target 34
1659 |   ]
1660 |   edge
1661 |   [
1662 |     source 62
1663 |     target 61
1664 |   ]
1665 |   edge
1666 |   [
1667 |     source 62
1668 |     target 20
1669 |   ]
1670 |   edge
1671 |   [
1672 |     source 62
1673 |     target 45
1674 |   ]
1675 |   edge
1676 |   [
1677 |     source 62
1678 |     target 17
1679 |   ]
1680 |   edge
1681 |   [
1682 |     source 62
1683 |     target 27
1684 |   ]
1685 |   edge
1686 |   [
1687 |     source 62
1688 |     target 56
1689 |   ]
1690 |   edge
1691 |   [
1692 |     source 63
1693 |     target 27
1694 |   ]
1695 |   edge
1696 |   [
1697 |     source 63
1698 |     target 58
1699 |   ]
1700 |   edge
1701 |   [
1702 |     source 63
1703 |     target 59
1704 |   ]
1705 |   edge
1706 |   [
1707 |     source 63
1708 |     target 42
1709 |   ]
1710 |   edge
1711 |   [
1712 |     source 64
1713 |     target 63
1714 |   ]
1715 |   edge
1716 |   [
1717 |     source 64
1718 |     target 9
1719 |   ]
1720 |   edge
1721 |   [
1722 |     source 64
1723 |     target 32
1724 |   ]
1725 |   edge
1726 |   [
1727 |     source 64
1728 |     target 60
1729 |   ]
1730 |   edge
1731 |   [
1732 |     source 64
1733 |     target 2
1734 |   ]
1735 |   edge
1736 |   [
1737 |     source 64
1738 |     target 6
1739 |   ]
1740 |   edge
1741 |   [
1742 |     source 64
1743 |     target 47
1744 |   ]
1745 |   edge
1746 |   [
1747 |     source 64
1748 |     target 13
1749 |   ]
1750 |   edge
1751 |   [
1752 |     source 65
1753 |     target 0
1754 |   ]
1755 |   edge
1756 |   [
1757 |     source 65
1758 |     target 27
1759 |   ]
1760 |   edge
1761 |   [
1762 |     source 65
1763 |     target 17
1764 |   ]
1765 |   edge
1766 |   [
1767 |     source 65
1768 |     target 63
1769 |   ]
1770 |   edge
1771 |   [
1772 |     source 65
1773 |     target 56
1774 |   ]
1775 |   edge
1776 |   [
1777 |     source 65
1778 |     target 20
1779 |   ]
1780 |   edge
1781 |   [
1782 |     source 66
1783 |     target 65
1784 |   ]
1785 |   edge
1786 |   [
1787 |     source 66
1788 |     target 59
1789 |   ]
1790 |   edge
1791 |   [
1792 |     source 66
1793 |     target 24
1794 |   ]
1795 |   edge
1796 |   [
1797 |     source 66
1798 |     target 44
1799 |   ]
1800 |   edge
1801 |   [
1802 |     source 66
1803 |     target 48
1804 |   ]
1805 |   edge
1806 |   [
1807 |     source 67
1808 |     target 16
1809 |   ]
1810 |   edge
1811 |   [
1812 |     source 67
1813 |     target 41
1814 |   ]
1815 |   edge
1816 |   [
1817 |     source 67
1818 |     target 46
1819 |   ]
1820 |   edge
1821 |   [
1822 |     source 67
1823 |     target 53
1824 |   ]
1825 |   edge
1826 |   [
1827 |     source 67
1828 |     target 49
1829 |   ]
1830 |   edge
1831 |   [
1832 |     source 68
1833 |     target 67
1834 |   ]
1835 |   edge
1836 |   [
1837 |     source 68
1838 |     target 15
1839 |   ]
1840 |   edge
1841 |   [
1842 |     source 68
1843 |     target 50
1844 |   ]
1845 |   edge
1846 |   [
1847 |     source 68
1848 |     target 21
1849 |   ]
1850 |   edge
1851 |   [
1852 |     source 68
1853 |     target 51
1854 |   ]
1855 |   edge
1856 |   [
1857 |     source 68
1858 |     target 7
1859 |   ]
1860 |   edge
1861 |   [
1862 |     source 68
1863 |     target 22
1864 |   ]
1865 |   edge
1866 |   [
1867 |     source 68
1868 |     target 8
1869 |   ]
1870 |   edge
1871 |   [
1872 |     source 69
1873 |     target 4
1874 |   ]
1875 |   edge
1876 |   [
1877 |     source 69
1878 |     target 24
1879 |   ]
1880 |   edge
1881 |   [
1882 |     source 69
1883 |     target 28
1884 |   ]
1885 |   edge
1886 |   [
1887 |     source 69
1888 |     target 50
1889 |   ]
1890 |   edge
1891 |   [
1892 |     source 69
1893 |     target 11
1894 |   ]
1895 |   edge
1896 |   [
1897 |     source 70
1898 |     target 69
1899 |   ]
1900 |   edge
1901 |   [
1902 |     source 70
1903 |     target 43
1904 |   ]
1905 |   edge
1906 |   [
1907 |     source 70
1908 |     target 65
1909 |   ]
1910 |   edge
1911 |   [
1912 |     source 70
1913 |     target 20
1914 |   ]
1915 |   edge
1916 |   [
1917 |     source 70
1918 |     target 56
1919 |   ]
1920 |   edge
1921 |   [
1922 |     source 70
1923 |     target 62
1924 |   ]
1925 |   edge
1926 |   [
1927 |     source 70
1928 |     target 27
1929 |   ]
1930 |   edge
1931 |   [
1932 |     source 71
1933 |     target 60
1934 |   ]
1935 |   edge
1936 |   [
1937 |     source 71
1938 |     target 18
1939 |   ]
1940 |   edge
1941 |   [
1942 |     source 71
1943 |     target 14
1944 |   ]
1945 |   edge
1946 |   [
1947 |     source 71
1948 |     target 34
1949 |   ]
1950 |   edge
1951 |   [
1952 |     source 71
1953 |     target 54
1954 |   ]
1955 |   edge
1956 |   [
1957 |     source 71
1958 |     target 38
1959 |   ]
1960 |   edge
1961 |   [
1962 |     source 71
1963 |     target 61
1964 |   ]
1965 |   edge
1966 |   [
1967 |     source 71
1968 |     target 31
1969 |   ]
1970 |   edge
1971 |   [
1972 |     source 72
1973 |     target 71
1974 |   ]
1975 |   edge
1976 |   [
1977 |     source 72
1978 |     target 2
1979 |   ]
1980 |   edge
1981 |   [
1982 |     source 72
1983 |     target 10
1984 |   ]
1985 |   edge
1986 |   [
1987 |     source 72
1988 |     target 3
1989 |   ]
1990 |   edge
1991 |   [
1992 |     source 72
1993 |     target 40
1994 |   ]
1995 |   edge
1996 |   [
1997 |     source 72
1998 |     target 52
1999 |   ]
2000 |   edge
2001 |   [
2002 |     source 73
2003 |     target 7
2004 |   ]
2005 |   edge
2006 |   [
2007 |     source 73
2008 |     target 49
2009 |   ]
2010 |   edge
2011 |   [
2012 |     source 73
2013 |     target 53
2014 |   ]
2015 |   edge
2016 |   [
2017 |     source 73
2018 |     target 67
2019 |   ]
2020 |   edge
2021 |   [
2022 |     source 73
2023 |     target 46
2024 |   ]
2025 |   edge
2026 |   [
2027 |     source 74
2028 |     target 73
2029 |   ]
2030 |   edge
2031 |   [
2032 |     source 74
2033 |     target 2
2034 |   ]
2035 |   edge
2036 |   [
2037 |     source 74
2038 |     target 72
2039 |   ]
2040 |   edge
2041 |   [
2042 |     source 74
2043 |     target 5
2044 |   ]
2045 |   edge
2046 |   [
2047 |     source 74
2048 |     target 10
2049 |   ]
2050 |   edge
2051 |   [
2052 |     source 74
2053 |     target 52
2054 |   ]
2055 |   edge
2056 |   [
2057 |     source 74
2058 |     target 3
2059 |   ]
2060 |   edge
2061 |   [
2062 |     source 74
2063 |     target 40
2064 |   ]
2065 |   edge
2066 |   [
2067 |     source 75
2068 |     target 20
2069 |   ]
2070 |   edge
2071 |   [
2072 |     source 75
2073 |     target 66
2074 |   ]
2075 |   edge
2076 |   [
2077 |     source 75
2078 |     target 48
2079 |   ]
2080 |   edge
2081 |   [
2082 |     source 75
2083 |     target 57
2084 |   ]
2085 |   edge
2086 |   [
2087 |     source 75
2088 |     target 44
2089 |   ]
2090 |   edge
2091 |   [
2092 |     source 76
2093 |     target 75
2094 |   ]
2095 |   edge
2096 |   [
2097 |     source 76
2098 |     target 27
2099 |   ]
2100 |   edge
2101 |   [
2102 |     source 76
2103 |     target 59
2104 |   ]
2105 |   edge
2106 |   [
2107 |     source 76
2108 |     target 20
2109 |   ]
2110 |   edge
2111 |   [
2112 |     source 76
2113 |     target 70
2114 |   ]
2115 |   edge
2116 |   [
2117 |     source 76
2118 |     target 66
2119 |   ]
2120 |   edge
2121 |   [
2122 |     source 76
2123 |     target 56
2124 |   ]
2125 |   edge
2126 |   [
2127 |     source 76
2128 |     target 62
2129 |   ]
2130 |   edge
2131 |   [
2132 |     source 77
2133 |     target 73
2134 |   ]
2135 |   edge
2136 |   [
2137 |     source 77
2138 |     target 22
2139 |   ]
2140 |   edge
2141 |   [
2142 |     source 77
2143 |     target 7
2144 |   ]
2145 |   edge
2146 |   [
2147 |     source 77
2148 |     target 51
2149 |   ]
2150 |   edge
2151 |   [
2152 |     source 77
2153 |     target 21
2154 |   ]
2155 |   edge
2156 |   [
2157 |     source 77
2158 |     target 8
2159 |   ]
2160 |   edge
2161 |   [
2162 |     source 78
2163 |     target 77
2164 |   ]
2165 |   edge
2166 |   [
2167 |     source 78
2168 |     target 23
2169 |   ]
2170 |   edge
2171 |   [
2172 |     source 78
2173 |     target 50
2174 |   ]
2175 |   edge
2176 |   [
2177 |     source 78
2178 |     target 28
2179 |   ]
2180 |   edge
2181 |   [
2182 |     source 78
2183 |     target 22
2184 |   ]
2185 |   edge
2186 |   [
2187 |     source 78
2188 |     target 8
2189 |   ]
2190 |   edge
2191 |   [
2192 |     source 78
2193 |     target 68
2194 |   ]
2195 |   edge
2196 |   [
2197 |     source 78
2198 |     target 7
2199 |   ]
2200 |   edge
2201 |   [
2202 |     source 78
2203 |     target 51
2204 |   ]
2205 |   edge
2206 |   [
2207 |     source 79
2208 |     target 31
2209 |   ]
2210 |   edge
2211 |   [
2212 |     source 79
2213 |     target 43
2214 |   ]
2215 |   edge
2216 |   [
2217 |     source 79
2218 |     target 30
2219 |   ]
2220 |   edge
2221 |   [
2222 |     source 79
2223 |     target 19
2224 |   ]
2225 |   edge
2226 |   [
2227 |     source 79
2228 |     target 29
2229 |   ]
2230 |   edge
2231 |   [
2232 |     source 79
2233 |     target 35
2234 |   ]
2235 |   edge
2236 |   [
2237 |     source 79
2238 |     target 55
2239 |   ]
2240 |   edge
2241 |   [
2242 |     source 80
2243 |     target 79
2244 |   ]
2245 |   edge
