Add Binomial operators to EDO

edo/src/edoEstimatorBinomial.h

@@ -0,0 +1,76 @@
+/*
+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) 2013 Thales group
+*/
+/*
+Authors:
+    Johann Dréo <johann.dreo@thalesgroup.com>
+*/
+
+#ifndef _edoEstimatorBinomial_h
+#define _edoEstimatorBinomial_h
+
+#include "edoEstimator.h"
+#include "edoBinomial.h"
+
+/** An estimator for edoBinomial
+ *
+ * @ingroup Estimators
+ * @ingroup Binomial
+ */
+template< class EOT, class D = edoBinomial<EOT> >
+class edoEstimatorBinomial : public edoEstimator< edoBinomial< EOT > >
+{
+    public:
+        /** This generic implementation makes no assumption about the underlying
+         * atom type of the EOT. It can be any type that may be interpreted as
+         * true or false.
+         *
+         * For instance, you can use a vector<int>, and any variable greater
+         * than one will increase the associated probability.
+         *
+         * FIXME: Partial template specializations without the conditional branching may be more efficient.
+         */
+        edoBinomial<EOT> operator()( eoPop<EOT>& pop )
+        {
+            unsigned int popsize = pop.size();
+            assert(popsize > 0);
+
+            unsigned int dimsize = pop[0].size();
+            assert(dimsize > 0);
+
+            edoBinomial<EOT> probas(dimsize, 0.0);
+
+            for (unsigned int i = 0; i < popsize; ++i) {
+                for (unsigned int d = 0; d < dimsize; ++d) {
+                    // if this variable is true (whatever that means, x=1, x=true, etc.)
+                    // if( pop[i][d] ) {
+                    //     probas[d] += 1/popsize; // we hope the compiler optimization pre-computes 1/p
+                    // }
+                    probas[d] += static_cast<double>(pop[i][d]) / popsize;
+                }
+            }
+
+            return probas;
+        }
+};
+
+#endif // !_edoEstimatorBinomial_h
+