Source code for NiaPy.benchmarks.bentcigar
# encoding=utf8
"""Implementations of Bent Cigar functions."""
from NiaPy.benchmarks.benchmark import Benchmark
__all__ = ['BentCigar']
[docs]class BentCigar(Benchmark):
r"""Implementations of Bent Cigar functions.
Date: 2018
Author: Klemen Berkovič
License: MIT
Function:
**Bent Cigar Function**
:math:`f(\textbf{x}) = x_1^2 + 10^6 \sum_{i=2}^D x_i^2`
**Input domain:**
The function can be defined on any input domain but it is usually
evaluated on the hypercube :math:`x_i ∈ [-100, 100]`, for all :math:`i = 1, 2,..., D`.
**Global minimum:**
:math:`f(x^*) = 0`, at :math:`x^* = (420.968746,...,420.968746)`
LaTeX formats:
Inline:
$f(\textbf{x}) = x_1^2 + 10^6 \sum_{i=2}^D x_i^2$
Equation:
\begin{equation} f(\textbf{x}) = x_1^2 + 10^6 \sum_{i=2}^D x_i^2 \end{equation}
Domain:
$-100 \leq x_i \leq 100$
Reference:
http://www5.zzu.edu.cn/__local/A/69/BC/D3B5DFE94CD2574B38AD7CD1D12_C802DAFE_BC0C0.pdf
"""
Name = ['BentCigar']
[docs] def __init__(self, Lower=-100.0, Upper=100.0):
r"""Initialize of Bent Cigar benchmark.
Args:
Lower (Optional[float]): Lower bound of problem.
Upper (Optional[float]): Upper bound of problem.
See Also:
:func:`NiaPy.benchmarks.Benchmark.__init__`
"""
Benchmark.__init__(self, Lower, Upper)
[docs] @staticmethod
def latex_code():
r"""Return the latex code of the problem.
Returns:
str: Latex code
"""
return r'''$f(\textbf{x}) = x_1^2 + 10^6 \sum_{i=2}^D x_i^2$'''
[docs] def function(slef):
r"""Return benchmark evaluation function.
Returns:
Callable[[int, Union[int, float, List[int, float], numpy.ndarray]], float]: Fitness function
"""
def f(D, sol):
r"""Fitness function.
Args:
D (int): Dimensionality of the problem
sol (Union[int, float, List[int, float], numpy.ndarray]): Solution to check.
Returns:
float: Fitness value for the solution.
"""
val = 0.0
for i in range(1, D): val += sol[i] ** 2
return sol[0] ** 2 + 10 ** 6 * val
return f
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