Remove prefix category from each example filename.

The examples that import other examples are also modified
to fit the new module name.

--HG--
branch : dev
rename : examples/coev/coev_coop_adapt.py => examples/coev/coop_adapt.py
rename : examples/coev/coev_coop_base.py => examples/coev/coop_base.py
rename : examples/coev/coev_coop_evol.py => examples/coev/coop_evol.py
rename : examples/coev/coev_coop_gen.py => examples/coev/coop_gen.py
rename : examples/coev/coev_coop_niche.py => examples/coev/coop_niche.py
rename : examples/coev/coev_hillis.py => examples/coev/hillis.py
rename : examples/coev/coev_symbreg.py => examples/coev/symbreg.py
rename : examples/de/de_basic.py => examples/de/basic.py
rename : examples/de/de_dynamic.py => examples/de/dynamic.py
rename : examples/de/de_sphere.py => examples/de/sphere.py
rename : examples/eda/eda_fctmin.py => examples/eda/fctmin.py
rename : examples/eda/eda_pbil.py => examples/eda/pbil.py
rename : examples/es/cmaes1pl_minfct.py => examples/es/cma_1+l_minfct.py
rename : examples/es/cmaes_bipop.py => examples/es/cma_bipop.py
rename : examples/es/cmaes_minfct.py => examples/es/cma_minfct.py
rename : examples/es/cmaes_plotting.py => examples/es/cma_plotting.py
rename : examples/es/es_fctmin.py => examples/es/fctmin.py
rename : examples/es/es_onefifth.py => examples/es/onefifth.py
rename : examples/ga/ga_knn.py => examples/ga/evoknn.py
rename : examples/ga/ga_knn_jmlr.py => examples/ga/evoknn_jmlr.py
rename : examples/ga/ga_evosn.py => examples/ga/evosn.py
rename : examples/ga/ga_knapsack.py => examples/ga/knapsack.py
rename : examples/ga/ga_kursawefct.py => examples/ga/kursawefct.py
rename : examples/ga/ga_nqueens.py => examples/ga/nqueens.py
rename : examples/ga/ga_nsga2.py => examples/ga/nsga2.py
rename : examples/ga/ga_onemax.py => examples/ga/onemax.py
rename : examples/ga/ga_onemax_island.py => examples/ga/onemax_island.py
rename : examples/ga/ga_onemax_mp.py => examples/ga/onemax_mp.py
rename : examples/ga/ga_onemax_multidemic.py => examples/ga/onemax_multidemic.py
rename : examples/ga/ga_onemax_numpy.py => examples/ga/onemax_numpy.py
rename : examples/ga/ga_onemax_short.py => examples/ga/onemax_short.py
rename : examples/ga/ga_tsp.py => examples/ga/tsp.py
rename : examples/gp/gp_adf_symbreg.py => examples/gp/adf_symbreg.py
rename : examples/gp/gp_ant.py => examples/gp/ant.py
rename : examples/gp/gp_multiplexer.py => examples/gp/multiplexer.py
rename : examples/gp/gp_parity.py => examples/gp/parity.py
rename : examples/gp/gp_spambase.py => examples/gp/spambase.py
rename : examples/gp/gp_symbreg.py => examples/gp/symbreg.py
rename : examples/gp/gp_symbreg_numpy.py => examples/gp/symbreg_numpy.py
rename : examples/pso/pso_basic.py => examples/pso/basic.py
rename : examples/pso/pso_multiswarm.py => examples/pso/multiswarm.py
rename : examples/pso/pso_speciation.py => examples/pso/speciation.py

examples/coev/coev_coop_adapt.py → examples/coev/coop_adapt.py

@@ -29,10 +29,10 @@
 from deap import algorithms
 from deap import tools
 
-import coev_coop_base
+import coop_base
 
-IND_SIZE = coev_coop_base.IND_SIZE
-SPECIES_SIZE = coev_coop_base.SPECIES_SIZE
+IND_SIZE = coop_base.IND_SIZE
+SPECIES_SIZE = coop_base.SPECIES_SIZE
 TARGET_SIZE = 30
 NUM_SPECIES = 1
 