2246 |   [
2247 |     source 80
2248 |     target 37
2249 |   ]
2250 |   edge
2251 |   [
2252 |     source 80
2253 |     target 29
2254 |   ]
2255 |   edge
2256 |   [
2257 |     source 81
2258 |     target 16
2259 |   ]
2260 |   edge
2261 |   [
2262 |     source 81
2263 |     target 5
2264 |   ]
2265 |   edge
2266 |   [
2267 |     source 81
2268 |     target 40
2269 |   ]
2270 |   edge
2271 |   [
2272 |     source 81
2273 |     target 10
2274 |   ]
2275 |   edge
2276 |   [
2277 |     source 81
2278 |     target 72
2279 |   ]
2280 |   edge
2281 |   [
2282 |     source 81
2283 |     target 3
2284 |   ]
2285 |   edge
2286 |   [
2287 |     source 82
2288 |     target 81
2289 |   ]
2290 |   edge
2291 |   [
2292 |     source 82
2293 |     target 74
2294 |   ]
2295 |   edge
2296 |   [
2297 |     source 82
2298 |     target 39
2299 |   ]
2300 |   edge
2301 |   [
2302 |     source 82
2303 |     target 77
2304 |   ]
2305 |   edge
2306 |   [
2307 |     source 82
2308 |     target 80
2309 |   ]
2310 |   edge
2311 |   [
2312 |     source 82
2313 |     target 30
2314 |   ]
2315 |   edge
2316 |   [
2317 |     source 82
2318 |     target 29
2319 |   ]
2320 |   edge
2321 |   [
2322 |     source 82
2323 |     target 7
2324 |   ]
2325 |   edge
2326 |   [
2327 |     source 83
2328 |     target 53
2329 |   ]
2330 |   edge
2331 |   [
2332 |     source 83
2333 |     target 81
2334 |   ]
2335 |   edge
2336 |   [
2337 |     source 83
2338 |     target 69
2339 |   ]
2340 |   edge
2341 |   [
2342 |     source 83
2343 |     target 73
2344 |   ]
2345 |   edge
2346 |   [
2347 |     source 83
2348 |     target 46
2349 |   ]
2350 |   edge
2351 |   [
2352 |     source 83
2353 |     target 67
2354 |   ]
2355 |   edge
2356 |   [
2357 |     source 83
2358 |     target 49
2359 |   ]
2360 |   edge
2361 |   [
2362 |     source 84
2363 |     target 83
2364 |   ]
2365 |   edge
2366 |   [
2367 |     source 84
2368 |     target 24
2369 |   ]
2370 |   edge
2371 |   [
2372 |     source 84
2373 |     target 49
2374 |   ]
2375 |   edge
2376 |   [
2377 |     source 84
2378 |     target 52
2379 |   ]
2380 |   edge
2381 |   [
2382 |     source 84
2383 |     target 3
2384 |   ]
2385 |   edge
2386 |   [
2387 |     source 84
2388 |     target 74
2389 |   ]
2390 |   edge
2391 |   [
2392 |     source 84
2393 |     target 10
2394 |   ]
2395 |   edge
2396 |   [
2397 |     source 84
2398 |     target 81
2399 |   ]
2400 |   edge
2401 |   [
2402 |     source 84
2403 |     target 5
2404 |   ]
2405 |   edge
2406 |   [
2407 |     source 85
2408 |     target 6
2409 |   ]
2410 |   edge
2411 |   [
2412 |     source 85
2413 |     target 14
2414 |   ]
2415 |   edge
2416 |   [
2417 |     source 85
2418 |     target 38
2419 |   ]
2420 |   edge
2421 |   [
2422 |     source 85
2423 |     target 43
2424 |   ]
2425 |   edge
2426 |   [
2427 |     source 85
2428 |     target 80
2429 |   ]
2430 |   edge
2431 |   [
2432 |     source 85
2433 |     target 12
2434 |   ]
2435 |   edge
2436 |   [
2437 |     source 85
2438 |     target 26
2439 |   ]
2440 |   edge
2441 |   [
2442 |     source 85
2443 |     target 31
2444 |   ]
2445 |   edge
2446 |   [
2447 |     source 86
2448 |     target 44
2449 |   ]
2450 |   edge
2451 |   [
2452 |     source 86
2453 |     target 53
2454 |   ]
2455 |   edge
2456 |   [
2457 |     source 86
2458 |     target 75
2459 |   ]
2460 |   edge
2461 |   [
2462 |     source 86
2463 |     target 57
2464 |   ]
2465 |   edge
2466 |   [
2467 |     source 86
2468 |     target 48
2469 |   ]
2470 |   edge
2471 |   [
2472 |     source 86
2473 |     target 80
2474 |   ]
2475 |   edge
2476 |   [
2477 |     source 86
2478 |     target 66
2479 |   ]
2480 |   edge
2481 |   [
2482 |     source 87
2483 |     target 86
2484 |   ]
2485 |   edge
2486 |   [
2487 |     source 87
2488 |     target 17
2489 |   ]
2490 |   edge
2491 |   [
2492 |     source 87
2493 |     target 62
2494 |   ]
2495 |   edge
2496 |   [
2497 |     source 87
2498 |     target 56
2499 |   ]
2500 |   edge
2501 |   [
2502 |     source 87
2503 |     target 24
2504 |   ]
2505 |   edge
2506 |   [
2507 |     source 87
2508 |     target 20
2509 |   ]
2510 |   edge
2511 |   [
2512 |     source 87
2513 |     target 65
2514 |   ]
2515 |   edge
2516 |   [
2517 |     source 88
2518 |     target 49
2519 |   ]
2520 |   edge
2521 |   [
2522 |     source 88
2523 |     target 58
2524 |   ]
2525 |   edge
2526 |   [
2527 |     source 88
2528 |     target 83
2529 |   ]
2530 |   edge
2531 |   [
2532 |     source 88
2533 |     target 69
2534 |   ]
2535 |   edge
2536 |   [
2537 |     source 88
2538 |     target 46
2539 |   ]
2540 |   edge
2541 |   [
2542 |     source 88
2543 |     target 53
2544 |   ]
2545 |   edge
2546 |   [
2547 |     source 88
2548 |     target 73
2549 |   ]
2550 |   edge
2551 |   [
2552 |     source 88
2553 |     target 67
2554 |   ]
2555 |   edge
2556 |   [
2557 |     source 89
2558 |     target 88
2559 |   ]
2560 |   edge
2561 |   [
2562 |     source 89
2563 |     target 1
2564 |   ]
2565 |   edge
2566 |   [
2567 |     source 89
2568 |     target 37
2569 |   ]
2570 |   edge
2571 |   [
2572 |     source 89
2573 |     target 25
2574 |   ]
2575 |   edge
2576 |   [
2577 |     source 89
2578 |     target 33
2579 |   ]
2580 |   edge
2581 |   [
2582 |     source 89
2583 |     target 55
2584 |   ]
2585 |   edge
2586 |   [
2587 |     source 89
2588 |     target 45
2589 |   ]
2590 |   edge
2591 |   [
2592 |     source 90
2593 |     target 5
2594 |   ]
2595 |   edge
2596 |   [
2597 |     source 90
2598 |     target 8
2599 |   ]
2600 |   edge
2601 |   [
2602 |     source 90
2603 |     target 23
2604 |   ]
2605 |   edge
2606 |   [
2607 |     source 90
2608 |     target 0
2609 |   ]
2610 |   edge
2611 |   [
2612 |     source 90
2613 |     target 11
2614 |   ]
2615 |   edge
2616 |   [
2617 |     source 90
2618 |     target 50
2619 |   ]
2620 |   edge
2621 |   [
2622 |     source 90
2623 |     target 24
2624 |   ]
2625 |   edge
2626 |   [
2627 |     source 90
2628 |     target 69
2629 |   ]
2630 |   edge
2631 |   [
2632 |     source 90
2633 |     target 28
2634 |   ]
2635 |   edge
2636 |   [
2637 |     source 91
2638 |     target 29
2639 |   ]
2640 |   edge
2641 |   [
2642 |     source 91
2643 |     target 48
2644 |   ]
2645 |   edge
2646 |   [
2647 |     source 91
2648 |     target 66
2649 |   ]
2650 |   edge
2651 |   [
2652 |     source 91
2653 |     target 69
2654 |   ]
2655 |   edge
2656 |   [
2657 |     source 91
2658 |     target 44
2659 |   ]
2660 |   edge
2661 |   [
2662 |     source 91
2663 |     target 86
2664 |   ]
2665 |   edge
2666 |   [
2667 |     source 91
2668 |     target 57
2669 |   ]
2670 |   edge
2671 |   [
2672 |     source 91
2673 |     target 80
2674 |   ]
2675 |   edge
2676 |   [
2677 |     source 92
2678 |     target 91
2679 |   ]
2680 |   edge
2681 |   [
2682 |     source 92
2683 |     target 35
2684 |   ]
2685 |   edge
2686 |   [
2687 |     source 92
2688 |     target 15
2689 |   ]
2690 |   edge
2691 |   [
2692 |     source 92
2693 |     target 86
2694 |   ]
2695 |   edge
2696 |   [
2697 |     source 92
2698 |     target 48
2699 |   ]
2700 |   edge
2701 |   [
2702 |     source 92
2703 |     target 57
2704 |   ]
2705 |   edge
2706 |   [
2707 |     source 92
2708 |     target 61
2709 |   ]
2710 |   edge
2711 |   [
2712 |     source 92
2713 |     target 66
2714 |   ]
2715 |   edge
2716 |   [
2717 |     source 92
2718 |     target 75
2719 |   ]
2720 |   edge
2721 |   [
2722 |     source 93
2723 |     target 0
2724 |   ]
2725 |   edge
2726 |   [
2727 |     source 93
2728 |     target 23
2729 |   ]
2730 |   edge
2731 |   [
2732 |     source 93
2733 |     target 80
2734 |   ]
2735 |   edge
2736 |   [
2737 |     source 93
2738 |     target 16
2739 |   ]
2740 |   edge
2741 |   [
2742 |     source 93
2743 |     target 4
2744 |   ]
2745 |   edge
2746 |   [
2747 |     source 93
2748 |     target 82
2749 |   ]
2750 |   edge
2751 |   [
2752 |     source 93
2753 |     target 91
2754 |   ]
2755 |   edge
2756 |   [
2757 |     source 93
2758 |     target 41
2759 |   ]
2760 |   edge
2761 |   [
2762 |     source 93
2763 |     target 9
2764 |   ]
2765 |   edge
2766 |   [
2767 |     source 94
2768 |     target 34
2769 |   ]
2770 |   edge
2771 |   [
2772 |     source 94
2773 |     target 19
2774 |   ]
2775 |   edge
2776 |   [
2777 |     source 94
2778 |     target 55
2779 |   ]
2780 |   edge
2781 |   [
2782 |     source 94
2783 |     target 79
2784 |   ]
2785 |   edge
2786 |   [
2787 |     source 94
2788 |     target 80
2789 |   ]
2790 |   edge
2791 |   [
2792 |     source 94
2793 |     target 29
2794 |   ]
2795 |   edge
2796 |   [
2797 |     source 94
2798 |     target 30
2799 |   ]
2800 |   edge
2801 |   [
2802 |     source 94
2803 |     target 82
2804 |   ]
2805 |   edge
2806 |   [
2807 |     source 94
2808 |     target 35
2809 |   ]
2810 |   edge
2811 |   [
2812 |     source 95
2813 |     target 70
2814 |   ]
2815 |   edge
2816 |   [
2817 |     source 95
2818 |     target 69
2819 |   ]
2820 |   edge
2821 |   [
2822 |     source 95
2823 |     target 76
2824 |   ]
2825 |   edge
2826 |   [
2827 |     source 95
2828 |     target 62
2829 |   ]
2830 |   edge
2831 |   [
2832 |     source 95
