advanced_example_custom_pop

Complexity

Total Complexity

4

Size/Duplication

Total Lines	43
Duplicated Lines	23.26 %

Importance

Changes

0

2 Methods

Rating	Name	Duplication	Size	Complexity
A	MyBenchmark.__init__()	2	2	1
A	MyBenchmark.function()	6	6	2

# encoding=utf8
# This is temporary fix to import module from parent folder
# It will be removed when package is published on PyPI
import sys
sys.path.append('../')

from NiaPy.task import StoppingTask, OptimizationType
from NiaPy.benchmarks import Benchmark
from NiaPy.algorithms.basic import GreyWolfOptimizer
from numpy import random as rand, apply_along_axis

# our custom benchmark class
class MyBenchmark(Benchmark):

This code seems to be duplicated in your project.

	def __init__(self):
		Benchmark.__init__(self, -10, 10)

	def function(self):
		def evaluate(D, sol):
			val = 0.0
			for i in range(D): val += sol[i] ** 2
			return val
		return evaluate


# custom initialization population function
def MyInit(task, NP, rnd=rand, **kwargs):
    pop = 0.2 + rnd.rand(NP, task.D) * task.bRange
    fpop = apply_along_axis(task.eval, 1, pop)
    return pop, fpop

# we will run 10 repetitions of Grey Wolf Optimizer against our custom MyBenchmark benchmark function
for i in range(10):
    task = StoppingTask(D=20, nGEN=100, optType=OptimizationType.MINIMIZATION, benchmark=MyBenchmark())

    # parameter is population size
    algo = GreyWolfOptimizer(NP=20, InitPopFunc=MyInit)

    # running algorithm returns best found minimum
    best = algo.run(task)

    # printing best minimum
    print(best[-1])