52eb FreshPorts -- math/py-apgl
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Port details
py-apgl 0.7.1 math on this many watch lists=0 search for ports that depend on this port
A fast python graph library with some machine learning features
Maintained by: wen@FreeBSD.org search for ports maintained by this maintainer
Port Added: 28 Oct 2010 13:20:34
Also Listed In: python
License: not specified in port


Another Python Graph Library is a simple, fast and easy to use graph library
with some machine learning features. The main features are as follows:

    * Directed, undirected and multigraphs designed under a hierarchical
class structure
    * Sparse and Dense graph structures using numpy and scipy for fast linear
algebra computations
    * Many operations on graphs such as subgraphs, search, Floyd-Warshall,
Dijkstras algorithm
    * Erdos-Renyi, Small-World and Albert-Barabasi random graphs
    * Write to Pajek, and simple CSV files
    * Some machine learning features - data preprocessing, kernels, PCA, KCCA,
wrappers for LibSVM, and some mlpy learning algorithms
    * Unit tested using the Python unittest framework

WWW:   http://packages.python.org/apgl/
SVNWeb : Main Web Site : Distfiles Availability : PortsMon

NOTE: FreshPorts displays only required dependencies information. Optional dependencies are not covered.

Required To Build:
  1. math/py-numpy
  2. science/py-scipy
  3. devel/py-setuptools
  4. lang/python27
Required To Run:
  1. math/py-numpy
  2. science/py-scipy
  3. devel/py-setuptools
  4. lang/python27
There are no ports dependent upon this port

To install the port: cd /usr/ports/math/py-apgl/ && make install clean
To add the package: pkg_add -r py27-apgl


Configuration Options
     No options to configure

Master Sites:
  1. ftp://ftp.FreeBSD.org/pub/FreeBSD/ports/distfiles/
  2. http://b.pypi.python.org/packages/source/a/apgl/
  3. http://c.pypi.python.org/packages/source/a/apgl/
  4. http://d.pypi.python.org/packages/source/a/apgl/
  5. http://e.pypi.python.org/packages/source/a/apgl/
  6. http://f.pypi.python.org/packages/source/a/apgl/
  7. http://pypi.inqbus.de/apgl/
  8. http://pypi.it.uwosh.edu/apgl/
  9. http://pypi.python.jp/apgl/
  10. http://pypi.python.org/packages/source/a/apgl/

Number of commits found: 12

Commit History - (may be incomplete: see SVNWeb link above for full details)
DateByDescription
04 Sep 2012 07:14:51
Original commit files touched by this commit  0.7.1
wen search for other commits by this committer
- Update to 0.7.1
18 Apr 2012 00:11:43
Original commit files touched by this commit  0.7
wen search for other commits by this committer
- Update to 0.7
05 Apr 2012 09:22:25
Original commit files touched by this commit  0.6.10
wen search for other commits by this committer
- Update to 0.6.10

Feature safe:   yes
11 Jan 2012 05:26:07
Original commit files touched by this commit  0.6.9
wen search for other commits by this committer
- Update to 0.6.9
09 Nov 2011 07:07:23
Original commit files touched by this commit  0.6.8
wen search for other commits by this committer
- Update to 0.6.8
15 Sep 2011 06:15:39
Original commit files touched by this commit  0.6.7
wen search for other commits by this committer
- Update to 0.6.7
01 Jul 2011 06:15:51
Original commit files touched by this commit  0.6.6
wen search for other commits by this committer
- Update to 0.6.6
09 May 2011 06:40:43
Original commit files touched by this commit  0.6.5
wen search for other commits by this committer
- Update to 0.6.5
08 Mar 2011 07:39:55
Original commit files touched by this commit  0.6.4
wen search for other commits by this committer
- Update to 0.6.4
15 Jan 2011 14:03:53
Original commit files touched by this commit  0.6.1
wen search for other commits by this committer
- Update to 0.6.1

Feature safe:   yes
06 Dec 2010 13:57:30
Original commit files touched by this commit  0.6
wen search for other commits by this committer
- Update to 0.6
28 Oct 2010 13:20:08
Original commit files touched by this commit  0.5.9.1
wen search for other commits by this committer
Another Python Graph Library is a simple, fast and easy to use graph library
with some machine learning features. The main features are as follows:

    * Directed, undirected and multigraphs designed under a hierarchical
class structure
    * Sparse and Dense graph structures using numpy and scipy for fast linear
algebra computations
    * Many operations on graphs such as subgraphs, search, Floyd-Warshall,
Dijkstras algorithm
    * Erdos-Renyi, Small-World and Albert-Barabasi random graphs
    * Write to Pajek, and simple CSV files
    * Some machine learning features - data preprocessing, kernels, PCA, KCCA,
wrappers for LibSVM, and some mlpy learning algorithms
    * Unit tested using the Python unittest framework

WWW:   http://packages.python.org/apgl/

Number of commits found: 12

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