NiaPy/algorithms/basic/ba.py 1 location
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@@ 81-96 (lines=16) @@
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| 78 |
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self.best[i] = self.Sol[j][i] |
| 79 |
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self.f_min = self.Fitness[j] |
| 80 |
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| 81 |
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def init_bat(self): |
| 82 |
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"""Initialize bat.""" |
| 83 |
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| 84 |
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for i in range(self.D): |
| 85 |
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self.Lb[i] = self.Lower |
| 86 |
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self.Ub[i] = self.Upper |
| 87 |
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| 88 |
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for i in range(self.NP): |
| 89 |
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self.Q[i] = 0 |
| 90 |
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for j in range(self.D): |
| 91 |
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rnd = random.uniform(0, 1) |
| 92 |
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self.v[i][j] = 0.0 |
| 93 |
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self.Sol[i][j] = self.Lb[j] + (self.Ub[j] - self.Lb[j]) * rnd |
| 94 |
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self.Fitness[i] = self.Fun(self.D, self.Sol[i]) |
| 95 |
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self.evaluations = self.evaluations + 1 |
| 96 |
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self.best_bat() |
| 97 |
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| 98 |
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@classmethod |
| 99 |
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def simplebounds(cls, val, lower, upper): |
NiaPy/algorithms/modified/hba.py 1 location
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@@ 61-74 (lines=14) @@
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| 58 |
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self.best[i] = self.Sol[j][i] |
| 59 |
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self.f_min = self.Fitness[j] |
| 60 |
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| 61 |
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def init_bat(self): |
| 62 |
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for i in range(self.D): |
| 63 |
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self.Lb[i] = self.Lower |
| 64 |
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self.Ub[i] = self.Upper |
| 65 |
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| 66 |
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for i in range(self.NP): |
| 67 |
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self.Q[i] = 0 |
| 68 |
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for j in range(self.D): |
| 69 |
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rnd = random.uniform(0, 1) |
| 70 |
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self.v[i][j] = 0.0 |
| 71 |
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self.Sol[i][j] = self.Lb[j] + (self.Ub[j] - self.Lb[j]) * rnd |
| 72 |
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self.Fitness[i] = self.Fun(self.D, self.Sol[i]) |
| 73 |
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self.evaluations = self.evaluations + 1 |
| 74 |
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self.best_bat() |
| 75 |
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| 76 |
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@classmethod |
| 77 |
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def simplebounds(cls, val, lower, upper): |
NiaPy/algorithms/basic/fpa.py 1 location
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@@ 67-79 (lines=13) @@
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| 64 |
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val = upper |
| 65 |
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return val |
| 66 |
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| 67 |
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def init_flower(self): |
| 68 |
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for i in range(self.D): |
| 69 |
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self.Lb[i] = self.Lower |
| 70 |
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self.Ub[i] = self.Upper |
| 71 |
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| 72 |
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for i in range(self.NP): |
| 73 |
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for j in range(self.D): |
| 74 |
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rnd = random.uniform(0, 1) |
| 75 |
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self.dS[i][j] = 0.0 |
| 76 |
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self.Sol[i][j] = self.Lb[j] + (self.Ub[j] - self.Lb[j]) * rnd |
| 77 |
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self.Fitness[i] = self.Fun(self.D, self.Sol[i]) |
| 78 |
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self.evaluations = self.evaluations + 1 |
| 79 |
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self.best_flower() |
| 80 |
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| 81 |
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def move_flower(self): |
| 82 |
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S = [[0.0 for i in range(self.D)] for j in range(self.NP)] |
NiaOrg /
NiaPy