2833 |     target 56
2834 |   ]
2835 |   edge
2836 |   [
2837 |     source 95
2838 |     target 27
2839 |   ]
2840 |   edge
2841 |   [
2842 |     source 95
2843 |     target 17
2844 |   ]
2845 |   edge
2846 |   [
2847 |     source 95
2848 |     target 87
2849 |   ]
2850 |   edge
2851 |   [
2852 |     source 95
2853 |     target 37
2854 |   ]
2855 |   edge
2856 |   [
2857 |     source 96
2858 |     target 48
2859 |   ]
2860 |   edge
2861 |   [
2862 |     source 96
2863 |     target 17
2864 |   ]
2865 |   edge
2866 |   [
2867 |     source 96
2868 |     target 76
2869 |   ]
2870 |   edge
2871 |   [
2872 |     source 96
2873 |     target 27
2874 |   ]
2875 |   edge
2876 |   [
2877 |     source 96
2878 |     target 56
2879 |   ]
2880 |   edge
2881 |   [
2882 |     source 96
2883 |     target 65
2884 |   ]
2885 |   edge
2886 |   [
2887 |     source 96
2888 |     target 20
2889 |   ]
2890 |   edge
2891 |   [
2892 |     source 96
2893 |     target 87
2894 |   ]
2895 |   edge
2896 |   [
2897 |     source 97
2898 |     target 5
2899 |   ]
2900 |   edge
2901 |   [
2902 |     source 97
2903 |     target 86
2904 |   ]
2905 |   edge
2906 |   [
2907 |     source 97
2908 |     target 58
2909 |   ]
2910 |   edge
2911 |   [
2912 |     source 97
2913 |     target 11
2914 |   ]
2915 |   edge
2916 |   [
2917 |     source 97
2918 |     target 59
2919 |   ]
2920 |   edge
2921 |   [
2922 |     source 97
2923 |     target 63
2924 |   ]
2925 |   edge
2926 |   [
2927 |     source 98
2928 |     target 97
2929 |   ]
2930 |   edge
2931 |   [
2932 |     source 98
2933 |     target 77
2934 |   ]
2935 |   edge
2936 |   [
2937 |     source 98
2938 |     target 48
2939 |   ]
2940 |   edge
2941 |   [
2942 |     source 98
2943 |     target 84
2944 |   ]
2945 |   edge
2946 |   [
2947 |     source 98
2948 |     target 40
2949 |   ]
2950 |   edge
2951 |   [
2952 |     source 98
2953 |     target 10
2954 |   ]
2955 |   edge
2956 |   [
2957 |     source 98
2958 |     target 5
2959 |   ]
2960 |   edge
2961 |   [
2962 |     source 98
2963 |     target 52
2964 |   ]
2965 |   edge
2966 |   [
2967 |     source 98
2968 |     target 81
2969 |   ]
2970 |   edge
2971 |   [
2972 |     source 99
2973 |     target 89
2974 |   ]
2975 |   edge
2976 |   [
2977 |     source 99
2978 |     target 34
2979 |   ]
2980 |   edge
2981 |   [
2982 |     source 99
2983 |     target 14
2984 |   ]
2985 |   edge
2986 |   [
2987 |     source 99
2988 |     target 85
2989 |   ]
2990 |   edge
2991 |   [
2992 |     source 99
2993 |     target 54
2994 |   ]
2995 |   edge
2996 |   [
2997 |     source 99
2998 |     target 18
2999 |   ]
3000 |   edge
3001 |   [
3002 |     source 99
3003 |     target 31
3004 |   ]
3005 |   edge
3006 |   [
3007 |     source 99
3008 |     target 61
3009 |   ]
3010 |   edge
3011 |   [
3012 |     source 99
3013 |     target 71
3014 |   ]
3015 |   edge
3016 |   [
3017 |     source 100
3018 |     target 99
3019 |   ]
3020 |   edge
3021 |   [
3022 |     source 100
3023 |     target 82
3024 |   ]
3025 |   edge
3026 |   [
3027 |     source 100
3028 |     target 13
3029 |   ]
3030 |   edge
3031 |   [
3032 |     source 100
3033 |     target 2
3034 |   ]
3035 |   edge
3036 |   [
3037 |     source 100
3038 |     target 15
3039 |   ]
3040 |   edge
3041 |   [
3042 |     source 100
3043 |     target 32
3044 |   ]
3045 |   edge
3046 |   [
3047 |     source 100
3048 |     target 64
3049 |   ]
3050 |   edge
3051 |   [
3052 |     source 100
3053 |     target 47
3054 |   ]
3055 |   edge
3056 |   [
3057 |     source 100
3058 |     target 39
3059 |   ]
3060 |   edge
3061 |   [
3062 |     source 100
3063 |     target 6
3064 |   ]
3065 |   edge
3066 |   [
3067 |     source 101
3068 |     target 51
3069 |   ]
3070 |   edge
3071 |   [
3072 |     source 101
3073 |     target 30
3074 |   ]
3075 |   edge
3076 |   [
3077 |     source 101
3078 |     target 94
3079 |   ]
3080 |   edge
3081 |   [
3082 |     source 101
3083 |     target 1
3084 |   ]
3085 |   edge
3086 |   [
3087 |     source 101
3088 |     target 79
3089 |   ]
3090 |   edge
3091 |   [
3092 |     source 101
3093 |     target 58
3094 |   ]
3095 |   edge
3096 |   [
3097 |     source 101
3098 |     target 19
3099 |   ]
3100 |   edge
3101 |   [
3102 |     source 101
3103 |     target 55
3104 |   ]
3105 |   edge
3106 |   [
3107 |     source 101
3108 |     target 35
3109 |   ]
3110 |   edge
3111 |   [
3112 |     source 101
3113 |     target 29
3114 |   ]
3115 |   edge
3116 |   [
3117 |     source 102
3118 |     target 100
3119 |   ]
3120 |   edge
3121 |   [
3122 |     source 102
3123 |     target 74
3124 |   ]
3125 |   edge
3126 |   [
3127 |     source 102
3128 |     target 52
3129 |   ]
3130 |   edge
3131 |   [
3132 |     source 102
3133 |     target 98
3134 |   ]
3135 |   edge
3136 |   [
3137 |     source 102
3138 |     target 72
3139 |   ]
3140 |   edge
3141 |   [
3142 |     source 102
3143 |     target 40
3144 |   ]
3145 |   edge
3146 |   [
3147 |     source 102
3148 |     target 10
3149 |   ]
3150 |   edge
3151 |   [
3152 |     source 102
3153 |     target 3
3154 |   ]
3155 |   edge
3156 |   [
3157 |     source 103
3158 |     target 102
3159 |   ]
3160 |   edge
3161 |   [
3162 |     source 103
3163 |     target 33
3164 |   ]
3165 |   edge
3166 |   [
3167 |     source 103
3168 |     target 45
3169 |   ]
3170 |   edge
3171 |   [
3172 |     source 103
3173 |     target 25
3174 |   ]
3175 |   edge
3176 |   [
3177 |     source 103
3178 |     target 89
3179 |   ]
3180 |   edge
3181 |   [
3182 |     source 103
3183 |     target 37
3184 |   ]
3185 |   edge
3186 |   [
3187 |     source 103
3188 |     target 1
3189 |   ]
3190 |   edge
3191 |   [
3192 |     source 103
3193 |     target 70
3194 |   ]
3195 |   edge
3196 |   [
3197 |     source 104
3198 |     target 72
3199 |   ]
3200 |   edge
3201 |   [
3202 |     source 104
3203 |     target 11
3204 |   ]
3205 |   edge
3206 |   [
3207 |     source 104
3208 |     target 0
3209 |   ]
3210 |   edge
3211 |   [
3212 |     source 104
3213 |     target 93
3214 |   ]
3215 |   edge
3216 |   [
3217 |     source 104
3218 |     target 67
3219 |   ]
3220 |   edge
3221 |   [
3222 |     source 104
3223 |     target 41
3224 |   ]
3225 |   edge
3226 |   [
3227 |     source 104
3228 |     target 16
3229 |   ]
3230 |   edge
3231 |   [
3232 |     source 104
3233 |     target 87
3234 |   ]
3235 |   edge
3236 |   [
3237 |     source 104
3238 |     target 23
3239 |   ]
3240 |   edge
3241 |   [
3242 |     source 104
3243 |     target 4
3244 |   ]
3245 |   edge
3246 |   [
3247 |     source 104
3248 |     target 9
3249 |   ]
3250 |   edge
3251 |   [
3252 |     source 105
3253 |     target 89
3254 |   ]
3255 |   edge
3256 |   [
3257 |     source 105
3258 |     target 103
3259 |   ]
3260 |   edge
3261 |   [
3262 |     source 105
3263 |     target 33
3264 |   ]
3265 |   edge
3266 |   [
3267 |     source 105
3268 |     target 62
3269 |   ]
3270 |   edge
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3761 | 


--------------------------------------------------------------------------------
/data/jazz.net:
--------------------------------------------------------------------------------
   1 | *Vertices 198
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   3 | 2 "2" -181.74585 -1081.682 0.0
   4 | 3 "3" -788.42645 545.07074 0.0
   5 | 4 "4" -1102.9778 18.539915 0.0
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  17 | 16 "16" 982.68207 540.7922 0.0
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 200 | *Edges
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 202 | 1 24 2.0
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 204 | 1 42 2.0
 205 | 1 46 2.0
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 230 | 3 172 2.0
 231 | 4 5 2.0
 232 | 4 13 2.0
 233 | 4 26 2.0
 234 | 4 77 2.0
 235 | 4 85 2.0
 236 | 4 102 2.0
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1098 | 50 81 2.0
1099 | 50 88 2.0
1100 | 50 106 2.0
1101 | 50 110 2.0
1102 | 50 111 2.0
1103 | 50 114 2.0
1104 | 50 123 2.0
1105 | 50 131 2.0
1106 | 50 132 2.0
1107 | 50 139 2.0
1108 | 50 158 2.0
1109 | 50 166 2.0
1110 | 50 168 2.0
1111 | 50 179 2.0
1112 | 50 183 2.0
1113 | 50 196 2.0
1114 | 51 75 2.0
1115 | 51 76 2.0
1116 | 51 79 2.0
1117 | 51 96 2.0
1118 | 51 126 2.0
1119 | 51 128 2.0
1120 | 51 136 2.0
1121 | 51 144 2.0
1122 | 51 147 2.0
1123 | 51 149 2.0
1124 | 51 153 2.0
1125 | 51 167 2.0
1126 | 51 172 2.0
1127 | 51 174 2.0
1128 | 51 181 2.0
1129 | 52 53 2.0
1130 | 52 60 2.0
1131 | 52 83 2.0
1132 | 52 88 2.0
1133 | 52 196 2.0
1134 | 53 54 2.0
1135 | 53 55 2.0
1136 | 53 56 2.0
1137 | 53 57 2.0
1138 | 53 60 2.0
1139 | 53 61 2.0
1140 | 53 67 2.0
1141 | 53 71 2.0
1142 | 53 81 2.0
1143 | 53 83 2.0
1144 | 53 88 2.0
1145 | 53 111 2.0
1146 | 53 112 2.0
1147 | 53 113 2.0
1148 | 53 114 2.0
1149 | 53 129 2.0
1150 | 53 131 2.0
1151 | 53 132 2.0
1152 | 53 149 2.0
1153 | 53 150 2.0
1154 | 53 158 2.0
1155 | 53 161 2.0
1156 | 53 164 2.0
1157 | 53 170 2.0
1158 | 53 178 2.0
1159 | 53 183 2.0
1160 | 53 194 2.0
1161 | 53 195 2.0
1162 | 53 196 2.0
1163 | 53 197 2.0
1164 | 54 55 2.0
1165 | 54 56 2.0
1166 | 54 57 2.0
1167 | 54 60 2.0
1168 | 54 61 2.0
1169 | 54 67 2.0
1170 | 54 69 2.0
1171 | 54 70 2.0
1172 | 54 83 2.0
