Hyper-Complex Search Space Optimization

Optimize problems in hyper-complex spaces using quaternions or octonions with HyperComplexSpace and spanning decorators.

Example Code

import numpy as np
from opytimark.markers.n_dimensional import Sphere

import opytimizer.math.hyper as h
from opytimizer import Opytimizer
from opytimizer.core import Function
from opytimizer.core.stopping import MaxIterations
from opytimizer.optimizers.single_objective.swarm import PSO
from opytimizer.spaces import HyperComplexSpace

# Random seed for experimental consistency
np.random.seed(0)

# Number of agents, decision variables and dimensions
n_agents = 20
n_variables = 2
n_dimensions = 4
n_objectives = 1

# Lower and upper bounds (has to be the same size as `n_variables`)
lower_bound = [-10, -10]
upper_bound = [10, 10]

# Wraps the objective function with a spanning decorator,
# allowing values to be spanned between lower and upper bounds
@h.span_to_hyper_value(lower_bound, upper_bound)
def wrapper(x):
    z = Sphere()
    return z(x)


# Creates the space, optimizer and function
space = HyperComplexSpace(n_agents, n_variables, n_dimensions, n_objectives)
optimizer = PSO()
function = Function(wrapper)

# Bundles every piece into Opytimizer class
opt = Opytimizer(space, optimizer, function, save_agents=False)

# Runs the optimization task
opt.start(MaxIterations(1000))