Code Duplication - NiaOrg/NiaPy - Measure and Improve Code Quality continuously with Scrutinizer

Code Duplication Length = 27-32 lines in 3 locations

NiaPy/algorithms/modified/jde.py 1 location


__all__ = ['SelfAdaptiveDifferentialEvolutionAlgorithm']


class SolutionjDE(object):

    def __init__(self, D, LB, UB, F, CR):
        self.D = D
        self.LB = LB
        self.UB = UB
        self.F = F
        self.CR = CR
        self.Solution = []
        self.Fitness = float('inf')
        self.generateSolution()

    def generateSolution(self):
        """Generate solution."""

        self.Solution = [self.LB + (self.UB - self.LB) * rnd.random()
                         for _i in range(self.D)]

    def evaluate(self):
        """Evaluate solution."""

        self.Fitness = SolutionjDE.FuncEval(self.D, self.Solution)

    def repair(self):
        for i in range(self.D):
            if self.Solution[i] > self.UB:
                self.Solution[i] = self.UB
            if self.Solution[i] < self.LB:
                self.Solution[i] = self.LB

    def __eq__(self, other):
        return self.Solution == other.Solution and self.Fitness == other.Fitness


class SelfAdaptiveDifferentialEvolutionAlgorithm(object):

NiaPy/algorithms/basic/ga.py 1 location


__all__ = ['GeneticAlgorithm']


class Chromosome(object):
    def __init__(self, D, LB, UB):
        self.D = D
        self.LB = LB
        self.UB = UB

        self.Solution = []
        self.Fitness = float('inf')
        self.generateSolution()

    def generateSolution(self):
        self.Solution = [self.LB + (self.UB - self.LB) * rnd.random()
                         for _i in range(self.D)]

    def evaluate(self):
        self.Fitness = Chromosome.FuncEval(self.D, self.Solution)

    def repair(self):
        for i in range(self.D):
            if self.Solution[i] > self.UB:
                self.Solution[i] = self.UB
            if self.Solution[i] < self.LB:
                self.Solution[i] = self.LB

    def __eq__(self, other):
        return self.Solution == other.Solution and self.Fitness == other.Fitness

    def toString(self):
        print([i for i in self.Solution])


class GeneticAlgorithm(object):

NiaPy/algorithms/basic/de.py 1 location


__all__ = ['DifferentialEvolutionAlgorithm']


class SolutionDE(object):

    def __init__(self, D, LB, UB):
        self.D = D
        self.LB = LB
        self.UB = UB

        self.Solution = []
        self.Fitness = float('inf')
        self.generateSolution()

    def generateSolution(self):
        self.Solution = [self.LB + (self.UB - self.LB) * rnd.random()
                         for _i in range(self.D)]

    def evaluate(self):
        self.Fitness = SolutionDE.FuncEval(self.D, self.Solution)

    def repair(self):
        for i in range(self.D):
            if self.Solution[i] > self.UB:
                self.Solution[i] = self.UB
            if self.Solution[i] < self.LB:
                self.Solution[i] = self.LB

    def __eq__(self, other):
        return self.Solution == other.Solution and self.Fitness == other.Fitness


class DifferentialEvolutionAlgorithm(object):

		@@ 8-39 (lines=32) @@
5		__all__ = ['SelfAdaptiveDifferentialEvolutionAlgorithm']
6
7
8		class SolutionjDE(object):
9
10		def __init__(self, D, LB, UB, F, CR):
11		self.D = D
12		self.LB = LB
13		self.UB = UB
14		self.F = F
15		self.CR = CR
16		self.Solution = []
17		self.Fitness = float('inf')
18		self.generateSolution()
19
20		def generateSolution(self):
21		"""Generate solution."""
22
23		self.Solution = [self.LB + (self.UB - self.LB) * rnd.random()
24		for _i in range(self.D)]
25
26		def evaluate(self):
27		"""Evaluate solution."""
28
29		self.Fitness = SolutionjDE.FuncEval(self.D, self.Solution)
30
31		def repair(self):
32		for i in range(self.D):
33		if self.Solution[i] > self.UB:
34		self.Solution[i] = self.UB
35		if self.Solution[i] < self.LB:
36		self.Solution[i] = self.LB
37
38		def __eq__(self, other):
39		return self.Solution == other.Solution and self.Fitness == other.Fitness
40
41
42		class SelfAdaptiveDifferentialEvolutionAlgorithm(object):

		@@ 8-36 (lines=29) @@
5		__all__ = ['GeneticAlgorithm']
6
7
8		class Chromosome(object):
9		def __init__(self, D, LB, UB):
10		self.D = D
11		self.LB = LB
12		self.UB = UB
13
14		self.Solution = []
15		self.Fitness = float('inf')
16		self.generateSolution()
17
18		def generateSolution(self):
19		self.Solution = [self.LB + (self.UB - self.LB) * rnd.random()
20		for _i in range(self.D)]
21
22		def evaluate(self):
23		self.Fitness = Chromosome.FuncEval(self.D, self.Solution)
24
25		def repair(self):
26		for i in range(self.D):
27		if self.Solution[i] > self.UB:
28		self.Solution[i] = self.UB
29		if self.Solution[i] < self.LB:
30		self.Solution[i] = self.LB
31
32		def __eq__(self, other):
33		return self.Solution == other.Solution and self.Fitness == other.Fitness
34
35		def toString(self):
36		print([i for i in self.Solution])
37
38
39		class GeneticAlgorithm(object):

		@@ 8-34 (lines=27) @@
5		__all__ = ['DifferentialEvolutionAlgorithm']
6
7
8		class SolutionDE(object):
9
10		def __init__(self, D, LB, UB):
11		self.D = D
12		self.LB = LB
13		self.UB = UB
14
15		self.Solution = []
16		self.Fitness = float('inf')
17		self.generateSolution()
18
19		def generateSolution(self):
20		self.Solution = [self.LB + (self.UB - self.LB) * rnd.random()
21		for _i in range(self.D)]
22
23		def evaluate(self):
24		self.Fitness = SolutionDE.FuncEval(self.D, self.Solution)
25
26		def repair(self):
27		for i in range(self.D):
28		if self.Solution[i] > self.UB:
29		self.Solution[i] = self.UB
30		if self.Solution[i] < self.LB:
31		self.Solution[i] = self.LB
32
33		def __eq__(self, other):
34		return self.Solution == other.Solution and self.Fitness == other.Fitness
35
36
37		class DifferentialEvolutionAlgorithm(object):

NiaOrg / NiaPy

Code Duplication Length = 27-32 lines in 3 locations

NiaPy/algorithms/modified/jde.py 1 location

NiaPy/algorithms/basic/ga.py 1 location

NiaPy/algorithms/basic/de.py 1 location