@@ -41,9 +41,9 @@
              "1##1###1###11111##1##1000#0##0###0#0000##000000##0#00#0#00######",
              "0##0###0###00000##0##0000#0##0###0#0000##001111##1#11#1#11######")
 
-toolbox = coev_coop_base.toolbox
+toolbox = coop_base.toolbox
 if plt:
-    toolbox.register("evaluate_nonoise", coev_coop_base.matchSetStrengthNoNoise)
+    toolbox.register("evaluate_nonoise", coop_base.matchSetStrengthNoNoise)
 
 def main(extended=True, verbose=True):
     target_set = []

examples/coev/coev_coop_evol.py → examples/coev/coop_evol.py

@@ -31,10 +31,10 @@
 from deap import algorithms
 from deap import tools
 
-import coev_coop_base
+import coop_base
 
-IND_SIZE = coev_coop_base.IND_SIZE
-SPECIES_SIZE = coev_coop_base.SPECIES_SIZE
+IND_SIZE = coop_base.IND_SIZE
+SPECIES_SIZE = coop_base.SPECIES_SIZE
 NUM_SPECIES = 1
 TARGET_SIZE = 30
 IMPROVMENT_TRESHOLD = 0.5
@@ -47,8 +47,8 @@
              "1##1###1###11111##1##1000#0##0###0#0000##000000##0#00#0#00######",
              "0##0###0###00000##0##0000#0##0###0#0000##001111##1#11#1#11######")
 
-toolbox = coev_coop_base.toolbox
-toolbox.register("evaluateContribution", coev_coop_base.matchSetContribution)
+toolbox = coop_base.toolbox
+toolbox.register("evaluateContribution", coop_base.matchSetContribution)
 
 def main(extended=True, verbose=True):
     target_set = []

examples/coev/coev_coop_gen.py → examples/coev/coop_gen.py

@@ -30,10 +30,10 @@
 from deap import algorithms
 from deap import tools
 
-import coev_coop_base
+import coop_base
 
-IND_SIZE = coev_coop_base.IND_SIZE
-SPECIES_SIZE = coev_coop_base.SPECIES_SIZE
+IND_SIZE = coop_base.IND_SIZE
+SPECIES_SIZE = coop_base.SPECIES_SIZE
 NUM_SPECIES = 4
 TARGET_SIZE = 30
 
@@ -42,10 +42,10 @@
              "1##1###1###11111##1##1000#0##0###0#0000##000000##0#00#0#00######",
              "0##0###0###00000##0##0000#0##0###0#0000##001111##1#11#1#11######")
 
-toolbox = coev_coop_base.toolbox
+toolbox = coop_base.toolbox
 if plt:
     # This will allow to plot the match strength of every target schemata
-    toolbox.register("evaluate_nonoise", coev_coop_base.matchSetStrengthNoNoise)
+    toolbox.register("evaluate_nonoise", coop_base.matchSetStrengthNoNoise)
 
 def main(extended=True, verbose=True):
     target_set = []

examples/coev/coev_coop_niche.py → examples/coev/coop_niche.py

@@ -27,10 +27,10 @@
 from deap import algorithms
 from deap import tools
 
-import coev_coop_base
+import coop_base
 
-IND_SIZE = coev_coop_base.IND_SIZE
-SPECIES_SIZE = coev_coop_base.SPECIES_SIZE
+IND_SIZE = coop_base.IND_SIZE
+SPECIES_SIZE = coop_base.SPECIES_SIZE
 TARGET_SIZE = 200
 TARGET_TYPE = 2
 
@@ -41,7 +41,7 @@ def nicheSchematas(type, size):
     rept = int(size/type)
     return ["#" * (i*rept) + "1" * rept + "#" * ((type-i-1)*rept) for i in range(type)]
 
