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<title>delta/python-packages/networkx.git/networkx/algorithms/centrality/group.py, branch main</title>
<subtitle>github.com: networkx/networkx.git
</subtitle>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/'/>
<entry>
<title>Fix typos (#6620)</title>
<updated>2023-04-04T16:45:17+00:00</updated>
<author>
<name>Harri Nieminen</name>
<email>moiman@posteo.net</email>
</author>
<published>2023-04-04T16:45:17+00:00</published>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/commit/?id=7297ae8a37dd3356b64d383cb0c55735a6364bcc'/>
<id>7297ae8a37dd3356b64d383cb0c55735a6364bcc</id>
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</content>
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<pre>
</pre>
</div>
</content>
</entry>
<entry>
<title>Lint using Ruff (#6371)</title>
<updated>2023-02-19T17:14:00+00:00</updated>
<author>
<name>danieleades</name>
<email>33452915+danieleades@users.noreply.github.com</email>
</author>
<published>2023-02-19T17:14:00+00:00</published>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/commit/?id=5fcf01b9a43a097c4f579486023d1279b2b88619'/>
<id>5fcf01b9a43a097c4f579486023d1279b2b88619</id>
<content type='text'>
* lint and fix using ruff

* add flake8-pie lints

* remove useless import alias

* bump version

* bump deps

---------

Co-authored-by: daniel.eades &lt;daniel.eades@hotmail.com&gt;</content>
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<pre>
* lint and fix using ruff

* add flake8-pie lints

* remove useless import alias

* bump version

* bump deps

---------

Co-authored-by: daniel.eades &lt;daniel.eades@hotmail.com&gt;</pre>
</div>
</content>
</entry>
<entry>
<title>MAINT: Cleanup centrality module, remove unused variables (#5308)</title>
<updated>2022-06-04T17:22:18+00:00</updated>
<author>
<name>Mridul Seth</name>
<email>seth.mridul@gmail.com</email>
</author>
<published>2022-06-04T17:22:18+00:00</published>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/commit/?id=ddb1cb663d1c0be293aaa4d4284eab641255014f'/>
<id>ddb1cb663d1c0be293aaa4d4284eab641255014f</id>
<content type='text'>
* MAINT: Cleanup centrality module, remove unused variables

* make isort linter happy

* MAINT: make the loop more readable

Co-authored-by: Dan Schult &lt;dschult@colgate.edu&gt;

* make black happy

* Use a different name for internal function variable

Co-authored-by: Jarrod Millman &lt;jarrod.millman@gmail.com&gt;

* rename closeness_cen to closeness_dict

* minor cleanup in current_flow_betweenness and group

Co-authored-by: Dan Schult &lt;dschult@colgate.edu&gt;
Co-authored-by: Jarrod Millman &lt;jarrod.millman@gmail.com&gt;</content>
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<pre>
* MAINT: Cleanup centrality module, remove unused variables

* make isort linter happy

* MAINT: make the loop more readable

Co-authored-by: Dan Schult &lt;dschult@colgate.edu&gt;

* make black happy

* Use a different name for internal function variable

Co-authored-by: Jarrod Millman &lt;jarrod.millman@gmail.com&gt;

* rename closeness_cen to closeness_dict

* minor cleanup in current_flow_betweenness and group

Co-authored-by: Dan Schult &lt;dschult@colgate.edu&gt;
Co-authored-by: Jarrod Millman &lt;jarrod.millman@gmail.com&gt;</pre>
</div>
</content>
</entry>
<entry>
<title> Use isort with pre-commit to enforce import guidelines (#5659)</title>
<updated>2022-06-02T15:54:09+00:00</updated>
<author>
<name>Mridul Seth</name>
<email>seth.mridul@gmail.com</email>
</author>
<published>2022-06-02T15:54:09+00:00</published>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/commit/?id=5c0b11afb4c0882a070d522ef3fa41482ba935d3'/>
<id>5c0b11afb4c0882a070d522ef3fa41482ba935d3</id>
<content type='text'>
* Add isort to pre-commit

* Run isort on all python files (except __init__.py ones)</content>
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<pre>
* Add isort to pre-commit

* Run isort on all python files (except __init__.py ones)</pre>
</div>
</content>
</entry>
<entry>
<title>DOC: Fix links, use DOI links, wayback machine where required (#4868)</title>
<updated>2021-06-08T16:58:38+00:00</updated>
<author>
<name>Mridul Seth</name>
<email>seth.mridul@gmail.com</email>
</author>
<published>2021-06-08T16:58:38+00:00</published>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/commit/?id=5bc077c27155649f2503150a2623f49de093b332'/>
<id>5bc077c27155649f2503150a2623f49de093b332</id>
<content type='text'>
* Fix links, use DOI links, wayback machine where required

* Add nx-guides to intersphinx mapping.

* Replace external mpl link w/ intersphinx.

* Update mpl intersphinx mapping.

Co-authored-by: Ross Barnowski &lt;rossbar@berkeley.edu&gt;</content>
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<pre>
* Fix links, use DOI links, wayback machine where required

* Add nx-guides to intersphinx mapping.

