rename everything from 'do' to 'edo'

src/edoSamplerNormalMono.h

@@ -0,0 +1,91 @@
+/*
+The Evolving Distribution Objects framework (EDO) is a template-based, 
+ANSI-C++ evolutionary computation library which helps you to write your 
+own estimation of distribution algorithms.
+
+This library is free software; you can redistribute it and/or
+modify it under the terms of the GNU Lesser General Public
+License as published by the Free Software Foundation; either
+version 2.1 of the License, or (at your option) any later version.
+
+This library is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+Lesser General Public License for more details.
+
+You should have received a copy of the GNU Lesser General Public
+License along with this library; if not, write to the Free Software
+Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+Copyright (C) 2010 Thales group
+*/
+/*
+Authors:
+    Johann Dréo <johann.dreo@thalesgroup.com>
+    Caner Candan <caner.candan@thalesgroup.com>
+*/
+
+#ifndef _edoSamplerNormalMono_h
+#define _edoSamplerNormalMono_h
+
+#include <utils/eoRNG.h>
+
+#include "edoSampler.h"
+#include "edoNormalMono.h"
+#include "edoBounder.h"
+
+/**
+ * edoSamplerNormalMono
+ * This class uses the NormalMono distribution parameters (bounds) to return
+ * a random position used for population sampling.
+ */
+template < typename EOT >
+class edoSamplerNormalMono : public edoSampler< edoNormalMono< EOT > >
+{
+public:
+    typedef typename EOT::AtomType AtomType;
+
+    edoSamplerNormalMono( edoBounder< EOT > & bounder )
+	: edoSampler< edoNormalMono< EOT > >( bounder )
+    {}
+
+    EOT sample( edoNormalMono< EOT >& distrib )
+    {
+	unsigned int size = distrib.size();
+	assert(size > 0);
+
+
+	//-------------------------------------------------------------
+	// Point we want to sample to get higher a set of points
+	// (coordinates in n dimension)
+	// x = {x1, x2, ..., xn}
+	//-------------------------------------------------------------
+
+	EOT solution;
+
+	//-------------------------------------------------------------
+
+
+	//-------------------------------------------------------------
+	// Sampling all dimensions
+	//-------------------------------------------------------------
+
+	for (unsigned int i = 0; i < size; ++i)
+	    {
+		AtomType mean = distrib.mean()[i];
+		AtomType variance = distrib.variance()[i];
+	        AtomType random = rng.normal(mean, variance);
+
+		assert(variance >= 0);
+
+		solution.push_back(random);
+	    }
+
+	//-------------------------------------------------------------
+
+
+	return solution;
+    }
+};
+
+#endif // !_edoSamplerNormalMono_h