-toolbox = coev_coop_base.toolbox
+toolbox = coop_base.toolbox
 
 def main(extended=True, verbose=True):
     target_set = []

examples/coev/coev_symbreg.py → examples/coev/symbreg.py

@@ -20,30 +20,17 @@
 
 from deap import base
 from deap import creator
-from deap import gp
 from deap import tools
 
-sys.path.append("../gp")
+from deap.gp import stringify
 
-# gp_symbreg already defines some useful structures
-import gp_symbreg
+# GP example "symbreg.py" already defines some useful structures
+sys.path.append("..")
+import gp.symbreg as symbreg
 
 creator.create("FitnessMax", base.Fitness, weights=(1.0,))
 creator.create("IndGA", list, fitness=creator.FitnessMax)
 
-def refFunc(x):
-    return x**4 + x**3 + x**2 + x
-
-def evalSymbReg(expr, data):
-    # Transform the tree expression in a callable function
-    func = tools_gp.lambdify(expr=expr)
-    # Evaluate the sum of squared difference between the expression
-    # and the real function : x**4 + x**3 + x**2 + x
-    values = data
-    diff_func = lambda x: (func(x)-refFunc(x))**2
-    diff = sum(map(diff_func, values))
-    return diff,
-
 toolbox_ga = base.Toolbox()
 
 toolbox_ga.register("float", random.uniform, -1, 1)
@@ -54,47 +41,40 @@ def evalSymbReg(expr, data):
 toolbox_ga.register("mate", tools.cxTwoPoints)
 toolbox_ga.register("mutate", tools.mutGaussian, mu=0, sigma=0.01, indpb=0.05)
 
-tools_gp = gp_symbreg.toolbox
+toolbox_gp = symbreg.toolbox
 
 def main():
     pop_ga = toolbox_ga.population(n=200)
-    pop_gp = tools_gp.population(n=200)
-
-    stats_ga = tools.Statistics(lambda ind: ind.fitness.values)
-    stats_ga.register("avg", numpy.mean)
-    stats_ga.register("std", numpy.std)
-    stats_ga.register("min", numpy.min)
-    stats_ga.register("max", numpy.max)
+    pop_gp = toolbox_gp.population(n=200)
 
-    stats_gp = tools.Statistics(lambda ind: ind.fitness.values)
-    stats_gp.register("avg", numpy.mean)
-    stats_gp.register("std", numpy.std)
-    stats_gp.register("min", numpy.min)
-    stats_gp.register("max", numpy.max)
+    stats = tools.Statistics(lambda ind: ind.fitness.values)
+    stats.register("avg", numpy.mean)
+    stats.register("std", numpy.std)
+    stats.register("min", numpy.min)
+    stats.register("max", numpy.max)
 
     best_ga = tools.selRandom(pop_ga, 1)[0]
     best_gp = tools.selRandom(pop_gp, 1)[0]
 
     for ind in pop_gp:
-        ind.fitness.values = evalSymbReg(ind, best_ga)  
+        ind.fitness.values = toolbox_gp.evaluate(ind, points=best_ga)  
 
     for ind in pop_ga:
-        ind.fitness.values = evalSymbReg(best_gp, ind)
+        ind.fitness.values = toolbox_gp.evaluate(best_gp, points=ind)
 
-    stats_ga.record(pop_ga, gen=0, type='ga', evals=len(pop_ga))
-    stats_gp.record(pop_gp, gen=0, type='gp', evals=len(pop_gp))
-    print(stats_ga.stream)
-    print(stats_gp.stream)
+    stats.record(pop_ga, gen=0, type='ga', evals=len(pop_ga))
+    stats.record(pop_gp, gen=0, type='gp', evals=len(pop_gp))
+    print(stats.stream)
 
     CXPB, MUTPB, NGEN = 0.5, 0.2, 50
 
     # Begin the evolution
     for g in range(1, NGEN):
         # Select and clone the offspring
         off_ga = toolbox_ga.select(pop_ga, len(pop_ga))
-        off_gp = tools_gp.select(pop_gp, len(pop_gp))
+        off_gp = toolbox_gp.select(pop_gp, len(pop_gp))
         off_ga = [toolbox_ga.clone(ind) for ind in off_ga]        
-        off_gp = [tools_gp.clone(ind) for ind in off_gp]
+        off_gp = [toolbox_gp.clone(ind) for ind in off_gp]
 
