# Copyright 2021-2023 Lawrence Livermore National Security, LLC and other
# MuyGPyS Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: MIT
"""
Noise modeling
Defines data structures and functors that handle noise priors for MuyGPs models.
"""
from typing import Callable
import MuyGPyS._src.math as mm
from MuyGPyS.gp.hyperparameter import ScalarParam
from MuyGPyS.gp.noise.noise_fn import NoiseFn
[docs]class NullNoise(ScalarParam, NoiseFn):
"""
A zero noise assumption model.
"""
def __init__(self, *args, **kwargs):
self.val = 0.0
self.bounds = "fixed"
def __call__(self, *args, **kwargs):
return 0.0
[docs] def perturb(self, K: mm.ndarray, **kwargs) -> mm.ndarray:
"""
Null noise perturbation.
Simply returns the input tensor unchanged.
Args:
K:
A tensor of shape `(batch_count, nn_count, nn_count)` containing
the `(nn_count, nn_count)`-shaped kernel matrices corresponding
to each of the batch elements.
Returns:
The same tensor.
"""
return K
def perturb_fn(self, fn: Callable) -> Callable:
return fn