(#57) fix overflow error

requirements.txt

@@ -4,6 +4,7 @@ grip==4.6.2
 iniconfig==2.0.0
 Markdown==3.6
 Markdown-Editor==1.0.7
+mpmath==1.3.0
 numpy==1.26.2
 path-and-address==2.0.1
 pluggy==1.5.0

src/problems/single_objective/continuous/bentcigar.py

@@ -1,5 +1,5 @@
 from problems.abstract_problem import AbstractProblem
-from numpy import power as pw
+from mpmath import power as pw
 
 class Bentcigar(AbstractProblem):
     """

src/problems/single_objective/continuous/bohachevsky.py

@@ -1,6 +1,6 @@
 from numpy import cos
 from numpy import pi
-from numpy import power as pw
+from mpmath import power as pw
 from problems.abstract_problem import AbstractProblem
 
 class Bohachevsky(AbstractProblem):

src/problems/single_objective/continuous/holzman.py

@@ -1,5 +1,5 @@
 from problems.abstract_problem import AbstractProblem
-from numpy import power as pw
+from mpmath import power as pw
 
 class Holzman(AbstractProblem):
     """

src/problems/single_objective/continuous/levy.py

@@ -1,6 +1,6 @@
 from problems.abstract_problem import AbstractProblem
 import math
-from numpy import power as pw
+from mpmath import power as pw
 
 class Levy(AbstractProblem):
     """

src/problems/single_objective/continuous/matyas.py

@@ -1,5 +1,5 @@
 from problems.abstract_problem import AbstractProblem
-from numpy import power as pw
+from mpmath import power as pw
 
 class Matyas(AbstractProblem):
     """

src/problems/single_objective/continuous/pow.py

@@ -1,5 +1,5 @@
 from problems.abstract_problem import AbstractProblem
-from numpy import power as pw
+from mpmath import power as pw
 
 class Pow(AbstractProblem):
     """

src/problems/single_objective/continuous/powell.py

@@ -1,5 +1,6 @@
 from problems.abstract_problem import AbstractProblem
-import numpy as np
+from mpmath import power as pw
+
 
 class Powell(AbstractProblem):
     """
@@ -42,10 +43,10 @@ def f(self, x: list) -> float:
         d = n // 4
 
         for i in range(d):
-            a = np.power(x[4*i] + 10 * x[4*i + 1], 2)
-            b = np.power(x[4*i + 2] - x[4*i + 3], 2)
-            c = np.power(x[4*i + 1] - 2 * x[4*i + 2], 4)
-            e = np.power(x[4*i] - x[4*i + 3], 4)
+            a = pw(x[4*i] + 10 * x[4*i + 1], 2)
+            b = pw(x[4*i + 2] - x[4*i + 3], 2)
+            c = pw(x[4*i + 1] - 2 * x[4*i + 2], 4)
+            e = pw(x[4*i] - x[4*i + 3], 4)
             fitness += a + 5 * b + c + 10 * e
 
         return round(fitness, 1)

src/problems/single_objective/continuous/rosenbrock.py

@@ -1,5 +1,5 @@
 from problems.abstract_problem import AbstractProblem
-from numpy import power as pw
+from mpmath import power as pw
 class Rosenbrock(AbstractProblem):
     """
     Rosenbrock function implementation for optimization problems.

src/problems/single_objective/continuous/rothellipsoid.py

@@ -1,5 +1,5 @@
 from problems.abstract_problem import AbstractProblem
-import numpy as np
+from mpmath import power as pw
 
 class Rothellipsoid(AbstractProblem):
     """
@@ -41,6 +41,6 @@ def f(self, x: list) -> float:
         n = len(x)
 
         for i in range(n):
-            fitness += (i + 2) * np.power(x[i], 2)
+            fitness += (i + 2) * pw(x[i], 2)
 
         return round(fitness, 3)

src/problems/single_objective/continuous/schaffer.py

@@ -1,5 +1,5 @@
 import numpy as np
-from numpy import power as pw
+from mpmath import power as pw
 from problems.abstract_problem import AbstractProblem
 
