update visualization

Author: ngocbh

.gitignore

@@ -3,6 +3,8 @@ __pycache__/
 *.py[cod]
 *$py.class
 
+# vim
+.vim/*
 # vscode
 .vscode/*
 

.vim/coc-settings.json

@@ -7,6 +7,7 @@
 from geneticpython.core.individual import BinaryIndividual
 from geneticpython import Population, GAEngine
 from geneticpython.core.operators import RouletteWheelSelection, UniformCrossover, FlipBitMutation, RouletteWheelReplacement
+from geneticpython.utils.visualization import plot_single_objective_history
 
 Item = namedtuple("Item", ['index', 'value', 'weight'])
 
@@ -47,9 +48,7 @@ def read_input():
                   selection_size=100,
                   crossover=crossover,
                   mutation=mutation,
-                  replacement=replacement,
-                  max_iter=1000)
-
+                  replacement=replacement)
 
 @engine.maximize_objective
 def fitness(indv):
@@ -69,8 +68,8 @@ def fitness(indv):
 
 
 # engine.create_seed(seed)
-history = engine.run()
-print(history.history)
+history = engine.run(generations=1000)
 ans = engine.get_best_indv()
 print(ans)
 # print(engine.population)
+plot_single_objective_history({'geneticpython': history})

examples/knapsack/knapsack.py

@@ -7,6 +7,13 @@
 # Created by ngocjr7 on [14-06-2020 21:22:52]
 """
 from __future__ import absolute_import
+
+import sys
+import os
+
+WORKING_DIR = os.path.dirname(os.path.abspath(__file__))
+sys.path.append(os.path.join(WORKING_DIR, '../../../geneticpython'))
+
 import time
 import json
 import random
@@ -21,16 +28,11 @@
 from utils import WusnInput
 from parameters import *
 
-from geneticpython.operators import TournamentSelection, SBXCrossover, PolynomialMutation
+from geneticpython.core.operators import TournamentSelection, SBXCrossover, PolynomialMutation
 from geneticpython import Population
-from geneticpython.individual import NetworkRandomKeys
+from geneticpython.core.individual import NetworkRandomKeys
 from geneticpython.engines import NSGAIIEngine
-
-import sys
-import os
-
-WORKING_DIR = os.path.dirname(os.path.abspath(__file__))
-sys.path.append(os.path.join(WORKING_DIR, '../../../geneticpython'))
+from geneticpython.utils.visualization import save_history_as_gif
 
 
 class MultiHopIndividual(NetworkRandomKeys):
@@ -78,7 +80,7 @@ def init_bias_genes(length, n_relays_edges, rand: Random = Random()):
     #         break
     # return
 
-    population = Population(indv_temp, POPULATION_SIZE)
+    population = Population(indv_temp, MH_POP_SIZE)
 
     @population.register_initialization
     def init_population(rand: Random = Random()):
@@ -97,20 +99,19 @@ def init_population(rand: Random = Random()):
             ret.append(new_indv)
         return ret
 
-    selection = TournamentSelection(tournament_size=TOURNAMENT_SIZE)
+    selection = TournamentSelection(tournament_size=MH_TOURNAMENT_SIZE)
     crossover = SBXCrossover(
-        pc=CROSSOVER_PROB, distribution_index=CROSSOVER_DISTRIBUTION_INDEX)
+        pc=MH_CRO_PROB, distribution_index=MH_CRO_DI)
     mutation = PolynomialMutation(
-        pm=MUTATION_PROB, distribution_index=MUTATION_DISTRIBUTION_INDEX)
+        pm=MH_MUT_PROB, distribution_index=MH_MUT_DI)
 
     engine = NSGAIIEngine(population, selection=selection,
                           crossover=crossover,
                           mutation=mutation,
-                          selection_size=SELECTION_SIZE,
-                          max_iter=MAX_ITER,
-                          random_state=SEED)
+                          selection_size=MH_SLT_SIZE,
+                          random_state=MH_SEED)
 
