NiaPy/algorithms/basic/ba.py 1 location
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@@ 69-79 (lines=11) @@
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| 66 |
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self.Fun = self.benchmark.function() |
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| 68 |
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def best_bat(self): |
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"""Find best bat.""" |
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i = 0 |
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j = 0 |
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for i in range(self.NP): |
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if self.Fitness[i] < self.Fitness[j]: |
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j = i |
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for i in range(self.D): |
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self.best[i] = self.Sol[j][i] |
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self.f_min = self.Fitness[j] |
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def init_bat(self): |
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"""Initialize bat.""" |
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NiaPy/algorithms/modified/hba.py 1 location
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@@ 51-59 (lines=9) @@
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| 48 |
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| 49 |
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self.F = 0.5 |
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self.CR = 0.9 |
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def best_bat(self): |
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i = 0 |
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j = 0 |
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for i in range(self.NP): |
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if self.Fitness[i] < self.Fitness[j]: |
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j = i |
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for i in range(self.D): |
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self.best[i] = self.Sol[j][i] |
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self.f_min = self.Fitness[j] |
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def init_bat(self): |
NiaPy/algorithms/basic/fpa.py 1 location
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@@ 49-57 (lines=9) @@
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| 46 |
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self.Fitness = [0] * self.NP # fitness |
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self.best = [0] * self.D # best solution |
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self.evaluations = 0 # evaluations counter |
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def best_flower(self): |
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i = 0 |
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j = 0 |
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for i in range(self.NP): |
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if self.Fitness[i] < self.Fitness[j]: |
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j = i |
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for i in range(self.D): |
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self.best[i] = self.Sol[j][i] |
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self.f_min = self.Fitness[j] |
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@classmethod |