pyFM.signatures.WKS_functions

Functions

WKS(evals, evects, energy_list, sigma[, scaled])

Returns the Wave Kernel Signature for some energy values.

auto_WKS(evals, evects, num_E[, landmarks, ...])

Compute WKS with an automatic choice of scale and energy

lm_WKS(evals, evects, landmarks, ...[, scaled])

Returns the Wave Kernel Signature for some landmarks and energy values.

mesh_WKS(mesh, num_E[, landmarks, k])

Compute the Wave Kernel Signature for a mesh
pyFM.signatures.WKS_functions.WKS(evals, evects, energy_list, sigma, scaled=False)

Returns the Wave Kernel Signature for some energy values.

Parameters:

  • evects – (N,K) array with the K eigenvectors of the Laplace Beltrami operator

  • evals – (K,) array of the K corresponding eigenvalues

  • energy_list – (num_E,) values of e to use

  • sigma – (float) [positive] standard deviation to use

  • scaled – (bool) Whether to scale each energy level

Returns:

WKS – (N,num_E) array where each column is the WKS for a given e

Return type:

np.ndarray

pyFM.signatures.WKS_functions.lm_WKS(evals, evects, landmarks, energy_list, sigma, scaled=False)

Returns the Wave Kernel Signature for some landmarks and energy values.

Parameters:

  • evects – (N,K) array with the K eigenvectors of the Laplace Beltrami operator

  • evals – (K,) array of the K corresponding eigenvalues

  • landmarks – (p,) indices of landmarks to compute

  • energy_list – (num_E,) values of e to use

  • sigma (int) – standard deviation

Returns:

landmarks_WKS – (N,num_E*p) array where each column is the WKS for a given e for some landmark

Return type:

np.ndarray

pyFM.signatures.WKS_functions.auto_WKS(evals, evects, num_E, landmarks=None, scaled=True)

Compute WKS with an automatic choice of scale and energy

Parameters:

  • evals – (K,) array of K eigenvalues

  • evects – (N,K) array with K eigenvectors

  • landmarks – (p,) If not None, indices of landmarks to compute.

  • num_E – (int) number values of e to use

Returns:

WKS or lm_WKS –

(N,num_E) or (N,p*num_E) array where each column is the WKS for a given e

and possibly for some landmarks

Return type:

np.ndarray

pyFM.signatures.WKS_functions.mesh_WKS(mesh, num_E, landmarks=None, k=None)

Compute the Wave Kernel Signature for a mesh

Parameters:

  • mesh (TriMesh) – mesh on which to compute the XKS

  • num_T (int) – number of time values to use

  • landmarks (np.ndarray, optional) – (p,) indices of landmarks to use

  • k (int, optional) – number of eigenvalues to use

Returns:

WKS – (N,num_T) array where each line is the HKS for a given t

Return type:

np.ndarray