* Replace external mpl link w/ intersphinx.

* Update mpl intersphinx mapping.

Co-authored-by: Ross Barnowski &lt;rossbar@berkeley.edu&gt;</pre>
</div>
</content>
</entry>
<entry>
<title>adding weight description to centrality metrices (#4610)</title>
<updated>2021-02-17T20:50:29+00:00</updated>
<author>
<name>guy rozenberg</name>
<email>guyroznb@gmail.com</email>
</author>
<published>2021-02-17T20:50:29+00:00</published>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/commit/?id=d5d4c414f3ac7e3e8e75beaf4c8f0bdc53f51fae'/>
<id>d5d4c414f3ac7e3e8e75beaf4c8f0bdc53f51fae</id>
<content type='text'>
Fixes #3921 

* weight description</content>
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<pre>
Fixes #3921 

* weight description</pre>
</div>
</content>
</entry>
<entry>
<title>Add prominent group algorithm (#4560)</title>
<updated>2021-02-05T21:31:42+00:00</updated>
<author>
<name>guy rozenberg</name>
<email>guyroznb@gmail.com</email>
</author>
<published>2021-02-05T21:31:42+00:00</published>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/commit/?id=dcd3ce622dcd73a85969bd732d26ae41f36216c9'/>
<id>dcd3ce622dcd73a85969bd732d26ae41f36216c9</id>
<content type='text'>
Adds prominent_group function to the centrality package

Co-authored-by: Ross Barnowski &lt;rossbar@berkeley.edu&gt;</content>
<content type='xhtml'>
<div xmlns='http://www.w3.org/1999/xhtml'>
<pre>
Adds prominent_group function to the centrality package

Co-authored-by: Ross Barnowski &lt;rossbar@berkeley.edu&gt;</pre>
</div>
</content>
</entry>
<entry>
<title>improve group betweenness centrality (#4435)</title>
<updated>2021-01-19T20:04:34+00:00</updated>
<author>
<name>guy rozenberg</name>
<email>guyroznb@gmail.com</email>
</author>
<published>2021-01-19T20:04:34+00:00</published>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/commit/?id=31c70c24d5ab657b02d453fbe3196071d15cd099'/>
<id>31c70c24d5ab657b02d453fbe3196071d15cd099</id>
<content type='text'>
* In this PR I improved the group betweenness centrality algorithm by using the algorithm of Puzis et al. "Fast algorithm for successive computation of group betweenness centrality".

In the previous implementation of the algorithm, for each pair of source - target non - group node permutation all the shortest paths were found and if one of them go through one of the nodes in the group then the group betweenness centrality increases. This was done for each group.

Here i used Pusiz et al. implementation, which finds the GBC with running time of $O(K^3)$ for each group (k is the number of nodes in the group) and with a preprocessing time of $O(mn)$ for all the groups.

This unable us to find the GBC of many groups in one preprocessing step.
 furthermore, the article shows how to find the prominent group of size k (the group with the highest GBC among those with size k), which i would add in future PR.

* In this PR I improved the group betweenness centrality algorithm by using the algorithm of Puzis et al. "Fast algorithm for successive computation of group betweenness centrality".

In the previous implementation of the algorithm, for each pair of source - target non - group node permutation all the shortest paths were found and if one of them go through one of the nodes in the group then the group betweenness centrality increases. This was done for each group.

Here i used Pusiz et al. implementation, which finds the GBC with running time of $O(K^3)$ for each group (k is the number of nodes in the group) and with a preprocessing time of $O(mn)$ for all the groups.

This unable us to find the GBC of many groups in one preprocessing step.
 furthermore, the article shows how to find the prominent group of size k (the group with the highest GBC among those with size k), which i would add in future PR.

* In this PR I improved the group betweenness centrality algorithm by using the algorithm of Puzis et al. "Fast algorithm for successive computation of group betweenness centrality".

In the previous implementation of the algorithm, for each pair of source - target non - group node permutation all the shortest paths were found and if one of them go through one of the nodes in the group then the group betweenness centrality increases. This was done for each group.

Here i used Pusiz et al. implementation, which finds the GBC with running time of $O(K^3)$ for each group (k is the number of nodes in the group) and with a preprocessing time of $O(mn)$ for all the groups.

This unable us to find the GBC of many groups in one preprocessing step.
 furthermore, the article shows how to find the prominent group of size k (the group with the highest GBC among those with size k), which i would add in future PR.

* In this PR I improved the group betweenness centrality algorithm by using the algorithm of Puzis et al. "Fast algorithm for successive computation of group betweenness centrality".

In the previous implementation of the algorithm, for each pair of source - target non - group node permutation all the shortest paths were found and if one of them go through one of the nodes in the group then the group betweenness centrality increases. This was done for each group.

Here i used Pusiz et al. implementation, which finds the GBC with running time of $O(K^3)$ for each group (k is the number of nodes in the group) and with a preprocessing time of $O(mn)$ for all the groups.

