"""
---
Copyright (c) 2018 Baskar Ganapathysubramanian, Balaji Sesha Sarath Pokuri
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
---
"""
## --- end license text --- ##
import numpy as np
[docs]class KernelFunction:
"""
Attributes:
:var theta: Kernel parameters. Can be None, a scalar, or a vector. Should be initialized to the appropriate \
type/len during initialization.
:var theta0: Scaling factor
"""
theta = None
theta0 = 1.0
def __init__(self):
pass
[docs] def eval(self, x1: np.array, x2: np.array) -> float:
"""
Evaluate the kernel function
:param x1: location 1
:param x2: location 2
:return:
"""
raise NotImplemented('Kernel function eval not implemented')
[docs] def derivative(self, x1: np.array, x2: np.array) -> np.array:
"""
Evaluate the derivative of the kernel
:param x1: location 1
:param x2: location 2
:return:
"""
raise NotImplemented('Kernel function derivative not implemented')