Typo in TournamentSelection: "random_permuations" should be "random_p…

…ermutations" #669

pymoo/algorithms/moo/ctaea.py

@@ -14,7 +14,7 @@
 from pymoo.util.display.multi import MultiObjectiveOutput
 from pymoo.util.dominator import Dominator
 from pymoo.util.function_loader import load_function
-from pymoo.util.misc import has_feasible, random_permuations
+from pymoo.util.misc import has_feasible, random_permutations
 from pymoo.util.nds.non_dominated_sorting import NonDominatedSorting
 
 
@@ -63,7 +63,7 @@ def _do(self, problem, Hm, n_select, n_parents, **kwargs):
         n_random = n_select * n_parents * self.pressure
         n_perms = math.ceil(n_random / n_pop)
         # get random permutations and reshape them
-        P = random_permuations(n_perms, n_pop)[:n_random]
+        P = random_permutations(n_perms, n_pop)[:n_random]
         P = np.reshape(P, (n_select * n_parents, self.pressure))
         if Pc <= Pd:
             # Choose from DA

pymoo/algorithms/moo/pinsga2.py

@@ -1,25 +1,22 @@
-import numpy as np
 import sys
-
 from abc import ABC, abstractmethod
+
+import numpy as np
+
 from pymoo.algorithms.base.genetic import GeneticAlgorithm
+from pymoo.algorithms.moo.nsga2 import binary_tournament
 from pymoo.docs import parse_doc_string
 from pymoo.operators.crossover.sbx import SBX
 from pymoo.operators.mutation.pm import PM
-from pymoo.operators.survival.rank_and_crowding import RankAndCrowding
 from pymoo.operators.sampling.rnd import FloatRandomSampling
-from pymoo.operators.selection.tournament import compare, TournamentSelection
+from pymoo.operators.selection.tournament import TournamentSelection
+from pymoo.operators.survival.rank_and_crowding import RankAndCrowding
 from pymoo.termination.default import DefaultMultiObjectiveTermination
-from pymoo.util.display.multi import MultiObjectiveOutput
-from pymoo.util.dominator import Dominator
-from pymoo.util.vf_dominator import VFDominator
-from pymoo.util.misc import has_feasible
-from pymoo.util.reference_direction import select_points_with_maximum_distance
 from pymoo.util import value_functions as mvf
+from pymoo.util.display.multi import MultiObjectiveOutput
 from pymoo.util.nds.non_dominated_sorting import NonDominatedSorting
-
-from pymoo.algorithms.moo.nsga2 import binary_tournament
-from pymoo.algorithms.moo.nsga2 import RankAndCrowdingSurvival
+from pymoo.util.reference_direction import select_points_with_maximum_distance
+from pymoo.util.vf_dominator import VFDominator
 
 
 # =========================================================================================================

pymoo/operators/selection/rnd.py

@@ -3,7 +3,7 @@
 import numpy as np
 
 from pymoo.core.selection import Selection
-from pymoo.util.misc import random_permuations
+from pymoo.util.misc import random_permutations
 
 
 class RandomSelection(Selection):
@@ -16,7 +16,7 @@ def _do(self, _, pop, n_select, n_parents, **kwargs):
         n_perms = math.ceil(n_random / len(pop))
 
         # get random permutations and reshape them
-        P = random_permuations(n_perms, len(pop))[:n_random]
+        P = random_permutations(n_perms, len(pop))[:n_random]
 
         return np.reshape(P, (n_select, n_parents))
 

pymoo/operators/selection/tournament.py

@@ -3,7 +3,7 @@
 import numpy as np
 
 from pymoo.core.selection import Selection
-from pymoo.util.misc import random_permuations
+from pymoo.util.misc import random_permutations
 
 
 class TournamentSelection(Selection):
@@ -42,7 +42,7 @@ def _do(self, _, pop, n_select, n_parents=1, **kwargs):
         n_perms = math.ceil(n_random / len(pop))
 
         # get random permutations and reshape them
-        P = random_permuations(n_perms, len(pop))[:n_random]
+        P = random_permutations(n_perms, len(pop))[:n_random]
         P = np.reshape(P, (n_select * n_parents, self.pressure))
 
         # compare using tournament function

pymoo/util/misc.py

@@ -58,7 +58,7 @@ def parameter_less_constraints(F, CV, F_max=None):
     return F
 
 
-def random_permuations(n, l, concat=True):
+def random_permutations(n, l, concat=True):
     P = []
     for i in range(n):
         P.append(np.random.permutation(l))