# encoding=utf8
"""Implementation of benchmarks utility function."""
import logging
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
logging.basicConfig()
logger = logging.getLogger('niapy.benchmarks.benchmark')
logger.setLevel('INFO')
__all__ = ['Benchmark']
[docs]class Benchmark:
r"""Class representing benchmarks.
Attributes:
Name (List[str]): List of names representing benchmark names.
lower (Union[int, float, list, numpy.ndarray]): Lower bounds.
upper (Union[int, float, list, numpy.ndarray]): Upper bounds.
"""
Name = ['Benchmark', 'BBB']
[docs] def __init__(self, lower, upper):
r"""Initialize benchmark.
Args:
lower (Union[int, float, list, numpy.ndarray]): Lower bounds.
upper (Union[int, float, list, numpy.ndarray]): Upper bounds.
"""
self.lower = lower
self.upper = upper
[docs] @staticmethod
def latex_code():
r"""Return the latex code of the problem.
Returns:
str: Latex code
"""
return r'''$f(x) = \infty$'''
[docs] def function(self):
r"""Get the optimization function.
Returns:
Callable[[int, Union[list, numpy.ndarray]], float]: Fitness function.
"""
def fun(dimension, x):
r"""Initialize benchmark.
Args:
dimension (int): Dimensionality of the problem.
x (Union[int, float, list, numpy.ndarray]): Solution to the problem.
Returns:
float: Fitness value for the solution.
"""
return np.inf
return fun
[docs] def __call__(self):
r"""Get the optimization function.
Returns:
Callable[[int, Union[list, numpy.ndarray]], float]: Fitness function.
"""
return self.function()
[docs] def plot2d(self):
r"""Plot 2D graph."""
pass
@staticmethod
def __2d_fun(x, y, f):
r"""Calculate function value.
Args:
x (float): First coordinate.
y (float): Second coordinate.
f (Callable[[int, Union[int, float, List[int, float], numpy.ndarray]], float]): Evaluation function.
Returns:
float: Calculate functional value for given input.
"""
return f(2, [x, y])
[docs] def plot3d(self, scale=0.32):
r"""Plot 3d scatter plot of benchmark function.
Args:
scale (float): Scale factor for points.
"""
fig = plt.figure()
ax = Axes3D(fig)
func = self.function()
xr, yr = np.arange(self.lower, self.upper, scale), np.arange(self.lower, self.upper, scale)
x, y = np.meshgrid(xr, yr)
z = np.vectorize(self.__2d_fun)(x, y, func)
ax.plot_surface(x, y, z, rstride=8, cstride=8, alpha=0.3)
ax.contourf(x, y, z, zdir='z', offset=-10, cmap=cm.coolwarm)
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
plt.show()
# vim: tabstop=3 noexpandtab shiftwidth=3 softtabstop=3
