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Remove n_vars in examples for evolutionary_based package
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@thieupu
thieupu committed Mar 24, 2024
1 parent 5d3944f commit e297d76
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Showing 8 changed files with 21 additions and 21 deletions.
4 changes: 2 additions & 2 deletions mealpy/evolutionary_based/CRO.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,7 @@ class OriginalCRO(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
Expand Down Expand Up @@ -208,7 +208,7 @@ class OCRO(OriginalCRO):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
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8 changes: 4 additions & 4 deletions mealpy/evolutionary_based/DE.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@ class OriginalDE(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
Expand Down Expand Up @@ -178,7 +178,7 @@ class JADE(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
Expand Down Expand Up @@ -313,7 +313,7 @@ class SADE(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
Expand Down Expand Up @@ -434,7 +434,7 @@ class SAP_DE(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
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4 changes: 2 additions & 2 deletions mealpy/evolutionary_based/EP.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@ class OriginalEP(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
Expand Down Expand Up @@ -122,7 +122,7 @@ class LevyEP(OriginalEP):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
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8 changes: 4 additions & 4 deletions mealpy/evolutionary_based/ES.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ class OriginalES(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
Expand Down Expand Up @@ -110,7 +110,7 @@ class LevyES(OriginalES):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
Expand Down Expand Up @@ -186,7 +186,7 @@ class CMA_ES(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
Expand Down Expand Up @@ -307,7 +307,7 @@ class Simple_CMA_ES(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
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2 changes: 1 addition & 1 deletion mealpy/evolutionary_based/FPA.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ class OriginalFPA(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "minmax": "min",
>>> "obj_func": objective_function
>>> }
Expand Down
10 changes: 5 additions & 5 deletions mealpy/evolutionary_based/GA.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,7 @@ class BaseGA(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "obj_func": objective_function,
>>> "minmax": "min",
>>> }
Expand Down Expand Up @@ -348,7 +348,7 @@ class SingleGA(BaseGA):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "obj_func": objective_function,
>>> "minmax": "min",
>>> }
Expand Down Expand Up @@ -462,7 +462,7 @@ class EliteSingleGA(SingleGA):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "obj_func": objective_function,
>>> "minmax": "min",
>>> }
Expand Down Expand Up @@ -582,7 +582,7 @@ class MultiGA(BaseGA):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "obj_func": objective_function,
>>> "minmax": "min",
>>> }
Expand Down Expand Up @@ -682,7 +682,7 @@ class EliteMultiGA(MultiGA):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "obj_func": objective_function,
>>> "minmax": "min",
>>> }
Expand Down
2 changes: 1 addition & 1 deletion mealpy/evolutionary_based/MA.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ class OriginalMA(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "obj_func": objective_function,
>>> "minmax": "min",
>>> }
Expand Down
4 changes: 2 additions & 2 deletions mealpy/evolutionary_based/SHADE.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@ class OriginalSHADE(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "obj_func": objective_function,
>>> "minmax": "min",
>>> }
Expand Down Expand Up @@ -186,7 +186,7 @@ class L_SHADE(Optimizer):
>>> return np.sum(solution**2)
>>>
>>> problem_dict = {
>>> "bounds": FloatVar(n_vars=30, lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "bounds": FloatVar(lb=(-10.,) * 30, ub=(10.,) * 30, name="delta"),
>>> "obj_func": objective_function,
>>> "minmax": "min",
>>> }
Expand Down

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