researchers and developers, written in C++.
Its purpose is to simplify the visualization needs faced by a roboticist
daily - using visualization as a debugging aid or making fancy slides for
a presentation, for example.
Chris Petrik (chris@officialunix.com)
WWW: http://www.peekabot.org
PR: 135892
Submitted by: Chris Petrik <c.petrik.sosa@gmail.com>
modular xorg.
- supply corresponding USE_XORG for all imake-using ports that need it
- USE_IMAKE no longer implies USE_XLIB in absence of USE_XORG
- retire USE_X_PREFIX which is not really used anywhere after the
above change
- a few minor nits like whitespace and SF macro
Tested by: 2 tinderbox runs by pav
Approved by: portmgr (pav)
- Fix WITH_MPICH
- Use LOCALBASE for reference to bits installed by others
- Pass maintainership to the submitter
- Pet portlint(1): IGNORE
PR: ports/133242
Submitted by: Florian Smeets <flo at kasimir.com>
Approved by: Stephen Montgomery-Smith <stephen at math.missouri.edu> (maintainer)
describe macromolecules, a macromolecule is just a molecule that
consists of several "domains". For example, a protein consists
of aminoacid residues, or a nucleic acid consists of bases. Therefore
Chemistry::MacroMol is derived from Chemistry::Mol, with additional
methods to handle the domains.
WWW: http://search.cpan.org/dist/Chemistry-MacroMol/
PR: ports/134609
Submitted by: Wen Heping <wenheping at gmail.com>
is commonly used to describe proteins, particularly those stored in the
Protein Data Bank.
WWW: http://search.cpan.org/dist/Chemistry-File-PDB/
PR: ports/134612
Submitted by: Wen Heping <wenheping at gmail.com>
describe molecules. It consists of several modules: Chemistry::Mol,
Chemistry::Atom, Chemistry::Bond, and Chemistry::File.
WWW: http://search.cpan.org/dist/Chemistry-Mol/
PR: ports/134462
Submitted by: Wen Heping <wenheping at gmail.com>
predictive modeling. It makes extensive use of numpy (http://scipy.org)
to provide fast N-dimensional array manipulation and easy integration of
C code. mlpy provides high level procedures that support, with few lines
of code, the design of rich Data Analysis Protocols (DAPs) for
preprocessing, clustering, predictive classification and feature
selection. Methods are available for feature weighting and ranking, data
resampling, error evaluation and experiment landscaping.The package
includes tools to measure stability in sets of ranked feature lists.
WWW: http://mlpy.fbk.eu/
PR: ports/133932
Submitted by: Wen Heping <wenheping at gmail.com>