1173 | 54 87 2.0
1174 | 54 93 2.0
1175 | 54 94 2.0
1176 | 54 96 2.0
1177 | 54 111 2.0
1178 | 54 125 2.0
1179 | 54 129 2.0
1180 | 54 130 2.0
1181 | 54 146 2.0
1182 | 54 149 2.0
1183 | 54 150 2.0
1184 | 54 158 2.0
1185 | 54 161 2.0
1186 | 54 164 2.0
1187 | 54 168 2.0
1188 | 54 170 2.0
1189 | 54 174 2.0
1190 | 54 177 2.0
1191 | 54 178 2.0
1192 | 54 186 2.0
1193 | 54 190 2.0
1194 | 54 192 2.0
1195 | 54 193 2.0
1196 | 54 194 2.0
1197 | 54 195 2.0
1198 | 54 196 2.0
1199 | 54 197 2.0
1200 | 55 56 2.0
1201 | 55 57 2.0
1202 | 55 60 2.0
1203 | 55 61 2.0
1204 | 55 67 2.0
1205 | 55 81 2.0
1206 | 55 83 2.0
1207 | 55 129 2.0
1208 | 55 150 2.0
1209 | 55 158 2.0
1210 | 55 164 2.0
1211 | 55 170 2.0
1212 | 55 178 2.0
1213 | 55 194 2.0
1214 | 55 195 2.0
1215 | 55 196 2.0
1216 | 55 197 2.0
1217 | 56 57 2.0
1218 | 56 60 2.0
1219 | 56 61 2.0
1220 | 56 67 2.0
1221 | 56 81 2.0
1222 | 56 83 2.0
1223 | 56 88 2.0
1224 | 56 111 2.0
1225 | 56 114 2.0
1226 | 56 129 2.0
1227 | 56 131 2.0
1228 | 56 132 2.0
1229 | 56 150 2.0
1230 | 56 158 2.0
1231 | 56 164 2.0
1232 | 56 170 2.0
1233 | 56 178 2.0
1234 | 56 183 2.0
1235 | 56 194 2.0
1236 | 56 195 2.0
1237 | 56 196 2.0
1238 | 56 197 2.0
1239 | 57 60 2.0
1240 | 57 61 2.0
1241 | 57 70 2.0
1242 | 57 71 2.0
1243 | 57 83 2.0
1244 | 57 89 2.0
1245 | 57 111 2.0
1246 | 57 112 2.0
1247 | 57 113 2.0
1248 | 57 114 2.0
1249 | 57 121 2.0
1250 | 57 129 2.0
1251 | 57 130 2.0
1252 | 57 136 2.0
1253 | 57 142 2.0
1254 | 57 158 2.0
1255 | 57 161 2.0
1256 | 57 164 2.0
1257 | 57 185 2.0
1258 | 57 192 2.0
1259 | 57 194 2.0
1260 | 57 195 2.0
1261 | 57 196 2.0
1262 | 57 197 2.0
1263 | 58 60 2.0
1264 | 58 62 2.0
1265 | 58 63 2.0
1266 | 58 64 2.0
1267 | 58 65 2.0
1268 | 58 66 2.0
1269 | 58 98 2.0
1270 | 58 99 2.0
1271 | 58 100 2.0
1272 | 58 101 2.0
1273 | 58 105 2.0
1274 | 58 106 2.0
1275 | 58 107 2.0
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1278 | 58 110 2.0
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1280 | 58 123 2.0
1281 | 58 131 2.0
1282 | 58 132 2.0
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1284 | 58 154 2.0
1285 | 58 162 2.0
1286 | 58 168 2.0
1287 | 58 179 2.0
1288 | 58 187 2.0
1289 | 58 188 2.0
1290 | 59 82 2.0
1291 | 59 99 2.0
1292 | 59 100 2.0
1293 | 59 118 2.0
1294 | 59 121 2.0
1295 | 59 122 2.0
1296 | 59 136 2.0
1297 | 59 143 2.0
1298 | 59 158 2.0
1299 | 59 162 2.0
1300 | 59 174 2.0
1301 | 60 61 2.0
1302 | 60 62 2.0
1303 | 60 63 2.0
1304 | 60 64 2.0
1305 | 60 65 2.0
1306 | 60 66 2.0
1307 | 60 68 2.0
1308 | 60 69 2.0
1309 | 60 70 2.0
1310 | 60 72 2.0
1311 | 60 78 2.0
1312 | 60 80 2.0
1313 | 60 81 2.0
1314 | 60 83 2.0
1315 | 60 88 2.0
1316 | 60 89 2.0
1317 | 60 91 2.0
1318 | 60 93 2.0
1319 | 60 94 2.0
1320 | 60 95 2.0
1321 | 60 98 2.0
1322 | 60 99 2.0
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1327 | 60 107 2.0
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1330 | 60 110 2.0
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1332 | 60 112 2.0
1333 | 60 114 2.0
1334 | 60 118 2.0
1335 | 60 121 2.0
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1337 | 60 123 2.0
1338 | 60 125 2.0
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1340 | 60 129 2.0
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1342 | 60 131 2.0
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1344 | 60 135 2.0
1345 | 60 136 2.0
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1348 | 60 146 2.0
1349 | 60 150 2.0
1350 | 60 151 2.0
1351 | 60 154 2.0
1352 | 60 158 2.0
1353 | 60 161 2.0
1354 | 60 164 2.0
1355 | 60 166 2.0
1356 | 60 168 2.0
1357 | 60 171 2.0
1358 | 60 174 2.0
1359 | 60 179 2.0
1360 | 60 183 2.0
1361 | 60 187 2.0
1362 | 60 190 2.0
1363 | 60 192 2.0
1364 | 60 193 2.0
1365 | 60 194 2.0
1366 | 60 195 2.0
1367 | 60 196 2.0
1368 | 60 197 2.0
1369 | 61 69 2.0
1370 | 61 70 2.0
1371 | 61 106 2.0
1372 | 61 111 2.0
1373 | 61 112 2.0
1374 | 61 114 2.0
1375 | 61 123 2.0
1376 | 61 127 2.0
1377 | 61 129 2.0
1378 | 61 130 2.0
1379 | 61 141 2.0
1380 | 61 151 2.0
1381 | 61 158 2.0
1382 | 61 177 2.0
1383 | 61 192 2.0
1384 | 61 194 2.0
1385 | 61 195 2.0
1386 | 61 196 2.0
1387 | 61 197 2.0
1388 | 62 63 2.0
1389 | 62 64 2.0
1390 | 62 65 2.0
1391 | 62 66 2.0
1392 | 62 98 2.0
1393 | 62 99 2.0
1394 | 62 100 2.0
1395 | 62 101 2.0
1396 | 62 105 2.0
1397 | 62 106 2.0
1398 | 62 107 2.0
1399 | 62 108 2.0
1400 | 62 109 2.0
1401 | 62 110 2.0
1402 | 62 122 2.0
1403 | 62 123 2.0
1404 | 62 131 2.0
1405 | 62 132 2.0
1406 | 62 135 2.0
1407 | 62 154 2.0
1408 | 62 168 2.0
1409 | 62 179 2.0
1410 | 63 64 2.0
1411 | 63 65 2.0
1412 | 63 66 2.0
1413 | 63 91 2.0
1414 | 63 98 2.0
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1416 | 63 100 2.0
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1420 | 63 107 2.0
1421 | 63 108 2.0
1422 | 63 109 2.0
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1424 | 63 122 2.0
1425 | 63 123 2.0
1426 | 63 131 2.0
1427 | 63 132 2.0
1428 | 63 135 2.0
1429 | 63 154 2.0
1430 | 63 168 2.0
1431 | 63 179 2.0
1432 | 64 65 2.0
1433 | 64 66 2.0
1434 | 64 98 2.0
1435 | 64 99 2.0
1436 | 64 100 2.0
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1438 | 64 105 2.0
1439 | 64 106 2.0
1440 | 64 107 2.0
1441 | 64 108 2.0
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1444 | 64 122 2.0
1445 | 64 123 2.0
1446 | 64 131 2.0
1447 | 64 132 2.0
1448 | 64 135 2.0
1449 | 64 139 2.0
1450 | 64 154 2.0
1451 | 64 168 2.0
1452 | 64 170 2.0
1453 | 64 179 2.0
1454 | 65 66 2.0
1455 | 65 98 2.0
1456 | 65 99 2.0
1457 | 65 100 2.0
1458 | 65 101 2.0
1459 | 65 105 2.0
1460 | 65 106 2.0
1461 | 65 107 2.0
1462 | 65 108 2.0
1463 | 65 109 2.0
1464 | 65 110 2.0
1465 | 65 122 2.0
1466 | 65 123 2.0
1467 | 65 131 2.0
1468 | 65 132 2.0
1469 | 65 135 2.0
1470 | 65 136 2.0
1471 | 65 139 2.0
1472 | 65 154 2.0
1473 | 65 168 2.0
1474 | 65 170 2.0
1475 | 65 179 2.0
1476 | 66 98 2.0
1477 | 66 99 2.0
1478 | 66 100 2.0
1479 | 66 101 2.0
1480 | 66 105 2.0
1481 | 66 106 2.0
1482 | 66 107 2.0
1483 | 66 108 2.0
1484 | 66 109 2.0
1485 | 66 110 2.0
1486 | 66 122 2.0
1487 | 66 123 2.0
1488 | 66 131 2.0
1489 | 66 132 2.0
1490 | 66 135 2.0
1491 | 66 136 2.0
1492 | 66 139 2.0
1493 | 66 154 2.0
1494 | 66 168 2.0
1495 | 66 170 2.0
1496 | 66 179 2.0
1497 | 66 182 2.0
1498 | 67 70 2.0
1499 | 67 81 2.0
1500 | 67 83 2.0
1501 | 67 84 2.0
1502 | 67 87 2.0
1503 | 67 103 2.0
1504 | 67 127 2.0
1505 | 67 134 2.0
1506 | 67 135 2.0
1507 | 67 136 2.0
1508 | 67 149 2.0
1509 | 67 150 2.0
1510 | 67 158 2.0
1511 | 67 159 2.0
1512 | 67 164 2.0
1513 | 67 170 2.0
1514 | 67 174 2.0
1515 | 67 178 2.0
1516 | 67 192 2.0
1517 | 67 194 2.0
1518 | 67 195 2.0
1519 | 67 196 2.0
1520 | 68 99 2.0
1521 | 68 101 2.0
1522 | 68 132 2.0
1523 | 68 135 2.0
1524 | 68 154 2.0
1525 | 68 166 2.0
1526 | 68 168 2.0
1527 | 68 171 2.0
1528 | 68 183 2.0
1529 | 68 187 2.0
1530 | 69 70 2.0
1531 | 69 73 2.0
1532 | 69 86 2.0
1533 | 69 87 2.0
1534 | 69 88 2.0
1535 | 69 90 2.0
1536 | 69 93 2.0
1537 | 69 94 2.0
1538 | 69 95 2.0
1539 | 69 96 2.0
1540 | 69 99 2.0
1541 | 69 108 2.0
1542 | 69 109 2.0
1543 | 69 110 2.0
1544 | 69 111 2.0
1545 | 69 112 2.0
1546 | 69 114 2.0
1547 | 69 118 2.0
1548 | 69 121 2.0
1549 | 69 122 2.0
1550 | 69 125 2.0
1551 | 69 127 2.0
1552 | 69 130 2.0
1553 | 69 132 2.0
1554 | 69 136 2.0
1555 | 69 141 2.0
1556 | 69 142 2.0
1557 | 69 143 2.0
1558 | 69 146 2.0
1559 | 69 150 2.0
1560 | 69 151 2.0
1561 | 69 158 2.0
1562 | 69 161 2.0
1563 | 69 164 2.0
1564 | 69 168 2.0
1565 | 69 171 2.0
1566 | 69 174 2.0
1567 | 69 175 2.0
1568 | 69 177 2.0
1569 | 69 183 2.0
1570 | 69 186 2.0
1571 | 69 190 2.0
1572 | 69 192 2.0
1573 | 69 193 2.0
1574 | 69 194 2.0
1575 | 69 195 2.0
1576 | 70 73 2.0
1577 | 70 83 2.0
1578 | 70 86 2.0
1579 | 70 87 2.0
1580 | 70 88 2.0
1581 | 70 93 2.0
1582 | 70 94 2.0
1583 | 70 95 2.0
1584 | 70 96 2.0
1585 | 70 99 2.0
1586 | 70 108 2.0
1587 | 70 110 2.0
1588 | 70 111 2.0
1589 | 70 112 2.0
1590 | 70 114 2.0
1591 | 70 118 2.0
1592 | 70 121 2.0
1593 | 70 122 2.0
1594 | 70 125 2.0
1595 | 70 127 2.0
1596 | 70 130 2.0
1597 | 70 132 2.0
1598 | 70 136 2.0
1599 | 70 141 2.0
1600 | 70 142 2.0
1601 | 70 143 2.0
1602 | 70 146 2.0
1603 | 70 150 2.0
1604 | 70 151 2.0
1605 | 70 158 2.0
1606 | 70 161 2.0
1607 | 70 164 2.0
1608 | 70 167 2.0
1609 | 70 168 2.0
1610 | 70 170 2.0
1611 | 70 171 2.0
1612 | 70 174 2.0
1613 | 70 175 2.0
1614 | 70 177 2.0
1615 | 70 178 2.0
1616 | 70 183 2.0
1617 | 70 185 2.0
1618 | 70 186 2.0
1619 | 70 190 2.0
1620 | 70 192 2.0
1621 | 70 193 2.0
1622 | 70 194 2.0
1623 | 70 195 2.0
1624 | 71 72 2.0
1625 | 71 74 2.0
1626 | 71 83 2.0
1627 | 71 103 2.0
1628 | 71 111 2.0
1629 | 71 112 2.0
1630 | 71 113 2.0
1631 | 71 114 2.0
1632 | 71 116 2.0
1633 | 71 117 2.0
1634 | 71 118 2.0
1635 | 71 121 2.0
1636 | 71 122 2.0
1637 | 71 137 2.0
1638 | 71 150 2.0
1639 | 71 153 2.0
1640 | 71 158 2.0
1641 | 71 161 2.0
1642 | 71 164 2.0
1643 | 71 168 2.0
1644 | 71 195 2.0
1645 | 71 196 2.0
1646 | 72 74 2.0
1647 | 72 103 2.0
1648 | 72 150 2.0
1649 | 72 161 2.0
1650 | 72 164 2.0
1651 | 73 77 2.0
1652 | 73 85 2.0
1653 | 73 86 2.0
1654 | 73 88 2.0
1655 | 73 90 2.0
1656 | 73 96 2.0
1657 | 73 99 2.0
1658 | 73 110 2.0
1659 | 73 128 2.0
1660 | 73 136 2.0
1661 | 73 140 2.0
1662 | 73 143 2.0
1663 | 73 147 2.0
1664 | 73 149 2.0
1665 | 73 155 2.0
