Smooth¶

SmoothingInfo dataclass to store smoothing-related information.

class smudgy.smooth.SmoothingInfo(tree: object = None, num_neighbors: int = None, nn_inds: ndarray = None, nn_dists: ndarray = None, nn_dists_vec: ndarray = None, smoLens: ndarray = None, smoTens: ndarray = None, smoTens_eigvals: ndarray = None, smoTens_eigvecs: ndarray = None, kernel_name: str = None, density_iso: ndarray = None, density_aniso: ndarray = None)[source]¶

Bases: object

Dataclass to store smoothing-related information.

Parameters:

tree (object) – Neighbor search tree (e.g., KDTree) for efficient neighbor queries.
num_neighbors (int) – Number of nearest neighbors used for smoothing.
nn_inds (np.ndarray) – Indices of nearest neighbors for each particle.
nn_dists (np.ndarray) – Distances to nearest neighbors for each particle.
nn_dists_vec (np.ndarray) – Vector distances to nearest neighbors for each particle.
smoLens (np.ndarray) – Smoothing lengths for each particle.
smoTens (np.ndarray) – Smoothing tensors for each particle.
smoTens_eigvals (np.ndarray) – Eigenvalues of the smoothing tensors.
smoTens_eigvecs (np.ndarray) – Eigenvectors of the smoothing tensors.
kernel_name (str) – Name of the smoothing kernel used.
density_iso (np.ndarray) – Isotropic density estimates for each particle.
density_aniso (np.ndarray) – Anisotropic density estimates for each particle.

tree: object = None¶

num_neighbors: int = None¶

nn_inds: ndarray = None¶

nn_dists: ndarray = None¶

nn_dists_vec: ndarray = None¶

smoLens: ndarray = None¶

smoTens: ndarray = None¶

smoTens_eigvals: ndarray = None¶

smoTens_eigvecs: ndarray = None¶

kernel_name: str = None¶

density_iso: ndarray = None¶

density_aniso: ndarray = None¶