def __init__(self,
lambda_weights: float = 0.1,
lambda_leaves: float = 0.1,
**loss_kwargs):
super().__init__(lambda_weights, lambda_leaves, **loss_kwargs)
check_pars(self.required_pars, **loss_kwargs)
self.alphas = self.kwargs['alphas']
def __init__(self,
lambda_weights: float = 0.1,
lambda_leaves: float = 0.1,
**loss_kwargs):
super().__init__(lambda_weights, lambda_leaves, **loss_kwargs)
check_pars(self.required_pars, **loss_kwargs)
self.n_harmonics = self.kwargs['n_harmonics']
self.cosines = None
self.sines = None
self.P = None
def __init__(self,
lambda_weights: float = 0.1,
lambda_leaves: float = 0.1,
**loss_kwargs):
super().__init__(lambda_weights, lambda_leaves, **loss_kwargs)
check_pars(self.required_pars, **loss_kwargs)
self.lambda_smooth = self.kwargs['lambda_smooth']
self.lambdas = None
self.Q_inv = None
self.D = None
def __init__(self,
lambda_weights: float = 0.1,
lambda_leaves: float = 0.1,
**loss_kwargs):
super().__init__(lambda_weights, lambda_leaves, **loss_kwargs)
check_pars(self.required_pars, **loss_kwargs)
self.S = self.kwargs['S']
self.precision = self.kwargs['precision']
self.S_inv = np.linalg.inv(self.S.T @ self.S)
self.lambdas, self.Q = eigh(
self.S.T @ self.kwargs['precision'] @ self.S)
self.Q_inv = np.linalg.inv(self.Q)
self.H_inv = lambda H: self.compute_H_inv(np.mean(H))
self.n_dims = self.S.shape[1]
