NiaPy/algorithms/basic/ba.py 1 location
|
@@ 81-96 (lines=16) @@
|
| 78 |
|
j = i |
| 79 |
|
for i in range(self.D): |
| 80 |
|
self.best[i] = self.Sol[j][i] |
| 81 |
|
self.f_min = self.Fitness[j] |
| 82 |
|
|
| 83 |
|
def eval_true(self): |
| 84 |
|
"""Check evauations.""" |
| 85 |
|
|
| 86 |
|
if self.evaluations == self.nFES: |
| 87 |
|
self.eval_flag = False |
| 88 |
|
|
| 89 |
|
def init_bat(self): |
| 90 |
|
"""Initialize bat.""" |
| 91 |
|
|
| 92 |
|
for i in range(self.D): |
| 93 |
|
self.Lb[i] = self.Lower |
| 94 |
|
self.Ub[i] = self.Upper |
| 95 |
|
|
| 96 |
|
for i in range(self.NP): |
| 97 |
|
self.Q[i] = 0 |
| 98 |
|
for j in range(self.D): |
| 99 |
|
rnd = random.uniform(0, 1) |
NiaPy/algorithms/modified/hba.py 1 location
|
@@ 61-74 (lines=14) @@
|
| 58 |
|
j = i |
| 59 |
|
for i in range(self.D): |
| 60 |
|
self.best[i] = self.Sol[j][i] |
| 61 |
|
self.f_min = self.Fitness[j] |
| 62 |
|
|
| 63 |
|
def eval_true(self): |
| 64 |
|
"""Check evauations.""" |
| 65 |
|
|
| 66 |
|
if self.evaluations == self.nFES: |
| 67 |
|
self.eval_flag = False |
| 68 |
|
|
| 69 |
|
def init_bat(self): |
| 70 |
|
for i in range(self.D): |
| 71 |
|
self.Lb[i] = self.Lower |
| 72 |
|
self.Ub[i] = self.Upper |
| 73 |
|
|
| 74 |
|
for i in range(self.NP): |
| 75 |
|
self.Q[i] = 0 |
| 76 |
|
for j in range(self.D): |
| 77 |
|
rnd = random.uniform(0, 1) |
NiaPy/algorithms/basic/fpa.py 1 location
|
@@ 67-79 (lines=13) @@
|
| 64 |
|
self.evaluations = 0 # evaluations counter |
| 65 |
|
|
| 66 |
|
def best_flower(self): |
| 67 |
|
i = 0 |
| 68 |
|
j = 0 |
| 69 |
|
for i in range(self.NP): |
| 70 |
|
if self.Fitness[i] < self.Fitness[j]: |
| 71 |
|
j = i |
| 72 |
|
for i in range(self.D): |
| 73 |
|
self.best[i] = self.Sol[j][i] |
| 74 |
|
self.f_min = self.Fitness[j] |
| 75 |
|
|
| 76 |
|
def eval_true(self): |
| 77 |
|
"""Check evaluations.""" |
| 78 |
|
|
| 79 |
|
if self.evaluations == self.nFES: |
| 80 |
|
self.eval_flag = False |
| 81 |
|
|
| 82 |
|
@classmethod |