490e837f7a
.../
... + -- EO
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+-- src ----- + -- EDO
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+-- test + -- MO
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+-- tutorial + -- MOEO
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+-- doc + -- SMP
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... + -- EOMPI
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+ -- EOSERIAL
Question for current maintainers: ./README: new release?
Also:
* Moving out eompi & eoserial modules (issue #2).
* Correction of the errors when executing "make doc" command.
* Adding a solution for the conflicting headers problem (see the two CMake Cache
Values: PROJECT_TAG & PROJECT_HRS_INSTALL_SUBPATH) (issue #1)
* Header inclusions:
** src: changing absolute paths into relative paths ('#include <...>' -> '#include "..."')
** test, tutorial: changing relative paths into absolute paths ('#include "..."' -> '#include <...>')
* Moving out some scripts from EDO -> to the root
* Add a new script for compilation and installation (see build_gcc_linux_install)
* Compilation with uBLAS library or EDO module: now ok
* Minor modifications on README & INSTALL files
* Comment eompi failed tests with no end
*** TODO: CPack (debian (DEB) & RedHat (RPM) packages) (issues #6 & #7) ***
61 lines
1.5 KiB
C++
Executable file
61 lines
1.5 KiB
C++
Executable file
/*
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* Copyright (C) 2005 Maarten Keijzer
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of version 2 of the GNU General Public License as
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* published by the Free Software Foundation.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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*/
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#ifndef ERROR_MEASURE_H
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#define ERROR_MEASURE_H
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#include "Scaling.h"
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class ErrorMeasureImpl;
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class Sym;
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class Dataset;
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class ErrorMeasure {
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ErrorMeasureImpl* pimpl;
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public :
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enum measure {
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absolute,
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mean_squared,
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mean_squared_scaled,
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};
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struct result {
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double error;
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Scaling scaling;
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result();
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bool valid() const;
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};
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ErrorMeasure(const Dataset& data, double train_perc, measure meas = mean_squared);
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~ErrorMeasure();
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ErrorMeasure(const ErrorMeasure& that);
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ErrorMeasure& operator=(const ErrorMeasure& that);
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result calc_error(Sym sym);
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std::vector<result> calc_error(const std::vector<Sym>& sym);
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double worst_performance() const;
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};
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#endif
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