bayeso.utils.utils_gp¶
It is utilities for Gaussian process regression and Student-\(t\) process regression.
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bayeso.utils.utils_gp.
get_prior_mu
(prior_mu: Optional[Callable], X: numpy.ndarray) → numpy.ndarray¶ It computes the prior mean function values over inputs X.
Parameters: - prior_mu (function or NoneType) – prior mean function or None.
- X (numpy.ndarray) – inputs for prior mean function. Shape: (n, d) or (n, m, d).
Returns: zero array, or array of prior mean function values. Shape: (n, 1).
Return type: numpy.ndarray
Raises: AssertionError
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bayeso.utils.utils_gp.
validate_common_args
(X_train: numpy.ndarray, Y_train: numpy.ndarray, str_cov: str, prior_mu: Optional[Callable], debug: bool, X_test: Optional[numpy.ndarray] = None) → None¶ It validates the common arguments for various functions.
Parameters: - X_train (numpy.ndarray) – inputs. Shape: (n, d) or (n, m, d).
- Y_train (numpy.ndarray) – outputs. Shape: (n, 1).
- str_cov (str.) – the name of covariance function.
- prior_mu (NoneType, or function) – None, or prior mean function.
- debug (bool.) – flag for printing log messages.
- X_test (numpy.ndarray, or NoneType, optional) – inputs or None. Shape: (l, d) or (l, m, d).
Returns: None.
Return type: NoneType
Raises: AssertionError