Log of /trunk/hist/hist/src/TPrincipal.cxx
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44507 -
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Modified
Mon Jun 4 12:30:41 2012 UTC (2 years, 7 months ago) by
axel
File length: 53639 byte(s)
Diff to
previous 44225
Remove
using namespace std;
from Riostream.h, which has huge consequences for all of ROOT.
Riostream.h is now a simple wrapper for fstream, iostream, iomanip for backward compatibility; Riosfwd.h simply wraps iosfwd.
Because of templates and their inline functions, Riostream.h needed to be included in headers, too (e.g. TParameter.h), which violated the assumption that Riostream.h is not exposing its using namespace std to headers.
ROOT now requires R__ANSISTREAM, R__SSTREAM, which does not change the set of supported compilers.
Without "using namespace std", several identifiers are now prefixed by std::; e.g. roofit/* source files now have a using namespace std to keep their coding style.
TFile::MakeProject() now generates "using namespace std" to convert the CINT-style class names into C++ ones.
Revision
15134 -
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Modified
Tue May 23 04:47:42 2006 UTC (8 years, 8 months ago) by
brun
Original Path:
trunk/hist/src/TPrincipal.cxx
File length: 52536 byte(s)
Diff to
previous 15072
From Federico Carminati:
"I have implemented all copy and equal operators needed to silence all
warnings in AliRoot, as requested. I have implemented shallow copies as
would do the default operators synthetized by the compiler.
Most operators are protected. If users complain, you just have to move
them into the public area, but class derivation is of course supported.
It has been a terrible job, I have modified 278 files, but the changes
are backward compabile, and this goes a long way to permitting user to
use the effc++ flag with root headers."
Revision
8013 -
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Modified
Sun Jan 25 20:33:32 2004 UTC (11 years ago) by
brun
Original Path:
trunk/hist/src/TPrincipal.cxx
File length: 49338 byte(s)
Diff to
previous 7204
New Linear Algebra package from Eddy Offermann.
This new package reimplements the previous classes TMatrix and TMatrixD.
The new classes should be back compatible with the previous version except
the function GetElements.
New classes have been introduced for symmetric matrices,
lazy matrices.
New algorithms (LU, SVD) have been introduced.
A new test suite test/stressLinear.cxx is introduced.
A complete description of this package will be posted in the coming days.
The classes are well documented in the implementation headers.
Revision
5717 -
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Modified
Mon Dec 2 18:50:12 2002 UTC (12 years, 1 month ago) by
rdm
Original Path:
trunk/hist/src/TPrincipal.cxx
File length: 49239 byte(s)
Diff to
previous 4405
mega patch to remove almost all compiler warnings on MacOS X where the
compiler is by default in pedantic mode (LHCb also like to use this option).
The following issues have been fixed:
- removal of unused arguments
- comparison between signed and unsigned integers
- not calling of base class copy ctor in copy ctor's
To be done, the TGeo classes where we get still many hundred warnings of
the above nature. List forwarded to Andrei.
Revision
3578 -
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Modified
Fri Jan 4 08:07:38 2002 UTC (13 years ago) by
brun
Original Path:
trunk/hist/src/TPrincipal.cxx
File length: 49230 byte(s)
Diff to
previous 3326
Implement the following improvements by Eddy A.J.M. Offermann (Renaissance Technologies Corp.)
Somebody at Renaissance asked me how to get eigenvectors/values with ROOT.
I knew of the existance of the proper routines in TPrincipal by Christian.
However, no convenient way existed to apply them to an existing matrix.
So I did the following:
1) Took the routines to Tridiagonalize, Calculate eigenvectors/values
and Sort and inserted them into TMatrix(D)
2) Have TPrincipal use the TMatrixD method EigenVector
3) Have the three routines mentioned above directly access the TMatrix/
TVector data member fElements, so no having the go through the
"()" operator (remember that TMatrix stores Fortran-wise)
4) Have the routine index starting at 0 instead of 1 (Still puzzles me
how Cambridge-Press let them get away with it in Num. Recipes)
5) Change TPrincipal so that it also starts indexing at 0, changed also
the tex/html comments.
6) Changed TVector(D).h so that TMatrix is also a friend (TVector was
already a friend of TMatrix)
7) Checked that principal.C in tutorials still does its thing.
What is still lacking:
1) Support for non-symmetrical matrices.
