pyfracval.pca_kernels#

PCA-specific JIT kernels for PyFracVAL.

JIT-compiled batch functions for PCA position calculation and overlap checking.

These kernels support the PCA stage in the FracVAL-style aggregation pipeline [Morán et al., 2019].

Functions#

batch_calculate_positions_pca

JIT batch calculation of particle positions during PCA.

batch_check_overlaps_pca

JIT parallel overlap checker for PCA batch operations.

Module Contents#

pyfracval.pca_kernels.batch_calculate_positions_pca(vec_0, i_vec, j_vec, angles)[source]#

Calculate batch of positions on intersection circle for PCA.

Uses Numba parallel loops to compute multiple rotation positions simultaneously.

Parameters:

  • vec_0 (np.ndarray) – [x0, y0, z0, r0] - center and radius of intersection circle

  • i_vec (np.ndarray) – First basis vector (3D)

  • j_vec (np.ndarray) – Second basis vector (3D)

  • angles (np.ndarray) – Array of rotation angles (1D)

Returns:

(N, 3) array of positions, one per angle

Return type:

np.ndarray

pyfracval.pca_kernels.batch_check_overlaps_pca(coords_agg, radii_agg, candidate_positions, radius_new, tolerance)[source]#

Check overlap for batch of candidate positions (PCA).

Uses Numba parallel loops to evaluate multiple positions simultaneously.

Parameters:

  • coords_agg (np.ndarray) – Current aggregate coordinates (n_agg, 3)

  • radii_agg (np.ndarray) – Current aggregate radii (n_agg,)

  • candidate_positions (np.ndarray) – Batch of candidate positions to test (n_candidates, 3)

  • radius_new (float) – Radius of new particle

  • tolerance (float) – Overlap tolerance

Returns:

(n_candidates,) array of max overlap values for each position

Return type:

np.ndarray