1666 | 73 156 2.0
1667 | 73 167 2.0
1668 | 73 172 2.0
1669 | 73 174 2.0
1670 | 73 184 2.0
1671 | 73 189 2.0
1672 | 73 191 2.0
1673 | 74 78 2.0
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1676 | 74 104 2.0
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1678 | 74 112 2.0
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1680 | 74 150 2.0
1681 | 74 154 2.0
1682 | 74 161 2.0
1683 | 74 164 2.0
1684 | 74 168 2.0
1685 | 74 171 2.0
1686 | 75 76 2.0
1687 | 75 79 2.0
1688 | 75 86 2.0
1689 | 75 96 2.0
1690 | 75 126 2.0
1691 | 75 128 2.0
1692 | 75 136 2.0
1693 | 75 144 2.0
1694 | 75 147 2.0
1695 | 75 149 2.0
1696 | 75 163 2.0
1697 | 75 167 2.0
1698 | 75 172 2.0
1699 | 75 174 2.0
1700 | 75 198 2.0
1701 | 76 79 2.0
1702 | 76 96 2.0
1703 | 76 126 2.0
1704 | 76 128 2.0
1705 | 76 136 2.0
1706 | 76 144 2.0
1707 | 76 147 2.0
1708 | 76 149 2.0
1709 | 76 153 2.0
1710 | 76 172 2.0
1711 | 76 174 2.0
1712 | 77 85 2.0
1713 | 77 86 2.0
1714 | 77 88 2.0
1715 | 77 90 2.0
1716 | 77 96 2.0
1717 | 77 97 2.0
1718 | 77 102 2.0
1719 | 77 124 2.0
1720 | 77 128 2.0
1721 | 77 136 2.0
1722 | 77 138 2.0
1723 | 77 140 2.0
1724 | 77 147 2.0
1725 | 77 149 2.0
1726 | 77 167 2.0
1727 | 77 169 2.0
1728 | 77 172 2.0
1729 | 77 173 2.0
1730 | 77 184 2.0
1731 | 77 191 2.0
1732 | 78 80 2.0
1733 | 78 91 2.0
1734 | 78 95 2.0
1735 | 78 99 2.0
1736 | 78 100 2.0
1737 | 78 103 2.0
1738 | 78 104 2.0
1739 | 78 108 2.0
1740 | 78 136 2.0
1741 | 78 137 2.0
1742 | 78 154 2.0
1743 | 78 158 2.0
1744 | 78 168 2.0
1745 | 78 171 2.0
1746 | 78 174 2.0
1747 | 78 179 2.0
1748 | 78 182 2.0
1749 | 78 188 2.0
1750 | 79 86 2.0
1751 | 79 96 2.0
1752 | 79 118 2.0
1753 | 79 126 2.0
1754 | 79 128 2.0
1755 | 79 136 2.0
1756 | 79 142 2.0
1757 | 79 143 2.0
1758 | 79 144 2.0
1759 | 79 147 2.0
1760 | 79 149 2.0
1761 | 79 163 2.0
1762 | 79 167 2.0
1763 | 79 172 2.0
1764 | 79 174 2.0
1765 | 80 91 2.0
1766 | 80 95 2.0
1767 | 80 135 2.0
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1769 | 80 162 2.0
1770 | 80 168 2.0
1771 | 80 179 2.0
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1773 | 80 189 2.0
1774 | 81 83 2.0
1775 | 81 98 2.0
1776 | 81 99 2.0
1777 | 81 100 2.0
1778 | 81 101 2.0
1779 | 81 104 2.0
1780 | 81 105 2.0
1781 | 81 106 2.0
1782 | 81 108 2.0
1783 | 81 123 2.0
1784 | 81 131 2.0
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1786 | 81 136 2.0
1787 | 81 150 2.0
1788 | 81 158 2.0
1789 | 81 164 2.0
1790 | 81 170 2.0
1791 | 81 174 2.0
1792 | 81 178 2.0
1793 | 81 182 2.0
1794 | 81 183 2.0
1795 | 81 194 2.0
1796 | 81 195 2.0
1797 | 81 196 2.0
1798 | 81 197 2.0
1799 | 82 99 2.0
1800 | 82 118 2.0
1801 | 82 121 2.0
1802 | 82 122 2.0
1803 | 82 136 2.0
1804 | 82 143 2.0
1805 | 83 84 2.0
1806 | 83 87 2.0
1807 | 83 89 2.0
1808 | 83 90 2.0
1809 | 83 98 2.0
1810 | 83 99 2.0
1811 | 83 100 2.0
1812 | 83 101 2.0
1813 | 83 103 2.0
1814 | 83 105 2.0
1815 | 83 108 2.0
1816 | 83 109 2.0
1817 | 83 111 2.0
1818 | 83 114 2.0
1819 | 83 118 2.0
1820 | 83 121 2.0
1821 | 83 127 2.0
1822 | 83 131 2.0
1823 | 83 132 2.0
1824 | 83 134 2.0
1825 | 83 135 2.0
1826 | 83 136 2.0
1827 | 83 137 2.0
1828 | 83 141 2.0
1829 | 83 142 2.0
1830 | 83 149 2.0
1831 | 83 150 2.0
1832 | 83 158 2.0
1833 | 83 159 2.0
1834 | 83 164 2.0
1835 | 83 168 2.0
1836 | 83 170 2.0
1837 | 83 174 2.0
1838 | 83 178 2.0
1839 | 83 182 2.0
1840 | 83 185 2.0
1841 | 83 192 2.0
1842 | 83 194 2.0
1843 | 83 195 2.0
1844 | 83 196 2.0
1845 | 83 197 2.0
1846 | 84 118 2.0
1847 | 84 129 2.0
1848 | 84 134 2.0
1849 | 84 135 2.0
1850 | 84 136 2.0
1851 | 84 158 2.0
1852 | 84 159 2.0
1853 | 84 170 2.0
1854 | 84 175 2.0
1855 | 84 183 2.0
1856 | 84 194 2.0
1857 | 84 195 2.0
1858 | 85 86 2.0
1859 | 85 102 2.0
1860 | 85 128 2.0
1861 | 85 140 2.0
1862 | 85 147 2.0
1863 | 85 149 2.0
1864 | 85 155 2.0
1865 | 85 156 2.0
1866 | 85 167 2.0
1867 | 85 169 2.0
1868 | 85 189 2.0
1869 | 85 191 2.0
1870 | 86 88 2.0
1871 | 86 90 2.0
1872 | 86 96 2.0
1873 | 86 97 2.0
1874 | 86 102 2.0
1875 | 86 124 2.0
1876 | 86 128 2.0
1877 | 86 136 2.0
1878 | 86 138 2.0
1879 | 86 140 2.0
1880 | 86 147 2.0
1881 | 86 149 2.0
1882 | 86 153 2.0
1883 | 86 155 2.0
1884 | 86 156 2.0
1885 | 86 163 2.0
1886 | 86 167 2.0
1887 | 86 169 2.0
1888 | 86 172 2.0
1889 | 86 173 2.0
1890 | 86 176 2.0
1891 | 86 184 2.0
1892 | 86 189 2.0
1893 | 86 191 2.0
1894 | 86 198 2.0
1895 | 87 96 2.0
1896 | 87 103 2.0
1897 | 87 112 2.0
1898 | 87 114 2.0
1899 | 87 130 2.0
1900 | 87 150 2.0
1901 | 87 158 2.0
1902 | 87 161 2.0
1903 | 87 164 2.0
1904 | 87 186 2.0
1905 | 87 192 2.0
1906 | 87 194 2.0
1907 | 87 195 2.0
1908 | 88 90 2.0
1909 | 88 96 2.0
1910 | 88 97 2.0
1911 | 88 99 2.0
1912 | 88 110 2.0
1913 | 88 114 2.0
1914 | 88 128 2.0
1915 | 88 131 2.0
1916 | 88 132 2.0
1917 | 88 136 2.0
1918 | 88 140 2.0
1919 | 88 143 2.0
1920 | 88 147 2.0
1921 | 88 149 2.0
1922 | 88 158 2.0
1923 | 88 167 2.0
1924 | 88 172 2.0
1925 | 88 174 2.0
1926 | 88 183 2.0
1927 | 88 184 2.0
1928 | 88 191 2.0
1929 | 88 196 2.0
1930 | 89 95 2.0
1931 | 89 118 2.0
1932 | 89 121 2.0
1933 | 89 127 2.0
1934 | 89 132 2.0
1935 | 89 136 2.0
1936 | 89 141 2.0
1937 | 89 142 2.0
1938 | 89 149 2.0
1939 | 89 158 2.0
1940 | 89 171 2.0
1941 | 89 174 2.0
1942 | 89 196 2.0
1943 | 90 96 2.0
1944 | 90 97 2.0
1945 | 90 124 2.0
1946 | 90 125 2.0
1947 | 90 128 2.0
1948 | 90 133 2.0
1949 | 90 136 2.0
1950 | 90 138 2.0
1951 | 90 140 2.0
1952 | 90 147 2.0
1953 | 90 149 2.0
1954 | 90 153 2.0
1955 | 90 167 2.0
1956 | 90 169 2.0
1957 | 90 172 2.0
1958 | 90 173 2.0
1959 | 90 176 2.0
1960 | 90 184 2.0
1961 | 90 191 2.0
1962 | 90 198 2.0
1963 | 91 95 2.0
1964 | 91 104 2.0
1965 | 91 105 2.0
1966 | 91 107 2.0
1967 | 91 116 2.0
1968 | 91 119 2.0
1969 | 91 134 2.0
1970 | 91 135 2.0
1971 | 91 139 2.0
1972 | 91 168 2.0
1973 | 91 179 2.0
1974 | 92 148 2.0
1975 | 92 153 2.0
1976 | 92 163 2.0
1977 | 93 94 2.0
1978 | 93 95 2.0
1979 | 93 108 2.0
1980 | 93 111 2.0
1981 | 93 114 2.0
1982 | 93 118 2.0
1983 | 93 121 2.0
1984 | 93 122 2.0
1985 | 93 125 2.0
1986 | 93 127 2.0
1987 | 93 130 2.0
1988 | 93 132 2.0
1989 | 93 136 2.0
1990 | 93 146 2.0
1991 | 93 168 2.0
1992 | 93 171 2.0
1993 | 93 175 2.0
1994 | 93 177 2.0
1995 | 93 183 2.0
1996 | 93 190 2.0
1997 | 93 192 2.0
1998 | 93 193 2.0
1999 | 94 95 2.0
2000 | 94 108 2.0
2001 | 94 111 2.0
2002 | 94 114 2.0
2003 | 94 118 2.0
2004 | 94 121 2.0
2005 | 94 122 2.0
2006 | 94 125 2.0
2007 | 94 130 2.0
2008 | 94 132 2.0
2009 | 94 136 2.0
2010 | 94 146 2.0
2011 | 94 168 2.0
2012 | 94 171 2.0
2013 | 94 175 2.0
2014 | 94 177 2.0
2015 | 94 183 2.0
2016 | 94 190 2.0
2017 | 94 192 2.0
2018 | 94 193 2.0
2019 | 95 98 2.0
2020 | 95 99 2.0
2021 | 95 100 2.0
2022 | 95 101 2.0
2023 | 95 108 2.0
2024 | 95 110 2.0
2025 | 95 111 2.0
2026 | 95 122 2.0
2027 | 95 125 2.0
2028 | 95 127 2.0
2029 | 95 131 2.0
2030 | 95 132 2.0
2031 | 95 135 2.0
2032 | 95 136 2.0
2033 | 95 141 2.0
2034 | 95 142 2.0
2035 | 95 146 2.0
2036 | 95 154 2.0
2037 | 95 158 2.0
2038 | 95 168 2.0
2039 | 95 171 2.0
2040 | 95 174 2.0
2041 | 95 179 2.0
2042 | 95 190 2.0
2043 | 95 192 2.0
2044 | 95 193 2.0
2045 | 96 97 2.0
2046 | 96 124 2.0
2047 | 96 125 2.0
2048 | 96 126 2.0
2049 | 96 128 2.0
2050 | 96 130 2.0
2051 | 96 136 2.0
2052 | 96 138 2.0
2053 | 96 140 2.0
2054 | 96 142 2.0
2055 | 96 144 2.0
2056 | 96 147 2.0
2057 | 96 149 2.0
2058 | 96 150 2.0
2059 | 96 153 2.0
2060 | 96 158 2.0
2061 | 96 161 2.0
2062 | 96 163 2.0
2063 | 96 164 2.0
2064 | 96 167 2.0
2065 | 96 169 2.0
2066 | 96 172 2.0
2067 | 96 173 2.0
2068 | 96 176 2.0
2069 | 96 184 2.0
2070 | 96 186 2.0
2071 | 96 191 2.0
2072 | 96 192 2.0
2073 | 96 194 2.0
2074 | 96 198 2.0
2075 | 97 124 2.0
2076 | 97 128 2.0
2077 | 97 136 2.0
2078 | 97 138 2.0
2079 | 97 147 2.0
2080 | 97 149 2.0
2081 | 97 167 2.0
2082 | 97 169 2.0
2083 | 97 172 2.0
2084 | 98 99 2.0
2085 | 98 100 2.0
2086 | 98 101 2.0
2087 | 98 105 2.0
2088 | 98 106 2.0
2089 | 98 107 2.0
2090 | 98 108 2.0
2091 | 98 109 2.0
2092 | 98 110 2.0
2093 | 98 122 2.0
2094 | 98 123 2.0
2095 | 98 131 2.0
2096 | 98 132 2.0
2097 | 98 135 2.0
2098 | 98 136 2.0
2099 | 98 154 2.0
2100 | 98 164 2.0
2101 | 98 168 2.0
2102 | 98 170 2.0
2103 | 98 171 2.0
2104 | 98 174 2.0
2105 | 98 178 2.0
2106 | 98 179 2.0
2107 | 98 182 2.0
2108 | 98 194 2.0
2109 | 98 197 2.0
2110 | 99 100 2.0
2111 | 99 101 2.0
2112 | 99 105 2.0
2113 | 99 106 2.0
2114 | 99 107 2.0
2115 | 99 108 2.0
2116 | 99 109 2.0
2117 | 99 110 2.0
2118 | 99 118 2.0
2119 | 99 121 2.0
2120 | 99 122 2.0
2121 | 99 123 2.0
2122 | 99 131 2.0
2123 | 99 132 2.0
2124 | 99 135 2.0
2125 | 99 136 2.0
2126 | 99 143 2.0
2127 | 99 154 2.0
2128 | 99 164 2.0
2129 | 99 166 2.0
2130 | 99 168 2.0
2131 | 99 170 2.0
2132 | 99 171 2.0
2133 | 99 174 2.0
2134 | 99 178 2.0
2135 | 99 179 2.0
2136 | 99 182 2.0
2137 | 99 187 2.0
2138 | 99 194 2.0
2139 | 99 197 2.0
2140 | 100 101 2.0
2141 | 100 105 2.0
2142 | 100 106 2.0
2143 | 100 107 2.0
2144 | 100 108 2.0
2145 | 100 109 2.0
2146 | 100 110 2.0
2147 | 100 122 2.0
2148 | 100 123 2.0
2149 | 100 131 2.0
2150 | 100 132 2.0
2151 | 100 135 2.0
2152 | 100 136 2.0
2153 | 100 154 2.0
2154 | 100 164 2.0
2155 | 100 168 2.0
2156 | 100 170 2.0
2157 | 100 171 2.0
2158 | 100 174 2.0
2159 | 100 178 2.0
2160 | 100 179 2.0
2161 | 100 182 2.0
2162 | 100 194 2.0
2163 | 100 197 2.0
2164 | 101 105 2.0
