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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