I might tackle this by importing Single-Value-Decomposition routines.
Although maybe not the most efficient solution, it does have the
advantage of also making those routines available.
2) Support for returning/calculating only those eigenvectors
that belong to the largest eigenvalues.
Revision
3326 -
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Modified
Thu Nov 29 08:27:39 2001 UTC (13 years, 1 month ago) by
brun
Original Path:
trunk/hist/src/TPrincipal.cxx
File length: 59459 byte(s)
Diff to
previous 3034
Christion Holm Christensen has made the following improvements:
I've just realised that I've done something extreemly stupid in
TPrincipal::MakeHistograms which can make one waste enourmous amounts
of space and time. The problem was, that the method looped over the
user data wether or not you actually wanted to plot it or not, thereby
wasting a lot of time. Also, I allocated arrays via new in each
iteration, which is ofcourse a waste of time, so I moved that outside
the loop and added a zeroing loop instead.
Further, I added the option 'd' to the CTOR, so that one may opt to
_not_ store the input data. This reguired a new data member, and
hence a version bumb. The default is to store the input data. I
think this is a useful option for some, since the data arrays can
become quite large.
Thirdly, I modified the histogram names to be 0 padded upto 3 digits.
That is, the format is "%03d" rather than "%d", since that allows for
better overview in the browser.
Revision
1205 -
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Modified
Wed Dec 13 15:13:57 2000 UTC (14 years, 1 month ago) by
brun
Original Path:
trunk/hist/src/TPrincipal.cxx
File length: 59353 byte(s)
Diff to
previous 700
W A R N I N G !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
==================================================================
A very long list of changes in this pre-release of version 3.00.
We have modified the signature of many functions (in particular TObject)
to introduce more constness in the system.
You must change your code if your class derives from TObject and uses
one of the modified functions such as ls, Print, Compare, Hash, etc.
The modified functions in TObject have the following signature:
virtual TObject *Clone() const;
virtual Int_t Compare(const TObject *obj) const;
virtual void Delete(Option_t *option=""); // *MENU*
virtual void DrawClass() const; // *MENU*
virtual void DrawClone(Option_t *option="") const; // *MENU*
virtual void Dump() const; // *MENU*
virtual TObject *FindObject(const TObject *obj) const;
virtual char *GetObjectInfo(Int_t px, Int_t py) const;
virtual ULong_t Hash() const;
virtual void Inspect() const; // *MENU*
virtual Bool_t IsEqual(const TObject *obj) const;
virtual void ls(Option_t *option="") const;
virtual void Print(Option_t *option="") const;
A similar operation has been done with classes such as TH1, TVirtualPad,
TTree, etc.
Revision
469 -
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Modified
Tue Aug 15 09:22:33 2000 UTC (14 years, 5 months ago) by
brun
Original Path:
trunk/hist/src/TPrincipal.cxx
File length: 58905 byte(s)
Diff to
previous 468
To avoid a fatal error in MakeRealCode on SGI with gcc2.95, replace:
Char_t* prefix = (isMethod ? Form("%s::", classname) : "");
Char_t* cv_qual = (isMethod ? "" : "static ");
by
const Char_t* prefix = (isMethod ? Form("%s::", classname) : "");
const Char_t* cv_qual = (isMethod ? "" : "static ");
Revision
459 -
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Added
Tue Aug 15 07:48:50 2000 UTC (14 years, 5 months ago) by
brun
Original Path:
trunk/hist/src/TPrincipal.cxx
File length: 59088 byte(s)
Introduction of a new class TPrincipal implemented by Christian Holm Cristensen.
The Principal Components Analysis class
=======================================
In many applications of various fields of research, the treatment of
large amounts of data requires powerful techniques capable of rapid
data reduction and analysis. Usually, the quantities most
conveniently measured by the experimentalist, are not necessarily the
most significant for classification and analysis of the data. It is
then useful to have a way of selecting an optimal set of variables
necessary for the recognition process and reducing the dimensionality
of the problem, resulting in an easier classification procedure.
TPrincipal is the implementation of one such method of
feature selection, namely the principal components analysis.
This multidimensional technique is well known in the field of pattern
recognition and and its use in Particle Physics has been documented
elsewhere (cf. H. Wind, <I>Function Parameterization</I>, CERN
72-21).
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