import numpy as np
[docs]
def angle_modulation_function(coeffs: np.ndarray, n_features: int) -> np.ndarray:
"""Homomorphous mapping between binary-valued and continuous-valued space used by the Angle
Modulated Differential Evolution (AMDE) algorithm.
Parameters
----------
coeffs: np.ndarray (4,)
The AMDE evolves values for the four coefficients a, b, c, and d. The first coefficient
represents the horizontal shift of the function, the second coefficient represents the
maximum frequency of the sine function, the third coefficient represents the frequency of
the cosine function, and the fourth coefficient represents the vertical shift of the
function.
n_features: int
Number of variables in the original space (e.g., features in a subcomponent).
Returns
-------
binary_solution: np.ndarray (n_features,)
Binary solution in the original space.
"""
a, b, c, d = coeffs
x = np.linspace(-2, 2, n_features)
trig_function = np.sin(2 * np.pi * (x - a) * b * np.cos(2 * np.pi * (x - a) * c)) + d
binary_solution = (trig_function > 0).astype(int)
return binary_solution
[docs]
def shifted_heaviside_function(real_solution: np.ndarray, shift: float = 0.5) -> np.ndarray:
"""Convert continuous solutions into binary solutions through the heaviside step function.
Parameters
----------
real_solution: np.ndarray (n_features,)
Solution with continuous values.
shift: float, default 0.5
Threshold for coding the solution from continuous-valued space to binary-valued space.
Each solution value will be mapped to 1 if it is greater than or equal to shift and 0
otherwise.
Returns
-------
binary_solution: np.ndarray (n_features,)
Real solution encoded in a binary representation.
"""
binary_solution = (real_solution >= shift).astype(int)
return binary_solution