-    @engine.register_objective
+    @engine.minimize_objective
     def objective1(indv):
         network = indv.decode()
         if network.is_valid:
@@ -120,7 +121,7 @@ def objective1(indv):
 
     best_mr = defaultdict(lambda: float('inf'))
 
-    @engine.register_objective
+    @engine.minimize_objective
     def objective2(indv):
         nonlocal best_mr
         network = indv.decode()
@@ -132,43 +133,7 @@ def objective2(indv):
         else:
             return float('inf')
 
-    f1_max = None
-    f2_max = None
-    if visualization:
-        @engine.register_reporter
-        def report(gen):
-            if gen % 5 == 0 or gen < 20:
-                nonlocal f1_max, f2_max
-                solutions = engine.get_all_solutions()
-                # print(solutions)
-                f1_arr = [solution.objectives[0]
-                          for solution in solutions if solution.objectives[0] != float('inf')]
-                f2_arr = [solution.objectives[1]
-                          for solution in solutions if solution.objectives[1] != float('inf')]
-
-                if f1_max:
-                    f1_arr.append(f1_max)
-                if f2_max:
-                    f2_arr.append(f2_max)
-                if len(f1_arr) > 0:
-                    f1_max = max(f1_arr)
-                    f1_max_temp = f1_max * 1.05
-                else:
-                    f1_max_temp = None
-                if len(f2_arr) > 0:
-                    f2_max = max(f2_arr)
-                    f2_max_temp = f2_max * 1.05
-                else:
-                    f2_max_temp = None
-
-                visualize_solutions(solutions,
-                                    'results/multi_hop/{}/solutions-gen-{}.png'.format(
-                                        basename, (3 - len(str(gen))) * '0' + str(gen)),
-                                    title='solutions-gen-{}'.format(
-                                        (3 - len(str(gen))) * '0' + str(gen)),
-                                    show=False, f1_max=f1_max_temp, f2_max=f2_max_temp)
-
-    engine.run()
+    history = engine.run(generations=MH_GENS)
 
     pareto_front = engine.get_pareto_front()
     solutions = engine.get_all_solutions()
@@ -183,6 +148,12 @@ def report(gen):
     save_results(pareto_front, solutions, best_mr,
                  out_dir, visualization=visualization)
 
+    
+    save_history_as_gif(history, 
+                        title="NSGAII", 
+                        objective_name=['relays', 'energy'], 
+                        gen_filter=lambda x : (x % 5 == 0), 
+                        out_dir=out_dir)
 
 if __name__ == '__main__':
     solve('data/medium/multi_hop/uu-dem1_r25_1_40.json', visualization=True)

examples/wusn/multi_hop_nsgaii.py

@@ -8,7 +8,7 @@
 WORKING_DIR = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(os.path.join(WORKING_DIR, '../../../geneticpython'))
 
-from geneticpython.individual import Network
+from geneticpython.core.individual import Network
 from collections import deque
 from utils.input import WusnInput, WusnConstants
 from utils.point import distance

examples/wusn/networks.py

@@ -8,26 +8,80 @@
 
 import os
 
-WORKING_DIR = os.path.dirname(os.path.abspath(__file__))
-
-SEED = 42
-
-POPULATION_SIZE = 10
-
-SELECTION_SIZE = 10
-
-MAX_ITER = 2
-
-TOURNAMENT_SIZE = 5
+SH_MODEL = "0.0.1"
+MH_MODEL = "test"
 
-CROSSOVER_PROB = 0.9
+WORKING_DIR = os.path.dirname(os.path.abspath(__file__))
 
-CROSSOVER_DISTRIBUTION_INDEX = 20
+SH_SEED = 42
+SH_POP_SIZE = 10
+SH_SLT_SIZE = 10
+SH_GENS = 2
+SH_TOURNAMENT_SIZE = 5
+SH_CRO_PROB = 0.9
+SH_CRO_DI = 20
+SH_MUT_PROB = 1.0/30
+SH_MUT_DI = 5
 
