[51765] trunk/dports/PortIndex

[portindex at macports.org]

Revision: 51765
          http://trac.macports.org/changeset/51765
Author:   portindex at macports.org
Date:     2009-06-02 13:54:20 -0700 (Tue, 02 Jun 2009)
Log Message:
-----------

Total number of ports parsed:	5825 
Ports successfully parsed:	5825	 
Ports failed:			0

Modified Paths:
--------------
    trunk/dports/PortIndex

Modified: trunk/dports/PortIndex
===================================================================
--- trunk/dports/PortIndex	2009-06-02 20:32:01 UTC (rev 51764)
+++ trunk/dports/PortIndex	2009-06-02 20:54:20 UTC (rev 51765)
@@ -8241,7 +8241,7 @@
 py25-numeric 404
 variants {macosx puredarwin} portdir python/py25-numeric description {fast numerical array language for python} homepage http://numpy.scipy.org/ epoch 0 platforms darwin depends_lib port:python25 name py25-numeric long_description {Numerical Python adds a fast, compact, multidimensional array language facility to Python.} maintainers nomaintainer version 24.2 categories {python devel math} revision 1
 py25-numexpr 1048
-portdir python/py25-numexpr description {Multiple-operator array expression evaluator} homepage http://code.google.com/p/numexpr/ epoch 0 platforms darwin depends_lib {port:python25 port:py25-numpy} name py25-numexpr maintainers {blb openmaintainer} long_description {The numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. Also, numexpr has support for the Intel VML (Vector Math Library) -- integrated in Intel MKL (Math Kernel Library) --, allowing nice speed-ups when computing transcendental functions (like trigonometrical, exponentials...) on top of Intel-compatible platforms. This support also allows to use multiple cores in your comp
 utations.} version 1.2 categories {python math} revision 0
+portdir python/py25-numexpr description {Multiple-operator array expression evaluator} homepage http://code.google.com/p/numexpr/ epoch 0 platforms darwin depends_lib {port:python25 port:py25-numpy} name py25-numexpr maintainers {blb openmaintainer} long_description {The numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. Also, numexpr has support for the Intel VML (Vector Math Library) -- integrated in Intel MKL (Math Kernel Library) --, allowing nice speed-ups when computing transcendental functions (like trigonometrical, exponentials...) on top of Intel-compatible platforms. This support also allows to use multiple cores in your comp
 utations.} version 1.3 categories {python math} revision 0
 py25-numpy 410
 portdir python/py25-numpy description {The core utilities for the scientific library scipy for Python} homepage http://numpy.scipy.org/ epoch 0 platforms darwin depends_lib {port:python25 port:fftw-3 port:py25-hashlib port:py25-nose} name py25-numpy maintainers {ram openmaintainer} long_description {{The core utilities for the scientific library scipy for Python}} version 1.3.0 categories python revision 0
 py25-ode 333
@@ -8623,7 +8623,7 @@
 py26-numeric 412
 variants {macosx puredarwin} portdir python/py26-numeric description {fast numerical array language for python} homepage http://numpy.scipy.org/ epoch 0 platforms darwin depends_lib port:python26 name py26-numeric long_description {Numerical Python adds a fast, compact, multidimensional array language facility to Python.} maintainers {jmr openmaintainer} version 24.2 categories {python devel math} revision 0
 py26-numexpr 1147
-portdir python/py26-numexpr description {Multiple-operator array expression evaluator} homepage http://code.google.com/p/numexpr/ epoch 0 platforms darwin depends_lib {port:python26 port:py26-numpy} name py26-numexpr maintainers {blb openmaintainer} long_description {The numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. Also, numexpr has support for the Intel VML (Vector Math Library) -- integrated in Intel MKL (Math Kernel Library) --, allowing nice speed-ups when computing transcendental functions (like trigonometrical, exponentials...) on top of Intel-compatible platforms. This support also allows to use multiple cores in your comp
 utations. WARNING: numpy 1.2.1, on which py26-numexpr depends, is not yet fully functional under Python 2.6.} version 1.2 categories {python math} revision 0
+portdir python/py26-numexpr description {Multiple-operator array expression evaluator} homepage http://code.google.com/p/numexpr/ epoch 0 platforms darwin depends_lib {port:python26 port:py26-numpy} name py26-numexpr maintainers {blb openmaintainer} long_description {The numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime. Also, numexpr has support for the Intel VML (Vector Math Library) -- integrated in Intel MKL (Math Kernel Library) --, allowing nice speed-ups when computing transcendental functions (like trigonometrical, exponentials...) on top of Intel-compatible platforms. This support also allows to use multiple cores in your comp
 utations. WARNING: numpy 1.2.1, on which py26-numexpr depends, is not yet fully functional under Python 2.6.} version 1.3 categories {python math} revision 0
 py26-numpy 416
 variants universal portdir python/py26-numpy description {The core utilities for the scientific library scipy for Python} homepage http://numpy.scipy.org/ epoch 0 platforms darwin depends_lib {port:python26 port:fftw-3 port:py26-nose} name py26-numpy long_description {{The core utilities for the scientific library scipy for Python}} maintainers {mcalhoun openmaintainer} version 1.3.0 categories python revision 0
 py26-opengl 557
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