 

src/problems/single_objective/continuous/styblinskitang.py

@@ -1,5 +1,5 @@
 from problems.abstract_problem import AbstractProblem
-from numpy import power as pw
+from mpmath import power as pw
 
 class StyblinskiTang(AbstractProblem):
     """

src/problems/single_objective/continuous/sumofdifferentpowers.py

@@ -1,4 +1,5 @@
 import numpy as np
+from mpmath import power as pw
 from problems.abstract_problem import AbstractProblem
 
 class Sumofdifferentpowers(AbstractProblem):
@@ -25,6 +26,6 @@ def f(self, x: list) -> float:
         for i in range(len(x)):
             a = np.abs(x[i])
             b = i + 1
-            fitness += np.power(a, b)
+            fitness += pw(a, b)
 
         return round(fitness, 3)

src/problems/single_objective/continuous/threehumps.py

@@ -1,5 +1,5 @@
 from problems.abstract_problem import AbstractProblem
-from numpy import power as pw
+from mpmath import power as pw
 
 class Threehumps(AbstractProblem):
     """

src/problems/single_objective/continuous/zakharov.py

@@ -1,5 +1,5 @@
 from problems.abstract_problem import AbstractProblem
-from numpy import power as pw
+from mpmath import power as pw
 class Zakharov(AbstractProblem):
     """
     Zakharov function implementation for optimization problems.

src/problems/single_objective/continuous/zettle.py

@@ -1,5 +1,5 @@
 from problems.abstract_problem import AbstractProblem
-from numpy import power as pw
+from mpmath import power as pw
 
 class Zettle(AbstractProblem):
     """

src/tests/test_optimizer_alpha_cga.py

@@ -1,6 +1,6 @@
 import pytest
 from optimizer import alpha_cga, GeneType, TournamentSelection, ByteOnePointCrossover, ByteMutationRandom, OnePointCrossover, BitFlipMutation, PMXCrossover, SwapMutation
-import numpy as np
+import mpmath as mp
 from typing import List
 
 class RealProblem:
@@ -30,7 +30,7 @@ def f(self, x):
         float
             The computed value of the function given the input x.
         """
-        return sum(np.power(xi, 2) for xi in x)
+        return sum(mp.power(xi, 2) for xi in x)
 
 def test_optimizer_alpha_cga_real():
     """Test alpha_cga on a real-valued sum of squares problem."""

src/tests/test_optimizer_ccga.py

@@ -1,6 +1,5 @@
 import pytest
 from optimizer import ccga, GeneType, TournamentSelection, ByteOnePointCrossover, ByteMutationRandom, OnePointCrossover, BitFlipMutation, PMXCrossover, SwapMutation
-import numpy as np
 from typing import List
 
 class BinaryProblem:

src/tests/test_optimizer_cga.py

@@ -1,6 +1,6 @@
 import pytest
 from optimizer import cga, GeneType, TournamentSelection, ByteOnePointCrossover, ByteMutationRandom, OnePointCrossover, BitFlipMutation, PMXCrossover, SwapMutation
-import numpy as np
+import mpmath as mp
 from typing import List
 
 class RealProblem:
@@ -30,7 +30,7 @@ def f(self, x):
         float
             The computed value of the function given the input x.
         """
-        return sum(np.power(xi, 2) for xi in x)
+        return sum(mp.power(xi, 2) for xi in x)
 
 def test_optimizer_cga_real():
     """Test CGA on a real-valued sum of squares problem."""

src/tests/test_optimizer_mccga.py

@@ -1,6 +1,6 @@
 import pytest
 from optimizer import mcccga, GeneType, TournamentSelection, ByteOnePointCrossover, ByteMutationRandom, OnePointCrossover, BitFlipMutation, PMXCrossover, SwapMutation
-import numpy as np
+import mpmath as mp
 from typing import List
 
 class RealProblem:
@@ -30,7 +30,7 @@ def f(self, x):
         float
             The computed value of the function given the input x.
         """
-        return sum(np.power(xi, 2) for xi in x)
+        return sum(mp.power(xi, 2) for xi in x)
 
 def test_optimizer_mcccga_binary():
     """Test mcccga on a binary OneMax problem."""

src/tests/test_optimizer_sync_cga.py

@@ -1,6 +1,6 @@
 import pytest
 from optimizer import sync_cga, GeneType, TournamentSelection, ByteOnePointCrossover, ByteMutationRandom, OnePointCrossover, BitFlipMutation, PMXCrossover, SwapMutation
-import numpy as np
+import mpmath as mp
 from typing import List
 
 class RealProblem:
@@ -30,7 +30,7 @@ def f(self, x):
         float
             The computed value of the function given the input x.
         """
-        return sum(np.power(xi, 2) for xi in x)
+        return sum(mp.power(xi, 2) for xi in x)
 
 def test_optimizer_sync_cga_real():
     """Test sync_cga on a real-valued sum of squares problem."""