2165 | 101 106 2.0
2166 | 101 107 2.0
2167 | 101 108 2.0
2168 | 101 109 2.0
2169 | 101 110 2.0
2170 | 101 122 2.0
2171 | 101 123 2.0
2172 | 101 131 2.0
2173 | 101 132 2.0
2174 | 101 135 2.0
2175 | 101 136 2.0
2176 | 101 154 2.0
2177 | 101 164 2.0
2178 | 101 166 2.0
2179 | 101 168 2.0
2180 | 101 170 2.0
2181 | 101 171 2.0
2182 | 101 174 2.0
2183 | 101 178 2.0
2184 | 101 179 2.0
2185 | 101 182 2.0
2186 | 101 187 2.0
2187 | 101 194 2.0
2188 | 101 197 2.0
2189 | 102 128 2.0
2190 | 102 138 2.0
2191 | 102 140 2.0
2192 | 102 147 2.0
2193 | 102 156 2.0
2194 | 102 167 2.0
2195 | 102 169 2.0
2196 | 102 172 2.0
2197 | 102 173 2.0
2198 | 102 176 2.0
2199 | 102 189 2.0
2200 | 103 104 2.0
2201 | 103 108 2.0
2202 | 103 112 2.0
2203 | 103 114 2.0
2204 | 103 150 2.0
2205 | 103 154 2.0
2206 | 103 161 2.0
2207 | 103 164 2.0
2208 | 103 168 2.0
2209 | 103 171 2.0
2210 | 103 178 2.0
2211 | 104 105 2.0
2212 | 104 107 2.0
2213 | 104 108 2.0
2214 | 104 154 2.0
2215 | 104 159 2.0
2216 | 104 168 2.0
2217 | 104 171 2.0
2218 | 105 106 2.0
2219 | 105 107 2.0
2220 | 105 108 2.0
2221 | 105 109 2.0
2222 | 105 110 2.0
2223 | 105 122 2.0
2224 | 105 123 2.0
2225 | 105 131 2.0
2226 | 105 132 2.0
2227 | 105 135 2.0
2228 | 105 136 2.0
2229 | 105 154 2.0
2230 | 105 164 2.0
2231 | 105 168 2.0
2232 | 105 170 2.0
2233 | 105 174 2.0
2234 | 105 178 2.0
2235 | 105 179 2.0
2236 | 105 182 2.0
2237 | 105 194 2.0
2238 | 105 197 2.0
2239 | 106 107 2.0
2240 | 106 108 2.0
2241 | 106 109 2.0
2242 | 106 110 2.0
2243 | 106 111 2.0
2244 | 106 122 2.0
2245 | 106 123 2.0
2246 | 106 131 2.0
2247 | 106 132 2.0
2248 | 106 135 2.0
2249 | 106 154 2.0
2250 | 106 168 2.0
2251 | 106 179 2.0
2252 | 106 183 2.0
2253 | 106 187 2.0
2254 | 106 188 2.0
2255 | 107 108 2.0
2256 | 107 109 2.0
2257 | 107 110 2.0
2258 | 107 122 2.0
2259 | 107 123 2.0
2260 | 107 131 2.0
2261 | 107 132 2.0
2262 | 107 135 2.0
2263 | 107 154 2.0
2264 | 107 162 2.0
2265 | 107 168 2.0
2266 | 107 179 2.0
2267 | 107 187 2.0
2268 | 107 188 2.0
2269 | 108 109 2.0
2270 | 108 110 2.0
2271 | 108 111 2.0
2272 | 108 122 2.0
2273 | 108 123 2.0
2274 | 108 125 2.0
2275 | 108 131 2.0
2276 | 108 132 2.0
2277 | 108 135 2.0
2278 | 108 136 2.0
2279 | 108 146 2.0
2280 | 108 154 2.0
2281 | 108 164 2.0
2282 | 108 168 2.0
2283 | 108 170 2.0
2284 | 108 171 2.0
2285 | 108 174 2.0
2286 | 108 178 2.0
2287 | 108 179 2.0
2288 | 108 182 2.0
2289 | 108 190 2.0
2290 | 108 192 2.0
2291 | 108 193 2.0
2292 | 108 194 2.0
2293 | 108 197 2.0
2294 | 109 110 2.0
2295 | 109 122 2.0
2296 | 109 123 2.0
2297 | 109 131 2.0
2298 | 109 132 2.0
2299 | 109 135 2.0
2300 | 109 154 2.0
2301 | 109 168 2.0
2302 | 109 170 2.0
2303 | 109 177 2.0
2304 | 109 179 2.0
2305 | 110 122 2.0
2306 | 110 123 2.0
2307 | 110 131 2.0
2308 | 110 132 2.0
2309 | 110 135 2.0
2310 | 110 136 2.0
2311 | 110 139 2.0
2312 | 110 143 2.0
2313 | 110 154 2.0
2314 | 110 168 2.0
2315 | 110 170 2.0
2316 | 110 171 2.0
2317 | 110 174 2.0
2318 | 110 179 2.0
2319 | 110 182 2.0
2320 | 111 116 2.0
2321 | 111 117 2.0
2322 | 111 118 2.0
2323 | 111 121 2.0
2324 | 111 122 2.0
2325 | 111 123 2.0
2326 | 111 125 2.0
2327 | 111 132 2.0
2328 | 111 137 2.0
2329 | 111 146 2.0
2330 | 111 153 2.0
2331 | 111 168 2.0
2332 | 111 170 2.0
2333 | 111 171 2.0
2334 | 111 190 2.0
2335 | 111 192 2.0
2336 | 111 193 2.0
2337 | 111 194 2.0
2338 | 111 195 2.0
2339 | 111 196 2.0
2340 | 112 113 2.0
2341 | 112 114 2.0
2342 | 112 127 2.0
2343 | 112 130 2.0
2344 | 112 141 2.0
2345 | 112 150 2.0
2346 | 112 151 2.0
2347 | 112 158 2.0
2348 | 112 161 2.0
2349 | 112 164 2.0
2350 | 112 192 2.0
2351 | 112 195 2.0
2352 | 112 196 2.0
2353 | 113 114 2.0
2354 | 113 158 2.0
2355 | 113 161 2.0
2356 | 113 164 2.0
2357 | 113 196 2.0
2358 | 114 125 2.0
2359 | 114 127 2.0
2360 | 114 130 2.0
2361 | 114 131 2.0
2362 | 114 132 2.0
2363 | 114 136 2.0
2364 | 114 141 2.0
2365 | 114 142 2.0
2366 | 114 146 2.0
2367 | 114 151 2.0
2368 | 114 158 2.0
2369 | 114 161 2.0
2370 | 114 164 2.0
2371 | 114 183 2.0
2372 | 114 190 2.0
2373 | 114 192 2.0
2374 | 114 193 2.0
2375 | 114 195 2.0
2376 | 114 196 2.0
2377 | 115 148 2.0
2378 | 115 152 2.0
2379 | 115 153 2.0
2380 | 115 157 2.0
2381 | 115 167 2.0
2382 | 115 172 2.0
2383 | 116 117 2.0
2384 | 116 118 2.0
2385 | 116 119 2.0
2386 | 116 121 2.0
2387 | 116 122 2.0
2388 | 116 134 2.0
2389 | 116 135 2.0
2390 | 116 137 2.0
2391 | 116 153 2.0
2392 | 116 168 2.0
2393 | 116 179 2.0
2394 | 116 181 2.0
2395 | 117 118 2.0
2396 | 117 121 2.0
2397 | 117 122 2.0
2398 | 117 137 2.0
2399 | 117 153 2.0
2400 | 117 168 2.0
2401 | 117 179 2.0
2402 | 117 183 2.0
2403 | 118 121 2.0
2404 | 118 122 2.0
2405 | 118 125 2.0
2406 | 118 129 2.0
2407 | 118 132 2.0
2408 | 118 136 2.0
2409 | 118 137 2.0
2410 | 118 142 2.0
2411 | 118 143 2.0
2412 | 118 146 2.0
2413 | 118 153 2.0
2414 | 118 168 2.0
2415 | 118 170 2.0
2416 | 118 174 2.0
2417 | 118 175 2.0
2418 | 118 177 2.0
2419 | 118 183 2.0
2420 | 118 190 2.0
2421 | 118 192 2.0
2422 | 118 193 2.0
2423 | 118 194 2.0
2424 | 119 120 2.0
2425 | 119 134 2.0
2426 | 119 135 2.0
2427 | 119 179 2.0
2428 | 121 122 2.0
2429 | 121 125 2.0
2430 | 121 132 2.0
2431 | 121 136 2.0
2432 | 121 137 2.0
2433 | 121 142 2.0
2434 | 121 143 2.0
2435 | 121 146 2.0
2436 | 121 153 2.0
2437 | 121 158 2.0
2438 | 121 168 2.0
2439 | 121 174 2.0
2440 | 121 175 2.0
2441 | 121 177 2.0
2442 | 121 183 2.0
2443 | 121 190 2.0
2444 | 121 192 2.0
2445 | 121 193 2.0
2446 | 121 196 2.0
2447 | 122 123 2.0
2448 | 122 125 2.0
2449 | 122 131 2.0
2450 | 122 132 2.0
2451 | 122 135 2.0
2452 | 122 136 2.0
2453 | 122 137 2.0
2454 | 122 143 2.0
2455 | 122 146 2.0
2456 | 122 153 2.0
2457 | 122 154 2.0
2458 | 122 168 2.0
2459 | 122 171 2.0
2460 | 122 179 2.0
2461 | 122 190 2.0
2462 | 122 192 2.0
2463 | 122 193 2.0
2464 | 123 131 2.0
2465 | 123 132 2.0
2466 | 123 135 2.0
2467 | 123 154 2.0
2468 | 123 162 2.0
2469 | 123 168 2.0
2470 | 123 179 2.0
2471 | 123 183 2.0
2472 | 123 187 2.0
2473 | 123 188 2.0
2474 | 124 128 2.0
2475 | 124 138 2.0
2476 | 124 140 2.0
2477 | 124 153 2.0
2478 | 124 176 2.0
2479 | 124 184 2.0
2480 | 124 198 2.0
2481 | 125 130 2.0
2482 | 125 132 2.0
2483 | 125 136 2.0
2484 | 125 142 2.0
2485 | 125 146 2.0
2486 | 125 151 2.0
2487 | 125 168 2.0
2488 | 125 171 2.0
2489 | 125 175 2.0
2490 | 125 177 2.0
2491 | 125 183 2.0
2492 | 125 190 2.0
2493 | 125 192 2.0
2494 | 125 193 2.0
2495 | 126 128 2.0
2496 | 126 136 2.0
2497 | 126 144 2.0
2498 | 126 147 2.0
2499 | 126 149 2.0
2500 | 126 153 2.0
2501 | 126 167 2.0
2502 | 126 172 2.0
2503 | 126 174 2.0
2504 | 127 130 2.0
2505 | 127 136 2.0
2506 | 127 141 2.0
2507 | 127 142 2.0
2508 | 127 150 2.0
2509 | 127 151 2.0
2510 | 127 158 2.0
2511 | 127 164 2.0
2512 | 127 171 2.0
2513 | 127 174 2.0
2514 | 127 178 2.0
2515 | 127 185 2.0
2516 | 127 192 2.0
2517 | 127 195 2.0
2518 | 128 136 2.0
2519 | 128 138 2.0
2520 | 128 140 2.0
2521 | 128 144 2.0
2522 | 128 147 2.0
2523 | 128 149 2.0
2524 | 128 153 2.0
2525 | 128 155 2.0
2526 | 128 156 2.0
2527 | 128 167 2.0
2528 | 128 169 2.0
2529 | 128 172 2.0
2530 | 128 173 2.0
2531 | 128 176 2.0
2532 | 128 184 2.0
2533 | 128 189 2.0
2534 | 128 191 2.0
2535 | 128 192 2.0
2536 | 129 136 2.0
2537 | 129 170 2.0
2538 | 129 175 2.0
2539 | 129 183 2.0
2540 | 129 194 2.0
2541 | 129 195 2.0
2542 | 129 196 2.0
2543 | 129 197 2.0
2544 | 130 136 2.0
2545 | 130 141 2.0
2546 | 130 146 2.0
2547 | 130 150 2.0
2548 | 130 151 2.0
2549 | 130 158 2.0
2550 | 130 161 2.0
2551 | 130 164 2.0
2552 | 130 177 2.0
2553 | 130 185 2.0
2554 | 130 186 2.0
2555 | 130 190 2.0
2556 | 130 192 2.0
2557 | 130 193 2.0
2558 | 130 194 2.0
2559 | 130 195 2.0
2560 | 131 132 2.0
2561 | 131 135 2.0
2562 | 131 136 2.0
2563 | 131 139 2.0
2564 | 131 154 2.0
2565 | 131 158 2.0
2566 | 131 164 2.0
2567 | 131 168 2.0
2568 | 131 170 2.0
2569 | 131 171 2.0
2570 | 131 174 2.0
2571 | 131 178 2.0
2572 | 131 179 2.0
2573 | 131 182 2.0
2574 | 131 183 2.0
2575 | 131 194 2.0
2576 | 131 196 2.0
2577 | 131 197 2.0
2578 | 132 135 2.0
2579 | 132 136 2.0
2580 | 132 141 2.0
2581 | 132 142 2.0
2582 | 132 146 2.0
2583 | 132 154 2.0
2584 | 132 158 2.0
2585 | 132 164 2.0
2586 | 132 166 2.0
2587 | 132 168 2.0
2588 | 132 170 2.0
2589 | 132 171 2.0
2590 | 132 174 2.0
2591 | 132 178 2.0
2592 | 132 179 2.0
2593 | 132 182 2.0
2594 | 132 183 2.0
2595 | 132 187 2.0
2596 | 132 190 2.0
2597 | 132 192 2.0
2598 | 132 193 2.0
2599 | 132 194 2.0
2600 | 132 196 2.0
2601 | 132 197 2.0
2602 | 133 155 2.0
2603 | 133 156 2.0
2604 | 133 167 2.0
2605 | 133 180 2.0
2606 | 134 135 2.0
2607 | 134 159 2.0
2608 | 134 179 2.0
2609 | 134 195 2.0
2610 | 135 139 2.0
2611 | 135 154 2.0
2612 | 135 159 2.0
2613 | 135 162 2.0
2614 | 135 166 2.0
2615 | 135 168 2.0
2616 | 135 171 2.0
2617 | 135 179 2.0
2618 | 135 187 2.0
2619 | 135 189 2.0
2620 | 135 195 2.0
2621 | 136 137 2.0
2622 | 136 138 2.0
2623 | 136 140 2.0
2624 | 136 141 2.0
2625 | 136 142 2.0
2626 | 136 143 2.0
2627 | 136 144 2.0
2628 | 136 146 2.0
2629 | 136 147 2.0
2630 | 136 149 2.0
2631 | 136 150 2.0
2632 | 136 151 2.0
2633 | 136 158 2.0
2634 | 136 161 2.0
2635 | 136 162 2.0
2636 | 136 163 2.0
2637 | 136 164 2.0
2638 | 136 167 2.0
2639 | 136 168 2.0
2640 | 136 170 2.0
2641 | 136 171 2.0
2642 | 136 172 2.0
2643 | 136 174 2.0
2644 | 136 175 2.0
2645 | 136 177 2.0