This unable us to find the GBC of many groups in one preprocessing step.
 furthermore, the article shows how to find the prominent group of size k (the group with the highest GBC among those with size k), which i would add in future PR.

* backwards-compatible with the previous implementation

* backwards-compatible with the previous implementation

* After review

* After review

* After review

* After review

* improving the runtime of the algorithm and fixing bug

* changing the help functions

* changing the help functions

* changing the help functions

* change the helper function and now the output value for a single group is an integer

* change the helper function and now the output value for a single group is an integer

* change the function description

* after review. Change normalize and docstring

* divide by 2 if G is undirected

* after changes</content>
<content type='xhtml'>
<div xmlns='http://www.w3.org/1999/xhtml'>
<pre>
* In this PR I improved the group betweenness centrality algorithm by using the algorithm of Puzis et al. "Fast algorithm for successive computation of group betweenness centrality".

In the previous implementation of the algorithm, for each pair of source - target non - group node permutation all the shortest paths were found and if one of them go through one of the nodes in the group then the group betweenness centrality increases. This was done for each group.

Here i used Pusiz et al. implementation, which finds the GBC with running time of $O(K^3)$ for each group (k is the number of nodes in the group) and with a preprocessing time of $O(mn)$ for all the groups.

This unable us to find the GBC of many groups in one preprocessing step.
 furthermore, the article shows how to find the prominent group of size k (the group with the highest GBC among those with size k), which i would add in future PR.

* In this PR I improved the group betweenness centrality algorithm by using the algorithm of Puzis et al. "Fast algorithm for successive computation of group betweenness centrality".

In the previous implementation of the algorithm, for each pair of source - target non - group node permutation all the shortest paths were found and if one of them go through one of the nodes in the group then the group betweenness centrality increases. This was done for each group.

Here i used Pusiz et al. implementation, which finds the GBC with running time of $O(K^3)$ for each group (k is the number of nodes in the group) and with a preprocessing time of $O(mn)$ for all the groups.

This unable us to find the GBC of many groups in one preprocessing step.
 furthermore, the article shows how to find the prominent group of size k (the group with the highest GBC among those with size k), which i would add in future PR.

* In this PR I improved the group betweenness centrality algorithm by using the algorithm of Puzis et al. "Fast algorithm for successive computation of group betweenness centrality".

In the previous implementation of the algorithm, for each pair of source - target non - group node permutation all the shortest paths were found and if one of them go through one of the nodes in the group then the group betweenness centrality increases. This was done for each group.

Here i used Pusiz et al. implementation, which finds the GBC with running time of $O(K^3)$ for each group (k is the number of nodes in the group) and with a preprocessing time of $O(mn)$ for all the groups.

This unable us to find the GBC of many groups in one preprocessing step.
 furthermore, the article shows how to find the prominent group of size k (the group with the highest GBC among those with size k), which i would add in future PR.

* In this PR I improved the group betweenness centrality algorithm by using the algorithm of Puzis et al. "Fast algorithm for successive computation of group betweenness centrality".

In the previous implementation of the algorithm, for each pair of source - target non - group node permutation all the shortest paths were found and if one of them go through one of the nodes in the group then the group betweenness centrality increases. This was done for each group.

Here i used Pusiz et al. implementation, which finds the GBC with running time of $O(K^3)$ for each group (k is the number of nodes in the group) and with a preprocessing time of $O(mn)$ for all the groups.

This unable us to find the GBC of many groups in one preprocessing step.
 furthermore, the article shows how to find the prominent group of size k (the group with the highest GBC among those with size k), which i would add in future PR.

* backwards-compatible with the previous implementation

* backwards-compatible with the previous implementation

* After review

* After review

* After review

* After review

* improving the runtime of the algorithm and fixing bug

* changing the help functions

* changing the help functions

* changing the help functions

* change the helper function and now the output value for a single group is an integer

* change the helper function and now the output value for a single group is an integer

* change the function description

* after review. Change normalize and docstring

* divide by 2 if G is undirected

* after changes</pre>
</div>
</content>
</entry>
<entry>
<title>Format w/ black</title>
<updated>2020-07-10T16:44:54+00:00</updated>
<author>
<name>Jarrod Millman</name>
<email>jarrod.millman@gmail.com</email>
</author>
<published>2020-07-10T06:12:10+00:00</published>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/commit/?id=b22d6b36ce0545995c99d233546e8a1fe7e27fc5'/>
<id>b22d6b36ce0545995c99d233546e8a1fe7e27fc5</id>
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</pre>
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</content>
</entry>
<entry>
<title>Remove superfluous encoding information</title>
<updated>2019-11-11T21:39:06+00:00</updated>
<author>
<name>Jarrod Millman</name>
<email>jarrod.millman@gmail.com</email>
</author>
<published>2019-11-09T07:58:15+00:00</published>
<link rel='alternate' type='text/html' href='http://91.123.203.49/cgit/delta/python-packages/networkx.git/commit/?id=cd2bde7856dc8057c8269696110ffb75795edf13'/>
<id>cd2bde7856dc8057c8269696110ffb75795edf13</id>
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