-MUTATION_PROB = 1.0/30
+MH_SEED = 42
+MH_POP_SIZE = 10
+MH_SLT_SIZE = 10
+MH_GENS = 2
+MH_TOURNAMENT_SIZE = 5
+MH_X_PROB = 0.9
+MH_CRO_DI = 20
+MH_MUT_PROB = 1.0/30
+MH_MUT_DI = 5
+ALPHA = 2
+BETA = 6
 
-MUTATION_DISTRIBUTION_INDEX = 5
+def __load_sh_model(model):
+    global SH_SEED, SH_POP_SIZE, SH_SLT_SIZE, SH_GENS
+    global SH_TOURNAMENT_SIZE, SH_CRO_PROB, SH_CRO_DI, SH_MUT_DI, SH_MUT_PROB
+    if model == 'test':                 
+        SH_SEED = 42
+        SH_POP_SIZE = 10
+        SH_SLT_SIZE = 10
+        SH_GENS = 2
+        SH_TOURNAMENT_SIZE = 5
+        SH_CRO_PROB = 0.9
+        SH_CRO_DI = 20
+        SH_MUT_PROB = 1.0/30
+        SH_MUT_DI = 5
+    elif model == '0.0.1':
+        SH_SEED = 42
+        SH_POP_SIZE = 100
+        SH_SLT_SIZE = 100
+        SH_GENS = 100
+        SH_TOURNAMENT_SIZE = 5
+        SH_CRO_PROB = 0.9
+        SH_CRO_DI = 20
+        SH_MUT_PROB = 1.0/30
+        SH_MUT_DI = 5
 
-ALPHA = 2
+def __load_mh_model(model):
+    global MH_SEED, MH_POP_SIZE, MH_SLT_SIZE, MH_GENS
+    global  MH_TOURNAMENT_SIZE, MH_CRO_PROB, MH_CRO_DI, MH_MUT_DI, MH_MUT_PROB
+    if model == 'test':                 
+        MH_SEED = 42
+        MH_POP_SIZE = 10
+        MH_SLT_SIZE = 10
+        MH_GENS = 2
+        MH_TOURNAMENT_SIZE = 5
+        MH_CRO_PROB = 0.9
+        MH_CRO_DI = 20
+        MH_MUT_PROB = 1.0/30
+        MH_MUT_DI = 5
+    elif model == '0.0.1':
+        MH_SEED = 42
+        MH_POP_SIZE = 100
+        MH_SLT_SIZE = 100
+        MH_GENS = 100
+        MH_TOURNAMENT_SIZE = 5
+        MH_CRO_PROB = 0.9
+        MH_CRO_DI = 20
+        MH_MUT_PROB = 1.0/30
+        MH_MUT_DI = 5
 
-BETA = 6
+__load_sh_model(SH_MODEL)
+__load_mh_model(MH_MODEL)

examples/wusn/parameters.py

@@ -1,12 +1,30 @@
-44 0.0016010961579917128
-45 0.0016011382640617783
-46 0.0018011582640617783
-47 0.0014011182640617783
-48 0.0014011057826279405
-49 0.0016011257826279404
-50 0.0012010970816107834
-51 0.001401099939588667
-52 0.001400986551478805
-53 0.0014011174203246693
-54 0.0012010974203246693
-56 0.0016011257826279404
+30 0.0010010770816107832
+31 0.0010010657826279403
+32 0.0010010424397270295
+33 0.0010010424397270295
+34 0.0010010073457078846
+35 0.0010009969630479626
+36 0.0010009240064270208
+37 0.001000893148119278
+38 0.0008010582640617784
+39 0.0008010582640617784
+40 0.0008010582640617784
+41 0.0008010582640617784
+42 0.0008010582640617784
+43 0.0008010582640617784
+44 0.0008010582640617784
+45 0.0008010582640617784
+46 0.0010010000005773938
+47 0.0010010424397270295
+48 0.0010010424397270295
+49 0.0010010424397270295
+50 0.0010010424397270295
+51 0.0010010424397270295
+52 0.0010010657826279403
+53 0.0010010424397270295
+54 0.0010010424397270295
+55 0.0012010200005773937
+56 0.0012010654141478814
+57 0.0012010857826279405
+58 0.0012010857826279405
+59 0.0010010782640617784