feat: add separate eoRankingCached.h file

eo/src/eoRankingCached.h

@@ -0,0 +1,139 @@
+/** -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
+
+   -----------------------------------------------------------------------------
+   eoRankingCached.h
+   (c) Maarten Keijzer, Marc Schoenauer, 2001
+
+   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 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., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
+
+    Contact: todos@geneura.ugr.es, http://geneura.ugr.es
+             Marc.Schoenauer@polytechnique.fr
+             mkeijzer@dhi.dk
+ */
+//-----------------------------------------------------------------------------
+
+#ifndef eoRankingCached_h
+#define eoRankingCached_h
+
+#include "eoPerf2Worth.h"
+
+/**
+ * @class eoRankingCached
+ * @brief Cached version of eoRanking that stores precomputed values for better performance
+ *
+ * This class implements the same ranking algorithm as eoRanking but adds a caching layer
+ * that stores frequently used values when the population size remains constant between
+ * calls. This optimization is particularly useful in steady-state evolution where the
+ * population size typically doesn't change between selection operations.
+ *
+ * The caching mechanism stores:
+ * - Population size related values (pSize, pSizeMinusOne)
+ * - Precomputed coefficients (alpha, beta, gamma)
+ *
+ * @warning This optimization should only be used when the population size remains constant
+ * between calls to the operator. For dynamic population sizes, use the standard eoRanking.
+ *
+ * @ingroup Selectors
+ */
+template <class EOT>
+class eoRankingCached : public eoPerf2Worth<EOT>
+{
+public:
+    using eoPerf2Worth<EOT>::value;
+
+    /* Ctor:
+     @param _p selective pressure (in (1,2]
+     @param _e exponent (1 == linear)
+    */
+    eoRankingCached(double _p = 2.0, double _e = 1.0) : pressure(_p), exponent(_e), cached_pSize(0)
+    {
+        assert(1 < pressure and exponent <= 2);
+    }
+
+    /*
+     Computes the ranked fitness with caching optimization
+     Fitnesses range in [m,M] where:
+     - m = 2-pressure/popSize
+     - M = pressure/popSize
+     The progression between m and M depends on the exponent (linear when exponent=1)
+
+     @param _pop The population to rank
+     */
+    virtual void operator()(const eoPop<EOT> &_pop)
+    {
+        unsigned pSize = _pop.size();
+
+        if (pSize <= 1)
+            throw eoPopSizeException(pSize, "cannot do ranking with population of size <= 1");
+
+        // value() refers to the std::vector of worthes (we're in an eoParamvalue)
+        value().resize(pSize);
+
+        // Cache population-size dependent values only when population size changes
+        if (pSize != cached_pSize)
+        {
+            cached_pSize = pSize;
+            cached_pSizeMinusOne = pSize - 1;
+            cached_beta = (2 - pressure) / pSize;
+            cached_gamma = (2 * pressure - 2) / pSize;
+            cached_alpha = (2 * pressure - 2) / (pSize * cached_pSizeMinusOne);
+        }
+
+        std::vector<const EOT *> rank;
+        _pop.sort(rank);
+
+        // map of indices for the population
+        std::unordered_map<const EOT *, unsigned> indexMap;
+        for (unsigned i = 0; i < pSize; ++i)
+        {
+            indexMap[&_pop[i]] = i;
+        }
+
+        if (exponent == 1.0) // no need for exponetial then (linear case)
+        {
+            for (unsigned i = 0; i < pSize; i++)
+            {
+                const EOT *indiv = rank[i];
+                int which = indexMap[indiv];
+                value()[which] = cached_alpha * (pSize - i) + cached_beta;
+            }
+        }
+        else // non-linear case (exponent != 1)
+        {
+            for (unsigned i = 0; i < pSize; i++)
+            {
+                const EOT *indiv = rank[i];
+                int which = indexMap[indiv];
+                // value in in [0,1]
+                double tmp = ((double)(pSize - i)) / pSize;
+                // to the exponent, and back to [m,M]
+                value()[which] = cached_gamma * pow(tmp, exponent) + cached_beta;
+            }
+        }
+    }
+
+private:
+    double pressure; // selective pressure (1 < pressure <= 2)
+    double exponent; // exponent (1 = linear)
+
+    // Cached values (recomputed only when population size changes)
+    unsigned cached_pSize;         // last seen population size
+    unsigned cached_pSizeMinusOne; // pSize - 1
+    double cached_alpha;           // linear scaling coefficient
+    double cached_beta;            // base value coefficient
+    double cached_gamma;           // non-linear scaling coefficient
+};
+
+#endif