2646 | 136 178 2.0
2647 | 136 182 2.0
2648 | 136 183 2.0
2649 | 136 184 2.0
2650 | 136 185 2.0
2651 | 136 188 2.0
2652 | 136 190 2.0
2653 | 136 191 2.0
2654 | 136 192 2.0
2655 | 136 193 2.0
2656 | 136 194 2.0
2657 | 136 196 2.0
2658 | 136 197 2.0
2659 | 137 153 2.0
2660 | 137 158 2.0
2661 | 137 168 2.0
2662 | 137 188 2.0
2663 | 138 145 2.0
2664 | 138 147 2.0
2665 | 138 149 2.0
2666 | 138 155 2.0
2667 | 138 167 2.0
2668 | 138 169 2.0
2669 | 138 172 2.0
2670 | 138 173 2.0
2671 | 138 178 2.0
2672 | 139 162 2.0
2673 | 139 179 2.0
2674 | 139 189 2.0
2675 | 140 147 2.0
2676 | 140 149 2.0
2677 | 140 153 2.0
2678 | 140 155 2.0
2679 | 140 156 2.0
2680 | 140 167 2.0
2681 | 140 169 2.0
2682 | 140 172 2.0
2683 | 140 173 2.0
2684 | 140 176 2.0
2685 | 140 184 2.0
2686 | 140 189 2.0
2687 | 140 191 2.0
2688 | 140 198 2.0
2689 | 141 142 2.0
2690 | 141 151 2.0
2691 | 141 158 2.0
2692 | 141 171 2.0
2693 | 141 174 2.0
2694 | 141 192 2.0
2695 | 141 195 2.0
2696 | 142 143 2.0
2697 | 142 149 2.0
2698 | 142 150 2.0
2699 | 142 158 2.0
2700 | 142 161 2.0
2701 | 142 164 2.0
2702 | 142 168 2.0
2703 | 142 171 2.0
2704 | 142 174 2.0
2705 | 142 185 2.0
2706 | 142 193 2.0
2707 | 142 196 2.0
2708 | 143 174 2.0
2709 | 144 147 2.0
2710 | 144 149 2.0
2711 | 144 153 2.0
2712 | 144 172 2.0
2713 | 144 174 2.0
2714 | 144 198 2.0
2715 | 145 167 2.0
2716 | 146 151 2.0
2717 | 146 168 2.0
2718 | 146 171 2.0
2719 | 146 175 2.0
2720 | 146 177 2.0
2721 | 146 183 2.0
2722 | 146 190 2.0
2723 | 146 192 2.0
2724 | 146 193 2.0
2725 | 147 149 2.0
2726 | 147 153 2.0
2727 | 147 156 2.0
2728 | 147 167 2.0
2729 | 147 169 2.0
2730 | 147 172 2.0
2731 | 147 173 2.0
2732 | 147 174 2.0
2733 | 147 176 2.0
2734 | 147 184 2.0
2735 | 147 189 2.0
2736 | 147 191 2.0
2737 | 148 153 2.0
2738 | 149 150 2.0
2739 | 149 153 2.0
2740 | 149 155 2.0
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/modularity_maximization/__init__.py:
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 1 | # -*- coding: utf-8 -*-
 2 | 
 3 | from modularity_maximization.community_newman import partition
 4 | from modularity_maximization.utils import get_modularity
 5 | 
 6 | __version__ = '0.0.1rc4'
 7 | __author__ = """Zhiya Zuo"""
 8 | __email__ = """zhiyazuo@gmail.com"""
 9 | 
10 | __license__ = """
11 | Copyright 2018 Zhiya Zuo
12 | 
13 | Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
14 | 
15 | The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
16 | 
17 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
18 | """
19 | 
20 | 


--------------------------------------------------------------------------------
/modularity_maximization/_divide.py:
--------------------------------------------------------------------------------
  1 | # -*- coding: utf-8 -*-
  2 | 
  3 | import numpy as np
  4 | import networkx as nx
  5 | from scipy import sparse
  6 | from modularity_maximization import utils
  7 | 
  8 | def _divide(network, community_dict, comm_index, B, refine=False):
  9 |     '''
 10 |     Bisection of a community in `network`.
 11 | 
 12 |     Parameters
 13 |     ----------
 14 |     network : nx.Graph or nx.DiGraph
 15 |         The network of interest
 16 | 
 17 |     Returns
 18 |     -------
 19 |     tuple
 20 |         If the given community is indivisible, return (None, None)
 21 |         If the given community is divisible, return a tuple where
 22 |         the 1st element is a node list for the 1st sub-group and
 23 |         the 2nd element is a node list for the original group
 24 |     '''
 25 | 
 26 |     comm_nodes = tuple(u for u in community_dict \
 27 |                   if community_dict[u] == comm_index)
 28 |     B_hat_g = utils.get_mod_matrix(network, comm_nodes, B)
 29 | 
 30 |     # compute the top eigenvector u₁ and β₁
 31 |     if B_hat_g.shape[0] < 3:
 32 |         beta_s, u_s = utils.largest_eig(B_hat_g)
 33 |     else:
 34 |         beta_s, u_s = sparse.linalg.eigs(B_hat_g, k=1, which='LR')
 35 |     u_1 = u_s[:, 0]
 36 |     beta_1 = beta_s[0]
 37 |     if beta_1 > 0:
 38 |         # divisible
 39 |         s = sparse.csc_matrix(np.asmatrix([[1 if u_1_i > 0 else -1] for u_1_i in u_1]))
 40 |         if refine:
 41 |             improve_modularity(network, comm_nodes, s, B)
 42 |         delta_modularity = utils._get_delta_Q(B_hat_g, s)
 43 |         if delta_modularity > 0:
 44 |             g1_nodes = np.array([comm_nodes[i] \
 45 |                                  for i in range(u_1.shape[0]) \
 46 |                                  if s[i,0] > 0])
 47 |             #g1 = nx.subgraph(g, g1_nodes)
 48 |             if len(g1_nodes) == len(comm_nodes) or len(g1_nodes) == 0:
 49 |                 # indivisble, return None
 50 |                 return None, None
 51 |             # divisible, return node list for one of the groups
 52 |             return g1_nodes, comm_nodes
 53 |     # indivisble, return None
 54 |     return None, None
 55 | 
 56 | def improve_modularity(network, comm_nodes, s, B):
 57 |     '''
 58 |     Fine tuning of the initial division from `_divide`
 59 |     Modify `s` inplace
 60 | 
 61 |     Parameters
 62 |     ----------
 63 |     network : nx.Graph or nx.DiGraph
 64 |         The network of interest
 65 |     comm_nodes: iterable
 66 |         List of nodes for the original group
 67 |     s: np.matrix
 68 |         A matrix of node membership. Only +1/-1
 69 |     B: np.amtrix
 70 |         Modularity matrix for `network`
 71 |     '''
 72 | 
 73 |     # iterate until no increment of Q
 74 |     B_hat_g = utils.get_mod_matrix(network, comm_nodes, B)
 75 |     while True:
 76 |         unmoved = list(comm_nodes)
 77 |         # node indices to be moved
 78 |         node_indices = np.array([], dtype=int)
 79 |         # cumulative improvement after moving
 80 |         node_improvement = np.array([], dtype=float)
 81 |         # keep moving until none left
 82 |         while len(unmoved) > 0:
 83 |             # init Q
 84 |             Q0 = utils._get_delta_Q(B_hat_g, s)
 85 |             scores = np.zeros(len(unmoved))
 86 |             for k_index in range(scores.size):
 87 |                 k = comm_nodes.index(unmoved[k_index])
 88 |                 s[k, 0] = -s[k, 0]
 89 |                 scores[k_index] = utils._get_delta_Q(B_hat_g, s) - Q0
 90 |                 s[k, 0] = -s[k, 0]
 91 |             _j = np.argmax(scores)
 92 |             j = comm_nodes.index(unmoved[_j])
 93 |             # move j, which has the largest increase or smallest decrease
 94 |             s[j, 0] = -s[j, 0]
 95 |             node_indices = np.append(node_indices, j)
 96 |             if node_improvement.size < 1:
 97 |                 node_improvement = np.append(node_improvement, scores[_j])
 98 |             else:
 99 |                 node_improvement = np.append(node_improvement, \
100 |                                         node_improvement[-1]+scores[_j])
101 |             #print len(unmoved), 'max: ', max(scores), node_improvement[-1]
102 |             unmoved.pop(_j)
103 |         # the biggest improvement
104 |         max_index = np.argmax(node_improvement)
105 |         # change all the remaining nodes
106 |         # which are not helping
107 |         for i in range(max_index+1, len(comm_nodes)):
108 |             j = node_indices[i]
109 |             s[j,0] = -s[j, 0]
110 |         # if we swap all the nodes, it is actually doing nothing
111 |         if max_index == len(comm_nodes) - 1:
112 |             delta_modularity = 0
113 |         else:
114 |             delta_modularity = node_improvement[max_index]
115 |         # Stop if ΔQ <= 0 
116 |         if delta_modularity <= 0:
117 |             break
118 | 


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/modularity_maximization/community_newman.py:
--------------------------------------------------------------------------------
  1 | # -*- coding: utf-8 -*-
  2 | 
  3 | import numpy as np
  4 | import networkx as nx
  5 | from collections import deque
  6 | from modularity_maximization import utils, _divide
  7 | 
  8 | def partition(network, refine=True):
  9 |     '''
 10 |     Cluster a network into several modules
 11 |     using modularity maximization by spectral methods.
 12 | 
 13 |     Supports directed and undirected networks.
 14 |     Edge weights are ignored
 15 | 
 16 |     See:
 17 | 
 18 |     Newman, M. E. J. (2006). Modularity and community structure in networks.
 19 |     Proceedings of the National Academy of Sciences of the United States of America,
 20 |     103(23), 8577–82. https://doi.org/10.1073/pnas.0601602103
 21 | 
 22 |     Leicht, E. A., & Newman, M. E. J. (2008). Community Structure in Directed Networks.
 23 |     Physical Review Letters, 100(11), 118703. https://doi.org/10.1103/PhysRevLett.100.118703
 24 | 
 25 |     Parameters
 26 |     ----------
 27 |     network : nx.Graph or nx.DiGraph
 28 |         The network of interest
 29 |     refine: Boolean
 30 |         Whether refine the `s` vector from the initial clustering
 31 |         by repeatedly moving nodes to maximize modularity
 32 | 
 33 |     Returns
 34 |     -------
 35 |     dict
 36 |         A dictionary that saves membership.
