NiaOrg / NiaPy

"""Example demonstrating the use of NiaPy Runner."""

class MyBenchmark(Benchmark):

	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

runner = Runner(

    D=40,

from numpy import random as rand, apply_along_axis

# our custom benchmark class

class MyBenchmark(Benchmark):

	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

from NiaPy.algorithms.basic import GreyWolfOptimizer

# our custom benchmark class

class MyBenchmark(Benchmark):

	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

# we will run 10 repetitions of Grey Wolf Optimizer against our custom MyBenchmark benchmark function

from NiaPy.benchmarks import Benchmark

from NiaPy.algorithms.basic import ParticleSwarmAlgorithm

class MyBenchmark(Benchmark):

	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

# we will run Particle Swarm Algorithm with on custom benchmark