 
         # Apply crossover and mutation
@@ -106,7 +86,7 @@ def main():
 
         for ind1, ind2 in zip(off_gp[::2], off_gp[1::2]):
             if random.random() < CXPB:
-                tools_gp.mate(ind1, ind2)
+                toolbox_gp.mate(ind1, ind2)
                 del ind1.fitness.values
                 del ind2.fitness.values
 
@@ -117,33 +97,32 @@ def main():
 
         for ind in off_gp:
             if random.random() < MUTPB:
-                tools_gp.mutate(ind)
+                toolbox_gp.mutate(ind)
                 del ind.fitness.values
 
         # Evaluate the individuals with an invalid fitness
         for ind in off_ga:
-            ind.fitness.values = evalSymbReg(best_gp, ind)
+            ind.fitness.values = toolbox_gp.evaluate(best_gp, points=ind)
 
         for ind in off_gp:
-            ind.fitness.values = evalSymbReg(ind, best_ga)
+            ind.fitness.values = toolbox_gp.evaluate(ind, points=best_ga)
 
         # Replace the old population by the offspring
         pop_ga = off_ga
         pop_gp = off_gp
 
-        stats_ga.record(pop_ga, gen=g, type='ga', evals=len(pop_ga))
-        stats_gp.record(pop_gp, gen=g, type='gp', evals=len(pop_gp))
-        print(stats_ga.stream)
-        print(stats_gp.stream)
+        stats.record(pop_ga, gen=g, type='ga', evals=len(pop_ga))
+        stats.record(pop_gp, gen=g, type='gp', evals=len(pop_gp))
+        print(stats.stream)
 
         best_ga = tools.selBest(pop_ga, 1)[0]
-        best_gp = tools.selBest(pop_gp, 1)[0]    
+        best_gp = tools.selBest(pop_gp, 1)[0]
 
 
     print("Best individual GA is %s, %s" % (best_ga, best_ga.fitness.values))
-    print("Best individual GP is %s, %s" % (gp.stringify(best_gp), best_gp.fitness.values))
+    print("Best individual GP is %s, %s" % (stringify(best_gp), best_gp.fitness.values))
 
-    return pop_ga, pop_gp, stats_ga, stats_gp, best_ga, best_gp
+    return pop_ga, pop_gp, best_ga, best_gp, stats
 
 if __name__ == "__main__":
     main()

examples/gp/__init__.py

@@ -0,0 +1,14 @@
+#    This file is part of DEAP.
+#
+#    DEAP 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 3 of
+#    the License, or (at your option) any later version.
+#
+#    DEAP 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 DEAP. If not, see <http://www.gnu.org/licenses/>.

examples/gp/gp_symbreg.py → examples/gp/symbreg.py

@@ -52,17 +52,16 @@ def safeDiv(left, right):
 toolbox.register("population", tools.initRepeat, list, toolbox.individual)
 toolbox.register("lambdify", gp.lambdify, pset=pset)
 
-def evalSymbReg(individual):
+def evalSymbReg(individual, points):
     # Transform the tree expression in a callable function
     func = toolbox.lambdify(expr=individual)
     # Evaluate the sum of squared difference between the expression
     # and the real function : x**4 + x**3 + x**2 + x
-    values = (x/10. for x in range(-10,10))
     diff_func = lambda x: (func(x)-(x**4 + x**3 + x**2 + x))**2
-    diff = sum(map(diff_func, values))
+    diff = sum(map(diff_func, points))
     return diff,
 
-toolbox.register("evaluate", evalSymbReg)
+toolbox.register("evaluate", evalSymbReg, points=[x/10. for x in range(-10,10)])
 toolbox.register("select", tools.selTournament, tournsize=3)
 toolbox.register("mate", gp.cxOnePoint)
 toolbox.register("expr_mut", gp.genFull, min_=0, max_=2)