 37 |         Key: node label; Value: community index
 38 |     '''
 39 |     ## preprocessing
 40 |     network = nx.convert_node_labels_to_integers(network, first_label=1, label_attribute="node_name")
 41 |     node_name = nx.get_node_attributes(network, 'node_name')
 42 | 
 43 |     ## only support unweighted network 
 44 |     nx.set_edge_attributes(G=network, name='weight', values={edge:1 for edge in network.edges})
 45 | 
 46 |     B = utils.get_base_modularity_matrix(network)
 47 | 
 48 |     ## set flags for divisibility of communities
 49 |     ## initial community is divisible
 50 |     divisible_community = deque([0])
 51 | 
 52 |     ## add attributes: all node as one group
 53 |     community_dict = {u: 0 for u in network}
 54 | 
 55 |     ## overall modularity matrix
 56 | 
 57 |     comm_counter = 0
 58 | 
 59 |     while len(divisible_community) > 0:
 60 |         ## get the first divisible comm index out
 61 |         comm_index = divisible_community.popleft()
 62 |         g1_nodes, comm_nodes = _divide._divide(network, community_dict, comm_index, B, refine)
 63 |         if g1_nodes is None:
 64 |             ## indivisible, go to next
 65 |             continue
 66 |         ## Else divisible, obtain the other group g2
 67 |         #### Get the subgraphs (sub-communities)
 68 |         g1 = network.subgraph(g1_nodes)
 69 |         g2 = network.subgraph(set(comm_nodes).difference(set(g1_nodes)))
 70 |         parent = "%d"%comm_index
 71 | 
 72 |         ## add g1, g2 to tree and divisible list
 73 |         comm_counter += 1
 74 |         #community_tree.create_node(comm_counter, "%d" %comm_counter,\
 75 |         #                           parent = parent, data = g1_nodes)
 76 |         divisible_community.append(comm_counter)
 77 |         ## update community
 78 |         for u in g1:
 79 |             community_dict[u] = comm_counter
 80 | 
 81 |         #community_tree.create_node(comm_counter, "%d" %comm_counter,\
 82 |         #                          parent = parent, data = list(g2))
 83 |         comm_counter += 1
 84 |         divisible_community.append(comm_counter)
 85 |         ## update community
 86 |         for u in g2:
 87 |             community_dict[u] = comm_counter
 88 | 
 89 |         '''
 90 |         print '------'
 91 |         community_tree.show()
 92 |         partition = []
 93 |         for comm_index in set(community_dict.values()):
 94 |             print comm_index
 95 |             partition.append(set([node_name[i] for i in community_dict if community_dict[i]==comm_index]))
 96 |             print sorted(list(partition[-1]))
 97 |         print 'Modularity: ', utils.get_modularity(network, community_dict)
 98 |         '''
 99 | 
100 |     return {node_name[u]: community_dict[u] for u in network}
101 | 


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/modularity_maximization/utils.py:
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  1 | # -*- coding: utf-8 -*-
  2 | import numpy as np
  3 | import networkx as nx
  4 | from scipy import sparse
  5 | from scipy.linalg import eig
  6 | from itertools import product
  7 | 
  8 | def get_base_modularity_matrix(network):
  9 |     '''
 10 |     Obtain the modularity matrix for the whole network
 11 | 
 12 |     Parameters
 13 |     ----------
 14 |     network : nx.Graph or nx.DiGraph
 15 |         The network of interest
 16 | 
 17 |     Returns
 18 |     -------
 19 |     np.matrix
 20 |         The modularity matrix for `network`
 21 | 
 22 |     Raises
 23 |     ------
 24 |     TypeError
 25 |         When the input `network` does not fit either nx.Graph or nx.DiGraph
 26 |     '''
 27 | 
 28 |     if type(network) == nx.Graph:
 29 |         return sparse.csc_matrix(nx.modularity_matrix(network))
 30 |     elif type(network) == nx.DiGraph:
 31 |         return sparse.csc_matrix(nx.directed_modularity_matrix(network))
 32 |     else:
 33 |         raise TypeError('Graph type not supported. Use either nx.Graph or nx.Digraph')
 34 | 
 35 | def _get_delta_Q(X, a):
 36 |     '''
 37 |     Calculate the detal modularity
 38 |     .. math::
 39 |         \deltaQ = s^T \cdot \^{B_{g}} \cdot s
 40 |     .. math:: \deltaQ = s^T \cdot \^{B_{g}} \cdot s
 41 | 
 42 |     Parameters
 43 |     ----------
 44 |     X : np.matrix
 45 |         B_hat_g
 46 |     a : np.matrix
 47 |         s, which is the membership vector
 48 | 
 49 |     Returns
 50 |     -------
 51 |     float
 52 |         The corresponding :math:`\deltaQ`
 53 |     '''
 54 | 
 55 |     delta_Q = (a.T.dot(X)).dot(a)
 56 | 
 57 |     return delta_Q[0,0]
 58 | 
 59 | def get_modularity(network, community_dict):
 60 |     '''
 61 |     Calculate the modularity. Edge weights are ignored.
 62 | 
 63 |     Undirected:
 64 |     .. math:: Q = \frac{1}{2m}\sum_{i,j} \(A_ij - \frac{k_i k_j}{2m}\) * \detal_(c_i, c_j)
 65 | 
 66 |     Directed:
 67 |     .. math:: Q = \frac{1}{m}\sum_{i,j} \(A_ij - \frac{k_i^{in} k_j^{out}}{m}\) * \detal_{c_i, c_j}
 68 | 
 69 |     Parameters
 70 |     ----------
 71 |     network : nx.Graph or nx.DiGraph
 72 |         The network of interest
 73 |     community_dict : dict
 74 |         A dictionary to store the membership of each node
 75 |         Key is node and value is community index
 76 | 
 77 |     Returns
 78 |     -------
 79 |     float
 80 |         The modularity of `network` given `community_dict`
 81 |     '''
 82 | 
 83 |     Q = 0
 84 |     G = network.copy()
 85 |     nx.set_edge_attributes(G, {e:1 for e in G.edges}, 'weight')
 86 |     A = nx.to_scipy_sparse_matrix(G).astype(float)
 87 | 
 88 |     if type(G) == nx.Graph:
 89 |         # for undirected graphs, in and out treated as the same thing
 90 |         out_degree = in_degree = dict(nx.degree(G))
 91 |         M = 2.*(G.number_of_edges())
 92 |         print("Calculating modularity for undirected graph")
 93 |     elif type(G) == nx.DiGraph:
 94 |         in_degree = dict(G.in_degree())
 95 |         out_degree = dict(G.out_degree())
 96 |         M = 1.*G.number_of_edges()
 97 |         print("Calculating modularity for directed graph")
 98 |     else:
 99 |         print('Invalid graph type')
100 |         raise TypeError
101 | 
102 |     nodes = list(G)
103 |     Q = np.sum([A[i,j] - in_degree[nodes[i]]*\
104 |                          out_degree[nodes[j]]/M\
105 |                  for i, j in product(range(len(nodes)),\
106 |                                      range(len(nodes))) \
107 |                 if community_dict[nodes[i]] == community_dict[nodes[j]]])
108 |     return Q / M
109 | 
110 | def get_mod_matrix(network, comm_nodes=None, B=None):
111 |     '''
112 |     This function computes the modularity matrix
113 |     for a specific group in the network.
114 |     (a.k.a., generalized modularity matrix)
115 | 
116 |     Specifically,
117 |     .. math::
118 |         B^g_{i,j} = B_ij - \delta_{ij} \sum_(k \in g) B_ik
119 |         m = \abs[\Big]{E}
120 |         B_ij = A_ij - \dfrac{k_i k_j}{2m}
121 |         OR...
122 |         B_ij = \(A_ij - \frac{k_i^{in} k_j^{out}}{m}
123 | 
124 |     When `comm_nodes` is None or all nodes in `network`, this reduces to :math:`B`
125 | 
126 |     Parameters
127 |     ----------
128 |     network : nx.Graph or nx.DiGraph
129 |         The network of interest
130 |     comm_nodes : iterable (list, np.array, or tuple)
131 |         List of nodes that defines a community
132 |     B : np.matrix
133 |         Modularity matrix of `network`
134 | 
135 |     Returns
136 |     -------
137 |     np.matrix
138 |         The modularity of `comm_nodes` within `network`
139 |     '''
140 | 
141 |     if comm_nodes is None:
142 |         comm_nodes = list(network)
143 |         return get_base_modularity_matrix(network)
144 | 
145 |     if B is None:
146 |         B = get_base_modularity_matrix(network)
147 | 
148 |     # subset of mod matrix in g
149 |     indices = [list(network).index(u) for u in comm_nodes]
150 |     B_g = B[indices, :][:, indices]
151 |     #print 'Type of `B_g`:', type(B_g)
152 | 
153 |     # B^g_(i,j) = B_ij - δ_ij * ∑_(k∈g) B_ik
154 |     # i, j ∈ g
155 |     B_hat_g = np.zeros((len(comm_nodes), len(comm_nodes)), dtype=float)
156 | 
157 |     # ∑_(k∈g) B_ik
158 |     B_g_rowsum = np.asarray(B_g.sum(axis=1))[:, 0]
159 |     if type(network) == nx.Graph:
160 |         B_g_colsum = np.copy(B_g_rowsum)
161 |     elif type(network) == nx.DiGraph:
162 |         B_g_colsum = np.asarray(B_g.sum(axis=0))[0, :]
163 | 
164 |     for i in range(B_hat_g.shape[0]):
165 |         for j in range(B_hat_g.shape[0]):
166 |             if i == j:
167 |                 B_hat_g[i,j] = B_g[i,j] - 0.5 * (B_g_rowsum[i] + B_g_colsum[i])
168 |             else:
169 |                 B_hat_g[i,j] = B_g[i,j]
170 | 
171 |     if type(network) == nx.DiGraph:
172 |         B_hat_g = B_hat_g + B_hat_g.T
173 | 
174 |     return sparse.csc_matrix(B_hat_g)
175 | 
176 | def largest_eig(A):
177 |     '''
178 |         A wrapper over `scipy.linalg.eig` to produce
179 |         largest eigval and eigvector for A when A.shape is small
180 |     '''
181 |     vals, vectors = eig(A.todense())
182 |     real_indices = [idx for idx, val in enumerate(vals) if not bool(val.imag)]
183 |     vals = [vals[i].real for i in range(len(real_indices))]
184 |     vectors = [vectors[i] for i in range(len(real_indices))]
185 |     max_idx = np.argsort(vals)[-1]
186 |     return np.asarray([vals[max_idx]]), np.asarray([vectors[max_idx]]).T
187 | 


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/requirements.txt:
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1 | numpy
2 | scipy
3 | networkx
4 | 


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/setup.py:
--------------------------------------------------------------------------------
 1 | # Always prefer setuptools over distutils
 2 | from setuptools import setup, find_packages
 3 | # To use a consistent encoding
 4 | import os, codecs
 5 | 
 6 | HERE = os.path.abspath(os.path.dirname(__file__))
 7 | 
 8 | 
 9 | def read(*parts):
10 |     """
11 |     Build an absolute path from *parts* and and return the contents of the
12 |     resulting file.  Assume UTF-8 encoding.
13 |     """
14 |     with codecs.open(os.path.join(HERE, *parts), "rb", "utf-8") as f:
15 |         return f.read()
16 | 
17 | import modularity_maximization
18 | VERSION = modularity_maximization.__version__
19 | 
20 | setup(
21 |     name='python-modularity-maximization',
22 |     # You can just specify the packages manually here if your project is
23 |     # simple. Or you can use find_packages().
24 |     packages=['modularity_maximization'],
25 |     exclude_package_data={'': ['data*']},
26 | 
27 |     # Versions should comply with PEP440.  For a discussion on single-sourcing
28 |     # the version across setup.py and the project code, see
29 |     # https://packaging.python.org/en/latest/single_source_version.html
30 |     version=VERSION,
31 | 
32 |     description='Community detection using Newman spectral methods to maximize modularity',
33 |     long_description=read("README.rst"),
34 | 
35 |     # The project's main homepage.
36 |     url='http://zhiyzuo.github.io/python-modularity-maximization/',
37 |     download_url='https://github.com/zhiyzuo/python-modularity-maximization/tarball/' + VERSION,
38 | 
39 |     # Author details
40 |     author='Zhiya Zuo',
41 |     author_email='zhiyazuo@gmail.com',
42 | 
43 |     # Choose your license
44 |     license='MIT',
45 | 
46 |     # See https://pypi.python.org/pypi?%3Aaction=list_classifiers
47 |     classifiers=[
48 |         # How mature is this project? Common values are
49 |         #   3 - Alpha
50 |         #   4 - Beta
51 |         #   5 - Production/Stable
52 |         'Development Status :: 3 - Alpha',
53 | 
54 |         # Indicate who your project is intended for
55 |         'Intended Audience :: Education',
56 |         'Intended Audience :: Science/Research',
57 |         'Intended Audience :: Information Technology',
58 |         'Topic :: Scientific/Engineering :: Information Analysis',
59 | 
60 |         # Pick your license as you wish (should match "license" above)
61 |         'License :: OSI Approved :: MIT License',
62 | 
63 |         # Specify the Python versions you support here. In particular, ensure
64 |         # that you indicate whether you support Python 2, Python 3 or both.
65 |         'Programming Language :: Python :: 2',
66 |         'Programming Language :: Python :: 3',
67 |     ],
68 | 
69 |     keywords='modularity newman community-detection network-analysis clustering',
70 | 
71 |     install_requires=[
72 |         "scipy",
73 |         "numpy",
74 |         "networkx",
75 |     ]
76 | )
77 | 


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