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

Code Duplication Length = 27-27 lines in 2 locations

NiaPy/algorithms/modified/jde.py 1 location


__all__ = ['SelfAdaptiveDifferentialEvolutionAlgorithm']


class SolutionjDE(object):
    def __init__(self, D, LB, UB):
        self.D = D
        self.LB = LB
        self.UB = UB
        self.F = 0.5
        self.Cr = 0.9
        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 = 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:
    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:

		@@ 22-48 (lines=27) @@
19		__all__ = ['SelfAdaptiveDifferentialEvolutionAlgorithm']
20
21
22		class SolutionjDE(object):
23		def __init__(self, D, LB, UB):
24		self.D = D
25		self.LB = LB
26		self.UB = UB
27		self.F = 0.5
28		self.Cr = 0.9
29		self.Solution = []
30		self.Fitness = float('inf')
31		self.generateSolution()
32
33		def generateSolution(self):
34		self.Solution = [self.LB + (self.UB - self.LB) * rnd.random()
35		for _i in range(self.D)]
36
37		def evaluate(self):
38		self.Fitness = SolutionjDE.FuncEval(self.D, self.Solution)
39
40		def repair(self):
41		for i in range(self.D):
42		if self.Solution[i] > self.UB:
43		self.Solution[i] = self.UB
44		if self.Solution[i] < self.LB:
45		self.Solution[i] = self.LB
46
47		def __eq__(self, other):
48		return self.Solution == other.Solution and self.Fitness == other.Fitness
49
50
51		class SelfAdaptiveDifferentialEvolutionAlgorithm(object):

		@@ 18-44 (lines=27) @@
15
16		__all__ = ['GeneticAlgorithm']
17
18		class Chromosome:
19		def __init__(self, D,LB,UB):
20		self.D = D
21		self.LB = LB
22		self.UB = UB
23
24		self.Solution = []
25		self.Fitness = float('inf')
26		self.generateSolution()
27
28		def generateSolution(self):
29		self.Solution = [self.LB + (self.UB - self.LB) * rnd.random() for i in range(self.D)]
30
31		def evaluate(self):
32		self.Fitness = Chromosome.FuncEval(self.D,self.Solution)
33
34		def repair(self):
35		for i in range(self.D):
36		if (self.Solution[i] > self.UB):
37		self.Solution[i] = self.UB
38		if self.Solution[i] < self.LB:
39		self.Solution[i] = self.LB
40		def __eq__(self,other):
41		return self.Solution == other.Solution and self.Fitness == other.Fitness
42
43		def toString(self):
44		print([i for i in self.Solution])
45
46
47		class GeneticAlgorithm:

NiaOrg / NiaPy

Code Duplication Length = 27-27 lines in 2 locations

NiaPy/algorithms/modified/jde.py 1 location

NiaPy/algorithms/basic/ga.py 1 location