spectralbrain.compute_functional_map#

spectralbrain.compute_functional_map(decomp_a, decomp_b, *, n_basis=30, descriptor_pairs=None, regularize=0.001)[source]#

Estimate a functional map C between two shapes.

The functional map C : F(M_a) → F(M_b) is represented in the truncated eigenbasis as a (n_basis × n_basis) matrix satisfying:

Φ_b^T · M_b · f_b ≈ C · (Φ_a^T · M_a · f_a)

for corresponding functions f_a, f_b.

Parameters:

  • decomp_a (SpectralDecomposition) – Source and target spectral decompositions.

  • decomp_b (SpectralDecomposition) – Source and target spectral decompositions.

  • n_basis (int) – Truncation size for the functional map.

  • descriptor_pairs (list of (ndarray, ndarray), optional) – Pairs of corresponding descriptors (f_a, f_b) on the two shapes. If None, uses HKS at several time-scales as default correspondence signals.

  • regularize (float) – Tikhonov regularisation weight.

Returns:

C (ndarray, shape (n_basis, n_basis)) – Functional map matrix.

Return type:

ndarray